2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)最新文献_第10页

A BrainNet (BrN) based New Approach to Classify Brain Stroke from CT Scan Images 基于脑网络的脑卒中CT扫描图像分类新方法

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141780

Dhonita Tripura, Imdadul Haque, M. Dutta, Shaikat Dev, Tanjila Jahan, Shomitro Kumar Ghosh, M. Islam

{"title":"A BrainNet (BrN) based New Approach to Classify Brain Stroke from CT Scan Images","authors":"Dhonita Tripura, Imdadul Haque, M. Dutta, Shaikat Dev, Tanjila Jahan, Shomitro Kumar Ghosh, M. Islam","doi":"10.1109/InCACCT57535.2023.10141780","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141780","url":null,"abstract":"Worldwide, brain stroke is known as the 2nd leading cause of death, and based on Indian history, three people have suffered every minute. There are mainly two different types of brain stroke: ischemic stroke and Hemorrhagic stroke used to train the proposed models. Ischemic stroke is the most common and it contributes mostly to 80% of the brain stroke and Hemorrhagic stroke contributes mostly to 20% of the brain stroke. In the proposed model, there has been used a hybrid model called BrainNet (BrN) as CNN(Convolutional Neural Network) and SVM(Support Vector Machine)to classify brain stroke disease. After applying the required proposed model, it has produced a smart score of 91.91% accuracy, and compared to the existing model it performs pretty well. The BrainNet (BrN) model is mainly designed based on a deep neural network with dataset collection, preprocessing, and feature extraction with the desired model and make the classification concerning SVM. With compare to the existing model, it is an acceptable performance that belongs to the collected dataset designed with Ischemic stroke and Hemorrhagic stroke disease within the total number of 2515 data.","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":"121036780","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

Multi Modal Smart Diagnosis of Pulmonary Diseases 肺部疾病的多模式智能诊断

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141833

S. U. Priya, S. R. Ganesh Tarun, S. Shamitha, Anusha S. Rao, V. R. Badri Prasad

{"title":"Multi Modal Smart Diagnosis of Pulmonary Diseases","authors":"S. U. Priya, S. R. Ganesh Tarun, S. Shamitha, Anusha S. Rao, V. R. Badri Prasad","doi":"10.1109/InCACCT57535.2023.10141833","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141833","url":null,"abstract":"Health is an outfit that looks different on everybody. Lively health and factors on their counterpart have diseases and cures. There is a wide range of ailments, some of them being chronic and requiring timely treatment. On the grounds of the human body segments different maladies such as coronary, pulmonary, neurological disorders, and many more can be caused. Pulmonary diseases affect the lungs causing obstruction in the airflow. Pulmonary illness requires continuous monitoring of the victim under the supervision of a medical expert for a reasonable duration in order for it to be cured. Contacting the medical practitioner will not always be within boundaries of reach and timely, therefore there is a need for computerization and mechanizing the Screening Process of Pulmonary diseases namely covid, lung cancer, pneumonia, and tuberculosis(TB), and providing a pre-consult notice to the sufferer. Techs such as machine learning(ML) and deep learning(DL), mainly autoencoders(AE) along with flask to support a web interface are used. The research is distinct for it takes into consideration four different diseases and draws conclusions based on symptoms and medical scans. KNeighbors(KNN) model on symptoms gave a test accuracy of around ninety-four percent. AE on computed tomography(CT) scan and chest X-ray(CXR) has a test accuracy of about eighty-eight and ninety-two percent respectively.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"156 5 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":"125914824","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

Image Analysis for E-Healthcare Systems using Multi-Biometric Recognition Model 基于多生物特征识别模型的电子医疗系统图像分析

