J. B. Institute of Engineering and Technology

About: J. B. Institute of Engineering and Technology is a based out in . It is known for research contribution in the topics: Antenna (radio) & The Internet. The organization has 126 authors who have published 126 publications receiving 409 citations. The organization is also known as: JBIET & JB Institute of Technology.

A Comparative Analysis of Machine Learning Algorithms for Detection of Organic and Nonorganic Cotton Diseases

Abstract: Cotton is the natural fiber produced, and the commercial crop grown in monoculture on 2.5% of total agricultural land. Cotton is a drought-resistant crop that provides a reliable income to the farmers that grow under the area with a threat from climatic change. These cotton crops are being affected by bacterial, fungal, viral, and other parasitic diseases that may vary due to the climatic conditions resulting in the crop’s low productivity. The most prone to diseases is the leaf that results in the damage of the plant and sometimes the whole crop. Most of the diseases occur only on leaf parts of the cotton plant. The primary purpose of disease detection has always been to identify the diseases affecting the plant in the early stages using traditional techniques for better production. To detect these cotton leaf diseases appropriately, the prior knowledge and utilization of several image processing methods and machine learning techniques are helpful.

A Novel Feature Selection Method Using Whale Optimization Algorithm and Genetic Operators for Intrusion Detection System in Wireless Mesh Network

Abstract: Machine learning–based intrusion detection system (IDS) is an important requirement for securing data traffic in wireless mesh networks. The noisy and redundant features of network data tend to degrade the performance of the attack detection classifiers. Therefore , the selection of informative features plays a vital role in the enhancement to the IDS. In this paper, we propose a wrapper-based approach using the modified whale optimization algorithm (WOA). One drawback of WOA is that premature convergence results in a local optimal solution. To overcome this limitation, we proposed a method in which the genetic algorithm operators were combined with the WOA. The crossover operator was used to further improve the search space of whales, and the mutation operator helped to avoid being stuck in the local optimum. The proposed method selects the informative features in the network data, which helps to accurately detect intrusions. Using a support vector machine (SVM), we identified the types of intrusions based on the selected features. The performance of the improved method was analyzed by using the CICIDS2017 and ADFA-LD standard datasets. Our proposed method had better attack detection rate than the standard WOA and other evolutionary algorithms; it also had good accuracy and was suitable for IDS in the wireless mesh networks. The performance of the IDS was increased by selecting the informative features with the improved whale optimization algorithm. The attack detection ratio was higher than that of the standard WOA.

Investigation on Simulation-Based Specific Absorption Rate in Ultra-Wideband Antenna for Breast Cancer Detection

Abstract: The electrical properties of the cancer affected cell or malignant tumor cell are completely different from normal healthiest breast tissue. Specific absorption rate (SAR) is used as one of the best parameter to identify the malignant tissue in breast with the help of electrical properties of the human breast tissue, for example, permittivity and conductivity. The design of modified octagonal shaped ultra-wideband monopole microstrip antenna with size of $27\times 29\times 1.6$ mm3, fabricated with FR-4 material, is found suitable for ultra-wideband applications and used to detect the cancer. The antenna impedance bandwidth of simulated and measured results are good (S11 < −10 dB) and its operating frequency ranges from 3 to 15 GHz with voltage standing wave ratio ≤ 2. A 3-D breast model is designed with 60 mm radius, and simulated SAR values are tabulated for skin, fatty tissue, glandular tissue, and tumor. As glandular tissue is one of the softest tissues in human female breast, it has the possibility of developing tumor in lobules and ducts. The tumors of different size are incorporated in glandular tissue. It is found that the SAR value varies based on the tumor size in glandular tissue.

Numerical investigation of flow around cylinder at Reynolds number = 3900 with large eddy simulation technique: Effect of spanwise length and mesh resolution:

Abstract: Flow around a cylinder at a Reynolds number of 3900 was studied using large eddy simulation with ICEM CFD and Fluent tools for meshing and analysis, respectively. Although this issue has been explo...