Search results for: noise web data learning

Authors: S. B. Kotsiantis, D. Kanellopoulos, P. E. Pintelas

Abstract:

Many factors affect the success of Machine Learning (ML) on a given task. The representation and quality of the instance data is first and foremost. If there is much irrelevant and redundant information present or noisy and unreliable data, then knowledge discovery during the training phase is more difficult. It is well known that data preparation and filtering steps take considerable amount of processing time in ML problems. Data pre-processing includes data cleaning, normalization, transformation, feature extraction and selection, etc. The product of data pre-processing is the final training set. It would be nice if a single sequence of data pre-processing algorithms had the best performance for each data set but this is not happened. Thus, we present the most well know algorithms for each step of data pre-processing so that one achieves the best performance for their data set.

Keywords: Data mining, feature selection, data cleaning.

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Authors: Zenaide Carvalho da Silva, Leandro Rodrigues Ferreira, Andrey Ricardo Pimentel

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Learning styles (LS) refer to the ways and forms that the student prefers to learn in the teaching and learning process. Each student has their own way of receiving and processing information throughout the learning process. Therefore, knowing their LS is important to better understand their individual learning preferences, and also, understand why the use of some teaching methods and techniques give better results with some students, while others it does not. We believe that knowledge of these styles enables the possibility of making propositions for teaching; thus, reorganizing teaching methods and techniques in order to allow learning that is adapted to the individual needs of the student. Adapting learning would be possible through the creation of online educational resources adapted to the style of the student. In this context, this article presents the structure of a learning object interface adaptation based on the LS. The structure created should enable the creation of the adapted learning object according to the student's LS and contributes to the increase of student’s motivation in the use of a learning object as an educational resource.

Keywords: Adaptation, interface, learning object, learning style.

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Authors: Kazunari Meguro, Daisuke Yamamoto, Shinichi Motomura, Toshihiko Sasama, Takao Kawamura, Kazunori Sugahara

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We have developed a distributed asynchronous Web based training system. In order to improve the scalability and robustness of this system, all contents and functions are realized on mobile agents. These agents are distributed to computers, and they can use a Peer to Peer network that modified Content-Addressable Network. In the proposed system, only text data can be included in a exercise. To make our proposed system more useful, the mechanism that it not only adapts to multimedia data but also it doesn-t influence the user-s learning even if the size of exercise becomes large is necessary.

Keywords: e-Learning, multimedia, Mobile Agent.

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Authors: S. K. Lujara, M. M. Kissaka, E. P. Bhalalusesa, L. Trojer

Abstract:

The Information and Communication Technologies (ICTs), and the Wide World Web (WWW) have fundamentally altered the practice of teaching and learning world wide. Many universities, organizations, colleges and schools are trying to apply the benefits of the emerging ICT. In the early nineties the term learning object was introduced into the instructional technology vernacular; the idea being that educational resources could be broken into modular components for later combination by instructors, learners, and eventually computes into larger structures that would support learning [1]. However in many developing countries, the use of ICT is still in its infancy stage and the concept of learning object is quite new. This paper outlines the learning object design considerations for developing countries depending on learning environment.

Keywords: e-Learning resources, granularity, learning objects, secondary schools.

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Authors: Hao-Hsi Tseng, Hsin-Yun Lee, Yu-Cheng Kuo

Abstract:

In order to understand whether there is a better than the learning function of learning methods and improve the CAD Courses for enterprise’s design human resource development, this research is applied in learning practical learning computer graphics software. In this study, Revit building information model for learning content, design of two different modes of learning curriculum to learning, learning functions, respectively, and project learning. Via a post-test, questionnaires and student interviews, etc., to study the effectiveness of a comparative analysis of two different modes of learning. Students participate in a period of three weeks after a total of nine-hour course, and finally written and hands-on test. In addition, fill in the questionnaire response by the student learning, a total of fifteen questionnaire title, problem type into the base operating software, application software and software-based concept features three directions. In addition to the questionnaire, and participants were invited to two different learning methods to conduct interviews to learn more about learning students the idea of two different modes. The study found that the ad hoc short-term courses in learning, better learning outcomes. On the other hand, functional style for the whole course students are more satisfied, and the ad hoc style student is difficult to accept the ad hoc style of learning.

Keywords: Development, education, human resource, learning.

