Search results for: healthcare data security

Authors: Chih Hsing Lin, Wen-Ching Chen, Ssu-Ying Chen, Chih-Chyau Yang, Chien-Ming Wu, Chun-Ming Huang

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Critical structures such as buildings, bridges and dams require periodic inspections to ensure safe operation. The reliable inspection of structures can be achieved by combing temperature sensor and accelerometers. In this work, we propose a building structure health monitoring device (BSHMD) with using three 1-axis accelerometers, gateway, analog to digital converter (ADC), and data logger to monitoring the building structure. The proposed BSHMD achieves the features of low cost by using three 1-axis accelerometers with the data synchronization problem being solved, and easily installation and removal. Furthermore, we develop a packet acquisition program to receive the sensed data and then classify it based on time and date. Compared with 3-axis accelerometer, our proposed 1-axis accelerometers based device achieves 64.3% cost saving. Compared with previous structural monitoring device, the BSHMD achieves 89% area saving. Therefore, with using the proposed device, the realtime diagnosis system for building damage monitoring can be conducted effectively.

Keywords: building structure health monitoring, cost effective, 1-axis accelerometers, real-time diagnosis

Procedia PDF Downloads 360

Authors: Mukondi Nethavhakone

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The high prevalence of violence against women is a global public health problem. Our societies have become dangerous places for women. Women during their child-bearing ages are at a higher risk of experiencing emotional, physical, and sexual violence. What makes it more concerning is that these violent acts are perpetrated by family members or partners, or ex-partners. Intimate Partner Violence (IPV) is associated with long-lasting physical, reproductive, sexual, mental, and maternal health implications. Expectedly women’s mental health would dimmish as a result of experiencing IPV. The burden of violence against women is seen to be heavier in low- and middle-income countries (LMICs) compared to the rest of the world. Countries have committed to eliminating all forms of violence against women through the sustainable development goal, aiming to see changes by the year 2030. As such, various countries have implemented psychosocial interventions of different levels of impact. However, little is known, especially in low- and middle-income countries, with regard to the potential of psychosocial interventions for IPV to improve the mental health outcomes for the survivors and/or victims of IPV. Analysing the risk for IPV through a social-ecological theoretical approach, low- and middle-income countries still readdressing gender inequality which is the cause of intimate partner violence. That is why it is taking time for these countries to shift psychosocial interventions to focus more on the improvement of the mental health of the survivors. It is, therefore, against this backdrop that the researcher intends to undertake a scoping review to understand the nature and characteristics of psychosocial interventions that have been implemented in low- and middle-income countries. With the findings from the scoping review, the researcher aims to develop a conceptual framework that may be a useful resource for healthcare practitioners and researchers in low- and middle-income countries. As this area of research has not been thoroughly reviewed, the results from this scoping will determine whether a systematic review will be justifiable. Additionally, the researcher will identify gaps and opportunities for future research in this area.

Keywords: mental health improvement, psychosocial interventions, intimate partner violence, LMICs

Procedia PDF Downloads 125

Authors: Ladda Leungratanamart, Seree Chadcham

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Fluid intelligence declines along with age, but it can be developed. For this reason, increasing fluid intelligence in young adults can be possible. This study examined the effects of a two-month treadmill exercise program on fluid intelligence. The researcher designed a treadmill exercise program to promote cardiorespiratory fitness. Thirty-eight healthy voluntary students from the Boromarajonani College of Nursing, Chon Buri were assigned randomly to an exercise group (n=18) and a control group (n=20). The experiment consisted of three sessions: The baseline session consisted of measuring the VO₂max, electroencephalogram and behavioral response during performed the Raven Progressive Matrices (RPM) test, a measure of fluid intelligence. For the exercise session, an experimental group exercises using treadmill training at 60 % to 80 % maximum heart rate for 30 mins, three times per week, whereas the control group did not exercise. For the following two sessions, each participant was measured the same as baseline testing. The data were analyzed using the t-test to examine whether there is significant difference between the means of the two groups. The results showed that the mean VO₂ max in the experimental group were significantly more than the control group (p<.05), suggesting a two-month treadmill exercise program can improve fluid intelligence. When comparing the behavioral data, it was found that experimental group performed RPM test more accurately and faster than the control group. Neuroelectric data indicated a significant increase in percentages of alpha band ERD (%ERD) at P3 and Pz compared to the pre-exercise condition and the control group. These data suggest that a two-month treadmill exercise program can contribute to the development of cardiorespiratory fitness which influences an increase fluid intelligence. Exercise involved in cortical activation in difference brain areas.

