Статьи журнала - International Journal of Modern Education and Computer Science
Все статьи: 1064
An Aligned Assessment Item Authoring Environment based on Interoperability Standards
Статья научная
Standard representations support sharing assessment items and learning objects among learning environments. Different standards have been developed to provide interoperability-based descriptions for all learning aspects. Designing assessment items or questions using standard representations became a key point in learning/teaching domain. This paper proposes an environment for authoring assessment items using a combination of standards linked together to align the produced questions. The environment consists of a set of tools. The first tool is dedicated for building question body using IMS (Innovation, Adoption, and Learning) QTI (Question and Test Interoperability) standards. An extension to IMS QTI was designed to represent question Intended Learning Outcomes (ILOs), difficulty degree, assessed concepts, and target groups. The second tool manipulates competency definitions bank which is used in representing assessment item ILOs. The third tool deals with target groups to whom question will be delivered.
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An Analysis of Application Level Security in Service Oriented Architecture
Статья научная
In computing, the software elements like objects and components emphasize on reusability using design tools of abstraction and separation of concerns. Software architecture has appeared as an initial idea to develop huge, complicated and heterogeneous distributed systems successfully. Service Oriented Architecture (SOA) combines services together to make systems having a greater impact on the way software systems are developed. SOA addresses the need of standards-based, loosely connected, and distributed computing which is protocol independent. It is not easy to ensure the secure transaction of data, where the movement of data occurs through loosely connected services. A number of techniques have been proposed in the contemporary literature to guide the SOA implementation in distributed system. These techniques offer certain benefits, but pose some challenges alongside such as the use of meta-data as framework and standard, contract documents, security patterns and security adviser, etc. The objective of this research is to provide a comprehensive analysis of various approaches used to provide application level security to the web services in SOA. These approaches have been compared based on a number of parameters. In addition, we critically evaluate different security methods used in SOA. The study also discusses some future directions in this domain.
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An Analysis of Performance Testing in Distributed Software Applications
Статья научная
Testing is a crucial step in designing and implementing software in the distributed environment. Testing in the distributed applications is not only difficult, but also a costly method. This Research briefly discusses the performance testing in the distributed software environment along with different other testing techniques proposed in the literature that correspond to distributed applications. Additionally, we discuss the key testing challenges faced during the whole process of testing the distributed applications. Much of the focus of this paper is on intelligent agent-based testing. Agent based testing is provide better coordination mechanism between multiple testers and exert more controllability and observablility on fault detection. In this study we have critically analyzed testing methodologies being practiced in the distributed environment. We have studied the merits and limitations of these methodologies proposed in the contemporary literature and have identified the possible improvements in those methodologies to make them more robust.
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An Analysis on Digital Watermarking in Videos based on Frequency Domain Techniques
Статья научная
As Watermarking have been considered as an emerging technique for copyright protection, data security and protection of ownership, several techniques and algorithms have been developed and created either in spatial domain or frequency domain mainly to achieve the properties of digital watermarking like robustness, imperceptibility, fidelity, etc. It is also found that the frequency domain techniques provides a better solution in obtaining these properties than the spatial domain. So, most researchers have used this domain in developing a good watermarking scheme for achieving robustness and other important properties of digital watermarking against all kinds of intentional and unintentional attacks. The attacks may include image processing attacks like compression, frame dropping, piracy, geometric distortions, loss of quality, etc. So, utmost importance must be given on how to create a scheme which can achieve robustness against all these attacks at the same time. The medium for watermarking is chosen as video because of its vast future scope So, in this paper, a thorough research on the various techniques available in watermarking based on frequency domain has been done to find out a secure technique that can withstand any kinds of attacks in a digital video.