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Authors: Watcharin Kaewapichai, Pakorn Kaewtrakulpong

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In this paper, a method to detect multiple ellipses is presented. The technique is efficient and robust against incomplete ellipses due to partial occlusion, noise or missing edges and outliers. It is an iterative technique that finds and removes the best ellipse until no reasonable ellipse is found. At each run, the best ellipse is extracted from randomly selected edge patches, its fitness calculated and compared to a fitness threshold. RANSAC algorithm is applied as a sampling process together with the Direct Least Square fitting of ellipses (DLS) as the fitting algorithm. In our experiment, the method performs very well and is robust against noise and spurious edges on both synthetic and real-world image data.

Keywords: Direct Least Square Fitting, Ellipse Detection, RANSAC

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Authors: Wernhuar Tarng, Weichian Tsai

Abstract:

The major purpose of this study is to use network and multimedia technologies to build a game-based learning system for junior high school students to apply in learning “World Geography" through the “role-playing" game approaches. This study first investigated the motivation and habits of junior high school students to use the Internet and online games, and then designed a game-based learning system according to situated and game-based learning theories. A teaching experiment was conducted to analyze the learning effectiveness of students on the game-based learning system and the major factors affecting their learning. A questionnaire survey was used to understand the students- attitudes towards game-based learning. The results showed that the game-based learning system can enhance students- learning, but the gender of students and their habits in using the Internet have no significant impact on learning. Game experience has a significant impact on students- learning, and the higher the experience value the better the effectiveness of their learning. The results of questionnaire survey also revealed that the system can increase students- motivation and interest in learning "World Geography".

Keywords: Game-based learning, situated learning, role playing, learning effectiveness, learning motivation.

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Authors: Samson T. Obafemi, Seraphin D. Eyono Obono

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Information and Communication Technologies (ICTs) are pervasive nowadays, including in education where they are expected to improve the performance of learners. However, the hope placed in ICTs to find viable solutions to the problem of poor academic performance in schools in the developing world has not yet yielded the expected benefits. This problem serves as a motivation to this study whose aim is to examine the perceptions of educators on the advantages and disadvantages of e-learning. This aim will be subdivided into two types of research objectives. Objectives on the identification and design of theories and models will be achieved using content analysis and literature review. However, the objective on the empirical testing of such theories and models will be achieved through the survey of educators from different schools in the Pinetown District of the South African Kwazulu-Natal province. SPSS is used to quantitatively analyse the data collected by the questionnaire of this survey using descriptive statistics and Pearson correlations after assessing the validity and the reliability of the data. The main hypothesis driving this study is that there is a relationship between the demographics of educators’ and their adherence to learning theories on one side, and their perceptions on the advantages and disadvantages of e-learning on the other side, as argued by existing research; but this research views these learning theories under three perspectives: educators’ adherence to self-regulated learning, to constructivism, and to progressivism. This hypothesis was fully confirmed by the empirical study except for the demographic factor where teachers’ level of education was found to be the only demographic factor affecting the perceptions of educators on the advantages and disadvantages of e-learning.

Keywords: Academic performance, e-learning, Learning theories, Teaching and Learning.

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Authors: Kamaldeep Joshi, Rajkumar Yadav, Sachin Allwadhi

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Image steganography is the best aspect of information hiding. In this, the information is hidden within an image and the image travels openly on the Internet. The Least Significant Bit (LSB) is one of the most popular methods of image steganography. In this method, the information bit is hidden at the LSB of the image pixel. In one bit LSB steganography method, the total numbers of the pixels and the total number of message bits are equal to each other. In this paper, the LSB method of image steganography is used for watermarking. The watermarking is an application of the steganography. The watermark contains 80*88 pixels and each pixel requirs 8 bits for its binary equivalent form so, the total number of bits required to hide the watermark are 80*88*8(56320). The experiment was performed on standard 256*256 and 512*512 size images. After the watermark insertion, histogram analysis was performed. A noise factor (salt and pepper) of 0.02 was added to the stego image in order to evaluate the robustness of the method. The watermark was successfully retrieved after insertion of noise. An experiment was performed in order to know the imperceptibility of stego and the retrieved watermark. It is clear that the LSB watermarking scheme is robust to the salt and pepper noise.

Keywords: LSB, watermarking, salt and pepper, PSNR.

