Search results for: knowledge fusion

Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Lèvy flight, situation awareness, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence.

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Authors: Dilusha Weeraddana, Ashanie Gunathillake, Samiru Gayan

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In an emergency, combining Wireless Sensor Network's data with the knowledge gathered from various other information sources and navigation algorithms, could help safely guide people to a building exit while avoiding the risky areas. This paper presents an emergency response and navigation support architecture for data gathering, knowledge manipulation, and navigational support in an emergency situation. At normal state, the system monitors the environment. When an emergency event detects, the system sends messages to first responders and immediately identifies the risky areas from safe areas to establishing escape paths. The main functionalities of the system include, gathering data from a wireless sensor network which is deployed in a multi-story indoor environment, processing it with information available in a knowledge base, and sharing the decisions made, with first responders and people in the building. The proposed architecture will act to reduce risk of losing human lives by evacuating people much faster with least congestion in an emergency environment. 

Keywords: Emergency response, Firefighters, Navigation, Wireless sensor network.

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Authors: Shahrazed Medeghri, Saad Hamzaoui, Mokhtar Zerdali

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The metallurgical grade silicon (MG-Si) is obtained from the reduction of silica (SiO₂) in an induction furnace or an electric arc furnace. Impurities inherent in reduction process also depend on the quality of the raw material used. Among the applications of the silicon, it is used as a substrate for the photovoltaic conversion of solar energy and this conversion is wider as the purity of the substrate is important. Research is being done where the purpose is looking for new methods of manufacturing and purification of silicon, as well as new materials that can be used as substrates for the photovoltaic conversion of light energy. In this research, the technique of production of silicon in an induction furnace, using a high vacuum for fusion. Diatomaceous Silica (SiO2) used is 99 mass% initial purities, the carbon used is 6N of purity and the particle size of 63μm as starting materials. The final achieved purity of the material was above 50% by mass. These results demonstrate that this method is a technically reliable, and allows obtaining a better return on the amount 50% of silicon.

Keywords: Induction, amorphous silica, carbon microstructure, silicon.

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Authors: Marina Nosik, Irina Rymanova, Sergei Sevostyanihin, Natalya Sergeeva, Alexander Sobkin

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This paper presents results of the survey regarding the awareness about HIV/AIDS among HIV-infected individuals. A questionnaire covering various aspects of HIV-infection was conducted among 110 HIV-infected individuals who attended the G.A. Zaharyan Moscow Tuberculosis Clinic, Department for treatment of TB patients with HIV. The questionnaire included questions about modes of HIV transmission and preventive measures against HIV/AIDS, as well as questions about age, gender, education and employment status. The survey revealed that the respondents in the whole had a good knowledge regarding modes of HIV transmission and preventive measures against HIV/AIDS: about 83,6% male respondents and 85,7% female respondents gave an accurate answers regarding the HIV-infection. However, the overwhelming majority of the study participants, that is, 88,5% men and 98% women, was quite ignorant about the risk of acquiring HIV through saliva and toothbrush of HIV-infected individual. Though that risk is rather insignificant, it is still biologically possible. And this gap in knowledge needs to be filled. As the study showed another point of concern was the fact, that despite the knowledge of HIV transmission risk through unprotected sex about 40% percent of HIVpositive men and 25% of HIV-positive women did not insist on using condoms with their sexual partners. These findings indicate that there are still some aspects about HIV-infection which needed to be clarified and explained through more detailed and specific educational programs.

Keywords: AIDS, HIV transmission risks, HIV misconceptions, risk behavior.

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Authors: Somruedee Pongsena

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The purpose of this study is to follow – up the graduated students of Bachelor of Science in Applied Statistics from Suan Sunandha Rajabhat University (SSRU) during the 1999 – 2012 academic years and to provide the fundamental guideline for developing the current curriculum according to Thai Qualifications Framework for Higher Education (TQF: HEd). The sample was collected from 75 graduates by interview and online questionnaire. The content covered 5 subjects were Ethics and Moral, Knowledge, Cognitive Skills, Interpersonal Skill and Responsibility, Numerical Analysis as well as Communication and Information Technology Skills. Data were analyzed by using statistical methods as percentiles, means, standard deviation, t- tests, and F- tests. The findings showed that samples were mostly female had less than 26 years old. The majority of graduates had income in the range of 10,001-20,000 Baht and experience range were 2-5 years. In addition, overall opinions from receiving knowledge to apply to work were at agree; mean score was 3.97 and standard deviation was 0.40. In terms of, the hypothesis testing’s result indicate gender only had different opinion at a significance level of 0.05.

