Search results for: the health belief model

Authors: Nooshin Salari, Viliam Makis, Jane Doe

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This paper presents a maintenance policy for a system consisting of two units. Unit 1 is gradually deteriorating and is subject to soft failure. Unit 2 has a general lifetime distribution and is subject to hard failure. Condition of unit 1 of the system is monitored periodically and it is considered as failed when its deterioration level reaches or exceeds a critical level N. At the failure time of unit 2 system is considered as failed, and unit 2 will be correctively replaced by the next inspection epoch. Unit 1 or 2 are preventively replaced when deterioration level of unit 1 or age of unit 2 exceeds the related preventive maintenance (PM) levels. At the time of corrective or preventive replacement of unit 2, there is an opportunity to replace unit 1 if its deterioration level reaches the opportunistic maintenance (OM) level. If unit 2 fails in an inspection interval, system stops operating although unit 1 has not failed. A mathematical model is derived to find the preventive and opportunistic replacement levels for unit 1 and preventive replacement age for unit 2, that minimize the long run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process (SMDP) framework. Numerical example is provided to illustrate the performance of the proposed model and the comparison of the proposed model with an optimal policy without opportunistic maintenance level for unit 1 is carried out.

Keywords: condition-based maintenance, opportunistic maintenance, preventive maintenance, two-unit system

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Authors: Salman Abdul Majeed, Vidur Solanki, Ruqiya Shama Tareen

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BACKGROUND: The COVID-19 pandemic has affected the way of living as we have known for all strata of society. While disease containment measures imposed by governmental agencies have been instrumental in controlling the spread of the virus, it has had profound collateral impacts on all populations. However, the disruption caused in the lives of one segment of population has been far more damaging than most others: the emotional wellbeing of our child and adolescent populations. This impact was even more pronounced in children who already suffered from neurodevelopmental or psychiatric disorders. In particular, school closures have not only led to profound social isolation, but also negative impacts on normal developmental opportunities and interruptions in mental health services obtained through school systems. It is too soon to understand the full impacts of quarantine, isolation, stress of social detachment and fear of pandemic, but we have started to see the devastating impact on C&A already. This review intends to shed light on the current understanding of psychiatric wellbeing of C&A during COVID-19 pandemic. METHOD: Literature search utilizing key words COVID-19 and children, quarantine and children, social isolation, Loneliness, pandemic stress and children, and mental health of children, disease containment measures was carried out. Over 200 articles were identified, out of which 81 articles were included in this review article. RESULTS: The disruption caused by COVID-19 in the lives of C&A is much more damaging and its impact is far reaching. The C&A ED visits for possible suicide attempts have jumped to 22.3% in 2020 and 39.1% during 2021. One study utilizing T1-weighted structural images, computed the thickness of cortical and subcortical structures including amygdala, hippocampus, and nucleus accumbens. The Peri-COVID group showed reduced cortical and subcortical thickness and more advanced brain aging compared to pre pandemic studies. CONCLUSION: Mental health resources for C&A remain under funded, neglected, and inaccessible to population that needs it most. Children with ongoing mental health disorders were impacted worst, along with those with predisposed biopsychosocial risk factors.

Keywords: COVID-19 and children, quarantine and children, social isolation, Loneliness, pandemic stress and children, disease containment measures, mental health of children

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Authors: Reza E. Sedgh, Rajesh P. Dhakal

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Shear walls have been used extensively as the main lateral force resisting systems in multi-storey buildings. The recent development in performance based design urges practicing engineers to conduct nonlinear static or dynamic analysis to evaluate seismic performance of multi-storey shear wall buildings by employing distinct analytical models suggested in the literature. For practical purpose, application of macroscopic models to simulate the global and local nonlinear behavior of structural walls outweighs the microscopic models. The skill level, computational time and limited access to RC specialized finite element packages prevents the general application of this method in performance based design or assessment of multi-storey shear wall buildings in design offices. Hence, this paper organized to verify capability of nonlinear shell element in commercially available package (Sap2000) in simulating results of some specimens under monotonic and cyclic loads with very oversimplified available cyclic material laws in the analytical tool. The selection of constitutive models, the determination of related parameters of the constituent material and appropriate nonlinear shear model are presented in detail. Adoption of proposed simple model demonstrated that the predicted results follow the overall trend of experimental force-displacement curve. Although, prediction of ultimate strength and the overall shape of hysteresis model agreed to some extent with experiment, the ultimate displacement(significant strength degradation point) prediction remains challenging in some cases.

