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5th International Conference on Data science, Machine Learning and applications, ICDSMLA 2023

作者： Goyal, Manish Kumar Shahid, Mohammad Karthikeyan, M.P. Kumar, Ritesh Department of Computer Science & Application Vivekananda Global University Jaipur India Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

Clinical imaging techniques such as X-ray, Magnetic Resonance Imaging (MRI), and laptop Tomography (CT) scanners are used to diagnose, compare, and deal with sufferers. Automatic Anomaly Detection is an automatic technique for identifying and diagnosing abnormalities in clinical imaging. It has been diagnosed that Support Vector Machines (SVM) can be effectively used to generate correct automatic anomaly detection for scientific imaging. SVM is an approach that uses supervised getting-to-know to create a choice boundary between classes, with the decision primarily based on the information to be had. The gain of SVM is that it plays an automatic function extracting from the medical imaging facts and uses those extracted capabilities for anomaly detection. It combines photograph segmentation and classification to classify the abnormal regions in an image. So one can enhance the accuracy of SVM;it's miles viable to use an expansion of kernel capabilities and unique parameter tuning. Moreover, introducing an automatic pipeline from training to deploying SVM reduces the efforts of manual feature extraction from photos. Consequently, aid Vector Machines is a feasible approach for automatic anomaly detection in scientific imaging. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image segmentation

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Using Asynchronous Frameworks and Database Connection Pools to Enhance Web application Performance in High-Concurrency Environments 8

Using Asynchronous Frameworks and Database Connection Pools ...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Ju, Lei Yadav, Amit Khan, Asif Sah, Abhishek Pratap Yadav, Dakshina Chengdu Neusoft University College of Intelligent Science and Engineering Chengdu China Charles Darwin University College of Engineering It and Environment NT Australia Integral University Department of Computer Application Lucknow India University of Electronic Science and Technology of China School of Management Science and Engineering Chengdu China Plant Industry Department of Industry Tourism and Trade Line Darwin Australia

ISBN: (纸本)9798350376425

Modern web applications are experiencing exponential expansion in terms of the number of users and data volume, which puts increased demand on the system's capacity for high concurrent processing. This paper aims to explore the use of asynchronous frameworks and database connection pools in high-concurrency environments to significantly enhance the performance of web applications. Asynchronous framework enables applications to handle requests in a non-blocking manner, effectively releasing thread resources and improving the system's concurrency processing capability. Simultaneously, database connection pool optimizes the management of database connections resulting in reduced overhead of connection creation and destruction, thereby alleviating the burden on the database. This paper elucidates the significant impact of adopting asynchronous frameworks and database connection pools on improving system performance. The design adopts Springer WebFlux, an asynchronous framework, along with the proper configuration and utilization of database connection pool design, which exhibits lower average response time, higher throughput, better stability, and outstanding performance in high-concurrency scenarios. The developed model is tested, and it exhibits better results than synchronous models and outperforms asynchronous models without connection pool. This research holds practical guidance for enhancing web application performance and optimizing user experience. © 2024 IEEE.

关键词： Database systems

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Health Fit system in Current Era using React JS 5

Health Fit system in Current Era using React JS

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5th IEEE International Conference on Advances in Electronics, computers and Communications, ICAECC 2023

作者： Bhatt, Chandradeep Negi, Ayush Singh Chauhan, Rahul Bhatt, Pashupati Singh, Teekam Sharma, Sanjay Graphic Era Hill University CSE Department Dehradun India Computer Science and Engineering Graphic Era Hill University Dehradun India Institute of Technology & Management Department of Information Technology Uttarakhand India Computer Science and Engineering Graphic Era Deemed to Be University Dehradun India SGRRITS Computer Application Department Dehradun India

ISBN: (纸本)9798350305449

The purpose of this system is to update the existing systems with the help of computer technology (i.e. to improve the API's which current systems lacked a lot) and the best computers to meet their needs, so that valuable information/data can be stored for a longer period of time and made it easily accessible and functional. Software and hardware should be simple and easy to use. As mentioned above, the Gym fit system provides error free, safe, secure and fast administration. It helps users focus on other activities rather than focusing on data storage. Therefore, it will help the organization make better use of resources. Organizations can store information on computers without further access. This means that people can access information without being hindered by irrelevant information. The aim is to keep the best computers information to make the current book uses with the help of computer hardware and to meet their needs / useful information can be stored for a longer time and easily accessed and used. Basically, the work describes how to manage to achieve quality and serve customers better. © 2023 IEEE.

关键词： Digital storage

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Robotic Process Automation for Automating Business Processes: A use case 7

Robotic Process Automation for Automating Business Processes...

