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A framework for applying an intelligent agent to monitor, interpret, and report risk of online computer game addiction in children and early adolescents in Thailand

A framework for applying an intelligent agent to monitor, in...

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IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2012. In Conj. with the 8th Int. Symp.on Medical Devices and Biosensors and the 7th Int. Symp. on Biomedical and Health engineering

作者： Kongkarn, V. Sukree, S. Technopreneurship and Innovation Management Program Graduate School Chulalongkorn University Bangkok Thailand Department of Computer Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9781457721779

An intelligent agent for monitoring, interpreting, and reporting risk of online computer game addiction in children and early adolescents in Thailand was designed with the aim to help parents, clinicians, and experts recognize behaviors of young individuals who take part in computer and online gaming. The information studied includes the type of gaming, as well as the duration and frequency of play. Conversations during gaming are also reviewed, which can demonstrate rudeness, anger, and need for control of the game. Such factors are interpreted as a risk of gaming addiction in children and early adolescents, and will consequently lead to a preventive-care plan to prevent a higher level of gaming addiction. Recognition of these factors can also lead to treatment of lower rates of addiction, and can reduce errors in basic gaming addiction assessments. The present-day self-assessment works to ameliorate gaming addiction issues in children and early adolescents in Thailand Self-assessment is a passive practice, but it can work as a very powerful proactive remedy. © 2012 IEEE.

关键词： Computer games

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Artificial intelligence and successful factors for selecting product innovation development

Artificial intelligence and successful factors for selecting...

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3rd International Conference on Intelligent Systems Modelling and Simulation, ISMS 2012

作者： Klintong, Noppakorn Vadhanasindhu, Pakpachong Thawesaengskulthai, Natcha Technopreneurship and Innovation Management Program Graduate School Chulalongkorn University Bangkok Thailand Faculty of Commerce and Accountancy Chulalongkorn University Bangkok Thailand Faculty of Engineering Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9780769546681

The firm's capability to develop product innovation and successfully launch new products has been regarded as crucial determinant in sustaining a firm's competitive advantage. Firms have been faced with a complicated problem in selecting innovation development project. From review of the related studies we found two groups of capability;firm's innovative capability and firm's new product development capability together with the external competitive environment factor are the factors influence the successful development of product innovation. We also review the predictive ability of Artificial intelligence;Artificial Neural Network (ANN), Fuzzy Logic (FL), and Genetic Algorithms (GAs) and found that it is possible that they will provide a superior predictive system for use in selecting the product innovation development project. © 2012 IEEE.

关键词： Genetic algorithms

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Effect of Kapok Fibers/Recycled Rayon Wastes on Motor Oil Sorption Capacity

Effect of Kapok Fibers/Recycled Rayon Wastes on Motor Oil So...

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International Conference on Systems and Electronic engineering(ICSEE’2012);International Conference on Civil and Architectural applications (ICCAA’2012);International Conference on Advances in Electrical and Mechanical engineering(ICAEME’2012);International Conference on Business,Finance and Geography(ICBFG’2012);International Conference on Ecology,Agriculture and Chemical engineering(ICEACS’2012);International Conference on Biotechnology,Biological and Biosystems engineering(ICBBBE’2012)

作者： Panadda Kongsricharoen Darathip Pejprom Chaowalit Senanurakwarkul Sutha Khaodhiar Department of Environmental engineering Chulalongkorn University Technopreneurship and Innovation Management program Graduate School Chulalongkorn University

In this study the application of kapok as oil sorbent was investigated. The oil sorbent was prepared by mixing kapok with rayon fibers and viscose mixtures, the waste generated from the viscose fiber rayon manufacturing process. Motor oil was used in the oil sorption study. The results indicated that the sorbent, prepared from 100 % by wt of kapok fibers, 14 % by wt of viscose mixtures and 50 grams sodium sulfate, has the highest sorption capacity for motor oil. The sorbents were tested for short test (15 minutes) and long test (24 hours) according to ASTM (F726-06) standard. The sorption capacity was 28.10 and 29.29 g of motor oil/g of sorbent, respectively. After the 6 th cycle of reuse, the sorption capacity decreased to 44 %. Comparison between the prepared sorbent and PP oil sorbent showed that the prepared sorbent performance was better than commercially available PP.

关键词： cellulose sponge, kapok fiber, oil sorbent, polypropylene, rayon fiber

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Utilization of Recycled Rayon Waste-Kapok Mixture (RRWK) as a sorbent for oil removal

Utilization of Recycled Rayon Waste-Kapok Mixture (RRWK) as ...