Keywords: analytical model, nonlinear shell element, structural wall, shear behavior

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Authors: Arezoo Sadrinezhad, Kallol Sett, S. I. Hariharan

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In this paper, a probabilistic framework based on Fokker-Planck-Kolmogorov (FPK) approach has been applied to simulate triaxial cyclic constitutive behavior of uncertain soils. The framework builds upon previous work of the writers, and it has been extended for cyclic probabilistic simulation of triaxial undrained behavior of soils. von Mises elastic-perfectly plastic material model is considered. It is shown that by using probabilistic framework, some of the most important aspects of soil behavior under cyclic loading can be captured even with a simple elastic-perfectly plastic constitutive model.

Keywords: elasto-plasticity, uncertainty, soils, fokker-planck equation, fourier spectral method, finite difference method

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Authors: Turki Alotaibi

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Student counseling programs can provide many benefits to students in schools all around the world. In theory, the government of the Kingdom of Saudi Arabia (Saudi Arabia) has committed itself to school counseling programs in educational institutions throughout the country. Student counselors face a number of burdens and obstacles that impact student counseling programs. It is also widely known that Saudi Arabia has extremely high prevalence rates for overweight and obesity, anxiety and depression, and diabetes in children. It has also been demonstrated that teachers and staff are inadequately prepared when dealing with health issues relating to diabetes in schools in Saudi Arabia. This study will clearly demonstrate how student counselors in Saudi Arabia could become 'New Educators' in Saudi schools in relation to these health issues. This would allow them to leverage their position as student counselor to improve the management of these health issues in Saudi schools, to improve the quality of care provided to school children, and to overcome burdens and obstacles that are currently negatively affecting student counseling in Saudi schools.

Keywords: anxiety and depression, diabetes, overweight and obesity, policy recommendations, student counseling, The Kingdom of Saudi Arabia

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Authors: Alok Kumar Routa, Priya Ranjan Mohanty

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Complex seismic signatures are generated due to the complexity of the subsurface which is difficult to interpret. In the present study, an attempt has been made to model the complex subsurface using the Ray tracing modeling technique. Add to this, for the imaging of these geological features, Kirchhoff’s prestack depth migration is applied over the synthetic common shot gather dataset. It is found that the Kirchhoff’s migration technique in addition with the Ray tracing modeling concept has the flexibility towards the imaging of various complex geology which gives satisfactory results with proper delineation of the reflectors at their respective true depth position. The entire work has been carried out under the MATLAB environment.

Keywords: Kirchhoff's migration, Prestack depth migration, Ray tracing modelling, velocity model

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Authors: Ali Javaid, Rizwan Latif, Syed Adnan Qasim, Imran Shafi

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To control combustion inside a direct injection diesel engine, fuel atomization is the best tool. Controlling combustion helps in reducing emissions and improves efficiency. Cavitation is one of the most important factors that significantly affect the nature of spray before it injects into combustion chamber. Typical fuel injector nozzles are small and operate at a very high pressure, which limits the study of internal nozzle behavior especially in case of diesel engine. Simulating cavitation in a fuel injector will help in understanding the phenomenon and will assist in further development. There is a parametric variation between high speed and high torque low speed diesel engines. The objective of this study is to simulate internal spray characteristics for a low speed high torque diesel engine. In-nozzle cavitation has strong effects on the parameters e.g. mass flow rate, fuel velocity, and momentum flux of fuel that is to be injected into the combustion chamber. The external spray dynamics and subsequently the air – fuel mixing depends on a lot of the parameters of fuel injecting the nozzle. The approach used to model turbulence induced in – nozzle cavitation for high-torque low-speed diesel engine, is homogeneous equilibrium model. The governing equations were modeled using Matlab. Complete Model in question was extensively evaluated by performing 3-D time-dependent simulations on Open FOAM, which is an open source flow solver and implemented in CFD (Computational Fluid Dynamics). Results thus obtained will be analyzed for better evaporation in the near-nozzle region. The proposed analyses will further help in better engine efficiency, low emission, and improved fuel economy.