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An Analysis on Performance of Decision Tree Algorithms using Student’s Qualitative Data
Статья научная
Decision Tree is the most widely applied supervised classification technique. The learning and classification steps of decision tree induction are simple and fast and it can be applied to any domain. In this research student qualitative data has been taken from educational data mining and the performance analysis of the decision tree algorithm ID3, C4.5 and CART are compared. The comparison result shows that the Gini Index of CART influence information Gain Ratio of ID3 and C4.5. The classification accuracy of CART is higher when compared to ID3 and C4.5. However the difference in classification accuracy between the decision tree algorithms is not considerably higher. The experimental results of decision tree indicate that student’s performance also influenced by qualitative factors.
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An Analytical Study of the Use of Social Networks for Collaborative Learning in Higher Education
Статья научная
In recent years, the use of social networks has been growing at an unprecedented speed. Changing the way people communicate, interact and learn. Instead of passively consuming information, users are actively participating in the creation of knowledge, as a part of the social connection and interaction Social Networking Sites (SNSs) are built upon. And since learning, at abstract, is a social activity, educators around the world have been embracing the notion of incorporating social networks technology into the educational environment to support and enhance the teaching-learning experience. This work investigates the usage of social networks in higher education to support collaborative learning, improve the learning process and enhance students' engagement and academic achievements. A comprehensive review of the current literature is conducted to thoroughly analyze the use and impact of social networks on higher education students. In order to propose a framework for educational social networks that will support collaborative learning and enhance learning outcomes for higher education students.
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Статья научная
Using graduates from the newly-upgraded colleges as a sample, we used the Wiles test on the Human Capital Hypothesis vs. the Screening Hypothesis of education economics. The results were in favor of the former, i.e., higher education was more likely a production means than just a signal in the job market. Thus the newly-upgraded colleges should adjust their curriculum and faculty structure to accommodate the skill demands in job markets.
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An Appraisal of Off-line Signature Verification Techniques
Статья научная
Biometrics is being commonly used nowadays for the identification and verification of humans everywhere in the world. In biometrics humans unique characteristics like palm, fingerprints, iris etc. are being used. Pattern Recognition and image processing are the major areas where research on signature verification is carried out. Hand written Signature of an individual is also unique and for identification of humans are being used and accepted specially in the banking and other financial transactions. The hand written signatures due to its importance are at target of fraudulence. In this paper we have surveyed different papers on techniques that are currently used for the identification and verification of Offline signatures.
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An Approach Towards Customized Multi-Tenancy
Статья научная
Multi-tenant applications are usually cloud based software services which can serve different users at the same time. This is done using single instance of applications by sharing hardware, infrastructure, data storage and virtualization. To achieve multi tenancy different approaches are there at every layer (Application, Data, hardware).Multi tenancy helps to minimize the effort needed for deployment and maintenance with an adequate level of security and privacy. Now a day the work is going on custom multi tenancy by sharing everything at each layer. This paper will describe the techniques of multi tenancy and how security, flexibility and scalability relate to each other when it comes to multi tenancy for customization.a
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An Approach for Discovering and Maintaining Links in RDF Linked Data
Статья научная
Many datasets are published on the Web using semantic Web technologies. These datasets contain data that represent links to similar resources. If these datasets are linked together by properly constructed links, users can easily query the data through a uniform interface, as if they were querying a single dataset. In this paper we propose an approach to discover (semi) automatically links between RDF data based on the description models that appear around the resources. Our approach also includes a (semi) automatic process to maintain links when a data-change occurs.
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An Approach to Solving Technical Difficulties Facing Non-CS Students in a Database Class
Статья научная
Today, an organization's biggest asset is its data. Knowledge of relational databases and SQL (Structured Query Language) is one of the most valued technical skills and in high demand in most organizations. Students of any major can benefit in their careers from learning these fundamental database concepts. At our school, database classes for both CS (Computer Science) and non-CS students are offered by our computer science faculty members. Teaching database concepts can be challenging especially to non-CS students. In this paper, we discuss the technical difficulties our non-CS students experience in their database class and an approach to solving these problems.
