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2024 International Conference on Automation in Manufacturing, Transportation and Logistics, ICaMaL 2024

作者： Li, Xiaorui Ban, Xiaojuan Shao, Yizhou Chen, Haowei Yao, Chao Yuan, Zhaolin Liu, Guangsheng Guo, Lijie Institute of Artificial Intelligence University of Science and Technology Beijing Beijing China School of Artificial Intelligence Hebei University of Technology Beijing China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Hong Kong Polytechnic University Department of Industrial and Systems Engineering Hong Kong Hong Kong BGRIMM Technology Group Beijing China

ISBN: (纸本)9798350378658

In process CPS systems, highly accurate modeling of the production system is essential for optimal control, fault diagnosis, and flexible manufacturing. Traditional data-driven modeling of industrial processes focuses on predicting future trends based on variable periodicity and trends, often neglecting the impact of control variables. This paper proposes a new approach to improve CPS accuracy, particularly for systems heavily influenced by controlled variables. Firstly, CPS modeling is redefined as a time series imputation problem, introducing exogenous variables via a sequence modeling algorithm based on a state space model to enhance forecasting accuracy. Secondly, sequence inputs are encoded in patches, improving the model's ability to process local sequence information. The proposed method is evaluated on a real deep cone thickener underflow concentration forecasting task and compared with state-of-The-Art time series forecasting methods, demonstrating superior performance. This study not only provides a more accurate model for CPS but also offers a framework for integrating control variables into predictive modeling. © 2024 IEEE.

关键词： Flexible manufacturing systems

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Detecting Hallucinations in Large Language Model Generation: A Token Probability Approach 26th

Detecting Hallucinations in Large Language Model Generation...

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26th International Conference on Artificial Intelligence and Applications, ICAI 2024, held as part of the World Congress in computer science, computer engineering and Applied Computing, CSCE 2024

作者： Quevedo, Ernesto Salazar, Jorge Yero Koerner, Rachel Rivas, Pablo Cerny, Tomas Department of Computer Science Baylor University Texas United States Department of Systems and Industrial Engineering The University of Arizona Tucson United States

ISBN: (纸本)9783031866227

Concerns regarding the propensity of Large Language Models (LLMs) to produce inaccurate outputs, also known as hallucinations, have escalated. Detecting them is vital for ensuring the reliability of applications relying on LLM-generated content. Current methods often demand substantial resources and rely on extensive LLMs or employ supervised learning with multidimensional features or intricate linguistic and semantic analyses difficult to reproduce and largely depend on using the same LLM that hallucinated. This paper introduces a supervised learning approach employing two simple classifiers utilizing only four numerical features derived from tokens and vocabulary probabilities obtained from other LLM evaluators, which are not necessarily the same. The method yields promising results, surpassing state-of-the-art outcomes in multiple tasks across three different benchmarks. Additionally, we provide a comprehensive examination of the strengths and weaknesses of our approach, highlighting the significance of the features utilized and the LLM employed as an evaluator. We have released our code publicly at https://***/Baylor-AI/HalluDetect. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Supervised learning

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Innovative Data Encryption Techniques using AI for Wireless Sensor Actuator Network Security

Innovative Data Encryption Techniques using AI for Wireless ...

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Distributed Computing and Optimization Techniques (ICDCOT), International Conference on

作者： M Dharmateja Prabha K.P. Rama N Asha P Nithya S. Lalitha P Manojkumar Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai Tamil Nadu India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore Tamil Nadu India Department of computer science and Engineering Arunai Engineering college Tiruvannamalai Tamil Nadu India Department of Electrical and Electronics Engineering Bannari Amman Institute of Technology Sathyamangalam Tamil Nadu India

Wireless Sensor Actuator Networks (WSANs) are sensitive to cyber threats due to present static encryption techniques. Adaptive security methods are required in WSAN settings to reduce evolving dangers and maintain data integrity. The paper introduces a novel method for encrypting WSAN data using AI and machine learning. Long Short-Term Memory (LSTM) networks process data, Genetic Algorithms (GAs) optimize encryption, and Isolation Forests detect threats in real-time. The proposed system achieved remarkable performance, with scores of 98% data integrity, 96% error repair, and 95% threat detection accuracy. Encryption rates reach their max at 200 Mbps, with optimal resource usage (30% CPU, 25% RAM) and a 5% false positive rate. The proposed AI-driven security architecture improves data integrity, encryption speed, and overall security efficacy in WSANs, surpassing existing methods. The paper overcomes the limitations of static encryption methods and proposes a proactive protection mechanism against developing cyber threats, making a substantial contribution to WSAN security improvement.

