Search results for: online training
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1589

Search results for: online training

1139 Application of BP Neural Network Model in Sports Aerobics Performance Evaluation

Authors: Shuhe Shao

Abstract:

This article provides partial evaluation index and its standard of sports aerobics, including the following 12 indexes: health vitality, coordination, flexibility, accuracy, pace, endurance, elasticity, self-confidence, form, control, uniformity and musicality. The three-layer BP artificial neural network model including input layer, hidden layer and output layer is established. The result shows that the model can well reflect the non-linear relationship between the performance of 12 indexes and the overall performance. The predicted value of each sample is very close to the true value, with a relative error fluctuating around of 5%, and the network training is successful. It shows that BP network has high prediction accuracy and good generalization capacity if being applied in sports aerobics performance evaluation after effective training.

Keywords: BP neural network, sports aerobics, performance, evaluation.

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1138 Machine Learning Development Audit Framework: Assessment and Inspection of Risk and Quality of Data, Model and Development Process

Authors: Jan Stodt, Christoph Reich

Abstract:

The usage of machine learning models for prediction is growing rapidly and proof that the intended requirements are met is essential. Audits are a proven method to determine whether requirements or guidelines are met. However, machine learning models have intrinsic characteristics, such as the quality of training data, that make it difficult to demonstrate the required behavior and make audits more challenging. This paper describes an ML audit framework that evaluates and reviews the risks of machine learning applications, the quality of the training data, and the machine learning model. We evaluate and demonstrate the functionality of the proposed framework by auditing an steel plate fault prediction model.

Keywords: Audit, machine learning, assessment, metrics.

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1137 Personal Information Classification Based on Deep Learning in Automatic Form Filling System

Authors: Shunzuo Wu, Xudong Luo, Yuanxiu Liao

Abstract:

Recently, the rapid development of deep learning makes artificial intelligence (AI) penetrate into many fields, replacing manual work there. In particular, AI systems also become a research focus in the field of automatic office. To meet real needs in automatic officiating, in this paper we develop an automatic form filling system. Specifically, it uses two classical neural network models and several word embedding models to classify various relevant information elicited from the Internet. When training the neural network models, we use less noisy and balanced data for training. We conduct a series of experiments to test my systems and the results show that our system can achieve better classification results.

Keywords: Personal information, deep learning, auto fill, NLP, document analysis.

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1136 Prediction the Limiting Drawing Ratio in Deep Drawing Process by Back Propagation Artificial Neural Network

Authors: H.Mohammadi Majd, M.Jalali Azizpour, M. Goodarzi

Abstract:

In this paper back-propagation artificial neural network (BPANN) with Levenberg–Marquardt algorithm is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found.

Keywords: BPANN, deep drawing, prediction, limiting drawingratio (LDR), Levenberg–Marquardt algorithm

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1135 When Psychology Meets Ecology: Cognitive Flexibility for Quarry Rehabilitation

Authors: J. Fenianos, C. Khater, D. Brouillet

Abstract:

Ecological projects are often faced with reluctance from local communities hosting the project, especially when this project involves variation from preset ideas or classical practices. This paper aims at appreciating the contribution of environmental psychology through cognitive flexibility exercises to improve the acceptability of local communities in adopting more ecological rehabilitation scenarios. The study is based on a quarry site located in Bekaa- Lebanon. Four groups were considered with different levels of involvement, as follows: Group 1 is Training (T) – 50 hours of on-site training over 8 months, Group 2 is Awareness (A) – 2 hours of awareness raising session, Group 3 is Flexibility (F) – 2 hours of flexibility exercises and Group 4 is the Control (C). The results show that individuals in Group 3 (F) who followed flexibility sessions accept comparably the ecological rehabilitation option over the more classical one. This is also the case for the people in Group 1 (T) who followed a more time-demanding “on-site training”. Another experience was conducted on a second quarry site combining flexibility with awareness-raising. This research confirms that it is possible to reduce resistance to change thanks to a limited in-time intervention using cognitive flexibility. This methodological approach could be transferable to other environmental problems involving local communities and changes in preset perceptions.

Keywords: Acceptability, ecological restoration, environmental psychology, Lebanon, local communities, resistance to change.

