Information retrieval system has been using to connect users of the information and information repository corpora. Even though the task of information retrieval systems is to retrieve relevant information, it is very difficult to find a perfect information retrieval system which is capable of retrieving relevant and only relevant documents as per user's query. The aim of this research is to increase precision of an Amharic information retrieval system while preserving the original recall. In order to achieve this bi-gram technique has been adopted for the query expansion. The main reason for performing query expansion is to provide relevant documents as per users' query that can satisfy their information need. Because users are not fully knowledgeable about the information domain area, they mostly formulate weak queries to retrieve documents. Thus, they end up frustrated with the results found from an information retrieval system. Amharic language has many meaning for a single word and also the word can be found in different form. These are some of the challenges that made the information retrieval system performing at very low level. Query expansion methods outperform in differentiating the various meanings of a polysemous term and find synonymous terms for reformulating users' query. Bi-gram technique uses the underling theory of expanding a query; using terms that appear adjacent to a query term frequently. The proposed technique was integrated to an information retrieval system. Then the retrieval system is tested with and without using bi-gram technique query expansion. The test result showed that bi-gram based method outperformed the original query based retrieval, and scored 8% improvement in total F-measure. This is an encouraging result to design an applicable search engine, for Amharic language.

This paper provide an overview of the analysis and implementation Multi-Attribute Decision Making (MADM) for food selection or food choice. Food choice aim to find the solution on lack of food. Food choice can be doing with diversification. Food diversification aims to find best choice of food alternatives. Food alternative is rice, corn, cassava, potato, sago, sorghum, wheat, and analog rice. The method used is Simple Additive Weighting (SAW) and Weighted Product (WP). The use of this method is expected to help and provide the best decision in food choice. Alternative on MADM as data training, alternative on SAW method and alternative on WP method as data testing. Experimental result on SAW method, best alternative (highest value) is wheat with value 0.8833. On WP method, best alternative (highest value) is wheat with value 0.1563. On SAW method and WP method, decision is the same with wheat as best alternative in MADM on food choice.

Amplification attacks take advantage of insecurity of different OSI layers. By targeting broadcast address of the victim networks and sending a few packets by the attackers, they force the legitimate user in the victim networks to response to these packets and attack their own trusted networks unknowingly. Despite importance of amplification attacks, there is not any work to implement these attacks to identify their procedure and quantify and compare their impacts on the networks. In this work, we use NS2 to achieve these goals. A variety range of scenarios are designed to implement DDoS amplification attacks and collect the results in terms of different network performance measures. The quantitative results prove devastating impact of the attacks which are easily capable of rendering the target wireless networks disable for their legitimate users. 

This paper presents a customized application in term of LCD interfacing through soft-core microcontroller by implementing its control circuitry in FPGA. Therefore optimum efficiency is achieved. This provide the single chip solution by replacing conventional model which contain separate microcontroller circuit, therefore the efficient resource utilization of FPGA is made, day by day as an increase in the complexity of Embedded system design thus gives many advantages over conventional designed processors such as platform independence, less cost, flexibility and greater immunity to obsolescence.

Multi Criteria Decision Making (MCDM) methods are useful for evaluating several complex factors of multiple selection problems. The Multi-Objective problems are an extension of Single-Objective problems. The goal of MCDM is to help the decision maker to make a choice among a finite number of alternatives or to sort or rank a finite set of alternatives in terms of multiple criteria. Among the MCDM methods, the most widely applied method is TOPSIS. It is applied for different kinds of MCDM problems. In laptop selection process, it is difficult to select better laptop because relatively all laptops are seems to be same. By applying the TOPSIS method to the alternatives it is simple to differentiate the laptops from one another. The better laptop has been selected using TOPSIS based on conflicting criteria such as warranty, size, battery life, specification and others. This methodology also has been evaluated by MCDM evaluation metrics such as Time and Space Complexity, Sensitivity Analysis, ranking reversal and relative closeness coefficient. 

This paper presents the calculation of the classic-curvature and the intensity-curvature term before interpolation of a bivariate polynomial model function. The classic-curvature is termed as yc (x, y) and the intensity-curvature term before interpolation is termed as E0. The classic-curvature is defined as the sum of the four second order partial derivatives of the bivariate polynomial. The intensity-curvature term before interpolation is defined as the integral of the product between the pixel intensity value termed as f(0, 0) and the classic-curvature calculated at the origin of the coordinate system of the pixel. This paper presents an application of the calculation of classic-curvature and the intensity-curvature term before interpolation using two-dimensional Magnetic Resonance Imaging (MRI) data and reports for the first time in the literature on the behavior of the intensity-curvature term before interpolation.

Agile development gets more appreciation from the market due to its flexible nature and high productivity. Scrum provides better management of the processes as compared to other agile modes. Scrum model has several features and strengths but still it lacks in engineering practices and quality. This research deals with the improvement of Scrum processes for better management and quality of software using the infusion of different practices from internationally renowned capability maturity model integration (CMMI) quality standard. Survey is used as a research design to validate the proposed framework. Statistical analysis shows that there is a profound effect on Scrum model due to the proposed research developing high quality software.

Fault tolerant scheduling of many jobs in an environment with millions of unpredictable nodes is not an easy issue. To the best of our knowledge, no work in the literature has proposed a solution that combines the merits of active and passive replication schemes of fault tolerance with the advantages of performance-driven load balancing so as to make the most of the strong points of each. While extensive fault tolerant scheduling and load balancing methods have been presented for the sequential jobs, none have taken into account fault-tolerant load balancing that minimizes the job make-span, provides efficient network and node utilization, achieves a Ill-balanced load and high system flexibility even during the resource failures. Hence, in this article, I present an Adaptive Scheduling Algorithm namely ASA that overcomes these problems. With thorough simulations, I conclude that ASA allocates any number of jobs to a million nodes with relatively low overhead and high flexibility. Experimental results show that the performance of ASA is better than those of its counterparts.