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141736

Naman Bansal, P. Arora, D. Sharma, K. D. Gupta, Chandana Kuntala

引用次数: 0

IoT Botnet Creation and Detection using Machine Learning 使用机器学习创建和检测物联网僵尸网络

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141717

H. Esha, Basanagouda S Hadimani, S. P. Devika, P. Shanthala, R. Bhavana

{"title":"IoT Botnet Creation and Detection using Machine Learning","authors":"H. Esha, Basanagouda S Hadimani, S. P. Devika, P. Shanthala, R. Bhavana","doi":"10.1109/InCACCT57535.2023.10141717","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141717","url":null,"abstract":"According to ethical hacking specialists, malware has been present in online environments for a very long time. More malware is being disseminated online as new technology is developed. The prevalence of botnets has increased. Infected software first creates a botnet before spreading the bot throughout a network. A botnet is employed in scenarios with infected massive computers. Ethical hacking instructors issue a warning due to the botnet’s ability to infect vast numbers of computers. Cybersecurity is increasingly relying on botnets. Botnets attack the vast majority of enterprises. To tackle this issue, researchers began to use machine learning (ML).We give a quick review of the various machine learning (ML) techniques used in botnet identification in this study. This paper’s main goal is to undertake various malware analysis to build our botnet, analyze it using a packet-capturing tool, and further validate our machine-learning models utilizing the botnet. To develop reliable and effective real-time online detection and mitigation systems as well as more reliable models, a comprehensive knowledge of these functions is essential.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"328 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":"121675280","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

Development of Simulation and Visualization System of Aircraft Assembly Process Technology Based on DELMIA Software 基于DELMIA软件的飞机装配工艺仿真可视化系统开发

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141825

Md Helal Miah, D. S. Chand, Gurmail Singh Malhi

{"title":"Development of Simulation and Visualization System of Aircraft Assembly Process Technology Based on DELMIA Software","authors":"Md Helal Miah, D. S. Chand, Gurmail Singh Malhi","doi":"10.1109/InCACCT57535.2023.10141825","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141825","url":null,"abstract":"The main purpose of the digital aircraft assembly process is to ensure the high assembly accuracy of aircraft products, flexibility and reduce the assembly time. Also, reduce the assembly and manufacture error of tooling (Jig/Fixture) design for particular aircraft products. Generally, the aircraft product assembly process is complex, and it performs through the assembly and disassembly process. Regarding the complexity of the aircraft product assembly process, this research illustrates the systematic analysis of the simulation and visualization technology for the aircraft assembly process. This research introduces key technologies and solutions to realize the aircraft’s assembly process visualization system. Then assembly simulation environment is implemented based on virtual reality modelling language (VRML), network, assembly process simulation, and visualization of assembly process documents. The digital aircraft assembly process technology has been divided into simulation and visualization systems in this research. The simulation process includes manufacturing factors, assembly objects, assembly sites, process equipment, tools, and devices. The visualization system visually processes the assembly simulation results and then outputs the processed results in the workshop workplace. It includes the related simulation results and adds necessary text technology to make it easier to understand the concept using visualization techniques to process the results. The research has practical value in the modern aircraft industry to propose an aircraft product simulation process based on computer-aided 3D design.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"48 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":"121991132","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 Review on Brain Tumor Prediction using Deep Learning 基于深度学习的脑肿瘤预测研究进展

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141790

S. Keerthi, Yukta N Shettigar, K. Keerthanan, K. R. Divyashree, S. Bhargavi

{"title":"A Review on Brain Tumor Prediction using Deep Learning","authors":"S. Keerthi, Yukta N Shettigar, K. Keerthanan, K. R. Divyashree, S. Bhargavi","doi":"10.1109/InCACCT57535.2023.10141790","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141790","url":null,"abstract":"Detection and segmentation of brain tumors is important in the healthcare domain. Since brain tumors can possibly lead to cancer, it is a crucial task to detect it early through Magnetic Resonance Imaging (MRI) or Computed Tomography (CT), which are the techniques that use radio waves and magnetic fields to present a detailed view of the body organs. The images obtained from the MRI makes it hard to locate the exact position of the tumor and hence it is a challenging task to detect the tumor accurately. Thus, computer-aided methods (segmentation, detection and classification processes) with better accuracy are required for early tumor diagnosis. The segmentation of brain tumor which is usually carried out manually by the radiologists through their expertise and skill is a highly prolonged task and there can be chances of some faulty predictions, hence, the semantic segmentation is proven to be an effective method to overcome this problem. Semantic segmentation method is applied to brain tumors which are automatically segmented with the aid of deep learning techniques (CNN, RNN, GAN, LSTMs, etc.). The usage of deep learning techniques with greater accuracy and robustness are proven to be effective for the precise diagnosis of brain tumor. The primary objective of this paper is to examine the previously published techniques using deep learning for the human brain tumor prediction.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"32 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":"121541712","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