Keywords: treadmill exercise, fluid intelligence, raven progressive matrices test, alpha band

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Authors: Ya-Li Tsai

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Nitrogen is a vital element crucial for crop growth, significantly influencing crop yield. In rice cultivation, farmers often apply substantial nitrogen fertilizer to maximize yields. However, excessive nitrogen application increases the risk of lodging and pest infestation, leading to yield losses. Additionally, conventional flooded irrigation methods consume significant water resources, necessitating precise agricultural and intelligent water management systems. In this study, it leveraged physiological data and field images captured by unmanned aerial vehicles, considering fertilizer treatment and irrigation as key factors. Statistical models incorporating rice physiological data, yield, and vegetation indices from image data were developed. Missing physiological data were addressed using multiple imputation and regression methods, and regression models were established using principal component analysis and stepwise regression. Target nitrogen accumulation at key growth stages was identified to optimize fertilizer application, with the difference between actual and target nitrogen accumulation guiding recommendations for ear dressing dosage. Field experiments conducted in 2022 validated the recommended ear dressing dosage, demonstrating no significant difference in final yield compared to traditional fertilizer levels under alternate wetting and drying irrigation. These findings highlight the efficacy of applying recommended dosages based on fertilizer decision models, offering the potential for reduced fertilizer use while maintaining yield in rice cultivation.

Keywords: intelligent fertilizer management, nitrogen top and ear dressing fertilizer, rice, yield optimization

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Authors: Oli Sophie Meredith, Jacquelyn Osborne, Sarah Verdon, Jane Frawley

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PROJECT OVERVIEW AND BACKGROUND: Over one million Australians are affected by ADHD at an economic and social cost of over $20 billion per annum. Despite health outcomes being significantly worse compared with men, women have historically been overlooked in ADHD diagnosis and treatment. While research suggests physical activity and other non-prescription options can help with ADHD symptoms, the frontline response to ADHD remains expensive stimulant medications that can have adverse side effects. By interviewing women with ADHD, this research will examine women’s self-directed approaches to managing symptoms, including alternatives to prescription medications. It will investigate barriers and affordances to potentially helpful approaches and identify any concerning strategies pursued in lieu of diagnosis. SIGNIFICANCE AND INNOVATION: Despite the economic and societal impact of ADHD on women, research investigating how women manage their symptoms is scant. This project is significant because although women’s ADHD symptoms are markedly different to those of men, mainstream treatment has been based on the experiences of men. Further, it is thought that in developing nuanced coping strategies, women may have masked their symptoms. Thus, this project will highlight strategies which women deem effective in ‘thriving’ rather than just ‘hiding’. By investigating the health service use, self-care and physical activity of women with ADHD, this research aligns with a priority research areas as identified by the November 2023 senate ADHD inquiry report. APPROACH AND METHODS: Semi-structured interviews will be conducted with up to 20 women with ADHD. Interviews will be conducted in person and online to capture experience across rural and metropolitan Australia. Participants will be recruited in partnership with the peak representative body, ADHD Australia. The research will use an intersectional framework, and data will be analysed thematically. This project is led by an interdisciplinary and cross-institutional team of women with ADHD. Reflexive interviewing skills will be employed to help interviewees feel more comfortable disclosing their experiences, especially where they share common ground ENGAGEMENT, IMPACT AND BENEFIT: This research will benefit women with ADHD by increasing knowledge of strategies and alternative treatments to prescription medications, reducing the social and economic burden of ADHD on Australia and on individuals. It will also benefit women by identifying risks involved with some self-directed approaches in lieu of medical advice. The project has an accessible impact plan to directly benefit end-users, which includes the development of a podcast and a PDF resource translating findings. The resources will reach a wide audience through ADHD Australia’s extensive national networks. We will collaborate with Charles Sturt’s Accessibility and Inclusion Division of Safety, Security and Well-being to create a targeted resource for students with ADHD.

Keywords: ADHD, women's health, self-directed strategies, health service use, physical activity, public health

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Authors: Arditya Nugraha, Herry Gunawan, Agung P. Widodo

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The various possible strategies to find hydrocarbon are explored within a wide ranging of efforts. It started to identify petroleum concept in the basin. The main objectives of this paper are to integrate and develop information, knowledge, and evaluation from Indonesia’s sedimentary basins system in terms of their suitability for exploration activity and estimate the hydrocarbon potential available. The system which compiled data information and knowledge and comprised exploration and production data of all basins in Indonesia called as Basin Professor which stands for Basin Professional and Processor. Basin Professor is a website application using Geography Information System which consists of all information about basin montage, basin summary, petroleum system, stratigraphy, development play, risk factor, exploration history, working area, regional cross section, well correlation, prospect & lead inventory and infrastructure spatial. From 82 identified sedimentary basins, North Sumatra, Central Sumatra, South Sumatera, East Java, Kutai, and Tarakan basins are respectively positioned of the Indonesia’ s mature basin and the most productive basin. The Eastern of Indonesia also have many hydrocarbon potential and discovered several fields in Papua and East Abadi. Basin Professor compiled the well data in all of the basin in Indonesia from mature basin to frontier basin. Well known geological data, subsurface mapping, prospect and lead, resources and established infrastructures are the main factors make these basins have higher suitability beside another potential basin. The hydrocarbon potential resulted from this paper based on the degree of geological data, petroleum, and economic evaluation. Basin Professor has provided by a calculator tool in lead and prospect for estimate the hydrocarbon reserves, recoverable in place and geological risk. Furthermore, the calculator also defines the preliminary economic evaluation such as investment, POT IRR and infrastructures in each basin. From this Basin Professor, petroleum companies are able to estimate that Indonesia has a huge potential of hydrocarbon oil and gas reservoirs and still interesting for hydrocarbon exploration and production activity.

