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International Conference on Intelligent Systems and Networks, ICISN 2024

作者： Nguyen, Tran Khanh Dong, Nguyen Trinh Hai, Vu Tuan Luan, Pham Hoai Faculty of Computer Science University of Information Technology Ho Chi Minh City Viet Nam Faculty of Software Engineering University of Information Technology Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam Nara Institute of Science and Technology Takayama-cho Nara Ikoma Japan

ISBN: (纸本)9789819755035

Image compression is an important problem in the image processing field and has been applied widely in various applications, from storage optimization and print media to image exchange. Almost all compressed image formats, such as Joint Photographic Experts Group (JPEG) and Portable Network Graphics (PNG), have pros and cons, but there is always a balance between file size and image quality;the larger the file size, the greater the loss on the image. However, the hybrid quantum-classical approach provides us with a new way to compress images more efficiently. In this research, we propose a scheme that turns the image into a unitary operator’s parameter, then we make a new image format via the quantum state preparation algorithm. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： hypergraph ansatz image compressing quantum computing

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New In-Air Signature Datasets

New In-Air Signature Datasets

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2023 International Symposium on Networks, computers and Communications, ISNCC 2023

作者： Alobaidi, Abdulazeez R. Dhieb, Thameur Nuimi, Zeina N. Hamdani, Tarek M. Wali, Ali Alimi, Adel M. University of Sfax REGIM-Lab.: REsearch Groups in Intelligent Machines Enis Tunisia Imam ja'Afar Al-Sadiq University Faculty of Information Technology Department of Computer Techniques Engineering Iraq Higher Institute of Business Administration University of Gafsa Tunisia College of Engineering Department of Electrical Engineering University of Misan Iraq Higher Institute of Computer Science Mahdia University of Monastir Tunisia Higher Institute of Computer Science and Multimedia of Sfax University of Sfax Tunisia University of Johannesburg Faculty of Engineering and the Built Environment Department of Electrical and Electronic Engineering Science South Africa

ISBN: (纸本)9798350335590

Compared to traditional biometric systems, in-air signatures are considered more robust and secure than classical pen paper. A few datasets capturing in-air signatures have been introduced, utilizing various devices such as the Leap Motion and the Microsoft Kinect sensor camera. However, these devices are not exempt from shortcomings and exhibit certain limitations. The expenses associated with their implementation and the requirement for technical proficiency in operating them present notable challenges for in-air signature analysis. Additionally, users may encounter difficulties in adapting their finger movements to fit within the device's limited field of view, particularly if they lack familiarity with these devices. To address these concerns, this paper proposes the creation of three in-air signature datasets using solely the camera of a laptop or a smartphone, eliminating the need for any additional specialized equipment. Our datasets were collected in three ways. The first is the In-Air Signature dataset (IAS dataset) and the second is the In-Air Signature dataset using a transparent Glass Plate (IASGP dataset) while the third is the In-Air Signature dataset using Smart Phone (IASSP dataset). Forty volunteers participated in the construction of these datasets. Their ages ranged from 21 to 40 years. Each volunteer signs in the air five signatures and imitates five signatures of five other volunteers. Our in-air signatures datasets are publicly available and can be used for various research tasks like in-air signature verification and identification. © 2023 IEEE.

关键词： Cameras

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Atomizing E-Government Facilities Using Big Data Analytic 1

Atomizing E-Government Facilities Using Big Data Analytic

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1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021

作者： Hemalatha, S. Kanimozhi, K.V. Nagappan, G. Mahesh, P.C. Senthil Priya, R. Vidhya, M. Department of Computer Science and Engineering Panimalar Institute of Technology Tamil Nadu Chennai600123 India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering Saveetha Engineering College TamilNadu Chennai600127 India Department of Computer Science and Engineering Annamacharya Institute Of Technology & Sciences New Boyanapalli Rajampet Andhra Pradesh 516126 India Department of Computer Science and Enginerring Panimalar Engineering College Poonamaller Tamil Nadu Chennai India

ISBN: (纸本)9781607685395

During the last two decades, technical advancements in data bases and query processing have replaced hard copy maintenance in government sectors, resulting in an increase in the use of software applications to simplify human tasks in a matter of seconds. Any official task that has to be more efficient requires improvement and quick *** demographic information is also a major concern for government authorities. This article offers a method for gathering people's data and organising it as a hierarchy using a tree structure, which may be used to produce unique data and reduce redundant data. The Hadoop Map Reduction function can be used to complete this expected task. © The Electrochemical Society

关键词： Big data Big Data Analytics E-Governance Hadoop Map Reduction function MapReduce - Algorithm

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Smart Agriculture: Enhancing Crop Management through IoT-Based Real-Time Monitoring and Automation

Smart Agriculture: Enhancing Crop Management through IoT-Bas...

