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Upper and Lower Bounds of the α-Universal Triple I Method for Unified Interval Implications

computers, Materials & Continua 2024年第4期79卷 1063-1088页

作者： Yiming Tang Jianwei Gao Yifan Huang School of Computer and Information Hefei University of TechnologyHefei230601China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6R 2V4Canada

Theα-universal triple I(α-UTI)method is a recognized scheme in the field of fuzzy reasoning,whichwas proposed by our research group *** robustness of fuzzy reasoning determines the quality of reasoning algorithms to a large extent,which is quantified by calculating the disparity between the output of fuzzy reasoning with interference and the output without ***,in this study,the interval robustness(embodied as the interval stability)of theα-UTI method is explored in the interval-valued fuzzy *** begin with,the stability of theα-UTI method is explored for the case of an individual rule,and the upper and lower bounds of its results are estimated,using four kinds of unified interval implications(including the R-interval implication,the S-interval implication,the QL-interval implication and the interval t-norm implication).Through analysis,it is found that theα-UTI method exhibits good interval stability for an individual ***,the stability of theα-UTI method is revealed in the case of multiple rules,and the upper and lower bounds of its outcomes are *** results show that theα-UTI method is stable for multiple rules when four kinds of unified interval implications are used,***,theα-UTI reasoning chain method is presented,which contains a chain structure with multiple *** corresponding solutions and their interval perturbations are *** is found that theα-UTI reasoning chain method is stable in the case of chain *** application examples in affective computing are given to verify the stability of theα-*** summary,through theoretical proof and example verification,it is found that theα-UTImethod has good interval robustness with four kinds of unified interval implications aiming at the situations of an individual rule,multi-rule and reasoning chain.

关键词： Fuzzy reasoning the CRI method the triple I method fuzzy implication interval robustness

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Excitonic Single- and Two-Photon Photoluminescence Excitations in Bilayer GaN/AlN Nanowires

Excitonic Single- and Two-Photon Photoluminescence Excitatio...

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Cui, Liangqing Wu, You Wu, Yuanpeng Mi, Zetian Kira, Mackillo Norris, Theodore B. Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States

The energy difference between the 1s and 2p exciton states of bilayer GaN/AlN is measured and computed by comparing excitonic resonances in photoluminescence excitation spectra following single- versus two-photon abso... 详细信息

关键词： Photoluminescence

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Data-Driven Human Factors Enabled Digital Twin 49

Data-Driven Human Factors Enabled Digital Twin

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Kolesnikov, Mikhail V. Atmojo, Udayanto Dwi Vyatkin, Valeriy Aalto University Department of Electrical Engineering and Automation Espoo Finland Lulea Tekniska Universitet Department of Computer Science Computer and Space Engineering Sweden

ISBN: (纸本)9798350331820

This paper presents a methodology for increasing human-centric production systems flexibility using human factors-enabled digital twins. The paper includes an analysis of the relevant projects that incorporate human-related data collection and processing. The proposed system is capable of collecting human factors-related data from various sources and then use a decision-making algorithm to schedule the tasks according to assessed human operator conditions in real-time. The formed Digital Twin is able to depict the condition of the labourer and production system status in real-time using Visual Components simulation environment. Shown results prove that existing production systems are capable of adapting to the changing condition of the worker flexibly, optimising workflow, distributing tasks with AGVs and cobots, and applying changes in workplace ergonomics to achieve better safety and performance of the worker. © 2023 IEEE.

关键词： Decision making

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Improving Speed of MUX-FSM-based Stochastic Computing for On-device Neural Networks

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Journal of Computing science and engineering 2022年第2期16卷 79-87页

作者： Kang, Jongsung Kim, Taewhan Department of Electrical Engineering and Computer Science Seoul National University Seoul Korea Republic of

We propose an acceleration technique for processing multiplication operations using stochastic computing (SC) in ondevice neural networks. Recently, multiplexor driven finite state machine (MUX-FSM)-based SCs, which employ a MUX controlled by an FSM to generate a (repeated but short) bit sequence of a binary number to count up for a multiplication operation, considerably reduce the processing time of MAC operations over the traditional stochastic number generator (SNG) based SC. Nevertheless, the existing MUX-FSM-based SCs still do not meet the multiplication processing time required for the wide adoption of on-device neural networks in practice even though it offers a very economical hardware implementation. In this respect, this work proposes a solution that speeds up the conventional MUX-FSMbased SCs. Precisely, we analyze the bit counting pattern produced by MUX-FSM and replace the counting redundancy by shift operation, resulting in a shortening of the length of the required bit sequence significantly, together with analytically formulating the number of computation cycles. Through experiments, we have shown that the enhanced SC technique can reduce the processing time by 44.1% on average over the conventional MUX-FSM-based SCs. © 2022. The Korean Institute of Information Scientists and Engineers