Keywords: basin summary, petroleum system, resources, economic evaluation

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Authors: My Linh Hoang, Van Dung Hoang

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Environmental, Social, and Governance (ESG) factors have become a focus for companies globally, as businesses are now focusing on long-term sustainable goals rather than only operating for the goals of profit maximization. According to recent research, in several countries, companies have shown positive results in their financial performance by improving their ESG performance. The construction industry is one of the most crucial components of social and economic development; as a result, considerations for ESG factors are becoming more and more essential for companies in this sector. In Vietnam, the construction industry has been growing rapidly in recent years; however, it has yet to be discussed and studied extensively in Vietnam how ESG factors create impacts on corporate financial performance in general and construction corporations’ financial performance in particular. This research aims to examine the relationship between ESG factors and financial indicators in construction companies from 2011 to 2021 through panel data analysis of 75 listed construction companies in Vietnam and to provide insights into how these companies can better integrate ESG considerations into their operations to enhance their financial performance. The data was analyzed through 3 main methods: descriptive statistics, correlation coefficient analysis applied to all dependent, explanatory and control variables, and panel data analysis method. In panel data analysis, the study uses the fixed effects model (FEM) and random effects model (REM). The Hausman test will be used to select which model is suitable to be used. The findings indicate that maintaining a strong commitment to ESG principles can have a positive impact on financial performance. Finally, FGLS estimation will be performed when the problem of autocorrelation and variable variance appears in the model. This is significant for all parties involved, including investors, company managers, decision-makers, and industry regulators.

Keywords: ESG, financial performance, construction company, Vietnam

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Authors: Wenwen Liu, Robert Burton, Simon McKeown

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Climate change is seriously threatening human security and development, leading to global warming and economic, political, and social chaos. Many artists have created visual responses that challenge perceptions on climate change, actively guiding people to think about the climate issues and potential crises after urban industrialization and explore positive solutions. This project is an interdisciplinary and intertextual study where art practice is informed by culture, philosophy, psychology, ecology, and science. By correlating theory and artistic practice, it studies how art practice creates a new way of understanding climate issues and uses art as a way of exploring speculative futures. In the context of practical-based research, arts-based practice as research and creative practice as interdisciplinary research are applied alternately to seek the original solution and new knowledge. Through creative art practice, this project has established new visual ways of looking at climate change and has developed it into a new model to generate more possibilities, an alternative social imagination. It not only encourages people to think and find a sustainable speculative future conducive to all species but also proves that people have the ability to realize positive futures.

Keywords: climate change, creative practice as interdisciplinary research, arts-based practice as research, creative art practice, speculative future

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Authors: Monisha Pattanaik

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In scenarios where users have to work with large amounts of hierarchical data structures combined with visualizations (For example, Construction 3d Models, Manufacturing equipment's models, Gantt charts, Building Plans), the data structures have a high density in terms of consisting multiple parent nodes up to 50 levels and their siblings to descendants, therefore convey an immediate feeling of complexity. With customers moving to consumer-grade enterprise software, it is crucial to make sophisticated features made available to touch devices or smaller screen sizes. This paper evaluates the UI component that allows users to scroll through all deep density levels using a slider overlay on top of the hierarchy table, performing several actions to focus on one set of objects at any point in time. This overlay component also solves the problem of excessive horizontal scrolling of the entire table on a fixed pane for a hierarchical table. This component can be customized to navigate through parents, only siblings, or a specific component of the hierarchy only. The evaluation of the UI component was done by End Users of application and Human-Computer Interaction (HCI) experts to test the UI component's usability with statistical results and recommendations to handle complex hierarchical data visualizations.

Keywords: building information modeling, digital twin, navigation, UI component, user interface, usability, visualization

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Authors: V. Jafari, M. Jafari

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When long-term changes in normal weather patterns happen in a certain area, it generally could be identified as climate change. Concentration of principal's greenhouse gases such as carbon dioxide, nitrous oxide, methane, ozone, and water vapor will cause climate change and perhaps climate variability. Main climate factors are temperature, precipitation, air pressure, and humidity. Extreme events may be the result of the changing of carbon dioxide concentration levels in the atmosphere which cause a change in temperature. Extreme events in some ways will affect the productivity of crop and dairy livestock. In this research, the correlation of milk production and temperature as the main climate factor in ChaharMahal and Bakhtiari province in Iran has been considered. The methodology employed for this study consists, collect reports and published national and provincial data, available recorded data on climate factors and analyzing collected data using statistical software. Milk production in ChaharMahal and Bakhtiari province is in the same pattern as national milk production in Iran. According to the current study results, there is a significant negative correlation between milk production in ChaharMahal and Bakhtiari provinces and temperature as the main climate change factor.