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作者： Chaowalit Senanurakwarkul Panadda Kongsricharoen Darathip Pejprom Sutha Khaodhiar Supawan Tantayanon Technopreneurship and Innovation Management program Graduate School Chulalongkorn University Department of Environmental Engineering Chulalongkorn University Department of Chemistry Faculty of Science Chulalongkorn University Center of Petroleum and Advanced Material Chulalongkorn University Technopreneurship and Innovation Management Graduate School Chulalongkorn University

The aim of this study was to investigate the utilization of a recycled rayon waste-kapok mixture as an oil sorbent for the removal of diesel and motor oil. The oil-sorption capacity of the materials under static conditions was evaluated. The results show the high sorption capacity of the recycled rayon waste-kapok mixture for both diesel and motor oil after 15 minutes (14.30 g of oil/g of sorbent for diesel oil and 24.17 g of oil/g of sorbent for motor oil) and after 24 hours (15.30 g of oil/g of sorbent for diesel oil and 25.05 g of oil/g of sorbent for motor oil). It can be concluded that RRWK, which can be produced by utilizing industrial waste, is an effective low cost, environmentally friendly oil sorbent with comparable performance to commercial products.

关键词： Recycled rayon waste-kapok mixture, oil sorbent

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Design management Review 2014年第1期25卷

作者： Woodie Flowers Sarah Stein Greenberg Richard K. Miller Srikant M. Datar Pappalardo Professor Emeritus of mechanical engineering at the Massachusetts Institute of Technology. He helped create MIT's renowned INTRODUCTION TO DESIGN COURSE. Flowers also received national recognition in his role as host for the PBS television series Scientific American Frontiers from 1990 to 1993 and received a New England EMMY Award for a special PBS program on design. He is a member of the National Academy of Engineering a Fellow of the American Association for the Advancement of Science and of the American Society of Mechanical Engineering and has received three honorary doctorates. He is a MacVicar Faculty Fellow for extraordinary contributions to undergraduate education at MIT where he is a member of the faculty advisory committee for MITX the Massachusetts Innovation & Technology Exchange. He was also the inaugural recipient of the Woodie Flowers Award from FIRST (For Inspiration and Recognition of Science and Technology). He recently received the Edward F. Church Medal and the Spira Outstanding Design Educator Award from ASME. Currently Flowers is a director or scientific advisor for four companies. He is also national advisor and chairman of the executive advisor board for FIRST. Has been managing director of the Hasso Plattner Institute of Design at Stanford University (also known as the d.school) since 2010. Previously she worked in the innovation practice of Monitor Group in the US and India and advised multinational companies on developing innovation capabilities. Her background includes developing new products and services in a number of emerging markets in Asia and Africa. In the classroom Stein Greenberg has co‐taught the d.school's foundational class Design Thinking Bootcamp and its renowned course on design for the developing world Entrepreneurial Design for Extreme Affordability. She recently launched an experimental new program featuring short‐format “pop‐up” classes. She holds an MBA from Stanford University and a BA in history from Oberlin College. Among other pursuits she s

Being a “gracious professional” is the key to leadership, whether you’re an engineer, a scientist, or an MIT professor. As managing director of Stanford University's ***, this Renaissance woman spends her time developing “adaptive learners.” Olin College's first president (and first employee) has plenty to say about engineering—and education. Rethinking the MBA at Harvard Business School.

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Improving accuracy of authentication process via short free text using Bayesian network

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International Journal of Computer Science Issues 2012年第2 2-3期9卷 10-16页

作者： Chantan, Charoon Sinthupinyo, Sukree Rungkasiri, Tippakorn Techopreneurship and Innovation management Program Graduate School Chulalongkorn University Bangkok Thailand Department of Computer Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Faculty of Commerce and Accountancy Chulalongkorn University Bangkok Thailand

The internet security problems are a crucial threat to all users in the cyber world. One of the important problems about internet security concerned with user classification and authentication. However, there are multiple components to classify and authenticate users. The first one is using username/password and the second method is OTP or Token. This paper presents a novel method which cans Classify User via Short-text and IP Model (CUSIM) to grant or reject a user in authentication. CUSIM is a Bayesian network model which utilizes the Bayesian Inference to authenticate the user. The objective of this paper is to use the model based on conditional independent with the prior knowledge, i.e. Keystroke dynamics, location used to connect to the internet, and IP address. Finally, a numerical example is provided to illustrate the probability of incorrect authentication and use an algorithm of machine learning to test the efficiency and find out the accuracy, FAR, and FRR. The model results gave better value of accuracy, FAR, and FRR. © 2012 International Journal of Computer Science Issues.

关键词： Bayesian networks

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Artificial Intelligence and Successful Factors for Selecting Product innovation Development

Artificial Intelligence and Successful Factors for Selecting...

