Search results for: gradual change detection

Authors: Farmesk Abubaker, Francesco Tortorici, Marco Capogni, Concetta Sutera, Vincenzo Bellini

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This project concerns with the detection efficiency of the portable triple-to-double coincidence ratio (TDCR) at the National Institute of Metrology of Ionizing Radiation (INMRI-ENEA) which allows direct activity measurement and radionuclide standardization for pure-beta emitter or pure electron capture radionuclides. The dependency of the simulated detection efficiency of the TDCR, by using Monte Carlo simulation Geant4 code, on the Birks factor (kB) and defocusing parameter has been examined especially for low energy beta-emitter radionuclides such as 3H and 14C, for which this dependency is relevant. The results achieved in this analysis can be used for selecting the best kB factor and the defocusing parameter for computing theoretical TDCR parameter value. The theoretical results were compared with the available ones, measured by the ENEA TDCR portable detector, for some pure-beta emitter radionuclides. This analysis allowed to improve the knowledge of the characteristics of the ENEA TDCR detector that can be used as a traveling instrument for in-situ measurements with particular benefits in many applications in the field of nuclear medicine and in the nuclear energy industry.

Keywords: Birks constant, defocusing parameter, GEANT4 code, TDCR parameter

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Authors: Evan Hajani, Ataur Rahman, Khaled Haddad

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Climate change will affect the hydrological cycle in many different ways such as increase in evaporation and rainfalls. There have been growing interests among researchers to identify the nature of trends in historical rainfall data in many different parts of the world. This paper examines the trends in annual maximum rainfall data from 30 stations in New South Wales, Australia by using two non-parametric tests, Mann-Kendall (MK) and Spearman’s Rho (SR). Rainfall data were analyzed for fifteen different durations ranging from 6 min to 3 days. It is found that the sub-hourly durations (6, 12, 18, 24, 30, and 48 minutes) show statistically significant positive (upward) trends whereas longer duration (sub-daily and daily) events generally show a statistically significant negative (downward) trend. It is also found that the MK test and SR test provide notably different results for some rainfall event durations considered in this study. Since shorter duration sub-hourly rainfall events show positive trends at many stations, the design rainfall data based on stationary frequency analysis for these durations need to be adjusted to account for the impact of climate change. These shorter durations are more relevant to many urban development projects based on smaller catchments having a much shorter response time.

Keywords: climate change, Mann-Kendall test, Spearman’s Rho test, trends, design rainfall

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Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

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The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

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Authors: Nana Benma Osei

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Patient discharge can be a hectic process. Patients are sometimes sent to the wrong location or forgotten in lounges in the waiting room. This ends up compromising patient care because the delay in picking the patients can affect how they adhere to medication. Patients may fail to take their medication, and this will lead to negative outcomes. The situation highlights the demands of modern-day healthcare, and the use of technology can help in reducing such challenges and in enhancing the patient’s experience, leading to greater satisfaction with the care provided. The paper contains the proposed changes to a healthcare facility by introducing the clinical decision support system, which will be needed to improve coordination and communication during patient discharge. This will be done under Kurt Lewin’s Change Management Model, which recognizes the different phases in the change process. A pilot program is proposed initially before the program can be implemented in the entire organization. This allows for the identification of challenges and ways of managing them. The paper anticipates some of the possible challenges that may arise during implementation, and a multi-disciplinary approach is considered the most effective. Opposition to the change is likely to arise because staff members may lack information on how the changes will affect them and the skills they will need to learn to use the new system. Training will occur before the technology can be implemented. Every member will go for training, and adequate time is allocated for training purposes. A comparison of data will determine whether the project has succeeded.

Keywords: patient discharge, clinical decision support system, communication, collaboration

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Authors: Ripon Sarkar, Kabita Chaterjee, Ananya Barui

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Smoking is one of the leading causes of oral cancer. Cigarette smoke affects various cellular parameters and alters molecular metabolism of cells. Epithelial cells losses their cytoskeleton structure, membrane integrity, cellular polarity that subsequently initiates the process of epithelial cells to mesenchymal transition due to long exposure of cigarette smoking. It changes the normal cellular metabolic activity which induces oxidative stress and enhances the reactive oxygen spices (ROS) formation. Excessive ROS and associated oxidative stress are considered to be a driving force in alteration in cellular phenotypes, polarity distribution and mitochondrial metabolism. Noninvasive assessment of such parameters plays essential role in development of routine screening system for early diagnosis of oral cancer. Electrical cell-substrate impedance sensing (ECIS) is one of such method applied for detection of cellular membrane impedance which can be correlated to cell membrane integrity. Present study intends to explore the alteration in cellular impedance along with the expression of cellular polarity molecules and cytoskeleton distributions in oral epithelial cells of habitual smokers and to correlate the outcome to that of clinically diagnosed oral leukoplakia and oral squamous cell carcinoma patients. Total 80 subjects were categorized into four study groups: nonsmoker (NS), cigarette smoker (CS), oral leukoplakia (OLPK) and oral squamous cell carcinoma (OSCC). Cytoskeleton distribution was analyzed by staining of actin filament and generation of ROS was measured using assay kit using standard protocol. Cell impedance was measured through ECIS method at different frequencies. Expression of E-cadherin and protease-activated receptor (PAR) proteins were observed through immune-fluorescence method. Distribution of actin filament is well organized in NS group however; distribution pattern was grossly varied in CS, OLPK and OSCC. Generation of ROS was low in NS which subsequently increased towards OSCC. Expressions of E-cadherin and change in cellular electrical impedance in different study groups indicated the hallmark of cancer progression from NS to OSCC. Expressions of E-cadherin, PAR protein, and cell impedance were decreased from NS to CS and farther OSCC. Generally, the oral epithelial cells exhibit apico-basal polarity however with cancer progression these cells lose their characteristic polarity distribution. In this study expression of polarity molecule and ECIS observation indicates such altered pattern of polarity among smoker group. Overall the present study monitored the alterations in intracellular ROS generation and cell metabolic function, membrane integrity in oral epithelial cells in cigarette smokers. Present study thus has clinical significance, and it may help in developing a noninvasive technique for early diagnosis of oral cancer amongst susceptible individuals.