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Information technology and Digital Applications (ICITDA), IEEE International Conference on

作者： Hushalictmy Paliyanny Rajermani Thinakaran Somasekar Jalari Vikram Neerugatti Madhusudana Rao Nalluri Ravindra Raman Cholla Faculty of Data Science and Information Technology INTI International University Malaysia Department of Computer Science and Engineering Faculty of Engineering and technology Jain (Deemed-to-be University) Bangalore India Department of Computer Science and Engineering ICFAI Foundation for Higher Education Hyderabad Telangana India

ISBN: (数字)9798331510732

ISBN: (纸本)9798331510749

Internet of Things plays an important role in agriculture in order to provide an innovative and smart solution to traditional farming. IOT is all about connecting physical devices to the internet and can access from a remote place. So that crop monitoring becomes easy even if the farmer is in a remote place. Due to automation, human efforts are required less. Also the IoT data helps the farmer make decisions about planting, harvesting or fertilizing. This paper explains the system we have implemented for monitoring the agriculture with the help of IoT. The system is developed in order to provide real time information on crop conditions to the farmer. For that, it uses various types of sensors connected to the microcontroller in order to measure parameters like temperature, soil moisture, and water level, and accordingly, it activates actuators like a fan, motor or pump to manage ventilation and irrigation. We have used the GSM module to send the alert to the farmer and the WiFi module is used to send the agriculture data to the cloud platform. So that farmer can monitor the farm or crops remotely. The system is continuously collecting farm data from the sensors. If the crop soil is very dry them system will turn on the water pump. Also, for high temperature, the fan will get activated in order to cool down that area. This feature is mostly used in indoor farming. The farmer can monitor the farm condition in real time with the help of cloud platform. This system is helpful for improving productivity, crop management, and save resources i.e. efficient use of water which prevents water wastage.

关键词： Temperature sensors Temperature measurement Fans Soil moisture Crops Real-time systems Water pumps Water resources Monitoring Farming

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Decision Tree based Smart System for Pregnant Women Diagnosis

Decision Tree based Smart System for Pregnant Women Diagnosi...

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2022 International Conference on Intelligent technology, System and Service for Internet of Everything, ITSS-IoE 2022

作者： Al-Hagree, Salah Alsayadi, Hamzah A. Alsurori, Muneer Mohammed, Marwan Mohsen, Ayedh Abdulaziz Albazel, Mohammad Gawbah, Hezam Alndary, Ebtisam Ibb University Faculty of Sciences Computer Science Department Yemen Alqalam University Faculty of Information Technology and Engineering Information Technology Department Yemen University of Science and Technology Information Technology Department Yemen

ISBN: (数字)9781665459983

ISBN: (纸本)9781665459983

one of the reasons of women and newborns death in developing countries is the complications during pregnancy and childbirth. An early diagnosis of pregnancy problems would help to alleviate some of these risks. In this work, a suggested solution to help the physicians for fast pregnant diagnosis is proposed. A smart system is designed for easing women diagnosis during pregnancy. The core purpose of this research work is to build up an Android application which gives a deliberate approach in providing the best diagnosis of pregnancy so that women will not be caught in the is the complications during pregnancy. Android application uses Machine Learning algorithms such as decision tree algorithm. In this paper, decision tree algorithm (DT) is used for predicting pregnancy states, which performs better and more robust than the other models. The best diagnosis of pregnancy is predicted using C4.5 and CART algorithms. Proposed system had used decision tree algorithms that employed a database of the most diseases associated with women during pregnancy. Pregnant women is interacted with proposed system via an android application mobile interface, they had provided the algorithm with the case conditions, which processed to guide both physician and pregnant women on the level of risk. Response of the system is based on input data that processed according to predetermined variables and decision tree outcomes. Implemented experiments had proofed the efficiency of the system to facilitate diagnosis for better pregnant mothers' health care. The CART algorithm has gained a better level of evaluation comparing to other C4.5 algorithm. CART algorithm has achieved the highest correctly classified instances and incorrectly classified instances, which were 89.65% in correctly classified instances, 90.77 % in incorrectly classified instances, 9.23% evaluation measure. © 2022 IEEE.