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1134 Endogenous Fantasy – Based Serious Games: Intrinsic Motivation and Learning

Authors: Robert F. Kenny, Glenda A. Gunter

Abstract:

Current technological advances pale in comparison to the changes in social behaviors and 'sense of place' that is being empowered since the Internet made it on the scene. Today-s students view the Internet as both a source of entertainment and an educational tool. The development of virtual environments is a conceptual framework that needs to be addressed by educators and it is important that they become familiar with who these virtual learners are and how they are motivated to learn. Massively multiplayer online role playing games (MMORPGs), if well designed, could become the vehicle of choice to deliver learning content. We suggest that these games, in order to accomplish these goals, must begin with well-established instructional design principles that are co-aligned with established principles of video game design. And have the opportunity to provide an instructional model of significant prescriptive power. The authors believe that game designers need to take advantage of the natural motivation player-learners have for playing games by developing them in such a way so as to promote, intrinsic motivation, content learning, transfer of knowledge, and naturalization.

Keywords: serious games, endogenous fantasy, intrinsic motivation, online learning.

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1133 Inductive Grammar, Student-Centered Reading, and Interactive Poetry: The Effects of Teaching English with Fun in Schools of Two Villages in Lebanon

Authors: Talar Agopian

Abstract:

Teaching English as a Second Language (ESL) is a common practice in many Lebanese schools. However, ESL teaching is done in traditional ways. Methods such as constructivism are seldom used, especially in villages. Here lies the significance of this research which joins constructivism and Piaget’s theory of cognitive development in ESL classes in Lebanese villages. The purpose of the present study is to explore the effects of applying constructivist student-centered strategies in teaching grammar, reading comprehension, and poetry on students in elementary ESL classes in two villages in Lebanon, Zefta in South Lebanon and Boqaata in Mount Lebanon. 20 English teachers participated in a training titled “Teaching English with Fun”, which focused on strategies that create a student-centered class where active learning takes place and there is increased learner engagement and autonomy. The training covered three main areas in teaching English: grammar, reading comprehension, and poetry. After participating in the training, the teachers applied the new strategies and methods in their ESL classes. The methodology comprised two phases: in phase one, practice-based research was conducted as the teachers attended the training and applied the constructivist strategies in their respective ESL classes. Phase two included the reflections of the teachers on the effects of the application of constructivist strategies. The results revealed the educational benefits of constructivist student-centered strategies; the students of teachers who applied these strategies showed improved engagement, positive attitudes towards poetry, increased motivation, and a better sense of autonomy. Future research is required in applying constructivist methods in the areas of writing, spelling, and vocabulary in ESL classrooms of Lebanese villages.

Keywords: Active learning, constructivism, learner engagement, student-centered strategies.

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1132 Social Media: The Major Trigger of Online and Offline Political Activism

Authors: Chan Eang Teng, Tang Mui Joo

Abstract:

With the viral factor on social media, the sense of persuasion is generated by repetition and popularity. When users’ interest is captured, political awareness increases to spark political enthusiasm, but, the level of user’s political participation and political attitude of those active users is still questionable. An online survey on 250 youth and in-depth interview on two politicians are conducted to answer the main question in this paper. The result shows that Facebook significantly increases political awareness among youths. Social media may not be the major trigger to political activism among youths as most respondents opined that they would still vote without Facebook. Other factors could be political campaigning, political climate, age, peer pressure or others. Finding also shows that majority of respondents did not participate in online political debates or political groups. Many also wondered if the social media was the main power switch that triggers the political influx among young voters. The research finding is significant to understand how the new media, Facebook, has reshaped the political landscape in Malaysia, creating the Social Media Election that changed the rules of the political game. However, research finding does not support the ideal notion that the social media is the major trigger to youth’s political activism. This research outcome has exposed the flaws of the Social Media Election. It has revealed the less optimistic side of youth political activism. Unfortunately, results fall short of the idealistic belief that the social media have given rise to political activism among youths in the 13th General Election in Malaysia. The research outcome also highlights an important lesson for the democratic discourse of Malaysia which is making informed and educated decisions takes more commitment, proactive and objective attitude.

Keywords: Social media, political participation, political activism, democracy, political communication.

