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检索条件"机构=Computer Science And Medical Engineering Faculty of Engineering and Technology"

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technology acceptance model (TAM) for mobile durian plantation apps(Pro Durian);The analysis for Malaysian farmers 5

Technology acceptance model (TAM) for mobile durian plantati...

引用

5th International Congress on Human-computer Interaction, Optimization and Robotic Applications, HORA 2023

作者： Kamarudin, Noraziahtulhidayu Yusoff, Aiman Basari, Abd Samad Hasan Safar, Noor Zuraidin Bin Mohd Hussin, Mohd Hatta Universiti Tun Hussein Onn Multimedia and Signal Processing Focus Group Faculty of Computer Science and Information Department of Multimedia Malaysia Universiti Tun Hussein Onn Faculty of Computer Science and Information Department of Multimedia Malaysia Universiti Tun Hussein Onn Faculty of Computer Science and Information Technology Department of Software Engineering Malaysia Universiti Tun Hussein Onn Faculty of Computer Science and Information Department of Information Security and Web Technology Malaysia Pertubuhan Peladang Senggarang Johor Darul Takzim Malaysia

ISBN: (纸本)9798350337525

During the application development process, it is important for a developer to analyze user requirements. This is crucial to the success of interactive systems and is an essential component of the design of information systems. User requirement analysis aids developers in understanding and analyzing users' needs and technology requirements. Throughout this case study, it is able to forecast the understanding, and technology acceptance, and at the same time improve the quality of work, reducing training and support costing and perennially improve customer or user satisfaction. The method of research selected is questionnaires that focused on collecting the data directly from Malaysian farmers through Google Forms as an online medium. The method was chosen because it is easy to implement and inexpensive due to the current situation of Covid-19. The questionnaire is designed with two sections where;a) includes the participant's demography to analyze information of the intended audience while b)focused on the knowledge of participants about recognition images. Results demonstrate the farmer's opinion and knowledge of the technology of image recognition in the agriculture sector. The quantitative research was undertaken using an online platform due to the Covid-19 pandemic. From the analysis, it is justified that the technology Acceptance Model (TAM) together with the mobile farming image recognition app is useful in collecting farmers' feedback and positive results have an outcome on the challenges faced by the durian farmers. © 2023 IEEE.

关键词： Image recognition

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Comments on "A Lightweight Privacy Preserving Authentication Protocol for VANETs" 9

Comments on "A Lightweight Privacy Preserving Authentication...

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9th International Conference on computer and Communications, ICCC 2023

作者： Awais, Syed Muhammad Yucheng, Wu Mahmood, Khalid Kharel, Rupak Chongqing University School of Microelectronics and Communication Engineering Chongqing China University of Central Lancashire School of Psychology and Computer Science Graduate School of Intelligent Data Science Preston United Kingdom National Yunlin University of Science and Technology School of Psychology and Computer Science Graduate School of Intelligent Data Science Yunlin64002 Taiwan University of Central Lancashire School of Psychology and Computer Science Faculty of Electrical and Electronics Engineering Preston United Kingdom Ton Duc Thang University School of Psychology and Computer Science Faculty of Electrical and Electronics Engineering Ho Chi Minh City Viet Nam

ISBN: (纸本)9798350317251

Vehicle use and the concept of a "smart city"are developing quickly. As a result of this progression, the Vehicular Ad-Hoc Network (VANET) is a popular network for inter-vehicular communication. The data gathering about the state of the road, the whereabouts of vehicles, their speeds, and the description of traffic congestion are obtained using the VANET. The public nature of information flow on the VANET creates serious security risks. Data security is typically one of the most important duties of VANET. As a result, it becomes one of the researchers' top priorities. Li et al. [1] introduced a Lightweight Privacy Preserving Authentication Protocol for VANETs. They stated that several attacks could be resisted using their secure authentication devised protocol. However, after analyzing we discovered that their authentication protocol is susceptible to roadside impersonation attack and it does not provide vehicle anonymity. In the end, we have provided a few suggestions to cope with Li et al.'s devised protocol current shortcomings. © 2023 IEEE.

关键词： Vehicular ad hoc networks

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Leveraging Smart Contracts for Automated Counterfeit Prevention in E-Commerce 2

Leveraging Smart Contracts for Automated Counterfeit Prevent...

