2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)最新文献_第5页

Identification of Polycystic Ovary Syndrome in ultrasound images of Ovaries using Distinct Threshold based Image Segmentation 基于不同阈值的卵巢超声图像识别多囊卵巢综合征

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141800

B. Poorani, Rashmita Khilar

{"title":"Identification of Polycystic Ovary Syndrome in ultrasound images of Ovaries using Distinct Threshold based Image Segmentation","authors":"B. Poorani, Rashmita Khilar","doi":"10.1109/InCACCT57535.2023.10141800","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141800","url":null,"abstract":"Polycystic Ovary Syndrome (PCOS) is a common hormonal disorder among women of reproductive age and it can lead to infertility, metabolic disorders and other health problems. Ultrasound is an important tool for the diagnosis of PCOS. In medical image processing, the threshold segmentation plays a critical role in the identification of PCOS by isolating and accurately analyzing the cysts. In this paper, the PCOMorphology is extracted from the ultrasound images using three threshold-based segmentation algorithms: Adaptive Mean Threshold, Adaptive Gaussian Threshold, and Otsu Threshold. The performance of these algorithms is evaluated based on several metrics such as accuracy, sensitivity, specificity, and F1 score. The results show that the Otsu Threshold algorithm provides the best performance in terms of follicle detection and accuracy, followed by Adaptive Gaussian Threshold and Adaptive Mean Threshold. In conclusion, the comparison of these three algorithms shows that Otsu Threshold algorithm is the most suitable for the identification of PCOS using ultrasound images. The results of this study have important implications for the diagnosis of PCOS and further research is needed to improve the accuracy of the diagnosis. The proposed algorithms can be integrated into the existing clinical diagnosis systems to improve the accuracy and efficiency of the diagnosis process. This study provides a promising direction for future research in the field of medical image processing and PCOS diagnosis","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"27 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130201348","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

Private Cloud Hybrid Architecture for Protected Data Communication 保护数据通信的私有云混合架构

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141705

Abdul Majid Soomro, Awad Bin Naeem, Sanjoy Kumar Debnath, Susama Bagchi, S. Gupta, Kamal Saluja

引用次数: 0

A Novel Approach to Degin Home Automation using IoT Applications 使用物联网应用设计家庭自动化的新方法

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141754

Parul Dubey, Harshita Chourasia, Shilpa Ghode

{"title":"A Novel Approach to Degin Home Automation using IoT Applications","authors":"Parul Dubey, Harshita Chourasia, Shilpa Ghode","doi":"10.1109/InCACCT57535.2023.10141754","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141754","url":null,"abstract":"The design of home automation systems is getting more challenging as more and more people adopt new technologies. There is still a significant amount of work to be done before end users will have full control over the monitoring and programming capabilities of their own houses. There may be a need for a self-sufficient and scalable household system that is able to support a diverse collection of appliances, tools, and pieces of technology. This article demonstrates how apps for the Android operating system may be used to control and monitor home appliances from a distant location. Those who are unable to move without the use of a wheelchair would benefit tremendously from this. The practical goal of this research is to build an android home automation system that is capable of existing in both virtual and real environments. Orders are sent from an Android phone to a nodeMCU for all of the home appliances to function properly. The key purposes of this system are the control of the lighting and fans, as well as the detection of smoke in the case that there is a fire. We also compare the proposed design with the existing models and fund that this is much cheaper with no compromise in the features of the system.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122432657","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

Design and Develop A Delay Sensitive Smart Health Framework Using Nature Inspired Load Balancer 使用自然启发负载平衡器设计和开发延迟敏感智能健康框架

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141806

Navneet Kumar Rajpoot, Prabhdeep Singh, B. Pant

{"title":"Design and Develop A Delay Sensitive Smart Health Framework Using Nature Inspired Load Balancer","authors":"Navneet Kumar Rajpoot, Prabhdeep Singh, B. Pant","doi":"10.1109/InCACCT57535.2023.10141806","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141806","url":null,"abstract":"A smart healthcare system that uses fog computing and the internet of things is of paramount importance at the present time. Managing the ever-increasing load on fog nodes can be especially challenging in dynamic and diverse fog networks due to the high potential for overhead. As the number and variety of IoT-based devices grow, so ensure their processing requirements; this is where fog computing comes in. Delay in providing medical attention can have severe consequences. In order to address this issue, a delay-sensitive smart health framework has been proposed in this study. The framework uses a nature-inspired load balancer based on ant colony optimization algorithm, which primarily aims to decrease delay and performance issues. The Ant Colony Optimization Technique is a nature-inspired technique that improves system efficiency by balancing loads, decreasing response times, and minimizing delay. Our proposed approach is superior to the state-of-the-art in all these important metrics: latency, response time, overall system accuracy, and system stability. This will result in faster response times and improved medical services for patients in emergency situations.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126339954","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 Smart Spotify Assistance and Recommendation System 一个智能Spotify辅助和推荐系统

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141810

Keshav Allawadi, Charvi Vij

引用次数: 0

Analyzing The Prediction Accuracy Of Corn Leaf Diseases Using A Pre-Trained Network Model 基于预训练网络模型的玉米叶片病害预测精度分析