Keywords: cigarette smoking, early oral cancer detection, electric cell-substrate impedance sensing, noninvasive screening

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Authors: Leena Alfarani

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Although mobile devices are ubiquitous on university campuses, teacher-readiness for mobile learning has yet to be fully explored in the non-western nations. This study shows that two main factors affect the adoption and use of m-learning among female teachers within a university in Saudi Arabia—resistance to change and perceived social culture. These determinants of the current use and intention to use of m-learning were revealed through the analysis of an online questionnaire completed by 165 female faculty members. This study reveals several important issues for m-learning research and practice. The results further extend the body of knowledge in the field of m-learning, with the findings revealing that resistance to change and perceived social culture are significant determinants of the current use of and the intention to use m-learning.

Keywords: blended learning, mobile learning, technology adoption, devices

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Authors: Shizra Waris, Bilal Shoaib, Munib Ahmad

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Background; The using of clinical decision support systems (CDSSs) may recover unceasing disease organization, which requires regular visits to multiple health professionals, treatment monitoring, disease control, and patient behavior modification. The objective of this survey is to determine if these CDSSs improve the processes of unceasing care including diagnosis, treatment, and monitoring of diseases. Though artificial intelligence is not a new idea it has been widely documented as a new technology in computer science. Numerous areas such as education business, medical and developed have made use of artificial intelligence Methods: The survey covers articles extracted from relevant databases. It uses search terms related to information technology and viral hepatitis which are published between 2000 and 2016. Results: Overall, 80% of studies asserted the profit provided by information technology (IT); 75% of learning asserted the benefits concerned with medical domain;25% of studies do not clearly define the added benefits due IT. The CDSS current state requires many improvements to hold up the management of liver diseases such as HCV, liver fibrosis, and cirrhosis. Conclusion: We concluded that the planned model gives earlier and more correct calculation of hepatitis B and it works as promising tool for calculating of custom hepatitis B from the clinical laboratory data.

Keywords: detection, hapataties, observation, disesese

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Authors: Pier Andrea Marras, Daniela Lima, Pedro Matos Soares, Rita Maria Cardoso, Daniela Medas, Elisabetta Dore, Giovanni De Giudici

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Climate change effects on the hydrologic cycle are the main concern for the evaluation of water management strategies. Climate models project scenarios of precipitation changes in the future, considering greenhouse emissions. In this study, the EURO-CORDEX (European Coordinated Regional Downscaling Experiment) climate models were first evaluated in a Mediterranean island (Sardinia) against observed precipitation for a historical reference period (1976-2005). A weighted multi-model ensemble (ENS) was built, weighting the single models based on their ability to reproduce observed rainfall. Future projections (2071-2100) were carried out using the 8.5 RCP emissions scenario to evaluate changes in precipitations. ENS was then used as climate forcing for the SWAT model (Soil and Water Assessment Tool), with the aim to assess the consequences of such projected changes on streamflow and runoff of two small catchments located in the South-West Sardinia. Results showed that a decrease of mean rainfall values, up to -25 % at yearly scale, is expected for the future, along with an increase of extreme precipitation events. Particularly in the eastern and southern areas, extreme events are projected to increase by 30%. Such changes reflect on the hydrologic cycle with a decrease of mean streamflow and runoff, except in spring, when runoff is projected to increase by 20-30%. These results stress that the Mediterranean is a hotspot for climate change, and the use of model tools can provide very useful information to adopt water and land management strategies to deal with such changes.