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Authors: Layla Albdr

Abstract:

Saudi Arabia instituted the policy of sensitizing and training stakeholders for e-learning and witnessed wide adoption in many institutions. However, it is at the infancy stage and needs time to develop to mirror the US and UK. The majority of the higher education institutions in Saudi Arabia have adopted e-learning as an alternative to traditional methods to advance education. Conversely, effective implementation of the policy of sensitization and training of stakeholders for e-learning implementation has not been attained because of various challenges. The objectives included determining the challenges and opportunities of the e-learning policy of sensitization and training of stakeholders in Saudi Arabia's higher education and examining if sensitization and training of stakeholder's policy will help promote the implementation of e-learning in institutions. The study employed a descriptive research design based on qualitative analysis. The researcher recruited 295 students and 60 academic staff from four Saudi Arabian universities to participate in the study. An online questionnaire was used to collect the data. The data were then analyzed and reported both quantitatively and qualitatively. The analysis provided an in-depth understanding of the opportunities and challenges of e-learning policy in Saudi Arabian universities. The main challenges identified as internal challenges were the lack of educators’ interest in adopting the policy, and external challenges entailed lack of ICT infrastructure and Internet connectivity. The study recommends encouraging, sensitizing, and training all stakeholders to address these challenges and adopt the policy.

Keywords: e-learning, educational policy, Saudi Arabian higher education, policy of sensitization and training

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Authors: A. O. Oladele

Abstract:

The purpose of this study was to find out the effectiveness of neurological impress method and repeated reading technique on reading fluency of children with learning disabilities. Thirty primary four pupils in three public primary schools participated in the study. There were two experimental groups and a control. This research employed a 3 by 2 factorial matrix and the participants were taught for one session. Two hypotheses were formulated to guide the research. T-test was used to analyse the data gathered, and data analysis revealed that pupils exposed to the two treatment strategies had improvement in their reading fluency. It was recommended that the two strategies used in the study can be used to intervene in reading fluency problems in children with learning disabilities.

Keywords: Learning disabilities, neurological impress method, repeated reading, reading fluency.

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: Deep learning, indoor quality, metabolism, predictive model.

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Authors: Jeongim Kang, Moon Hee Kim, Seong Baeg Kim

Abstract:

This paper proposes a novel e-learning model that is  based on a dynamic formative evaluation. On evaluating the existing  format of e-learning, conditions regarding repetitive learning to  achieve mastery, causes issues for learners to lose tension and become  neglectful of learning. The dynamic formative evaluation proposed is  able to supplement limitation of the existing approaches. Since a  repetitive learning method does not provide a perfect feedback, this  paper puts an emphasis on the dynamic formative evaluation that is  able to maximize learning achievement. Through the dynamic  formative evaluation, the instructor is able to refer to the evaluation  result when making an estimation about the learner. To show the flow  chart of learning, based on the dynamic formative evaluation, the  model proves its effectiveness and validity.

 

Keywords: Online learning, dynamic formative evaluation, mastery learning, repetitive learning method, learning achievement.

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Authors: V. Anil Kumar, Abhijit Mitra, S. R. Mahadeva Prasanna

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We analyze the effectivity of different pseudo noise (PN) and orthogonal sequences for encrypting speech signals in terms of perceptual intelligence. Speech signal can be viewed as sequence of correlated samples and each sample as sequence of bits. The residual intelligibility of the speech signal can be reduced by removing the correlation among the speech samples. PN sequences have random like properties that help in reducing the correlation among speech samples. The mean square aperiodic auto-correlation (MSAAC) and the mean square aperiodic cross-correlation (MSACC) measures are used to test the randomness of the PN sequences. Results of the investigation show the effectivity of large Kasami sequences for this purpose among many PN sequences.

Keywords: Speech encryption, pseudo-noise codes, maximallength, Gold, Barker, Kasami, Walsh-Hadamard, autocorrelation, crosscorrelation, figure of merit.

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Authors: Heba Mohammed Nagy, Walid Mohamed Aly, Osama Fathy Hegazy

Abstract:

Educational  data mining  is  a  specific  data   mining field applied to data originating from educational environments, it relies on different  approaches to discover hidden knowledge  from  the  available   data. Among these approaches are   machine   learning techniques which are used to build a system that acquires learning from previous data. Machine learning can be applied to solve different regression, classification, clustering and optimization problems.

In  our  research, we propose  a “Student  Advisory  Framework” that  utilizes  classification  and  clustering  to  build  an  intelligent system. This system can be used to provide pieces of consultations to a first year  university  student to  pursue a  certain   education   track   where  he/she  will  likely  succeed  in, aiming  to  decrease   the  high  rate   of  academic  failure   among these  students.  A real case study  in Cairo  Higher  Institute  for Engineering, Computer  Science  and  Management  is  presented using  real  dataset   collected  from  2000−2012.The dataset has two main components: pre-higher education dataset and first year courses results dataset. Results have proved the efficiency of the suggested framework.

