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arXiv 2025年

作者： Chen, Wei-Lun Hsieh, Chia-Yeh Kao, Yu-Hsiang Liu, Kai-Chun Peng, Sheng-Yu Tsao, Yu Research Center for Information Technology Innovation Academic Sinica Taiwan Graduate Institute of Electrical Engineering National Taiwan University Taiwan Bachelor’s Program in Medical Informatics and Innovative Applications Fu Jen Catholic University Taiwan Department of Electrical Engineering National Taiwan University Taiwan College of Information and Computer Sciences University of Massachusetts AmherstMA01003 United States Department of Electrical Engineering National Taiwan University of Science of Technology Taiwan

This study presents a novel approach to human keypoint detection in low-resolution thermal images using transfer learning techniques. We introduce the first application of the Timed Up and Go (TUG) test in thermal image computer vision, establishing a new paradigm for mobility assessment. Our method leverages a MobileNetV3-Small encoder and a ViTPose decoder, trained using a composite loss function that balances latent representation alignment and heatmap accuracy. The model was evaluated using the Object Keypoint Similarity (OKS) metric from the COCO Keypoint Detection Challenge. The proposed model achieves better performance with AP, AP50, and AP75 scores of 0.861, 0.942, and 0.887 respectively, outperforming traditional supervised learning approaches like Mask R-CNN and ViTPose-Base. Moreover, our model demonstrates superior computational efficiency in terms of parameter count and FLOPS. This research lays a solid foundation for future clinical applications of thermal imaging in mobility assessment and rehabilitation monitoring. Copyright © 2025, The Authors. All rights reserved.

关键词： Thermography (imaging)

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Tumor ploidy determination in low-pass whole genome sequencing and allelic copy number visualization using the Constellation Plot

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Genome biology 2025年第1期26卷 132页

作者： Sarah H Johnson James B Smadbeck Roman M Zenka Michael T Barrett Athanasios Gaitatzes Arnav Solanki Angela B Florio Mitesh J Borad John C Cheville George Vasmatzis Biomarker Discovery Program Mayo Clinic Rochester MN 55905 USA. Center for Individualized Medicine Mayo Clinic Rochester MN 55905 USA. Quantitative Health Sciences Mayo Clinic Rochester MN 55905 USA. Hematology/Oncology Mayo Clinic Scottsdale AZ 85259 USA. Center for Digital Health Mayo Clinic Rochester MN 55905 USA. Department of Electrical and Computer Engineering University of Minnesota Minneapolis MN 55455 USA. Mayo Clinic Graduate School of Biomedical Sciences Rochester MN 55905 USA. Anatomic Pathology Mayo Clinic Rochester MN 55905 USA. Biomarker Discovery Program Mayo Clinic Rochester MN 55905 USA. Vasmatzis.George@mayo.edu. Department of Molecular Medicine Mayo Clinic Rochester MN 55905 USA. Vasmatzis.George@mayo.edu.

Ploidy determination across the genome has been challenging for low-pass-WGS tumor-only samples. We present BACDAC, a method that calculates tumor ploidy down to 1.2X effective tumor coverage. Allele fraction patterns displayed in the Constellation Plot verify tumor ploidy and reveal subclonal populations. BACDAC outputs a metric, 2NLOH, that when combined with ploidy better distinguishes near-diploid from high-ploidy tumors. Validated using TCGA, BACDAC had good agreement with other methods and 88% agreement with experimental methods. Discrepancies occur mainly when BACDAC predicts diploidy with subclones rather than high-ploidy. Applied to 653 low-pass-WGS samples spanning 12 cancer subtypes, BACDAC calls 40% as high-ploidy.

关键词： Loss of heterozygosity Next generation sequencing Ploidy Whole genome doubling

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Nonlocal flat optics for size-selective image processing and denoising

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Nature Communications 2025年第1期16卷 1-9页

作者： Chamoli, Sandeep Kumar Jin, Chunqi Fan, Yandong Kiani, Mehdi Goh, Heedong Huang, Chen Guo, Shuyu Wang, Yuntong Zhu, Fei Xing, Guohua Li, Bo Bai, Tian Alù, Andrea Li, Wei GPL Photonics Laboratory State Key Laboratory of Luminescence Science and Technology Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences Changchun Jilin 130033 China University of Chinese Academy of Sciences Beijing 100049 China Photonics Initiative Advanced Science Research Center City University of New York New York 10031 NY United States Physics Program Graduate Center of the City University of New York New York 10016 NY United States College of Computer Science and Technology Jilin University Changchun 130012 China

