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1st International Conference on information and Communications technology, ICOIACT 2018

作者： Condrobimo, A. Raharto Abbas, Bahtiar Saleh Trisetyarso, Agung Suparta, Wayan Kang, Chul-Ho Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information System Department School of Information System Bina Nusantara University Jakarta11480 Indonesia Civil Engineering Department University of Technology Yogyakarta Yogyakarta Indonesia Department of Electronic and Communication Engineering Kwangwoon University Korea Republic of

ISBN: (纸本)9781538609545

This study aims to apply data mining techniques with cluster analysis on stock data registered in LQ45 in Indonesia Stock Exchange. The cluster analysis used in this method is k-means algorithm, the data in this research is taken from Indonesia Stock Exchange. The cluster analysis in this study analyzed the characteristics of data volumes and stock values, while the results in this study were presented in the form of cluster members visually. Therefore, this cluster analysis in this research can be used for quick and efficient identifier for each member of LQ45 index cluster based on share value for each cluster and its volume. The identification results can be used by beginner-level investors that begun to be interested in stock investments to help make informed decisions about stock trading on desired cluster groups. © 2018 IEEE.

关键词： Cluster analysis

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Correction to: 4-Chloro-3-nitro-N-butylbenzenesulfonamide acts on KV3.1 channels by an open-channel blocker mechanism

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Amino acids 2018年第1期50卷 199-200页

作者： Carlos Alberto Zanutto Bassetto Junior Wamberto Antonio Varanda Eduardo René Pérez González Fine Organic Chemistry Laboratory Department of Chemistry and Biochemistry Faculty of Science and Technology São Paulo State University (Unesp)-Campus of Presidente Prudente Presidente Prudente SP Brazil. cbjunior@fc.unesp.br. Post-Graduate Program in Science and Material Technology Presidente Prudente SP Brazil. cbjunior@fc.unesp.br. Department of Physiology Ribeirão Preto Medical School University of São Paulo Ribeirão Preto Brazil. Fine Organic Chemistry Laboratory Department of Chemistry and Biochemistry Faculty of Science and Technology São Paulo State University (Unesp)-Campus of Presidente Prudente Presidente Prudente SP Brazil. Post-Graduate Program in Science and Material Technology Presidente Prudente SP Brazil.

Unfortunately, grey trace on Figure 2c was missing in the original publication of the article.

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Atrial fibrillation detection using RR-interval irregularity supported by particle swarm optimization

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Journal of Physics: Conference Series 2019年第1期1153卷

作者： M Eliana Nuryani Nuryani Anto Satriyo Nugroho Department of Physics Graduate Program Universitas Sebelas Maret Jl. Ir. Sutami 36A Kentingan Jebres Surakarta 57126 INDONESIA Center for Information & Communication Technology Agency for Assessment and Application of Technology INDONESIA

Atrial Fibrillation (AF) is the most common arrhythmia. AF has increased peoples health and financial burdens. Patients with AF should be stratified according to a predictive stroke-risk score. According to the complication, risk factor and data of epidemiology, AF is always interesting to be multidisciplinary research topic, one of which is the developing algorithms for auto-detect software. In this study we use analogue recorded of electrocardiography (ECG) data who converted to digital data. Before detecting the presences of AF, we detect R-Peaks of that ECG wave using differential operating method (DOM). Then we analyse the presence of AF by determining irregularities of RR-interval. To detect the occurrence of AF we use two methods, finding anomalies beat around the mean (FAM) and comparison of each other's beat (CEO). Both of methods are optimized using Particle Swarm Optimization (PSO).The principle of FAM is to look for intervals that have a big margin compared to mean of intervals in a segment. While CEO's principle is to compared all of intervals in the segment each other, then it find the big different to declare the presence of AF. The role of PSO is to optimize their performance by initializing and evaluating their parameters to create the threshold between normal and AF. We have used this method to test the patient's data from MIT-BIH. The performance of FAM is presented in accuracy, sensitivity, and specificity of 90.46%, 95.81, and 84.84% respectively. The performance of CEO is presented in accuracy, sensitivity, and specificity of 85.30%, 94.46%, and 77.19% respectively.

