Search results for: Learning Management Tool
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5826

Search results for: Learning Management Tool

3906 Image Modeling Using Gibbs-Markov Random Field and Support Vector Machines Algorithm

Authors: Refaat M Mohamed, Ayman El-Baz, Aly A. Farag

Abstract:

This paper introduces a novel approach to estimate the clique potentials of Gibbs Markov random field (GMRF) models using the Support Vector Machines (SVM) algorithm and the Mean Field (MF) theory. The proposed approach is based on modeling the potential function associated with each clique shape of the GMRF model as a Gaussian-shaped kernel. In turn, the energy function of the GMRF will be in the form of a weighted sum of Gaussian kernels. This formulation of the GMRF model urges the use of the SVM with the Mean Field theory applied for its learning for estimating the energy function. The approach has been tested on synthetic texture images and is shown to provide satisfactory results in retrieving the synthesizing parameters.

Keywords: Image Modeling, MRF, Parameters Estimation, SVM Learning.

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3905 A Game Design Framework for Vocational Education

Authors: Heide Lukosch, Roy Van Bussel, Sebastiaan Meijer

Abstract:

Serious games have proven to be a useful instrument to engage learners and increase motivation. Nevertheless, a broadly accepted, practical instructional design approach to serious games does not exist. In this paper, we introduce the use of an instructional design model that has not been applied to serious games yet, and has some advantages compared to other design approaches. We present the case of mechanics mechatronics education to illustrate the close match with timing and role of knowledge and information that the instructional design model prescribes and how this has been translated to a rigidly structured game design. The structured approach answers the learning needs of applicable knowledge within the target group. It combines advantages of simulations with strengths of entertainment games to foster learner-s motivation in the best possible way. A prototype of the game will be evaluated along a well-respected evaluation method within an advanced test setting including test and control group.

Keywords: Serious Gaming, Simulation, Complex Learning.

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3904 Green Lean TQM Human Resource Management Practices in Malaysian Automotive Companies

Authors: Noor Azlina Mohd Salleh, Salmiah Kasolang, Ahmed Jaffar

Abstract:

Green Lean Total Quality Management (LTQM) Human Resource Management (HRM) System is a system comprises of HRM in Environmental Management System (EMS) practices which is integrated to TQM with Lean Manufacturing (LM) principles. HRM is essential especially in dealing with low motivation and less productive employees. The ultimate goal of this system is to focus on achieving total human resource development that is motivated and capable to optimize their creativity to be a part of Green and Lean TQM organization. A survey questionnaire was developed and distributed to 30 highly active automotive vendors in Malaysia and analyzed by Minitab v16 and SPSS v17. It was found out companies that are practicing Green LTQM HRM practices have generated more revenue and have RND capability. However, years of company establishment do not affect the openness of the company to adapt new initiatives that can help to improve the effectiveness of the operations. It was also found out the importance of training, communication and rewards for employees. The Green LTQM HRM practices framework model established in this study hopefully will give preliminary insight especially to companies that are still looking for system that can improve their productivity from managing human resource. This is preliminary study that combined 4 awards practices, ISO/TS16949, Toyota Production System SAEJ4000, MAJAICO Lean Production System and EMS focusing on highly active companies that have been involved in MAJAICO Program and Proton Vendor Development Program. Future study can be conducted to know the status at other industry as well as case study pertaining to this system.

Keywords: Automotive Industry, Lean Manufacturing, Operational Engineering Management, Total Quality Management. Environmental Management System.

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3903 A Software Tool Design for Cerebral Infarction of MR Images

Authors: Kyoung-Jong Park, Woong-Gi Jeon, Hee-Cheol Kim, Dong-Eog Kim, Heung-Kook Choi

Abstract:

The brain MR imaging-based clinical research and analysis system were specifically built and the development for a large-scale data was targeted. We used the general clinical data available for building large-scale data. Registration period for the selection of the lesion ROI and the region growing algorithm was used and the Mesh-warp algorithm for matching was implemented. The accuracy of the matching errors was modified individually. Also, the large ROI research data can accumulate by our developed compression method. In this way, the correctly decision criteria to the research result was suggested. The experimental groups were age, sex, MR type, patient ID and smoking which can easily be queries. The result data was visualized of the overlapped images by a color table. Its data was calculated by the statistical package. The evaluation for the utilization of this system in the chronic ischemic damage in the area has done from patients with the acute cerebral infarction. This is the cause of neurologic disability index location in the center portion of the lateral ventricle facing. The corona radiate was found in the position. Finally, the system reliability was measured both inter-user and intra-user registering correlation.

