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7th International Conference on Soft Computing: Theories and Applications, SoCTA 2023

作者： Prakash, Vijay Aggarwal, Venu Yadav, Rajesh Garg, Lalit Singh, Pardeep School of Computer Science University of Petroleum and Energy Studies Dehradun India Department of Computer Information Systems University of Malta Msida Malta Department of Computer Science & Engineering Graphic Era Hill University Dehradun India

ISBN: (纸本)9789819720309

With the increasing need for secure communication and storage of sensitive data in various formats like text, audio and images, there is a growing concern for protecting this information from unauthorized access or data breaches. Although encryption techniques are widely used for secure data transmission, they may not be sufficient for hiding data in plain sight. The proposed approach addresses the challenge of securing sensitive data in text, audio and image formats by implementing robust steganography and encryption techniques while ensuring seamless data storage and data monitoring in cloud storage platforms like Amazon S3. The proposed approach utilizes the least significant bit (LSB) steganography method, where the least significant bit of each pixel or sample in the media is replaced with a bit of the personal data, ensuring minimal visual or audible changes. The proposed approach will be designed to embed secret messages into carrier data using steganography algorithms and encrypt the resulting data using a symmetric key. The encrypted data will be stored in an Amazon S3 bucket for secure storage, and the entire bucket will be monitored using Dynatrace for performance and security analysis. The proposed approach received 90% of security breaches, indicating the monitoring system is highly accurate. Further, the approach could reduce the response time from 5 to 2 s and increase the throughput from 100 requests per second to 500 requests per second. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Steganography

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A Practical Embedded System Utilizing Artificial Intelligence Technology 4

A Practical Embedded System Utilizing Artificial Intelligenc...

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4th International Multidisciplinary Information Technology and engineering Conference, IMITEC 2024

作者： Molapo, Makhabane Tu, Chunling Du Plessis, Deao Du, Shengzhi Tshwane University of Technology Computer Systems Engineering Pretoria South Africa Tshwane University of Technology Computer Science Department Pretoria South Africa

ISBN: (纸本)9798350387988

Thereis a clear and present lethal clash between South Africa's wildlife and its expanding population. Some of its main effects are harm to people and property. Fatalities, crop damage, livestock threads, and habitat devastation. We are inspired by the need for data-driven approaches in artificial intelligence in today's technologies. We have built an embedded system called 'SmartFarmApp' by leveraging datasets for object detection. This system capably serves as the backbone of computer vision models by focusing on detecting and classifying livestock according to their classes using the Florence 2 AI (Artificial Intelligence) model. We have livestock of interest and wild animals as a threat to our livestock and if wild animals are around this class label the message for security concern must be raised. This system utilizes the Florence 2 AI vision-language model developed by Microsoft that excels in various vision tasks, including object detection where we use object detection Application programmable Interfaces (APIs) to do detection for this system in a realistic outdoor environment. However, Florence 2 as vision tasks it does not support Object tracking, so we improved Florence 2 model to work by allowing tracking. Florence 2 model feeds our system, while built-in Raspberry Pi devices equipped with cameras feed this system in real-time using the mobile application to remotely view daily activities in our farms. © 2024 IEEE.

关键词： Livestock

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Enhanced Adaptive Brain-computer Interface Approach for Intelligent Assistance to Disabled Peoples

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computer systems science & engineering 2023年第8期46卷 1355-1369页

作者： Ali Usman Javed Ferzund Ahmad Shaf Muhammad Aamir Samar Alqhtani Khlood M.Mehdar Hanan Talal Halawani Hassan A.Alshamrani Abdullah A.Asiri Muhammad Irfan Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajran61441Saudi Arabia Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Radiological Sciences Department College of Applied Medical Sciences and Information SystemsNajran UniversityNajran61441Kingdom of Saudi Arabia Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia

Assistive devices for disabled people with the help of Brain-computer Interaction(BCI)technology are becoming vital bio-medical *** with physical disabilities need some assistive devices to perform their daily *** these devices,higher latency factors need to be addressed ***,the main goal of this research is to implement a real-time BCI architecture with minimum latency for command *** proposed architecture is capable to communicate between different modules of the system by adopting an automotive,intelligent data processing and classification ***-sky mind wave device has been used to transfer the data to our implemented server for command ***-Net Convolutional Neural Network(TN-CNN)architecture has been proposed to recognize the brain signals and classify them into six primary mental states for data *** collection and processing are the responsibility of the central integrated server for system load *** of implemented architecture and deep learning model shows excellent *** proposed system integrity level was the minimum data loss and the accurate commands processing *** training and testing results are 99%and 93%for custom model implementation based on *** proposed real-time architecture is capable of intelligent data processing unit with fewer errors,and it will benefit assistive devices working on the local server and cloud server.

关键词： Disable person electroencephalogram convolutional neural network brain signal classification

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Fostering Digital Innovation in Indonesia: The Role of STEM-AI Skills in Overcoming Talent Deficits and Gender Stereotypes 4

Fostering Digital Innovation in Indonesia: The Role of STEM-...

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4th International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024

作者： Halim, Erwin Zahra, Amalia Maryani Wulandhari, Lili Ayu Fitrianah, Devi Puspita, Virienia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Communication Department Jakarta11480 Indonesia

ISBN: (纸本)9798331506490

This research explores the optimization of digital talent in advanced industries, particularly in the context of rapid digital transformation. Despite the increasing importance of digital talent for gaining a competitive edge, several challenges persist. In Indonesia, for example, there is a significant shortage of digitally skilled workers, with the World Bank reporting a gap of 9 million skilled individuals over the past 15 years. Additionally, artificial intelligence (AI) is expected to impact 9.5 million jobs, further exacerbating the demand for digital skills. Furthermore, the employability of graduates remains low, largely due to inadequate training, poor language proficiency, and limited cultural sensitivity. Many companies face difficulties in finding qualified individuals, quickly upskilling their workforce, and fostering an innovative organizational culture. This study seeks to evaluate the factors influencing digital talent performance in the context of these challenges. It examines seven key variables: digital readiness, digital technology adoption, relevance of AI, digital skills, individual performance, problem-solving ability, and overall digital talent performance. Hypotheses were tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). Data was collected from 378 participants, primarily students with STEM backgrounds, in the Jabodetabek area of Indonesia in November 2024. The findings reveal that all hypotheses are significant, with results indicating that user satisfaction and the perceived value of digital talent in Indonesia have a notable impact on continued usage intentions in digital roles. © 2024 IEEE.

关键词： digital readiness digital talent performances digital technology individual performance STEM-AI

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SeRTS: Self-Rewarding Tree Search for Biomedical Retrieval-Augmented Generation

SeRTS: Self-Rewarding Tree Search for Biomedical Retrieval-A...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Hu, Minda Zong, Licheng Wang, Hongru Zhou, Jingyan Li, Jingjing Gao, Yichen Wong, Kam-Fai Li, Yu King, Irwin Department of Computer Science and Engineering Hong Kong Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9798891761681

Large Language Models (LLMs) have shown great potential in the biomedical domain with the advancement of retrieval-augmented generation (RAG). However, existing retrieval-augmented approaches face challenges in addressing diverse queries and documents, particularly for medical knowledge queries, resulting in sub-optimal performance. To address these limitations, we propose a novel plug- and-play LLM-based retrieval method called Self-Rewarding Tree Search (SeRTS) based on Monte Carlo Tree Search (MCTS) and a self-rewarding paradigm. By combining the reasoning capabilities of LLMs with the effectiveness of tree search, SeRTS boosts the zero-shot performance of retrieving high-quality and informative results for RAG. We further enhance retrieval performance by fine-tuning LLMs with Proximal Policy Optimization (PPO) objectives using the trajectories collected by SeRTS as feedback. Controlled experiments using the BioASQ-QA dataset with GPT-3.5-Turbo and LLama2-7b demonstrate that our method significantly improves the performance of the BM25 retriever and surpasses the strong baseline of self-reflection in both efficiency and scalability. Moreover, SeRTS generates higher-quality feedback for PPO training than self-reflection. Our proposed method effectively adapts LLMs to document retrieval tasks, enhancing their ability to retrieve highly relevant documents for RAG in the context of medical knowledge queries. This work presents a significant step forward in leveraging LLMs for accurate and comprehensive biomedical question answering. © 2024 Association for Computational Linguistics.

