International Journal of Scientific Research in Computer Science, Engineering and Information Technology最新文献

{"title":"The Emotion Analysis of Indian Political Tweets using Machine Learning","authors":"Parth Sharma, Mansi Vegad","doi":"10.32628/cseit2410255","DOIUrl":"https://doi.org/10.32628/cseit2410255","url":null,"abstract":"In this day and age web-based entertainment is a major region for information examination and exploration work. For Feeling Examination, I select Tweeter handle. I use Tweepy for getting to tweeter information. I perform opinion examination on Indian Political information. I got 117545 tweets of 2019 Indian Political race. I use SVM (Backing Vector Machine) Classifier for feeling Examination. Feeling assessment oversees recognizing and portraying evaluations or sentiments conveyed in source message. Electronic diversion is creating an enormous proportion of feeling rich data as tweets, sees, blog sections, etc. Feeling examination of this client made data is especially useful in knowing the appraisal of the gathering. Twitter feeling assessment is problematic stood out from general assessment examination on account of the presence of work related conversation words and erroneous spellings. The most outrageous limitation of characters that are allowed in Twitter is 140. Data base philosophy and AI approach are the two frameworks used for separating suppositions from the text. In this paper, we endeavor to analyze the twitter posts about electronic things like mobiles, workstations, etc using AI approach.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"83 S3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140709461","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}

{"title":"Survey on Concept of Object-Oriented Programming","authors":"Mansi Dhirajsinh Parmar, Sarthavi Parmar","doi":"10.32628/cseit243647","DOIUrl":"https://doi.org/10.32628/cseit243647","url":null,"abstract":"These days, object-oriented programming is regarded as an essential programming concept.The moment Simula brought it into life. The use of object-oriented programming (OOP) has expanded in the software real world due to the future growth of the software business and the advancement of software engineering.\u0000The following review examines different oop concepts that are essential to object-orientation, in great detail. Many widely used object-oriented programming languages implement various parts of inheritance and polymorphism. We come to the conclusion that much more work needs to be done to find a middle ground so that these can accomplish OOPs features.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"43 9-10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140735146","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}

{"title":"Dockerized Application with Web Interface","authors":"Abhishek M Nair, Sivaiswarya CK, Sidharth S, Visakh KK, Jibin Joy","doi":"10.32628/cseit243646","DOIUrl":"https://doi.org/10.32628/cseit243646","url":null,"abstract":"Developing an application can be a task if any kind of conflict arises during deploying the code or while running them and it can be due to the storage or the code being not supported by the other party’s system. Thus to provide a solution for this matter, we are introducing the project concept of Dockerized application deployment through a web interface. This proposed project combines the efficiency of Docker containers with a web interface to create a platform for running and managing applications easily. When a programmer or a developer or anyone in the field of programming has conflict in uploading, running or deploying their application code from another programmer’s system to their own due to the inefficiency or lack of facilities in their system, they can use this web interface as a solution. Especially during the time of any rush, they can opt for this web interface as it does not require the installation of a local Docker software and any extra dependency management, as installation of Dockers are a bit time lagging. One of the main factors of this project is that this web interface can be run in any kind of computer system without any extra facilities being added to it. Whether the system is less efficient or high efficient regardless of the type of the system, this web interface is easy to access for the users. Users can upload their application code, build Docker images, and run them directly from the web interface. With the advantage of Docker’s utility methodologies for shipping, testing and deploying code, you can reduce the delay between writing codes and running applications .It has additional features like users can define environment variables for their applications, configure network settings for container communication ,mount persistent volumes to store application data with help of virtual cloud, implement user roles and permissions for secure access control .The front end of the web page is created using NEXT Programming Language meanwhile the backend is applied using NEXT, Docker and Python Flask API. About NEXT Programming Language that in this language, when the front-end is applied the backend function gets directly deployed making us use less effort in creating the webpage. It's a newly created advanced programming language. Overall, this Dockerized application deployment web-interface offers a user-friendly and efficient solution for developers, system administrators, and DevOps teams, streamlining the application development and deployment process.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"20 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140734573","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}

