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Enhancing the Swanepoel method: precise envelope detection of thin-film transmission spectra

Optics Express 2025年第6期33卷 13376-13400页

作者： Ballester, Manuel Marquez, Almudena P. Lopez-Tapia, Santiago Fernandez, Susana Bass, John Minkov, Dorian Wuersch, Christoph Willomitzer, Florian Marquez, Emilio Katsaggelos, Aggelos K. Computer Science Department Northwestern University EvanstonIL60208 United States Department of Mathematics Faculty of Science University of Cadiz Puerto Real11510 Spain Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States CIEMAT Avenida Complutense 40 Madrid28040 Spain Wyant College of Optical Sciences University of Arizona TucsonAZ85721 United States Sofia1000 Bulgaria Institute for Computational Engineering ICE OST Eastern Switzerland University of Applied Sciences Switzerland Department of Condensed-matter Physics Faculty of Science University of Cadiz Puerto Real11510 Spain

The Swanepoel method is a widely used optical technique for characterizing thin films through normal-incidence transmission measurements. A critical step in this approach involves extracting the upper and lower envelopes of the measured oscillatory spectrum. By analyzing the transmission spectrum and its corresponding envelopes, the Swanepoel procedure enables precise determination of the film refractive index and extinction coefficient. However, even minor inaccuracies in envelope construction can propagate significant errors into the final characterization results. To address this challenge, we present what we believe to be a novel physics-informed optimization algorithm for envelope detection. Our mathematical model reformulates the envelope detection problem as a global optimization task that enforces the physical properties of the Swanepoel envelopes. Extensive validation on fifty randomly generated transmission spectra demonstrates unprecedented accuracy: the method achieves root-mean-square errors (RMSE) below 0.10% for the upper envelope and 0.06% for the lower envelope (more than doubling the accuracy of current state-of-the-art approaches). Furthermore, the proposed model has been assessed with two experimental transmission spectra, demonstrating its robustness and accuracy with real noisy data. We have developed an open-source Python software package (see text below). This software includes not only our innovative envelope construction algorithm but also additional envelope drawing algorithms for comparison and an efficient implementation of the Swanepoel method, enabling complete optical characterization of thin films. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Mean square error

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Online Menu-Based Scheduling of Electric Vehicle Charging

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IEEE Transactions on Smart Grid 2025年第3期16卷 2478-2491页

作者： Mathioudaki, Angeliki Tsaousoglou, Georgios Varvarigos, Emmanouel Fotakis, Dimitris National Technical University of Athens School of Electrical and Computer Engineering Zografou15772 Greece Technical University of Denmark Department of Applied Mathematics and Computer Science Section for Dynamical Systems Kongens Lyngby2800 Denmark Archimedes Research Unit Athena Research Center Marousi15125 Greece

This paper addresses the problem of efficiently scheduling of EV charging requests in a single Charging Station (CS), also taking into consideration the inability of EV users to express their preferences in closed-form utility functions. We consider a paradigm where a menu of possible charging intervals, each associated with an urgency price, is generated online. By letting the EV users pick their most preferable menu option, the proposed algorithm commits on each EV’s charging completion time upon its arrival, achieves a near optimal total weighted charging completion time, and prevents the users from strategically misreporting their preferences, while offering a practical and implementable solution to the problem of EVs - charging station interaction. Our experimental evaluation demonstrates that our algorithmic approach performs nearly optimal in a variety of practically relevant scenarios. © 2010-2012 IEEE.

关键词： Charging stations

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Development of Additive Manufacturing Design Based on Machine Learning: A Biomedical engineering Approach 1

Development of Additive Manufacturing Design Based on Machin...

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1st International Conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Khan, Akbar Valivarthi, Dharma Teja Banik, Shampa Kakkad, Ashish Sujatha, B. Acharya, Deepak Nimra College of Engineering and Technology ECE Department Andhra Pradesh Vijayawada India Tek Leaders TX United States Dhaka Bangladesh Marwadi University Faculty of Physiotherapy Rajkot India Department of Computer Science and Engineering Tamilnadu Tiruchengode India The University of Alabama in Huntsville Department of computer science United States

