http://dspace.ewubd.edu:8080/xmlui/handle/2525/2937 Mon, 06 Apr 2026 12:05:08 GMT 2026-04-06T12:05:08Z http://dspace.ewubd.edu:8080/xmlui/handle/123456789/3185 Robust Gene Network Topology Construction Based on the Evolutionary Algorithm and Artificial Neural Network Aunjum, Md. Tanvir; Hasan, Md.Nazmul; Rahman, Md. Jahidur Design and implementation of automatic gene regulatory network are essential to construct and analyze the complex biological system. The recent study shows that Darwinian evolution can gradually develop higher topological robustness. In these consequences, this thesis presents an integrated scheme to simulate gene expressions dataset for identifyin g network topologies to find the robustness based on an evolutionary approach and artificial neural network. The final outcome is the most robust topology from a gene regulation dataset. The proposed method was verified using randomly sampled parameter spaces and threshold are generated by the network itself. Here, final result shed lights on the relationship among genes and corresponding transcription factors. Transcription factors are combined to specify the on-and-off states of genes. This binding form a regulatory network and constituting the wire diagram for a cell. The proposed network shows the whole combinatorial and co-association of transcription factors, co-relation and the robustness of human genes. Therefore, this research will play a crucial role in interpreting personal genome sequences and understanding basic principles of human health evolution in near future. This thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering of East West University, Dhaka, Bangladesh. Tue, 18 Sep 2018 00:00:00 GMT http://dspace.ewubd.edu:8080/xmlui/handle/123456789/3185 2018-09-18T00:00:00Z http://dspace.ewubd.edu:8080/xmlui/handle/123456789/3135 Secure Distribution of Certificate Revocation List (CRL) in Vehicular Ad-hoc Network (VANET) Islam, Md. Imamul; Barua, Shuvo; Islam, Md. Ariful In this study, we have implemented Public Key Infrastructure (PKI) with Certification Authority (CA) that will issue and verify the digital certificate of any entity or vehicle in a Vehicular Ad-hoc network (VANET). After revoking a certificate for whatever reasons, the CA generates a Certificate Revocation List (CRL), where there will be the list of revoked certificates. Distribution of CRL is crucial for the quick removal of faulty or misbehaving nodes or any entity whose key pair has been compromised. Secure distribution of CRLs can be ensured with the help of the PKI, to the VANET. We have evaluated the performance of three VANET protocols. These are Ad hoc On-Demand Distance Vector (AODV), Dynamic Source Routing Protocol (DSR) and Destination Sequence Distance Routing Protocol (DSDV). We have evaluated their performance regarding average Lost Packet Ratio (LPR) and average End to End Delay to investigate which protocol performs efficiently in propagating the CRL message to the all nodes. Our results help that there is no best protocol that performs well in every situation, rather depending on the situation, the routing protocol can be selected for the quickest distribution of CRLs. This thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering of East West University, Dhaka, Bangladesh. Sun, 01 Apr 2018 00:00:00 GMT http://dspace.ewubd.edu:8080/xmlui/handle/123456789/3135 2018-04-01T00:00:00Z http://dspace.ewubd.edu:8080/xmlui/handle/2525/3029 Food and Formalin Detector Using Machine Learning Approach Memi, Afsana Azad; Sultana, Nasrin; Tabassum, Kanij Unethical use of formalin, in the preservation of food items posing threat to public health. Without chemical experts accurately Formalin detection is a time consuming and complicated task. Moreover, the presence of naturally occurring formalin in food items may interfere in detecting artificially added formalin. Purpose of the study was to develop a simple cost-effective and reliable detection technique that can detect contaminated food. Therefore, quantifying artificially added formalin and naturally formed extent it is important to dynamically detect food for the comparison. With this view in mind, we have applied different machine learning algorithms like Naïve Bayes, Logistic regression, Support Vector Machine, K-NN Classifier on fruit’s feature dataset to build a predictive model. We found that the K-NN algorithm works best in terms of accuracy. Finally using food conductance to electricity Rules have been developed and uploaded to the microcontroller unit. Combining with Arduino and the VOC HCHO gas sensor our own android application is able to detect 1-50 ppm of formalin. Several Tests are conducted and polynomial regression has been applied to predict the concentration of formalin in a given sample. This thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering of East West University, Dhaka, Bangladesh. Mon, 17 Sep 2018 00:00:00 GMT http://dspace.ewubd.edu:8080/xmlui/handle/2525/3029 2018-09-17T00:00:00Z http://dspace.ewubd.edu:8080/xmlui/handle/2525/3028 Facial Expression Recognition Using Subspace Learning On LBP asnem, Kazi Nuzhat T; Ahmed, Tazin There is different types of methods that can recognize the facial expression but none of them were able to generate the accurate result due to the lack of generalizability. This field has a huge possibilities and can open new doors to human machine interaction. As a result the demand of recognizing the human expression correctly is increasing day by day. So there are many ways to recognize the facial expression. Here in this paper, we are trying to analyze the facial expression on different sub space. First we applied a conventional method, LBP. Then we tried to apply Principal Component Analysis (PCA). We tried another subspace algorithm called Kernel Principal Component Analysis. Then we compared the results. We compared the accuracy of recognizing facial expression of these two algorithm using BSVM tool. This thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering of East West University, Dhaka, Bangladesh. Sat, 05 May 2018 00:00:00 GMT http://dspace.ewubd.edu:8080/xmlui/handle/2525/3028 2018-05-05T00:00:00Z