Search results for: autonomous learning system

Authors: Arup Saha Chaudhuri

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Structural steel is a very ductile material with high strength carrying capacity, thus it is very useful to make earthquake resistant buildings. It is a homogeneous material also. The member section and the structural system can be made very efficient for economical design. As the steel is recyclable and reused, it is a green material. The embodied energy for the efficiently designed steel structure is less than the RC structure. For sustainable green building steel is the best material nowadays. Moreover, pre-engineered and pre-fabricated faster construction methodologies help the development work to complete within the stipulated time. In this paper, the usefulness of Eccentric Bracing Frame (EBF) in steel structure over Moment Resisting Frame (MRF) and Concentric Bracing Frame (CBF) is shown. Stability of the steel structures against horizontal forces especially in seismic condition is efficiently possible by Eccentric bracing systems with economic connection details. The EBF is pin–ended, but the beam-column joints are designed for pin ended or for full connectivity. The EBF has several desirable features for seismic resistance. In comparison with CBF system, EBF system can be designed for appropriate stiffness and drift control. The link beam is supposed to yield in shear or flexure before initiation of yielding or buckling of the bracing member in tension or compression. The behavior of a 2-D steel frame is observed under seismic loading condition in the present paper. Ductility and brittleness of the frames are compared with respect to time period of vibration and dynamic base shear. It is observed that the EBF system is better than MRF system comparing the time period of vibration and base shear participation.

Keywords: steel building, green and sustainable, earthquake resistant, EBF system

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Authors: Ahmed Z. Gabr, Ahmed A. Helal, Hussein E. Said

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With the incessant increase of power systems capacity and voltage grade, the safety of grounding grid becomes more and more prominent. In this paper, the designing substation grounding grid is presented by means of genetic algorithm (GA). This approach purposes to control the grounding cost of the power system with the aid of controlling grounding rod number and conductor lengths under the same safety limitations. The proposed technique is used for the design of the substation grounding grid in Khalda Petroleum Company “El-Qasr” power plant and the design was simulated by using CYMGRD software for results verification. The result of the design is highly complying with IEEE 80-2000 standard requirements.

Keywords: genetic algorithm, optimum grounding grid design, power system analysis, power system protection, single layer model, substation

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Authors: H. K. V. Narayan

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This study was conducted at Tata Memorial Hospital (TMH), Mumbai, India. The study was to evaluate the impact of adapting Smart Card (SC) for clinical and business transactions in order to reduce Lead times and to enforce business rules of the hospital. The objective for implementing the Smart Card was to improve the patient perception of quality in terms of structures process and outcomes and also to improve the productivity of the Institution. The Smart Card was implemented in phases from 2011 and integrated with the Hospital Information System (HIS/EMR). The implementation was a learning curve for all the stake holders as software obviated the need to use hardcopies of transactions. The acceptability to the stake holders was challenge in change management. The study assessed the impact 3 years into the implementation and the observed trends have suggested that it has decreased the lead times for services and increased the no of transactions and thereby the productivity. Patients who used to complain of multiple queues and cumbersome transactions now compliment the administration for effective use of Information and Communication Technology.

Keywords: smart card, high availability of health care information, reduction in potential medical errors due to elimination of transcription errors, reduction in no of queues, increased transactions, augmentation of revenue

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Authors: Om Prakash Bharti, Aanchal Verma, R. K. Saket

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The Doubly-Fed Induction Generator (DFIG) is suggested for Wind Energy Conversion System (WECS) to extract wind power. DFIG is preferably employed due to its robustness towards variable wind and rotor speed. DFIG has the adaptable property because the system parameters are smoothly dealt with, including real power, reactive power, DC-link voltage, and the transient and dynamic responses, which are needed to analyze constantly. The analysis becomes more prominent during any unusual condition in the electrical power system. Hence, the study and improvement in the system parameters and transient response performance of DFIG are required to be accomplished using some controlling techniques. For fulfilling the task, the present work implements and compares the optimization methods for the design of the DFIG controller for WECS. The bio-inspired optimization techniques are applied to get the optimal controller design parameters for DFIG-based WECS. The optimized DFIG controllers are then used to retrieve the transient response performance of the six-order DFIG model with a step input. The results using MATLAB/Simulink show the betterment of the Firefly algorithm (FFA) over other control techniques when compared with the other controller design methods.