Keywords: Software tool design, Cerebral infarction, Brain MR image, Registration

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3902 Key Issues in Transfer Stage of BOT Project: Experience from China

Authors: Wang Liguang, Zhang Xueqing

Abstract:

The build-operate-transfer (BOT) project delivery system has provided effective routes to mobilize private sector funds, innovative technologies, management skills and operational efficiencies for public infrastructure development and have been widely used in China during the last 20 years. Many BOT projects in China will be smoothly transferred to the government soon and the transfer stage, which is considered as the last stage, must be studied carefully and handled well to achieve the overall success of BOT projects. There will be many issues faced by both the public sector and private sector in the transfer stage of BOT projects, including project post-assessment, technology and documents transfer, personal training and staff transition, etc. and sometimes additional legislation is needed for future operation and management of facilities. However, most previous studies focused on the bidding, financing, and building and operation stages instead of transfer stage. This research identifies nine key issues in the transfer stage of BOT projects through a comprehensive study on three cases in China, and the expert interview and expert discussion meetings are held to validate the key issues and give detail analysis. A proposed framework of transfer management is prepared based on the experiences derived and lessons drawn from the case studies and expert interview and discussions, which is expected to improve the transfer management of BOT projects in practice.

Keywords: BOT project, key issues, transfer management transfer stage.

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3901 The Necessity of Optimized Management on Surface Water Sources of Zayanderood Basin

Authors: A. Gandomkar, K. Fouladi

Abstract:

One of the efficient factors in comprehensive development of an area is to provide water sources and on the other hand the appropriate management of them. Population growth and nourishment security for such a population necessitate the achievement of constant development besides the reforming of traditional management in order to increase the profit of sources; In this case, the constant exploitation of sources for the next generations will be considered in this program. The achievement of this development without the consideration and possibility of water development will be too difficult. Zayanderood basin with 41500 areas in square kilometers contains 7 sub-basins and 20 units of hydrologic. In this basin area, from the entire environment descending, just a small part will enter into the river currents and the rest will be out of efficient usage by various ways. The most important surface current of this basin is Zayanderood River with 403 kilometers length which is originated from east slopes of Zagros mount and after draining of this basin area it will enter into Gaavkhooni pond. The existence of various sources and consumptions of water in Zayanderood basin, water transfer of the other basin areas into this basin, of course the contradiction between the upper and lower beneficiaries, the existence of worthwhile natural ecosystems such as Gaavkhooni swamp in this basin area and finally, the drought condition and lack of water in this area all necessitate the existence of comprehensive management of water sources in this central basin area of Iran as this method is a kind of management which considers the development and the management of water sources as an equilibrant way to increase the economical and social benefits. In this study, it is tried to survey the network of surface water sources of basin in upper and lower sections; at the most, according to the difficulties and deficiencies of an efficient management of water sources in this basin area, besides the difficulties of water draining and the destructive phenomenon of flood-water, the appropriate guidelines according to the region conditions are presented in order to prevent the deviation of water in upper sections and development of regions in lower sections of Zayanderood dam.

Keywords: Zayanderood Basin, Efficient Management, Hydrology Climate.

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3900 Personalized Applications for Advanced Healthcare through AI-ML and Blockchain

Authors: Anuja Vyas, Aikel Indurkhya, Hari Krishna Garg

Abstract:

Nearly 25 years have passed since the landmark publication of the Human Genome Project, yet scientists have only begun to scratch the surface of its potential benefits. To bridge this gap, a personalized genomic application has been envisioned as a transformative tool accessible to people worldwide. This innovative solution proposes an integrated framework combining blockchain technology, genome-specific applications, and data compression techniques, ensuring operations to be swift, secure, transparent, and space-efficient. The software harnesses advanced Artificial Intelligence and Machine Learning methodologies, such as neural networks, evaluation matrices, fuzzy logic, and expert systems, to analyze individual genomic data. It generates personalized reports by comparing a user's genome with a reference genome, highlighting significant differences. Blockchain technology, with its inherent security, encryption, and immutability features, is leveraged for robust data transport and storage. In addition, a 'Data Abbreviation' technique ensures that genetic data and reports occupy minimal space. This integrated approach promises to be a significant leap forward, potentially transforming human health and well-being on a global scale.

