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A brief review of integrated and passive photonic reservoir computing systems and an approach for achieving extra non-linearity in passive devices

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Science China(Information Sciences) 2020年第6期63卷 97-104页

作者： Dachuan WU Yasha YI Yuxiao ZHANG Integrated Nano Optoelectronics Laboratory Department of Electrical and Computer Engineering University of Michigan Energy Institute University of Michigan

Photonic-based reservoir computing(RC) systems have attracted significant attention. Integrated and purely passive systems are compatible with complementary metal-oxide-semiconductor devices,but are limited by the lack of non-linear components. This study consists of two parts: firstly, a review on the published integrated and passive RC system is presented. The review focuses on the structural configuration(rather than the mathematical model) of the neural network; secondly, a new approach for achieving an integrated and passive photonic RC system is introduced and discussed. This approach employs a mode combiner in front of the reservoir to achieve an extra non-linearity in a purely passive device. Moreover,the approach is numerically investigated, and an XOR(exclusive or) task is used to test the device, and the result shows that the new approach satisfies the requirement of an RC system.

关键词： reservoir computing integrated photonics neural network non-linearity

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Experiences from the first delivery of a new immersive software engineering course: mathematical foundations and data analytics

Experiences from the first delivery of a new immersive softw...

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IEEE Annual International computer Software and Applications Conference (COMPSAC)

作者： Florenc Demrozi Marina Marchisio Tiziana Margaria Matteo Sacchet Department of Electrical Engineering and Computer Science University of Stavanger Norway Department of Computer Science and Information Systems University of Limerick Ireland Department of Molecular Biotechnology and Health Sciences University of Turin Italy

According to data from the US Bureau of Labor Statistics, the number of job postings for software engineers has steadily increased over the past few years and is expected to grow by 22% from 2019 to 2029. This paper presents the pedagogical experience within the new Immersive Software engineering (ISE) program concerning mathematical foundations and data analytics topics. These topics were designed to cover essential mathematical concepts such as calculus, linear algebra, probability, and statistics and their integration within data analytic tools and techniques such as time-series forecasting, data cleaning, data visualization, and introduction to pattern recognition. In addition, hands-on projects and real-world applications were incorporated throughout the course to provide students with practical experience in these areas. We reflect on the first delivery of the ISE course, which provided students with a new innovative blended learning environment, and how it will be further developed towards Open Educational Resources (OER) components and refined to respond to the rapidly evolving needs of the software engineering industry.

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Iterative Motion Planning in Multi-agent systems with Opportunistic Communication under Disturbance

arXiv

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arXiv 2025年

作者： Thelasingha, Neelanga Julius, Agung Humann, James Dotterweich, James Dept. of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute NY United States James Humann and James Dotterweich are with DEVCOM Army Research Laboratory MD United States

— In complex multi-agent systems involving heterogeneous teams, uncertainty arises from numerous sources like environmental disturbances, model inaccuracies, and changing tasks. This causes planned trajectories to become infeasible, requiring replanning. Further, different communication architectures used in multi-agent systems give rise to asymmetric knowledge of planned trajectories across the agents. In such systems, replanning must be done in a communication-aware fashion. This paper establishes the conditions for synchronization and feasibility in epistemic planning scenarios introduced by opportunistic communication architectures. We also establish conditions on task satisfaction based on quantified recoverability of disturbances in an iterative planning scheme. We further validate these theoretical results experimentally in a UAV–UGV task assignment problem. © 2025, CC BY.

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An Adaptive Decision-Making Approach for Better Selection of Blockchain Platform for Health Insurance Frauds Detection with Smart Contracts: Development and Performance Evaluation 14

An Adaptive Decision-Making Approach for Better Selection of...