Keywords: doubly-fed induction generator, wind turbine, wind energy conversion system, induction generator, transfer function, proportional, integral, derivatives

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Authors: Assem I. El-Ansary

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This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Multi-Agent Railway Control System (MARCS). The Event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are the Behavioral Pattern Analysis (BPA) modeling methodology, and the development of an interactive software tool (DECISION), which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, multi-agent, railway control, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases

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Authors: Hefzollah Mohammadian, Mohammad Bagher Heidari

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This paper deals with the technical and economic effects of various parameters on the performance of heat recovery system on gas complex turbo generator. Given the importance of this issue, that is the main goal of economic efficiency and reduces costs; this project has been implemented similar plans in which the target is the implementation of specific patterns. The project will also help us in the process of gas refineries and the actual efficiency of the process after adding a system to analyze the turbine and predict potential problems and fix them and take appropriate measures according to the results of simulation analysis and results of the process gain. The results of modeling and the effect of different parameters on this line, have been done using Thermo Flow.

Keywords: turbo compressor, turbo generator, heat recovery boiler, gas turbines

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Authors: Morteza Pourazar, Fatemeh Mirakhori, Fazlolah Bagherzadeh, Rasool Hemayattalab

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The purpose of study was to examine the effects of external and internal focus of attention in the motor learning of children with cerebral palsy. The study involved 30 boys (7 to 12 years old) with CP type 1 who practiced throwing beanbags. The participants were randomly assigned to the internal focus, external focus, and control groups, and performed six blocks of 10-trial with attentional focus reminders during a practice phase and no reminders during retention and transfer tests. Analysis of variance (ANOVA) with repeated measures on the last factor was used. The results show that significant main effects were found for time and group. However, the interaction of time and group was not significant. Retention scores were significantly higher for the external focus group. The external focus group performed better than other groups; however, the internal focus and control groups’ performance did not differ. The study concluded that motor skills in Spastic Hemiparetic Cerebral Palsy (SHCP) children could be enhanced by external attention.

Keywords: cerebral palsy, external attention, internal attention, throwing task

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Authors: Chia-Hung Liao, Shih-Chieh Lin

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X-ray computed tomography (CT) technology has been used in the electronics industry as one of the non-destructive inspection tools for years. The key advantage of X-ray computed tomography technology superior to traditional optical inspection is the penetrating characteristics of X-rays can be used to detect defects in the interior of objects. The objective of this study is to find a way to estimate the system geometric deviation of X-ray CT equipment. Projection trajectories of the characteristic points of standard parts were tracked, and ways to calculate the deviation of various geometric parameters of the system will be proposed and evaluated. A simulation study will be conducted to first find out the effects of system geometric deviation on projected trajectories. Then ways to estimate geometric deviation with collected trajectories will be proposed and tested through simulations.

Keywords: geometric calibration, X-ray computed tomography, trajectory tracing, reconstruction optimization