Keywords: Artificial intelligence in genomics, blockchain technology, data abbreviation, data compression, data security in genomics, data storage, expert systems, fuzzy logic, genome applications, genomic data analysis, human genome project, neural networks, personalized genomics.

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3899 Information Technology for Business Process Management in Insurance Companies

Authors: Vesna Bosilj Vukšić, Darija Ivandić Vidović, Ljubica Milanović Glavan

Abstract:

Information technology plays an irreplaceable role in introducing and improving business process orientation in a company. It enables implementation of the theoretical concept, measurement of results achieved and undertaking corrective measures aimed at improvements. Information technology is a key concept in the development and implementation of the business process management systems as it establishes a connection to business operations. Both in the literature and practice, insurance companies are often seen as highly process oriented due to the nature of their business and focus on customers. They are also considered leaders in using information technology for business process management. The research conducted aimed to investigate whether the perceived leadership status of insurance companies is well deserved, i.e. to establish the level of process orientation and explore the practice of information technology use in insurance companies in the region. The main instrument for primary data collection within this research was an electronic survey questionnaire sent to the management of insurance companies in the Republic of Croatia, Bosnia and Herzegovina, Slovenia, Serbia and Macedonia. The conducted research has shown that insurance companies have a satisfactory level of process orientation, but that there is also a huge potential for improvement, especially in the segment of information technology and its connection to business processes.

Keywords: Business processes management, process orientation, information technology, insurance companies.

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3898 An Analysis of Classification of Imbalanced Datasets by Using Synthetic Minority Over-Sampling Technique

Authors: Ghada A. Alfattni

Abstract:

Analysing unbalanced datasets is one of the challenges that practitioners in machine learning field face. However, many researches have been carried out to determine the effectiveness of the use of the synthetic minority over-sampling technique (SMOTE) to address this issue. The aim of this study was therefore to compare the effectiveness of the SMOTE over different models on unbalanced datasets. Three classification models (Logistic Regression, Support Vector Machine and Nearest Neighbour) were tested with multiple datasets, then the same datasets were oversampled by using SMOTE and applied again to the three models to compare the differences in the performances. Results of experiments show that the highest number of nearest neighbours gives lower values of error rates. 

Keywords: Imbalanced datasets, SMOTE, machine learning, logistic regression, support vector machine, nearest neighbour.

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3897 The Index of Sustainable Functionality: An Application for Measuring Sustainability

Authors: G.T. Cirella, L. Tao

Abstract:

The index of sustainable functionality (ISF) is an adaptive, multi-criteria technique that is used to measure sustainability; it is a concept that can be transposed to many regions throughout the world. An ISF application of the Southern Regional Organisation of Councils (SouthROC) in South East Queensland (SEQ) – the fastest growing region in Australia – indicated over a 25 year period an increase of over 10% level of functionality from 58.0% to 68.3%. The ISF of SouthROC utilised methodologies that derived from an expert panel based approach. The overall results attained an intermediate level of functionality which amounted to related concerns of economic progress and lack of social awareness. Within the region, a solid basis for future testing by way of measured changes and developed trends can be established. In this regard as management tool, the ISF record offers support for regional sustainability practice and decision making alike. This research adaptively analyses sustainability – a concept that is lacking throughout much of the academic literature and any reciprocal experimentation. This lack of knowledge base has been the emphasis of where future sustainability research can grow from and prove useful in rapidly growing regions. It is the intentions of this research to help further develop the notions of index-based quantitative sustainability.

Keywords: Environmental engineering, index of sustainable functionality, sustainability indicators, sustainable development.

