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arXiv 2018年

作者： Nayebi, Aran Bear, Daniel Kubilius, Jonas Kar, Kohitij Ganguli, Surya Sussillo, David DiCarlo, James J. Yamins, Daniel L.K. Neurosciences PhD Program Stanford University StanfordCA94305 United States Department of Psychology Stanford University StanfordCA94305 United States Department of Computer Science Stanford University StanfordCA94305 United States Department of Applied Physics Stanford University StanfordCA94305 United States McGovern Institute for Brain Research MIT CambridgeMA02139 United States Department of Brain and Cognitive Sciences MIT CambridgeMA02139 United States Brain and Cognition KU Leuven Leuven Belgium Google Brain Google Inc. Mountain ViewCA94043 United States Wu Tsai Neurosciences Institute StanfordCA94305 United States

Feed-forward convolutional neural networks (CNNs) are currently state-of-the-art for object classification tasks such as ImageNet. Further, they are quantitatively accurate models of temporally-averaged responses of neurons in the primate brain's visual system. However, biological visual systems have two ubiquitous architectural features not shared with typical CNNs: local recurrence within cortical areas, and long-range feedback from downstream areas to upstream areas. Here we explored the role of recurrence in improving classification performance. We found that standard forms of recurrence (vanilla RNNs and LSTMs) do not perform well within deep CNNs on the ImageNet task. In contrast, novel cells that incorporated two structural features, bypassing and gating, were able to boost task accuracy substantially. We extended these design principles in an automated search over thousands of model architectures, which identified novel local recurrent cells and long-range feedback connections useful for object recognition. Moreover, these task-optimized ConvRNNs matched the dynamics of neural activity in the primate visual system better than feedforward networks, suggesting a role for the brain's recurrent connections in performing difficult visual behaviors. Copyright © 2018, The Authors. All rights reserved.

关键词： Neurons

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A Bayesian mixture model for clustering on the stiefel manifold

arXiv

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arXiv 2017年

作者： Sengupta, Subhajit Pal, Subhadip Mitra, Riten Guo, Ying Banerjee, Arunava Ji, Yuan Program for Computational Genomics and Medicine NorthShore University HealthSystem Department of Bioinformatics and Biostatistics University of Louisville Department of Biostatistics and Bioinformatics Emory University Department of Computer and Information Science and Engineering University of Florida Department of Public Health Sciences University of Chicago

Analysis of a Bayesian mixture model for the Matrix Langevin distribution on the Stiefel manifold is presented. The model exploits a particular parametrization of the Matrix Langevin distribution, various aspects of which are elaborated on. A general, and novel, family of conjugate priors, and an efficient Markov chain Monte Carlo (MCMC) sampling scheme for the corresponding posteriors is then developed for the mixture model. Theoretical properties of the prior and posterior distributions, including posterior consistency, are explored in detail. Extensive simulation experiments are presented to validate the efficacy of the framework. Real-world examples, including a large scale neuroimaging dataset, are analyzed to demonstrate the computational tractability of the approach. Copyright © 2017, The Authors. All rights reserved.

关键词： Mixtures

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Wildlife-microbiome interactions and disease: exploring opportunities for disease mitigation across ecological scales

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Drug Discovery Today: Disease Models 2018年 28卷 105-115页

作者： Williams, Candace L. Caraballo-Rodríguez, Andrés Mauricio Allaband, Celeste Zarrinpar, Amir Knight, Rob Gauglitz, Julia M. Institute for Conservation Research San Diego Zoo Global United States Collaborative Mass Spectrometry Innovation Center Skaggs School of Pharmacy and Pharmaceutical Sciences University of California La Jolla San Diego 92307 CA United States Biomedical Sciences Graduate Program University of California La Jolla San Diego 92307 CA United States Department of Medicine University of California La Jolla San Diego 92307 CA United States Veterans Affairs San Diego Healthcare System San Diego California University of California La Jolla San Diego 92307 CA United States Department of Pediatrics University of California La Jolla San Diego 92037 CA United States Department of Bioengineering University of California La Jolla San Diego 92093 CA United States Department of Computer Science and Engineering University of California La Jolla San Diego 92093 CA United States Center for Microbiome Innovation University of California La Jolla San Diego 92307 CA United States

