Search results for: knowledge%20discovery

Authors: Hanaa Bajilan

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Gender statuses are inherently unequal; it is difficult to establish equality between men and women in the light of traditional inequalities across the world. This research focuses on the similarities and differences among women from different generations, different kinds of educational backgrounds and highlights the conflict experiences of the characters in Githa Hariharan’s novel “The Thousand Faces of Night”. The purpose is to show how women are suffering and are being humiliated in a male-dominated society. The paper depicts how women in India grapple from male domination aggressiveness as well as the cultural, social and religious controlling in the society they live in. The paper also seeks to explore the importance of knowledge as a powerful component which produces positive effects at the level of desire. The paper is based on the theories of Simone Beauvoir, Pierre Bourdieu, Edward Said, Rene Descartes and Amy Bhatt. Finally, the research emphasizes survival against hegemonic regimes and hope of Indian women for better life.

Keywords: Equality, gender, Githa Hariharan, humiliation, identity, Indian women, knowledge.

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Authors: Thabet Slimani, Boutheina Ben Yaghlane, Khaled Mellouli

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In the last few years, the Semantic Web gained scientific acceptance as a means of relationships identification in knowledge base, widely known by semantic association. Query about complex relationships between entities is a strong requirement for many applications in analytical domains. In bioinformatics for example, it is critical to extract exchanges between proteins. Currently, the widely known result of such queries is to provide paths between connected entities from data graph. However, they do not always give good results while facing the user need by the best association or a set of limited best association, because they only consider all existing paths but ignore the path evaluation. In this paper, we present an approach for supporting association discovery queries. Our proposal includes (i) a query language PmSPRQL which provides a multiparadigm query expressions for association extraction and (ii) some quantification measures making easy the process of association ranking. The originality of our proposal is demonstrated by a performance evaluation of our approach on real world datasets.

Keywords: Association extraction, query Language, relationships, knowledge base, multi-paradigm query.

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Authors: Balasundaram Prasaant, Ploix Stephane, Delinchant Benoit, Muresan Cristian

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Hardware in Loop (HIL) testing is done to test and validate a particular product especially in building technology. When it comes to building technology, it is more important to test the products for their efficiency. The test rig in the HIL simulator may contribute to some uncertainties on measured efficiency. The uncertainties include physical uncertainties and scenario-based uncertainties. In this paper, a simple uncertainty analysis framework for an HIL setup is shown considering only the physical uncertainties. The entire modeling of the HIL setup is done in Dymola. The uncertain sources are considered based on available knowledge of the components and also on expert knowledge. For the propagation of uncertainty, Monte Carlo Simulation is used since it is the most reliable and easy to use. In this article it is shown how an HIL setup can be modeled and how uncertainty propagation can be performed on it. Such an approach is not common in building energy analysis.

Keywords: Energy in Buildings, Hardware in Loop, Modelica (Dymola), Monte Carlo Simulation, Uncertainty Propagation.

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Authors: Andressa dos Santos Nicolau, João P. da S.C Algusto, Claudio Márcio do N. A. Pereira, Roberto Schirru

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In case of abnormal situations, the nuclear power plant (NPP) operators must follow written procedures to check the condition of the plant and to classify the type of emergency. In this paper, we proposed a Real Time Expert System in order to improve operator’s performance in case of transient or accident with reactor shutdown. The expert system’s knowledge is based on the sequence of events (SoE) of known accident and two emergency procedures of the Brazilian Pressurized Water Reactor (PWR) NPP and uses two kinds of knowledge representation: rule and logic trees. The results show that the system was able to classify the response of the automatic protection systems, as well as to evaluate the conditions of the plant, diagnosing the type of occurrence, recovery procedure to be followed, indicating the shutdown root cause, and classifying the emergency level.

Keywords: Emergence procedure, expert system, operator support, PWR nuclear power plant.

