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A Market Surveillance and an Evaluation Methodology Based on Power Quality, Electromagnetic Compatibility, and Photometric data for LED Light Sources

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ieee ACCESS 2025年 13卷 74963-74979页

作者： Athanasiadis, Themistoklis L. Nicolopoulou, Eleni P. Madias, Evangelos-Nikolaos D. Polykrati, Aikaterini D. Christodoulou, Christos A. Doulos, Lambros T. Gonos, Ioannis F. Natl & Tech Univ Athens Sch Elect & Comp Engn Athens 15780 Greece Hellen Open Univ Sch Appl Arts & Sustainable Design Patras 26335 Greece

In lighting projects, cost and energy consumption are often the primary selection criteria for LED lamps. However, additional technical factors such as electromagnetic emissions, harmonic current emissions, overvoltage susceptibility, visual flicker and photometric performance are crucial for ensuring system reliability and long-term regulatory compliance. Ignoring these factors results into power quality issues, electromagnetic interference, flicker, biological hazards and reduced lamp lifespan- particularly in commercial and hospitality environments where lighting operates extensively. This study introduces a comprehensive evaluation framework that extends beyond cost and energy efficiency, incorporating in a versatile and scalable manner technical performance criteria into the selection process. Within a market surveillance study, ten commercially available LED lamps were assessed through measurements and tests in an accredited laboratory. While all tested lamps currently meet harmonized Standards, a large number would exceed the stricter harmonic current limits of EN IEC 61000-3-2 (2019), once harmonized. A weight-based ranking methodology addressing installation-specific requirements is proposed as a tool for identifying the optimum lighting solution. The results showcase that the best performing lamps are not necessarily the most expensive. Additionally, the study explores various electrical environments and lighting scenarios in relation to key UN Sustainable Development Goals 1, 3, 7, 9, 11, 13, 15 and 17.

关键词： Lighting Harmonic analysis IEC Standards visualization LED lamps Fluctuations Power system harmonics Energy efficiency Surges Surge protection electromagnetic compatibility harmonic distortion LED lamp ranking methodology visual flicker

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Applying Innovative AI Techniques to Complex U.S. Army datasets 71

Applying Innovative AI Techniques to Complex U.S. Army Datas...

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71st Annual Reliability and Maintainability symposium, RAMS 2025

作者： Mills, Jordan Shumate, Megan Walker, Kris Alexander, Russ INTUITIVE Research and Technologies Corporation 5030 Bradford Drive Bldg. 2 Ste. 205 HuntsvilleAL35805 United States RAM Engineering & System Assessment Division DEVCOM Aviation & Missile Center 5400 Fowler Road Redstone Arsenal AL35898 United States SpecTrum A&T Solutions LLC United States

ISBN: (纸本)9798350367744

As the amount of data that engineers and analysts needed to evaluate increases, the use of Artificial Intelligence (AI) techniques become more critical. Big data analytics tools can be used to find patterns and relationships within large data sets and the domain of Reliability, Availability, and Maintainability (RAM) for aircraft and missiles provides an ideal application for these big data methods. For aviation data, looking at relationships and patterns within and between maintenance events and on-board flight sensor data can provide added value for maintenance and logistics managers. For missile system data, looking at relationships and patterns within different collections of test data for the weapon system helps support important RAM decisions related to root cause analysis, the identification of reliability degradation trends, and the extension of missile shelf life. In this paper, the authors detail the integration of big data analytics tools and techniques to provide value to RAM stakeholders through the innovative analysis of aviation and missile datasets. © 2025 ieee.

关键词： data reliability

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Multi-Criteria Decision analysis for Aiding Glyph Design

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ieee Transactions on visualization and Computer Graphics 2025年 PP卷 PP页

作者： Hsieh, Hong-Po Zavatsky, Amy Chen, Min University of Oxford United Kingdom

Glyph-based visualization is one of the main techniques for visualizing complex multivariate data. With small glyphs, data variables are typically encoded with relatively low visual and perceptual precision. Glyph designers have to contemplate the trade-offs in allocating visual channels when there is a large number of data variables. While there are many successful glyph designs in the literature, there is not yet a systematic method for assisting visualization designers to evaluate different design options that feature different types of tradeoffs. In this paper, we present an evaluation scheme based on the multi-criteria decision analysis (MCDA) methodology. The scheme provides designers with a structured way to consider their glyph designs from a range of perspectives, while rendering a semi-quantitative template for evaluating different design options. In addition, this work provides guideposts for future empirical research to obtain more quantitative measurements that can be used in MCDA-aided glyph design processes. © 2025 ieee.

