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Statistical analysis for validating ACO-KNN algorithm as feature selection in sentiment analysis

AIP Conference Proceedings 2017年第1期1891卷

作者： Siti Rohaidah Ahmad Nurhafizah Moziyana Mohd Yusop Azuraliza Abu Bakar Mohd Ridzwan Yaakub 1Department of Computer Science Faculty of Defence Science & Technology Universiti Pertahanan Nasional Malaysia 57000 Kuala Lumpur Malaysia 2Data Mining and Optimization Research Group Centre for Artificial Intelligence Technology Faculty of Information Science & Technology Universiti Kebangsaan Malaysia 46000 Bangi Selangor Malaysia

This research paper aims to propose a hybrid of ant colony optimization (ACO) and k-nearest neighbor (KNN) algorithms as feature selections for selecting and choosing relevant features from customer review datasets. information gain (IG), genetic algorithm (GA), and rough set attribute reduction (RSAR) were used as baseline algorithms in a performance comparison with the proposed algorithm. This paper will also discuss the significance test, which was used to evaluate the performance differences between the ACO-KNN, IG-GA, and IG-RSAR algorithms. This study evaluated the performance of the ACO-KNN algorithm using precision, recall, and F-score, which were validated using the parametric statistical significance tests. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. The evaluation process has statistically proven that this ACO-KNN algorithm has been significantly improved compared to the baseline algorithms. In addition, the experimental results have proven that the ACO-KNN can be used as a feature selection technique in sentiment analysis to obtain quality, optimal feature subset that can represent the actual data in customer review data.

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Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

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The Lancet 2020年第10258期396卷 1204-1222页

作者： Abbafati, Cristiana Abbas, Kaja M. Abbasi, Mohammad Abbasifard, Mitra Abbasi-Kangevari, Mohsen Abbastabar, Hedayat Abd-Allah, Foad Abdelalim, Ahmed Abdollahi, Mohammad Abdollahpour, Ibrahim Abedi, Aidin Abedi, Parisa Abegaz, Kedir Hussein Abolhassani, Hassan Abosetugn, Akine Eshete Aboyans, Victor Abrams, Elissa M. Abreu, Lucas Guimarães Abrigo, Michael R.M. Abu Haimed, Abdulaziz Khalid Abualhasan, Ahmed Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Abushouk, Abdelrahman I. Acebedo, Alyssa Ackerman, Ilana N. Adabi, Maryam Adair, Tim Adamu, Abdu A. Adebayo, Oladimeji M. Adedeji, Isaac Akinkunmi Adekanmbi, Victor Adelson, Jaimie D. Adeoye, Abiodun Moshood Adetokunboh, Olatunji O. Adham, Davoud Advani, Shailesh M. Afarideh, Mohsen Afshari, Mahdi Afshin, Ashkan Agardh, Emilie E. Agarwal, Gina Agasthi, Pradyumna Agesa, Kareha M. Aghaali, Mohammad Aghamir, Seyed Mohammad Kazem Agrawal, Anurag Ahmad, Tauseef Ahmadi, Alireza Ahmadi, Keivan Ahmadi, Mehdi Ahmadieh, Hamid Ahmadpour, Ehsan Ahmed, Muktar Beshir Aji, Budi Akalu, Temesgen Yihunie Akinyemi, Rufus Olusola Akinyemiju, Tomi Akombi, Blessing Akunna, Chisom Joyqueenet Alahdab, Fares Al-Aly, Ziyad Alam, Khurshid Alam, Noore Alam, Samiah Alam, Tahiya Alanezi, Fahad Mashhour Alanzi, Turki M. Albertson, Samuel B. Alcalde-Rabanal, Jacqueline Elizabeth Alema, Niguse Meles Alemu, Biresaw Wassihun Alemu, Yihun Mulugeta Alhabib, Khalid F. Alhassan, Robert Kaba Ali, Muhammad Ali, Saqib Alicandro, Gianfranco Alijanzadeh, Mehran Alinia, Cyrus Alipour, Vahid Alizade, Hesam Aljunid, Syed Mohamed Alla, François Allebeck, Peter Almadi, Majid Abdulrahman Hamad Almasi, Ali Almasi-Hashiani, Amir Almasri, Nihad A. Al-Mekhlafi, Hesham M. Almulhim, Abdulaziz M. Alonso, Jordi Al-Raddadi, Rajaa M. Altirkawi, Khalid A. Alumran, Arwa Khalid Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Amare, Bekalu Amini, Saeed Amini-Rarani, Mostafa Aminorroaya, Arya Amiri, Fatemeh Amit, Arianna Maever L. Amugsi, Dickson A. Amul, Gianna Gayle Herrera Anbesu, Etsay Woldu Ancuceanu, Robert Anderl Department of Juridical and Economic Studies La Sapienza University Rome Italy Department of Infectious Disease Epidemiology London School of Hygiene and Tropical Medicine London United Kingdom Social Determinants of Health Research Center Tehran Iran Department of Neurology Cairo University Cairo Egypt School of Pharmacy Tehran Iran The Institute of Pharmaceutical Sciences (TIPS) Tehran Iran Neuroscience Research Center Isfahan University of Medical Sciences Isfahan Iran Biostatistics Department Near East University Nicosia Cyprus Biostatistics and Health Informatics Madda Walabu University Bale Robe Ethiopia Research Center for Immunodeficiencies Tehran Iran Karolinska University Hospital Huddinge Sweden Department of Cardiology Dupuytren University Hospital Limoges France University of Limoges Limoges France Department of Pediatric Dentistry Federal University of Minas Gerais Belo Horizonte Brazil Department of Research Philippine Institute for Development Studies Quezon City Philippines Department of Healthcare Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Harvard Medical School Boston MA United States Department of Medicine Ain Shams University Cairo Egypt Hamadan University of Medical Sciences Hamadan Iran School of Medicine Cardiff University Cardiff United Kingdom School of Laboratory Medicine and Science University College Hospital Ibadan Ibadan Nigeria Institute of Cardiovascular Diseases University of Ibadan Ibadan Nigeria Centre of Excellence for Epidemiological Modelling and Analysis Stellenbosch University Cape Town South Africa Department of Global Health Stellenbosch University Cape Town South Africa School of Health Ardabil University of Medical Science Ardabil Iran Social Behavioral Research Branch National Institute of Health Bethesda MD United States Department of Oncology Georgetown University Washington DC DC United States Department of Health Metrics Sciences School of Medicine Seattle WA

