Search results for: Activity Learning

Authors: Huay Lit Woo, Qiyun Wang

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Weblog is an Internet tool that is believed to possess great potential to facilitate learning in education. This study wants to know if weblog can be used to promote students- critical thinking. It used a group of secondary two students from a Singapore school to write weblogs as a means of substitution for their traditional handwritten assignments. The topics for the weblogging are taken from History syllabus but modified to suit the purpose of this study. Weblogs from the students were collected and analysed using a known coding system for measuring critical thinking. Results show that the topic for blogging is crucial in determining the types of critical thinking employed by the students. Students are seen to display critical thinking traits in the areas of information sourcing, linking information to arguments and viewpoints justification. Students- criticalness is more profound when the information for writing a topic is readily available. Otherwise, they tend to be less critical and subjective. The study also found that students lack the ability to source for external information suggesting that students may need to be taught information literacy in order to widen their use of critical thinking skills.

Keywords: Affordance, blog, critical thinking, perception, weblog.

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Authors: Pedro Barbosa Cabral, Neuza Pedro, Ana Mafalda Gonçalves

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The purpose of this research is the analysis of the impact of ICT-related training in the adoption of a learning management systems (LMS) for teaching practicesby faculties in a higher education institution. Based on comparative analyses the impact will be obtained by the number of LMS courses created and managed by participants in ICT for teaching workshops and those who have not attended to any workshops. Involving near 1320 LMS courses and 265 faculties, the results evidence that(i) faculties who have not attend any workshop present a larger distribution of empty courses and (ii) faculties who have attended three or more workshops managed a higher distribution of courses with a considerable level of use intensity, when compared to the others groups. These findings supportthe idea that faculty training is a crucial factor in the process of LMS integration in higher education institutions and that faculties who have been enrolled in three or more workshops develop a higher level of technical and pedagogical proficiency in LMS.

Keywords: Higher Education, Faculty Training, LMS, Comparative Analyses

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Authors: Daniel Morariu, Lucian N. Vintan, Volker Tresp

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Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of features selection methods to reduce the dimensionality of the document-representation vector. Four feature selection methods are evaluated: Random Selection, Information Gain (IG), Support Vector Machine (called SVM_FS) and Genetic Algorithm with SVM (GA_FS). We showed that the best results were obtained with SVM_FS and GA_FS methods for a relatively small dimension of the features vector comparative with the IG method that involves longer vectors, for quite similar classification accuracies. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).

Keywords: Features selection, learning with kernels, support vector machine, genetic algorithms and classification.

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Authors: Ahyoung Jeon, Geunchul Park, Jung-Hoon Ro, Gye-rok Geon

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Falls are the primary cause of accidents in people over the age of 65, and frequently lead to serious injuries. Since the early detection of falls is an important step to alert and protect the aging population, a variety of research on detecting falls was carried out including the use of accelerators, gyroscopes and tilt sensors. In exiting studies, falls were detected using an accelerometer with errors. In this study, the proposed method for detecting falls was to use two accelerometers to reject wrong falls detection. As falls are accompanied by the acceleration of gravity and rotational motion, the falls in this study were detected by using the z-axial acceleration differences between two sites. The falls were detected by calculating the difference between the analyses of accelerometers placed on two different positions on the chest of the subject. The parameters of the maximum difference of accelerations (diff_Z) and the integration of accelerations in a defined region (Sum_diff_Z) were used to form the fall detection algorithm. The falls and the activities of daily living (ADL) could be distinguished by using the proposed parameters without errors in spite of the impact and the change in the positions of the accelerometers. By comparing each of the axial accelerations, the directions of falls and the condition of the subject afterwards could be determined.In this study, by using two accelerometers without errors attached to two sites to detect falls, the usefulness of the proposed fall detection algorithm parameters, diff_Z and Sum_diff_Z, were confirmed.

Keywords: Tri-axial accelerometer, fall detection.

