2023 7th International Conference on Computing Methodologies and Communication (ICCMC)最新文献_第8页

A Novel Trust Value Based Mobile Ad hoc Networks (MANETs) Security 一种基于信任值的移动自组网安全算法

2023 7th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2023-02-23 DOI: 10.1109/ICCMC56507.2023.10084006

Sarumathi R, Jayalakshmi V

{"title":"A Novel Trust Value Based Mobile Ad hoc Networks (MANETs) Security","authors":"Sarumathi R, Jayalakshmi V","doi":"10.1109/ICCMC56507.2023.10084006","DOIUrl":"https://doi.org/10.1109/ICCMC56507.2023.10084006","url":null,"abstract":"Mobile ad hoc networks, abbreviated as MANETs, are a type of self-configuring network in which several wireless nodes temporarily set up linkages between each other. Due to the fact that MANET is a dynamic network, navigating it can be exceedingly difficult, and it is also more susceptible to a variety of attacks. Traditional security measures like cryptographic techniques need a significant consumption of resources like memory, speed, and transmission bandwidth in mobile ad-hoc networks and by Such methods make it impossible to identify malicious or flawed behaviour and self-centred nodes that damage the network. In Mobile ad-hoc Networks, trust methods are those that calculate the trust of mobile nodes and, as a result, help to identify malicious, selfish, and malfunctioning nodes Network. In this paper, a Trust Calculation based on nodes properties and recommendations are proposed to calculate trust for mobile Ad-hoc network. The proposed technique is very efficient to detect malicious and selfish nodes in MANET and allows trusted routing by eliminating malicious nodes. The findings of this research demonstrate that the proposed technique has a detection rate that is significantly greater than that of any other trust model used in Mobile ad-hoc networks. Routing protocols utilize trust mechanisms to identify a secure route in an efficient manner.","PeriodicalId":197059,"journal":{"name":"2023 7th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130209567","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

Vector Control of an Induction Motor for Speed Regulation 异步电动机的矢量调速控制

2023 7th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2023-02-23 DOI: 10.1109/ICCMC56507.2023.10084248

Gurram Satyanarayana, M. Karthikeyan, R. Mahalakshmi, T. Vandarkuzhali

{"title":"Vector Control of an Induction Motor for Speed Regulation","authors":"Gurram Satyanarayana, M. Karthikeyan, R. Mahalakshmi, T. Vandarkuzhali","doi":"10.1109/ICCMC56507.2023.10084248","DOIUrl":"https://doi.org/10.1109/ICCMC56507.2023.10084248","url":null,"abstract":"In electric motor drives, speed regulation plays an essential part in describing the overall performance of the system drive. To control the motor speed of an Induction motor (IM), an indirect vector control method is implemented in this paper. Scalar control is a simple and effective technique, but it responds slowly to transients and is unsatisfactory for regulating motors with dynamic behavior. The currents are controlled via the field-oriented control (FOC) approach, allowing for quick reactions. This approach meets the demands of dynamic drives, wherein quick response is required. The flux location is calculated indirectly in indirect control methods by rotor speed and slip calculation. The indirect control technique has grown in popularity due to the lack of rotor flux position sensors and the capacity to work at low speeds. A PI controller is utilized in the speed controller to control the motor torque by producing quadrature-axis current reference iq*. The motor's flux is controlled by direct axis current reference id*. The IM is operated by a current-controlled PWM inverter. The designed model is simulated using MATLAB and the results show an accurate speed response of the IM motor.","PeriodicalId":197059,"journal":{"name":"2023 7th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126680043","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

Efficient Intensity Bedded Sonata Wiles System using IoT 使用物联网的高效强度床上奏鸣曲怀尔斯系统

2023 7th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2023-02-23 DOI: 10.1109/ICCMC56507.2023.10084287

M. Kathiravan, S. Manohar, R. Jayanthi, R. Dheepthi, R. V. Sekhar, N. Bharathiraja

{"title":"Efficient Intensity Bedded Sonata Wiles System using IoT","authors":"M. Kathiravan, S. Manohar, R. Jayanthi, R. Dheepthi, R. V. Sekhar, N. Bharathiraja","doi":"10.1109/ICCMC56507.2023.10084287","DOIUrl":"https://doi.org/10.1109/ICCMC56507.2023.10084287","url":null,"abstract":"The human face plays a significant role in interpreting emotional states. Most nonverbal communication between humans occurs through changes in facial expressions. People listen to music to lift their spirits, calm their nerves, and re-energize them. It also hints that hearing the right song at the right time can have a positive effect on one's mood. Now more than ever, thanks to the proliferation of mobile networks and digital multimedia, music is an integral part of many young people's daily lives. Conversely, music has been shown to significantly impact listeners' emotional states. People of all ages, nationalities, languages, economic standings, social standings, and demographic groups can find common ground via shared appreciation of music. Music players and streaming apps are in high demand since users may listen to their music whenever and wherever they like. The study proposes a mood-based music playback system that can identify the user's emotional state in real time and make song recommendations accordingly. It uses a webcam to record the human face in all its expressive glory. Using this information, a playlist of songs that are congruent with the “mood” determined from previous facial expressions can be built. Music players that analyse facial expressions use a set of criteria to scan the user's face and then play songs based on what they see.","PeriodicalId":197059,"journal":{"name":"2023 7th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126840488","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

