Search results for: building performance rating tool

Authors: Zachary Blanks, Solomon Sonya

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Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

Procedia PDF Downloads 292

Authors: Kyoung-Jae Kim

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Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.

Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition

Procedia PDF Downloads 289

Authors: Youngji Yoo, Seung Hwan Park, Daewoong An, Sung-Shick Kim, Jun-Geol Baek

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The yield management system is very important to produce high-quality semiconductor chips in the semiconductor manufacturing process. In order to improve quality of semiconductors, various tests are conducted in the post fabrication (FAB) process. During the test process, large amount of data are collected and the data includes a lot of information about defect. In general, the defect on the wafer is the main causes of yield loss. Therefore, analyzing the defect data is necessary to improve performance of yield prediction. The wafer bin map (WBM) is one of the data collected in the test process and includes defect information such as the fail bit patterns. The fail bit has characteristics of spatial point patterns. Therefore, this paper proposes the feature extraction method using the spatial point pattern analysis. Actual data obtained from the semiconductor process is used for experiments and the experimental result shows that the proposed method is more accurately recognize the fail bit patterns.

Keywords: semiconductor, wafer bin map, feature extraction, spatial point patterns, contour map

Procedia PDF Downloads 384

Authors: Costrie Ganes Widayanti

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Learning Disabilities (LDs) are less understood by the Indonesia’s educational practitioners. As a result, students with LDs are at risk of being outcast from the learning process that requires participation, which potentially disconnects them academically and socially. Its objective is to raise the voice of students with LDs regarding their engagement in the classroom. This research is conducted in two urban regular public primary schools in Indonesia. The study uses an ethnographic case study research design, which explores the views and experiences of four (4) students with LDs. The data were collected using participant observations and interviews. The preliminary findings highlighted two areas: 1) the stigmatization about LDs; and 2) perceived membership. Having LDs was a barrier to fully engage in the academic and social life. Interestingly, they were more likely dependent on each other for support as limited assistance was offered by teachers and peers. Their peers did not take a keen interest in helping them when they found difficulties with the assignments. Furthermore, due to their low academic performance, they were not in favor of being nominated as a group member. In a situation that required them to do a group assignment, they were not expected to give a contribution, positioning themselves as incompatible. These findings indicated that such practices legitimate the hegemony of the superior over those who are powerless and left behind.

Keywords: engagement, experiences, learning disability, qualitative design

Procedia PDF Downloads 127

Authors: Andreas Aceranti, Riccardo Dossena, Marco Colorato, Simonetta Vernocchi

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By the term “limbic resonance,” we usually refer to a state of deep connection, both emotional and physiological, between people who, when in resonance, find their limbic systems in tune with one another. Limbic resonance is not only about sharing emotions but also physiological states. In fact, people in such resonance can influence each other’s heart rate, blood pressure, and breathing. Limbic resonance is fundamental for human beings to connect and create deep bonds among a certain group. It is fundamental for our social skills. A relationship between gifted and resonant subjects is perceived as feeling safe, living the relation like an isle of serenity where it is possible to recharge, to communicate without words, to understand each others without giving explanations, to strengthen the balance of each member of the group. Within the circle, self-esteem is consolidated and makes it stronger to face what is outside, others, and reality. The idea that gifted people who are together may be unfit for the world does not correspond to the truth. The circle made up of people with high cognitive potential characterized by a limbic resonance is, in general, experienced as a solid platform from which you can safely move away and where you can return to recover strength. We studied 8 adults (between 21 and 47 years old). All of them with IQ higher than 130. We monitored their brain waves frequency (alpha, beta, theta, gamma, delta) by means of biosensing tracker along with their physiological states (heart beat frequency, blood pressure, breathing frequency, pO2, pCO2) and some blood works only (5-HT, dopamine, catecholamines, cortisol). The subjects of the study were asked to adhere to a protocol involving bonding activities (such as team building activities), role plays, meditation sessions, and group therapy. All these activities were carried out together. We observed that after about 4 months of activities, their brain waves frequencies tended to tune quicker and quicker. After 9 months, the bond among them was so important that they could “sense” each other inner states and sometimes also guess each others’ thoughts. According to our findings, it may be hypothesized that large synchronized outbursts of cortex neurons produces not only brain waves but also electromagnetic fields that may be able to influence the cortical neurons’ activity of other people’s brain by inducing action potentials in large groups of neurons and this is reasonably conceivable to be able to transmit information such as different emotions and cognition cues to the other’s brain. We also believe that upcoming research should focus on clarifying the role of brain magnetic particles in brain-to-brain communication. We also believe that further investigations should be carried out on the presence and role of cryptochromes to evaluate their potential roles in direct brain-to-brain communication.