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3896 Component Based Framework for Authoring and Multimedia Training in Mathematics

Authors: Ion Smeureanu, Marian Dardala, Adriana Reveiu

Abstract:

The new programming technologies allow for the creation of components which can be automatically or manually assembled to reach a new experience in knowledge understanding and mastering or in getting skills for a specific knowledge area. The project proposes an interactive framework that permits the creation, combination and utilization of components that are specific to mathematical training in high schools. The main framework-s objectives are: • authoring lessons by the teacher or the students; all they need are simple operating skills for Equation Editor (or something similar, or Latex); the rest are just drag & drop operations, inserting data into a grid, or navigating through menus • allowing sonorous presentations of mathematical texts and solving hints (easier understood by the students) • offering graphical representations of a mathematical function edited in Equation • storing of learning objects in a database • storing of predefined lessons (efficient for expressions and commands, the rest being calculations; allows a high compression) • viewing and/or modifying predefined lessons, according to the curricula The whole thing is focused on a mathematical expressions minicompiler, storing the code that will be later used for different purposes (tables, graphics, and optimisations). Programming technologies used. A Visual C# .NET implementation is proposed. New and innovative digital learning objects for mathematics will be developed; they are capable to interpret, contextualize and react depending on the architecture where they are assembled.

Keywords: Adaptor, automatic assembly learning component and user control.

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3895 AI-Based Techniques for Online Social Media Network Sentiment Analysis: A Methodical Review

Authors: A. M. John-Otumu, M. M. Rahman, O. C. Nwokonkwo, M. C. Onuoha

Abstract:

Online social media networks have long served as a primary arena for group conversations, gossip, text-based information sharing and distribution. The use of natural language processing techniques for text classification and unbiased decision making has not been far-fetched. Proper classification of these textual information in a given context has also been very difficult. As a result, a systematic review was conducted from previous literature on sentiment classification and AI-based techniques. The study was done in order to gain a better understanding of the process of designing and developing a robust and more accurate sentiment classifier that could correctly classify social media textual information of a given context between hate speech and inverted compliments with a high level of accuracy using the knowledge gain from the evaluation of different artificial intelligence techniques reviewed. The study evaluated over 250 articles from digital sources like ACM digital library, Google Scholar, and IEEE Xplore; and whittled down the number of research to 52 articles. Findings revealed that deep learning approaches such as Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), Bidirectional Encoder Representations from Transformer (BERT), and Long Short-Term Memory (LSTM) outperformed various machine learning techniques in terms of performance accuracy. A large dataset is also required to develop a robust sentiment classifier. Results also revealed that data can be obtained from places like Twitter, movie reviews, Kaggle, Stanford Sentiment Treebank (SST), and SemEval Task4 based on the required domain. The hybrid deep learning techniques like CNN+LSTM, CNN+ Gated Recurrent Unit (GRU), CNN+BERT outperformed single deep learning techniques and machine learning techniques. Python programming language outperformed Java programming language in terms of development simplicity and AI-based library functionalities. Finally, the study recommended the findings obtained for building robust sentiment classifier in the future.

Keywords: Artificial Intelligence, Natural Language Processing, Sentiment Analysis, Social Network, Text.

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3894 Optimization of Three-dimensional Electrical Performance in a Solid Oxide Fuel Cell Stack by a Neural Network

Authors: Shih-Bin Wang, Ping Yuan, Syu-Fang Liu, Ming-Jun Kuo

Abstract:

By the application of an improved back-propagation neural network (BPNN), a model of current densities for a solid oxide fuel cell (SOFC) with 10 layers is established in this study. To build the learning data of BPNN, Taguchi orthogonal array is applied to arrange the conditions of operating parameters, which totally 7 factors act as the inputs of BPNN. Also, the average current densities achieved by numerical method acts as the outputs of BPNN. Comparing with the direct solution, the learning errors for all learning data are smaller than 0.117%, and the predicting errors for 27 forecasting cases are less than 0.231%. The results show that the presented model effectively builds a mathematical algorithm to predict performance of a SOFC stack immediately in real time. Also, the calculating algorithms are applied to proceed with the optimization of the average current density for a SOFC stack. The operating performance window of a SOFC stack is found to be between 41137.11 and 53907.89. Furthermore, an inverse predicting model of operating parameters of a SOFC stack is developed here by the calculating algorithms of the improved BPNN, which is proved to effectively predict operating parameters to achieve a desired performance output of a SOFC stack.

