Ant Colony Optimization Algorithms for the Knapsack and traveling salesman problems
This paper is a simple tutorial for researchers interested in ant colony optimization (ACO) in general and max-min ant system (MMAS) in particular. The paper compares the differences in implementing these algorithms to solve sequencing and selection problems. For selection problems, we use the famous knapsack problem (KP) to demonstrate how MMAS can be used, whereas, for the sequencing problem, we use the famous traveling salesman problem (TSP). Results from the literature show how the MMAS algorithm can outperform other meta-heuristics in solving these two types of problems.
Published by: Sammy Ibrahim
Author: Sammy Ibrahim
Paper ID: V7I5-1315
Paper Status: published
Published: October 6, 2021
Recipient based malicious discovery for overloaded Wireless Networks based on recipients
We remember utility maximization in networks the place the sources do not employ go with the flow manage and may just accordingly overload the group. Inside the absence of go-with-flow manipulation on the sources, some packets will inevitably have got to be dropped when the neighborhood is in overload. To that end, we first advance a disbursed, threshold situated packet-shedding protection that maximizes the weighted sum throughput. Subsequently, we don't forget utility maximization and strengthen a receiver-headquartered waft manipulate scheme that, when combined with threshold-situated packet shedding, achieves the best utility. The glide manipulation scheme creates digital queues on the receivers as a push-back mechanism to optimize the number of talents dropped at the destinations by means of again-strain routing. A wi-fi sensor neighborhood can get separated into a few associated add-ons due to the failure of some of its nodes, which is known as a cut-down. In this article, we recollect the mission of detecting cuts with the aid of the remaining nodes of a wi-fi sensor community. We suggest an algorithm that allows for (i) each and every node to realize when the connectivity to a specially detailed node has been misplaced, and (ii) a number of nodes (that are connected to the targeted node after the scale down) to understand the incidence of the cut. The algorithm is allotted and asynchronous: each node desires to hold up a correspondence with excellent those nodes which will also be inside its verbal trade range. The algorithm is established on the iterative computation of a fictitious electrical knowledge of the nodes.
Published by: M. Harika, Jasmine Sabeena
Author: M. Harika
Paper ID: V7I5-1309
Paper Status: published
Published: October 6, 2021
Novel Approach of Energy efficient Massive MIMO Communication by optimized Clustering in 5G
In general, network plays a vital role in tranferring the information from one node to other. Various techniques are developing to convey the data efficiently. Additionally, in today’s era; less energy utilization, high throughput and serving numerous users at a time are the essential requirements of wireless communication system. So, these requirements can be fulfilled with the help of Massive Multiple-Input Multiple-Output (MIMO) technology to some extent where in the same time-frequency resources; many users can be served with a Base Station (BS) equipped with very large number of antennas. Hence, it is a favourable technology for next generations of wireless systems such as in 5th generation. To communicate inside the large network, it is divided into clusters in which cluster head to be chosen and energy is optimized to some extent using Bacterium forging optimization technique.
Published by: Sweety Sharma
Author: Sweety Sharma
Paper ID: V7I5-1310
Paper Status: published
Published: October 5, 2021
Pneumonia detection using Deep Learning
Effective and accurate health care has always been the need of the hour. Early detection of various diseases such as pneumonia, tumor, and cancer is very much essential. Pneumonia, an acute respiratory infection ranked eighth in the list of the top 10 causes of death in the United States [1]. According to WHO, it accounts for about 1.6 million deaths a year in this age group - 18% of all deaths among children under five [2]. The paper aims to automatically detect pneumonia using chest x-ray images. We prepared five different models and analyzed their performance and choose the best-suited model for developing Pneumonia Detection System. Five different pre-trained deep Convolutional Neural Network (CNN): VGG16, ResNet50, InceptionV3, InceptionResNetV2, and Xception network were used for transfer learning. VGG16 network performed well with better accuracy of 92% which is better than other CNNs.
Published by: Sathwik G. S., Soumil Diwan, Vivek S. Patil, Yatish J., Vathsala M. K.
Author: Sathwik G. S.
Paper ID: V7I5-1311
Paper Status: published
Published: October 5, 2021
Fraud examination of Kingfisher Airlines
This paper primarily dwells on the fraud examination of the legendary airline company, Kingfisher Airlines, led by the flamboyant Chairman of the United Breweries Group and hitherto Kingfisher Airlines, Mr. Vijay Mallya. For the purpose of examination of fraud, two financial models in relation to the topic were employed and tested, viz. Beneish Model and Benford’s Law, while analyzing, in brief, the quality of financial auditing done using the annual reports of Kingfisher Airlines Ltd. for the period of 5 years from the financial year 2008-2009 to 2012-2013. The three variable and the five variable models of the Beneish Model were employed to obtain a score <-2.2, indicating that it was ineffective in identifying fraud by Kingfisher Airlines. Benford’s Law proved to be more effective. Due to the presence of abnormal data points or anomalies, a high chance of fraud was proved in the company’s financials.
Published by: Aditi Holla, Aditya Kanal, Ananya Mathur, Aman Chheda, Aditya Krishna
Author: Aditi Holla
Paper ID: V7I5-1305
Paper Status: published
Published: October 5, 2021
Frictionless electricity generation using propeller shaft
The shaft can generate electricity if it gets magnetized which can be used to power other components. A vehicle such as this can generate electricity for operating a hybrid engine or recharging batteries by use of an electricity-generating driveshaft. The electricity-generating drive shaft consists of a magnetized driveshaft which acts as a rotor, and a series of copper wire coils surrounding the magnetized driveshaft which acts as a stator in an electrical generator. In this project, we will use the propeller shaft which rotates at high speed, on which we will mount the disc magnet and the wooden or aluminum plates to hold the coils near the magnets mounted on the propeller shaft. This rotational movement creates a magnetic field and generates EMF into the coil as defined by Faraday’s law of electromagnetic inductions.
Published by: Abhinav Khirid, Akshay Talbar, Hrithik Naik
Author: Abhinav Khirid
Paper ID: V7I5-1304
Paper Status: published
Published: October 5, 2021
