Search results for: reliable

Authors: Kiran Datta, Daniella Holland-Hart, Anthony Byrne

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Introduction: Oesophago-gastric (OG) cancers are the fifth commonest in the UK, accounting for over 12,000 deaths each year. Most patients will present at later stages of the disease, with only 21% of patients with stage 4 disease surviving longer than a year. As a result, many patients are unsuitable for curative surgery and instead receive palliative treatment to improve prognosis and symptom burden. However, palliative chemotherapy can result in significant toxicity: almost half of the patients are unable to complete their chemotherapy regimen, with this proportion rising significantly in older and frailer patients. In addition, clinical trials often exclude older and frailer patients due to strict inclusion criteria, meaning there is limited evidence to guide which patients are most likely to benefit from palliative chemotherapy. Inappropriate chemotherapy administration is at odds with the goals of palliative treatment and care, which are to improve quality of life, and this also represents a significant resource expenditure. This literature review aimed to examine and appraise evidence regarding treatment resilience in order to guide clinicians in identifying the most suitable candidates for palliative chemotherapy. Factors influencing treatment resilience were assessed, as measured by completion rates, dose reductions, and toxicities. Methods: This literature review was conducted using rapid review methodology, utilising modified systematic methods. A literature search was performed across the MEDLINE, EMBASE, and Cochrane Library databases, with results limited to papers within the last 15 years and available in English. Key inclusion criteria included: 1) participants with either oesophageal, gastro-oesophageal junction, or gastric cancers; 2) patients treated with palliative chemotherapy; 3) available data evaluating the association between baseline participant characteristics and treatment resilience. Results: Of the 2326 papers returned, 11 reports of 10 studies were included in this review after excluding duplicates and irrelevant papers. Treatment resilience factors that were assessed included: age, performance status, frailty, inflammatory markers, and sarcopenia. Age was generally a poor predictor for how well patients would tolerate chemotherapy, while poor performance status was a better indicator of the need for dose reduction and treatment non-completion. Frailty was assessed across one cohort using multiple screening tools and was an effective marker of the risk of toxicity and the requirement for dose reduction. Inflammatory markers included lymphopenia and the Glasgow Prognostic Score, which assessed inflammation and hypoalbuminaemia. Although quick to obtain and interpret, these findings appeared less reliable due to the inclusion of patients treated with palliative radiotherapy. Sarcopenia and body composition were often associated with chemotherapy toxicity but not the rate of regimen completion. Conclusion: This review demonstrates that there are numerous measures that can estimate the ability of patients with oesophago-gastric cancer to tolerate palliative chemotherapy, and these should be incorporated into clinical assessments to promote personalised decision-making around treatment. Age should not be a barrier to receiving chemotherapy and older and frailer patients should be included in future clinical trials to better represent typical patients with oesophago-gastric cancers. Decisions regarding palliative treatment should be guided by these factors identified as well as patient preference.

Keywords: frailty, oesophago-gastric cancer, palliative chemotherapy, treatment resilience

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Authors: Milos Travar, Jovana Nikolov, Andrej Vranicar, Natasa Todorovic

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Over the years, High Purity Germanium (HPGe) detectors proved to be an excellent practical tool and, as such, have established their today's wide use in low background γ-spectrometry. One of the advantages of gamma-ray spectrometry is its easy sample preparation as chemical processing and separation of the studied subject are not required. Thus, with a single measurement, one can simultaneously perform both qualitative and quantitative analysis. One of the most prominent features of HPGe detectors, besides their excellent efficiency, is their superior resolution. This feature virtually allows a researcher to perform a thorough analysis by discriminating photons of similar energies in the studied spectra where otherwise they would superimpose within a single-energy peak and, as such, could potentially scathe analysis and produce wrongly assessed results. Naturally, this feature is of great importance when the identification of radionuclides, as well as their activity concentrations, is being practiced where high precision comes as a necessity. In measurements of this nature, in order to be able to reproduce good and trustworthy results, one has to have initially performed an adequate full-energy peak (FEP) efficiency calibration of the used equipment. However, experimental determination of the response, i.e., efficiency curves for a given detector-sample configuration and its geometry, is not always easy and requires a certain set of reference calibration sources in order to account for and cover broader energy ranges of interest. With the goal of overcoming these difficulties, a lot of researches turned towards the application of different software toolkits that implement the Monte Carlo method (e.g., MCNP, FLUKA, PENELOPE, Geant4, etc.), as it has proven time and time again to be a very powerful tool. In the process of creating a reliable model, one has to have well-established and described specifications of the detector. Unfortunately, the documentation that manufacturers provide alongside the equipment is rarely sufficient enough for this purpose. Furthermore, certain parameters tend to evolve and change over time, especially with older equipment. Deterioration of these parameters consequently decreases the active volume of the crystal and can thus affect the efficiencies by a large margin if they are not properly taken into account. In this study, the optimisation method of two HPGe detectors through the implementation of the Geant4 toolkit developed by CERN is described, with the goal of further improving simulation accuracy in calculations of FEP efficiencies by investigating the influence of certain detector variables (e.g., crystal-to-window distance, dead layer thicknesses, inner crystal’s void dimensions, etc.). Detectors on which the optimisation procedures were carried out were a standard traditional co-axial extended range detector (XtRa HPGe, CANBERRA) and a broad energy range planar detector (BEGe, CANBERRA). Optimised models were verified through comparison with experimentally obtained data from measurements of a set of point-like radioactive sources. Acquired results of both detectors displayed good agreement with experimental data that falls under an average statistical uncertainty of ∼ 4.6% for XtRa and ∼ 1.8% for BEGe detector within the energy range of 59.4−1836.1 [keV] and 59.4−1212.9 [keV], respectively.

Keywords: HPGe detector, γ spectrometry, efficiency, Geant4 simulation, Monte Carlo method

Procedia PDF Downloads 88

Authors: Marielle Leijten, Catherine Meulemans, Sven De Maeyer, Luuk Van Waes

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For the diagnosis of Alzheimer's disease (AD), a large variety of neuropsychological tests are available. In some of these tests, linguistic processing - both oral and written - is an important factor. Language disturbances might serve as a strong indicator for an underlying neurodegenerative disorder like AD. However, the current diagnostic instruments for language assessment mainly focus on product measures, such as text length or number of errors, ignoring the importance of the process that leads to written or spoken language production. In this study, it is our aim to describe and test differences between cognitive and impaired elderly on the basis of a selection of writing process variables (inter- and intrapersonal characteristics). These process variables are mainly related to pause times, because the number, length, and location of pauses have proven to be an important indicator of the cognitive complexity of a process. Method: Participants that were enrolled in our research were chosen on the basis of a number of basic criteria necessary to collect reliable writing process data. Furthermore, we opted to match the thirteen cognitively impaired patients (8 MCI and 5 AD) with thirteen cognitively healthy elderly. At the start of the experiment, participants were each given a number of tests, such as the Mini-Mental State Examination test (MMSE), the Geriatric Depression Scale (GDS), the forward and backward digit span and the Edinburgh Handedness Inventory (EHI). Also, a questionnaire was used to collect socio-demographic information (age, gender, eduction) of the subjects as well as more details on their level of computer literacy. The tests and questionnaire were followed by two typing tasks and two picture description tasks. For the typing tasks participants had to copy (type) characters, words and sentences from a screen, whereas the picture description tasks each consisted of an image they had to describe in a few sentences. Both the typing and the picture description tasks were logged with Inputlog, a keystroke logging tool that allows us to log and time stamp keystroke activity to reconstruct and describe text production processes. The main rationale behind keystroke logging is that writing fluency and flow reveal traces of the underlying cognitive processes. This explains the analytical focus on pause (length, number, distribution, location, etc.) and revision (number, type, operation, embeddedness, location, etc.) characteristics. As in speech, pause times are seen as indexical of cognitive effort. Results. Preliminary analysis already showed some promising results concerning pause times before, within and after words. For all variables, mixed effects models were used that included participants as a random effect and MMSE scores, GDS scores and word categories (such as determiners and nouns) as a fixed effect. For pause times before and after words cognitively impaired patients paused longer than healthy elderly. These variables did not show an interaction effect between the group participants (cognitively impaired or healthy elderly) belonged to and word categories. However, pause times within words did show an interaction effect, which indicates pause times within certain word categories differ significantly between patients and healthy elderly.

Keywords: Alzheimer's disease, keystroke logging, matching, writing process

Procedia PDF Downloads 332

Authors: Mariam Jaber, Abdullah Yahya, Mohammad Alkhedher

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The shift toward sustainable energy solutions increasingly focuses on hydrogen, recognized for its potential as a clean energy carrier. Despite its benefits, hydrogen storage poses significant challenges, primarily due to its low energy density and high volatility. Among the various solutions, pressure vessels designed for hydrogen storage range from Type I to Type V, each tailored for specific needs and benefits. Notably, Type V vessels, with their all-composite, liner-less design, significantly reduce weight and costs while optimizing space and decreasing maintenance demands. This study focuses on optimizing Type V hydrogen storage tanks by examining how different shapes affect performance in drop tests—a crucial aspect of achieving ISO 15869 certification. This certification ensures that if a tank is dropped, it will fail in a controlled manner, ideally by leaking before bursting. While cylindrical vessels are predominant in mobile applications due to their manufacturability and efficient use of space, spherical vessels offer superior stress distribution and require significantly less material thickness for the same pressure tolerance, making them advantageous for high-pressure scenarios. However, spherical tanks are less efficient in terms of packing and more complex to manufacture. Additionally, this study introduces toroidal vessels to assess their performance relative to the more traditional shapes, noting that the toroidal shape offers a more space-efficient option. The research evaluates how different shapes—spherical, cylindrical, and toroidal—affect drop test outcomes when combined with various composite materials and layup configurations. The ultimate goal is to identify optimal vessel geometries that enhance the safety and efficiency of hydrogen storage systems. For our materials, we selected high-performance composites such as Carbon T-700/Epoxy, Kevlar/Epoxy, E-Glass Fiber/Epoxy, and Basalt/Epoxy, configured in various orientations like [0,90]s, [45,-45]s, and [54,-54]. Our tests involved dropping tanks from different angles—horizontal, vertical, and 45 degrees—with an internal pressure of 35 MPa to replicate real-world scenarios as closely as possible. We used finite element analysis and first-order shear deformation theory, conducting tests with the Abaqus Explicit Dynamics software, which is ideal for handling the quick, intense stresses of an impact. The results from these simulations will provide valuable insights into how different designs and materials can enhance the durability and safety of hydrogen storage tanks. Our findings aim to guide future designs, making them more effective at withstanding impacts and safer overall. Ultimately, this research will contribute to the broader field of lightweight composite materials and polymers, advancing more innovative and practical approaches to hydrogen storage. By refining how we design these tanks, we are moving toward more reliable and economically feasible hydrogen storage solutions, further emphasizing hydrogen's role in the landscape of sustainable energy carriers.