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Testing Temperature-Dependent Resistors as Potential Physical Unclonable Functions

Testing Temperature-Dependent Resistors as Potential Physica...

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IEEE World Forum on Internet of Things (WF-IoT)

作者： El Mehdi Bahoum Nico Mexis Stefan Katzenbeisser Tolga Arul Nikolaos Athanasios Anagnostopoulos Faculty of Computer Science and Mathematics University of Passau Passau Germany Chair of Computer Engineering University of Passau Passau Germany Chair of Reliable Distributed Systems University of Passau Passau Germany

ISBN: (数字)9798350373011

ISBN: (纸本)9798350373028

This work investigates the potential of temperature-dependent resistors to serve as Physical Unclonable Functions (PUFs). Five types of temperature-dependent resistors were subjected to testing at four different temperatures. The analysis of the collected data revealed patterns and trends that do not immediately qualify the devices as PUFs, but indicate their potential to be utilised for the realisation of unique responses based on them. In particular, by applying a binary discretisation technique, distinct behaviour profiles were identified for temperature sensors of the Platinum 100 (Pt100) type, enabling the differentiation of these sensors based on their response characteristics. On the contrary, the sensors of the Pt1000 type did not display such distinct behaviour, as some of these sensors result in exactly the same binary response. In general, our work offers a systematic approach towards the creation of PUFs based on temperature-dependent resistors, paving the way for their use in enhancing the security of the devices in which these sensors are incorporated.

关键词： Temperature sensors Resistors Temperature measurement Temperature Systematics Sensor phenomena and characterization Physical unclonable function Security Electrical resistance measurement Testing

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Nonlinear Bandwidth and Bode Diagrams based on Scaled Relative Graphs

arXiv

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arXiv 2025年

作者： Krebbekx, Julius P.J. Tóth, Roland Das, Amritam Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Netherlands Systems and Control Lab HUN-REN Institute for Computer Science and Control Budapest Hungary

Scaled Relative Graphs (SRGs) provide a novel graphical frequency domain method for the analysis of nonlinear systems. In this paper, we use the restriction of the SRG to particular input spaces to compute frequency-dependent gain bounds for incrementally stable nonlinear systems. This leads to a nonlinear (NL) generalization of the Bode diagram, where the sinusoidal, harmonic, and subharmonic inputs are considered separately. When applied to the analysis of the NL loop transfer and sensitivity, we define a notion of bandwidth for both the open-loop and closed-loop, compatible with the LTI definitions. We illustrate the power of our method on the analysis of a DC motor with a parasitic nonlinearity, verifying our results in simulations. © 2025, CC BY.

关键词： Frequency domain analysis

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Electric Bike Security and Protection System

Electric Bike Security and Protection System

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Artificial Intelligence and Machine Learning Applications Theme: Healthcare and Internet of Things (AIMLA), International Conference on

作者： P. Maniraj A. Durai Murugan Gokul R Shalini A S Kesavan K Kavin P Department of Electrical and Electronics Engineering M. Kumarasamy College of Engineering Karur India Department of Computer Science and Business Systems M. Kumarasamy College of Engineering Karur India Computer Science and Business Systems M. Kumarasamy College of Engineering Karur India Electrical and Electronics Engineering M. Kumarasamy College of Engineering Karur India

ISBN: (数字)9798350349221

ISBN: (纸本)9798350349238

With the developing prevalence of electric bicycles (e-bicycles) as a feasible and proficient method of transportation, guaranteeing their security has turned into a foremost concern. Electric bicycles are important resources helpless against robbery and harm, to conquer this issue the venture proposes the improvement of an Electric Vehicle Burglary Location and Warning Framework utilizing IOT innovation. The framework integrates sensors to screen electric vehicles for unapproved access and utilizes Radio Recurrence ID innovation to improve security. After recognizing an unfair RFID section or any dubious movement, the framework sets off a caution to tell the proprietor and naturally locks the back tire, forestalling robbery. This framework could be an instrument for deflecting the robbery of electric vehicles and keeping proprietors from monetary misfortunes. In a period of developing IOT-based security arrangements, this framework offers an important expansion to safeguard electric vehicle and their venture.

