Search results for: Arabic Language acquisition and learning

Authors: Chothmal, Basant Agarwal

Abstract:

Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: Feature selection methods, Machine learning, NB, One-class SVM, Sentiment Analysis, Support Vector Machine.

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Authors: Ya-Hui Lee, Ching-Yi Lu, Hui-Chuan Wei

Abstract:

The purpose of this research was to explore the relation between proactive coping and well-being of middle-aged adults. We conducted survey research that with t-test, one way ANOVA, Pearson correlation and stepwise multiple regression to analyze. This research drew on a sample of 395 participants from the senior learning centers of Taiwan. The results provided the following findings: 1.The participants from different residence areas associated significant difference with proactive coping, but not with well-being. 2. The participants’ perceived of financial level associated significant difference with both proactive coping and well-being. 3. There was significant difference between participants’ income and well-being. 4. The proactive coping was positively correlated with well-being. 5. From stepwise multiple regression analysis showed that two dimensions of proactive coping had positive predictability. Finally, these results of this study can be provided as references for designing older adult educational programs in Taiwan.

Keywords: Middle-age adults, learners, proactive coping, well-being.

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Authors: Hasan Karal, Yasemin Aydin, Ömer Faruk Ursavas

Abstract:

Primary studies are being carried out in Turkey for expanding information and communication technologies (ICT) aided instruction activities. Subject of the present study is to identify whether those studies achieved their goals in the application. Information technologies (IT) formative teachers in the primary schools, and academicians in the faculties of education were interviewed to investigate the process and results of implementing computer-aided instruction methods whose basis is strengthened in theory. Analysis of the results gained from two separate surveys demonstrated that capability of the teachers in elementary education institutions for carrying into effect computer-aided instruction and technical infrastructure has not been established for computer-aided instruction practices yet. Prospective teachers must be well-equipped in ICT to duly fulfill requirements of modern education and also must be self-confident. Finally, scope and intensity of the courses given in connection with teaching of the ICT in faculties of education needs to be revised.

Keywords: Information and Communication Technologies, Teacher, Education

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Authors: G. Shanmugasundar, R. Sivaramakrishnan, S. Venugopal

Abstract:

Robots are booming as an essential substituent in the field of inspection. In hazardous environments like nuclear waste disposal, robots are really a necessitate one. In a view to meet such demands, this paper presents the seven degree of freedom articulated inspection robot. To design such a robot the kinematic analysis of seven Degree of freedom robot which can inspect the hazardous nuclear waste storage tanks is done. The effective utilization of universal joints for arms and screw jack mechanisms at the base gives the higher order of degree of freedom to the newly designed robot. The analytical method of deriving the manipulator forward as well as inverse kinematics is explained elaborately using the Denavit-Hartenberg Approach for the purpose of calculating the robot joints, links and end-effector parameters. The comparison of the geometric and the analytical approach is stated. The self-developed kinematic model gives the accurate positions of the end effector. The Graphical User Interface (GUI) is developed in Visual Basic language for the manipulation of kinematic results easily. This software gives the expected position of the end-effector accurately at short time compared to manual manipulations.

Keywords: Robot kinematics, screw jack mechanisms, Denavit-Hartenberg approach, universal joints.

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Authors: M. T. Becerra, F. Martín, P. Gutiérrez, S. Cubo, E. Iglesias, A. A. Sáenz del Castillo, P. Cañamero

Abstract:

The consolidation of the European Higher Education Area (EHEA) in universities has led to significant changes in student training. This paper, part of a Teaching Innovation Project, starts from new training requirements that are fit within Undergraduate Thesis Project, a subject that culminate student learning. Undergraduate Thesis Project is current assessment system that weigh the student acquired training in university education. Students should develop a range of cross curricular competences such as public presentation of ideas, problems and solutions both orally and writing in Undergraduate Thesis Project. Specifically, we intend with our innovation proposal to provide resources that enable university students from Teacher Degree in Education Faculty of University of Extremadura (Spain) to develop the cross curricular competence of public speaking.

