2023 3rd International Conference on Intelligent Technologies (CONIT)最新文献

Approaches to Selective Imaging of Live Systems via Memory Forensics 通过内存取证对活动系统进行选择性成像的方法

2023 3rd International Conference on Intelligent Technologies (CONIT) Pub Date : 2023-06-23 DOI: 10.1109/CONIT59222.2023.10205824

Sarishma Dangi, K. Ghanshala, Sachin Sharma

{"title":"Approaches to Selective Imaging of Live Systems via Memory Forensics","authors":"Sarishma Dangi, K. Ghanshala, Sachin Sharma","doi":"10.1109/CONIT59222.2023.10205824","DOIUrl":"https://doi.org/10.1109/CONIT59222.2023.10205824","url":null,"abstract":"Modern day forensic investigations rely on forensically sound digital evidence which is acceptable in a court of law. The increase cybersecurity attacks have enormously increased the need of forensic investigations leading to a huge corpus of data. Mostly, the memory image dump is so huge for individual cases out of which the critical evidence is present in a comparatively smaller amount of memory. Selective imaging provides a way to partially image the memory of target device without necessarily copying the rest of the image that may be of little or no use to the investigation. Selective imaging allows the investigator to forensically acquire memory in a strategic manner depending upon the nature of the case at hand. In this work, we explore the realm of selective imaging and present a consolidated literature review along with the various approaches available for considering selective memory imaging for live systems to conduct forensic investigations via live memory forensics. The work concludes by pointing the research directions around selective imaging for enhancing the effectiveness of live memory forensics.","PeriodicalId":377623,"journal":{"name":"2023 3rd International Conference on Intelligent Technologies (CONIT)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123123456","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: 2

Multi-Document Summarization Made Easy: An Abstractive Query-Focused System Using Web Scraping and Transformer Models 简化多文档摘要:使用Web抓取和转换模型的以查询为中心的抽象系统

2023 3rd International Conference on Intelligent Technologies (CONIT) Pub Date : 2023-06-23 DOI: 10.1109/CONIT59222.2023.10205946

Isaac Ritharson P, D. Sujitha Juliet, J. Anitha, S. Immanuel Alex Pandian

{"title":"Multi-Document Summarization Made Easy: An Abstractive Query-Focused System Using Web Scraping and Transformer Models","authors":"Isaac Ritharson P, D. Sujitha Juliet, J. Anitha, S. Immanuel Alex Pandian","doi":"10.1109/CONIT59222.2023.10205946","DOIUrl":"https://doi.org/10.1109/CONIT59222.2023.10205946","url":null,"abstract":"The paper proposes a web-based abstractive query-focused multi-document summarization system that aims to simplify the process of summarizing multiple documents on a given topic. The system leverages a range of technologies and techniques, including web scraping, natural language processing, and transformer models, to automate the summarization process and improve the accessibility of information for users. The system is designed to take user input in the form of a query, the number of words to be summarized, and the number of documents to be referred to. It then utilizes Google search engine API integration to retrieve the most relevant webpages based on their ranking, and performs web scraping of tags using beautiful soup (bs4) and selenium frameworks. The scraped data undergoes pre-processing, including stop word removal, tokenization using Auto tokenizer, and visualizing frequency matrix and word-cloud plots with seaborn and matplotlib. The system employs a transformer model ‘mt5-small Pretrained’ as the pipeline summarizer. The transformer model ranks the words based on frequency and generates a summary of the text that is coherent, concise, and relevant to the user’s query. The system delivers the output in the form of a well-structured summary that captures the essential information from multiple documents. The experimental results demonstrate the potential of integrating different technologies and techniques to automate the summarization process and provide users with high-quality summaries of multiple documents on a given query.","PeriodicalId":377623,"journal":{"name":"2023 3rd International Conference on Intelligent Technologies (CONIT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117057113","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

E-Certificate Generation using MVC Model 使用MVC模型生成电子证书

2023 3rd International Conference on Intelligent Technologies (CONIT) Pub Date : 2023-06-23 DOI: 10.1109/CONIT59222.2023.10205702

Shubhada Labde, Aayushi Vaibhav Mehta, Akshit Dinesh Mandani, Rehan Ali Siddiqui

引用次数: 0

Low Leakage and High Speed Sub-threshold 128-bit Fin-FET SRAM for Ultra-Low-Power Applications 用于超低功耗应用的低泄漏和高速亚阈值128位翅片fet SRAM

