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arXiv 2022年

作者： Qin, Rong Huangfu, Luwen Hood, Devon Ma, James Huang, Sheng School of Big Data & Software Engineering Chongqing University Chongqing400044 China Fowler College of Business San Diego State University San DiegoCA92182 United States Center for Human Dynamics in the Mobile Age San Diego State University San DiegoCA92182 United States College of Science San Diego State University San DiegoCA92182 United States Department of Business Analysis University of Colorado Colorado SpringsCO80918 United States Ministry of Education Key Laboratory of Dependable Service Computing in Cyber Physical Society Chongqing University Chongqing400044 China

Pavement Distress Recognition (PDR) is an important step in pavement inspection and can be powered by image-based automation to expedite the process and reduce labor costs. Pavement images are often in high-resolution with a low ratio of distressed to non-distressed areas. Advanced approaches leverage these properties via dividing images into patches and explore discriminative features in the scale space. However, these approaches usually suffer from information loss during image resizing and low efficiency due to complex learning frameworks. In this paper, we propose a novel and efficient method for PDR. A light network named the Kernel Inversed Pyramidal Resizing Network (KIPRN) is introduced for image resizing, and can be flexibly plugged into the image classification network as a pre-network to exploit resolution and scale information. In KIPRN, pyramidal convolution and kernel inversed convolution are specifically designed to mine discriminative information across different feature granularities and scales. The mined information is passed along to the resized images to yield an informative image pyramid to assist the image classification network for PDR. We applied our method to three well-known Convolutional Neural Networks (CNNs), and conducted an evaluation on a large-scale pavement image dataset named CQU-BPDD. Extensive results demonstrate that KIPRN can generally improve the pavement distress recognition of these CNN models and show that the simple combination of KIPRN and EfficientNetB3 significantly outperforms the state-of-the-art patch-based method in both performance and efficiency. © 2022, CC BY-NC-SA.

关键词： Convolution

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Artificial Intelligence without Restriction Surpassing Human Intelligence with Probability One: Theoretical Insight into Secrets of the Brain with AI Twins of the Brain

arXiv

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arXiv 2024年

作者： Huang, Guang-Bin Westover, M. Brandon Tan, Eng-King Wang, Haibo Cui, Dongshun Ma, Wei-Ying Wang, Tiantong He, Qi Wei, Haikun Wang, Ning Tian, Qiyuan Lam, Kwok-Yan Yao, Xin Wong, Tien Yin School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Beth Israel Deaconess Medical Center Harvard Medical School Boston United States Department of Neurology National Neuroscience Institute Singapore Research Centre of Big Data and Artificial Intelligence for Medicine First Affiliated Hospital of Sun Yat-Sen University Guangzhou China Duke-NUS Medical School National University of Singapore Singapore Mind PointEye Singapore Institute for AI Industry Research Tsinghua University Beijing China College of Computing and Data Science Nanyang Technological University Singapore School of Biomedical Engineering Tsinghua University Beijing China Singapore AI Safety Institute Nanyang Technological University Singapore School of Data Science Lingnan University Hong Kong School of Computer Science University of Birmingham United Kingdom Singapore Eye Research Institute Singapore National Eye Centre Singapore Tsinghua Medicine Tsinghua University Beijing China