Keywords: cavitation, HEM model, nozzle flow, open foam, turbulence

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Authors: Zubair Ahmad, Paolo Esposito

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The management of solid waste from its collection to disposal is a widespread issue all around the world. This is a stinging issue in the rural and urban areas of the developing and developed states of the world. The mismanagement in Pakistan in the context of solid waste is required to be recognized because it is not only affecting the health of the public but also affecting the health of the environment. Therefore, this study conducts qualitative research methodology and conducted interviews in Lahore, Karachi, Quetta, Peshawar and Islamabad’s solid waste management’s officials and waste pickers, for analyzing uses Grounded theory for the lens of thematic analysis to highlight how public value is being destroyed by the mismanagement of solid waste in Pakistan. This study critically examines the effects of corruption, mismanagement, lawlessness, lack of accountability, budgetary issues, and improper methods for the disposal of solid waste as the major factors that are destroying public value. Recognizing and addressing these factors is essential to improving the system of solid waste management in developing countries

Keywords: solid waste management, public value destruction, health, environment, accountability, grounded theory

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Authors: Mosses E. Lufuke, Lorna M. Kamau

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This paper attempted to assess whether the size of the regional economic bloc has an impact to the flow of trade to a particular country. Two different sized blocs (COMESA and EAC) and one country (Tanzania) have been used as the point of references. Using the results from of the analyses, the paper also was anticipated to establish whether it was rational for Tanzania to withdraw its membership from COMESA (the larger bloc) to join EAC (the small one). Gravity model has been used to estimate the relationship between the variables, from which the bilateral trade flows between Tanzania and the eighteen member countries of the two blocs (COMESA and EAC) was employed for the time between 2000 and 2013. In the model, the dummy variable for regional bloc (bloc) at which the Tanzania trade partner countries belong are also added to the model to understand which trade bloc exhibit higher trade flow with Tanzania. From the findings, it was noted that over the period of study (2000-2013) Tanzania acknowledged more than 257% of trade volume in EAC than in COMESA. Conclusive, it was noted that the flow of trade is explained by many other variables apart from the size of regional bloc; and that the size by itself offer insufficient evidence in causality relationship. The paper therefore remain neutral on such staggered switching decision since more analyses are required to establish the country’s trade flow, especially when if it had been in multiple membership of COMESA and EAC.

Keywords: economic bloc, flow of trade, size of bloc, switching

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Authors: D. B. Gohil

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Closed die forging is a very complex process, and measurement of actual forces for real material is difficult and time consuming. Hence, the modelling technique has taken the advantage of carrying out the experimentation with the proper model material which needs lesser forces and relatively low temperature. The results of experiments on the model material then may be correlated with the actual material by using the theory of similarity. There are several methods available to resolve the complexity involved in the closed die forging process. Finite Element Method (FEM) and Finite Difference Method (FDM) are relatively difficult as compared to the slab method. The slab method is very popular and very widely used by the people working on shop floor because it is relatively easy to apply and reasonably accurate for most of the common forging load requirement computations.

Keywords: experimentation, forging, process modeling, strain distribution

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Authors: Nileshkumar Vishnav, Aditya Tatu

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A recent approach of representing graph signals and graph filters as polynomials is useful for graph signal processing. In this approach, the adjacency matrix plays pivotal role; instead of the more common approach involving graph-Laplacian. In this work, we follow the adjacency matrix based approach and corresponding algebraic signal model. We further expand the theory and introduce the concept of similarity of two graphs. The similarity of graphs is useful in that key properties (such as filter-response, algebra related to graph) get transferred from one graph to another. We demonstrate potential applications of the relation between two similar graphs, such as nonuniform filter design, DTMF detection and signal reconstruction.

Keywords: graph signal processing, algebraic signal processing, graph similarity, isospectral graphs, nonuniform signal processing

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Authors: Zhiyan Meng, Dan Liu, Jintao Meng

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Dependable encrypted traffic classification is crucial for improving cybersecurity and handling the growing amount of data. Large language models have shown that learning from large datasets can be effective, making pre-trained methods for encrypted traffic classification popular. However, attention-based pre-trained methods face two main issues: their large neural parameters are not suitable for low-computation environments like mobile devices and real-time applications, and they often overfit by getting stuck in local minima. To address these issues, we developed a lightweight transformer model, which reduces the computational parameters through lightweight vocabulary construction and Squeeze-and-Excitation Block. We use sharpness-aware optimization to avoid local minima during pre-training and capture temporal features with relative positional embeddings. Our approach keeps the model's classification accuracy high for downstream tasks. We conducted experiments on four datasets -USTC-TFC2016, VPN 2016, Tor 2016, and CICIOT 2022. Even with fewer than 18 million parameters, our method achieves classification results similar to methods with ten times as many parameters.

