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32nd International Conference on Machine Learning, ICML 2015

作者： Luo, Luo Xie, Yubo Zhang, Zhihua Li, Wu-Jun Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Institute of Data Science Department of Computer Science and Engineering Shanghai Jiao Tong University China National Key Laboratory for Novel Software Technology Collaborative Innovation Center of Novel Software Technology and Industrialization Department of Computer Science and Technology Nanjing University China

ISBN: (纸本)9781510810587

In many classification problems such as electroencephalogram (EEG) classification and image classification, the input features are naturally represented as matrices rather than vectors or s-calars. In general, the structure information of the original feature matrix is useful and informative for data analysis tasks such as classification. One typical structure information is the correlation between columns or rows in the feature matrix. To leverage this kind of structure information, we propose a new classification method that we call support matrix machine (SMM). Specifically, SMM is defined as a hinge loss plus a so-called spectral elastic net penalty which is a spectral extension of the conventional elastic net over a matrix. The spectral elastic net enjoys a property of grouping effect, i.e., strongly correlated columns or rows tend to be selected altogether or not. Since the optimization problem for SMM is convex, this encourages us to devise an alternating direction method of multipliers (ADMM) algorithm for solving the problem. Experimental results on EEG and image classification data show that our model is more robust and efficient than the state-of-the-art methods. Copyright © 2015 by the author(s).

关键词： Classification (of information)

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Predicting valence-arousal ratings of words using a weighted graph method

Predicting valence-arousal ratings of words using a weighted...

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53rd Annual Meeting of the Association for Computational Linguistics and 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015

作者： Yu, Liang-Chih Wang, Jin Robert Lai, K. Zhang, Xue-Jie Department of Information Management Yuan Ze University Taiwan Department of Computer Science and Engineering Yuan Ze University Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taiwan School of Information Science and Engineering Yunnan University Yunnan China

ISBN: (纸本)9781510808461

Compared to the categorical approach that represents affective states as several discrete classes (e.g., positive and negative), the dimensional approach represents affective states as continuous numerical values on multiple dimensions, such as the valence-arousal (VA) space, thus allowing for more fine-grained sentiment analysis. In building dimensional sentiment applications, affective lexicons with valence-arousal ratings are useful resources but are still very rare. Therefore, this study proposes a weighted graph model that considers both the relations of multiple nodes and their similarities as weights to automatically determine the VA ratings of affective words. Experiments on both English and Chinese affective lexicons show that the proposed method yielded a smaller error rate on VA prediction than the linear regression, kernel method, and pagerank algorithm used in previous studies. © 2015 Association for Computational Linguistics.

关键词： Sentiment analysis

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Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: the Global Burden of Diseases Study 2019

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The Lancet HIV 2021年第10期8卷 e633-e651页

作者： Jahagirdar, Deepa Walters, Magdalene K. Novotney, Amanda Brewer, Edmond D. Frank, Tahvi D. Carter, Austin Biehl, Molly H. Abbastabar, Hedayat Abhilash, E.S. Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Adekanmbi, Victor Adeyinka, Daniel Adedayo Adnani, Qorinah Estiningtyas Sakilah Afzal, Saira Aghababaei, Soodabeh Ahinkorah, Bright Opoku Ahmad, Sajjad Ahmadi, Keivan Ahmadi, Sepideh Ahmadpour, Ehsan Ahmed, Muktar Beshir Rashid, Tarik Ahmed Salih, Yusra Ahmed Aklilu, Addis Akram, Tayyaba Akunna, Chisom Joyqueenet Al Hamad, Hanadi Alahdab, Fares Alanezi, Fahad Mashhour Aleksandrova, Ekaterina A. Alene, Kefyalew Addis Ali, Liaqat Alipour, Vahid Almustanyir, Sami Alvis-Guzman, Nelson Ameyaw, Edward Kwabena Amu, Hubert Andrei, Catalina Liliana Andrei, Tudorel Anvari, Davood Arabloo, Jalal Aremu, Olatunde Arulappan, Judie Atnafu, Desta Debalkie Quintanilla, Beatriz Paulina Ayala Ayza, Muluken Altaye Azari, Samad Darshan, B.B. Banach, Maciej Bärnighausen, Till Winfried Barra, Fabio Barrow, Amadou Basu, Sanjay Bazargan-Hejazi, Shahrzad Belay, Habtamu Gebrehana Berheto, Tezera Moshago Bezabhe, Woldesellassie Mequanint Bezabih, Yihienew Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Nikha Bhardwaj, Pankaj Bhattacharyya, Krittika Bibi, Sadia Bijani, Ali Bisignano, Catherine Bolarinwa, Obasanjo Afolabi Boloor, Archith Boltaev, Azizbek A. Briko, Nikolay Ivanovich Buonsenso, Danilo Burkart, Katrin Butt, Zahid A. Cao, Chao Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Choudhari, Sonali Gajanan Chu, Dinh-Toi Couto, Rosa A.S. Cowden, Richard G. Dachew, Berihun Assefa Dadras, Omid Dagnew, Amare Belachew Dahlawi, Saad M.A. Dai, Xiaochen Dandona, Lalit Dandona, Rakhi das Neves, José Degenhardt, Louisa Demeke, Feleke Mekonnen Desta, Abebaw Alemayehu Deuba, Keshab Dhamnetiya, Deepak Dhungana, Govinda Prasad Dianatinasab, Mostafa Diaz, Daniel Djalalinia, Shirin Doan, Linh Phuong Dorostkar, Fariba Edinur, Hisham Atan Effiong, Andem Eftekharzadeh, Sahar El Sayed Zaki, Maysaa Elayedath, Rajesh Elhadi, Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Allergy and Infectious Diseases University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States School of Social Work University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Vagelos College of Physicians and Surgeones Columbia University Medical Center New York NY United States Division of Data Analytics and Delivery for Impact WHO Geneva Switzerland Advanced Diagnostic and Interventional Radiology Research Centre Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Centre Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Paediatric Chronic Kidney Disease Research Centre Tehran University of Medical Sciences Tehran Iran Department of Psychiatry Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Centre Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Centre Tehran University of Medical Sciences Tehran Iran Research Centre for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Centre Tehran University of Medical Sciences Tehran Iran Department of Botany Sree Narayana Guru College Chelannur Kozhikode India Clinical Sciences Department University of Sharjah Sharjah United Arab Emirates Mass Communication Department University of Sharjah Sharjah United Arab Emirates Department of Health-Care Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Department of Population Medicine Ca

Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. Methods: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). Findings: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1–38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78–0·91) per female living with HIV in 2019, 0·99 male infections (0·91–1·10) for every female infection, and 1·02 male deaths (0·95–1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58–35·43, and a 39·66% decrease in deaths, 36·49–42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05–0·06) and the global incidence-to-mortality ratio was

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Building open student model based on assessment framework of iteration programming 23

Building open student model based on assessment framework of...

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23rd International Conference on Computers in Education, ICCE 2015

作者： Chou, Chih-Yueh Wang, Chien-Tse Chen, Zhi-Hong Tseng, Shu-Fen Chao, Po-Yao Department of Computer Engineering and Science Yuan Ze University Taiwan Department of Information Communication Yuan Ze University Taiwan Department of Information Management Yuan Ze University Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taiwan

ISBN: (纸本)9784990801458

Programming involves complex skills and knowledge. Novice students encounter many difficulties and lack information for reflecting and improving their proficiencies in programming skills and knowledge. This paper presents a work-in-progress research to design a system with an open student model based on an assessment framework of iteration programming. The assessment framework includes strategies of counter-controlled loop and sentinel-controlled loop, implementation skills of while, for, and do-while, and program tracing abilities. The system presents open student models to students in order to assist students in reflecting their proficiencies in iteration programming.

关键词： Students

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Learning analytics of core competencies: A comparative study of students, academics, and industries 23

Learning analytics of core competencies: A comparative study...

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23rd International Conference on Computers in Education, ICCE 2015

作者： Chou, Chih-Yueh Tseng, Shu-Fen Chen, Zhi-Hong Chao, Po-Yao Peng, Kung-Chen Lin, Yi-Lung Department of Computer Science and Engineering Yuan Ze University Taiwan Department of Information Management Yuan Ze University Taiwan Department of Information Communication Yuan Ze University Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University Taiwan

ISBN: (纸本)9784990801472

Core competencies are the combination of pooled knowledge and technical capacities that allow a person to be competitive in the marketplace. In this study, we applied a curriculum-level, competency-based visualized analytic system (the VACC) that has been developed by Yuan Ze University to analyze the levels of students' core competencies. The VACC system provides visual diagnostic functions for quickly understanding and positioning levels of students' core competencies. The course-Taken data of 335 students from the Information Management Department at Yuan Ze University were collected and analyzed. In addition, to understand whether students' core competencies have matched marketplace, we surveyed 21 professors from the department and 53 managers from related industries to understand their perceptions of importance of core competencies. The results of competency perceptions from the academia and industries were further compared to students' core competency charts that were generated from the VACC system to measure the gaps among these three stakeholders. The diagnostic results of VACC showed that students have taken more courses on building their competencies of cultivating a broad knowledge and skills in the field of information management. There was a huge gap when students' core competency radar charts were matched to those from academia and industries. While faculties perceived the development of professional skills and the capacity of problem solving was more important than the other competencies, managers from industries suggested whether students can collaborate and team up with others was the crucial competency that market needs. Through learning analytics of students' core competencies and comparison of competency perception among faculties and managers, we can refer these results to diagnose current curriculum and facilitate course design in the future.

