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Impact of Machine Learning-Driven Predictive Models on Patient Outcomes in Modern Healthcare Systems 1

Impact of Machine Learning-Driven Predictive Models on Patie...

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1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Sharma, Madhuri Gautam, Rishikesh Kumar Shukla, Medhavi Kumar, Jitendra Singh, Ajay Pal Yaminipriya, S. CHRI Campus Dept. of Life Sciences Gwalior India Madhav University Dept. of Humanities & S.Science Pindwara India J.S. University Dept. of Computer Science Shikohabad India Lingayas Vidyapeeth Dept. of Pharmacy Faridabad India Dhanalakshmi Srinivasan College Dept. Biomedical Engineering Coimbatore India

ISBN: (纸本)9798350356816

Traditional healthcare systems often struggle to meet the diverse needs of patients, leading to inefficiencies and less-than-optimal outcomes. The integration of machine learning (ML) is transforming healthcare by focusing on value-based care and enabling personalized, effective treatments. Modern healthcare devices are equipped with applications that collect and store comprehensive patient data, forming the basis for ML-driven predictive *** research investigates the transformative impact of ML in healthcare, highlighting its ability to improve patient care and optimize resource allocation. A proposed predictive model utilizes patient data and key parameters to forecast diseases, leveraging extensive datasets from diverse populations. These tools empower healthcare providers to identify and manage high-risk cases proactively, improving outcomes while streamlining care delivery *** study also explores the broader implications of ML adoption in value-based healthcare systems. By emphasizing personalized and proactive interventions, it demonstrates how ML-powered models can revolutionize traditional practices. The integration of ML in healthcare offers efficient, patient-centric solutions, enhancing the responsiveness and capacity of healthcare systems to meet growing patient demands and address complex medical challenges effectively. © 2024 IEEE.

关键词： ML Modern healthcare Patient data Predictive models Value- based treatment

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Blockchain-Based Secure e-KYC Solution for Banking System 16

Blockchain-Based Secure e-KYC Solution for Banking System

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16th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2024

作者： Tabassum, Zoya Arsheen, Sobiya Ahmad, Khaleel Ozdemir, Gulcihan Maulana Azad National Urdu University Dept. of Computer Science and Information Technology Hyderabad India Informatics Institute Istanbul Technical University Istanbul Turkey

ISBN: (纸本)9798331505264

Blockchain technology offers a secured, digital, decentralized, ever-growing ledger that keeps records tamper-proof. The distributed ledger means that, even if one node is attacked or hacked, data may be accessed from other nodes, making the system more resistant to attacks and ensuring data availability. The hash function is used to strengthen the data integrity. E-KYC stands for electronic Know Your Customer, a way to verify a customer's identity. The banks frequently require the customer's identity documents for verification. Therefore, they spend an unwanted cost, effort, and abundant time during the KYC process. Sometimes, the information stored locally can be misleading. With unique features, blockchain-enabled e-KYC systems can protect sensitive data, reduce data breach risks, and ensure the integrity and confidentiality of e-KYC procedures. With its distributed ledger, blockchain technology stores e-KYC data across nodes and cryptographic techniques and can effectively increase e-KYC safety. Decentralization and immutability make blockchain technology a strong foundation for securing sensitive customer data. Strong authentication and public key cryptographic methods to protect e-KYC data. © 2024 IEEE.

关键词： Distributed ledger

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Enhanced QSAR Modeling for Drug Discovery: Leveraging Advanced Computational Tools and Techniques

Enhanced QSAR Modeling for Drug Discovery: Leveraging Advanc...