Keywords: EURO-CORDEX, climate change, hydrology, SWAT model, Sardinia, multi-model ensemble

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Authors: J. J. Rickard, A. Belli, P. Goldberg Oppenheimer

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Medical diagnostics, environmental monitoring, homeland security and forensics increasingly demand specific and field-deployable analytical technologies for quick point-of-care diagnostics. Although technological advancements have made optical methods well-suited for miniaturization, a highly-sensitive detection technique for minute sample volumes is required. Raman spectroscopy is a well-known analytical tool, but has very weak signals and hence is unsuitable for trace level analysis. Enhancement via localized optical fields (surface plasmons resonances) on nanoscale metallic materials generates huge signals in surface-enhanced Raman scattering (SERS), enabling single molecule detection. This enhancement can be tuned by manipulation of the surface roughness and architecture at the sub-micron level. Nevertheless, the development and application of SERS has been inhibited by the irreproducibility and complexity of fabrication routes. The ability to generate straightforward, cost-effective, multiplex-able and addressable SERS substrates with high enhancements is of profound interest for SERS-based sensing devices. While most SERS substrates are manufactured by conventional lithographic methods, the development of a cost-effective approach to create nanostructured surfaces is a much sought-after goal in the SERS community. Here, a method is established to create controlled, self-organized, hierarchical nanostructures using electrohydrodynamic (HEHD) instabilities. The created structures are readily fine-tuned, which is an important requirement for optimizing SERS to obtain the highest enhancements. HEHD pattern formation enables the fabrication of multiscale 3D structured arrays as SERS-active platforms. Importantly, each of the HEHD-patterned individual structural units yield a considerable SERS enhancement. This enables each single unit to function as an isolated sensor. Each of the formed structures can be effectively tuned and tailored to provide high SERS enhancement, while arising from different HEHD morphologies. The HEHD fabrication of sub-micrometer architectures is straightforward and robust, providing an elegant route for high-throughput biological and chemical sensing. The superior detection properties and the ability to fabricate SERS substrates on the miniaturized scale, will facilitate the development of advanced and novel opto-fluidic devices, such as portable detection systems, and will offer numerous applications in biomedical diagnostics, forensics, ecological warfare and homeland security.

Keywords: hierarchical electrohydrodynamic patterning, medical diagnostics, point-of care devices, SERS

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Authors: Karolina Wieczorek, Zofia Przypaśniak

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Climate change is a rapidly growing threat to global health, and part of the responsibility to combat it lies within the healthcare sector itself, including adequate education of future medical professionals. To mitigate the consequences, the General Medical Council (GMC) has equipped medical schools with a list of outcomes regarding sustainability teaching. Students are expected to analyze the impact of the healthcare sector’s emissions on climate change. The delivery of the related teaching content is, however, often inadequate and insufficient time is devoted for exploration of the topics. Teaching curricula lack in-depth exploration of the learning objectives. This study aims to assess the extent and characteristics of climate change and sustainability subjects teaching in the curriculum of a chosen UK medical school (Barts and The London School of Medicine and Dentistry). It compares the data to the national average scores from the Climate Change and Sustainability Teaching (C.A.S.T.) in Medical Education Audit to draw conclusions about teaching on a regional level. This is a single-center audit of the timetabled sessions of teaching in the medical course. The study looked at the academic year 2020/2021 which included a review of all non-elective, core curriculum teaching materials including tutorials, lectures, written resources, and assignments in all five years of the undergraduate and graduate degrees, focusing only on mandatory teaching attended by all students (excluding elective modules). The topics covered were crosschecked with GMC Outcomes for graduates: “Educating for Sustainable Healthcare – Priority Learning Outcomes” as gold standard to look for coverage of the outcomes and gaps in teaching. Quantitative data was collected in form of time allocated for teaching as proxy of time spent per individual outcomes. The data was collected independently by two students (KW and ZP) who have received prior training and assessed two separate data sets to increase interrater reliability. In terms of coverage of learning outcomes, 12 out of 13 were taught (with the national average being 9.7). The school ranked sixth in the UK for time spent per topic and second in terms of overall coverage, meaning the school has a broad range of topics taught with some being explored in more detail than others. For the first outcome 4 out of 4 objectives covered (average 3.5) with 47 minutes spent per outcome (average 84 min), for the second objective 5 out of 5 covered (average 3.5) with 46 minutes spent (average 20), for the third 3 out of 4 (average 2.5) with 10 mins pent (average 19 min). A disproportionately large amount of time is spent delivering teaching regarding air pollution (respiratory illnesses), which resulted in the topic of sustainability in other specialties being excluded from teaching (musculoskeletal, ophthalmology, pediatrics, renal). Conclusions: Currently, there is no coherent strategy on national teaching of climate change topics and as a result an unstandardized amount of time spent on teaching and coverage of objectives can be observed.