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14th International Conference on Ambient systems, Networks and Technologies Networks, ANT 2023 and The 6th International Conference on Emerging Data and Industry 4.0, EDI40 2023

作者： Kaafarani, Rima Ismail, Leila Zahwe, Oussama ICCS-Lab Computer Science Department American University of Culture and Education Beirut1507 Lebanon Laboratory School of Computing and Information Systems The University of Melbourne Melbourne Australia Laboratory Department of Computer Science and Software Engineering College of Information Technology United Arab Emirates University Abu Dhabi United Arab Emirates National Water and Energy Center United Arab Emirates University Abu Dhabi United Arab Emirates

Blockchain technology has piqued the interest of businesses of all types, while consistently improving and adapting to business requirements. Several blockchain platforms have emerged, making it challenging to select a suitable one for a specific type of business. This paper presents a classification of over one hundred blockchain platforms. We develop smart contracts for detecting healthcare insurance frauds using the top two blockchain platforms selected based on our proposed decision-making map approach which selects the top suitable platforms for healthcare insurance frauds detection application. Our classification shows that the largest percentage of platforms can be used for all types of application domains, the second biggest percentage for financial services, and a small number is to develop applications in specific domains. Our decision-making map and performance evaluations reveal that Hyperledger Fabric surpassed Neo in all metrics for detecting healthcare insurance frauds. © 2023 Elsevier B.V.. All rights reserved.

关键词： Smart contract

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Market Design for Capacity Sharing in Networks

arXiv

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arXiv 2023年

作者： Amin, Saurabh Jaillet, Patrick Pulyassary, Haripriya Wu, Manxi Laboratory for Information and Decision Systems MIT United States Department of Electrical Engineering and Computer Sciences MIT United States Operations Research and Information Engineering Cornell University United States

We study a market mechanism that sets edge prices to incentivize strategic agents to efficiently share limited network capacity. In this market, agents form coalitions, with each coalition sharing a unit capacity of a selected route and making payments to cover edge prices. Our focus is on the existence and computation of market equilibrium, where challenges arise from the interdependence between coalition formation among strategic agents with heterogeneous preferences and route selection that induces a network flow under integral capacity constraints. To address this interplay between coalition formation and network capacity utilization, we introduce a novel approach based on combinatorial auction theory and network flow theory. We establish sufficient conditions on the network topology and agents’ preferences that guarantee both the existence and polynomial-time computation of a market equilibrium. Additionally, we identify a particular market equilibrium that maximizes utilities for all agents and is equivalent to the classical Vickrey-Clarke-Groves mechanism. Furthermore, we extend our results to multi-period settings and general networks, showing that when the sufficient conditions are not met, an equilibrium may still exist but requires more complex, path-based pricing mechanisms that set differentiated prices based on agents’ preference parameters. Copyright © 2023, The Authors. All rights reserved.

关键词： Commerce

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Btcp: Binary Temporal Convolutional Network-Based Data Prefetcher for Low Inference Latency and Storage Overhead Considering Hardware Implementation

SSRN

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SSRN 2024年

作者： Ryu, Chang Ho Kang, Ju Yeon Han, Tae Hee Department of Artificial Intelligence Sungkyunkwan University Korea Republic of Department of Electrical and Computer Engineering Korea Republic of Department of Semiconductor Systems Engineering Sungkyunkwan University Korea Republic of Sungkyunkwan University Korea Republic of

Data prefetching is a crucial strategy for hiding long-latency memory access on modern high-performance processors. Machine learning (ML)-based data prefetchers have demonstrated superior address prediction performance than traditional rule-based prefetchers by learning complex patterns to hide long-latency memory access. However, prioritizing only predictive performance introduces challenges, such as increased inference latency and significant storage demands, when deployed in real hardware systems. To address these issues, we propose a binary temporal convolutional network-based data prefetcher (BTCP) that offers advantages for computational efficiency and memory requirements, enabling feasible hardware implementation. BTCP aids in detecting memory patterns by processing addresses and program counters through bitwise XOR operations and feeding them into a neural network. We employed positional delta maps to predict the closest future address, integrating address deltas with temporal weights for labeling. BTCP facilitates variable-degree prefetching by incorporating the ratio of irregular addresses into the positional delta map for enhanced training. The inference latency and storage overhead of BTCP were measured at 134 cycles and 4,654 bytes, respectively, indicating a substantial decrease of 95.87% and 99.70%, respectively, compared to the leading ML-based prefetcher, TransFetch. With benchmark evaluations using SPEC 2006, SPEC 2017, and GAP, BTCP achieved an IPC improvement of 18.70% over systems without prefetching, surpassing the state-of-the-art rule-based prefetcher SPP by 3.83% and ML-based prefetcher TransFetch by 0.16%. © 2024, The Authors. All rights reserved.

