Search results for: algorithm symbol recognition

Authors: Joy Cao, Min Zhou

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Purpose: Acute Type A aortic dissection is a well-known cause of extremely high mortality rate. A highly accurate and cost-effective non-invasive predictor is critically needed so that the patient can be treated at earlier stage. Although various CFD approaches have been tried to establish some prediction frameworks, they are sensitive to uncertainty in both image segmentation and boundary conditions. Tedious pre-processing and demanding calibration procedures requirement further compound the issue, thus hampering their clinical applicability. Using the latest physics informed deep learning methods to establish an accurate and cost-effective predictor framework are amongst the main goals for a better Type A aortic dissection treatment. Methods: Via training a novel physics-informed deep residual network, with non-invasive 4D MRI displacement vectors as inputs, the trained model can cost-effectively calculate all these biomarkers: aortic blood pressure, WSS, and OSI, which are used to predict potential type A aortic dissection to avoid the high mortality events down the road. Results: The proposed deep learning method has been successfully trained and tested with both synthetic 3D aneurysm dataset and a clinical dataset in the aortic dissection context using Google colab environment. In both cases, the model has generated aortic blood pressure, WSS, and OSI results matching the expected patient’s health status. Conclusion: The proposed novel physics-informed deep residual network shows great potential to create a cost-effective, non-invasive predictor framework. Additional physics-based de-noising algorithm will be added to make the model more robust to clinical data noises. Further studies will be conducted in collaboration with big institutions such as Cleveland Clinic with more clinical samples to further improve the model’s clinical applicability.

Keywords: type-a aortic dissection, deep residual networks, blood flow modeling, data-driven modeling, non-invasive diagnostics, deep learning, artificial intelligence.

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Authors: Mathilde Pavis

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From Schumann to Van Gogh, Frida Kahlo, and Ray Charles, the stories narrating the careers of artists with physical or mental disabilities are becoming increasingly popular. From the emergence of ‘pathography’ at the end of 18th century to cinematographic portrayals, the work and lives of differently-abled creative individuals continue to fascinate readers, spectators and researchers. The achievements of those artists form the tip of the iceberg composed of complex politico-cultural movements which continue to advocate for wider recognition of disabled artists’ contribution to western culture. This paper envisages copyright law as a potential tool to such end. It investigates the array of rights available to artists with intellectual disabilities to assert their position as authors of their artwork in the twenty-first-century looking at international and national copyright laws (UK and US). Put simply, this paper questions whether an artist’s intellectual disability could be a barrier to assert their intellectual property rights over their creation. From a legal perspective, basic principles of non-discrimination would contradict the representation of artists’ disability as an obstacle to authorship as granted by intellectual property laws. Yet empirical studies reveal that artists with intellectual disabilities are often denied the opportunity to exercise their intellectual property rights or any form of agency over their work. In practice, it appears that, unlike other non-disabled artists, the prospect for differently-abled creators to make use of their right is contingent to the context in which the creative process takes place. Often will the management of such rights rest with the institution, art therapist or mediator involved in the artists’ work as the latter will have necessitated greater support than their non-disabled peers for a variety of reasons, either medical or practical. Moreover, the financial setbacks suffered by medical institutions and private therapy practices have renewed administrators’ and physicians’ interest in monetising the artworks produced under their supervision. Adding to those economic incentives, the rise of criminal and civil litigation in psychiatric cases has also encouraged the retention of patients’ work by therapists who feel compelled to keep comprehensive medical records to shield themselves from liability in the event of a lawsuit. Unspoken transactions, contracts, implied agreements and consent forms have thus progressively made their way into the relationship between those artists and their therapists or assistants, disregarding any notions of copyright. The question of artists’ authorship finds itself caught in an unusually multi-faceted web of issues formed by tightening purse strings, ethical concerns and the fear of civil or criminal liability. Whilst those issues are playing out behind closed doors, the popularity of what was once called the ‘Art of the Insane’ continues to grow and open new commercial avenues. This socio-economic context exacerbates the need to devise a legal framework able to help practitioners, artists and their advocates navigate through those issues in such a way that neither this minority nor our cultural heritage suffers from the fragmentation of the legal protection available to them.

Keywords: authorship, copyright law, intellectual disabilities, art therapy and mediation

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Authors: Tiziana Ferrero-Regis, Marissa Lindquist

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Circular Economy (CE) is increasingly seen as the reorganisation of production and consumption, and cities are acknowledged as the sources of many ecological and social problems; at the same time, they can be re-imagined through an ecologically and socially resilient future. The concept of the CE has received pointed critiques for its techno-deterministic orientation, focus on science and transformation by the policy. At the heart of our local re-imagining of the CE into circularity through contact zones there is the acknowledgment of collective, spontaneous and shared imaginations of alternative and sustainable futures through the creation of networks of community initiatives that are transformative, creating opportunities that simultaneously make cities rich and enrich humans. This paper presents a mapping project of the fashion and textile ecosystem in Brisbane, Queensland, Australia. Brisbane is currently the most aspirational city in Australia, as its population growth rate is the highest in the country. Yet, Brisbane is considered the least “fashion city” in the country. In contrast, the project revealed a greatly enhanced picture of distinct fashion and textile clusters across greater Brisbane and the adjacency of key services that may act to consolidate CE community contact zones. Clusters to the north of Brisbane and several locales to the south are zones of a greater mix between public/social amenities, walkable zones and local transport networks with educational precincts, community hubs, concentration of small enterprises, designers, artisans and waste recovery centers that will help to establish knowledge of key infrastructure networks that will support enmeshing these zones together. The paper presents two case studies of independent designers who work on new and re-designed clothing through recovering pre-consumer textiles and that operate from within creative precincts. The first case is designer Nelson Molloy, who recently returned to the inner city suburb of West End with their Chasing Zero Design project. The area was known in the 1980s and 1990s for its alternative lifestyle with creative independent production, thrifty clothing shops, alternative fashion and a socialist agenda. After 30 years of progressive gentrification of the suburb, which has dislocated many of the artists, designers and artisans, West End is seeing the return and amplification of clusters of artisans, artists, designers and architects. The other case study is Practice Studio, located in a new zone of creative growth, Bowen Hills, north of the CBD. Practice Studio combines retail with a workroom, offers repair and remaking services, becoming a point of reference for young and emerging Australian designers and artists. The paper demonstrates the spatial politics of the CE and the way in which new cultural capital is produced thanks to cultural specificities and resources. It argues for the recognition of contact zones that are created by local actors, communities and knowledge networks, whose grass-roots agency is fundamental for the co-production of CE’s systems of local governance.