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw value

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Promoting Business Analytics and Quantitative Management of technology: Preface for ITQM 2016

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Procedia Computer science 2016年 91卷 1-8页

作者： Lee, Heeseok Shi, Yong Lee, Jongwon Cordova, Felisa Dzitac, Ioan Kou, Gang Li, Jaiping College of Business Korea Advanced Institute Science and Technology Dongdaemum-gu Seoul130-722 Korea Republic of Research Center on Fictitiotus Economy and Data Science Key Lab 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 Business Administration Hoseo University Asan-si Chungcheongnam-do336-795 Korea Republic of Faculty of Engineering and Business University Finis Terrae Pedro de Valdivia 1509. Providencia Santiago Chile Universitatea Agora Agora University Piata Tineretului 8 Oradea410526 Romania School of Business Administration Southwestern University of Finance and Economics Chengdu Sichuan61130 China Institute of Policy and Management Chinese Academy of Sciences Beijing100190 China

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Remote Sensing and Land Suitability Analysis to Establish Local Specific Inputs for Paddy Fields in Subang, West Java

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Procedia Environmental sciences 2016年 33卷 94-107页

作者： Widiatmaka Wiwin Ambarwulan Paulus B.K. Santoso Supiandi Sabiham Machfud Muhammad Hikmat Department of Soil Science and Land Resources Bogor Agricultural University Bogor 16680 Indonesia Geospatial Information Agency Indonesia Center for Data and Information Ministry of Agriculture Indonesia Faculty of Agricultural Technology Bogor Agricultural University Indonesia Soil Research Institute Ministry of Agriculture Indonesia

