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Fuzzy Intelligence Learning Based on Bounded Rationality in IoMT Systems: A Case Study in Parkinson's Disease

IEEE Transactions on Computational Social Systems 2023年第4期10卷 1607-1621页

作者： Zhang, Chao Ding, Juanjuan Zhan, Jianming Sangaiah, Arun Kumar Li, Deyu Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University School of Computer and Information Technology Taiyuan030006 China Hubei Minzu University School of Mathematics and Statistics Enshi445000 China International Graduate Institute of Artificial Intelligence National Yunlin University of Science and Technology Douliou64002 Taiwan Lebanese American University Department of Electrical and Computer Engineering Byblos1102-2801 Lebanon

As a cause of interfering with routine activities, freezing of gait (FOG) is a severe syndrome of Parkinson's disease (PD) and usually performs as an abrupt and momentary inability to effective stepping forward. Advanced wearable acceleration sensors based on socially implemented Internet of medical things (IoMT) devices can remotely provide a platform for recognizing FOG. However, due to the diverse data acquisition modes that appear in classic IoMT devices, the obtained data may contain imprecise, hesitant, and incomplete ones. Meanwhile, the bounded rationality owned by neurologists usually has a big impact on using wearable acceleration sensors to predict illnesses. Therefore, the objective of this article lies in exploring a fuzzy intelligence learning approach based on bounded rationality in IoMT systems and providing a valid scheme for biomedical data analysis. Specifically, a brand-new three-way group decision-making approach by means of TODIM (an acronym in Portuguese for interactive multicriteria decision-making) with incomplete dual hesitant fuzzy (DHF) information and its applications in detecting FOG in PD using IoMT devices are systematically explored. First, taking advantage of DHF sets (DHFSs) when depicting realistic group decision information, the concept of multigranulation (MG) incomplete DHF information systems is built. Second, adjustable MG DHF probabilistic rough sets (PRSs) are further put forward via DHF similarity relations. Third, a three-way group decision-making approach is constructed by virtue of adjustable MG DHF PRSs and TODIM. Finally, the validity, effectiveness, and practicality of the constructed three-way group decision-making approach are investigated by a University of California, Irvine (UCI) dataset with several experimental analyses in the background of FOG detection in PD using IoMT devices. The experimental result indicates that the developed fuzzy intelligence learning approach achieves reasonable diagnostic conclusions

关键词： Diagnosis

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Successive Pose Estimation and Beam Tracking for mmWave Vehicular Communication Systems

Successive Pose Estimation and Beam Tracking for mmWave Vehi...

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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Liu, Cen Zhu, Guangxu Liu, Fan Liu, Yuanwei Huang, Kaibin National University of Singapore Department of Electrical and Computer Engineering Singapore Shenzhen Research Institute of Big Data Shenzhen China Peng Cheng Laboratory Shenzhen China Guangzhou China Southern University of Science and Technology Department of Electronic and Electrical Engineering Shenzhen China School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong

ISBN: (纸本)9798350370218

The millimeter wave (mmWave) radar sensing-aided communications in vehicular mobile communication systems is investigated. To alleviate the beam training overhead under high mobility scenarios, a successive pose estimation and beam tracking (SPEBT) scheme is proposed to facilitate mmWave communications with the assistance of mmWave radar sensing. The proposed SPEBT scheme first resorts to a Fast Conservative Filtering for Efficient and Accurate Radar odometry (Fast-CFEAR) approach to estimate the vehicle pose consisting of 2-dimensional position and yaw from radar point clouds collected by mmWave radar sensor. Then, the pose estimation information is fed into an extend Kalman filter to perform beam tracking for the line-of-sight channel. Owing to the intrinsic robustness of mmWave radar sensing, the proposed SPEBT scheme is capable of operating reliably under extreme weather/illumination conditions and large-scale global navigation satellite systems (GNSS)-denied environments. The practical deployment of the SPEBT scheme is verified through rigorous testing on a real-world sensing dataset. Simulation results demonstrate that the proposed SPEBT scheme is capable of providing precise pose estimation information and accurate beam tracking output, while reducing the proportion of beam training overhead to less than 5% averagely. © 2023 IEEE.