All-optical image processing based on metasurfaces is a swiftly advancing field of technology, due to its high speed, large integrability and inherently low energy requirements. So far, the proposed devices have been focusing on canonical operations, such as differentiations to perform edge detection across all objects in a complex scene. Yet, undesired background noise and clutter can hinder such operations, requiring target selection with digital post-processing which inherently limits the overall accuracy, efficiency and speed. Here, we introduce an optical solution for real-time size-selective image processing and experimentally demonstrate the concept with a metal-dielectric-metal film performing a spatial band-pass filter in momentum space. We show high-resolution (~0.9 μm) edge detection and real-time dynamic denoising, ideally suited for bio-imaging applications and target recognitions. Our demonstrated k-space filtering metasurface expands the scope of nonlocal flat optics for analog image processing, ushering in opportunities for ultra-compact, cost-effective, and multifunctional image processors. © The Author(s) 2025.

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Towards the selection of testable use cases and a real experience

Towards the selection of testable use cases and a real exper...

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作者： Rodrigues, Andreia Pinheiro, Plácido Rogério Rodrigues, Maikol Magalhães Albuquerque, Adriano Bessa Gonçalves, Francisca Márcia Graduate Program in Applied Computer Sciences Av. Washington Soares 1321 Fortaleza Ce Brazil

ISBN: (纸本)9783642047565

Nowadays, software organizations have needed to develop excellent and reliable products. This scenario has helped to increase the relevance of quality assurance activities, especially the testing discipline. However, sometimes the time and resources are limited and not all tests can be executed, demanding organizations to decide what use cases should be tested, to guarantee the predictability of the project's time and *** multiple criteria methodologies support decisions, considering many factors, not only professional experience. This paper presents a multiple criteria model to support the decision of selecting the use cases that should be tested. © 2009 Springer Berlin Heidelberg.

关键词： Decision theory

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Improved LSTM hyperparameters alongside sentiment walk-forward validation for time series prediction

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Journal of Open Innovation: Technology, Market, and Complexity 2025年第1期11卷

作者： Wahyuddin, Eko Putra Caraka, Rezzy Eko Kurniawan, Robert Caesarendra, Wahyu Gio, Prana Ugiana Pardamean, Bens Department of Statistical Computing Politeknik Statistika STIS Jakarta 13330 Indonesia Statistics Indonesia (BPS) Jl. Dr Sutomo 6-8 Jakarta Indonesia School of Economics and Business Telkom University Bandung 40257 Indonesia Research Center for Data and Information Sciences Research Organization for Electronics and Informatics National Research and Innovation Agency (BRIN) Bandung 40135 Indonesia Faculty of Integrated Technologies Universiti Brunei Darussalam Gadong BE1410 Brunei Darussalam Department of Mathematics Universitas Sumatera Utara Medan 20155 Indonesia Bioinformatics and Data Science Research Centre Bina Nusantara University DKI Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University DKI Jakarta 11480 Indonesia

This study aims to address the common issue of biased estimation errors in time series modeling by analyzing the error in locating ideal hyperparameters and defining appropriate validation methods. Specifically, it focuses on predicting the stock price of Bank Rakyat Indonesia using a combination of historical stock prices, technical indicators, exchange rates, and news sentiment data, while determining the optimal variables for deep learning models. Employing a deep learning-based Long-Short Term Memory (LSTM) model, the study optimizes hyperparameters alongside walk-forward validation for time series prediction. It explores different combinations of variables and adapts the sliding window approach to the context of the data. The results highlight the importance of optimizing hyperparameters and utilizing walk-forward validation for accurate time series prediction. The model incorporating historical stock prices and sentiment scores outperforms others, achieving an RMSE of 96.61 and MAE of 86.97. Incorporating sentiment scores reduces RMSE by 39.55 % compared to models using only historical stock prices, while adding technical indicators does not yield improvement. This study contributes to the field by addressing the issue of biased estimation errors in time series modeling, offering insights into the optimization of hyperparameters and validation methods for accurate predictions. It also underscores the significance of incorporating sentiment analysis alongside historical stock prices for improved forecasting accuracy. © 2024 The Authors

关键词： LSTM Sentiment analysis Stock price prediction Time series modeling Validation methods

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Possibilities to use the practice of telemedicine in actual technological conditions to remote areas

Possibilities to use the practice of telemedicine in actual ...

