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arXiv 2024年

作者： Zhang, Kunpeng Yi, Xinlei Wen, Guanghui Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China The Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States The Department of Mathematics Southeast University Nanjing210096 China The Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers the distributed bandit convex optimization problem with time-varying inequality constraints over a network of agents, where the goal is to minimize network regret and cumulative constraint violation. Existing distributed online algorithms require that each agent broadcasts its decision to its neighbors at each iteration. To better utilize the limited communication resources, we propose a distributed event-triggered online primal-dual algorithm with two-point bandit feedback. Under several classes of appropriately chosen decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. These bounds are comparable to the results achieved by distributed event-triggered online algorithms with full-information feedback. Finally, a numerical example is provided to verify the theoretical results. Copyright © 2024, The Authors. All rights reserved.

关键词： Convex optimization

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Mm-Wave to Sub-THz Frequencies for Non-Invasive Melamine Detection in Food Safety

Mm-Wave to Sub-THz Frequencies for Non-Invasive Melamine Det...

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IEEE Conference on Antenna Measurements & Applications (CAMA)

作者： Nguyen Ngoc Mai-Khanh Shitaro Takada Keizo Inagaki Ahmad Alkasimi Anh-Vu Pham Akio Higo Bich-Yen Nguyen Tetsuya Kawanishi Systems Design Lab (d.lab) The University of Tokyo Tokyo Japan Faculty of Science and Engineering Waseda University Tokyo Japan National Inst. Of Information and Conmmunications Technology (NICT) Tokyo Japan Department of Electrical and Computer Engineering King Abdulaziz University Jeddah Saudi Arabia Electrical and Computer Engineering University of California Davis California U.S. Soitec France Waseda University Tokyo Japan

This paper presents the exploration of the detection of melamine, a harmful substance, across a wide mm-wave frequency range for food safety applications. The experiment investigates the presence of melamine impurities in rice and milk powders. To conduct the experiment, two different approaches are utilized: a 77-GHz radar approach and a vector network analyzer connected to frequency extenders and standard horn antennas. These approaches cover two frequency bands, namely 220-330 GHz and then 330-500 GHz. The substances involved in the measurements are melamine, milk, rice, and their mixtures. In addition, we propose a technique for the quantitative determination of melamine in mixtures. This method was validated through measurements taken mm-wave frequency range. The results demonstrate the feasibility of determining melamine concentrations in mixtures across diverse mm-wave and sub-THz frequency bands.

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Fine-Tuning Pre-Trained Models for Automated Analysis of Ophthalmic Imaging in Diagnosing Eye Diseases

Fine-Tuning Pre-Trained Models for Automated Analysis of Oph...

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Information Technology (ACIT)

作者： Rabia Emhamed Al Mamlook Ahmad Nasayreh Hasan Gharaibeh Mohammad Aljaidi Qais Al-Na'amneh Dalia Alzu'bi Hanin Bzizi Abdelrahman Abdeltawab Dep. of Business Administration Trine University Indiana USA Department of Industrial Engineering University Zawia Tripoli Libia Dep. Computer Science Yarmouk University Irbid Jordan Dep. of Computer Science Zarqa University Zarqa Jordan Dep. of Cyber Security Applied Science Private University Amman Jordan Dep. Information and Systems Engineering Concordia University Montreal Canada Dep of Biomedical Science Western Michigan University Kalamazoo MI USA Faculty of pharmacy Bani Sweif university Bani Suwayf Egypt

This paper searches into the convergence of such ad-vanced techniques with architectures like DenseNet201, VGG16, InceptionResNetV2, and NasNetMobile. Our focus centers on harnessing deep learning capabilities for the precise detection of eye ailments. Preliminary findings spotlight a notable uplift in diagnostic precision. Among the tested algorithms, the Nas-NetMobile architecture emerged superior, boasting an impressive accuracy rate of 92% on the chosen dataset. Through this work, we extend a significant advancement in the realm of automated eye disease diagnosis, potentially equipping medical professionals with sharper, swifter diagnostic tools. The outcomes presented herein could play a seminal role in sculpting more sophisticated and precise diagnostic approaches within ophthalmology.

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Exploiting Optical Nonlinear Temporal Coupling for Implementing Physical Unclonable Functions

Exploiting Optical Nonlinear Temporal Coupling for Implement...

