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IEEE International Conference on Systems, Man and Cybernetics

作者： Tao Peng Yidong Gu Yanqing Xu Caishan Wang Lei Zhang Jing Cai School of Future Science and Engineering Soochow University Suzhou China Department of Radiation Oncology UT Southwestern Medical Center Dallas TX USA Department of Medical Ultrasound the Affiliated Suzhou Hospital of Nanjing Medical University Suzhou Municipal Hospital Suzhou Jiangsu China McDermott Center for Human Growth and Development University of Texas Southwestern Medical Center Dallas Texas USA Department of Ultrasound the Second Affiliated Hospital of Soochow University Suzhou China Graduate Program of Medical Physics and Data Science Research Center Duke Kunshan University Kunshan Jiangsu China Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong China

Ultrasound kidney image segmentation presents significant challenges due to missing or ambiguous boundaries. In this study, we introduce a coarse-to-refinement approach incorporating four novel aspects. Firstly, we leverage the properties of a principal curve (PC) to automatically fine-tune the curve shape and employ a neural network's learning ability to reduce model error. Secondly, a deep fusion learning network is utilized for the coarse segmentation step, incorporating a parallel architecture to enhance deep-learning performance. Thirdly, addressing the limitation of standard PC-based methods in determining the number of vertices automatically, we propose an automatic searching polygon tracking method using a mean shift clustering-based approach to replace the projection and vertex extension step in standard PC-based methods. Lastly, we develop an explainable mathematical map function for the kidney contour, as denoted by the neural network output (i.e., optimized vertices), which aligns well with the ground truth contour. We conducted various experiments to evaluate our method's performance, demonstrating its effectiveness in ultrasound kidney image segmentation.

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A Neural Network Based Modeling of Closed Room Thermal Comfort Environmental Prediction for Sensor Hub

A Neural Network Based Modeling of Closed Room Thermal Comfo...

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International Conference on Electrical Engineering/Electronics, computer, Telecommunications and Information technology, ECTI-CON

作者： Pornpawee Thongkhome Natasha Dejdumrong Science-Mathematics Program Triamudomsuksa Pattanakarn School Bangkok Thailand Dept. of Computer Engineering King Mongkut’s University of Technology Thonburi Bangkok Thailand

ISBN: (数字)9781728164861

ISBN: (纸本)9781728164878

Currently, environmental protection and intelligence system are topics of interest in smart homes and intelligent buildings. This work represents an environmental prediction study of the closed room which installed a split-type air-conditioning system and a newly designed sensor hub using a feed-forward back-propagation artificial neural network-based prediction for human thermal comfort and indirectly concerned to the growth or existence of diseases, contagious diseases and allergies. The RPROP algorithm was utilized to train the closed room environmental parameters that get from sensor hub especial relative humidity in the ANN model and validate the model by using cohen's kappa and ROC curve to represents the degree of accuracy and reliability. The result obtained from the ANN trained data agreed closely with those obtained from a sensor hub with the high perfect agreement. The benefit of the ANN-based strategy in this study could be utilized for the design of a sensor hub that can realize the adaptive adjustment of environmental parameters through the air conditioning system.

关键词： Humidity Artificial neural networks Predictive models Buildings Temperature sensors Computational modeling Prediction algorithms

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Third-order asymptotics of variable-length compression allowing errors

arXiv

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arXiv 2020年

作者： Sakai, Yuta Yavas, Recep Can Tan, Vincent Y.F. The Department of Electronics and Computer Science Graduate School of Engineering University of Hyogo The Department of Electrical Engineering California Institute of Technology The Department of Electrical and Computer Engineering The Department of Mathematics National University of Singapore Singapore

This study investigates the fundamental limits of variable-length compression in which prefix-free constraints are not imposed (i.e., one-to-one codes are studied) and non-vanishing error probabilities are permitted. Due in part to a crucial relation between the variable-length and fixed-length compression problems, our analysis requires a careful and refined analysis of the fundamental limits of fixed-length compression in the setting where the error probabilities are allowed to approach either zero or one polynomially in the blocklength. To obtain the refinements, we employ tools from moderate deviations and strong large deviations. Finally, we provide the third-order asymptotics for the problem of variable-length compression with non-vanishing error probabilities. We show that unlike several other information-theoretic problems in which the third-order asymptotics are known, for the problem of interest here, the third-order term depends on the permissible error probability. Copyright © 2020, The Authors. All rights reserved.

