Search results for: Activity Learning

Authors: Caihong Sun, Xizi Zhang

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Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: Factorization machines, feature engineering, negative ratings, recommendation systems.

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Authors: Myriam Noureddine

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During their activity, all systems must be operational without failures and in this context, the dependability concept is essential avoiding disruption of their function. As computer networks are systems with the same requirements of dependability, this article deals with an analysis of failures for a computer network. The proposed approach integrates specific tools of the plat-form KB3, usually applied in dependability studies of industrial systems. The methodology is supported by a multi-agent system formed by six agents grouped in three meta agents, dealing with two levels. The first level concerns a modeling step through a conceptual agent and a generating agent. The conceptual agent is dedicated to the building of the knowledge base from the system specifications written in the FIGARO language. The generating agent allows producing automatically both the structural model and a dependability model of the system. The second level, the simulation, shows the effects of the failures of the system through a simulation agent. The approach validation is obtained by its application on a specific computer network, giving an analysis of failures through their effects for the considered network.

Keywords: Computer network, dependability, KB3 plat-form, multi-agent system, failure.

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Authors: Mihai Caramihai, Irina Severin

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Despite the extensive use of eLearning systems, there is no consensus on a standard framework for evaluating this kind of quality system. Hence, there is only a minimum set of tools that can supervise this judgment and gives information about the course content value. This paper presents two kinds of quality set evaluation indicators for eLearning courses based on the computational process of three known metrics, the Euclidian, Hamming and Levenshtein distances. The “distance" calculus is applied to standard evaluation templates (i.e. the European Commission Programme procedures vs. the AFNOR Z 76-001 Standard), determining a reference point in the evaluation of the e-learning course quality vs. the optimal concept(s). The case study, based on the results of project(s) developed in the framework of the European Programme “Leonardo da Vinci", with Romanian contractors, try to put into evidence the benefits of such a method.

Keywords: eLearning, European programme, metrics, quality evaluation

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Authors: Ismail I. Abo-Ghanema, El-Nasharty M.A., El-Far A. H., Hanan A.Ghonium

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In this study, we investigated the effects of ginger and L-carnitine on the reproductive performance of male rats with respect to semen parameters, male sex hormones and the testicular antioxidant system. A total of sixty mature male albino rats were divided into four groups of fifteen rats. The control group received saline, whereas the other three groups received ginger (100 mg kg-1 d- 1.), L-carnitine (150 mg kg-1 d-1.) or a combination of both ginger (100 mg kg-1 d-1.) and L-carnitine (150 mg kg-1 d-1.) via a stomach tube daily for one month. At the end of the treatment period, the rats were sacrificed, and their sperm characteristics (count, motility and viability), antioxidant enzyme factors levels (reduced glutathione, catalase, superoxide dismutase and total antioxidant capacity) and sex hormone levels (testosterone, Follicle stimulating hormone(FSH) and luteinizing hormone (LH) were analysed. Our results showed that the three experimental treatments improved sperm parameters, antioxidant enzyme activity and testosterone hormone levels; the most pronounced positive effects were observed in the group that received a combination of both ginger and L-carnitine. Therefore, the administration of a combination of ginger and L-carnitine may be beneficial for improving male sexual performance.

Keywords: Ginger, L-Carnitine, Spermatogenesis, Rats.

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Authors: Hossein Morshedlou, Ahmad Abdollahzade Barforoush

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Recent developments in storage technology and networking architectures have made it possible for broad areas of applications to rely on data streams for quick response and accurate decision making. Data streams are generated from events of real world so existence of associations, which are among the occurrence of these events in real world, among concepts of data streams is logical. Extraction of these hidden associations can be useful for prediction of subsequent concepts in concept shifting data streams. In this paper we present a new method for learning association among concepts of data stream and prediction of what the next concept will be. Knowing the next concept, an informed update of data model will be possible. The results of conducted experiments show that the proposed method is proper for classification of concept shifting data streams.

Keywords: Data Stream, Classification, Concept Shift, History.