Keywords: Follow up, Graduates, knowledge, opinion, Work performance.

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Authors: Zaihisma C. Cob, Alicia Y.C. Tang, Sharifah J. Syed Aziz

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This paper proposes a new model to support user queries on postgraduate research information at Universiti Tenaga Nasional. The ontology to be developed will contribute towards shareable and reusable domain knowledge that makes knowledge assets intelligently accessible to both people and software. This work adapts a methodology for ontology development based on the framework proposed by Uschold and King. The concepts and relations in this domain are represented in a class diagram using the Protégé software. The ontology will be used to support a menudriven query system for assisting students in searching for information related to postgraduate research at the university.

Keywords: Ontology, Protégé, postgraduate program, query system.

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Authors: Ganesan V.

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Application of Expert System in the area of agriculture would take the form of Integrated Crop Management decision aids and would encompass water management, fertilizer management, crop protection systems and identification of implements. In order to remain competitive, the modern farmer often relies on agricultural specialists and advisors to provide information for decision-making. An expert system normally composed of a knowledge base (information, heuristics, etc.), inference engine (analyzes knowledge base), and end user interface (accepting inputs, generating outputs). Software named 'CROP-9-DSS' incorporating all modern features like, graphics, photos, video clippings etc. has been developed. This package will aid as a decision support system for identification of pest and diseases with control measures, fertilizer recommendation system, water management system and identification of farm implements for leading crops of Kerala (India) namely Coconut, Rice, Cashew, Pepper, Banana, four vegetables like Amaranthus, Bhindi, Brinjal and Cucurbits. 'CROP-9-DSS' will act as an expert system to agricultural officers, scientists in the field of agriculture and extension workers for decision-making and help them in suggesting suitable recommendations.

Keywords: Diagnostic, inference engine, knowledge base and user interface.

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Authors: Jo Rhodes, Peter Lok, Zahra Sadeghinejad

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The aim of this study is to determine the impact of metacognition on top management team members and firm performance based on full team integration. A survey of 1500 small to medium enterprises (SMEs) was initiated and 140 firms were obtained in this study (with response rate of 9%). The result showed that different metacognitive abilities of managers [knowledge and experience] could enhance team decision-making and problem solving, resulting in greater firm performance. This is a significant finding for SMEs because these organisations have small teams with owner leadership and entrepreneurial orientation.

Keywords: Metacognition, behavioural integration, top management team, performance.

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Authors: Pisit Chanvarasuth

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The use of e-business in small and medium-sized enterprises (SMEs) has been recently received an enormous attention in information systems research by both academic and practitioners. With the adoption of new and efficient technologies to enhance businesses, Thai SMEs should be able to compete worldwide. Unfortunately, most of the owners are not used to new technologies. It is clear that most Thai SMEs prefer to work manually rather than electronically. This paper aims to provide a fundamental conceptual framework for E-business adoption by Thai SMEs. Rooted in Knowledge transfer model, several factors are identified, which drive and enable e-business adoption. By overlooking the benefits associated with implementing new technologies, it is difficult for Thai SMEs to perform well enough to compete globally. The paper also helps Thai SMEs to understand factors related to E-business adoption.

Keywords: E-business, SME, Adoption, Knowledge Transfer, Thailand.