Keywords: limbic resonance, psychotherapy, brain waves, emotion regulation, giftedness

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Authors: Taisir Eldos, Aws Kanan, Waleed Nazih, Ahmad Khatatbih

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Chemical Reaction Optimization (CRO) is an optimization metaheuristic inspired by the nature of chemical reactions as a natural process of transforming the substances from unstable to stable states. Starting with some unstable molecules with excessive energy, a sequence of interactions takes the set to a state of minimum energy. Researchers reported successful application of the algorithm in solving some engineering problems, like the quadratic assignment problem, with superior performance when compared with other optimization algorithms. We adapted this optimization algorithm to the Printed Circuit Board Drilling Problem (PCBDP) towards reducing the drilling time and hence improving the PCB manufacturing throughput. Although the PCBDP can be viewed as instance of the popular Traveling Salesman Problem (TSP), it has some characteristics that would require special attention to the transactions that explore the solution landscape. Experimental test results using the standard CROToolBox are not promising for practically sized problems, while it could find optimal solutions for artificial problems and small benchmarks as a proof of concept.

Keywords: evolutionary algorithms, chemical reaction optimization, traveling salesman, board drilling

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Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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The present study deals with the selection of the most suitable quantitative structure-retention relationship (QSRR) models which should be used in prediction of the retention behavior of basic, neutral, acidic and phenolic pesticides which belong to different classes: fungicides, herbicides, metabolites, insecticides and plant growth regulators. Sum of ranking differences (SRD) approach can give a different point of view on selection of the most consistent QSRR model. SRD approach can be applied not only for ranking of the QSRR models, but also for detection of similarity or dissimilarity among them. Applying the SRD analysis, the most similar models can be found easily. In this study, selection of the best model was carried out on the basis of the reference ranking (“golden standard”) which was defined as the row average values of logarithm of retention time (logtr) defined by high performance liquid chromatography (HPLC). Also, SRD analysis based on experimental logtr values as reference ranking revealed similar grouping of the established QSRR models already obtained by hierarchical cluster analysis (HCA).

Keywords: chemometrics, chromatography, pesticides, sum of ranking differences

Procedia PDF Downloads 375

Authors: Chejarla Raghunathababu, E. Logashanmugam

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An antenna is an assortment of linked devices that function together to transmit and receive radio waves as a single antenna. Antennas occur in a variety of sizes and forms, but the microstrip patch antenna outperforms other types in terms of effectiveness and prediction. These antennas are easy to generate with discreet benefits. Nevertheless, the antenna's effectiveness will be affected because of the patch's shape above a thick dielectric substrate. As a result, a double-pole rectangular microstrip antenna with nanofillers was suggested in this study. By employing nano-composite substances (Fumed Silica and Aluminum Oxide), which are composites of graphene with nanofillers, the physical characteristics of the microstrip antenna, that is, the elevation of the microstrip antenna substrate and the width of the patch microstrip antenna have been improved in this research. The surface conductivity of graphene may be modified to function at specific frequencies. In order to prepare for future wireless communication technologies, a microstrip patch antenna operating at 93 GHz resonant frequency is constructed and investigated. The goal of this study was to reduce VSWR and increase gain. The simulation yielded results for the gain and VSWR, which were 8.26 dBi and 1.01, respectively.

Keywords: graphene, microstrip patch antenna, substrate material, wireless communication, nanocomposite material

Procedia PDF Downloads 111

Authors: Ly. Benbahouche

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Currently, several soft switching topologies have been studied to achieve high power switching efficiency, reduced cost, improved reliability and reduced parasites. It is well known that improvement in power electronics systems always depend on advanced in power devices. The IGBT has been successfully used in a variety of switching applications such as motor drives and appliance control because of its superior characteristics. The aim of this paper is focuses on simulation and explication of the internal dynamics of IGBTs behaviour under the most popular soft switching schemas that is Zero Current Switching (ZCS) environments. The main purpose of this paper is to point out some mechanisms relating to current tail during the turn-off and examination of the response at turn-off with variation of temperature, inductance L, snubber capacitors Cs, and bus voltage in order to achieve an improved understanding of internal carrier dynamics. It is shown that the snubber capacitor, the inductance and even the temperature controls the magnitude and extent of the tail current, hence the turn-off time (switching speed of the device). Moreover, it has also been demonstrated that the ZCS switching can be utilized efficiently to improve and reduce the power losses as well as the turn-off time. Furthermore, the turn-off loss in ZCS was found to depend on the time of switching of the device.