Keywords: Chaharmahal and Bakhtiari, climate change, impacts, Iran, milk production

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Authors: Adrian Ionita, Ana-Maria Ghimes

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The lack of features, design and the lack of promoting an integrated booking application are some of the reasons why most online travel platforms only offer automation of old booking processes, being limited to the integration of a smaller number of services without addressing the user experience. This paper represents a practical study on how to improve travel applications creating user-profiles through data-mining based on neural networks and genetic algorithms. Choices made by users and their ‘friends’ in the ‘social’ network context can be considered input data for a recommendation engine. The purpose of using these algorithms and this design is to improve user experience and to deliver more features to the users. The paper aims to highlight a broader range of improvements that could be applied to travel applications in terms of design and service integration, while the main scientific approach remains the technical implementation of the neural network solution. The motivation of the technologies used is also related to the initiative of some online booking providers that have made the fact that they use some ‘neural network’ related designs public. These companies use similar Big-Data technologies to provide recommendations for hotels, restaurants, and cinemas with a neural network based recommendation engine for building a user ‘DNA profile’. This implementation of the ‘profile’ a collection of neural networks trained from previous user choices, can improve the usability and design of any type of application.

Keywords: artificial intelligence, big data, cloud computing, DNA profile, genetic algorithms, machine learning, neural networks, optimization, recommendation system, user profiling

Procedia PDF Downloads 158

Authors: Mohammad H. Yarmohammadian, Reza Safdari, Mahmoud Keyvanara, Nahid Tavakoli

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One of the greatest challenges in disaster and emergencies is patient tracking. The concept of tracking has different denotations. One of the meanings refers to tracking patients’ physical locations and the other meaning refers to tracking patients ‘medical needs during emergency services. The main goal of patient tracking is to provide patient safety during disaster and emergencies and manage the flow of patient and information in different locations. In most of cases, there are not sufficient and accurate data regarding the number of injuries, medical conditions and their accommodation and transference. The objective of the present study is to survey on patient tracking issue in natural disaster and emergencies. Methods: This was a narrative study in which the population was E-Journals and the electronic database such as PubMed, Proquest, Science direct, Elsevier, etc. Data was gathered by Extraction Form. All data were analyzed via content analysis. Results: In many countries there is no appropriate and rapid method for tracking patients and transferring victims after the occurrence of incidents. The absence of reliable data of patients’ transference and accommodation, even in the initial hours and days after the occurrence of disasters, and coordination for appropriate resource allocation, have faced challenges for evaluating needs and services challenges. Currently, most of emergency services are based on paper systems, while these systems do not act appropriately in great disasters and incidents and this issue causes information loss. Conclusion: Patient tracking system should update the location of patients or evacuees and information related to their states. Patients’ information should be accessible for authorized users to continue their treatment, accommodation and transference. Also it should include timely information of patients’ location as soon as they arrive somewhere and leave therein such a way that health care professionals can be able to provide patients’ proper medical treatment.

Keywords: patient tracking, challenges, disaster, emergency

Procedia PDF Downloads 299

Authors: Neda Zamani

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The present study aimed to investigate the effectiveness of training courses and their limitations using the CIPP model. The investigations were done on Isfahan Refinery as a case study. From a purpose point of view, the present paper is included among applied research and from a data gathering point of view, it is included among descriptive research of the field type survey. The population of the study included participants in training courses, their supervisors and experts of the training department. Probability-proportional-to-size (PPS) was used as the sampling method. The sample size for participants in training courses included 195 individuals, 30 supervisors and 11 individuals from the training experts’ group. To collect data, a questionnaire designed by the researcher and a semi-structured interview was used. The content validity of the data was confirmed by training management experts and the reliability was calculated through 0.92 Cronbach’s alpha. To analyze the data in descriptive statistics aspect (tables, frequency, frequency percentage and mean) were applied, and inferential statistics (Mann Whitney and Wilcoxon tests, Kruskal-Wallis test to determine the significance of the opinion of the groups) have been applied. Results of the study indicated that all groups, i.e., participants, supervisors and training experts, absolutely believe in the importance of training courses; however, participants in training courses regard content, teacher, atmosphere and facilities, training process, managing process and product as to be in a relatively appropriate level. The supervisors also regard output to be at a relatively appropriate level, but training experts regard content, teacher and managing processes as to be in an appropriate and higher than average level.