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Authors: Suresh Salla

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In this paper, author explores for most sustainable last mile transport mode addressing present problems of traffic congestion, jams, pollution and travel stress. Development of energy-efficient sustainable integrated transport system(s) is/are must to make our cities more livable. Emphasis on autonomous, connected, electric, sharing system for effective utilization of systems (vehicles and public infrastructure) is on the rise. Many surface mobility innovations like PBS, Ride hailing, ride sharing, etc. are, although workable but if we analyze holistically, add to the already congested roads, difficult to ride in hostile weather, causes pollution and poses commuter stress. Sustainability of transportation is evaluated with respect to public adoption, average speed, energy consumption, and pollution. Why public prefer certain mode over others? How commute time plays a role in mode selection or shift? What are the factors play-ing role in energy consumption and pollution? Based on the study, it is clear that public prefer a transport mode which is exhaustive (i.e., less need for interchange – network is widespread) and intensive (i.e., less waiting time - vehicles are available at frequent intervals) and convenient with latest technologies. Average speed is dependent on stops, number of intersections, signals, clear route availability, etc. It is clear from Physics that higher the kerb weight of a vehicle; higher is the operational energy consumption. Higher kerb weight also demands heavier infrastructure. Pollution is dependent on source of energy, efficiency of vehicle, average speed. Mode can be made exhaustive when the unit infrastructure cost is less and can be offered intensively when the vehicle cost is less. Reliable and seamless integrated mobility till last ¼ mile (Five Minute Walk-FMW) is a must to encourage sustainable public transportation. Study shows that average speed and reliability of dedicated modes (like Metro, PRT, BRT, etc.) is high compared to road vehicles. Electric vehicles and more so battery-less or 3rd rail vehicles reduce pollution. One potential mode can be Cycleloop PRT, where commuter rides e-cycle in a dedicated path – elevated, at grade or underground. e-Bike with kerb weight per rider at 15 kg being 1/50th of car or 1/10th of other PRT systems makes it sustainable mode. Cycleloop tube will be light, sleek and scalable and can be modular erected, either on modified street lamp-posts or can be hanged/suspended between the two stations. Embarking and dis-embarking points or offline stations can be at an interval which suits FMW to mass public transit. In terms of convenience, guided e-Bike can be made self-balancing thus encouraging driverless on-demand vehicles. e-Bike equipped with smart electronics and drive controls can intelligently respond to field sensors and autonomously move reacting to Central Controller. Smart switching allows travel from origin to destination without interchange of cycles. DC Powered Batteryless e-cycle with voluntary manual pedaling makes it sustainable and provides health benefits. Tandem e-bike, smart switching and Platoon operations algorithm options provide superior through-put of the Cycleloop. Thus Cycleloop PRT will be exhaustive, intensive, convenient, reliable, speedy, sustainable, safe, pollution-free and healthy alternative mode for last mile connectivity in cities.

Keywords: cycleloop PRT, five-minute walk, lean modular infrastructure, self-balanced intelligent e-cycle

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Authors: Nattapol Pourprasert, Siriwan Manowan

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This study aims to find out what budget problems Thailand is facing with and how the results from the comparison between the budgeting reform by Thailand and the reforms by OECD member countries can be used for carrying out budgeting reform of Thailand. The findings from the study on the budget problems that Thailand is facing with reveal that the budgeting system of Thailand lacks of the assessment for the cost-effectiveness of the expenditure of borrowed money and budgets in order to determine whether the expenses are worth the taxes collected from people or not. This is because most popularity policies have unlimited budgets which can lead to the financial risks. Also, these policies create great tax burdens for the descendants in the future and affect the fair distribution of incomes but the Parliament of Thailand never considers these facts. The findings from the comparison between Thai budgeting reform and those by OECD member countries manifest that the traditional budgeting system of Thailand is the department-based budgeting, which is still used without being changed or adjusted in order to fit the new administrative regimes. This traditional budgeting system suggests that a department is responsible for budgeting tasks. Meanwhile, in OECD member countries, budgeting reforms are carried out simultaneously with the reforms of civil service systems so that they are driven in the same directions. The budgeting reforms that rely only on the analyses on economic or technical dimension can hardly lead to success. The budgeting systems of OECD member countries are designed to deal with the unique problems that each of the member countries is facing with rather than adopting the modern system developed by other countries. The budgeting system that has a complicated concept and practice has to be implemented under a flexible strategy so that the departments that implement it can learn about and adjust itself to the system. Continuous and consistent development and training for staff members are also necessary.

Keywords: budgeting reforms, Thailand, OECD member countries, budget problems

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Authors: D. Maneetham

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The developed exoskeleton device has to control joints between shoulder and arm. Exoskeleton device can help patients with hemiplegia upper so that the patient can help themselves in their daily life. Exoskeleton device includes a robot arm wear that looks like the movement is similar to the normal arm. Exoskeleton arm is powered by the motor through the cable with a control system that developed to control the movement of the joint of a robot arm. The arm will include the shoulder, the elbow, and the wrist. The control system is used Arduino Mega 2560 controller and the operation of the DC motor through the relay module. The control system can be divided into two modes such as the manual control with the joystick mode and automatically control with the movement of the head by Gyro sensor. The controller is also designed to move between the shoulder and the arm movement from their original location. Results have shown that the controller gave the best performance and all movements can be controlled.

