Search results for: Knowledge based systems in medicine

Authors: S.K. Mazloomi, Nasri b. Sulaiman

Abstract:

By analyzing the sources of energy and power loss in PWM (Pulse Width Modulation) controlled drivers of water electrolysis cells, it is possible to reduce the power dissipation and enhance the efficiency of such hydrogen production units. A PWM controlled power driver is based on a semiconductor switching element where its power dissipation might be a remarkable fraction of the total power demand of an electrolysis system. Power dissipation in a semiconductor switching element is related to many different parameters which could be fitted into two main categories: switching losses and conduction losses. Conduction losses are directly related to the built, structure and capabilities of a switching device itself and indeed the conditions in which the element is handling the switching application such as voltage, current, temperature and of course the fabrication technology. On the other hand, switching losses have some other influencing variables other than the mentioned such as control system, switching method and power electronics circuitry of the PWM power driver. By analyzings the characteristics of recently developed power switching transistors from different families of Bipolar Junction Transistors (BJT), Metal Oxide Semiconductor Field Effect Transistors (MOSFET) and Insulated Gate Bipolar Transistors (IGBT), some recommendations are made in this paper which are able to lead to achieve higher hydrogen production efficiency by utilizing PWM controlled water electrolysis cells.

Keywords: Power switch, PWM, Semiconductor switch, Waterelectrolysis

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Authors: Muhamad S., Norasrudin S, Rahmat A.

Abstract:

The objective of current study is to investigate the differences of winning and losing teams in terms of goal scoring and passing sequences. Total of 31 matches from UEFA-EURO 2012 were analyzed and 5 matches were excluded from analysis due to matches end up drawn. There are two groups of variable used in the study which is; i. the goal scoring variable and: ii. passing sequences variable. Data were analyzed using Wilcoxon matched pair rank test with significant value set at p < 0.05. Current study found the timing of goal scored was significantly higher for winning team at 1st half (Z=-3.416, p=.001) and 2nd half (Z=-3.252, p=.001). The scoring frequency was also found to be increase as time progressed and the last 15 minutes of the game was the time interval the most goals scored. The indicators that were significantly differences between winning and losing team were the goal scored (Z=-4.578, p=.000), the head (Z=-2.500, p=.012), the right foot (Z=-3.788,p=.000), corner (Z=-.2.126,p=.033), open play (Z=-3.744,p=.000), inside the penalty box (Z=-4.174, p=.000) , attackers (Z=-2.976, p=.003) and also the midfielders (Z=-3.400, p=.001). Regarding the passing sequences, there are significance difference between both teams in short passing sequences (Z=-.4.141, p=.000). While for the long passing, there were no significance difference (Z=-.1.795, p=.073). The data gathered in present study can be used by the coaches to construct detailed training program based on their objectives.

Keywords: Football, goals scored, passing, timing.

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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: N. Boshkova, K. Kamburova, N. Tabakova, N. Boshkov, Ts. Radeva

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Coatings based on polyaniline (PANI) can improve the resistance of steel against corrosion. In this work, the preparation of stable suspensions of colloidal PANI-SiO₂ particles, suitable for obtaining of composite anticorrosive coating on steel, is described. Electrokinetic data as a function of pH are presented, showing that the zeta potentials of the PANI-SiO₂ particles are governed primarily by the charged groups at the silica oxide surface. Electrosteric stabilization of the PANI-SiO₂ particles’ suspension against aggregation is realized at pH>5.5 (EB form of PANI) by adsorption of positively charged polyelectrolyte molecules onto negatively charged PANI-SiO₂ particles. The PANI-SiO₂ particles are incorporated by electrodeposition into the metal matrix of zinc in order to obtain composite (hybrid) coatings. The latter are aimed to ensure sacrificial protection of steel mainly in aggressive media leading to local corrosion damages. The surface morphology of the composite zinc coatings is investigated with SEM. The influence of PANI-SiO₂ particles on the cathodic and anodic processes occurring in the starting electrolyte for obtaining of the coatings is followed with cyclic voltammetry. The electrochemical and corrosion behavior is evaluated with potentiodynamic polarization curves and polarization resistance measurements. The beneficial effect of the stabilized PANI-SiO₂ particles for the increased protective ability of the composites is commented and discussed.

Keywords: Corrosion, polyaniline particles, zinc, protective ability.