Indonesia requires a considerable increase in rice production in the future to keep pace with rapid population growth. Increased production can be done through the specific location-based inputs provision. This study aimed to map land resources in Subang Regency, West Java Province, at a scale of 1:25,000, to evaluate land suitability on any land mapping units and to recommend local specific inputs for paddy fields. The methodology used included land mapping unit delineation, delineation of existing paddy fields using SPOT-6 imagery, soil sampling and laboratory analysis, and land suitability evaluation for the paddy fields. The results showed that in Subang Regency, most paddy fields still allow for intensification through the provision of inputs that are location specific. In the case of the Subang Regency, the local specific inputs include provision of organic matter, provision of lime, provision of N, P and K fertilizer, and construction of irrigation infrastructure. Using the Geographic information System, the location where the input is necessary can be given in detail. Moreover, beyond the existing paddy field, there are still areas where actual land use is not paddy field but are identified as having potential for the development of paddy fields. As in the case of existing paddy fields, such areas require local specific inputs according to land characteristics that differ from one place to another and can be spatially delineated.

关键词： temporal automated land evaluation system land characteristic land use and land cover SPOT-6 imagery

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Virtual states in the complex scaling method

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AIP Conference Proceedings 2018年第1期2038卷

作者： Kiyoshi Katō Myagmarjav Odsuren Takayuki Myo Hiroshi Masui Yuma Kikuchi 1Nuclear Data Center Faculty of Science Hokkaido University Sapporo 060-0810 Japan 2School of Engineering and Applied Sciences Nuclear Research Center National University of Mongolia Ulaanbaatar 210646 Mongolia 3General Education Faculty of Engineering Osaka Institute of Technology Osaka 535-8585 Japan 4Research Center for Nuclear Physics (RCNP) Osaka University Ibaraki 567-0047 Japan 5Information Processing Center Kitami Institute of Technology Kitami 090-8507 Japan 6Department of Physics Osaka City University Osaka 558-8585 Japan

A virtual state plays an important role in reaction cross sections just above the breakup threshold energy, such as producing the peak behaviour. However, the virtual state cannot be directly obtained as an isolated pole solution in the complex scaling method (CSM) because of a limit of the scaling angle in the CSM. Recently, we proposed a useful approach to find the pole position of the virtual state using the continuum level density (CLD), the scattering phase shift, and scattering length calculated in the CSM [4]. On the basis of the proposed method, we investigate the photo-disintegration cross sections of resonance and virtual states above the threshold energy to see their differences.

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Extended Measurement of the Cosmic-Ray Electron and Positron Spectrum from 11 GeV to 4.8 TeV with the Calorimetric Electron Telescope on the International Space Station

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Physical Review Letters 2018年第26期120卷 261102-261102页

