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Algebraic Reproduction of Triage Decision Making on Simple Heuristics of Boolean Multivalued Logic

Algebraic Reproduction of Triage Decision Making on Simple H...

引用

computational intelligence in Health and Medicine (CIHM), ieee symposium on

作者： Taira Watanabe Taishi Nishizaka Kujira Suzuki Atsushi Nishikawa Hitoshi Katai Hisashi Suzuki Graduate School of Engineering Science Osaka University Osaka Japan Faculty of Science and Engineering Chuo University Tokyo Japan Cancer Center Tachikawa Hospital Tokyo Japan

ISBN: (数字)9798331508333

ISBN: (纸本)9798331508340

In this research, we consider a simplified disaster situation for a thought experiment where priorities must be assigned when treating victims. We model egalitarian decision making, utilitarian decision making, and triage decision making (which combines both egalitarian and utilitarian decision makings) using a quantum computing-like multivalued logic that forms a Boolean algebra in contrast to popular multivalued logics that lack algebraic consistency. As a result, this article reports that some simple heuristic rules can quantitatively and algebraically reproduce and control human decisions regarding the prioritization of treatment for victims that reflects bioethical considerations.

关键词： Ethics Quantum computing Disasters computational modeling Decision making Multivalued logic Boolean algebra computational intelligence Dementia

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Identifying and Implementing Common Tactics to Disrupt IoT Device Functionality Over TCP/IP Stacks

Identifying and Implementing Common Tactics to Disrupt IoT D...

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International symposium on computational intelligence and Informatics

作者： Szabolcs Hajdu Gerlinda Boglarka Kis Albert Zsombor Fekete Dénes Nimród Kutasi Department of Electrical Engineering Sapientia Hungarian University of Transylvania Targu Mures Romania Tetronic SRL Targu Mures Romania

ISBN: (数字)9798350353433

ISBN: (纸本)9798350353440

The proliferation of Internet of Things (IoT) devices in home automation systems has introduced unprecedented convenience but also raised serious concerns regarding security vulnerabilities [1]. This paper delves into the exploration of common vulnerabilities present in IoT-based home automation systems and proposes easily implemented solutions to disrupt their functionality. Through a comprehensive analysis of popular IoT devices, protocols, and communication channels, we identify key vulnerabilities that expose these systems to potential attacks, encompassing unauthorized access, data breaches, and device manipulation. Our findings contribute to the ongoing discourse on securing IoT devices and systems, emphasizing the need for proactive measures to safeguard user privacy, data integrity, and overall system reliability. By disseminating easily deployable solutions, we intend to foster a safer and more resilient environment for the growing landscape of IoT home automation.

关键词： Wireless communication Home automation Protocols Filtering TCPIP Passwords Time measurement Internet of Things Object recognition Reliability

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Classification of Reachable Markings for Automated Manufacturing Systems with Multiple Unreliable Resources 21

Classification of Reachable Markings for Automated Manufactu...

引用

21st International Conference on Networking, Sensing and control, ICNSC 2024

作者： Shen, Jiahui Qian, Chenyang Liu, Huixia Sun, Wenqiang School of Electrical Engineering and Automation Nantong University Nantong China Ore Terminal Branch Yantai Port Co. Ltd Yantai China

ISBN: (纸本)9798350365221

It is a hot issue to discuss the robust control policy for automated manufacturing systems (AMSs) with unreliable resources in recent years. Before designing a robust controller, it is necessary to analyze the production processes of AMSs with unreliable resources. In our work, we study the classification of production states for AMSs with multiple unreliable resources. First, Petri nets are utilized to model the above systems. Second, the reachable markings of Petri nets describing undesired production states are classified into four types, such as deadlocks, F-deadlocks, F-blockings and FP-blockings by the structural characterization, maximal perfect resource-transition circuits, of Petri nets. Next, we prove that all undesired reachable markings are only the above four types for a kind of AMSs with multiple unreliable resources. Finally, an algorithm to compute all deadlocks, F-deadlocks, F-blockings and FP-blockings with low computational complexity is presented, and an example is utilized to illustrate the validity of the conclusion and the algorithm. © 2024 ieee.

关键词： Robust control

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A Structure-Based Method for Prediction of Protein-Protein Interaction Sites Through Combining Local and Global Features 8th

A Structure-Based Method for Prediction of Protein-Protein...