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Authors: Mesfer Al Duhayyim, Paul Newbury

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This paper proposes an effective adaptive e-learning system that uses a coloured concept map to show the learner's knowledge level for each concept in the chosen subject area. A Fuzzy logic system is used to evaluate the learner's knowledge level for each concept in the domain, and produce a ranked concept list of learning materials to address weaknesses in the learner’s understanding. This system obtains information on the learner's understanding of concepts by an initial pre-test before the system is used for learning and a post-test after using the learning system. A Fuzzy logic system is used to produce a weighted concept map during the learning process. The aim of this research is to prove that such a proposed novel adapted e-learning system will enhance learner's performance and understanding. In addition, this research aims to increase participants' overall understanding of their learning level by providing a coloured concept map of understanding followed by a ranked concepts list of learning materials.

Keywords: Adaptive e-learning system, coloured concept map, fuzzy logic, ranked concept list.

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Authors: Suzanne Yaganeh, Janni Nielsen, Leif Bloch Rasmussen

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This paper invites to dialogue and reflections on innovation and entrepreneurship by presenting concepts of innovation leading to the introduction of a complex theoretical framework; Cooperative Innovation (CO-IN). CO-IN is a didactic model enhancing and scaffolding processes of cooperation creating innovation drawing on a Scandinavian tradition. CO-IN is based on a cross-sectorial and multidisciplinary approach. We introduce the concept of complementarity to help capture the validity of diversity and we suggest the concept of “the space in between" to understand the creation of identity as a collective mind. We see dialogue and the use of multi modal techniques as essential tools for conceptualizations giving possibility for clarification of the complexity and diversity leading to decision making based on knowledge as commons. We introduce the didactic design and present our empirical findings from an innovation workshop in Argentina. In a final paragraph we reflect on the design as a support of the development of common ground, collective mind and collective action and the creation of knowledge as commons to facilitate innovation and entrepreneurship.

Keywords: CO-operative Innovation, didactic design, dialogue and ICT.

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Authors: Mesnan Silalahi, Dana Indra Sensuse, Indra Budi

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Many studies have revealed the fact of the complexity of ontology building process. Therefore there is a need for a new approach which one of that addresses the socio-technical aspects in the collaboration to reach a consensus. Meta-design approach is considered applicable as a method in the methodological model of socio-technical ontology engineering. Principles in the meta-design framework are applied in the construction phases of the ontology. A web portal is developed to support the meta-design principles requirements. To validate the methodological model semantic web applications were developed and integrated in the portal and also used as a way to show the usefulness of the ontology. The knowledge based system will be filled with data of Indonesian medicinal plants. By showing the usefulness of the developed ontology in a semantic web application, we motivate all stakeholders to participate in the development of knowledge based system of medicinal plants in Indonesia.

Keywords: Socio-technical, meta-design, ontology engineering methodology, semantic web application.

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Authors: Lucia Abbamonte, Olimpia Matarazzo

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In recent years linguistic research has turned increasing attention to covert/overt strategies to modulate authorial stance and positioning in scientific texts, and to the recipients' response. This study discussed some theoretical implications of the use of rhetoric in scientific communication and analysed qualitative data from the authoritative The Cognitive Neurosciences III (2004) volume. Its genre-identity, status and readability were considered, in the social interactive context of contemporary disciplinary discourses – in their polyphony of traditional and new, emerging genres. Evidence was given of the ways its famous authors negotiate and shape knowledge and research results – explicitly appraising team work and promoting faith in the fast-paced progress of Cognitive Neuroscience, also through experiential metaphors – by presenting a set of examples, ordered according to their dominant rhetorical quality.

Keywords: Appraisal, disciplinary discourses, experientialmetaphors, genre, identity, knowledge, readability, rhetoric, strategies, theoretical implications.

