2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET)最新文献

Implementation of Convolutional Neural Network for Epileptic Seizure Detection 卷积神经网络在癫痫发作检测中的实现

2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET) Pub Date : 2022-09-22 DOI: 10.1109/ICIIET55458.2022.9967535

S. Loganathan, C. Sujatha, R. Guru Nivash., R. Krish Srinivas., J. Niveddita., V. Nivedha.

{"title":"Implementation of Convolutional Neural Network for Epileptic Seizure Detection","authors":"S. Loganathan, C. Sujatha, R. Guru Nivash., R. Krish Srinivas., J. Niveddita., V. Nivedha.","doi":"10.1109/ICIIET55458.2022.9967535","DOIUrl":"https://doi.org/10.1109/ICIIET55458.2022.9967535","url":null,"abstract":"Epilepsy is a neurological disorder and disability in which the brain activity becomes abnormal causing seizures. A seizure is characterized by the unprovoked sudden alteration of the electrical activity of the brain. It is defined by a prolonged inclination to cause epileptic seizures and by the pathophysiological, psychological, cognitive, and social ramifications of this state, thus early detection of epileptic seizures is crucial. In this work, the convolutional neural network (CNN) is used to extract the important spatial information from Electroencephalogram (EEG) signals and a classification task using pre-trained networks by transfer learning is performed on the extracted features to detect the onset of a seizure. An accuracy of 95.09% is achieved using MATLAB. Pre-trained neural networks involve an enormous number of computations. Hence, a novel 30-30-10-10 neural network is devised as a feedforward fully connected neural network to reduce computational complexity. Simulation is performed in Verilog using Xilinx Vivado, achieving an accuracy of 96.6667%.","PeriodicalId":341904,"journal":{"name":"2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115750864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Early Detection and Mitigation of DoS Attacks in SDN Controller SDN控制器中DoS攻击的早期检测与缓解

2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET) Pub Date : 2022-09-22 DOI: 10.1109/ICIIET55458.2022.9967650

Saritakumar N, A. V.

引用次数: 2

Design and Analysis of Flexible 2-Port MIMO Antenna with Reflector Ground for WLAN Applications 无线局域网用反射地柔性2端口MIMO天线的设计与分析

2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET) Pub Date : 2022-09-22 DOI: 10.1109/ICIIET55458.2022.9967524

Elizabeth M Ribitha, M. Vadivel

引用次数: 0

Securing IoT Chips from Hardware Trojan using Machine Learning Classifiers 使用机器学习分类器保护物联网芯片免受硬件木马攻击

2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET) Pub Date : 2022-09-22 DOI: 10.1109/ICIIET55458.2022.9967617

T. Lavanya, K. Rajalakshmi

{"title":"Securing IoT Chips from Hardware Trojan using Machine Learning Classifiers","authors":"T. Lavanya, K. Rajalakshmi","doi":"10.1109/ICIIET55458.2022.9967617","DOIUrl":"https://doi.org/10.1109/ICIIET55458.2022.9967617","url":null,"abstract":"Recent trend shows that there is a widespread of Internet of Things (IoTs). IoTs are a network of devices that establish interconnectivity between them and communicate with each other. These IoTs had impacted every person in their daily lives through various applications such as smart homes, smart vehicles, smart medical, etc. The growing applications show the involvement of hardware devices and these devices are prone to attacks from the adversary. Hence, there is a need for securing the devices which in turn secure the IoTs. The attacks from adversaries are more in recent days to access secret information, perform Denial-of-service, performance degradation, etc. these attacks are performed as per the intention of the adversary. These types of attacks through hardware are called Hardware Trojan (HT) attacks. Hence, there is a requirement of security in a hardware device which is achieved by applying the non-destructive machine learning classifier method. This proposed methodology detects the HT present in a circuit by classifying the different parametric features of the circuit under test by differentiating the unknown and known netlists and detects the particular net as a ‘Trojan net’ or ‘normal net’, with the achievement of 94.4% of accuracy and 0.9 of f-measure.","PeriodicalId":341904,"journal":{"name":"2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114753455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving the Quality of Image Captioning using CNN and LSTM Method 利用CNN和LSTM方法提高图像字幕质量

