Search results for: Clinical Knowledge

Authors: P. Siriarchawatana, K. Leungchavaphongse, N. Covavisaruch, K. Rojananuangnit, P. Boondaeng, N. Panyayingyong

Abstract:

Glaucoma is a disease that causes visual loss in adults. Glaucoma causes damage to the optic nerve and its overall pathophysiology is still not fully understood. Vasculopathy may be one of the possible causes of nerve damage. Photographic imaging of retinal vessels by fundus camera during eye examination may complement clinical management. This paper presents an innovation for measuring central light reflex width-to-retinal vessel diameter ratio (CRR) from digital retinal photographs. Using our edge detection technique, CRRs from glaucoma and normal eyes were compared to examine differences and associations. CRRs were evaluated on fundus photographs of participants from Mettapracharak (Wat Raikhing) Hospital in Nakhon Pathom, Thailand. Fifty-five photographs from normal eyes and twenty-one photographs from glaucoma eyes were included. Participants with hypertension were excluded. In each photograph, CRRs from four retinal vessels, including arteries and veins in the inferotemporal and superotemporal regions, were quantified using edge detection technique. From our finding, mean CRRs of all four retinal arteries and veins were significantly higher in persons with glaucoma than in those without glaucoma (0.34 vs. 0.32, p < 0.05 for inferotemporal vein, 0.33 vs. 0.30, p < 0.01 for inferotemporal artery, 0.34 vs. 0.31, p < 0.01 for superotemporal vein, and 0.33 vs. 0.30, p < 0.05 for superotemporal artery). From these results, an increase in CRRs of retinal vessels, as quantitatively measured from fundus photographs, could be associated with glaucoma.

Keywords: Glaucoma, retinal vessel, central light reflex, image processing, fundus photograph, edge detection.

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Authors: Margaret F. Shipley

Abstract:

Fuzzy logic can be used when knowledge is incomplete or when ambiguity of data exists. The purpose of this paper is to propose a proactive fuzzy set- based model for reacting to the risk inherent in investment activities relative to a complete view of portfolio management. Fuzzy rules are given where, depending on the antecedents, the portfolio size may be slightly or significantly decreased or increased. The decision maker considers acceptable bounds on the proportion of acceptable risk and return. The Fuzzy Controller model allows learning to be achieved as 1) the firing strength of each rule is measured, 2) fuzzy output allows rules to be updated, and 3) new actions are recommended as the system continues to loop. An extension is given to the fuzzy controller that evaluates potential financial loss before adjusting the portfolio. An application is presented that illustrates the algorithm and extension developed in the paper.

Keywords: Portfolio Management, Financial Market Monitoring, Fuzzy Controller, Fuzzy Logic,

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Authors: Rajesh S.Prasad, U. V. Kulkarni, Jayashree.R.Prasad

Abstract:

As the enormous amount of on-line text grows on the World-Wide Web, the development of methods for automatically summarizing this text becomes more important. The primary goal of this research is to create an efficient tool that is able to summarize large documents automatically. We propose an Evolving connectionist System that is adaptive, incremental learning and knowledge representation system that evolves its structure and functionality. In this paper, we propose a novel approach for Part of Speech disambiguation using a recurrent neural network, a paradigm capable of dealing with sequential data. We observed that connectionist approach to text summarization has a natural way of learning grammatical structures through experience. Experimental results show that our approach achieves acceptable performance.

Keywords: Artificial Neural Networks (ANN); Computational Intelligence (CI); Connectionist Text Summarizer ECTS (ECTS); Evolving Connectionist systems; Evolving systems; Fuzzy systems (FS); Part of Speech (POS) disambiguation.

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Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim

Abstract:

The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.

Keywords: Data mining, Korean linguistic feature, literary fiction, relationship extraction.

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Authors: Jiri Brozovsky

Abstract:

Modulus of elasticity is one of the important parameters of construction materials, which considerably influence their deformation properties and which can also be determined by means of non-destructive test methods like ultrasonic pulse method. However, measurement results of ultrasonic pulse methods are influenced by various factors, one of which is the natural frequency of the transducers. The paper states knowledge about influence of natural frequency of the transducers (54; 82 and 150kHz) on ultrasonic pulse velocity and dynamic modulus of elasticity (Young's Dynamic modulus of elasticity). Differences between ultrasonic pulse velocity and dynamic modulus of elasticity were found with the same smallest dimension of test specimen in the direction of sounding and density their value decreases as the natural frequency of transducers grew.