Keywords: a SOFC stack, BPNN, inverse predicting model of operating parameters, optimization of the average current density

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3893 Tracing Quality Cost in a Luggage Manufacturing Industry

Authors: S. B. Jaju, R. R. Lakhe

Abstract:

Quality costs are the costs associated with preventing, finding, and correcting defective work. Since the main language of corporate management is money, quality-related costs act as means of communication between the staff of quality engineering departments and the company managers. The objective of quality engineering is to minimize the total quality cost across the life of product. Quality costs provide a benchmark against which improvement can be measured over time. It provides a rupee-based report on quality improvement efforts. It is an effective tool to identify, prioritize and select quality improvement projects. After reviewing through the literature it was noticed that a simplified methodology for data collection of quality cost in a manufacturing industry was required. The quantified standard methodology is proposed for collecting data of various elements of quality cost categories for manufacturing industry. Also in the light of research carried out so far, it is felt necessary to standardise cost elements in each of the prevention, appraisal, internal failure and external failure costs. . Here an attempt is made to standardise the various cost elements applicable to manufacturing industry and data is collected by using the proposed quantified methodology. This paper discusses the case study carried in luggage manufacturing industry.

Keywords: Quality Costs, PAF model, quantified methodology, Case study.

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3892 The Role of Social and Technical Lean Implementation in Improving Operational Performance: Insights from the Pharmaceutical Industry

Authors: M. Bernasconi, M. Grothkopp, T. Friedli

Abstract:

The objective of this paper is to examine the relationships between technical and social lean bundles as well as operational performance in the context of the pharmaceutical industry. We investigate the direct and mediating effects of the lean bundles Total Productive Maintenance (TPM), Total Quality Management (TQM), Just-In-Time (JIT), and Human Resource Management (HRM) on operational performance. Our analysis relies on 113 manufacturing facilities from the St.Gallen OPEX benchmarking database. The results show that HRM has a positive indirect effect on operational performance mediated by the technical lean bundles.

Keywords: Human resource management, operational performance, pharmaceutical industry, technical lean practices.

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3891 Causal Relation Identification Using Convolutional Neural Networks and Knowledge Based Features

Authors: Tharini N. de Silva, Xiao Zhibo, Zhao Rui, Mao Kezhi

Abstract:

Causal relation identification is a crucial task in information extraction and knowledge discovery. In this work, we present two approaches to causal relation identification. The first is a classification model trained on a set of knowledge-based features. The second is a deep learning based approach training a model using convolutional neural networks to classify causal relations. We experiment with several different convolutional neural networks (CNN) models based on previous work on relation extraction as well as our own research. Our models are able to identify both explicit and implicit causal relations as well as the direction of the causal relation. The results of our experiments show a higher accuracy than previously achieved for causal relation identification tasks.

Keywords: Causal relation identification, convolutional neural networks, natural Language Processing, Machine Learning.

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3890 Identifying and Adopting Latter Instruments Determining the Sustainable Company Competitiveness

Authors: Andrej Miklošík, Petra Horváthová, Štefan Žák

Abstract:

Nowadays companies in all sectors are looking for the sources of competitive advantages. Holistic marketing approach searches for their emergence based on the integration of all components and elements across the organization. Modern marketing sees the sources of competitive advantage in implementing the latest managerial practices, motivation, intelligent project management, knowledge management, collaborative marketing, CSR and, in the recent years, also in the business process optimization. With the use of modern tools including business process management and business process modelling the company can markedly increase its internal efficiency which can lead not only to lowering the costs but to creating the environment for optimal customer care, positive corporate culture and for origination of innovations as well. In the article the authors analyze the recent trend in this area and introduce suggestions to companies to identify and optimize the key processes that have a significant impact of the company´s competitiveness.

Keywords: business process optimization, competitive advantage, corporate social responsibility, knowledge management

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3889 Impact of Quality Assurance Mechanisms on the Work Efficiency of Staff in the Educational Space of Georgia

Authors: B. Gechbaia, K. Goletiani, G. Gabedava, N. Mikeltadze

Abstract:

At this stage, Georgia is a country which is actively involved in the European integration process, for which the primary priority is effective integration in the European education system. The modern Georgian higher education system is the process of establishing a new sociocultural reality, whose main priorities are determined by the Quality System as a continuous cycle of planning, implementation, checking and acting. Obviously, in this situation, the issue of management of education institutions comes out in the foreground, since the proper planning and implementation of personnel management processes is one of the main determinants of the company's performance. At the same time, one of the most important factors is the psychological comfort of the personnel, ensuring their protection and efficiency of stress management policy.