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

作者： Laxmaiah, Bagam Subburam, S. Al-Fatlawy, Ramy Riad Sravanthi, Jajimoggala Sharma, Himanshu Rajaram, Gnanajeyaraman Department of CSE CMR Technical Campus Telangana Hyderabad India New Prince Shri Bhavani College of Engineering and Technology Department of IT Tamil Nadu Chennai600073 India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq GRIET Bachupally Department of CSE Telangana Hyderabad India GLA University Department of Computer Engineering & Applications Mathura India Saveetha Institute of Medical and Technical Sciences SIMATS Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350368109

This research's abstract highlights the use of intelligent contracts for the automation of counterfeit prevention in online retailing. The manuscript shows a considerable decrease in the number of counterfeit events and identification time, including the integration of machine learning nacle models with blockchain smart contracts. The analyses presented points out that the use of ML models in detecting fake goods based on their characteristics enhances the ability of counterfeit reduction since the models demonstrate high accuracy in their performance. Besides, with the help of smart contracts, actual operations can be monitored and checked in real-time to learn whether they adhere to the rules they are supposed to or not. However, as the results indicate, several challenges, including the compliance with regulations and the issue of interoperability, must be solved to push for the wider adoption of smart contracts in e-commerce environments. As it follows, further research should pay attention to optimizing smart contract management, work on an increased system's capacity, and counter present novel risks represented in counterfeiting. Thus, preparing for further research, it is also possible to emphasize the fact that the use of smart contracts will lead to the creation of a more trusting atmosphere in e-commerce for both consumers and businesses due to increased trust, transparency, and security of online transactions. © 2024 IEEE.

关键词： Smart contract

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Counteracting Rowhammer by Data Alternation

Counteracting Rowhammer by Data Alternation

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IEEE European Test Symposium (ETS)

作者： Stefan A. Lung Georgi Gaydadjiev Said Hamdioui Mottaqiallah Taouil Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft The Netherlands

ISBN: (数字)9798350349320

ISBN: (纸本)9798350349337

Modern DRAMs are vulnerable to Rowhammer attacks, demanding robust protection methods to mitigate these attacks. Existing solutions aim at increased resilience by improving design and/or adjusting operation parameters, limit row access count by throttling and prevent bit flips by timely row refreshing. However, scaling these methods for future DRAM technologies may incur significant costs in terms of area, power and/or latency. This study analyses the impact of the values of the neighbouring cells on victim cells and introduces a row alternation protection method, which is a novel approach that alternates the data of attacker rows on each access to lower the chance of bit flips in victim rows. Our analysis show that the minimum Rowhammer count to cause a bitflip in a particular cell does not only depend on vertical neighbours from the attacker row, but also on the value of the horizontal neighbours from the victim row as well as diagonal cells from the attacker row. Row alternation is able to protect the majority of the vulnerable cells (i.e., with 65%) for the DRAM used in our case study and in cases where unsuccessful it significantly increases the average minimum required Rowhammer account by 18%.

关键词： Costs Random access memory Europe Protection Resilience

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Next-Gen Coaching: IoT and Linear Regression for Adaptive Training Load Management 8

Next-Gen Coaching: IoT and Linear Regression for Adaptive Tr...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Rajasekaran, Mothiram Sekar, Satheeshkumar Manikandaprabhu, K. Vijayakumar, R. Rajmohan, M. Murugan, S. Pine Candle Way Saint AugustineFL United States Mphasis Corporation ChandlerAZ United States Chennai Institute of Technology Department of Computer Science and Engineering Tamil Nadu Chennai India Department of Electronics and Communication Engineering Tamil Nadu Namakkal India Hindustan Institute of Technology and Science Department of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350376425

With the growth of data analytics and Internet of Things (IoT) devices, the world of sports coaching is also transforming due to the continuous evolution of technology. This paper shows how athletes might benefit from adaptive training load management using IoT sensors and linear regression (LR) analysis. Athletes' performance, physiology, and environmental variables may be studied in detail with the help of IoT devices like smart gear and wearable sensors. Coaches may create individualized training plans for their athletes by combining this data with advanced analytics tools like linear regression. LR models will examine how different training parameters relate to performance results. Coaches may dynamically alter training loads in real time by creating prediction models based on past data to improve performance, reduce injuries, and promote overall athlete well-being. In addition, with the help of IoT technology, coaches can monitor their players' physical health and recuperation status in real-time, whether exercising or going about their everyday lives. The efficacy of training programs may be maximized by coaches making informed decisions about training intensity, volume, and recuperation procedures using this real-time feedback loop. It allows unprecedented personalization and flexibility in training load management, making it a potential approach to next-generation coaching. With data-driven insights, coaches can help their athletes perform at their best without putting them in danger of injury or overtraining. © 2024 IEEE.