Keywords: audit, climate change, sustainability, education

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Authors: Smita Singh

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Through the constructivist perspective, this paper explores the transformation of India’s nuclear identity from an irresponsible nuclear weapon power to a ‘de-facto nuclear power’ in the emerging international nuclear order From a nuclear abstainer to a bystander and finally as a ‘de facto nuclear weapon state’, India has put forth its case as a unique and exceptional nuclear power as opposed to Iran, Iraq and North Korea with similar nuclear ambitions, who have been snubbed as ‘rogue states’ by the international community. This paper investigates the reasons behind international community’s gradual acceptance of India’s nuclear weapons capabilities and nuclear identity after the Indo-U.S. Nuclear Deal. In this paper, the central concept of analysis is the inter-subjective nature of identity in the nuclear arena. India’s nuclear behaviour has been discursively constituted by India through evolving images of the ‘self’ and the ‘other.’ India’s sudden heightened global status is not solely the consequence of its 1998 nuclear tests but a calibrated projection as a responsible stakeholder in other spheres such as economic potential, market prospects, democratic credentials and so on. By examining India’s nuclear discourse this paper contends that India has used its material and discursive power in presenting a n striking image as a responsible nuclear weapon power (though not yet a legal nuclear weapon state as per the NPT). By historicising India’s nuclear trajectory through an inter-subjective analysis of identities, this paper moves a step ahead in providing a theoretical interpretation of state actions and nuclear identity construction.

Keywords: nuclear identity, India, constructivism, international stakeholder

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Authors: Remus Pravalie, Georgeta Bandoc

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Forests are crucial for humanity and biodiversity, through the various ecosystem services and functions they provide all over the world. Forest ecosystems are vital in Romania as well, through their various benefits, known as provisioning (food, wood, or fresh water), regulating (water purification, soil protection, carbon sequestration or control of climate change, floods, and other hazards), cultural (aesthetic, spiritual, inspirational, recreational or educational benefits) and supporting (primary production, nutrient cycling, and soil formation processes, with direct or indirect importance for human well-being) ecosystem services. These ecological benefits are of great importance in Romania, especially given the fact that forests cover extensive areas countrywide, i.e. ~6.5 million ha or ~27.5% of the national territory. However, the diversity and functionality of these ecosystem services fundamentally depend on certain key attributes of forests, such as biomass, which has so far not been studied nationally in terms of potential changes due to climate change and other driving forces. This study investigates, for the first time, changes in forest biomass in Romania in recent decades, based on a high volume of satellite data (Landsat images at high spatial resolutions), downloaded from the Google Earth Engine platform and processed (using specialized software and methods) across Romanian forestland boundaries from 1987 to 2018. A complex climate database was also investigated across Romanian forests over the same 32-year period, in order to detect potential similarities and statistical relationships between the dynamics of biomass and climate data. The results obtained indicated considerable changes in forest biomass in Romania in recent decades, largely triggered by the climate change that affected the country after 1987. Findings on the complex pattern of recent forest changes in Romania, which will be presented in detail in this study, can be useful to national policymakers in the fields of forestry, climate, and sustainable development.

Keywords: forests, biomass, climate change, trends, romania

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Authors: Raj Kumar, Navjyoti Dhingra

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Academic libraries are the hubs in which knowledge is a major resource and the performances of these knowledge in terms of adding and delivering value to their users depend upon their ability and effectiveness in engendering, arranging, managing, and using this knowledge. Developments in Information and Communication Technology’s (ICT), the libraries have been incorporated at the electronic edge to facilitate a rapid transfer of information on a global scale. Web2.0 refers to the development of online services that encourage collaboration, communication and information sharing. Web 2.0 reflects changes in how one can use the web rather than describing any technical or structural change. Libraries provide manifold channels of Information access to its e-users. The rapid expansion of tools, formats, services and technologies has presented many options to unfold Library Collection. Academic libraries must develop ways and means to meet their user’s expectations and remain viable. Web 2.0 tools are the first step on that journey. Web 2.0 has been widely used by the libraries to promote functional services like access to catalogue or for external activities like information or photographs of library events, enhancement of usage of library resources and bringing users closer to the library. The purpose of this paper is to provide a reconnaissance of Web 2.0 tools for enhancing library services in India. The study shows that a lot of user-friendly tools can be adopted by information professionals to effectively cater to information needs of its users. The authors have suggested a roadmap towards a revitalized future for providing various information opportunities to techno-savvy users.

Keywords: academic libraries, change management, social media, Web 2.0

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Authors: A. I. Khalafalla, K. A. Al-Busada, I. M. El-Sabagh

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Pox and pox-like diseases of camels are a group of exanthematous skin conditions that have become increasingly important economically. They may be caused by three distinct viruses: camelpox virus (CMPV), camel contagious ecthyma virus (CCEV) and camel papillomavirus (CAPV). These diseases are difficult to differentiate based on clinical presentation in disease outbreaks. Molecular methods such as PCR targeting species-specific genes have been developed and used to identify CMPV and CCEV, but not simultaneously in a single tube. Recently, multiplex PCR has gained reputation as a convenient diagnostic method with cost- and time–saving benefits. In the present communication, we describe the development, optimization and validation a multiplex PCR assays able to detect simultaneously the genome of the three viruses in one single test allowing for rapid and efficient molecular diagnosis. The assay was developed based on the evaluation and combination of published and new primer sets, and was applied to the detection of 110 tissue samples. The method showed high sensitivity, and the specificity was confirmed by PCR-product sequencing. In conclusion, this rapid, sensitive and specific assay is considered a useful method for identifying three important viruses in specimens from camels and as part of a molecular diagnostic regime.

