"There is nothing permanent except change" Heraclites of Ephesus (535-475 BC) It is no exaggeration when we say that the IUP Journal of Computer Sciences is one among the million causes that will contribute to the growth of research in the country. Computer Science is one field that is calling for higher visibility for experimentation and theory works as the driving force. This issue is no exception and it showcases some of the current experimental research within the panoply of computer science disciplines, illustrating its many forms including observation, measurement, replication of previous work and novelty.

Geographical Information Systems, a multidisciplinary area, plays an important role in collection of data, their analysis, and providing the necessary support for taking decisions in planning and execution. This issue starts with the paper, "Management of Urban Development Using Neural Networks with OD Matrix", by A K Ojha and Dushmanta Mallick on GIS, where it estimates the Orientation Destination (OD) distribution matrix of the urban transportation network using the Hopfield Neural Network (HNN). OD distribution is an important data for the design and reconstruction of cities. The authors have concluded that using the HNN model, the estimation of OD distribution of `n' nodes is feasible and satisfactory.

The second paper, "A Novel High Security Message Authentication Code MACJER-320 and its Performance Evaluation", deals with a new message authentication code and its performance evaluation. Sheena Mathew and K Poulose Jacob, the authors of the paper, use a 320-bit hash function called JERIM-320 in their Message Authentication Code MACJER-320. JERIM-320 is designed to operate on four parallel lines of message processing, resulting in a higher degree of security. MACJER-320's performance is evaluated in comparison with HMAC, where the 160-bit hash function SHA-1, is used.

The third paper, "The New Semantic Similarity Measure Using Ontology and Corpus", describes a new semantic similarity measure using Ontology and Corpus, i.e., distance between terms. This measure, according to the authors, P Selvi and N P Gopalan, combines the strengths and complements the weaknesses of the existing measures that use knowledge base as the primary source. It uses a new feature of common specificity besides the path length feature. This common specificity feature is derived from information content of concepts and information content of the knowledge base. The semantic similarity measure gives the best correlation of 0.874 with human scores in the benchmark test set, compared to the existing measures.

An interesting paper, "Finite-State Automata based Classification of News Segments", on Finite-State Automata (FSA)-based system to retrieve contextual structure from news video database falls in this issue as fourth one. Parsing video programs into program segments is useful in retrieving individual segments and video segmentation. The authors, Ankush Mittal and Sumit Gupta, present a FSA-based system that extracts a contextual structure from news video database. Each of the video segments such as newscaster sequence, weather sequence, etc., becomes a node in the FSA. The transition is fired from one node to another node based on arc conditions, which can easily be obtained by employing statistical methods on classified data. Modeling with FSA avoids the use of the complex rule-based system. Experimental results presented here, according to authors, show an accuracy of 88% in recognizing the components of news video data of more than eight hours.

The next paper, "An Efficient All Spanning Tree Generation Algorithm", written by Sanjay Kumar Pal and Samar Sen Sarma, dwells with the generation of all spanning trees of a symmetric and connected graph. Without duplicate spanning trees and non-tree subgraphs, this paper considers the generation of all spanning trees of a connected graph, the application of which can be seen in the areas of networking and circuit analysis. Since the number of spanning trees in a graph is exponential, the proposed algorithm reduces the time complexity in comparison with the existing ones.

The last paper, "Technological Research Challenges in Realizing Adaptive E-Learning", surveys e-learning activities and technological research challenges that are to be addressed. The authors, Asim Zafar and Nesar Ahmad, discuss various e-learning systems, e-learning standards, e-learning activities, and technological research challenges. The authors conclude that the focus of the paper is how the content can be distributed with a measurable quality to devices in order to improve the users' learning process.

- CRK Prasad
Consulting Editor