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1131 Arabic Character Recognition Using Regression Curves with the Expectation Maximization Algorithm

Authors: Abdullah A. AlShaher

Abstract:

In this paper, we demonstrate how regression curves can be used to recognize 2D non-rigid handwritten shapes. Each shape is represented by a set of non-overlapping uniformly distributed landmarks. The underlying models utilize 2nd order of polynomials to model shapes within a training set. To estimate the regression models, we need to extract the required coefficients which describe the variations for a set of shape class. Hence, a least square method is used to estimate such modes. We then proceed by training these coefficients using the apparatus Expectation Maximization algorithm. Recognition is carried out by finding the least error landmarks displacement with respect to the model curves. Handwritten isolated Arabic characters are used to evaluate our approach.

Keywords: Shape recognition, Arabic handwritten characters, regression curves, expectation maximization algorithm.

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1130 Improved Torque Control of Electrical Load Simulator with Parameters and State Estimation

Authors: Nasim Ullah, Shaoping Wang

Abstract:

ELS is an important ground based hardware in the loop simulator used for aerodynamics torque loading experiments of the actuators under test. This work focuses on improvement of the transient response of torque controller with parameters uncertainty of Electrical Load Simulator (ELS).The parameters of load simulator are estimated online and the model is updated, eliminating the model error and improving the steady state torque tracking response of torque controller. To improve the Transient control performance the gain of robust term of SMC is updated online using fuzzy logic system based on the amount of uncertainty in parameters of load simulator. The states of load simulator which cannot be measured directly are estimated using luenberger observer with update of new estimated parameters. The stability of the control scheme is verified using Lyapunov theorem. The validity of proposed control scheme is verified using simulations.

Keywords: ELS, Observer, Transient Performance, SMC, Extra Torque, Fuzzy Logic.

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1129 Free Fatty Acid Assessment of Crude Palm Oil Using a Non-Destructive Approach

Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim, Rashidah Ghazali, Noramli Abdul Razak

Abstract:

Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of prediction models has facilitated the estimation process in recent years. In this study, 110 crude palm oil (CPO) samples were used to build a free fatty acid (FFA) prediction model. 60% of the collected data were used for training purposes and the remaining 40% used for testing. The visible peaks on the NIR spectrum were at 1725 nm and 1760 nm, indicating the existence of the first overtone of C-H bands. Principal component regression (PCR) was applied to the data in order to build this mathematical prediction model. The optimal number of principal components was 10. The results showed R2=0.7147 for the training set and R2=0.6404 for the testing set.

Keywords: Palm oil, fatty acid, NIRS, regression.

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1128 The Net as a Living Experience of Distance Motherhood within Italian Culture

Authors: C. Papapicco

Abstract:

Motherhood is an existential human relationship that lasts for the whole life and is always interwoven with subjectivity and culture. As a result of the brain drain, the motherhood becomes motherhood at distance. Starting from the hypothesis that re-signification of the mother at distance practices is culturally relevant; the research aims to understand the experience of mother at a distance in order to extrapolate the strategies of management of the empty nest. Specifically, the research aims to evaluate the experience of a brain drain’s mother, who created a blog that intends to take care of other parents at a distance. Actually, the blog is the only artifact symbol of the Italian culture of motherhood at distance. In the research, a Netnographic Analysis of the blog mammedicervelliinfuga.com is offered with the aim of understanding if the online world becomes an opportunity to manage the role of mother at a distance. A narrative interview with the blog creator was conducted and then the texts were analyzed by means of a Diatextual Analysis approach. It emerged that the migration projects of talented children take on different meanings and representations for parents. Thus, it is shown that the blog becomes a new form of understanding and practicing motherhood at a distance.

Keywords: Brain drain, diatextual analysis, distance motherhood blog, online and offline narrations.

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1127 Analysis and Design of Security Oriented Communication System

Authors: Jiří Barta

Abstract:

The paper deals with results of a project “Interoperability Workplaces to Support Teaching of Security Management in a Computer Network". This project is focused on the perspectives and possibilities of "new approaches" to education, training and crisis communication of rescue teams in the Czech Republic. It means that common technologies considering new perspectives are used to educate selected members of crisis management. The main part concentrates on possibilities of application of new technology and computer-aided tools to education and training of Integrated Rescue System teams.This project uses the COST principle for the creation of specialized centers and for all communication between these workplaces.