Keywords: multiplex PCR, diagnosis, pox and pox-like diseases, camels

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Authors: Dua K. S. Y. Klaas, Monzur A. Imteaz, Ika Sudiayem, Elkan M. E. Klaas, Eldav C. M. Klaas

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Developing tailored management strategies to ensure the sustainability of groundwater resource under climate and demographic changes is critical for tropical karst island, where relatively small watershed and highly porous soil nature make this natural resource highly susceptible and thus very sensitive to those changes. In this study, long-term impacts of climate variability on groundwater recharge and discharge at the Oemau spring, Rote Island, Indonesia were investigated. Following calibration and validation of groundwater model using MODFLOW code, groundwater flow was simulated for period of 2020-2090 under HadCM3 global model climate (GCM) scenarios, using input data of weather variables downscaled by Statistical Downscaling Model (SDSM). The reported analysis suggests that the sustainability of groundwater resources will be adversely affected by climate change during dry years. The area is projected to variably experience 2.53-22.80% decrease of spring discharge. A subsequent comprehensive set of management strategies as palliative and adaptive efforts was proposed to be implemented by relevant stakeholders to assist the community dealing with water deficit during the dry years. Three main adaptive strategies, namely socio-cultural, technical, and ecological measures, were proposed by incorporating physical and socio-economic characteristics of the area. This study presents a blueprint for assessing groundwater sustainability under climate change scenarios and developing tailored management strategies to cope with adverse impacts of climate change, which may become fundamental necessities across other tropical karst islands in the future.

Keywords: climate change, groundwater, management strategies, tropical karst island, Rote Island, Indonesia

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Authors: Abdulsalam M. Alhawsawi

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Estimation of a radiation detector's efficiency plays a significant role in calculating the activity of radioactive samples. Detector efficiency is measured using sources that emit a variety of energies from low to high-energy photons along the energy spectrum. Some photon energies are hard to find in lab settings either because check sources are hard to obtain or the sources have short half-lives. This work aims to develop a method to determine the efficiency of a High Purity Germanium Detector (HPGe) based on the 662 keV gamma ray photon emitted from Cs-137. Cesium-137 is readily available in most labs with radiation detection and health physics applications and has a long half-life of ~30 years. Several photon efficiencies were calculated using the MCNP5 simulation code. The simulated efficiency of the 662 keV photon was used as a base to calculate other photon efficiencies in a point source and a Marinelli Beaker form. In the Marinelli Beaker filled with water case, the efficiency of the 59 keV low energy photons from Am-241 was estimated with a 9% error compared to the MCNP5 simulated efficiency. The 1.17 and 1.33 MeV high energy photons emitted by Co-60 had errors of 4% and 5%, respectively. The estimated errors are considered acceptable in calculating the activity of unknown samples as they fall within the 95% confidence level.

Keywords: MCNP5, MonteCarlo simulations, efficiency calculation, absolute efficiency, activity estimation, Cs-137

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

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Authors: Essebti Dhahri

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We present a new refrigerant La₀.₇Ca₀.₁₅Sr₀.₁₅Mn₁₋ₓGaₓO₃ (x = 0.0-0.1) manganites. These compounds were prepared by the sol-gel method. The refinement of the X-ray diffraction reveals that all samples crystallize in a rhombohedral structure (space group R3 ̅c). Detailed measurements of the magnetization as a function of temperature and magnetic applied field M (µ₀H, T) were carried out. From the M(µ₀H, T) curves, we have calculated the magnetic entropy change (ΔSM) according to the Maxwell relation. The temperature dependence of the magnetization M(T) reveals a decrease of M when increasing the x content. The magnetic entropy change (ΔSM) reaches a maximum value near room temperature. It was also found that this compound exhibits a large magnetocaloric effect MCE which increases when decreasing Ga concentration. So, the studied compounds could be considered potential materials for magnetic refrigeration application.

Keywords: magnetic measurements, Rietveld refinement, magnetic refrigeration, magnetocaloric effect

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Authors: Brittany Richardson, Ying Wang

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For physical therapy, exercise prescription, athlete training, and regular fitness training, it is crucial to perform health assessments or fitness assessments periodically. An accurate assessment is propitious for tracking recovery progress, preventing potential injury and making long-range training plans. Assessments include necessary measurements, height, weight, blood pressure, heart rate, body fat, etc. and advanced evaluation, muscle group strength, stability-mobility, and movement evaluation, etc. In the current standard assessment procedures, the accuracy of assessments, especially advanced evaluations, largely depends on the experience of physicians, coaches, and personal trainers. And it is challenging to track clients’ progress in the current assessment. Unlike the tradition assessment, in this paper, we present a deep learning based face recognition algorithm for accurate, comprehensive and trackable assessment. Based on the result from our assessment, physicians, coaches, and personal trainers are able to adjust the training targets and methods. The system categorizes the difficulty levels of the current activity for the client or user, furthermore make more comprehensive assessments based on tracking muscle group over time using a designed landmark detection method. The system also includes the function of grading and correcting the form of the clients during exercise. Experienced coaches and personal trainer can tell the clients' limit based on their facial expression and muscle group movements, even during the first several sessions. Similar to this, using a convolution neural network, the system is trained with people’s facial expression to differentiate challenge levels for clients. It uses landmark detection for subtle changes in muscle groups movements. It measures the proximal mobility of the hips and thoracic spine, the proximal stability of the scapulothoracic region and distal mobility of the glenohumeral joint, as well as distal mobility, and its effect on the kinetic chain. This system integrates data from other fitness assistant devices, including but not limited to Apple Watch, Fitbit, etc. for a improved training and testing performance. The system itself doesn’t require history data for an individual client, but the history data of a client can be used to create a more effective exercise plan. In order to validate the performance of the proposed work, an experimental design is presented. The results show that the proposed work contributes towards improving the quality of exercise plan, execution, progress tracking, and performance.