Keywords: Calcium silicate brick, ultrasonic pulse method, ultrasonic pulse velocity, dynamic modulus of elasticity.

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Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

Abstract:

This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: Data mining, textile production, decision trees, classification.

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Authors: S. Ishak, M. G. Nasuruddin

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This paper looks at healing performances as ethnographic expressions of local knowledge and culture embedded within the Malay psyche and gemeinschaft. As society develops and progresses, these healing performances are caught within conflicting trajectories which become compounded by the contestations of tradition, religious concerns, locality and modernity. As exemplifications of the Malay ethos, these performances practice common rituals, cater to the innate needs of the practitioners and serve the targeted, closed, local community. This paper traces the ethnographic methods in documenting these practices as rituals of healing in a post-modern world. It delineates the ethnographic concepts used to analyze these rituals, and to semiotically read the varied binarial oppositions and juxtapositions. The paper concludes by highlighting the reconciliatory processes involved in maintaining these ritual performances as exemplifications of the Malay ethos playing an important role in the re-aligning, re-balancing and healing of the Malay community’s psyche.

Keywords: Angin/winds, Semangat/spirits, Traditional Theatres, Trance.

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Authors: R. Monib, C. I. Goodier, A. Gibb

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The aim of this paper is to investigate the key drivers in planning the construction phase for infrastructure projects to reduce project delays. To achieve this aim, the research conducted three case studies using semi-structured and unstructured interviews (n = 59). The results conclude that a lack of modularization awareness is among the key factors attributed to project delays. The current emotive and ill-informed approach to decision-making, coupled with the lack of knowledge regarding appropriate construction method selection, prevents the potential benefits of modularization being fully realized. To assist with decision-making for the best construction method, the research presents project management tools to help decision makers to choose the most appropriate construction approach through optimizing the use of modularization in engineering and construction (EC). A decision-making checklist is presented in this paper. This checklist tool assists the project team in determining the best construction method, taking into consideration the module type.

Keywords: Infrastructure, modularization, decision support, planning.

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Authors: Sajjad Farashi, Mohammadjavad Abolhassani, Mostafa Taghavi Kani

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Information in the nervous system is coded as firing patterns of electrical signals called action potential or spike so an essential step in analysis of neural mechanism is detection of action potentials embedded in the neural data. There are several methods proposed in the literature for such a purpose. In this paper a novel method based on empirical mode decomposition (EMD) has been developed. EMD is a decomposition method that extracts oscillations with different frequency range in a waveform. The method is adaptive and no a-priori knowledge about data or parameter adjusting is needed in it. The results for simulated data indicate that proposed method is comparable with wavelet based methods for spike detection. For neural signals with signal-to-noise ratio near 3 proposed methods is capable to detect more than 95% of action potentials accurately.

Keywords: EMD, neural data processing, spike detection, wavelet decomposition.

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Authors: Barath Kumar, Oliver Niggemann, Juergen Jasperneite

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Model-based approaches have been applied successfully to a wide range of tasks such as specification, simulation, testing, and diagnosis. But one bottleneck often prevents the introduction of these ideas: Manual modeling is a non-trivial, time-consuming task. Automatically deriving models by observing and analyzing running systems is one possible way to amend this bottleneck. To derive a model automatically, some a-priori knowledge about the model structure–i.e. about the system–must exist. Such a model formalism would be used as follows: (i) By observing the network traffic, a model of the long-term system behavior could be generated automatically, (ii) Test vectors can be generated from the model, (iii) While the system is running, the model could be used to diagnose non-normal system behavior. The main contribution of this paper is the introduction of a model formalism called 'probabilistic regression automaton' suitable for the tasks mentioned above.

Keywords: Model-based approach, Probabilistic regression automata, Statistical models and Timed automata.

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Authors: M. Umabharathi, S. Vijayabaskar

Abstract:

Evolutionary Fuzzy PID Speed Controller for Permanent Magnet Synchronous Motor (PMSM) is developed to achieve the Speed control of PMSM in Closed Loop operation and to deal with the existence of transients. Consider a Fuzzy PID control design problem, based on common control Engineering Knowledge. If the transient error is big, that Good transient performance can be obtained by increasing the P and I gains and decreasing the D gains. To autotune the control parameters of the Fuzzy PID controller, the Evolutionary Algorithms (EA) are developed. EA based Fuzzy PID controller provides better speed control and guarantees the closed loop stability. The Evolutionary Fuzzy PID controller can be implemented in real time Applications without any concern about instabilities that leads to system failure or damage.