关键词： data visualization

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Qiwu: Exploiting Ciphertext-Level SIMD Parallelism in Homomorphic Encryption Programs 25

Qiwu: Exploiting Ciphertext-Level SIMD Parallelism in Homomo...

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23rd ACM/ieee International symposium on Code Generation and Optimization, CGO 2025

作者： Zhang, Zhongcheng Liu, Ying Zhang, Yuyang Chen, Zhenchuan Zhao, Jiacheng Feng, Xiaobing Cui, Huimin Xue, Jingling SKLP ICT CAS UCAS Zhongguancun Laboratory Beijing China SKLP ICT CAS UCAS Beijing China SKLP ICT CAS Beijing China UNSW Sydney Australia

ISBN: (纸本)9798400712753

Fully Homomorphic Encryption (FHE), particularly the CKKS scheme, enables computation on encrypted data, facilitating secure task offloading to untrusted servers. CKKS allows packing multiple complex values into a single ciphertext, crucial for fixed-point arithmetic in machine learning, while leveraging SIMD parallelism at the plaintext level. However, operations such as reductions can degrade performance by creating a large number of bubbles (or gaps) in intermediate ciphertexts, leading to wasted computational resources. We introduce Qiwu, a ciphertext-level vectorization approach that enhances performance by fusing multiple ciphertexts containing bubbles. Qiwu uses a DSL to specify zero bubbles in input ciphertexts and nonzero bubbles in output ciphertexts, employs data-flow analysis to track them, and formulates a fusion plan guided by a cost-benefit assessment. Implemented in an existing FHE compiler, Qiwu was evaluated on four applications (including three machine learning tasks) and three kernels. It achieves speedups of up to 18.0× on CPUs, averaging 3.4× (geometric mean), compared to the state-of-the-art compiler that exploit only plaintext-level parallelism. © 2025 Copyright held by the owner/author(s).

关键词： data flow analysis

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Multi-Agent hierarchical workflow for autonomous code generation with large Language Models

Multi-Agent hierarchical workflow for autonomous code genera...

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2025 ieee International Students' Conference on Electrical, Electronics and Computer Science, SCEECS 2025

作者： Akilesh, S. Sekar, Rajeev Om Kumar, C.U. Prakalya, D. Suguna, M. Vellore Institute of Technology School of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331529833

This paper presents a multi-agent hierarchical workflow tailored for automating data analysis, code generation, and visualization, focusing specifically on user-provided CSV datasets. The workflow integrates AlphaCodium with LangChain, LangGraph, and GPT, enabling autonomous code generation, unit test development, and debugging. The system operates by analyzing the uploaded dataset, assigning agents that work sequentially: a programmer agent generates code using the Skeleton-Of-Code approach, a unit test agent verifies the code, and an executor agent runs the code. A debugging agent is also included to identify and resolve any issues. The AI agents involved are capable of dynamically accessing online resources, including documentation and references to enhance their decision-making processes. This work attempts to exemplify the application of AI in automating not only code execution but also the planning and validation stages by writing unit tests in the software development process to reflect the increasing role of AI in advancing automation for rapid code generation within the software industry. © 2025 ieee.

关键词： Software design

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Medvisiochat: A Multimodal large Language Model Framework for Interpretable Diagnosis with Visual Grounding in CXRs

Medvisiochat: A Multimodal Large Language Model Framework fo...