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An Assessment of Extreme Programming Based Requirement Engineering Process
Статья научная
Comprehensive requirement engineering (RE) process acts as a backbone of any successful project. RE processes are very complex because most of the requirement engineering documentation is written in natural languages, which are less formal and often distract the designers and developers of the system. To streamline different phases of the software lifecycle, first we need to model the requirement document so that we can analyze and integrate the software artifacts. Designers can ensure completeness and consistency of the system by generating models using the requirement documents. In this paper, we have made an attempt to analyze extreme programming based RE approach to understand its utility in the requirement elicitation phase. In this study, different RE process models are evaluated and a comparison of the extreme programming technique is drawn to highlight the merits of the latter technique over the conventional RE techniques.
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Статья научная
Learning is based on collaborative learning theory. Collaborative learning theory has interaction, individual accountability, teamwork and personalized guidance. All these aspects can be performed in web 2.0 using social networking sites. So e-learning 2.0 on web 2.0 is not a new class of learning management system or a pedagogy but which promotes the user to collaborate and build the information and not just a mere spectator/consumer of information. In this paper the researchers have made an assessment of 23 e-learning systems, a survey on some of the popular tools/sites which will be useful and augment e-learning 2.0 and have discussed the features of an experimental web solution to have a look and feel of these tools.
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An Automatic Approach to Detect Software Anomalies in Cloud Computing Using Pragmatic Bayes Approach
Статья научная
Software detection of anomalies is a vital element of operations in data centers and service clouds. Statistical Process Control (SPC) cloud charts sense routine anomalies and their root causes are identified based on the differential profiling strategy. By automating the tasks, most of the manual overhead incurred in detecting the software anomalies and the analysis time are reduced to a larger extent but detailed analysis of profiling data are not performed in most of the cases. On the other hand, the cloud scheduler judges both the requirements of the user and the available infrastructure to equivalent their requirements. OpenStack prototype works on cloud trust management which provides the scheduler but complexity occurs when hosting the cloud system. At the same time, Trusted Computing Base (TCB) of a computing node does not achieve the scalability measure. This unique paradigm brings about many software anomalies, which have not been well studied. This work, a Pragmatic Bayes approach studies the problem of detecting software anomalies and ensures scalability by comparing information at the current time to historical data. In particular, PB approach uses the two component Gaussian mixture to deviations at current time in cloud environment. The introduction of Gaussian mixture in PB approach achieves higher scalability measure which involves supervising massive number of cells and fast enough to be potentially useful in many streaming scenarios. Wherein previous works has been ensured for scheduling often lacks of scalability, this paper shows the superiority of the method using a Bayes per section error rate procedure through simulation, and provides the detailed analysis of profiling data in the marginal distributions using the Amazon EC2 dataset. Extensive performance analysis shows that the PB approach is highly efficient in terms of runtime, scalability, software anomaly detection ratio, CPU utilization, density rate, and computational complexity.
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An Efficient Algorithm for Finding a Fuzzy Rough Set Reduct Using an Improved Harmony Search
Статья научная
To increase learning accuracy, it is important to remove misleading, redundant, and irrelevant features. Fuzzy rough set offers formal mathematical tools to reduce the number of attributes and determine the minimal subset. Unfortunately, using the formal approach is time consuming, particularly if a large dataset is used. In this paper, an efficient algorithm for finding a reduct is introduced. Several techniques are proposed and combined with the harmony search, such as using a balanced fitness function, fusing the classical ranking methods with the fuzzy-rough method, and applying binary operations to speed up implementation. Comprehensive experiments on 18 datasets demonstrate the efficiency of using the suggested algorithm and show that the new algorithm outperforms several well-known algorithms.
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An Efficient Approach of Power Consumption in Cloud using Scheduling of Resources
Статья научная
Cloud computing is the stage for a choice of services like software, infrastructure as a cloud service and each person wants to have the benefit of that cloud services using the cloud computing concept, which ultimately increases the data size and loaded records on cloud servers. Due to increased number of files on the cloud database the retrieval of files becomes much more time consuming and complex. Also this file retrieval doesn't ensure the exact retrieval of files from the storage. Besides, the privacy apprehensions affect to the appropriate documents regained by the cloud user in the afterward phase in view of the fact that they may also enclose sensitive data and make known information about sensitive exploration words or phrase. Here in this paper an efficient approach of power consumption using scheduling of resources is implemented.