关键词： Errors

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Linkage-FFD algorithm for dental crown and abutment shape design

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computer-Aided Design and Applications 2018年第4期15卷 532-541页

作者： Li, Xun Chen, Ming Shenzhen Graduate School Harbin Institute of Technology China School of Computer Science and Information Technology Guangxi Normal University China

In dental CAD, crown design is one core function and the thickness between the crown and the corresponding abutment should be in the standard range. However, the thickness requirement is currently not considered when designing the crown. In this paper, a novel algorithm, i.e., linkage free-form deformation (L-FFD) is proposed to automatically ensure the thickness requirement in the crown design. The algorithm of the direct manipulation of free-form deformation (DMFFD) [3] is implemented to support the crown design, and three more steps, i.e., local adjustment by DMFFD, thickness detection and smoothing, are performed on the abutment alternately and itera-tively, which will make sure the abutment is smooth and at the same time the thickness requirement is automatically met. As the thickness requirement varies at different parts of a tooth, the local coordinate system is established in this paper to help quickly classify the vertices of the tooth. The algorithm is implemented and the tested examples show that it is efficient and valid, which can speed up the crown design by saving the manual modification of abutment for satisfying the thickness requirement. © 2018 CAD Solutions, LLC.

关键词： computer aided design

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Parallel computing proximal method for nonsmooth convex optimization with fixed point constraints of quasi-nonexpansive mappings

Applied Set-Valued Analysis and Optimization

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Applied Set-Valued Analysis and Optimization 2020年第1期2卷 1-17页

作者： Shimizu, Kengo Hishinuma, Kazuhiro Iiduka, Hideaki Computer Science Course Graduate School of Science and Technology Meiji University 1-1-1 Higashimita Tama-ku Kawasaki-shi Kanagawa214-8571 Japan Department of Computer Science Meiji University 1-1-1 Higashimita Tama-ku Kawasaki-shi Kanagawa214-8571 Japan

We present a parallel computing proximal method for solving the problem of minimizing the sum of convex functions over the intersection of fixed point sets of quasi-nonexpansive mappings in a real Hilbert space. We also provide a convergence analysis of the method for constant and diminishing step sizes under certain assumptions as well as a convergence-rate analysis for a diminishing step size. Numerical comparisons show that the performance of the algorithm is comparable with existing subgradient methods. ©2020 Applied Set-Valued Analysis and Optimization

关键词： Numerical methods

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Deactivation/Regeneration Studies in Structured Monolithic Ni-Based Catalysts Applied in Dry Reforming of Methane

SSRN

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SSRN 2022年

作者： de Araújo, Ítalo R.S. Ribeiro, André T.S. Garcia, Ramón R.P. Sales, Deivson C.S. Almeida, Luciano C. Department of Chemical Engineering Technology and Geoscience Center Federal University of Pernambuco PE Recife50740-521 Brazil Polytechnic School of Pernambuco University of Pernambuco Rua Benfica 455 Madalena PE Recife50720-001 Brazil Materials Science and Engineering Graduate Program Federal University of Piauí PI Teresina Brazil Federal Rural University of Pernambuco Academic Unit of Cabo de Santo Agostinho PE Cabo de Santo Agostinho Brazil

In this work, the Ni/γ-Al2O3 (Ni/Al) and Ni/LA2O3-γ-Al2O3 (Ni/La-Al) catalysts were synthesized by the all-in-one method and used in the Dry Reforming of Methane (DRM). The catalysts were characterized and a smaller Ni crystallite size for the La-promoted catalyst was observed. The effects of the feed ratio (CH4:CO2), the use of La as a promoter of the catalyst support, and the use of the structured system in DRM reaction were investigated. Raman spectroscopy, scanning electron microscopy (SEM), and X-ray diffraction (XRD) were applied to investigate the catalytic deactivation effects. The deactivation of the structured catalysts was also evaluated by applying different weight hourly space velocities (WHSV): 20, 30, and 40 L gcat-1 h-1. Besides that, the regeneration of the catalysts was developed through the comparison of the treatment with CO2 and H2 atmospheres. The catalytic study of the powder samples showed that the lower the CH4:CO2 ratio the higher reactants conversion for both catalysts. It was also noted that the CH4:CO2 feed ratio of 4 provided a conversion 10 % higher for the Ni/La-Al catalyst in comparison with the Ni/Al catalyst. The analogy between the powder and structured systems implied greater conversion for the structured system. Furthermore, the greater and the lower deactivation of the structured systems were identified for the WHSV values of 40 and 20 L gcat-1 h-1, respectively. Finally, the regeneration treatment with CO2 showed to be more efficient than the treatment with H2 © 2022, The Authors. All rights reserved.