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2024 IEEE Region 10 Symposium, TENSYMP 2024

作者： Tanay, Mogalluru Chidhvilas Rathnam, Rahul Krishna, Pamba Vamshi Devnath, Mrinal Punn, Narinder Singh ABV-IIITM Gwalior Dept. of Information Technology M.P. India Centre for Biomedical Research ABV-IIITM Gwalior Dept. of Computer Science and Engineering M.P. India

ISBN: (纸本)9798350364866

In this research, we present a comprehensive Quan-titative Structure-Activity Relationship (QSAR) methodology uti-lizing advanced computational tools and techniques for drug discovery targeting the SARS 3-C like proteinase. By integrating data retrieval from the ChEMBL database, calculation of Lipin-ski parameters, molecular fingerprint generation using PaDEL, and Gaussian Process Regressor modeling, we aimed to enhance the predictive accuracy and reliability of QSAR models. Our results demonstrate the effectiveness of the proposed method-ology in accurately predicting compound bioactivity against the target protein. The Gaussian Process Regressor, with its probabilistic modeling capabilities and flexibility in capturing complex nonlinear relationships, proved to be a suitable choice for modeling intricate interactions between chemical structures and bioactivities. This approach offers a promising foundation for future research and advancements in computational drug design, potentially accelerating the development of novel therapeutic agents for various diseases. © 2024 IEEE.

关键词： Gaussian distribution

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Micro-Mobility in Indonesia: Examining the Legal and Policy Implications of Emerging Transportation Technologies 9

Micro-Mobility in Indonesia: Examining the Legal and Policy ...

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9th International Conference on Business and Industrial Research, ICBIR 2024

作者： Suci Meinarni, Ni Putu Vandika, Arnes Yuli Misnawati Institut Bisnis Dan Teknologi Indonesia Dept. Informatics Engineering Denpasar Indonesia Universitas Bandar Lampung Dept. Computer Science Bandarlampung Indonesia Universitas Palangka Raya Dept. Indonesian Language and Literature Education Palangka Raya Indonesia

ISBN: (纸本)9798350383010

This study delves into micro-mobility in Indonesia, focusing on legal, safety, and policy aspects of electric scooters, bicycles, and similar devices. The absence of specific regulations and safety concerns pose challenges, compounded by infrastructure deficiencies and public perception complexities. A literature review provides insights, identifying gaps and guiding research goals. Legal analysis reveals a regulatory void, emphasizing the need for clear guidelines and dedicated safety measures, amid infrastructure challenges and public perception issues. The study underscores the importance of aligning urban planning, efficient enforcement, and public engagement for sustainable micro-mobility. A collaborative and comprehensive framework, incorporating clear regulations, safety measures, infrastructure development, efficient enforcement, and positive public perception, is essential for the successful integration of micro-mobility in Indonesia's urban landscape. Strategic and informed approaches are crucial as Indonesia leads the way in embracing these innovative transportation technologies. © 2024 IEEE.

关键词： Urban transportation

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Real-Time Object Detection with IOT Using a Smart Cart 18

Real-Time Object Detection with IOT Using a Smart Cart

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18th International Conference on Ubiquitous Information Management and Communication, IMCOM 2024

作者： Omer, Muhammad Ali, Sardar Jaffar Raza, Syed Muhammad Le, Duc-Tai Choo, Hyunseung College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of Sungkyunkwan University Dept. of Computer Science and Engineering Suwon Korea Republic of Sungkyunkwan University Dept. of AI System Engineering Suwon Korea Republic of Sungkyunkwan University Dept. of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798350331011

With Industry 4.0's technological advancements, the convenience and affordability of Artificial Intelligence (AI) and IoT have increased. However, customers still face long waiting times in payment queues during the smart shopping experience. Current solutions rely on expensive sensor-based RFIDs or simple barcodes, making them impractical and limited in scalability. This paper proposes an economically smart solution with two cameras on NVIDIA JETSON NANO for realtime object monitoring and automated shopping. Communication between modules is facilitated by TCP/IP and HTTP protocols. By utilizing the YOLO v7, real-time monitoring is achieved. This innovative approach revolutionizes the customer experience by providing a seamless interface and time-saving features. Additionally, it offers potential integration with e-commerce businesses and payment gateways, further enhancing the overall customer and vendor experience. © 2024 IEEE.