Keywords: PT-IGBT, ZCS, turn-off losses, dV/dt

Procedia PDF Downloads 317

Authors: D. Jagath Kumari, K. Srinivasa Rao

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Quality assurance of the structures subjected to high temperatures is now enforcing measure for the Structural Engineers. The existing relations between strength and nondestructive measurements have been established under normal conditions are not suitable to concretes that have been exposed to high temperatures. The scope of the work is to investigate the influence of high temperatures of short durations on the residual properties of reinforced HVFA concrete columns that affect the strength by non-destructive tests (NDT). Fly ash concrete is increasingly used in the design of normal strength, high strength and high performance concretes. In this paper, the authors revealed the influence of high temperatures on HVFA concrete columns. These columns are heated from 100oC to 800oC with increments of 100oC and allowed to cool to room temperature by two methods one is air cooling method and the other immediate water quenching method. All the specimens were tested identically, before heating and after heating for compressive strength and material integrity by rebound hammer and ultrasonic pulse velocity (UPV) meter respectively. HVFA concrete retained more residual strength by water quenching method than air-cooling method.

Keywords: HVFA concrete, NDT methods, residual strength, non-destructive tests

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Authors: Somboon Sarasit

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This research aims to develop a model small ceramic kiln using burner from a high-pressure household gas stove. The efficiency of the kiln and community technology transfer. The study of history shows that this area used to be a source of pottery on the old capital of Ayutthaya. There is evidence from pottery kilns unearthed many types of wood kiln since 2535 and was assumed that the production will end when the war with Burma in the Ayutthaya period. The result of the research design and performance testing of ceramic kiln using burners by gas cooker and outside from 200-liter steel drums inside with ceramic fiber. It was found that the Graze Firing of the products to be at a temperature of 1230°C. The duration of the burn approximately 5-6 hours and uses only 3-4 kg of LPG products, a coffee can burn up to 40-50 pieces. It is an energy-efficient Kiln. Use safe and appropriate opportunities for entrepreneurs, small ceramic and entrepreneurs with new investments or those who want to produce ceramic products as a hobby. The community interest in the pottery to create a new one to continue the product development and manufacturing in the harshest existence forever.

Keywords: ceramics kiln design and development, ceramic gas kiln, burners application, high-pressure of household gas stove

Procedia PDF Downloads 549

Authors: Liliana M. Marinelli, Cristina T. Varanese

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In the last few years, students from higher education have difficulties in grasping mathematical concepts which support physical matters, especially those in the first years of this education. Classical Physics teaching turns to be complex when students are not able to make use of mathematical tools which lead to the conceptual structure of Physics. When derivation and integration rules are not used or developed in parallel with other disciplines, the physical meaning that we attempt to convey turns to be complicated. Due to this fact, it could be of great use to see the Classical Mechanics from an axiomatic approach, where the correspondence rules give physical meaning, if we expect students to understand concepts clearly and accurately. Using the Minkowski point of view adapted to a two-dimensional space and time where vectors, matrices, and straight lines (worked from an affine space) give mathematical and physical rigorosity even when it is more abstract. An interesting option would be to develop the disciplinary contents from an axiomatic version which embraces the Classical Mechanics as a particular case of Relativistic Mechanics. The observation about the increase in the difficulties stated by students in the first years of education allows this idea to grow as a possible option to improve performance and understanding of the concepts of this subject.

Keywords: axioms, classical physics, physical concepts, relativity

Procedia PDF Downloads 306

Authors: Veruska C. Dutra, Lucio F.M. Adorno, Mary L. G. S. Senna

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Since it recognized the importance of planning sustainable tourism, which has been discussed effective methods of monitoring tourist. In this sense, the indicators, can transmit a set of information about complex processes, events or trends, showing up as an important monitoring tool and aid in the environmental assessment, helping to identify the progress of it and to chart future actions, contributing, so for decision making. The World Tourism Organization - WTO recognizes the importance of indicators to appraise the tourism activity in the point of view of sustainability, launching in 1995 eleven Keys Indicators of Sustainable Tourism to assist in the monitoring of tourist destinations. So we propose a case study to examine the applicability or otherwise of a monitoring methodology and aid in the understanding of tourism sustainability, analyzing the effectiveness of local indicators on the approach defined by the WTO. The study was applied to the Lagoa da Confusão City, in the state of Tocantins - North Brazil. The case study was carried out in 2006/2007, with the guiding deductive method. The indicators were measured by specific methodologies adapted to the study site, so that could generate quantitative results which could be analyzed at the proposed scale WTO (0 to 10 points). Applied indicators: Attractive Protection – AP (level of a natural and cultural attractive protection), Sociocultural Impact–SI (level of socio-cultural impacts), Waste Management - WM (level of management of solid waste generated), Planning Process-PP (trip planning level) Tourist Satisfaction-TS (satisfaction of the tourist experience), Community Satisfaction-CS (satisfaction of the local community with the development of local tourism) and Tourism Contribution to the Local Economy-TCLE (tourist level of contribution to the local economy). The city of Lagoa da Confusão was presented as an important object of study for the methodology in question, as offered condition to analyze the indicators and the complexities that arose during the research. The data collected can help discussions on the sustainability of tourism in the destination. The indicators TS, CS, WM , PP and AP appeared as satisfactory as allowed the measurement "translating" the reality under study, unlike TCLE and the SI indicators that were not seen as reliable and clear and should be reviewed and discussed for an adaptation and replication of the same. The application and study of various indicators of sustainable tourism, give better able to analyze the local tourism situation than monitor only one of the indicators, it does not demonstrate all collected data, which could result in a superficial analysis of the tourist destination.