Keywords: exercise prescription, facial recognition, landmark detection, fitness assessments

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Authors: Ghodbane Azeddine, Saad Maarouf, Boland Jean-Francois, Thibeault Claude

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This paper proposes a new design of an active fault-tolerant flight control system against abrupt actuator faults. This overall system combines a multiple time scale sliding mode controller for fault compensation and a geometric approach for fault detection and diagnosis. The proposed control system is able to accommodate several kinds of partial and total actuator failures, by using available healthy redundancy actuators. The overall system first estimates the correct fault information using the geometric approach. Then, and based on that, a new reconfigurable control law is designed based on the multiple time scale sliding mode technique for on-line compensating the effect of such faults. This approach takes advantages of the fact that there are significant difference between the time scales of aircraft states that have a slow dynamics and those that have a fast dynamics. The closed-loop stability of the overall system is proved using Lyapunov technique. A case study of the non-linear model of the F16 fighter, subject to the rudder total loss of control confirms the effectiveness of the proposed approach.

Keywords: actuator faults, fault detection and diagnosis, fault tolerant flight control, sliding mode control, multiple time scale approximation, geometric approach for fault reconstruction, lyapunov stability

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Authors: Khalid Alhudaib

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Potato is considered as one of the most important and potential vegetable crops in Saudi Arabia. Alfalfa mosaic virus (AMV), genus Alfamovirus, family Bromoviridae is among the broad spread of viruses in potato. During spring and fall growing seasons of potato in 2015 and 2016, several field visits were conducted in the four major growing areas of potato cultivation (Riyadh-Qaseem-Hail-Hard). The presence of AMV was detected in samples using ELISA, dot blot hybridization and/or RT-PCR. The highest occurrence of AMV was observed as 18.6% in Qaseem followed by Riyadh with 15.2% while; the lowest infection rates were recorded in Hard and Hail, 8.3 and 10.4%, respectively. The sequences of seven isolates of AMV obtained in this study were determined and the sequences were aligned with the other sequences available in the GenBank database. Analyses confirmed the low variability among AMV isolated in this study, which means that all AMV isolates may originate from the same source. Due to high incidence of AMV, other economic susceptible crops may become affected by high incidence of this virus in potato crops. This requires accurate examination of potato seed tubers to prevent the spread of the virus in Saudi Arabia. The obtained results indicated that the hybridization and ELISA are suitable techniques in the routine detection of AMV in a large number of samples while RT-PCR is more sensitive and essential for molecular characterization of AMV.

Keywords: Alfamovirus, AMV, Alfalfa mosaic virus, PCR, potato

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Authors: Gauravi Agarkar, Mahendra Rai

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Fungi are closely associated with the plants in various types of interactions such as mycorrhizal, parasitic or endophytic. Some of these interactions are beneficial and a few are harmful to the host plants. It has been suggested that these plant-associated fungi are able to change their lifestyle abd this means endophyte may become parasite or vice versa. This phenomenon may have profound effect on plant-fungal interactions and various ecological niches. Therefore, it is necessary to identify the factors that trigger the change in fungal lifestyle and understand whether these different lifestyles are interconnected at some points either by physiological, biochemical or molecular routes. This review summarizes the factors affecting plant fungal interactions and discusses the possible mechanisms for lifestyles switching of fungi based on available experimental evidences. Research should be boosted in this direction to fetch more advantages in future and to avoid the severe consequences in agriculture and other related fields.

Keywords: endophytic, lifestyle switching, mycorrhizal, parasitic, plant-fungal interactions

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Authors: Chargui Ridha, Agrebi Sameh

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The integration of phase change materials (PCM) for the storage of thermal energy during the period of sunshine before being released during the night is a complement of free energy to improve the system formed by a solar collector, tank storage, and a heat exchanger. This paper is dedicated to the design of a thermal storage tank based on a PCM-based heat exchanger. The work is divided into two parts: an experimental part using paraffin as PCM was carried out within the Laboratory of Thermal Processes of Borj Cedria in order to improve the performance of the system formed by the coupling of a flat solar collector and a thermal storage tank and to subsequently determine the influence of PCM on the whole system. This phase is based on the measurement instrumentation, namely, a differential scanning calorimeter (DSC) and the thermal analyzer (hot disk: HOT DISK) in order to determine the physical properties of the paraffin (PCM), which has been chosen. The second phase involves the detailed design of the PCM heat exchanger, which is incorporated into a thermal storage tank and coupled with a solar air collector installed at the Research and Technology Centre of Energy (CRTEn). A numerical part based on the TRANSYS and Fluent software, as well as the finite volume method, was carried out for the storage reservoir systems in order to determine the temperature distribution in each chosen system.