Keywords: Interaction, Public Speaking, Student, University.

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Authors: Salvatore Marra, Francesco C. Morabito

Abstract:

In this paper we present an efficient approach for the prediction of two sunspot-related time series, namely the Yearly Sunspot Number and the IR5 Index, that are commonly used for monitoring solar activity. The method is based on exploiting partially recurrent Elman networks and it can be divided into three main steps: the first one consists in a “de-rectification" of the time series under study in order to obtain a new time series whose appearance, similar to a sum of sinusoids, can be modelled by our neural networks much better than the original dataset. After that, we normalize the derectified data so that they have zero mean and unity standard deviation and, finally, train an Elman network with only one input, a recurrent hidden layer and one output using a back-propagation algorithm with variable learning rate and momentum. The achieved results have shown the efficiency of this approach that, although very simple, can perform better than most of the existing solar activity forecasting methods.

Keywords: Elman neural networks, sunspot, solar activity, time series prediction.

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Authors: Margaret F. Shipley

Abstract:

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

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

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Authors: Frank Emmert Streib, Matthias Dehmer, Gökhan H. Bakır, Max Mühlhauser

Abstract:

In this paper we investigate the influence of external noise on the inference of network structures. The purpose of our simulations is to gain insights in the experimental design of microarray experiments to infer, e.g., transcription regulatory networks from microarray experiments. Here external noise means, that the dynamics of the system under investigation, e.g., temporal changes of mRNA concentration, is affected by measurement errors. Additionally to external noise another problem occurs in the context of microarray experiments. Practically, it is not possible to monitor the mRNA concentration over an arbitrary long time period as demanded by the statistical methods used to learn the underlying network structure. For this reason, we use only short time series to make our simulations more biologically plausible.

Keywords: Dynamic Bayesian networks, structure learning, gene networks, Markov chain Monte Carlo, microarray data.

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Authors: Dr.K.Sri Rama Krishna, J.Lakshmi Narayana, Dr.L.Pratap Reddy

Abstract:

Microstrip lines, widely used for good reason, are broadband in frequency and provide circuits that are compact and light in weight. They are generally economical to produce since they are readily adaptable to hybrid and monolithic integrated circuit (IC) fabrication technologies at RF and microwave frequencies. Although, the existing EM simulation models used for the synthesis and analysis of microstrip lines are reasonably accurate, they are computationally intensive and time consuming. Neural networks recently gained attention as fast and flexible vehicles to microwave modeling, simulation and optimization. After learning and abstracting from microwave data, through a process called training, neural network models are used during microwave design to provide instant answers to the task learned.This paper presents simple and accurate ANN models for the synthesis and analysis of Microstrip lines to more accurately compute the characteristic parameters and the physical dimensions respectively for the required design specifications.

Keywords: Neural Models, Algorithms, Microstrip Lines, Analysis, Synthesis

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Authors: Ethan Shafer, Timothy Graziano, Jay Fisher

Abstract:

This research seeks to answer whether first-year courses at institutions of higher learning can impact STEM major selection. Unlike many universities, an entry-level technology course (often referred to as CS0) is required for all United States Military Academy (USMA) students–regardless of major–in their first year of attendance. Students at the Academy choose their major at the end of their first year of studies. Through student responses to a multi-semester survey, this paper identifies a number of factors that potentially influence STEM major selection. Student demographic data, pre-existing exposure and access to technology, perceptions of STEM subjects, and initial desire for a STEM major are captured before and after taking a CS0 course. An analysis of factors that contribute to student perception of STEM and major selection are presented. This work provides recommendations and suggestions for institutions currently providing or looking to provide CS0-like courses to their students.

Keywords: STEM major, STEM, pedagogy, digital literacy.