Keywords: hydrogen storage, drop test, composite materials, type V tanks, finite element analysis

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Authors: G. Hubert, S. Aubry

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The earth is constantly bombarded by cosmic rays that can be of either galactic or solar origin. Thus, humans are exposed to high levels of galactic radiation due to altitude aircraft. The typical total ambient dose equivalent for a transatlantic flight is about 50 μSv during quiet solar activity. On the contrary, estimations differ by one order of magnitude for the contribution induced by certain solar particle events. Indeed, during Ground Level Enhancements (GLE) event, the Sun can emit particles of sufficient energy and intensity to raise radiation levels on Earth's surface. Analyses of GLE characteristics occurring since 1942 showed that for the worst of them, the dose level is of the order of 1 mSv and more. The largest of these events was observed on February 1956 for which the ambient dose equivalent rate is in the orders of 10 mSv/hr. The extra dose at aircraft altitudes for a flight during this event might have been about 20 mSv, i.e. comparable with the annual limit for aircrew. The most recent GLE, occurred on September 2017 resulting from an X-class solar flare, and it was measured on the surface of both the Earth and Mars using the Radiation Assessment Detector on the Mars Science Laboratory's Curiosity Rover. Recently, Hubert et al. proposed a GLE model included in a particle transport platform (named ATMORAD) describing the extensive air shower characteristics and allowing to assess the ambient dose equivalent. In this approach, the GCR is based on the Force-Field approximation model. The physical description of the Solar Cosmic Ray (i.e. SCR) considers the primary differential rigidity spectrum and the distribution of primary particles at the top of the atmosphere. ATMORAD allows to determine the spectral fluence rate of secondary particles induced by extensive showers, considering altitude range from ground to 45 km. Ambient dose equivalent can be determined using fluence-to-ambient dose equivalent conversion coefficients. The objective of this paper is to analyze the GCR and SCR impacts on ambient dose equivalent considering a high number statistic of world-flight paths. Flight trajectories are based on the Eurocontrol Demand Data Repository (DDR) and consider realistic flight plan with and without regulations or updated with Radar Data from CFMU (Central Flow Management Unit). The final paper will present exhaustive analyses implying solar impacts on ambient dose equivalent level and will propose detailed analyses considering route and airplane characteristics (departure, arrival, continent, airplane type etc.), and the phasing of the solar event. Preliminary results show an important impact of the flight path, particularly the latitude which drives the cutoff rigidity variations. Moreover, dose values vary drastically during GLE events, on the one hand with the route path (latitude, longitude altitude), on the other hand with the phasing of the solar event. Considering the GLE occurred on 23 February 1956, the average ambient dose equivalent evaluated for a flight Paris - New York is around 1.6 mSv, which is relevant to previous works This point highlights the importance of monitoring these solar events and of developing semi-empirical and particle transport method to obtain a reliable calculation of dose levels.

Keywords: cosmic ray, human dose, solar flare, aviation

Procedia PDF Downloads 187

Authors: Anil Kumar, Rajnish Kaur, Mateusz Czyzycki, Alessandro Migilori, Andreas Germanos Karydas, Sanjiv Puri

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The radiative decay of Li(i=1-3) sub-shell vacancies produced through photoionization results in production of the characteristic emission spectrum comprising several X-ray lines, whereas non-radiative vacancy decay results in Auger electron spectrum. Accurate reliable data on the Li(i=1-3) sub-shell X-ray production (XRP) cross sections is of considerable importance for investigation of atomic inner-shell ionization processes as well as for quantitative elemental analysis of different types of samples employing the energy dispersive X-ray fluorescence (EDXRF) analysis technique. At incident photon energies in vicinity of the absorption edge energies of an element, the many body effects including the electron correlation, core relaxation, inter-channel coupling and post-collision interactions become significant in the photoionization of atomic inner-shells. Further, in case of compounds, the characteristic emission spectrum of the specific element is expected to get influenced by the chemical environment (coordination number, oxidation state, nature of ligand/functional groups attached to central atom, etc.). These chemical effects on L X-ray fluorescence parameters have been investigated by performing the measurements at incident photon energies much higher than the Li(i=1-3) sub-shell absorption edge energies using EDXRF spectrometers. In the present work, the cross sections for production of the Lk(k= γ2,3, γ4) X-rays have been measured for some compounds of 66Dy, namely, Dy2O3, Dy2(CO3)3, Dy2(SO4)3.8H2O, DyI2 and Dy metal by tuning the incident photon energies few eV above the L1 absorption-edge energy in order to investigate the influence of chemical effects on these cross sections in presence of the many body effects which become significant at photon energies close to the absorption-edge energies. The present measurements have been performed under vacuum at the IAEA end-station of the X-ray fluorescence beam line (10.1L) of ELETTRA synchrotron radiation facility (Trieste, Italy) using self-supporting pressed pellet targets (1.3 cm diameter, nominal thicknesses ~ 176 mg/cm2) of 66Dy compounds (procured from Sigma Aldrich) and a metallic foil of 66Dy (nominal thickness ~ 3.9 mg/cm2, procured from Good Fellow, UK). The present measured cross sections have been compared with theoretical values calculated using the Dirac-Hartree-Slater(DHS) model based fluorescence and Coster-Kronig yields, Dirac-Fock(DF) model based X-ray emission rates and two sets of L1 sub-shell photoionization cross sections based on the non-relativistic Hartree-Fock-Slater(HFS) model and those deduced from the self-consistent Dirac-Hartree-Fock(DHF) model based total photoionization cross sections. The present measured XRP cross sections for 66Dy as well as for its compounds for the L2,3 and L4 X-rays, are found to be higher by ~14-36% than the two calculated set values. It is worth to be mentioned that L2,3 and L4 X-ray lines are originated by filling up of the L1 sub-shell vacancies by the outer sub-shell (N2,3 and O2,3) electrons which are much more sensitive to the chemical environment around the central atom. The present observed differences between measured and theoretical values are expected due to combined influence of the many-body effects and the chemical effects.

Keywords: chemical effects, L X-ray production cross sections, Many body effects, Synchrotron radiation

Procedia PDF Downloads 109

Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

Procedia PDF Downloads 124

Authors: Rubaiat S. Ahmed, Jemer Garrido, Sergey M. Motov

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Clinical informatics (CI) enables the transformation of data into a systematic organization that improves the quality of care and the generation of positive health outcomes.Innovative technology through informatics that compiles accurate data on analgesic utilization in the emergency department can enhance pain management in this important clinical setting. We aim to establish a simplified reporting system through CI to examine and assess the analgesic prescribing practices in the EDthrough executing a U.S. federal grant project on opioid reduction initiatives. Queried data points of interest from a level-one trauma ED’s electronic medical records were used to create data sets and develop informational/visual reporting dashboards (on Microsoft Excel and Google Sheets) concerning analgesic usage across several pre-defined parameters and performance metrics using CI. The data was then qualitatively analyzed to evaluate ED analgesic prescribing trends by departmental clinicians and leadership. During a 12-month reporting period (Dec. 1, 2020 – Nov. 30, 2021) for the ongoing project, about 41% of all ED patient visits (N = 91,747) were for pain conditions, of which 81.6% received analgesics in the ED and at discharge (D/C). Of those treated with analgesics, 24.3% received opioids compared to 75.7% receiving opioid alternatives in the ED and at D/C, including non-pharmacological modalities. Demographics showed among patients receiving analgesics, 56.7% were aged between 18-64, 51.8% were male, 51.7% were white, and 66.2% had government funded health insurance. Ninety-one percent of all opioids prescribed were in the ED, with intravenous (IV) morphine, IV fentanyl, and morphine sulfate immediate release (MSIR) tablets accounting for 88.0% of ED dispensed opioids. With 9.3% of all opioids prescribed at D/C, MSIR was dispensed 72.1% of the time. Hydrocodone, oxycodone, and tramadol usage to only 10-15% of the time, and hydromorphone at 0%. Of opioid alternatives, non-steroidal anti-inflammatory drugs were utilized 60.3% of the time, 23.5% with local anesthetics and ultrasound-guided nerve blocks, and 7.9% with acetaminophen as the primary non-opioid drug categories prescribed by ED providers. Non-pharmacological analgesia included virtual reality and other modalities. An average of 18.5 ED opioid orders and 1.9 opioid D/C prescriptions per 102.4 daily ED patient visits was observed for the period. Compared to other specialties within our institution, 2.0% of opioid D/C prescriptions are given by ED providers, compared to the national average of 4.8%. Opioid alternatives accounted for 69.7% and 30.3% usage, versus 90.7% and 9.3% for opioids in the ED and D/C, respectively.There is a pressing need for concise, relevant, and reliable clinical data on analgesic utilization for ED providers and leadership to evaluate prescribing practices and make data-driven decisions. Basic computer software can be used to create effective visual reporting dashboards with indicators that convey relevant and timely information in an easy-to-digest manner. We accurately examined our ED's analgesic prescribing practices using CI through dashboard reporting. Such reporting tools can quickly identify key performance indicators and prioritize data to enhance pain management and promote safe prescribing practices in the emergency setting.

