2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)最新文献_第9页

Anonymity-Enabled Mix Network: Owing to Techniques and Proof of correctness 启用匿名的混合网络:由于技术和正确性证明

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037727

Fayaz Naikoo, Khaleel Ahmad, Khairol Amali Bin Ahmad

引用次数: 0

Holistic Smart Cities Viewed Through the Lens of Performance Evaluation Schemes 从绩效评估体系看整体智慧城市

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037622

Charul Sharma, Sanjay Kumar Sharma, Dharmendra Gill

{"title":"Holistic Smart Cities Viewed Through the Lens of Performance Evaluation Schemes","authors":"Charul Sharma, Sanjay Kumar Sharma, Dharmendra Gill","doi":"10.1109/ICCCIS56430.2022.10037622","DOIUrl":"https://doi.org/10.1109/ICCCIS56430.2022.10037622","url":null,"abstract":"In the modern urban space cities are crumbling under the burden of urbanization. Holistic smart cities offer a multifaceted point of view for future cities. By compiling data on smart city components from 23 evaluation schemes, covering 13 countries and 4 geographic regions, this study dissects the intricate nature of comprehensive smart cities. We divide the smart city components into 9 sub categories and 3 main categories based on recurring themes among smart city components. The findings demonstrate that the six predefined components—Economy, People, Environment, Mobility, Living, and Governance—are inextricably linked to the holistic approach. New components including Technology, Infrastructure, Energy, Pandemic Resiliency that result from the study endorse the dynamic nature of the holistic smart cities. We propose that the three major categories should be represented in a well-balanced manner in the assessment schemes for reliable and better holistic evaluation of smart cities. As a result, the holistic approach gains value and smart cities become truly holistic by fostering diversity and context-specificity. Researchers and policy-makers can use the study to upgrade evaluation schemes for analyzing smart cities holistically.","PeriodicalId":286808,"journal":{"name":"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"14 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120846525","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

Assessment of Blood Donor Information Using Kernel Density Maps: A Case Study at Gangtok District, Sikkim and Modeling of a Web Application. 使用核密度图评估献血者信息:锡金Gangtok地区的案例研究和Web应用程序建模。

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037725

Madhab Nirola, Mousumi Gupta, Arpan Sharma

{"title":"Assessment of Blood Donor Information Using Kernel Density Maps: A Case Study at Gangtok District, Sikkim and Modeling of a Web Application.","authors":"Madhab Nirola, Mousumi Gupta, Arpan Sharma","doi":"10.1109/ICCCIS56430.2022.10037725","DOIUrl":"https://doi.org/10.1109/ICCCIS56430.2022.10037725","url":null,"abstract":"Acquiring blood donor information is a very time-consuming process and may put the patient’s health at risk. Finding blood donor data is essential for receiving the correct type of blood as quickly as possible. This study aims to develop a web application to alleviate the hassles faced by critical patients. We acquire sample data from CRH hospital in Gangtok, Sikkim. We assess data from blood donors using ArcGIS platforms. Further, we generate a region-wise heat map. We include 391 blood donor records of which 165 are A+ Ve, 94 are B+ Ve, 43 are AB+ Ve, 3 are B- Ve, and 86 were O+ Ve. Through the modeled application users can locate blood donor information near them and communicate with the blood donor by direct phone call using the assessed heatmaps. Users can also register themselves by providing information such as their personal information, blood type, etc., which will be displayed on the heatmap for future use. Through the modeled application blood banks in that area can Figure out which locations have a higher volume of a specific blood type that they require, and then set up a camp or encourage volunteers to donate blood to help.","PeriodicalId":286808,"journal":{"name":"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121307135","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

Low complexity 16-point DCT approximation for image compression 低复杂度的16点DCT近似图像压缩

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037721

V. P. S. Thoudam, Tana Sera, Xi Chaow Xi Marak, M. Saddam, Rebecca Lalparmawii

引用次数: 0

Genetic Algorithm Based Optimization in Solving Multi Robot Task Allocation Problems 基于遗传算法优化求解多机器人任务分配问题

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037687

M. Rohini, B. Manohari, S. Adhithyan

引用次数: 0

Autoencoder Feature Based Kinship Verification using Machine Learning Classifiers 基于自编码器特征的基于机器学习分类器的亲属关系验证

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037706

D. Jeyashaju, Y. J. Raj

{"title":"Autoencoder Feature Based Kinship Verification using Machine Learning Classifiers","authors":"D. Jeyashaju, Y. J. Raj","doi":"10.1109/ICCCIS56430.2022.10037706","DOIUrl":"https://doi.org/10.1109/ICCCIS56430.2022.10037706","url":null,"abstract":"Verification of kinship in an automatic way is a new challenge in vision on the computer that intends to determine if two given individuals have any kinship relationship based on their facial features. Verification of Kinship by facial pictures is difficult since face images have a lot of intra-class variations due to age, genetic and gender difference. Videos can provide more information as they have additional sources of information as compared to single image verification. In this paper, deep learning based Supervised Mixed Norm regularization Autoencoder (SMNAE) is suggested for verification of kinship in unconfined videos. This proposed SMNAE based approach employs the spatial information to test kinship in the video frames. The Random Forest (RF), Support Vector Machine (SVM), and Decision Tree (DT) classifiers are used to Classify the decision borderline among kin and non-kin classes. The efficacy of this proposed approach is evaluated on seven kin relationships using a kinship video (KIVI) face dataset of kin pairs. According to experimental results SMNAE spatial features with DT classifier produce 70.14% of f1score, which performs much better than other classifiers. It gives improvement in f1 score of +24.52%, +22.05% than SVM and RF classifiers respectively. Furthermore, when compared to existing systems, the proposed SMNAE spatial features with DT framework performs exceptionally well in kinship verification.","PeriodicalId":286808,"journal":{"name":"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117305286","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