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Authors: Muhibul H. Bhuyan, Mafujul Hasan

Abstract:

If a person can monitor his/her heart rate regularly then he/she can detect heart disease early and thus he/she can enjoy longer life span. Therefore, this disease should be taken seriously. Hence, many health care devices and monitoring systems are being designed to keep track of the heart disease. This work reports a design and simulation processes of an Arduino microcontroller based heart rate measurement and monitoring system in Proteus environment. Clipping sensors were utilized to sense the heart rate of an individual from the finger tips. It is a digital device and uses mainly infrared (IR) transmitter (mainly IR LED) and receiver (mainly IR photo-transistor or IR photo-detector). When the heart pumps the blood and circulates it among the blood vessels of the body, the changed blood pressure is detected by the transmitter and then reflected back to the receiver accordingly. The reflected signals are then processed inside the microcontroller through a software written assembly language and appropriate heart rate (HR) is determined by it in beats per minute (bpm) from the detected signal for a duration of 10 seconds and display the same in bpm on the LCD screen in digital format. The designed system was simulated on several persons with varying ages, for example, infants, adult persons and active athletes. Simulation results were found very satisfactory.

Keywords: Heart rate measurement, design, simulation, Proteus, Arduino Uno microcontroller.

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Authors: Cuong Nguyen Khac, Ju H. Park, Ho-Youl Jung

Abstract:

This paper proposes a new approach to perform the problem of real-time face detection. The proposed method combines primitive Haar-Like feature and variance value to construct a new feature, so-called Variance based Haar-Like feature. Face in image can be represented with a small quantity of features using this new feature. We used SVM instead of AdaBoost for training and classification. We made a database containing 5,000 face samples and 10,000 non-face samples extracted from real images for learning purposed. The 5,000 face samples contain many images which have many differences of light conditions. And experiments showed that face detection system using Variance based Haar-Like feature and SVM can be much more efficient than face detection system using primitive Haar-Like feature and AdaBoost. We tested our method on two Face databases and one Non-Face database. We have obtained 96.17% of correct detection rate on YaleB face database, which is higher 4.21% than that of using primitive Haar-Like feature and AdaBoost.

Keywords: AdaBoost, Haar-Like feature, SVM, variance, Variance based Haar-Like feature.

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Authors: Mohammed Salahat, Steve Wade

Abstract:

This paper presents and compares the SSDDD “Systematic Soft Domain Driven Design Framework” to DDD “Domain Driven Design Framework” as a soft system approach of information systems development. The framework use SSM as a guiding methodology within which we have embedded a sequence of design tasks based on the UML leading to the implementation of a software system using the Naked Objects framework. This framework has been used in action research projects that have involved the investigation and modelling of business processes using object-oriented domain models and the implementation of software systems based on those domain models. Within this framework, Soft Systems Methodology (SSM) is used as a guiding methodology to explore the problem situation and to develop the domain model using UML for the given business domain. The framework is proposed and evaluated in our previous works, a comparison between SSDDD and DDD is presented in this paper, to show how SSDDD improved DDD as an approach to modelling and implementing business domain perspectives for Information Systems Development. The comparison process, the results, and the improvements are presented in the following sections of this paper.

Keywords: SSM, UML, domain-driven design, soft domain-driven design, naked objects, soft language, information retrieval, multimethodology.

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Authors: García López

Abstract:

The Government Departments of Health have the task of informing and educating citizens about public health issues. For this, they use channels like Twitter, key in the search for health information and the propagation of content. The tweets, important in the virality of the content, may contain emotions that influence the contagion and exchange of knowledge. The goal of this study is to perform an analysis of the emotional projection of health information shared on Twitter by official American accounts: the disease control account CDCgov, National Institutes of Health, NIH, the government agency HHSGov, and the professional organization PublicHealth. For this, we used Tone Analyzer, an International Business Machines Corporation (IBM) tool specialized in emotion detection in text, corresponding to the categorical model of emotion representation. For 15 days, all tweets from these accounts were analyzed with the emotional analysis tool in text. The results showed that their tweets contain an important emotional load, a determining factor in the success of their communications. This exposes that official accounts also use subjective language and contain emotions. The predominance of emotion joy over sadness and the strong presence of emotions in their tweets stimulate the virality of content, a key in the work of informing that government health departments have.

Keywords: Emotions in tweets emotion detection in text, health information on Twitter, American health official accounts, emotions on Twitter, emotions and content.