关键词： Machine learning

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Lymphocyte-Infiltrated Periportal Region Detection With Structurally-Refined Deep Portal Segmentation and Heterogeneous Infiltration Features

IEEE Open Journal of Engineering in Medicine and Biology

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IEEE Open Journal of engineering in Medicine and Biology 2024年 5卷 261-270页

作者： Tsai, Hung-Wen Chiou, Chien-Yu Yang, Wei-Jong Hsieh, Tsan-An Chen, Cheng-Yi Hsu, Che-Wei Lin, Yih-Jyh Hsieh, Min-En Yeh, Matthew M. Chen, Chin-Chun Shen, Meng-Ru Chung, Pau-Choo National Cheng Kung University Department of Pathology National Cheng Kung University Hospital College of Medicine Tainan701 Taiwan National Cheng Kung University Department of Electrical Engineering Tainan701 Taiwan National Chin-Yi University of Technology Department of Artificial Intelligence and Computer Engineering Taichung411030 Taiwan National Cheng Kung University Institute of Computer and Communication Engineering Tainan701 Taiwan National Cheng Kung University College of Medicine Department of Cell Biology and Anatomy Tainan701 Taiwan National Cheng Kung University Department of Surgery National Cheng Kung University Hospital College of Medicine Tainan701 Taiwan University of Washington School of Medicine Department of Laboratory Medicine and Pathology SeattleWA98195 United States National Cheng Kung University Department of Statistics Tainan701 Taiwan National Cheng Kung University Department of Pharmacology National Cheng Kung University Hospital College of Medicine Tainan701 Taiwan

Goal: The early diagnosis and treatment of hepatitis is essential to reduce hepatitis-related liver function deterioration and mortality. One component of the widely-used Ishak grading system for the grading of periportal interface hepatitis is based on the percentage of portal borders infiltrated by lymphocytes. Thus, the accurate detection of lymphocyte-infiltrated periportal regions is critical in the diagnosis of hepatitis. However, the infiltrating lymphocytes usually result in the formation of ambiguous and highly-irregular portal boundaries, and thus identifying the infiltrated portal boundary regions precisely using automated methods is challenging. This study aims to develop a deep-learning-based automatic detection framework to assist diagnosis. Methods: The present study proposes a framework consisting of a Structurally-REfined Deep Portal Segmentation module and an Infiltrated Periportal Region Detection module based on heterogeneous infiltration features to accurately identify the infiltrated periportal regions in liver Whole Slide Images. Results: The proposed method achieves 0.725 in F1-score of lymphocyte-infiltrated periportal region detection. Moreover, the statistics of the ratio of the detected infiltrated portal boundary have high correlation to the Ishak grade (Spearman's correlations more than 0.87 with p-values less than 0.001) and medium correlation to the liver function index aspartate aminotransferase and alanine aminotransferase (Spearman's correlations more than 0.63 and 0.57 with p-values less than 0.001). Conclusions: The study shows the statistics of the ratio of infiltrated portal boundary have correlation to the Ishak grade and liver function index. The proposed framework provides pathologists with a useful and reliable tool for hepatitis diagnosis. © 2020 IEEE.

