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Health Data Analytics Using IoT: Transforming Healthcare Management and Treatment Strategies for Improved Patient Outcomes

Health Data Analytics Using IoT: Transforming Healthcare Man...

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2024 International Conference on Innovative computing, Intelligent Communication and Smart Electrical Systems, ICSES 2024

作者： Tuan, Dinh Cong Unnikrishnan, Paravthy Dhandayuthapani, Bala Vennila, M.E.M. Long, Choi Sang Sahoo, Deepali Rani Dai Nam University Faculty of Communication Viet Nam Amritapuri690525 India College of Computing and Information Sciences University of Technology and Applied Sciences Department of It Shinas Campus Oman Karpaga Vinayaga College of Engineering and Technology Department of Robotics and Automation Chengalpattu India Raffles University Faculty of Business Malaysia Symbiosis Law School Noida India Pune India

ISBN: (纸本)9798331543617

The integration of Web of Things (IoT) innovation within the healthcare segment has revolutionized conventional healthcare administration and treatment procedures, driving progressed quiet results. This paper looks at the transformative effect of well-being information analytics utilizing IoT in upgrading healthcare administrations, optimizing understanding care, and advancing preventive measures. The paper analyzes the key components and applications of IoT in healthcare, emphasizing its part in information collection, real-time observation, and examination of understanding imperative signs, action levels, and pharmaceutical adherence. With the help of IoT-enabled gadgets such as wearables, sensors, and keen checking frameworks, healthcare experts can assemble comprehensive, real-time persistent information, encouraging early discovery and opportune mediation for basic well-being issues. Besides, the utilization of IoT in well-being information analytics empowers the improvement of personalized treatment plans custom-fitted to a person's persistent needs, cultivating a patient-centric approach to healthcare conveyance. By leveraging machine learning calculations and prescient analytics, healthcare suppliers can expect potential well-being complications, in this manner minimizing the chance of antagonistic occasions and clinic readmissions. In addition, the execution of IoT-based healthcare arrangements advances further understanding and observing, empowering healthcare suppliers to offer ceaseless, personalized care past conventional healthcare settings. © 2024 IEEE.

关键词： Patient treatment

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A Machine-Learning Based IoT Smart Home System to Detect and Reduce Urban Insecurity in Uganda: A Case of Kampala Metropolitan Area

A Machine-Learning Based IoT Smart Home System to Detect and...

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International Conference on Advances in Big Data, computing and Data Communication Systems (icABCD)

作者： Edward Miiro Ismael Kato Department of Computer Science & Engineering Faculty of Computing & Informatics Makerere University Business School Kampala Uganda Dept. of Applied Computing & Information Technology Faculty of Computing & Informatics Makerere University Business School Kampala Uganda

ISBN: (数字)9798350387902

ISBN: (纸本)9798350387919

This study sought to develop and test a machine learning based prototype of a smart home security system for Kampala Metropolitan area in Uganda. The researchers used a Design Science Research (DSR) method to execute the project. The researchers identified a problem- which was high level of insecurity and crimes around homes in Kampala and its metropolitan areas, defined objectives, collected requirements, designed and developed the artifact, then demonstrated, evaluated, and communicated the artifact to stakeholders. The team created a working prototype of a home-security system that was later tested, demonstrated, validated among potential users. Practically, this project was implemented in a simulated environment using Tinkercad Arduino software. The developed system prototype was simulated on screen and tested on at least one home to ensure its effectiveness in reducing unauthorized entry, robbery, and other forms of crimes that are widely prevalent in Kampala today. One limitation of the project was that Arduino board used was quite limited on the number of pins that were available for use. The initial project idea had featured a temperature sensor to that was intended to regulate the temperature in the home by making use of the fan. However, the researchers did not implement this due to the limited pins and the capacity of the Arduino Uno R3 board that was used. Higher capacity industrial tools could provide a more realistic design of a similar system. The project simulated an environment of a smart home security system that can be used to detect and reduce crime. This study is part of a wider project to test ML and IoT systems in building secure smart homes. The authors envisage the application on more advanced ML algorithms and techniques in improving the system.

关键词： Temperature sensors Urban areas Prototypes Smart homes Machine learning Software Pins

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Business documents analysis using text mining techniques

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International Review on Computers and Software 2012年第4期7卷 1663-1677页

作者： Almanaseer, Orabe Alkhaleefah, Mohammad Elmanaseer, Sakha'a Faculty of information Technology and Systems University of Jordan Aqaba Jordan Faculty of Rahma College Al-Balqa Applied University Jordan Information system Department Faculty of Computing and Information Technology King Abdul Aziz University Saudi Arabia

Interchange of business data and documents between applications and databases, "Document Interoperability", is one of the most important issues to be investigating in the ebusiness arena, particularly, business documents which are transferred between SMEs using an email-based system. Mining textual documents to discover hidden patterns and relationships in the contents of these documents is an emergent topic in the data mining community. Several text mining techniques can be used to automatically analyse the structure of business documents and extract information from them in order to support seamless document interchange in different formats between SMEs. The purpose of this paper is to design a classification system for analysing business documents that are transferred between SMEs via email in order to address the problem of documents' interoperability. To reach this purpose, the design process which should be implemented consists of five main phases which include document standardisation, text preprocessing, document representation and dataset generation, classifier learning, and system evaluation. Each phase consists of several steps, and different algorithms, tools and techniques are used in each step. © 2012 Praise Worthy Prize S.r.l. - All rights reserved.