Keywords: clinical informatics, dashboards, emergency department, health informatics, healthcare informatics, medical informatics, opioids, pain management, technology

Procedia PDF Downloads 118

Authors: Z. Zaman Asam, M. Ajmal, R. Saeed, H. Miraj, M. Muhammad Ahtisham, B. Hameed, A. -Sattar Nizami

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In Pakistan, environmental degradation and consequent human health deterioration has rapidly accelerated in the past decade due to solid waste mismanagement. As the situation worsens with time, establishment of proper waste management practices is urgently needed especially in semi urban and rural areas of Pakistan. This study uses a concept of Waste Bank, which involves a transfer station for collection of sorted waste fractions and its delivery to the targeted market such as recycling industries, biogas plants, composting facilities etc. The management efficiency and effectiveness of Waste Bank depend strongly on the proficient sorting and collection of solid waste fractions at household level. However, the social attitude towards such a solution in semi urban/rural areas of Pakistan demands certain prerequisites to make it workable. Considering these factors the objectives of this study are to: [A] Obtain reliable data about quantity and characteristics of generated waste to define feasibility of business and design factors, such as required storage area, retention time, transportation frequency of the system etc. [B] Analyze the effects of various social factors on waste generation to foresee future projections. [C] Quantify the improvement in waste sorting efficiency after awareness campaign. We selected Gujrat city of Central Punjab province of Pakistan as it is semi urban adjoined by rural areas. A total of 60 houses (20 from each of the three selected colonies), belonging to different social status were selected. Awareness sessions about waste segregation were given through brochures and individual lectures in each selected household. Sampling of waste, that households had attempted to sort, was then carried out in the three colored bags that were provided as part of the awareness campaign. Finally, refined waste sorting, weighing of various fractions and measurement of dry mass was performed in environmental laboratory using standard methods. It was calculated that sorting efficiency of waste improved from 0 to 52% as a result of the awareness campaign. The generation of waste (dry mass basis) on average from one household was 460 kg/year whereas per capita generation was 68 kg/year. Extrapolating these values for Gujrat Tehsil, the total waste generation per year is calculated to be 101921 tons dry mass (DM). Characteristics found in waste were (i) organic decomposable (29.2%, 29710 tons/year DM), (ii) recyclables (37.0%, 37726 tons/year DM) that included plastic, paper, metal and glass, and (iii) trash (33.8%, 34485 tons/year DM) that mainly comprised of polythene bags, medicine packaging, pampers and wrappers. Waste generation was more in colonies with comparatively higher income and better living standards. In future, data collection for all four seasons and improvements due to expansion of awareness campaign to educational institutes will be quantified. This waste management system can potentially fulfill vital sustainable development goals (e.g. clean water and sanitation), reduce the need to harvest fresh resources from the ecosystem, create business and job opportunities and consequently solve one of the most pressing environmental issues of the country.

Keywords: integrated solid waste management, waste segregation, waste bank, community development

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Authors: M. Mueller, M. Kuehn, M. Voelker

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In small and medium-sized enterprises (SMEs), the challenge is to create a well-grounded and reliable basis for process analysis, optimization and planning due to a lack of data. SMEs have limited access to methods with which they can effectively and efficiently analyse processes and identify cause-and-effect relationships in order to generate the necessary database and derive optimization potential from it. The implementation of digitalization within the framework of Industry 4.0 thus becomes a particular necessity for SMEs. For these reasons, the abstract presents an analysis methodology that is subject to the objective of developing an SME-appropriate methodology for efficient, temporarily feasible data collection and evaluation in flexible production and logistics systems as a basis for process analysis and optimization. The overall methodology focuses on retrospective, event-based tracing and analysis of material flow objects. The technological basis consists of Bluetooth low energy (BLE)-based transmitters, so-called beacons, and smart mobile devices (SMD), e.g. smartphones as receivers, between which distance data can be measured and derived motion profiles. The distance is determined using the Received Signal Strength Indicator (RSSI), which is a measure of signal field strength between transmitter and receiver. The focus is the development of a software-based methodology for interpretation of relative movements of transmitters and receivers based on distance data. The main research is on selection and implementation of pattern recognition methods for automatic process recognition as well as methods for the visualization of relative distance data. Due to an existing categorization of the database regarding process types, classification methods (e.g. Support Vector Machine) from the field of supervised learning are used. The necessary data quality requires selection of suitable methods as well as filters for smoothing occurring signal variations of the RSSI, the integration of methods for determination of correction factors depending on possible signal interference sources (columns, pallets) as well as the configuration of the used technology. The parameter settings on which respective algorithms are based have a further significant influence on result quality of the classification methods, correction models and methods for visualizing the position profiles used. The accuracy of classification algorithms can be improved up to 30% by selected parameter variation; this has already been proven in studies. Similar potentials can be observed with parameter variation of methods and filters for signal smoothing. Thus, there is increased interest in obtaining detailed results on the influence of parameter and factor combinations on data quality in this area. The overall methodology is realized with a modular software architecture consisting of independently modules for data acquisition, data preparation and data storage. The demonstrator for initialization and data acquisition is available as mobile Java-based application. The data preparation, including methods for signal smoothing, are Python-based with the possibility to vary parameter settings and to store them in the database (SQLite). The evaluation is divided into two separate software modules with database connection: the achievement of an automated assignment of defined process classes to distance data using selected classification algorithms and the visualization as well as reporting in terms of a graphical user interface (GUI).

Keywords: event-based tracing, machine learning, process classification, parameter settings, RSSI, signal smoothing

Procedia PDF Downloads 102

Authors: Pedro M. Rodrigues, Claudia Raposo, Denise Schrama, Marco Cerqueira

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Farmed fish welfare is a very recent concept, widely discussed among the scientific community. Consumers’ interest regarding farmed animal welfare standards has significantly increased in the last years posing a huge challenge to producers in order to maintain an equilibrium between good welfare principles and productivity, while simultaneously achieve public acceptance. The major bottleneck of standard aquaculture is to impair considerably fish welfare throughout the production cycle and with this, the quality of fish protein. Welfare assessment in farmed fish is undertaken through the evaluation of fish stress responses. Primary and secondary stress responses include release of cortisol and glucose and lactate to the blood stream, respectively, which are currently the most commonly used indicators of stress exposure. However, the reliability of these indicators is highly dubious, due to a high variability of fish responses to an acute stress and the adaptation of the animal to a repetitive chronic stress. Our objective is to use comparative proteomics to identify and validate a fingerprint of proteins that can present an more reliable alternative to the already established welfare indicators. In this way, the culture conditions will improve and there will be a higher perception of mechanisms and metabolic pathway involved in the produced organism’s welfare. Due to its high economical importance in Portuguese aquaculture Gilthead seabream will be the elected species for this study. Protein extracts from Gilthead Seabream fish muscle, liver and plasma, reared for a 3 month period under optimized culture conditions (control) and induced stress conditions (Handling, high densities, and Hipoxia) are collected and used to identify a putative fish welfare protein markers fingerprint using a proteomics approach. Three tanks per condition and 3 biological replicates per tank are used for each analisys. Briefly, proteins from target tissue/fluid are extracted using standard established protocols. Protein extracts are then separated using 2D-DIGE (Difference gel electrophoresis). Proteins differentially expressed between control and induced stress conditions will be identified by mass spectrometry (LC-Ms/Ms) using NCBInr (taxonomic level - Actinopterygii) databank and Mascot search engine. The statistical analysis is performed using the R software environment, having used a one-tailed Mann-Whitney U-test (p < 0.05) to assess which proteins were differentially expressed in a statistically significant way. Validation of these proteins will be done by comparison of the RT-qPCR (Quantitative reverse transcription polymerase chain reaction) expressed genes pattern with the proteomic profile. Cortisol, glucose, and lactate are also measured in order to confirm or refute the reliability of these indicators. The identified liver proteins under handling and high densities induced stress conditions are responsible and involved in several metabolic pathways like primary metabolism (i.e. glycolysis, gluconeogenesis), ammonia metabolism, cytoskeleton proteins, signalizing proteins, lipid transport. Validition of these proteins as well as identical analysis in muscle and plasma are underway. Proteomics is a promising high-throughput technique that can be successfully applied to identify putative welfare protein biomarkers in farmed fish.

Keywords: aquaculture, fish welfare, proteomics, welfare biomarkers

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Authors: Mona Ghafouri-Azar, Sara Diamond, Jeremy Bowes, Grace Yuan, Aimee Burnett, Michelle Wyndham-West, Sara Wagner, Anand Pariyarath

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Transportation is the fastest growing source of greenhouse gas emissions worldwide. In Canada, it is responsible for 23% of total CO2emissions from fuel combustion, and emissions from the transportation sector are the second largest source of emissions after the oil and gas sector. Currently, most Canadian public transportation systems rely on buses that operateon fossil fuels.Canada is currently investing billions of dollars to replacediesel buses with electric busesas this isperceived to have a significant impact on climate mitigation. This paper focuses on the possible impacts of zero emission buses (ZEB) on sustainable development, considering three dimensions of sustainability; environmental quality, economic growth, and social development.A sustainable transportation system is one that is safe, affordable, accessible, efficient, and resilient and that contributes minimal emissions of carbon and other pollutants.To enable implementation of these goals, relevant indicators were selected and defined that measure progress towards a sustainable transportation system. These were drawn from Canadian and international examples. Studies compare different European cities in terms of development, sustainability, and infrastructures, by using transport performance indicators. A Normalized Transport Sustainability index measures and compares policies in different urban areas and allows fine-tuning of policies. Analysts use a number ofmethods for sustainable analysis, like cost-benefit analysis (CBA) toassess economic benefit, life-cycle assessment (LCA) to assess social, economic, and environment factors and goals, and multi-criteria decision making (MCDM) analysis which can comparediffering stakeholder preferences.A multi criteria decision making approach is an appropriate methodology to plan and evaluate sustainable transit development and to provide insights and meaningful information for decision makers and transit agencies. It is essential to develop a system thataggregates specific discrete indices to assess the sustainability of transportation systems.Theseprioritize indicators appropriate for the differentCanadian transit system agencies and theirpreferences and requirements. This studywill develop an integrating index that alliesexistingdiscrete indexes to supporta reliable comparison between the current transportation system (diesel buses) and the new ZEB system emerging in Canada. As a first step, theindexes for each category are selected, and the index matrix constructed. Second, the selected indicators arenormalized to remove anyinconsistency between them. Next, the normalized matrix isweighted based on the relative importance of each index to the main domains of sustainability using the analytical hierarchy process (AHP) method. This is accomplished through expert judgement around the relative importance of different attributes with respect to the goals through apairwise comparison matrix. The considerationof multiple environmental, economic, and social factors (including equity and health) is integrated intoa sustainable transit planning index (STPI) which supportsrealistic ZEB implementation in Canada and beyond and is useful to different stakeholders, agencies, and ministries.