Keywords: Classification, Clustering, Educational Data Mining (EDM), Machine Learning.

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Authors: Ibraheem Alzahrani

Abstract:

This paper seeks to discover the relationship between both the social constructivist learning theory and the collaborative learning environment. This relationship can be identified through given an example of the learning environment. Due to wiki characteristics, wiki can be used to understand the relationship between constructivist learning theory and collaborative learning environment. However, several evidences will come in this paper to support the idea of why wiki is the suitable method to explore the relationship between social constructivist theory and the collaborative learning and their role in learning. Moreover, learning activities in wiki classroom will be discussed in this paper to find out the result of the learners' interaction in the classroom groups, which will be through two types of communication; synchronous and asynchronous.

Keywords: Social constructivist, collaborative, environment, wiki, activities.

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Authors: Jihad S. Daba, J. P. Dubois

Abstract:

Fading noise degrades the performance of cellular communication, most notably in femto- and pico-cells in 3G and 4G systems. When the wireless channel consists of a small number of scattering paths, the statistics of fading noise is not analytically tractable and poses a serious challenge to developing closed canonical forms that can be analysed and used in the design of efficient and optimal receivers. In this context, noise is multiplicative and is referred to as stochastically local fading. In many analytical investigation of multiplicative noise, the exponential or Gamma statistics are invoked. More recent advances by the author of this paper utilized a Poisson modulated-weighted generalized Laguerre polynomials with controlling parameters and uncorrelated noise assumptions. In this paper, we investigate the statistics of multidiversity stochastically local area fading channel when the channel consists of randomly distributed Rayleigh and Rician scattering centers with a coherent Nakagami-distributed line of sight component and an underlying doubly stochastic Poisson process driven by a lognormal intensity. These combined statistics form a unifying triply stochastic filtered marked Poisson point process model.

Keywords: Cellular communication, femto- and pico-cells, stochastically local area fading channel, triply stochastic filtered marked Poisson point process.

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Authors: Bahloul Amel

Abstract:

This study is an attempt to raise the awareness of the stakeholders and the authorities on the sensitivity of Algerian secondary school teachers of English as a Foreign Language about the students’ loss of English language skills learned during formal schooling with effort and at expense and the supposed measures to arrest that loss. Data was collected from secondary school teachers of EFL and analyzed quantitatively using a questionnaire containing open-ended and close-ended questions. The results advocate a consensus about the need for actions to be adopted to make assessment techniques outcome-oriented. Most of the participants were in favor of including curricular activities involving contextualized learning, problem-solving learning critical selfawareness, self and peer-assisted learning, use of computers and internet so as to make learners autonomous.

Keywords: Contextualized learning, EFL, Lifelong learning.

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Authors: H. Katkhuda

Abstract:

A time domain approach is used in this paper to identify unknown dynamic forces applied on two dimensional frames using the measured dynamic structural responses for a sub-structure in the two dimensional frame. In this paper a sub-structure finite element model with short length of measurement from only three or four accelerometers is required, and an iterative least-square algorithm is used to identify the unknown dynamic force applied on the structure. Validity of the method is demonstrated with numerical examples using noise-free and noise-contaminated structural responses. Both harmonic and impulsive forces are studied. The results show that the proposed approach can identify unknown dynamic forces within very limited iterations with high accuracy and shows its robustness even noise- polluted dynamic response measurements are utilized.

Keywords: Dynamic Force Identification, Dynamic Responses, Sub-structure and Time Domain.

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Authors: Toshihiko Matsuka, James E. Corter

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Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.

Keywords: category learning, cognitive modeling, radial basis function, stochastic optimization.

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Authors: Haydar Kepekçi, Baha Zafer, Hasan Rıza Güven

Abstract:

Noise disturbance is one of the major factors considered in the fast development of aircraft technology. This paper reviews the flow field, which is examined on the 2D NACA0015 and 3D NACA0012 blade profile using SST k-ω turbulence model to compute the unsteady flow field. We inserted the time-dependent flow area variables in Ffowcs-Williams and Hawkings (FW-H) equations as an input and Sound Pressure Level (SPL) values will be computed for different angles of attack (AoA) from the microphone which is positioned in the computational domain to investigate effect of augmentation of unsteady 2D and 3D airfoil region noise level. The computed results will be compared with experimental data which are available in the open literature. As results; one of the calculated Cp is slightly lower than the experimental value. This difference could be due to the higher Reynolds number of the experimental data. The ANSYS Fluent software was used in this study. Fluent includes well-validated physical modeling capabilities to deliver fast, accurate results across the widest range of CFD and multiphysics applications. This paper includes a study which is on external flow over an airfoil. The case of 2D NACA0015 has approximately 7 million elements and solves compressible fluid flow with heat transfer using the SST turbulence model. The other case of 3D NACA0012 has approximately 3 million elements.