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Identification of atrial fibrillation using descriptive statistic features and adaptive Neuro-Fuzzy inference system

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Journal of Physics: Conference Series 2019年第1期1153卷

作者： Mar'atus Solikhah Nuryani Nuryani Anto Satriyo Nugroho Physics Department of Graduate Program Sebelas Maret University Jl. Ir. Sutami 36A Kentingan Jebres Surakarta 57126 INDONESIA Center for Information & Communication Technology Agency for Assessment and Application of Technology INDONESIA

Atrial fibrillation (AF) is one of the most common arrhythmia which can cause a serious problem. Nevertheless, well treated AF might not lead to any further complication. Early detection of AF could be an important preventative step that have to be conducted. In this article, we aim to make an automatic detection of atrial fibrillation. Seven descriptive statistic features have been utilized to detect AF. The features obtained could differ between two condition: normal and AF. Later, we use Adaptive Neuro-Fuzzy Inference System (ANFIS) as a classification method. Sugeno-type fuzzy inference system along with Gaussian type of fuzzy are utilized to classify the condition. The proposed method is applied on MIT-BIH Atrial Fibrillation database. The performance obtained from this proposed method might be considered for a medical application.

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Changes in Antioxidant Enzyme Activities and Elemental Profiling of Abutilon indicum L. Subjected to Copper Stress

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Proceedings of the National Academy of Sciences India Section B - Biological Sciences 2017年第4期87卷 1469-1478页

作者： Rout, Jyoti R. Sahoo, Santi L. Das, Ritarani Ram, Shidharth S. Chakraborty, Anindita Sudarshan, Mathummal Biochemistry and Molecular Biology Laboratory Post Graduate Department of Botany Utkal University Vani Vihar Bhubaneswar 751004 Odisha India UGC-DAE Consortium of Scientific Research Kolkata Centre Bidhan Nagar Salt Lake Kolkata 700098 India Post Graduate Department of Biotechnology Academy of Management and Information Technology 67/68 IID Centre Bidya Vihar Barunei Hills Khurda 752057 Odisha India

The effects of Cu stress on the alterations in the activities of antioxidant enzymes from both leaf and root samples of Abutilon indicum L. were studied under controlled climatic conditions. Plants were treated with different concentrations of Cu (0, 25, 50, 100 and 200 mg/kg of soil) for 15 days. In most plants supplemented with 50 and 100 mg of Cu, a rapid increase in antioxidant activities such as catalase (CAT), guaiacol peroxidase (GPX) and superoxide dismutase (SOD) were detected but at higher concentration (200 mg/kg of soil), the activities were declined. Isoforms of CAT, GPX and SOD were separated using native-polyacrylamide gel electrophoresis and their activities were analyzed. Major reshuffling in isoenzyme pattern of CAT, GPX and SOD were detected in response to Cu treatment. Elemental contents were analyzed by energy dispersive X-ray fluorescence spectrometer from both leaf and root samples of control and treated plants. The increasing concentrations of Cu have a great impact on the alternation in concentration of other elements namely Mg, P, S, K, Ca, Mn, Fe and Zn. The trace elements which act as cofactors for antioxidant enzymes like Mn, Fe and Zn significantly decreased depending on Cu concentration. © 2016, The National Academy of Sciences, India.

关键词： Catalase Copper stress Energy dispersive X-ray fluorescence (EDXRF) Guaiacol peroxidase Isoenzyme Superoxide dismutase

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Using a Recurrent Neural Network Model for Classification of Tweets Conveyed Influenza-related information 1

Using a Recurrent Neural Network Model for Classification of...

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1st International Workshop on Digital Disease Detection using Social Media, DDDSM 2017, co-located with the 8th International Joint Conference on Natural Language Processing, IJCNLP 2017

作者： Wang, Chen-Kai Singh, Onkar Tang, Zhao-Li Dai, Hong-Jie Graduate Institute of Biomedical Informatics Taipei Medical University Taipei Taiwan Bioinformatics Program Taiwan International Graduate Program Institute of Information Science Academia Sinica Taipei Taiwan Institute of Biomedical Informatics National Yang-Ming University Taipei Taiwan Department of Computer Science and Information Engineering National Taitung University Taitung Taiwan Interdisciplinary Program of Green and Information Technology National Taitung University Taitung Taiwan

ISBN: (纸本)9781948087070

Traditional disease surveillance systems depend on outpatient reporting and virological test results released by hospitals. These data have valid and accurate information about emerging outbreaks but it's often not timely. In recent years the exponential growth of users getting connected to social media provides immense knowledge about epidemics by sharing related information. Social media can now flag more immediate concerns related to outbreaks in real time. In this paper we apply the long short-term memory recurrent neural network (RNN) architecture to classify tweets conveyed influenza-related information and compare its performance with baseline algorithms including support vector machine (SVM), decision tree, naive Bayes, simple logistics, and naive Bayes multinomial. The developed RNN model achieved an F-score of 0.845 on the MedWeb task test set, which outperforms the F-score of SVM without applying the synthetic minority oversampling technique by 0.08. The F-score of the RNN model is within 1% of the highest score achieved by SVM with oversampling technique. © 2017 AFNLP

关键词： Support vector machines

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Classifying Attitudes of Thai Business Organizations Toward the Perceived Benefit of Customer Predictive Analytics

Classifying Attitudes of Thai Business Organizations Toward ...