Keywords: zero emission buses, sustainability, sustainable transit, transportation, analytical hierarchy process, environment, economy, social

Procedia PDF Downloads 96

Authors: Hugo Daneluzzo, Christelle Rabbat, Alan Jean-Marie

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Water electrolysis is one of the most advanced technologies for producing hydrogen and can be easily combined with electricity from different sources. Under the influence of electric current, water molecules can be split into oxygen and hydrogen. The production of hydrogen by water electrolysis favors the integration of renewable energy sources into the energy mix by compensating for their intermittence through the storage of the energy produced when production exceeds demand and its release during off-peak production periods. Among the various electrolysis technologies, anion exchange membrane (AEM) electrolyser cells are emerging as a reliable technology for water electrolysis. Modeling and simulation are effective tools to save time, money, and effort during the optimization of operating conditions and the investigation of the design. The modeling and simulation become even more important when dealing with multiphysics dynamic systems. One of those systems is the AEM electrolysis cell involving complex physico-chemical reactions. Once developed, models may be utilized to comprehend the mechanisms to control and detect flaws in the systems. Several modeling methods have been initiated by scientists. These methods can be separated into two main approaches, namely equation-based modeling and graph-based modeling. The former approach is less user-friendly and difficult to update as it is based on ordinary or partial differential equations to represent the systems. However, the latter approach is more user-friendly and allows a clear representation of physical phenomena. In this case, the system is depicted by connecting subsystems, so-called blocks, through ports based on their physical interactions, hence being suitable for multiphysics systems. Among the graphical modelling methods, the bond graph is receiving increasing attention as being domain-independent and relying on the energy exchange between the components of the system. At present, few studies have investigated the modelling of AEM systems. A mathematical model and a bond graph model were used in previous studies to model the electrolysis cell performance. In this study, experimental data from literature were simulated using OpenModelica using bond graphs and mathematical approaches. The polarization curves at different operating conditions obtained by both approaches were compared with experimental ones. It was stated that both models predicted satisfactorily the polarization curves with error margins lower than 2% for equation-based models and lower than 5% for the bond graph model. The activation polarization of hydrogen evolution reactions (HER) and oxygen evolution reactions (OER) were behind the voltage loss in the AEM electrolyzer, whereas ion conduction through the membrane resulted in the ohmic loss. Therefore, highly active electro-catalysts are required for both HER and OER while high-conductivity AEMs are needed for effectively lowering the ohmic losses. The bond graph simulation of the polarisation curve for operating conditions at various temperatures has illustrated that voltage increases with temperature owing to the technology of the membrane. Simulation of the polarisation curve can be tested virtually, hence resulting in reduced cost and time involved due to experimental testing and improved design optimization. Further improvements can be made by implementing the bond graph model in a real power-to-gas-to-power scenario.

Keywords: hydrogen production, anion-exchange membrane, electrolyzer, mathematical modeling, multiphysics modeling

Procedia PDF Downloads 54

Authors: Ugo Galvanetto, Pirto G. Pavan, Mirco Zaccariotto

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The discipline of Computer-integrated surgery (CIS) will provide equipment able to improve the efficiency of healthcare systems and, which is more important, clinical results. Surgeons and machines will cooperate in new ways that will extend surgeons’ ability to train, plan and carry out surgery. Patient specific CIS of the brain requires several steps: 1 - Fast generation of brain models. Based on image recognition of MR images and equipped with artificial intelligence, image recognition techniques should differentiate among all brain tissues and segment them. After that, automatic mesh generation should create the mathematical model of the brain in which the various tissues (white matter, grey matter, cerebrospinal fluid …) are clearly located in the correct positions. 2 – Reliable and fast simulation of the surgical process. Computational mechanics will be the crucial aspect of the entire procedure. New algorithms will be used to simulate the mechanical behaviour of cutting through cerebral tissues. 3 – Real time provision of visual and haptic feedback A sophisticated human-machine interface based on ergonomics and psychology will provide the feedback to the surgeon. The present work will address in particular point 2. Modelling the cutting of soft tissue in a structure as complex as the human brain is an extremely challenging problem in computational mechanics. The finite element method (FEM), that accurately represents complex geometries and accounts for material and geometrical nonlinearities, is the most used computational tool to simulate the mechanical response of soft tissues. However, the main drawback of FEM lies in the mechanics theory on which it is based, classical continuum Mechanics, which assumes matter is a continuum with no discontinuity. FEM must resort to complex tools such as pre-defined cohesive zones, external phase-field variables, and demanding remeshing techniques to include discontinuities. However, all approaches to equip FEM computational methods with the capability to describe material separation, such as interface elements with cohesive zone models, X-FEM, element erosion, phase-field, have some drawbacks that make them unsuitable for surgery simulation. Interface elements require a-priori knowledge of crack paths. The use of XFEM in 3D is cumbersome. Element erosion does not conserve mass. The Phase Field approach adopts a diffusive crack model instead of describing true tissue separation typical of surgical procedures. Modelling discontinuities, so difficult when using computational approaches based on classical continuum Mechanics, is instead easy for novel computational methods based on Peridynamics (PD). PD is a non-local theory of mechanics formulated with no use of spatial derivatives. Its governing equations are valid at points or surfaces of discontinuity, and it is, therefore especially suited to describe crack propagation and fragmentation problems. Moreover, PD does not require any criterium to decide the direction of crack propagation or the conditions for crack branching or coalescence; in the PD-based computational methods, cracks develop spontaneously in the way which is the most convenient from an energy point of view. Therefore, in PD computational methods, crack propagation in 3D is as easy as it is in 2D, with a remarkable advantage with respect to all other computational techniques.

Keywords: computational mechanics, peridynamics, finite element, biomechanics

Procedia PDF Downloads 50

Authors: Jesus Carretero, Mario Vasile, Javier Garcia-Blas, Felix Garcia-Carballeira

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Supporting cross-border secure and reliable exchange of data and documents and to promote data interoperability is critical for Europe to enhance sector (like eFinance, eJustice and eHealth). This work presents the status and results of the European Project MADE, a Research Project funded by Connecting Europe facility Programme, to provide secure e-invoicing and e-document exchange systems among Europe countries in compliance with the eIDAS Regulation (Regulation EU 910/2014 on electronic identification and trust services). The main goal of MADE is to develop six new AS4 Access Points and SMP in Europe to provide secure document exchanges using the eDelivery DSI (Digital Service Infrastructure) amongst both private and public entities. Moreover, the project demonstrates the feasibility and interest of the solution provided by providing several months of interoperability among the providers of the six partners in different EU countries. To achieve those goals, we have followed a methodology setting first a common background for requirements in the partner countries and the European regulations. Then, the partners have implemented access points in each country, including their service metadata publisher (SMP), to allow the access to their clients to the pan-European network. Finally, we have setup interoperability tests with the other access points of the consortium. The tests will include the use of each entity production-ready Information Systems that process the data to confirm all steps of the data exchange. For the access points, we have chosen AS4 instead of other existing alternatives because it supports multiple payloads, native web services, pulling facilities, lightweight client implementations, modern crypto algorithms, and more authentication types, like username-password and X.509 authentication and SAML authentication. The main contribution of MADE project is to open the path for European companies to use eDelivery services with cross-border exchange of electronic documents following PEPPOL (Pan-European Public Procurement Online) based on the e-SENS AS4 Profile. It also includes the development/integration of new components, integration of new and existing logging and traceability solutions and maintenance tool support for PKI. Moreover, we have found that most companies are still not ready to support those profiles. Thus further efforts will be needed to promote this technology into the companies. The consortium includes the following 9 partners. From them, 2 are research institutions: University Carlos III of Madrid (Coordinator), and Universidad Politecnica de Valencia. The other 7 (EDICOM, BIZbrains, Officient, Aksesspunkt Norge, eConnect, LMT group, Unimaze) are private entities specialized in secure delivery of electronic documents and information integration brokerage in their respective countries. To achieve cross-border operativity, they will include AS4 and SMP services in their platforms according to the EU Core Service Platform. Made project is instrumental to test the feasibility of cross-border documents eDelivery in Europe. If successful, not only einvoices, but many other types of documents will be securely exchanged through Europe. It will be the base to extend the network to the whole Europe. This project has been funded under the Connecting Europe Facility Agreement number: INEA/CEF/ICT/A2016/1278042. Action No: 2016-EU-IA-0063.