Keywords: phase change materials, storage tank, heat exchanger, flat plate collector

Procedia PDF Downloads 94

Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

Abstract:

Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

Procedia PDF Downloads 65

Authors: M. Barsa

Abstract:

This paper argues that current liberal trade regimes have had the unfortunate effect of concentrating food production by area and by crop. While such hyper-specialization and standardization might be efficient under ordinary climate conditions, the increasing severity of climate shocks makes such a food production system especially vulnerable. Examining domestic US crop production, and the fact that similar patterns are evident worldwide, this paper explores the vulnerabilities of several major crops and suggests that the academic arguments surrounding increasing liberalization of trade are ill-suited to the climate challenges to come. Indeed, a case can be made that protectionist measures—especially by developing countries whose agricultural sectors are vulnerable to the cheap US and European exports—are increasingly necessary to scatter food production geographically and to retain a resilient diversity of crop varieties.

Keywords: climate change, crop resilience, diversity, international trade

Procedia PDF Downloads 130

Authors: Mian Adnan Kakakhel, NIshita Narwal, Majid Rasta, Shi Xiaotao

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The widespread use of nanoparticles means that they are significantly increasing in the aquatic ecosystem, where they are likely to pose threat to aquatic organism. In particular, the influence of nanoparticles exposure combined with varying water velocities on fish behavior remain poorly understood. Emerging evidences suggested a probable correlation between fish swimming behavior and gut bacterial dysbiosis. Therefore, the current study aimed to investigate the effects of nanomaterials in different water velocities on fish gut bacterial composition, which in results change in fish swimming behavior. The obtained findings showed that the contamination of nanoparticles was reduced as the velocity increased. However, the synergetic effects of nanoparticles and water velocity significantly (p < 0.05) decreased the bacterial composition, which plays a critical role in fish development, metabolism, digestion, enzymes production, and energy production such as Bacteroidetes and Firmicutes. This group of bacterial also support fish in swimming behavior by providing them a significant energy during movement. The obtained findings of this study suggested that the presence of nanoparticles in different water velocities have had a significant correlation with fish gut bacterial dysbiosis, as results the gut dysbiosis had been linked to the change in fish behavior. The study provides an important insight into the mechanisms by which the nanoparticles possibly affect the fish behavior.

Keywords: water velocities, fish behavior, gut bacteria, secondary metabolites, regulation

Procedia PDF Downloads 82

Authors: Mohsina Aktar, Bishawjit Mallick

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Bangladesh faces the multidimensional manifestations of climate change e.g. flood, cyclone, sea level rise, drainage congestion, salinity, etc. This study aimed at to find out the community’s perception of the perceived impact of climate change on their wetland resource based livelihood, to analyze their present livelihood scenario and to find out required institutional setup to strengthen present livelihood scenario. Therefore, this study required both quantitative analysis like quantification of wetland resources, occupation, etc. and also exploratory information like policy and institutional reform. For quantitative information 200 questionnaire survey and in some cases observation survey and for socially shareable qualitative and quantitative issues case study and focus group discussion were conducted. In-Depth interview was conducted for socially non-shareable qualitative issues. The overall findings of this study have been presented maintaining a sequence- perception about climate change effect, livelihood scenario and required institutional support of the wetland community. Flood has been ranked where cyclone effect is comparatively less disastrous in this area. Heavy rainfall comes after the cyclone. Female members responded almost same about the ranking and effects of frequently occurred and devastating effects of climate change. People are much more aware of the impact of climate change. Training of Care in RVCC project helps to increase their knowledge level. If the level of education can be increased, people can fight against calamity and poverty with more confidence. People seem to overcome the problems of water logging and thus besides involving in Hydroponics (33.3%) as prime occupation in monsoon; they are also engaged in other business related activities. January to May is the low-income season for the farmers. But some people don’t want to change their traditional occupation and their age is above 45. The young earning member wants to utilize their lean income period by alternative occupation. People who do not have own land and performing water transportation or other types of occupation are now interested about Hydroponics. People who give their land on rent are now thinking about renting their land in monsoon as through that they can earn a sound amount rather than get nothing. What they require is just seed, training, and capital. Present marketing system faces the problem of communication. So this sector needed to be developed. Involvement of women in income earning activity is very low (5.1%), and 100% women are housewives. They became inferior due to their educational level and dominance of their husband. Only one NGO named BCAS (Bangladesh Center for Advanced Studies) has been found engage training facilities and advocacy for this purpose. Upazilla agricultural extension office like other GO remains inactive to give support the community for extension and improvement of Hydroponics agriculture. If the community gets proper support and inspiration, they can fight against crisis of low-income and climate change, with the Hydroponics cultivation system successfully.