Keywords: training courses, limitations of training effectiveness, CIPP model, Isfahan oil refinery company

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Authors: Kumar Manoj, Ramesh Kumar, Kumari Arti, Kumar Prashant

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Routing protocols have a central role in any mobile ad hoc network (MANET). There are many routing protocols that exhibit different performance levels in different scenarios. In this paper we compare AODV, DSDV, DSR and ZRP routing protocol in mobile ad hoc networks to determine the best operational conditions for each protocol. We analyses these routing protocols by extensive simulations in OPNET simulator and show that how pause time and the number of nodes affect their performance. In this study, performance is measured in terms of control traffic received, control traffic sent, data traffic received, data traffic sent, throughput, retransmission attempts.

Keywords: MANET, AODV, DSDV, DSR, ZRP

Procedia PDF Downloads 673

Authors: Eid Nasr Saad Nasr

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Although human rights protection in the industrial sector has increased, human rights violations continue to occur. Although the government has passed human rights laws, labor laws, and an international treaty ratified by the United States, human rights crimes continue to occur and go undetected. The growing number of textile companies in Bekasi is also leading to an increase in human rights violations as the government has no obligation to protect them. The United States government and business leaders should respect, protect and defend the human rights of workers. The article discusses the human rights violations faced by garment factory workers in the context of the law, as well as ideas for improving the protection of workers' rights. The connection between development and human rights has long been the subject of academic debate. Therefore, to understand the dynamics between these two concepts, a number of principles have been adopted, ranging from the right to development to a human rights-based approach to development. Despite these attempts, the precise connection between development and human rights is not yet fully understood. However, the inherent interdependence between these two concepts and the idea that development efforts must respect human rights guarantees has gained momentum in recent years. It will then be examined whether the right to sustainable development is recognized.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security

Procedia PDF Downloads 52

Authors: Boumediene Hamzi, Turky N. AlOtaiby, Saleh AlShebeili, Arwa AlAnqary

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We introduce a data-driven method for seizure detection drawing on recent progress in Machine Learning. The method is based on embedding probability measures in a high (or infinite) dimensional reproducing kernel Hilbert space (RKHS) where the Maximum Mean Discrepancy (MMD) is computed. The MMD is metric between probability measures that are computed as the difference between the means of probability measures after being embedded in an RKHS. Working in RKHS provides a convenient, general functional-analytical framework for theoretical understanding of data. We apply this approach to the problem of seizure detection.

Keywords: kernel methods, maximum mean discrepancy, seizure detection, machine learning

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Authors: Kaushik Sathupadi, Sandesh Achar

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Human action recognition modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view football datasets. Our HMR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH multi-view football datasets, respectively.

Keywords: computer vision, human motion analysis, random forest, machine learning

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Authors: Fouzia Amireche-Ziar, Ilham Mokbel, Jacques Jose

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The vapour pressures of the three binary mixtures: 1, 2- dichloroethane + 1,3-dioxolane, + 1,4-dioxane or + tetrahydropyrane, are carried out at ten temperatures ranging from 273 to 353.15 K. An accurate static device was employed for these measurements. The VLE data were reduced using the Redlich-Kister equation by taking into consideration the vapour pressure non-ideality in terms of the second molar virial coefficient. The experimental data were compared to the results predicted with the DISQUAC and Dortmund UNIFAC group contribution models for the total pressures P and the excess molar Gibbs energies GE.

Keywords: disquac model, dortmund UNIFAC model, excess molar Gibbs energies GE, VLE

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Authors: Mathieu Bourdeau, Philippe Basset, Julien Waeytens, Elyes Nefzaoui

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As residential buildings account for a third of the overall energy consumption and greenhouse gas emissions in Europe, building energy modeling is an essential tool to reach energy efficiency goals. In the energy modeling process, calibration is a mandatory step to obtain accurate and reliable energy simulations. Nevertheless, the comparison between simulation results and the actual building energy behavior often highlights a significant performance gap. The literature discusses different origins of energy performance gaps, from building design to building operation. Then, building operation description in energy models, especially energy usages and users’ behavior, plays an important role in the reliability of simulations but is also the most accessible target for post-occupancy energy management and optimization. Therefore, the present study aims to discuss results on the calibration ofresidential building energy models using real operation data. Data are collected through a sensor network of more than 180 sensors and advanced energy meters deployed in three collective residential buildings undergoing major retrofit actions. The sensor network is implemented at building scale and in an eight-apartment sample. Data are collected for over one year and half and coverbuilding energy behavior – thermal and electricity, indoor environment, inhabitants’ comfort, occupancy, occupants behavior and energy uses, and local weather. Building energy simulations are performed using a physics-based building energy modeling software (Pleaides software), where the buildings’features are implemented according to the buildingsthermal regulation code compliance study and the retrofit project technical files. Sensitivity analyses are performed to highlight the most energy-driving building features regarding each end-use. These features are then compared with the collected post-occupancy data. Energy-driving features are progressively replaced with field data for a step-by-step calibration of the energy model. Results of this study provide an analysis of energy performance gap on an existing residential case study under deep retrofit actions. It highlights the impact of the different building features on the energy behavior and the performance gap in this context, such as temperature setpoints, indoor occupancy, the building envelopeproperties but also domestic hot water usage or heat gains from electric appliances. The benefits of inputting field data from an extensive instrumentation campaign instead of standardized scenarios are also described. Finally, the exhaustive instrumentation solution provides useful insights on the needs, advantages, and shortcomings of the implemented sensor network for its replicability on a larger scale and for different use cases.