关键词： Technological innovation Insurance Transportation Bicycles Forestry Electric vehicles Tires

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Cognitive Workload and Usability of Virtual Reality Simulation for Prosthesis Training

Cognitive Workload and Usability of Virtual Reality Simulati...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Park, Junho Music, Austin Delgado, Daniel Berman, Joseph Dodson, Albert Liu, Yunmei Ruiz, Jaime Huang, He Kaber, David Zahabi, Maryam Texas A&m University Wm Michael Barnes '64 Department of Industrial & Systems Engineering College StationTX United States University of Florida Department of Computer & Information Science & Engineering GainesvilleFL United States North Carolina State University Department of Electrical and Computer Engineering RaleighNC United States North Carolina State University University of North Carolina at Chapel Hill Joint Department of Biomedical Engineering RaleighNC United States University of Florida Department of Industrial and Systems Engineering GainesvilleFL United States

ISBN: (纸本)9798350337020

Amputees use prosthetic devices to perform activities of daily living. However, some users reject their devices due to the lack of usability or high cognitive workload. Although virtual reality has been studied in this domain for training purposes, there has not been any investigation on usability and cognitive workload of using virtual reality simulations for training of prosthetic devices. The objective of this study was to compare cognitive workload and usability of using virtual reality-based simulation of electromyography based prosthetic devices and physical devices. The findings suggested that using virtual reality simulations were helpful in reducing cognitive workload and increasing perceived usability of prosthetic devices. © 2023 IEEE.

关键词： cognitive workload prosthesis training usability virtual reality

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Freestanding region-responsive bilayer for functional packaging of ingestible devices

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Microsystems & Nanoengineering 2023年第3期9卷 285-295页

作者： Michael A.Straker Joshua A.Levy Justin M.Stine Vivian Borbash Luke A.Beardslee Reza Ghodssi Fischell Department of Bioengineering University of MarylandCollege ParkMD 20742USA Institute for Systems Research University of MarylandCollege ParkMD 20740USA Robert E.Fischell Institute for Biomedical Devices University of MarylandCollege ParkMD 20850USA Department of Material Science and Engineering University of MarylandCollege ParkMD 20740USA Department of Electrical and Computer Engineering University of MarylandCollege ParkMD 20742USA

Ingestible capsules have the potential to become an attractive alternative to traditional means of treating and detecting gastrointestinal(GI)*** device complexity increases,so too does the demand for more effective capsule packaging technologies to elegantly target specific GI *** pH-responsive coatings have been traditionally used for the passive targeting of specific GI regions,their application is limited due to the geometric restrictions imposed by standard coating ***,pan,and spray coating methods only enable the protection of microscale unsupported openings against the harsh GI ***,some emerging technologies have millimeter-scale components for performing functions such as sensing and drug *** this end,we present the freestanding region-responsive bilayer(FRRB),a packaging technology for ingestible capsules that can be readily applied for various functional ingestible capsule *** bilayer is composed of rigid polyethylene glycol(PEG)under a flexible pH-responsive Eudragit®FL 30 D 55,which protects the contents of the capsule until it arrives in the targeted intestinal *** FRRB can be fabricated in a multitude of shapes that facilitate various functional packaging mechanisms,some of which are demonstrated *** this paper,we characterize and validate the use of this technology in a simulated intestinal environment,confirming that the FRRB can be tuned for small intestinal *** also show a case example where the FRRB is used to protect and expose a thermomechanical actuator for targeted drug delivery.