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Authors: Hazim J. Al-Daraji

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The aim of this study was to investigate the effects of supplementing the diluent of roosters' semen with different levels of olive oil on motility, viability, morphology and acrosome integrity of chicken spermatozoa after in vitro storage for up to 72 h. Semen was collected from 60 White Layer males (62 wk of age) kept in separated floor pens and randomly divided into six treatment groups (10 males in each group). Experimental groups were as follows: T1 :fresh semen, T2 : semen extended 1:1 with Al – Daraji 2 diluent (AD2D) alone, T3 – T6 :semen samples extended 1:1 with AD2D supplemented with 2 ml, 4 ml, 6 ml or 8 ml of olive oil / 100 ml of diluent, respectively. Semen samples were then stored at 5 °C for 24 h, 48 h or 72 h. There was a clear influence of diluent supplementation with olive oil on the spermatozoa motility profile; olive oil groups (T3, T4, T5 and T6) recorded the highest scores of mass activity and individual motility during all storage periods compared to T1 and T2 groups. In addition, the inclusion of olive oil into semen diluent (T3, T4, T5 and T6) gave significantly higher percentages of viable spermatozoa, normal morphologically spermatozoa and intact acrosomes irrespective of storage period. These results clearly show that supplementation the diluent of roosters' semen with olive oil can improve semen quality when semen samples in vitro stored at 5 °C for up to 72 h.

Keywords: Olive oil, diluent, liquid storage, semen quality of roosters.

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Authors: Asha Rani, Christian Micheloni, Gian Luca Foresti

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In this paper, a neural tree (NT) classifier having a simple perceptron at each node is considered. A new concept for making a balanced tree is applied in the learning algorithm of the tree. At each node, if the perceptron classification is not accurate and unbalanced, then it is replaced by a new perceptron. This separates the training set in such a way that almost the equal number of patterns fall into each of the classes. Moreover, each perceptron is trained only for the classes which are present at respective node and ignore other classes. Splitting nodes are employed into the neural tree architecture to divide the training set when the current perceptron node repeats the same classification of the parent node. A new error function based on the depth of the tree is introduced to reduce the computational time for the training of a perceptron. Experiments are performed to check the efficiency and encouraging results are obtained in terms of accuracy and computational costs.

Keywords: Neural Tree, Pattern Classification, Perceptron, Splitting Nodes.

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Authors: Mabel Ortiz, Claudio Díaz

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This paper explores Chilean pre-service teachers' perceptions about the provision of corrective feedback in a wiki environment during the collaborative writing of an argumentative essay. After conducting a semi-structured interview on 22 participants, the data were processed through the content analysis technique. The results show that students have positive perceptions about corrective feedback, provided through a wiki virtual environment, which in turn facilitates feedback provision and impacts language learning effectively. Some of the positive perceptions about virtual feedback refer to permanent access, efficiency, simultaneous revision and immediacy. It would then be advisable to integrate wiki-based feedback as a methodology for the language classroom and collaborative writing tasks.

Keywords: Argumentative essay, focused corrective feedback, perception, wiki environment.

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Authors: Ferial M. Abu-Salem, Marwa H. Mahmoud, M. H. El-Kalyoub, A. Y. Gibriel, Azza Abou-Arab

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In order to characterize the soy protein hydrolysate obtained in this study, gel chromatography on Sephadex G-25 was used to perform the separation of the peptide mixture and electrophoresis in SDS-polyacrylamide gel has been employed. Protein hydrolysate gave high antioxidant activities, but didn't give any antimicrobial activities. The antioxidant activities of protein hydrolysate was in the same trend of peptide content which gave high antioxidant activities and high peptide content between fractions 15 to 50. With increasing peptide concentrations, the scavenging effect on DPPH radical increased until about 70%, thereafter reaching a plateau. In compare to different concentrations of BHA, which exhibited higher activity (90%), soybean protein hydrolysate exhibited high antioxidant activities (70%) at a concentration of 1.45 mg/ml at fraction 25. Electrophoresis analysis indicated that, low- MW hydrolysate fractions (F1) appeared, on average, to have higher DPPH scavenging activities than high-MW fractions. These results revealed that soybean peptides probably contain substances that were proton donors and could react with free radicals to convert them to stable diamagnetic molecules. 