Keywords: Evolutionary Algorithm (EA), Fuzzy system, Genetic Algorithm (GA), Membership, Permanent Magnet Synchronous Motor (PMSM).

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Authors: Xi Gu, Guan Heng Yeoh, Victoria Timchenko

Abstract:

In the current work, a three-dimensional geometry of a 75% stenosed blood vessel is analyzed. Large eddy simulation (LES) with the help of a dynamic subgrid scale Smagorinsky model is applied to model the turbulent pulsatile flow. The geometry, the transmural pressure and the properties of the blood and the elastic boundary were based on clinical measurement data. For the flexible wall model, a thin solid region is constructed around the 75% stenosed blood vessel. The deformation of this solid region was modelled as a deforming boundary to reduce the computational cost of the solid model. Fluid-structure interaction is realized via a twoway coupling between the blood flow modelled via LES and the deforming vessel. The information of the flow pressure and the wall motion was exchanged continually during the cycle by an arbitrary Lagrangian-Eulerian method. The boundary condition of current time step depended on previous solutions. The fluctuation of the velocity in the post-stenotic region was analyzed in the study. The axial velocity at normalized position Z=0.5 shows a negative value near the vessel wall. The displacement of the elastic boundary was concerned in this study. In particular, the wall displacement at the systole and the diastole were compared. The negative displacement at the stenosis indicates a collapse at the maximum velocity and the deceleration phase.

Keywords: Large Eddy Simulation, Fluid Structural Interaction, Constricted Artery, Computational Fluid Dynamics.

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Authors: Edlira Kalemi, Sule Yildirim-Yayilgan

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Online Social Networks (OSNs) are nowadays being used widely and intensively for crime investigation and prevention activities. As they provide a lot of information they are used by the law enforcement and intelligence. An extensive review on existing solutions and models for collecting intelligence from this source of information and making use of it for solving crimes has been presented in this article. The main focus is on smart solutions and models where ontologies have been used as the main approach for representing criminal domain knowledge. A framework for a prototype ontology named SC-Ont will be described. This defines terms of the criminal domain ontology and the relations between them. The terms and the relations are extracted during both this review and the discussions carried out with domain experts. The development of SC-Ont is still ongoing work, where in this paper, we report mainly on the motivation for using smart ontology models and the possible benefits of using them for solving crimes.

Keywords: Criminal digital evidence, social media, ontologies, reasoning.

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Authors: Stella Ouma, M. E. Herselman

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The Application of e-health solutions has brought superb advancements in the health care industry. E-health solutions have already been embraced in the industrialized countries. In an effort to catch up with the growth, the developing countries have strived to revolutionize the healthcare industry by use of Information technology in different ways. Based on a technology assessment carried out in Kenya – one of the developing countries – and using multiple case studies in Nyanza Province, this work focuses on an investigation on how five rural hospitals are adapting to the technology shift. The issues examined include the ICT infrastructure and e-health technologies in place, the knowledge of participants in terms of benefits gained through the use of ICT and the challenges posing barriers to the use of ICT technologies in these hospitals. The results reveal that the ICT infrastructure in place is inadequate for e-health implementations as a result to various challenges that exist. Consequently, suggestions on how to tackle the various challenges have been addressed in this paper.

Keywords: Challenges, e-health, healthcare, information communication technology, rural areas.

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Authors: Dení Stincer Gómez, Zuraya Monroy Nasr

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Pedagogy of science historically has given priority to teaching strategies that mobilize the cognitive mechanisms leaving out emotional mechanisms. Modern epistemology, cognitive psychology and psychoanalysis begin to argue and prove that emotions are relevant epistemological functions. They are 1) the selection function: that allows the perception and reason choose, to multiple alternative explanation of a particular fact, those are relevant and discard those that are not, 2) heuristic function: that is related to the activation cognitive processes that are effective in the process of knowing; and 3) the so-called content-bearing function: it argues that emotions provide the material reasoning that is subsequently transformed into linguistic propositions. According to these hypotheses, scientific knowledge seems to come from emotions that meet these functions. This paper argues that science education must start from the presence of certain emotions in the learner if we want to form citizens with a scientific or cultural future.