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Authors: Shu-Yin Yu

Abstract:

With the advancement of artificial intelligence technology, most companies are aware of the profound potential of artificial intelligence in commercial marketing. Man-machine dialogue has become the latest trend in marketing customer service. However, chatbots are often considered to be lack of intelligent or unfriendly conversion, which instead reduces the communication effect of chatbots. To ensure that chatbots represent the brand image and provide a good user experience, companies and users attach great importance. In this study, customer service chatbot was used as the research sample. The research variables are based on the theory of artificial intelligence emotions, integrating the technology acceptance model and innovation diffusion theory, and the three aspects of pleasure, arousal, and dominance of the human-machine PAD (Pleasure, Arousal and Dominance) dimension. The results show that most of the participants have a higher acceptance of innovative technologies and are high pleasure and arousal in the user experience. Participants still have traditional gender (female) service stereotypes about customer service chatbots. Users who have high trust in using chatbots can easily enhance brand acceptance and easily accept brand messages, extend the trust of chatbots to trust in the brand, and develop a positive attitude towards the brand.

Keywords: Brand attitude, chatbot, emotional interaction, user experience.

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Authors: Mine Uslu Uysal

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This paper interested in the mechanical deformation behavior of shear deformable functionally graded ceramic-metal (FGM) plates. Theoretical formulations are based on power law theory when build up functional graded material. The mechanical properties of the plate are graded in the thickness direction according to a power-law Displacement and stress is obtained using finite element method (FEM). The load is supposed to be a uniform distribution over the plate surface (XY plane) and varied in the thickness direction only. An FGM’s gradation in material properties allows the designer to tailor material response to meet design criteria. An FGM made of ceramic and metal can provide the thermal protection and load carrying capability in one material thus eliminating the problem of thermo-mechanical deformation behavior. This thesis will explore analysis of FGM flat plates and shell panels, and their applications to r structural problems. FGMs are first characterized as flat plates under pressure in order to understand the effect variation of material properties has on structural response. In addition, results are compared to published results in order to show the accuracy of modeling FGMs using ABAQUS software.

Keywords: Functionally graded material, finite element method, thermal and structural loading.

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

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With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: Activities of daily living, classification, internet of things, machine learning, smart home.

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Authors: C. Gunavathi, K. Premalatha

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Microarray technology is universally used in the study of disease diagnosis using gene expression levels. The main shortcoming of gene expression data is that it includes thousands of genes and a small number of samples. Abundant methods and techniques have been proposed for tumor classification using microarray gene expression data. Feature or gene selection methods can be used to mine the genes that directly involve in the classification and to eliminate irrelevant genes. In this paper statistical measures like T-Statistics, Signal-to-Noise Ratio (SNR) and F-Statistics are used to rank the genes. The ranked genes are used for further classification. Particle Swarm Optimization (PSO) algorithm and Shuffled Frog Leaping (SFL) algorithm are used to find the significant genes from the top-m ranked genes. The Naïve Bayes Classifier (NBC) is used to classify the samples based on the significant genes. The proposed work is applied on Lung and Ovarian datasets. The experimental results show that the proposed method achieves 100% accuracy in all the three datasets and the results are compared with previous works.

Keywords: Microarray, T-Statistics, Signal-to-Noise Ratio, FStatistics, Particle Swarm Optimization, Shuffled Frog Leaping, Naïve Bayes Classifier.

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Authors: T. Mokhele, O. Mutanga, F. Ahmed

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South Africa is one of the few countries that have stopped using the same Enumeration Areas (EAs) for census enumeration and dissemination. The advantage of this change is that confidentiality issue could be addressed for census dissemination as the design of geographic unit for collection is mainly to ensure that this unit is covered by one enumerator. The objective of this paper was to evaluate the performance of automated zone design output areas against non-zone design developed geographies using the 2001 census data, and 2011 census to some extent, as the main input. The comparison of the Automated Zone-design Tool (AZTool) census output areas with the Small Area Layers (SALs) and SubPlaces based on confidentiality limit, population distribution, and degree of homogeneity, as well as shape compactness, was undertaken. Further, SPSS was employed for validation of the AZTool output results. The results showed that AZTool developed output areas out-perform the existing official SAL and SubPlaces with regard to minimum population threshold, population distribution and to some extent to homogeneity. Therefore, it was concluded that AZTool program provides a new alternative to the creation of optimised census output areas for dissemination of population census data in South Africa.

Keywords: AZTool, enumeration areas, small areal layers, South Africa.