Keywords: sharpness-aware optimization, encrypted traffic classification, squeeze-and-excitation block, pretrained model

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Authors: Meinrad Haule Lembuka

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Ubuntu is an African philosophy and model with the meaning of 'humanity to others' or 'care for other’s needs because of the guiding principle of interdependence’ that embraces collective and holistic efforts in development through the human face. The study uses a literature review method reflecting Julius Nyerere’s contributions in realizing Ubuntu and social work practice. Nyerere strived to restore Africa development in the lens of humanism through the values of solidarity, communal participation, compassion, care, justice etc; He later founded developmental social work through Ujamaa model, educational for self reliance and African dignity. Nyerere was against post-colonial syndromes through African socialism that envisioned values and principles of social work to provide social justice, human dignity, social change and social development. Also, he managed to serve the primary mission of the social work profession to enhance human wellbeing and help meet basic human needs of all people, with particular attention to the needs and empowerment of people who are vulnerable, oppressed, and living in poverty with African Ubuntu practice of equal distribution of resources. Nyerere further endorsed social work legal framework that embraced universal human rights: service, equality, social justice, and human dignity, Importance of human relationship, integrity and competence. Nyerere proved that Indigenous model can work with formal system like Social work profession. In 2014 the National Heritage Council of South Africa (NHC) honored him an Award of African Ubuntu champion. Nyerere strongly upheld to be an ambassador of social work through his remarkably contributions in developmental social work (Ujamaa model), social change, human dignity, equality, social unity and social justice in Africa and globe at large.

Keywords: ubuntu, Indiginious knowledge, Indiginious social work, ubuntu social work

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Authors: Dawn Watling, Lorraine Lecourtois, Adnan Levent, Ryan Jeffries, Aysha Bellamy

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Mental health diagnoses are on the rise for adolescents worldwide, with many being unable to access support and increasing use of social prescribing time in nature. There is an increasing need to better understand the preventive benefits of spending time in nature. In this paper, research findings from 599 seven to 12-year-olds completed two sets of questionnaires (before the visit and after a walk in nature). Participants spent time in one of three different biodiverse habitats. Findings explore predictors (including age, sex, and mental health) of increases in connection to nature and well-being. Secondly, research findings from 313 eighteen to 87-year-olds who completed questionnaires and had their heart rate monitored, followed by a self-guided walk, will be discussed. Findings explore predictors (including age, sex, connectedness to nature, well-being, and heart rate as a proxy measure of stress) of increases in mood and feelings of restoration. The discussion will focus on the converging evidence for taking time to notice nature and the role of different environments in enhancing connection to nature, well-being, and positive mental health.

Keywords: nature, connectedness to nature, social prescribing, wellbeing

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Authors: Precious Roselyn Obuobi

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Background: In Ghana, water-borne diseases remain a public health concern due to its impact. While marine pollution has been linked to outbreak of diseases especially in communities along the coast, associated risks such as oil spillage, marine debris, erosion, improper waste disposal and management practices persist. Objective: The study seeks to investigate sanitation practices that contribute to marine pollution in Prampram and the prevalence of selected water-borne diseases (diarrhea and typhoid fever). Method: This study used a descriptive cross-sectional design, employing the mix-method (qualitative and quantitative) approach. Twenty-two (22) participants were selected and semistructured questionnaire were administered to them. Additionally, interviews were conducted to collect more information. Further, an observation check-list was used to aid the data collection process. Secondary data comprising information on water-borne diseases in the district was acquired from the district health directorate to determine the prevalence of selected water-borne diseases in the community. Data Analysis: The qualitative data was analyzed using NVIVO® software by adapting the six steps thematic analysis by Braun and Clarke whiles STATA® version 16 was used to analyze the secondary data collected from the district health directorate. A descriptive statistic employed using mean, standard deviation, frequencies and proportions were used to summarize the results. Results: The results showed that open defecation and indiscriminate waste disposal were the main practices contributing to marine pollution in Prampram and its effect on public health. Conclusion: These findings have implications on public health and the environment, thus effort needs to be stepped up in educating the community on best sanitation practices.