The purpose of this research is to determine how intensely the relationship is between the psychological comfort of the personnel and the efficiency of the quality system in the institution as the quality assurance mechanisms of educational institutions affect the stability of personnel, prevention and management of the stressful situation. The research was carried out within the framework of the Internal Grant Project «The Role of Organizational Culture in the Process of Settlement of Management of Stress and Conflict, Georgian Reality and European Experience » of the Batumi Navigation Teaching University, based on the analysis of the survey results of target groups. The small-scale research conducted by us has revealed that the introduction of quality assurance system and its active implementation increased the quality of management of Georgian educational institutions, increased the level of universal engagement in internal and external processes and as a result, it has improved the quality of education as well as social and psychological comfort indicators of the society.

Keywords: Quality assurance, effective management, stability of personnel, psychological comfort, stress management.

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3888 Problems of Lifelong Education Course in Information and Communication Technology

Authors: Hisham Md Suhadi, Faaizah Shahbodin, Jamaluddin Hashim

Abstract:

The study is the way to identify the problems that occur in organizing short course’s lifelong learning in the information and communication technology (ICT) education which are faced by the lecturer and staff at the Mara Skill Institute and Industrial Training Institute in Pahang Malaysia. The important aspects of these issues are classified to five which are selecting the courses administrative. Fifty lecturers and staff were selected as a respondent. The sample is selected by using the non-random sampling method purpose sampling. The questionnaire is used as a research instrument and divided into five main parts. All the data that gain from the questionnaire are analyzed by using the SPSS in term of mean, standard deviation and percentage. The findings showed, there are the problems occur in organizing the short course for lifelong learning in ICT education.

Keywords: Lifelong education, information and communication technology (ICT), short course, ICT education, courses administrative.

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3887 Improving the Quality of Transport Management Services with Fuzzy Signatures

Authors: Csaba I. Hencz, István Á. Harmati

Abstract:

Nowadays the significance of road transport is gradually increasing. All transport companies are working in the same external environment where the speed of transport is defined by traffic rules. The main objective is to accelerate the speed of service and it is only dependent on the individual abilities of the managing members. These operational control units make decisions quickly (in a typically experiential and/or intuitive way). For this reason, support for these decisions is an important task. Our goal is to create a decision support model based on fuzzy signatures that can assist the work of operational management automatically. If the model sets parameters properly, the management of transport could be more economical and efficient.

Keywords: Freight transport, decision support, information handling, fuzzy methods.

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3886 A Fuzzy Logic Based Model to Predict Surface Roughness of A Machined Surface in Glass Milling Operation Using CBN Grinding Tool

Authors: Ahmed A. D. Sarhan, M. Sayuti, M. Hamdi

Abstract:

Nowadays, the demand for high product quality focuses extensive attention to the quality of machined surface. The (CNC) milling machine facilities provides a wide variety of parameters set-up, making the machining process on the glass excellent in manufacturing complicated special products compared to other machining processes. However, the application of grinding process on the CNC milling machine could be an ideal solution to improve the product quality, but adopting the right machining parameters is required. In glass milling operation, several machining parameters are considered to be significant in affecting surface roughness. These parameters include the lubrication pressure, spindle speed, feed rate and depth of cut. In this research work, a fuzzy logic model is offered to predict the surface roughness of a machined surface in glass milling operation using CBN grinding tool. Four membership functions are allocated to be connected with each input of the model. The predicted results achieved via fuzzy logic model are compared to the experimental result. The result demonstrated settlement between the fuzzy model and experimental results with the 93.103% accuracy.

Keywords: CNC-machine, Glass milling, Grinding, Surface roughness, Cutting force, Fuzzy logic model.