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Authors: Hachem Ben Naceur, Amel Ben Rejeb Jenhani, Mohamed Salah Romdhane

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Endemic Artemia franciscana populations can be found throughout the American continent and also as an introduced specie in several country all over the world, such as in the Mediterranean region where Artemia franciscana was identified as an invasive specie replacing native Artemia parthenogenetica and Artemia salina. In the present study, the characterization of the new invasive Artemia franciscana reported from Sabkhet Halk El-Menzel (Tunisia) was done based on the cysts biometry, nauplii instar-I length, Adult sexual dimorphism and fatty acid profile. The mean value of the diameter of non-decapsulated and decapsulated cysts, chorion thickness and naupliar length is 235.8, 226.3, 4.75 and 426.8 μm, respectively. Sexual dimorphism for adults specimen showed that maximal distance between compound eyes, diameter for compound eyes, length of first antenna and the abdomen length compared to the total body length ratio, are the most important variables for males and females discrimination with a total contribution of 62.39 %. The analysis of fatty acid methyl esters profile of decapsulated cysts resulted in low levels of linolenic acid (LLA, C18:3n-3) and high levels of eicosapentaenoic acid (EPA, C20:5n-3) with 3.11 and 11.10 %, respectively. Low quantity of docosahexaenoic acid (DHA, 22:6n-3) was also observed with 0.17 mg.g-1 dry weight.

Keywords: Invasive Artemia franciscana, biometry, sexualdimorphism, fatty acid, Tunisia.

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Authors: N. F. Hanna, A. M. Haridy

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One of the main drawbacks of the Modal Pushover Analysis (MPA) is the need to perform nonlinear time-history analysis, which complicates the analysis method and time. A simplified version of the MPA has been proposed based on the concept of the inelastic deformation ratio. Furthermore, the effect of the higher modes of vibration is considered by assuming linearly-elastic responses, which enables the use of standard elastic response spectrum analysis. In this thesis, the simplified MPA (SMPA) method is applied to determine the target global drift and the inter-story drifts of steel frame building. The effect of the higher vibration modes is considered within the framework of the SMPA. A comprehensive survey about the inelastic deformation ratio is presented. After that, a suitable expression from literature is selected for the inelastic deformation ratio and then implemented in the SMPA. The estimated seismic demands using the SMPA, such as target drift, base shear, and the inter-story drifts, are compared with the seismic responses determined by applying the standard MPA. The accuracy of the estimated seismic demands is validated by comparing with the results obtained by the nonlinear time-history analysis using real earthquake records.

Keywords: Modal analysis, pushover analysis, seismic performance, target displacement.

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Authors: Ahmad Sharif Ahmadi, Yoshitaka Kajita

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With massive population expansion and fast economic development in last decade, urban land has increasingly expanded and formed high informal development territory in Kabul city. This paper investigates integrated urbanization trends in Kabul city since the formation of the basic structure of the present city using GIS and remote sensing. This study explores the spatial and temporal difference of urban land expansion and land use categories among different time intervals, 1964-1978 and 1978-2008 from 1964 to 2008 in Kabul city. Furthermore, the goal of this paper is to understand the extent of urban land expansion and the factors driving urban land expansion in Kabul city. Many factors like population expansion, the return of refugees from neighboring countries and significant economic growth of the city affected urban land expansion. Across all the study area urban land expansion rate, population expansion rate and economic growth rate have been compared to analyze the relationship of driving forces with urban land expansion. Based on urban land change data detected by interpreting land use maps, it was found that in the entire study area the urban territory has been expanded by 14 times between 1964 and 2008.

Keywords: GIS, Kabul city, land use, urban land expansion, urbanization.

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Authors: Sanae Attioui, Said Najah

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The Earth's surface is constantly changing through forces of nature and human activities. Reliable, accurate, and timely change detection is critical to environmental monitoring, resource management, and planning activities. Recently, interest in deep learning algorithms, especially convolutional neural networks, has increased in the field of image change detection due to their powerful ability to extract multi-level image features automatically. However, these networks are prone to drawbacks that limit their applications, which reside in their inability to capture spatial relationships between image instances, as this necessitates a large amount of training data. As an alternative, Capsule Network has been proposed to overcome these shortcomings. Although its effectiveness in remote sensing image analysis has been experimentally verified, its application in change detection tasks remains very sparse. Motivated by its greater robustness towards improved hierarchical object representation, this study aims to apply a capsule network for PolSAR image Change Detection. The experimental results demonstrate that the proposed change detection method can yield a significantly higher detection rate compared to methods based on convolutional neural networks.