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Authors: A. Althobaiti, M. Munro

Abstract:

Communication and effective information exchange within technology has become a crucial part of delivering knowledge to students during the learning process. It enables better understanding, builds trust and respect, and increases the sharing of knowledge between students. This paper examines the communication between undergraduate students and their lecturers during the traditional lecture and when using the Interactive Electronic Lecture System (IELS). The IELS is an application that offers a set of components which support the effective communication between students and their peers and between students and their lecturers. Moreover, this paper highlights communication skills such as sender, receiver, channel and feedback. It will show how the IELS creates a rich communication environment between its users and how they communicate effectively. To examine and assess the effectiveness of communication, an experiment was conducted on groups of users; students and lecturers. The first group communicated in the traditional lecture while the second group communicated by means of the IELS application. The results show that there was more effective communication between the second group than the first.

Keywords: Communication, effective information exchange.

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Authors: William Anderson, Kyle Kobold, Oleg Yakimenko

Abstract:

Green microgrids using mostly renewable energy (RE) for generation, are complex systems with inherent nonlinear dynamics. Among a variety of different optimization tools there are only a few ones that adequately consider this complexity. This paper evaluates applicability of two somewhat similar optimization tools tailored for standalone RE microgrids and also assesses a machine learning tool for performance prediction that can enhance the reliability of any chosen optimization tool. It shows that one of these microgrid optimization tools has certain advantages over another and presents a detailed routine of preparing input data to simulate RE microgrid behavior. The paper also shows how neural-network-based predictive modeling can be used to validate and forecast solar power generation based on weather time series data, which improves the overall quality of standalone RE microgrid analysis.

Keywords: Microgrid, renewable energy, complex systems, optimization, predictive modeling, neural networks.

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Authors: Tanvir Ahmed, Thanh N. Long, Phan T. Huong, Donald E. Stewart

Abstract:

This paper presents views on condom use and the contexts of safe and unsafe sexual practices with different sexual partners and their relationships among Injecting Drug Users (IDUs) in Hai Phong, Vietnam. Fifteen IDUs participated and two local interviewers conducted qualitative semi-structured face-to-face interviews in September-October, 2012 in Vietnamese language. Data were analyzed thematically. Non-protective condom attitudes include negotiate or convince Female Sex Workers (FSW); not realizing risk, importance or necessity; partner doesn’t like, and having extra money/drug from clients. On the other hand, self-awareness, family-consciousness, suspicion of STI presence, fear of getting HIV, and client negotiation sometimes resulted in a safe-sex practice. A thematic diagram was developed to present the relationship (strong/weak) between condom attitude and sexual practice (safe/unsafe) by partner types. The experiences and views reflected in the qualitative information emphasize the heightened need for safe-sex education especially among young IDUs (male/female) highlighting sexual transmission risk.

Keywords: AIDS, HIV, injecting drug user, risk behaviors, Vietnam.

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Authors: Chokri Slim

Abstract:

The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.

Keywords: Neuro-fuzzy, Extended Kalman filter, nonlinear systems, financial time series.

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Authors: Darren Zou

Abstract:

Forecasting the stock market is a very challenging task. Various economic indicators such as GDP, exchange rates, interest rates, and unemployment have a substantial impact on the stock market. Time series models are the traditional methods used to predict stock market changes. In this paper, a machine learning method, Bayesian Additive Regression Tree (BART) is used in predicting stock market indexes based on multiple economic indicators. BART can be used to model heterogeneous treatment effects, and thereby works well when models are misspecified. It also has the capability to handle non-linear main effects and multi-way interactions without much input from financial analysts. In this research, BART is proposed to provide a reliable prediction on day-to-day stock market activities. By comparing the analysis results from BART and with time series method, BART can perform well and has better prediction capability than the traditional methods.

Keywords: Bayesian, Forecast, Stock, BART.