Keywords: Antioxidant peptides, hydrolysis, protein hydrolysate, peptide fractions.

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Authors: Magdi M. Nabi, Ding-Li Yu

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Control of a semi-batch polymerization reactor using an adaptive radial basis function (RBF) neural network method is investigated in this paper. A neural network inverse model is used to estimate the valve position of the reactor; this method can identify the controlled system with the RBF neural network identifier. The weights of the adaptive PID controller are timely adjusted based on the identification of the plant and self-learning capability of RBFNN. A PID controller is used in the feedback control to regulate the actual temperature by compensating the neural network inverse model output. Simulation results show that the proposed control has strong adaptability, robustness and satisfactory control performance and the nonlinear system is achieved.

Keywords: Chylla-Haase polymerization reactor, RBF neural networks, feed-forward and feedback control.

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Authors: Nestor A. Garcia Fragoso, Tetyana Baydyk, Ernst Kussul

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This article contains information from our investigation in the field of voice recognition. For this purpose, we created a voice database that contains different phrases in two languages, English and Spanish, for men and women. As a classifier, the LIRA (Limited Receptive Area) grayscale neural classifier was selected. The LIRA grayscale neural classifier was developed for image recognition tasks and demonstrated good results. Therefore, we decided to develop a recognition system using this classifier for voice recognition. From a specific set of speakers, we can recognize the speaker’s voice. For this purpose, the system uses spectrograms of the voice signals as input to the system, extracts the characteristics and identifies the speaker. The results are described and analyzed in this article. The classifier can be used for speaker identification in security system or smart buildings for different types of intelligent devices.

Keywords: Extreme learning, LIRA neural classifier, speaker identification, voice recognition.

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Authors: Daniel Olmos-Liceaga

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Ventricular fibrillation is a very important health problem as is the cause of most of the sudden deaths in the world. Waves of electrical activity are sent by the SA node, propagate through the cardiac tissue and activate the mechanisms of cell contraction, and therefore are responsible to pump blood to the body harmonically. A spiral wave is an abnormal auto sustainable wave that is responsible of certain types of arrhythmias. When these waves break up, give rise to the fibrillation regime, in which there is a complete loss in the coordination of the contraction of the heart muscle. Interaction of spiral waves and obstacles is also of great importance as it is believed that the attachment of a spiral wave to an obstacle can provide with a transition of two different arrhythmias. An obstacle can be partially excitable or non excitable. In this talk, we present a numerical study of the interaction of meandering spiral waves with partially and non excitable obstacles and focus on the problem where the obstacle plays a fundamental role in the switch between different spiral regimes, which represent different arrhythmic regimes. Particularly, we study the phenomenon of destabilization of spiral waves due to the presence of obstacles, a phenomenon not completely understood (This work will appear as a Chapter in a Book named Cardiac Arrhytmias by INTECH under the name "Spiral Waves, Obstacles and Cardiac Arrhythmias", ISBN 979-953-307-050-5.).

Keywords: Arrhythmias, Cardiac tissue, Obstacles, Spiral waves

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Authors: B. Geethanjali, K. Adalarasu, R. Rajsekaran

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Music has a great effect on human body and mind; it can have a positive effect on hormone system. Objective of this study is to analysis the effect of music (carnatic, hard rock and jazz) on brain activity during mental work load using electroencephalography (EEG). Eight healthy subjects without special musical education participated in the study. EEG signals were acquired at frontal (Fz), parietal (Pz) and central (Cz) lobes of brain while listening to music at three experimental condition (rest, music without mental task and music with mental task). Spectral powers features were extracted at alpha, theta and beta brain rhythms. While listening to jazz music, the alpha and theta powers were significantly (p < 0.05) high for rest as compared to music with and without mental task in Cz. While listening to Carnatic music, the beta power was significantly (p < 0.05) high for with mental task as compared to rest and music without mental task at Cz and Fz location. This finding corroborates that attention based activities are enhanced while listening to jazz and carnatic as compare to Hard rock during mental task.

