Informatics Publishing Limited

Vinay Chopra ¹, Amardeep Singh ²

Affiliations
1 Computer Science & Engineering Department with the DAV Institute of Engineering and Technology, Jalandhar, Punjab, IN
2 Computer Science & Engineering Department with University College of Engineering, Punjabi University, Patiala, Punjab, IN

Abstract

In this paper ANT colony optimization algorithm are used to solve geometric FPGA routing for a route based routing constraint model in FPGA design architecture. In our method geometric FPGA routing task is transformed into a Boolean satisfiability (SAT) equation with the property that any assignment of input variables that satisfies the equation specifies a valid route. The satisfiability equation is then modeled as Constraint Satisfaction problem, which helps in reducing procedural programming. Satisfying assignment for particular route will result in a valid routing and absence of a satisfying assignment implies that the layout is unroutable. In second phase ant colony optimization algorithm is applied on the Boolean equation for solving routing alternatives utilizing approach of hard combinatorial optimization problems for stationary and non-stationary environments. The ACO based solution to SAT is then compared with the other SAT solver algorithms such as zChaff and GRASP. Preliminary experimental results suggest that the developed ant colony optimization algorithm is taking mlogm iterations, where m is number of Boolean instances. The experiments has shown that that ACO has performed efficiently to solve SAT based FPGA routing than classical algorithms and has improved complexity of O(nm/ρ log n).

Keywords

FPGA Routing, Route Based Model, Constraint Satisfaction Programming, Boolean Satisfiability.

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Richa Arora ¹, Vinay Chopra ²

Affiliations
1 Mehr Chand Polytechnic College, Jalandhar, State, Punjab, IN
2 DAV Institute of Engineering and Technology, Jalandhar, State Punjab, IN

Abstract

DNA computing, also known as molecular computing,is a new approach to massively parallel computation. It harnesses the enormous parallel computing ability and high memory density of biomolecules,which brings potential challenges and opportunities to traditional cryptography. DNA Steganography is a new field arising with DNA computing research in recent years. Most of the techniques that were implemented were based on modulating a media file to hide the information required to be transmitted. If the transmission is rather continuous in time, one may refer to the technique as a covert communication channel between two parties.Various methods of advanced steganalysis techniques, with varying degrees of success, were developed to detect the existence of such hidden messages in a media file.

In this work, we present an alternative approach to hiding data in text files. We use different DNA-operations and the message is embedded within a vector sequence. The proposed method covers all the words of English Dictionary for framing a message.

Keywords

DNA Computing, DNA Steganography, DNA Vector.

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Dharminder Kumar ¹, Vinay Chopra ¹

Affiliations
1 Department of Computer Science & Engg, D.A.V. I.E.T., Jalandhar, Punjab, IN

Abstract

Bacteria Foraging Optimization a nature-inspired optimization has drawn the attention of researchers because of its efficiency in solving real-world optimization problems arising in several application domains. Color image quantization is an important process of representing true color images using a small number of colors. Existing color reduction techniques tend to alter image color structure and distribution. Thus the researchers are always finding alternative strategies for color quantization. In cylindrical color spaces like HSI, color is represented by hue, saturation and intensity. These components are closer to the way human perceives and describes color. Hue, saturation and intensity can also reveal image features that are not so obvious in other color spaces. The objective of this research work, is to design an algorithm for Image Quantization using HSI color space based on Bacteria Foraging Optimization. To implement and test the proposed algorithm. To compare the designed algorithm with other quantization techniques. The conducted experiments indicate that proposed algorithm generally results in a significant improvement of image quality compared to other well-known approaches.

Keywords

Color Reduction, Bacteria Foraging Optimization, HSI Color Space, Euclidean Distance, Swarm Intelligence.

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Amandeep Kaur ¹, Vinay Chopra ¹

Affiliations
1 DAV Institute of Engineering. & Technology, Jalandhar, IN

Abstract

Designing of Fuzzy model for optimizing the strategic decision can be very helpful to protect the failures in the system and software. The systems and software development industry is characterized by a paradigm of project failure. One of the known contributing causes of these project failures is poor requirements engineering and management, poor design strategy which has been repeatedly and widely issued and documented. The above problems could be easily countered by the Fuzzy logic, because fuzzy logic has ability to deal with uncertainty and multi valued logic This paper explains the technique for tracking the progress of the software project being built and the technique for selecting an optimal PERT chart developed by using fuzzy logic and it also explains the important variables that effects the strategic decisions connected with the software project.

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Sandeep Kad ¹, Vinay Chopra ²

Affiliations
1 Department of Information Technology, Amritsar College of Engg. & Technology, Amritsar, Punjab, IN
2 Department of Computer Science, DAV Institute of Engg. & Technology, Jalandhar, Punjab,, IN

Abstract

Software development effort estimation is among one of the most challenging jobs that software developers need to perform. Due to the lack of information during the early stages of software development, the developers often express their inability to estimate accurately the effort, cost and schedule of the software under consideration. This inaccuracy in estimation leads to monetary losses as well delay in delivery of the product. In this paper, a soft computing based technique is explored to overcome the problems of uncertainty and imprecision resulting in improved process of software development effort estimation. In doing so, fuzzy logic is applied to different parameters of Constructive Cost Model (COCOMO) II. Results shows that the value of MMRE (Mean of Magnitude of Relative Error) and pred obtained by means of applying fuzzy logic is much better than of MMRE of algorithmic model. The validation of results is carried out on COCOMO dataset.

Keywords

Software Cost Estimation, COCOMO, Soft Computing, Fuzzy Logic.

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Gagan Kumar ¹, Vinay Chopra ²

Affiliations
1 Department of Computer Science and Engineering, IK Gujral Punjab Technical University, IN
2 Master of Computer Applications, D.A.V. Institute of Engineering and Technology, IN

Abstract

Software testing is an essential phase in software design process, accounting for more than half of the total cost due to its rigorous and time-consuming nature. Path test data generation is the most important stage in software testing, and researchers have devised several methods to automate it. In this research, a novel approach based on ant colony optimization and negative selection algorithm (NSA) is projected to automatically create test data for path testing. The most widely used benchmark programs such as triangle classification, dayfinder, minmax and isprime, has been used to test the proposed approach. When compared to random testing, the experimental findings reveal that the proposed method is more efficient in terms of coverage, execution time and more effective in terms of test data creation.

Keywords

Test Data Generation (TDG), Meta-Heuristic, Artificial Immune Algorithm, ACO, NSA, Path Coverage, Fitness Function

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