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Journal of experimental & clinical cancer research : CR 2024年第1期43卷 37页

作者： Ying Lin Yun Wu Qiangzu Zhang Xunwei Tu Sufang Chen Junfan Pan Nengluan Xu Ming Lin Peiwei She Gang Niu Yusheng Chen Hongru Li Department of Respiratory and Critical Care Medicine Shengli Clinical Medical College Fujian Medical University Fujian Provincial Hospital Fuzhou 350001 Fujian China. Department of General Practice Medicine Fujian Provincial Hospital Fuzhou 350001 China. The High Performance Computing Research Center Institute of Computing Technology Chinese Academy of Sciences Beijing 100095 China. The Centre for Experimental Research in Clinical Medicine Fujian Provincial Hospital Fuzhou 350001 Fujian China. The High Performance Computing Research Center Institute of Computing Technology Chinese Academy of Sciences Beijing 100095 China. g.niu@***. Department of Respiratory and Critical Care Medicine Shengli Clinical Medical College Fujian Medical University Fujian Provincial Hospital Fuzhou 350001 Fujian China. cysktz@***. Department of Respiratory and Critical Care Medicine Shengli Clinical Medical College Fujian Medical University Fujian Provincial Hospital Fuzhou 350001 Fujian China. muzi131122@***. Fujian Provincial Key Laboratory of Medical Big Data Engineering Fujian Provincial Hospital Shengli Clinical College of Fujian Medical University Fuzhou 350001 Fujian China. muzi131122@***.

The complete mitochondrial genome ofPelecanus occidentalis(Pelecaniformes: Pelecanidae) and its phylogenetic analysis

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Mitochondrial DNA Part B 2018年第2期3卷 782-783页

作者： Tian Huang Jiao Peng Yunlin Zhao Zhenggang Xu College of Bioscience and Biotechnology Hunan Agricultural University Changsha ChinaCollege of Information and Electronic Engineering Hunan City University YiYang Hunan Province China Hunan Engineering Research Center for Internet of Animals Changsha China Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province Central South University of Forestry and Technology Changsha China College of Information and Electronic Engineering Hunan City University YiYang Hunan Province ChinaKey Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province Central South University of Forestry and Technology Changsha China

Pelecanus occidentalis, in the order Pelecaniformes, is one of the most abundant and widespread waterbird species in the coast of America. However, the phylogenetic relationships among Pelecaniformes, Suliformes, and Ciconiiformes remain unresolved, particularly in Pelecanidae and Ciconiidae. In this study, we first sequenced and described the complete mitochondrial genome and phylogeny ofP. occidentalis. The whole genome ofP. occidentaliswas 17,315 bp in length, and contained 13 protein-coding genes, 21 transfer RNA genes, two ribosome RNA genes, and one non-coding control region. The overall base composition of the mitochondrial DNA was 30.1% for A, 23.7% for T, 31.5% for C, and 14.6% for G, with a GC content of 46.1%. A phylogenetic tree confirmed thatP. occidentalis(Pelecaniformes) was sister toC. boyciana(Ciconiiformes), and Ardeidae and Threskiornithidae were both monophyletic group. This information will be useful in the current understanding of the phylogeny and evolution of Pelecaniformes.

关键词： Pelecanus occidentalis Pelecaniformes mitochondrial genome phylogeny

Study of Circuit Evolution to Repair Design Flaws in FPGA Edge Computing Chips

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Study of Circuit Evolution to Repair Design Flaws in FPGA Ed...

International Microsystems, Packaging, Assembly and Circuits Technology (IMPACT)

作者： Kuo-Chi Chang Kai-Chun Chu Yuh-Chung Lin Hsiao-Chuan Wang Tsui-Lien Hsu Fu-Hsiang Chang Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China School of Information Science and Engineering Fujian University of Technology Fuzhou China College of Mechanical & Electrical Engineering National Taipei University of Technology Taipei Taiwan North Borneo University College Sabah Malaysia No3 Xueyuan Road University Town Minhou Fuzhou Fujian Province China No. 1 Section 3 Zhongxiao East Road Taipei City Taiwan Lot 47 Block-F Alamesra Permai Plaza 2 Jln Sulaman Kota Kinabalu Sabah Malaysia Fujian University of Technology Fuzhou China Institute of Environmental Engineering National Taiwan University Taipei Taiwan No.1 Section 4 Roosevelt Road Taipei City Taiwan Institute of Construction Engineering and Management National Central University Taoyuan Taiwan No. 300 Zhongda Rd. Zhongli District Taoyuan City Taiwan Shih-Hsin University Taipei Taiwan No. 1 Ln. 17 Sec. 1 Muzha Rd. Wenshan Dist. Taipei City Taiwan