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7th International Conference on Computing Methodologies and Communication, ICCMC 2023

作者： Bhardwaj, Vivek Virender Kumar, Mukesh Thakur, Deepak Lamba, Vikas School of Computer Science and Engineering Lovely Professional University Jalandhar India Chandigarh University Punjab India School of Computer Application Lovely Professional University Jalandhar India Chitkara University Institute of Engineering and Technology Chitkara University Punjab 140401 India

ISBN: (纸本)9781665464086

Numerous advances and changes have been brought about by digitalization in both our daily lives and the business world. RPA is an all-purpose technology for developing specialized agents, or "bots," that communicate with GUI components to carry out routine, rule-based operations. Anyone can utilize the RPA to automate digital operations. RPA deployment in business processes can help to provide better service and guarantee that processes adhere to more efficiency and accuracy. The objective of this study is to enable human workers to assign their regular generic repetitive tasks to a software bot, freeing them up to concentrate on more challenging and difficult activities. This study presents a methodology for implementing RPA to extract employee information from the XMLpages. © 2023 IEEE.

关键词： Automation Anywhere Business Processes RPA Software BOT

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Unlocking the Power of Natural Language Processing to Automate Knowledge Discovery 3

Unlocking the Power of Natural Language Processing to Automa...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Ravikumar, V. Kodmelwar, Manohar K. Adlin Jebakumari, S. Shekhawat, Jyoti Sakhare, Nitin N. Vijayalakshmi, V.J. Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Chennai India Vishwakarma Institute of Information Technology Department of Information Technology Pune India Department of Computer Science and Information Technology Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore India

ISBN: (纸本)9798350319125

natural language processing (NLP) is an increasing number of powerful tools for knowledge discovery, permitting companies to automate techniques like textual content analysis and sentiment analysis that used to require big manual effort. NLP helps the automation of tasks inclusive of information person intent, comprehending textual content, extracting records, producing summaries, and classifying documents. With NLP, those duties can be achieved in a fraction of the time with some distance extra accuracy and without the want for manual processing. By way of leveraging present technology, companies can liberate the energy of NLP to automate knowledge discovery and substantially improve their aggressive advantage. © 2023 IEEE.

关键词： automation information substantially summaries techniques

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Improving Medical Image Classification Through Transfer Learning and Meta Learning 5th

Improving Medical Image Classification Through Transfer Lear...

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5th International Conference on Data science, Machine Learning and applications, ICDSMLA 2023

作者： Arora, Sonia Jebakumari, S. Adlin Singh, Vaishali Kharbas, Vikas Kumar Noida Institute of Engineering and Technology Uttar Pradesh Greater Noida India Karnataka Bangalore India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India Department of Computer Science and Application Vivekananda Global University Jaipur India

ISBN: (纸本)9789819780426

This paper presents an observation of improving clinical picture classification via transfer getting to know and meta-studying. Switching getting-to-know and meta-learning methods are usually employed in medical imaging class tasks. Transfer studying objectives to switch information and illustration from a properly-trained version and mildew that expertise to higher healthy the problem at hand, while meta-gaining knowledge is a version of switch gaining knowledge of which targets to seize and adapt the generalizable expertise of a project domain, and to allow a progressed impact for the goal tasks. Inside the clinical imaging scenario, the two procedures can dig deeper into the several layers which might be involved in gaining deep knowledge of algorithms. The authors compare the effectiveness of the proposed strategies in five publicly available medical imaging datasets. Effects have shown that the proposed techniques notably advanced the usual type accuracy for a few datasets. Furthermore, it was found that the 2-step technique showed higher performance than the one-step technique. This study presents a higher understanding of the efficacy of transfer learning and meta-mastering techniques for clinical photo-type tasks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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Leveraging Adaptive Algorithms for Real-Time Data Analysis 15

Leveraging Adaptive Algorithms for Real-Time Data Analysis

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Sahoo, Girija Shankar Hannah Jessie Rani, R. Goyal, Manish Kumar Mohammed, Vazeer Ali Jana, D Little Femilin Wasatkar, Namrata N. Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Electrical and Electronics Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Application Jaipur India Lewis University Illinois Department of Computer & Information System United States Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350370249

This paper proposes the use of adaptive algorithms for real-time data analysis. Adaptive algorithms are a set of practical methods used for acting information-driven optimization and studying. They have a wide variety of applications and may be implemented to a selection of facts analysis obligations. This paper offers an overview of existing adaptive algorithms and descriptions of several new programs in the area of actual-time facts analysis. In particular, the paper discusses the notion of adaptive thresholding, which allows for practical real-time evaluation of large datasets. The paper also provides a novel technique for making use of these algorithms in an online learning environment. Results from simulations illustrate the ability of the proposed method in real-international packages. Sooner or later, the paper presents numerous key lessons discovered and affords recommendations for future research and packages in this area. © 2024 IEEE.