Keywords: Music, Brain Function, Electroencephalography (EEG), Mental Task, Features extraction parameters

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Authors: Veruska C. Dutra, Mary L. G. S. Senna

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The principle of sustainability has been studied by different sciences with the purpose of formulating clear and concrete models. Much has been discussed about sustainability, and several points of view have been used to try to explain it; environmental science emerges from various environmental discourses that are willing to establish a new concept for understanding this complexity. This way, we focus on the activity of ecotourism as a way to integrate sustainable practices proposed by environmental science, and thus, make it possible to create a new perspective for eco-tourists and the managers of tourist destinations towards nature. The aim of this study was to suggest a direction for environmental awareness, based on environmental science, to change the eco-tourist's view of nature in ecotourism tours. The methodology used was based on a case study concerning the Jalapão State Park - JSP, located in the State of Tocantins, Northern Brazil. The study was based on discussions, theoretical studies, bibliographical research and on-site research. We have identified that to incite the tourists’ awareness, they need to visit nature to understand the environmental problems and promote actions for its preservation. We highlight in this study actions to drive their human perception through environmental science, so that the ecotourism itinerary tours to the JSP, promote a balance between the natural environment and the tourist, making them, in this way, environmental tourists.

Keywords: Science, environmental, ecotourism, Jalapão.

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Authors: Chia-Ling Chang, Chung-Sheng Liao

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The present study focuses on the discussion over the parameter of Artificial Neural Network (ANN). Sensitivity analysis is applied to assess the effect of the parameters of ANN on the prediction of turbidity of raw water in the water treatment plant. The result shows that transfer function of hidden layer is a critical parameter of ANN. When the transfer function changes, the reliability of prediction of water turbidity is greatly different. Moreover, the estimated water turbidity is less sensitive to training times and learning velocity than the number of neurons in the hidden layer. Therefore, it is important to select an appropriate transfer function and suitable number of neurons in the hidden layer in the process of parameter training and validation.

Keywords: Artificial Neural Network (ANN), sensitivity analysis, turbidity.

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Authors: Hrudaya Ku. Tripathy, B. K. Tripathy, Pradip K. Das

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Knowledge Discovery in Databases (KDD) has evolved into an important and active area of research because of theoretical challenges and practical applications associated with the problem of discovering (or extracting) interesting and previously unknown knowledge from very large real-world databases. Rough Set Theory (RST) is a mathematical formalism for representing uncertainty that can be considered an extension of the classical set theory. It has been used in many different research areas, including those related to inductive machine learning and reduction of knowledge in knowledge-based systems. One important concept related to RST is that of a rough relation. In this paper we presented the current status of research on applying rough set theory to KDD, which will be helpful for handle the characteristics of real-world databases. The main aim is to show how rough set and rough set analysis can be effectively used to extract knowledge from large databases.

Keywords: Data mining, Data tables, Knowledge discovery in database (KDD), Rough sets.

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Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. Medical dataset is a vital ingredient used in predicting patient’s health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. WEKA software was used for the implementation of the algorithms. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. From the results obtained, DTA performed better than ANN. The Root Mean Squared Error (RMSE) of MLP is 0.3913 that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: Artificial neural network, classification, decision tree, diabetes mellitus.

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Authors: Pongsiri Kingkan

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This paper aims to study the role and activities of the participants and the impact of activities created in the local area in order to sustainably develop the local areas. This study applied both qualitative and quantitative approaches presented in descriptive style; the data was collected via survey, observation and in-depth interviews with samples. The results illustrated five sorts of roles of participants of the Cicada Walking-street and four types of creative activities; recreation based, art based, cultural based, and live events. Integration of local characteristics, arts and cultures were presented creatively and interestingly. Participants are various. The roles of the participants found in the Cicada Market are group of the property and area management, entrepreneurs, leisure (entertaining persons), local people, and tourists. The good impacts on local communities are those in terms of economy, environmental friendly and local arts and cultures promoting. On the other hand, the traffic congestion, waste and the increasing of energy consumption are negative impacts from area development.