关键词： Decision trees

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Advancing Mobile Health Technologies in Chronic Disease Management and Patient Empowerment 7

Advancing Mobile Health Technologies in Chronic Disease Mana...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Deepthi, N. Lakshmi Kaliyaperumal, Gopal Nijhawan, Ginni Mounika, T. Sharma, Saurabh Albawi, Ali Institute of Aeronautical Engineering Dundigal Hyderabad500043 India New Horizon College of Engineering Department of Mechanical Engineering Bangalore India Lovely Professional University Phagwara India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Lloyd Law College Uttar Pradesh Greater Noida India The Islamic University College of Medical Technology Radiology Techniques Department Najaf Iraq

ISBN: (纸本)9798350350067

APE, PTR, and DHRA, three revolutionary techniques in the Adaptive Mobile Health Framework (AMHF), empower patients and improve chronic illness management. These systems promote individualized treatment, quick risk assessment, and patient interaction to accomplish personalized healthcare goals. The PTR algorithm analyses the patient's health, medical history, and preferences to offer the best treatment. This makes therapy personalized and relevant. The AMHF's patient-centered treatment improves drug adherence and outcomes. DHRA software monitors patient health to determine health risks in real time. This lets the AMHF make quick, fact-based judgements. Chronic disease drugs work better when the system monitors and adjusts treatment regimens based on risk. Before sending personalized messages, the APE technology evaluates patient participation. By changing engagement tactics, including instructional aids, prompts, and supporting encouragement, the APE algorithm helps patients follow health programs and manage their health. Chronic disease management relies on the AUC-ROC statistic, and the PTR algorithm beats traditional methods. The DHRA program rapidly adjusts therapy as the patient's condition changes. The APE algorithm's engagement strategies improve chronic disease management by increasing patients' treatment adherence and autonomy. © 2024 IEEE.

关键词： Electronic health record

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AKQ: A Hybrid Quantum-Classical Image Encryption System

AKQ: A Hybrid Quantum-Classical Image Encryption System

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2023 RIVF International Conference on Computing and Communication Technologies, RIVF 2023

作者： Nguyen, Tran Khanh Thi Thanh Truc, Nguyen Hai, Vu Tuan University of Information Technology VNU-HCM Ho Faculty of Computer Science Chi Minh city Viet Nam University of Information Technology VNU-HCM Ho Faculty of Software Engineering Chi Minh city Viet Nam

ISBN: (纸本)9798350315844

Image encryption is an essential field between computer vision and security which aims to protect the image before future attacks. Nowadays, it is threatened by quantum computers, which can break some classical cryptography. The encryption system has been upgraded from quantum key exchange protocol to post-quantum key-establishment mechanisms, but they are not explicitly designed for the image encryption task. In this paper, we propose a hybrid quantum-classical theoretical framework and its instance AKQ system which is more secure and suitable in the post-quantum era. © 2023 IEEE.

关键词： Quantum computers

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A Blockchain-based IoT-Verifiable Query Service for Efficient and Authentic Data Retrieval in Cloud Systems 2

A Blockchain-based IoT-Verifiable Query Service for Efficien...

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2nd IEEE Global Conference on Communications and Information Technologies, GCCIT 2024

作者： Mabel Rani, A. Jaya Samuthira Pandi, V. Jackson, Beulah Kumar, K.Suresh Lakshmi Priya, J. Dickson Irudayaraj, V. Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India Chennai Institute of Technology Centre for Advanced Wireless Integrated Technology Chennai India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Ece India Panimalar Engineering College Department of Mba Poonamallee Chennai India Saveetha Engineering College Department of Ece Chennai India Dhanalakshmi College of Engineering Department of Ai&ds Chennai India

ISBN: (纸本)9798350388916

The integration of blockchain technology into various sectors has shown promise in enhancing security and data integrity, particularly in Internet of Things (IoT) systems. However, this amalgamation introduces challenges in data query efficiency and authenticity, especially in cloud-based settings. While blockchain offers operational streamlining and robust security, its inherent architecture involving distributed ledgers and consensus algorithms poses efficiency issues in data querying. This paper addresses the critical challenge of balancing query efficiency and data authenticity in Internet of Things (IoT)-based cloud systems. Existing solutions often lack scalability, real-time efficiency, and adaptability to the unique constraints of IoT environments. To overcome these limitations, this paper introduces the IoT-Verifiable Query Service (IoT-VQS), a scalable and secure architecture optimized for real-time data querying and verification in blockchains. This architecture demonstrates high throughput and verification accuracy, desirable for real-time cloud based applications. © 2024 IEEE.

