Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 1064
A Study of Time Series Models ARIMA and ETS
Статья научная
The aim of the study is to introduce some appropriate approaches which might help in improving the efficiency of weather’s parameters. Weather is a natural phenomenon for which forecasting is a great challenge today. Weather parameters such as Rainfall, Relative Humidity , Wind Speed , Air Temperature are highly non-linear and complex phenomena, which include statistical simulation and modeling for its correct forecasting. Weather Forecasting is used to simplify the purpose of knowledge and tools which are used for the state of atmosphere at a given place. The expectations are becoming more complicated due to changing weather state. There are different software and their types are available for Time Series forecasting. Our aim is to analyze the parameter and do the comparison of some strategies in predicting these temperatures. Here we tend to analyze the data of given parameters and to notice their predictions for a particular period by using the strategy of Autoregressive Integrated Moving Average (ARIMA) and Exponential Smoothing (ETS) .The data from meteorological centers has been taken for the comparison of methods using packages such as ggplot2, forecast, time Date in R and automatic prediction strategies which are available within the package applied for modeling with ARIMA and ETS methods. On the basis of accuracy we tend to attempt the simplest methodology and then we will compare our model on the basis of MAE, MASE, MAPE and RMSE. An identification of model will be the chromatic checkup of both the ACF and PACF to hypothesize many probable models which are going to be projected by selection criteria i.e. AIC, AICc and BIC.
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Статья научная
In this paper, the system comprises of a commensal (S1), two hosts S2 and S3 ie., S2 and S3 both benefit S1, without getting themselves effected either positively or adversely. Further S2 is a commensal of S3, S3 is a host of both S1, S2 and all the three species have limited resources. The basic equations for this model constitute as three first order non-linear ordinary difference equations. All possible equilibrium points are identified based on the model equations and criteria for their stability are discussed. Further the numerical solutions are computed for specific values of the various parameters and the initial conditions.
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A Study on the Role of Motivation in Foreign Language Learning and Teaching
Статья научная
Motivation has been called the “neglected heart” of language teaching. As teachers, we often forget that all of our learning activities are filtered through our students’ motivation. In this sense, students control the flow of the classroom. Without student motivation, there is no pulse, there is no life in the class. When we learn to incorporate direct approaches to generating student motivation in our teaching, we will become happier and more successful teachers. This paper is an attempt to look at EFL learners’ motivation in learning a foreign language from a theoretical approach. It includes a definition of the concept, the importance of motivation, specific approaches for generating motivation, difference between integrative and instrumental motivation, difference between intrinsic and extrinsic motivation, factors influencing motivation, and adopting motivational teaching practice.
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Статья научная
The aim of this paper is to propose an efficient method for identification of web document topics which is often considered as one of the debatable challenges in many information retrieval systems. Most of the previous works have focused on analyzing the entire text using time-consuming methods and also many of them have used unsupervised approaches to identify the main topic of documents. However, in this paper, it is attempted to exploit the most widely-used Hyper-Text Markup Language (HTML) features to extract topics from web documents using a supervised approach. Hiring an interactive crawler, we firstly try to analyze HTML structures of 5000 webpages in order to identify the most widely-used HTML features. In the next step, the selected features of 1500 webpages are extracted using the same crawler. Suitable topics are given to each web document by users in a supervised learning process. A topic modeling technique is used over extracted features to build four classifiers- C4.5, Decision Tree, Naïve Bayes and Maximum Entropy- which are separately adopted to train and test our data. The results of classifiers are compared and the high accurate classifier is selected. In order to examine our approach in a larger scale, a new set of 3500 web documents is evaluated using the selected classifier. Results show that the proposed system provides remarkable performance which is able to obtain 71.8% recognition rate.
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A Survey for Replica Placement Techniques in Data Grid Environment
Статья научная
In data grids, data replication on variant nodes can change some problems such as response time and availability. Also, in data replication, there are some challenges to finding the best replica efficiently in relation to performance and location of physical storage systems. In this paper, various replica placement strategies are discussed. These replica placement strategies are available in the works. Replica placement contains recognizing the best possible node to duplicate data based on network latency and user request. These strategies measure and analyze different parameters such as access cost, bandwidth consumption, scalability, execution time and storage consumption. This paper also analyses the performance of various strategies with respect to the parameters mentioned above in data grid.
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A Survey on Face Detection and Recognition Techniques in Different Application Domain
Статья научная
In recent technology the popularity and demand of image processing is increasing due to its immense number of application in various fields. Most of these are related to biometric science like face recognitions, fingerprint recognition, iris scan, and speech recognition. Among them face detection is a very powerful tool for video surveillance, human computer interface, face recognition, and image database management. There are a different number of works on this subject. Face recognition is a rapidly evolving technology, which has been widely used in forensics such as criminal identification, secured access, and prison security. In this paper we had gone through different survey and technical papers of this field and list out the different techniques like Linear discriminant analysis, Viola and Jones classification and adaboost learning curvature analysis and discuss about their advantages and disadvantages also describe some of the detection and recognition algorithms, mention some application domain along with different challenges in this field. . We had proposed a classification of detection techniques and discuss all the recognition methods also.
