Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 1064
Статья научная
It is difficult for higher education institutes to manage the growing volumes of educational data accurately and efficiently using conventional ways. Modern technology is required to deal with this difficulty and ICT is an emerging technology that can solve this problem. In this study, Service-Oriented Computing (SOC) is used to develop a Service-Oriented Registrar System (SORS) for Debre Markos University Burie campus registrar office. Web services are used to develop highly cohesive and loosely coupled subsystems that support location transparency and manage the academic records of students accurately and efficiently. Moreover, the developed system is secured, easily maintainable, expandable and open for either inter or intra-application integration on the campus.
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Shapley's Axiomatics for Lexicographic Cooperative Games
Статья научная
In classical cooperative game theory one of the most important principle is defined by Shapley with three axioms common payoff fair distribution's Shapley value (or Shapley vector). In the last decade the field of its usage has been spread widely. At this period of time Shapley value is used in network and social systems. Naturally, the question is if it is possible to use Shapley's classical axiomatics for lexicographic cooperative games. Because of this in the article for m dimensional lexicographic cooperative v= (vT ,...,vM )1T game game is introduced Shapley's axiomatics, as the principle of a fair distribution in the case of dimensional payoff functions, when the criteria are strictly ranking. It has been revealed that axioms discussed by Shapley for classical games are sufficient in lexicographic cooperative games corresponding with the payoffs of distribution. Besides we are having a very interesting case: according to the proved theorem, Shapley's classical principle simultaneously transforms on the composed scalar v1,…, vm games of a lexicographic cooperative game, nevertheless, v2,…, vm games could not be superadditive.
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Статья научная
Feature driven development (FDD) is a process oriented and client centric agile software development model which develops a software according to client valued features. Like other agile models it also has adaptive and incremental nature to implement required functionality in short iterations. FDD mainly focus on designing and building aspects of software development with more emphasis on quality. However less responsiveness to changing requirements, reliance on experienced staff and less appropriateness for small scale projects are the main problems. To overcome these problems a Simplified Feature Driven Development (SFDD) model is proposed in this paper. In SFDD we have modified the phases of classical FDD for small to medium scale projects that can handle changing requirements with small teams in efficient and effective manner.
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Simulation and Analysis of AODV and DSR Routing Protocol under Black Hole Attack
Статья научная
In this paper, two routing protocols (AODV and DSR) are simulated under regular operation, single and cooperative black hole attack. This work has been performed by simulator to show consequence of black hole attacks in MANET by using various graphs which are used to collect data in term of several metrics. One common method to perform most of researches in the MANET security field is to simulate and analyze the routing protocols in various scenarios. This work has been based on the implementation and experiments in the OPNET modeler version 14.5. Finally the results have been computed and compared to stumble on which protocol is least affected by these attacks.
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Статья научная
Recording of ground motions with high amplitudes of acceleration and velocity play a key role for designing engineering projects. Here we try to represent a reasonable prediction of peak ground acceleration which may create more than g acceleration in different regions. In this study, applying different structures of Neural Networks (NN) and using four key parameters, moment magnitude, rupture distance, site class, and style of faulting which an earthquake may cause serious effects on a site. We introduced a radial basis function network (RBF) with mean error of 0.014, as the best network for estimating the occurrence probability of an earthquake with large value of PGA ≥1g in a region. Also the results of applying back propagation in feed forward neural network (FFBP) show a good coincidence with designed RBF results for predicting high value of PGA, with Mean error of 0.017.
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Статья научная
In this paper, Coded Orthogonal Frequency Division Multiplexing (COFDM) based Radio over Fiber (RoF) system is simulated (for different bit rates) for different modulation techniques to observe impact on system parameter [quality factor (Q)]. Influence of increasing bit rates has been observed for 2 km long linear multimode fiber. To reduce dispersion due to multimode fiber, convolutional encoder (code rate ½, generator polynomial 1338, 1718) and viterbi hard decision decoding algorithm are chosen for simulative model of COFDM based RoF system. Transmission of 32 sub-carriers with externally modulated continuous wave laser source gave satisfied results for Q values.
