2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)最新文献_第2页

The Smart Performance Analysis of Reliability based Optimization Service for Secured Cloud Servers using Priority based Scheduling 基于优先级调度的安全云服务器可靠性优化服务智能性能分析

2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC) Pub Date : 2023-07-06 DOI: 10.1109/ICESC57686.2023.10193451

Parnapalli Maruthi, C. Sivakumar

{"title":"The Smart Performance Analysis of Reliability based Optimization Service for Secured Cloud Servers using Priority based Scheduling","authors":"Parnapalli Maruthi, C. Sivakumar","doi":"10.1109/ICESC57686.2023.10193451","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193451","url":null,"abstract":"Reliability-based optimization service is a cloud server security solution designed to ensure optimal system reliability and security while ensuring that the costs associated with protective measures are kept within acceptable limits. The service provides a comprehensive approach to service reliability, utilizing real-time analytics to measure the security and performance of cloud servers. These metrics are then used to prioritize the allocation of resources to ensure that the most cost-effective security and reliability safeguards are achieved. It includes the implementation of network segmentation, code patching, malware protection, and authentication services. Priority-based scheduling allows the cloud service provider, or CSP, to prioritize certain operations while de-prioritizing operations that require fewer resources or security. By using priority-based scheduling, CSPs can improve their cloud servers' performance while ensuring that any operations requiring special attention, such as security operations, are given priority. The goal of priority scheduling is to ensure that critical operations receive the necessary resources and attention without compromising the performance of the cloud servers. Furthermore, priority scheduling helps CSPs avoid bottlenecks during peak hours by utilizing sparsely used resources for additional operations. In addition, priority scheduling facilitates the integration of the various components of cloud computing and ensures the availability of resources for operations in the future.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113979055","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

Production Enhancement and Process Analysis for Pharmaceutical Industries 制药工业的生产改进与工艺分析

2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC) Pub Date : 2023-07-06 DOI: 10.1109/ICESC57686.2023.10193278

T. Murali, A. Priya

{"title":"Production Enhancement and Process Analysis for Pharmaceutical Industries","authors":"T. Murali, A. Priya","doi":"10.1109/ICESC57686.2023.10193278","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193278","url":null,"abstract":"“Production Enhancement and Process Analysis for pharmaceutical industries” is a Pharma analytics process, which harnesses the power of data analytics to improve operations in the pharmaceutical industry. To provide recommendations to increase the production flow rate in the continuous process. Run-time recommendations and insights based on multivariate parameters to help operators achieve optimal outcomes. The process of working with different teams concerning their shifts working day and night is monitored. The fluctuations in the system help to investigate how each parameter is working in the plant individually and the best range of parameters to guarantee optimized production consistently are identified. In the existing system, the analysis was made unit-wise and batch-wise. Since it was not a continuous process, analysis was done batch by batch without any difficulties. Continuous manufacturing is favored because the results of one production run do not have an impact on the outcomes of subsequent runs, unlike batch manufacturing. Whereas in the proposed system, it was a continuous process which doesn’t contain any batches to overcome this challenge cycle time and lag time approach was used.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124046831","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

ICESC 2023 Cover Page icesc2023封面

2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC) Pub Date : 2023-07-06 DOI: 10.1109/icesc57686.2023.10193242

引用次数: 0

Certain Investigation on Adders and Multipliers for Different Applications 不同应用的加法器和乘法器的若干研究

2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC) Pub Date : 2023-07-06 DOI: 10.1109/ICESC57686.2023.10193736

M. Supriya, M. Kathirvelu

引用次数: 0

Optimized Plant Disease Prediction using CNN and Fertilizer Recommendation Engine 利用CNN和肥料推荐引擎优化植物病害预测

2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC) Pub Date : 2023-07-06 DOI: 10.1109/ICESC57686.2023.10193314

