Abul Hashem Beg

Lowest Data Replication Storage of Binary Vote Assignment Data Grid

Data replication is one of the mechanisms in data grid architecture since it improves data access and reliability. There are many replication techniques exist in distributed systems environment include Read-One-Write-All (ROWA), Branch Replication Scheme (BRS), Hierarchical Replication Scheme (HRS) and our previous Binary Vote Assignment Data Grid (BVADG) techniques. All these techniques deploy different approaches of data placement in distributed environment. This paper presents the comparison of the replication storage between all these techniques. The result shows that BVADG has the lowest data replication storage between ROWA, BRS and HRS due to the small quorum approach of data placement.

Mental and Spiritual Relaxation by Recitation of the Holy Quran

Nowadays, Tension or Stress is a common and serious problem in our Global Village. Stress and stress related factors contribute to tension and reduced ability to handle lifes everyday challenges. This paper proposes a new method to reduce the stress and tension of our life and also proves that mentally, spiritually and physically relaxation can be achieved by the recitation of the holy Quran. In this technique of listening, reading and watching the text of the Holy Quran subject (User) can involve the whole body. The entire process will be controlled by brain, as a result during this practice the whole body will receive relaxation/refreshment, and the exhaustion, boring and tiredness will be finished. This physiological biofeedback manner provides groceries for spirit. Hence this means can be used in hospitals for mentally disturb and depression effected patients, for relaxation of the soldiers, for refreshing the students, to cool down workers in industries and for the entertainment of passengers in buses and airplanes. This approach replaces negative thoughts with positive and truthful thoughts.

MaxD K-Means: A Clustering Algorithm for Auto-generation of Centroids and Distance of Data Points in Clusters

K-Means is one of the unsupervised learning and partitioning clustering algorithms. It is very popular and widely used for its simplicity and fastness. The main drawback of this algorithm is that user should specify the number of cluster in advance. As an iterative clustering strategy, K-Means algorithm is very sensitive to the initial starting conditions. In this paper, we propose a clustering technique called MaxD K-Means clustering algorithm. MaxD K-Means algorithm auto generates initial k (the desired number of cluster) without asking for input from the user. MaxD K-means also used a novel strategy of setting the initial centroids. The experiment of the Max-D means has been conducted using synthetic data, which is taken from the Llyod’s K-Means experiments. The results from the new algorithm show that the number of iteration improves tremendously, and the number of iterations is reduced by confirming an improvement rate is up to 78%.

Improved Parameterless K-Means: Auto-Generation Centroids and Distance Data Point Clusters

Internet has brought a major drift in user community. Apart from its well-known usage, it also promotes social networking. Research on such social networking has advanced significantly in recent years which have been highly influenced by the online social websites. People perceive the web as a social medium that allows larger interaction among people, sharing of knowledge, or experiences. Internet or social web forums act as an agent to reproduce some general information that would benefit the users. A product review by the user is a more accurate representation of its real-world performance and web-forums are generally used to post such reviews. Though commercial review websites allow users to express their opinions in whatever way they feel, the number of reviews that a product receives could be very high. Hence, opinion mining techniques can be used to analyze the user-reviews, classify the content as positive or negative, and thereby find out how the product fares. This paper focuses its attention on providing a recommendation to the products available on the web by analyzing the context to score the sentences for each review by identifying the opinion and feature words using a novel algorithm.

MT2Way: A Novel Strategy for Pair-Wise Test Data Generation

Reducing the number of test cases by utilizing minimum possible amount of time during the testing process of software and hardware is highly desirable. For ensuring the reliability of the method the combination of a complete set of available inputs is recommended to be executed. But generally an exhaustive numbers of test cases are hard to execute. Besides, test data generation is an NP-hard (non-deterministic polynomial-time hard) problem. This is likely to present considerable difficulties in defining the best possible method for generating the test data. The reduction of test cases depends on the interaction level, 2-way interaction or pair-wise test data can reduce high number of test cases and it efficiently addresses most of the software errors. This paper presents MT2Way, an effective 2-way interaction algorithm to generate the test data which is more acceptable in terms of the number of test cases and execution time. The performance tests show that MT2Way achieve better results in terms of system configuration, generated test size, and executing time as compared to other techniques.

Synchronous Replication: Novel Strategy of Software Persistence Layer Supporting Heterogeneous System

Synchronous replication is the ideal solution for organizations: search for the fastest possible data recovery, minimal data loss and protection against the problems of database integrity. This ensures that the remote copy of data that is identical to the primary copy is created at the same time the primary copy is updated. However, most of the synchronous replication does not consider the heterogeneous system. In this paper, a software persistence layer for heterogeneous synchronous replication has been designed and developed based on multi-threading known as PLSR. The main objective of this strategy is to make the persistence layer adaptive and make the synchronous replication process reliable and faster than other existing replication processes concerning cost minimization. In the proposed PLSR replication technique, the replication servers are OS independent and the entire replication process is not inter dependent nevertheless on the main server. Adding a new replication server is easier than other processes. The technique also introduces the modification of replication servers without making impairment to the entire process. The comparative Results with SQL server data replication show the PLSR is more acceptable in terms of transactional insertions and sync time. The result shows that PLSR outstanding performs 88.5 % faster than SQL server for transactional insert.

Framework of Persistence Layer Synchronous Replication to Improve Data Availability into a Heterogeneous System

Data replication is an important technique in peer to peer network, data grid architecture, clustering and distributed system, where it increases data availability and enhances data access and reliability and minimizes the cost of data transmission. In this paper, we proposed a framework and structure of synchronous replication from the persistence layer that supports heterogeneous system. In this framework, we developed the multithreading based persistence layer. Our objective is to make the persistence layer more adaptive. In this adaptive persistency system, the replication server will not depend on the main server, so forth, adding a new replication server will be easier than ever, easy to cope with heterogeneous system, cost minimizing and finally there will be no down time.

Artificial intelligent strategy to control heart rate variability

This research proposes a new artificial intelligence strategy to enhance software games based on heart rate variability. The model consists of two modules (visual learning and IQ test) that will conjoined with a biofeedback device connected to a computer to monitor student heart rate and record its changes in a stressful situation and generate appropriate reports. By playing these two games student will be able to improve their learning capability and control their heart rate variability.

Notice of Retraction Framework of intelligent game and software for improvement of learning performance based on heart rate variability

In many cases, students become stressed and they become worried about their study, which in terms become a great impediment to their learning capability. This paper proposes new framework of intelligent game model based on biofeedback techniques. The model consists of two modules (visual learning and IQ test) that will conjoined with a biofeedback device connected to a computer to monitor student heart rate and record its changes in a stressful situation and generate appropriate reports. The two games have different purpose to serve. Visual learning games will improve learners visual learning capability, memorizing capability and IQ test will improve analytical ability.