Keywords: contact zones, circular citities, fashion and textiles, circular neighbourhoods, australia

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Authors: Jothilakshmy Nagammal

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This research paper deals with the different case studies, where the Form-Based Codes are adopted in general and the different implementation methods in particular are discussed to develop a method for formulating a new planning model. The organizing principle of the Form-Based Codes, the transect is used to zone the city into various context specific transects. An approach is adopted to develop the new planning model, city Specific Planning Model (CSPM), as a tool to achieve sustainability for any city in general. A case study comparison method in terms of the planning tools used, the code process adopted and the various control regulations implemented in thirty two different cities are done. The analysis shows that there are a variety of ways to implement form-based zoning concepts: Specific plans, a parallel or optional form-based code, transect-based code /smart code, required form-based standards or design guidelines. The case studies describe the positive and negative results from based zoning, Where it is implemented. From the different case studies on the method of the FBC, it is understood that the scale for formulating the Form-Based Code varies from parts of the city to the whole city. The regulating plan is prepared with the organizing principle as the transect in most of the cases. The various implementation methods adopted in these case studies for the formulation of Form-Based Codes are special districts like the Transit Oriented Development (TOD), traditional Neighbourhood Development (TND), specific plan and Street based. The implementation methods vary from mandatory, integrated and floating. To attain sustainability the research takes the approach of developing a regulating plan, using the transect as the organizing principle for the entire area of the city in general in formulating the Form-Based Codes for the selected Special Districts in the study area in specific, street based. Planning is most powerful when it is embedded in the broader context of systemic change and improvement. Systemic is best thought of as holistic, contextualized and stake holder-owned, While systematic can be thought of more as linear, generalisable, and typically top-down or expert driven. The systemic approach is a process that is based on the system theory and system design principles, which are too often ill understood by the general population and policy makers. The system theory embraces the importance of a global perspective, multiple components, interdependencies and interconnections in any system. In addition, the recognition that a change in one part of a system necessarily alters the rest of the system is a cornerstone of the system theory. The proposed regulating plan taking the transect as an organizing principle and Form-Based Codes to achieve sustainability of the city has to be a hybrid code, which is to be integrated within the existing system - A Systemic Approach with a Systematic Process. This approach of introducing a few form based zones into a conventional code could be effective in the phased replacement of an existing code. It could also be an effective way of responding to the near-term pressure of physical change in “sensitive” areas of the community. With this approach and method the new Context Specific Planning Model is created towards achieving sustainability is explained in detail this research paper.

Keywords: context based planning model, form based code, transect, systemic approach

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Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

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Authors: Haresh Sharma, Jaimini Luharia

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The ecology in the Western Himalayan region transforms with the change in altitude. This change is observed in terms of topography, species of flora and fauna and the quality of the soil. The current study focuses on women of indigenous communities of Pangi Valley, which is located in the state of Himachal Pradesh, India. The valley is bifurcated into three different areas –Saichu, Hudan Bhatori, and Sural Bhatori valleys. It is one of the most remote, rugged and difficult to access tribal regions of Chamba district. The altitude of the valley ranges from 2,000 m to 6,000 m above sea level. The Pangi valley is inhabited by ‘Pangwals’ and ‘Bhots’ tribes of the Himalayas who speak their local tribal language called’ Pangwali’. The valley is cut-off from the mainland due to heavy snow and lack of proper roads during peak winters. Due to difficult geographical location, the daily lives of the people are constantly challenged, and they are most of the times deprived of benefits targeted through government programs. However, the indigenous communities earn their livelihood through livestock and forest-based produce while some of them migrate to nearby places for better work. The current study involves snowball sampling methodology for data collection along with in-depth interviews of women members of Self-Help Groups and women farmers. The findings reveal that the lives of these indigenous communities largely depend on forest-based products. So, it creates all the more significance of enhancing, maintaining, and consuming natural resources sustainably. Under such circumstances, the women of the community play a significant role of guardians in conservation and protection of the forests. They are the custodians of traditional knowledge of environment conservation practices that have been followed for many years in the region. The present study also sought to establish a relationship between some of the development initiatives undertaken by the women in the valley that stimulate sustainable mountain economy and conservation practices. These initiatives include cultivation of products like hazelnut, ‘Gucchi’ rare quality mushroom, medicinal plants exclusively found in the region, thereby promoting long term sustainable conservation of agro-biodiversity of the Western Himalayan region. The measures taken by the community women are commendable as they ensure access and distribution of natural resources as well as manage them for future generations. Apart from this, the tribal women have actively formed Self-Help Groups promoting financial inclusion through various activities that augment ownership and accountability towards the overall development of the communities. But, the results also suggest that there’s not enough recognition given to women’s role in forests conservation practices due to several local socio-political reasons. There are not enough research studies done on communities of Pangi Valley due to inaccessibility created out of lack of proper roads and other resources. Also, there emerged a need to concretize indigenous and traditional knowledge of conservation practices followed by women in the community.

Keywords: forest conservation, indigenous community women, sustainable livelihoods, sustainable development, poverty alleviation, Western Himalayas

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Authors: O. F. Elkommos

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“Humour studies” is an interdisciplinary research area that is relatively recent. It interests researchers from the disciplines of psychology, sociology, medicine, nursing, in the work place, gender studies, among others, and certainly teaching, language learning, linguistics, and literature. Linguistic theories of humour research are numerous; some of which are of interest to the present study. In spite of the fact that humour courses are now taught in universities around the world in the Egyptian context it is not included. The purpose of the present study is two-fold: to review the state of arts and to show how linguistic theories of humour can be possibly used as an art and craft of teaching and of learning in EFL literature classes. In the present study linguistic theories of humour were applied to selected literary texts to interpret humour as an intrinsic artistic communicative competence challenge. Humour in the area of linguistics was seen as a fifth component of communicative competence of the second language leaner. In literature it was studied as satire, irony, wit, or comedy. Linguistic theories of humour now describe its linguistic structure, mechanism, function, and linguistic deviance. Semantic Script Theory of Verbal Humor (SSTH), General Theory of Verbal Humor (GTVH), Audience Based Theory of Humor (ABTH), and their extensions and subcategories as well as the pragmatic perspective were employed in the analyses. This research analysed the linguistic semantic structure of humour, its mechanism, and how the audience reader (teacher or learner) becomes an interactive interpreter of the humour. This promotes humour competence together with the linguistic, social, cultural, and discourse communicative competence. Studying humour as part of the literary texts and the perception of its function in the work also brings its positive association in class for educational purposes. Humour is by default a provoking/laughter-generated device. Incongruity recognition, perception and resolving it, is a cognitive mastery. This cognitive process involves a humour experience that lightens up the classroom and the mind. It establishes connections necessary for the learning process. In this context the study examined selected narratives to exemplify the application of the theories. It is, therefore, recommended that the theories would be taught and applied to literary texts for a better understanding of the language. Students will then develop their language competence. Teachers in EFL/ESL classes will teach the theories, assist students apply them and interpret text and in the process will also use humour. This is thus easing students' acquisition of the second language, making the classroom an enjoyable, cheerful, self-assuring, and self-illuminating experience for both themselves and their students. It is further recommended that courses of humour research studies should become an integral part of higher education curricula in Egypt.

Keywords: ABTH, deviance, disjuncture, episodic, GTVH, humour competence, humour comprehension, humour in the classroom, humour in the literary texts, humour research linguistic theories, incongruity-resolution, isotopy-disjunction, jab line, longer text joke, narrative story line (macro-micro), punch line, six knowledge resource, SSTH, stacks, strands, teaching linguistics, teaching literature, TEFL, TESL

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Authors: Mostafa Zandi, Ramin Mansouri

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Spillways are one of the most important hydraulic structures of dams that provide the stability of the dam and downstream areas at the time of flood. Morning-Glory spillway is one of the common spillways for discharging the overflow water behind dams, these kinds of spillways are constructed in dams with small reservoirs. In this research, the hydraulic flow characteristics of a morning-glory spillways are investigated with CFD model. Two dimensional unsteady RANS equations were solved numerically using Finite Volume Method. The PISO scheme was applied for the velocity-pressure coupling. The mostly used two-equation turbulence models, k- and k-, were chosen to model Reynolds shear stress term. The power law scheme was used for discretization of momentum, k , and  equations. The VOF method (geometrically reconstruction algorithm) was adopted for interface simulation. The results show that the fine computational grid, the input speed condition for the flow input boundary, and the output pressure for the boundaries that are in contact with the air provide the best possible results. Also, the standard wall function is chosen for the effect of the wall function, and the turbulent model k -ε (Standard) has the most consistent results with experimental results. When the jet is getting closer to end of basin, the computational results increase with the numerical results of their differences. The lower profile of the water jet has less sensitivity to the hydraulic jet profile than the hydraulic jet profile. In the pressure test, it was also found that the results show that the numerical values of the pressure in the lower landing number differ greatly in experimental results. The characteristics of the complex flows over a Morning-Glory spillway were studied numerically using a RANS solver. Grid study showed that numerical results of a 57512-node grid had the best agreement with the experimental values. The desired downstream channel length was preferred to be 1.5 meter, and the standard k-ε turbulence model produced the best results in Morning-Glory spillway. The numerical free-surface profiles followed the theoretical equations very well.