Exchange Rate Prediction with Machine Learning, Deep Learning, and Time Series Methods Using Alternative Data 汇率预测与机器学习，深度学习和时间序列方法使用替代数据

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141844

Aklant Das, Dhanya Pramod

引用次数: 0

Deep Learning Based Model for Fake Review Detection 基于深度学习的虚假评论检测模型

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141826

Digvijay Singh, M. Memoria, Rajiv Kumar

{"title":"Deep Learning Based Model for Fake Review Detection","authors":"Digvijay Singh, M. Memoria, Rajiv Kumar","doi":"10.1109/InCACCT57535.2023.10141826","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141826","url":null,"abstract":"In present time, peoples are more inclined towards the e-commerce for their purchases and their choices are much influenced by the reviews available over there as review plays an important role in making their decision. If the reviews are more positive the possibility to buy the product is comparatively high. Here, the necessity arrives to develop a sustainable approach for the detection of malicious reviews to save the customers from the fraud. There are many sites or agencies are available which are hired by the merchandise to generate the positive reviews for them to increase their sales or damage the competitor’s product sales. Deep learning methodologies for malicious review detection includes, Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) are proposed in this paper. We have also compared the performance of these methods with state of arts techniques such as Naive Bayes (NB), K Nearest Neighbour (KNN) and Support Vector Machine (SVM) for the detection of fake reviews and ultimately, its efficiency is illustrated for both the traditional and the deep learning classifiers.","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"80 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":"127100114","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

An Emergency Rescue Framework through Smart IoT LPWAN 基于智能物联网LPWAN的应急救援框架

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141728

K. Jain, Hemant Kumar Saini

{"title":"An Emergency Rescue Framework through Smart IoT LPWAN","authors":"K. Jain, Hemant Kumar Saini","doi":"10.1109/InCACCT57535.2023.10141728","DOIUrl":"https://doi.org/10.1109/InCACCT57535.2023.10141728","url":null,"abstract":"with the emerging population vehicle are expanding on a streets in the present reality. Because of the deficient rescue administrations, expanded street traffic, street accidents are broadening that lead to loss of lives and property. Such outcomes results in the demise rate per year, which becomes a serious issue in supporting human existence. Notwithstanding, vehicles are implanted with pattern innovation, however the accident count will rise day by day because of such delays in communicating the data to the concerned individual or to protect group. This paper will introduce the different LoRa (Long range) design with low power utilization. Cloud technology is used for accident detection and emergency ambulance transportation from the scene of the unplanned tragedy to the closest hospital where emergency healthcare can be delivered. Likewise, emergency data can be shipped off the cloud right away, and its response in alarming the environmental elements and telling the proper clinic. The proposed model fabricated a compelling brilliant vehicular framework involving GPS for distinguishing the accident spot and getting to the scene early and impact sensors for identifying hindrances","PeriodicalId":405272,"journal":{"name":"2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT)","volume":"14 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":"122301914","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

Vulnerability Analysis Architecture Utilizing Auto Encoding Bayesian Algorithm 基于自编码贝叶斯算法的漏洞分析体系结构

2023 International Conference on Advancement in Computation & Computer Technologies (InCACCT) Pub Date : 2023-05-05 DOI: 10.1109/InCACCT57535.2023.10141759

D.Salangai Nayegi, Dhanalakshmi, Soumyadip Roy, Sanjivani, Darshan J

引用次数: 0