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Authors: S. Divya Gnanarathinam, S. Sundaramurthy

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The tremendous increase in the population of the world creates the immediate need for the energy resources. All the people in the world need the sustainable energy resources which have low costs. Solar energy is appraised as one of the main energy resources in warm countries. The areas in the west of India like Rajasthan, Gujarat, etc. are immensely rich in solar energy resources. This paper deals with the development of dual axis solar tracker using Arduino board. Depending on the astronomical estimates of the sun from the GPS and sensor image processing outcomes, a methodology is proposed to locate the position of the sun to obtain the maximum solar energy. Based on the outcomes, the solar tracking system figures out whether to use image processing outcomes or astronomical estimates to attain the maximum efficiency of the solar panel. Finally, the experimental values obtained from the solar tracker for both the sunny and the rainy days are being tabulated.

Keywords: Dual axis solar tracker, Arduino board, LDR sensors, global positioning system.

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Authors: Othman Maklouf, Abdurazag Ghila, Saleh Gashoot, Ahmed Abdulla

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Flight management system (FMS) is a specialized computer system that automates a wide variety of in-flight tasks, reducing the workload on the flight crew to the point that modern aircraft no longer carry flight engineers or navigators. The primary function of FMS is to perform the in-flight management of the flight plan using various sensors (such as GPS and INS often backed up by radio navigation) to determine the aircraft's position. From the cockpit FMS is normally controlled through a Control Display Unit (CDU) which incorporates a small screen and keyboard or touch screen. This paper investigates the performance of GPS/ INS integration techniques in which the data fusion process is done using Kalman filtering. This will include the importance of sensors calibration as well as the alignment of the strap down inertial navigation system. The limitations of the inertial navigation systems are investigated in order to understand why INS sometimes is integrated with other navigation aids and not just operating in standalone mode. Finally, both the loosely coupled and tightly coupled configurations are analyzed for several types of situations and operational conditions.

Keywords: GPS, INS, Kalman Filter.

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Authors: Noemy Witt Ferreira, Flávio de São Paulo Filho

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Innovation, technology and knowledge are the trilogy of impact to support the challenges arising from uncertainty. Evidence showed an opportunity to ask how to manage in this environment under constant innovation. In an attempt to get a response from the field of Management Sciences, based in the Contingency Theory, a research was conducted, with phenomenological and descriptive approaches, using the Case Study Method and the usual procedures for this task involving a focus group composed of managers and employees working in the pharmaceutical field. The problem situation was raised; the state of the art was interpreted and dissected the facts. In this tasks were involved four establishments. The result indicates that these focused ventures have been managed by its founder empirically and is experimenting agility described in this work. The expectation of this study is to improve concepts for stakeholders on creativity in business.

Keywords: Administration. Innovation. Knowledge, Management Technology

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Authors: Christiana Gauci-Sciberras

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The first language (L1) could be used in foreign language teaching and learning as a pedagogical tool to scaffold new knowledge in the target language (TL) upon linguistic knowledge that the learner already has. In a bilingual context, code-switching between the two languages usually occurs in classrooms. One of the reasons for code-switching is because both languages are used for scaffolding new knowledge. This research paper aims to find out why both the L1 (Maltese) and the L2 (English) are used in the classroom of Mandarin Chinese as a foreign language (CFL) in the bilingual context of Malta. This research paper also aims to find out the learners’ perceptions of the use of a bilingual medium of instruction. Two research methods were used to collect qualitative data; semi-structured interviews with adult learners of Mandarin Chinese and lesson observations. These two research methods were used so that the data collected in the interviews would be triangulated with data collected in lesson observations. The L1 (Maltese) is the language of instruction mostly used. The teacher and the learners switch to the L2 (English) or to any other foreign language according to the need at a particular instance during the lesson.

Keywords: Chinese, bilingual, pedagogical purpose of L1 and L2, CFL acquisition.

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Authors: Rajeev Kaula

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Business rules and data warehouse are concepts and technologies that impact a wide variety of organizational tasks. In general, each area has evolved independently, impacting application development and decision-making. Generating knowledge from data warehouse is a complex process. This paper outlines an approach to ease import of information and knowledge from a data warehouse star schema through an inference class of business rules. The paper utilizes the Oracle database for illustrating the working of the concepts. The star schema structure and the business rules are stored within a relational database. The approach is explained through a prototype in Oracle-s PL/SQL Server Pages.

Keywords: Business Rules, Data warehouse, PL/SQL ServerPages, Relational model, Web Application.