Keywords: morning-glory spillway, CFD model, hydraulic characteristics, wall function

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Authors: Evgeny V. Blagin, Aleksandr I. Dovgjallo, Dmitry A. Uglanov

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This article deals with research of the working process in the thermocompressor which operates on cryogenic working fluid. Thermocompressor is device suited for the conversation of heat energy directly to the potential energy of pressure. Suggested thermocompressor is suited for operation during liquid natural gas (LNG) re-gasification and is placed after evaporator. Such application of thermocompressor allows using of the LNG cold energy for rising of working fluid pressure, which then can be used for electricity generation or another purpose. Thermocompressor consists of two chambers divided by the regenerative heat exchanger. Calculation algorithm for unsteady calculation of thermocompressor working process was suggested. The results of this investigation are to change of thermocompressor’s chambers temperature and pressure during the working cycle. These distributions help to find out the parameters, which significantly influence thermocompressor efficiency. These parameters include regenerative heat exchanger coefficient of the performance (COP) dead volume of the chambers, working frequency of the thermocompressor etc. Exergy analysis was performed to estimate thermocompressor efficiency. Cryogenic thermocompressor operated on nitrogen working fluid was chosen as a prototype. Calculation of the temperature and pressure change was performed with taking into account heat fluxes through regenerator and thermocompressor walls. Temperature of the cold chamber significantly differs from the results of steady calculation, which is caused by friction of the working fluid in regenerator and heat fluxes from the hot chamber. The rise of the cold chamber temperature leads to decreasing of thermocompressor delivery volume. Temperature of hot chamber differs negligibly because losses due to heat fluxes to a cold chamber are compensated by the friction of the working fluid in the regenerator. Optimal working frequency was selected. Main results of the investigation: -theoretical confirmation of thermocompressor operation capability on the cryogenic working fluid; -optimal working frequency was found; -value of the cold chamber temperature differs from the starting value much more than the temperature of the hot chamber; -main parameters which influence thermocompressor performance are regenerative heat exchanger COP and heat fluxes through regenerator and thermocompressor walls.

Keywords: cold energy, liquid natural gas, thermocompressor, regenerative heat exchanger

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Authors: Evren Isen

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In grid-connected renewable energy systems, input power is controlled by AC/DC converter or/and DC/DC converter depending on output voltage of input source. The power is injected to DC-link, and DC-link voltage is regulated by inverter controlling the grid current. Inverter performance is considerable in grid-connected renewable energy systems to meet the utility standards. In this paper, modelling and simulation of hysteresis current controlled single-phase grid-connected inverter that is utilized in renewable energy systems, such as wind and solar systems, are presented. 2 kW single-phase grid-connected inverter is simulated in Simulink and modeled in Matlab-m-file. The grid current synchronization is obtained by phase locked loop (PLL) technique in dq synchronous rotating frame. Although dq-PLL can be easily implemented in three-phase systems, there is difficulty to generate β component of grid voltage in single-phase system because single-phase grid voltage exists. Inverse-Park PLL with low-pass filter is used to generate β component for grid angle determination. As grid current is controlled by constant bandwidth hysteresis current control (HCC) technique, average switching frequency and variation of switching frequency in a fundamental period are considered. 3.56% total harmonic distortion value of grid current is achieved with 0.5 A bandwidth. Average value of switching frequency and total harmonic distortion curves for different hysteresis bandwidth are obtained from model in m-file. Average switching frequency is 25.6 kHz while switching frequency varies between 14 kHz-38 kHz in a fundamental period. The average and maximum frequency difference should be considered for selection of solid state switching device, and designing driver circuit. Steady-state and dynamic response performances of the inverter depending on the input power are presented with waveforms. The control algorithm regulates the DC-link voltage by adjusting the output power.

Keywords: grid-connected inverter, hysteresis current control, inverter modelling, single-phase inverter

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Authors: Rezvan Ravanfar Haghighi, V. C. Vani, Suresh Perumal, Sabyasachi Chatterjee, Pratik Kumar

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X-ray attenuation coefficient [µ(E)] of any substance, for energy (E), is a sum of the contributions from the Compton scattering [ μCom(E)] and photoelectric effect [µPh(E)]. In terms of the, electron density (ρe) and the effective atomic number (Zeff) we have µCom(E) is proportional to [(ρe)fKN(E)] while µPh(E) is proportional to [(ρeZeffx)/Ey] with fKN(E) being the Klein-Nishina formula, with x and y being the exponents for photoelectric effect. By taking the sample's HU at two different excitation voltages (V=V1, V2) of the CT machine, we can solve for X=ρe, Y=ρeZeffx from these two independent equations, as is attempted in DECT inversion. Since µCom(E) and µPh(E) are both energy dependent, the coefficients of inversion are also dependent on (a) the source spectrum S(E,V) and (b) the detector efficiency D(E) of the CT machine. In the present paper we tabulate these coefficients of inversion for different practical manifestations of S(E,V) and D(E). The HU(V) values from the CT follow: <µ(V)>=<µw(V)>[1+HU(V)/1000] where the subscript 'w' refers to water and the averaging process <….> accounts for the source spectrum S(E,V) and the detector efficiency D(E). Linearity of μ(E) with respect to X and Y implies that (a) <µ(V)> is a linear combination of X and Y and (b) for inversion, X and Y can be written as linear combinations of two independent observations <µ(V1)>, <µ(V2)> with V1≠V2. These coefficients of inversion would naturally depend upon S(E, V) and D(E). We numerically investigate this dependence for some practical cases, by taking V = 100 , 140 kVp, as are used for cardiological investigations. The S(E,V) are generated by using the Boone-Seibert source spectrum, being superposed on aluminium filters of different thickness lAl with 7mm≤lAl≤12mm and the D(E) is considered to be that of a typical Si[Li] solid state and GdOS scintilator detector. In the values of X and Y, found by using the calculated inversion coefficients, errors are below 2% for data with solutions of glycerol, sucrose and glucose. For low Zeff materials like propionic acid, Zeffx is overestimated by 20% with X being within1%. For high Zeffx materials like KOH the value of Zeffx is underestimated by 22% while the error in X is + 15%. These imply that the source may have additional filtering than the aluminium filter specified by the manufacturer. Also it is found that the difference in the values of the inversion coefficients for the two types of detectors is negligible. The type of the detector does not affect on the DECT inversion algorithm to find the unknown chemical characteristic of the scanned materials. The effect of the source should be considered as an important factor to calculate the coefficients of inversion.