Keywords: Change detection, capsule network, deep network, Convolutional Neural Networks, polarimetric synthetic aperture radar images, PolSAR images.

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Authors: Farhad Alizadeh, Alireza Faregh Gharamaleki, Mojtaba Jalilzadeh, Houshang Gholami, Ali Akhoundzadeh

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This study presented hybrid pre-processing approach along with a conceptual model to enhance the accuracy of river discharge prediction. In order to achieve this goal, Ensemble Empirical Mode Decomposition algorithm (EEMD), Discrete Wavelet Transform (DWT) and Mutual Information (MI) were employed as a hybrid pre-processing approach conjugated to Least Square Support Vector Machine (LSSVM). A conceptual strategy namely multi-station model was developed to forecast the Souris River discharge more accurately. The strategy used herein was capable of covering uncertainties and complexities of river discharge modeling. DWT and EEMD was coupled, and the feature selection was performed for decomposed sub-series using MI to be employed in multi-station model. In the proposed feature selection method, some useless sub-series were omitted to achieve better performance. Results approved efficiency of the proposed DWT-EEMD-MI approach to improve accuracy of multi-station modeling strategies.

Keywords: River stage-discharge process, LSSVM, discrete wavelet transform (DWT), ensemble empirical decomposition mode (EEMD), multi-station modeling.

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Authors: Adam L. Yanagihara, Yong Seok Park

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The goal of this paper is to converge upon a design of a brake system that could be used for a roller coaster found at an amusement park. It was necessary to find what could be deemed as a “comfortable” deceleration so that passengers do not feel as if they are suddenly jerked and pressed against the restraining harnesses. A human factors engineering approach was taken in order to determine this deceleration. Using a previous study that tested the deceleration of transit vehicles, it was found that a -0.45 G deceleration would be used as a design requirement to build this system around. An adjustable linear eddy current brake using permanent magnets would be the ideal system to use in order to meet this design requirement. Anthropometric data were then used to determine a realistic weight and length of the roller coaster that the brake was being designed for. The weight and length data were then factored into magnetic brake force equations. These equations were used to determine how the brake system and the brake run layout would be designed. A final design for the brake was determined and it was found that a total of 12 brakes would be needed with a maximum braking distance of 53.6 m in order to stop a roller coaster travelling at its top speed and loaded to maximum capacity. This design is derived from theoretical calculations, but is within the realm of feasibility.

Keywords: Eddy current brake, engineering design, human factors engineering.

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Authors: Wipada Chaiwchan, Patcharee Klinhom

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This research is aimed to develop the online-class scheduling management system and improve as a complex problem solution, this must take into consideration in various conditions and factors. In addition to the number of courses, the number of students and a timetable to study, the physical characteristics of each class room and regulations used in the class scheduling must also be taken into consideration. This system is developed to assist management in the class scheduling for convenience and efficiency. It can provide several instructors to schedule simultaneously. Both lecturers and students can check and publish a timetable and other documents associated with the system online immediately. It is developed in a web-based application. PHP is used as a developing tool. The database management system was MySQL. The tool that is used for efficiency testing of the system is questionnaire. The system was evaluated by using a Black-Box testing. The sample was composed of 2 groups: 5 experts and 100 general users. The average and the standard deviation of results from the experts were 3.50 and 0.67. The average and the standard deviation of results from the general users were 3.54 and 0.54. In summary, the results from the research indicated that the satisfaction of users were in a good level. Therefore, this system could be implemented in an actual workplace and satisfy the users’ requirement effectively.

Keywords: Timetable, schedule, management system, online.

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Authors: B. Varaprasad, C. Srinivasa Rao

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In the manufacturing sector, hard turning has emerged as vital machining process for cutting hardened steels. Besides many advantages of hard turning operation, one has to implement to achieve close tolerances in terms of surface finish, high product quality, reduced machining time, low operating cost and environmentally friendly characteristics. In the present study, three-dimensional CAE (Computer Aided Engineering) based simulation of  hard turning by using commercial software DEFORM 3D has been compared to experimental results of  stresses, temperatures and tool forces in machining of AISI D3 steel using mixed Ceramic inserts (CC6050). In the present analysis, orthogonal cutting models are proposed, considering several processing parameters such as cutting speed, feed, and depth of cut. An exhaustive friction modeling at the tool-work interfaces is carried out. Work material flow around the cutting edge is carefully modeled with adaptive re-meshing simulation capability. In process simulations, feed rate and cutting speed are constant (i.e.,. 0.075 mm/rev and 155 m/min), and analysis is focused on stresses, forces, and temperatures during machining. Close agreement is observed between CAE simulation and experimental values.

