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Mythili, S.
- Evaluation of Soil Fertility Status in Teak Plantations of South India
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Indian Forester, Vol 124, No 2 (1998), Pagination: 146-149Abstract
In the present study, the available macro-nutrient status and the physico-chemical properties of soils at different Teak plantations of Sterling Tree Magnum (India) Ltd., were evaluated. It has been found that the nitrogen (Alkaline KMnO4), phosphorus (Bray I-P and Olsen-P) and potassium (NH4OAc) status of the plantations were low to medium, low and medium to high levels, respectively. Thus, Soil Fertility Evaluation could form the basis for better discriminatory fertilizer recommendation to the growing Teak plantations of India for the maintenance of soil fertility status and to have sustainable Teak production.
- Fabric Defect Detection Using Steerable Pyramid
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Authors
Affiliations
1 Department of Computer Science & Engineering, United Institute of Technology, Tamil Nadu, IN
1 Department of Computer Science & Engineering, United Institute of Technology, Tamil Nadu, IN
Source
ICTACT Journal on Image and Video Processing, Vol 1, No 4 (2011), Pagination: 204-212Abstract
In this paper, a novel idea is proposed for fabric defect detection. De-fects are detected in the fabric using steerable pyramid along with a defect detection algorithm. Various steerable pyramid of four size 256256, 128128, 6464, 3232 and with four orientation bands 00,450, 900, 1350 are used. Utilizing a Steerable pyramid proved ade-quate in the representation of fabric images in multi-scale and multi-orientations; thus allowing defect detection algorithms to run more effectively. Defect detection algorithm identifies and locates the im-perfection in the defective sample using the statistics mean and stan-dard deviation. This statistics represents the relative amount of inten-sity in the texture and is sufficient to measure defects in the current model .The obtained result are compared with the existing methods wavelet based system and with Gaussian and Laplacian pyramid.Keywords
Fabric Automatic Visual Inspection, Steerable Pyramid, Feature Extractor, Defect Detector.- Parallel Implementation of Genetic Algorithm using K-Means Clustering
Abstract Views :126 |
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Authors
Affiliations
1 Department of Computer Applications, Hindusthan College of Arts and Science, Coimbatore, IN
1 Department of Computer Applications, Hindusthan College of Arts and Science, Coimbatore, IN
Source
International Journal of Advanced Networking and Applications, Vol 3, No 6 (2012), Pagination: 1450-1455Abstract
The existing clustering algorithm has a sequential execution of the data. The speed of the execution is very less and more time is taken for the execution of a single data. A new algorithm Parallel Implementation of Genetic Algorithm using KMeans Clustering (PIGAKM) is proposed to overcome the existing algorithm. PIGAKM is inspired by using KM clustering over GA. This process indicates that, while using KM algorithm, it covers the local minima and it initialization is normally done randomly, by KM and GA. It always converge the global optimum eventually by PIGAKM. To speed up GA process, the evalution is done parallely not individually. To show the performance and efficiency of this algorithms, the comparative study of this algorithm has been done.Keywords
Clustering, Genetic Algorithm, K-Means, Mutation, Parallel.Full Text
- Design And Analysis of Koch Fractal Antenna for Wlan Applications
Abstract Views :142 |
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Authors
Affiliations
1 Department of Electronics and Communication Engineering, Rajiv Gandhi College of Engineering College, IN
1 Department of Electronics and Communication Engineering, Rajiv Gandhi College of Engineering College, IN
Source
ICTACT Journal on Microelectronics, Vol 6, No 2 (2020), Pagination: 923-927Abstract