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Authors: Hei-Chia Wang, Che-Tsung Yang

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While the explosive increase in information published on the Web, researchers have to filter information when searching for conference related information. To make it easier for users to search related information, this paper uses Topic Maps and social information to implement ontology since ontology can provide the formalisms and knowledge structuring for comprehensive and transportable machine understanding that digital information requires. Besides enhancing information in Topic Maps, this paper proposes a method of constructing research Topic Maps considering social information. First, extract conference data from the web. Then extract conference topics and the relationships between them through the proposed method. Finally visualize it for users to search and browse. This paper uses ontology, containing abundant of knowledge hierarchy structure, to facilitate researchers getting useful search results. However, most previous ontology construction methods didn-t take “people" into account. So this paper also analyzes the social information which helps researchers find the possibilities of cooperation/combination as well as associations between research topics, and tries to offer better results.

Keywords: Ontology, topic maps, social information, co-authorship.

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Authors: A.M. Fahim, A. M. Salem, F. A. Torkey, M. A. Ramadan

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Clustering algorithms are attractive for the task of class identification in spatial databases. However, the application to large spatial databases rises the following requirements for clustering algorithms: minimal requirements of domain knowledge to determine the input parameters, discovery of clusters with arbitrary shape and good efficiency on large databases. The well-known clustering algorithms offer no solution to the combination of these requirements. In this paper, a density based clustering algorithm (DCBRD) is presented, relying on a knowledge acquired from the data by dividing the data space into overlapped regions. The proposed algorithm discovers arbitrary shaped clusters, requires no input parameters and uses the same definitions of DBSCAN algorithm. We performed an experimental evaluation of the effectiveness and efficiency of it, and compared this results with that of DBSCAN. The results of our experiments demonstrate that the proposed algorithm is significantly efficient in discovering clusters of arbitrary shape and size.

Keywords: Clustering Algorithms, Arbitrary Shape of clusters, cluster Analysis.

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Authors: Francesco Maiorana

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In this paper a one-dimension Self Organizing Map algorithm (SOM) to perform feature selection is presented. The algorithm is based on a first classification of the input dataset on a similarity space. From this classification for each class a set of positive and negative features is computed. This set of features is selected as result of the procedure. The procedure is evaluated on an in-house dataset from a Knowledge Discovery from Text (KDT) application and on a set of publicly available datasets used in international feature selection competitions. These datasets come from KDT applications, drug discovery as well as other applications. The knowledge of the correct classification available for the training and validation datasets is used to optimize the parameters for positive and negative feature extractions. The process becomes feasible for large and sparse datasets, as the ones obtained in KDT applications, by using both compression techniques to store the similarity matrix and speed up techniques of the Kohonen algorithm that take advantage of the sparsity of the input matrix. These improvements make it feasible, by using the grid, the application of the methodology to massive datasets.

Keywords: Clustering algorithm, Data mining, Feature selection, Grid, Kohonen Self Organizing Map.

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Authors: Sajed A. Habib

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Problem-based learning (PBL) is a student-centered pedagogy that originated in the medical field and has also been used extensively in other knowledge disciplines with recognized advantages and limitations. PBL has been used in various undergraduate engineering programs with mixed outcomes. The current fourth industrial revolution (digital era or Industry 4.0) has made it essential for many science and engineering students to receive effective training in advanced courses such as industrial automation and robotics. This paper presents a case study at Assumption University of Thailand, where a PBL-like approach was used to teach some aspects of automation and robotics to selected groups of undergraduate engineering students. These students were given some basic level training in automation prior to participating in a subsequent training session in order to solve technical problems with increased complexity. The participating students’ evaluation of the training sessions in terms of learning effectiveness, skills enhancement, and incremental knowledge following the problem-solving session was captured through a follow-up survey consisting of 14 questions and a 5-point scoring system. From the most recent training event, an overall 70% of the respondents indicated that their skill levels were enhanced to a much greater level than they had had before the training, whereas 60.4% of the respondents from the same event indicated that their incremental knowledge following the session was much greater than what they had prior to the training. The instructor-facilitator involved in the training events suggested that this method of learning was more suitable for senior/advanced level students than those at the freshmen level as certain skills to effectively participate in such problem-solving sessions are acquired over a period of time, and not instantly.