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Authors: Moulay A. Akhloufi, Abdelhakim Bendada

Abstract:

Face recognition in the infrared spectrum has attracted a lot of interest in recent years. Many of the techniques used in infrared are based on their visible counterpart, especially linear techniques like PCA and LDA. In this work, we introduce a probabilistic Bayesian framework for face recognition in the infrared spectrum. In the infrared spectrum, variations can occur between face images of the same individual due to pose, metabolic, time changes, etc. Bayesian approaches permit to reduce intrapersonal variation, thus making them very interesting for infrared face recognition. This framework is compared with classical linear techniques. Non linear techniques we developed recently for infrared face recognition are also presented and compared to the Bayesian face recognition framework. A new approach for infrared face extraction based on SVM is introduced. Experimental results show that the Bayesian technique is promising and lead to interesting results in the infrared spectrum when a sufficient number of face images is used in an intrapersonal learning process.

Keywords: Face recognition, biometrics, probabilistic imageprocessing, infrared imaging.

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Authors: Beata Wentura-Dudek

Abstract:

In the United States in 2007-2010 before the crisis, the US labour market policy focused mainly on providing residents with unemployment insurance, after the recession this policy changed. The aim of the article was to present quantitative research presenting the most effective labor market instruments contributing to reducing unemployment during the crisis in the USA. The article presents research based on the analysis of available documents and statistical data. The results of the conducted research show that the most effective forms of counteracting unemployment at that time were: direct job creation, job search assistance, subsidized employment, training and employment promotion using new technologies, including social media.

Keywords: United States, financial crisis, unemployment, employment promotion, social media, job creation, training, labour market, employment agencies, lifelong learning, job search assistance, subsidized employment, companies, tax.

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Authors: John Walton, Vishal Parikh

Abstract:

Contact centres have been exemplars of scientific management in the discipline of operations management for more than a decade now. With the movement of industries from a resource based economy to knowledge based economy businesses have started to realize the customer eccentricity being the key to sustainability amidst high velocity of the market. However, as technologies have converged and advanced, so have the contact centres. Contact Centres have redirected the supply chains and the concept of retailing is highly diminished due to over exaggeration of cost reduction strategies. In conditions of high environmental velocity together with services featuring considerable information intensity contact centres will require up to date and enlightened agents to satisfy the demands placed upon them by those requesting their services. In this paper we examine salient factors such as Power Distance, Knowledge structures and the dynamics of job specialisation and enlargement to suggest critical success factors in the domain of contact centres.

Keywords: Post Taylorism, Knowledge Management, Power Distance, Organisational Learning

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Authors: Murat Koklu, Yavuz Unal

Abstract:

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

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

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Authors: Markus Kaiser, Johannes Buchmann

Abstract:

In this article we explore the application of a formal proof system to verification problems in cryptography. Cryptographic properties concerning correctness or security of some cryptographic algorithms are of great interest. Beside some basic lemmata, we explore an implementation of a complex function that is used in cryptography. More precisely, we describe formal properties of this implementation that we computer prove. We describe formalized probability distributions (σ-algebras, probability spaces and conditional probabilities). These are given in the formal language of the formal proof system Isabelle/HOL. Moreover, we computer prove Bayes- Formula. Besides, we describe an application of the presented formalized probability distributions to cryptography. Furthermore, this article shows that computer proofs of complex cryptographic functions are possible by presenting an implementation of the Miller- Rabin primality test that admits formal verification. Our achievements are a step towards computer verification of cryptographic primitives. They describe a basis for computer verification in cryptography. Computer verification can be applied to further problems in cryptographic research, if the corresponding basic mathematical knowledge is available in a database.

Keywords: prime numbers, primality tests, (conditional) probabilitydistributions, formal proof system, higher-order logic, formalverification, Bayes' Formula, Miller-Rabin primality test.