In this paper, a Koch fractal antenna is designed for Wireless Local Area Network (WLAN) applications. Koch snowflake design is symmetrical and self-similar structure that induces space filling capability and improves the surface current on the antenna. The overall fractal antenna structure consist of a copper foils (Patch and Ground Plane) mounted on either sides of the dielectric material (Flame Retardant-4 (FR-4) with permittivity εr =4.4 and loss tangent δ=0.02). The antenna is fed using a microstrip line feed. The dimensions of the Koch fractal antenna are 30x30x1.6mm3 which is compact sized design made on High Frequency Structure Simulator (HFSS) platform. The simulation outputs are internally compared with different iterations implemented on the patch using Iterated Function System (IFS) and the difference in the radiating frequency, return loss, bandwidth, gain and directivity of all three different iterations. The resonating frequency for three iterations ranges from 5.8GHz to 7.47GHz which can be used in WLAN applications. Thus, the proposed Koch snowflake fractal antenna design provides improvements in the antenna parameters on increasing scale of iteration such as S11 from -21.35dB to -36.32dB, average gain of 3dB and Impedance Bandwidth of 25.90%.Keywords
Antenna Design, FR-4, Ground Plane, Koch Snowflake, Patch, WLAN Application.- Performance Analysis of Anomalous Detection Scehmes Based on Modified Support Vector Machine and Enhanced Relevance Vector Machine
Abstract Views :156 |
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Authors
Affiliations
1 Department of Computer Science, Kongunadu Arts and Science College, IN
2 Department of Information Technology, Kongunadu Arts and Science College, IN
1 Department of Computer Science, Kongunadu Arts and Science College, IN
2 Department of Information Technology, Kongunadu Arts and Science College, IN
Source
ICTACT Journal on Soft Computing, Vol 11, No 3 (2021), Pagination: 2364-2377Abstract
Anomalous transactions are common activity happening on the financial oriented transaction. Detecting those anomalous transactions from the financial transaction patterns is the most complex task which is focused in this work. In the existing work it is achieved by introducing the method namely Fuzzy Exception and Fuzzy Anomalous Rule (FEFAR). The accuracy of this existing work FEFAR found to be lesser which is resolved in the proposed research work. There are two research works has been proposed those are namely Rule Pruning based Anomalous Rule Detection Strategy (RPARD) and Lasso Regression based Improved Anomalous Detection Scheme (LR-IADS). Both of these methods attempt to find the anomalous transaction from the given input database by finding the anomalous rules. Each method differ in its methodologies, thus the accuracy of the methods would differ. The main goal of this analysis work is to compare the performance of existing and proposed methodologies based on simulation outcome. This research work aims to highlight the performance variation between the proposed and existing techniques and the best method that can offer accurate anomalous transaction detection. The analysis of the research work is carried out on matlab environment over four databases namely soil, bank, german statlog and auto mpg based on which performance outcome has been given.Keywords
Anomalous Transaction, Anomalous Rules, Accuracy, RPARD, LR-IADS, FEFAR.References
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- T. Zhang, W. Zhang, X.U. Wei and H.A.O. Haijing, “Multiple Instance Learning for Credit Risk Assessment with Transaction Data”, Knowledge-Based Systems, Vol. 161, pp. 65-77, 2018.
- S. Senthil Kumar and S. Mythili, “Survey on Exception Rules and Anomaly Detection”, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, Vol. 2, No. 6, pp.521- 525, 2017.
- S. Senthil Kumar and S. Mythili, “Accurate Fuzzy Anomalous Rule Identification Using Classification Algorithms”, Journal of Advance Research in Dynamical and Control Systems, Vol. 11, No. 5, pp. 241-262, 2019.
- S. Chen, M. Peng, H. Xiong and S. Wu, “An Anomaly Detection Method based on Lasso”, Cluster Computing, Vol. 22, No. 3, pp.5407-5419, 2019.