{"title":"The Evolving Threat Landscape: How Cyber Threat Intelligence Empowers Proactive Defenses against WannaCry Ransomware","authors":"Jumoke Eluwa, Patrick Omorovan, Dipo Adewumi, Oluwafunmilayo Ogbeide","doi":"10.32628/cseit243648","DOIUrl":"https://doi.org/10.32628/cseit243648","url":null,"abstract":"Cyber threat intelligence (CTI) is a rapidly growing field that plays an essential role in ensuring the security of online systems. CTI refers to the intelligence that is gathered, analyzed, and disseminated to help organizations understand and respond to cyber threats. This information can be used to identify vulnerabilities, detect potential attacks, and develop strategies to mitigate risks. The field of CTI is constantly evolving, as cyber threats become more sophisticated and complex. Legacy security measures like firewalls and anti-virus software are no longer enough to protect organizations from the many threats they face. CTI provides a proactive approach to cybersecurity, by enabling organizations to anticipate and prepare for threats before they occur. CTI relies on the collection and analysis of data from multiple sources, such as open-source intelligence (OSINT), dark web forums, social media, and other threat intelligence streams. The data is analyzed using a wide range of tools and techniques, including machine learning and artificial intelligence, to identify patterns and trends that may indicate a potential threat. One of the key benefits of CTI is its ability to help organizations understand the tactics, techniques, and procedures of attackers. By analyzing the behaviors, strategies, tactics, and actions of threat actors, organizations can develop a more comprehensive understanding of the threats they face and can better prepare for potential attacks.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"79 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140747393","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}

{"title":"Advanced Machine Learning Techniques for Liver Tumor Classification in MRI Imaging","authors":"Jalpaben Kandoriya, Dr.Sheshang Degadwala","doi":"10.32628/cseit2410233","DOIUrl":"https://doi.org/10.32628/cseit2410233","url":null,"abstract":"In this research into liver tumor categorization within MRI images, diverse machine learning methodologies were scrutinized for their efficacy. The study delved into the integration of shape and texture features, aiming to bolster classification accuracy. Among the algorithms explored, the Extra Trees model emerged as the most promising contender, exhibiting superior performance compared to its counterparts. Leveraging the distinctive capabilities of the Extra Trees model, the study underscored its effectiveness in accurately categorizing liver tumors. This highlights its potential to enhance diagnostic precision in clinical contexts. Through rigorous experimentation and analysis, the research elucidated the significance of incorporating shape and texture features into machine learning frameworks for improved tumor classification. The findings not only contribute to advancing the field of medical imaging but also underscore the importance of leveraging innovative methodologies to address healthcare challenges. Overall, the study sheds light on the promising prospects of employing advanced machine learning techniques in medical imaging for more accurate and efficient diagnosis of liver tumors.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"531 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140749758","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}

{"title":"A High-Speed Floating Point Matrix Multiplier Implemented in Reconfigurable Architecture","authors":"Atri Sanyal, Ashika Jain, Anwesha Dey, Prakash Kumar Gupta","doi":"10.32628/cseit2390661","DOIUrl":"https://doi.org/10.32628/cseit2390661","url":null,"abstract":"Matrix multiplication is a fundamental operation in computational applications across various domains. This paper introduces a novel reconfigurable co-processor that enhances the efficiency of matrix multiplication by concurrently executing addition and multiplication operations upon matrix elements of different sizes. The proposed design aims to reduce computation time and improve efficiency for matrix multiplication equations. Experimental evaluations were conducted on matrices of different sizes to demonstrate the effectiveness of the processor. The results reveal substantial improvements in both time and efficiency when compared to traditional approaches. The reconfigurable transformation processor harnesses parallel processing capabilities, enabling the simultaneous execution of addition and multiplication operations by partitioning input matrices into smaller submatrices and performing parallel computations, thus the processor achieves faster results. Additionally, the design incorporates configurable arithmetic units that dynamically adapt to matrix characteristics, further optimizing performance. The experimental evaluations provide evidence of reduction in computation time and improvement in efficiency. present significant benefits over traditional sequential methods. This makes this co-processor ideally fit for domains that require intensive linear algebra computations such as computer vision, machine learning, and signal processing.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140225905","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}