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141840

C. Ashwini, V. Sellam

{"title":"Analyzing The Prediction Accuracy Of Corn Leaf Diseases Using A Pre-Trained Network Model","authors":"C. Ashwini, V. Sellam","doi":"10.1109/InCACCT57535.2023.10141840","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141840","url":null,"abstract":"During corn’s exploration and manufacturing phases, farmers have a complicated issue in accurately diagnosing corn crop infections. To solve this issue, this work provides a method for specific position three prevalent diseases of corn leaves: grey spot, leaf blight, and rusty depending on grouping and an upgraded deep learning method. Deep learning advancements paved the path for enhancing prediction accuracy as its significance is adopted over various research fields. Disease prediction and classification is time-consuming due to the lesser foreground and background intensity information. To identify three illnesses, first cluster reference images using the clustering technique, then input them into the enhanced deep network. The influences of various ‘k’ values on corn diagnostic techniques are investigated in this research. The trial findings show that the approach has the most significant identification impact on observations with the analytical prediction of corn disease, rust, and grey spot disease. Here, VGG-16 and ResNet18 likewise produce the best diagnostic findings, with an average diagnostic accuracy, respectively. The technique presented in this study has a diagnostic performance of 95% for the three corn diseases. It has a more substantial diagnostic impact than another four techniques and can be used to safeguard crops in the agricultural area. The simulation is done in the MATLAB 2020a environment, and various performance metrics like accuracy, precision, F1-score, recall and some other statistical measures are evaluated and compared with existing approaches.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130393486","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

Spread Analysis and Prediction of Covid-19 in India using Machine Learning 利用机器学习分析和预测印度Covid-19的传播

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141756

Anuradha Yenkikar, C. Babu

{"title":"Spread Analysis and Prediction of Covid-19 in India using Machine Learning","authors":"Anuradha Yenkikar, C. Babu","doi":"10.1109/InCACCT57535.2023.10141756","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141756","url":null,"abstract":"Since its breakout, the coronavirus (covid-19) has wreaked devastation all over the world. There hasn’t been a nation that hasn’t been affected by it, and India is no exception. Finding a treatment for this sickness and stopping its spread is one of the hardest problems humanities has ever faced. World Health organization (WHO) figures show that the mortality rate and the number of people with covid-19 are both increased exponentially in some countries during the peak waves. In this study, we use machine learning approaches to forecast the number of covid-19 confirmations, recoveries, and mortality cases over a period of time and assess the coronavirus outbreak in India. The polynomial regression (PR), support vector regression (SVR), and an autoregressive integrated moving average (ARIMA) model are three techniques that are used. The findings demonstrate that, in terms of prediction outcomes, the ARIMA model provides the least Root Mean Squared Error (RMSE), closely followed by polynomial regression. SVR doesn’t perform well since predictions are either too low or too high. Overall, the proposed system can significantly aid in comprehending the pattern of spread in other nations and assist governmental bodies in taking action to lessen its effects in future.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131092154","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

Deep Learning Based Face Mask Detection Model For COVID-19 Prevention 基于深度学习的COVID-19口罩检测模型

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141733

S. Mohapatra, F. A. Ali, P. Sarangi, Premananda Sahu, J. Mohanty

引用次数: 0

Design of Interactive Portal for Skin Disease Detection and Live Counseling 交互式皮肤病检测与实时咨询门户的设计

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141781

M. Kshirsagar, Haziquddin Ansari, Himanshu Upase, D. Ansari, Meghashree Mohane

{"title":"Design of Interactive Portal for Skin Disease Detection and Live Counseling","authors":"M. Kshirsagar, Haziquddin Ansari, Himanshu Upase, D. Ansari, Meghashree Mohane","doi":"10.1109/InCACCT57535.2023.10141781","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141781","url":null,"abstract":"Skin conditions are among the most challenging to diagnose quickly, easily, and accurately due to their high complexity and high cost of care, as well as the difficulties and subjectivity associated with human interpretation. This is especially true in developing and underdeveloped nations with limited healthcare resources. Additionally, it is well known that the likelihood of serious outcomes is decreased in many disease instances by early identification. These skin conditions have just recently become more prevalent due to current environmental influences. Early detection of our key conditions–-eczema, dermatitis, melanoma, and psoriasis–-can eliminate a person’s risk of death. The development of medical technology based on photonics and lasers has made it possible to identify skin illnesses considerably more rapidly and precisely. However, the expense of such a diagnosis is still burdensome and high. Our study helps create a model that uses CNN to categorize skin conditions and offers a platform for consultation with a dermatologist for accurate disease diagnosis. In order to identify skin diseases, we suggested an easy to use, effective and inexpensive approach based on image processing which doesn’t necessitate any equipment’s beyond a webcam and a computer. This method takes digital photo of the diseased skin area and uses image analysis to identify the type of skin disease.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117029490","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

Design And Development Of Unmanned Hydroponic Setup Using IoT 基于物联网的无人水培装置设计与开发

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141749

B. Megha Nair, R. Sujatha, Amala Ipe

{"title":"Design And Development Of Unmanned Hydroponic Setup Using IoT","authors":"B. Megha Nair, R. Sujatha, Amala Ipe","doi":"10.1109/InCACCT57535.2023.10141749","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141749","url":null,"abstract":"Farmers need top-notch soil with strong natural mineral contents for the traditional farming approach. It also involves labour costs. It also requires a lot of land and water for weeding and ploughing. When it comes to seasonal plants, the yield falls short of meeting both consumer demands and farmer productivity expectations. Due to these characteristics,a farming technique that is less expensive to implement and thatalso makes it simple to manage and regulate key variables like light, temperature, and humidity all through the year is required. The procedure of cultivating plants hydroponically without light from the sun or soil is described in the proposed study. The level of the fertilizer solution and the presence of algae are monitored, and variables like humidity and temperature are assessed. As the level of the nutrient solution drops, a mechanism for automatically dispensing nutrient solution is also designed. The fresh nutrient solution is supplied to the container after emptying the current solution when presence of algae is identified. Farmers can routinely check their crops to improve their growth and output from the cloud-basedstorage of the sensor data.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114849625","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