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Authors: Muhammad Atif, Cang Yan

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The enhancement of low-light images is a significant area of study aimed at enhancing the quality of captured images in challenging lighting environments. Recently, methods based on Convolutional Neural Networks (CNN) have gained prominence as they offer state-of-the-art performance. However, many approaches based on CNN rely on increasing the size and complexity of the neural network. In this study, we propose an alternative method for improving low-light images using an Autoencoders-based multiscale knowledge transfer model. Our method leverages the power of three autoencoders, where the encoders of the first two autoencoders are directly connected to the decoder of the third autoencoder. Additionally, the decoder of the first two autoencoders is connected to the encoder of the third autoencoder. This architecture enables effective knowledge transfer, allowing the third autoencoder to learn and benefit from the enhanced knowledge extracted by the first two autoencoders. We further integrate the proposed model into the Pix-to-Pix GAN framework. By integrating our proposed model as the generator in the GAN framework, we aim to produce enhanced images that not only exhibit improved visual quality but also possess a more authentic and realistic appearance. These experimental results, both qualitative and quantitative, show that our method is better than the state-of-the-art methodologies.

Keywords: Low light image enhancement, deep learning, convolutional neural network, image processing.

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Authors: B. Al-Naami, N. Gharaibeh, A. AlRazzaq Kheshman

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Alzheimer is known as the loss of mental functions such as thinking, memory, and reasoning that is severe enough to interfere with a person's daily functioning. The appearance of Alzheimer Disease symptoms (AD) are resulted based on which part of the brain has a variety of infection or damage. In this case, the MRI is the best biomedical instrumentation can be ever used to discover the AD existence. Therefore, this paper proposed a fusion method to distinguish between the normal and (AD) MRIs. In this combined method around 27 MRIs collected from Jordanian Hospitals are analyzed based on the use of Low pass -morphological filters to get the extracted statistical outputs through intensity histogram to be employed by the descriptive box plot. Also, the artificial neural network (ANN) is applied to test the performance of this approach. Finally, the obtained result of t-test with confidence accuracy (95%) has compared with classification accuracy of ANN (100 %). The robust of the developed method can be considered effectively to diagnose and determine the type of AD image.

Keywords: Alzheimer disease, Brain MRI analysis, Morphological filter, Box plot, Intensity histogram, ANN.

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Authors: Emna Benmohamed, Hela Ltifi, Mounir Ben Ayed

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Bayesian Network (BN) is one of the most efficient classification methods. It is widely used in several fields (i.e., medical diagnostics, risk analysis, bioinformatics research). The BN is defined as a probabilistic graphical model that represents a formalism for reasoning under uncertainty. This classification method has a high-performance rate in the extraction of new knowledge from data. The construction of this model consists of two phases for structure learning and parameter learning. For solving this problem, the K2 algorithm is one of the representative data-driven algorithms, which is based on score and search approach. In addition, the integration of the expert's knowledge in the structure learning process allows the obtainment of the highest accuracy. In this paper, we propose a hybrid approach combining the improvement of the K2 algorithm called K2 algorithm for Parents and Children search (K2PC) and the expert-driven method for learning the structure of BN. The evaluation of the experimental results, using the well-known benchmarks, proves that our K2PC algorithm has better performance in terms of correct structure detection. The real application of our model shows its efficiency in the analysis of the phosphate laundry effluents' impact on the watershed in the Gafsa area (southwestern Tunisia).

Keywords: Classification, Bayesian network; structure learning, K2 algorithm, expert knowledge, surface water analysis.

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Authors: Kunyanuth Kularbphettong, Cholticha Tongsiri

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This paper aims to create the model for student in choosing an emphasized track of student majoring in computer science at Suan Sunandha Rajabhat University. The objective of this research is to develop the suggested system using data mining technique to analyze knowledge and conduct decision rules. Such relationships can be used to demonstrate the reasonableness of student choosing a track as well as to support his/her decision and the system is verified by experts in the field. The sampling is from student of computer science based on the system and the questionnaire to see the satisfaction. The system result is found to be satisfactory by both experts and student as well. 