关键词： Carbon dioxide

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ALBFL: A Novel Neural Ranking Model for Software Fault Localization via Combining Static and Dynamic Features

ALBFL: A Novel Neural Ranking Model for Software Fault Local...

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Yuqing Pan Xi Xiao Guangwu Hu Bin Zhang Qing Li Haitao Zheng School of Information Technology University of International Business and Economics Beijing China Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen China Peng Cheng Laboratory Shenzhen China School of Computer Science Shenzhen Institute of Information Technology Shenzhen China Southern University of Science and Technology Shenzhen China

ISBN: (数字)9781665403924

ISBN: (纸本)9781665403931

Automatic fault localization plays a significant role in assisting developers to fix software bugs efficiently. Although existing approaches, e.g., static methods and dynamic ones, have greatly alleviated this problem by analyzing static features in source code and diagnosing dynamic behaviors in software running state respectively, the fault localization accuracy still does not meet user requirements. To improve the fault locating ability with statement granularity, this paper proposes ALBFL, a novel neural ranking model that involves the attention mechanism and the LambdaRank model, which can integrate the static and dynamic features and achieve very high accuracy for identifying software faults. ALBFL first introduces a transformer encoder to learn the semantic features from software source code. Also, it leverages other static statistical features and dynamic features, i.e., eleven Spectrum-Based Fault Localization (SBFL) features, three mutation features, to evaluate software together. Specially, the two types of features are integrated through a self-attention layer, and fed into the LambdaRank model so as to rank a list of possible fault statements. Finally, thorough experiments are conducted on 5 open-source projects with 357 faulty programs in Defects4J. The results show that ALBFL outperforms 11 traditional SBFL methods (by three times) and 2 state-of-the-art approaches (by 13%) on ranking faulty statements in the first position.

关键词： Location awareness Fault diagnosis Semantics Switches Software Space exploration Security

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Simultaneous outlier detection and elimination in hyperspectral unmixing via weighted non-negative matrix tri-factorization

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Machine Learning 2025年第7期114卷

作者： Hashemi-Nazari, Yasin Saberi-Movahed, Farid Tajaddini, Azita Moreira, Catarina Ning, Xin Tiwari, Prayag Department of Applied Mathematics Faculty of Mathematics and Computer Shahid Bahonar University of Kerman Kerman Iran Department of Applied Mathematics Faculty of Sciences and Modern Technologies Graduate University of Advanced Technology Kerman Iran Data Science Institute University of Technology Sydney Sydney Australia AnnLab Institute of Semiconductors Chinese Academy of Sciences Beijing China School of Information Technology Halmstad University Halmstad Sweden

Hyperspectral unmixing (HU) involves separating mixed pixel spectra into pure endmember spectra and their corresponding abundance fractions. However, it faces significant challenges due to outliers in the hyperspectral data, which often appear as pixel and band anomalies. Outliers in pixels could result in incorrect classification and inaccurate quantification of materials, while outliers in bands could alter spectral characteristics, leading to misidentifying endmembers and incorrect estimates of abundance. To tackle these issues, this paper introduces a new approach, named simultaneous outlier detection and elimination via weighted non-negative matrix tri-factorization (SODE-WNMTF), which offers an efficient means of addressing the impact of outliers in the unmixing process. Leveraging the co-clustering property of NMTF, SODE-WNMTF introduces a novel weighting matrix, which involves simultaneous clustering of both pixels and spectral bands to effectively detect and mitigate the negative impact of both pixel and band outliers during the unmixing process. At the same time, the inherent structure of the hyperspectral image (HSI) is utilized through the examination of local and global connections among pixels and spectral bands, consequently improving the co-clustering procedure. In addition, SODE-WNMTF proposes a spatial weighting factor, which utilizes the similarity of adjacent pixels, to promote piecewise smoothness in abundance maps while mitigating the impact of outliers. Moreover, since pixels in regions dominated by a single endmember exhibit spectra closely resembling that endmember, SODE-WNMTF incorporates a sparse estimation technique for endmember signatures. Finally, to verify the performance of SODE-WNMTF, a series of experiments is conducted on both synthetic and real HSIs, with outcomes proving its superiority against other cutting-edge approaches. The source code is also available at https://***/yasinhashemi/SODE-WNMTF. © The Author(s) 2025.