Keywords: indicators, Lagoa da Confusão, Tocantins, Brazil, monitoring, sustainability

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Authors: Klaus Froehlich-Gildhoff, Ullrich Boettinger, Katharina Rauh, Angela Schickler

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The Prevention Network Ortenaukreis, PNO, funded by the German Ministry of Education and Research, aims to promote physical and mental health as well as the social inclusion of 3 to 10 years old children and their families in the Ortenau district. Within a period of four years starting 11/2014 a community network will be established. One regional and five local prevention representatives are building networks with stakeholders of the prevention and health promotion field bridging the health care, educational and youth welfare system in a multidisciplinary approach. The regional prevention representative implements regularly convening prevention and health conferences. On a local level, the 5 local prevention representatives implement round tables in each area as a platform for networking. In the setting approach, educational institutions are playing a vital role when gaining access to children and their families. Thus the project will offer 18 month long organizational development processes with specially trained coaches to 25 kindergarten and 25 primary schools. The process is based on a curriculum of prevention and health promotion which is adapted to the specific needs of the institutions. Also to ensure that the entire region is reached demand oriented advanced education courses are implemented at participating day care centers, kindergartens and schools. Evaluation method: The project is accompanied by an extensive research design to evaluate the outcomes of different project components such as interview data from community prevention agents, interviews and network analysis with families at risk on their support structures, data on community network development and monitoring, as well as data from kindergarten and primary schools. The latter features a waiting-list control group evaluation in kindergarten and primary schools with a mixed methods design using questionnaires and interviews with pedagogues, teachers, parents, and children. Results: By the time of the conference pre and post test data from the kindergarten samples (treatment and control group) will be presented, as well as data from the first project phase, such as qualitative interviews with the prevention coordinators as well as mixed methods data from the community needs assessment. In supporting this project, the Federal Ministry aims to gain insight into efficient components of community prevention and health promotion networks as it is implemented and evaluated. The district will serve as a model region, so that successful components can be transferred to other regions throughout Germany. Accordingly, the transferability to other regions is of high interest in this project.

Keywords: childhood research, health promotion, physical health, prevention network, psychological well-being, social inclusion

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Authors: Martin Wiseman, Rachel Thompson, Panagiota Mitrou, Kate Allen

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Since 1997 World Cancer Research Fund (WCRF) International and the American Institute for Cancer Research (AICR) have been at the forefront of synthesising and interpreting the accumulated scientific literature on the link between diet, nutrition, physical activity and cancer, and deriving evidence-based Cancer Prevention Recommendations. The 2007 WCRF/AICR 2nd Expert Report was a landmark in the analysis of evidence linking diet, body weight and physical activity to cancer and led to the establishment of the Continuous Update Project (CUP). In 2018, as part of the CUP, WCRF/AICR will publish a new synthesis of the current evidence and update the Cancer Prevention Recommendations. This will ensure that everyone - from policymakers and health professionals to members of the public - has access to the most up-to-date information on how to reduce the risk of developing cancer. Overweight and obesity play a significant role in cancer risk, and rates of both are increasing in many parts of the world. This session will give an overview of new evidence relating obesity to cancer since the 2007 report. For example, since the 2007 Report, the number of cancers for which obesity is judged to be a contributory cause has increased from seven to eleven. The session will also shed light on the well-established mechanisms underpinning obesity and cancer links. Additionally, the session will provide an overview of diet and physical activity related factors that promote positive energy imbalance, leading to overweight and obesity. Finally, the session will highlight how policy can be used to address overweight and obesity at a population level, using WCRF International’s NOURISHING Framework. NOURISHING formalises a comprehensive package of policies to promote healthy diets and reduce obesity and non-communicable diseases; it is a tool for policymakers to identify where action is needed and assess if an approach is sufficiently comprehensive. The framework brings together ten policy areas across three domains: food environment, food system, and behaviour change communication. The framework is accompanied by a regularly updated database providing an extensive overview of implemented government policy actions from around the world. In conclusion, the session will provide an overview of obesity and cancer, highlighting the links seen in the epidemiology and exploring the mechanisms underpinning these, as well as the influences that help determine overweight and obesity. Finally, the session will illustrate policy approaches that can be taken to reduce overweight and obesity worldwide.