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8th International Conference on Life System Modeling and Simulation, LSMS 2024 and 8th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Zhang, Hongyang Zhao, Yanpeng Liu, Ziyi He, Song Bo, Xiaochen Zan, Peng School of Mechatronics Engineering and Automation Shanghai Key Laboratory of Power Station Automation Technology Shanghai University Shanghai200444 China Department of Biotechnology Institute of Health Service and Transfusion Medicine Beijing100850 China

ISBN: (纸本)9789819601875

The identification of protein-protein interaction(PPI) sites is critical for drug discovery and analysis of protein function. So far, numerous computational methods based on artificial intelligence have been developed to accelerate the identification of PPI sites. However, those methods learned only sequential features or local structural features, leading to low predictive performance. Therefore, it is urgently necessary to develop a new method to improve the performance of predicting PPI sites. Herein, a new structure-based method for predicting the protein-protein interaction sites through combing the local and global encoder, SLGPPIS, was therefore proposed. Specifically, SLGPPIS utilizes the local and global encoder to extract the residue feature respectively and concatenating them to predict the PPI sites. Compared with other existing methods, SLGPPIS exhibited superior performance on prediction of PPI sites. Moreover, a visual interpretative experiment was conducted to systematically investigate the prediction process of SLGPPIS. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Prediction models

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Robot PID control Using Reinforcement Learning

Robot PID Control Using Reinforcement Learning

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ieee symposium Series on computational intelligence (SSCI)

作者： Guillermo Puriel Xiaoou Li Brisbane Ovilla-Martinez Wen Yu Departamento de Control Automático CINVESTAV-IPN Mexico City Mexico Departamento de Computación CINVESTAV-IPN Mexico City Mexico

In this paper, the robot PID control is compensated by the reinforcement learning. The controller adjustment is proposed by the stability analysis. The reinforcement learning can compensate the dynamics of the robot. This method avoids the problems due to big integral gain of classical PID control. The experimental results show the effectiveness of the proposed controller.

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Speeding-Up Complex RF IC Sizing Optimizations with a Process, Voltage and Temperature Corner Performance Estimator based on ANNs

Speeding-Up Complex RF IC Sizing Optimizations with a Proces...

引用

ieee International symposium on Circuits and Systems (ISCAS)

作者： Vaz, Pedro Gusmao, Antonio Horta, Nuno Lourenco, Nuno Martins, Ricardo Inst Telecomunicacoes Aveiro Portugal Univ Lisbon Inst Super Tecn Lisbon Portugal Univ Evora Evora Portugal

ISBN: (纸本)9781665484855

The automatic sizing of radio-frequency (RF) integrated circuit (IC) blocks in deep nanometer technologies has moved towards process, voltage, and temperature (PVT)-inclusive optimizations, to ensure their robustness. Each sizing solution is exhaustively simulated in a set of PVT corners, thus pushing modern workstations' capabilities to their limits. This paper presents innovative research towards the automation of RF IC design by using deep learning to assist the simulation-based sizing tools in time-consuming PVT-inclusive optimizations. The proposed PVT regressor inputs the circuit's sizing and the nominal performances to estimate the PVT corner performances via multiple parallel artificial neural networks. Two control phases prevent the optimization process from being misled by inaccurate performance estimates. The proposed controlled PVT estimator is tested on a state-of-the-art class C/D voltage-controlled oscillator, reducing the workload of the circuit simulator up to 79% while achieving a speed-up factor of 2.92x, ultimately saving more than 16 days of computational effort.

关键词： Artificial Neural Networks Radio-Frequency Integrated Circuits Electronic Design automation Deep Learning

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computationally Efficient CNN Based Smart Dehaze Net for Haze Removal of Biomedical Images

Computationally Efficient CNN Based Smart Dehaze Net for Haz...

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2024 ieee International Conference on Signal Processing, Informatics, Communication and Energy Systems, SPICES 2024

作者： Padmadarsan Biju, K.S. Sravan, M.S. Government Polytechnic College Neyyattinkara Department of Electronics and Communication Thiruvananthapuram695126 India College of Engineering Thiruvananthapuram Department of Electronics and Communication Thiruvananthapuram695016 India Directorate of Technical Education Kerala Department of Electronics and Communication Thiruvananthapuram695023 India