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International Conference on Intelligent Systems, Modelling and Simulation (ISMS)

作者： Noppakorn Klintong Pakpachong Vadhanasindhu Natcha Thawesaengskulthai Technopreneurship and Innovation Management Program Graduate School Chulalongkom University Bangkok Thailand Faculty of Commerce and Accountancy Chulalongkom University Bangkok Thailand Faculty of Engineering Chulalongkom University Bangkok Thailand

The firm's capability to develop product innovation and successfully launch new products has been regarded as crucial determinant in sustaining a firm's competitive advantage. Firms have been faced with a complicated problem in selecting innovation development project. From review of the related studies we found two groups of capability, firm's innovative capability and firm's new product development capability together with the external competitive environment factor are the factors influence the successful development of product innovation. We also review the predictive ability of Artificial intelligence, Artificial Neural Network (ANN), Fuzzy Logic (FL), and Genetic Algorithms (GAs) and found that it is possible that they will provide a superior predictive system for use in selecting the product innovation development project.

关键词： Technological innovation Artificial neural networks Fuzzy logic Product development Artificial intelligence Job shop scheduling innovation management

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Real Options approach to estimate financial benefit of advanced process control

Real Options approach to estimate financial benefit of advan...

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IEEE/SICE International Symposium on System Integration

作者： Anukoon Asawachatroj David Banjerdpongchai Pornanong Busaratragoon Technoprenuership and Innovation Management Program Graduate School Chulalongkorn University Thailand Department of Electrical Engineering Faculty of Engineering Chulalongkorn University Thailand Department of Banking and Finance Faculty of Commerce and Accountancy Chulalongkorn Business School Thailand

Benefit estimation is one of the most important parts of feasibility study of investment projects. In order to make a solid business justification in investment, the management team always quantified the benefit from the projects. Current industrial approach to estimate benefit of advanced process control (APC) is based on the conventional estimation techniques, namely, statistical analysis and payback period. Due to the chaos information and uncertainties of business environment, these conventional techniques cannot effectively provide the alternative consideration of the investment. In this paper, we develop the Real Options technique for the benefit estimation with application to APC. The Real Options technique will be employed to the Innovative Recommender System for control system project assessment tools as part of the Integrated Economic Assessment (IEA) Framework. We demonstrate the effectiveness of the proposed method to a case study of control automation project subject to business environment uncertainty.

关键词： Investments Estimation Educational institutions Economics Analytical models Pricing

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Ordinal Classification Method for the Evaluation Of Thai Non-life Insurance Companies

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International Journal of Computer Science Issues 2012年第1 1-2期9卷 362-366页

作者： Jhonpita, Phaiboon Sinthupinyo, Sukree Chaiyawat, Thitivadee Technopreneurship and Innovation Management Program Graduate School Chulalongkorn University Bangkok Thailand Department of Computer Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Statistics Faculty of Commerce and Accountancy Chulalongkorn University Bangkok Thailand

This paper proposes a use of an ordinal classifier to evaluate the financial solidity of non-life insurance companies as strong, moderate, weak, and insolvency. This study constructed an efficient classification model that can be used by regulators to evaluate the financial solidity and to determine the priority of further examination as an early warning system. The proposed model is beneficial to policy-makers to create guidelines for the solvency regulations and roles of the government in protecting the public against insolvency. © 2012 International Journal of Computer Science Issues.

关键词： Insurance

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Decision Support System using Artificial Neural Network for Managing Product innovation

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International Journal of Computer Science Issues 2012年第2 2-2期9卷 114-122页

作者： Klintong, Noppakorn Vadhanasindhu, Pakpachong Thawesaengskulthai, Natcha Technopreneurship and Innovation Management Program Graduate School Chulalongkorn University Bangkok Bangkok 10330 Thailand Faculty of Commerce and Accountancy Chulalongkorn University Bangkok Bangkok 10330 Thailand Faculty of Engineering Chulalongkorn University Bangkok Bangkok 10330 Thailand

The firm's capability to develop product innovation and successfully launch new products has been regarded as crucial determinant in sustaining a firm's competitive advantage. Firms have been faced with a complicated problem in selecting innovation development project. From review of the related studies we found two groups of capability;firm's innovative capability and firm's new product development capability together with the external competitive environment factor are the factors influence the successful development of product innovation. We use the Artificial intelligence;Artificial Neural Network (ANN), to develop the decision support system concerning the selecting of product innovation development projects and found that The ANN model provide a fast, flexible and strong predictive ability for selecting the product innovation development project. © 2012 International Journal of Computer Science Issues.

关键词： Neural networks

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