Keywords: exoskeleton arm, hemiplegia upper, shoulder and arm, stroke

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Authors: Zachary Pan

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Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

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Authors: Juliane Toce, Steven Holochwost

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A substantial and growing literature has demonstrated that arts education benefits young children’s socioemotional and cognitive development. Less is known about the capacity of arts-integrated instruction to yield benefits to similar domains, particularly among demographically and socioeconomically diverse groups of young children. However, the small literature on this topic suggests that arts-integrated instruction may foster young children’s socioemotional and cognitive development by presenting opportunities to 1) engage in instructional content in diverse ways, 2) experience and regulate strong emotions, 3) experience growth-oriented feedback, and 4) engage in collaborative work with peers. Start with the Art is a new program of arts-integrated instruction currently being implemented in four schools in a school district that serves students from a diverse range of backgrounds. The program employs a co-teaching model in which teaching artists and classroom teachers engage in collaborative lesson planning and instruction over the course of the academic year and is currently the focus of an impact study featuring a randomized-control design, as well as an implementation study, both of which are funded through an Educational Innovation and Research grant from the United States Department of Education. The paper will present the early results from the Start with the Art implementation study. These results will provide an overview of the extent to which the program was implemented in accordance with design, with a particular emphasis on the degree to which the four opportunities enumerated above (e.g., opportunities to engage in instructional content in diverse ways) were presented to students. There will be a review key factors that may influence the fidelity of implementation, including classroom teachers’ reception of the program and the extent to which extant conditions in the classroom (e.g., the overall level of classroom organization) may have impacted implementation fidelity. With the explicit purpose of creating a program that values and meets the needs of the teachers and students, Start with the Art incorporates the feedback from individuals participating in the intervention. Tracing its trajectory from inception to ongoing development and examining the adaptive changes made in response to teachers' transformative experiences in the post-pandemic classroom, Start with the Art continues to solicit input from experts in integrating artistic content into core curricula within educational settings catering to students from under-represented backgrounds in the arts. Leveraging the input from this rich consortium of experts has allowed for a comprehensive evaluation of the program’s implementation. The early findings derived from the implementation study emphasize the potential of arts-integrated instruction to incorporate restorative practices. Such practices serve as a crucial support system for both students and educators, providing avenues for children to express themselves, heal emotionally, and foster social development, while empowering teachers to create more empathetic, inclusive, and supportive learning environments. This all-encompassing analysis spotlights Start with the Art’s adaptability to any learning environment through the program’s effectiveness, resilience, and its capacity to transform - through art - the classroom experience within the ever-evolving landscape of education.

Keywords: arts-integration, social emotional learning, diverse learners, co-teaching, teaching artists, post-pandemic teaching

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Authors: Pimpisa Rattanadilok Na Phuket

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This research study aims to examine: 1) teaching competency of the native English-speaking teacher (NEST) 2) the English language learning achievement of Thai students, and 3) students’ perceptions toward their NEST. The population considered in this research was a group of 39 undergraduate students of the academic year 2013. The tools consisted of a questionnaire employed to measure the level of competency of NEST, pre-test and post-test used to examine the students’ achievement on English pronunciation, and an interview used to discover how participants perceived their NEST. The data was statistically analysed as percentage, mean, standard deviation and One-sample-t-test. In addition, the data collected by interviews was qualitatively analyzed. The research study found that the level of teaching competency of native speaker teachers of English was mostly low, the English pronunciation achievement of students had increased significantly at the level of 0.5, and the students’ perception toward NEST is combined. The students perceived their NEST as an English expertise, but they felt that NEST had not recognized students' linguistic difficulty and cultural differences.

Keywords: competency, native English-speaking teacher (NET), English teaching, learning achievement

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Authors: Chan Ka Lok Sobel

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The rapid evolution of digital media platforms has given rise to new forms of narrative engagement, particularly through multi-channel storytelling. This research focuses on exploring the teaching pedagogy and effectiveness of multi-channel storytelling for social media, cinema, games, and streaming platforms. The study employs case studies of the popular series "Squid Game" to investigate the diverse pedagogical approaches and strategies used in teaching multi-channel storytelling. Through qualitative research methods, including interviews, surveys, and content analysis, the research assesses the effectiveness of these approaches in terms of student engagement, knowledge acquisition, critical thinking skills, and the development of digital literacy. The findings contribute to understanding best practices for incorporating multi-channel storytelling into educational contexts and enhancing learning outcomes in the digital media landscape.