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Software Defect Prediction Using Variant based Ensemble Learning and Feature Selection Techniques
Статья научная
Testing is considered as one of the expensive activities in software development process. Fixing the defects during testing process can increase the cost as well as the completion time of the project. Cost of testing process can be reduced by identifying the defective modules during the development (before testing) stage. This process is known as “Software Defect Prediction”, which has been widely focused by many researchers in the last two decades. This research proposes a classification framework for the prediction of defective modules using variant based ensemble learning and feature selection techniques. Variant selection activity identifies the best optimized versions of classification techniques so that their ensemble can achieve high performance whereas feature selection is performed to get rid of such features which do not participate in classification and become the cause of lower performance. The proposed framework is implemented on four cleaned NASA datasets from MDP repository and evaluated by using three performance measures, including: F-measure, Accuracy, and MCC. According to results, the proposed framework outperformed 10 widely used supervised classification techniques, including: “Naïve Bayes (NB), Multi-Layer Perceptron (MLP), Radial Basis Function (RBF), Support Vector Machine (SVM), K Nearest Neighbor (KNN), kStar (K*), One Rule (OneR), PART, Decision Tree (DT), and Random Forest (RF)”
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Software Inspection in Software Industry: A Pakistan's Perspective
Статья научная
Today in software world the qualifying criterion for a software product is to be of high quality. Quality enables a software product to conform to customer's expectations. It is another name for best available services and is made acceptable through many practices like reviews, inspections and testing. Among these software inspection is the one which is cost efficient and easy to implement technique. Software inspection is composed of many activities to result in improving the underlying document better and creates consistent understanding. This research presents the different activities in the inspection and practicing of these activities in the software industry of Pakistan. This research is carried out through questionnaires. The answers demonstrate that software inspection is source of better quality products and customer satisfaction without using any proper framework of inspection.
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Software Testing Resource Allocation and Release Time Problem: A Review
Статья научная
Software testing Resource allocation and release time decisions are vital for the software systems. The objective behind such critical decisions may differ from firm to firm. The motive of the firm may be maximization of software reliability or maximization of number of faults to be removed from each module or it may be minimization of number of faults remaining in the software or minimization of testing resources. Taking into consideration these different aims, various authors have investigated the problem of resource allocation and release time problem. In this paper we investigate various software release policies and resource allocation problem, for example, policies based on the dual constraints of cost and reliability.
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Solution and Level Identification of Sudoku Using Harmony Search
Статья научная
Different optimization techniques have been used to solve Sudoku. Zong Woo Geem have applied harmony search in Sudoku to get better result. He has taken a Sudoku and time complexity has been optimized by different values of parameters. But, he has not given way of solution in details. He has also not given any idea to recognize the level of Sudoku. In this paper, an algorithm has been proposed based on harmony search to solve and identify the Sudoku efficiently. It has been observed that time complexity i.e. the maximum number of iteration has been reduced by choosing appropriate parameter values. The level of Sudoku has also been identified using probability metric. Finally, the number of iterations has been calculated with different values of parameters and the level of different Sudoku has been identified.
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Solution for Using FEMM in Electrostatic Problems with Discrete Distribution Electric Charge
Статья научная
Finite Element Method Magnetics (FEMM) is an open source software package for solving electromagnetic problems based on the finite element method. The application can numerically solve linear electrostatic problems and magnetostatic 2D problems, respectively low frequency magnetic, linear harmonic and nonlinear. FEMM is a product much used in science and engineering that, in the last 15 years, has begun to be used more and more in the academic environment. Despite the fact that FEMM can be used to solve complex problems in science and engineering, electrostatic FEMM cannot work directly with discrete electric charge distributions, that is, point electric charge. This work presents a FEMM model for simulating point electric charge that can be used in case of electrostatic problems with discrete charge distributions. The numerical solution for the electrostatic field is compared with the analytical solution. This model can be used in the case of an assembly of point electric charges with axial symmetry.