Keywords: security, e-delivery, e-invoicing, e-delivery, e-document exchange, trust

Procedia PDF Downloads 227

Authors: Imen Asma Mbarek, Alexis Rusinek, Etienne Petit, Guy Sutter, Gautier List

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Over the past two decades, the automotive, aerospace and army industries have been paying an increasing attention to Finite Elements (FE) numerical simulations of the fracture process of their structures. Thanks to the numerical simulations, it is nowadays possible to analyze several problems involving costly and dangerous extreme loadings safely and at a reduced cost such as blast or ballistic impact problems. The present paper is concerned with ballistic impact and perforation problems involving ductile fracture of thin armor steel targets. The target fracture process depends usually on various parameters: the projectile nose shape, the target thickness and its mechanical properties as well as the impact conditions (friction, oblique/normal impact...). In this work, the investigations are concerned with the normal impact of a conical head-shaped projectile on thin armor steel targets. The main aim is to establish a comparative study of four fracture criteria that are commonly used in the fracture process simulations of structures subjected to extreme loadings such as ballistic impact and perforation. Usually, the damage initiation results from a complex physical process that occurs at the micromechanical scale. On a macro scale and according to the following fracture models, the variables on which the fracture depends are mainly the stress triaxiality ƞ, the strain rate, temperature T, and eventually the Lode angle parameter Ɵ. The four failure criteria are: the critical strain to failure model, the Johnson-Cook model, the Wierzbicki model and the Modified Hosford-Coulomb model MHC. Using the SEM, the observations of the fracture facies of tension specimen and of armor steel targets impacted at low and high incident velocities show that the fracture of the specimens is a ductile fracture. The failure mode of the targets is petalling with crack propagation and the fracture facies are covered with micro-cavities. The parameters of each ductile fracture model have been identified for three armor steels and the applicability of each criterion was evaluated using experimental investigations coupled to numerical simulations. Two loading paths were investigated in this study, under a wide range of strain rates. Namely, quasi-static and intermediate uniaxial tension and quasi-static and dynamic double shear testing allow covering various values of stress triaxiality ƞ and of the Lode angle parameter Ɵ. All experiments were conducted on three different armor steel specimen under quasi-static strain rates ranging from 10-4 to 10-1 1/s and at three different temperatures ranging from 297K to 500K, allowing drawing the influence of temperature on the fracture process. Intermediate tension testing was coupled to dynamic double shear experiments conducted on the Hopkinson tube device, allowing to spot the effect of high strain rate on the damage evolution and the crack propagation. The aforementioned fracture criteria are implemented into the FE code ABAQUS via VUMAT subroutine and they were coupled to suitable constitutive relations allow having reliable results of ballistic impact problems simulation. The calibration of the four damage criteria as well as a concise evaluation of the applicability of each criterion are detailed in this work.

Keywords: armor steels, ballistic impact, damage criteria, ductile fracture, SEM

Procedia PDF Downloads 288

Authors: Chung-Ming Lo, Chung-Chien Lee

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In many countries, the lifetime prevalence of shoulder pain is up to 70%. In America, the health care system spends 7 billion per year about the healthy issues of shoulder pain. With respect to the origin, up to 70% of shoulder pain is attributed to rotator cuff lesions This study proposed a computer-aided diagnosis (CAD) system to assist radiologists classifying rotator cuff lesions with less operator dependence. Quantitative features were extracted from the shoulder ultrasound images acquired using an ALOKA alpha-6 US scanner (Hitachi-Aloka Medical, Tokyo, Japan) with linear array probe (scan width: 36mm) ranging from 5 to 13 MHz. During examination, the postures of the examined patients are standard sitting position and are followed by the regular routine. After acquisition, the shoulder US images were drawn out from the scanner and stored as 8-bit images with pixel value ranging from 0 to 255. Upon the sonographic appearance, the boundary of each lesion was delineated by a physician to indicate the specific pattern for analysis. The three lesion categories for classification were composed of 20 cases of tendon inflammation, 18 cases of calcific tendonitis, and 18 cases of supraspinatus tear. For each lesion, second-order statistics were quantified in the feature extraction. The second-order statistics were the texture features describing the correlations between adjacent pixels in a lesion. Because echogenicity patterns were expressed via grey-scale. The grey-scale co-occurrence matrixes with four angles of adjacent pixels were used. The texture metrics included the mean and standard deviation of energy, entropy, correlation, inverse different moment, inertia, cluster shade, cluster prominence, and Haralick correlation. Then, the quantitative features were combined in a multinomial logistic regression classifier to generate a prediction model of rotator cuff lesions. Multinomial logistic regression classifier is widely used in the classification of more than two categories such as the three lesion types used in this study. In the classifier, backward elimination was used to select a feature subset which is the most relevant. They were selected from the trained classifier with the lowest error rate. Leave-one-out cross-validation was used to evaluate the performance of the classifier. Each case was left out of the total cases and used to test the trained result by the remaining cases. According to the physician’s assessment, the performance of the proposed CAD system was shown by the accuracy. As a result, the proposed system achieved an accuracy of 86%. A CAD system based on the statistical texture features to interpret echogenicity values in shoulder musculoskeletal ultrasound was established to generate a prediction model for rotator cuff lesions. Clinically, it is difficult to distinguish some kinds of rotator cuff lesions, especially partial-thickness tear of rotator cuff. The shoulder orthopaedic surgeon and musculoskeletal radiologist reported greater diagnostic test accuracy than general radiologist or ultrasonographers based on the available literature. Consequently, the proposed CAD system which was developed according to the experiment of the shoulder orthopaedic surgeon can provide reliable suggestions to general radiologists or ultrasonographers. More quantitative features related to the specific patterns of different lesion types would be investigated in the further study to improve the prediction.

Keywords: shoulder ultrasound, rotator cuff lesions, texture, computer-aided diagnosis

Procedia PDF Downloads 254

Authors: Fossarello Maurizio, Mattana Giorgio, Tatti Filippo.

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The most widely performed surgical procedure in Open-Angle Glaucoma (OAG) is trabeculectomy. Although this filtering procedure is extremely effective, surgical failure and postoperative complications are reported. Due to the its invasive nature and possible complications, trabeculectomy is usually reserved, in practice, for patients who are refractory to medical and laser therapy. Recently, a number of micro-invasive surgical techniques (MIGS: Micro-Invasive Glaucoma Surgery), have been introduced in clinical practice. They meet the criteria of micro-incisional approach, minimal tissue damage, short surgical time, reliable IOP reduction, extremely high safety profile and rapid post-operative recovery. Xen45 Gel Implant (Allergan, Dublin, Ireland) is one of the MIGS alternatives, and consists in a porcine gelatin tube designed to create an aqueous flow from the anterior chamber to the subconjunctival space, bypassing the resistance of the trabecular meshwork. In this study we report the results of this technique as a favorable option in the treatment of OAG for its benefits in term of efficacy and safety, either alone or in combination with cataract surgery. This is a retrospective, single-center study conducted in consecutive OAG patients, who underwent Xen45 Gel Stent implantation alone or in combination with phacoemulsification, from October 2018 to June 2019. The primary endpoint of the study was to evaluate the reduction of both IOP and number of antiglaucoma medications at 12 months. The secondary endpoint was to correlate filtering bleb morphology evaluated by means of anterior segment OCT with efficacy in IOP lowering and eventual further procedures requirement. Data were recorded on Microsoft Excel and study analysis was performed using Microsoft Excel and SPSS (IBM). Mean values with standard deviations were calculated for IOPs and number of antiglaucoma medications at all points. Kolmogorov-Smirnov test showed that IOP followed a normal distribution at all time, therefore the paired Student’s T test was used to compare baseline and postoperative mean IOP. Correlation between postoperative Day 1 IOP and Month 12 IOP was evaluated using Pearson coefficient. Thirty-six eyes of 36 patients were evaluated. As compared to baseline, mean IOP and the mean number of antiglaucoma medications significantly decreased from 27,33 ± 7,67 mmHg to 16,3 ± 2,89 mmHg (38,8% reduction) and from 2,64 ± 1,39 to 0,42 ± 0,8 (84% reduction), respectively, at 12 months after surgery (both p < 0,001). According to bleb morphology, eyes were divided in uniform group (n=8, 22,2%), subconjunctival separation group (n=5, 13,9%), microcystic multiform group (n=9, 25%) and multiple internal layer group (n=14, 38,9%). Comparing to baseline, there was no significative difference in IOP between the 4 groups at month 12 follow-up visit. Adverse events included bleb function decrease (n=14, 38,9%), hypotony (n=8, 22,2%) and choroidal detachment (n=2, 5,6%). All eyes presenting bleb flattening underwent needling and MMC injection. The higher percentage of patients that required secondary needling was in the uniform group (75%), with a significant difference between the groups (p=0,03). Xen45 gel stent, either alone or in combination with phacoemulsification, provided a significant lowering in both IOP and medical antiglaucoma treatment and an elevated safety profile.

Keywords: anterior segment OCT, bleb morphology, micro-invasive glaucoma surgery, open angle glaucoma, Xen45 gel implant

Procedia PDF Downloads 103

Authors: Maria Corazon Tapang-Lopez, Alyn Joy Dela Cruz Baltazar, Bobby Jones Villanueva Domdom

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The requisite for an organization implementing quality management system to sustain its compliance to the requirements and commitment for continuous improvement is even higher. It is expected that the offices and units has high and consistent compliance to the established processes and procedures. The Development Academy of the Philippines has been operating under project management to which is has a quality management certification. To further realize its mandate as a think-tank and capacity builder of the government, DAP expanded its operation and started to grant graduate degree through its Graduate School of Public and Development Management (GSPDM). As the academic arm of the Academy, GSPDM offers graduate degree programs on public management and productivity & quality aligned to the institutional trusts. For a time, the documented procedures and processes of a project management seem to fit the Graduate School. However, there has been a significant growth in the operations of the GSPDM in terms of the graduate programs offered that directly increase the number of students. There is an apparent necessity to align the project management system into a more educational system otherwise it will no longer be responsive to the development that are taking place. The strongly advocate and encourage its students to pursue internal and external improvement to cope up with the challenges of providing quality service to their own clients and to our country. If innovation will not take roots in the grounds of GSPDM, then how will it serve the purpose of “walking the talk”? This research was conducted to assess the diverse flow of the existing internal operations and processes of the DAP’s project management and GSPDM’s school management that will serve as basis to develop a system that will harmonize into one, the Learning Management System. The study documented the existing process of GSPDM following the project management phases of conceptualization & development, negotiation & contracting, mobilization, implementation, and closure into different flow charts of the key activities. The primary source of information as respondents were the different groups involved into the delivery of graduate programs - the executive, learning management team and administrative support offices. The Learning Management System (LMS) shall capture the unique and critical processes of the GSPDM as a degree-granting unit of the Academy. The LMS is the harmonized project management and school management system that shall serve as the standard system and procedure for all the programs within the GSPDM. The unique processes cover the three important areas of school management – student, curriculum, and faculty. The required processes of these main areas such as enrolment, course syllabus development, and faculty evaluation were appropriately placed within the phases of the project management system. Further, the research shall identify critical reports and generate manageable documents and records to ensure accuracy, consistency and reliable information. The researchers had an in-depth review of the DAP-GSDPM’s mandate, analyze the various documents, and conducted series of focused group discussions. A comprehensive review on flow chart system prior and various models of school management systems were made. Subsequently, the final output of the research is a work instructions manual that will be presented to the Academy’s Quality Management Council and eventually an additional scope for ISO certification. The manual shall include documented forms, iterative flow charts and program Gantt chart that will have a parallel development of automated systems.