Keywords: Epistemic emotions, science education, formation of citizens and scientists, epistemic functions of emotions.

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Authors: Roslina Ibrahim, Azizah Jaafar

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Educational games (EG) seem to have lots of potential due to digital games popularity and preferences of our younger generations of learners. However, most studies focus on game design and its effectiveness while little has been known about the factors that can affect users to accept or to reject EG for their learning. User acceptance research try to understand the determinants of information systems (IS) adoption among users by investigating both systems factors and users factors. Upon the lack of knowledge on acceptance factors for educational games, we seek to understand the issue. This study proposed a model of acceptance factors based on Unified Theory of Acceptance and Use of Technology (UTAUT). We use original model (performance expectancy, effort expectancy and social influence) together with two new determinants (learning opportunities and enjoyment). We will also investigate the effect of gender and gaming experience that moderate the proposed factors.

Keywords: educational games, games acceptance, user acceptance model, UTAUT

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Authors: Nur Azaliah Abu Bakar, Harihodin Selamat, Mohd Nazri Kama

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This article provides a systematic review of existing research related to the Service-oriented Enterprise Architecture (SoEA) adoption and maturity measurement model. The review’s main goals are to support research; to facilitate other researchers’ search for relevant studies; and to propose areas for future studies within this area. In addition, this article provides useful information on SoEA adoption issues and its related maturity model, based on research-based knowledge. The review results suggest that motives, critical success factors (CSFs), implementation status, and benefits are the most frequently studied areas, and that each of these areas would benefit from further exposure.

Keywords: Systematic Literature Review, Service-oriented Architecture, Adoption, Maturity Model.

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Authors: Shahrol Mohamaddan, Keith Case, Ana Sakura Zainal Abidin

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Human movement in the real world provides important information for developing human behaviour models and simulations. However, it is difficult to assess ‘real’ human behaviour since there is no established method available. As part of the AUNTSUE (Accessibility and User Needs in Transport – Sustainable Urban Environments) project, this research aimed to propose a method to assess human movement and behaviour in crowded areas. The method is based on the three major steps of video recording, conceptual behavior modelling and video analysis. The focus is on individual human movement and behaviour in normal situations (panic situations are not considered) and the interactions between individuals in localized areas. Emphasis is placed on gaining knowledge of characteristics of human movement and behaviour in the real world that can be modelled in the virtual environment.

Keywords: Video observation, Human movement, Behaviour, Crowds, Ergonomics, AUNT-SUE

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Authors: Saeid Fazli, Hadis Askarifar, Maryam Sheikh Shoaie

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Human identification at a distance has recently gained growing interest from computer vision researchers. Gait recognition aims essentially to address this problem by identifying people based on the way they walk [1]. Gait recognition has 3 steps. The first step is preprocessing, the second step is feature extraction and the third one is classification. This paper focuses on the classification step that is essential to increase the CCR (Correct Classification Rate). Multilayer Perceptron (MLP) is used in this work. Neural Networks imitate the human brain to perform intelligent tasks [3].They can represent complicated relationships between input and output and acquire knowledge about these relationships directly from the data [2]. In this paper we apply MLP NN for 11 views in our database and compare the CCR values for these views. Experiments are performed with the NLPR databases, and the effectiveness of the proposed method for gait recognition is demonstrated.

Keywords: Human motion analysis, biometrics, gait recognition, principal component analysis, MLP neural network.

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Authors: Shigeaki Sakurai, Youichi Kitahara, Ryohei Orihara

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Sequential mining methods efficiently discover all frequent sequential patterns included in sequential data. These methods use the support, which is the previous criterion that satisfies the Apriori property, to evaluate the frequency. However, the discovered patterns do not always correspond to the interests of analysts, because the patterns are common and the analysts cannot get new knowledge from the patterns. The paper proposes a new criterion, namely, the sequential interestingness, to discover sequential patterns that are more attractive for the analysts. The paper shows that the criterion satisfies the Apriori property and how the criterion is related to the support. Also, the paper proposes an efficient sequential mining method based on the proposed criterion. Lastly, the paper shows the effectiveness of the proposed method by applying the method to two kinds of sequential data.