Keywords: Automation, industry 4.0, model-based design training, problem-based learning.

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Authors: Javier Parra-Domínguez, Juan Manuel Corchado

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At present, public efficiency is a concept that intends to maximize return on public investment focus on minimizing the use of resources and maximizing the outputs. The concept takes into account statistical criteria drawn up according to techniques such as DEA (Data Envelopment Analysis). The purpose of the current work is to consider, more precisely, the theoretical application of CBR (Case-Based Reasoning) from economics and computer science, as a preliminary step to improving the efficiency of law enforcement agencies (public sector). With the aim of increasing the efficiency of the public sector, we have entered into a phase whose main objective is the implementation of new technologies. Our main conclusion is that the application of computer techniques, such as CBR, has become key to the efficiency of the public sector, which continues to require economic valuation based on methodologies such as DEA. As a theoretical result and conclusion, the incorporation of CBR systems will reduce the number of inputs and increase, theoretically, the number of outputs generated based on previous computer knowledge.

Keywords: Case-based reasoning, knowledge, police, public efficiency.

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Authors: Siriporn Poolsuwan, Kanyarat Bussaban

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This research aims to investigate and analyze user’s behaviour towards the utilization of the online news clipping database at Suan Sunandha Rajabhat University, Thailand. Data is gathered from 214 lecturers and 380 undergraduate students by using questionnaires. Findings show that most users knew the online news clipping service from their friends, library’s website and their teachers. The users learned how to use it by themselves and others learned by training of SSRU library. Most users used the online news clipping database one time per month at home and always used the service for general knowledge, up-to-date academic knowledge and assignment reference. Moreover, the results of using the online news clipping service problems include the users themselves, service management, service device- computer and tools – and the network, service provider, and publicity. This research would be benefit for librarians and teachers for planning and designing library services in their works and organization

Keywords: Online Database, User Behaviour.

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Authors: Reihaneh Montazeri Shatouri, Rosmini Omar, Kunio Igusa

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Although automotive industry has brought different beneficiaries to human life, it is being pointed out as one of the major cause of global air pollution which resulted in climate change, smog, green house gases (GHGs), and human diseases by many reasons. Since auto industry is one of the largest consumers of fossil fuels, the realization of green innovations is becoming a crucial choice to meet the challenges towards sustainable development. Recently, many auto manufacturers have embarked on green technology initiatives to gain a competitive advantage in the global market; however, innovative manufacturing systems and technologies can enhance operational performance only if the human resource management is in place to elicit the motivation of the employees and develop their organizational expertise. No organization can perform at peak levels unless each employee is committed to the company goals and works as an effective team member. Strategic human resource practices are the primary means by which firms can shape the skills, attitudes, and behavior of individuals to align with the business strategic objectives. This study investigates on the comprehensive approach of multiple advanced technology innovations and human resource management at Toyota Motor Corporation as the market leader of full hybrid technology in the automotive industry. Then, HRM framework of the company is described and three sets of human resource practices that support the innovation-oriented HR system, presented. Finally, a conceptual framework for innovativeness in green technology in automotive industry by applying a deliberate strategic HR management system and knowledge management with the intervening factors of organizational culture, knowledge application and knowledge sharing is proposed.

Keywords: Automotive Industry, Green Technology, Innovation, Strategic Human Resource Management

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Authors: Renata Martins Pacheco, João Claro