A Blockchain Supported Model for Secure Exchange of Land Ownership: An Innovative Approach 区块链支持的土地所有权安全交换模型:一种创新方法

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037224

S. Rana, Sanjeev Kumar Rana, A. Rana, Sardar M. N. Islam

{"title":"A Blockchain Supported Model for Secure Exchange of Land Ownership: An Innovative Approach","authors":"S. Rana, Sanjeev Kumar Rana, A. Rana, Sardar M. N. Islam","doi":"10.1109/ICCCIS56430.2022.10037224","DOIUrl":"https://doi.org/10.1109/ICCCIS56430.2022.10037224","url":null,"abstract":"Due to the duplicity and inefficiencies in the current land registration system, the land records are not secured, and citizens face the brunt of this. Similar to this, thousands of people are dealing with this situation. Fraudsters use numerous faults in the current property registration process to swindle both the public and the government. The implementation of a secure land registration using Blockchain and majority consensus is examined in this study. The adoption of Blockchain by the land register significantly lowers security issues. Since each block is linked to the hash of the one before it, each block’s hash value will be unique. It uses a hashing algorithm known as SHA256. The security of the data linked with each transaction is improved by the Proof of Work (PoW) method with SHA256. Each hash in the message digest is fixed for all the blocks and represents the complete collection of transactions contained in these blocks. The responsibility for mining new blocks, chaining with existing Blockchain and validating transactions falls on a node. Hashes are used to link transactions together via merge trees, which requires less storage. Thus, a 99% decrease in the human record-keeping effort is offered by the suggested usage of Blockchain for land registration.","PeriodicalId":286808,"journal":{"name":"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115351043","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

Knowledge Base Entity Lookup using Named Entity Recognition: a case study on YAGO 基于命名实体识别的知识库实体查找:以YAGO为例

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037689

Aatif Ahmad Khan, S. K. Malik

引用次数: 0

Comparative Study On Various Architectures Of Yolo Models Used In Object Recognition 不同Yolo模型结构在目标识别中的比较研究

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037635

Baranidharan Balakrishnan, Rashmi Chelliah, Madhumitha Venkatesan, Chetan Sah

{"title":"Comparative Study On Various Architectures Of Yolo Models Used In Object Recognition","authors":"Baranidharan Balakrishnan, Rashmi Chelliah, Madhumitha Venkatesan, Chetan Sah","doi":"10.1109/ICCCIS56430.2022.10037635","DOIUrl":"https://doi.org/10.1109/ICCCIS56430.2022.10037635","url":null,"abstract":"In the last few decades, the deep learning paradigm has been widely used in the Machine Learning Community, thereby accounting for some of the most outstanding results on several complex cognitive results, performing on par or even better than human-level performance. One of these many complex tasks is Object Detection. This paper aims to do a comparative study on the YOLO model used in Object Detection, which would help the visually impaired understand their surroundings. With a wide use case in multiple industries and sectors, it has been a hot topic amongst the community for the past decade. Object detection is a method of finding instances of objects from an image of a certain class. Object Detection has been witnessing a brisk revolutionary change in recent times, resulting in many advanced and complex algorithms like YOLO, SSD, Fast R-CNN, Faster R-CNN, HOG, and many more. This research paper explains the architecture of the YOLO algorithm which is widely used in object detection and classifying objects. We have used the COCO dataset to train our model. Our aim of this research study is to trying to identify the best implementation of the YOLO Model.","PeriodicalId":286808,"journal":{"name":"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131061359","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

An Approach to Criminal Suspect Prediction Software using Machine Learning Classifiers 基于机器学习分类器的犯罪嫌疑人预测软件研究

2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) Pub Date : 2022-11-04 DOI: 10.1109/ICCCIS56430.2022.10037685

Ashima Arya, Mitu Sehgal, Neha Bhatia, Nitisha Aggarwal, Shiraz Khurana

{"title":"An Approach to Criminal Suspect Prediction Software using Machine Learning Classifiers","authors":"Ashima Arya, Mitu Sehgal, Neha Bhatia, Nitisha Aggarwal, Shiraz Khurana","doi":"10.1109/ICCCIS56430.2022.10037685","DOIUrl":"https://doi.org/10.1109/ICCCIS56430.2022.10037685","url":null,"abstract":"The goal and the objective of this project is to predict the suspect of criminal and its location by analyzing criminal records and finding criminal hotspots. Investigations in India regarding larceny are very futile in nature and seldom result in apprehension of the criminal. Our software is for police officials to lead their investigation effectively and work towards capturing the unrighteous using data analytics thereby uncovering theft and criminal trends. Such trends lead to uncovering dimensions for an investigation which are difficult to recognize through manual inspection techniques. Such software is not only helpful for the police for effective and smart work in case of low-profile crimes but also the increase in arrests for larceny would ultimately lead to low crime rate and a lawful society. The inclusion of machine learning technique such as KNN technique is used to suspect the criminal by analyzing its data. Through the use of such software for police work in the hope of reduction in crime rate is a progressive step forward for Digital India.","PeriodicalId":286808,"journal":{"name":"2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128723451","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