ISBN: (纸本)9798331518578

Additive manufacturing (AM) is a versatile and complex manufacturing technique that is extensively employed in the production of personalized biopolymer-orientated items and sophisticated medical architecture. One of the most developed AM techniques is selective laser melting (SLM), which uses a laser as an energy resource to completely melt successive layers of granular resources. SLM produces titanium-oriented alloys that are highly biocompatible and have exceptionally excellent physical qualities, which have led to their widespread usage in biomedical uses. An artificial neural network-based optimizing approach was established to enhance the standard of Ti-6Al-4V SLM-based parts and assist manufacturing professionals in selecting optimum process settings. The approach relates 4 primary procedure settings to two target characteristics of the part. To improve the system's accuracy throughout neural network training, several techniques were employed to address undesirable issues. The denseness and surface hardness values of the system's R2 of 99 percent demonstrated its effectiveness. After that, a selection system was developed that lets users select the best process variables for manufactured goods whose attributes satisfy particular user requirements. The optimum part quality produced by tests using the ideal process variables suggested by the optimizing approach was almost the same as those specified by the user, with only 0.9 to 4.4 percent of mistakes at the high, significantly confirming the system's dependability. © 2025 IEEE.

关键词： Titanium alloys

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Designing a cellular manufacturing system as a step toward creating sustainable cells under uncertain demand condition

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Journal of Remanufacturing 2025年第1期15卷 151-177页

作者： Almasarwah, Najat Abdelall, Esraa Bhutta, Mohammed Khurrum S. Saraireh, Mohammad Department of Industrial Systems Engineering Mutah University Alkarak 61710 Jordan Industrial Engineering Department Jordan University of Science and Technology P.O. Box 3030 Irbid 22110 Jordan Department of Management College of Business Ohio University Athens 45701 OH United States Department of Computer Engineering Mutah University Alkarak 61710 Jordan

This paper focuses on designing a cellular manufacturing system as a step toward creating sustainable cells. The proposed design aims to manufacture final products and remanufacture the returned products to diminish waste, where the return rate for each product is known. Firstly, the product families are formed using the uncapacitated mathematical model. Secondly, a nonlinear stochastic mathematical model is utilized for the propounded design as a step toward creating sustainable cells, where machine duplications are allowed. Besides, a simulation model is developed to handle the uncertainty in demand. Further, the performance of the proposed design with flexible cells is compared to regular cells. The results explain the ability of the proposed design to minimize the total number of machines. Furthermore, allowing machine duplication in the proposed design enhances the system flexibility;thus, machine breakdown will not impact system performance. The total number of machines required to cover the demand increases as the risk level of demand cover decreases. Therefore, the average waiting time and average work in process increase. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.

关键词： Designing a cellular manufacturing system as a step toward creating sustainable cells Flexible cells Nonlinear mathematical model Simulation Stochastic demand

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Enhancing Image Understanding in Automatic Captioning using Spatially-Aware Transformer Architectures

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Procedia computer science 2025年 258卷 2081-2090页

作者： Varun Prakash Saxena Malaram Kumhar Jitendra Bhatia Sudeep Tanwar Sudesh Rani Mayank Gupta Rushi H. Prajapati Department of Computer Engineering Govt. Women Engineering College Ajmer India Department of Computer Science and Engineering Institute of Technology Nirma University Ahmedabad India Department of Computer Science and Engineering Punjab Engineering College (Deemed to be University) Chandigarh India Sahana Systems Limited Ahmedabad

Automatic captioning of images (ACI) is a sophisticated methodology combining image analysis and text generation, with the attention mechanism playing a critical role in identifying key image elements for elaboration. While transformer-based architectures have proven effective in text analysis and translation, their application to image captioning has been challenged by the structural disparity between image semantics typically identified by object detection models and sentence words. To bridge this gap, we introduce the Image Transformer, a novel model featuring a reformed encoding transformer tailored for spatial relationships among image regions and an implicit decoding transformer. This adaptation significantly enhances the standard transformer architecture, making it more suitable for image structures. Our model sets new state-of-the-art performance benchmarks on both online and offline MS COCO dataset testing platforms by utilizing regional features as inputs, representing a substantial advancement in ACI. Experimental results show that our spatially-aware transformer architecture achieved a BLEU-4 score of 38.4, a CIDEr score of 128.4, and a METEOR score of 27 on the MS COCO dataset, outperforming baseline methods significantly. Additionally, the model demonstrated robust performance with a 4.2% accuracy increase on the ImageNet dataset, validating its effectiveness across diverse scenarios. Its robust performance across diverse scenarios demonstrates its potential for broad application and substantial advancements in automatic image captioning.