P. Kanaga Priya, T. Vaishnavi, T. Pavithra, R. Sivaranjani, A. Reethika, G. Ramesh Kalyan

{"title":"Optimized Plant Disease Prediction using CNN and Fertilizer Recommendation Engine","authors":"P. Kanaga Priya, T. Vaishnavi, T. Pavithra, R. Sivaranjani, A. Reethika, G. Ramesh Kalyan","doi":"10.1109/ICESC57686.2023.10193314","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193314","url":null,"abstract":"A large portion of the Indian economy depends on agricultural productivity, and the impact of plant diseases can be significant. The consequences of a plant being affected by a disease can result in a considerable decrease in output, and the experiencing decline in financial losses is a unique consequence of a decline in both the caliber and amount of agricultural goods. To avoid a reduction in agricultural productivity and quantity, it is essential to recognize plant diseases. While enormous acres of crops are being monitored, plant disease detection is receiving an increasing amount of attention. Thus, this is possible by making use of image processing methods for plant disease diagnosis. The major limitation of the existing system is, it only predicts a plant disease, and this work not only detects the plant disease but also recommends a suitable fertilizer. The dataset used in the proposed model contains 16870 images and the model is implemented using a deeper Convolutional Neural Network (CNN). The level of accuracy accomplished by the model is 96% for fruit leaves and 89% for vegetable leaves.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130057102","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

Scalable AR Integration Pipeline for Immersive Textbook Learning Experience 可扩展的AR集成管道沉浸式教科书学习体验

2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC) Pub Date : 2023-07-06 DOI: 10.1109/ICESC57686.2023.10193488

K. Selvakumaran, Shreya Kishore, Appsara Narayanasamy, Ashwin Radhakrishnan, M. Malarvel

{"title":"Scalable AR Integration Pipeline for Immersive Textbook Learning Experience","authors":"K. Selvakumaran, Shreya Kishore, Appsara Narayanasamy, Ashwin Radhakrishnan, M. Malarvel","doi":"10.1109/ICESC57686.2023.10193488","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193488","url":null,"abstract":"The availability of learning tools in schools that are accessible to low-income households is generally very limited when compared to most private schools that cater to the well-off masses. Contrarily, the accessibility, and usage of smartphones in the low-income population is surprisingly comparable to that of the medium and high-income populations due to the presence of affordable smartphones. Hence, enhancing the learning experience of children from low-income households through resourceful strategies that utilize smartphones can counter their school’s deficit of learning tools. One such strategy is proposed by this study, where an immersive and interactive learning experience can be created through the integration of Augmented-Reality based visualizations in textbooks that make concepts more appealing and clear. This approach is ideal for low-budget schools as it does not require any setup expenses from students or the school. This pipeline made scalability a key priority in order to accommodate a vast number of AR experiences that can cover an entire curriculum composed of different subjects.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131769577","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

Breast Cancer Detection in Deep Learning based Architectures using Mammogram Images 基于乳房x光片图像的深度学习架构中的乳腺癌检测

2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC) Pub Date : 2023-07-06 DOI: 10.1109/ICESC57686.2023.10193572

Ghaith Bilal, Dinesh Kumar, Sejal Shah, Rohit M. Thanki

{"title":"Breast Cancer Detection in Deep Learning based Architectures using Mammogram Images","authors":"Ghaith Bilal, Dinesh Kumar, Sejal Shah, Rohit M. Thanki","doi":"10.1109/ICESC57686.2023.10193572","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193572","url":null,"abstract":"Breast cancer is a very devastating type of cancer that typically develops in breast cells and in the past few decades, the incidence rate of breast cancer has risen steadily. The diagnosis mostly depends on the radiologists’ experience, questionable diagnoses are common, and there are worries about lawsuits due to incorrect diagnoses or missed lesions. Therefore, developing deep learning models for breast cancer identification is urgently needed, despite substantial advancements in the treatment of primary breast cancer during the past ten years. In Deep Learning, the convolutional neural network can be a useful technique for classification problems.In this study, some of the Transfer learning models are applied, which are pre-trained models that are trained on huge datasets such as the ImageNet dataset, which contains about 1.2 million images. However, these models are VGG16 VGG19 Mobilenet V2, and it is known that these models are used for classification problems, and therefore it will be used in this study in addition to developing a Convolutional Neural Network, which achieved the highest accuracy and best performance, compared to the applied models. These models were applied to the presented Mammogram Images dataset, which contains eight classes, each of which represents a form of mass that can be cancerous or benign. And since the dataset is unbalanced in terms of the distribution of samples for the classes, the Oversampling technique was applied, which had a key role in improving the performance of the models, especially for the CNN network, which obtained the highest accuracy of 96%.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130823205","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