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

作者： Stavros G. Stavrinides Lydia Bush-Espinosa Carol de Benito Nikolaos Athanasios Anagnostopoulos Tolga Arul Stefan Katzenbeisser Christos Tjortjis M. Moner Al Chawa Rodrigo Picos Physics Department International Hellenic University Kavala Greece Industrial Engineering Department Universitat de les Illes Balears Palma Spain Faculty of Computer Science and Mathematics University of Passau Passau Germany School of Science and Technology International Hellenic University Thessaloniki Greece Institute of Circuits and Systems Technical University Dresden Dresden Germany

ISBN: (数字)9798350311617

ISBN: (纸本)9798350311624

In this work, we study the possibility of utilizing an LED-LDR pair for generating a Physical Unclonable Function. Towards this, the nonlinear response between an optically cou-pled LED-LDR pair, as well as the dynamic behavior of the LDR, were considered. The resulting behavior was highly nonlinear and strongly dependent on the actual physical properties of the components. We tested the idea using different LEDs (red, green, and blue; two of each color), and an LDR. Using a low-cost system (an Arduino development board), we showed that although the static response is very linear, the dynamic response is highly unpredictable, when the system is driven by random values. However, this response is identical for the same LED-LDR pairs, but different for other combinations. Additionally, the described behavior is fully repeatable. Thus, a low-cost PUF can be created using these simple components, allowing not only discrimination of the LED's color, but also for the creation of a digital fingerprint as well as authentication/verification.

关键词： Resistors Resistance Color Fingerprint recognition Physical unclonable function Light emitting diodes Nonlinear optical devices

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Right-side-stretched multifractal spectra indicate small-worldness in networks

arXiv

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arXiv 2017年

作者： Oświȩcimka, Pawel Livi, Lorenzo Drozdz, Stanislaw Complex Systems Theory Department Institute of Nuclear Physics Polish Academy of Sciences KrakówPL-31-342 Poland Department of Computer Science College of Engineering Mathematics and Physical Sciences University of Exeter ExeterEX4 4QF United Kingdom Faculty of Physics Mathematics and Computer Science Cracow University of Technology KrakówPL-31-155 Poland

Complex network formalism allows to explain the behavior of systems composed by interacting units. Several prototypical network models have been proposed thus far. The small-world model has been introduced to mimic two important features observed in real-world systems: i) local clustering and ii) the possibility to move across a network by means of long-range links that significantly reduce the characteristic path length. A natural question would be whether there exist several "types" of small-world architectures, giving rise to a continuum of models with properties (partially) shared with other models belonging to different network families. Here, we take advantage of the interplay between network theory and time series analysis and propose to investigate small-world signatures in complex networks by analyzing mul- tifractal characteristics of time series generated from such networks. In particular, we suggest that the degree of right-sided asymmetry of multifractal spectra is linked with the degree of small-worldness present in networks. This claim is supported by numerical simulations performed on several parametric models, including prototypical small-world networks, scale-free, fractal and also real-world networks describing protein molecules. Our results also indicate that right-sided asymmetry emerges with the presence of the following topological properties: low edge density, low average shortest path, and high clustering coefficient. Copyright © 2017, The Authors. All rights reserved.

关键词： Time series analysis

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Using process mining for workarounds analysis in context: Learning from a small and medium-sized company case

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International Journal of Information Management Data Insights 2023年第1期3卷

作者： Wijnhoven, Fons Hoffmann, Petra Bemthuis, Rob Boksebeld, Jurian Department of High-Tech Business and Entrepreneurship Faculty of Behavioural Management and Social Sciences University of Twente Hallenweg 17 Enschede 7522NH Netherlands Department of Pervasive Systems Faculty of Electrical Engineering Mathematics and Computer Science Hallenweg 17 Enschede 7522NH Netherlands

Workarounds are deviations in the execution of designed, de jure, work processes. Process mining research has developed methods for unobtrusive workaround analysis using process-aware systems’ datasets. This study applies process mining for workaround analysis in a medium-sized enterprise (SME). SME contexts can be challenging for workaround mining because SMEs often lack de jure process designs and their process-supportive information systems may have ambiguous semantics. The identification of de jure models and the solving of systems data ambiguities are the first steps in workarounds identification. A semantically well-defined information system may enable factual, de facto, process mining. Comparing the de jure and de facto process models may give candidate workarounds. Our study shows that (1) incomplete de jure models hinder the use of process mining for detecting workarounds, and (2) human interpretation of process mining outcomes is needed to realize a useful triple loop organizational learning from workarounds mining. © 2023 The Author(s)