ISBN: (数字)9781728198514

ISBN: (纸本)9781728198521

Field Programmable Logic Gate Array (FPGA) seems to be a semicustom circuit in the field of special application integrated circuits and use in edge computing. In this study, the chip-level reliability design of the system is carried out from the perspective of fault tolerance and fault self-repair. A real-time fault-tolerant self-repair system structure based on SRAM FPGA is proposed, and the design structure is verified on Xilinx Virtex-6 FPGA. It was found that the energy consumption of different modules in this study increased under the fault-tolerant self-repair design, and when the number of carry chains increased, the detection delay and reconstruction time also increased, which is in line with physical phenomena. However, it has been verified by the designer, it is found that the design time of the designer can be greatly reduced by about 50%, which is an important contribution.

关键词： Ions 5G mobile communication Urban areas Radio frequency Legged locomotion Field programmable gate arrays Three-dimensional displays

Study Of Fpga-Based Edge Computing In Semiconductor Manufacturing Safety Management Application

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Study Of Fpga-Based Edge Computing In Semiconductor Manufact...

International Microsystems, Packaging, Assembly and Circuits Technology (IMPACT)

作者： Kuo-Chi Chang Kai-Chun Chu Yuh-Chung Lin Hsiao-Chuan Wang Tsui-Lien Hsu Fu-Hsiang Chang Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China No3 Xueyuan Road University Town Minhou Fuzhou Fujian Province China School of Information Science and Engineering Fujian University of Technology Fuzhou China College of Mechanical & Electrical Engineering National Taipei University of Technology Taipei Taiwan No. 1 Section 3 Zhongxiao East Road Taipei City Taiwan North Borneo University College Sabah Malaysia Lot 47 Block-F Alamesra Permai Plaza 2 Jln Sulaman Kota Kinabalu Sabah Malaysia Fujian University of Technology Fuzhou China Institute of Environmental Engineering National Taiwan University Taipei Taiwan No.1 Section 4 Roosevelt Road Taipei City Taiwan Institute of Construction Engineering and Management National Central University Taoyuan Taiwan No. 300 Zhongda Rd. Zhongli District Taoyuan City Taiwan Shih-Hsin University Taipei Taiwan No. 1 Ln. 17 Sec. 1 Muzha Rd. Wenshan Dist. Taipei City Taiwan

ISBN: (数字)9781728198514

ISBN: (纸本)9781728198521

This study is based on the LOPA and ISD strategies as the basis for safety management, and explores the edge computing solutions that are extended in response to the vigorous development of 5G and IoT in the future, resulting in excessive cloud computing load. This study mainly uses FPGA to combine AES algorithm to achieve the edge computing function based on the aforementioned LOPA and ISD strategies for safety management under big data. However, the results of this study found that the system established in this study can effectively reduce the personnel management error rate by more than 50% and reduce the cloud computing load by 30%. High-tech factory operation safety management has significant benefits and contributions.

关键词： Ions Urban areas Tin Safety management Manufacturing Legged locomotion Field programmable gate arrays

Study of Green Supply Chain Management Platform Performance for Intelligent Hightech Factory Based on Advanced CSR Governance

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Study of Green Supply Chain Management Platform Performance ...