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3885 Game based Learning to Enhance Cognitive and Physical Capabilities of Elderly People: Concepts and Requirements

Authors: Aurelie Aurilla Bechina Arntzen

Abstract:

The last decade has seen an early majority of people The last decade, the role of the of the information communication technologies has increased in improving the social and business life of people. Today, it is recognized that game could contribute to enhance virtual rehabilitation by better engaging patients. Our research study aims to develop a game based system enhancing cognitive and physical capabilities of elderly people. To this end, the project aims to develop a low cost hand held system based on existing game such as Wii, PSP, or Xbox. This paper discusses the concepts and requirements for developing such game for elderly people. Based on the requirement elicitation, we intend to develop a prototype related to sport and dance activities.

Keywords: Elderly people, Game based learning system, Health systems, rehabilitation

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3884 Determinants of R&D Outsourcing at Japanese Firms: Transaction Cost and Strategic Management Perspectives

Authors: Dai Miyamoto

Abstract:

This paper examines the factors, which determine R&D outsourcing behaviour at Japanese firms, from the viewpoints of transaction cost and strategic management, since the latter half of the 1990s. This study uses empirical analysis, which involves the application of large-sample data. The principal findings of this paper are listed below. Firms that belong to a wider corporate group are more active in executing R&D outsourcing activities. Diversification strategies such as the expansion of product and sales markets have a positive effect on the R&D outsourcing behaviour of firms. Moreover, while quantitative R&D resources have positive influences on R&D outsourcing, qualitative indices have no effect. These facts suggest that R&D outsourcing behaviour of Japanese firms are consistent with the two perspectives of transaction cost and strategic management. Specifically, a conventional corporate group network plays an important role in R&D outsourcing behaviour. Firms that execute R&D outsourcing leverage 'old' networks to construct 'new' networks and use both networks properly.

Keywords: Corporate Group Networks, R&D Outsourcing, Strategic Management Perspective, Transaction Cost Perspective.

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3883 Predictive Maintenance of Industrial Shredders: Efficient Operation through Real-Time Monitoring Using Statistical Machine Learning

Authors: Federico Pittino, Dominik Holzmann, Krithika Sayar-Chand, Stefan Moser, Sebastian Pliessnig, Thomas Arnold

Abstract:

The shredding of waste materials is a key step in the recycling process towards circular economy. Industrial shredders for waste processing operate in very harsh operating conditions, leading to the need of frequent maintenance of critical components. The maintenance optimization is particularly important also to increase the machine’s efficiency, thereby reducing the operational costs. In this work, a monitoring system has been developed and deployed on an industrial shredder located at a waste recycling plant in Austria. The machine has been monitored for several months and methods for predictive maintenance have been developed for two key components: the cutting knives and the drive belt. The large amount of collected data is leveraged by statistical machine learning techniques, thereby not requiring a very detailed knowledge of the machine or its live operating conditions. The results show that, despite the wide range of operating conditions, a reliable estimate of the optimal time for maintenance can be derived. Moreover, the trade-off between the cost of maintenance and the increase in power consumption due to the wear state of the monitored components of the machine is investigated. This work proves the benefits of real-time monitoring system for efficient operation of industrial shredders.

Keywords: predictive maintenance, circular economy, industrial shredder, cost optimization, statistical machine learning

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3882 Muscle: The Tactile Texture Designed for the Blind

Authors: Chantana Insra

Abstract:

The research objective focuses on creating a prototype media of the tactile texture of muscles for educational institutes to help visually impaired students learn massage extra learning materials further than the ordinary curriculum. This media is designed as an extra learning material. The population in this study was 30 blinded students between 4th - 6th grades who were able to read Braille language. The research was conducted during the second semester in 2012 at The Bangkok School for the Blind. The method in choosing the population in the study was purposive sampling. The methodology of the research includes collecting data related to visually impaired people, the production of the tactile texture media, human anatomy and Thai traditional massage from literature reviews and field studies. This information was used for analyzing and designing 14 tactile texture pictures presented to experts to evaluate and test the media.

Keywords: Blind, Tactile Texture, Muscle.

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3881 Future-Proofing the Workforce: A Case Study of Integrated Human Capability Frameworks to Support Business Success

Authors: P. Paliadelis, A. Jones, G. Campbell

Abstract:

This paper discusses the development of co-designed capability frameworks for two large multinational organizations led by a university department. The aim was to create evidence-based, integrated capability frameworks that could define, identify, and measure human skill capabilities independent of specific work roles. The frameworks capture and cluster human skills required in the workplace and capture their application at various levels of mastery. Identified capability gaps inform targeted learning opportunities for workers to enhance their employability skills. The paper highlights the value of this evidence-based framework development process in capturing, defining, and assessing desired human-focused capabilities for organizational growth and success.