Keywords: wetland community, hydroponics, climate change adaptation, livelihood

Procedia PDF Downloads 274

Authors: Madhushi Bandara, Dharshana Kasthurirathna, Danaja Maldeniya, Mahendra Piraveenan

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Community detection is an extremely useful technique in understanding the structure and function of a social network. Louvain algorithm, which is based on Newman-Girman modularity optimization technique, is extensively used as a computationally efficient method extract the communities in social networks. It has been suggested that the nodes that are in close geographical proximity have a higher tendency of forming communities. Variants of the Newman-Girman modularity measure such as dist-modularity try to normalize the effect of geographical proximity to extract geographically dispersed communities, at the expense of losing the information about the geographically proximate communities. In this work, we propose a method to extract geographically dispersed communities while preserving the information about the geographically proximate communities, by analyzing the ‘community network’, where the centroids of communities would be considered as network nodes. We suggest that the inter-community link strengths, which are normalized over the community sizes, may be used to identify and extract the ‘overlay communities’. The overlay communities would have relatively higher link strengths, despite being relatively apart in their spatial distribution. We apply this method to the Gowalla online social network, which contains the geographical signatures of its users, and identify the overlay communities within it.

Keywords: social networks, community detection, modularity optimization, geographically dispersed communities

Procedia PDF Downloads 235

Authors: A. Selmi, A. Bettaibi, H. Rahmouni, R. M’nassri, N. Chniba Boudjada, A. Chiekhrouhou, K. Khirouni

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Investigation of magnetic and magnetocaloric properties of Pr₀.₇Ca₀.₃Mn₀.₉M₀.₁O₃ perovskite manganites (M=Cr and Ni) has been carried out. Our compounds were prepared by the conventional solid-state reaction method at high temperatures. Rietveld refinement of X-ray diffraction pattern using FULLPROF method shows that all compounds adopt the orthorhombic structure with Pnma space group. The partial substitution of Mn-site drives the system from charge order state to ferromagnetic one with a Curie temperature T𝒸=150K, 118k and 116K for M=Cr and Ni, respectively. Magnetization measurements versus temperature in a magnetic applied field of 0.05T show that all our samples exhibit a paramagnetic–ferromagnetic transition with decreasing temperature. From M(H) isotherms, we have deduced the magnetic entropy change, which present maximum values of 2.37 J/kg.K and 2.94 J/kg.K, in a magnetic field change of 5T for M=Cr and Ni, respectively.

Keywords: manganites, magnetocaloric, magnetic, refrigeration

Procedia PDF Downloads 79

Authors: Thilini M. Yatanwala

Abstract:

CCTV (Closed-Circuit-Television) Surveillance System is being used in public places over decades and a large variety of data is being produced every moment. However, most of the CCTV data is stored in isolation without having integrity. As a result, identification of the behavior of suspicious people along with their location has become strenuous. This research was conducted to acquire more accurate and reliable timely information from the CCTV video records. The implemented system can identify human objects in public places based on outfit colors. Inter-process communication technologies were used to implement the CCTV camera network to track people in the premises. The research was conducted in three stages and in the first stage human objects were filtered from other movable objects available in public places. In the second stage people were uniquely identified based on their outfit colors and in the third stage an individual was continuously tracked in the CCTV network. A face detection algorithm was implemented using cascade classifier based on the training model to detect human objects. HAAR feature based two-dimensional convolution operator was introduced to identify features of the human face such as region of eyes, region of nose and bridge of the nose based on darkness and lightness of facial area. In the second stage outfit colors of human objects were analyzed by dividing the area into upper left, upper right, lower left, lower right of the body. Mean color, mod color and standard deviation of each area were extracted as crucial factors to uniquely identify human object using histogram based approach. Color based measurements were written in to XML files and separate directories were maintained to store XML files related to each camera according to time stamp. As the third stage of the approach, inter-process communication techniques were used to implement an acknowledgement based CCTV camera network to continuously track individuals in a network of cameras. Real time analysis of XML files generated in each camera can determine the path of individual to monitor full activity sequence. Higher efficiency was achieved by sending and receiving acknowledgments only among adjacent cameras. Suspicious incidents such as a person staying in a sensitive area for a longer period or a person disappeared from the camera coverage can be detected in this approach. The system was tested for 150 people with the accuracy level of 82%. However, this approach was unable to produce expected results in the presence of group of people wearing similar type of outfits. This approach can be applied to any existing camera network without changing the physical arrangement of CCTV cameras. The study of human identification and suspicious incident detection using outfit color analysis can achieve higher level of accuracy and the project will be continued by integrating motion and gait feature analysis techniques to derive more information from CCTV videos.

Keywords: CCTV surveillance, human detection and identification, image processing, inter-process communication, security, suspicious detection

Procedia PDF Downloads 183