作者： O. Adriani Y. Akaike K. Asano Y. Asaoka M. G. Bagliesi E. Berti G. Bigongiari W. R. Binns S. Bonechi M. Bongi P. Brogi J. H. Buckley N. Cannady G. Castellini C. Checchia M. L. Cherry G. Collazuol V. Di Felice K. Ebisawa H. Fuke T. G. Guzik T. Hams M. Hareyama N. Hasebe K. Hibino M. Ichimura K. Ioka W. Ishizaki M. H. Israel K. Kasahara J. Kataoka R. Kataoka Y. Katayose C. Kato N. Kawanaka Y. Kawakubo K. Kohri H. S. Krawczynski J. F. Krizmanic T. Lomtadze P. Maestro P. S. Marrocchesi A. M. Messineo J. W. Mitchell S. Miyake A. A. Moiseev K. Mori M. Mori N. Mori H. M. Motz K. Munakata H. Murakami S. Nakahira J. Nishimura G. A. de Nolfo S. Okuno J. F. Ormes S. Ozawa L. Pacini F. Palma P. Papini A. V. Penacchioni B. F. Rauch S. B. Ricciarini K. Sakai T. Sakamoto M. Sasaki Y. Shimizu A. Shiomi R. Sparvoli P. Spillantini F. Stolzi J. E. Suh A. Sulaj I. Takahashi M. Takayanagi M. Takita T. Tamura N. Tateyama T. Terasawa H. Tomida S. Torii Y. Tsunesada Y. Uchihori S. Ueno E. Vannuccini J. P. Wefel K. Yamaoka S. Yanagita A. Yoshida K. Yoshida Department of Physics University of Florence Via Sansone 1—50019 Sesto Fiorentino Italy INFN Sezione di Florence Via Sansone 1—50019 Sesto Fiorentino Italy Department of Physics University of Maryland Baltimore County 1000 Hilltop Circle Baltimore Maryland 21250 USA Astroparticle Physics Laboratory NASA/GSFC Greenbelt Maryland 20771 USA Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa Chiba 277-8582 Japan Research Institute for Science and Engineering Waseda University 3-4-1 Okubo Shinjuku Tokyo 169-8555 Japan JEM Utilization Center Human Spaceflight Technology Directorate Japan Aerospace Exploration Agency 2-1-1 Sengen Tsukuba Ibaraki 305-8505 Japan Department of Physical Sciences Earth and Environment University of Siena via Roma 56 53100 Siena Italy INFN Sezione di Pisa Polo Fibonacci Largo B. Pontecorvo 3—56127 Pisa Italy Department of Physics Washington University One Brookings Drive St. Louis Missouri 63130-4899 USA Department of Physics and Astronomy Louisiana State University 202 Nicholson Hall Baton Rouge Louisiana 70803 USA Institute of Applied Physics (IFAC) National Research Council (CNR) Via Madonna del Piano 10 50019 Sesto Fiorentino Italy Department of Physics and Astronomy University of Padova Via Marzolo 8 35131 Padova Italy INFN Sezione di Padova Via Marzolo 8 35131 Padova Italy University of Rome “Tor Vergata” Via della Ricerca Scientifica 1 00133 Rome Italy INFN Sezione di Rome “Tor Vergata” Via della Ricerca Scientifica 1 00133 Rome Italy Institute of Space and Astronautical Science Japan Aerospace Exploration Agency 3-1-1 Yoshinodai Chuo Sagamihara Kanagawa 252-5210 Japan CRESST and Astroparticle Physics Laboratory NASA/GSFC Greenbelt Maryland 20771 USA St. Marianna University School of Medicine 2-16-1 Sugao Miyamae-ku Kawasaki Kanagawa 216-8511 Japan Kanagawa University 3-27-1 Rokkakubashi Kanagawa Yokohama Kanagawa 221-8686 Japan Faculty of Science and Technol

Extended results on the cosmic-ray electron + positron spectrum from 11 GeV to 4.8 TeV are presented based on observations with the Calorimetric Electron Telescope (CALET) on the International Space Station utilizing the data up to November 2017. The analysis uses the full detector acceptance at high energies, approximately doubling the statistics compared to the previous result. CALET is an all-calorimetric instrument with a total thickness of 30 X0 at normal incidence and fine imaging capability, designed to achieve large proton rejection and excellent energy resolution well into the TeV energy region. The observed energy spectrum in the region below 1 TeV shows good agreement with Alpha Magnetic Spectrometer (AMS-02) data. In the energy region below ∼300 GeV, CALET’s spectral index is found to be consistent with the AMS-02, Fermi Large Area Telescope (Fermi-LAT), and Dark Matter Particle Explorer (DAMPE), while from 300 to 600 GeV the spectrum is significantly softer than the spectra from the latter two experiments. The absolute flux of CALET is consistent with other experiments at around a few tens of GeV. However, it is lower than those of DAMPE and Fermi-LAT with the difference increasing up to several hundred GeV. The observed energy spectrum above ∼1 TeV suggests a flux suppression consistent within the errors with the results of DAMPE, while CALET does not observe any significant evidence for a narrow spectral feature in the energy region around 1.4 TeV. Our measured all-electron flux, including statistical errors and a detailed breakdown of the systematic errors, is tabulated in the Supplemental Material in order to allow more refined spectral analyses based on our data.