Keywords: attenuation coefficient, computed tomography, photoelectric effect, source spectrum

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Authors: Berfin Yildiz

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These days, increasing global warming effects, limited amount of energy resources, etc., necessitates the awareness that must be present in every profession group. The architecture and construction sectors are responsible for both the embodied and operational energy of the materials. This responsibility has led designers to seek alternative solutions for energy-efficient material selection. The choice of energy-efficient material requires consideration of the entire life cycle, including the building's production, use, and disposal energy. The aim of this study is to investigate the method of material selection of external thermal insulation composite systems (ETICS). Embodied and in-use energy values of material alternatives were used for the evaluation in this study. The operational energy is calculated according to the u-value calculation method defined in the TS 825 (Thermal Insulation Requirements) standard for Turkey, and the embodied energy is calculated based on the manufacturer's Energy Performance Declaration (EPD). ETICS consists of a wall, adhesive, insulation, lining, mechanical, mesh, and exterior finishing materials. In this study, lining, mechanical, and mesh materials were ignored because EPD documents could not be obtained. The material selection problem is designed as a hypothetical volume area (5x5x3m) and defined as a multi-objective discrete optimization problem for external thermal insulation composite systems. Defining the problem as a discrete optimization problem is important in order to choose between materials of various thicknesses and sizes. Since production and use energy values, which are determined as optimization objectives in the study, are often conflicting values, material selection is defined as a multi-objective optimization problem, and it is aimed to obtain many solution alternatives by using Hypervolume (HypE) algorithm. The enrollment process started with 100 individuals and continued for 50 generations. According to the obtained results, it was observed that autoclaved aerated concrete and Ponce block as wall material, glass wool, as insulation material gave better results.

Keywords: embodied energy, multi-objective discrete optimization, performative design, thermal insulation

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Authors: Fathonah Siti, Ardiana Irma

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Indonesia is currently on its track to achieve Universal Health Coverage (UHC) by 2019. The program aims to address issues on disintegration in the implementation and coverage of various health insurance schemes and fragmented fund pooling. Family planning service is covered as one of benefit packages under preventive care. However, little has been done to examine how family planning program are appropriately managed across levels of governments and how family planning services are delivered to the end user. The study is performed through focus group discussion to related policy makers and selected programmers at central and district levels. The study is also benefited from relevant studies on family planning in the UHC scheme and other supporting data. The study carefully investigates some programmatic implications when family planning is integrated in the UHC program encompassing the need to recalculate contraceptive logistics for beneficiaries (eligible couple); policy reformulation for contraceptive service provision including supply chain management; establishment of family planning standard of procedure; and a call to update Management Information System. The study confirms that there is a significant increase in the numbers of contraceptive commodities needs to be procured by the government. Holding an assumption that contraceptive prevalence rate and commodities cost will be as expected increasing at 0.5% annually, the government need to allocate almost IDR 5 billion by 2019, excluded fee for service. The government shifts its focus to maintain eligible health facilities under National Population and Family Planning Board networks. By 2019, the government has set strategies to anticipate the provision of family planning services to 45.340 health facilities distributed in 514 districts and 7 thousand sub districts. Clear division of authorities has been established among levels of governments. Three models of contraceptive supply planning have been developed and currently in the process of being institutionalized. Pre service training for family planning services has been piloted in 10 prominent universities. The position of private midwives has been appreciated as part of the system. To ensure the implementation of quality and health expenditure control, family planning standard has been established as a reference to determine set of services required to deliver to the clients properly and types of health facilities to conduct particular family planning services. Recognition to individual status of program participation has been acknowledged in the Family Enumeration since 2015. The data is precisely recorded by name by address for each family and its members. It supplies valuable information to 15.131 Family Planning Field Workers (FPFWs) to provide information and education related to family planning in an attempt to generate demand and maintain the participation of family planning acceptors who are program beneficiaries. Despite overwhelming efforts described above, some obstacles remain. The program experiences poor socialization and yet removes geographical barriers for those living in remote areas. Family planning services provided for this sub population conducted outside the scheme as a complement strategy. However, UHC program has brought remarkable improvement in access and quality of family planning services.

Keywords: beneficiary, family planning services, national population and family planning board, universal health coverage

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Authors: Naser Kazemi Eilaki, Carolyn Ahmer, Ilona Heldal, Bjarne Christian Hagen

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Older people and people with disabilities are recognized as at-risk groups when it comes to egress and travel from hazard zone to safe places. One's disability can negatively influence her or his escape time, and this becomes even more important when people from this target group live alone. This research deals with the fire safety of mentioned people's buildings by means of probabilistic methods. For this purpose, fire safety is addressed by modeling the egress of our target group from a hazardous zone to a safe zone. A common type of detached house with a prevalent plan has been chosen for safety analysis, and a limit state function has been developed according to the time-line evacuation model, which is based on a two-zone and smoke development model. An analytical computer model (B-Risk) is used to consider smoke development. Since most of the involved parameters in the fire development model pose uncertainty, an appropriate probability distribution function has been considered for each one of the variables with indeterministic nature. To achieve safety and reliability for the at-risk groups, the fire safety index method has been chosen to define the probability of failure (causalities) and safety index (beta index). An improved harmony search meta-heuristic optimization algorithm has been used to define the beta index. Sensitivity analysis has been done to define the most important and effective parameters for the fire safety of the at-risk group. Results showed an area of openings and intervals to egress exits are more important in buildings, and the safety of people would improve with increasing dimensions of occupant space (building). Fire growth is more critical compared to other parameters in the home without a detector and fire distinguishing system, but in a home equipped with these facilities, it is less important. Type of disabilities has a great effect on the safety level of people who live in the same home layout, and people with visual impairment encounter more risk of capturing compared to visual and movement disabilities.

Keywords: fire safety, at-risk groups, zone model, egress time, uncertainty

Procedia PDF Downloads 104

Authors: Farrah Putri Salmanida, Mei-Li Wu, Rika Wahyuningtyas, Wen-Bin Chung, Hso-Chi Chaung, Ko-Tung Chang

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Within the field of immunotherapy, oncolytic virotherapy (OVT) employs dual approaches that directly eliminate tumor cells while preserving healthy ones and indirectly reprogram the tumor microenvironment (TME) to elicit antitumor responses. Within the TME, tumor associated macrophages (TAMs) manifest characteristics akin to those of anti-inflammatory M2 macrophages, thus earning the designation of M2-like TAMs. In prior research, two antigens denoted as A1 (g6Ld10T) and A3 (ORF6L5), derived from a complete sequence of ORF5 with partial sequence of ORF6 in Porcine Reproductive and Respiratory Syndrome Virus Genotype 2 (PRRSV-2), demonstrated the capacity to repolarize M2-type porcine alveolar macrophages (PAMs) into M1 phenotypes. In this study, we sought for utilizing OVT strategies by introducing A1 or A3 on TAMs to endow them with the anti-tumor traits of M1 macrophages while retaining their capacity to target cancer cells. Upon exposing human THP-1-derived M2 macrophages to a cross-species test with 2 µg/ml of either A1 or A3 for 24 hours, real time PCR revealed that A3, but not A1, treated cells exhibited upregulated gene expressions of M1 markers (CCR7, IL-1ß, CCL2, Cox2, CD80). These cells reacted to virus-derived antigen, as evidenced by increased expression of pattern-recognition receptors TLR3, TLR7, and TLR9, subsequently providing feedback in the form of type I interferon responses like IFNAR1, IFN-ß, IRF3, IRF7, OAS1, Mx1, and ISG15. Through an MTT assay, only after 15 µg/ml of A3 treatment could the cell viability decrease, with a predicted IC50 of 16.96 µg/ml. Interestingly, A3 caused dose-dependent toxicity to a rat C6 glial cancer cell line even at doses as low as 2.5 µg/ml and reached its IC50 at 9.419 µg/ml. Using Annexin V/7AAD staining and PCR test, we deduced that a significant proportion of C6 cells were undergoing the early apoptosis phase predominantly through the intrinsic apoptosis cascade involving Bcl-2 family proteins. Following this stage, we conducted a test on A3’s repolarization ability, which revealed a significant rise in M1 gene expression markers, such as TNF, CD80, and IL-1ß, in M2-like TAMs generated in vitro from murine RAW264.7 macrophages grown with conditioned medium of 4T1 breast cancer cells. This was corroborated by the results of transcriptome analysis, which revealed that the primary subset among the top 10 to top 30 significantly upregulated differentially expressed genes (DEGs) dominantly consisted of M1 macrophages profiles, including Ccl3, Ccl4, Csf3, TNF, Bcl6b, Stc1, and Dusp2. Our findings unveiled the remarkable potential of the PRRSV-derived antigen A3 to repolarize macrophages while also being capable of selectively inducing apoptosis in cancerous cells. While further in vivo study is needed for A3, it holds promise as an adjuvant by its dual effects in cancer therapy modalities.