Keywords: Hard-turning, computer-aided engineering, computational machining, finite element method.

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Authors: A.H. Sajedipoor, N. Hedayat, A.Rohani, Z.Yazdi

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Sediment formation and its transport along the river course is considered as important hydraulic consideration in river engineering. Their impact on the morphology of rivers on one hand and important considerations of which in the design and construction of the hydraulic structures on the other has attracted the attention of experts in arid and semi-arid regions. Under certain conditions where the momentum energy of the flow stream reaches a specific rate, the sediment materials start to be transported with the flow. This can usually be analyzed in two different categories of suspended and bed load materials. Sedimentation phenomenon along the waterways and the conveyance of vast volume of materials into the canal networks can potentially influence water abstraction in the intake structures. This can pose a serious threat to operational sustainability and water delivery performance in the canal networks. The situation is serious where ineffective watershed management (poor vegetation cover in the water basin) is the underlying cause of soil erosion which feeds the materials into the waterways that intern would necessitate comprehensive study. The present paper aims to present an analytical investigation of the sediment process in the waterways on one hand and estimation of the sediment load transport into the lined canals using the SHARC software on the other. For this reason, the paper focuses on the comparative analysis of the hydraulic behaviors of the Sabilli main canal that feeds the pumping station with that of the Western canal in the Greater Dezful region to identify effective factors in sedimentation and ways of mitigating their impact on water abstraction in the canal systems. The method involved use of observational data available in the Dezful Dastmashoon hydrometric station along a 6 km waterway of the Sabilli main canal using the SHARC software to estimate the suspended load concentration and bed load materials. Results showed the transport of a significant volume of sediment loads from the waterways into the canal system which is assumed to have arisen from the absence of stilling basin on one hand and the gravity flow on the other has caused serious challenges. This is contrary to what occurs in the Sabilli canal, where the design feature which incorporates a settling basin just before the pumping station is the major cause of reduced sediment load transport into the canal system.Results showed that modification of the present design features by constructing a settling basin just upstream of the western intake structure can considerably reduce the entry of sediment materials into the canal system. Not only this can result in the sustainability of the hydraulic structures but can also improve operational performance of water conveyance and distribution system, all of which are the pre-requisite to secure reliable and equitable water delivery regime for the command area.

Keywords: Sedimentation, main canal, Sabilli, western canal, dez diversion weir.

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Authors: O. F. Elkommos

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Teaching and learning EFL speaking modules is one of the most challenging productive modules for both instructors and learners. In a student-centered interactive communicative language teaching approach, learners and instructors should be aware of the fact that the target language must be taught as/for communication. The student must be empowered by tools that will work on more than one level of their communicative competence. Communicative learning will need a teaching and learning methodology that will address the goal. Teaching turn-taking rules, pragmatic principles and speech acts will enhance students' sociolinguistic competence, strategic competence together with discourse competence. Sociolinguistic competence entails the mastering of speech act conventions and illocutionary acts of refusing, agreeing/disagreeing; emotive acts like, thanking, apologizing, inviting, offering; directives like, ordering, requesting, advising, and hinting, among others. Strategic competence includes enlightening students’ consciousness of the various particular turn-taking systemic rules of organizing techniques of opening and closing conversation, adjacency pairs, interrupting, back-channeling, asking for/giving opinion, agreeing/disagreeing, using natural fillers for pauses, gaps, speaker select, self-select, and silence among others. Students will have the tools to manage a conversation. Students are engaged in opportunities of experiencing the natural language not as a mere extra student talking time but rather an empowerment of knowing and using the strategies. They will have the component items they need to use as well as the opportunity to communicate in the target language using topics of their interest and choice. This enhances students' communicative abilities. Available websites and textbooks now use one or more of these tools of turn-taking or pragmatics. These will be students' support in self-study in their independent learning study hours. This will be their reinforcement practice on e-Learning interactive activities. The students' target is to be able to communicate the intended meaning to an addressee that is in turn able to infer that intended meaning. The combination of these tools will be assertive and encouraging to the student to beat the struggle with what to say, how to say it, and when to say it. Teaching the rules, principles and techniques is an act of awareness raising method engaging students in activities that will lead to their pragmatic discourse competence. The aim of the paper is to show how the suggested pragmatic model will empower students with tools and systems that would support their learning. Supporting students with turn taking rules, speech act theory, applying both to texts and practical analysis and using it in speaking classes empowers students’ pragmatic discourse competence and assists them to understand language and its context. They become more spontaneous and ready to learn the discourse pragmatic dimension of the speaking techniques and suitable content. Students showed a better performance and a good motivation to learn. The model is therefore suggested for speaking modules in EFL classes.