Captive wildlife are a unique set of animals, whose diverse host–microbe symbioses are underexplored. Compared to their wild counterparts they are particularly susceptible to a variety of diseases, many of which have explicit or purported links to the microbiome. In this perspective, we will examine how the microbiome influences gastrointestinal disorders, metabolic dysregulation, reproduction, and disease susceptibility in captive wildlife. Investigation of wildlife, and specifically captive wildlife, affords a unique opportunity to gain understanding of the broad diversity of the associated microbiota and learn from nature's molecular and microbial responses to disease. Studies like these could lead to the discovery of new interventions, ranging from dietary changes to the use of microbes or their natural products as treatment. Intervention strategies can lead to the discovery of medically relevant small molecules and the development of a novel platform for N-of-1 targeted medical investigations. © 2019 Elsevier Ltd

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Detecting "Smart" Spammers on Social Network: A Topic Model Approach

Detecting "Smart" Spammers on Social Network: A Topic Model ...

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2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016 - Student Research Workshop, SRW 2016

作者： Liu, Linqing Lu, Yao Luo, Ye Zhang, Renxian Itti, Laurent Lu, Jianwei iLab Tongji School of Software Engineering Tongji University China Dept. of Computer Science and Technology Tongji University China Dept. of Computer Science and Neuroscience Program University of Southern California United States Institute of Translational Medicine Tongji University China

ISBN: (纸本)9781941643815

Spammer detection on social network is a challenging problem. The rigid anti-spam rules have resulted in emergence of "smart" spammers. They resemble legitimate users who are difficult to identify. In this paper, we present a novel spammer classification approach based on Latent Dirichlet Allocation (LDA), a topic model. Our approach extracts both the local and the global information of topic distribution patterns, which capture the essence of spamming. Tested on one benchmark dataset and one self-collected dataset, our proposed method outperforms other state-of-the-art methods in terms of averaged F1-score. © 2016 Association for Computational Linguistics.

关键词： Statistics

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Risk factors for the development of knee osteoarthritis across the lifespan: A systematic review and meta-analysis

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Osteoarthritis and Cartilage 2025年

作者： Duong, Vicky Abdel Shaheed, Christina Ferreira, Manuela L. Narayan, Sujita W. Venkatesha, Venkatesha Hunter, David J. Zhu, Jimmy Atukorala, Inoshi Kobayashi, Sarah Goh, Siew Li Briggs, Andrew M. Cross, Marita Espinosa-Morales, Rolando Fu, Kai Guillemin, Francis Keefe, Francis Stefan Lohmander, L. March, Lyn Milne, George J. Mei, Yifang Mobasheri, Ali Namane, Mosedi Peat, George Risberg, May Arna Sharma, Saurab Sit, Regina Telles, Rosa Weiss Zhang, Yuqing Cooper, Cyrus Sydney Musculoskeletal Health Kolling Institute Faculty of Medicine and Health University of Sydney Level 10 St Leonards Sydney 2065 NSW Australia Faculty of Medicine and Health School of Public Health University of Sydney Level 10N King George V Building Royal Prince Alfred Hospital Sydney 2050 NSW Australia The George Institute for Global Health Faculty of Medicine and Health The University of New South Wales Level 18 International Towers 3 300 Barangaroo Ave Barangaroo Sydney 2000 NSW Australia Northern Sydney Local Health District Executive Royal North Shore Hospital The Kolling Institute Level 10 St Leonards Sydney 2065 NSW Australia Department of Rheumatology Royal North Shore Hospital Clinical Administration 7C St Leonards Sydney 2065 NSW Australia Liverpool Hospital Sydney NSW Australia Department of Clinical Medicine University of Colombo Colombo Sri Lanka Centre for Epidemiology and Evidence-Based Practice Universiti Malaya Kuala Lumpur Malaysia Sports and Exercise Medicine Research and Education Group Faculty of Medicine Universiti Malaya Kuala Lumpur Malaysia Curtin School of Allied Health Curtin University Perth 6845 WA Australia National Institute of Rehabilitation National University Autonomous of Mexico Mexico City Mexico Department of Orthopedic Surgery Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine No. 600 Yishan Road Xuhui District Shanghai 200233 China Université de Lorraine Inserm INSPIIRE Nancy 54500 France Duke Pain Prevention and Treatment Research Program Department of Psychiatry and Behavioral Sciences Duke University School of Medicine Durham NC United States Department of Clinical Sciences Lund Orthopedics Lund University PO Box 117 Lund 22100 Sweden Marshall Centre for Infectious Disease Research and Department of Computer Science and Software Engineering University of Western Australia 35 Stirling Highway Crawley 6009 WA Australia Department of