International Microsystems, Packaging, Assembly and Circuits Technology (IMPACT)

作者： Hsiao-Chuan Wang Kuo-Chi Chang Kai-Chun Chu Yuh-Chung Lin Tsui- Lien Hsu Fu-Hsiang Chang Institute of Environmental Engineering National Taiwan University Taipei Taiwan No.1 Section 4 Roosevelt Road Taipei City Taiwan Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China No3 Xueyuan Road University Town Minhou Fuzhou Fujian Province China School of Information Science and Engineering Fujian University of Technology Fuzhou China College of Mechanical & Electrical Engineering National Taipei University of Technology Taipei Taiwan No. 1 Section 3 Zhongxiao East Road Taipei City Taiwan North Borneo University College Sabah Malaysia Lot 47 Block-F Alamesra Permai Plaza 2 Jln Sulaman Kota Kinabalu Sabah Malaysia Fujian University of Technology Fuzhou China Institute of Construction Engineering and Management National Central University Taoyuan Taiwan No. 300 Zhongda Rd. Zhongli District Taoyuan City Taiwan Shih-Hsin University Taipei Taiwan No. 1 Ln. 17 Sec. 1 Muzha Rd. Wenshan Dist. Taipei City Taiwan

ISBN: (数字)9781728198514

ISBN: (纸本)9781728198521

Nowadays, the critical dimensions (CD) of semiconductor manufacturing processes are gradually declining, and various materials, reactants, or machine equipment is becoming more and more difficult. Therefore, the green supply chain management (GSCM) of smart high-tech factories has also become the target of competition for cutting-edge companies, because of this management. The more mature the mechanism of high production speed, lower operating costs and the higher the quality. In addition, corporate social responsibility (CSR) governance has also become an important investment evaluation item for semiconductor factories in recent years. As long as internationally renowned manufacturers start CSR, it is a pity that there are already some manufacturers. The establishment of a supply chain management system also synchronously promotes CSR, but there are few manufacturers that integrate CSR and green supply chain management, let alone the application of an intelligent management platform (IMP). This study builds a GSM platform (GSMP) based on the aforementioned problems, and the cluster analysis of K-means is used to optimize the management platform to optimize the overall performance of the management platform. Through the simulation results of this study, it is found that the performance of this management platform is far superior to the current mechanism of using human operation, whether it is the speed of emergency processing or the final management operation performance, which shows that this study industry contribution.

关键词： Green products data mining Recycling Carbon Supply chains Production facilities Roads

Max-min fairness user scheduling and power allocation in full-duplex OFDMA systems

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arXiv 2018年

作者： Zhang, Xiaozhou Chang, Tsung-Hui Liu, Ya-Feng Shen, Chao Zhu, Gang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Science and Engineering Chinese University of Hong Kong Shenzhen China Shenzhen Research Institute of Big Data Shenzhen China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

In a full-duplex (FD) multi-user network, the system performance is not only limited by the self-interference but also by the co-channel interference due to the simultaneous uplink and downlink transmissions. Joint design of the uplink/downlink transmission direction of users and the power allocation is crucial for achieving high system performance in the FD multi-user network. In this paper, we investigate the joint uplink/downlink transmission direction assignment (TDA), user paring (UP) and power allocation problem for maximizing the system max-min fairness (MMF) rate in a FD multi-user orthogonal frequency division multiple access (OFDMA) system. The problem is formulated with a two-time-scale structure where the TDA and the UP variables are for optimizing a long-term MMF rate while the power allocation is for optimizing an instantaneous MMF rate during each channel coherence interval. We show that the studied joint MMF rate maximization problem is NP-hard in general. To obtain high-quality suboptimal solutions, we propose efficient methods based on simple relaxation and greedy rounding techniques. Simulation results are presented to show that the proposed algorithms are effective and achieve higher MMF rates than the existing heuristic methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Optimization

Research on artificial intelligence ethics based on the evolution of population knowledge base

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arXiv 2018年

作者： Liu, Feng Shi, Yong Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China The Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China College of Information Science and Technology University of Nebraska at Omaha OmahaNE68182 United States School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China

The unclear developmentdirection of human society is a deep reason for that it is difficult to form a uniform ethical standard for human society and artificial intelligence. Since the 21st century, the latest advances in the Internet, brain science and artificial intelligence have brought new inspiration to the researchon the developmentdirection of human society. Through the study of the Internet brain model, AI's IQ evaluation, and the evolution of the brain, this paper proposes that the evolution of population knowledge base is the key for judging the development direction of human society,thereby discussing the standards and norms for the construction of artificial intelligence ethics. Copyright © 2018, The Authors. All rights reserved.