Keywords: Capability framework, human skills, work-integrated learning, credentialing, digital badging.

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3880 Feature Based Unsupervised Intrusion Detection

Authors: Deeman Yousif Mahmood, Mohammed Abdullah Hussein

Abstract:

The goal of a network-based intrusion detection system is to classify activities of network traffics into two major categories: normal and attack (intrusive) activities. Nowadays, data mining and machine learning plays an important role in many sciences; including intrusion detection system (IDS) using both supervised and unsupervised techniques. However, one of the essential steps of data mining is feature selection that helps in improving the efficiency, performance and prediction rate of proposed approach. This paper applies unsupervised K-means clustering algorithm with information gain (IG) for feature selection and reduction to build a network intrusion detection system. For our experimental analysis, we have used the new NSL-KDD dataset, which is a modified dataset for KDDCup 1999 intrusion detection benchmark dataset. With a split of 60.0% for the training set and the remainder for the testing set, a 2 class classifications have been implemented (Normal, Attack). Weka framework which is a java based open source software consists of a collection of machine learning algorithms for data mining tasks has been used in the testing process. The experimental results show that the proposed approach is very accurate with low false positive rate and high true positive rate and it takes less learning time in comparison with using the full features of the dataset with the same algorithm.

Keywords: Information Gain (IG), Intrusion Detection System (IDS), K-means Clustering, Weka.

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3879 Emergency Health Management at a South African University

Authors: R. Tandlich, S. Hoossein, K. A. Tagwira, M. M. Marais, T. A. Ludwig, R. P. Chidziva, M. N. Munodawafa, W. M. Wrench

Abstract:

Response to the public health-related emergencies is analysed here for a rural university in South Africa. The structure of the designated emergency plan covers all the phases of the disaster management cycle. The plan contains elements of the vulnerability model and the technocratic model of emergency management. The response structures are vertically and horizontally integrated, while the planning contains elements of scenario-based and functional planning. The available number of medical professionals at the Rhodes University, along with the medical insurance rates, makes the staff and students potentially more medically vulnerable than the South African population. The main improvements of the emergency management are required in the tornado response and the information dissemination during health emergencies. The latter should involve the increased use of social media and e-mails, following the Taylor model of communication. Infrastructure must be improved in the telecommunication sector in the face of unpredictable electricity outages.

Keywords: Public health, Rural university, Taylor model of communication.

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3878 An Evaluation of ISO 9001:2008 and ISO 9001:2015 Standard Changes in Quality Management System

Authors: Filiz Ersoz, Deniz Merdin, Taner Ersoz

Abstract:

The objective of this study provides an insight into enterprises, who need to carry on their sustainability in harmony with the changing competition conditions, technology and laws, regarding the ISO 9001:2015. In the study, ISO 9001:2015, which is planned to be put in force and exists as a draft, was studied and its differences from the previous standard, ISO 9001:2008, were determined. To find out the differences, a survey was conducted among enterprises that implement a quality system. According to the findings obtained at the end of the study, it was observed that the enterprises attach importance to quality and follow the developments about quality management system, and they find the changes in the new draft document necessary.

Keywords: ISO 9001, quality, quality management system, quality revision.

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3877 Eye Tracking: Biometric Evaluations of Instructional Materials for Improved Learning

Authors: Janet Holland

Abstract:

Eye tracking is a great way to triangulate multiple data sources for deeper, more complete knowledge of how instructional materials are really being used and emotional connections made. Using sensor based biometrics provides a detailed local analysis in real time expanding our ability to collect science based data for a more comprehensive level of understanding, not previously possible, for teaching and learning. The knowledge gained will be used to make future improvements to instructional materials, tools, and interactions. The literature has been examined and a preliminary pilot test was implemented to develop a methodology for research in Instructional Design and Technology. Eye tracking now offers the addition of objective metrics obtained from eye tracking and other biometric data collection with analysis for a fresh perspective.

Keywords: Area of interest, eye tracking, biometrics, fixation, fixation count, fixation sequence, fixation time, gaze points, heat map, saccades, time to first fixation.

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