Keywords: cancer cell apoptosis, interferon responses, macrophage repolarization, recombinant protein

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Authors: Khadija Refouh

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Culture bound-expressions have been a bottleneck for Natural Language Processing (NLP) and comprehension, especially in the case of machine translation (MT). In the last decade, the field of machine translation has greatly advanced. Neural machine translation NMT has recently achieved considerable development in the quality of translation that outperformed previous traditional translation systems in many language pairs. Neural machine translation NMT is an Artificial Intelligence AI and deep neural networks applied to language processing. Despite this development, there remain some serious challenges that face neural machine translation NMT when translating culture bounded-expressions, especially for low resources language pairs such as Arabic-English and Arabic-French, which is not the case with well-established language pairs such as English-French. Machine translation of opaque idioms from English into French are likely to be more accurate than translating them from English into Arabic. For example, Google Translate Application translated the sentence “What a bad weather! It runs cats and dogs.” to “يا له من طقس سيء! تمطر القطط والكلاب” into the target language Arabic which is an inaccurate literal translation. The translation of the same sentence into the target language French was “Quel mauvais temps! Il pleut des cordes.” where Google Translate Application used the accurate French corresponding idioms. This paper aims to perform NMT experiments towards better translation of opaque idioms using high quality clean multilingual corpus. This Corpus will be collected analytically from human generated idiom translation. AutoML translation, a Google Neural Machine Translation Platform, is used as a custom translation model to improve the translation of opaque idioms. The automatic evaluation of the custom model will be compared to the Google NMT using Bilingual Evaluation Understudy Score BLEU. BLEU is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another. Human evaluation is integrated to test the reliability of the Blue Score. The researcher will examine syntactical, lexical, and semantic features using Halliday's functional theory.

Keywords: multilingual corpora, natural language processing (NLP), neural machine translation (NMT), opaque idioms

Procedia PDF Downloads 151

Authors: Asnakew Mulualem Tegegne, Tarun Kumar Lohani, Abunu Atlabachew Eshete

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Groundwater potential delineation is essential for efficient water resource utilization and long-term development. The scarcity of potable and irrigation water has become a critical issue due to natural and anthropogenic activities in meeting the demands of human survival and productivity. With these constraints, groundwater resources are now being used extensively in Ethiopia. Therefore, an innovative convolutional neural network (CNN) is successfully applied in the Gunabay watershed to delineate groundwater potential based on the selected major influencing factors. Groundwater recharge, lithology, drainage density, lineament density, transmissivity, and geomorphology were selected as major influencing factors during the groundwater potential of the study area. For dataset training, 70% of samples were selected and 30% were used for serving out of the total 128 samples. The spatial distribution of groundwater potential has been classified into five groups: very low (10.72%), low (25.67%), moderate (31.62%), high (19.93%), and very high (12.06%). The area obtains high rainfall but has a very low amount of recharge due to a lack of proper soil and water conservation structures. The major outcome of the study showed that moderate and low potential is dominant. Geodetoctor results revealed that the magnitude influences on groundwater potential have been ranked as transmissivity (0.48), recharge (0.26), lineament density (0.26), lithology (0.13), drainage density (0.12), and geomorphology (0.06). The model results showed that using a convolutional neural network (CNN), groundwater potentiality can be delineated with higher predictive capability and accuracy. CNN-based AUC validation platform showed that 81.58% and 86.84% were accrued from the accuracy of training and testing values, respectively. Based on the findings, the local government can receive technical assistance for groundwater exploration and sustainable water resource development in the Gunabay watershed. Finally, the use of a detector-based deep learning algorithm can provide a new platform for industrial sectors, groundwater experts, scholars, and decision-makers.

Keywords: CNN, geodetector, groundwater influencing factors, Groundwater potential, Gunabay watershed

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Authors: A. Gonzalez Aguna, J. M. Santamaria Garcia, J. L. Gomez Gonzalez, R. Barchino Plata, M. Fernandez Batalla, S. Herrero Jaen

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Background: Computer Science is a field that transcends other disciplines of knowledge because it allows to support all kinds of physical and mental tasks. Health centres have a greater number and complexity of technological devices and the population consume and demand services derived from technology. Also, nursing education plans have included competencies related to and, even, courses about new technologies are offered to health professionals. However, nurses still limit their performance to the use and evaluation of products previously built. Objective: Develop a teaching-learning methodology for acquiring skills on designing applications for care. Methodology: Blended learning teaching with a group of graduate nurses through official training within a Master's Degree. The study sample was selected by intentional sampling without exclusion criteria. The study covers from 2015 to 2017. The teaching sessions included a four-hour face-to-face class and between one and three tutorials. The assessment was carried out by written test consisting of the preparation of an IEEE 830 Standard Specification document where the subject chosen by the student had to be a problem in the area of care. Results: The sample is made up of 30 students: 10 men and 20 women. Nine students had a degree in nursing, 20 diploma in nursing and one had a degree in Computer Engineering. Two students had a degree in nursing specialty through residence and two in equivalent recognition by exceptional way. Except for the engineer, no subject had previously received training in this regard. All the sample enrolled in the course received the classroom teaching session, had access to the teaching material through a virtual area and maintained at least one tutoring. The maximum of tutorials were three with an hour in total. Among the material available for consultation was an example of a document drawn up based on the IEEE Standard with an issue not related to care. The test to measure competence was completed by the whole group and evaluated by a multidisciplinary teaching team of two computer engineers and two nurses. Engineers evaluated the correctness of the characteristics of the document and the degree of comprehension in the elaboration of the problem and solution elaborated nurses assessed the relevance of the chosen problem statement, the foundation, originality and correctness of the proposed solution and the validity of the application for clinical practice in care. The results were of an average grade of 8.1 over 10 points, a range between 6 and 10. The selected topic barely coincided among the students. Examples of care areas selected are care plans, family and community health, delivery care, administration and even robotics for care. Conclusion: The applied methodology of learning-teaching for the design of technologies demonstrates the success in the training of nursing professionals. The role of expert is essential to create applications that satisfy the needs of end users. Nursing has the possibility, the competence and the duty to participate in the process of construction of technological tools that are going to impact in care of people, family and community.