关键词： Interoperability

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A Novel 3D Medical Image Segmentation Model Using Improved SAM

A Novel 3D Medical Image Segmentation Model Using Improved S...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Kuang, Yuansen Ma, Xitong Zhao, Jing Wang, Guangchen Zeng, Yijie Liu, Song Key Laboratory of Computing Power Network and Information Security Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9781665410205

3D medical image segmentation is an essential task in the medical image field, which aims to segment organs or tumours into different labels. A number of issues exist with the current 3D medical image segmentation task: existing models cannot simultaneously obtain the space correlation and depth correlation of 3D slices;previous models suffer from local detail loss of positional embedding in 3D images;previous approaches often have blurring of boundaries in segmenting 3D images. To solve these shortcomings, we propose a 3D medical image segmentation model named TPM-SAM. In our model, we design a twinchannel image encoder to simultaneously capture the space correlation and depth correlation of 3D slices through a multi-head attention mechanism and improved adapters. Furthermore, we design a prompt encoding generator, which divides the volumetric image into small blocks and better captures the local detail information. In addition, we introduce a multi-layer aggregation decoder by employing U-Net with multi-level skip connection to solve the blurring of boundaries in processing 3D images. Finally, we experimented and evaluated our model on KiTS21 and LiTS17 datasets to compare with other baseline models. © 2024 IEEE.

关键词： Image segmentation

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An interval version of the backward differentiation (BDF) method

An interval version of the backward differentiation (BDF) me...

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12th GAMM-IMACS International Symposium on Scientific computing, Computer Arithmetic and Validated Numerics, SCAN 2006

作者： Jankowska, Malgorzata Marcinak, Andrzej Poznan University of Technology Institute of Applied Mechanics Piotrowo 3 60-965 Poznan Poland Poznan University of Technology Institute of Computing Science Piotrowo 2 60-965 Poznan Poland Adam Mickiewicz University Faculty of Mathematics and Computer Science Umultowska 87 61-614 Poznan Poland

ISBN: (纸本)076952821X

We present an interval version of the backward differentiation method for solving the initial value problem (IVP) for ordinaiy differential equations (ODEs). The method considered belongs to a group of the interval multistep methods. A number of the explicit and implicit interval multistep methods are tested on selected problems and the comparison is given.

关键词： Initial value problems

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IoT Based Smart Fish-Feeder and Monitoring System

IoT Based Smart Fish-Feeder and Monitoring System

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2022 International Conference on Business Analytics for technology and Security, ICBATS 2022

作者： Abu-Khadrah, Ahmed Issa, Ghassan F. Aslam, Shaukat Shahzad, Muhammad Ateeq, Karamath Hussain, Munawar Saudi Electronic University College of Computing and Informatics Riyadh Saudi Arabia Skyline University College School of Information Technology Sharjah United Arab Emirates NCBAandE School of Computer Science Lahore Pakistan Riphah International University Department of Computing and Applied Sciences Lahore Pakistan Skyline University Bsit Faculty Sharjah United Arab Emirates

ISBN: (纸本)9781665409209

People have always enjoyed having pets around them, but in today's hectic world, it might be difficult to properly care for pets, particularly fish, which require more attention. When fish owners are out of town, their fish may be left with a feed shortfall or over-feed. Another consideration is the water quality (temperature, PH level, and so on). As a result, a solution is provided in this article to address the aforementioned issues. Two components comprise the proposed system. The first is for fish eating, while the second is for water feature and level monitoring. The first module also includes electrical, automatic, and communication parts that are connected to the Internet of Things (IoT) to allow fish to be fed on a schedule or remotely through a web interface. Microcontrollers with PH, Ammonia, Temperature and other sensors are included in the second module, which is used to monitor the aquarium's environment. © 2022 IEEE.

关键词： Internet of things

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Intelligent computing and Automation 1

Intelligent Computing and Automation

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丛书名： Smart Innovation, Systems and Technologies

1000年

作者： Vikrant Bhateja Maitreyee Dey Milan Simic

ISBN: (数字)9789819601431

ISBN: (纸本)9789819601424;9789819601455

The book presents the proceedings of the 12th International Conference on Frontiers of Intelligent computing: Theory and Applications (FICTA 2024), held at Intelligent Systems Research Group (ISRG), London Metropolitan University, London, United Kingdom, during June 6–7, 2024. Researchers, scientists, engineers and practitioners exchange new ideas and experiences in the domain of intelligent computing theories with prospective applications in various engineering disciplines in the book. This book is divided into four volumes. It covers broad areas of information and decision sciences, with papers exploring both the theoretical and practical aspects of data-intensive computing, data mining, evolutionary computation, knowledge management and networks, sensor networks, signal processing, wireless networks, protocols and architectures. This book is a valuable resource for postgraduate students in various engineering disciplines.