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ieee International symposium on Biomedical Imaging

作者： Ling Yang Zhanyu Wang Luping Zhou School of Electrical and Computer Engineering The University of Sydney Australia

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Multimodal large Language Models (MLLMs) have enhanced the interpretability of disease diagnosis, leading to more accurate outcomes and improved patient understanding. A key advancement is visual grounding, linking textual information with medical images like chest x-rays (CXRs) for deeper analysis. This approach combines visual details with expert medical language, enabling MLLMs to detect patterns and disease indicators effectively. However, challenges persist, particularly in multi-category classification and precise visual grounding in CXRs. To address this, we introduce MedVisioChat, an MLLM with visual grounding capabilities for seamless integration of medical images and diagnoses. Pre-trained on large datasets and fine-tuned with specific GPT-4 Turbo instructions, MedVisioChat aims to provide accurate, interactive diagnostics, demonstrating superiority over existing models and promising an inter-pretable visual medical diagnosis.

关键词： visualization Accuracy Grounding Biological system modeling large language models data models Medical diagnosis Medical diagnostic imaging X-ray imaging Diseases

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An Empirical analysis on the Use and Reporting of National Security Letters 25

An Empirical Analysis on the Use and Reporting of National S...

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4th ACM symposium on Computer Science and Law, CS and LAW 2025

作者： Bellon, Alex Haller, Miro Labunets, Andrey Liu, Enze Savage, Stefan UC San Diego San DiegoCA United States

ISBN: (纸本)9798400714214

Government investigatory and surveillance powers are important tools for examining crime and protecting public safety. However, since these tools must be employed in secret, it can be challenging to identify abuses or changes in use that could be of significant public interest. In this paper, we evaluate this phenomenon in the context of National Security Letters (NSLs). NSLs are a form of legal process that empowers parts of the United States federal government to request certain pieces of information for national security purposes. After initial concerns about the lack of public oversight, Congress worked to increase transparency by mandating government agencies to publish aggregated statistics on the NSL usage and by allowing the private sector to report information on NSLs in transparency reports. The implicit goal is that these transparency mechanisms should deter large-scale abuse by making it visible. We evaluate how well these mechanisms work by carefully analyzing the full range of publicly available data related to NSL use. Our findings suggest that they may not lead to the desired public scrutiny as we find published information requires significant manual effort to collect and parse data due to the lack of structure and context. Moreover, we discovered mistakes (subsequently fixed after our reporting to the ODNI), which suggests a lack of active auditing. Taken together, our case study of NSLs provides insights and suggestions for the successful construction of transparency mechanisms that enable effective public auditing. © 2025 Copyright held by the owner/author(s).

关键词： NSL

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Rigorous Floating-Point Round-Off Error analysis in PRECiSA 4.0 26th

Rigorous Floating-Point Round-Off Error Analysis in PRECiSA ...

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26th International symposium on Formal Methods (FM)

作者： Titolol, Laura Moscato, Mariano Feliu, Marco A. Masci, Paolo Munoz, Cesar A. Analyt Mech Associates Inc Hampton VA 23666 USA NASA Langley Res Ctr Hampton VA 23665 USA

ISBN: (纸本)9783031711763;9783031711770

Small round-off errors in safety-critical systems can lead to catastrophic consequences. In this context, determining if the result computed by a floating-point program is accurate enough with respect to its ideal real-number counterpart is essential. This paper presents PRECiSA 4.0, a tool that rigorously estimates the accumulated round-off error of a floating-point program. PRECiSA 4.0 combines static analysis, optimization techniques, and theorem proving to provide a modular approach for computing a provably correct round-off error estimation. PRECiSA 4.0 adds several features to previous versions of the tool that enhance its applicability and performance. These features include support for data collections such as lists, records, and tuples;support for recursion schemas;an updated floating-point formalization that closely characterizes the ieee-754 standard;an efficient and modular analysis of function calls that improves the performances for large programs;and a new user interface integrated into Visual Studio Code.

关键词： User interfaces

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23rd International Conference on Web-Based Learning, ICWL 2024 was held in conjunction with the 9th International symposium on Emerging Technologies for Education, SETE 2024

23rd International Conference on Web-Based Learning, ICWL 20...