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Wildfires are becoming an increasing concern worldwide, causing substantial social, economic, and environmental disruptions. This situation is especially relevant in Mediterranean-climate regions, present in all the five continents of the world, in which fire is not only a natural component of the environment but also perhaps one of the most important evolutionary forces. The rise in wildfire occurrences and their associated impacts suggests the need for identifying knowledge gaps and enhancing the basis of scientific evidence on how managers and policymakers may act effectively to address them. Considering that the main goal of a systematic map is to collate and catalog a body of evidence to describe the state of knowledge for a specific topic, it is a suitable approach to be used for this purpose. In this context, the aim of this study is to systematically map the research trends in wildfire management practices in Mediterranean-climate regions. A total of 201 wildfire management studies were analyzed and systematically mapped in terms of their: Year of publication; Place of study; Scientific outlet; Research area (Web of Science) or Research field (Scopus); Wildfire phase; Central research topic; Main objective of the study; Research methods; and Main conclusions or contributions. The results indicate that there is an increasing number of studies being developed on the topic (most from the last 10 years), but more than half of them are conducted in few Mediterranean countries (60% of the analyzed studies were conducted in Spain, Portugal, Greece, Italy or France), and more than 50% are focused on pre-fire issues, such as prevention and fuel management. In contrast, only 12% of the studies focused on “Economic modeling” or “Human factors and issues,” which suggests that the triple bottom line of the sustainability argument (social, environmental, and economic) is not being fully addressed by fire management research. More than one-fourth of the studies had their objective related to testing new approaches in fire or forest management, suggesting that new knowledge is being produced on the field. Nevertheless, the results indicate that most studies (about 84%) employed quantitative research methods, and only 3% of the studies used research methods that tackled social issues or addressed expert and practitioner’s knowledge. Perhaps this lack of multidisciplinary studies is one of the factors hindering more progress from being made in terms of reducing wildfire occurrences and their impacts.

Keywords: Management Mediterranean-climate regions, policy, wildfire.

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Authors: Jawad Makki, Anne-Marie Alquier, Violaine Prince

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In this paper we propose an NLP-based method for Ontology Population from texts and apply it to semi automatic instantiate a Generic Knowledge Base (Generic Domain Ontology) in the risk management domain. The approach is semi-automatic and uses a domain expert intervention for validation. The proposed approach relies on a set of Instances Recognition Rules based on syntactic structures, and on the predicative power of verbs in the instantiation process. It is not domain dependent since it heavily relies on linguistic knowledge. A description of an experiment performed on a part of the ontology of the PRIMA1 project (supported by the European community) is given. A first validation of the method is done by populating this ontology with Chemical Fact Sheets from Environmental Protection Agency2. The results of this experiment complete the paper and support the hypothesis that relying on the predicative power of verbs in the instantiation process improves the performance.

Keywords: Information Extraction, Instance Recognition Rules, Ontology Population, Risk Management, Semantic analysis.

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Authors: Samir Abdelhamid, Noureddine Bouguechal

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We report in this paper the model adopted by our system of continuous speech recognition in Arab language SySRA and the results obtained until now. This system uses the database Arabdic-10 which is a corpus of word for the Arab language and which was manually segmented. Phonetic decoding is represented by an expert system where the knowledge base is translated in the form of production rules. This expert system transforms a vocal signal into a phonetic lattice. The higher level of the system takes care of the recognition of the lattice thus obtained by deferring it in the form of written sentences (orthographical Form). This level contains initially the lexical analyzer which is not other than the module of recognition. We subjected this analyzer to a set of spectrograms obtained by dictating a score of sentences in Arab language. The rate of recognition of these sentences is about 70% which is, to our knowledge, the best result for the recognition of the Arab language. The test set consists of twenty sentences from four speakers not having taken part in the training.

Keywords: Continuous speech recognition, lexical analyzer, phonetic decoding, phonetic lattice, vocal signal.

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Authors: Jia-Yu Dai, Don-Lin Yang, Jungpin Wu, Ming-Chuan Hung

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In an era of knowledge explosion, the growth of data increases rapidly day by day. Since data storage is a limited resource, how to reduce the data space in the process becomes a challenge issue. Data compression provides a good solution which can lower the required space. Data mining has many useful applications in recent years because it can help users discover interesting knowledge in large databases. However, existing compression algorithms are not appropriate for data mining. In [1, 2], two different approaches were proposed to compress databases and then perform the data mining process. However, they all lack the ability to decompress the data to their original state and improve the data mining performance. In this research a new approach called Mining Merged Transactions with the Quantification Table (M2TQT) was proposed to solve these problems. M2TQT uses the relationship of transactions to merge related transactions and builds a quantification table to prune the candidate itemsets which are impossible to become frequent in order to improve the performance of mining association rules. The experiments show that M2TQT performs better than existing approaches.