关键词： Graphical user interfaces

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Monolithic 3D Printed Micro-Optofluidic Device for Two-phase Flow Monitoring and Bioapplications 13

Monolithic 3D Printed Micro-Optofluidic Device for Two-phase...

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13th IEEE International Conference and Expositions on Electric and Power Engineering, EPEi 2024

作者： Saitta, Lorena Cutuli, Emanuela Celano, Giovanni Tosto, G Claudio Guarino, Francesca Cicala, Gianluca Bucolo, Maide University of Catania Dept.of Civil Engineering and Architecture Catania95125 Italy University of Catania Dept. of Electrical Electronic and Computer Science Engineering Catania95125 Italy University of Catania Dept. of Biomedical and Biotechnological Science Catania95125 Italy

ISBN: (纸本)9798350356199

In this work, a biocompatible 3D printed micro-optofluidic (MoF) device designed for monitoring two-phase flows is presented. It was manufactured using the Projection Micro-Stereolithography (PμSL) 3D printing technique combined with a biocompatible resin. This device successfully monitored both an air-water slug-flow and a two-phase mixture of micrometric eukaryotic yeast cells (Saccharomyces cerevisiae) suspended in a phosphate-buffered saline (PBS) solution. Its working principle relies on the absorption phenomenon, since different light transmissions are correlated to either the fluid or the cells interfering with a laser beam in a microchannel section. To accomplish this, the MoF device was designed with two micrometric slots for the insertion of optical fibers to capture the light signal. Both the micro-optical and microfluidic components, each 200 μm in size, were integrated into the MoF device as a monolithic structure. A wide experimental campaign was performed on the MoF device investigating different flow rates and cells concentrations. The optimal operative condition for achieving the most robust working ability were determined using a Design of Experiments (DoE) approach. © 2024 IEEE.

关键词： Two phase flow

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Digital Twin and Industrial Internet of Things Architecture to Reduce Carbon Emissions 4

Digital Twin and Industrial Internet of Things Architecture ...

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4th International Conference on computer Communication and the Internet, ICCCI 2022

作者： Metallidou, Chrysi Psannis, Kostas E. Vergados, Dimitrios D. Dossis, Michael University of Macedonia University of Western Macedonia Dept. of Applied Informatics Dept. of Economics/Computer Science Kastoria Thessaloniki Greece University of Piraeus Dept. of Informatics Piraeus Greece University of Western Macedonia Dept. of Computer Science Kastoria Greece

ISBN: (数字)9781665469920

ISBN: (纸本)9781665469920

The rapid growth of digital technology implies the progress of industry, by utilizing Industrial Internet of Things and Digital Twins, in collecting data through sensors and digitally monitoring and testing a product, with a view to improving its features, before the production of the physical product, in real world. At the same time, industrial carbon emissions are a major issue to be confronted. Since, Digital Twin is a connection between the physical and digital world, transferring data bidirectionally and providing insights into the lifecycle of a production process, it also can be utilized for the reduction of industrial carbon emissions. In this paper, we implement a method for the reduction of carbon emissions, by applying the Industrial Internet of Things to collect past data from manufacturing factors and a Digital Twin architecture to monitor present data, compose a model and predict its future behavior, considering renewable energy resources and less carbon emissions. This method contributes in improved decision making regarding the manufacturing process and energy efficient industrial operation. © 2022 IEEE.

关键词： Energy efficiency

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Product Recommendation Using Collaborative Filtering and K-Means Clustering 5

Product Recommendation Using Collaborative Filtering and K-M...

