2023 2nd International Conference on Computational Systems and Communication (ICCSC)最新文献_第2页

Live College Bus Tracking and Route Mapping Using Internet of Things 基于物联网的实时大学巴士跟踪和路线映射

2023 2nd International Conference on Computational Systems and Communication (ICCSC) Pub Date : 2023-03-03 DOI: 10.1109/ICCSC56913.2023.10143028

Bibin Vincent, Jestin Sahu, Cerlin Mathew, Sachin S Nair, Sharon Biju George, Saleema D

{"title":"Live College Bus Tracking and Route Mapping Using Internet of Things","authors":"Bibin Vincent, Jestin Sahu, Cerlin Mathew, Sachin S Nair, Sharon Biju George, Saleema D","doi":"10.1109/ICCSC56913.2023.10143028","DOIUrl":"https://doi.org/10.1109/ICCSC56913.2023.10143028","url":null,"abstract":"The proposed system works on GPS based tracking system which uses ReactJS to develop this application. This system displays the attendance report of the students who have boarded the bus, gives the estimated arrival time and live video feed to monitor the students for their safety. Beyond this feature it also offers the ability to create or update routes and places in the database. This system can be utilized by any travelling organization to get information about the vehicles' current locations. The user will be able to access the system using any web browser or through an Android Application. The system mainly uses Server module, Bus Unit module and End User Application module. The Server module is in charge of monitoring and recording the bus location. The Bus Unit module is in charge of tracking the bus's current location, recording the attendance of each student in the bus and provides it to server. The essential components of this module are internet-connected microcontroller, RFID and GPS modules. The end user application module provides user interfaces for both administrators and users.","PeriodicalId":184366,"journal":{"name":"2023 2nd International Conference on Computational Systems and Communication (ICCSC)","volume":"168 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115758171","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

A Secure Optical Encryption Using DWT and Bit Swapping 基于DWT和位交换的安全光加密

2023 2nd International Conference on Computational Systems and Communication (ICCSC) Pub Date : 2023-03-03 DOI: 10.1109/ICCSC56913.2023.10142980

Anusree. L, M. Rahiman

引用次数: 0

Long-Term Survival Prediction Of Liver Transplantation Using Deep Learning Techniques 利用深度学习技术预测肝移植的长期生存

2023 2nd International Conference on Computational Systems and Communication (ICCSC) Pub Date : 2023-03-03 DOI: 10.1109/ICCSC56913.2023.10143013

Juby Raju, S. Sathyalakshmi

{"title":"Long-Term Survival Prediction Of Liver Transplantation Using Deep Learning Techniques","authors":"Juby Raju, S. Sathyalakshmi","doi":"10.1109/ICCSC56913.2023.10143013","DOIUrl":"https://doi.org/10.1109/ICCSC56913.2023.10143013","url":null,"abstract":"The forecasting of survival following liver transplantation is one of the greatest and most crucial areas of medical investigation. The most efficient choice of treatment for advanced liver disease is liver transplantation. Before any transplant, everyone will take their prospects of survival into account. An overview of the clinical and computational predictions for patients who have undergone liver transplants is given in this article. This research analyses multiple deep learning algorithms that can predict the survival of patients who went through liver transplants using data from the United Nations for Organ Sharing (UNOS). We considered liver transplants made in the United States of America between October 1, 1987, and June 30, 2021, using a database from the United Network for Organ Sharing (UNOS) that comprises 65535 donor-recipient pairings and 421 variables. Several methodologies, including proportional-hazards regression models and AI techniques, including Random Forest, Artificial Neural Network, Transformer, and K Nearest Neighbor were evaluated using 29 correlated features obtained through WEKA Software. All the Deep learning models were compared based on accuracy. With an accuracy of 0.89, the FT-transformer model outperformed all other models.","PeriodicalId":184366,"journal":{"name":"2023 2nd International Conference on Computational Systems and Communication (ICCSC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114453685","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

Acne Assessment and Grading: Challenges and Opportunity 痤疮评估和分级:挑战和机遇

2023 2nd International Conference on Computational Systems and Communication (ICCSC) Pub Date : 2023-03-03 DOI: 10.1109/ICCSC56913.2023.10143016

Paluri Krishna Veni, Ashish Gupta

引用次数: 0

A Comprehensive and Systematic Review of Deep Learning Based Object Recognition Techniques for the Visually Impaired 基于深度学习的视障对象识别技术的全面系统综述

2023 2nd International Conference on Computational Systems and Communication (ICCSC) Pub Date : 2023-03-03 DOI: 10.1109/ICCSC56913.2023.10143007