关键词： Embedded systems

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Neural Reactivity to Haptics: Virtual Tasks Versus Physical Tasks

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IEEE Sensors Journal 2024年第7期24卷 11817-11828页

作者： Liu, Yi-Hung Vaitheeshwari, R. Yeh, Shih-Ching Wu, Eric Hsiao-Kuang Institute of Electrical and Control Engineering National Yang Ming Chiao Tung University Hsinchu300093 Taiwan National Central University Department of Computer Science and Information Engineering Taoyuan320 Taiwan

This study investigates the effectiveness of haptic feedback in hand rehabilitation exercises, within both virtual reality (VR) and real-world settings, to enhance upper limb functionality in post-stroke recovery. We developed a VR system that incorporates haptic feedback into pinch simulations and compared its efficacy with similar real-world pinch training exercises, primarily focusing on the rehabilitation of the paretic hand. Our main objective was to ascertain the similarity of the simulated haptic feedback in the VR environment to actual tactile feedback in the real world. This was achieved by analyzing electroencephalogram (EEG) features and psychometric data collected from 35 healthy subjects. A key aspect of our approach was the use of machine learning (ML) techniques to classify the EEG signal features as originating from VR or Real tasks. This classification was based on data from the top-n electrode channels, enabling us to assess the degree of similarity in brain responses to tactile stimulation in both environments. The study's results revealed that the brain activity patterns elicited by haptic feedback were comparable in both the VR and real-world setups. Additionally, the VR feedback system was positively received by users, scoring high on experience and satisfaction metrics. This research provides a replicable methodology for assessing tactile feedback in existing rehabilitation systems and lays the groundwork for the development of novel therapeutic applications. Our findings are crucial for designing future rehabilitation interventions that effectively utilize haptic feedback, potentially leading to improved treatment outcomes for stroke patients. © 2001-2012 IEEE.

关键词： Electroencephalography

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WORK IN PROGRESS: Sensory feedback in laboratories for introductory circuit theory courses

WORK IN PROGRESS: Sensory feedback in laboratories for intro...

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2023 ASEE Annual Conference and Exposition - The Harbor of engineering: Education for 130 Years, ASEE 2023

作者： Faulkner, Brian Marley, Jennifer F. Maguire, Daniel J. Electrical and Computer Engineering Department Milwaukee School of Engineering United States Electrical and Computer Engineering Department Valparaiso University United States

WORK IN PROGRESS: Most engineering students take a course in electric circuits. In a typical circuit laboratory, the focus is on discrete passive components: resistors, inductors, and capacitors. These components do not convert any energy into a form that can be detected by the human senses. The function of the circuit can only be probed with the instrumentation. In this study, we explore the effect of incorporating a transducer (a loudspeaker) as a circuit component. The control group of students construct a high-pass filter with a discrete resistor and capacitor. The experiment group uses a loudspeaker instead of a resistor. Both groups perform a frequency sweep to see the transfer function of the filter. The frequency of the signal manifests itself as the pitch of the sound from the speaker, and the magnitude manifests as the sound volume. Through a brief survey instrument, we investigate how the additional information present in the sound produced by the loudspeaker affects student understanding of high pass and low pass systems and ability to diagnose errors in hardware circuit implementation. Many students reported using their perception of the frequency and volume of the tonal output in their assessment of the circuit purpose (lowpass/highpass). Overall, the students used the output of the speaker to troubleshoot and validate their circuit. Human factors issues related to audible perception were also observed. Qualitative data indicates students use the sensory feedback to interpret the quantitative data and identify errors in their hardware setup. © American Society for engineering Education, 2023.

关键词： Students

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An approach of a quantum-inspired document ranking algorithm by using feature selection methodology

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International Journal of Information Technology (Singapore) 2023年第8期15卷 4041-4053页

作者： Bhagawati, Rupam Subramanian, Thiruselvan Department of Computer Science and Engineering Presidency University Bangalore India Department of Computer Science and Engineering Gitam (Deemed to be University) Bangalore India