Keywords: overweight, obesity, nutrition, cancer, mechanisms, policy

Procedia PDF Downloads 157

Authors: Hongyu Chen, Li Jiang

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Ubiquitous anomalies endanger the security of our system con- stantly. They may bring irreversible damages to the system and cause leakage of privacy. Thus, it is of vital importance to promptly detect these anomalies. Traditional supervised methods such as Decision Trees and Support Vector Machine (SVM) are used to classify normality and abnormality. However, in some case, the abnormal status are largely rarer than normal status, which leads to decision bias of these methods. Generative adversarial network (GAN) has been proposed to handle the case. With its strong generative ability, it only needs to learn the distribution of normal status, and identify the abnormal status through the gap between it and the learned distribution. Nevertheless, existing GAN-based models are not suitable to process data with discrete values, leading to immense degradation of detection performance. To cope with the discrete features, in this paper, we propose an efficient GAN-based model with specifically-designed loss function. Experiment results show that our model outperforms state-of-the-art models on discrete dataset and remarkably reduce the overhead.

Keywords: GAN, discrete feature, Wasserstein distance, multiple intermediate layers

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Authors: Muhammad Babar Suleman

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Transgressing the boundaries of the real and the virtual, the temporal and the spatial and the personal and the political, Four Broken Hearts is a hybrid storyworld encompassing film, live performance, location-based experiences and social media. The project is scheduled for launch early next year and is currently a work-in-progress undergoing initial user testing. The story of Four Broken Hearts is being told by taking each of the classic elements of fiction- character, setting, exposition, climax and denouement - and bringing them ‘to life’ in the medium that conveys them to the highest degree of mimesis: Characters are built and explored through social media, Setting is experienced through location-based storytelling, the Backstory is fleshed out using film and the Climax is performed as an immersive drama. By taking advantage of what each medium does best while complementing the other mediums, Four Broken Hearts is presented in the form of a rich transmedia experience that allows audiences to explore the story world across many different platforms while still tying it all together within a cohesive narrative. This article presents an investigation of the project’s narrative outputs produced so far.

Keywords: narratology, storyworld, transmedia, narrative, storytelling

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Authors: Saleem Rao, Mohammed Al-Ghadeer, Archan Banerjee, Hossein Fariborzi

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Materials imperfection, particularly two-level-system (TLS) defects in planer superconducting quantum circuits, contributes significantly to decoherence, ultimately limiting the performance of quantum computation and sensing. Oxides at air interfaces are among the host of TLS, and different material has been used to reduce TLS losses. Passivation with an inorganic layer is not an option to reduce these interface oxides; however, they can be etched away, but their regrowth remains a problem. Here, we report the chemisorption of molecular self-assembled monolayers (SAMs) at air interfaces of superconducting co-planer waveguide (CPW) resonators that suppress the regrowth of oxides and also modify the dielectric constant of the interface. With SAMs, we observed sustained order of magnitude improvement in quality factor -better than oxide etched interfaces. Quality factor measurements at millikelvin temperature and at single photon, XPS data, and TEM images of SAM passivated air interface sustenance our claim. Compatibility of SAM with micro-/nano-fabrication processes opens new ways to improve the coherence time in cQED.

Keywords: superconducting circuits, quality-factor, self-assembled monolayer, coherence

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Authors: Iannick Gagnon, Alain April

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The performance of a metaheuristic on a given problem class depends on the class itself and the choice of parameters. Parameter tuning is the most time-consuming phase of the optimization process after the main calculations and it often nullifies the speed advantage of metaheuristics over traditional optimization algorithms. Several off-the-shelf parameter tuning algorithms are available, but when the objective function is expensive to evaluate, these can be prohibitively expensive to use. This paper presents a surrogate-like method for finding adequate parameters using fitness landscape analysis on simple benchmark functions and real-world objective functions. The result is a simple compound similarity metric based on the empirical correlation coefficient and a measure of convexity. It is then used to find the best benchmark functions to serve as surrogates. The near-optimal parameter set is then found using fractional factorial design. The real-world problem of NACA airfoil lift coefficient maximization is used as a preliminary proof of concept. The overall aim of this research is to reduce the computational overhead of metaheuristics parameterization.

Keywords: metaheuristics, stochastic optimization, particle swarm optimization, exploratory landscape analysis

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Authors: Joaquin Navarro Perales, Ana Lidia Franzoni Velázquez, Francisco Cervantes Pérez

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The Mexican educational system faces diverse challenges related with the quality and coverage of education. The development of Intelligent Tutoring Systems (ITS) may help to solve some of them by helping teachers to customize their classes according to the performance of the students in online courses. In this work, we propose the adaptation of a functional ITS based on Bloom’s taxonomy called Sistema de Apoyo Generalizado para la Enseñanza Individualizada (SAGE), to measure student’s metacognition and their emotional response based on Marzano’s taxonomy. The students and the system will share the control over the advance in the course, so they can improve their metacognitive skills. The system will not allow students to get access to subjects not mastered yet. The interaction between the system and the student will be implemented through Natural Language Processing techniques, thus avoiding the use of sensors to evaluate student’s response. The teacher will evaluate student’s knowledge utilization, which is equivalent to the last cognitive level in Marzano’s taxonomy.