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Spam Mail Detection through Data Mining – A Comparative Performance Analysis
Статья научная
As web is expanding day by day and people generally rely on web for communication so e-mails are the fastest way to send information from one place to another. Now a day's all the transactions all the communication whether general or of business taking place through e-mails. E-mail is an effective tool for communication as it saves a lot of time and cost. But e-mails are also affected by attacks which include Spam Mails. Spam is the use of electronic messaging systems to send bulk data. Spam is flooding the Internet with many copies of the same message, in an attempt to force the message on people who would not otherwise choose to receive it. In this study, we analyze various data mining approach to spam dataset in order to find out the best classifier for email classification. In this paper we analyze the performance of various classifiers with feature selection algorithm and without feature selection algorithm. Initially we experiment with the entire dataset without selecting the features and apply classifiers one by one and check the results. Then we apply Best-First feature selection algorithm in order to select the desired features and then apply various classifiers for classification. In this study it has been found that results are improved in terms of accuracy when we embed feature selection process in the experiment. Finally we found Random Tree as best classifier for spam mail classification with accuracy = 99.72%. Still none of the algorithm achieves 100% accuracy in classifying spam emails but Random Tree is very nearby to that.
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Статья научная
This study employed geographic information systems (GIS) to analyze the spatial factors related to dengue fever (DF), dengue hemorrhagic fever (DHF), and dengue shock syndrome (DSS) epidemics. Chachoengsao province, Thailand, was chosen as the study area. This study examines the diffusion pattern of disease. Clinical data including gender and age of patients with disease were analyzed. The hotspot zonation of disease was carried out during the outbreaks for years 2001 and 2007 by using local spatial autocorrelation statistics (LSAS) and kernel-density estimation (KDE) methods. The mean center locations and movement patterns of the disease were found. A risk zone map was generated for the incidence. Data for spatio-temporal analysis and risk zonation of DF/DHF/DSS were employed for years 2000 to 2007. Results found that the age distribution of the cases was different from the general population’s age distribution. Taking into account that the quite high incidence of DF/DHF/DSS cases was in the age group of 13-24 years old and the percentage rate of incidence was 42.9%, a DF/DHF/DSS virus transmission out of village is suspected. An epidemic period of 20 weeks, starting on 1st May and ending on 31st September, was analyzed. Approximately 25% of the cases occurred between Weeks 6-8. A pattern was found using mean centers of the data in critical months, especially during rainy season. Finally, it can be identified that from the total number of villages affected (821), the highest risk zone covered 7 villages (0.85%); the moderate risk zone comprised 39 villages (4.75%); for the low risk zone 22 villages (2.68%) were found; the very low risk zone consisted of 120 villages (14.62%); and no case occurred in 633 villages (77.10%). The zones most at risk were shown in districts Mueang Chachoengsao, Bang Pakong, and Phanom Sarakham. This research presents useful information relating to the DF/DHF/DSS. To analyze the dynamic pattern of DF/DHF/DSS outbreaks, all cases were positioned in space and time by addressing the respective villages. Not only is it applicable in an epidemic, but this methodology is general and can be applied in other application fields such as dengue outbreak or other diseases during natural disasters.
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Spatial and Transform Domain Filtering Method for Image De-noising: A Review
Статья научная
Present investigation reveals the quantum of work carried in the filtering methods for image de-noising. An image is often gets corrupted by various noises that are visible or invisible while being gathered, coded, acquired and transmitted. Noise influences various process parameters that may cause a quality problem for further image processing. De-noising of natural images is appears to be very simple however when considered under practical situations becomes complex. It has been cited by various author that parameter such as type and quantum of noise, image etc. through single algorithm or approach becomes cumbersome when results are optimized. In order to improve the quality of an image noise must be removed when the image is pre-processed and the important signal features like edge details should be retained as much as possible. The search on efficient image de-noising methods is still a valid challenge at the crossing of functional analysis and statistics. This paper reviews significant de-noising methods (spatial and transform domain method) and their salient features and applications. One filter in each category has been taken in consideration to understand the characteristics of both spatial and transform domain filters.
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Specialization Impact on Internet Resource Usage: Omani Undergraduate Learner’s Perspectives
Статья научная
The current educational processes need various tools and technological supports in order to attain the required level of knowledge. The learning processes have been simplified with the help of different resources including internet resources. The usage of internet resources usage depends on the learner’s requirements in the field of study. This research had identified the significant impacts of the specialization of the learners on the internet resource usage. Also, the paper identified some specializations that have major influences in using such internet resources in learning processes. The study had been conducted in Omani undergraduate student’s environment with respect to selected specializations. The specialization impacts on the frequency of using internet resources, places of searching and purpose of using internet resources in the learning processes were analyzed using conditional probabilities and impacts had been identified with the help of decision tree diagram. The results showed that the students studying Information Technology specialization had greater impact in using internet resources in their learning processes compared to others at undergraduate levels.