关键词： Wearable sensors

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Numerical Simulation and Analysis of Structural Dynamic Response of Solid Rocket Motor under Oscillating Internal Pressure 2

Numerical Simulation and Analysis of Structural Dynamic Resp...

引用

2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023

作者： Alkkhayat, A.H. Pandey, Sandeep Ramani, S. Mahaboob Basha, S. Jeyakani, P. Anumula Swarnalatha, A.P. College of Technical Engineering The Islamic University Najaf Iraq Department of Electrical & Electronics Engineering IES College Of Technology MP Bhopal462044 India Department of Electronics and Communication Engineering Sreenidhi Institute of Science & Technology Telangana Hyderabad500029 India Department of Computer Science and Engineering Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Saveetha University Tamilnadu Chennai India New Prince Shri Bhavani College Of Engineering And Technology Tamilnadu India Department Of Aeronautical And Aerospace Engineering KCG College of Technology Tamilnadu Chennai India

ISBN: (纸本)9798350305418

The causes of combustion instability of solid rocket motor are very complex. Studies have shown that structural vibration may be the direct cause of combustion instability, but there are very few reports about structural dynamic response and its effects on grain. In order to study the effects of structural dynamic response of solid rocket motor grain under oscillating internal pressure on combustion process and verify a new method to study combustion instability from the perspective of structural dynamics, the dynamic response of solid rocket motor grain under oscillating internal pressure was numerically simulated in this paper, and the distribution of grain strain was obtained. Meanwhile, the damages of oscillating internal pressure to the grain structure were predicted. The viscoelastic constitutive model of solid propellant was established by WLF equation, and the oscillating process of internal pressure was described by cyclic load. Based on the theories of modal analysis and harmonic response analysis, numerical simulation and comparative analysis were carried out for different pressure, different length diameter ratio and different residual thickness. The results show that when the internal pressure is 8 to 14 MPa, the maximum principal strain of grain increases continuously with the increase of internal pressure, and the local strain values exceed 20\%, which may lead to the increase of combustion rate. The maximum principal strain increases with the increase of length diameter ratio, and the increasing trend is nonlinear. The maximum principal strain increases with the decrease of residual charge thickness. When the thickness of the residual propellant is 1/5 of the initial thickness, the maximum principal strain reach or exceed 40\%, which is higher than the axial tensile elongation of the propellant. In a word, the oscillating internal pressure has some significant effects on the dynamic response of solid rocket motor grain, and the dynamic response is gr

关键词： Combustion Instability Dynamic Response Pressure

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Cloud-Based Passenger Experience Management in Bus Fare Ticketing Systems Using Random Forest Algorithm 11

Cloud-Based Passenger Experience Management in Bus Fare Tick...

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11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Vadivel, M. Marin, V. Bini Balasubramani, S. Hemalatha, S. Murugan, S. Velmurugan, S. Vidya Jyothi Institute of Technology Department of Electronics and Communication Engineering Telangana Hyderabad India Srm Institute of Science and Technology Faculty of Management Studies Ramapuram Chennai India R.M.D. Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Tagore Engineering College Department of Artificial Intelligence and Data Science Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Biomedical Engineering Tamil Nadu Chennai India Tjs Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350350357

Sustainable urban mobility requires optimizing public transit passenger experiences. This system integrates cloud technologies and the Random Forest algorithm with bus fare ticketing systems to improve efficiency and customer pleasure. Cloud systems provide real-time data processing for price structure and route optimization in research. Cloud computing lets transportation providers quickly adjust to shifting demand, enhancing service dependability and responsiveness. The Random Forest algorithm is integrated into ticketing procedures to estimate passenger demand and optimize prices. Historical ridership data, weather, and special events are used to provide reliable fare estimates and suggestions using machine learning. This case study shows that the suggested approach improves passenger experience, waiting times, and system efficiency in a metropolitan transport network. Scalable, cloud-based infrastructure adapts to different transportation system sizes and configurations. Findings show that cloud computing and machine learning algorithms may make public transportation systems more responsive and passenger-centric. As cities seek smarter, more environmentally friendly transportation solutions, such breakthrough technology offers potential for public transit. © 2024 IEEE.