Keywords: Aeroacoustics, Ffowcs-Williams and Hawkings equations, SST k-ω turbulence model, Noise Disturbance, 3D Blade Profile, 2D Blade Profile.

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Authors: M. Sarrab, M. Elbasir

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The use of information technology in education have changed not only the learners learning style but also the way they taught, where nowadays learners are connected with diversity of information sources with means of knowledge available everywhere. The advantage of network wireless technologies and mobility technologies used in the education and learning processes lead to mobile learning as a new model of learning technology. Currently, most of mobile learning applications are developed for the formal education and learning environment. Despite the long history and large amount of research on mobile learning and instruction design model still there is a need of well-defined process in designing mobile learning applications. Based on this situation, this paper emphasizes on identifying instruction design phase’s considerations and influencing factors in developing mobile learning application. This set of instruction design steps includes analysis, design, development, implementation, evaluation and continuous has been built from a literature study, with focus on standards for learning, mobile application software quality and guidelines. The effort is part of an Omani-funded research project investigating the development, adoption and dissemination of mobile learning in Oman.

Keywords: Instruction design, mobile learning, mobile application.

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Authors: Melvin A. Ballera

Abstract:

Prior literature in the field of adaptive and personalized learning sequence in e-learning have proposed and implemented various mechanisms to improve the learning process such as individualization and personalization, but complex to implement due to expensive algorithmic programming and need of extensive and prior data. The main objective of personalizing learning sequence is to maximize learning by dynamically selecting the closest teaching operation in order to achieve the learning competency of learner. In this paper, a revolutionary technique has been proposed and tested to perform individualization and personalization using modified reversed roulette wheel selection algorithm that runs at O(n). The technique is simpler to implement and is algorithmically less expensive compared to other revolutionary algorithms since it collects the dynamic real time performance matrix such as examinations, reviews, and study to form the RWSA single numerical fitness value. Results show that the implemented system is capable of recommending new learning sequences that lessens time of study based on student's prior knowledge and real performance matrix.

Keywords: E-learning, fitness value, personalized learning sequence, reversed roulette wheel selection algorithms.

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Authors: R. Biondi, G. Dys, G. Ferone, T. Renard, M. Zysman

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This paper describes an automated implementable system for impulsive signals detection and recognition. The system uses a Digital Signal Processing device for the detection and identification process. Here the system analyses the signals in real time in order to produce a particular response if needed. The system analyses the signals in real time in order to produce a specific output if needed. Detection is achieved through normalizing the inputs and comparing the read signals to a dynamic threshold and thus avoiding detections linked to loud or fluctuating environing noise. Identification is done through neuronal network algorithms. As a setup our system can receive signals to “learn” certain patterns. Through “learning” the system can recognize signals faster, inducing flexibility to new patterns similar to those known. Sound is captured through a simple jack input, and could be changed for an enhanced recording surface such as a wide-area recorder. Furthermore a communication module can be added to the apparatus to send alerts to another interface if needed.

Keywords: Sound Detection, Impulsive Signal, Background Noise, Neural Network.

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Authors: T. Y. Liu, C. H Lin., Y. M Ferng

Abstract:

Wind energy is one of the clean renewable energy. However, the low frequency (20-200HZ) noise generated from the wind turbine blades, which bothers the residents, becomes the major problem to be developed. It is useful for predicting the aerodynamic noise by flow field and pressure distribution analysis on the wind turbine blades. Therefore, the main objective of this study is to use different turbulence models to analyze the flow field and pressure distributions of the wing blades.

Three-dimensional Computation Fluid Dynamics (CFD) simulation of the flow field was used to calculate the flow phenomena for the National Renewable Energy Laboratory (NREL) Phase VI horizontal axis wind turbine rotor. Two different flow cases with different wind speeds were investigated: 7m/s with 72rpm and 15m/s with 72rpm.

Four kinds of RANS-based turbulence models, Standard k-ε, Realizable k-ε, SST k-ω, and v2f, were used to predict and analyze the results in the present work. The results show that the predictions on pressure distributions with SST k-ω and v2f turbulence models have good agreements with experimental data.