Keywords: care, learning, nursing, technology

Procedia PDF Downloads 137

Authors: Sana Fatima, Paul Sadler, Jon Cooper, David Mendel, Ayesha Jameel

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Background: Neurodiversity refers to intrinsic differences between human minds and encompasses dyspraxia, dyslexia, attention deficit hyperactivity disorder, dyscalculia, autism spectrum disorder, and Tourette syndrome. There is increasing recognition of neurodiversity in relation to disability/diversity in medical education and the associated impact on training, career progression, and personal and professional wellbeing. In addition, documented and anecdotal evidence suggests that medical educators and training providers in all four nations (UK) are increasingly concerned about understanding neurodiversity and identifying and providing support for neurodivergent trainees. Summary of Work: A national Neurodiversity Task and Finish group were established to survey Health Education England local office Professional Support teams about insights into infrastructure, training for educators, triggers for assessment, resources, and intervention protocols. This group drew from educational leadership, professional and personal neurodiverse expertise, occupational medicine, employer human resource, and trainees. An online, exploratory survey was conducted to gather insights from supervisors and trainers across England using the Professional Support Units' platform. Summary of Results: This survey highlighted marked heterogeneity in the identification, assessment, and approaches to support and management of neurodivergent trainees and highlighted a 'deficit' approach to neurodiversity. It also demonstrated a paucity of educational and protocol resources for educators and supervisors in supporting neurodivergent trainees. Discussions and Conclusions: In phase one, we focused on faculty development. An educational repository for all supervising trainees using a thematic approach was formalised. This was guided by our survey findings specific for neurodiversity and took a triple 'A' approach: awareness, assessment, and action. This is further supported by video material incorporating stories in training as well as mobile workshops for trainers for more immersive learning. The subtle theme from both the survey and Task and finish group suggested a move away from deficit-focused methods toward a positive holistic, interdisciplinary approach within a biopsychosocial framework. Contributions: 1. Faculty Knowledge and basic understanding of neurodiversity are key to supporting trainees with known or underlying Neurodiverse conditions. This is further complicated by challenges around non-disclosure, varied presentations, stigma, and intersectionality. 2. There is national (and international) inconsistency in the approach to how trainees are managed once a neurodiverse condition is suspected or diagnosed. 3. A carefully constituted and focussed Task and Finish group can rapidly identify national inconsistencies in neurodiversity and implement rapid educational interventions. 4. Nuanced findings from surveys and discussion can reframe the approach to neurodiversity; from a medical model to a more comprehensive, asset-based, biopsychosocial model of support, fostering a cultural shift, accepting 'diversity' in all its manifestations, visible and hidden.

Keywords: neurodiversity, professional support, human considerations, workplace wellbeing

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Authors: Tingting Huang, Sha Li, Geoffrey Griffiths, Martin Lukac, Jianning Zhu

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Territorial landscapes have experienced a gradual loss of their typical characteristics during long-term human activities. In order to protect the integrity of regional landscapes, it is necessary to characterize, evaluate and protect them in a graded manner. The study takes Fujian, China, as an example and classifies the landscape characters of the site at the regional scale, middle scale, and detailed scale. A multi-scale approach combining parametric and holistic approaches is used to classify and partition the landscape character types (LCTs) and landscape character areas (LCAs) at different scales, and a multi-element landscape assessment approach is adopted to explore the conservation strategies of the landscape character. Firstly, multiple fields and multiple elements of geography, nature and humanities were selected as the basis of assessment according to the scales. Secondly, the study takes a parametric approach to the classification and partitioning of landscape character, Principal Component Analysis, and two-stage cluster analysis (K-means and GMM) in MATLAB software to obtain LCTs, combines with Canny Operator Edge Detection Algorithm to obtain landscape character contours and corrects LCTs and LCAs by field survey and manual identification methods. Finally, the study adopts the Landscape Sensitivity Assessment method to perform landscape character conservation analysis and formulates five strategies for different LCAs: conservation, enhancement, restoration, creation, and combination. This multi-scale identification approach can efficiently integrate multiple types of landscape character elements, reduce the difficulty of broad-scale operations in the process of landscape character conservation, and provide a basis for landscape character conservation strategies. Based on the natural background and the restoration of regional characteristics, the results of landscape character assessment are scientific and objective and can provide a strong reference in regional and national scale territorial spatial planning.

Keywords: parameterization, multi-scale, landscape character identify, landscape character assessment

Procedia PDF Downloads 100

Authors: Manpreet Kaur, Cheol-Hong Min

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The increasing advancement in the robotics equipped with machine vision sensors applied to precision agriculture is a demanding solution for various problems in the agricultural farms. An important issue related with the machine vision system concerns crop row and weed detection. This paper proposes an automatic furrow detection system based on real-time processing for identifying crop rows in maize fields in the presence of weed. This vision system is designed to be installed on the farming vehicles, that is, submitted to gyros, vibration and other undesired movements. The images are captured under image perspective, being affected by above undesired effects. The goal is to identify crop rows for vehicle navigation which includes weed removal, where weeds are identified as plants outside the crop rows. The images quality is affected by different lighting conditions and gaps along the crop rows due to lack of germination and wrong plantation. The proposed image processing method consists of four different processes. First, image segmentation based on HSV (Hue, Saturation, Value) decision tree. The proposed algorithm used HSV color space to discriminate crops, weeds and soil. The region of interest is defined by filtering each of the HSV channels between maximum and minimum threshold values. Then the noises in the images were eliminated by the means of hybrid median filter. Further, mathematical morphological processes, i.e., erosion to remove smaller objects followed by dilation to gradually enlarge the boundaries of regions of foreground pixels was applied. It enhances the image contrast. To accurately detect the position of crop rows, the region of interest is defined by creating a binary mask. The edge detection and Hough transform were applied to detect lines represented in polar coordinates and furrow directions as accumulations on the angle axis in the Hough space. The experimental results show that the method is effective.

Keywords: furrow detection, morphological, HSV, Hough transform

Procedia PDF Downloads 231

Authors: Auwal Abubakar, Shazril Imran Shaukat, Noor Khairiah A. Karim, Mohammed Zakir Kassim, Gokula Kumar Appalanaido, Hafiz Mohd Zin

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Background: Voluntary deep inspiration breath-hold radiotherapy (vDIBH-RT) is an effective cardiac dose reduction technique during left breast radiotherapy. This study aimed to assess the accuracy of the implementation of the vDIBH technique among left breast cancer patients without the use of a special device such as a surface-guided imaging system. Methods: The vDIBH-RT technique was implemented among thirteen (13) left breast cancer patients at the Advanced Medical and Dental Institute (AMDI), Universiti Sains Malaysia. Breath-hold monitoring was performed based on breath-hold skin marks and laser light congruence observed on zoomed CCTV images from the control console during each delivery. The initial setup was verified using cone beam computed tomography (CBCT) during breath-hold. Each field was delivered using multiple beam segments to allow a delivery time of 20 seconds, which can be tolerated by patients in breath-hold. The data were analysed using an in-house developed MATLAB algorithm. PTV margin was computed based on van Herk's margin recipe. Results: The setup error analysed from CBCT shows that the population systematic error in lateral (x), longitudinal (y), and vertical (z) axes was 2.28 mm, 3.35 mm, and 3.10 mm, respectively. Based on the CBCT image guidance, the Planning target volume (PTV) margin that would be required for vDIBH-RT using CCTV/Laser monitoring technique is 7.77 mm, 10.85 mm, and 10.93 mm in x, y, and z axes, respectively. Conclusion: It is feasible to safely implement vDIBH-RT among left breast cancer patients without special equipment. The breath-hold monitoring technique is cost-effective, radiation-free, easy to implement, and allows real-time breath-hold monitoring.