关键词： Cosmic ray acceleration Cosmic ray composition & spectra Cosmic ray propagation Cosmic ray sources Cosmic rays & astroparticles Particle dark matter

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Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals (vol 52, pg 1314, 2020)

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NATURE GENETICS 2021年第5期53卷 762-762页

作者： Surendran, Praveen Feofanova, Elena V. Lahrouchi, Najim Ntalla, Ioanna Karthikeyan, Savita Cook, James Chen, Lingyan Mifsud, Borbala Yao, Chen Kraja, Aldi T. Cartwright, James H. Hellwege, Jacklyn N. Giri, Ayush Tragante, Vinicius Thorleifsson, Gudmar Liu, Dajiang J. Prins, Bram P. Stewart, Isobel D. Cabrera, Claudia P. Eales, James M. Akbarov, Artur Auer, Paul L. Bielak, Lawrence F. Bis, Joshua C. Braithwaite, Vickie S. Brody, Jennifer A. Daw, E. Warwick Warren, Helen R. Drenos, Fotios Nielsen, Sune Fallgaard Faul, Jessica D. Fauman, Eric B. Fava, Cristiano Ferreira, Teresa Foley, Christopher N. Franceschini, Nora Gao, He Giannakopoulou, Olga Giulianini, Franco Gudbjartsson, Daniel F. Guo, Xiuqing Harris, Sarah E. Havulinna, Aki S. Helgadottir, Anna Huffman, Jennifer E. Hwang, Shih-Jen Kanoni, Stavroula Kontto, Jukka Larson, Martin G. Li-Gao, Ruifang Lindstrom, Jaana Lotta, Luca A. Lu, Yingchang Luan, Jian'an Mahajan, Anubha Malerba, Giovanni Masca, Nicholas G. D. Mei, Hao Menni, Cristina Mook-Kanamori, Dennis O. Mosen-Ansorena, David Muller-Nurasyid, Martina Pare, Guillaume Paul, Dirk S. Perola, Markus Poveda, Alaitz Rauramaa, Rainer Richard, Melissa Richardson, Tom G. Sepulveda, Nuno Sim, Xueling Smith, Albert V. Smith, Jennifer A. Staley, James R. Stanakova, Alena Sulem, Patrick Theriault, Sebastien Thorsteinsdottir, Unnur Trompet, Stella Varga, Tibor V. Velez Edwards, Digna R. Veronesi, Giovanni Weiss, Stefan Willems, Sara M. Yao, Jie Young, Robin Yu, Bing Zhang, Weihua Zhao, Jing-Hua Zhao, Wei Zhao, Wei Evangelou, Evangelos Aeschbacher, Stefanie Asllanaj, Eralda Blankenberg, Stefan Bonnycastle, Lori L. Bork-Jensen, Jette Brandslund, Ivan Braund, Peter S. Burgess, Stephen Cho, Kelly Christensen, Cramer Connell, John de Mutsert, Renee Dominiczak, Anna F. Dorr, Marcus Eiriksdottir, Gudny Farmaki, Aliki-Eleni Gaziano, J. Michael Grarup, Niels Grove, Megan L. Hallmans, Goran Hansen, Torben Have, Christian T. Heiss, Gerardo Jorgensen, Marit E. Jousilahti, Pekka Kajantie, Eero Kamat, Mihir Karajamaki, AnneMari Kar British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge UK British Heart Foundation Centre of Research Excellence University of Cambridge Cambridge UK Health Data Research UK Cambridge Wellcome Genome Campus and University of Cambridge Cambridge UK Rutherford Fund Fellow Department of Public Health and Primary Care University of Cambridge Cambridge UK MRC Biostatistics Unit University of Cambridge Cambridge UK National Institute for Health Research Cambridge Biomedical Research Centre University of Cambridge and Cambridge University Hospitals Cambridge UK MRC Integrative Epidemiology Unit (IEU) Population Health Sciences Bristol Medical School University of Bristol Bristol UK Robertson Centre for Biostatistics University of Glasgow Glasgow UK MRC Epidemiology Unit University of Cambridge School of Clinical Medicine Cambridge UK Department of Immunology and Inflammation Imperial College London London UK Centre for Non-communicable Disease Research (CNCR) Dhaka Bangladesh National Institute for Health Research (NIHR) Blood and Transplant Research Unit (BTRU) in Donor Health and Genomics at the University of Cambridge Cambridge UK Department of Human Genetics Wellcome Sanger Institute Wellcome Genome Campus Hinxton Cambridge UK Department of Biostatistics and Epidemiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Center for Non-Communicable Diseases Karachi Pakistan Department of Genetics Novo Nordisk Research Centre Oxford Oxford UK Human Genetics Center Department of Epidemiology Human Genetics and Environmental Sciences School of Public Health University of Texas Health Science Center at Houston Houston TX USA Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA Cardiovascular Research Center Center for Genomic Medicine