Keywords: Data mining technique, the decision support system, knowledge and decision rules.

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Authors: K. Kalaiselvan, A. Elango, N. M. Nagarajan

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Laser beam welding for the dissimilar Titanium and Aluminium thin sheets is an emerging area which is having wider applications in aerospace, aircraft, automotive, electronics and in other industries due to its high speed, non-contact, precision with low heat effects, least welding distortion, low labor costs and convenient operation. Laser beam welding of dissimilar metal combinations are increasingly demanded due to high energy densities with small fusion and heat affected zones. Furthermore, no filler or electrode material is required and contamination of weld is also very small. The present study is to reviews the influence of different parameters like laser power, welding speed, power density, beam diameter, focusing distance and type of shielding gas on the mechanical properties of dissimilar metal combinations like SS/Al, Cu/Al and Ti/Al focusing on aluminum to other materials. Research findings reveal that Ti/Al combination gives better metallurgical and mechanical properties than other combinations such as SS/Al and Cu/Al.

Keywords: Laser Beam Welding, dissimilar metals, SS/Al, Cu/Al and Ti/Al sheets.

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Authors: Jörg Linde, Ekaterina Buyko, Robert Altwasser, Udo Hahn, Reinhard Guthke

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Reverse engineering of full-genomic interaction networks based on compendia of expression data has been successfully applied for a number of model organisms. This study adapts these approaches for an important non-model organism: The major human fungal pathogen Candida albicans. During the infection process, the pathogen can adapt to a wide range of environmental niches and reversibly changes its growth form. Given the importance of these processes, it is important to know how they are regulated. This study presents a reverse engineering strategy able to infer fullgenomic interaction networks for C. albicans based on a linear regression, utilizing the sparseness criterion (LASSO). To overcome the limited amount of expression data and small number of known interactions, we utilize different prior-knowledge sources guiding the network inference to a knowledge driven solution. Since, no database of known interactions for C. albicans exists, we use a textmining system which utilizes full-text research papers to identify known regulatory interactions. By comparing with these known regulatory interactions, we find an optimal value for global modelling parameters weighting the influence of the sparseness criterion and the prior-knowledge. Furthermore, we show that soft integration of prior-knowledge additionally improves the performance. Finally, we compare the performance of our approach to state of the art network inference approaches.

Keywords: Pathogen, network inference, text-mining, Candida albicans, LASSO, mutual information, reverse engineering, linear regression, modelling.

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Authors: C. C. Yee, Y.Y.Chen

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Performance appraisal of employee is important in managing the human resource of an organization. With the change towards knowledge-based capitalism, maintaining talented knowledge workers is critical. However, management classification of “outstanding", “poor" and “average" performance may not be an easy decision. Besides that, superior might also tend to judge the work performance of their subordinates informally and arbitrarily especially without the existence of a system of appraisal. In this paper, we propose a performance appraisal system using multifactorial evaluation model in dealing with appraisal grades which are often express vaguely in linguistic terms. The proposed model is for evaluating staff performance based on specific performance appraisal criteria. The project was collaboration with one of the Information and Communication Technology company in Malaysia with reference to its performance appraisal process.

Keywords: Multifactorial Evaluation Model, performance appraisal system, decision support system.

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Authors: Patricia Diogo

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As teachers and researchers, we often find ourselves grappling with a central question about what it truly means to teach project in architecture in Portugal in the 21st century. It is a question that transcends the simple transmission of technical knowledge or even the sharing of our personal experiences. Rather, it is about developing a teaching pedagogy that responds to and reflects the profound social, environmental, and technological shifts we are currently navigating. Teaching architecture in Portugal today is not a mere continuation of tradition; it is, in essence, a living laboratory of innovation. Each new generation of students enters our classrooms with a hunger not just for design techniques, but for meaning—seeking to understand the role they can play in reshaping our physical and cultural environments. They are not passive recipients of knowledge, but active participants in the creation of a more sustainable, ethical, and thoughtful architecture.

Keywords: Architecture, heritage, memories, project studio, teaching.