关键词： Feature extraction

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Explaining complex systems: a tutorial on transparency and interpretability in machine learning models (part II)

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IFAC-PapersOnLine 2024年第15期58卷 497-501页

作者： Donatello Materassi Sean Warnick Cristian Rojas Maarten Schoukens Elizabeth Cross Department of Electrical and Computer Engineering University of Minnesota US Department of Homeland Security Science and Technology Directorate EECS/Division of Decision and Control Systems KTH Royal Institute of Technology Control Systems Group Eindhoven University of Technology Eindhoven The Netherlands Department of Mechanical Engineering University of Sheffield

In the second segment of the tutorial, we transition from the granularity of local interpretability to a broader exploration of eXplainable AI (XAI) methods. Building on the specific focus of the first part, which delved into Local Interpretable Model-Agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP), this section takes a more expansive approach. We will navigate through various XAI techniques of more global nature, covering counterfactual explanations, equation discovery, and the integration of physics-informed AI. Unlike the initial part, which concentrated on two specific methods, this section offers a general overview of these broader classes of techniques for explanation. The objective is to provide participants with a comprehensive understanding of the diverse strategies available for making complex machine learning models interpretable on a more global scale.

关键词： eXplainable AI

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Kaiser and Cumulative Proportion Principal Component Analysis for Temperature Compensation of Vibration in Reinforced Concrete Bridge 14

Kaiser and Cumulative Proportion Principal Component Analysi...

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14th IEEE International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2022

作者： Concepcion, Ronnie Cruz, Febus Reidj G. Carpio, Joy Bandala, Argel Relano, R-Jay De Leon, Joseph Aristotle Genevie Janairo, Adrian Guillermo, Marielet Galupino, Joenel Genoguin, Marvin Jade James Loresco, Pocholo De la Salle University Department of Manufacturing Engineering and Management Manila Philippines Mapua University School of Electrical Electronics and Computer Engineering Manila Philippines University of California Systems Engineering Department BerkeleyCA United States De la Salle University Department of Electronics and Computer Engineering Manila Philippines De la Salle University Department of Civil Engineering Manila Philippines Eastern Visayas State University Department of Civil Engineering Tacloban City Philippines FEU Institute of Technology Electrical and Electronics Engineering Department Manila Philippines

ISBN: (纸本)9781665464932

Structural health monitoring (SHM) was developed to provide diagnosis of the state of civil structures, such as bridge and building, throughout their lifespan. The superstructure degrades over time mainly because of the continuous effect of environmental factors including temperature, wind, humidity, and traffic loading. Consequently, this study is concerned in reducing the masking effect of environmental factors, specifically on temperature. Principal component analysis (PCA), a supervised machine learning algorithm, was employed as the embedded statistical treatment for multidimensional reduction of feature matrix data to eliminate the temperature effect. Kaiser's criterion eliminated data variance of almost 20% that may result to poor data reconstruction. Cumulative proportion (CP) criterion eliminated data variance around 4%, which is a better choice for deciding the number of principal components to eliminate. Thus, the proposed experimental study addressed successful temperature compensation from reinforced concrete bridge vibration data by using PCA and CP criterion. © 2022 IEEE.

关键词： Structural health monitoring

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Majorizing Measures, Codes, and Information

arXiv

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arXiv 2023年

作者： Chu, Yifeng Raginsky, Maxim Department of Electrical and Computer Engineering Coordinated Science Laboratory University of Illinois UrbanaIL61801 United States

The majorizing measure theorem of Fernique and Talagrand is a fundamental result in the theory of random processes. It relates the boundedness of random processes indexed by elements of a metric space to complexity measures arising from certain multiscale combinatorial structures, such as packing and covering trees. This paper builds on the ideas first outlined in a little-noticed preprint of Andreas Maurer to present an information-theoretic perspective on the majorizing measure theorem, according to which the boundedness of random processes is phrased in terms of the existence of efficient variable-length codes for the elements of the indexing metric space. © 2023, CC BY.

关键词： Random processes

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