Artificial Intelligence (AI) has apparently become one of the most important techniques discovered by humans in history while the human brain is widely recognized as one of the most complex systems in the universe. One fundamental critical question which would affect human sustainability remains open: Will artificial intelligence (AI) evolve to surpass human intelligence in the future? This paper shows that in theory new AI twins with fresh cellular level of AI techniques for neuroscience could approximate the brain and its functioning systems (e.g. perception and cognition functions) with any expected small error and AI without restrictions could surpass human intelligence with probability one in the end. This paper indirectly proves the validity of the conjecture made by Frank Rosenblatt 70 years ago about the potential capabilities of AI, especially in the realm of artificial neural networks. This paper also gives the answer to the two widely discussed fundamental questions: 1) whether AI could have potentials of discovering new principles in nature;2) whether error backpropagation (BP) algorithm commonly and efficiently used in tuning parameters in AI applications is also adopted in the brain. Intelligence is just one of fortuitous but sophisticated creations of the nature which has not been fully discovered. Like mathematics and physics, with no restrictions artificial intelligence would lead to a new subject with its self-contained systems and principles. We anticipate that this paper opens new doors for 1) AI twins and other AI techniques to be used in cellular level of efficient neuroscience dynamic analysis, functioning analysis of the brain and brain illness solutions;2) new worldwide collaborative scheme for interdisciplinary teams concurrently working on and modelling different types of neurons and synapses and different level of functioning subsystems of the brain with AI techniques;3) development of low energy of AI techniques with the aid of fundament

关键词： Neurology

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An empirical "high-confidence" candidate zone for Fermi BL Lacertae Objects

arXiv

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arXiv 2020年

作者： Kang, Shi-Ju Zhu, Kerui Feng, Jianchao Wu, Qingwen Zhang, Bin-Bin Yin, Yue Wang, Fei-Fei Liu, Yu Zheng, Tian-Yuan School of Physics and Electrical Engineering Liupanshui Normal University Liupanshui Guizhou553004 Guizhou Provincial Key Laboratory of Radio Astronomy and Data Processing Guiyang Guizhou550001 Department of Physics Yunnan Normal University Kunming Yunnan650092 School of Physics and Electronic Science Guizhou Normal University Guiyang Guizhou550001 China School of Physics Huazhong University of Science and Technology Wuhan Hubei430074 China School of Astronomy and Space Science Nanjing University Nanjing210093 China Key Laboratory of Modern Astronomy and Astrophysics Nanjing University Ministry of Education Department of Physics and Astronomy University of Nevada Las VegasNV89154 United States School of Mathematics and Physics Qingdao University of Science and Technology Qingdao Shandong266061 China High School Affiliated to Anhui Normal University Wuhu Anhui241000 China

In the third catalog of active galactic nuclei detected by the Fermi Large Area Telescope Clean (3LAC) sample, there are 402 blazars candidates of uncertain type (BCU). The proposed analysis will help to evaluate the potential optical classification flat spectrum radio quasars (FSRQs) versus BL Lacertae (BL Lacs) objects of BCUs, which can help to understand which is the most elusive class of blazar hidden in the Fermi sample. By studying the 3LAC sample, we found some critical values of γ-ray photon spectral index (Γph), variability index (VI) and radio flux (FR) of the sources separate known FSRQs and BL Lac objects. We further utilize those values to defined an empirical "high-confidence" candidate zone that can be used to classify the BCUs. Within such a zone (ΓphRph, VI and FR. Copyright © 2020, The Authors. All rights reserved.

关键词： Gamma rays

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Chemistry: A single iron site confined in a graphene matrix for the catalytic oxidation of benzene at room temperature

引用

Science Advances 2015年第11期1卷

作者： Deng, Dehui Chen, Xiaoqi Yu, Liang Wu, Xing Liu, Qingfei Liu, Yun Yang, Huaixin Tian, Huanfang Hu, Yongfeng Du, Peipei Si, Rui Wang, Junhu Cui, Xiaoju Li, Haobo Xiao, Jianping Xu, Tao Deng, Jiao Yang, Fan Duchesne, Paul N. Zhang, Peng Zhou, Jigang Sun, Litao Li, Jianqi Pan, Xiulian Bao, Xinhe State Key Laboratory of Catalysis Collaborative Innovation Center of Chemistry for Energy Materials Dalian Institute of Chemical Physics Chinese Academy of Sciences Zhongshan Road 457 Dalian116023 China SEU-FEI Nano-Pico Center Key Laboratory of MEMS of Ministry of Education School of Electronic Science and Engineering Southeast University Nanjing210096 China Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing100190 China Canadian Light Source Inc. University of Saskatchewan 44 Innovation Boulevard Saskatoon SaskatchewanS7N2V3 Canada Shanghai Synchrotron Radiation Facility Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai201204 China Mössbauer Effect Data Center Dalian Institute of Chemical Physics Chinese Academy of Sciences Zhongshan Road 457 Dalian116023 China Department of Chemistry Dalhousie University HalifaxNSB3H4R2 Canada