- Robust Tristate Security Mechanism to Protect Against Selective Forwarding Attack and Black Hole Attack in Intra-Cluster Multi-Hop Communication
Abstract Views :96 |
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Authors
A. Anitha
1,
S. Mythili
2
Affiliations
1 Department of Computer Science, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu., IN
2 Department of Information Technology, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu., IN
1 Department of Computer Science, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu., IN
2 Department of Information Technology, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu., IN
Source
International Journal of Computer Networks and Applications, Vol 10, No 3 (2023), Pagination: 443-455Abstract
Security is the most vital issue to be addressed in Wireless Sensor Networks (WSNs). The WSN dominates since it has an effectiveness of applications in numerous fields. Though it has effectiveness towards its applications likewise it is susceptible to two different kinds of attacks (i.e.) external attacks and internal attacks existence of constrained reckoning resources, low memory, inadequate battery lifetime, handling control, and nonexistence of interfere resilient packet. Handle internal attacks such as selective forwarding attacks (SFAs) and black hole attacks (BHA) are considered to be the most common security extortions in wireless sensor networks. The attacker nodes will execute mischievous activities during data communication by creating traffic load, delaying packet delivery, dropping packets selectively or dropping all packets, energy consumption, and depleting all network resources. These attacks can be handled efficiently by implementing the proposed methodology for detecting, preventing, and recovering Cluster Heads (CHs), Cluster Members (CMs), and Transient Nodes (TNs) from SFAs and BHA in intra-cluster multi-hop. It is accomplished by proposing a robust strategy for overcoming internal attacks on cluster head, cluster member, and transient node. The Fuzzy C-Means clustering is used to discover the prominent cluster head. The uncertainty entropy model is used to detect internal attacks by removing the malicious node from the transition path. The intermediate node is been selected based on the degree and dimension. The experimental results of the proposed Robust Tristate Security Mechanism (RTSSM) against SFAs and BHA are evaluated with packet delivery ratio, throughput, and packet drop and the results prove the effectiveness of the proposed methodology and it also aids in the extension of the network lifetime.Keywords
Cluster Head, Cluster Member, Intra-Cluster, Multi-Hop, Clustering, Wireless Sensor Networks, Uncertainty, Robust, Fuzzy Membership, Entropy.Full Text
References
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- Anitha, S.Mythili, “An Approach for Detection and Prevention of Cluster Head and Cluster Member from Selective Forwarding Attacks and Black Hole Attack in Intra-Cluster Multi-Hop Communication,” Design Engineering, Vol. 2021, Issue.06, pp. 1032-1060.
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- Empowered Chicken Swarm Optimization with Intuitionistic Fuzzy Trust Model for Optimized Secure and Energy Aware Data Transmission in Clustered Wireless Sensor Networks
Abstract Views :98 |
PDF Views:1
Authors
A. Anitha
1,
S. Mythili
2
Affiliations
1 Department of Computer Science, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu, IN
2 Department of Information Technology, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu, IN
1 Department of Computer Science, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu, IN
2 Department of Information Technology, Kongunadu Arts and Science College, Coimbatore, Tamil Nadu, IN
Source
International Journal of Computer Networks and Applications, Vol 10, No 4 (2023), Pagination: 511-526Abstract
Each sensor node functions autonomously to conduct data transmission in wireless sensor networks. It is very essential to focus on energy dissipation and sensor nodes lifespan. There are many existing energy consumption models, and the problem of selecting optimized cluster head along with efficient path selection is still challenging. To address this energy consumption issue in an effective way the proposed work is designed with a two-phase model for performing cluster head selection, clustering, and optimized route selection for the secure transmission of data packets with reduced overhead. The scope of the proposed methodology is to choose the most prominent cluster head and assistant cluster head which aids in prolonging the network lifespan and also securing the inter-cluster components from selective forwarding attack (SFA) and black hole attack (BHA). The proposed methodology is Empowered Chicken Swarm Optimization (ECSO) with Intuitionistic Fuzzy Trust Model (IFTM) in Inter-Cluster communication. ECSO provides an efficient clustering technique and cluster head selection and IFTM provides a secure and fast routing path from SFA and BHA for Inter-Cluster Single-Hop and Multi-Hop Communication. ESCO uses chaos theory for local optima in cluster head selection. The IFTM incorporates reliance of neighbourhood nodes, derived confidence of nodes, estimation of data propagation of nodes and an element of trustworthiness of nodes are used to implement security in inter-cluster communication. Experimental results prove that the proposed methodology outperforms the existing approaches by increasing packet delivery ratio and throughput, and minimizing packet drop ratio and energy consumption.Keywords
Wireless Sensor Networks, Chicken Swarm Optimization, Intuitionistic Fuzzy Trust Model, Energy Aware, Security, Cluster Head, Clustering and Inter-Cluster Communication.Full Text
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