Keywords: Horizontal Axis Wind Turbine, turbulence model, noise.

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Authors: Ahmed Abdulla Ashlam, Atta Badii, Frederic Stahl

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In recent years, SQL injection attacks have been identified as being prevalent against web applications. They affect network security and user data, which leads to a considerable loss of money and data every year. This paper presents the use of classification algorithms in machine learning using a method to classify the login data filtering inputs into "SQLi" or "Non-SQLi,” thus increasing the reliability and accuracy of results in terms of deciding whether an operation is an attack or a valid operation. A method as a Web-App is developed for auto-generated data replication to provide a twin of the targeted data structure. Shielding against SQLi attacks (WebAppShield) that verifies all users and prevents attackers (SQLi attacks) from entering and or accessing the database, which the machine learning module predicts as "Non-SQLi", has been developed. A special login form has been developed with a special instance of the data validation; this verification process secures the web application from its early stages. The system has been tested and validated, and up to 99% of SQLi attacks have been prevented.

Keywords: SQL injection, attacks, web application, accuracy, database, WebAppShield.

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Authors: Ava Dodd, Jonathan Adams

Abstract:

The purpose of this study is to explore the characteristics of developing a machine learning application using synthetic data. The study is structured to develop the application for the purpose of deploying the computer vision model. The findings discuss the realities of attempting to develop a computer vision model for practical purpose, and detail the processes, tools and techniques that were used to meet accuracy requirements. The research reveals that synthetic data represent another variable that can be adjusted to improve the performance of a computer vision model. Further, a suite of tools and tuning recommendations are provided.

Keywords: computer vision, machine learning, synthetic data, YOLOv4

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Authors: Dina Tareq Ismail, Alexandria A. Proff

Abstract:

The United Arab Emirates (UAE) is a nation seeking to advance in all fields, particularly education. One area of focus for UAE 2021 agenda is to restructure UAE schools and universities by equipping them with highly developed technology. The agenda also advises educational institutions to prepare students with applicable and transferrable Information and Communication Technology (ICT) skills. Despite the emphasis on ICT and computer literacy skills, there exists limited empirical data on the use of M-Learning in the literature. This qualitative study explores the motivation of higher primary Arabic teachers in private schools toward implementing and integrating M-Learning apps in their classrooms. This research employs a phenomenological approach through the use of semistructured interviews with nine purposefully selected Arabic teachers. The data were analyzed using a content analysis via multiple stages of coding: open, axial, and thematic. Findings reveal three primary themes: (1) Arabic teachers with high levels of procedural knowledge in ICT are more motivated to implement M-Learning; (2) Arabic teachers' perceptions of self-efficacy influence their motivation toward implementation of M-Learning; (3) Arabic teachers implement M-Learning when they possess high utility and/or intrinsic value in these applications. These findings indicate a strong need for further training, equipping, and creating buy-in among Arabic teachers to enhance their ICT skills in implementing M-Learning. Further, given the limited availability of M-Learning apps designed for use in the Arabic language on the market, it is imperative that developers consider designing M-Learning tools that Arabic teachers, and Arabic-speaking students, can use and access more readily. This study contributes to closing the knowledge gap on teacher-motivation for implementing M-Learning in their classrooms in the UAE.

Keywords: ICT Skills, M-Learning, self-efficacy, teachermotivation.

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Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

Abstract:

2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: Artificial Intelligence, machine learning, deep learning, convolutional neural networks.

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Authors: Mikhail Vladimirovich Deryabin, Morten Willatzen

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In this work, we address theoretically the influence of red and white Gaussian noise for electronic energies and eigenstates of cylindrically shaped quantum dots. The stochastic effect can be imagined as resulting from crystal-growth statistical fluctuations in the quantum-dot material composition. In particular we obtain analytical expressions for the eigenvalue shifts and electronic envelope functions in the k . p formalism due to stochastic variations in the confining band-edge potential. It is shown that white noise in the band-edge potential leaves electronic properties almost unaffected while red noise may lead to changes in state energies and envelopefunction amplitudes of several percentages. In the latter case, the ensemble-averaged envelope function decays as a function of distance. It is also shown that, in a stochastic system, constant ensembleaveraged envelope functions are the only bounded solutions for the infinite quantum-wire problem and the energy spectrum is completely discrete. In other words, the infinite stochastic quantum wire behaves, ensemble-averaged, as an atom.

Keywords: cylindrical quantum dots, electronic eigen energies, red and white Gaussian noise, ensemble averaging effects.

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