Keywords: digital literacy, game-based learning, artificial intelligence, animation production, educational technology

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Authors: Selim M. Khan, Aaron A. Goodarzi, Joshua M. Taron, Tryggve Rönnqvist

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Indoor air quality, a prime determinant of health, is strongly influenced by the presence of hazardous radon gas within the built environment. As a health issue, dangerously high indoor radon arose within the 20th century to become the 2nd leading cause of lung cancer. While the 21st century building metrics and human behaviors have captured, contained, and concentrated radon to yet higher and more hazardous levels, the issue is rapidly worsening in Canada. It is established that Canadians in the Prairies are the 2nd highest radon-exposed population in the world, with 1 in 6 residences experiencing 0.2-6.5 millisieverts (mSv) radiation per week, whereas the Canadian Nuclear Safety Commission sets maximum 5-year occupational limits for atomic workplace exposure at only 20 mSv. This situation is also deteriorating over time within newer housing stocks containing higher levels of radon. Deep machine learning (LSTM) algorithms were applied to analyze multiple quantitative and qualitative features, determine the most important contributory factors, and predicted radon levels in the known past (1990-2020) and projected future (2021-2050). The findings showed gradual downwards patterns in Sweden, whereas it would continue to go from high to higher levels in Canada over time. The contributory factors found to be the basement porosity, roof insulation depthness, R-factor, and air dynamics of the indoor environment related to human window opening behaviour. Building codes must consider including these factors to ensure adequate indoor ventilation and healthy living that can prevent lung cancer in non-smokers.

Keywords: radon, building metrics, deep learning, LSTM prediction model, lung cancer, canada, sweden

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Authors: Nádia Pereira, Paula Ferreira, Sofia Francisco, Sofia Oliveira, Sidclay Souza, Paula Paulino, Ana Margarida Veiga Simão

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Social media has progressed into a platform for hate speech among its users, and thus, there is an increasing need to develop automatic detection classifiers of offense and conflicts to help decrease the prevalence of such incidents. Online communication can be used to intentionally harm someone, which is why such classifiers could be essential in social networks. A possible application of these classifiers is the automatic detection of cyberbullying. Even though identifying the aggressive language used in online interactions could be important to build cyberbullying datasets, there are other criteria that must be considered. Being able to capture the language, which is indicative of the intent to harm others in a specific context of online interaction is fundamental. Offense and hate speech may be the foundation of online conflicts, which have become commonly used in social media and are an emergent research focus in machine learning and natural language processing. This study presents two Portuguese language offense-related datasets which serve as examples for future research and extend the study of the topic. The first is similar to other offense detection related datasets and is entitled Aggressiveness dataset. The second is a novelty because of the use of the history of the interaction between users and is entitled the Conflicts/Attacks dataset. Both datasets were developed in different phases. Firstly, we performed a content analysis of verbal aggression witnessed by adolescents in situations of cyberbullying. Secondly, we computed frequency analyses from the previous phase to gather lexical and linguistic cues used to identify potentially aggressive conflicts and attacks which were posted on Twitter. Thirdly, thorough annotation of real tweets was performed byindependent postgraduate educational psychologists with experience in cyberbullying research. Lastly, we benchmarked these datasets with other machine learning classifiers.

Keywords: aggression, classifiers, cyberbullying, datasets, hate speech, machine learning

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Authors: S. H. Iranmanesh, L. Aliabadi, A. Mollajan

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Integrated resilience engineering (IRE) is capable of returning banking systems to the normal state in extensive economic circumstances. In this study, information system of a large bank (with several branches) is assessed and optimized under severe economic conditions. Data envelopment analysis (DEA) models are employed to achieve the objective of this study. Nine IRE factors are considered to be the outputs, and a dummy variable is defined as the input of the DEA models. A standard questionnaire is designed and distributed among executive managers to be considered as the decision-making units (DMUs). Reliability and validity of the questionnaire is examined based on Cronbach's alpha and t-test. The most appropriate DEA model is determined based on average efficiency and normality test. It is shown that the proposed integrated design provides higher efficiency than the conventional RE design. Results of sensitivity and perturbation analysis indicate that self-organization, fault tolerance, and reporting culture respectively compose about 50 percent of total weight.

