KUET Institutional Repository (Khulna University of Engineering & Technology)
Not a member yet
1045 research outputs found
Sort by
A Technique for Assuring Secrecy and Lossless Properties of Digital Image
No full textThis thesis is submitted to the Department of Computer Science and Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, September 2020.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 42-47).Due to various disease diagnosis, the volume of medical data is rising fast. Also, for telemedicine, while medical image transmits over the public network, the distortion of pixels may cause erroneous disease diagnosis. Here, encryption of the image by multiple chaos-based schemes along with DNA cryptography can be a safeguard. As chaotic schemes are very sensitive to the initial conditions, a small difference in the initial conditions yields entirely uncorrelated sequences that assure the strength of encryption. To get high randomness, several DNA encoding and computing rules are deployed. This thesis proposes a multi-stage chaotic encryption technique for the medical image through Logistic map along with Lorenz attractor and DNA cryptography, where both schemes possess the most significant value of control parameters. Thus, their consecutive deployment generates colossal chaotic sequences that ensure the robustness of the proposed technique. At first, the usage of the Logistic map with SHA-256 hash value generates a chaotic sequence that converts the plain medical image into a confusing image. Now, this sequence is used to create a confusion key to encrypt this blur image. Later on, to overcome the limitations of DNA computing rules and to get high randomness, encode this blur image and Lorenz attractor based key according to DNA encoding rules. These rules are determined randomly from eight encoding rules. Then, execute DNA operations between encoded blur image and Lorenz key using the four DNA computing rules and these rules are also determined by chaotic logistic sequence. Thus, the ultimate cipher is generated. Then, to approve the potency of the cipher, a randomness test according to NIST, security and statistical analyses and comparisons are performed.Md. Siddiqur Rahman TanveerMaster of Science in Computer Science and Engineerin
Protein Folding Optimization in a Hydrophobic-Polar Model for Predicting Tertiary Structure Using Fruit Fly Optimization Algorithm
No full textThis thesis is submitted to the Department of Computer Science and Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, February 2020.Cataloged from PDF Version of Thesis.Includes bibliographical references (pages 59-64).The prediction of the three-dimensional structure of a protein from its amino acid sequence is an experiment that is very much well known optimization problem which is known as the Protein Folding Optimization (PFO) in many years. The PFO problem states to the computational problem of how to predict the local structure of a protein from its amino acid.
PFO problem is the NP-hard and most challenging problem. Various kind of optimization algorithm already applied for solving the PFO problem, but none of the existing algorithm not provide the accurate result within optimal time. Fruit Fly Optimization Algorithm (FOA)
is a recent metaheuristics algorithm that have the intensity and diversity characteristics of searching technique. Therefore, we applied FOA for solving PFO problem in the HP (Hydrophobic-Polar) cubic lattice model. In order to increase the convergence of the FOA, we have designed and developed three different operators of FOA: smell-based search, local vision-based search and global vision-based search technique for the perspective of PFO problem. The proposed algorithm is based on two extra mechanisms centroid hydrophobic and moderator mechanism, which are accountable for improving the accomplishment of the algorithm. The centroid hydrophobic mechanism tries to move the hydrophobic monomers to the center position of the structure. The moderator mechanisms try to move a part of monomers in the protein sequence each possible directions and place at the position where the maximum energy value found. This two extra mechanisms improved the performance of the propose algorithm magically. Moreover, we have developed a reconstruction operator for producing an accurate 3D structure of protein sequences by erasing overlapping in cubic lattice points. The experiment result shows of our proposed Fruit Fly Optimization Algorithm for Protein Folding Optimization (PFO_FOA) provide better accuracy than the existing algorithms.Sajib ChatterjeeMaster of Science in Computer Science and Engineerin