关键词： Image captioning models Object Detection Real-Time Processing R-CNN Gated Linear Unit (GLU) Natural Language Processing (NLP) Artificial Intelligence (AI) Long Short Term Memory(LSTM)

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Speech Method for Caregiving Robots Considering Uncertainty 16th

Speech Method for Caregiving Robots Considering Uncertainty

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16th International Conference on Social Robotics, ICSR + AI 2024

作者： Shindo, Arisa Kawasaki, Yosuke Takahashi, Masaki School of Science for Open and Environmental Systems Graduate School of Science and Technology Keio University Kanagawa Japan Department of System Design Engineering Faculty of Science and Technology Keio University Kanagawa Japan

ISBN: (纸本)9789819635214

Recent studies have explored the integration of large language models (LLMs) into caregiving robots. The use of LLMs facilitates the generation of human-like natural dialogues and diverse, varied expressions. However, in case of a lack of direct and specific instructions from a user, gaining an accurate understanding of the user's intent is challenging, which may result in miscommunication. Thus, this study proposed a method to achieve robust communication even in the absence of direct instructions by considering the uncertainty in destination prediction probabilities. The proposed system leveraged GPT-4 to generate various Japanese speech content candidates and employed neighborhood components analysis to facilitate dimensionality reduction. Consequently, notable features of the rich linguistic embeddings were preserved while transforming them into manageable data. The system selected appropriate utterances based on the destination prediction probabilities. Furthermore, this study investigated changes in the speech content according to the variations in these probabilities, and the incorporation of uncertainty in communication was validated. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Dimensionality reduction

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Remote Patient Healthcare Monitoring and Pose Recognition over Video Sensors

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Traitement du Signal 2025年第2期42卷 995-1005页

作者： Alabdullah, Bayan Tayyab, Muhammad Alhasson, Haifa F. Alshammari, Naif S. Jalal, Ahmad Department of Information Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University Riyadh11671 Saudi Arabia Department of Computer Science Air University Islamabad44000 Pakistan Department of Information Technology College of Computer Qassim University Buraydah52571 Saudi Arabia Department of Computer Sciences College of Computer and Information Sciences Majmaah University Majmaah11952 Saudi Arabia Department of Computer Science and Engineering College of Informatics Korea University Seoul02841 Korea Republic of

Considering the fact of increasing population and as a result, the number of patients is constantly increasing the delivery of medical services must be prompt and of good quality. There is no question that any perfect healthcare system should track the given activities, behaviours, schedules, and even general health of the patients. The focus of this study is in utilizing ML and DL in tracing patients and diagnosing ailments. Mounted cameras from different orientations and placements are intended for health monitoring and event surveillance for possible medical issues in the future. Classical ML and more advanced DL methods are applied for analyzing physiological and behavioral patterns to identify health conditions and stress the importance of high accuracy and real-time performance for practical purposes. Initial outcomes show that patient outcomes are enhanced by getting timely medical advice while decreasing hospital-based burdens on staff. Two challenging datasets, ETRI-Activity3D and NTU-RGB-D, are pre-processed to remove unimportant data and reduce computational load. A strong multi-feature description system can extract gradient values, and the process is followed by feature matching and feature optimization. Then, in the last Maximum Entropy Markov Model (MEMM) classifier is used, achieving an accuracy of 97.2% for ETRI-Activity3D, and 98.3% for the NTU-RGB-D dataset. ©2025 The authors.

关键词： Remote patient monitoring

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Automated Topology Synthesis of Analog Integrated Circuits With Frequency Compensation

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IEEE Transactions on computer-Aided Design of Integrated Circuits and systems 2025年第3期44卷 832-844页

作者： Zhao, Zhenxin Liu, Jun Zhao, Wen-Sheng Zhang, Lihong Hangzhou Dianzi University Innovation Center for Electronic Design Automation Technology Zhejiang Hangzhou310018 China Memorial University of Newfoundland Faculty of Engineering and Applied Science Department of Electrical and Computer Engineering St. John'sNLA1C 5S7 Canada