Keywords: Communicative competence, EFL, empowering learners, enhance learning, speech acts, teaching speaking, turn-taking, learner centered, pragmatics.

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Authors: J.-C. Cexus, A.O. Boudraa

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In this paper, a new approach for target recognition based on the Empirical mode decomposition (EMD) algorithm of Huang etal. [11] and the energy tracking operator of Teager [13]-[14] is introduced. The conjunction of these two methods is called Teager-Huang analysis. This approach is well suited for nonstationary signals analysis. The impulse response (IR) of target is first band pass filtered into subsignals (components) called Intrinsic mode functions (IMFs) with well defined Instantaneous frequency (IF) and Instantaneous amplitude (IA). Each IMF is a zero-mean AM-FM component. In second step, the energy of each IMF is tracked using the Teager energy operator (TEO). IF and IA, useful to describe the time-varying characteristics of the signal, are estimated using the Energy separation algorithm (ESA) algorithm of Maragos et al .[16]-[17]. In third step, a set of features such as skewness and kurtosis are extracted from the IF, IA and IMF energy functions. The Teager-Huang analysis is tested on set of synthetic IRs of Sonar targets with different physical characteristics (density, velocity, shape,? ). PCA is first applied to features to discriminate between manufactured and natural targets. The manufactured patterns are classified into spheres and cylinders. One hundred percent of correct recognition is achieved with twenty three echoes where sixteen IRs, used for training, are free noise and seven IRs, used for testing phase, are corrupted with white Gaussian noise.

Keywords: Target recognition, Empirical mode decomposition, Teager-Kaiser energy operator, Features extraction.

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Authors: A. Faro, D. Giordano, F. Maiorana

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Data mining uses a variety of techniques each of which is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optimize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is able to automatically suggest a strategy to optimize the number of classes optimization, but also support both tree classifications and semi-lattice organizations of the classes to give to the users the possibility of passing from one class to the ones with which it has some aspects in common. Examples of using tree and semi-lattice classifications are given to illustrate advantages and problems. The tool is applied to classify macroeconomic data that report the most developed countries- import and export. It is possible to classify the countries based on their economic behaviour and use the tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation. Possible interrelationships between the classes and their meaning are also discussed.

Keywords: Unsupervised classification, Kohonen networks, macroeconomics, Visual data mining, Cluster interpretation.

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Authors: Dipali Bansal, Rashima Mahajan, Shweta Singh, Dheeraj Rathee, Sujit Roy

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Non-invasive Brain Computer Interface like Electroencephalography (EEG) which directly taps neurological signals, is being widely explored these days to connect paralytic patients/elderly with the external environment. However, in India the research is confined to laboratory settings and is not reaching the mass for rehabilitation purposes. An attempt has been made in this paper to analyze real time acquired EEG signal using cost effective and portable headset unit EMOTIV. Signal processing of real time acquired EEG is done using EEGLAB in MATLAB and EDF Browser application software platforms. Independent Component Analysis algorithm of EEGLAB is explored to identify deliberate eye blink in the attained neural signal. Time Frequency transforms and Data statistics obtained using EEGLAB along with component activation results of EDF browser clearly indicate voluntary eye blink in AF3 channel. The spectral analysis indicates dominant frequency component at 1.536000Hz representing the delta wave component of EEG during voluntary eye blink action. An algorithm is further designed to generate an active high signal based on thoughtful eye blink that can be used for plethora of control applications for rehabilitation.

Keywords: Brain Computer Interface, EDF Browser, EEG, EEGLab, EMOTIV, Real time Acquisition

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Authors: I. Badhrees

Abstract:

This paper is an attempt to describe some of the results that had been found through a journey of study in the field of particle physics. This study consists of two parts, one about the measurement of the cross section of the decay of the Z particle in two electrons, and the other deals with the measurement of the cross section of the multi-photon absorption process using a beam of Laser in the Liquid Argon Time Projection Chamber.