ISBN: (数字)9798350376135

ISBN: (纸本)9798350376135

Artificial intelligence has made significant strides recently especially in the field of computer vision. It played a pivotal role in revolutionising the automation, reliability and robustness of the most modern biomedical applications like CT scan, PET scan, Fundoscopy etc. Due to the wide spread use of camera sensors for examining the internal organs like Liver, Gall bladder, Retina etc, haze free images are absolutely essential. Most of the images captured by the visual sensors have haze introduced due to various environmental factors like suspended particles in air which badly affects the fidelity of the images captured by camera sensors. Image dehazing is a process of removing the haze and thereby improving the overall image quality. Image dehazing finds extensive applications especially in the fields of surveillance systems, defence, air traffic control, traffic cameras, self-driven cars, under water imaging etc. In this paper a computationally efficient CNN architecture with eight convolution and three concatenation layers is proposed which removes the haze without much degradation in colour and contrast of the image. The Proposed model is trained on NYU2 dataset and provided a 166% hike in the PSNR when compared with the best of the available haze removal techniques. Also the BRISQUE value and entropy of the haze removed image went up by 80.95 %. and 100.78% respectively over the current state of the art haze removal techniques. Also the model shown 59% reduction in computational time. © 2024 ieee.

关键词： Air traffic control

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Wind Power Scenario Generation Based on Denoising Diffusion Probabilistic Model

Wind Power Scenario Generation Based on Denoising Diffusion ...

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2023 ieee International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Xu, Chenglong Dai, Yuxin Xu, Peidong Gao, Tianlu Zhang, Jun School of Electrical Engineering and Automation Wuhan University Wuhan China

ISBN: (纸本)9798350337020

The intermittency and randomness of wind power output have a negative impact on the stable operation of the power grid. Accurately modeling the uncertainty of wind power output is essential, and the primary method to achieve this is through scenario generation. Traditional scenario generation methods suffer from limitations such as low accuracy and high computational complexity. In this paper, a novel generation framework based on the denoising diffusion probabilistic model is presented and proposed for scenario generation of wind power. This method can overcome the limitations of traditional methods and learn the distribution of real data to generate reliable wind power scenarios. Compared to a homogeneous generative model, the proposed method shows improved performance in precisely capturing features of wind power scenarios. © 2023 ieee.

关键词： deep learning diffusion model scenario generation wind power

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Adaptive Fault-Tolerant Tracking control of Flexible Spacecraft against Actuator Failures

Adaptive Fault-Tolerant Tracking Control of Flexible Spacecr...

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2023 CAA symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2023

作者： Lu, Shuangshuang Zhao, Dong Huang, Darong Ren, Wenjing Anhui University School of Artificial Intelligence Hefei China Hefei University of Technology School of Electrical Engineering and Automation Hefei China

ISBN: (纸本)9798350337754

This paper studies an actuator boundary fault compensation problem for flexible spacecrafts, using a model transform based direct adaptive control technique. In order to portray the strong coupling characteristics of flexible vibration and rigid motion precisely, the overall system dynamics is modeled by an interconnected partial differential equation-ordinary differential equation. By introducing a new auxiliary signal, a pioneering adaptive fault-tolerant boundary control scheme is put forth. The complete closed-loop system stability is ensured by using the modified direct Lyapunov method. © 2023 ieee.

关键词： Closed loop systems

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Fail-Safe Decision Architecture for Positioning Failures on Automated Vehicles 9

Fail-Safe Decision Architecture for Positioning Failures on ...

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9th ieee Smart World Congress, SWC 2023

作者： Rodriguez-Arozamena, Mario Aranguren-Mendieta, Inigo Perez, Joshue Zubizarreta, Asier Tecnalia Basque Research and Technology Alliance Bilbao Derio Spain Basque Research and Technology Alliance Industry and Mobility Unit Tecnalia Derio Spain Dept. of Automatic Control and Systems Engineering Bilbao Spain

ISBN: (纸本)9798350319804

Precise localization is essential for the operation of Connected and Automated Vehicles (CAVs) in urban scenarios. Camera and LiDAR-based solutions are currently used in some of the CAVs around the world, but they entail an expensive performance in terms of computational time and economic cost. Due to this, Global Navigation Satellite System (GNSS) based solutions remains the preferred solution for positioning Automated Vehicles in different Operational Design Domains (ODDs). Although several improvements in system reliability have been made recently, in case of positioning failures most of the architectures rely on system redundancy or automation disengagements to achieve minimal risk conditions. This paper presents a fail-safe decision architecture for mitigating positioning failures of automated vehicles in urban scenarios. The proposed architecture utilizes a combination of sensor fusion localization and decision-making modules to ensure the safe and efficient operation of the vehicle in the event of a positioning failure. The proposed approach is evaluated through simulation in a representative urban scenario and is shown to effectively handle positioning failures, improving the localization accuracy provided by each information source. © 2023 ieee.

关键词： automated driving fail-safe operation fallback strategy positioning failure safe state

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