Keywords: Association rule, data mining, merged transaction, quantification table.

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Authors: Fátima Gonçalves, Joaquim Brigas, Jorge Gonçalves

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The proliferation of mobile devices in society enables the media to disseminate information and knowledge more rapidly. Higher education students access these contents and share them with each other, in the most diverse platforms, allowing the ubiquity in access to information. This article presents the results and respective quantitative analysis of a survey applied to communication students of two higher education institutions: one in Portugal and another in Spain. The results show that, in this sample, higher education students regularly access news content believing traditional news sources to be more credible. Regarding online sources, it was verified that the access was mostly to free news contents. This study intends to promote the knowledge about the changes that occur in the relationship of higher education students with the media, characterizing how news consumption is processed by these students, considering the resulting effects of the digital media evolution. It is intended to present not only the news sources they use, but also to know some of their habits and relationship with the news media.

Keywords: Students’ perceptions, communication design, mass media, higher education, digital media.

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Authors: Kawpong Polyorat, Nathamon Buaprommee

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Because of the outbreak of mad cow disease and bird flu, consumers have become more concerned with quality and safety of meat and poultry. As a consequence, meat traceability has been implemented as a tool to raise the standard in the meat production industry. In Thailand, while traceability is relatively common among the manufacturer-wholesaler-retailers cycle, it is rarely used as a marketing tool specifically designed to persuade consumers who are the actual meat endusers. Therefore, the present study attempts to understand what influences consumers to spread their words-of-mouth (WOM) regarding meat with traceability by conducting a study in Thailand where research in this area is rather scant. Data were collected from one hundred and sixty-seven consumers in the northeastern region and analyzed with SEM. The study results reveal that perceived usefulness of traceability system, social norms, and product class knowledge are significant antecedents where consumers spread positive words regarding meat with traceability system. A number of theoretical and managerial implications as well as future study directions are offered at the end of this study report.

Keywords: Perceived usefulness, product knowledge, social norms, traceability, word-of-mouth,

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Authors: Jonqlan Lin, C. Y. Tasi, K. H. Lin

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This paper addresses the issue of the autonomous mobile robot (AMR) navigation task based on the hybrid control modes. The novel hybrid control mode, based on multi-sensors information by using the fuzzy approach, has been presented in this research. The system operates in real time, is robust, enables the robot to operate with imprecise knowledge, and takes into account the physical limitations of the environment in which the robot moves, obtaining satisfactory responses for a large number of different situations. An experiment is simulated and carried out with a pioneer mobile robot. From the experimental results, the effectiveness and usefulness of the proposed AMR obstacle avoidance and navigation scheme are confirmed. The experimental results show the feasibility, and the control system has improved the navigation accuracy. The implementation of the controller is robust, has a low execution time, and allows an easy design and tuning of the fuzzy knowledge base.

Keywords: Autonomous mobile robot, obstacle avoidance, MEMS, hybrid control mode, navigation control.

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Authors: Mahathir Sarjan, Ramos Radzly, Noor Baiti Jamaluddin, Mohd Hafiz Zakaria, Hisham Suhadi

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Creativity is marked by the ability or power, to produce through imaginative skill and create something anew. The University is one of the great places to improve the talent in imaginative skill. The purpose of this study was to identify a creativity of the student in presentation product development. Two hundred seventeen Technical and Vocational Education (TVE) students in Universiti Tun Hussein Onn had chosen as a respondent. This study is to survey the level of creativity which is focused on knowledge, skills, presentation style, and character of creative personnel. The level of creativity was measured based on the scale at low, medium and high followed by mean score level. The data collected by questionnaire, then analyzed using SPSS version 20.0.The result of the study indicated that the students showed a higher of creativity (mean score in Knowledge = 4.12 and Skills= 4.02). In conjunction with the findings, implications and recommendations were suggested forward like to ensconce the research and improve with a more creativity concept in presentation product of development for learning and teaching process.