Keywords: Communication of Crisis Management, Information System, Interoperability, specializedcenter, Security Oriented Information System.

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1126 A Critical Social Research Perspective on Self-Directed Learning and Information Technology Practitioners

Authors: Roelien Goede

Abstract:

Information systems practitioners are frequently required to master new technology, often without the aid of formal training. They require the skill to manage their own learning and, when this skill is developed in their formal training, their adaptability to new technology may be improved. Self- directed learning is the ability of the learner to manage his or her own learning experience with some guidance from a facilitator. Self-directed learning skills are best improved when practiced. This paper reflects on a critical social research project to improve the self-directed learning skills of fourth year Information Systems students. Critical social research differs from other research paradigms in that the researcher is viewed as the agent of change to achieve the desired outcome in the problem situation.

Keywords: Action Research, Critical Social Research, Information Systems Education, Self-directed Learning.

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1125 Parameter Sensitivity Analysis of Artificial Neural Network for Predicting Water Turbidity

Authors: Chia-Ling Chang, Chung-Sheng Liao

Abstract:

The present study focuses on the discussion over the parameter of Artificial Neural Network (ANN). Sensitivity analysis is applied to assess the effect of the parameters of ANN on the prediction of turbidity of raw water in the water treatment plant. The result shows that transfer function of hidden layer is a critical parameter of ANN. When the transfer function changes, the reliability of prediction of water turbidity is greatly different. Moreover, the estimated water turbidity is less sensitive to training times and learning velocity than the number of neurons in the hidden layer. Therefore, it is important to select an appropriate transfer function and suitable number of neurons in the hidden layer in the process of parameter training and validation.

Keywords: Artificial Neural Network (ANN), sensitivity analysis, turbidity.

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1124 E-Learning Network Support Services: A Comparative Case Study of Australian and United States Universities

Authors: Sayed Hadi Sadeghi

Abstract:

This research study examines the current state of support services for e-network practice in an Australian and an American university. It identifies information that will be of assistance to Australian and American universities to improve their existing online programs. The study investigated the two universities using a quantitative methodological approach. Participants were students, lecturers and admins of universities engaged with online courses and learning management systems. The support services for e-network practice variables, namely academic support services, administrative support and technical support, were investigated for e-practice. Evaluations of e-network support service and its sub factors were above average and excellent in both countries, although the American admins and lecturers tended to evaluate this factor higher than others did. Support practice was evaluated higher by all participants of an American university than by Australians. One explanation for the results may be that most suppliers of the Australian university e-learning system were from eastern Asian cultural backgrounds with a western networking support perspective about e-learning.

Keywords: Support services, e-network practice, Australian universities, United States universities.

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1123 Distributed Case Based Reasoning for Intelligent Tutoring System: An Agent Based Student Modeling Paradigm

Authors: O. P. Rishi, Rekha Govil, Madhavi Sinha

Abstract:

Online learning with Intelligent Tutoring System (ITS) is becoming very popular where the system models the student-s learning behavior and presents to the student the learning material (content, questions-answers, assignments) accordingly. In today-s distributed computing environment, the tutoring system can take advantage of networking to utilize the model for a student for students from other similar groups. In the present paper we present a methodology where using Case Based Reasoning (CBR), ITS provides student modeling for online learning in a distributed environment with the help of agents. The paper describes the approach, the architecture, and the agent characteristics for such system. This concept can be deployed to develop ITS where the tutor can author and the students can learn locally whereas the ITS can model the students- learning globally in a distributed environment. The advantage of such an approach is that both the learning material (domain knowledge) and student model can be globally distributed thus enhancing the efficiency of ITS with reducing the bandwidth requirement and complexity of the system.

Keywords: CBR, ITS, student modeling, distributed system, intelligent agent.