关键词： Block chain cloud data authentication query verification

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Developing Thailand Wildfire Prevention Decision Support System 43

Developing Thailand Wildfire Prevention Decision Support Sys...

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43rd Asian Conference on Remote Sensing, ACRS 2022

作者： Buntub, Jirapast Punyabukkana, Proadpran Juntakut, Pongpun Pratanwanich, Ploy N. Defense Engineering and Technology Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand Department of Computer Engineering Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand Department of Civil Engineering Academic Division Chulachomklao Royal Military Academy Nakhon Nayok26000 Thailand Department of Mathematics and Computer Science Faculty of Science Chulalongkorn University Bangkok10330 Thailand

This study presents the development of Thailand Wildfire Prevention Decision Support System (ThaiWDSS) with AI-based community detection. The system assists authorities in wildfire incident management and control with focus on the residential areas. The features include the ability to predict wildfire spread, detect community areas in danger, assess damages, and simulate firebreaks. We utilized Rothermel fire spread equation and the opensource Geographic Resources Analysis Support System (GRASS GIS) while retrieving the most recent hotspot and Digital Elevation Model (DEM) from NASA’s Fire Information for Resource Management System (FIRMS). We fetch wind data from external data providers, extract land cover data relevant to Thailand from Copernicus Global Land Cover Layers (CGLS) to calculate fuel models specific to Thailand based on 13 standard fuel behavior models from Landscape Fire and Resource Management Planning Tools (LANDFIRE). The users can observe the areas where fire may damage in various time frames. It also detects any community buildings in danger by a deep learning model to detect structures in the satellite images. We are able to identify temples and schools from *** because temples and schools are usually set up as shelters when it is necessary to evacuate people from the affected areas. One of the most important features of the ThaiWDSS is the capability to allow the authorities to simulate firebreaks and visualize the risks of fire spread prediction in real time. This assessment is an essence of the planning process before they make the final decision to manage such incidents. We allowed the users to experiment our proposed system using two case studies from actual fire incidents in Thailand. Preliminary comments from experts and authorities from the Royal Thai Army Air Defense Command suggest that ThaiWDSS will be a great asset during the operation as well as in the training process. © 43rd Asian Conference on Remote Sensing, ACRS 2

关键词： Forecasting

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Oxygen uptake response to switching stairs exercise by non-parametric modeling

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Control Theory and technology 2024年第2期22卷 315-325页

作者： Hairong Yu Chenyu Zhang Kai Cao Hamzah M.Alqudah Steven Weidong Su Key Laboratory of Child Development and Learning Science of Ministry of Education and the School of Biological Science and Medical Engineering Southeast UniversityNanjing210096JiangsuChina College of Artificial Intelligence and Big Data for Medical Science Shandong First Medical University and Shandong Academy of Medical SciencesJinan250117ShandongChina Faculty of Engineering and Information Technology University of Technology SydneyUltimoNSW2007Australia

Oxygen uptake plays a crucial role in the evaluation of endurance performance during exercise and is extensively utilized for metabolic assessment. This study records the oxygen uptake during the exercise phase (i.e., ascending or descending) of the stair exercise, utilizing an experimental dataset that includes ten participants and covers various exercise periods. Based on the designed experiment protocol, a non-parametric modeling method with kernel-based regularization is generally applied to estimate the oxygen uptake changes during the switching stairs exercise, which closely resembles daily life activities. The modeling results indicate the effectiveness of the non-parametric modeling approach when compared to fixed-order models in terms of accuracy, stability, and compatibility. The influence of exercise duration on estimated fitness reveals that the model of the phase-oxygen uptake system is not time-invariant related to respiratory metabolism regulation and muscle fatigue. Consequently, it allows us to study the humans’ conversion mechanism at different metabolic rates and facilitates the standardization and development of exercise prescriptions.

关键词： Non-parametric modeling Interval stair training exercise Kernel method.Cardiorespiratory response Oxygen uptake

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