Analog circuit topology synthesis suffers from weak synthesis capability and low-synthesis efficiency, which result in a bottleneck toward its practical industrial applications. This article presents a proximal-policy-optimization-based circuit topology synthesis framework, which features a superior convergence rate. To further promote its synthesis efficiency, we have improved a deterministic optimization method by incorporating a bias-aware scheme and group concept, which is applied as a filter to eliminate the undesirable topologies in the early evaluation stage. Moreover, a graph-based refinement scheme is proposed to perform deterministically on the generated circuit topologies, which can efficiently add frequency compensation circuits. Compared with the state-of-the-art approaches, our proposed method not only boosts the synthesis efficiency by at least 3 times but also enhances the synthesis capability with a deterministic compensation scheme, showcasing significant advancement of performance efficacy. © 2024 IEEE.

关键词： Network topology

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ABL-SMOTE: A Novel Resampling Method by Handling Noisy and Borderline Challenge for Imbalanced Dataset for Software Defect Prediction

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IEEE Access 2025年 13卷 78781-78794页

作者： Bashir, Kamal Abdelwahab Ghorashi, Sara Ahmed, Ali Khader, Abdolraheem Karary University College of Computer Science and Information Technology Department of Information Technology Omdurman12304 Sudan Princess Nourah bint Abdulrahman University College of Computer and Information Sciences Department of Computer Sciences P.O. Box 84428 Riyadh11671 Saudi Arabia King Abdulaziz University Faculty of Computing and Information Technology Jeddah21589 Saudi Arabia Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210094 China

Machine learning algorithms face important implementation difficulties due to imbalanced learning since the Synthetic Minority Oversampling Technique (SMOTE) helps improve performance through the creation of new minority class examples in feature space before preprocessing. The underlying problem leading to performance deterioration emerges from noise and boundary instances found in the minority class rather than an excessive imbalance ratio. Noise and marginal samples become problematic during oversampling operations since they reduce the performance of classification models. This paper proposes an advanced version of Borderline-SMOTE (BL-SMOTE), called ABL-SMOT approach that utilizes INFFC for noise filtering to optimize data quality in the dataset. This improvement method for minority class sample placement and noise filtering ensures higher classifier performance through ABL-SMOTE. The proposed technique receives assessment through the usage of software defect datasets along with multiple testing classifiers against conventional data sampling procedures. The experimental outcomes show that ABL-SMOTE performs better than alternative approaches in most tested datasets because it is an effective preprocessing tool for imbalanced classification problems. © 2013 IEEE.

关键词： Software testing

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StegMamba: Distortion-Free Immune-Cover for Multi-Image Steganography With State Space Model

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IEEE Transactions on Circuits and systems for Video Technology 2025年第5期35卷 4576-4591页

作者： Luo, Ting Zhou, Yuhang He, Zhouyan Jiang, Gangyi Xu, Haiyong Qi, Shuren Zhang, Yushu Ningbo University College of Science and Technology Ningbo315212 China Ningbo University Faculty of Information Science and Engineering Ningbo315211 China The Chinese University of Hong Kong Department of Mathematics Hong Kong Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing211106 China

Multi-image steganography ensures privacy protection while avoiding suspicion from third parties by embedding multiple secret images within a cover image. However, existing multi-image steganographic methods fail to model global spatial correlations to reduce image damage at the low computation cost. Moreover, they do not account for the anti-distortion capability of the cover image, which is crucial for achieving imperceptible and ensuring security. To overcome these limitations, we propose StegMamba, a distortion-free immune-cover for multi-image steganography architecture with a state space model. Specifically, we first explore the potential of the linear computational cost model Mamba for data hiding tasks through a steganography Mamba block (SMB), whose efficiency makes it suitable for real-time applications. Subsequently, considering that images with distortion resistance reduce embedding damage, the original cover image is reconstructed through immune-cover construction module (ICCM) and associated with the steganography task. Moreover, well-coupled features facilitate fusion, and thus a wavelet-based interaction module (WIM) is designed for effective communication between the immune-cover and the secret images. Compared with the state-of-the-art global attention-based methods, the proposed StegMamba obtains PSNR gains of 3.30 dB, 1.37 dB, and 1.92 dB for the stego image, and two secret recovery images, respectively, and the reduction of 2.87% in detection accuracy for anti-steganalysis. © 1991-2012 IEEE.

关键词： Cost reduction

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