关键词： Non-negative matrix factorization

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Exponential acceleration of macroscopic quantum tunneling in a Floquet Ising model

arXiv

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arXiv 2023年

作者： Grattan, George Barton, Brandon A. Feeney, Sean Mossi, Gianni Patnaik, Pratik Sagal, Jacob C. Carr, Lincoln D. Oganesyan, Vadim Kapit, Eliot Quantum Engineering Program Colorado School of Mines 1523 Illinois St CO Golden80401 United States Department of Computer Science Colorado School of Mines 1500 Illinois St CO Golden80401 United States Department of Applied Mathematics and Statistics Colorado School of Mines 1500 Illinois St CO Golden80401 United States Department of Physics Colorado School of Mines 1523 Illinois St CO Golden80401 United States KBR Inc. 601 Jefferson St. HoustonTX77002 United States NASA Ames Research Center Moffett FieldCA94035 United States Department of Physics and Astronomy College of Staten Island CUNY Staten IslandNY10314 United States Physics program and Initiative for the Theoretical Sciences The Graduate Center CUNY New YorkNY10016 United States Center for Computational Quantum Physics Flatiron Institute 162 5th Avenue New YorkNY10010 United States

The exponential suppression of macroscopic quantum tunneling (MQT) in the number of elements to be reconfigured is an essential element of broken symmetry phases. Slow MQT is also a core bottleneck in quantum algorithms, such as traversing an energy landscape in optimization, and adiabatic state preparation more generally. In this work, we demonstrate the possibility to accelerate MQT through Floquet engineering with the application of a uniform, high frequency transverse drive field. Using the ferromagnetic phase of the transverse field Ising model in one and two dimensions as a prototypical example, we identify three qualitatively distinct regimes as a function of drive strength: (i) for weak drive, the system exhibits exponentially slow MQT alongside robust magnetic order, as expected;(ii) at intermediate drive strength, we find polynomial decay of rates alongside vanishing magnetic order consistent with critical or paramagnetic state;(iii) at very strong drive strengths both the tunnelling rate and time-averaged magnetic order remain finite with increasing system size. We support these claims with extensive full wavefunction and matrix-product state numerical simulations, and theoretical analysis. An experimental test of these results presents a technologically important and novel scientific question accessible on NISQ-era quantum computers. © 2023, CC BY.

关键词： Ising model

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Comparison of temperature elevation between in physical phantom skin and in human skin during local exposure to a 28 GHz millimeter-wave

Comparison of temperature elevation between in physical phan...

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2019 Joint International Symposium on Electromagnetic Compatibility, Sapporo and Asia-Pacific International Symposium on Electromagnetic Compatibility, EMC Sapporo/APEMC 2019

作者： Kageyama, Itsuki Masuda, Hiroshi Morimatsu, Yoshitaka Ishitake, Tatsuya Sakakibara, Keita Hikage, Takashi Hirata, Akimasa Kurume University School of Medicine Dept. of Environmental Medicine Kurume Fukuoka Japan Graduate School of Information Science and Technology Hokkaido University Sapporo Hokkaido Japan Nagoya Institute of Technology Dept. of Computer Science and Engineering Nagoya Aichi Japan

ISBN: (纸本)9784885523229

A millimeter-wave (MMW) at 28 GHz band, a candidate frequency for 5th generation wireless systems (5G), causes some concern about possible adverse effects on the human body. To investigate biological effects of local exposure to MMW, exposure systems equipped with a newly lens antenna, that can irradiate focused beam, were developed and characteristics of exposure for the skin were evaluated. The basic exposure performance of the systems was evaluated using temperature monitoring in physical phantom simulated human's skin and actual skin of forearm. Local temperature elevations were observed in both exposed skins, meaning achievement of results we expected in dosimetry. However, the time courses of these elevations were significantly different. These results suggest that some elements related to the temperature control such as heat conductivity and cooling by skin blood flow should be considered. © 2019 The Institute of Electronics, Information and Communication Engineer.

关键词： Phantoms

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