关键词： Adaptive algorithms

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Bio-assembled smart nanocapsules for targeted delivery of KRAS shRNA and cancer cell bioimage

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Chinese Chemical Letters 2023年第1期34卷 270-273页

作者： Maonan Wang Zengchao Guo Jiayu Zeng Liu Liu Yihan Wang Jinpeng Wang Hongbing Lu Haijun Zhang Hui Jiang Xuemei Wang State Key Laboratory of Bioelectronics(Chien-Shiung Wu Lab) School of Biological Science and Medical EngineeringSoutheast UniversityNanjing 210096China Department of Biomedical Engineering/Computer Application Fourth Military Medical UniversityXi’an 710032China Department of Oncology Zhongda HospitalMedical School of Southeast UniversityNanjing 210009China

The five-year survival rate for pancreatic cancer is less than 5%. However, the current clinical multimodal therapy combined with first-line chemotherapy drugs only increases the patient’s median survival from 5.0 months to 7.2 months. Consequently, a new strategy of cancer treatments is urgently needed to overcome this high-fatality disease. Through a series of biometric analyses, we found that KRAS is highly expressed in the tumor of pancreatic cancer patients, and this high expression is closely related to the poor prognosis of patients. It shows that inhibiting the expression of KRAS has great potential in gene therapy for pancreatic cancer. Given those above, we have exploited the possibility of targeted delivery of KRAS shRNA with the intelligent and bio-responsive nanomedicine to detect the special oxidative stress microenvironment of cancer cells and realize efficient cancer theranostics. Our observations demonstrate that by designing the smart self-assembled nanocapsules of melanin with fluorescent nanoclusters we can readily achieve the bio-recognition and bioimaging of cancer cells in biological solution or *** self-assembled nanocapsules can make a significant bio-response to the oxidative stress microenvironment of cancer cells and generate fluorescent zinc oxide Nanoclusters in situ for targeted cell bioimaging. Moreover, it can also readily facilitate cancer cell suppression through the targeted delivery of KRAS shRNA and low-temperature hyperthermia. This raises the possibility to provide a promising theranostics platform and self-assembled nanomedicine for targeted cancer diagnostics and treatments through special oxidative stress-responsive effects of cancer cells.

关键词： Smart bio-responsive nanocapsules Intelligent nanomedicine shRNA KRAS Fluorescent bioimaging Oxidative stress response

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SVM-Guided Dynamic Routing for Post-Harvest Quality Preservation in Smart Warehouses with IoT 3

SVM-Guided Dynamic Routing for Post-Harvest Quality Preserva...

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3rd International Conference for Innovation in Technology, INOCON 2024

作者： Umamaheswari, K. Antony Joseph Rajan, D. Ramasamy, Jayabharathi Seeni, Senthil Kumar Meenakshi, R. Thamizhamuthu, R. VR. Siddhartha Engineering College Department of Electronics and Instrumentation Engineering Andhra Pradesh Vijayawada India Saveetha Institute of Medical and Technical Sciences Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Rmk College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Cognizant Technology Solutions Department of Mobile Application Development Buffalo GroveIL United States Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur Campus-Chengalpattu Tamil Nadu Chennai India

ISBN: (纸本)9798350381931

This research presents a new approach to smart warehouse quality preservation after harvest by combining the Internet of Things (IoT) with Support Vector Machine (SVM)-guided dynamic routing. Preserving the quality of harvested goods during storage and transportation is of utmost importance in today's agricultural supply chain. Critical characteristics like temperature and humidity are monitored using real-time data acquired from sensors via the IoT. It uses the SVM algorithm to optimize the items' route dynamically according to the changing environmental conditions. The adaptable and efficient flow of agricultural goods throughout the warehouse is guaranteed by this dynamic routing method, which is led by SVM decision-making. A number of aspects that impact quality preservation, the method lessen the possibility of degradation during transit and storage. The effectiveness of the suggested strategy is supported by simulation findings, which demonstrate better preservation of post-harvest quality in comparison to conventional approaches. Smart warehouses may benefit greatly from the combination of SVM and the IoT, which solves many problems in the agricultural supply chain and helps improve sustainable postharvest management. © 2024 IEEE.

关键词： Sensor networks

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Residual and Attention Mechanism-Based Network for Aluminum-Silicon Alloy Microstructure Image Classification 11

Residual and Attention Mechanism-Based Network for Aluminum-...

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11th International Conference on Information Systems and Computing Technology, ISCTech 2023

作者： Yang, Xiao Shen, Tao Yin, Jiancheng Liu, Yingli Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650093 China Kunming University of Science and Technology Yunnan Key Laboratory of Computer Technologies Application Kunming650500 China Kunming University of Science and Technology Faculty of Materials Science and Engineering Kunming650093 China

ISBN: (纸本)9798350342406

To enhance the accuracy of aluminum-silicon alloy microstructure image classification, we propose an aluminum-silicon alloy microstructure image classification model based on an improved residual network, incorporating attention mechanisms and multi-scale thinking. The model is built upon the ResNet18 architecture, utilizing enhanced basic residual blocks to select informative features. Additionally, a multi-scale attention module is incorporated into the network to fuse multi-scale features and further extract effective features. Experimental results on an aluminum-silicon alloy microstructure image classification dataset demonstrate that compared to the best-performing model currently available, the proposed model achieves an increase in classification accuracy, precision, recall, and F1 score by 3.17%, 0.74%, 5.53%, and 3.26%, respectively, reaching 94.97%, 96.39%, 93.97%, and 95.17%. These results indicate that the proposed model exhibits strong capabilities in classifying aluminum-silicon alloy microstructure images and can facilitate further research on the properties of aluminum-silicon alloys. © 2023 IEEE.

关键词： Image classification

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