Keywords: banking system, Data Envelopment Analysis (DEA), Integrated Resilience Engineering (IRE), performance evaluation, perturbation analysis

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Authors: Soban Najam, S. M. Jahanzeb, Ahmed Sohail, Faraz Idris Khan

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With the recent increase in reliance on Gas as the primary source of energy across the world, there has been a lot of research conducted on gas distribution networks. As the complexity and size of these networks grow, so does the leakage of gas in the distribution network. One of the most crucial factors in the production and distribution of gas is UFG or Unaccounted for Gas. The presence of UFG signifies that there is a difference between the amount of gas distributed, and the amount of gas billed. Our approach is to use information that we acquire from several specified points in the network. This information will be used to calculate the loss occurring in the network using the developed algorithm. The Algorithm can also identify the leakages at any point of the pipeline so we can easily detect faults and rectify them within minimal time, minimal efforts and minimal resources.

Keywords: FLA, fault location analysis, GDN, gas distribution network, GIS, geographic information system, NMS, network Management system, OMS, outage management system, SSGC, Sui Southern gas company, UFG, unaccounted for gas

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Authors: Nicky Wilson, Graeme Ralph

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Legacy aerostructure assembly is defined by large components, low build rates, and manual assembly methods. With an increasing demand for commercial aircraft and emerging markets such as the eVTOL (electric vertical take-off and landing) market, current methods of manufacturing are not capable of efficiently hitting these higher-rate demands. This project will look at how legacy manufacturing processes can be rate enabled by taking a holistic view of data usage, focusing on how data can be collected to enable fully integrated digital factories and supply chains. The study will focus on how data is flowed both up and down the supply chain to create a digital thread specific to each part and assembly while enabling machine learning through real-time, closed-loop feedback systems. The study will also develop a bespoke architecture to enable connectivity both within the factory and the wider PLM (product lifecycle management) system, moving away from traditional point-to-point systems used to connect IO devices to a hub and spoke architecture that will exploit report-by-exception principles. This paper outlines the key issues facing legacy aircraft manufacturers, focusing on what future manufacturing will look like from adopting Industry 4 principles. The research also defines the data architecture of a PLM system to enable the transfer and control of a digital thread within the supply chain and proposes a standardised communications protocol to enable a scalable solution to connect IO devices within a production environment. This research comes at a critical time for aerospace manufacturers, who are seeing a shift towards the integration of digital technologies within legacy production environments, while also seeing build rates continue to grow. It is vital that manufacturing processes become more efficient in order to meet these demands while also securing future work for many manufacturers.

Keywords: Industry 4, digital transformation, IoT, PLM, automated assembly, connected factories

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Authors: Farzane Sadatnia, Bahram Fathi

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Today, all public and private organizations have found that the management of the world for key information related to the activities of a staff and its main essence and philosophy, though they constitute the management information systems are very helpful in this respect the right to apply systems can save a lot in terms of economic organizations including reducing the time decision - making, improve the quality of decision making, and cost savings to bring information systems is a backup system that can never be instead of logic and human reasoning, which can be used in the series is spreading, providing resources, and provide the necessary facilities, provide better services for users, balanced budget allocation, determine strengths and weaknesses and previous plans to review the current decisions and especially the decision . Hence; in this study attempts to the effect of an information system on a review of the organization.

Keywords: information system, planning, organization, coordination, control

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Authors: Muzaffar Hussain

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Requests strategies are considered as a part of the speech acts, which are frequently used in everyday communication. Each language provides speech acts to the speakers; therefore, the selection of appropriate form seems more culture-specific rather than language. The present paper investigates the gender-based difference in the use of request strategies by native speakers of Urdu/Punjabi male and female who are learning English as a second language. The data for the present study were collected from 68 graduate students, who are learning English as an L2 in Pakistan. They were given an online close-ended questionnaire, based on Discourse Completion Test (DCT). After analyzing the data, it was found that the L1 male Urdu/Punjabi speakers were inclined to use more direct request strategies while the female Urdu/Punjabi speakers used indirect request strategies. This paper also found that in some situations female participants used more direct strategies than male participants. The present study concludes that the use of request strategies is influenced by culture, social status, and power distribution in a society.