Aakriti Kinra, Wamica Walia, S. Sharanya

{"title":"A Comprehensive and Systematic Review of Deep Learning Based Object Recognition Techniques for the Visually Impaired","authors":"Aakriti Kinra, Wamica Walia, S. Sharanya","doi":"10.1109/ICCSC56913.2023.10143007","DOIUrl":"https://doi.org/10.1109/ICCSC56913.2023.10143007","url":null,"abstract":"Object detection is one of computer vision's most essential and challenging visual recognition tasks. The primary focus is to detect objects belonging to different classes and assign each one of them a predefined class label. The dearth of support at diagnosis centers, restricted access to actions and data, stigma created by society, and lack of employment frequently lead visually challenged individuals to seclusion. Existing technologies include A Path Force Feedback Belt (PF belt), Eye Substitution, and Radio Frequency Identification Walking Stick (RFIWS). They detect and localize objects to offer the visually impaired an understanding of the environment around them utilizing the operations of sensors. These systems do not provide real-time responses and are suitable only for outdoor coverage. Due to ultrasonic or radio frequency limitations, the detection range of these systems is between 1m to 5m. The primary intent of this work is to deliver a complete and extensive analysis of the research done in the field of object recognition for VI-challenged people.","PeriodicalId":184366,"journal":{"name":"2023 2nd International Conference on Computational Systems and Communication (ICCSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125442839","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

Early Detection of Anxiety, Depression and Stress among Potential Patients using machine learning and deep learning models 利用机器学习和深度学习模型在潜在患者中早期发现焦虑、抑郁和压力

2023 2nd International Conference on Computational Systems and Communication (ICCSC) Pub Date : 2023-03-03 DOI: 10.1109/ICCSC56913.2023.10143026

Alphonsa Sini P. J, Sherly K. K

{"title":"Early Detection of Anxiety, Depression and Stress among Potential Patients using machine learning and deep learning models","authors":"Alphonsa Sini P. J, Sherly K. K","doi":"10.1109/ICCSC56913.2023.10143026","DOIUrl":"https://doi.org/10.1109/ICCSC56913.2023.10143026","url":null,"abstract":"Depression, anxiety and stress are the three important mental health conditions. Only a small portion of the millions of people who experience depression, anxiety and stress each year receives a prompt treatment. The development of technology that helps clinicians detect various types of mental diseases has greatly benefited from the progress of Machine Learning (ML) techniques over the past few decades. This study presents a comparison of three important mental health issues (Depression, Anxiety, and stress) using machine learning and Deep Learning (DL) algorithms. The proposed work also investigates about how the ML and DL techniques might help with the detection, diagnosis, and management of mental health diseases with a better effective and novel approach. As a result, three different algorithms (SVM, ANN and XgBoost) has been implemented in which Support vector machine (SVM) has achieved the better accuracy in detecting the mental health. The accuracy achieved in detecting depression, anxiety and stress are 99.32%, 99.80% and 98.44% respectively. Henceforth the proposed study was able to achieve a satisfactory result that helps to improve the decision-making and clinical practice.","PeriodicalId":184366,"journal":{"name":"2023 2nd International Conference on Computational Systems and Communication (ICCSC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127957449","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

Synthetic Dataset Generation From Histopathology Images For Quantizing Necrosis In Post Neo-Adjuvant Chemotherapy Resection Specimen 从组织病理学图像生成用于量化新辅助化疗切除标本中坏死的合成数据集

2023 2nd International Conference on Computational Systems and Communication (ICCSC) Pub Date : 2023-03-03 DOI: 10.1109/ICCSC56913.2023.10143027

T. S. Saleena, Muhamed Ilyas P, Sajna V. M. Kutty

{"title":"Synthetic Dataset Generation From Histopathology Images For Quantizing Necrosis In Post Neo-Adjuvant Chemotherapy Resection Specimen","authors":"T. S. Saleena, Muhamed Ilyas P, Sajna V. M. Kutty","doi":"10.1109/ICCSC56913.2023.10143027","DOIUrl":"https://doi.org/10.1109/ICCSC56913.2023.10143027","url":null,"abstract":"The death of tumor tissues after chemotherapy is the most important decision factor in the treatment plan in the case of Osteosarcoma and Renal Cell Carcinoma. The percentage of necrosis accumulated due to such chemotherapy will help the doctors to assess the severity of cancer in the patient. Deep learning algorithms can automatically segment the region of necrosis and find the volume of the region using digital histopathology images. This can reduce the inter-observer disagreement that arises at the time of manual segmentation by the pathologists. But the undersupply of data, especially in pathology images is an ever-time obstacle in deep learning algorithms. In our study we have created a synthetic dataset from 47 images which are captured and manually annotated by experienced pathologists. Each image captured is of dimensions 2592×1932, which are split into patches of size 512×512. So we can have 15 patches from each image and thereby we created a dataset of 705 samples. Different augmentation techniques can be applied to this dataset that can again increment the number.","PeriodicalId":184366,"journal":{"name":"2023 2nd International Conference on Computational Systems and Communication (ICCSC)","volume":"72 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117251893","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