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Статья научная
In Project management, team's motivation is one of the most important factors in the success of a project. Project Managersmanage the whole project by assuring that all the members are performing the duties they are assigned. Emotional Intelligence is the ability to identify the attitude of a team member towards a project. In developing countrieslack of emotional intelligence factors may cost people their jobs. In this paper conflict management, technical management, interest development and stress management problems are discussed with reference to developing countries and an efficient approach to resolve these issues is also proposed. Therefore project managers should raise their EI (emotional intelligence) and also help members to raise their EI. This paper explores the related work in EI, and then finds the useful Emotional Intelligence factors which are appropriate for the project manager. Then this paper also determinesa framework which is useful for project managers.
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Статья научная
Biggest internet security threat is the rise of Botnets having modular and flexible structures. The combined power of thousands of remotely controlled computers increases the speed and severity of attacks. In this paper, we provide a comparative analysis of machine-learning based classification of botnet command & control(C&C) traffic for proactive detection of Peer-to-Peer (P2P) botnets. We combine some of selected botnet C&C traffic flow features with that of carefully selected botnet behavioral characteristic features for better classification using machine learning algorithms. Our simulation results show that our method is very effective having very good test accuracy and very little training time. We compare the performances of Decision Tree (C4.5), Bayesian Network and Linear Support Vector Machines using performance metrics like accuracy, sensitivity, positive predictive value(PPV) and F-Measure. We also provide a comparative analysis of our predictive models using AUC (area under ROC curve). Finally, we propose a rule induction algorithm from original C4.5 algorithm of Quinlan. Our proposed algorithm produces better accuracy than the original decision tree classifier.
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An Efficient Technique for Optimality Measurement of Approximation Algorithms
Статья научная
Many algorithms have been proposed for the solution of the minimum vertex cover (MVC) problem, but the researchers are unable to find the optimality of an approximation algorithm. In this paper, we have proposed a method to evaluate that either the result returned by an approximation algorithm for the minimum vertex cover problem is optimal or not. The proposed method is tested on three algorithms, i.e., maximum degree greedy (MDG) algorithm, modified vertex support algorithm (MVSA) and clever steady strategy algorithm (CSSA). The proposed method provides an opportunity to test the optimality of an approximation algorithm for MVC problem with low computation complexity. The proposed method has performed well during experimentation, and its results brighten the path of successful implementation of the method for the evaluation of approximation algorithms for the minimum vertex cover (MVC) problem. The testing of the proposed method was carried out on small graph instances. The proposed method has resolved the problem to test the optimality of the approximation algorithm for the minimum vertex cover problem. This technique has digitized the process of finding out the accuracy of the optimal solution returned by approximation algorithms for MVC.
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An Efficient Virtual Machine Scheduling Technique in Cloud Computing Environment
Статья научная
Cloud is a collection of heterogeneous resources and requirements of these resources can change dynamically. Cloud providers are always interested in maximizing the resources utilization and the associated revenues, by trimming down energy consumption and operational expenses, while on the other hand cloud users are interested in minimizing response time and optimizing overall application throughput. In cloud environment to allocate the resources with minimum overhead time along with efficient utilization of available resources is very challenging task. The resources in cloud datacenter are allocated using a virtual machine (VM) scheduling technique. So there is a need of an efficient VM scheduling technique to maximize system performance and cost saving. In this paper two dynamic virtual machine scheduling techniques i.e. Best fit and Worst fit are proposed for reducing the response time along with efficient and balanced resource utilization. The proposed algorithms removes the limitations of the previously proposed Novel Vector based algorithm and minimizes the response time complexity in order of O(logn) and O(1) using Best Fit and Worst Fit strategies respectively.
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