Keywords: vDIBH, cone beam computed tomography, radiotherapy, left breast cancer

Procedia PDF Downloads 57

Authors: Kottaridi Klimentia, Demopoulos Vasilis, Sidiropoulos Anastasios, Ihara Diego, Nikolaidis Vasileios, Antonopoulos Dimitrios

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Aflatoxins are highly poisonous and carcinogenic compounds produced by species of the genus Aspergillus spp. that can infect a variety of agricultural foods, including dried figs. Biological and environmental factors, such as population, pathogenicity, and aflatoxinogenic capacity of the strains, topography, soil, and climate parameters of the fig orchards, are believed to have a strong effect on aflatoxin levels. Existing methods for aflatoxin detection and measurement, such as high performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), can provide accurate results, but the procedures are usually time-consuming, sample-destructive, and expensive. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the health and financial impact of a contaminated crop. Consequently, there is interest in developing a tool that predicts aflatoxin levels based on topography and soil analysis data of fig orchards. This paper describes the development of a risk assessment tool for the contamination of aflatoxin on dried figs, based on the location and altitude of the fig orchards, the population of the fungus Aspergillus spp. in the soil, and soil parameters such as pH, saturation percentage (SP), electrical conductivity (EC), organic matter, particle size analysis (sand, silt, clay), the concentration of the exchangeable cations (Ca, Mg, K, Na), extractable P, and trace of elements (B, Fe, Mn, Zn and Cu), by employing machine learning methods. In particular, our proposed method integrates three machine learning techniques, i.e., dimensionality reduction on the original dataset (principal component analysis), metric learning (Mahalanobis metric for clustering), and k-nearest neighbors learning algorithm (KNN), into an enhanced model, with mean performance equal to 85% by terms of the Pearson correlation coefficient (PCC) between observed and predicted values.

Keywords: aflatoxins, Aspergillus spp., dried figs, k-nearest neighbors, machine learning, prediction

Procedia PDF Downloads 184

Authors: Mamoon Masud, Suleman Mazhar

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Indus river basin’s irrigation system in Pakistan is extremely complex, spanning over 50,000 km. Maintenance and monitoring of this demands enormous resources. This paper describes the development of a streamlined and low-cost autonomous underwater vehicle (AUV) for the monitoring of irrigation canals including water quality monitoring and water theft detection. The vehicle is a hovering-type AUV, designed mainly for monitoring irrigation canals, with fully documented design and open source code. It has a length of 17 inches, and a radius of 3.5 inches with a depth rating of 5m. Multiple sensors are present onboard the AUV for monitoring water quality parameters including pH, turbidity, total dissolved solids (TDS) and dissolved oxygen. A 9-DOF Inertial Measurement Unit (IMU), GY-85, is used, which incorporates an Accelerometer (ADXL345), a Gyroscope (ITG-3200) and a Magnetometer (HMC5883L). The readings from these sensors are fused together using directional cosine matrix (DCM) algorithm, providing the AUV with the heading angle, while a pressure sensor gives the depth of the AUV. 2 sonar-based range sensors are used for obstacle detection, enabling the vehicle to align itself with the irrigation canals edges. 4 thrusters control the vehicle’s surge, heading and heave, providing 3 DOF. The thrusters are controlled using a proportional-integral-derivative (PID) feedback control system, with heading angle and depth being the controller’s input and the thruster motor speed as the output. A flow sensor has been incorporated to monitor canal water level to detect water-theft event in the irrigation system. In addition to water theft detection, the vehicle also provides information on water quality, providing us with the ability to identify the source(s) of water contamination. Detection of such events can provide useful policy inputs for improving irrigation efficiency and reducing water contamination. The AUV being low cost, small sized and suitable for autonomous maneuvering, water level and quality monitoring in the irrigation canals, can be used for irrigation network monitoring at a large scale.

Keywords: the autonomous underwater vehicle, irrigation canal monitoring, water quality monitoring, underwater line tracking

Procedia PDF Downloads 148

Authors: Elżbieta Turska

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Introduction: One of the most difficult times in a person’s life is adolescence. The experiences in this period may shape the future life of this person to a large extent. This is the reason why many young people experience sadness, dejection, hopelessness, sense of worthlessness, as well as losing interest in various activities and social relationships, all of which are often classified as mood disorders. As many as 15-40% adolescents experience depressed moods and for most of them they resolve and are not carried into adulthood. However, (5-6%) of those affected by mood disorders develop the depressive syndrome and as many as (1-3%) develop full-blown clinical depression. Materials: A large questionnaire was given to 2508 students, aged 13–16 years old, and one of its parts was the Burns checklist, i.e. the standard test for identifying depressed mood. The questionnaire asked about many aspects of the student’s life, it included a total of 53 questions, most of which had subquestions. It is important to note that the data suffered from many problems, the most important of which were missing data and collinearity. Aim: In order to identify the correlates of mood disorders we built predictive models which were then trained and validated. Our aim was not to be able to predict which students suffer from mood disorders but rather to explore the factors influencing mood disorders. Methods: The problems with data described above practically excluded using all classical statistical methods. For this reason, we attempted to use the following Artificial Intelligence (AI) methods: classification trees with surrogate variables, random forests and xgboost. All analyses were carried out with the use of the mlr package for the R programming language. Resuts: The predictive model built by classification trees algorithm outperformed the other algorithms by a large margin. As a result, we were able to rank the variables (questions and subquestions from the questionnaire) from the most to least influential as far as protection against mood disorder is concerned. Thirteen out of twenty most important variables reflect the relationships with parents. This seems to be a really significant result both from the cognitive point of view and also from the practical point of view, i.e. as far as interventions to correct mood disorders are concerned.

Keywords: mood disorders, adolescents, family, artificial intelligence

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Authors: Larissa Bolliger, Junoš Lukan, Mitja Lustrek, Dirk De Bacquer, Els Clays

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Introduction and Aim: Chronic workplace stress and its health-related consequences like mental and cardiovascular diseases have been widely investigated. This project focuses on the sources and context of psychosocial daily workplace stress in a real-world setting. The main objective is to analyze and model real-time relationships between (1) psychosocial stress experiences within the natural work environment, (2) micro-level work activities and events, and (3) physiological signals and behaviors in office workers. Methods: An Ecological Momentary Assessment (EMA) protocol has been developed, partly building on machine learning techniques. Empatica® wristbands will be used for real-life detection of stress from physiological signals; micro-level activities and events at work will be based on smartphone registrations, further processed according to an automated computer algorithm. A field study including 100 office-based workers with high-level problem-solving tasks like managers and researchers will be implemented in Slovenia and Belgium (50 in each country). Data mining and state-of-the-art statistical methods – mainly multilevel statistical modelling for repeated data – will be used. Expected Results and Impact: The project findings will provide novel contributions to the field of occupational health research. While traditional assessments provide information about global perceived state of chronic stress exposure, the EMA approach is expected to bring new insights about daily fluctuating work stress experiences, especially micro-level events and activities at work that induce acute physiological stress responses. The project is therefore likely to generate further evidence on relevant stressors in a real-time working environment and hence make it possible to advise on workplace procedures and policies for reducing stress.