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Sell and Buy Homegrown Vegetables and Fruits Online Using E-Commerce UML Algorithm

Sell and Buy Homegrown Vegetables and Fruits Online Using E-...

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2023 International Conference on Intelligent systems for Communication, IoT and Security, ICISCoIS 2023

作者： Preethi, C. Saran, V.S. Shree Meikannan, M. Hammed, S.Shahul Haripriya, K. Kumar, B.Arun PSNA College of Engineering and Technology Department of Computer Science and Business Systems Dindigul India Sri Krishna College of Engineering and Technology Department of Computer Science and Business Systems Dindigul India

ISBN: (纸本)9798350335835

E-commerce, also known as electronic commerce or internet commerce, refers to the exchange of money and data for the purpose of business operations through the internet. The term 'ecommerce' is commonly used to refer to the online sale of tangible goods, but it may also refer to any type of commercial transaction made possible via the internet. It is nowadays one of the most important components of the internet. Electronic commerce is the process of conducting business using computer networks. An individual sitting in front of a computer may use all of the Internet's resources to purchase or sell things. E-commerce, which began in the early 1990s, has made enormous strides in the world of computers. B2B e-commerce is used to increase the usage of e-commerce in developing nations by enhancing access to global markets for enterprises in developing countries. Regardless of the rapid growth of technology, e-commerce has reached its apex. This article proposes a novel application concept. It describes the public's needs for M-Commerce, as well as the analysis and literacy survey of essential components of mobile devices that use such apps. The design and security of the application are both carefully studied. This study examines the characteristics and possibilities of a mobile E-App for selling and purchasing fresh vegetables. The outcomes demonstrate how the application has impacted the public, employment, and long-Term growth. © 2023 IEEE.

关键词： Developing countries

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Relevance Classification of Flood-related Twitter Posts via Multiple Transformers

Relevance Classification of Flood-related Twitter Posts via ...

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2022 MediaEval Workshop, MediaEval 2022

作者： Mukhtiar, Wisal Rizwan, Waliiya Habib, Aneela Afridi, Yasir Saleem Hasan, Laiq Ahmad, Kashif Department of Computer Systems Engineering University of Engineering and Technology Peshawar Pakistan Department of Computer Science Munsters Technological University Cork Ireland

In recent years, social media has been widely explored as a potential source of communication and information in disasters and emergency situations. Several interesting works and case studies of disaster analytics exploring different aspects of natural disasters have been already conducted. Along with the great potential, disaster analytics comes with several challenges mainly due to the nature of social media content. In this paper, we explore one such challenge and propose a text classification framework to deal with Twitter noisy data. More specifically, we employed several transformers both individually and in combination, so as to differentiate between relevant and non-relevant Twitter posts, achieving the highest F1-score of 0.87. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Disasters

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A Robust Automated Framework for Classification of CT Covid-19 Images Using MSI-ResNet

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computer systems science & engineering 2023年第6期45卷 3215-3229页