关键词： Computational Intelligence Artificial Intelligence Mobile and Network Security Signal, Image and Speech Processing

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A Survey on Graph Neural Networks for Fraud Detection in Ride Hailing Platforms

A Survey on Graph Neural Networks for Fraud Detection in Rid...

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International Conference on Artificial Intelligence and Big Data (ICAIBD)

作者： Kanishka Hewageegana Janani Harischandra Nipuna Senanayake Gihan Danansuriya Kavindu Hapuarachchi Pooja Illangarathne School of Computing Informatics Institute of Technology Colombo Sri Lanka Faculty of Applied Sciences Rajarata University Sri Lanka Faculty of Applied Sciences University of Sri Jayewardenepura Sri Lanka

ISBN: (数字)9798350385106

ISBN: (纸本)9798350385113

This study investigates fraud detection in ride-hailing platforms through Graph Neural Networks (GNNs), focusing on the effectiveness of various models. By analyzing prevalent fraudulent activities, the research highlights and compares the existing work related to fraud detection which can be useful when addressing fraudulent incidents within the online ride hailing platforms. Also, the paper highlights addressing class imbalance and fraudulent camouflage. It also outlines a structured overview of GNN architectures and methodologies applied to anomaly detection, identifying significant methodological progress and gaps. The paper calls for further exploration into real-world applicability and technical improvements to enhance fraud detection strategies in the rapidly evolving ride-hailing industry.

关键词： Industries Surveys Focusing Artificial neural networks Big Data Graph neural networks Fraud

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Cyberbullying Detection Using Deep Learning: A Comparative Study 2

Cyberbullying Detection Using Deep Learning: A Comparative S...

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2nd International Conference on Cyber Resilience, ICCR 2024

作者： Alkasassbeh, Mouhammd Almomani, Ammar Aldweesh, Amjad Al-Qerem, Ahmad Alauthman, Mohammad Nahar, Khalid Mago, Beenu Princess Sumaya University For Technology Computer Science Department Amman Jordan School Of Computing Skyline University College Sharjah United Arab Emirates AlHuson University College AlBalqa Applied University I.T. Department Irbid Jordan College Of Computing And It Shaqra University Shaqra Saudi Arabia Zarqa University Faculty Of Information Technology Computer Science Department Zarqa13110 Jordan University Of Petra Faculty Of Information Technology Department Of Information Security Amman Jordan Yarmouk University Faculty Of I.T Computer Science Department Irbid Jordan School Of Computing Skyline University College University City Of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9798350394962

Cyberbullying has become a serious issue with the rise in social media usage, especially among adolescents. Victims of cyberbullying often suffer from psychological distress, anxiety, depression and even suicidal tendencies. With the rapid growth of user-generated content online, manual detection of cyberbullying is extremely difficult. Hence, automated cyber-bullying detection systems are needed. In recent years, deep learning models have emerged as a promising technique for cyberbullying detection. This paper provides a comprehensive review of the use of deep learning for cyberbullying detection. The key contributions are: (1) a taxonomy of cyberbullying detection techniques, (2) a review of datasets used for model training and evaluation, (3) a comparative analysis of various deep learning models including CNN, RNN, LSTM, GRU and Transformer- based models, (4) a discussion of key challenges and limitations, and (5) suggestions for future research directions. The paper provides a critical perspective on model performance across multiple datasets. Key findings indicate RNNs and specifically LSTM and GRU models demonstrate state-of-the-art performance for sequential cyberbullying detection. The study concludes that deep ensemble models combining LSTMs and pretrained contextual embeddings show significant promise to advance the field. © 2024 IEEE.

关键词： Social networking (online)

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A Dyad-Based Mobile System to Support Older Adults and Informal Caregivers

A Dyad-Based Mobile System to Support Older Adults and Infor...

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IEEE Annual computing and Communication Workshop and Conference (CCWC)

作者： Tarek El Salti Edward R. Sykes Jordan Scrivo Brandon Plaza Vladislav Mun School of Applied Computing Faculty of Applied Science and Technology Sheridan College Oakville Canada Centre for Mobile Innovation (CMI) Sheridan College Oakville Canada

Despite a gradual rise in health care expenditures due to population aging between the Year 2020 and 2060 in several countries, the overall increase will contribute to additional GDP share (e.g., 1.3 percentage points in the EU). To potentially reduce costs, ongoing developments of mobile Health (mHealth) applications is essential which provide digital health care using mobile devices. However, there is no dyadic mHealth architecture (i.e., between caregivers and their older adults) exclusively utilizing smartphones, aimed at supporting older adults’ well-being through regular follow-ups for their caregivers. In response, we developed a novel dyad-based architecture, including mobile applications for caregivers to check on their older adults’ physical activities (e.g., walking). Our system is not only considered mobile but also highly accessible due to the pervasiveness of smartphones. This work in progress also included pilot usability study analysis for the user interface and experience design. Among the findings, participants mentioned that the proposed system strongly supports them in their caregiving for their older adults. This study will serve as a precursor for future usability studies that will include wearables.

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