Keywords: Creative Tourism Activity, Destination Development, Sustainable Development, Walking Street.

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Authors: T. S. Shashikumar

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Radon is a radioactive gas emitted from radium, a daughter product of uranium that occurs naturally in rocks and soil. Radon, together with its decay products, emits alpha particles that can damage lung tissue. The activity concentration of ²²²Ra has been analyzed in water samples collected from borewells and rivers in and around Hassan city, Karnataka State, India. The measurements were performed by Emanometry technique. The concentration of ²²²Rn in borewell waters varies from 18.49±1.89 to 397.26±12.3 Bql^-1 with geometric mean 120.48±12.87 Bql^-1 and in river waters it varies from 92.63±9.31 to 93.98±9.51 Bql^-1 with geometric mean of 93.16±9.33 Bql^-1. In the present study, the radon concentrations are higher in Adarshanagar and Viveka Nagar which are found to be 397.26±12.3 Bql^-1 and 325.78±32.56 Bql^-1. Most of the analysed samples show a ²²²Rn concentration more than 100 Bql^-1 and this can be attributed to the geology of the area where the ground waters are located, which is predominantly of granitic characteristic. The average inhalation dose and ingestion dose in the borewell water are found to be 0.405 and 0.033 µSvy^-1; and in river water it is found to be 0.234 and 0.019 µSvy^-1, respectively. The average total effective dose rate in borewell waters and river waters are found to be 0.433 and 0.253 µSvy^-1, which does not cause any health risk to the population of Hassan region.

Keywords: Borewell, effective dose, emanometry, 222Rn.

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Authors: Nina Robson, Kenneth John Faller II, Vishalkumar Ahir, Arthur Ricardo Deps Miguel Ferreira, John Buchanan, Amarnath Banerjee

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This paper describes the development of a virtual-reality system ARWED, which will be used in physical rehabilitation of patients with reduced upper extremity mobility to increase limb Active Range of Motion (AROM). The ARWED system performs a symmetric reflection and real-time mapping of the patient’s healthy limb on to their most affected limb, tapping into the mirror neuron system and facilitating the initial learning phase. Using the ARWED, future experiments will test the extension of the action-observation priming effect linked to the mirror-neuron system on healthy subjects and then stroke patients.

Keywords: Physical rehabilitation, mirror neuron, virtual reality, stroke therapy.

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Authors: Smail Hadj Mahammed

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Translation is not merely a process of conveying the meaning from one particular language into another to overcome language barriers and ensure a good understanding; it is also a work of civilization and progress. Without the translation of Greek, Indian and Persian works, Arabic and Islamic Civilization would not have taken off, and without the translations of Arabic works into Latin, and then into European languages, the scientific and technological revolution of the modern world would not have taken place. In this context, the present paper seeks to investigate how the translation movement contributed to the Arabic and Islamic Civilizations during the Golden Age. The paper consists of three major parts: the first part provides a brief historical overview of the translation movement during the golden age, which witnessed two important eras: the Umayyad and Abbasid eras. The second part shows the main reasons why translation was a prominent cultural activity during the Golden Age and why it gained great interest from the Arabs. The last part highlights the constructive contribution of translation to the Arabic and Islamic Civilization during the period (661–1258). The results demonstrate that Arabic translation movement during the Golden Age had significantly assisted in enriching the Arabic and Islamic civilizations considering the major and important scientific works of old Greek, Indian and Persian civilizations which had been absorbed.

Keywords: Arabic and Islamic civilization, contribution, golden age, translation.

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Authors: Walsh Joe, Climstein Mike, Heazlewood Ian Timothy, Burke Stephen, Kettunen Jyrki, Adams Kent, DeBeliso Mark

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Whilst there is growing evidence that activity across the lifespan is beneficial for improved health, there are also many changes involved with the aging process and subsequently the potential for reduced indices of health. Data gathered on a subsample of 535 football code athletes, aged 31-72 yrs ( = 47.4, s = ±7.1), competing at the Sydney World Masters Games (2009) demonstrated a significantly (p < 0.001), reduced classification of obesity using Body Mass Index (BMI) when compared to the general Australian population. This evidence of improved classification in one index of health (BMI < 30) for master athletes (when compared to the general population) implies there are either improved levels of this index of health due to adherence to sport or possibly the reduced BMI is advantageous and contributes to this cohort adhering (or being attracted) to masters sport. Demonstration of this proportionately under-investigated World Masters Games population having improved health over the general population is of particular interest.