Keywords: environment, sanitation, marine pollution, water-borne diseases

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Authors: M. Azharul Islam, M. Russel Sarker, M. Shahadat Hossen

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Air pollution is one of the major environmental problems that have gained importance in all over the world. Air pollution is a problem for all of us. The present study was conducted to explore the people’s perception level and awareness of air pollution in selected areas of Mymensingh in Bangladesh. Health impacts of air pollution also studied through personal interview and structured questionnaire. The relationship of independent variables (age, educational qualification, family size, residence and communication exposure) with the respondent’s perception level and awareness of air pollution (dependent variable) was studied to achieve the objectives of the study. About 600 respondents were selected randomly from six sites for collecting data during the period of July 2016 to June 2017. Pearson’s product-moment correlation coefficients were computed to examine the relationship between the concerned variables. The results revealed that about half (46.67%) of the respondents had a medium level of perception and awareness about air pollution in their areas where 31.67 percent had low, and 21.67 percent had a high level. In rural areas of the study sites, 43.33 percent respondents had low, 50 percent had medium, and only 6.67 percent had high perception and awareness on air pollution. In case of urban areas, 20 percent respondents had low, 43.33 percent had medium, and 36.67 percent had a high level of awareness and perception on air pollution. The majority of the respondents (93.33 percent) were lacking of proper awareness about air pollution in rural areas while 63.33 percent in urban areas. Out of five independent variables, three variables such as- educational qualification, residence status and communication exposure had positive and significant relationship. Age of respondents had negative and significant relationship with their awareness of air pollution where family size of the respondents had no significant relationship with their perception and awareness of air pollution. Thousands of people live in urban areas where urban smog, particle pollution, and toxic pollutants pose serious health concerns. But most of the respondents of the urban sites are not familiarize about the real causes of air pollution. Respondents exposed higher level of experience for air pollutants, such as- irritation of the eyes, coughing, tightness of chest and many health difficulties. But respondents of both rural and urban area hugely suffered such health problems and the tendency of certain difficulties increased day by day. In this study, most of the respondents had lack of knowledge on the causes of such health difficulties due to their lower perception level. Proper attempts should be taken to raise literacy level, communication exposure to increase the perception and awareness of air pollution among the respondents of the study areas. Extra care with above concerned fields should be taken to increase perception and awareness of air pollution in rural areas.

Keywords: air pollution, awareness, health impacts, perception of people

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Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

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Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

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Authors: Jaiden Xuan Schraut, Leon Liu, Yiqiao Yin

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Computer vision in medical diagnosis has achieved a high level of success in diagnosing diseases with high accuracy. However, conventional classifiers that produce an image to-label result provides insufficient information for medical professionals to judge and raise concerns over the trust and reliability of a model with results that cannot be explained. In order to gain local insight into cancerous regions, separate tasks such as imaging segmentation need to be implemented to aid the doctors in treating patients, which doubles the training time and costs which renders the diagnosis system inefficient and difficult to be accepted by the public. To tackle this issue and drive AI-first medical solutions further, this paper proposes a multi-output network that follows a U-Net architecture for image segmentation output and features an additional convolutional neural networks (CNN) module for auxiliary classification output. Class activation maps are a method of providing insight into a convolutional neural network’s feature maps that leads to its classification but in the case of lung diseases, the region of interest is enhanced by U-net-assisted Class Activation Map (CAM) visualization. Therefore, our proposed model combines image segmentation models and classifiers to crop out only the lung region of a chest X-ray’s class activation map to provide a visualization that improves the explainability and is able to generate classification results simultaneously which builds trust for AI-led diagnosis systems. The proposed U-Net model achieves 97.61% accuracy and a dice coefficient of 0.97 on testing data from the COVID-QU-Ex Dataset which includes both diseased and healthy lungs.

Keywords: multi-output network model, U-net, class activation map, image classification, medical imaging analysis

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Authors: Yun-Tao Zhang, Jong-Yeop Bae, Whoi-Yul Kim

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Background modeling and subtraction in video analysis has been widely proved to be an effective method for moving objects detection in many computer vision applications. Over the past years, a large number of approaches have been developed to tackle different types of challenges in this field. However, the dynamic background and illumination variations are two of the most frequently occurring issues in the practical situation. This paper presents a new two-layer model based on codebook algorithm incorporated with local binary pattern (LBP) texture measure, targeted for handling dynamic background and illumination variation problems. More specifically, the first layer is designed by block-based codebook combining with LBP histogram and mean values of RGB color channels. Because of the invariance of the LBP features with respect to monotonic gray-scale changes, this layer can produce block-wise detection results with considerable tolerance of illumination variations. The pixel-based codebook is employed to reinforce the precision from the outputs of the first layer which is to eliminate false positives further. As a result, the proposed approach can greatly promote the accuracy under the circumstances of dynamic background and illumination changes. Experimental results on several popular background subtraction datasets demonstrate a very competitive performance compared to previous models.