Systematic Literature Review on Deep Learning Techniques in Electronic Health Records 电子健康记录中深度学习技术的系统文献综述

2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC) Pub Date : 2023-07-06 DOI: 10.1109/ICESC57686.2023.10193025

G. Chitra, S. M. Basha

{"title":"Systematic Literature Review on Deep Learning Techniques in Electronic Health Records","authors":"G. Chitra, S. M. Basha","doi":"10.1109/ICESC57686.2023.10193025","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193025","url":null,"abstract":"Nowadays there is a tremendous amount of digital information stored in Electronic Health Records (EHR). The EHR incorporates a wealth of information consisting of clinical notes, patient information, medications, procedures, laboratory test reports and so on. Thus, it has also led to huge impetus on exploiting the EHour R to aid clinical decision support systems. There is a growing research body in this direction to develop useful insights from FHR The typical EHR data is irregularly sampled, heterogenous, multi-modal lacking annotations with noisy and missing information. An additional challenge of need for privacy also means very limited publicly available datasetsfor benchmarking. Machine learning techniques are at the forefront of this effort in providing tools to analyse the huge amount of heterogeneous data. Recent advances in deep learning techniques have immensely contributed to growing applications using EHR Towards this, overview of recent advancements and techniques employed to analyse EHR data is introduced. A review of the literature and discuss the challenges of different approaches. In addition to that birds-view summary of the methods to aid future research improvements and trigger innovative applications in healthcare.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130889976","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

Two Port Slotted MIMO Antenna for Wireless Sensor Networks 用于无线传感器网络的双端口开槽MIMO天线

2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC) Pub Date : 2023-07-06 DOI: 10.1109/ICESC57686.2023.10193061

D. Elanseela, U. Surendar, A. Balakumar

引用次数: 0

IoT based Solar Powered Induction Heating for Hyperthermia Treatment 基于物联网的热疗太阳能感应加热

2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC) Pub Date : 2023-07-06 DOI: 10.1109/ICESC57686.2023.10193637

P. S. Kumar, A. Aswini, M. Kaleeswari, P.Arockia Prasad, R. Manickavasagam, P. Devi

{"title":"IoT based Solar Powered Induction Heating for Hyperthermia Treatment","authors":"P. S. Kumar, A. Aswini, M. Kaleeswari, P.Arockia Prasad, R. Manickavasagam, P. Devi","doi":"10.1109/ICESC57686.2023.10193637","DOIUrl":"https://doi.org/10.1109/ICESC57686.2023.10193637","url":null,"abstract":"Induction heating technique is now the preferred heating method in various engineering, household, and therapeutic applications owing to its profits in terms of efficiency, rapid heating, safety, spotlessness, and accurate control. Solar energy is the greatest plentiful energy source for producing heat in induction heating system. In this project, an induction heating system integrating Internet of Things has been suggested for use in healthcare. The main aim of this research is to use internet of things technology and induction heating to assist treat cancer (IoT). According to a previously established notion, cancer cells cannot live in environments 5 to 6 degrees Celsius warmer than normal body temperature. Hyperthermia. involves heating to 39-45°C to promote susceptible to chemotherapy and radiotherapy, are routinely used in the clinic. In order to slaughter cancer cells without damaging healthy cells, a ferromagnetic implant will be positioned close to the cancerous cells in the body. By applying induction heating, the temperature of the implant can be elevated between 41 and 43 degrees Celsius. Small stand-alone photovoltaic (PV) systems can now be remotely supervised with the help of the Internet of Things (IoT). Additionally, IoT will monitor the patient’s behaviors and record everything in real-time to the cloud, where it can be accessed from any location with an internet connection at any time. They also constantly keep an eye on the temperature of the ferromagnetic implant to ensure that the therapy is comfortable.","PeriodicalId":235381,"journal":{"name":"2023 4th International Conference on Electronics and Sustainable Communication Systems (ICESC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133633361","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