Keywords: calibration, building energy modeling, performance gap, sensor network

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Authors: Zhidong Zhang

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This study established a mixed method model in assessing statistics learning with Bayesian network models. There are three variants in exploratory sequential designs. There are three linked steps in one of the designs: qualitative data collection and analysis, quantitative measure, instrument, intervention, and quantitative data collection analysis. The study used a scoring model of analysis of variance (ANOVA) as a content domain. The research study is to examine students’ learning in both semantic and performance aspects at fine grain level. The ANOVA score model, y = α+ βx1 + γx1+ ε, as a cognitive task to collect data during the student learning process. When the learning processes were decomposed into multiple steps in both semantic and performance aspects, a hierarchical Bayesian network was established. This is a theory-driven process. The hierarchical structure was gained based on qualitative cognitive analysis. The data from students’ ANOVA score model learning was used to give evidence to the hierarchical Bayesian network model from the evidential variables. Finally, the assessment results of students’ ANOVA score model learning were reported. Briefly, this was a mixed method research design applied to statistics learning assessment. The mixed methods designs expanded more possibilities for researchers to establish advanced quantitative models initially with a theory-driven qualitative mode.

Keywords: exploratory sequential design, ANOVA score model, Bayesian network model, mixed methods research design, cognitive analysis

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Authors: Xiaohua Zou, Yongxin Su

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The reasonable operation of heating, ventilation, and air conditioning (HVAC) is of great significance in improving the security, stability, and economy of power system operation. However, the uncertainty of the operating environment, thermal comfort varies by users and rapid decision-making pose challenges for HVAC demand response optimization. In this regard, this paper proposes a reinforcement learning-based method for HVAC demand response optimization considering few-shot personalized thermal comfort (PTC). First, an HVAC DR optimization framework based on few-shot PTC model and DRL is designed, in which the output of few-shot PTC model is regarded as the input of DRL. Then, a few-shot PTC model that distinguishes between awake and asleep states is established, which has excellent engineering usability. Next, based on soft actor criticism, an HVAC DR optimization algorithm considering the user’s PTC is designed to deal with uncertainty and make decisions rapidly. Experiment results show that the proposed method can efficiently obtain use’s PTC temperature, reduce energy cost while ensuring user’s PTC, and achieve rapid decision-making under uncertainty.

Keywords: HVAC, few-shot personalized thermal comfort, deep reinforcement learning, demand response

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Authors: Panwasn Mahalawalert

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The purposes of this research were analyzed differential item functioning and differential test functioning of SWUSAT aptitude test classification by sex variable. The data used in this research is the secondary data from Srinakharinwirot University Scholastic Aptitude Test 2013 (SWUSAT). SWUSAT test consists of four subjects. There are verbal ability test, number ability test, reasoning ability test and spatial ability test. The data analysis was analyzed in 2 steps. The first step was analyzing descriptive statistics. In the second step were analyzed differential item functioning (DIF) and differential test functioning (DTF) by using the DIFAS program. The research results were as follows: The results of DIF and DTF analysis for all 10 tests in year 2013. Gender was the characteristic that found DIF all 10 tests. The percentage of item number that found DIF is between 6.67% - 60%. There are 5 tests that most of items favors female group and 2 tests that most of items favors male group. There are 3 tests that the number of items favors female group equal favors male group. For Differential test functioning (DTF), there are 8 tests that have small level.

Keywords: aptitude test, differential item functioning, differential test functioning, educational measurement

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Authors: J. F. Reinoso-Gordo, F. J. Ariza-López, A. Mozas-Calvache, J. L. García-Balboa, S. Eddargani