Keywords: background subtraction, codebook model, local binary pattern, dynamic background, illumination change

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Authors: N. R. N. Mendis, S. N. Silva

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Introduction: Patient satisfaction of services provided by primary care health services depends on many factors. One key factor in this depends on is the nursing services received in primary care. Since majority of the primary care in Sri Lanka is provided by the private sector, it is important to assess patient satisfaction on this. Objective: To assess the satisfaction among the public on nurses working in dispensaries in Sri Lanka. Methods: A descriptive study was done on 200 individual selected using convenient sampling among dispensaries in Gampaha district, Sri Lanka. Results: 59.3% of the sample had long term illnesses or disabilities and all of them preferred speaking to a nurse. 70.9% of the sample used to make appointments with nurses while 57.8% out of them were comfortable in discussing their health concerns. 98.9 % agreed that they get individual attention by the nurses. Majority of the sample that is 34.2% spends around 20 minutes with the nurse without even making any pay. Significantly, the whole sample believes that the nurses are professional and admits that the care given is of high quality. All 100% of the sample said that the nurses could understand their concerns while 93.5% admitted that it was very useful in their recovery. Conclusions: Majority of the public were very much satisfied with the nurses and their practice at the dispensaries.

Keywords: health education, nurses practices, patient satisfaction, primary care

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Authors: Nancy Daly

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Migrant youth who have experienced traumatic events in their home countries or in their passage to the United States may require interventions or formal services to support varying levels and types of needs. The manner in which such youth are engaged and evaluated, as well as the framework of evaluation, can impact their educational services and placement. Evidenced-based trauma-informed practices that engage and support migrant youth serve as an important bridge to stabilization; however, ensuring long-term growth may require a range of integrated services, including special education and mental health services. Special education evaluations which consider the eligibility of Emotional Disturbance for migrant youth must carefully weigh issues of mental health needs against the exclusionary criteria of lack of access to education, limited language skills, as well as other environmental factors. Case studies of recently arrived migrant youth reveal both commonalities and differences in types and levels of need which underscores the importance of adept evaluation and case management to ensure the provision of services that support growth and resiliency.

Keywords: migrant youth, trauma-informed care, mental health services, special education

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Authors: Jafar Khodagholizadeh

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In this talk, we study the tensor mode equation of perturbation in the presence of nonzero $-\Lambda$ as dark energy, whose dynamic nature depends on the Hubble parameter $ H$ and/or its time derivative. Dark energy, according to the total vacuum contribution, has little effect during the radiation-dominated era, but it reduces the squared amplitude of gravitational waves (GWs) up to $60\%$ for the wavelengths that enter the horizon during the matter-dominated era. Moreover, the observations bound on dark energy models, such as running vacuum model (RVM), generalized running vacuum model (GRVM), and generalized running vacuum subcase (GRVS), are effective in reducing the GWs’ amplitude. Although this effect is less for the wavelengths that enter the horizon at later times, this reduction is stable and permanent.

Keywords: gravitational waves, dark energy, GW's amplitude, all stage universe

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Authors: Femy M. Makkar, S. Chandrakaran, N. Sankar

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The concept of reinforced earth has been used in the field of geotechnical engineering since 1960s, for many applications such as, construction of road and rail embankments, pavements, retaining walls, shallow foundations, soft ground improvement and so on. Conventionally, planar geosynthetic materials such as geotextiles and geogrids were used as the reinforcing elements. Recently, the use of three dimensional reinforcements becomes one of the emerging trends in this field. So, in the present investigation, three dimensional geogrid is proposed as a reinforcing material. Laboratory scaled plate load tests are conducted on a model square footing resting on 3D geogrid reinforced sand bed. The performance of 3D geogrids in triangular and square pattern was compared with conventional geogrids and the improvement in bearing capacity and reduction in settlement and heave are evaluated. When single layer of reinforcement was placed at an optimum depth of 0.25B from the bottom of the footing, the bearing capacity of conventional geogrid reinforced soil improved by 1.85 times compared to unreinforced soil, where as 3D geogrid reinforced soil with triangular pattern and square pattern shows 2.69 and 3.05 times improvement respectively compared to unreinforced soil. Also, 3D geogrids performs better than conventional geogrids in reducing the settlement and heave of sand bed around the model footing.

