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Innovative Approaches in Smart Technologies (ISAS), International Symposium on

作者： Sunitha Cheriyan Sudha Sakthivel Thirupathi Regula Kiran Kumar Said Al Riyami Department of IT College of Computing and Information Sciences University of Technology and Applied Sciences Muscat Oman

ISBN: (数字)9798331540104

ISBN: (纸本)9798331540111

Posture monitoring has emerged as a critical area of research and application, particularly considering increasing concerns about musculoskeletal disorders and their association with prolonged sitting and poor ergonomic practices. This study investigates the importance of posture monitoring and classification using a comprehensive dataset that includes demographic, and physiological, variables such as age, height, activity level, pain indicators, and personality traits. A pressure mapping system was used to gather data and various AI algorithms were applied to classify in-bed posture using the mined features of the dataset. With different in-bed postures, the study reached high classification accuracy. The performance of these algorithms was then evaluated with machine learning algorithms on the posture dataset. A dataset for posture monitoring and classification study is introduced for accurate and reliable monitoring and classification of these modern health and well-being issues. Relations between features and posture types are identified through the analysis and preprocessing of the dataset. We implemented the classification model using machine learning algorithms and evaluated the model performance evaluation using standard metrics like accuracy, precision, recall, and F1 Score. This paper details current posture assessment methods, providing an overview as well as a background for postural health management and ergonomic solutions. This study aims to propose an implementable posture classification model for a comprehensive assessment of body posture that may help bedridden patients have better health control and a better quality of life. This work might provide more effective care strategies to minimize the risks related to immobility. To achieve, both real-time monitoring and proactive health management, a smart classification monitoring system employs machine learning and Internet of Things technology to automatically identify, classify, and provide actionab

关键词： Machine learning algorithms Accuracy Ergonomics Machine learning Transforms Real-time systems Classification algorithms Monitoring Standards Testing

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Hill Matrix and Radix-64 Bit Algorithm to Preserve Data Confidentiality

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Computers, Materials & Continua 2023年第5期75卷 3065-3089页

作者： Ali Arshad Muhammad Nadeem Saman Riaz Syeda Wajiha Zahra Ashit Kumar Dutta Zaid Alzaid Rana Alabdan Badr Almutairi Sultan Almotairi Department of Computer Science National University of TechnologyIslamabadPakistan Department of Computing Abasyn UniversityIslamabadPakistan Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityRiyadh13713Saudi Arabia Department of Computer Science Faculty of Computer and Information SystemsIslamic university of MadinahMedinah42351Saudi Arabia Department of Information Systems Faculty of Computer and Information Sciences CollegeMajmaah University11952Saudi Arabia Department of Information Technology College of Computer Sciences and Information Technology CollegeMajmaah UniversityAl-Majmaah 11952Saudi Arabia Department of Natural and Applied Sciences Faculty of Community CollegeMajmaah UniversityMajmaah11952Saudi Arabia

There are many cloud data security techniques and algorithms available that can be used to detect attacks on cloud data,but these techniques and algorithms cannot be used to protect data from an *** cryptography is the best way to transmit data in a secure and reliable *** researchers have developed various mechanisms to transfer data securely,which can convert data from readable to unreadable,but these algorithms are not sufficient to provide complete data *** algorithm has some data security *** some effective data protection techniques are used,the attacker will not be able to decipher the encrypted data,and even if the attacker tries to tamper with the data,the attacker will not have access to the original *** this paper,various data security techniques are developed,which can be used to protect the data from attackers ***,a customized American Standard Code for Information Interchange(ASCII)table is *** value of each Index is defined in a customized ASCII *** an attacker tries to decrypt the data,the attacker always tries to apply the predefined ASCII table on the Ciphertext,which in a way,can be helpful for the attacker to decrypt the *** that,a radix 64-bit encryption mechanism is used,with the help of which the number of cipher data is doubled from the original *** the number of cipher values is double the original data,the attacker tries to decrypt each *** of getting the original data,the attacker gets such data that has no relation to the original *** that,a Hill Matrix algorithm is created,with the help of which a key is generated that is used in the exact plain text for which it is created,and this Key cannot be used in any other plain *** boundaries of each Hill text work up to that *** techniques used in this paper are compared with those used in various papers and discussed that how far the current algorithm is better than all other algorit

关键词： Cryptography symmetric cipher text encryption matrix cipher encoding decoding hill matrix 64-bit encryption

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An Overview of Tools and Techniques in Network Forensics 25

An Overview of Tools and Techniques in Network Forensics

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25th International Arab Conference on Information technology, ACIT 2024

作者： Asassfeh, Mahmoud Al-Mousa, Mohammad Rasmi Al-Dweikat, Hasan Al-Mashagbeh, Malak Hamad Afaneh, Suha Samara, Ghassan Zaid, Ali Abu Khouj, Mohammed Al Daoud, Essam Zarqa University Department of Cybersecurity Zarqa Jordan Applied Science Private University Cybersecurity and Cloud Computing Department Amman Jordan Zarqa University Department of Computer Science Zarqa Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia Zarqa University Faculty of Information Technology Zarqa Jordan

ISBN: (纸本)9798331540012

Network forensics pertains to a subfield of digital forensics that deals with network security. It is utilized in conjunction with computer network traffic monitoring and analysis, which acts as an intrusion detection system and firewall and facilitates the collection of data and digital proof for network security. This platform is designed to analyze and monitor data in a real-time network environment. It is a crucial instrument for identifying and resolving instances of real-time network misuse. This research shows the differences between network forensics and digital forensics as well as the tools and techniques used in network forensics. It also discusses building forensics platforms, developing network analysis methodologies, and talking about the future of network forensics. © 2024 IEEE.