Keywords: BMI, masters athlete, rugby union, soccer, touch football.

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Authors: Ahsan Bin Tufail, Ali Abidi, Adil Masood Siddiqui, Muhammad Shahzad Younis

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An early and accurate detection of Alzheimer's disease (AD) is an important stage in the treatment of individuals suffering from AD. We present an approach based on the use of structural magnetic resonance imaging (sMRI) phase images to distinguish between normal controls (NC), mild cognitive impairment (MCI) and AD patients with clinical dementia rating (CDR) of 1. Independent component analysis (ICA) technique is used for extracting useful features which form the inputs to the support vector machines (SVM), K nearest neighbour (kNN) and multilayer artificial neural network (ANN) classifiers to discriminate between the three classes. The obtained results are encouraging in terms of classification accuracy and effectively ascertain the usefulness of phase images for the classification of different stages of Alzheimer-s disease.

Keywords: Biomedical image processing, classification algorithms, feature extraction, statistical learning.

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Authors: Slimane Ouhmad, Abdellah Halimi

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In this work, neural networks methods MLP type were applied to a database from an array of six sensors for the detection of three toxic gases. The choice of the number of hidden layers and the weight values are influential on the convergence of the learning algorithm. We proposed, in this article, a mathematical formula to determine the optimal number of hidden layers and good weight values based on the method of back propagation of errors. The results of this modeling have improved discrimination of these gases and optimized the computation time. The model presented here has proven to be an effective application for the fast identification of toxic gases.

Keywords: Back-propagation, Computing time, Fast identification, MLP neural network, Number of neurons in the hidden layer.

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Authors: Tamanna Siddiqui, M. Afshar Alam

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Censored Production Rule is an extension of standard production rule, which is concerned with problems of reasoning with incomplete information, subject to resource constraints and problem of reasoning efficiently with exceptions. A CPR has a form: IF A (Condition) THEN B (Action) UNLESS C (Censor), Where C is the exception condition. Fuzzy CPR are obtained by augmenting ordinary fuzzy production rule “If X is A then Y is B with an exception condition and are written in the form “If X is A then Y is B Unless Z is C. Such rules are employed in situation in which the fuzzy conditional statement “If X is A then Y is B" holds frequently and the exception condition “Z is C" holds rarely. Thus “If X is A then Y is B" part of the fuzzy CPR express important information while the unless part acts only as a switch that changes the polarity of “Y is B" to “Y is not B" when the assertion “Z is C" holds. The proposed approach is an attempt to discover fuzzy censored production rules from set of discovered fuzzy if then rules in the form: A(X) ÔçÆ B(Y) || C(Z).

Keywords: Uncertainty Quantification, Fuzzy if then rules, Fuzzy Censored Production Rules, Learning algorithm.

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Authors: Oguz Ustun, Erdal Bekiroglu

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In the present study, position estimation of switched reluctance motor (SRM) has been achieved on the basis of the artificial neural networks (ANNs). The ANNs can estimate the rotor position without using an extra rotor position sensor by measuring the phase flux linkages and phase currents. Flux linkage-phase current-rotor position data set and supervised backpropagation learning algorithm are used in training of the ANN based position estimator. A 4-phase SRM have been used to verify the accuracy and feasibility of the proposed position estimator. Simulation results show that the proposed position estimator gives precise and accurate position estimations for both under the low and high level reference speeds of the SRM

Keywords: Artificial neural networks, modeling andsimulation, position observer, switched reluctance motor.