关键词： beam tracking extended Kalman filter millimeter wave pose estimation radar odometry Sensing-aided communications

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Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

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computer Modeling in engineering & sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

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Design of awideband symmetric large back-off range Doherty power amplifier based on impedance and phase hybrid optimization

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Frontiers of Information Technology & Electronic engineering 2025年第1期26卷 146-156页

作者： Zhongpeng NI Jing XIA Xinyu ZHOU Wa KONG Wence ZHANG Xiaowei ZHU School of Computer Science and Communication Engineering Jiangsu UniversityZhenjiang 212013China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic UniversityHong Kong 999077China State Key Laboratory of Millimeter Waves Southeast UniversityNanjing 210096China

The present paper proposes an optimization design method for the Doherty output matching network(OMN)using impedance–phase hybrid objective function constraints,which possesses the capability of enhancing the efficiency consistency of the Doherty power amplifier(DPA)using integrated enhancing reactance(IER)during the back-off power(BOP)*** calculating the desired reactance for an extended BOP range and combining it with the two-impedance matching method,the S-parameters of the OMN are ***,the impedance and phase constraints of the OMN are proposed to narrow the distribution range of the ***,a fragmenttype structure is employed in the OMN optimization so as to enhance the flexibility of the circuit optimization *** validate the proposed method,a 1.7–2.5 GHz symmetric DPA with a large BOP range was designed and *** results demonstrate that across the entire operating frequency band,the saturated output power is>44 dBm,and the efficiency ranges from 45%to 55%at a 9-dB BOP.

关键词： Back-off power range Doherty power amplifier Fragment-type structure Impedance-phase hybrid function

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A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 812-833页

作者： Xinlei Yi Shengjun Zhang Tao Yang Tianyou Chai Karl Henrik Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technologyand also affiliated with the Digital FuturesStockholm 10044Sweden Department of Electrical Engineering University of North TexasDentonTX 76203 USA IEEE State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China

The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchange is *** problem is an important component of many machine learning techniques with data parallelism,such as deep learning and federated *** propose a distributed primal-dual stochastic gradient descent(SGD)algorithm,suitable for arbitrarily connected communication networks and any smooth(possibly nonconvex)cost *** show that the proposed algorithm achieves the linear speedup convergence rate O(1/(√nT))for general nonconvex cost functions and the linear speedup convergence rate O(1/(nT)) when the global cost function satisfies the Polyak-Lojasiewicz(P-L)condition,where T is the total number of *** also show that the output of the proposed algorithm with constant parameters linearly converges to a neighborhood of a global *** demonstrate through numerical experiments the efficiency of our algorithm in comparison with the baseline centralized SGD and recently proposed distributed SGD algorithms.

关键词： Distributed nonconvex optimization linear speedup Polyak-Lojasiewicz(P-L)condition primal-dual algorithm stochastic gradient descent

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Evolution of Photonics Integrated Circuits for Microwave Photonics Applications

Evolution of Photonics Integrated Circuits for Microwave Pho...

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Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Jianping Yao Microwave Photonics Research Laboratory School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

Integrated microwave photonics to study the use of photonic integrated circuits (PICs) to implement microwave photonic subsystems and systems have been heavily studied for the last few years. In this talk, the evolution of PICs in microwave photonics applications will be discussed with an emphasis on the use of different materials systems to implement photonic integrated microwave photonic systems.