关键词： coating packaging attractive

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A novel method for the detection and classification of multiple diseases using transfer learning-based deep learning techniques with improved performance

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Neural Computing and Applications 2024年第30期36卷 18979-18997页

作者： Natarajan, Krishnamoorthy Muthusamy, Suresh Sha, Mizaj Shabil Sadasivuni, Kishor Kumar Sekaran, Sreejith Charles Gnanakkan, Christober Asir Rajan A.Elngar, Ahmed School of Computer Science Engineering and Information Systems Vellore Institute of Technology Tamil Nadu Vellore India Tamil Nadu Perundurai Erode India Centre for Advanced Materials Qatar University Doha Qatar Department of Mechanical and Industrial Engineering Qatar University PO Box 2713 Doha Qatar Department of Electrical Engineering National Institute of Technology Assam Silchar India Department of Electrical and Electronics Engineering Puducherry Technological University Puducherry India Faculty of Computers and Artificial Intelligence Beni-Suef University Beni-Suef City62511 Egypt

A disease is a distinct abnormal state that significantly affects the functioning of all or part of an individual and is not caused by external harm. Diseases are frequently understood as medical conditions connected with distinct indications and symptoms. According to a fairly wide categorization, diseases can also be categorized as mental disorders, deficient diseases, genetic diseases, degenerative diseases, self-inflicted diseases, infectious diseases, non-infectious diseases, social diseases, and physical diseases. Prevention of the diseases is of multiple instances. Primary prevention seeks to prevent illness or harm before it ever happens. Secondary prevention tries to lessen the effect of an illness or damage that has already happened. This is done through diagnosing and treating illness or injury as soon as feasible to stop or delay its course, supporting personal ways to avoid recurrence or reinjury, and implementing programs to restore individuals to their previous health and function to prevent long-term difficulties. Tertiary prevention tries to lessen the impact of a continuing sickness or injury that has enduring repercussions. Diagnosis of the disease at an earlier stage is important for the treatment of the disease. Hence, in this study, deep learning algorithms, such as VGG16, EfficientNetB4, and ResNet, are utilized to diagnose various diseases, such as Alzheimer's, brain tumors, skin diseases, and lung diseases. Chest X-rays, MRI scans, CT scans, and skin lesions are used to diagnose the mentioned diseases. Transfer learning algorithms, such as VGG16, VGG19, ResNet, InceptionV3, and EfficientNetB4, are utilized to categorize various diseases. EfficientNetB4 with the learning rate annealing, having obtained an accuracy of 94.04% on the test dataset, is observed. As a consequence, we observed that every network has unique particular skills on the multi-disease dataset, which includes chest X-rays, MRI scans, etc., © The Author(s) 2024.

关键词： Diseases

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Modern Hardware Security: A Review of Attacks and Countermeasures

arXiv

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arXiv 2025年

作者： Mishra, Jyotiprakash Sahay, Sanjay K. Department of Computer Science & Information Systems BITS Pilani K K Birla Goa Campus Goa Zuarinagar403726 India School of Computer Engineering KIIT University Odisha Bhubaneswar751024 India

With the exponential rise in the use of cloud services, smart devices, and IoT devices, advanced cyber attacks have become increasingly sophisticated and ubiquitous. Furthermore, the rapid evolution of computing architectures and memory technologies has created an urgent need to understand and address hardware security vulnerabilities. In this paper, we review the current state of vulnerabilities and mitigation strategies in contemporary computing systems. We discuss cache side-channel attacks (including Spectre and Meltdown), power side-channel attacks (such as Simple Power Analysis, Differential Power Analysis, Correlation Power Analysis, and Template Attacks), and advanced techniques like Voltage Glitching and Electromagnetic Analysis to help understand and build robust cybersecurity defense systems and guide further research. We also examine memory encryption, focusing on confidentiality, granularity, key management, masking, and re-keying strategies. Additionally, we cover Cryptographic Instruction Set Architectures, Secure Boot, Root of Trust mechanisms, Physical Unclonable Functions, and hardware fault injection techniques. The paper concludes with an analysis of the RISC-V architecture's unique security challenges. The comprehensive analysis presented in this paper is essential for building resilient hardware security solutions that can protect against both current and emerging threats in an increasingly challenging security landscape. © 2025, CC BY-NC-ND.

关键词： Cyber attacks

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