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Market Basket Analysis Using Apriori and FP-Growth for Analysis Consumer Expenditure Patterns at Berkah Mart in Pekanbaru Riau

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Mustakim Della Maulina Herianda Ahmad Ilham Achmad Daeng GS Folkes E. Laumal Nuning Kurniasih Akbar Iskandar Gloria Manulangga Ida Bagus Ary Indra Iswara Robbi Rahim Puzzle Research Data Technology UIN Sultan Syarif Kasim Riau Indonesia Department of Information System UIN Sultan Syarif Kasim Riau indonesia Informatics Department Universitas Muhammadiyah Semarang Semarang Indonesia Department of Management University of 45 Surabaya Surabaya Indonesia Department of Electrical Engineering Politeknik Negeri Kupang Kupang Indonesia Faculty of Communication Sciences Library and Information Science Program UniversitasPadjadjaran Bandung Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Informatics Department STMIK STIKOM Indonesia Denpasar Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Kubang Gajah Malaysia

Berkah Mart is one of the new minimarkets in Pekanbaru city which began to develop as a retail business to meet the needs of the community. In his operation, Berkah Mart still uses the traditional store management perception that the placement of product layout on sale shelves has not been through sales analysis. Existing products have not been reviewed from the consumer's point of view, whereas the marketing economics concept provides a variety of product and consumer management methods for business management in Berkah Mart, including market bucket analysis techniques and various itemset search algorithms. In this research, Market Basket Basket Analysis with FP-Growth algorithm is proposed to determine the layout and planning of goods availability. The application of FP-Growth algorithm proved to be useful in generating many and informative association rules to find out the consumer spending pattern at Berkah Mart in Pekanbaru. Moreover, from the rules of the customer association can be segmented separately to meet the specific needs of customers with cost-effective by using some special promotions for the general group. The experimental results show that FP-Growth algorithm can analyze quickly and efficiently informing consumer shopping pattern at Berkah Mart and can increase Berkah Mart revenue.

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Efficient mining of class association rules with the itemset constraint

Efficient mining of class association rules with the itemset...

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作者： Nguyen, Dang Nguyen, Loan T.T. Vo, Bay Pedrycz, Witold Division of Data Science Ton Duc Thang University Ho Chi Minh City Viet Nam Division of Knowledge and System Engineering for ICT Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ho Chi Minh City University of Technology Viet Nam College of Electronics and Information Engineering Sejong University Seoul Korea Republic of Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia Systems Research Institute Polish Academy of Sciences Warsaw Poland

Mining class association rules (CARs) with the itemset constraint is concerned with the discovery of rules, which contain a set of specific items in the rule antecedent and a class label in the rule consequent. This task is commonly encountered in mining medical data. For example, when classifying which section of the population is at high risk for the HIV infection, epidemiologists often concentrate on rules which include demographic information such as gender, age, and marital status in the rule antecedent, and HIV-Positive in the rule consequent. There are two naive strategies to solve this problem, namely pre-processing and post-processing. The post-processing methods have to generate and consider a huge number of candidate CARs while the performance of the pre-processing methods depend on the number of records filtered out. Therefore, such approaches are time consuming. This study proposes an efficient method for mining CARs with the itemset constraint based on a lattice structure and the difference between two sets of object identifiers (diffset). Firstly, a lattice structure is built to store all frequent itemsets in the dataset. To reduce memory usage, instead of the entire set of object identifiers, the diffset is used. Secondly, the lattice is traversed to generate only rules which satisfy the itemset constraint. The experimental results show that the proposed algorithm outperforms existing methods in terms of both the mining time and memory usage. © 2016 Elsevier B.V. All rights reserved.

关键词： data mining

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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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