关键词： Optical losses Microwave integrated circuits Costs Masers Photonic integrated circuits Laser stability Microwave circuits

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Van der Waals integration inch-scale 2D MoSe_(2) layers on Si for highly-sensitive broadband photodetection and imaging

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Nano Research 2023年第8期16卷 11422-11429页

作者： Yupiao Wu Shuo-En Wu Jinjin Hei Longhui Zeng Pei Lin Zhifeng Shi Qingming Chen Xinjian Li Xuechao Yu Di Wu School of Physics and Microelectronics and Key Laboratory of Material PhysicsZhengzhou UniversityZhengzhou 450052China Department of Electrical and Computer Engineering University of California San DiegoLa JollaCA 92093USA School of Microelectronics Science and Technology Sun Yat-Sen UniversityZhuhai 519082China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou Institute of Nano-Tech and Nano-BionicsChinese Academy of SciencesSuzhou 215123China

As one of the most promising materials for two-dimensional transition metal chalcogenides(2D TMDs),molybdenum diselenide(MoSe_(2))has great potential in photodetectors due to its excellent properties like tunable bandgap,high carrier mobility,and excellent air *** 2D MoSe_(2)-based photodetectors have been reported to exhibit admired performance,the large-area 2D MoSe_(2)layers are difficult to be achieved via conventional synthesis methods,which severely impedes its future ***,we present the controllable growth of large-area 2D MoSe_(2)layers over 3.5-inch with excellent homogeneity by a simple post-selenization ***,a high-quality n-MoSe_(2)/p-Si van der Waals(vdW)heterojunction device is in-situ fabricated by directly growing 2D n-MoSe_(2)layers on the patterned p-Si substrate,which shows a self-driven broadband photoresponse ranging from ultraviolet to mid-wave infrared with an impressive responsivity of 720.5 mA·W^(−1),a high specific detectivity of 10^(13) Jones,and a fast response time to follow nanosecond pulsed optical *** addition,thanks to the inch-level 2D MoSe_(2)layers,a 4×4 integrated heterojunction device array is achieved,which has demonstrated good uniformity and satisfying imaging *** large-area 2D MoSe_(2)layer and its heterojunction device array have great promise for high-performance photodetection and imaging applications in integrated optoelectronic systems.

关键词： molybdenum diselenide large-area synthesis broadband photodetector integrated device array van der Waals(vdW)heterojunction

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Scalable Community Mentorship: A vision for engineering Literacy & Access

Scalable Community Mentorship: A Vision for Engineering Lite...

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World engineering Education Forum - Global engineering Deans Council (WEEF-GEDC)

作者： Kyle Johnson Vicente Arroyos Liban Hussein Aisha Cora Eman Sherif Celeste Garcia Teanna Barrett Saara Uthmaan Samira Shirazy Jay Cunningham R. Benjamin Shapiro Vikram Iyer AVELA - A Vision for Engineering Literacy & Access Paul G. Allen School of Computer Science & Engineering University of Washington University of Washington Electrical & Computer Engineering University of Washington Human Centered Design & Engineering

ISBN: (数字)9798331519803

ISBN: (纸本)9798331519810

Black and Hispanic/Latine communities remain underrepresented in engineering careers due to persistent economic, social justice, and human rights issues. Consequently, students from these communities face unique challenges when entering into engineering fields. Barriers s tem from economic disenfranchisement, racial profiling, lack of community, and an absence of cultural competence. However, many programs that aim to tackle these issues are not holistic nor scalable to the degree needed for broader impact. To address the lack of holistic and scalable mentorship programs for Black and Hispanic/Latine students, we analyzed AVELA - A vision for engineering Literacy & Access’ (AVELA) holistic student-led STEM engagement model. This model leverages multi-tier near-peer mentorship, mentor-embodied community representation, culturally responsive experiential & service-based learning, and compensated student-led community engagement. Thus far, AVELA has supported 361 university student instructors in teaching to 4,412 secondary school students across 213 classrooms. To evaluate members’ motivations for participating in this mentorship program, we conducted 24 semi-structured interviews with undergraduate and graduate AVELA members. We find AVELA’s holistic student-led STEM engagement model improves Black and Hispanic/Latine engineering students’ experience in post-secondary education. Reduced power dynamics, community involvement, soft skill development, as well as financial support and technical skill building were indicated as key motivators for students’ participation in the program. Students expressed that the depth, applicability, and scale of their mentorship relationships cultivated a reliable student community that empowered them to build a robust professional skill set.