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The DEMs quality may depend on several factors such as data source, capture method, processing type used to derive them, or the cell size of the DEM. The two most important capture methods to produce regional-sized DEMs are photogrammetry and LiDAR; DEMs covering entire countries have been obtained with these methods. The quality of these DEMs has traditionally been evaluated by the national cartographic agencies through punctual sampling that focused on its vertical component. For this type of evaluation there are standards such as NMAS and ASPRS Positional Accuracy Standards for Digital Geospatial Data. However, it seems more appropriate to carry out this evaluation by means of a method that takes into account the superficial nature of the DEM and, therefore, its sampling is superficial and not punctual. This work is part of the Research Project "Functional Quality of Digital Elevation Models in Engineering" where it is necessary to control the quality of a DEM whose data source is an experimental LiDAR flight with a density of 14 points per square meter to which we call Point Cloud Product (PCpro). In the present work it is described the capture data on the ground and the postprocessing tasks until getting the point cloud that will be used as reference (PCref) to evaluate the PCpro quality. Each PCref consists of a patch 50x50 m size coming from a registration of 4 different scan stations. The area studied was the Spanish region of Navarra that covers an area of 10,391 km2; 30 patches homogeneously distributed were necessary to sample the entire surface. The patches have been captured using a Leica BLK360 terrestrial laser scanner mounted on a pole that reached heights of up to 7 meters; the position of the scanner was inverted so that the characteristic shadow circle does not exist when the scanner is in direct position. To ensure that the accuracy of the PCref is greater than that of the PCpro, the georeferencing of the PCref has been carried out with real-time GNSS, and its accuracy positioning was better than 4 cm; this accuracy is much better than the altimetric mean square error estimated for the PCpro (<15 cm); The kind of DEM of interest is the corresponding to the bare earth, so that it was necessary to apply a filter to eliminate vegetation and auxiliary elements such as poles, tripods, etc. After the postprocessing tasks the PCref is ready to be compared with the PCpro using different techniques: cloud to cloud or after a resampling process DEM to DEM.

Keywords: data quality, DEM, LiDAR, terrestrial laser scanner, accuracy

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Authors: Yemisrach Mihertu Amsale

Abstract:

The purpose of this study was to compare burnout and coping strategies between HIV counselors in face to face and online counseling settings in Addis Ababa. The study was mixed approach design that was quantitative and qualitative. For the quantitative data the participants involved in this study included 64 face to face and 47 online HIV counselors in both counseling settings. In addition, 23 participants were involved to offer qualitative data from both counseling settings. For the purpose of gathering the quantitative data, the instruments, namely, demographic questionnaire, Maslach Burnout Inventory and the COPE questionnaire, were used to gather quantitative data. Qualitative data was also gathered in the FGD Guide and Interview Guide. Thus, this study revealed that HIV counselors in online counseling settings scored high on emotional exhaustion, depersonalization and low in personal accomplishment dimensions of burnout as compared to HIV counselors in face to face setting and the difference was statistically significant in emotional exhaustion and personal accomplishment, but there was no a significant difference on depersonalization dimension of burnout between the two groups. In addition, the present study revealed a statistically significant difference on problem focused coping strategy between the two groups and yet for on the emotion focused coping strategy the difference was not statistically significant. Statistically negative correlation was observed between some demographic variables such as age with emotional exhaustion and depersonalization dimensions of burnout; years of experiences and personal accomplishment dimension of burnout. A statistically positive correlation was also observed between average number of clients served per day and emotional exhaustion. Sex was having a statistically positive correlation with coping strategy. Lastly, a significant positive correlation was also observed in the emotional exhaustion dimension of the burnout and the emotional focused coping strategy. Generally, this study has shown that HIV counselors suffer from moderate to high level of burnout. Based on the findings, conclusions were made and recommendations were forwarded.

Keywords: counseling, burnout management, psychological, behavioral sciences

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Authors: Jamuna Loganath

Abstract:

Education is the key to the development of any individual’s personality. Today’s students will be tomorrow’s citizens of the global society. The education of the student is the edifice on which his/her future will be built. Schools therefore should provide an all-round development of students so as to foster a healthy society. The behaviors and the attitude of the students in school play an essential role for the success of the education process. Frequent reports of misbehaviors such as clowning, harassing classmates, verbal insults are becoming common in schools today. If this issue is left unattended, it may develop a negative attitude and increase the delinquent behavior. So, the need of the hour is to find a solution to this problem. To solve this issue, it is important to monitor the students’ behaviors in school and give necessary feedback and mentor them to develop a positive attitude and help them to become a successful grownup. Nevertheless, measuring students’ behavior and attitude is extremely challenging. None of the present technology has proven to be effective in this measurement process because actions, reactions, interactions, response of the students are rarely used in the course of the data due to complexity. The purpose of this proposal is to recommend an effective supervising system after carrying out a feasibility study by measuring the behavior of the Students. This can be achieved by equipping schools with CCTV cameras. These CCTV cameras installed in various schools of the world capture the facial expressions and interactions of the students inside and outside their classroom. The real time raw videos captured from the CCTV can be uploaded to the cloud with the help of a network. The video feeds get scooped into various nodes in the same rack or on the different racks in the same cluster in Hadoop HDFS. The video feeds are converted into small frames and analyzed using various Pattern recognition algorithms and MapReduce algorithm. Then, the video frames are compared with the bench marking database (good behavior). When misbehavior is detected, an alert message can be sent to the counseling department which helps them in mentoring the students. This will help in improving the effectiveness of the education process. As Video feeds come from multiple geographical areas (schools from different parts of the world), BIG DATA helps in real time analysis as it analyzes computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions. It also analyzes data that can’t be analyzed by traditional software applications such as RDBMS, OODBMS. It has also proven successful in handling human reactions with ease. Therefore, BIG DATA could certainly play a vital role in handling this issue. Thus, effectiveness of the education process can be enhanced with the help of video analytics using the latest BIG DATA technology.