Keywords: Sequential mining, Support, Confidence, Apriori property

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Authors: Murat Koklu, Yavuz Unal

Abstract:

Data mining can be called as a technique to extract information from data. It is the process of obtaining hidden information and then turning it into qualified knowledge by statistical and artificial intelligence technique. One of its application areas is medical area to form decision support systems for diagnosis just by inventing meaningful information from given medical data. In this study a decision support system for diagnosis of illness that make use of data mining and three different artificial intelligence classifier algorithms namely Multilayer Perceptron, Naive Bayes Classifier and J.48. Pima Indian dataset of UCI Machine Learning Repository was used. This dataset includes urinary and blood test results of 768 patients. These test results consist of 8 different feature vectors. Obtained classifying results were compared with the previous studies. The suggestions for future studies were presented.

Keywords: Artificial Intelligence, Classifiers, Data Mining, Diabetic Patients.

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Authors: Eric Y. Zhang, L. Acu

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This paper is to point out the limitations of modern medical research and why the Traditional Chinese Medicine (TCM) can help address the limitations. Many of the modern medical research results are based on the findings in fundamental research disciplines, such as physics, and chemistry. However, this foundation is not as solid as it seems. The theory proposed in this paper, the Law of Chasm, or the Chasm Theory, states that there are two categories of objects to be studied. One is non-life objects, or lifeless objects; the other is living beings, or the objects that are alive. The laws and findings obtained by studying non-life objects may not all be extended to living beings, and vice versa. TCM is the study of medicine based on living beings. Therefore, TCM findings may not exist in the body of the knowledge obtained from studying non-life objects.

Keywords: TCM, Traditional Chinese Medicine, Law of Chasm, Chasm Theory, living-beings, non-life.

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Authors: Fatma Didin Sonmez, Pinar Sener

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Technology transfer by international trade and foreign direct investment is the most important positive outcome of open economy. It is widely accepted that new technology and knowledge have an important role in enhancing economic growth. Human capital is the other important factor assisting economic growth. In this study, the role of human capital in the growth process is examined in a view of new endogenous growth theory emphasizing on the technology transfer resulting from international trade. Using the panel data of 10 developed and 10 developing countries, impact of human capital and openness on the rate of economic growth of different countries is analysed. Evidence suggests the view that human capital and openness contribute to the economic growth in both developing and developed countries, but with different rates.

Keywords: economic growth, human capital, openness, technology

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Authors: Peyman Shadman Heidari, Mohammad Khorasani

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The principal purpose of this article is to present a new method based on Adaptive Neural Network Fuzzy Inference System (ANFIS) to generate additional artificial earthquake accelerograms from presented data, which are compatible with specified response spectra. The proposed method uses the learning abilities of ANFIS to develop the knowledge of the inverse mapping from response spectrum to earthquake records. In addition, wavelet packet transform is used to decompose specified earthquake records and then ANFISs are trained to relate the response spectrum of records to their wavelet packet coefficients. Finally, an interpretive example is presented which uses an ensemble of recorded accelerograms to demonstrate the effectiveness of the proposed method.

Keywords: Adaptive Neural Network Fuzzy Inference System, Wavelet Packet Transform, Response Spectrum.

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Authors: Wararat Rungworawut, Twittie Senivongse

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Business process model describes process flow of a business and can be seen as the requirement for developing a software application. This paper discusses a BPM2CD guideline which complements the Model Driven Architecture concept by suggesting how to create a platform-independent software model in the form of a UML class diagram from a business process model. An important step is the identification of UML classes from the business process model. A technique for object-oriented analysis called domain analysis is borrowed and key concepts in the business process model will be discovered and proposed as candidate classes for the class diagram. The paper enhances this step by using ontology search to help identify important classes for the business domain. As ontology is a source of knowledge for a particular domain which itself can link to ontologies of related domains, the search can give a refined set of candidate classes for the resulting class diagram.

Keywords: Business Process Model, Model DrivenArchitecture, Ontology, UML Class Diagram.

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Authors: Yi-Chun Chang, Jian-Wei Li

Abstract:

Web-based cooperative learning focuses on (1) the interaction and the collaboration of community members, and (2) the sharing and the distribution of knowledge and expertise by network technology to enhance learning performance. Numerous research literatures related to web-based cooperative learning have demonstrated that cooperative scripts have a positive impact to specify, sequence, and assign cooperative learning activities. Besides, literatures have indicated that role-play in web-based cooperative learning environments enhances two or more students to work together toward the completion of a common goal. Since students generally do not know each other and they lack the face-to-face contact that is necessary for the negotiation of assigning group roles in web-based cooperative learning environments, this paper intends to further extend the application of genetic algorithm (GA) and propose a GA-based algorithm to tackle the problem of role assignment in web-based cooperative learning environments, which not only saves communication costs but also reduces conflict between group members in negotiating role assignments.