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A Survey on ICT Education at the Secondary and Higher Secondary Levels in Bangladesh
Статья научная
In this study, we show the status of ICT education and find the gaps between rural and urban institutions for providing ICT education in secondary and higher secondary institutions in Bangladesh. For this purpose, we use primary data collected using a survey questionnaire that is answered by ICT teachers engaged in those institutions. The variables used in the questionnaire are the name of the respondents, educational qualification, locations of the institutions, syllabus structure, the total number of students for ICT courses, number of computers, etc. The data were collected from institutions located in urban and rural areas. We apply several statistical functions along with conditional logic to our data for getting the desired result. We find that the students-teacher ratio in secondary (resp., higher secondary) is about 288:1 (resp., 212:1), existing teachers have a heavy academic workload. We also find that there exist low facilities in rural institutions compared to the urban institutions because students-computer ratio (SCR) is 46 in rural areas whereas SCR is 22 in the urban area. Moreover, we find that more than 80% of the teachers conducting ICT classes have graduated from the discipline other than ICT or related discipline. Furthermore, teachers who cannot complete at least 80% of the ICT syllabus in time are mostly non-ICT graduate. Based on these findings, we propose some recommendations to meet the above gaps of the current ICT education in Bangladesh.
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A Survey on Interoperability in the Cloud Computing Environments
Статья научная
In the recent years, Cloud Computing has been one of the top ten new technologies which provides various services such as software, platform and infrastructure for internet users. The Cloud Computing is a promising IT paradigm which enables the Internet evolution into a global market of collaborating services. In order to provide better services for cloud customers, cloud providers need services that are in cooperation with other services. Therefore, Cloud Computing semantic interoperability plays a key role in Cloud Computing services. In this paper, we address interoperability issues in Cloud Computing environments. After a description of Cloud Computing interoperability from different aspects and references, we describe two architectures of cloud service interoperability. Architecturally, we classify existing interoperability challenges and we describe them. Moreover, we use these aspects to discuss and compare several interoperability approaches.
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A Survey on Journey of Topic Modeling Techniques from SVD to Deep Learning
Статья научная
Topic modeling techniques have been primarily being used to mine the topics from text corpora. These techniques reveal the hidden thematic structure in a collection of documents and facilitate to build up new ways to browse, search and summarize large archive of texts. A topic is a group of words that frequently occur together. A topic modeling can connect words with similar meanings and make a distinction between uses of words with several meanings. Here we present a survey on journey of topic modeling techniques comprising Latent Dirichlet Allocation (LDA) and non-LDA based techniques and the reason for classify the techniques into LDA and non-LDA is that LDA has ruled the topic modeling techniques since its inception. We have used the three hierarchical classification criteria’s for classifying topic models that include LDA and non-LDA based, bag-of-words or sequence-of-words approach and unsupervised or supervised learning for our survey. Purpose of this survey is to explore the topic modeling techniques since Singular Value Decomposition (SVD) topic model to the latest topic models in deep learning. Also, provide the brief summary of current probabilistic topic models as well as a motivation for future research.
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A Survey on Scheduling Heuristics in Grid Computing Environment
Статья научная
Job scheduling is one of the thrust research area in the discipline of Grid computing. Scheduling in the Grid environment is not only complicated but also known to be NP-Complete problem and that is all due to its unique characteristics. Thus, there are limited opportunities to find an optimal solution. In recent past, many eminent researchers reported a variety of Scheduling Heuristics that can have a substantial impact on the performance of the Grid systems. Unfortunately, it gives rise to difficulty in evaluating and keeping track of those solutions. Therefore, the motivation of this comprehensive study is to present firstly, an in-depth review of the topic under discussion mostly in the perspective of Grid Scheduling environment, and secondly, a proposal for a new state-of-the-art classification of the existing Scheduling Heuristics. All these Heuristics in each category have been further studied based on significant parameters frequently used in Scheduling Heuristics. The final part of this study includes a fair assessment of those mostly used dominating parameters. This report deals with the key concepts behind existing Scheduling Heuristics including Objectives, Types of Job Scheduling, Functionality of Grid, Nature of Grid, and the importance of the proposed classification.