Keywords: productivity, quality, learning management system, agency-based graduate school

Procedia PDF Downloads 294

Authors: Danah Al-Selahi, Sulaiman Al-Ghunaim, Bashayer Sadiq, Fatma Al-Otaibi, Ali Ameen

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In light of recent changes affecting the Oil & Gas Industry, optimization measures have become imperative for all companies globally, including Kuwait Oil Company (KOC). To keep abreast of the dynamic market, a detailed Integrated Asset Plan (IAP) was developed to drive optimization across the organization, which was facilitated through the in-house developed software “Well Inventory Data Entry” (WIDE). This comprehensive and integrated approach enabled centralization of all planned asset components for better well planning, enhancement of performance, and to facilitate continuous improvement through performance tracking and midterm forecasting. Traditionally, this was hard to achieve as, in the past, various legacy methods were used. This paper briefly describes the methods successfully adopted to meet the company’s objective. IAPs were initially designed using computerized spreadsheets. However, as data captured became more complex and the number of stakeholders requiring and updating this information grew, the need to automate the conventional spreadsheets became apparent. WIDE, existing in other aspects of the company (namely, the Workover Optimization project), was utilized to meet the dynamic requirements of the IAP cycle. With the growth of extensive features to enhance the planning process, the tool evolved into a centralized data-hub for all asset-groups and technical support functions to analyze and infer from, leading WIDE to become the reference two-year operational plan for the entire company. To achieve WIDE’s goal of operational efficiency, asset-groups continuously add their parameters in a series of predefined workflows that enable the creation of a structured process which allows risk factors to be flagged and helps mitigation of the same. This tool dictates assigned responsibilities for all stakeholders in a method that enables continuous updates for daily performance measures and operational use. The reliable availability of WIDE, combined with its user-friendliness and easy accessibility, created a platform of cross-functionality amongst all asset-groups and technical support groups to update contents of their respective planning parameters. The home-grown entity was implemented across the entire company and tailored to feed in internal processes of several stakeholders across the company. Furthermore, the implementation of change management and root cause analysis techniques captured the dysfunctionality of previous plans, which in turn resulted in the improvement of already existing mechanisms of planning within the IAP. The detailed elucidation of the 2 year plan flagged any upcoming risks and shortfalls foreseen in the plan. All results were translated into a series of developments that propelled the tool’s capabilities beyond planning and into operations (such as Asset Production Forecasts, setting KPIs, and estimating operational needs). This process exemplifies the ability and reach of applying advanced development techniques to seamlessly integrated the planning parameters of various assets and technical support groups. These techniques enables the enhancement of integrating planning data workflows that ultimately lay the founding plans towards an epoch of accuracy and reliability. As such, benchmarks of establishing a set of standard goals are created to ensure the constant improvement of the efficiency of the entire planning and operational structure.

Keywords: automation, integration, value, communication

Procedia PDF Downloads 117

Authors: M. Kadela

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The load caused by the traffic movement should be transferred in the road constructions in a harmless way to the pavement as follows: − on the stiff upper layers of the structure (e.g. layers of asphalt: abrading and binding), and − through the layers of principal and secondary substructure, − on the subsoil, directly or through an improved subsoil layer. Reliable description of the interaction proceeding in a system “road construction – subsoil” should be in such case one of the basic requirements of the assessment of the size of internal forces of structure and its durability. Analyses of road constructions are based on: − elements of mechanics, which allows to create computational models, and − results of the experiments included in the criteria of fatigue life analyses. Above approach is a fundamental feature of commonly used mechanistic methods. They allow to use in the conducted evaluations of the fatigue life of structures arbitrarily complex numerical computational models. Considering the work of the system “road construction – subsoil”, it is commonly accepted that, as a result of repetitive loads on the subsoil under pavement, the growth of relatively small deformation in the initial phase is recognized, then this increase disappears, and the deformation takes the character completely reversible. The reliability of calculation model is combined with appropriate use (for a given type of analysis) of constitutive relationships. Phenomena occurring in the initial stage of the system “road construction – subsoil” is unfortunately difficult to interpret in the modeling process. The classic interpretation of the behavior of the material in the elastic-plastic model (e-p) is that elastic phase of the work (e) is undergoing to phase (e-p) by increasing the load (or growth of deformation in the damaging structure). The paper presents the essence of the calibration process of cooperating subsystem in the calculation model of the system “road construction – subsoil”, created for the mechanistic analysis. Calibration process was directed to show the impact of applied constitutive models on its deformation and stress response. The proper comparative base for assessing the reliability of created. This work was supported by the on-going research project “Stabilization of weak soil by application of layer of foamed concrete used in contact with subsoil” (LIDER/022/537/L-4/NCBR/2013) financed by The National Centre for Research and Development within the LIDER Programme. M. Kadela is with the Department of Building Construction Elements and Building Structures on Mining Areas, Building Research Institute, Silesian Branch, Katowice, Poland (phone: +48 32 730 29 47; fax: +48 32 730 25 22; e-mail: m.kadela@ itb.pl). models should be, however, the actual, monitored system “road construction – subsoil”. The paper presents too behavior of subsoil under cyclic load transmitted by pavement layers. The response of subsoil to cyclic load is recorded in situ by the observation system (sensors) installed on the testing ground prepared for this purpose, being a part of the test road near Katowice, in Poland. A different behavior of the homogeneous subsoil under pavement is observed for different seasons of the year, when pavement construction works as a flexible structure in summer, and as a rigid plate in winter. Albeit the observed character of subsoil response is the same regardless of the applied load and area values, this response can be divided into: - zone of indirect action of the applied load; this zone extends to the depth of 1,0 m under the pavement, - zone of a small strain, extending to about 2,0 m.

Keywords: road structure, constitutive model, calculation model, pavement, soil, FEA, response of soil, monitored system

Procedia PDF Downloads 325

Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

Procedia PDF Downloads 51

Authors: H. K. Esfahani, B. Datta

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Groundwater is one of the most important natural resources in many parts of the world; however it is widely polluted due to human activities. Currently, effective and reliable groundwater management and remediation strategies are obtained using characterization of groundwater pollution sources, where the measured data in monitoring locations are utilized to estimate the unknown pollutant source location and magnitude. However, accurately identifying characteristics of contaminant sources is a challenging task due to uncertainties in terms of predicting source flux injection, hydro-geological and geo-chemical parameters, and the concentration field measurement. Reactive transport of chemical species in contaminated groundwater systems, especially with multiple species, is a complex and highly non-linear geochemical process. Although sufficient concentration measurement data is essential to accurately identify sources characteristics, available data are often sparse and limited in quantity. Therefore, this inverse problem-solving method for characterizing unknown groundwater pollution sources is often considered ill-posed, complex and non- unique. Different methods have been utilized to identify pollution sources; however, the linked simulation-optimization approach is one effective method to obtain acceptable results under uncertainties in complex real life scenarios. With this approach, the numerical flow and contaminant transport simulation models are externally linked to an optimization algorithm, with the objective of minimizing the difference between measured concentration and estimated pollutant concentration at observation locations. Concentration measurement data are very important to accurately estimate pollution source properties; therefore, optimal design of the monitoring network is essential to gather adequate measured data at desired times and locations. Due to budget and physical restrictions, an efficient and effective approach for groundwater pollutant source characterization is to design an optimal monitoring network, especially when only inadequate and arbitrary concentration measurement data are initially available. In this approach, preliminary concentration observation data are utilized for preliminary source location, magnitude and duration of source activity identification, and these results are utilized for monitoring network design. Further, feedback information from the monitoring network is used as inputs for sequential monitoring network design, to improve the identification of unknown source characteristics. To design an effective monitoring network of observation wells, optimization and interpolation techniques are used. A simulation model should be utilized to accurately describe the aquifer properties in terms of hydro-geochemical parameters and boundary conditions. However, the simulation of the transport processes becomes complex when the pollutants are chemically reactive. Three dimensional transient flow and reactive contaminant transport process is considered. The proposed methodology uses HYDROGEOCHEM 5.0 (HGCH) as the simulation model for flow and transport processes with chemically multiple reactive species. Adaptive Simulated Annealing (ASA) is used as optimization algorithm in linked simulation-optimization methodology to identify the unknown source characteristics. Therefore, the aim of the present study is to develop a methodology to optimally design an effective monitoring network for pollution source characterization with reactive species in polluted aquifers. The performance of the developed methodology will be evaluated for an illustrative polluted aquifer sites, for example an abandoned mine site in Queensland, Australia.