Keywords: genetic algorithm (GA), role assignment, role-play; web-based cooperative learning.

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Authors: Engin Yesil, Leon Urbas

Abstract:

Modeling of complex dynamic systems, which are very complicated to establish mathematical models, requires new and modern methodologies that will exploit the existing expert knowledge, human experience and historical data. Fuzzy cognitive maps are very suitable, simple, and powerful tools for simulation and analysis of these kinds of dynamic systems. However, human experts are subjective and can handle only relatively simple fuzzy cognitive maps; therefore, there is a need of developing new approaches for an automated generation of fuzzy cognitive maps using historical data. In this study, a new learning algorithm, which is called Big Bang-Big Crunch, is proposed for the first time in literature for an automated generation of fuzzy cognitive maps from data. Two real-world examples; namely a process control system and radiation therapy process, and one synthetic model are used to emphasize the effectiveness and usefulness of the proposed methodology.

Keywords: Big Bang-Big Crunch optimization, Dynamic Systems, Fuzzy Cognitive Maps, Learning.

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Authors: Ayed Salman, Fawaz Al-Anzi, Aseel Al-Minayes

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Heuristics-based search methodologies normally work on searching a problem space of possible solutions toward finding a “satisfactory" solution based on “hints" estimated from the problem-specific knowledge. Research communities use different types of methodologies. Unfortunately, most of the times, these hints are immature and can lead toward hindering these methodologies by a premature convergence. This is due to a decrease of diversity in search space that leads to a total implosion and ultimately fitness stagnation of the population. In this paper, a novel Decision Maturity framework (DMF) is introduced as a solution to this problem. The framework simply improves the decision on the direction of the search by materializing hints enough before using them. Ideas from this framework are injected into the particle swarm optimization methodology. Results were obtained under both static and dynamic environment. The results show that decision maturity prevents premature converges to a high degree.

Keywords: Heuristic Search, hints, Particle Swarm Optimization, Decision Maturity Framework.

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Authors: M. Karassartova, D. Shormanbayeva, A. Beissenova, S.Balshikeyev

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Forming a legal culture among citizens is a complicated and lengthy process, influencing all spheres of social life. It includes promoting justice, learning rights and duties, the introduction of juridical norms and knowledge, and also a process of developing a system of legal acts and constitutional norms. Currently, the evaluative and emotional influence of attempts to establish a legal culture among the citizens of Kazakhstan is limited by real legal practice. As a result, the values essential to a sound civil society are absent from the consciousness of the Kazakh people who are thus, in turn, not able to develop respect for these values. One of the disadvantages of the modern Kazakh educational system is a tendency to underrate the actual forces shaping the worldview of Kazakh youths. The mass-media, which are going through a personnel crisis, cannot provide society with the legal and political information necessary to form the sort of legal culture required for a true civil society.

Keywords: Kazakhstan society, Legal education, legal culture.

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Authors: Gülden Küçükakça, Şefika Dilek Güven, Rahşan Kolutek, Seçil Taylan

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Objective: Nursing students face with stress factors affecting academic performance and quality of life as from first moments of their educational life. Stress causes health problems in students such as physical, psycho-social, and behavioral disorders and might damage formation of professional identity by decreasing efficiency of education. In addition to determination of stress experienced by nursing students during their education, it was aimed to help review theoretical and clinical education settings for bringing stress of nursing students into positive level and to raise awareness of educators concerning their own professional behaviors. Methods: The study was conducted with 315 students studying at nursing department of Semra and Vefa Küçük Health High School, Nevşehir Hacı Bektaş Veli University in the academic year of 2015-2016 and agreed to participate in the study. “Personal Information Form” prepared by the researchers upon the literature review and “Nursing Education Stress Scale (NESS)” were used in this study. Data were assessed with analysis of variance and correlation analysis. Results: Mean NESS Scale score of the nursing students was estimated to be 66.46±16.08 points. Conclusions: As a result of this study, stress level experienced by nursing undergraduate students during their education was determined to be high. In accordance with this result, it can be recommended to determine sources of stress experienced by nursing undergraduate students during their education and to develop approaches to eliminate these stress sources.

Keywords: Stress, nursing education, nursing student, nursing education stress.

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