{"title":"IoT Empowered Harvest: Advancing NFT Hydroponics with Smart Agricultural Automation","authors":"Trupti Ghate, Kalpana Malpe","doi":"10.32628/cseit241025","DOIUrl":"https://doi.org/10.32628/cseit241025","url":null,"abstract":"For every nation, farmers play the most essential role and that is to feed the population. In the urban areas there is lack of open green space for farming and even if the land is available it is infertile for plants to grow on them. Problems faced in urban areas farms are due to the toxic elements let in the soil. The sources of toxic metals and effluents in urban soils are mainly from emissions from industries, automobiles, industrial as well as domestic sewage. In urban areas, people are busy in their work which leads them to buy pesticide and chemically treated food which in injurious to health and they are unable to grow organic vegetable at home due to deficit of space, time and un-fertile soil. \u0000Hydroponics is the method of cultivating plants without soil. Water with oxygen and required minerals acts as the cultivation medthod. Smart Hydroponic Farming using the NFT Method helps the farmer to stay connected to their farm anytime and anywhere. This hydroponic system requires special attention to several parameters such as the water temperature, water level, acidity (pH), and the concentration of the nutrient (EC/PPM). We first monitor and collect information from NFT Hydroponic farmer and then systematically evaluate and analyze them. Unfortunately, it is still controlled by using the conventional way (human), for example in controlling the concentrations of nutrient has to be done at least once a day, so much time is wasted. In addressing these issues, we need a system that can be applied and used easily. \u0000We built a hydroponic monitoring and automation system that can monitored using sensors connected to the Arduino Uno microcontrollerm, Wi-Fi module ESP8266 and Raspberry Pi 2 Model B microcomputers as the webserver with the concept Internet of Things, in which each block hydroponic farming can communicate with the webserver (broker). Web used as the interface of the system that allows user to monitor and control the NFT hydroponic farming. The NFT hydroponic web interface management systems using a responsive web framework, such as Bootstrap for the front-end, JQuery and JavaScript libraries. The result shows that this system helps farmers to increase the effectivity and efficiency on monitoring and controlling NFT Hydroponic Farm.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"190 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140235710","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}

{"title":"Road Accident Severity Detection In Smart Cities","authors":"Deeksha K, Kavya S, Nikita J, E. R. C, E. R. C","doi":"10.32628/cseit241024","DOIUrl":"https://doi.org/10.32628/cseit241024","url":null,"abstract":"Ensuring safety, in cities is a focus in the development of urban areas requiring new and creative methods for categorizing and managing accidents. Traditional approaches often face challenges in evaluating accident seriousness within changing city environments. This research utilizes Long Short Term Memory (LSTM) and Convolutional Neural Network (CNN) techniques to create a system that categorizes accidents into three severity levels; minor, moderate and severe. By leveraging learning capabilities, our method boosts the precision and efficiency of safety protocols in cities. The outcomes exhibit promising results in categorizing accident severity offering a tool for enhancing urban safety infrastructure. Through empowering cities to handle accidents, our model establishes a foundation for safety initiatives. In essence, this study contributes to enhancing safety standards in cities promoting resilience and sustainability, within settings.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"122 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140235997","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}

{"title":"Safety Measure Detection Using Deep Learning","authors":"Tejas Bagthaliya, Vaidehi Shah, Shubham Shelke, Devang Shukla, Yatin Shukla","doi":"10.32628/cseit2490216","DOIUrl":"https://doi.org/10.32628/cseit2490216","url":null,"abstract":"This implementation is for a computer vision application that detects individuals and verifies their compliance with safety gear regulations, such as safety jackets and hard-hats. The system counts the number of individuals violating safety standards and keeps track of the total number of individuals detected. The system uses advanced image processing techniques, including object detection and classification, to accurately identify the presence or absence of safety gear. The user interface provides real-time analysis of the data, with the option to alert the user of any violations. This implementation is a valuable tool for organizations looking to ensure the safety of their employees and customers, providing a comprehensive solution for monitoring compliance with safety regulations. It can also be used to analyze trends and identify areas for improvement, making it an essential tool for safety professionals and facilities managers.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"15 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140239220","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}

{"title":"YAATRIASSIST : Passenger Facilitation Using AI and ML","authors":"Ankit Dilip Nihalchandani, Shivang Deepak Kulshrestha, Raj Kirit Lakhani, Deepak Pandagre, Rachit Adhvaryu","doi":"10.32628/cseit2490219","DOIUrl":"https://doi.org/10.32628/cseit2490219","url":null,"abstract":"YaatriAssist is a revolutionary travel application that reimagines global adventures with unmatched convenience and sophistication. This innovative app integrates essential functionalities seamlessly, offering real-time GPS navigation for confident exploration and integrated weather updates for preparedness in diverse climates. It features a comprehensive travel log for capturing and cherishing memories, along with an optimized scheduler to maximize trip enjoyment. The curated news hub keeps travelers informed about local events and global developments, while Travel mate fosters connections between fellow explorers, enhancing journey richness. Language barriers are effortlessly overcome with translation and OCR functionalities. Customizable settings ensure personalized experiences, evolving with individual travel needs. Facilitating bookings for flights, accommodations, and activities directly through the app streamlines trip management, offering unparalleled convenience. In summary, YaatriAssist stands as the epitome of travel convenience, catering to both seasoned globetrotters and business travelers, empowering users to navigate, explore, and engage with the world confidently and effortlessly.","PeriodicalId":313456,"journal":{"name":"International Journal of Scientific Research in Computer Science, Engineering and Information Technology","volume":"15 59","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140237641","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}