Coordinatively unsaturated (CUS) iron sites are highly active in catalytic oxidation reactions;however, maintaining the CUS structure of iron during heterogeneous catalytic reactions is a great challenge. Here, we report a strategy to stabilize single-atom CUS iron sites by embedding highly dispersed FeN4 centers in the graphene matrix. The atomic structure of FeN4 centers in graphene was revealed for the first time by combining high-resolution transmission electron microscopy/high-angle annular dark-field scanning transmission electron microscopy with lowtemperature scanning tunneling microscopy. These confined single-atom iron sites exhibit high performance in the direct catalytic oxidation of benzene to phenol at room temperature, with a conversion of 23.4% and a yield of 18.7%, and can even proceed efficiently at 0°C with a phenol yield of 8.3% after 24 hours. Both experimental measurements and density functional theory calculations indicate that the formation of the Fe-O intermediate structure is a key step to promoting the conversion of benzene to phenol. These findings could pave the way toward highly efficient nonprecious catalysts for low-temperature oxidation reactions in heterogeneous catalysis and electrocatalysis. © 2015 The Authors, some rights reserved.

关键词： Catalytic oxidation

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Animal Shapes, Modal Analysis, and Visualization of Motion (II): Dynamics and Fourier Decomposition

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Journal of Geometric Analysis 2023年第10期33卷 309-309页

作者： Chen, Goong Wei, Chunqiu Sergeev, Alexey Yang, Jing Huang, Jingtong Kaya Scully, Matthew M. Chen, Ming-Chieh Krantz, Steven G. Yao, Pengfei Guo, Tiexin Wang, Junmin Department of Mathematics Texas A &M University College Station 77843 TX United States Institute for Quantum Science and Engineering Texas A &M University College Station 77843 TX United States Hsinchu Branch National Center for Theoretical Sciences National Tsing Hua University Hsinchu Taiwan Department of Mathematics and Data Science Beijing University of Civil Engineering and Architecture Beijing 100044 China School of Mathematics Beijing Institute of Technology Beijing 100081 China Department of Mechanical Engineering Cheng Shiu University Kaohsiung 83347 Taiwan Department of Mathematics Washington University at St. Louis St. Louis 63130 MO United States Key Laboratory of Complex Systems and Data Science of Ministry of Education School of Mathematics Shanxi University Shanxi Taiyuan 030006 China Institute of Systems Science Academy of Mathematics and Systems Science Academia Sinica Beijing 100190 China School of Mathematics and Statistics Central South University Hunan Changsha 410075 China

This paper begins with solving the linear elastodynamic equation with forcing by expanding it into Fourier series. We then proceed to prove the conservation laws of momentum, angular momentum, and energy. We intend the paper to provide a computational demonstration for modal analysis by showing that eigenmodes and frequencies of vibration of a free-suspending horse match with the modal analysis results of the horse after a short-impulse impact of the horse with a wall. The horse CAD model has to be modified to contain a rigid body portion to prevent the rotational-tumbling modes. A fast Fourier transform is applied to the sensorial time series data in the calculation of the vibration frequencies. One can see that many low-frequency modes and data match these modal analysis results. © 2023, Mathematica Josephina, Inc.