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Authors: Yah-Ling Hung

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eHealth is undoubtedly emerging as a promising vehicle to provide information for individual self-care management. However, the accessing ability, reading strategies and navigating behavior between higher literacy users and lower literacy users are significantly different. Yet, ways to tailor audiences’ health literacy and develop appropriate eHealth to feed their need become a big challenge. The purpose of this study is to compare the educational effectiveness of eHealth to deliver health knowledge between higher literacy users and lower literacy users, thus establishing useful design strategies of eHealth for users with different level of health literacy. The study was implemented in four stages, the first of which developed a website as the testing media to introduce health care knowledge relating to children’s allergy. Secondly, a reliability and validity test was conducted to make sure that all of the questions in the questionnaire were good indicators. Thirdly, a pre-post knowledge test was conducted with 66 participants, 33 users with higher literacy and 33 users with lower literacy respectively. Finally, a usability evaluation survey was undertaken to explore the criteria used by users with different levels of health literacy to evaluate eHealth. The results demonstrated that the eHealth Intervention in both groups had a positive outcome. There was no significant difference between the effectiveness of eHealth intervention between users with higher literacy and users with lower literacy. However, the average mean of lower literacy group was marginally higher than the average mean of higher literacy group. The findings also showed that the criteria used to evaluate eHealth could be analyzed in terms of the quality of information, appearance, appeal and interaction, but the users with lower literacy have different evaluation criteria from those with higher literacy. This is an interdisciplinary research which proposes the sequential key steps that incorporate the planning, developing and accessing issues that need to be considered when designing eHealth for patients with varying degrees of health literacy.

Keywords: eHealth, health intervention, health literacy, usability evaluation.

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Authors: Michael Harre, Terry Bossomaier, Ranqing Chu, Allan Snyder

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We introduce a novel approach to measuring how humans learn based on techniques from information theory and apply it to the oriental game of Go. We show that the total amount of information observable in human strategies, called the strategic information, remains constant for populations of players of differing skill levels for well studied patterns of play. This is despite the very large amount of knowledge required to progress from the recreational players at one end of our spectrum to the very best and most experienced players in the world at the other and is in contrast to the idea that having more knowledge might imply more 'certainty' in what move to play next. We show this is true for very local up to medium sized board patterns, across a variety of different moves using 80,000 game records. Consequences for theoretical and practical AI are outlined.

Keywords: Board Games, Cognitive Capacity, Decision Theory, Information Theory.

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Authors: Satoru Kaneko, Takeshi Ito, Kensuke Akiyama, Manabu Yasui, Chihiro Kato, Satomi Tanaka, Yasuo Hirabayashi, Takeshi Ozawa, Akira Matsuno, Takashi Nire, Hiroshi Funakubo, Mamoru Yoshimoto

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As application of re-activation of backside on power device Insulated Gate Bipolar Transistor (IGBT), laser annealing was employed to irradiate amorphous silicon substrate, and resistivities were measured using four point probe measurement. For annealing the amorphous silicon two lasers were used at wavelength of visible green (532 nm) together with Infrared (793 nm). While the green laser efficiently increased temperature at top surface the Infrared laser reached more deep inside and was effective for melting the top surface. A finite element method was employed to evaluate time dependent thermal distribution in silicon substrate.

Keywords: laser, annealing, silicon, recrystallization, thermal distribution, resistivity, finite element method, absorption, melting point, latent heat of fusion.

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Authors: Shahrinaz Ismail, Roslina Abdul Latif

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Social media has led to paradigm shifts in ways people work and do business, interact and socialize, learn and obtain knowledge. So much so that social media has established itself as an important spatial extension of this nation-s historicity and challenges. Regardless of the enabling reputation and recommendation features through social networks embedded in the social media system, the overflow of broadcasted and publicized media contents turns the table around from engendering trust to doubting the trust system. When the trust is at doubt, the effects include deactivation of accounts and creation of multiple profiles, which lead to the overflow of 'ghost' contents (i.e. “the abundance of abandoned ships"). In most literature, the study of trust can be related to culture; hence the difference between Western-s “openness" and Eastern-s “blue-chip" concepts in networking and relationships. From a survey on issues and challenges among Malaysian social media users, 'authenticity' emerges as one of the main factors that causes and is caused by other factors. The other issue that has surfaced is credibility either in terms of message/content and source. Another is the quality of the knowledge that is shared. This paper explores the terrains of this critical space which in recent years has been dominated increasingly by, arguably, social networks embedded in the social media system, the overflow of broadcasted and publicized media content.