The first part of the paper concerns the results based on the analysis of a data sample containing 8120 ee candidates to reconstruct the mass of the Z particle for each event where each event has an ee pair with PT_(e) > 20GeV, and η_(e) < 2.5. Monte Carlo templates of the reconstructed Z particle were produced as a function of the Z mass scale. The distribution of the reconstructed Z mass in the data was compared to the Monte Carlo templates, where the total cross section is calculated to be equal to 1432pb.

The second part concerns the Liquid Argon Time Projection Chamber, LAr TPC, the results of the interaction of the UV Laser, Nd-YAG with λ= 266mm, with LAr and through the study of the multi-photon ionization process as a part of the R&D at Bern University. The main result of this study was the cross section of the process of the multi-photon ionization process of the LAr, σ_e = 1.24±0.10stat±0.30sys.10 -56cm⁴.

Keywords: ATLAS, CERN, KACST, LArTPC, Particle Physics.

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Authors: Ameleh Aghajanloo, Moharam Dolatshahi Pirouz, Masoud Montazeri Namin

Abstract:

In this paper, a two-dimensional (2D) numerical model for the tidal currents simulation in Persian Gulf is presented. The model is based on the depth averaged equations of shallow water which consider hydrostatic pressure distribution. The continuity equation and two momentum equations including the effects of bed friction, the Coriolis effects and wind stress have been solved. To integrate the 2D equations, the Alternative Direction Implicit (ADI) technique has been used. The base of equations discritization was finite volume method applied on rectangular mesh. To evaluate the model validation, a dam break case study including analytical solution is selected and the comparison is done. After that, the capability of the model in simulation of tidal current in a real field is represented by modeling the current behavior in Persian Gulf. The tidal fluctuations in Hormuz Strait have caused the tidal currents in the area of study. Therefore, the water surface oscillations data at Hengam Island on Hormoz Strait are used as the model input data. The check point of the model is measured water surface elevations at Assaluye port. The comparison between the results and the acceptable agreement of them showed the model ability for modeling marine hydrodynamic.

Keywords: Persian Gulf, Tidal Currents, Shallow Water Equations, Finite Volumes

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Authors: Sunil Patel, Pallab Maji

Abstract:

To study the effect of adversarial attack environment must be controlled. Autonomous driving includes mainly 5 phases sense, perceive, map, plan, and drive. Autonomous vehicles sense their surrounding with the help of different sensors like cameras, radars, and lidars. Deep learning techniques are considered Blackbox and found to be vulnerable to adversarial attacks. In this research, we study the effect of the various known adversarial attacks with the help of the Unreal Engine-based, high-fidelity, real-time raytraced simulated environment. The goal of this experiment is to find out if adversarial attacks work in moving vehicles and if an unknown network may be targeted. We discovered that the existing Blackbox and Whitebox attacks have varying effects on different traffic signs. We observed that attacks that impair detection in static scenarios do not have the same effect on moving vehicles. It was found that some adversarial attacks with hardly noticeable perturbations entirely blocked the recognition of certain traffic signs. We observed that the daylight condition has a substantial impact on the model's performance by simulating the interplay of light on traffic signs. Our findings have been found to closely resemble outcomes encountered in the real world.

Keywords: Adversarial attack simulation, computer simulation, ray-traced environment, realistic simulation, unreal engine.

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Authors: Pavel Adámek

Abstract:

This study examines perception of environmental approach in small and medium-sized enterprises (SMEs) – the process by which firms integrate environmental concern into business. Based on a review of the literature, the paper synthesizes focus on environmental issues with the reflection in a case study in the Czech Republic. Two themes of corporate environmentalism are discussed – corporate environmental orientation and corporate stances toward environmental concerns. It provides theoretical material on greening organizational culture that is helpful in understanding the response of contemporary business to environmental problems. We integrate theoretical predictions with empirical findings confronted with reality. Scales to measure these themes are tested in a survey of managers in 229 Czech firms. We used the process of in-depth questioning. The research question was derived and answered in the context of the corresponding literature and conducted research. A case study showed us that environmental approach is variety different (depending on the size of the firm) in SMEs sector. The results of the empirical mapping demonstrate Czech company’s approach to environment and define the problem areas and pinpoint the main limitation in the expansion of environmental aspects. We contribute to the debate for recognition of the particular role of environmental issues in business reality.

Keywords: Corporate environmentalism, Czech Republic, empirical mapping, environmental performance.