关键词： Animal motions Eigenfunction expansions External forcing Frequency matching Sensors

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Yellow-b, -c, -e and -h are required for normal body coloration inHenosepilachna vigintioctopunctata

引用

Archives of Insect Biochemistry and Physiology 2021年第2期109卷

作者： Pei Wang Long-Ji Ze Lin Jin Guo-Qing Li Department of Entomology College of Plant Protection Education Ministry Key Laboratory of Integrated Management of Crop Diseases and Pests/State and Local Joint Engineering Research Center of Green Pesticide Invention and Application Nanjing Agricultural University Nanjing China Contribution: Data curation (equal) Investigation (equal) Resources (equal) Contribution: Data curation (equal) Investigation (equal) Methodology (equal)

The involvement of yellow genes y-b, y-c, y-e , and y-h in cuticle tanning has poorly been clarified. In the present paper, six putative yellow ( y-y, y-b, y-c, y-e y-f , and y-h ) genes were identified in Henosepilachna vigintioctopunctata . Hvy-b, Hvy-c, Hvy-e , and Hvy-h were abundantly transcribed at early larval and late pupal stages, especially in the epidermis. Accordingly, RNA interference (RNAi) experiments were performed by an injection of ds y-b , ds y-c , ds y-e , or ds y-h into the second instar larvae and 1-day-old pupae. The head capsule, scoli and strumae, and legs in the fourth-instar larvae became blacker; the blackish spots in the pupae were darkened and widened after RNAi of Hvy-b , compared with those of ds egfp -treated controls. Depletion of Hvy-b at the 1-day-old pupal stage expanded two pair of black markings on the sternum of the metathorax, and darkened the black patched on the sterna of the abdomen segments I–VI in the resultant adults. Depletion of Hvy-e caused darker pigmented adult body and elytral cuticles than those of ds egfp -introduced controls. However, there was no obvious difference in pigmentation of the black markings. Hvy-h -deficient larvae displayed dark yellow body color, whereas the body color of the ds egfp -injected control was pale yellow. There was no obvious difference in coloration of larval specific-black markings or pupal cuticle between ds Hvy-h - and ds egfp- treated animals. Moreover, silence of Hvy-c at the second instar larval stage lightened black markings in the resulting larvae and pupae, but had no influence on pale yellow body color. Our results demonstrated their different roles of the four yellow genes during body pigmentation: Hv Y-b and Hv Y-c, respectively, inhibit and facilitate the coloration within dark markings, whereas Hv Y-e and Hv Y-h, respectively, repress the pigmentation in adult and larval body cuticles outside the black patches in H. vigintioctopunctata . Hvy-b, Hvy-c, Hvy-e and Hvy-h a

关键词： function Henosepilachna vigintioctopunctata melanin pigmentation yellow

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Microstructure and mechanical properties of solid state recycled 4Cr5MoSiV (H11) steel prepared by powder metallurgy

Results in Materials

引用

Results in Materials 2021年 10卷

作者： Bhatta, Gyanendra De Los Santos Valladares, Luis Liu, Xinggang Ma, Zhaojun Bustamante Domínguez, A.G. Moreno, N.O. Espinoza Suarez, S.M. Barnes, C.H.W. Zhang, Deliang School of Materials Science and Engineering Northeastern University Liaoning Shenyang 110819 China Key Laboratory of Data Analytics and Optimization for Smart Industry (Ministry of Education) Northeastern University Shenyang 110819 China Laboratorio de Ceramicos y Nanomaterailes Facultad de Ciencias Físicas Universidad Nacional Mayor de San Marcos Ap. Postal 14-0149 Lima Peru Cavendish Laboratory Department of Physics University of Cambridge UK Cambridge CB3 0HE United Kingdom Departamento de Física Universidade Federal de Sergipe SE São Cristóvão 49100- 000 Brazil