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Authors: H. L. Ku, K. C. Yang, S. Y. Jhou, S. C. Lee, C. S. Lin

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Characterized as rich mineral substances, low temperature, few bacteria, and stability with numerous implementation aspects on aquaculture, food, drinking, and leisure, the deep sea water (DSW) development has become a new industry in the world. It has been report that marine algae contain various biologically active compounds. This research focued on the affections in cultivating Sagrassum cristaefolium with different concentration of deep sea water(DSW) and surface sea water(SSW). After two and four weeks, the total phenolic contents were compared in Sagrassum cristaefolium culturing with different ways, and the reductive activity of them was also be tried with potassium ferricyanide. Those fresh seaweeds were dried with oven and were ground to powder. Progressively, the marine algae we cultured was extracted by water under the condition with heating them at 90Ôäâ for 1hr.The total phenolic contents were be executed using Folin–Ciocalteu method. The results were explaining as follows: the highest total phenolic contents and the best reductive ability of all could be observed on the 1/4 proportion of DSW to SSW culturing in two weeks. Furthermore, the 1/2 proportion of DSW to SSW also showed good reductive ability and plentiful phenolic compositions. Finally, we confirmed that difference proportion of DSW and SSW is the major point relating to ether the total phenolic components or the reductive ability in the Sagrassum cristaefolium. In the future, we will use this way to mass production the marine algae or other micro algae on industry applications.

Keywords: deep sea water(DSW), surface sea water(SSW), phenolic contents, reductive ability.

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Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

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This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: Landslide, limit analysis, ANN, soil properties.

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Authors: Alicia Y. C. Tang, Sharifuddin M. Zain, Noorsaadah A. Rahman, Rukaini Abdullah

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This paper discusses a qualitative simulator QRiOM that uses Qualitative Reasoning (QR) technique, and a process-based ontology to model, simulate and explain the behaviour of selected organic reactions. Learning organic reactions requires the application of domain knowledge at intuitive level, which is difficult to be programmed using traditional approach. The main objective of QRiOM is to help learners gain a better understanding of the fundamental organic reaction concepts, and to improve their conceptual comprehension on the subject by analyzing the multiple forms of explanation generated by the software. This paper focuses on the generation of explanation based on causal theories to explicate various phenomena in the chemistry subject. QRiOM has been tested with three classes problems related to organic chemistry, with encouraging results. This paper also presents the results of preliminary evaluation of QRiOM that reveal its explanation capability and usefulness.

Keywords: Artificial intelligence, explanation, ontology, organicreactions, qualitative reasoning, QPT.

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Authors: Enas M. F. El Houby, Marwa S. Hassan

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Combined therapy using Interferon and Ribavirin is the standard treatment in patients with chronic hepatitis C. However, the number of responders to this treatment is low, whereas its cost and side effects are high. Therefore, there is a clear need to predict patient’s response to the treatment based on clinical information to protect the patients from the bad drawbacks, Intolerable side effects and waste of money. Different machine learning techniques have been developed to fulfill this purpose. From these techniques are Associative Classification (AC) and Decision Tree (DT). The aim of this research is to compare the performance of these two techniques in the prediction of virological response to the standard treatment of HCV from clinical information. 200 patients treated with Interferon and Ribavirin; were analyzed using AC and DT. 150 cases had been used to train the classifiers and 50 cases had been used to test the classifiers. The experiment results showed that the two techniques had given acceptable results however the best accuracy for the AC reached 92% whereas for DT reached 80%.

Keywords: Associative Classification, Data mining, Decision tree, HCV, interferon.

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Authors: Vijayalakshmy Periaswamy S., Kevin McDaid

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Testing accounts for the major percentage of technical contribution in the software development process. Typically, it consumes more than 50 percent of the total cost of developing a piece of software. The selection of software tests is a very important activity within this process to ensure the software reliability requirements are met. Generally tests are run to achieve maximum coverage of the software code and very little attention is given to the achieved reliability of the software. Using an existing methodology, this paper describes how to use Bayesian Belief Networks (BBNs) to select unit tests based on their contribution to the reliability of the module under consideration. In particular the work examines how the approach can enhance test-first development by assessing the quality of test suites resulting from this development methodology and providing insight into additional tests that can significantly reduce the achieved reliability. In this way the method can produce an optimal selection of inputs and the order in which the tests are executed to maximize the software reliability. To illustrate this approach, a belief network is constructed for a modern software system incorporating the expert opinion, expressed through probabilities of the relative quality of the elements of the software, and the potential effectiveness of the software tests. The steps involved in constructing the Bayesian Network are explained as is a method to allow for the test suite resulting from test-driven development.