Keywords: ecological momentary assessment, real-time, stress, work

Procedia PDF Downloads 162

Authors: Vladimir Smirnov, Roman Tominov, Vadim Avilov, Oleg Ageev

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The creation of a new generation micro- and nanoelectronics elements opens up unlimited possibilities for electronic devices parameters improving, as well as developing neuromorphic computing systems. Interest in the latter is growing up every year, which is explained by the need to solve problems related to the unstructured classification of data, the construction of self-adaptive systems, and pattern recognition. However, for its technical implementation, it is necessary to fulfill a number of conditions for the basic parameters of electronic memory, such as the presence of non-volatility, the presence of multi-bitness, high integration density, and low power consumption. Several types of memory are presented in the electronics industry (MRAM, FeRAM, PRAM, ReRAM), among which non-volatile resistive memory (ReRAM) is especially distinguished due to the presence of multi-bit property, which is necessary for neuromorphic systems manufacturing. ReRAM is based on the effect of resistive switching – a change in the resistance of the oxide film between low-resistance state (LRS) and high-resistance state (HRS) under an applied electric field. One of the methods for the technical implementation of neuromorphic systems is cross-bar structures, which are ReRAM cells, interconnected by cross data buses. Such a structure imitates the architecture of the biological brain, which contains a low power computing elements - neurons, connected by special channels - synapses. The choice of the ReRAM oxide film material is an important task that determines the characteristics of the future neuromorphic system. An analysis of literature showed that many metal oxides (TiO2, ZnO, NiO, ZrO2, HfO2) have a resistive switching effect. It is worth noting that the manufacture of nanocomposites based on these materials allows highlighting the advantages and hiding the disadvantages of each material. Therefore, as a basis for the neuromorphic structures manufacturing, it was decided to use ZnₓTiᵧHfzOᵢ nanocomposite. It is also worth noting that the ZnₓTiᵧHfzOᵢ nanocomposite does not need an electroforming, which degrades the parameters of the formed ReRAM elements. Currently, this material is not well studied, therefore, the study of the effect of resistive switching in forming-free ZnₓTiᵧHfzOᵢ nanocomposite is an important task and the goal of this work. Forming-free nanocomposite ZnₓTiᵧHfzOᵢ thin film was grown by pulsed laser deposition (Pioneer 180, Neocera Co., USA) on the SiO2/TiN (40 nm) substrate. Electrical measurements were carried out using a semiconductor characterization system (Keithley 4200-SCS, USA) with W probes. During measurements, TiN film was grounded. The analysis of the obtained current-voltage characteristics showed a resistive switching from HRS to LRS resistance states at +1.87±0.12 V, and from LRS to HRS at -2.71±0.28 V. Endurance test shown that HRS was 283.21±32.12 kΩ, LRS was 1.32±0.21 kΩ during 100 measurements. It was shown that HRS/LRS ratio was about 214.55 at reading voltage of 0.6 V. The results can be useful for forming-free nanocomposite ZnₓTiᵧHfzOᵢ films in neuromorphic systems manufacturing. This work was supported by RFBR, according to the research project № 19-29-03041 mk. The results were obtained using the equipment of the Research and Education Center «Nanotechnologies» of Southern Federal University.

Keywords: nanotechnology, nanocomposites, neuromorphic systems, RRAM, pulsed laser deposition, resistive switching effect

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Authors: A. Kyprianou, A. Tjirkallis

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Condition monitoring of structures in service is very important as it provides information about the risk of damage development. One of the essential constituents of structural condition monitoring is the damage detection methodology. In the context of condition monitoring of in service structures a damage detection methodology analyses data obtained from the structure while it is in operation. Usually, this means that the data could be affected by operational and environmental conditions in a way that could mask the effects of a possible damage on the data. This, depending on the damage detection methodology, could lead to either false alarms or miss existing damages. In this article a damage detection methodology that is based on the Spatio-temporal continuous wavelet transform (SPT-CWT) analysis of a sequence of experimental time responses of a cantilever beam is proposed. The cantilever is subjected to white and pink noise excitation to simulate different operating conditions. In addition, in order to simulate changing environmental conditions, the cantilever is subjected to heating by a heat gun. The response of the cantilever beam is measured by a high-speed camera. Edges are extracted from the series of images of the beam response captured by the camera. Subsequent processing of the edges gives a series of time responses on 439 points on the beam. This sequence is then analyzed using the SPT-CWT to identify damage. The algorithm proposed was able to clearly identify damage under any condition when the structure was excited by white noise force. In addition, in the case of white noise excitation, the analysis could also reveal the position of the heat gun when it was used to heat the structure. The analysis could identify the different operating conditions i.e. between responses due to white noise excitation and responses due to pink noise excitation. During the pink noise excitation whereas damage and changing temperature were identified it was not possible to clearly identify the effect of damage from that of temperature. The methodology proposed in this article for damage detection enables the separation the damage effect from that due to temperature and excitation on data obtained from measurements of a cantilever beam. This methodology does not require information about the apriori state of the structure.

Keywords: spatiotemporal continuous wavelet transform, damage detection, data normalization, varying temperature

Procedia PDF Downloads 279

Authors: A. Kourou, A. Ioakeimidou, E. Pelli, M. Panoutsopoulou, V. Abramea

Abstract:

Worldwide there is a growing recognition that education is a critical component of any disaster impacts reduction effort and a great challenge too. Given this challenge, a broad range of awareness raising projects at all levels are implemented and are continuously evaluated by Earthquake Planning and Protection Organization (EPPO). This paper presents an overview of EPPO educational initiative (seminars, lectures, workshops, campaigns and educational material) and its evaluation results. The abovementioned initiative is focused to aware the public, train teachers and civil protection staff, inform students and educate people with disabilities on subjects related to earthquake reduction issues. The better understating of how human activity can link to disaster and what can be done at the individual, family or workplace level to contribute to seismic reduction are the main issues of EPPO projects. Survey results revealed that a high percentage of teachers (included the ones of special schools) from all over the country have taken the appropriate preparedness measures at schools. On the other hand, the implementation of earthquake preparedness measures at various workplaces (kindergartens, banks, utilities etc.) has still significant room for improvement. Results show that the employees in banks and public utilities have substantially higher rates in preventive and preparedness actions in their workplaces than workers in kindergartens and other workplaces. One of the EPPO educational priorities is to enhance earthquake preparedness of people with disabilities. Booklets, posters and applications have been created with the financial support of the Council of Europe, addressed to people who have mobility impairments, learning difficulties or cognitive disability (ή intellectual disabilities). Part of the educational material was developed using the «easy-to-read» method and Makaton language program with the collaboration of experts on special needs education and teams of people with cognitive disability. Furthermore, earthquake safety seminars and earthquake drills have been implemented in order to develop children’s, parents’ and teachers abilities and skills on earthquake impacts reduction. To enhance the abovementioned efforts, EPPO is a partner at prevention and preparedness projects supported by EU Civil Protection Financial Instrument. One of them is E-PreS’ project (Monitoring and Evaluation of Natural Hazard Preparedness at School Environment). The main objectives of E-PreS project are: 1) to create smart tools which define, simulate and evaluate drills procedure at schools, centers of vocational training of people with disabilities or other workplaces, and 2) to involve students or adults with disabilities in the E-PreS system evacuation procedure in case of earthquake, flood, or volcanic occurrence. Two other EU projects (RACCE educational kit and EVANDE educational platform) are also with the aim of contributing to raising awareness among people with disabilities, students, teachers, volunteers etc. It is worth mentioning that even though in Greece many efforts have been done till now to build awareness towards earthquakes and establish preparedness status for prospective earthquakes, there are still actions to be taken.

Keywords: earthquake, emergency plans, E-PreS project, people with disabilities, special needs education

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