4Cr5MoSiV (H11) steel machining chips were crushed to a powder and then consolidated into discs by hot pressing under various consolidation parameters. The discs were subjected to modified spheroidizing annealing treatment, and their evolved microstructure, tensile mechanical properties and fracture behavior were studied. The microstructure consisted of α−Fe as a matrix, together with heterogeneously distributed non metallic inclusions from the chip-crushing step and precipitated secondary phases. The yield strength, fracture strength and elongation to fracture of the consolidated discs were determined to be in the range of 215∼264 MPa, 344∼415 MPa and 1.2∼2.6%, respectively. The strength of the recycled H11 steel was comparable with that of the ingot metallurgy (IM) H11 steel, but the tensile ductility of the former was significantly lower than that of the latter, being mainly caused by the fracture of the non-metallic inclusions along with the hard secondary phase particles in the IM H11 steel which leads to premature fracture of the samples. The Vickers hardness of the samples were in the range of 144∼194 HV being comparable to that of the IM counterpart. Factographs of the fracture surface demonstrated that the tensile test specimens fractured in a brittle fracture mode. © 2021 The Author(s)

关键词： Brittle fracture H11 Steel Microstructure Modified spheroidizing Solid state recycling Tensile properties

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Intention-sensitive Preference Learning Network for Personalized Session-based Recommendation

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ACM Transactions on Recommender Systems 1000年

作者： Qingbo Zhang Xiaochun Yang Hao Chen Bin Wang Xiangmin Zhou Computer Science and Engineering Northeastern University Shenyang China Northeastern University Shenyang China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Shenyang China Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Ministry of Education Shenyang China School of Computing Technologies RMIT University Melbourne Australia

Nowadays, research on session-based recommender systems (SRSs) is one of the hot spots in the recommendation domain. Existing methods make recommendations based on the user’s current intention (also called short-term preference) during a session, often overlooking the specific preferences associated with these intentions. In reality, users usually exhibit diverse preferences for different intentions, and even for the same intention, individual preferences can vary significantly between users. As users interact with items throughout a session, their intentions can shift accordingly. To enhance recommendation quality, it is crucial not only to consider the user’s intentions but also to dynamically learn their varying preferences as these intentions change. In this paper, we propose a novel Intention-sensitive Preference Learning Network (IPLN) including three main modules: intention recognizer, preference detector, and prediction layer. Specifically, the intention recognizer infers the user’s underlying intention within his/her current session by analyzing complex relationships among items. Based on the acquired intention, the preference detector learns the intention-specific preference by selectively integrating latent features from items in the user’s historical sessions. Besides, the user’s general preference is utilized to refine the obtained preference to reduce the potential noise carried from historical records. Ultimately, the fine-tuned preference and intention collaborate to instruct the next-item recommendation in the prediction layer. To prove the effectiveness of the proposed IPLN, we perform extensive experiments on two real-world datasets. The experiment results demonstrate the superiority of IPLN compared with other state-of-the-art models.

关键词： session-based recommender systems personalized next-item recommendation user intention intention-specific preference

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Correction to: Path-based estimation for link prediction

引用

International Journal of Machine Learning and Cybernetics 2021年第9期12卷 2459-2459页

作者： Ma, Guoshuai Yan, Hongren Qian, Yuhua Wang, Lingfeng Dang, Chuangyin Zhao, Zhongying Institute of Big Data Science and Industry Shanxi University Taiyuan China School of Computer and Information Technology Shanxi University Taiyuan China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University Taiyuan China Department of Electrical Engineering and Computer Science University of Wisconsin-Milwaukee Milwaukee USA Department of Manufacture Engineering and Engineering Management City University of Hong Kong Kowloon Tong Hong Kong The School of Computer Science and Engineering Shandong University of Science and Technology Qingdao China

A correction to this paper has been published: https://***/10.1007/s13042-021-01350-4

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Corrigendum to “GLRM: Logical pattern mining in the case of inconsistent data distribution based on multigranulation strategy” [Int. J. Approx. Reason. 143 (2022) 78–101]

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International Journal of Approximate Reasoning 2022年 151卷 271-271页

作者： Qian Guo Yuhua Qian Xinyan Liang Institute of Big Data Science and Industry Shanxi University Taiyuan 030006 Shanxi China Engineering Research Center for Machine Vision and Data Mining of Shanxi Province Taiyuan 030006 Shanxi China School of Computer and Information Technology Shanxi University Taiyuan 030006 Shanxi China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University Taiyuan 030006 Shanxi China

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