The main goal of an information retrieval system (IR) is ranking. Several methodologies were adopted with the integration of computing and advanced applied systems. However, traditional techniques have low stability, and machine learning techniques suffer from feature selection (FS) problems for exponentially growing data. This study speculates that combining quadratic unconstrained binary optimization (QUBO) with quantum annealing (QA) enhances the FS during the ranking process. QA is applied to reduce noisy and redundant data from the various state-of-the-art datasets in the field of IR. This study used the LETOR dataset. LETOR is divided into two versions: LETOR 3.0 (30,000 scientific documents) and LETOR 4.0 (more than 25 million documents). QA reveals the requisite quantum behavior in the findings using a processing unit known as the quantum processing unit (QPU). QPU addresses FS issues written as QUBO optimization problems successfully. The FS problem was QUBO formulated utilizing three quadratic models. A comparison was also made between the linear and QPU solvers employed in the ranking procedure. Quantum-based solutions outperform traditional methods in addressing ranking issues. Compared to the standard algorithms (LTR and LamdaMART), our suggested technique based on QA yields a normalized discounted cumulative gain of 0.39 and 0.80, respectively. QA can address real-world issues by offering practical solutions. QUBO and the QA process have improved feature selection for the ranking process. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Feature selection Information retrieval Quantum annealer Quantum computing Ranking

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A Survey on the Proposed Architectures for Efficient Execution of Irregular Applications Using Pipeline Parallelism

A Survey on the Proposed Architectures for Efficient Executi...

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2023 Congress in computer science, computer engineering, and Applied Computing, CSCE 2023

作者： Khojasteh, Haleh Tabatabaei, Hirad Bridgewater State University Department of Computer Science United States Northeastern University Department of Electrical & Computer Engineering United States

ISBN: (纸本)9798350327595

Irregular applications, which typically involve data structures such as graphs, trees and sparse matrices, present unpredictable memory and network access patterns. The general-purpose processors cannot accommodate the irregular memory access patterns often found in these applications and algorithms sufficiently. We address this challenge by conducting a study of microarchitecture designs aiming to improve the acceleration of irregular applications. This work has an emphasis on decoupled architectures in which applications can be structured as a pipeline of stages decoupled by queues. It also explores the solutions that introduce context switch and memory coalescing methods. © 2023 IEEE.

关键词： Decoupled Architecture Irregular Applications Multithreading Pipeline Parallelism

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LAN Based GIS Optimization for Coverage in Wireless Networks 5

LAN Based GIS Optimization for Coverage in Wireless Networks

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

作者： Atiyah, Israa Salman Cansever, Galip Ahmed, Ali Saadoon Altinbas University Department of Electrical and Computer Engineering Istanbul Turkey AlMaarif University College Department of Computer Science AlAnbar Iraq

ISBN: (纸本)9798350337525

Machine learning is a branch of artificial intelligence based on the idea that systems can learn to identify patterns and make decisions with a minimum of human intervention. In this Paper, demonstration learning will be used, using neural networks in a prototype of a drone built to perform trajectories in controlled environments. To accelerate the training convergence process, a new training data selection approach has been introduced, which picks data from the experience pool based on priority instead of randomness. An autonomous maneuver strategy for dual-UAV olive formation air warfare is provided, which makes use of UAV capabilities such as obstacle avoidance, formation, and confrontation to maximize the effectiveness of the attack. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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AI/ML-Based Water Quality Monitoring Mobile App for Predicting *** in Surface Waters 19

AI/ML-Based Water Quality Monitoring Mobile App for Predicti...

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19th International Conference on Ubiquitous Information Management and Communication, IMCOM 2025

作者： Karumanchi, Keerthi Priya Mhatre, Jui Lee, Ahyoung Lee, Hoseon Department of Computer Science Kennesaw State University MariettaGA30060 United States Department of Electrical and Computer Engineering Kennesaw State University MariettaGA30060 United States

ISBN: (纸本)9798331507817

*** contamination in surface waters has proven to be a significant public health concern, requiring innovative monitoring solutions. This paper presents the design of an AI-driven mobile application to predict whether *** bacteria are present at levels exceeding acceptable thresholds in surface waters. The methodology employs sensor devices to collect water quality data parameters, such as water temperature, pH, dissolved oxygen, and turbidity. A dataset is generated based on these parameters, and machine learning (ML) algorithms are applied to evaluate accuracy, precision, recall, and processing time. Additionally, our ML algorithms establish a correlation matrix among water quality parameters to identify the key factors influencing *** levels. We applied various machine learning techniques to the dataset, including Support Vector Regression (SVR), Random Forest Classification (RFC), XGBoost, and ensemble methods that combine these algorithms. Our findings indicate that the ensemble of Random Forest Classification and XGBoost achieved the highest accuracy at 99.9%. Our Mobile App lets Users view E. coli predictions based on current sensor values. © 2025 IEEE.

关键词： Random forests

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