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1122 Enabling Automated Deployment for Cluster Computing in Distributed PC Classrooms

Authors: Shuen-Tai Wang, Ying-Chuan Chen, Hsi-Ya Chang

Abstract:

The rapid improvement of the microprocessor and network has made it possible for the PC cluster to compete with conventional supercomputers. Lots of high throughput type of applications can be satisfied by using the current desktop PCs, especially for those in PC classrooms, and leave the supercomputers for the demands from large scale high performance parallel computations. This paper presents our development on enabling an automated deployment mechanism for cluster computing to utilize the computing power of PCs such as reside in PC classroom. After well deployment, these PCs can be transformed into a pre-configured cluster computing resource immediately without touching the existing education/training environment installed on these PCs. Thus, the training activities will not be affected by this additional activity to harvest idle computing cycles. The time and manpower required to build and manage a computing platform in geographically distributed PC classrooms also can be reduced by this development.

Keywords: PC cluster, automated deployment, cluster computing, PC classroom.

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1121 The Announcer Trainee Satisfaction by National Broadcasting and Telecommunications Commission of Thailand

Authors: Nareenad Panbun

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The objective is to study the knowledge utilization from the participants of the announcer training program by National Broadcasting and Telecommunications Commission (NBTC). This study is a quantitative research based on surveys and self-answering questionnaires. The population of this study is 100 participants randomly chosen by non-probability sampling method. The results have shown that most of the participants were satisfied with the topics of general knowledge about the broadcasting and television business for 37 people representing 37%, followed by the topics of broadcasting techniques. The legal issues, consumer rights, television business ethics, and credibility of the media are, in addition to the media's role and responsibilities in society, the use of language for successful communication. Therefore, the communication language skills are the most important for all of the trainees and will also build up the image of the broadcasting center.

Keywords: Announcer training program, participant, requirements announced, theory of utilization.

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1120 An Immersive Serious Game for Firefighting and Evacuation Training in Healthcare Facilities

Authors: Anass Rahouti, Guillaume Salze, Ruggiero Lovreglio, Sélim Datoussaïd

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In healthcare facilities, training the staff for firefighting and evacuation in real buildings is very challenging due to the presence of a vulnerable population in such an environment. In a standard environment, traditional approaches, such as fire drills, are often used to train the occupants and provide them with information about fire safety procedures. However, those traditional approaches may be inappropriate for a vulnerable population and can be inefficient from an educational viewpoint as it is impossible to expose the occupants to scenarios similar to a real emergency. Immersive serious games could be used as an alternative to traditional approaches to overcome their limitations. Serious games are already being used in different safety domains such as fires, earthquakes and terror attacks for several building types (e.g., office buildings, train stations, tunnels, etc.). In this study, we developed an immersive serious game to improve the fire safety skills of staff in healthcare facilities. An accurate representation of the healthcare environment was built in Unity3D by including visual and audio stimuli inspired from those employed in commercial action games. The serious game is organised in three levels. In each of them, the trainee is presented with a specific fire emergency and s/he can perform protective actions (e.g., firefighting, helping non-ambulant occupants, etc.) or s/he can ignore the opportunity for action and continue the evacuation. In this paper, we describe all the steps required to develop such a prototype, as well as the key questions that need to be answered, to develop a serious game for firefighting and evacuation in healthcare facilities.

Keywords: Fire Safety, healthcare, serious game, training.

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1119 The Influence of Fashion Bloggers on the Pre-Purchase Decision for Online Fashion Products among Generation Y Female Malaysian Consumers

Authors: Mohd Zaimmudin Mohd Zain, Patsy Perry, Lee Quinn

Abstract:

This study explores how fashion consumers are influenced by fashion bloggers towards pre-purchase decision for online fashion products in a non-Western context. Malaysians rank among the world’s most avid online shoppers, with apparel the third most popular purchase category. However, extant research on fashion blogging focuses on the developed Western market context. Numerous international fashion retailers have entered the Malaysian market from luxury to fast fashion segments of the market; however Malaysian fashion consumers must balance religious and social norms for modesty with their dress style and adoption of fashion trends. Consumers increasingly mix and match Islamic and Western elements of dress to create new styles enabling them to follow Western fashion trends whilst paying respect to social and religious norms. Social media have revolutionised the way that consumers can search for and find information about fashion products. For online fashion brands with no physical presence, social media provide a means of discovery for consumers. By allowing the creation and exchange of user-generated content (UGC) online, they provide a public forum that gives individual consumers their own voices, as well as access to product information that facilitates their purchase decisions. Social media empower consumers and brands have important roles in facilitating conversations among consumers and themselves, to help consumers connect with them and one another. Fashion blogs have become an important fashion information sources. By sharing their personal style and inspiring their followers with what they wear on popular social media platforms such as Instagram, fashion bloggers have become fashion opinion leaders. By creating UGC to spread useful information to their followers, they influence the pre-purchase decision. Hence, successful Western fashion bloggers such as Chiara Ferragni may earn millions of US dollars every year, and some have created their own fashion ranges and beauty products, become judges in fashion reality shows, won awards, and collaborated with high street and luxury brands. As fashion blogging has become more established worldwide, increasing numbers of fashion bloggers have emerged from non-Western backgrounds to promote Islamic fashion styles, such as Hassanah El-Yacoubi and Dian Pelangi. This study adopts a qualitative approach using netnographic content analysis of consumer comments on two famous Malaysian fashion bloggers’ Instagram accounts during January-March 2016 and qualitative interviews with 16 Malaysian Generation Y fashion consumers during September-October 2016. Netnography adapts ethnographic techniques to the study of online communities or computer-mediated communications. Template analysis of the data involved coding comments according to the theoretical framework, which was developed from the literature review. Initial data analysis shows the strong influence of Malaysian fashion bloggers on their followers in terms of lifestyle and morals as well as fashion style. Followers were guided towards the mix and match trend of dress with Western and Islamic elements, for example, showing how vivid colours or accessories could be worked into an outfit whilst still respecting social and religious norms. The blogger’s Instagram account is a form of online community where followers can communicate and gain guidance and support from other followers, as well as from the blogger.

Keywords: Fashion bloggers, Malaysia, qualitative, social media.

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1118 Online Monitoring Rheological Property of Polymer Melt during Injection Molding

Authors: Chung-Chih Lin, Chien-Liang Wu

Abstract:

The detection of the polymer melt state during manufacture process is regarded as an efficient way to control the molded part quality in advance. Online monitoring rheological property of polymer melt during processing procedure provides an approach to understand the melt state immediately. Rheological property reflects the polymer melt state at different processing parameters and is very important in injection molding process especially. An approach that demonstrates how to calculate rheological property of polymer melt through in-process measurement, using injection molding as an example, is proposed in this study. The system consists of two sensors and a data acquisition module can process the measured data, which are used for the calculation of rheological properties of polymer melt. The rheological properties of polymer melt discussed in this study include shear rate and viscosity which are investigated with respect to injection speed and melt temperature. The results show that the effect of injection speed on the rheological properties is apparent, especially for high melt temperature and should be considered for precision molding process.

Keywords: Injection molding, melt viscosity, shear rate, monitoring.

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1117 A Novel Estimation Method for Integer Frequency Offset in Wireless OFDM Systems

Authors: Taeung Yoon, Youngpo Lee, Chonghan Song, Na Young Ha, Seokho Yoon

Abstract:

Ren et al. presented an efficient carrier frequency offset (CFO) estimation method for orthogonal frequency division multiplexing (OFDM), which has an estimation range as large as the bandwidth of the OFDM signal and achieves high accuracy without any constraint on the structure of the training sequence. However, its detection probability of the integer frequency offset (IFO) rapidly varies according to the fractional frequency offset (FFO) change. In this paper, we first analyze the Ren-s method and define two criteria suitable for detection of IFO. Then, we propose a novel method for the IFO estimation based on the maximum-likelihood (ML) principle and the detection criteria defined in this paper. The simulation results demonstrate that the proposed method outperforms the Ren-s method in terms of the IFO detection probability irrespective of a value of the FFO.