Keywords: gender variation, request strategies, face-threatening, second language pragmatics, language competence

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Authors: Trisiladi Supriyanto

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This study aims to establish a concept of rate of profit on Islamic banking that can create economic justice and stability in the Islamic Financial Market (Banking and Capital Markets). A rate of profit that creates economic justice and stability can be achieved through its role in maintaining the stability of the financial system in which there is an equitable distribution of income and wealth. To determine the role of the rate of profit as the basis of the profit sharing system implemented in the Islamic financial system, we can see the connection of rate of profit in creating financial stability, especially in the asset-liability management of financial institutions that generate a stable net margin or the rate of profit that is not affected by the ups and downs of the market risk factors, including indirect effect on interest rates. Furthermore, Islamic financial stability can be seen from the role of the rate of profit on the stability of the Islamic financial assets value that are measured from the Islamic financial asset price volatility in the Islamic Bond Market in the Capital Market.

Keywords: economic justice, equitable distribution of income, equitable distribution of wealth, rate of profit, stability in the financial system

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Authors: Karina Guimaraes, Lilian Santos

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This study has the purpose of planning and instituting monitoring actions as a way of knowing the scenario of assistance to the patient with stoma, treated in the public health network in Brazil, from January to November of the year 2016, from the elaboration of a technical document containing the survey of the number of procedures offered and the value of the ostomy services, accredited in the Unified Health System-SUS. The purpose of this document is to improve the quality of these services in the efficient management of available financial resources, making it indispensable for the creation of strategies for the implementation and implementation of care services for people with stomata as a strategic tool in the promotion, prevention, qualification and efficiency in health care.

Keywords: health economic, management, ostomy, unified health system

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Authors: Saurabh Shukla, G. N. Pandey

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In recent times, oil exploration and monitoring in on-shore areas have gained much importance considering the fact that in India the oil import is 62 percent of the total imports. Thus, architectural model like wireless sensor network to monitor on-shore deep sea oil well is being developed to get better estimate of the oil prospects. The problem we are facing nowadays that we have very few restricted areas of oil left today. Countries like India don’t have much large areas and resources for oil and this problem with most of the countries that’s why it has become a major problem when we are talking about oil exploration in on-shore areas also the increase of oil prices has further ignited the problem. For this the use of wireless network system having relative simplicity, smallness in size and affordable cost of wireless sensor nodes permit heavy deployment in on-shore places for monitoring oil wells. Deployment of wireless sensor network in large areas will surely reduce the cost it will be very much cost effective. The objective of this system is to send real time information of oil monitoring to the regulatory and welfare authorities so that suitable action could be taken. This system architecture is composed of sensor network, processing/transmission unit and a server. This wireless sensor network system could remotely monitor the real time data of oil exploration and monitoring condition in the identified areas. For wireless sensor networks, the systems are wireless, have scarce power, are real-time, utilize sensors and actuators as interfaces, have dynamically changing sets of resources, aggregate behaviour is important and location is critical. In this system a communication is done between the server and remotely placed sensors. The server gives the real time oil exploration and monitoring conditions to the welfare authorities.

Keywords: sensor, wireless sensor network, oil, sensor, on-shore level

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Authors: Subrato Saha, Yun-Hyun Cho

Abstract:

This paper presents the design process of a high performance 3-phase 3.7 kW 2-pole line start permanent magnet synchronous motor for pumping system. A method was proposed to study the starting torque characteristics considering line start with high inertia load. A d-q model including cage was built to study the synchronization capability. Time-stepping finite element method analysis was utilized to accurately predict the dynamic and transient performance, efficiency, starting current, speed curve and, etc. Considering the load torque of pumps during starting stage, the rotor bar was designed with minimum demagnetization of permanent magnet caused by huge starting current.