2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET) Pub Date : 2022-09-22 DOI: 10.1109/ICIIET55458.2022.9967570

M. Pradeepan Lala, D. Kumar

引用次数: 0

Deep Reinforcement Learning based Resource Allocation in NOMA 基于深度强化学习的NOMA资源分配

2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET) Pub Date : 2022-09-22 DOI: 10.1109/ICIIET55458.2022.9967604

N. Iswarya, R. Venkateswari

{"title":"Deep Reinforcement Learning based Resource Allocation in NOMA","authors":"N. Iswarya, R. Venkateswari","doi":"10.1109/ICIIET55458.2022.9967604","DOIUrl":"https://doi.org/10.1109/ICIIET55458.2022.9967604","url":null,"abstract":"NOMA is a novel channel accessing strategy that delivers high throughput and fairness among various users by multiplexing many users across the same frequency resource. In order to guarantee the user's fairness, minimum data rate maximization, also referred to as the max-min approach is adopted. Apparently, transmission power optimization is employed to accomplish the max-min. However, the scalability of the number of users leads the optimization to a non-convex optimization problem. Consequently, the Dueling Double Deep Q Learning(Dueling DDQL) technique, a subclass of Reinforcement Learning is proposed to solve such problem. The Deep Q-Network is used by the DDQL approach in learning the actions that are best to do to maximize user power coefficients. The Markov Decision Process (MDP) model is essential to the DDQL method's effectiveness since it trains the DQN on choosing better actions. The dueling DDQL converges to the target value for 92% of the test cases. The proposed method is compared with the benchmark algorithms and it is illustrated that the proposed algorithm outperforms those comparative algorithms.","PeriodicalId":341904,"journal":{"name":"2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130924251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Hybrid DC-DC Converter for DC Microgrid Applications 用于直流微电网的混合式DC-DC变换器

2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET) Pub Date : 2022-09-22 DOI: 10.1109/ICIIET55458.2022.9967504

J. S. Sakthi Suriya Raj, P. Sivaraman

引用次数: 0

Optimal Path Finding Algorithm for Logistic Routing Problem 物流路径问题的最优寻径算法

2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET) Pub Date : 2022-09-22 DOI: 10.1109/ICIIET55458.2022.9967599

Madhura Srinivasan, K. Sireesha

{"title":"Optimal Path Finding Algorithm for Logistic Routing Problem","authors":"Madhura Srinivasan, K. Sireesha","doi":"10.1109/ICIIET55458.2022.9967599","DOIUrl":"https://doi.org/10.1109/ICIIET55458.2022.9967599","url":null,"abstract":"The Logistic Routing Problem (LRP) is a type of Vehicle Routing Problem (VRP) that is generally about the optimal set of routes for a group of vehicles to cross over to deliver to a given set of geographical locations as customers. Cost to company plays a vital role where the economy has changed the people’s way of buying things and logistics development has also increased due to this. Determining an optimal solution in a VRP is NP-hard, so the solution to solve such problems is limited. Taking this as the challenge and finding an algorithm to get an optimal solution is the goal of this paper. The optimal solution here is to minimize the traveling cost and find the best route which is an important factor in terms of logistic transportation. The proposed method is to hybridize the existing Ant colony optimization. Firstly, clustering is done to divide the larger geographical area into smaller parts using K-means Algorithm. After the clusters are availed, ACO is used for Route optimization to obtain the shortest route. The models are estimated based on the distance. The design was programmed using Python Programming in Visual Studio Code as the software platform.","PeriodicalId":341904,"journal":{"name":"2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124119877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Brain Tumor Segmentation Using Zernike Moments in U-Net 基于U-Net的Zernike矩脑肿瘤分割

2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET) Pub Date : 2022-09-22 DOI: 10.1109/ICIIET55458.2022.9967618

K. Manasa, V. Krishnaveni

引用次数: 0

A Performance Investigations of Modular Multilevel Inverter with Reduced Switch Count 减少开关数的模块化多电平逆变器性能研究

2022 International Conference on Intelligent Innovations in Engineering and Technology (ICIIET) Pub Date : 2022-09-22 DOI: 10.1109/ICIIET55458.2022.9967595

E. Parimalasundar, K. Suresh, R. Sindhuja, K. Manikandan

引用次数: 8