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A Systematic Literature Review on Spell Checkers for Bangla Language
Статья научная
Spell checkers check whether a word is misspelled and provide suggestions to correct it. Detection and correction of spelling errors in Bangla language which is the seventh most spoken native language in the world, is very onerous because of the complex rules of Bangla spelling. There is no systematic literature review on this research topic. In this paper, we present a systematic literature review on checking and correcting spelling errors in Bangla language. We investigate the current methods used for spell checking and find out what challenges are addressed by those methods. We also report the limitations of those methods. Recent relevant studies are selected based on a set of significant criteria. Our results indicate that there are research gaps in this research topic and has a potential for further investigation.
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A Systematic Review of 3D Metaphoric Information Visualization
Статья научная
Today, large volumes of complex data are collected in many application domains such as health, finance and business. However, using traditional data visualization techniques, it is challenging to visualize abstract information to gain valuable insights into complex multidimensional datasets. One major challenge is the higher cognitive load in interpreting information. In this context, 3D metaphor-based information visualization has become a key research area in helping to gain useful insight into abstract data. Therefore, it has become critical to investigate the evolution of 3D metaphors with HCI techniques to minimize the cognitive load on the human brain. However, there are only a few recent reviews can be found for 3D metaphor-based data visualization. Therefore, this paper provides a comprehensive review of multidimensional data visualization by investigating the evolution of 3D metaphoric data visualization and interaction techniques to minimize the cognitive load on the human brain. Complying with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines this paper performs a systematic review of 3D metaphor-based data visualizations. This paper contributes to advancing the present state of knowledge in 3D metaphoric data visualization by critically analyzing the evolution of interactive 3D metaphors for information visualization. Further, this review identifies six main 3D metaphor categories and ten cognitive load minimizing techniques used in modern data visualization. In addition, this paper contributes three taxonomies by synthesizing the literature with a critical review of the strengths and weaknesses of metaphors. Finally, the paper discusses potential exploration paths for future research improvements.
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Статья научная
Vides a proper solution to this limitation. There are broadly three main categories of Vector Space Model: term-document, word-content and pair-pattern matrices. The main aim of this paper is to discuss broadly the three main categories of VSM for semantic analysis of texts and make proper selection for automatic categorizing. The scenario taken up here is categorization of research papers for organizing a national or an international conference based on the proposed methodology. Computers do not understand human language and this makes it difficult when human wants the computer to do some specific task like categorization according to human need. Vector Space Model (VSM) for semantic analysis of texts and make proper selection of one of the three main categories for automatic categorizing of research papers for organizing a national or an international conference based on the proposed methodology.
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A Two Layers Novel Low-Cost and Optimized Embedded Board Based on TMS320C6713 DSP and Spartan-3 FPGA
Статья научная
This paper presents the design and implementation of a new low-cost and minimum embedded board based on TMS320C6713 (PYP 208-PIN (PQFP)) DSP and Spartan-3 (XCS400-4PQG208C) FPGA in two layers with mount elements on two sides of the board. The proposed embedded board was developed satisfactorily for different applications such as data acquisition of sensor’s with serial port, control units, finite state machines, signal processing algorithms, navigation computing, Kalman filtering etc. Goal of the design was to implement as many as possible low-cost and minimum sizes of the board, also to receive input signals in a short time period and as real time. The board features are include: mount elements in two side of the board for minimization of the proposed board and also placed decoupling capacitors (by pass) for the DSP and FPGA in bottom layer of board strictly below these two ICs because should be placed as close as possible to the power supply pins DSP and FPGA, GND polygon layer is used in total top layer and microcomputer ground for DSP & FPGA in bottom layer, use FPGA for two aim ones for implementation of glue logic total of board and interface between serial connectors, use three RS-232 serial port, one RS-422, and SPI serial port on FPGA, use MT48LC16M16A SDRAM-256MB(4*4MB*16), Am29LV400B Flash memory 4 Megabit (512 K x 8-Bit/256 K x 16-Bit) and XCF02S configuration PROM. The size of the proposed embedded board is 11.1cm*17. 7cm so this board is optimized of aspect cost, performance, power, weight, and size.
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Статья научная
Assessment and evaluation of Program Educational Objectives (PEOs) and Student Outcomes (SOs) is a challenging task. In this paper, we present a unified framework, which has been developed over a period of more than eight years, for the systematic assessment and evaluation of PEOs and SOs. The proposed framework is based on a balance sampling approach that thoroughly covers PEO/SO assessment and evaluation and also minimizes human effort. This framework is general but to prove its effectiveness, we present a case study where this framework is successfully adopted by our undergraduate computer science program in the department of computer science at King Abdulaziz University, Jeddah. The robustness of the proposed framework is ascertained by an independent evaluation by ABET who awarded us full six years accreditation without any comments or concerns. The most significant value of our proposed framework is that it provides a balanced sampling mechanism for assessment and evaluations of PEOs/SOs that can be adapted by any program seeking ABET accreditation.