Keywords: LSPM, starting analysis, demagnetization, FEA, pumping system

Procedia PDF Downloads 462

Authors: Joshua van Staden, Dane Brown, Karen Bradshaw

Abstract:

Gun violence is a significant problem in modern-day society. Early detection of carried handguns through closed-circuit television (CCTV) can aid in preventing potential gun violence. However, CCTV operators have a limited attention span. Machine learning approaches to automating the detection of dangerous gun carriers provide a way to aid CCTV operators in identifying these individuals. This study provides insight into the relationship between human key points extracted using human pose estimation (HPE) and their intention to fire a weapon. We examine the feature importance of each keypoint and their correlations. We use principal component analysis (PCA) to reduce the feature space and optimize detection. Finally, we run a set of classifiers to determine what form of classifier performs well on this data. We find that hips, shoulders, and knees tend to be crucial aspects of the human pose when making these predictions. Furthermore, the horizontal position plays a larger role than the vertical position. Of the 66 key points, nine principal components could be used to make nonlinear classifications with 86% accuracy. Furthermore, linear classifications could be done with 85% accuracy, showing that there is a degree of linearity in the data.

Keywords: feature engineering, human pose, machine learning, security

Procedia PDF Downloads 81

Authors: Zhi Liu, Xian Peng, Monika Domanska, Lingyun Kang, Sannyuya Liu

Abstract:

Massive Open education has become increasingly popular among worldwide learners. An increasing number of course reviews are being generated in Massive Open Online Course (MOOC) platform, which offers an interactive feedback channel for learners to express opinions and feelings in learning. These reviews typically contain subjective emotion and topic information towards the courses. However, it is time-consuming to artificially detect these opinions. In this paper, we propose an emotion-oriented topic detection model to automatically detect the students’ opinioned aspects in course reviews. The known overall emotion orientation and emotional words in each review are used to guide the joint probabilistic modeling of emotion and aspects in reviews. Through the experiment on real-life review data, it is verified that the distribution of course-emotion-aspect can be calculated to capture the most significant opinioned topics in each course unit. This proposed technique helps in conducting intelligent learning analytics for teachers to improve pedagogies and for developers to promote user experiences.

Keywords: Massive Open Online Course (MOOC), course reviews, topic model, emotion recognition, topical aspects

Procedia PDF Downloads 251

Authors: G. Rajeshwari, V. D. M. Jabez Daniel

Abstract:

Radio Frequency Identification systems are used for automated identification in various applications such as automobiles, health care and security. It is also called as the automated data collection technology. RFID readers are placed in any area to scan large number of tags to cover a wide distance. The placement of the RFID elements may result in several types of collisions. A major challenge in RFID system is collision avoidance. In the previous works the collision was avoided by using algorithms such as ALOHA and tree algorithm. This work proposes collision reduction and increased throughput through reading enhancement method with tree algorithm. The reading enhancement is done by improving interrogation procedure and increasing the data handling capacity of RFID reader with parallel processing. The work is simulated using Xilinx ISE 14.5 verilog language. By implementing this in the RFID system, we can able to achieve high throughput and avoid collision in the reader at a same instant of time. The overall system efficiency will be increased by implementing this.

Keywords: antenna, anti-collision protocols, data management system, reader, reading enhancement, tag

Procedia PDF Downloads 289

Authors: Seyong Jeong, Jinmo Park, Jinhyoun Park, Boram Kim, Kyoungsoo Ahn

Abstract:

Energy management in the maritime industry is being required by economics and in conformity with new legislative actions taken by the International Maritime Organization (IMO) and the European Union (EU). In response, the various performance monitoring methodologies and data collection practices have been examined by different stakeholders. While many assorted advancements in operation and technology are applicable, their adoption in the shipping industry stays small. This slow uptake can be considered due to many different barriers such as data analysis problems, misreported data, and feedback problems, etc. This study presents a conceptual design of an energy management system (EMS) and proposes the methodology to resolve the limitations (e.g., data normalization using naval architectural evaluation, management of misrepresented data, and feedback from shore to ship through management of performance analysis history). We expect this system to make even short-term charterers assess the ship performance properly and implement sustainable fleet control.

Keywords: data normalization, energy management system, naval architectural evaluation, ship performance analysis

Procedia PDF Downloads 439