Plant Classification based on Grey Wolf Optimizer based Support Vector Machine (GOS) Algorithm 基于灰狼优化器支持向量机(GOS)算法的植物分类

2023 7th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2023-02-23 DOI: 10.1109/ICCMC56507.2023.10083535

P. Keerthika, R. Devi, S. Prasad, R. Venkatesan, Hemalatha Gunasekaran, K. Sudha

{"title":"Plant Classification based on Grey Wolf Optimizer based Support Vector Machine (GOS) Algorithm","authors":"P. Keerthika, R. Devi, S. Prasad, R. Venkatesan, Hemalatha Gunasekaran, K. Sudha","doi":"10.1109/ICCMC56507.2023.10083535","DOIUrl":"https://doi.org/10.1109/ICCMC56507.2023.10083535","url":null,"abstract":"Leaves are the primary identifying feature of trees and other plants. Many of these plants are used in the pharmaceutical industry as industrial crops. Growing automation in industries including commerce and medicine has made accurate leaf identification crucial. Leaves are typically classified according to morphological or genetic characteristics. As a result of their numerous physical differences, however, it is becoming increasingly difficult to categorize the diverse leaf cultivars that exist. Several evolutionary shifts over the past several decades have resulted in an increase in the number of variants of a certain leaf type. To manually sift and identify these leaves is a laborious process. A novel hybrid GOS algorithm is proposed in this study for detecting leaves based on their shape, color, and texture. Three types of leaves (apple, cucumber, and mango) are used as examples, and features for each are extracted using Image Processing techniques, before being optimized with the Grey Wolf Optimizer and finally classified with the SVM (Support Vector Machine) classifier algorithm. Experimental results show that the proposed GOS work improves upon the SVM classifier, with a classification accuracy of 96.83 percent.","PeriodicalId":197059,"journal":{"name":"2023 7th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132841987","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

Road Damage Detection using Deep Learning 使用深度学习的道路损伤检测

2023 7th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2023-02-23 DOI: 10.1109/ICCMC56507.2023.10083795

P. S., Shreekanth M, V. S, Santhosh N S

{"title":"Road Damage Detection using Deep Learning","authors":"P. S., Shreekanth M, V. S, Santhosh N S","doi":"10.1109/ICCMC56507.2023.10083795","DOIUrl":"https://doi.org/10.1109/ICCMC56507.2023.10083795","url":null,"abstract":"Road damage occurs when the function and structure of road are unable to service the traffic above it optimally. In general, the damage is caused by flaws in planning and implementation, uneven maintenance, poor drainage, and poor road user behaviour. It has a negative impact on driving comfort, road safety, and vehicle condition, and it may cause a number of accidents. To address this issue, this study presents a Region-based Convolutional Neural Network (R-CNN) for locating the dangerous path. This type of neural network can find essential information in both time series and picture data is the RCNN. As a result, it is extremely useful for image-associate tasks including image identification, object categorization, and design recognition. A RCNN uses linear algebra methods such as matrix multiplication to discover patterns inside an image. Find the photographs first and pre-process them, then extract the features and choose them from the feature set of previously damaged images. Finally, categorise the captured photos to obtain the optimum result. When compared to other current approaches, the suggested method is more accurate.","PeriodicalId":197059,"journal":{"name":"2023 7th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"7 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132272050","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

Reduced Device Count 9-Level Inverter for Standalone Applications 减少设备计数9电平逆变器的独立应用

2023 7th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2023-02-23 DOI: 10.1109/ICCMC56507.2023.10084282

Satheesh Kumar Ghanapuram, Dileep Sirimalla, Venkatesh Edla, Sai Krishna Bykani, Lokesh Utpalla

引用次数: 0

Predicting the Driver Variants and Mutations in Lung Cancer Genome using Transcriptional Regulation Network 利用转录调控网络预测肺癌基因组驱动变异体和突变

2023 7th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2023-02-23 DOI: 10.1109/ICCMC56507.2023.10084125

Spandana Chereddy, Ippatapu Venkata Srisurya, Harshit Bogineni, P. R, Bharathi Mohan G