Keywords: monitoring network design, source characterization, chemical reactive transport process, contaminated mine site

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Authors: Emiliya Tsankova, Genoveva Zlateva, Violeta Kostadinova

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The challenges modern education faces undoubtedly require reforms and innovations aimed at the reconceptualization of existing educational strategies, the introduction of new concepts and novel techniques and technologies related to the recasting of the aims of education and the remodeling of the content and methodology of education which would guarantee the streamlining of our education with basic European values. Aim: The aim of the current research is the development of a didactic technology for the assessment of the applicability and efficacy of game techniques in pedagogic practice calibrated to specific content and the age specificity of learners, as well as for evaluating the efficacy of such approaches for the facilitation of the acquisition of biological knowledge at a higher theoretical level. Results: In this research, we examine the objectivity, reliability and validity of two newly introduced diagnostic parameters for assessing the durability of the acquired knowledge. A pedagogic experiment has been carried out targeting the verification of the hypothesis that the introduction of game techniques in biological education leads to an increase in the quantity, quality and durability of the knowledge acquired by students. For the purposes of monitoring the effect of the application of the pedagogical technique employing game methodology on the durability of the acquired knowledge a test-base examination has been applied to students from a control group (CG) and students form an experimental group on the same content after a six-month period. The analysis is based on: 1.A study of the statistical significance of the differences of the tests for the CG and the EG, applied after a six-month period, which however is not indicative of the presence or absence of a marked effect from the applied pedagogic technique in cases when the entry levels of the two groups are different. 2.For a more reliable comparison, independently from the entry level of each group, another “indicator of efficacy of game techniques for the durability of knowledge” which has been used for the assessment of the achievement results and durability of this methodology of education. The monitoring of the studied parameters in their dynamic unfolding in different age groups of learners unquestionably reveals a positive effect of the introduction of game techniques in education in respect of durability and permanence of acquired knowledge. Methods: In the current research the following battery of methods and techniques of research for diagnostics has been employed: theoretical analysis and synthesis; an actual pedagogical experiment; questionnaire; didactic testing and mathematical and statistical methods. The data obtained have been used for the qualitative and quantitative of the results which reflect the efficacy of the applied methodology. Conclusion: The didactic model of the parameters researched in the framework of a specific study of pedagogic diagnostics is based on a general, interdisciplinary approach. Enhanced durability of the acquired knowledge proves the transition of that knowledge from short-term memory storage into long-term memory of pupils and students, which justifies the conclusion that didactic plays have beneficial effects for the betterment of learners’ cognitive skills. The innovations in teaching enhance the motivation, creativity and independent cognitive activity in the process of acquiring the material thought. The innovative methods allow for untraditional means for assessing the level of knowledge acquisition. This makes possible the timely discovery of knowledge gaps and the introduction of compensatory techniques, which in turn leads to deeper and more durable acquisition of knowledge.

Keywords: objectivity, reliability and validity of pedagogical diagnostic parameters introduced in the framework of a specific research

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Authors: Ana Fonseca, Ana Gouveia, Edgar Ramalho, Rita Henriques, Filipa Figueiredo, João Nunes

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Due to persistent climate pressures, there is a need to find a resilient economic system that is regenerative in nature. Bioeconomy offers the possibility of replacing non-renewable and non-biodegradable materials derived from fossil fuels with ones that are renewable and biodegradable, while a Circular Economy aims at sustainable and resource-efficient operations. The term "Circular Bioeconomy", which can be summarized as all activities that transform biomass for its use in various product streams, expresses the interaction between these two ideas. Portugal has a very favourable context to promote a Circular Bioeconomy due to its variety of climates and ecosystems, availability of biologically based resources, location, and geomorphology. Recently, there have been political and legislative efforts to develop the Portuguese Circular Bioeconomy. The Action Plan for a Sustainable Bioeconomy, approved in 2021, is composed of five axes of intervention, ranging from sustainable production and the use of regionally based biological resources to the development of a circular and sustainable bioindustry through research and innovation. However, as some statistics show, Portugal is still far from achieving circularity. According to Eurostat, Portugal has circularity rates of 2.8%, which is the second lowest among the member states of the European Union. Some challenges contribute to this scenario, including sectorial heterogeneity and fragmentation, prevalence of small producers, lack of attractiveness for younger generations, and absence of implementation of collaborative solutions amongst producers and along value chains.Regarding the Portuguese industrial sector, there is a tendency towards complex bureaucratic processes, which leads to economic and financial obstacles and an unclear national strategy. Together with the limited number of incentives the country has to offer to those that pretend to abandon the linear economic model, many entrepreneurs are hesitant to invest the capital needed to make their companies more circular. Absence of disaggregated, georeferenced, and reliable information regarding the actual availability of biological resources is also a major issue. Low literacy on bioeconomy among many of the sectoral agents and in society in general directly impacts the decisions of production and final consumption. The WinBio project seeks to outline a strategic approach for the management of weaknesses/opportunities in the technology transfer process, given the reality of the territory, through road mapping and national and international benchmarking. The developed work included the identification and analysis of agents in the interior region of Portugal, natural endogenous resources, products, and processes associated with potential development. Specific flow of biological wastes, possible value chains, and the potential for replacing critical raw materials with bio-based products was accessed, taking into consideration other countries with a matured bioeconomy. The study found food industry, agriculture, forestry, and fisheries generate huge amounts of waste streams, which in turn provide an opportunity for the establishment of local bio-industries powered by this biomass. The project identified biological resources with potential for replication and applicability in the Portuguese context. The richness of natural resources and potentials known in the interior region of Portugal is a major key to developing the Circular Economy and sustainability of the country.

Keywords: circular bioeconomy, interior region of portugal, regional development., public policy

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Authors: George Charkoftakis, Panagiotis Liosatos, Nicolas-Alexander Tatlas, Dimitrios Goustouridis, Stelios M. Potirakis

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E-maintenance is a relatively new concept, generally referring to maintenance management by monitoring assets over the Internet. One of the key links in the chain of an e-maintenance system is data acquisition and transmission. Specifically for the case of a fleet of heavy-duty vehicles, where the main challenge is the diversity of the vehicles and vehicle-embedded self-diagnostic/reporting technologies, the design of the data acquisition and transmission unit is a demanding task. This clear if one takes into account that a heavy-vehicles fleet assortment may range from vehicles with only a limited number of analog sensors monitored by dashboard light indicators and gauges to vehicles with plethora of sensors monitored by a vehicle computer producing digital reporting. The present work proposes an adaptable internet of things (IoT) sensor node that is capable of addressing this challenge. The proposed sensor node architecture is based on the increasingly popular single-board computer – expansion boards approach. In the proposed solution, the expansion boards undertake the tasks of position identification by means of a global navigation satellite system (GNSS), cellular connectivity by means of 3G/long-term evolution (LTE) modem, connectivity to on-board diagnostics (OBD), and connectivity to analog and digital sensors by means of a novel design of expansion board. Specifically, the later provides eight analog plus three digital sensor channels, as well as one on-board temperature / relative humidity sensor. The specific device offers a number of adaptability features based on appropriate zero-ohm resistor placement and appropriate value selection for limited number of passive components. For example, although in the standard configuration four voltage analog channels with constant voltage sources for the power supply of the corresponding sensors are available, up to two of these voltage channels can be converted to provide power to the connected sensors by means of corresponding constant current source circuits, whereas all parameters of analog sensor power supply and matching circuits are fully configurable offering the advantage of covering a wide variety of industrial sensors. Note that a key feature of the proposed sensor node, ensuring the reliable operation of the connected sensors, is the appropriate supply of external power to the connected sensors and their proper matching to the IoT sensor node. In standard mode, the IoT sensor node communicates to the data center through 3G/LTE, transmitting all digital/digitized sensor data, IoT device identity, and position. Moreover, the proposed IoT sensor node offers WiFi connectivity to mobile devices (smartphones, tablets) equipped with an appropriate application for the manual registration of vehicle- and driver-specific information, and these data are also forwarded to the data center. All control and communication tasks of the IoT sensor node are performed by dedicated firmware. It is programmed with a high-level language (Python) on top of a modern operating system (Linux). Acknowledgment: This research has been co-financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH—CREATE—INNOVATE (project code: T1EDK- 01359, IntelligentLogger).

Keywords: IoT sensor nodes, e-maintenance, single-board computers, sensor expansion boards, on-board diagnostics

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Authors: Benjamin Arazi

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Blockchain is the technology behind cryptocurrencies like Bitcoin. It revolutionizes the meaning of trust in the sense of offering total reliability without relying on any central entity that controls or supervises the system. The Wall Street Journal states: “Blockchain Marks the Next Step in the Internet’s Evolution”. Blockchain was listed as #1 in Linkedin – The Learning Blog “most in-demand hard skills needed in 2020”. As stated there: “Blockchain’s novel way to store, validate, authorize, and move data across the internet has evolved to securely store and send any digital asset”. GSMA, a leading Telco organization of mobile communications operators, declared that “Blockchain has the potential to be for value what the Internet has been for information”. Motivated by these seminal observations, this paper presents the foundations of a Blockchain-based “Internet of Assets” academic program that joins under one roof leading application areas that are characterized by the transfer of assets over communication lines. Two such areas, which are pillars of our economy, are Fintech – Financial Technology and mobile communications services. The next application in line is Healthcare. These challenges are met based on available extensive professional literature. Blockchain-based assets communication is based on extending the principle of Bitcoin, starting with the basic question: If digital money that travels across the universe can ‘prove its own validity’, can this principle be applied to digital content. A groundbreaking positive answer here led to the concept of “smart contract” and consequently to DLT - Distributed Ledger Technology, where the word ‘distributed’ relates to the non-existence of reliable central entities or trusted third parties. The terms Blockchain and DLT are frequently used interchangeably in various application areas. The World Bank Group compiled comprehensive reports, analyzing the contribution of DLT/Blockchain to Fintech. The European Central Bank and Bank of Japan are engaged in Project Stella, “Balancing confidentiality and auditability in a distributed ledger environment”. 130 DLT/Blockchain focused Fintech startups are now operating in Switzerland. Blockchain impact on mobile communications services is treated in detail by leading organizations. The TM Forum is a global industry association in the telecom industry, with over 850 member companies, mainly mobile operators, that generate US$2 trillion in revenue and serve five billion customers across 180 countries. From their perspective: “Blockchain is considered one of the digital economy’s most disruptive technologies”. Samples of Blockchain contributions to Fintech (taken from a World Bank document): Decentralization and disintermediation; Greater transparency and easier auditability; Automation & programmability; Immutability & verifiability; Gains in speed and efficiency; Cost reductions; Enhanced cyber security resilience. Samples of Blockchain contributions to the Telco industry. Establishing identity verification; Record of transactions for easy cost settlement; Automatic triggering of roaming contract which enables near-instantaneous charging and reduction in roaming fraud; Decentralized roaming agreements; Settling accounts per costs incurred in accordance with agreement tariffs. This clearly demonstrates an academic education structure where fundamental technologies are studied in classes together with these two application areas. Advanced courses, treating specific implementations then follow separately. All are under the roof of “Internet of Assets”.