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25th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society

作者： Kmeteuk, O de Amorim, MF Graduate Program in Applied Computer Science Exact Sciences and Technology Center Pontifical Catholic University of Paraná Brazil

ISBN: (纸本)0780377893

One of the main factors that impede the practice of the telemedicine is not the lack of new technologies for the communication, but the lack of studies on the use of the technology already installed in the distant areas, in way to be used of a rational way. The objective of the telemedicine is to provide help to the cares with the health with quality the distant areas of the great attendance centers. Therefore, it cannot ignore the fact that these areas do not make use of point technologies for communication. Then, it is justified the need to accomplish studies that facilitate the practice of the independent telemedicine of the installed technology. Then, the objective of this work is to use as pilot an unit of remote health, contributing with a support system that allows the practice of the telemedicine using the technology of available transmission in the respective place, avoiding that the factor cost is a barrier for the telemedicine projects and can begin an improvement process in the quality of the attendance in units of distant health of the great centers of medical attendance.

关键词： telemedicine support system

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Supervised enhanced learning to simplify internal representations of multi-layered networks

Supervised enhanced learning to simplify internal representa...

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IASTED International Conference on Artificial Intelligence and Applications, AIA 2009

作者： Kamimura, Ryotaro Aoyama, Kenta IT Education Center Graduate Program in Computer Sciences Tokai University 1117 Kitakaname Hiratsuka Kanagawa 259-1292 Japan

ISBN: (纸本)9780889867802

In this paper, we propose a new method to enhance hidden unit activations of multi-layered networks and to retrain networks imitating enhanced hidden unit activations. One of the most serious problems of multilayered networks consists in difficulty in interpreting final internal representations obtained by learning. Though many methods have been proposed to solve this problem, the problem still remains unsolved. For this problem, we propose a method to enhance hidden unit activations with explicit responses to input patterns. In addition, we propose a new method to retrain networks by imitating the enhanced hidden unit activations. We applied the method to a student survey, a cabinet approval rating estimation and another student survey. In all these problems, we succeeded in producing explicit and interpretable final representations.

关键词： Surveys

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Advantages of two quantum programming platforms in quantum computing and quantum chemistry

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Journal of cheminformatics 2025年第1期17卷 77页

作者： Pei-Hua Wang Wei-Yeh Wu Che-Yu Lee Jia-Cheng Hong Yufeng Jane Tseng Undergraduate Program in Intelligent Computing and Big Data Chung Yuan Christian University No. 200 Zhongbei Road Taoyuan 320314 Taiwan. Quantum Information Center Chung Yuan Christian University No. 200 Zhongbei Road Taoyuan 320314 Taiwan. Department of Computer Science and Information Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. Graduate Institute of Biomedical Electronics and Bioinformatics College of Electrical Engineering and Computer Science National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. Department of Computer Science and Information Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. yjtseng@csie.ntu.edu.tw. Graduate Institute of Biomedical Electronics and Bioinformatics College of Electrical Engineering and Computer Science National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. yjtseng@csie.ntu.edu.tw. Physics Division National Center for Theoretical Sciences No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. yjtseng@csie.ntu.edu.tw. Center for Quantum Science and Engineering National Taiwan University No. 1 Sec. 4 Roosevelt Road Taipei 10617 Taiwan. yjtseng@csie.ntu.edu.tw.

Quantum computing is at the forefront of technological advancement and has the potential to revolutionize various fields, including quantum chemistry. Choosing an appropriate quantum programming language becomes critical as quantum education and research increase. In this paper, we comprehensively compare two leading quantum programming languages, Qiskit and PennyLane, focusing on their suitability for teaching and research. We delve into their basic and advanced usage, examine their learning curves, and evaluate their capabilities in quantum computing experiments. We also demonstrate using a quantum programming language to build a half adder and a machine learning model. Our study reveals that each language has distinct advantages. While PennyLane excels in research applications due to its flexibility to adjust parameters in detail and access multiple sources of real quantum devices, Qiskit stands out in education because of its web-based graphical user interface and smaller code size. The codes and the dataset used in the studies are available at https://***/wangpeihua1231/quantum-programming-platform .