Keywords: Orthogonal frequency division multiplexing, integer frequency offset, estimation, training symbol

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1116 NEAR: Visualizing Information Relations in Multimedia Repository A•VI•RE

Authors: Qian, C. Z., Chen, V. Y., R. F. Woodbury

Abstract:

This paper describes the NEAR (Navigating Exhibitions, Annotations and Resources) panel, a novel interactive visualization technique designed to help people navigate and interpret groups of resources, exhibitions and annotations by revealing hidden relations such as similarities and references. NEAR is implemented on A•VI•RE, an extended online information repository. A•VI•RE supports a semi-structured collection of exhibitions containing various resources and annotations. Users are encouraged to contribute, share, annotate and interpret resources in the system by building their own exhibitions and annotations. However, it is hard to navigate smoothly and efficiently in A•VI•RE because of its high capacity and complexity. We present a visual panel that implements new navigation and communication approaches that support discovery of implied relations. By quickly scanning and interacting with NEAR, users can see not only implied relations but also potential connections among different data elements. NEAR was tested by several users in the A•VI•RE system and shown to be a supportive navigation tool. In the paper, we further analyze the design, report the evaluation and consider its usage in other applications.

Keywords: measure similarity, trace reference, inherentrelation, information visualization, online multimedia repository

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1115 Verification and Validation of Simulated Process Models of KALBR-SIM Training Simulator

Authors: T. Jayanthi, K. Velusamy, H. Seetha, S. A. V. Satya Murty

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Verification and Validation of Simulated Process Model is the most important phase of the simulator life cycle. Evaluation of simulated process models based on Verification and Validation techniques checks the closeness of each component model (in a simulated network) with the real system/process with respect to dynamic behaviour under steady state and transient conditions. The process of Verification and Validation helps in qualifying the process simulator for the intended purpose whether it is for providing comprehensive training or design verification. In general, model verification is carried out by comparison of simulated component characteristics with the original requirement to ensure that each step in the model development process completely incorporates all the design requirements. Validation testing is performed by comparing the simulated process parameters to the actual plant process parameters either in standalone mode or integrated mode. A Full Scope Replica Operator Training Simulator for PFBR - Prototype Fast Breeder Reactor has been developed at IGCAR, Kalpakkam, INDIA named KALBR-SIM (Kalpakkam Breeder Reactor Simulator) where in the main participants are engineers/experts belonging to Modeling Team, Process Design and Instrumentation & Control design team. This paper discusses about the Verification and Validation process in general, the evaluation procedure adopted for PFBR operator training Simulator, the methodology followed for verifying the models, the reference documents and standards used etc. It details out the importance of internal validation by design experts, subsequent validation by external agency consisting of experts from various fields, model improvement by tuning based on expert’s comments, final qualification of the simulator for the intended purpose and the difficulties faced while co-coordinating various activities.

Keywords: Verification and Validation (V&V), Prototype Fast Breeder Reactor (PFBR), Kalpakkam Breeder Reactor Simulator (KALBR-SIM), Steady State, Transient State.

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1114 Humanoid Personalized Avatar Through Multiple Natural Language Processing

Authors: Jin Hou, Xia Wang, Fang Xu, Viet Dung Nguyen, Ling Wu

Abstract:

There has been a growing interest in implementing humanoid avatars in networked virtual environment. However, most existing avatar communication systems do not take avatars- social backgrounds into consideration. This paper proposes a novel humanoid avatar animation system to represent personalities and facial emotions of avatars based on culture, profession, mood, age, taste, and so forth. We extract semantic keywords from the input text through natural language processing, and then the animations of personalized avatars are retrieved and displayed according to the order of the keywords. Our primary work is focused on giving avatars runtime instruction from multiple natural languages. Experiments with Chinese, Japanese and English input based on the prototype show that interactive avatar animations can be displayed in real time and be made available online. This system provides a more natural and interesting means of human communication, and therefore is expected to be used for cross-cultural communication, multiuser online games, and other entertainment applications.

Keywords: personalized avatar, mutiple natural luanguage processing, social backgrounds, anmimation, human computer interaction

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1113 A Conversation about Inclusive Education: Revelations from Namibian Primary School Teachers

Authors: M. D. Nghiteke, A. Mji, G. T. Molepo

Abstract:

Inclusive education stems from a philosophy and vision, which argues that all children should learn together at school. It is not only about treating all pupils in the same way. It is also about allowing all children to attend school without any restrictions. Ten primary school teachers in a circuit in Namibia volunteered to participate in face-to-face interviews about inclusive education. The teachers responded to three questions about their (i) understanding of inclusive education; (ii) whether inclusive education was implemented in primary schools; and (iii) whether they were able to work with learners with special needs. Findings indicated that teachers understood what inclusive education entailed; felt that inclusive education was not implemented in their primary schools, and they were unable to work with learners with special needs in their classrooms. Further, the teachers identified training and resources as important components of inclusive education. It is recommended that education authorities should perhaps verify the findings reported here as well as ensure that the concerns raised by the teachers are addressed.