Keywords: Creativity, technical, vocational education, presentation products and development for learning and teaching process.

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Authors: Hadi Firouzi, Majid Nili Ahmadabadi, Babak N. Araabi

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Conceptualization strengthens intelligent systems in generalization skill, effective knowledge representation, real-time inference, and managing uncertain and indefinite situations in addition to facilitating knowledge communication for learning agents situated in real world. Concept learning introduces a way of abstraction by which the continuous state is formed as entities called concepts which are connected to the action space and thus, they illustrate somehow the complex action space. Of computational concept learning approaches, action-based conceptualization is favored because of its simplicity and mirror neuron foundations in neuroscience. In this paper, a new biologically inspired concept learning approach based on the probabilistic framework is proposed. This approach exploits and extends the mirror neuron-s role in conceptualization for a reinforcement learning agent in nondeterministic environments. In the proposed method, instead of building a huge numerical knowledge, the concepts are learnt gradually from rewards through interaction with the environment. Moreover the probabilistic formation of the concepts is employed to deal with uncertain and dynamic nature of real problems in addition to the ability of generalization. These characteristics as a whole distinguish the proposed learning algorithm from both a pure classification algorithm and typical reinforcement learning. Simulation results show advantages of the proposed framework in terms of convergence speed as well as generalization and asymptotic behavior because of utilizing both success and failures attempts through received rewards. Experimental results, on the other hand, show the applicability and effectiveness of the proposed method in continuous and noisy environments for a real robotic task such as maze as well as the benefits of implementing an incremental learning scenario in artificial agents.

Keywords: Concept learning, probabilistic decision making, reinforcement learning.

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Authors: Bhawat Chiamjinnawat

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The agri-food market transformation has implied market growth for the fruit industry in Thailand. This article focuses on analysis of farmer competence and farm resources which affect market strategies used by fruit farmers in Chanthaburi province of Thailand. The survey data were collected through the use of face-to-face interviews with structured questionnaires. This study identified 14 drivers related to farmer competence and farm resources of which some had significant effect on the decision to use either high-value markets or traditional markets. The results suggest that farmers who used high-value markets were better educated and they had longer experience and larger sized business. Identifying the important factors that match with the market transformation provides policy with opportunities to support the fruit farmers to increase their market power. Policies that promote business expansion of agricultural cooperatives and knowledge sharing among farmers are recommended to reduce limitations due to limited knowledge, low experience, and small business sizes.

Keywords: Farmer competence, farm resources, fruit industry, high-value markets, Thailand.

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Authors: A. Maddi, A. Guessoum, D. Berkani

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The purpose of this paper is to provide a practical example to the Linear Quadratic Gaussian (LQG) controller. This method includes a description and some discussion of the discrete Kalman state estimator. One aspect of this optimality is that the estimator incorporates all information that can be provided to it. It processes all available measurements, regardless of their precision, to estimate the current value of the variables of interest, with use of knowledge of the system and measurement device dynamics, the statistical description of the system noises, measurement errors, and uncertainty in the dynamics models. Since the time of its introduction, the Kalman filter has been the subject of extensive research and application, particularly in the area of autonomous or assisted navigation. For example, to determine the velocity of an aircraft or sideslip angle, one could use a Doppler radar, the velocity indications of an inertial navigation system, or the relative wind information in the air data system. Rather than ignore any of these outputs, a Kalman filter could be built to combine all of this data and knowledge of the various systems- dynamics to generate an overall best estimate of velocity and sideslip angle.

Keywords: Aircraft motion, Kalman filter, LQG control, Lateral stability, State estimator.