Keywords: Software testing, Test Driven Development, Bayesian Belief Networks.

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Authors: Chiung-Tsun Kuoa, Tzu-Hao Liu, Fang-Yi Lin, Tai-Hao Hsu, Hui-Yin Chen

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Hyperglycemia-mediated accumulation of advanced glycation end-products (AGEs) play a pivotal role in the development of diabetic complications by inducing inflammation. In the present study, we evaluated the possible effects of water/ethanol (1/1, v/v) extracts (WEE) and its fractions from Canarium album Raeusch. (Chinese olive) which is a fruit used on AGEs-stimulated oxidative stress and inflammation in monocytes and vascular endothelial cells. Co-incubation of EA.hy926 endothelial cells with WEE and its fractions for 24h resulted in a significant decrease of monocyte–endothelial cell adhesion, the expression of ICAM-1, generation of intracellular ROS and depletion of GSH induced by AGEs. Chinese olive fruit extracts also reduced the expression of pro-inflammatory mediates, such as TNF-α, IL-1β and IL-6 in THP-1 cells. These findings suggested that Chinese olive fruit was able to protect vascular endothelium from dysfunction induced by AGEs. 

Keywords: Advanced glycation end-products (AGEs), Canarium album Raeusch, endothelial dysfunction, inflammation.

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Authors: Chantana Insra

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The research “Buddha Images in Mudras Representing Days of a Week: Tactile Texture Design for the Blind” aims to provide original tactile format to institutions for the blind, as supplementary textbooks, to accumulate Buddhist knowledge, so that it could be extracurricular learning. The research studied on 33 students with both total and partial blindness, the latter with the ability to read Braille’s signs, of elementary 4 – 6, who are pursuing their studies on the second semester of the academic year 2013 at Bangkok School for the Blind. The researcher opted samples specifically, studied data acquired from both documents and fieldworks. Those methods must be related to the blind, tactile format production, and Buddha images in mudras representing days of a week. Afterwards, the formats will be analyzed and designed so that there would be 8 format pictures of Buddha images in mudras representing days of the week. Experts will next evaluate the media and try out.

Keywords: Blind, tactile texture, Thai Buddha images in Mudras representing days of the week.

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Authors: Fetah Eren, Ismail Sahin, Ismail Celik, Ahmet Oguz Akturk

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The aim of this study is to discover secondary school students’ perceptions related to information technologies and the connections between concepts in their cognitive structures. A word association test consisting of six concepts related to information technologies is used to collect data from 244 secondary school students. Concept maps that present students’ cognitive structures are drawn with the help of frequency data. Data are analyzed and interpreted according to the connections obtained as a result of the concept maps. It is determined students associate most with these concepts—computer, Internet, and communication of the given concepts, and associate least with these concepts—computer-assisted education and information technologies. These results show the concepts, Internet, communication, and computer, are an important part of students’ cognitive structures. In addition, students mostly answer computer, phone, game, Internet and Facebook as the key concepts. These answers show students regard information technologies as a means for entertainment and free time activity, not as a means for education.

Keywords: Word association test, cognitive structure, information technology, secondary school.

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Authors: Zhanna Mingaleva, Irina Mirskikh

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Innovational development of regions in Russia is generally faced with the essential influence from federal and local authorities. The organization of effective mechanism of innovation development (and self-development) is impossible without establishment of defined institutional conditions in the analyzed field. Creative utilization of scientific concepts and information should merge, giving rise to continuing innovation and advanced production. The paper presents an analysis of institutional conditions in the field of creation and development of innovation activity infrastructure and transferring of knowledge and skills between different economic agents in Russia. Knowledge is mainly privately owned, developed through R&D investments and incorporated into technology or a product. Innovation infrastructure is a strong concentration mechanism of advanced facilities, which are mainly located inside large agglomerations or city-regions in order to benefit from scale effects in both input markets (human capital, private financial capital) and output markets (higher education services, research services). The empirical results of the paper show that in the presence of more efficient innovation and knowledge transfer and transcoding system and of a more open attitude of economic agents towards innovation, the innovation and knowledge capacity of regional economy is much higher.