Keywords: intelligent tutoring systems, student modelling, metacognition, affective computing, natural language processing

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Authors: Amirreza Razzaghipour Sorkhab

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The exploration of the connection between cognition and Auditory Processing Disorder (APD) holds significant value. Individuals with APD experience challenges in processing auditory information through the central auditory nervous system's varied pathways. Understanding the importance of auditory attention in individuals with APD, as well as the primary diagnostic tools such as language and auditory attention tests, highlights the critical need for assessing their auditory attention abilities. While not all children with Auditory Processing Disorder (APD) show deficits in auditory attention, there are often deficiencies in cognitive and attentional performance. The link between various types of attention deficits and APD suggests impairments in sustained and divided auditory attention. Research into the origins of APD should also encompass higher-level processes, such as auditory attention. It is evident that investigating the interaction between APD and auditory and cognitive functions holds significant value. Furthermore, it was demonstrated that APD tests may be influenced by cognitive factors, but despite signs of auditory attention interaction with auditory processing skills and the influence of cognitive factors on tests for this disorder, auditory attention measures are not typically included in APD diagnostic protocols. Therefore, incorporating attention assessment tests into the battery of tests for individuals with auditory processing disorder will be beneficial for obtaining useful insights into their attentional abilities.

Keywords: auditory processing disorder, auditory attention, central auditory processing disorder, top-down pathway

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Authors: Eden G. Mariquit, Winarto Kurniawan, Masahiro Miyauchi, Hirofumi Hinode

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This research studied the effect of adding surfactant to the titanium dioxide (TiO2) sol-gel solution that was used to immobilize TiO2 on glass substrates by dip coating technique using TiO2 sol-gel solution mixed with different types of surfactants. After dipping into the TiO2 sol, the films were calcined and produced pure anatase crystal phase. The thickness of the thin film was varied by repeating the dip and calcine cycle. The prepared films were characterized using FE-SEM, TG-DTA, and XRD, and its photocatalytic performances were tested on degradation of an organic dye, methylene blue. Aside from its phocatalytic performance, the photo-induced hydrophilicity of thin TiO2 films surface was also studied. Characterization results showed that the addition of surfactant gave rise to characteristic patterns on the surface of the TiO2 thin film which also affects the photocatalytic activity. The addition of CTAB to the TiO2 dipping solution had a negative effect because the calcination temperature was not high enough to burn all the surfactants off. As for the surface wettability, the addition of surfactant also affected the induced surface hydrophilicity of the TiO2 films when irradiated under UV light.

Keywords: photocatalysis, surface hydrophilicity, TiO2 thin films, surfactant

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Authors: Amin Sedighfar, M. R. Moniri

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Determination of state of charge (SOC) in today’s world becomes an increasingly important issue in all the applications that include a battery. In fact, estimation of the SOC is a fundamental need for the battery, which is the most important energy storage in Hybrid Electric Vehicles (HEVs), smart grid systems, drones, UPS and so on. Regarding those applications, the SOC estimation algorithm is expected to be precise and easy to implement. This paper presents an online method for the estimation of the SOC of Valve-Regulated Lead Acid (VRLA) batteries. The proposed method uses the well-known Kalman Filter (KF), and Neural Networks (NNs) and all of the simulations have been done with MATLAB software. The NN is trained offline using the data collected from the battery discharging process. A generic cell model is used, and the underlying dynamic behavior of the model has used two capacitors (bulk and surface) and three resistors (terminal, surface, and end), where the SOC determined from the voltage represents the bulk capacitor. The aim of this work is to compare the performance of conventional integration-based SOC estimation methods with a mixed algorithm. Moreover, by containing the effect of temperature, the final result becomes more accurate. 

Keywords: Kalman filter, neural networks, state-of-charge, VRLA battery

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Authors: Ninlawat Phuangchoke, Waraporn Viyanon, Setta Sasananan

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The most important process of the water treatment plant process is the coagulation using alum and poly aluminum chloride (PACL), and the value of usage per day is a hundred thousand baht. Therefore, determining the dosage of alum and PACL are the most important factors to be prescribed. Water production is economical and valuable. This research applies an artificial neural network (ANN), which uses the Levenberg–Marquardt algorithm to create a mathematical model (Soft Jar Test) for prediction chemical dose used to coagulation such as alum and PACL, which input data consists of turbidity, pH, alkalinity, conductivity, and, oxygen consumption (OC) of Bangkhen water treatment plant (BKWTP) Metropolitan Waterworks Authority. The data collected from 1 January 2019 to 31 December 2019 cover changing seasons of Thailand. The input data of ANN is divided into three groups training set, test set, and validation set, which the best model performance with a coefficient of determination and mean absolute error of alum are 0.73, 3.18, and PACL is 0.59, 3.21 respectively.