Blockchain Based Verification of Educational and Professional Certificates 基于区块链的教育和专业证书验证

2023 2nd International Conference on Computational Systems and Communication (ICCSC) Pub Date : 2023-03-03 DOI: 10.1109/ICCSC56913.2023.10143008

Anjali Singh, S. Chauhan, A. Goel

{"title":"Blockchain Based Verification of Educational and Professional Certificates","authors":"Anjali Singh, S. Chauhan, A. Goel","doi":"10.1109/ICCSC56913.2023.10143008","DOIUrl":"https://doi.org/10.1109/ICCSC56913.2023.10143008","url":null,"abstract":"Educational Documents and Certificates are a proof of professional achievements for anyone. Without these documents, it is not possible to start your career and hence play a very important role in everyone's professional life. Till date, Colleges, Universities and various educational institutes issue paper based degrees and certificates which are prone to get damaged or may be lost. The other drawback is that this process of issuing of degrees and manual process of verification of those documents by third parties is a time taking and cumbersome process. The employers take a lot of time for verifying these paper based degrees and certificates before they give the job offer. Forgery of paper based documents is also easier and has led to many educational scams. This paper aims to give the solution to the problems mentioned above through Blockchain Implementation. Block chain technology is not only limited to crypto currencies but is also of great applications in various fields like health, supply chain management, finance, etc. It has disrupted the traditional education system. This paper highlights as to how the educational certificates can be verified using the Ethereum platform and smart contracts. The traditional paper certificates would be converted to digital certificates on student's request, their hash value would be calculated using cryptographic hash functions and stored on Blockchain. A unique certificate ID and transaction hash value would be generated which would then be used to verify the certificates through a common platform.","PeriodicalId":184366,"journal":{"name":"2023 2nd International Conference on Computational Systems and Communication (ICCSC)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116019160","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 Universal Model Predictive Control of DFIG in the Wind Solar Hybrid System 风能-太阳能混合系统DFIG的通用模型预测控制

2023 2nd International Conference on Computational Systems and Communication (ICCSC) Pub Date : 2023-03-03 DOI: 10.1109/ICCSC56913.2023.10143018

Dilsha M K, Sunil Kumar P R

{"title":"A Universal Model Predictive Control of DFIG in the Wind Solar Hybrid System","authors":"Dilsha M K, Sunil Kumar P R","doi":"10.1109/ICCSC56913.2023.10143018","DOIUrl":"https://doi.org/10.1109/ICCSC56913.2023.10143018","url":null,"abstract":"Hybrid Systems are the future of power generation. Together, they can make up for the inefficiency of one and give more effective result, as in the case of wind and solar generation. Double Fed Induction Generators (DFIG) are mainly used for Wind Energy Conversion because of the generation during variable wind speeds. There are two Voltage Source Converters (VSC) on the machine side and grid side of the Wind Energy Conversion System (WECS). A Solar Photo Voltaic System (SPVS) with a boost converter is equipped with an incremental conductance maximum power point tracking algorithm (MPPT). The conventional vector control suffers from complex decoupling processes, computational complexity, and slow dynamic response. To address these issues, this work presents Model Predictive Power Control (MPPC) to improve performance while reducing power ripples, current distortion, computation, and system complexity. The performance analysis is conducted for both vector control and MPPC by implementing the simulation model in MATLAB/SIMUINK. The performance of the PV system under different irradiances is carried out. THD analysis is carried out for MPDPC.","PeriodicalId":184366,"journal":{"name":"2023 2nd International Conference on Computational Systems and Communication (ICCSC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127164297","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

Energy Audit at LBS College of Engineering Kasaragod 伦敦商学院工程学院能源审计专业

2023 2nd International Conference on Computational Systems and Communication (ICCSC) Pub Date : 2023-03-03 DOI: 10.1109/ICCSC56913.2023.10143015

Abhishek Gopinath, Aruna P. Remesh, Harshith C, Jeswin Thomas, Jayakumar M

引用次数: 0