关键词： Business process management Process mining Triple loop learning Work systems Workarounds

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Entropically damped artificial compressibility for the discretization corrected particle strength exchange method in incompressible fluid mechanics

arXiv

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arXiv 2023年

作者： Singh, Abhinav Sbalzarini, Ivo F. Obeidat, Anas Technische Universität Dresden Faculty of Computer Science Dresden Germany Max Planck Institute of Molecular Cell Biology and Genetics Dresden Germany Center for Systems Biology Dresden Dresden Germany Cluster of Excellence Physics of Life TU Dresden Dresden Germany Department of Engineering Institute of Computational Engineering University of Luxembourg Luxembourg

We present a consistent mesh-free numerical scheme for solving the incompressible Navier-Stokes equations. Our method is based on entropically damped artificial compressibility for imposing the incompressibility constraint explicitly, and the Discretization-Corrected Particle Strength Exchange (DC-PSE) method to consistently discretize the differential operators on mesh-free particles. We further couple our scheme with Brinkman penalization to solve the Navier-Stokes equations in complex geometries. The method is validated using the 3D Taylor-Green vortex flow and the lid-driven cavity flow problem in 2D and 3D, where we also compare our method with hr-SPH and report better accuracy for DC-PSE. In order to validate DC-PSE Brinkman penalization, we study flow past obstacles, such as a cylinder, and report excellent agreement with previous studies. Copyright © 2023, The Authors. All rights reserved.

关键词： Navier Stokes equations

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Talk to your data: Enhancing Business Intelligence and Inventory Management with LLM-Driven Semantic Parsing and Text-to-SQL for Database Querying

Talk to your data: Enhancing Business Intelligence and Inven...

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Data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), International Conference on

作者： Jerry Zhu Saad Ahmed Bazaz Srimonti Dutta Bhavaraju Anuraag Imran Haider Srijita Bandopadhyay Faculty of Mathematics University of Waterloo Ontario Canada Dept. of Computer Science National University of Computer and Emerging Sciences Islamabad Pakistan School of Agro and Rural Technology Indian Institute of Technology Guwahati Guwahati India Dept. of Electronics and Communication Engineering Vellore Institute of Technology India Dept. of Industrial and Systems Engineering Indian Institute of Technology Kharagpur Kharagpur India Dept. of Electronics and Communication Engineering University of Engineering and Management Kolkata India

ISBN: (数字)9798350369786

ISBN: (纸本)9798350369793

This paper delves into the potential of Large Language Models (LLMs) in revolutionizing business intelligence and inventory management through semantic parsing and text-to-SQL methodologies. It assesses various LLM models, such as DIN-SQL, DSP, NSQL, GPT, CoPilot, and LLaMa, elucidating their capabilities and contributions. Two critical analyses are presented here. The first compares cutting-edge LLM models using cosine similarity and cost efficiency metrics. The second analysis enhances GPT’s precision through prompt engineerings, like few-shot techniques, and explores frameworks like DIN-SQL, NSQL, and DSP. DIN-SQL substantially boosts accuracy, and NSQL demonstrates potential in specific scenarios. This research underscores the transformative potential of LLM-driven models in business intelligence and inventory management. DIN-SQL, in particular, emerges as a game-changer with the potential to reshape inventory management practices. GPT showcases its versatility through fine-tuning for tasks beyond conventional programming, while CoPilot offers a cost-effective alternative. This study emphasizes the importance of cost-effectiveness in real-world applications, with LLaMa and CoPilot being practical choices. NSQL, with its budget-friendly and semi-accurate solution, holds promise for semantic parsing in growing companies. These insights are a foundation for further innovation, promising unmatched efficiency and competitiveness across industries in the evolving Artificial intelligence landscape.

关键词： Industries Structured Query Language Technological innovation Costs Large language models Semantics Inventory management

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3D polarimetry of laser induced speckle fields for phase detection thyroid gland polycrystalline structure and traumatic necrosis of human internal organs

3D polarimetry of laser induced speckle fields for phase det...