Keywords: knowledge economy, innovational development, transfer of knowledge, institutional preconditions, innovation andknowledge capacity.

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Authors: Kjersti Engan, Karl Skretting, Jostein Herredsvela, Thor Ole Gulsrud

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Texture classification is an important image processing task with a broad application range. Many different techniques for texture classification have been explored. Using sparse approximation as a feature extraction method for texture classification is a relatively new approach, and Skretting et al. recently presented the Frame Texture Classification Method (FTCM), showing very good results on classical texture images. As an extension of that work the FTCM is here tested on a real world application as detection of abnormalities in mammograms. Some extensions to the original FTCM that are useful in some applications are implemented; two different smoothing techniques and a vector augmentation technique. Both detection of microcalcifications (as a primary detection technique and as a last stage of a detection scheme), and soft tissue lesions in mammograms are explored. All the results are interesting, and especially the results using FTCM on regions of interest as the last stage in a detection scheme for microcalcifications are promising.

Keywords: detection, mammogram, texture classification, dictionary learning, FTCM

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Authors: Ilma Robo, Saimir Heta, Edona Hasanaj, Vera Ostreni

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The hybrid layer (HL), the way it is created and how it is protected against degradation over time, is the key to the clinical success of a composite restoration. The composite supports the dentinal structure exactly with the realized surface of micro-retention. Thus, this surface is in direct proportion to its size versus the duration of clinical use of composite dental restoration. Micro-retention occurs between dentin or acidified enamel and adhesive resin extensions versus pre-prepared spaces, such as hollow dentinal tubules. The way the adhesive resin binds to the acidified dentinal structure depends on the physical or chemical factors of this interrelationship between two structures with very different characteristics. During the acidification process, a precursor to the placement of the adhesive resin layer, activation of metalloproteinases of dental origin occurs, enzymes which are responsible for the degradation of the HL. These enzymes have expressed activity depending on the presence of Zn2+ or Ca2+ ions. There are several ways to inhibit these enzymes, and consequently, there are several ways to inhibit the degradation process of the HL. The study aim is to evaluate chlorhexidine (CHX) as a solution element, inhibitor of dentin activated metalloproteinases, as a result of the application of acidification. This study aims to look at this solution in advantage or contraindication theories, already published in the literature.

Keywords: Hybrid layer, chlorhexidine, degradation, smear layer.

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Authors: Wilailak Siripornadulsil, Siriyanapat Tasaku, Jutamas Buahorm, Surasak Siripornadulsil

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The objectives of this study were to isolate LAB from various sources, dietary supplement, Thai traditional fermented food, and freshwater fish and to characterize their potential as probiotic cultures. Out of 1,558 isolates, 730 were identified as LAB based on isolation on MRS agar supplemented with a bromocresol purple indicator&CaCO₃ and Gram-positive, catalase- and oxidase-negative characteristics. Eight isolates showed the potential probiotic properties including tolerance to acid, bile salt & heat, proteolytic, amylolytic & lipolytic activities and oxalate-degrading capability. They all showed the antimicrobial activity against some Gram-negative and Gram-positive pathogenic bacteria. Based on 16S rDNA sequence analysis, they were identified as Enterococcus faecalis BT2 & MG30, Leconostoc mesenteroides SW64 and Pediococcus pentosaceous BD33, CF32, NP6, PS34 & SW5. The health beneficial effects and food safety will be further investigated and developed as a probiotic or protective culture used in Nile tilapia belly flap meat fermentation.

Keywords: Lactic acid bacteria, pathogen, probiotic, protective culture.