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5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Kumar, M. Ranjith Vishnu, S. Roshen, G. Kumar, D. Niranjan Revathi, P. Baster, David Ricardo Ledo Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Mathematics Chennai India Amrita Vishwa Vidyapeetham Dept. of Computer Science & Engineering Amrita School of Computing Chennai India C. Abdul Hakeem College of Engineering and Technology Dept. of Computer Science & Engineering Vellore Melvisharam India University of Holguin Dept. of Informatics and Mathematics Cuba

ISBN: (纸本)9798350383522

The growth of e-commerce has altered how consumers shop, providing a digital space where convenience, vast product offerings, and competitive pricing converge. In today's world, e-commerce websites are transitioning from traditional search-driven methods to customized and intuitive approaches via product suggestions. Product recommendation systems are vital in e-commerce, from bringing new business to retaining existing ones. Our three-part recommendation system is designed so that new users have a great and engaging experience as the Product Popularity -Based System shows them carefully chosen products that are in demand. Collaborative Filtering Recommendations are highly personalized recommendations given to people who have already made their first purchases based on their prior actions and preferences. The K-Means Clustering-Based Recommendation System uses textual clustering analysis to deliver contextually relevant recommendations. We use a variety of evaluation metrics, such as click-through rates, user engagement, and the Silhouette Score, to assess the effectiveness and accuracy of our recommendation systems. Our findings show significant increases in user engagement, conversion rates, and relevant recommendations. Our findings demonstrate the transformative power of well-designed recommendation systems, which improve user experiences and retention and provide invaluable solutions for businesses entering the e-commerce space. This paper provides an in-dept. examination of the multifaceted landscape of e-commerce recommendations, shedding light on their far-reaching implications for customer acquisition and retention in this dynamic digital era. © 2024 IEEE.

关键词： clustering collaborative filtering E-commerce systems K-means algorithm recommender system

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Game-Based Learning for Engineering Education 6

Game-Based Learning for Engineering Education

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6th South-East Europe Design Automation, computer Engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2021

作者： Velaora, Chrysoula Kakarountas, Athanasios Dept. of Computer Science and Biomedical Informatics University of Thessaly Lamia Greece

ISBN: (纸本)9781665427425

The issue addressed in this work is the impact of virtual lab to distance learning of the cognitive object of logic design course. Thirty four digital electronic circuits were designed using an online application for electronics. Students were asked to implement a game using most of them and watch relevant educational videos in order to achieve it. This paper reports our evaluation of how the motivation of students is affected by online lab. In the survey participated 15 undergraduate students of the University of Thessaly in Greece. When the semester came to an end, they filled out a questionnaire based on IMMS (Instructional Materials Motivation Survey) tool which includes 36 sentences on the components of the Keller's ARCS motivation model: students' attention, relevance, confidence and satisfaction. The survey justifies that the design of virtual lab and corresponding educational material based on gamification and educational videos strengthens students' motivation. © 2021 IEEE

关键词： computer circuits

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An Approach to Detect Abnormal Submissions for CodeWorkout Dataset 8

An Approach to Detect Abnormal Submissions for CodeWorkout D...

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8th Educational Data Mining in computer science Education Workshop, CSEDM 2024

作者： Hicks, Alex Shi, Yang Lekshmi-Narayanan, Arun-Balajiee Yan, Wei Marwan, Samiha Dept of Computer Science Virginia Tech Blacksburg VA Dept of Computer Science Utah State University Logan UT Intelligent Systems Program University of Pittsburgh Pittsburgh PA School of Informatics Computing and Cyber Systems North Arizona University Flagstaff AZ Dept. of Computer Science University of Virginia wCharlottesville VA

Students’ interactions while solving problems in learning environments (i.e. log data) are often used to support students’ learning. For example, researchers use log data to develop systems that can provide students with personalized problem recommendations based on their knowledge level. However, anomalies in the students’ log data, such as cheating to solve programming problems, could introduce a hidden bias in the log data. As a result, these systems may provide inaccurate problem recommendations, and therefore, defeat their purpose. Classical cheating detection methods, such as MOSS, can be used to detect code plagiarism. However, these methods cannot detect other abnormal events such as a student gaming a system with multiple attempts of similar solutions to a particular programming problem. This paper presents a preliminary study to analyze log data with anomalies. The goal of our work is to overcome the abnormal instances when modeling personalizable recommendations in programming learning environments. © 2024 Copyright for this paper by its authors.

关键词： CS1 Dataset Cleaning Dataset Standards Educational Data Mining Introductory Programming

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