Keywords: Authenticity, credibility, knowledge quality and social media.

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Authors: Nittaya Kerdprasop, Narin Muenrat, Kittisak Kerdprasop

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A learning content management system (LCMS) is an environment to support web-based learning content development. Primary function of the system is to manage the learning process as well as to generate content customized to meet a unique requirement of each learner. Among the available supporting tools offered by several vendors, we propose to enhance the LCMS functionality to individualize the presented content with the induction ability. Our induction technique is based on rough set theory. The induced rules are intended to be the supportive knowledge for guiding the content flow planning. They can also be used as decision rules to help content developers on managing content delivered to individual learner.

Keywords: Decision rules, Knowledge induction, Learning content management system, Rough set.

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Authors: Vassilis S. Kodogiannis, John N. Lygouras

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In this research study, an intelligent detection system to support medical diagnosis and detection of abnormal lesions by processing endoscopic images is presented. The images used in this study have been obtained using the M2A Swallowable Imaging Capsule - a patented, video color-imaging disposable capsule. Schemes have been developed to extract texture features from the fuzzy texture spectra in the chromatic and achromatic domains for a selected region of interest from each color component histogram of endoscopic images. The implementation of an advanced fuzzy inference neural network which combines fuzzy systems and artificial neural networks and the concept of fusion of multiple classifiers dedicated to specific feature parameters have been also adopted in this paper. The achieved high detection accuracy of the proposed system has provided thus an indication that such intelligent schemes could be used as a supplementary diagnostic tool in endoscopy.

Keywords: Medical imaging, Computer aided diagnosis, Endoscopy, Neuro-fuzzy networks, Fuzzy integral.

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Authors: Nour Charara, Iman Jarkass, Maria Sokhn, Elena Mugellini, Omar Abou Khaled

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Intelligent Video-Surveillance (IVS) systems are being more and more popular in security applications. The analysis and recognition of abnormal behaviours in a video sequence has gradually drawn the attention in the field of IVS, since it allows filtering out a large number of useless information, which guarantees the high efficiency in the security protection, and save a lot of human and material resources. We present in this paper ADABeV, an intelligent video-surveillance framework for event recognition in crowded scene to detect the abnormal human behaviour. This framework is attended to be able to achieve real-time alarming, reducing the lags in traditional monitoring systems. This architecture proposal addresses four main challenges: behaviour understanding in crowded scenes, hard lighting conditions, multiple input kinds of sensors and contextual-based adaptability to recognize the active context of the scene.

Keywords: Behavior recognition, Crowded scene, Data fusion, Pattern recognition, Video-surveillance

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Authors: Chi Jung Kim, Mincheol Whang, Eui Chul Lee

Abstract:

In this paper, we propose a new method to distinguish between arousal and relaxation states by using multiple features acquired from a photoplethysmogram (PPG) and support vector machine (SVM). To induce arousal and relaxation states in subjects, 2 kinds of sound stimuli are used, and their corresponding biosignals are obtained using the PPG sensor. Two features–pulse to pulse interval (PPI) and pulse amplitude (PA)–are extracted from acquired PPG data, and a nonlinear classification between arousal and relaxation is performed using SVM. This methodology has several advantages when compared with previous similar studies. Firstly, we extracted 2 separate features from PPG, i.e., PPI and PA. Secondly, in order to improve the classification accuracy, SVM-based nonlinear classification was performed. Thirdly, to solve classification problems caused by generalized features of whole subjects, we defined each threshold according to individual features. Experimental results showed that the average classification accuracy was 74.67%. Also, the proposed method showed the better identification performance than the single feature based methods. From this result, we confirmed that arousal and relaxation can be classified using SVM and PPG features.

Keywords: Support Vector Machine, PPG, Emotion Recognition, Arousal, Relaxation

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