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Authors: Hui Fang Huang Su, Jia Borror

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This study compared two different interventions for math instruction among preschoolers with autism spectrum disorder (ASD). The first intervention, a combination of discrete trial teaching and Strategies for Teaching Based on Autism Research (STAR), was the regular math curriculum utilized at the preschool. The second activity-based, naturalistic intervention was Project Mind, also known as Math is Not Difficult. The curricular interventions were randomly assigned to four preschool classrooms with ASD students and implemented over three months for Project MIND. Measurements gained during the same three months for the STAR intervention were used. A quasi-experimental, pre-test/post-test design was selected to compare which intervention was the most effective in increasing mathematical knowledge and skills among preschoolers with ASD. Standardized pre and post-test instruments included the Bracken Basic Concept Scale-3 Receptive, the Applied Problems and Calculation subtests of the Woodcock-Johnson IV Tests of Achievement, and the TEMA 3: Test of Early Mathematics Ability – Third Edition. The STAR assessment is typically administered to all preschoolers at the study site three times per year, and those results were used in this study. We anticipated that the implementation of these two approaches would lead to improvement in the mathematical knowledge and skills of children with ASD. Still, it is essential to see whether a behavioral or naturalistic teaching approach leads to more significant results.

Keywords: Autism, mathematics, preschool, special education.

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Authors: Yogesh Aggarwal

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The paper discusses the results obtained to predict reinforcement in singly reinforced beam using Neural Net (NN), Support Vector Machines (SVM-s) and Tree Based Models. Major advantage of SVM-s over NN is of minimizing a bound on the generalization error of model rather than minimizing a bound on mean square error over the data set as done in NN. Tree Based approach divides the problem into a small number of sub problems to reach at a conclusion. Number of data was created for different parameters of beam to calculate the reinforcement using limit state method for creation of models and validation. The results from this study suggest a remarkably good performance of tree based and SVM-s models. Further, this study found that these two techniques work well and even better than Neural Network methods. A comparison of predicted values with actual values suggests a very good correlation coefficient with all four techniques.

Keywords: Linear Regression, M5 Model Tree, Neural Network, Support Vector Machines.

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Authors: Chantana Insra

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The main purpose of this research aimed to create tactile texture designed media for the blind used for extra learning outside classrooms in order to enhance imagination of the blind about Himmapan creatures, furthermore, the main objective of the research focused on improving the visual disabled perception to be equal to normal people. The target group of the research is blinded students studying in The Bangkok school for the blind between grade 4-6 in the second semester of 2011 who are able to read the braille language. The research methodology consisted of the field study and the documentary study related to the blind, tactile texture designed media and Himmapan creatures. 10 pictures of tactile texture designed media were created in the designing process which began after the analysis had conducted based the primary and secondary data. The works had presented to experts in the visual disabled field who evaluated the works. After approval, the works used as prototype to teach the blind. KeywordsBlind, Himmapan Creatures, Tactile Texture.

Keywords: Blind, Himmapan Creatures, Tactile Texture.

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Authors: Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma

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Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new framework model which can be trained and adapt itself to new data and make accurate predictions. This work also throws some light on use of SVM’s methodology for text classifiers from the obtained traffic data. Finally, it emphasizes the uniqueness and adaptability of SVMs methodology appropriate for this kind of research work.

Keywords: Road accident, machine learning, support vector machines.

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Authors: Alireza Barari

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Physical activity and diet are factors that influence the body's structure. The purpose of this study was to compare the effects of four weeks of resistance training, and glutamine supplement consumption on growth hormone (GH), and Insulin-like growth factor 1 (IGF-1) Axis. 40 amateur male bodybuilders, participated in this study. They were randomly divided into four equal groups, Resistance (R), Glutamine (G), Resistance with Glutamine (RG), and Control (C). The R group was assigned to a four week resistance training program, three times/week, three sets of 10 exercises with 6-10 repetitions, at the 80-95% 1RM (One Repetition Maximum), with 120 seconds rest between sets), G group is consuming l-glutamine (0.1 g/kg^-1/day^-1), RG group resistance training with consuming L-glutamine, and C group continued their normal lifestyle without exercise training. GH, IGF1, IGFBP-III plasma levels were measured before and after the protocol. One-way ANOVA indicated significant change in GH, IGF, and IGFBP-III between the four groups, and the Tukey test demonstrated significant increase in GH, IGF1, IGFBP-III plasma levels in R, and RG group. Based upon these findings, we concluded that resistance training at 80-95% 1RM intensity, and resistance training along with oral glutamine shows significantly increase secretion of GH, IGF-1, and IGFBP-III in amateur males, but the addition of oral glutamine to the exercise program did not show significant difference in GH, IGF-1, and IGFBP-III.