Keywords: blockchain, education, financial technology, mobile telecommunications services

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Authors: G. K. Viswanadh, B. Rajasekhar, G. Venkata Ramana

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Water distribution networks play a vital role in ensuring a reliable supply of clean water to urban areas. However, they face several challenges, including pressure control, pump speed optimization, and burst event detection. This paper combines insights from two studies to address these critical issues in Water distribution networks, focusing on the specific context of Kapra Municipality, India. The first part of this research concentrates on optimizing pressure control and pump speed in complex Water distribution networks. It utilizes the EPANET- MATLAB Toolkit to integrate EPANET functionalities into the MATLAB environment, offering a comprehensive approach to network analysis. By optimizing Pressure Reduce Valves (PRVs) and variable speed pumps (VSPs), this study achieves remarkable results. In the Benchmark Water Distribution System (WDS), the proposed PRV optimization algorithm reduces average leakage by 20.64%, surpassing the previous achievement of 16.07%. When applied to the South-Central and East zone WDS of Kapra Municipality, it identifies PRV locations that were previously missed by existing algorithms, resulting in average leakage reductions of 22.04% and 10.47%. These reductions translate to significant daily Water savings, enhancing Water supply reliability and reducing energy consumption. The second part of this research addresses the pressing issue of burst event detection and localization within the Water Distribution System. Burst events are a major contributor to Water losses and repair expenses. The study employs wireless sensor technology to monitor pressure and flow rate in real time, enabling the detection of pipeline abnormalities, particularly burst events. The methodology relies on transient analysis of pressure signals, utilizing Cumulative Sum and Wavelet analysis techniques to robustly identify burst occurrences. To enhance precision, burst event localization is achieved through meticulous analysis of time differentials in the arrival of negative pressure waveforms across distinct pressure sensing points, aided by nodal matrix analysis. To evaluate the effectiveness of this methodology, a PVC Water pipeline test bed is employed, demonstrating the algorithm's success in detecting pipeline burst events at flow rates of 2-3 l/s. Remarkably, the algorithm achieves a localization error of merely 3 meters, outperforming previously established algorithms. This research presents a significant advancement in efficient burst event detection and localization within Water pipelines, holding the potential to markedly curtail Water losses and the concomitant financial implications. In conclusion, this combined research addresses critical challenges in Water distribution networks, offering solutions for optimizing pressure control, pump speed, burst event detection, and localization. These findings contribute to the enhancement of Water Distribution System, resulting in improved Water supply reliability, reduced Water losses, and substantial cost savings. The integrated approach presented in this paper holds promise for municipalities and utilities seeking to improve the efficiency and sustainability of their Water distribution networks.

Keywords: pressure reduce valve, complex networks, variable speed pump, wavelet transform, burst detection, CUSUM (Cumulative Sum), water pipeline monitoring

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Authors: Ho-Ting Wu, Kai-Wei Ke, Bo-Yu Huang, Liang-Lin Yan, Chun-Ting Lin

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With the advances in advanced technology, wireless sensor network (WSN) has become one of the most promising candidates to implement the wireless industrial internet of things (IIOT) architecture. However, the legacy IEEE 802.15.4 based WSN technology such as Zigbee system cannot meet the stringent QoS requirement of low powered, real-time, and highly reliable transmission imposed by the IIOT environment. Recently, the IEEE society developed IEEE 802.15.4e Time Slotted Channel Hopping (TSCH) access mode to serve this purpose. Furthermore, the IETF 6TiSCH working group has proposed standards to integrate IEEE 802.15.4e with IPv6 protocol smoothly to form a complete protocol stack for IIOT. In this work, we develop key network technologies for IEEE 802.15.4e based wireless IIoT architecture, focusing on practical design and system implementation. We realize the OpenWSN-based wireless IIOT system. The system architecture is divided into three main parts: web server, network manager, and sensor nodes. The web server provides user interface, allowing the user to view the status of sensor nodes and instruct sensor nodes to follow commands via user-friendly browser. The network manager is responsible for the establishment, maintenance, and management of scheduling and topology information. It executes centralized scheduling algorithm, sends the scheduling table to each node, as well as manages the sensing tasks of each device. Sensor nodes complete the assigned tasks and sends the sensed data. Furthermore, to prevent scheduling error due to packet loss, a schedule inspection mechanism is implemented to verify the correctness of the schedule table. In addition, when network topology changes, the system will act to generate a new schedule table based on the changed topology for ensuring the proper operation of the system. To enhance the system performance of such system, we further propose dynamic bandwidth allocation and distributed scheduling mechanisms. The developed distributed scheduling mechanism enables each individual sensor node to build, maintain and manage the dedicated link bandwidth with its parent and children nodes based on locally observed information by exchanging the Add/Delete commands via two processes. The first process, termed as the schedule initialization process, allows each sensor node pair to identify the available idle slots to allocate the basic dedicated transmission bandwidth. The second process, termed as the schedule adjustment process, enables each sensor node pair to adjust their allocated bandwidth dynamically according to the measured traffic loading. Such technology can sufficiently satisfy the dynamic bandwidth requirement in the frequently changing environments. Last but not least, we propose a packet retransmission scheme to enhance the system performance of the centralized scheduling algorithm when the packet delivery rate (PDR) is low. We propose a multi-frame retransmission mechanism to allow every single network node to resend each packet for at least the predefined number of times. The multi frame architecture is built according to the number of layers of the network topology. Performance results via simulation reveal that such retransmission scheme is able to provide sufficient high transmission reliability while maintaining low packet transmission latency. Therefore, the QoS requirement of IIoT can be achieved.

Keywords: IEEE 802.15.4e, industrial internet of things (IIOT), scheduling mechanisms, wireless sensor networks (WSN)

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Authors: Katarzyna Lubecka, Kirsty Flower, Megan Beetch, Lucinda Kurzava, Hannah Buvala, Samer Gawrieh, Suthat Liangpunsakul, Tracy Gonzalez, George McCabe, Naga Chalasani, James M. Flanagan, Barbara Stefanska

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Hepatocellular carcinoma (HCC), the most prevalent type of primary liver cancer, is the second leading cause of cancer death worldwide. Late onset of clinical symptoms in HCC results in late diagnosis and poor disease outcome. Approximately 85% of individuals with HCC have underlying liver cirrhosis. However, not all cirrhotic patients develop cancer. Reliable early detection biomarkers that can distinguish cirrhotic patients who will develop cancer from those who will not are urgently needed and could increase the cure rate from 5% to 80%. We used Illumina-450K microarray to test whether blood DNA, an easily accessible source of DNA, bear site-specific changes in DNA methylation in response to HCC before diagnosis with conventional tools (pre-diagnostic). Top 11 differentially methylated sites were selected for validation by pyrosequencing. The diagnostic potential of the 11 pyrosequenced probes was tested in blood samples from a prospective cohort of cirrhotic patients. We identified 971 differentially methylated CpG sites in pre-diagnostic HCC cases as compared with healthy controls (P < 0.05, paired Wilcoxon test, ICC ≥ 0.5). Nearly 76% of differentially methylated CpG sites showed lower levels of methylation in cases vs. controls (P = 2.973E-11, Wilcoxon test). Classification of the CpG sites according to their location relative to CpG islands and transcription start site revealed that those hypomethylated loci are located in regulatory regions important for gene transcription such as CpG island shores, promoters, and 5’UTR at higher frequency than hypermethylated sites. Among 735 CpG sites hypomethylated in cases vs. controls, 482 sites were assigned to gene coding regions whereas 236 hypermethylated sites corresponded to 160 genes. Bioinformatics analysis using GO, KEGG and DAVID knowledgebase indicate that differentially methylated CpG sites are located in genes associated with functions that are essential for gene transcription, cell adhesion, cell migration, and regulation of signal transduction pathways. Taking into account the magnitude of the difference, statistical significance, location, and consistency across the majority of matched pairs case-control, we selected 11 CpG loci corresponding to 10 genes for further validation by pyrosequencing. We established that methylation of CpG sites within 5 out of those 10 genes distinguish cirrhotic patients who subsequently developed HCC from those who stayed cancer free (cirrhotic controls), demonstrating potential as biomarkers of early detection in populations at risk. The best predictive value was detected for CpGs located within BARD1 (AUC=0.70, asymptotic significance ˂0.01). Using an additive logistic regression model, we further showed that 9 CpG loci within those 5 genes, that were covered in pyrosequenced probes, constitute a panel with high diagnostic accuracy (AUC=0.887; 95% CI:0.80-0.98). The panel was able to distinguish pre-diagnostic cases from cirrhotic controls free of cancer with 88% sensitivity at 70% specificity. Using blood as a minimally invasive material and pyrosequencing as a straightforward quantitative method, the established biomarker panel has high potential to be developed into a routine clinical test after validation in larger cohorts. This study was supported by Showalter Trust, American Cancer Society (IRG#14-190-56), and Purdue Center for Cancer Research (P30 CA023168) granted to BS.

Keywords: biomarker, DNA methylation, early detection, hepatocellular carcinoma

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