2023 3rd International Conference on Intelligent Technologies (CONIT) Pub Date : 2023-06-23 DOI: 10.1109/CONIT59222.2023.10205883

T. V. Reddy, K. Madhava Rao, R. Reddy, P. Kavitha Reddy

{"title":"Low Leakage and High Speed Sub-threshold 128-bit Fin-FET SRAM for Ultra-Low-Power Applications","authors":"T. V. Reddy, K. Madhava Rao, R. Reddy, P. Kavitha Reddy","doi":"10.1109/CONIT59222.2023.10205883","DOIUrl":"https://doi.org/10.1109/CONIT59222.2023.10205883","url":null,"abstract":"The demand for Low power handheld devices are rapidly increasing in the recent past and memory is the heart of the processor. SRAM architecture of Fin-FETs is the most emerging design used for high computational designs functionality and performance near the sub-threshold region of operation. The demand for customer handheld equipment and rapid growth in technologies leads to high computational and innovative designs, especially in memory architectures. Traditional SRAM using CMOS designs that occupy the maximum area and high leakage power that leads to poor performance operating under a sub-threshold regime. PVT Variations, BTI, sizing, delay along with power consumption are some of the factors affecting performance. Switching is the primary factor that contributes to major leakage at the near-threshold region. The main objective of the proposed model is a literature survey to design a 128-bit FinFET-based SRAM architecture operating under a threshold region. The second objective is to analyze power, SNM, and delay. Comparative analysis of various effects on CMOS and Fin FinFET designs is done in the third objective. The final objective is framed on performance and functionality, and reliability to provide the trade tradeoff between CMOS Vs. FinFET designs.","PeriodicalId":377623,"journal":{"name":"2023 3rd International Conference on Intelligent Technologies (CONIT)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123728120","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

Opportunities, Challenges, and Benefits of 5G-IoT toward Sustainable Development of Green Smart Cities (SD-GSC) 5G-IoT助力绿色智慧城市可持续发展的机遇、挑战与效益

2023 3rd International Conference on Intelligent Technologies (CONIT) Pub Date : 2023-06-23 DOI: 10.1109/CONIT59222.2023.10205780

Nataraju A B, Devasis Pradhan, Suma Jambli

{"title":"Opportunities, Challenges, and Benefits of 5G-IoT toward Sustainable Development of Green Smart Cities (SD-GSC)","authors":"Nataraju A B, Devasis Pradhan, Suma Jambli","doi":"10.1109/CONIT59222.2023.10205780","DOIUrl":"https://doi.org/10.1109/CONIT59222.2023.10205780","url":null,"abstract":"This article provides an overview of the opportunities, challenges, and benefits of the 5G-IoT (Internet of Things) ecosystem toward the sustainable development of Green Smart Cities (GSC). The authors first describe the key characteristics and requirements of GSCs, which aim to promote environmental sustainability, economic growth, and social well-being through the integration of advanced technologies and innovative approaches. They then discuss the potential of 5G-IoT to enable the deployment of GSCs at scale, by providing high-speed, low-latency, and reliable connectivity to a wide range of devices and applications. There are several key opportunities and benefits of 5G-IoT for GSCs, including improved energy efficiency, enhanced transportation, smarter buildings, and better public safety and healthcare. They also discuss some of the key challenges associated with the deployment of 5G-IoT in GSCs, such as security and privacy concerns, interoperability issues, and the need for effective governance and collaboration among stakeholders. This paper highlight the importance of a holistic and inclusive approach to the development of GSCs, which involves engaging all stakeholders, including citizens, businesses, governments, and non-governmental organizations (NGOs), in the design and implementation of smart city solutions.","PeriodicalId":377623,"journal":{"name":"2023 3rd International Conference on Intelligent Technologies (CONIT)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125391119","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

Multiclass Brain Tumor Classification of MR-Images Using ResNet-50 and Dimensionality Reduction Techniques 基于ResNet-50和降维技术的核磁共振图像多类脑肿瘤分类

2023 3rd International Conference on Intelligent Technologies (CONIT) Pub Date : 2023-06-23 DOI: 10.1109/CONIT59222.2023.10205710

Anjana M Nair, L. Kumar, V. E R

引用次数: 0

Application Research of Machine Vision Platform Based on Ant Colony Algorithm and Software Engineering 基于蚁群算法和软件工程的机器视觉平台应用研究