关键词： PennyLane Qiskit Quantum chemistry Quantum computing Quantum programming language

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Real-time optimization using gradient adaptive selection and classification from infrared sensors measurement for esterification oleic acid with glycerol

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International Journal of Intelligent Computing and Cybernetics 2017年第2期10卷 130-144页

作者： Iwan Aang Soenandi Taufik Djatna Ani Suryani Irzaman Post Graduate Program of Agro-industrial Technology Bogor Agricultural UniversityBogorIndonesia and Faculty of Engineering and Computer ScienceKrida Wacana Christian UniversityJakartaIndonesia Post Graduate Program of Agro-industrial Technology Bogor Agricultural UniversityBogorIndonesia Department of Physics Faculty of Mathematics and Natural SciencesBogor Agricultural UniversityBogorIndonesia

Purpose-The production of glycerol derivatives by the esterification process is subject to many constraints related to the yield of the production target and the lack of process *** accurate monitoring and controlling of the process can improve production yield and *** purpose of this paper is to propose a real-time optimization(RTO)using gradient adaptive selection and classification from infrared sensor measurement to cover various disturbances and uncertainties in the ***/methodology/approach-The integration of the esterification process optimization using self-optimization(SO)was developed with classification process was combined with necessary condition optimum(NCO)as gradient adaptive selection,supported with laboratory scaled medium wavelength infrared(mid-IR)sensors,and measured the proposed optimization system indicator in the batch *** Process Modeling and Notation(BPMN 2.0)was built to describe the tasks of SO workflow in collaboration with NCO as an abstraction for the conceptual ***,Stateflow modeling was deployed to simulate the three states of gradient-based adaptive control combined with support vector machine(SVM)classification and Arduino microcontroller for ***-This new method shows that the real-time optimization responsiveness of control increased product yield up to 13 percent,lower error measurement with percentage error 1.11 percent,reduced the process duration up to 22 minutes,with an effective range of stirrer rotation set between 300 and 400 rpm and final temperature between 200 and 210℃ which was more efficient,as it consumed less *** limitations/implications-In this research the authors just have an experiment for the esterification process using glycerol,but as a development concept of RTO,it would be possible to apply for another chemical reaction or *** implications-This research introduces new development of an RTO approach to optimal con

关键词： Gradient technique Infrared sensor Real-time optimization Simulation and modelling Support vector machine

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Miniscope3D:optimized single-shot miniature 3D fluorescence microscopy

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Light(Science & Applications) 2020年第1期9卷 367-379页

作者： Kyrollos Yanny Nick Antipa William Liberti Sam Dehaeck Kristina Monakhova Fanglin Linda Liu Konlin Shen Ren Ng Laura Waller UCB/UCSF Joint Graduate Program in Bioengineering University of CaliforniaBerkeleyCA 94720USA Department of Electrical Engineering&Computer Sciences University of CaliforniaBerkeleyCA 94720USA TIPs Department Universite libre de Bruxelles(ULB)1050 BrusselsBelgium

Miniature fluorescence microscopes are a standard tool in systems ***,widefield miniature microscopes capture only 2D information,and modifications that enable 3D capabilities increase the size and weight and have poor resolution outside a narrow depth ***,we achieve the 3D capability by replacing the tube lens of a conventional 2D Miniscope with an optimized multifocal phase mask at the objective’s aperture *** the phase mask at the aperture stop significantly reduces the size of the device,and varying the focal lengths enables a uniform resolution across a wide depth *** phase mask encodes the 3D fluorescence intensity into a single 2D measurement,and the 3D volume is recovered by solving a sparsity-constrained inverse *** provide methods for designing and fabricating the phase mask and an efficient forward model that accounts for the fieldvarying aberrations in miniature *** demonstrate a prototype that is 17mm tall and weighs 2.5 grams,achieving 2.76μm lateral,and 15μm axial resolution across most of the 900×700×390μm^(3) volume at 40 volumes per *** performance is validated experimentally on resolution targets,dynamic biological samples,and mouse brain *** with existing miniature single-shot volume-capture implementations,our system is smaller and lighter and achieves a more than 2×better lateral and axial resolution throughout a 10×larger usable depth *** microscope design provides single-shot 3D imaging for applications where a compact platform matters,such as volumetric neural imaging in freely moving animals and 3D motion studies of dynamic samples in incubators and lab-on-a-chip devices.

关键词： enable resolution narrow

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