Keywords: Classrooms and schools, inclusive education, resources, training.

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1112 Detection of Moving Images Using Neural Network

Authors: P. Latha, L. Ganesan, N. Ramaraj, P. V. Hari Venkatesh

Abstract:

Motion detection is a basic operation in the selection of significant segments of the video signals. For an effective Human Computer Intelligent Interaction, the computer needs to recognize the motion and track the moving object. Here an efficient neural network system is proposed for motion detection from the static background. This method mainly consists of four parts like Frame Separation, Rough Motion Detection, Network Formation and Training, Object Tracking. This paper can be used to verify real time detections in such a way that it can be used in defense applications, bio-medical applications and robotics. This can also be used for obtaining detection information related to the size, location and direction of motion of moving objects for assessment purposes. The time taken for video tracking by this Neural Network is only few seconds.

Keywords: Frame separation, Correlation Network, Neural network training, Radial Basis Function, object tracking, Motion Detection.

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1111 Contextual SenSe Model: Word Sense Disambiguation Using Sense and Sense Value of Context Surrounding the Target

Authors: Vishal Raj, Noorhan Abbas

Abstract:

Ambiguity in NLP (Natural Language Processing) refers to the ability of a word, phrase, sentence, or text to have multiple meanings. This results in various kinds of ambiguities such as lexical, syntactic, semantic, anaphoric and referential. This study is focused mainly on solving the issue of Lexical ambiguity. Word Sense Disambiguation (WSD) is an NLP technique that aims to resolve lexical ambiguity by determining the correct meaning of a word within a given context. Most WSD solutions rely on words for training and testing, but we have used lemma and Part of Speech (POS) tokens of words for training and testing. Lemma adds generality and POS adds properties of word into token. We have designed a method to create an affinity matrix to calculate the affinity between any pair of lemma_POS (a token where lemma and POS of word are joined by underscore) of given training set. Additionally, we have devised an algorithm to create the sense clusters of tokens using affinity matrix under hierarchy of POS of lemma. Furthermore, three different mechanisms to predict the sense of target word using the affinity/similarity value are devised. Each contextual token contributes to the sense of target word with some value and whichever sense gets higher value becomes the sense of target word. So, contextual tokens play a key role in creating sense clusters and predicting the sense of target word, hence, the model is named Contextual SenSe Model (CSM). CSM exhibits a noteworthy simplicity and explication lucidity in contrast to contemporary deep learning models characterized by intricacy, time-intensive processes, and challenging explication. CSM is trained on SemCor training data and evaluated on SemEval test dataset. The results indicate that despite the naivety of the method, it achieves promising results when compared to the Most Frequent Sense (MFS) model.

Keywords: Word Sense Disambiguation, WSD, Contextual SenSe Model, Most Frequent Sense, part of speech, POS, Natural Language Processing, NLP, OOV, out of vocabulary, ELMo, Embeddings from Language Model, BERT, Bidirectional Encoder Representations from Transformers, Word2Vec, lemma_POS, Algorithm.

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1110 Improvement of Ground Truth Data for Eye Location on Infrared Driver Recordings

Authors: Sorin Valcan, Mihail Găianu

Abstract:

Labeling is a very costly and time consuming process which aims to generate datasets for training neural networks in several functionalities and projects. For driver monitoring system projects, the need of labeled images has a significant impact on the budget and distribution of effort. This paper presents the modifications done to a ground truth data generation algorithm for 2D eyes location on infrared images with drivers in order to improve the quality of the data and performance of the trained neural networks. The algorithm restrictions become tougher which makes it more accurate but also less constant. The resulting dataset becomes smaller and shall not be altered by any kind of manual labels adjustment before being used in the neural networks training process. These changes resulted in a much better performance of the trained neural networks.

Keywords: Labeling automation, infrared camera, driver monitoring, eye detection, Convolutional Neural Networks.

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