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Specific queries optimization using Jaya approach
Статья научная
The Fast query engine is a requirement as a supporting tool for the semantic web technology application such as Electronic Commerce environ. As the large data is represented using the effective data representation called RDF. The focus of this paper is to optimize the specific type of the query called Cyclic query and star query on main-memory RDF data model using ARQ query engine of Jena. For the considered problem, we ruminate a Jaya algorithm for rearrangement of the order of triple pattern and also compare the results with an already proposed approach in the literature. The evaluation result shows that Jaya performs better in terms of execution time in comparison to Ant Colony Optimization.
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Speed Learning: Maximizing Student Learning and Engagement in a Limited Amount of Time
Статья научная
Active learning has warranted great promise in improving student engagement and learning. It is not a new thought and has been promoted and encouraged as early as the 1980s. Due to the many benefits of active learning it is being practiced by many faculty in their classrooms. Faculty are urged to self-reflect on their teaching styles and work on improving the pedagogies to capture and maintain student interest by increasing student engagement. Although active learning has been used as an instrument to engage students and ultimately increase learning, it has seldom been implemented to directly impact learning relative to time. This paper explores the application of active learning pedagogy to help achieve maximum learning in a limited period of time. The active learning method employed in this study is grounded in classic pedagogies that have been developed based on various psychological theories of learning, motivation and engagement. After the employment of a series of this active learning technique a survey of the students revealed an increase in student learning.
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Stabilitty of Anti-periodic Solutions for Certain Shunting Inhibitory Cellular Neural Networks
Статья научная
In this paper, the existence and exponential stability of anti-periodic solutions for shunting inhibitory cellular neural networks (SICNNs) with continuously distributed delays are considered by constructing suitable Lyapunov fuctions and applying some critial analysis techniques. Our results remove restrictive conditions of the global Lipschitz and bounded conditions of activation functions and new sufficient conditions ensuring the exist-ence and exponential stability of anti-periodic solutions for SICNNs are obtained. Moreover, an example is given to illustrate the feasibility of the conditions in our results.
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Steganography on RGB Images Based on a “Matrix Pattern” using Random Blocks
Статья научная
In this paper, we describe a novel spatial domain method for steganography in RGB images where a secret message is embedded in the blue layer of certain blocks. In this algorithm, each block first chooses a unique t1xt2 matrix of pixels as a “matrix pattern” for each keyboard character, using the bit difference of neighbourhood pixels. Next, a secret message is embedded in the remaining part of the block, those without any role in the “matrix pattern” selection procedure. In this procedure, each pattern sums up with the blue layer of the image. For increasing the security, blocks are chosen randomly using a random generator. The results show that this algorithm is highly resistant against the frequency and spatial domain attacks including RS, Sample pair, X2 and DCT based attacks. In addition, the proposed algorithm could provide more than 84.26 times of capacity comparing with a competitive method. Moreover, the results indicated that stego-image has almost 1.73 times better transparency than the competitive algorithm.
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Stereo rectification of calibrated image pairs based on geometric transformation
Статья научная
The objective of stereo rectification is to make the corresponding epipolar lines of image pairs be parallel to the horizontal direction, so that the efficiency of stereo matching is improved as the corresponding points stay in the same horizontal lines of both images. In this paper，a simple and convenient rectification method of calibrated image pairs based on geometric transformation is proposed, which can avoid the complicated calculation of many previous algorithms such as based on epipolar lines, based on fundamental matrix or directly depend on corresponding points. This method is divided into two steps including coordinate system transformation and re-projection of image points. Firstly, we establish two virtual cameras with parallel optical axis by coordinate system transformation based on the pose relationship of the two cameras from calibration result. Secondly, we re-project the points of the original image onto new image planes of the virtual cameras through geometrical method, and then realized the stereo rectification. Experiments of real stereo image pairs show that the proposed method is able to realize the rectification of stereo image pairs accurately and efficiently.
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