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A Wavelet Based Approach for Compression of Color Images
Статья научная
The use of color in image analysis and compression is becoming more and more popular. The high quality color images are in demand, but the bandwidth and power resources are limited, this shows the requirement of effective color image compression algorithm which is suitable to human visual system. However most of the existing algorithms are designed for gray scale visual information. In this work a unique wavelet based approach is proposed for compression of color images. Wavelet families are used to characterize the quality of image by calculating quality estimation parameters, which are, peak signal to noise ratio, energy retained, entropy and redundancy. The entropy calculations are done using color histogram and coding programme is developed for estimation of PSNR, ER and redundancy of the compressed image. The results are analyzed and a set of criteria is determined for the acceptability of coding algorithm. Results show that Biorthogonal wavelet filter outperforms the orthogonal one in quality of compressed image but the orthogonal filter is more energy preserving.
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A case analysis on different registration methods on multi-modal brain images
Статья научная
Many applications of artificial vision need to compare or integrate images of the same object but obtained at different moments of time with different devices (cameras), from different positions, under different conditions, etc. These differences in capture give rise to images with important relative geometric differences that prevent these "Fit" with precision over each other. The registry eliminates these geometric differences so that located pixels in the same coordinates correspond to the same point of the object and, therefore, both images can easily be compared or integrated. The registration of images is essential in disciplines such as remote sensing, radiology, robotic vision, etc. ; Fields, all of them, that overlap images to study environmental phenomena, monitor tumours carcinogenic or to reconstruct the observed scene. This paper also study different measures of similarity used to measure their consistency and a novel procedure is proposed to improve the accuracy of the linear record by pieces. Specifically the elements that influence the estimation are analysed experimentally of probability distributions of the intensity levels of the images. These distributions are the basis for calculating measures of similarity based on entropy as mutual information (MI) or the Entropy correlation coefficient (ECC). Therefore, the effectiveness of these measures depends critically on their correct estimation.
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A clustering algorithm based on local density of points
Статья научная
Data clustering is very active and attractive research area in data mining; there are dozens of clustering algorithms that have been published. Any clustering algorithm aims to classify data points according to some criteria. DBSCAN is the most famous and well-studied algorithm. Clusters are recorded as dense regions separated from each other by spars regions. It is based on enumerating the points in Eps-neighborhood of each point. This paper proposes a clustering method based on k-nearest neighbors and local density of objects in data; that is computed as the total of distances to the most near points that affected on it. Cluster is defined as a continuous region that has points within local densities fall between minimum local density and maximum local density. The proposed method identifies clusters of different shapes, sizes, and densities. It requires only three parameters; these parameters take only integer values. So it is easy to determine. The experimental results demonstrate the superior of the proposed method in identifying varied density clusters.
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A detailed examination of the enterprise architecture frameworks being implemented in Pakistan
Статья научная
Managing the underlying structure of an enterprise is a daunting task. The business management and IT management alike have to deal with intricate layers of complexity that lies beneath the surface of the day-to-day operations of an enterprise. Without a proper Enterprise Architecture Framework, any organization regardless of size and magnitude of operations is bound to struggle in managing their business strategies. However, choosing a suitable Enterprise Architecture Framework is in itself a pretty hard endeavor that requires a deep dive into the terrifying maze of available Enterprise Architecture Frameworks and their respective characteristics. In this study, we compare the major Enterprise Architectu¬re Frameworks that are currently prevalent in Pakistan. Through a well-crafted questionnaire we conducted a survey and assessed what Enterprise Architecture Frameworks most of the industries in Pakistan are using and the enterprise’s level of satisfaction with the achieved results. By focusing on the trends of Enterprise Architecture Framework implementation in Pakistan we try to offer a unique perspective on the comparative studies of Enterprise Architecture Framework that are usually done on general basis.
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A dynamic feedback-based load balancing methodology
Статья научная
With the recent growth of Internet-based application services, the concurrent accessing requests arriving at the particular servers offering application services are growing significantly. It is one of the critical strategies that employing load balancing to cope with the massive concurrent accessing requests and improve the access performance is. To build up a better online service to users, load balancing solutions achieve to deal with the massive incoming concurrent requests in parallel through assigning and scheduling the work executed by the members within one server cluster. In this paper, we propose a dynamic feedback-based load balancing methodology. The method analyzes the real-time load and response status of each single cluster member through periodically collecting its work condition information to evaluate the current load pressure by comparing the learned load balancing performance with the preset threshold. In this way, since the load arriving at the cluster could be distributed dynamically with the optimized manner, the load balancing performance could thus be maintained so that the service throughput capacity would correspondingly be improved and the response delay to service requests would be reduced. The proposed result is contributed to strengthening the concurrent access capacity of server clusters. According to the experiment report, the overall performance of server system employing the proposed solution is better.
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