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Photonics Applications in Astronomy, Communications, Industry, and High Energy Physics Experiments 2024

作者： Ushenko, Olexander Bilookyi, Olexander Ushenko, Yuriy Dubolazov, Alexander Soltys, Irina Olar, Olexander Mikirin, Ivan Skliarchuk, Valeriy Salega, Olexander Karas, Oleksandr Rakhimbayeva, Gulbarshin Rogovyi, Yuriy Kozan, Nataliia Zheng, Jun Alimbayeva, Zhadyra Omiotek, Zbigniew Taizhou Institute of Zhejiang University Taizhou China Optics and Publishing Department Chernivtsi National University Chernivtsi Ukraine Department of Surgery Bucovinian State Medical University Chernivtsi Ukraine Computer Science Department Chernivtsi National University Chernivtsi Ukraine Biomedical Engineering and Optic-Electronic Systems Department Vinnitsia National Technical University Vinnytsia Ukraine Department of Information Communication Technologies Kazakh National Medical University named after S.D. Asfendiyarova Almaty Kazakhstan Department of Pathological Physiology Bucovinian State Medical University Chernivtsi Ukraine Department of Forensic Medicine Medical and Pharmaceutical Law State Medical Academy Ivano-Frankivsk Ukraine Kazakh National Women's Teacher Training University Almaty Kazakhstan Faculty of Electrical Engineering and Computer Science Lublin University of Technology Lublin Poland

ISBN: (数字)9781510685796

ISBN: (纸本)9781510685789

A short theory of the processes of formation of the laser speckle fields polarization structure of biological tissues with optically anisotropic architectonics is presented. A method of polarization interference mapping of speckle fields with layer-by-layer phase scanning of holographically reconstructed distributions of complex amplitudes of biological preparations of various morphological structures and physiological states has been proposed and experimentally tested - biopsies of the thyroid gland and blood films of rats with different severity of sepsis. Layer-by-layer maps of polarization ellipticity of native histological sections of thyroid biopsies from donors and sick patients were studied. As part of the statistical analysis of phase coordinate distributions of polarization ellipticity, objective markers for the differential diagnosis of thyroid pathology were found - nodular goiter, autoimmune thyroiditis and papillary cancer. Very good (~90%) and excellent (≥90%) accuracy of differential diagnosis was achieved. Statistical markers for temporal monitoring of septic changes in polarization azimuth maps of polycrystalline blood films of rats were found. An example of further research using laser-induced autofluorescence polarimetry methods is presented. © 2024 SPIE.

关键词： Optical anisotropy

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Brain multigraph prediction using topology-aware adversarial graph neural network

arXiv

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arXiv 2021年

作者： Bessadok, Alaa Mahjoub, Mohamed Ali Rekik, Islem BASIRA Lab Faculty of Computer and Informatics Istanbul Technical University Istanbul Turkey Higher Institute of Informatics and Communication Technologies University of Sousse Tunisia National Engineering School of Sousse University of Sousse LATIS- Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia School of Science and Engineering Computing University of Dundee United Kingdom

Brain graphs (i.e, connectomes) constructed from medical scans such as magnetic resonance imaging (MRI) have become increasingly important tools to characterize the abnormal changes in the human brain. Due to the high acquisition cost and processing time of multimodal MRI, existing deep learning frameworks based on Generative Adversarial Network (GAN) focused on predicting the missing multimodal medical images from a few existing modalities. While brain graphs help better understand how a particular disorder can change the connectional facets of the brain, synthesizing a target brain multigraph (i.e, multiple brain graphs) from a single source brain graph is strikingly lacking. Additionally, existing graph generation works mainly learn one model for each target domain which limits their scalability in jointly predicting multiple target domains. Besides, while they consider the global topological scale of a graph (i.e., graph connectivity structure), they overlook the local topology at the node scale (e.g., how central a node is in the graph). To address these limitations, we introduce topology-aware graph GAN architecture (topoGAN), which jointly predicts multiple brain graphs from a single brain graph while preserving the topological structure of each target graph. Its three key innovations are: (i) designing a novel graph adversarial auto-encoder for predicting multiple brain graphs from a single one, (ii) clustering the encoded source graphs in order to handle the mode collapse issue of GAN and proposing a cluster-specific decoder, (iii) introducing a topological loss to force the prediction of topologically sound target brain graphs. The experimental results using five target domains demonstrated the outperformance of our method in brain multigraph prediction from a single graph in comparison with baseline approaches. © 2021, CC BY-NC-SA.

关键词： Graphic methods

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