Keywords: Strength, glutamine, growth hormone, insulin-like growth factor 1.

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Authors: Sultan Noman Qasem

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This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.

Keywords: Radial basis function network, Hybrid learning, Multi-objective optimization, Genetic algorithm.

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Authors: S. Barbaqadze, M. Goderdzishvili, E. Mosidze, L. Lomtadze, V. Mshvildadze, L. Bakuridze, D. Berashvili, A. Bakuridze

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This paper focuses on the formulation of phytobiotic designated for further implantation in poultry farming. Composition was meant to be water-soluble powder containing antibacterial essential oils. The development process involved Thyme, Monarda and Clary sage essential oils. The antimicrobial activity of essential oils composite was meant to be tested against gram-negative and gram-positive bacterial strains. The results are processed using the statistical program Sigma STAT. To make essential oils composition water soluble surfactants were added to them. At the first stage of the study, nine options for the optimal composition of essential oils and surfactants were developed. The effect of the amount of surfactants on the essential oils composition solubility in water has been investigated. On the basis of biopharmaceutical studies, the formulation of phytobiotic has been determined: Thyme, monarda and clary sage essential oils 2:1:1 - 100 parts; Licorice extract 5.25 parts and inhalation lactose 300 parts. A technology for the preparation of phytobiotic has been developed and a technological scheme for the preparation of phytobiotic has been made up. The research was performed within the framework of the grant project CARYS-19-363 funded be the Shota Rustaveli National Science Foundation of Georgia.

Keywords: Clary, essential oils, monarda, phytobiotics, poultry, thyme.

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Authors: Moeiz Miraoui, Chakib Tadj, Chokri ben Amar

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Devices in a pervasive computing system (PCS) are characterized by their context-awareness. It permits them to provide proactively adapted services to the user and applications. To do so, context must be well understood and modeled in an appropriate form which enhance its sharing between devices and provide a high level of abstraction. The most interesting methods for modeling context are those based on ontology however the majority of the proposed methods fail in proposing a generic ontology for context which limit their usability and keep them specific to a particular domain. The adaptation task must be done automatically and without an explicit intervention of the user. Devices of a PCS must acquire some intelligence which permits them to sense the current context and trigger the appropriate service or provide a service in a better suitable form. In this paper we will propose a generic service ontology for context modeling and a context-aware service adaptation based on a service oriented definition of context.

Keywords: Pervasive computing system, context, contextawareness, service, context modeling, ontology, adaptation, machine learning.

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Authors: Mardiati Zain, N. Jamarun, A. S. Tjakradidjaja

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The effect of phosphorus supplementation of ammoniated rice straw was studied. The in vitro experiment was carried out following the first stage of Tilley and Terry method. The treatments consisting of four diets were A = 50% ammoniated rice straw + 50% concentrate (control), B = A + 0.2% Phosphor (P) supplement, C = A + 0.4% Phosphor (P) supplement, and D = A + 0.6% Phosphor (P) supplement of dry matter. Completely randomized design was used as the experimental design with differences among treatment means were examined using Duncan multiple range test. Variables measured were total bacterial and cellulolytic bacterial population, cellulolytic enzyme activity, ammonia (NH3) and volatile fatty acid (VFA) concentrations, as fermentability indicators and synthesized microbial protein, as well as degradability indicators including dry matter (DM), organic matter (OM), neutral detergent fibre (NDF), acid detergent fibre (ADF) and cellulose. The results indicated that fermentability and degradability of diets consisting ammoniated rice straw with P supplementation were significantly higher than the control diet (P< 0.05). It is concluded that P supplementation is important to improve fermentability and degradability of rations containing ammoniated RS and concentrate. In terms of the most effective level of P supplementation occurred at a supplementation rate of 0.4% of dry matter.