关键词： Efficiency

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Large Signal Stability Assessment of MPC-based Control for HVDC Electrical Grid

Large Signal Stability Assessment of MPC-based Control for H...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Rohan Kamat Tarcar Ajay Shetgaonkar Marjan Popov Aleksandra Lekić Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft The Netherlands

ISBN: (数字)9798350390421

ISBN: (纸本)9798350390438

The stability of an HVDC transmission network is very important for the reliable transfer of power from renewable energy resources. Therefore, this paper proposes a region of attraction stability analysis method for grid-forming-based modular multilevel converters. The grid forming control uses a model predictive control-based controller for the inner current loop. The stability analysis is carried out using the direct Lyapunov method. For the model predictive control, the modified version of the cost function is used; the same function is also used as the cost function for the direct Lyapunov method. Furthermore, the boundaries formed by the limiters and Lyapunov function entirely explain transient event behavior.

关键词： HVDC transmission Europe Power system stability Cost function Stability analysis Trajectory Smart grids Transient analysis Grid forming Lyapunov methods

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Cloud-Enabled K-Means Clustering for Advancing Wildlife Disease Surveillance and Outbreak Prediction

Cloud-Enabled K-Means Clustering for Advancing Wildlife Dise...

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2024 International Conference on Integration of Emerging Technologies for the Digital World, ICIETDW 2024

作者： Ranganathan, Chitra Sabapathy Rajasekaran, Mothiram Sakthisaravanan, B. Mohankumar, N. Rajmohan, M. Murugan, S. Mphasis Corporation Tamil Nadu Chennai India Pine Candle Way Saint AugustineFL United States Sri Venkateshwara College of Engineering Department of Computer Science and Engineering Karnataka Bengaluru India Symbiosis Institute of Technology Nagpur Campus Pune India Hindustan Institute of Technology and Science Department of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Biomedical Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331541170

The preservation of wildlife and the protection of public health depend on accurate disease monitoring and the ability to predict outbreaks. Advanced computational approaches are necessary since traditional methods struggle to handle massive data sets and the need for real-time analysis. An improved approach for monitoring animal diseases using cloud computing and K-Means clustering is proposed in this research. The method takes use of the scalability of cloud computing to handle massive amounts of data on wildlife health gathered from many sensors. Clustering this data using the K-Means technique to see trends and outliers that might be signs of disease outbreaks. The identification and prediction of wildlife disease outbreaks was greatly enhanced using the cloud-enabled K-Means clustering technology. When compared to more traditional methods, the system's ability to identify epidemics and detect patterns in disease transmission was significantly better. Quicker reaction times, which are essential for timely interventions, were made possible by real-time analytic capabilities. To improve the precision of disease monitoring and outbreak prediction, this method also yields useful data for conservation efforts. The new system is a major step forward in the industry, offering improved and timely management of wildlife health. © 2024 IEEE.

关键词： Electronic health record

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Machine Learning Approaches to Improve Visibility in Global Supply Chains 2

Machine Learning Approaches to Improve Visibility in Global ...

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

作者： Hassan, Muntather Muhsin Chintalapudi, S. Rao Anuradha, Kodali Sharma, Himanshu Theresa Cenate, C.F. Rajaram, Gnanajeyaraman The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq CMR Technical Campus Telangana Hyderabad India GRIET Bachupally Department of CSE Telangana Hyderabad India GLA University Department of Computer Engineering & Applications Mathura India New Prince Shri Bhavani College of Engineering and Technology Department of EEE Tamil Nadu Chennai600073 India Saveetha Institute of Medical and Technical Sciences SIMATS Saveetha School of Engineering Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350368109

Literature review is the main aspect of this research where special attention is given to learning the ways of applying machine learning to enhancing transparency of supply chains all over the world. This is achieved with the help of big data to blend a classical model with several features of the improved ML tool of demand forecasting, anomaly detection, or better route optimization. Data is the whole information collected for analyzing while pre processing means the step through which data is passed before analysis. Model development refers to the process of developing a model which will be followed in practice while implementation refers to the act of practicing what was envisaged in the development of the model. Last but not least, control is the last step in the model implementation process where the outcome of the model is critically determined. The outcome of the research has presented that reliability and effectiveness has been established to achieve an enhanced level of predictability in terms of hit ratio, delivery performance, inventory and overall organizational parameters. It reveals that, if helms properly, then the ML has the capability to increase the effectiveness and visibility of the global supply chain - which is a vital element of any business.. Learning, knowledge creation cannot be a one time process and hence needs continuous application where the stakeholders are the active participants. This study provides informed guidance on the factors that can be applied in integrating ML in supply management. © 2024 IEEE.

关键词： Adversarial machine learning

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