关键词： Network intrusion

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IoT based malaria website model using Digital Binary Code : A Mathematical Study 2

IoT based malaria website model using Digital Binary Code : ...

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2nd IEEE International Conference on IoT, Communication and Automation technology, ICICAT 2024

作者： Tripathi, Padmaja Chandra, Harish Keval, Ram Kesarvani, Atul Singh, Kundan Madan Mohan Malviya University of Technology Department of Mathematics and Scientific Computing Gorakhpur India MJP Rohilkhnad University Department of Applied Mathematics Bareily India Rajkiya Engineering College Department of Electronic Engineering India Rajkiya Engineering College Department of Electronics Engineering 231206 India

ISBN: (纸本)9798350368109

There has been a major increase in research on digitizing the disease's tracking systems. In the scientific community, automated screening for malaria is one of the detection methods that is becoming very common. Although the Fourth Industrial Revolution (4IR) has gained widespread acceptance, the treatment for malaria, one of the deadliest and most enduring diseases, has not evolved. Contextualization of malaria monitoring systems must be established at the national or regional level, and this requires process integration with other protocols. This study suggests a digital malaria monitoring system for a country or region in Africa. The development of a distinctive model for forecasting disease spread, grounded in the dynamics of various types of malaria, represents a significant benefit of this digital system. We analyze the SITRR (susceptible-infected-treated resistant-recovered) epidemic model of the illness's spread to produce a mathematical forecast and to define the design of the diagnosis system. © 2024 IEEE.

关键词： Diseases

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Who Should I Trust? A Visual Analytics Approach for Comparing Net Load Forecasting Models

Who Should I Trust? A Visual Analytics Approach for Comparin...

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2025 IEEE PES Grid Edge Technologies Conference and Exposition, Grid Edge 2025

作者： Bhattacharjee, Kaustav Kundu, Soumya Chakraborty, Indrasis Dasgupta, Aritra New Jersey Institute of Technology Department of Data Science United States Pacific Northwest National Laboratory Optimization and Control Group United States Lawrence Livermore National Laboratory Center for Applied Scientific Computing United States

ISBN: (纸本)9798350352528

Net load forecasting is crucial for energy planning and facilitating informed decision-making regarding trade and load distributions. However, evaluating forecasting models' performance against benchmark models remains challenging, thereby impeding experts' trust in the model's performance. In this context, there is a demand for technological interventions that allow scientists to compare models across various timeframes and solar penetration levels. This paper introduces a visual analytics-based application designed to compare the performance of deep-learning-based net load forecasting models with other models for probabilistic net load forecasting. This application employs carefully selected visual analytic interventions, enabling users to discern differences in model performance across different solar penetration levels, dataset resolutions, and hours of the day over multiple months. We also present observations made using our application through a case study, demonstrating the effectiveness of visualizations in aiding scientists in making informed decisions and enhancing trust in net load forecasting models. © 2025 IEEE.

关键词： AI/ML net load forecasting visual analytics

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Leveraging Digital Twins and AI for Enhanced Clinical Decision Support in Endometrial Cancer Treatment 5

Leveraging Digital Twins and AI for Enhanced Clinical Decisi...

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5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Palarimath, Suresh Maran, Pyingkodi Wilfred Blessing, N.R. Cibi, A. Kavitha, S.J. Steffi, S. College of Computing and Information Sciences University of Technology and Applied Sciences Salalah Oman Kongu Engineering College Department of Computer Application Erode India College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman Virtusa Consulting Service Private Limited Data & Analytics Visualizaation - Delivery Chennai India Vels Institute of Science Technology and Advanced Studies Department of Computer Science and Engineering Chennai India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Computer Science and Engineering Chennai India

ISBN: (纸本)9798331518097

Digital twins are a relatively new concept that have lately garnered interest in the industrial sector. Digital twins are virtual models that mirror actual products. In this research, we suggest using the technology of digital twins to the field of healthcare in order to enhance clinical decision support and to provide more individualized treatment for patients. When artificial intelligence (AI) is combined with digital twins, healthcare professionals are able to more effectively analyze large volumes of varied data and increase their ability to make diagnostic and therapeutic decisions. In this research, we provide a conceptual framework for leveraging digital twins and AI to solve existing limits in cancer care, notably endometrial cancer therapy. This research study mainly focuses on cancer care, and more specifically on endometrial cancer treatment. In addition, we analyze the possible challenges and opportunities that may arise throughout the process of integrating this technology in healthcare settings. Our overarching objective is to improve the standard of treatment as well as the clinical results for people who have cancer. © 2024 IEEE.

