A. S. M. Latiful Hoque

A New Technique for Database Fragmentation in Distributed Systems

Improving the performance of a database system is one of the key research issues now a day. Distributed processing is an effective way to improve reliability and performance of a database system. Distribution of data is a collection of fragmentation, allocation and replication processes. Previous research works provided fragmentation solution based on empirical data about the type and frequency of the queries submitted to a centralized system. These solutions are not suitable at the initial stage of a database design for a distributed system. In this paper we have presented a fragmentation technique that can be applied at the initial stage as well as in later stages of a distributed database system for partitioning the relations. Allocation of fragments is done simultaneously in our algorithm. Result shows that proposed technique can solve initial fragmentation problem of relational databases for distributed systems properly. General Terms Database, Distributed database, Fragmentation

Automated Essay Scoring Using Generalized Latent Semantic Analysis

Automated Essay Grading (AEG) is a very important research area in educational technology. Latent Semantic Analysis (LSA) is an information retrieval technique used for automated essay grading. LSA forms a word by document matrix and then the matrix is decomposed using Singular Value Decomposition (SVD) technique. Existing AEG systems based on LSA cannot achieve higher level of performance to be a replica of human grader. We have developed an AEG system using Generalized Latent Semantic Analysis (GLSA) which makes n-gram by document matrix instead of word by document matrix. We have evaluated this system using details representation and showed the performance of the system. Experimental results show that our system outperforms the existing system.

Dynamic Materialized View Selection Approach for Improving Query Performance

Because of the query intensive nature of data warehousing or online analytical processing applications, materialized view is quite promising in efficiently processing the queries and for improving the query performance. It is costly to rematerialize the view each time a change is made to the base tables that might affect it. So, it is desirable to propagate the changes incrementally. Hence, all of the views cannot be materialized due to the view maintenance cost. In this paper, we have developed a dynamic cost model based on threshold level incorporating the factors like view complexity, query access frequency, execution time and update frequency of the base table to select a subset of views from a large set of views to be materialized. A number of algorithms and mathematical equations have been designed and developed to define the dynamic threshold level.

Automated essay scoring using Generalized Latent Semantic Analysis

Automated Essay Grading (AEG) is a very important research area in educational technology. Latent Semantic Analysis (LSA) is an information retrieval technique used for automated essay grading. LSA forms a word by document matrix and then the matrix is decomposed using Singular Value Decomposition (SVD) technique. Existing AEG systems based on LSA cannot achieve higher level of performance to be a replica of human grader. We have developed an AEG system using Generalized Latent Semantic Analysis (GLSA) which makes n-gram by document matrix instead of word by document matrix. We have evaluated this system using details representation and showed the performance of the system. Experimental results show that our system outperforms the existing system.

Automated Bangla essay scoring system: ABESS

Essays are the most useful tool to assess learning outcomes. However, teachers have not enough time to evaluate a students writing properly because of their other assigned responsibilities. Several Automated Essay Grading (AEG) systems have been developed to evaluate the human written (not hand written) essays easily. But, most of the AEG systems are used for grading English language or essays written in pure European languages. We have developed an Automated Bangla Essay Scoring System (ABESS) using Generalized Latent Semantic Analysis (GLSA). GLSA is an improved information retrieval technique. The ABESS has been evaluated using essay sets for two domains: standard Bangla essays titled “Bangladesher Shadhinota Songram ()”, and “Karigori Shiksha ()”. We have gained a higher level of accuracy as compared to human grader.

H-HIBASE: Compression Enhancement of HIBASE Technique Using Huffman Coding

HIBASE compression technique simply replaces the attribute values in a tuple with fixed length code-words. However, fixed length coding system is not an optimal compression technique because some redundancies occur in the compressed table. This redundancy can be avoided if we use Huffman code-words. Moreover, using Huffman code-word will ensure optimal compression as well as High performance operation. The objectives of the research are to i) develop a dictionary by applying the principle of Huffman coding, ii) further compress the relational storage of HIBASE by applying dynamic Huffman coding, iii) develop algorithm to perform query operation on the compressed storage, iv) analyze the performance of the proposed system in terms of both storage and queries.

Towards mobile based e-learning in Bangladesh: A framework

Considering the rapid expansion of the usage of mobile communication devices in Bangladesh, development of technology and reduction in cost, well designed mobile based e-learning framework is expected to contribute significantly in educational development and thereby having a long term effect on poverty alleviation. This paper shows an M-Learning framework for Bangladesh.

Integrated data warehousing for telecommunication industries

Data warehousing provides an excellent opportunity in transforming operational data into useful and reliable information to support the decision making process in any organization. Data Warehouse (DW) generalizes and consolidates multidimensional (MD) data. Hence, DW has become an important platform for Online Analytical Processing (OLAP) which is based on a MD data model. In this paper, we propose an integrated data warehouse system for the telecommunication companies in Bangladesh .Our integrated DW provides a common framework based on temporal data from different telecommunication operators rendering their services. We develop a dimensional model architecture, data extraction methodology, transformation and loading techniques which provides analytical options with the implementation of relational OLAP.