Objective: To identify and quantify risk factors for incident knee osteoarthritis (KOA) across the lifespan. Methods: This systematic review and meta-analysis identified eligible studies from seven electronic databases and three registries. Longitudinal cohort studies or randomised controlled trials evaluating participants who developed incident symptomatic and/or radiographic KOA were included. Two independent reviewers completed data screening and extraction. Estimates were pooled using a random effects model and reported as odds ratio (OR), hazard ratio, or risk ratio and corresponding 95% confidence intervals (95% CI). Grading of Recommendations, Assessment, Development and Evaluation was used to determine the certainty of evidence. Population attributable fractions were calculated, including risk factors significantly associated with radiographic KOA based on the pooled meta-analysis and where we could determine communality scores using existing clinical datasets. Results: We identified 131 studies evaluating > 150 risk factors. Previous knee injury, older age and high bone mineral density were associated with an increased risk of incident radiographic KOA based on the pooled analysis [OR (95% CI): 2.67 (1.41, 5.05), 1.15 (1.00, 1.33) and 1.82 (1.12, 2.94), respectively], with moderate-to-high certainty. Two risk factors (overweight/obesity and previous knee injury) accounted for 14% of incident radiographic KOA. Other modifiable risk factors, including occupational physical activity, also contribute to radiographic or symptomatic KOA. Conclusion: Novel strategies addressing known modifiable risk factors including overweight/obesity, knee injuries and occupational physical activity are needed to reduce overall burden of KOA. Systematic review registration: PROSPERO ID: CRD42023391187 © 2025 The Authors

关键词： Cohort studies Knee osteoarthritis Risk factors

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Raman study of lattice vibrations in type II superlattice InAs/InAs1-xSbx

arXiv

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arXiv 2017年

作者： Liu, Henan Zhang, Yong Steenbergen, Elizabeth H. Liu, Shi Lin, Zhiyuan Zhang, Yong-Hang Kim, Jeomoh Ji, Mi-Hee Detchprohm, Theeradetch Dupuis, Russell D. Kim, Jin K. Hawkins, Samuel D. Klem, John F. Optical Science and Engineering Graduate Program Department of Electrical and Computer Engineering University of North Carolina at Charlotte Charlotte NC United States Center for Photonics Innovation and School of Electrical Computer and EnergyEngineering Arizona State University Tempe AZ United States Center for Compound Semiconductors and School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA United States Sandia National Laboratories Albuquerque NM United States

InAs/InAs1-xSbx superlattice system differ distinctly from two well-studied superlattice systems GaAs/AlAs and InAs/GaSb, in terms of electronic band alignment, common-element at the interface, and phonon spectrum overlapping of the constituents. This fact leads to unique electronic and vibrational properties of the InAs/InAs1-xSbx system when compared to the other two systems. In this work, we report a polarized Raman study on the vibrational properties of the InAs/InAs1-xSbx SLs as well as selected InAs1-xSbx alloys, all grown on GaSb substrates by either MBE or MOCVD, from both growth surface and cleaved edge. In the SL, from the (001) backscattering geometry, an InAs-like LO mode is observed as the primary feature and its intensity is found to increase with increasing Sb composition;from the (110) cleaved edge backscattering geometry, an InAs-like TO mode is observed as the main feature in two cross-polarization configurations, but an additional InAs-like "forbidden" LO mode was observed in two parallel-polarization configurations. InAs1-xSbx alloys lattice-matched to the substrate (xSb ~ 0.09) grown by MBE were also found to exhibit the "forbidden" LO mode, implying the existence of some unexpected [001] modulation, but the strained xSb ~ 0.35 samples grown by MOCVD were found to behavior like a disordered alloy. The primary conclusions are (1) the InAs-like LO or TO mode could be either a confined or quasi-confined mode in the InAs layers of the SL or extended mode of the whole structure, depending on the Sb composition;(2) InAs/InAsSb and InAs/GaSb SLs exhibit significantly different behaviors in the cleaved edge geometry, but qualitatively similar in the (001) geometry;and (3) the appearance of the "forbidden" LO-like mode is a universal signature for SLs and bulk systems resulting from mixing of phonon modes due to structural modulation or symmetry reduction. Copyright © 2017, The Authors. All rights reserved.

关键词： III-V semiconductors

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Applying the MVC EA-IRPM to reporting-guidelines in medicine: A strategy that is a web system

Applying the MVC EA-IRPM to reporting-guidelines in medicine...

