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Mohammed, Amin Salih
- Exploiting the Local Optima in Genetic Algorithm using Tabu Search
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Authors
Affiliations
1 Department of Information Technology, Lebanese French University, Erbil, Kurdistan Region, IQ
2 Department of Electronics and Communication Engineering, PSNA College of Engineering and Technology, Kothandaraman Nagar, Dindigul – 624622, Tamil Nadu, IN
1 Department of Information Technology, Lebanese French University, Erbil, Kurdistan Region, IQ
2 Department of Electronics and Communication Engineering, PSNA College of Engineering and Technology, Kothandaraman Nagar, Dindigul – 624622, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 12, No 1 (2019), Pagination: 1-13Abstract
Objectives: To explores the process of selecting retrieval schemes along with their weights, and fusion function for data fusion in information retrieval. Methods/Statistical Analysis: This has been carried out using the hybrid Genetic Algorithm. The fusion function, retrieval schemes and their weights lead to a tremendous combination. Finding an optimal solution from this great combination is entirely based on the exploration. Findings: We used, odd and even point crossover as an exploration tool. This exploration tool suffers a setback of slow convergence. The convergence rate can be improved by merging Tabu search, a best local search, with the genetic algorithm. This Tabu GA is used to select the retrieval schemes, weights and fusion function. The outcome of the experiments conducted over the test data sets namely: 1. adi, 2. cisi, and 3. cranlooks promising. We achieved 6.89% of improvement in performance, and the significance of the result is tested statistically. The convergence rate is also improved. Application/Improvements: We achieved 6.89% of improvement in performance, and the significance of the result is tested statistically. The convergence rate is also improved.Keywords
Genetic Algorithm, Information Retrieval, Odd and Even Point Crossover, Tabu GA, Tabu SearchFull Text
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- Detection of Accurate Facial Detection using Hybrid Deep Convolutional Recurrent Neural Network
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Authors
Affiliations
1 Department of Information Technology, Lebanese French University, IQ
1 Department of Information Technology, Lebanese French University, IQ
Source
ICTACT Journal on Soft Computing, Vol 9, No SP 2 (2019), Pagination: 1844-1850Abstract
Facial Landmark discovery is an imperative issue in numerous PC vision applications about appearances. It is extremely testing as human faces in wild conditions regularly present expansive varieties fit as a fiddle because of various stances, impediments or demeanors. Profound neural systems have been connected to take in the guide from face pictures to confront shapes. To the best of our insight, Recurrent Neural Network (RNN) has not been utilized in this issue yet. In this paper, we propose a technique which uses RNN and Deep Neural Network (DNN) to take in the face shape. To start with, we design a system utilizing Convolutional Neural Network (CNN) to get the underlying Landmark estimation of appearances. At that point, we utilize feed-forward neural systems for neighborhood look where a segment based seeking technique is investigated. By utilizing LSTM- CNN-RNN, the underlying estimation is more dependable which makes the accompanying segment based pursuit doable and exact. Tests demonstrate that the worldwide system utilizing CNN-LSTM-RNN shows signs of improvement results than past systems in the two recordings and single picture. Our technique beats the cutting edge calculations particularly regarding fine estimation of Landmark spots.Keywords
Facial landmark, Deep Neural Network, Recurrent Neural Network, Convolutional Neural Network.
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- Privacy Preserving Data Mining using Threshold Based Fuzzy C-Means Clustering
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Authors
Affiliations
1 Department of Information Technology, Lebanese French University, Erbil, IQ
1 Department of Information Technology, Lebanese French University, Erbil, IQ
Source
ICTACT Journal on Soft Computing, Vol 9, No 1 (2018), Pagination: 1813-1816Abstract
Privacy preserving is critical in the field of where data mining is transformed into cooperative task among individuals. In data mining, clustering algorithms are most skilled and frequently used frameworks. In this paper, we propose a privacy-preserving threshold clustering that uses code based technique with threshold estimation for sharing of secret data in privacy-preserving mechanism. The process includes code based methodology which enables the information to be partitioned into numerous shares and handled independently at various servers. The proposed method takes less number of iterations in comparison with existing methods that does not require any trust among the clients or servers. The paper additionally provides experimental results on security and computational efficiency of proposed method.Keywords
Privacy Preserving, Data Mining, Threshold Cryptography, Fuzzy C-Means Clustering, Vandermonde Matrix, Secure Multiparty Computation.References
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- Optimized Cooperative QOS Enhanced Distributed Multipath Routing Protocol
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Authors
Affiliations
1 Department of Computer Engineering, Lebanese French University, IQ
2 Department of Information Technology, Emirates College for Management and Information Technology, AE
3 Department of Master of Computer Application, Jain University, IN
1 Department of Computer Engineering, Lebanese French University, IQ
2 Department of Information Technology, Emirates College for Management and Information Technology, AE
3 Department of Master of Computer Application, Jain University, IN
Source
ICTACT Journal on Communication Technology, Vol 10, No 3 (2019), Pagination: 2061-2065Abstract
The link failure is considered in this paper in order to guarantee reliable and continuous transmission of data. And to ensure that cooperative routing is done faster response and effective packet transmission. Cooperative communications are the most recent fields of research; they combine wireless channels’ link quality and broadcasting nature. So communication in ad hoc mobile networks only works properly if the participating nodes work together in routing and transmission. A flow is divided into batches of data packets. When they leave the source node every packet in the same batch has the same forwarder list. The underlying routing protocol used in this work is Proactive Source Routing (PSR), which provides each node with all other nodes on the network. The forwarder list therefore contains the identity of the path nodes from the source node to the location. Once packets progress through the network, forwarding nodes can amend the forwarder list when any changes in the network topology have been observed. In addition, some other nodes not listed as transmitting data may also be transmitted, which is called as small-scale retransmission.Keywords
Link-Quality, QOS, Proactive Source Routing, Multipath Routing Protocol.References
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