关键词： Students

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Erratum: “Influence of heavy metal materials on magnetic properties of Pt/Co/heavy metal tri-layered structures” [Appl. Phys. Lett. 110, 012405 (2017)]

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Applied Physics Letters 2017年第10期110卷

作者： Boyu Zhang Anni Cao Junfeng Qiao Minghong Tang Kaihua Cao Xiaoxuan Zhao Sylvain Eimer Zhizhong Si Na Lei Zhaohao Wang Xiaoyang Lin Zongzhi Zhang Mingzhong Wu Weisheng Zhao 1Fert Beijing Research Institute Beihang University Beijing 100191 China 2Beijing Advanced Innovation Center for Big Data and Brain Computing (BDBC) Beihang University Beijing 100191 China 3School of Electronic and Information Engineering Beihang University Beijing 100191 China 4Key Laboratory of Micro and Nano Photonic Structures (Ministry of Education) Department of Optical Science and Engineering Fudan University Shanghai 200433 China 5Department of Physics Colorado State University Fort Collins Colorado 80523 USA

The following errors appeared in the above article.1

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Sentiment classification of short texts based on semantic clustering

Sentiment classification of short texts based on semantic cl...

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IEEE International Conference on Orange Technologies (ICOT)

作者： Yunchao He Chin-Sheng Yang Liang-Chih Yu K. Robert Lai Weiyi Liu School of Information Science and Engineering Yunnan University Yunnan P.R. China Innovation Center for Big Data and Digital Convergence Yuan Ze University Taiwan

ISBN: (纸本)9781467382380

Due to the popularity and ubiquity of social networks, sentiment analysis has become an important and well-covered research area. Short texts usually encounter sparsity problems in representations for their limited texts length. We address this issue by clustering short texts to form a long text. Specifically, we first use k-means clustering algorithms to form k clusters, where each cluster contains texts having close semantic similarity with the same sentiment polarity. Then, these clusters are used to train classifier. In evaluation, the unlabeled text is merged to the most similar positive and negative clusters respectively, and its sentiment polarity is determined by the change of the two clusters' probabilistic estimates. Experiments on the Twitter dataset show that our approach can achieve a significantly better performance than the bag-of-words method.

关键词： Semantics Sentiment analysis Training data Training Supervised learning Encyclopedias

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Design of an NGS MicroRNA predictor using multilayer hierarchical MapReduce framework

Design of an NGS MicroRNA predictor using multilayer hierarc...

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International Conference on data science and Advanced Analytics (DSAA)

作者： Ren-Hao Pan Lin-Yu Tseng I-En Liao Chien-Lung Chan K. Robert Lai Kai-Biao Lin Innovation Center for Big data and Digital Convergence Yuan Ze University Taoyuan Taiwan Department of Computer Science and Communication Engineering Providence University Taichung Taiwan Department of Computer Science and Engineering National Chung Hsing University Taichung Taiwan Department of Information Management Yuan Ze University Taoyuan Taiwan Department of Computer Science and Engineering Yuan Ze University Taoyuan Taiwan School of Computer & Information Engineering Xiamen University of Technology Xiamen China

ISBN: (纸本)9781467382748

MicroRNAs (miRNAs) are a group of small noncoding RNA (ncRNA) molecules that play an important role in biological functions. This paper proposes a microRNA prediction application, which is based on the multi-layer hierarchical MapReduce framework and provides four prediction workflows for four different datasets: miRNA-like sequences, miRNA cluster sequences, unknown miRNA sequences and the next generation sequencing (NGS) sequences. These workflows include four core procedures for finding the genome location, applying the biological filtering criteria and a genetic algorithm based pre-miRNA classifier. Each procedure works as a MapReduce task and uses JSON format to translate the MapReduce output to the next MapReduce procedure. Experimental results show that the proposed miRNA predictor not only achieves high sensitivity and accuracy, but also has ability to process more than million sequences in acceptable time by relying on the multi-layer hierarchical MapReduce framework.

关键词： RNA Bioinformatics Genetic algorithms Genomics Sequential analysis Proteins

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Precision Medicine:What Challenges Are We Facing?