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23rd International Conference on Web-Based Learning, ICWL 2024 was held in conjunction with the 9th International symposium on Emerging Technologies for Education, SETE 2024

ISBN: (纸本)9789819644063

The proceedings contain 21 papers. The special focus in this conference is on Web-Based Learning. The topics include: Towards Effective Collaborative Learning in Edu-Metaverse: A Study on Learners’ Anxiety, Perception, and Behaviour;an Empirical Study of Code Pattern Reuse and Pattern Preference Consistency in Novice Programmers;self-attentive Knowledge Tracing with Relative Position Encoding;students’ Pre-concepts of Robot Control Before Their First Robotics Lesson: A Pilot Study;evaluating Verbs of Chatting in large Language Models;mapping the Landscape of Digital and Intelligent Technologies in Intercultural Learning: A Bibliometric analysis (2014–2024);AI-Enhanced Intercultural Teaching: Investigating Chinese EFL University Teachers’ Technology Readiness and Acceptance of large Language Models;leveraging data visualization with ggplot2 in Translation Pedagogy: Enhancing Learning Through Visual Insights;AI-Assisted Writing on News Report: A Case Study on AI-Generated Content and Human-Generated Content;analysis of Interpreter Performance on Numbers, Proper Nouns, and Complex Sentences in AI-Assisted English-Chinese Simultaneous Interpreting: An Eye-Tracking Experimental Study;Human v.s. AI: A Comparative Study Between MTI Student Translators and AI Engines;knowledge Graph-Based Advance Preparation in Medical Interpreting;Quality Comparison of MT in Translating Chinese Music Historical Texts and Inspiration for Translation Pedagogy;Human-in-the-Loop: A Conceptual Framework for Business English Teachers’ AI-Empowered Assessment;an Exploratory Research on Reading Comprehension Question Generation Based on Annotated Clause Complex Corpus;ChatGPT Prompt Engineering Methods for Financial News Translation;A Robust and Secure Framework for an AI-Assisted Academic Writing Platform;an Automatic Model for Lesson Plans Generation Based on Logical Chains and Prompt Tuning.

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Synthetic data for AI-Powered Ultrafast Laser Based Micro-structuring Method Description 2nd

Synthetic Data for AI-Powered Ultrafast Laser Based Micro-s...

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2nd European symposium on Artificial Intelligence in Manufacturing, ESAIM 2024

作者： Blanco-Filgueira, Beatriz Delgado, Tamara Coto, Andrea Gregores Petit, Céline Bruneel, David Romero, Pablo Muiños-Landin, Santiago AIMEN Technology Centre Pontevedra Porrino36410 Spain LASEA Seraing4102 Belgium

ISBN: (纸本)9783031864889

High-power ultrashort pulse lasers (USPLs) represent a sustainable alternative for industrial surface processing. Laser Surface Texturing (LST) allows modification of surface properties such as mechanical, chemical or optical properties. The adoption of USPLs in industry will enable the surface functionalization of large 3D parts through the LST process. However, a real exploitation of USPLs still faces limitations related to high processing resolution, quality, productivity, and the need for expert knowledge in laser micro-structuring strategies. It is crucial to increase maturity, reliability and throughput of LST on a large scale, as well as to provide the industry with the necessary tools for selecting the suitable laser process for each specific application. Achieving these goals requires significant effort in data collection, which is costly in terms of processing times, results analysis and human resources. Additionally, the availability of software simulators for laser micro-structuring is limited, posing challenges for describing USPLs processes through numerical models and methods. In this context, Artificial Intelligence (AI) models represent a unique tool to enhance process understanding and results analysis, providing rapid prediction and visualization capabilities. However, developing AI-models requires vast amounts of data, which are not easily obtainable experimentally, but simulators can play a vital role in this aspect. We present a combined solution based on machine learning methods fed by synthetic data generated by LS-Plume® from LASEA for predicting femtosecond laser single beam-based grooves on stainless steel 316L. The methodology for developing such applications is described, and several regression models are compared. The analysis of metrics and prediction error demonstrates that leveraging the synergy between simulation tools and AI-models can be an effective strategy for training AI-models, thereby avoiding the need for a complete, system

关键词： Ultrashort pulses

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