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IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

作者： Patrick Letouze J. I. M. de Souza Valéria Martins Silva Glaubos Climaco F. B. Chagas Joao Y. Ishihara Faculty of Computer Science Universidade Federal do Tocantins Palmas Brazil Universidade Federal do Tocantins Palmas TO BR Graduate Program of Systems' Engineering and Computation Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil Department of Informatics Universidade Federal do Maranh/ ao - UFMA Faculty of Computer Science Faculdade Pitagoras Imperatriz Imperatriz Brazil Faculty of Electrical Engineering Universidade de Brasília Brasília Brazil

ISBN: (纸本)9781509041800

Reporting-Guidelines in Medicine play an important role in promoting the quality of reports in health-related research. For instance, a poorly reported research may induce misinterpretation and inappropriate clinical settings. Basically, three major issues regarding Reporting-Guidelines in Medicine has to be addressed: (1) the existence of lots of reporting guidelines covering a broad spectrum of medical research increases the difficulties when reporting a medical research because it may not be clear which guidelines are applicable, or if all related guidelines are considered; (2) most guideline developers have not described how their guidance was developed, consequently tracking guidelines and features for evaluation, or even for correcting, may be not possible; (3) few guideline developers have evaluated the effectiveness of their guidance, then the real value that the guideline brings to reporting the research is not assured. Hence, we propose a solution to these three issues based on the Model-View-Controller Evolutionary Acquisition Interdisciplinary Research Project Management (MVC EA-IRPM) that is simultaneously a strategy and a web system for the development and management of reporting guidelines.

关键词： Guidelines Project management Planning Adaptation models Phase measurement Systems architecture Systematics

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BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series

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Global Ecology and Biogeography 2025年第5期34卷

作者： Maria Dornelas Laura H. Antão Amanda E. Bates Viviana Brambilla Jonathan M. Chase Cher F. Y. Chow Ada Fontrodona-Eslava Anne E. Magurran Inês S. Martins Faye Moyes Alban Sagouis Samuel Adu-Acheampong Daniel Acquah-Lamptey Dušan Adam Penelope A. Ajani Aitor Albaina Pablo Almaraz Jeongseop An Roger Sigismund Anderson Madelaine Jean Robertson Anderson Alexsander Z. Antunes Ivan Arismendi Linda Armbrecht Pedro Aros-Mardones Sreejith Kalpuzha Ashtamoorthy Narayanan Ayyappan Gal Badihi Joseph J. Bailey Andrew H. Baird Mark Edward Baird Sreekumar Vadakkethil Balakrishnan José António L. Barão-Nóbrega Adi Barash Miguel Barbosa Jos Barlow Claus Bässler Matthieu Beaumont Natalie Beenaerts Tiago Octavio Begot Wallace Beiroz Ricardo Beldade David M. Bell Alecia Bellgrove Jonathan Belmaker Lisandro Benedetti-Cecchi Cassandra E. Benkwitt Pamela Medina-van Berkum Brandon T. Bestelmeyer Matthew G. Betts Maxwell Kelvin Billah Anne D. Bjorkman Magdalena Błażewicz Christopher P. Bloch Shane A. Blowes Antonio Bode Juliano A. Bogoni Thomas Bolger Timothy C. Bonebrake Erik Bonsdorff Roberta Bottarin Luke N. Brokensha Rob W. Brooker Andrew J. Brooks Helge Bruelheide Thiago Almeida Bueno Claire Laguionie Mariana Lopes Campagnoli James Cant Erica Pellegrini Caramaschi Alexandre Caron Tadhg Carroll Tancredi Caruso Juan Carvajal-Quintero Giuseppe Castaldelli Edward Castañeda-Moya Pedro V. Castilho Sonia Zanini Cechin Shahar Chaikin Uchangi Manjunatha Chandrashekara Tory J. Chase Chaolun Allen Chen Jorge José Cherem Sei-Woong Choi Erica M. Christensen Alexander V. Christianini Jackson Wing Four Chu Peter Coad Carl Van Colen Lise Comte Elisabeth J. Cooper J. Hans C. Cornelissen Eddy Cosson Unai Cotano Luc Crevecoeur Shannan Kyle Crow Graeme S. Cumming Vanessa S. Daga Gabriella Damasceno Gergana N. Daskalova Claire H. Davies Robert A. Davis Frank P. Day Sussy De-La-Zerda Amy Elizabeth Deacon Indradatta de Castro-Arrazola Steven Degraer Kharran Deonarinesingh Juan C. Diaz-Ricaurte Christopher R. Dickman Tara Dirilgen Ciaran John Dolan J. Emmet Centre for Biological Diversity School of Biology University of St Andrews Fife UK MARE—Centro de Ciências do Mar e do Ambiente Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Research Centre for Ecological Change Organismal and Evolutionary Biology Research Programme Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland Department of Biology University of Victoria Victoria British Columbia Canada German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig Leipzig Germany Department of Computer Science Martin Luther University Halle-Wittenberg Halle (Saale) Germany Leverhulme Centre for Anthropocene Biodiversity Department of Biology University of York York UK Department of Animal Biology and Conservation Science University of Ghana Accra Ghana Philipps Universität Marburg Marburg Germany Department of Forest Ecology Silva Tarouca Research Institute Brno Czech Republic School of Life Sciences University of Technology Sydney Sydney New South Wales Australia Zoology and Animal Cell Biology Department University of the Basque Country (UPV/EHU) Leioa Spain Grupo de Oceanografía de Ecosistemas Instituto de Ciencias Marinas de Andalucía CSIC Campus Universitario de Puerto Real Puerto Real Spain National Institute of Ecology Seocheon Republic of Korea African Regional Postgraduate Programme in Insect Science University of Ghana Accra Ghana Département de Biologie Université de Sherbrooke Sherbrooke Quebec Canada Núcleo de Conservação da Biodiversidade Instituto de Pesquisas Ambientais Secretaria de Meio Ambiente Infraestrutura e Logística do Estado de São Paulo São Paulo Brazil Department of Fisheries Wildlife and Conservation Sciences Oregon State University Corvallis Oregon USA Institute for Marine and Antarctic Studies Ecology & Biodiversity Centre University of Tasmania Hobart Tasmania Australia Graduate Program in Oceanography Department of Oceanography Faculty of Natural Scienc

Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

关键词： assemblage biodiversity community database ecoinformatics species taxa time

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Hybrid cryptosystem RSA – CRT optimization and VMPC

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Journal of Physics: Conference Series 2018年第1期978卷

作者： R Rahmadani H Mawengkang Sutarman Master Program (S2) of Informatics Engineering Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia. Department of Mathematics Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara Medan Indonesia.

Hybrid cryptosystem combines symmetric algorithms and asymmetric algorithms. This combination utilizes speeds on encryption/decryption processes of symmetric algorithms and asymmetric algorithms to secure symmetric keys. In this paper we propose hybrid cryptosystem that combine symmetric algorithms VMPC and asymmetric algorithms RSA – CRT optimization. RSA – CRT optimization speeds up the decryption process by obtaining plaintext with dp and p key only, so there is no need to perform CRT processes. The VMPC algorithm is more efficient in software implementation and reduces known weaknesses in RC4 key generation. The results show hybrid cryptosystem RSA – CRT optimization and VMPC is faster than hybrid cryptosystem RSA – VMPC and hybrid cryptosystem RSA – CRT – VMPC. Keyword : Cryptography, RSA, RSA – CRT, VMPC, Hybrid Cryptosystem.

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Analysis of user readiness toward ICT usage at small medium enterprise in south tangerang

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Journal of Physics: Conference Series 2018年第1期1007卷 012042-012042页

作者： Napitupulu, D Syafrullah, M Rahim, R Abdullah, D Setiawan, MI Research Center for Quality System & Testing Technology Indonesian Institute of Sciences Tangerang Selatan Banten Indonesia Program of Master of Computer Science Universitas Budi Luhur Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Malaysia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia

Utilization of Information and Communication Technology (ICT) is still relatively low in the level of SMEs due to various limitations ranging from access to capital, till the marketing network. ICT is present to provide the ability for SMEs in improving the benefits and competitive advantage of the organization. This study aims to determine the level of readiness of SMEs in utilizing technology, especially ICT. The methodology used is a survey to see the technology readiness of 107 SMEs in South Tangerang selected by purposive sampling. The approach used is TRI (Technology Readiness Index) which is the individual perception of technology based on four criteria that is optimism, innovativeness, discomfort and insecurity. The results showed that the optimism and innovativeness variables significantly positively influence the technology readiness while the variables of discomfort and insecurity also significantly positively influence the readiness of ICT.

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