关键词： Economics Cultural competence engineering profession Trajectory Stakeholders Reliability Interviews engineering education Faces STEM

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Massive Point-by-Point Temporal Pulse Shaping for Ultra-High-Speed and Long-Time-Duration Arbitrary Microwave Waveform Generation

Massive Point-by-Point Temporal Pulse Shaping for Ultra-High...

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International Topical Meeting on Microwave Photonics (MWP)

作者： Yiran Guan Jianping Yao Microwave Photonics Research Laboratory School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

ISBN: (数字)9798350375398

ISBN: (纸本)9798350375404

Massive point-by-point temporal pulse shaping to generate ultra-high-speed and long-time-duration arbitrary microwave waveforms based on a temporal Vernier caliper is reported. The temporal Vernier caliper is implemented using a mode-locked laser (MLL) and a fiber loop. The period of a mode-locked pulse train is considered as the main temporal scale division, while the round-trip time of the fiber loop serves as the temporal Vernier scale division. A slight detuning and interpolation between the two temporal divisions result in a small temporal interval, enabling the generation of arbitrary microwave waveforms with a high sampling rate. By temporal duplication of the input pulse, massive temporal pulse shaping with an increased number of points can be realized, enabling the generation of arbitrary microwave waveforms with an extended time duration and increased memory depth. The approach is evaluated experimentally. Analog waveforms at a sampling rate of up to 1 tera-sample-per-second (TSa/s) and communication signals (OOK and PAM4) with a large memory depth of 10.4 kilopoints (kpts) are experimentally generated.

关键词： Optical fibers Interpolation Laser mode locking Masers Microwave communication Optical fiber communication Pulse shaping methods Microwave photonics Fiber lasers

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Once Read is Enough: Domain-specific Pretraining-free Language Models with Cluster-guided Sparse Experts for Long-tail Domain Knowledge 38

Once Read is Enough: Domain-specific Pretraining-free Langua...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Dong, Fang Chen, Mengyi Zhou, Jixian Shi, Yubin Chen, Yixuan Dong, Mingzhi Wang, Yujiang Li, Dongsheng Yang, Xiaochen Zhu, Rui Dick, Robert Lv, Qin Yang, Fan Lu, Tun Gu, Ning Shang, Li China and Shanghai Key Laboratory of Data Science School of Computer Science Fudan University China Oxford Suzhou Centre for Advanced Research Suzhou China University of Bath United Kingdom Microsoft Research Asia Shanghai China School of Mathematics & Statistics University of Glasgow United Kingdom Bayes Business School City St George's University of London United Kingdom Department of Electrical Engineering and Computer Science University of Michigan United States Department of Computer Science University of Colorado Boulder United States School of Microelectronics Fudan University China

Language models (LMs) only pretrained on a general and massive corpus usually cannot attain satisfying performance on domain-specific downstream tasks, and hence, applying domain-specific pretraining to LMs is a common and indispensable practice. However, domain-specific pretraining can be costly and time-consuming, hindering LMs' deployment in real-world applications. In this work, we consider the incapability to memorize domain-specific knowledge embedded in the general corpus with rare occurrences and "long-tail" distributions as the leading cause for pretrained LMs' inferior downstream performance. Analysis of Neural Tangent Kernels (NTKs) reveals that those long-tail data are commonly overlooked in the model's gradient updates and, consequently, are not effectively memorized, leading to poor domain-specific downstream performance. Based on the intuition that data with similar semantic meaning are closer in the embedding space, we devise a Cluster-guided Sparse Expert (CSE) layer to actively learn long-tail domain knowledge typically neglected in previous pretrained LMs. During pretraining, a CSE layer efficiently clusters domain knowledge together and assigns long-tail knowledge to designate extra experts. CSE is also a lightweight structure that only needs to be incorporated in several deep layers. With our training strategy, we found that during pretraining, data of long-tail knowledge gradually formulate isolated, "outlier" clusters in an LM's representation spaces, especially in deeper layers. Our experimental results show that only pretraining CSE-based LMs is enough to achieve superior performance than regularly pretrained-finetuned LMs on various downstream tasks, implying the prospects of domain-specific-pretraining-free language models. © 2024 Neural information processing systems foundation. All rights reserved.

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