关键词： knowledge based systems

Analysis of the relation between artificial intelligence and the internet from the perspective of brain science

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arXiv 2018年

作者： Liu, Feng Shi, Yong Li, Peijia Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China College of Information Science and Technology University of Nebraska at Omaha OmahaNE68182 United States School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China

Artificial intelligence (AI) like deep learning, cloud AI computation has been advancing at a rapid pace since 2014. There is no doubt that the prosperity of AI is inseparable with the development of the Internet. However, there has been little attention to the link between AI and the internet. This paper explores them with brain insights mainly from four views:1) How is the general relation between artificial intelligence and Internet of Things, cloud computing, big data and Industrial Internet from the perspective of brain science. 2) Construction of a new AI system model with the Internet and brain science. Copyright © 2018, The Authors. All rights reserved.

关键词： Deep learning

Enhancing person-Job fit for talent recruitment: An ability-aware neural network approach

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arXiv 2018年

作者： Qin, Chuan Zhu, Hengshu Xu, Tong Zhu, Chen Jiang, Liang Chen, Enhong Xiong, Hui Anhui Province Key Lab of Big Data Analysis and Application University of Science and Technology of China Baidu Talent Intelligence Center Baidu Inc Business Intelligence Lab Baidu Research National Engineering Laboratory of Deep Learning Technology an Application China

The wide spread use of online recruitment services has led to information explosion in the job market. As a result, the recruiters have to seek the intelligent ways for Person-Job Fit, which is the bridge for adapting the right job seekers to the right positions. Existing studies on Person-Job Fit have a focus on measuring the matching degree between the talent qualification and the job requirements mainly based on the manual inspection of human resource experts despite of the subjective, incomplete, and inefficient nature of the human judgement. To this end, in this paper, we propose a novel end-to-end Ability-aware Person-Job Fit Neural Network (APJFNN) model, which has a goal of reducing the dependence on manual labour and can provide better interpretation about the fitting results. The key idea is to exploit the rich information available at abundant historical job application data. Specifically, we propose a word-level semantic representation for both job requirements and job seekers’ experiences based on Recurrent Neural Network (RNN). Along this line, four hierarchical ability-aware attention strategies are designed to measure the different importance of job requirements for semantic representation, as well as measuring the different contribution of each job experience to a specific ability requirement. Finally, extensive experiments on a large-scale real-world data set clearly validate the effectiveness and interpretability of the APJFNN framework compared with several baselines. Copyright © 2018, The Authors. All rights reserved.

关键词： Recurrent neural networks

Visual Feature Combination Approach for Zero-Shot Learning

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Ruan Jian Xue Bao/Journal of Software 2018年 29卷 16-29页

作者： Yang, Gang Liu, Jin-Lu Li, Xi-Rong Xu, Jie-Ping School of Information Renmin University of China Beijing100872 China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Beijing100872 China

Zero-Shot learning is an important research in the field of machine learning and image recognition. Zero-Shot learning methods normally use the semantic information among unseen classes and seen classes to transfer the knowledge which is learned from examples of seen classes to unseen classes, so as to recognize and classify the examples of unseen classes. In this study, a zero-shot learning approach based on construction of visual feature combination is proposed. The approach generates many examples of unseen class on visual feature level by the way of feature combination, which is first proposed, and thus transforms zero-shot learning problem to be a traditional classification problem solved by supervised learning. The approach mimics human cognition process of associative memory, and includes four steps: feature-attribute relation extraction, example construction, example screening, and domain adaption. On training examples of seen classes, the relationship between class attributes and dimensions of feature is extracted;on visual feature level, examples of unseen classes are generated by visual feature combination;dissimilarity representation is introduced to filter the generated examples of unseen classes;semi-supervised and unsupervised feature domain adaption are proposed to linearly transform the generated examples of unseen classes to be more effective. The proposed approach shows superior performance on three benchmark datasets (AwA, AwA2, and SUN), especially on dataset AwA, it obtains 82.6% top-1 accuracy which is the best result as far as we know. Experiment results demonstrate the effectiveness and superiority of the proposed approach. © Copyright 2018, Institute of Software, the Chinese Academy of Sciences. All rights reserved.

关键词： Image classification