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Authors: Júlia Szőke

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Negotiating across cultures needs consideration as different cultures have different norms, habits and behavioral patterns. The significance of cross-cultural negotiations lies in the fact that many business relationships have already failed due to the lack of cultural knowledge. Therefore, the paper deals with cross-cultural negotiations in case of Hungarian business negotiators. The aim of the paper is to introduce the findings of a two-phase research conducted among Hungarian business negotiators. In the first phase a qualitative research was conducted to reveal the importance of cultural differences in case of cross-cultural business negotiations from the viewpoint of Hungarian negotiators, whereas in the second phase a quantitative one was conducted to figure out whether cultural stereotypes affect the way how the respondents negotiate with people coming from different cultures. The research found out that in case of Hungarian negotiators it is mostly the lack of cultural knowledge that lurks behind the problems and miscommunication occurring during the negotiations. The research also revealed that stereotypes have an influence on the negotiation styles of Hungarian negotiators. The paper concludes that culture and cultural differences must be taken into consideration in case of cross-cultural negotiations so that problems and misunderstandings could be avoided.

Keywords: Business, culture, negotiations, stereotypes.

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Authors: Tiexin Wang, Sebastien Truptil, Frederick Benaben

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Model transformation, as a pivotal aspect of Modeldriven engineering, attracts more and more attentions both from researchers and practitioners. Many domains (enterprise engineering, software engineering, knowledge engineering, etc.) use model transformation principles and practices to serve to their domain specific problems; furthermore, model transformation could also be used to fulfill the gap between different domains: by sharing and exchanging knowledge. Since model transformation has been widely used, there comes new requirement on it: effectively and efficiently define the transformation process and reduce manual effort that involved in. This paper presents an automatic model transformation methodology based on semantic and syntactic comparisons, and focuses particularly on granularity issue that existed in transformation process. Comparing to the traditional model transformation methodologies, this methodology serves to a general purpose: crossdomain methodology. Semantic and syntactic checking measurements are combined into a refined transformation process, which solves the granularity issue. Moreover, semantic and syntactic comparisons are supported by software tool; manual effort is replaced in this way.

Keywords: Automatic model transformation, granularity issue, model-driven engineering, semantic and syntactic comparisons.

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Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

Abstract:

Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: Fake news detection, types of fake news, machine learning, natural language processing, classification techniques.

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Authors: Giulio Nisoli, Jonas Brüngger, Karin Hostettler, Nicole Stoller, Katrin Fischer

Abstract:

Technical operators in the railway domain are experts responsible for the supervisory control of the railway power grid as well as of the railway tunnels. The technical systems used to master these demanding tasks are constantly increasing in their degree of automation. It becomes therefore difficult for technical operators to maintain the control over the technical systems and the processes of their job. In particular, the operators must have the necessary experience and knowledge in dealing with a malfunction situation or unexpected event. For this reason, it is of growing importance that the skills relevant for the execution of the job are maintained and further developed beyond the basic training they receive, where they are educated in respect of technical knowledge and the work with guidelines. Training methods aimed at improving the cognitive skills needed by technical operators are still missing and must be developed. Goals of the present study were to identify which are the relevant cognitive skills of technical operators in the railway domain and to define which topics should be addressed by the training of these skills. Observational interviews were conducted in order to identify the main tasks and the organization of the work of technical operators as well as the technical systems used for the execution of their job. Based on this analysis, the most demanding tasks of technical operators could be identified and described. The cognitive skills involved in the execution of these tasks are those, which need to be trained. In order to identify and analyze these cognitive skills a cognitive task analysis (CTA) was developed. CTA specifically aims at identifying the cognitive skills that employees implement when performing their own tasks. The identified cognitive skills of technical operators were summarized and grouped in training topics. For every training topic, specific goals were defined. The goals regard the three main categories; knowledge, skills and attitude to be trained in every training topic. Based on the results of this study, it is possible to develop specific training methods to train the relevant cognitive skills of the technical operators.

Keywords: Cognitive skills, cognitive task analysis, technical operators in the railway domain, training topics.

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