Keywords: 3D reinforcing elements, bearing capacity, heavy, settlement

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Authors: A. El-S. Makled, M. K. Al-Tamimi

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A mathematical model to predict the performance parameters (thrusts, chamber pressures, fuel mass flow rates, mixture ratios, and regression rates during firing time) of hybrid rocket motor (HRM) is evaluated. The internal ballistic (IB) hybrid combustion model assumes that the solid fuel surface regression rate is controlled only by heat transfer (convective and radiative) from flame zone to solid fuel burning surface. A laboratory HRM is designed, manufactured, and tested for low thrust profile space missions (10-15 N) and for validating the mathematical model (computer program). The polymer material and gaseous oxidizer which are selected for this experimental work are polymethyle-methacrylate (PMMA) and polyethylene (PE) as solid fuel grain and gaseous oxygen (GO₂) as oxidizer. The variation of various operational parameters with time is determined systematically and experimentally in firing of up to 20 seconds, and an average combustion efficiency of 95% of theory is achieved, which was the goal of these experiments. The comparison between recording fire data and predicting analytical parameters shows good agreement with the error that does not exceed 4.5% during all firing time. The current mathematical (computer) code can be used as a powerful tool for HRM analytical design parameters.

Keywords: hybrid combustion, internal ballistics, hybrid rocket motor, performance parameters

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Authors: Nancy N. Sharmila, Aparna Mishra

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Hemiparesis affects almost 80% of stroke patients each year. It is marked by paralysis or weakness on one half of the body. Our model provides both assistance and physical therapy for hemiparesis patients for swift recovery. In order to accomplish our goal a force is provided that pulls the forearm up (as in flexing the arm), and pushes the forearm down (as in extending the arm), which will also assist the user during ADL (Activities of Daily Living). The model consists of a mechanical component which is placed around the patient’s bicep and an EMG control circuit to assist patients in daily activities, which makes it affordable and easy to use. In order to enhance the neuromuscular system’s effectiveness in synchronize the movement, proprioceptive neuromuscular facilitation (PNF) concept is used. The EMG signals are acquired from the unaffected arm as an input to drive the orthosis. This way the patient is invigorated to use the orthosis for regular exercise.

Keywords: EMG, hemiparesis, orthosis, rehabilitation

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Authors: Leorisyl D. Siarot

Abstract:

It is conventional to see and hear Filipinos, in general, speak two or more languages. This phenomenon brings us to a closer look on how our minds process the input and produce an output with a specific chosen language. This study aimed to generate a theoretical model which explained the interaction of the first and the second languages in the human mind. After a careful analysis of the gathered data, a theoretical prototype called Language Activation Model was generated. For every string, there are three specialized banks: lexico-semantics, morphono-syntax, and pragmatics. These banks are interrelated to other banks of other language strings. As the bilingual learns more languages, a new string is replicated and is filled up with the information of the new language learned. The principles of the first and second languages' interaction are drawn; these are expressed in laws, namely: law of dominance, law of availability, law of usuality and law of preference. Furthermore, difficulties encountered in the learning of second languages were also determined.

Keywords: bilingualism, psycholinguistics, second language learning, languages

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Authors: Celine Delacroix

Abstract:

Analyses of global emission scenarios demonstrate that slowing population growth could lead to substantial emissions reductions and play an important role to avoid dangerous climate change. For this reason, the advancement of individual reproductive rights might represent a valid climate change mitigation and adaptation option. With this focus, we reflected on population ethics and the ethical dilemmas associated with environmental degradation and climate change. We conducted a mixed-methods qualitative data study consisting of an online survey followed by in-depth interviews with stakeholders of the reproductive health and rights and environmental sustainability movements to capture the ways in which the linkages between family planning, population growth, and environmental sustainability are perceived by these actors. We found that the multi-layered marginalization of this issue resulted in two processes, the polarization of opinions and its eschewal from the public fora through population reductionism. Our results indicate that stakeholders of the reproductive rights and environmental sustainability movements find that population size and family planning influence environmental sustainability and overwhelmingly find that the reproductive health and rights ideological framework should be integrated in a wider sustainability frame reflecting environmental considerations. This position, whilst majoritarily shared by all participants, was more likely to be adopted by stakeholders of the environmental sustainability sector than those from the reproductive health and rights sector. We conclude that these processes, taken in the context of a context of a climate emergency, threaten to weaken the reproductive health and rights movement.