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Genomics, Proteomics & Bioinformatics 2016年第5期14卷 253-261页

作者： Yu Xue Eric-Wubbo Lameijer Kai Ye Kunlin Zhang Suhua Chang Xiaoyue Wang Jianmin Wu Ge Gao Fangqing Zhao Jian Li Chunsheng Han Shuhua Xu Jingfa Xiao Xuerui Yang Xiaomin Ying Xuegong Zhang Wei-Hua Chen Yun Liu Zhang Zhang Kun Huang Jun Yu MOE Key Lahoratory of Molecular Biophysics College of Life Science and Technology and the Collaborative Innovation Center for Brain ScienceHuazhong University of Science and TechnologyWuhan 430074China School of Electronic and Information Engineering.Xi'an Jiaotong University.Xi'an 710049 China CAS Key Laboratory of Mental Health Institute of PsychologyChinese Academy of SciencesBeijing 100101China State Key Laboratory of'Medical Molecular Biology Institute of Basic Medical SciencesChinese Academy of Medical SciencesPeking Union Medical CollegeBeijing 100005China MOE Beijing Key Laboratory of Carcinogenesis and Translatiooal ResearchCenter for Cancer BioinformaticsPeking University Cancer Hospital&InstituteBeijing 100142China Center for Bioinformatics State Key Laboratory of Protein and Plant Gene ResearchSchool of Life SciencesPeking UniversityBeijing 100871China Beijing Institutes of Life Science.Chinese Academy of Sciences Beijing 100101China MOE Key Lahoratory of Developnlental Genes and Human Disease Institute of Life SciencesSoutheast UniversityNanjing 210096China State Key Laboratory of Stem Cell and Reproductive Biology Institute of Zoology Chinese Academy of SciencesBeijing 100101China Max Planck Independent Research Group on Population Genomics CAS-MPG Partner Institute for Computational Biology(PICB)Shanghai Institutes for Biological SciencesChinese Academy of SciencesShanghai 200031China CAS Ker Laboratory of Genome Sciences and Information Chinese Academy of Sciences.Beijing 100101China MOE Key Laboratory of Bioinformatics School of Life Sciences Center for Synthetic and Systems BiologyTsinghua UniversityBeijing 100084China Computational Omics Lahoratory Center of Computational BiologyBeijing Institute of Basic Medical SciencesBeijing 100850China Bioinformatics Division TNLIST and MOE Key Laboratory for Bioinformatics Department of AutomationTsinghua UniversityBeijing 100084China Department of Bioinformatics and Systems Biology College of LifeScience and Technol

Following the publication of the US National Research Council （N RC） report ＂ Toward PrecMon Medicine.＂ Building a Knowledge Network for Biomedical Research and a New Taxonomy of Diseases＂ in 2011 [1], several n... 详细信息

关键词： PMI Precision Medicine data We

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Cover Picture: Brownmillerite-type Ca2FeCoO5as a Practicable Oxygen Evolution Reaction Catalyst (ChemSusChem 14/2017)

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ChemSusChem 2017年第14期10卷 2840-2840页

作者： Dr. Etsushi Tsuji Dr. Teruki Motohashi Hiroyuki Noda Dr. Damian Kowalski Dr. Yoshitaka Aoki Dr. Hajime Tanida Junji Niikura Dr. Yukinori Koyama Dr. Masahiro Mori Dr. Hajime Arai Dr. Tsutomu Ioroi Dr. Naoko Fujiwara Dr. Yoshiharu Uchimoto Dr. Zempachi Ogumi Dr. Hiroki Habazaki Division of Applied Chemistry Faculty of Engineering Hokkaido University Sapporo 060-8628 Japan Department of Chemistry and Biotechnology Tottori University Tottori 680-8550 Japan Department of Materials and Life Chemistry Kanagawa University Yokohama 221-8686 Japan Graduate School of Chemical Sciences and Engineering Hokkaido University Sapporo 060-8628 Japan Office of Society-Academia Collaboration for Innovation Kyoto University Kyoto 611-0011 Japan Present address: Battery Analysis Laboratory Device Analysis Department NISSAN ARC LTD. Kanagawa 237-0061 Japan Present address: Research and Services Division of Materials Data and Integrated System (MaDIS) Center for Materials Research by Information Integration (CMI2) National Institute for Materials Science (NIMS) Ibaraki 305-0047 Japan Present address: Materials Science Research Group Research Institute of Electrochemical Energy Department of Energy and Environment National Institute of Advanced Industrial Science and Technology (AIST) Osaka 563-8577 Japan Present address: School of Materials and Chemical Technology Tokyo Institute of Technology Yokohama 226-8502 Japan National Institute of Advanced Industrial Science and Technology Osaka 563-8577 Japan Graduate School of Human and Environmental Studies Kyoto University Kyoto 606-8501 Japan

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