2023 3rd International Conference on Intelligent Technologies (CONIT) Pub Date : 2023-06-23 DOI: 10.1109/CONIT59222.2023.10205742

Xing Song, Yanqing Yang, S. Fan

{"title":"Application Research of Machine Vision Platform Based on Ant Colony Algorithm and Software Engineering","authors":"Xing Song, Yanqing Yang, S. Fan","doi":"10.1109/CONIT59222.2023.10205742","DOIUrl":"https://doi.org/10.1109/CONIT59222.2023.10205742","url":null,"abstract":"The research on the application of machine vision platform based on ant colony algorithm and software engineering is aimed at the application of machine vision platform based on ant colony algorithm and software engineering. The main purpose of this study is to identify applications that can be developed using our proposed system. In order to better understand, we conducted a survey of colleagues from different universities and institutes to understand their feedback on this topic. We have collected information from them about their views on this project. It includes the following steps: 1. Design the system architecture and analyze its performance; 2. Develop necessary algorithms to achieve the expected results; 3. Implement the developed algorithm into the actual system with real-time requirements; 4. Analyze and test the implementation results of the algorithm in the actual system; 5. Improve or modify the existing algorithm to improve its performance and achieve the efficiency of the expected results; 6. Test new versions of existing or newly developed algorithms to improve their performance or efficiency.","PeriodicalId":377623,"journal":{"name":"2023 3rd International Conference on Intelligent Technologies (CONIT)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115206625","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

Speech Enhancement Using Modified Wiener Filtering With Silence Removal 基于改进维纳滤波和去噪的语音增强

2023 3rd International Conference on Intelligent Technologies (CONIT) Pub Date : 2023-06-23 DOI: 10.1109/CONIT59222.2023.10205900

C. R. Kumar, M. Sandhiya, B. S. Kumar, H. Shyam, M. Yuvaraj

引用次数: 0

Image-based Classification of Skin Cancer using Convolution Neural Network 基于图像的卷积神经网络皮肤癌分类

2023 3rd International Conference on Intelligent Technologies (CONIT) Pub Date : 2023-06-23 DOI: 10.1109/CONIT59222.2023.10205738

Priotosh Mondal, Aditi Bhatia, Roshini Panjwani, Shrey Panchamia, Indu Dokare

{"title":"Image-based Classification of Skin Cancer using Convolution Neural Network","authors":"Priotosh Mondal, Aditi Bhatia, Roshini Panjwani, Shrey Panchamia, Indu Dokare","doi":"10.1109/CONIT59222.2023.10205738","DOIUrl":"https://doi.org/10.1109/CONIT59222.2023.10205738","url":null,"abstract":"Skin cancer is a category or collection of cancer affecting the tissues and layers of skin. Skin cancer is classified into several types depending on the type of cell it affects. These types include melanoma, melanocytic nevus, basal cell carcinoma, benign keratosis, actinic keratosis, dermatofibroma, vascular lesion, and squamous cell carcinoma. Melanoma which affects the melanocytes and is considered to be the most fatal and deadly cancer, is growing at an alarming rate, especially in the western hemisphere and the Pacific region. The proposed system contained a web-based application where the image of an affected skin area can be uploaded and the likelihood of skin cancer is displayed. This system has used a convoluted neural network (CNN) based binary and multi-classification model making efficient use of image processing, computer vision, OpenCV, and Python to classify dermatoscopic lesion images into cancerous and non-cancerous along with their types. The implemented binary classifier achieves an accuracy of 92%. Further, the multi-class classification model is implemented based on CNN to classify dermatoscopic cancerous lesion images into nine types which achieved an accuracy of 97%. Among nine classes one of the classes is non-cancerous. The models aim to provide a means of diagnostic tool that will help in the preliminary diagnosis of skin lesions. Early detection and diagnosis are appropriate measures to combat the spread and lethality of skin cancer.","PeriodicalId":377623,"journal":{"name":"2023 3rd International Conference on Intelligent Technologies (CONIT)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114367492","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

Detection and Classification of Diabetic and Hypertensive Retinopathy Using CNN & Autoencoder 用CNN和自编码器检测和分类糖尿病和高血压视网膜病变

2023 3rd International Conference on Intelligent Technologies (CONIT) Pub Date : 2023-06-23 DOI: 10.1109/CONIT59222.2023.10205818

Amardeep Singh Kapoor, Akshat Jain, D. Vishwakarma

引用次数: 0