{"title":"Predicting the Driver Variants and Mutations in Lung Cancer Genome using Transcriptional Regulation Network","authors":"Spandana Chereddy, Ippatapu Venkata Srisurya, Harshit Bogineni, P. R, Bharathi Mohan G","doi":"10.1109/ICCMC56507.2023.10084125","DOIUrl":"https://doi.org/10.1109/ICCMC56507.2023.10084125","url":null,"abstract":"Among thousands of potential mutations, identifying and separating cancer driver genes remains a big difficulty. Precise identification of driver genes and mutations is crucial for cancer research and treatment personalization based on accurate patient classification. Many driver mutations within a gene exist at low rates due to inter-tumor genetic variability, making it difficult to identify them from non-driver mutations. Proposed model uses a transcription adjustment network and its data set from the database REGNETWORK. The subject of the paper is to discovery of genes that cause lung cancer with a network approach. To do this, centralization and socialization in graph is used. The degree of centrality, degree of mediocrity, and proximity are considered as parameters in identifying lung cancer gene (with the cancer-causing mutation). Socializing of data is implemented to find genes that are more closely related to each other. Various transcription factors, genes, and their interconnections make create a particular class of biological network called a transcriptional regulatory network. These networks were analyzed to look at how information moves through a biological system and to spot paths that are advantageous for various tasks. Nodes in this network are genes and transcripts, so there are two types of modules in the network, Gene module and transcription factor module. Edges represents physical or regulatory interaction between them Two different algorithms are used to build the network model and comparison is done using Accuracy, F1 Score, Recall, Precision. Using this algorithm, the influential genes (propagation occurs in them) are identified in each community, and finally the total of the influential genes. The results from all communities were predicted as lung cancer genes and evaluated using certain criteria.","PeriodicalId":197059,"journal":{"name":"2023 7th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133528813","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

Comparative Analysis on Aspect-based Sentiment using BERT 基于BERT的面向方面情感的比较分析

2023 7th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2023-02-23 DOI: 10.1109/ICCMC56507.2023.10084294

Aditi Tiwari, Khushboo Tewari, Sukriti Dawar, Ankit Singh, Nisha Rathee

引用次数: 0

Forensic Art with Image Recognition and Brain Computing Interface 具有图像识别和脑计算接口的法医艺术

2023 7th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2023-02-23 DOI: 10.1109/ICCMC56507.2023.10084031

J. Suganthi, S. Sivaranjani, M. Hariharan

{"title":"Forensic Art with Image Recognition and Brain Computing Interface","authors":"J. Suganthi, S. Sivaranjani, M. Hariharan","doi":"10.1109/ICCMC56507.2023.10084031","DOIUrl":"https://doi.org/10.1109/ICCMC56507.2023.10084031","url":null,"abstract":"This project uses software to generate forensic facial art by obtaining information directly from the human brain via a BCI headband. We can quickly cut the time necessary to design the victim's face by automatically picking the pre drawn structure. The above suggested approach will not only sketch the victim's face, but it will also search the criminal database at random to see if the victim's face has previously been recorded. First, we use the Brain Computing Interface Band to get the EEG signal from the witness's brain. The EEG data is then processed in bit Brain to categorise it into each instruction, and the classified signal is then moved to the next phase to choose the face portion. This study includes the previously collected pre-drawn facial components and categorized the images by this point. The CNN algorithm is significantly more accurate in classifying the images, and the classified images are saved with the trail in BCI computing to select the image in an accurate way. A categorized image data collection is used to generate the processed EEG signal. to discover the face region that is equivalent to an EEG signal. Drawing software was used to choose the selected face portion, which was then placed at the fundamental facial structure. When the painting is 40% complete, the face structure is compared to an existing criminal database to check whether the facial structure matches any previous crimes. This initiative aids in the identification of criminals and the creation of forensic art in considerably less time than the traditional method.","PeriodicalId":197059,"journal":{"name":"2023 7th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130792687","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

Identification of Voting Patterns using Clustering Methodology 使用聚类方法识别投票模式

2023 7th International Conference on Computing Methodologies and Communication (ICCMC) Pub Date : 2023-02-23 DOI: 10.1109/ICCMC56507.2023.10083748

Dharvi Kaur Minhas, Aabha Malik, S. Dubey

{"title":"Identification of Voting Patterns using Clustering Methodology","authors":"Dharvi Kaur Minhas, Aabha Malik, S. Dubey","doi":"10.1109/ICCMC56507.2023.10083748","DOIUrl":"https://doi.org/10.1109/ICCMC56507.2023.10083748","url":null,"abstract":"The act of separating a population or set of data points into a few groups or clusters so that data points in the same group are more like each other and distinct from data points in other groups is known as clustering. The purpose of this study is to categorize the respondents to identify groups with similar attitudes about science and technology and analyze their views. The difficulties of cluster analysis, determination of distance measure, number of clusters, and database structure have all been noted as possible issues with cluster analysis. To explore the respondents' grouping tendencies, several clustering approaches such as K-means, Hierarchical clustering, and so on are utilised The Hierarchical Clustering methodology itself may provide the analyst with the ideal number of clusters; human participation is not necessary. Dendrograms provide in clear imagery that is useful and simple to comprehend The centroids are computed by the K-means clustering method, which then iterates until it finds the ideal centroid It presumes that there are already known quantities of clusters. The flat clustering algorithm is another name for it. Since the data is binary, the clustering methods may be used to group the respondents. The clustering methods will be applied to the survey data by tracking the resultant decisions. Currently, all clustering algorithms have been used and it has been discovered that the data contains three or four clusters, each of which specifies a voting pattern that may be of interest.","PeriodicalId":197059,"journal":{"name":"2023 7th International Conference on Computing Methodologies and Communication (ICCMC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116865858","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