Keywords: soft jar test, jar test, water treatment plant process, artificial neural network

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Authors: Vinay Kumar Vanjakula, Frank Adam, Nils Goseberg, Christian Windt

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When a structure is installed on a seabed, the presence of the structure will influence the flow field around it. The changes in the flow field include, formation of vortices, turbulence generation, waves or currents flow breaking and pressure differentials around the seabed sediment. These changes allow the local seabed sediment to be carried off and results in Scour (erosion). These are a threat to the structure's stability. In recent decades, rapid developments of research work and the knowledge of scour On fixed structures (bridges and Monopiles) in rivers and oceans has been carried out, and very limited research work on scour and liquefaction for gravity anchors, particularly for floating Tension Leg Platform (TLP) substructures. Due to its importance and need for enhancement of knowledge in scour and liquefaction around marine structures, the MarTERA funded a three-year (2020-2023) research program called NuLIMAS (Numerical Modeling of Liquefaction Around Marine Structures). It’s a group consists of European institutions (Universities, laboratories, and consulting companies). The objective of this study is to build a numerical model that replicates the reality, which indeed helps to simulate (predict) underwater flow conditions and to study different marine scour and Liquefication situations. It helps to design a heavyweight anchor for the TLP substructure and to minimize the time and expenditure on experiments. And also, the achieved results and the numerical model will be a basis for the development of other design and concepts For marine structures. The Computational Fluid Dynamics (CFD) numerical model will build in OpenFOAM. A conceptual design of heavyweight anchor for TLP substructure is designed through taking considerations of available state-of-the-art knowledge on scour and Liquefication concepts and references to Previous existing designs. These conceptual designs are validated with the available similar experimental benchmark data and also with the CFD numerical benchmark standards (CFD quality assurance study). CFD optimization model/tool is designed as to minimize the effect of fluid flow, scour, and Liquefication. A parameterized model is also developed to automate the calculation process to reduce user interactions. The parameters such as anchor Lowering Process, flow optimized outer contours, seabed interaction study, and FSSI (Fluid-Structure-Seabed Interactions) are investigated and used to carve the model as to build an optimized anchor.

Keywords: gravity anchor, liquefaction, scour, computational fluid dynamics

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Authors: Keyur Joshi, Philip Dietrich, Tjark Windisch, Markus König

Abstract:

In the field of surveillance-based fire detection, the volume of incoming data is increasing rapidly. However, the labeling of a large industrial dataset is costly due to the high annotation costs associated with current state-of-the-art methods, which often require bounding boxes or segmentation masks for model training. This paper introduces VideoAssist, a video annotation solution that utilizes a video-based foundation model to annotate entire videos with minimal effort, requiring the labeling of bounding boxes for only a few keyframes. To the best of our knowledge, VideoAssist is the first method to significantly reduce the effort required for labeling fire detection videos. The approach offers bounding box and segmentation annotations for the video dataset with minimal manual effort. Results demonstrate that the performance of labels annotated by VideoAssist is comparable to those annotated by humans, indicating the potential applicability of this approach in fire detection scenarios.

Keywords: fire detection, label annotation, foundation models, object detection, segmentation

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Authors: Bachir Bentouati, Lakhdar Chaib, Saliha Chettih, Gai-Ge Wang

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The problem of economic dispatch (ED) is the basic problem of power framework, its main goal is to find the most favorable generation dispatch to generate each unit, reduce the whole power generation cost, and meet all system limitations. A heuristic algorithm, recently developed called Stud Krill Herd (SKH), has been employed in this paper to treat non-convex ED problems. The proposed KH has been modified using Stud selection and crossover (SSC) operator, to enhance the solution quality and avoid local optima. We are demonstrated SKH effects in two case study systems composed of 13-unit and 40-unit test systems to verify its performance and applicability in solving the ED problems. In the above systems, SKH can successfully obtain the best fuel generator and distribute the load requirements for the online generators. The results showed that the use of the proposed SKH method could reduce the total cost of generation and optimize the fulfillment of the load requirements.