Keywords: big data, cloud, CCTV, education process

Procedia PDF Downloads 237

Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

Procedia PDF Downloads 139

Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

Abstract:

Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

Procedia PDF Downloads 169

Authors: Zak Maas, Daniel Carson, Rachel McIntyre, Mark Omundsen, Teresa Holm

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Aim: After hemicolectomy a period of obligatory bowel dysfunction is expected, termed postoperative ileus (POI). Prolonged postoperative ileus (PPOI), typically four or more days, is associated with higher morbidity and extended inpatient stay. This leads to significant financial and resource-related burdens on healthcare systems. Several studies including a meta-analysis have compared rates of PPOI in left vs right hemicolectomy, which suggest that right-sided resections may be more likely to result in PPOI. Our study aims to further investigate whether significant differences in PPOI and obligatory POI exist between right versus extended right hemicolectomy. Methods: This is a retrospective review assessing rates of PPOI in patients who underwent right vs extended right hemicolectomy at Tauranga Hospital. Patients were divided and compared depending on approach (open versus laparoscopic) and acuity (acute versus elective). Exclusion criteria included synchronous major operations and patients preoperatively on parenteral nutrition. Primary outcome was PPOI as pre-defined in contemporary literature. Secondary outcomes were time to passage of flatus, passage of stool, toleration of oral diet and rate of complications. Results: There were 669 patients identified for analysis (507 laparoscopic vs 162 open; 194 acute vs 475 elective). Early analysis indicates rates of PPOI was significantly increased in patients undergoing extended right hemicolectomy. Factors including age, gender, ethnicity, preoperative haemaglobin, preoperative albumin and diagnosis of inflammatory bowel disease were examined by multivariate analysis to determine correlation with PPOI. Conclusion: PPOI is a common complication of hemicolectomy surgery. Higher rates of PPOI in extended right vs right hemicolectomy warrants further research into determining the cause. This study examines some other factors which may contribute to PPOI.

Keywords: hemicolectomy, colorectal, complications, postoperative ileus

Procedia PDF Downloads 82

Authors: Ismail Seçer, Kerime Meryem Dereli̇oğlu

Abstract:

This study is conducted to determine the effects of group counseling program on secondary school 9th grade students’ assertiveness skills. The study group was formed of 100 students who have received education in Erzurum Kültür Elementary School in 2015-2016 education years. RAE-Rathus Assertiveness Schedule developed by Voltan Acar was applied on this group to gather data. 40 students who got lower grades from the inventory were divided randomly into experimental and control groups. Each group is formed of 20 students. Group counseling program was carried out on the experimental group to improve the students’ assertiveness skills for 8 weeks. Single-way and two-way analysis of covariance (ANCOVA) were used in the analysis of the data. The data was analyzed by using the SPSS 19.00. The results of the study show that assertiveness skills of the students who participate in the group counseling program increased meaningfully compared to the control group and pre-experiment. Besides, it was determined that the change observed in the experimental group occurred separately from the age and socio-economic level variables, and it was determined with the monitoring test applied after four months that this affect was continued. According to this result, it can be said that the applied group counseling program is an effective means to improve the assertiveness skills of secondary school students.

Keywords: high school, assertiveness, assertiveness inventory, assertiveness education

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Authors: Jihad S. Daba, J. P. Dubois, Yvette Antar

Abstract:

With the exponential growth of cellular users, a new generation of cellular networks is needed to enhance the required peak data rates. The co-channel interference between neighboring base stations inhibits peak data rate increase. To overcome this interference, multi-cell cooperation known as coordinated multipoint transmission is proposed. Such a solution makes use of multiple-input-multiple-output (MIMO) systems under two different structures: Micro- and macro-diversity. In this paper, we study the capacity and bit error rate in cellular networks using MIMO technology. We analyse both micro- and macro-diversity schemes and develop a hybrid model that switches between macro- and micro-diversity in the case of hard handoff based on a cut-off range of signal-to-noise ratio values. We conclude that our hybrid switched micro-macro MIMO system outperforms classical MIMO systems at the cost of increased hardware and software complexity.

Keywords: cooperative multipoint transmission, ergodic capacity, hard handoff, macro-diversity, micro-diversity, multiple-input-multiple output systems, orthogonal frequency division multiplexing

Procedia PDF Downloads 305