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Authors: Lei Dou, Mitsuhiro Nakagawa, Fei Yan, Ping Li

Abstract:

Participation in global trade means that Chinas vegetables and fruits industry faces international food safety standards and increased scrutiny worldwide. The objectives of this paper were to investigate how existing food safety standards and regulations in the importing countries impact the export of vegetables and fruits from China. This paper discussed the current and historical situations of Chinas vegetables and fruits export from 1996 to 2010, analyzed the Maximum Residual Limit (MRL) standards of pesticides imposed by importing countries, quantitatively estimated the impacts of food safety standards on Chinas vegetables and fruits export based on a gravity model. The results showed that although transportation distance between trade partners and tariff rates on vegetables and fruits were still the importantly resistant factors for China export, vegetables and fruits export was sensitive to the number of regulated pesticides, the strictness, and the level of food safety standards imposed by importing countries, which showed a significant trade flow effect, stricter food safety standards, increased number of regulated pesticides significantly inhibit China export of vegetables and fruits. Moreover, Chinas food safety standards also showed a significantly effect on vegetables and fruits export, which inhibited export to some extent. KeywordsFood safety standards, MRL, Vegetables, Fruits, Export.

Keywords: Food safety standards, MRL, Vegetables, Fruits, Export.

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Authors: Amine Rezzoug, Said Abdi, Nadjet Bouhelal, Ismail Daoud

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This paper investigates the application of metallic coatings on high fiber volume fraction carbon/epoxy polymer matrix composites. For the grip of the metallic layer, a method of modifying the surface of the composite by introducing a mixture of copper and steel powder (filler powders) which can reduce the impact of thermal spray particles. The powder was introduced to the surface at the time of the forming. Arc spray was used to project the zinc coating layer. The substrate was grit blasted to avoid poor adherence. The porosity, microstructure, and morphology of layers are characterized by optical microscopy, SEM and image analysis. The samples were studied also in terms of hardness and erosion resistance. This investigation did not reveal any visible evidence damage to the substrates. The hardness of zinc layer was about 25.94 MPa and the porosity was around (∼6.70%). The erosion test showed that the zinc coating improves the resistance to erosion. Based on the results obtained, we can conclude that thermal spraying allows the production of protective coating on PMC. Zinc coating has been identified as a compatible material with the substrate. The filler powders layer protects the substrate from the impact of hot particles and allows avoiding the rupture of brittle carbon fibers.

Keywords: Arc spray, coating, composite, erosion.

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Authors: Hariton N. Costin, Iulian Ciocoiu, Tudor Barbu, Cristian Rotariu

Abstract:

In this paper three different approaches for person verification and identification, i.e. by means of fingerprints, face and voice recognition, are studied. Face recognition uses parts-based representation methods and a manifold learning approach. The assessment criterion is recognition accuracy. The techniques under investigation are: a) Local Non-negative Matrix Factorization (LNMF); b) Independent Components Analysis (ICA); c) NMF with sparse constraints (NMFsc); d) Locality Preserving Projections (Laplacianfaces). Fingerprint detection was approached by classical minutiae (small graphical patterns) matching through image segmentation by using a structural approach and a neural network as decision block. As to voice / speaker recognition, melodic cepstral and delta delta mel cepstral analysis were used as main methods, in order to construct a supervised speaker-dependent voice recognition system. The final decision (e.g. “accept-reject" for a verification task) is taken by using a majority voting technique applied to the three biometrics. The preliminary results, obtained for medium databases of fingerprints, faces and voice recordings, indicate the feasibility of our study and an overall recognition precision (about 92%) permitting the utilization of our system for a future complex biometric card.

Keywords: Biometry, image processing, pattern recognition, speech analysis.

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Authors: Dana M. Ragab, Jasim A. Ghaeb

Abstract:

The three-phase power system suffers from different challenging problems, e.g. voltage unbalance conditions at the load side. The voltage unbalance usually degrades the power quality of the electric power system. Several techniques can be considered for load balancing including load reconfiguration, static synchronous compensator and static reactive power compensator. In this work an efficient neural network is designed to control the unbalanced condition in the Aqaba-Qatrana-South Amman (AQSA) electric power system. It is designed for highly enhanced response time of the reactive compensator for voltage balancing. The neural network is developed to determine the appropriate set of firing angles required for the thyristor-controlled reactor to balance the three load voltages accurately and quickly. The parameters of AQSA power system are considered in the laboratory model, and several test cases have been conducted to test and validate the proposed technique capabilities. The results have shown a high performance of the proposed Neural Network Control (NNC) technique for correcting the voltage unbalance conditions at three-phase load based on accuracy and response time.

Keywords: Three-phase power system, reactive power control, voltage unbalance factor, neural network, power quality.

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