Keywords: environmental sustainability, family planning, population growth, population ethics, reproductive rights

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Authors: Kazuki Kamada, Haruka Yamashita

Abstract:

In Japan, taxi is one of the popular transportations and taxi industry is one of the big businesses. However, in recent years, there has been a difficult problem of reducing the number of taxi drivers. In the taxi business, mainly three passenger catching methods are applied. One style is "cruising" that drivers catches passengers while driving on a road. Second is "waiting" that waits passengers near by the places with many requirements for taxies such as entrances of hospitals, train stations. The third one is "dispatching" that is allocated based on the contact from the taxi company. Above all, the cruising taxi drivers need the experience and intuition for finding passengers, and it is difficult to decide "the destination for cruising". The strong recommendation system for the cruising taxies supports the new drivers to find passengers, and it can be the solution for the decreasing the number of drivers in the taxi industry. In this research, we propose a method of recommending a destination for cruising taxi drivers. On the other hand, as a machine learning technique, the embedding models that embed the high dimensional data to a low dimensional space is widely used for the data analysis, in order to represent the relationship of the meaning between the data clearly. Taxi drivers have their favorite courses based on their experiences, and the courses are different for each driver. We assume that the course of cruising taxies has meaning such as the course for finding business man passengers (go around the business area of the city of go to main stations) and course for finding traveler passengers (go around the sightseeing places or big hotels), and extract the meaning of their destinations. We analyze the cruising history data of taxis based on the embedding model and propose the recommendation system for passengers. Finally, we demonstrate the recommendation of destinations for cruising taxi drivers based on the real-world data analysis using proposing method.

Keywords: taxi industry, decision making, recommendation system, embedding model

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Authors: M.Rüştü Karaman, İsmail İşeri, Kadir Saltalı, A.Reşit Brohi, Ayhan Horuz, Mümin Dizman

Abstract:

Considerable relations has recently been given to the environmental hazardous caused by agricultural chemicals such as excess fertilizers. In this study, a neural network approach was investigated in the prediction of potential nitrate pollution across different land-use patterns by using a feedforward multilayered computer model of artificial neural network (ANN) with proper training. Periodical concentrations of some anions, especially nitrate (NO3-), and cations were also detected in drainage waters collected from the drain pipes placed in irrigated tomato field, unirrigated wheat field, fallow and pasture lands. The soil samples were collected from the irrigated tomato field and unirrigated wheat field on a grid system with 20 m x 20 m intervals. Site specific nitrate concentrations in the soil samples were measured for ANN based simulation of nitrate leaching potential from the land profiles. In the application of ANN model, a multi layered feedforward was evaluated, and data sets regarding with training, validation and testing containing the measured soil nitrate values were estimated based on spatial variability. As a result of the testing values, while the optimal structures of 2-15-1 was obtained (R2= 0.96, P < 0.01) for unirrigated field, the optimal structures of 2-10-1 was obtained (R2= 0.96, P < 0.01) for irrigated field. The results showed that the ANN model could be successfully used in prediction of the potential leaching levels of nitrate, based on different land use patterns. However, for the most suitable results, the model should be calibrated by training according to different NN structures depending on site specific soil parameters and varied agricultural managements.

Keywords: artificial intelligence, ANN, drainage water, nitrate pollution

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Authors: Newton Muhury, Armando A. Apan, Tek N. Marasani, Gebiaw T. Ayele

Abstract:

The changing climate has degraded freshwater availability in Australia that influencing vegetation growth to a great extent. This study assessed the vegetation responses to groundwater using Terra’s moderate resolution imaging spectroradiometer (MODIS), Normalised Difference Vegetation Index (NDVI), and soil water content (SWC). A hydrological model, SWAT, has been set up in a southeast Australian river catchment for groundwater analysis. The model was calibrated and validated against monthly streamflow from 2001 to 2006 and 2007 to 2010, respectively. The SWAT simulated soil water content for 43 sub-basins and monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) were applied in the machine learning tool, Waikato Environment for Knowledge Analysis (WEKA), using two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The assessment shows that different types of vegetation response and soil water content vary in the dry and wet seasons. The WEKA model generated high positive relationships (r = 0.76, 0.73, and 0.81) between NDVI values of all vegetation in the sub-basins against soil water content (SWC), the groundwater flow (GW), and the combination of these two variables, respectively, during the dry season. However, these responses were reduced by 36.8% (r = 0.48) and 13.6% (r = 0.63) against GW and SWC, respectively, in the wet season. Although the rainfall pattern is highly variable in the study area, the summer rainfall is very effective for the growth of the grass vegetation type. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

Procedia PDF Downloads 101