关键词： Lung cancer

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Efficiency Assessment of an Institute Through Parallel Network Data Envelopment Analysis 11th

Efficiency Assessment of an Institute Through Parallel Netwo...

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11th International Conference on Soft computing for Problem Solving, SocProS 2022

作者： Kumar, Atul Panwar, Ankita Pant, Millie Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Roorkee Roorkee247667 India Mehta Family School of Data Science and Artificial Intelligence Indian Institute of Technology Roorkee Roorkee247667 India

ISBN: (纸本)9789811965241

Conventional data envelopment analysis (DEA) is a non-parametric approach to examine the efficiency of similar decision-making units (DMUs) as a whole system without considering its internal structure, i.e., the system is considered as a black box. Therefore, a network DEA (NDEA) is needed to study the internal structure of a system. By allowing for the measurement of individual components, an NDEA model can reveal inefficiencies that a traditional DEA ignores. In this study, we use the parallel network DEA to calculate the efficiency of a higher education institute with 19 decision-making units (DMUs) using two parallel processes (teaching and research) and compare it with the conventional DEA, CCR model through a numerical example. The main advantages of the parallel NDEA model are (i) to identify which DMUs are inefficient and make necessary adjustments, and (ii) the parallel DEA model has a lower efficiency score than the traditional DEA model. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Efficiency

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Atmospheric Convection Model Based Digital Confidentiality Scheme

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Computers, Materials & Continua 2022年第6期71卷 4503-4522页

作者： Noor Munir Majid Khan Mohammad Mazyad Hazzazi Amer Aljaedi Sajjad Shaukat Jamal Iqtadar Hussain Department of Applied Mathematics and Statistics Institute of Space TechnologyIslamabadPakistan Department of Mathematics College of ScienceKing Khalid UniversityAbha61413Saudi Arabia College of Computing and Information Technology University of TabukTabuk71491Saudi Arabia Department of Mathematics Statistics and PhysicsQatar UniversityDoha2713Qatar

Nonlinear dynamics is a fascinating area that is intensely affecting a wide range of different disciplines of science and technology *** combination of different innovative topics of information security and high-speed computing has added new visions into the behavior of complex nonlinear dynamical systems which uncovered amazing results even in the least difficult *** generation of complex actions froma very simple dynamical method has a strong relation with information *** protection of digital content is one of the inescapable concerns of the digitally advanced ***,information plays an important role in everyday life and affects the surroundings *** digital contents consist of text,images,audio,and videos,*** to the vast usage of digital images in the number of social and web applications,its security is one of the biggest *** this work,we have offered an innovative image encryption technique based on present criteria of confusion and *** designed scheme comprises two major nonlinear dynamical *** have employed discrete fractional chaotic iterative maps to add confusion capability in our suggested algorithm and continuous chaotic Lorenz *** have verified our offered scheme by using statistical *** investigations under the statistical tests suggested that our proposed technique is quite reasonable for the security of digital data.

关键词： Lorenz atmospheric convection model fractional logistic map image encryption S-box

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A Mathematical Model to Minimize the Total Cultivation Cost of Sugarcane 11th

A Mathematical Model to Minimize the Total Cultivation Cost ...

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11th International Conference on Soft computing for Problem Solving, SocProS 2022

作者： Kumar, Sumit Pant, Millie Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Roorkee Uttarakhand Roorkee India Mehta Family School for Data Science and Artificial Intelligence Indian Institute of Technology Roorkee Uttarakhand Roorkee India

ISBN: (纸本)9789811965241

In the present study, a non-linear mathematical model is proposed to minimize the total expenditure made on sugarcane cultivation. The objective here is to optimize the costs involved in transportation, cultivation, and management of the deterioration of sugarcane. The optimization tools used are Differential Evolution (DE) and Particle Swarm Optimization (PSO). Further, the model is validated by comparing the actual expenditure of sugarcane cultivation with results obtained by PSO and DE, which indicates that the application of optimization methods may help in reducing the expenditure made on sugarcane cultivation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deterioration

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Availability and Demand of Jobs from the Perception of Automated Recruitment in Oman 7

Availability and Demand of Jobs from the Perception of Autom...

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7th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2023

作者： Karim Sadiq, Mohamed Abdul Al-Fannah, Nasser Mohammed Shanmugam, Thirumurugan Kausar, Firdous Oman Ministry of Transport Communications and Information Technology Muscat Oman College of Computing and Information Science Utas Suhar Oman College of Computing and Information Science University of Technology and Applied Sciences Suhar Oman Fisk University Department of Mathematics and Computer Science NashvilleTN United States

ISBN: (纸本)9798350342154

Natural Language Processing has been applied for automation of the recruitment process globally with the increase in volumes of profiles and jobs. This paper discusses certain challenges in the use of cutting-edge technologies for documents in the Arabic language. We analyze the availability and demand of jobs in Oman with reference to that in UAE. As a result, hurdles can be minimized in the job-resume matching process between the employers and prospective candidates. © 2023 IEEE.

关键词： Deep learning

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