Keywords: Ammoniated rice straw, phosphorus, fermentability, degradability and synthesized microbial protein.

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Authors: Elizabeth B. Varghese, M. Wilscy

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A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame. A lot of algorithms have been proposed for face recognition. Vector Quantization (VQ) based face recognition is a novel approach for face recognition. Here a new codebook generation for VQ based face recognition using Integrated Adaptive Fuzzy Clustering (IAFC) is proposed. IAFC is a fuzzy neural network which incorporates a fuzzy learning rule into a competitive neural network. The performance of proposed algorithm is demonstrated by using publicly available AT&T database, Yale database, Indian Face database and a small face database, DCSKU database created in our lab. In all the databases the proposed approach got a higher recognition rate than most of the existing methods. In terms of Equal Error Rate (ERR) also the proposed codebook is better than the existing methods.

Keywords: Face Recognition, Vector Quantization, Integrated Adaptive Fuzzy Clustering, Self Organization Map.

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Authors: Li Ni, Pen ManMan, Li KenLi

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Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: Chemical reaction optimization, expectation maximization, initial, objective function clustering.

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Authors: Berna Cantürk-Günhan, Esra Bukova-Güzel

Abstract:

The purpose of the study is to determine the primary mathematics student teachers- views related to use instructional technology tools in course of the learning process and to reveal how the sample presentations towards different mathematical concepts affect their views. This is a qualitative study involving twelve mathematics students from a public university. The data gathered from two semi-structural interviews. The first one was realized in the beginning of the study. After that the representations prepared by the researchers were showed to the participants. These representations contain animations, Geometer-s Sketchpad activities, video-clips, spreadsheets, and power-point presentations. The last interview was realized at the end of these representations. The data from the interviews and content analyses were transcribed and read and reread to explore the major themes. Findings revealed that the views of the students changed in this process and they believed that the instructional technology tools should be used in their classroom.

Keywords: Integrating Technology, Mathematics Education, Primary Education, Teacher Education.

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Authors: R. Bremananth

Abstract:

Biometric authentication is an essential task for any kind of real-life applications. In this paper, we contribute two primary paradigms to Iris recognition such as Robust Eyelash Detection (RED) using pathway kernels and hair curve fitting synthesized model. Based on these two paradigms, rotation invariant iris recognition is enhanced. In addition, the presented framework is tested with real-life iris data to provide the authentication for LRC (Learning Resource Center) users. Recognition performance is significantly improved based on the contributed schemes by evaluating real-life irises. Furthermore, the framework has been implemented using Java programming language. Experiments are performed based on 1250 diverse subjects in different angles of variations on the authentication process. The results revealed that the methodology can deploy in the process on LRC management system and other security required applications.

Keywords: Authentication, biometric, eye lashes detection, iris scanning, LRC security, secure access.

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Authors: Vandana Bali, Manab B. Bera, Parmjit S. Panesar

Abstract:

Microbial production of antimicrobials as biopreservatives is the major area of focus nowadays due to increased interest of consumers towards natural and safe preservation of ready to eat food products. The agro-industrial byproduct based medium and optimized process conditions can contribute in economical production of bacteriocins. Keeping this in view, the present investigation was carried out on agro-industrial byproducts utilization for the production of bacteriocin using Enterococcus faecium BS13 isolated from local fermented food. Different agro-industrial byproduct based carbon sources (whey, potato starch liquor, kinnow peel, deoiledrice bran and molasses), nitrogen sources (soya okra, pea pod and corn steep liquor), metal ions and surfactants were tested for optimal bacteriocin production. The effect of various process parameters such as pH, temperature, inoculum level, agitation and time were also tested on bacteriocin production. The optimized medium containing whey, supplemented with 4%corn steep liquor and polysorbate-80 displayed maximum bacteriocin activity with 2% inoculum, at pH 6.5, temperature 40^oC under shaking conditions (100 rpm).

Keywords: Bacteriocin, biopreservation, corn steep liquor, Enterococcus faecium, waste utilization, whey.

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