Keywords: stud krill herd, economic dispatch, crossover, stud selection, valve-point effect

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Authors: Oliver Chunho Ma, Tszying Chang

Abstract:

Background: Traditional Chinese Medicine (TCM) has been widely used in the treatment of eczema. However, there is currently a lack of comprehensive research on the overall effectiveness of TCM in treating eczema, particularly using the Eczema Area and Severity Index (EASI) score as an evaluation tool. Meta-analysis can integrate the results of multiple studies to provide more convincing evidence. Objective: To conduct a systematic review and meta-analysis based on the EASI score to evaluate the overall effectiveness of TCM in the treatment of eczema. Specifically, the study will review and analyze published clinical studies that investigate TCM treatments for eczema and use the EASI score as an outcome measure, comparing the differences in improving the severity of eczema between TCM and other treatment modalities, such as conventional Western medicine treatments. Methods: Relevant studies, including randomized controlled trials (RCTs) and non-randomized controlled trials, that involve TCM treatment for eczema and use the EASI score as an outcome measure will be searched in medical literature databases such as PubMed, CNKI, etc. Relevant data will be extracted from the selected studies, including study design, sample size, treatment methods, improvement in EASI score, etc. The methodological quality and risk of bias of the included studies will be assessed using appropriate evaluation tools (such as the Cochrane Handbook). The results of the selected studies will be statistically analyzed, including pooling effect sizes (such as standardized mean differences, relative risks, etc.), subgroup analysis (e.g., different TCM syndromes, different treatment modalities), and sensitivity analysis (e.g., excluding low-quality studies). Based on the results of the statistical analysis and quality assessment, the overall effectiveness of TCM in improving the severity of eczema will be interpreted. Expected outcomes: By integrating the results of multiple studies, we expect to provide more convincing evidence regarding the specific effects of TCM in improving the severity of eczema. Additionally, subgroup analysis and sensitivity analysis can further elucidate whether the effectiveness of TCM treatment is influenced by different factors. Besides, we will compare the results of the meta-analysis with the clinical data from our clinic. For both the clinical data and the meta-analysis results, we will perform descriptive statistics such as means, standard deviations, percentages, etc. and compare the differences between the two using statistical tests such as independent samples t-test or non-parametric tests to assess the statistical differences between them.

Keywords: Eczema, traditional Chinese medicine, EASI, systematic review, meta-analysis

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Authors: Satam Alotibi, Osama A. Hussein, Aziz H. Al-Shaibani, Nawaf A. Al-Aqeel, Abdellah Kaiba, Fatehia S. Alhakami, Mohammed Alyami, Talal F. Qahtan

Abstract:

The demand for sustainable and efficient energy conversion using solar energy has grown rapidly in recent years. In this pursuit, solar-to-chemical conversion has emerged as a promising approach, with oxygen vacancies-rich tungsten trioxide (WO₃) playing a crucial role. This study presents a method for synthesizing oxygen vacancies-rich WO3, resulting in a significant enhancement of its photocatalytic activity, representing a significant step towards sustainable energy solutions. Experimental results underscore the importance of oxygen vacancies in modifying the properties of WO₃. These vacancies introduce additional energy states within the material, leading to a reduction in the bandgap, increased light absorption, and acting as electron traps, thereby reducing emissions. Our focus lies in developing oxygen vacancies-rich WO₃, which demonstrates unparalleled potential for improved photocatalytic applications. The effectiveness of oxygen vacancies-rich WO₃ in solar-to-chemical conversion was showcased through rigorous assessments of its photocatalytic degradation performance. Sunlight irradiation was employed to evaluate the material's effectiveness in degrading organic pollutants in wastewater. The results unequivocally demonstrate the superior photocatalytic performance of oxygen vacancies-rich WO₃ compared to conventional WO₃ nanomaterials, establishing its efficacy in sustainable and efficient energy conversion. Furthermore, the synthesized material is utilized to fabricate films, which are subsequently employed in immobilized WO₃ and oxygen vacancies-rich WO₃ reactors for water purification under natural sunlight irradiation. This application offers a sustainable and efficient solution for water treatment, harnessing solar energy for effective decontamination. In addition to investigating the photocatalytic capabilities, we extensively analyze the structural and chemical properties of the synthesized material. The synthesis process involves in situ thermal reduction of WO₃ nano-powder in a nitrogen environment, meticulously monitored using thermogravimetric analysis (TGA) to ensure precise control over the synthesis of oxygen vacancies-rich WO₃. Comprehensive characterization techniques such as UV-Vis spectroscopy, X-ray photoelectron spectroscopy (XPS), FTIR, Raman spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), and selected area electron diffraction (SAED) provide deep insights into the material's optical properties, chemical composition, elemental states, structure, surface properties, and crystalline structure. This study represents a significant advancement in sustainable energy conversion through solar-to-chemical processes and water purification. By harnessing the unique properties of oxygen vacancies-rich WO₃, we not only enhance our understanding of energy conversion mechanisms but also pave the way for the development of highly efficient and environmentally friendly photocatalytic materials. The application of this material in water purification demonstrates its versatility and potential to address critical environmental challenges. These findings bring us closer to a sustainable energy future and cleaner water resources, laying a solid foundation for a more sustainable planet.

Keywords: sustainable energy conversion, solar-to-chemical conversion, oxygen vacancies-rich tungsten trioxide (WO₃), photocatalytic activity enhancement, water purification

Procedia PDF Downloads 69