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Authors: Peyman Shadman Heidari, Mohammad Khorasani

Abstract:

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

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

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Authors: A. K. Aswathy, Asha Manoharan, Arya Manoharan

Abstract:

The purpose of this study are to define the nature of oral sensory issues in children with autism spectrum disorder (ASD), identify important components of the assessment and treatment of this issues specific to this population, and delineate specific therapeutic techniques designed to improve assessment and treatment within therapeutic settings. Literature review and case example is used to define the predominant nature of the oral sensory issues that are experienced by some children on the autism spectrum. Characteristics of this complex disorder that can have an impact on feeding skill and behavior are also identified. These factors are then integrated to create assessment and intervention techniques that can be used in conjunction with traditional feeding approaches to facilitate improvements in eating as well as reducing oral apraxic component in this unique population. The complex nature of ASD and its many influences on feeding skills and behavior create the need for modification to both assessment and treatment approaches. Additional research is needed to create therapeutic protocols that can be used by speech-language pathologists to effectively assess and treat feeding and oro motor apraxic difficulties that are commonly encountered in children with ASD.

Keywords: Autism, feeding, intervention, oral sensory issues, oral apraxia.

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Authors: Samy Sadek, Ayoub Al-Hamadi, Bernd Michaelis, Usama Sayed

Abstract:

In this paper, we propose a supervised method for color image classification based on a multilevel sigmoidal neural network (MSNN) model. In this method, images are classified into five categories, i.e., “Car", “Building", “Mountain", “Farm" and “Coast". This classification is performed without any segmentation processes. To verify the learning capabilities of the proposed method, we compare our MSNN model with the traditional Sigmoidal Neural Network (SNN) model. Results of comparison have shown that the MSNN model performs better than the traditional SNN model in the context of training run time and classification rate. Both color moments and multi-level wavelets decomposition technique are used to extract features from images. The proposed method has been tested on a variety of real and synthetic images.

Keywords: Image classification, multi-level neural networks, feature extraction, wavelets decomposition.

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

Abstract:

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

Keywords: Kazakhstan society, Legal education, legal culture.

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Authors: Markus Kaiser, Johannes Buchmann

Abstract:

In this paper we explore the application of a formal proof system to verification problems in cryptography. Cryptographic properties concerning correctness or security of some cryptographic algorithms are of great interest. Beside some basic lemmata, we explore an implementation of a complex function that is used in cryptography. More precisely, we describe formal properties of this implementation that we computer prove. We describe formalized probability distributions (o--algebras, probability spaces and condi¬tional probabilities). These are given in the formal language of the formal proof system Isabelle/HOL. Moreover, we computer prove Bayes' Formula. Besides we describe an application of the presented formalized probability distributions to cryptography. Furthermore, this paper shows that computer proofs of complex cryptographic functions are possible by presenting an implementation of the Miller- Rabin primality test that admits formal verification. Our achievements are a step towards computer verification of cryptographic primitives. They describe a basis for computer verification in cryptography. Computer verification can be applied to further problems in crypto-graphic research, if the corresponding basic mathematical knowledge is available in a database.

Keywords: prime numbers, primality tests, (conditional) proba¬bility distributions, formal proof system, higher-order logic, formal verification, Bayes' Formula, Miller-Rabin primality test.

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Authors: Leonardo A. Ambrosio, Carlos. H. Silva Santos, Ivan E. L. Rodrigues, Ayumi K. de Campos, Leandro A. Machado

Abstract:

In this work, we propose an algorithm developed under Python language for the modeling of ordinary scalar Bessel beams and their discrete superpositions and subsequent calculation of optical forces exerted over dielectric spherical particles. The mathematical formalism, based on the generalized Lorenz-Mie theory, is implemented in Python for its large number of free mathematical (as SciPy and NumPy), data visualization (Matplotlib and PyJamas) and multiprocessing libraries. We also propose an approach, provided by a synchronized Software as Service (SaaS) in cloud computing, to develop a user interface embedded on a mobile application, thus providing users with the necessary means to easily introduce desired unknowns and parameters and see the graphical outcomes of the simulations right at their mobile devices. Initially proposed as a free Android-based application, such an App enables data post-processing in cloud-based architectures and visualization of results, figures and numerical tables.

Keywords: Bessel Beams and Frozen Waves, Generalized Lorenz-Mie Theory, Numerical Methods, Optical Forces.

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