作者： Aghila Rajagopal Sultan Ahmad Sudan Jha Ramachandran Alagarsamy Abdullah Alharbi Bader Alouffi Department of Computer Science and Business Systems Sethu Institute of TechnologyKariapattiVirudhunagar626115TamilnaduIndia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharj11942Saudi Arabia Department of Computer Science and Engineering School of EngineeringKathmandu UniversityBanepaKathmanduNepal Department of CSE University College of EngineeringPanrutiTamilnaduIndia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Nowadays,the COVID-19 virus disease is spreading *** are some testing tools and kits available for diagnosing the virus,but it is in a lim-ited *** diagnose the presence of disease from radiological images,auto-mated COVID-19 diagnosis techniques are *** enhancement of AI(Artificial Intelligence)has been focused in previous research,which uses X-ray images for detecting *** most common symptoms of COVID-19 are fever,dry cough and sore *** symptoms may lead to an increase in the rigorous type of pneumonia with a severe *** medical imaging is not suggested recently in Canada for critical COVID-19 diagnosis,computer-aided systems are implemented for the early identification of COVID-19,which aids in noticing the disease progression and thus decreases the death ***,a deep learning-based automated method for the extraction of features and classi-fication is enhanced for the detection of COVID-19 from the images of computer tomography(CT).The suggested method functions on the basis of three main pro-cesses:data preprocessing,the extraction of features and *** approach integrates the union of deep features with the help of Inception 14 and VGG-16 *** last,a classifier of Multi-scale Improved ResNet(MSI-ResNet)is developed to detect and classify the CT images into unique labels of *** the support of available open-source COVID-CT datasets that consists of 760 CT pictures,the investigational validation of the suggested method is *** experimental results reveal that the proposed approach offers greater performance with high specificity,accuracy and sensitivity.

关键词： Covid-19 CT images multi-scale improved ResNet AI inception 14 and VGG-16 models

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Recent Trends for Text Summarization in Scientific Documents 9

Recent Trends for Text Summarization in Scientific Documents

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9th IEEE International Conference on Computing, engineering and Design, ICCED 2023

作者： Sukmandhani, Arief Agus Arifin, Yulyani Zarlis, Muhammad Budiharto, Widodo Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Information Systems Management Information Systems Management Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350370126

Text summarization is a natural language processing (NLP) technique in artificial intelligence that has been studied in recent years. Every document containing text is tested to get a good summary result. In producing a good summary, proper accuracy is required;therefore, various techniques and methods are used, and another challenge is the use of language in the documents being tested. Various types of documents have been used as research for text summarization, including scientific documents, so researchers are interested in studying them more intensely to get the state of the art in research. This research was conducted to review previous research using literature studies from various publications that published research on text summarization in scientific documents. The researcher collected data from several publishers who had published this type of research from 1988 to 2023 quarter 1 and obtained three hundred and eleven articles, then the researcher analyzed the data using the Kitchenham method to get the right literature to answer the research question. Thirty-seven articles were selected for further in-depth analysis. In addition, the researcher found some interesting findings beyond the research question, including other techniques used to solve the text summarization problem and other types of output that are not commonly produced so that it can increase knowledge in researching text summarization. © 2023 IEEE.

关键词： Text processing

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AI Based Innovative Approach on Precision Agriculture Using IoT

AI Based Innovative Approach on Precision Agriculture Using ...

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International Conference on computer Vision and Internet of Things 2023, ICCVIoT 2023

作者： Priyanka, G. Anandakumar, H. Department of Computer Science and Business Systems Sri Eshwar College of Engineering Coimbatore India Department of Computer Science and Engineering Sri Eshwar College of Engineering Coimbatore India

ISBN: (纸本)9781839539848

In this paper, Precision agriculture uses the latest technology like the IOT and Artificial Intelligence to achieve more productivity and better resource utilization than traditional ways, resulting in lower costs and higher yields. The main objective of Precision farming is primarily based on viewing, estimating, and reacting to inter field and intra field interactions of crop with a lot of variation. Wireless technologies have recently advanced to the point that they can now be employed for diversified environmental monitoring applications. Sensors assist farmers in properly utilizing all available resources and applying hazardous goods in a controlled manner. The fusion of AI and IoT in precision agriculture offers a transformative solution that empowers farmers to make data-driven decisions, increase productivity, and mitigate environmental challenges. © The Institution of engineering & Technology 2023.

关键词： Big data

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