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Authors: Hamide Özyürek, Metin Yılmaz

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Standard processes, similar and limited production lines, the production of high direct costs will be more accurate than the use of parts of the traditional cost systems in the literature. However, direct costs, overhead expenses, in turn, decrease the burden of increasingly sophisticated production facilities, a situation that led the researchers to look for the cost of traditional systems of alternative techniques. Variety cost management approaches for example Total quality management (TQM), just-in-time (JIT), benchmarking, kaizen costing, targeting cost, life cycle costs (LLC), activity-based costing (ABC) value engineering have been introduced. Management and cost applications have changed over the past decade and will continue to change. Modern cost systems can provide relevant and accurate cost information. These methods provide the decisions about customer, product and process improvement. The aim of study is to describe and explain the adoption and application of costing systems in SME. This purpose reports on a survey conducted during 2014 small and medium sized enterprises (SME) in Ankara. The survey results were evaluated using SPSS18 package program.

Keywords: Cost Accounting, Costing, Modern Costing Systems, Managerial Accounting.

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Authors: Seifollah Bahramikia

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Amyloid aggregation of polypeptides is related to a growing number of pathologic states known as amyloid disorders. In recent years, blocking or reversing amyloid aggregation via the use of small compounds are considered as two useful approaches in hampering the development of these diseases. In this research, we have compared the ability of several manganese-salen derivatives, as synthetic compounds, and apigenin, as a natural flavonoid, to inhibit of hen egg-white lysozyme (HEWL) aggregation, as an in vitro model system. Different spectroscopic analyses such as Thioflavin T (ThT) and Anilinonaphthalene-8-sulfonic acid (ANS) fluorescence, Congo red (CR) absorbance along with transmission electron microscopy were used in this work to monitor the HEWL aggregation kinetic and inhibition. Our results demonstrated that both type of compounds were capable to prevent the formation of lysozyme amyloid aggregation in vitro. In addition, our data indicated that synthetic compounds had higher activity to inhibit of the β-sheet structures relative to natural compound. Regarding the higher antioxidant activities of the salen derivatives, it can be concluded that in addition to aromatic rings of each of the compounds, the potent antioxidant properties of salen derivatives contributes to lower lysozyme fibril accumulation.

Keywords: Aggregation, anti-amyloidogenic, apigenin, hen egg white lysozyme, salen derivatives.

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Authors: D. Sumathi, P. Poongodi

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Cloud Computing refers to applications delivered as services over the internet, and the datacenters that provide those services with hardware and systems software. These were earlier referred to as Software as a Service (SaaS). Scheduling is justified by job components (called tasks), lack of information. In fact, in a large fraction of jobs from machine learning, bio-computing, and image processing domains, it is possible to estimate the maximum time required for a task in the job. This study focuses on Trust based scheduling to improve cloud security by modifying Heterogeneous Earliest Finish Time (HEFT) algorithm. It also proposes TR-HEFT (Trust Reputation HEFT) which is then compared to Dynamic Load Scheduling.

Keywords: Software as a Service (SaaS), Trust, Heterogeneous Earliest Finish Time (HEFT) algorithm, Dynamic Load Scheduling.

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Authors: Julio Manuel de Luis Ruiz, Javier Sedano Cibrián, Rubén Pérez Álvarez, Raúl Pereda García, Cristina Diego Soroa

Abstract:

Nowadays, the use of drones has been extended to practically any human activity. One of the main applications is focused on the surveying field. In this regard, software programs that process the images captured by the sensor from the drone in an almost automatic way have been developed and commercialized, but they only allow contrasting the results through control points. This work proposes the contrast of a 3D model obtained from a flight developed by a drone and a non-metric camera (due to its low cost), with a second model that is obtained by means of the historically-endorsed classical methods. In addition to this, the contrast is developed over a certain territory with a significant unevenness, so as to test the model generated with photogrammetry, and considering that photogrammetry with drones finds more difficulties in terms of accuracy in this kind of situations. Distances, heights, surfaces and volumes are measured on the basis of the 3D models generated, and the results are contrasted. The differences are about 0.2% for the measurement of distances and heights, 0.3% for surfaces and 0.6% when measuring volumes. Although they are not important, they do not meet the order of magnitude that is presented by salespeople.

Keywords: Accuracy, classical topographic, 3D model, photogrammetry, UAV.

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