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International Symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Santisook Limpeeticharoenchot Nagul Cooharojananone Thira Chavarnakul Kanokwan Atchariyachanvanich Technopreneurship and Innovation Management Program Graduate School Chulalongkorn University Bangkok Thailand Department of Mathematics and Computer Science Faculty of Science Chulalongkorn University Bangkok Thailand Department of Commerce Chulalongkorn University Bangkok Thailand Faculty of Information Technology King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

ISBN: (纸本)9781538626344;9781538626337

In this paper, we applied K-means++, Agglomerative and Decision Tree techniques to classify characteristics of Thai business organizations toward the perceived benefit of predictive analytics. We believe that different characteristics of business organizations require different solution approaches to overcome challenges and gain business value. In the exploratory survey, we collected 84 respondents, who are data analysts, business analysts, business owners, management, and IT managers. The respondents' size of organization varies from small firms to large firms. The result from three techniques of classification shows that Thai business organizations perceiving the benefit of predictive analytics could be divided into two groups. We further confirmed that with the analysis of variance technique to identify the difference of means in each parameter. We also found that the most important descriptive profile is led by customer-related factors such as a change in the percentage of customers, the number of direct customers, and number of sales and marketing staff. These are followed by technology factors, which are the number of external and internal data sources and number of analytics and technologies currently used for data analytics.

关键词： Organizations Data analysis Clustering algorithms Big Data Organizational aspects Decision trees

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A first-principles study on the quantum tunneling of methylhydroxycarbene isomerization in various solvents

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Journal of Physics: Conference Series 2020年第1期1568卷

作者： E D Susanti F Rusydi I Puspitasari R N Fadilla N D Aisyah A Ahmad Research Center for Quantum Engineering Design Faculty of Science and Technology Universitas Airlangga Jl. Mulyorejo Surabaya 60115 Indonesia Department of Physics Faculty of Science and Technology Universitas Airlangga Jl. Mulyorejo Surabaya 60115 Indonesia Visiting Researcher at Precision Sciences & Technology and Applied Physics Graduate School of Engineering Osaka University Suita 565-0871 Japan Information System Study Program Faculty of Science and Technology Universitas Airlangga Jl. Mulyorejo Surabaya 60115 Indonesia School of Chemical Science and Food Technology Faculty of Science and Technology Universiti Kebangsaan Malaysia Bangi Selangor 43600 Malaysia

Quantum tunneling phenomenon allows a high-barrier reaction to occur even though thermal energy is not sufficient to surmount the barrier. The phenomenon has been suggested to exist in the isomerization of methylhydroxycarbene which occured at 11 K. Here we study the quantum tunneling that occured in the isomerization of methylhydroxycarbene to acetaldehyde and to vinyl alcohol based on density functional calculations. The isomerization pathways are determined under the effect of various solvents which are modeled by polarizable continuum model (PCM). We use Wentzel-Kramers-Brillouin (WKB) approximation to calculate the tunneling probability (T) and extend the usefulness of T into isomerization rate. The results show that the solvents give a significant effect on the isomerization rate of methylhydroxycarbene to acetaldehyde but an insignificant one on the isomerization rate to vinyl alcohol.

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information retrieval system in text-based skripsi document search file using vector space model method

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Journal of Physics: Conference Series 2019年第1期1367卷

作者： Mochammad Abdul Azis Abdul Hamid Ahmad Fauzi Yudhistira Eko Yulianto Verry Riyanto Ridwansyah Sfenrianto Information System Bina Sarana Informatika University Jakarta Indonesia. Departement of Informatic Technology STMIK Nusa Mandiri Jakarta Indonesia. Information Systems Management Department BINUS Graduate Program–Master of Information Systems Management Bina Nusantara University Jakarta Indonesia.

Speed and simplicity in the process of finding documents and information have become a necessity in the campus library. The speed in finding a skripsi document that is currently still very long to find the data and more simple in displaying what you are looking for then we aim to search and find skripsi documents in a digital library at a private university in Jakarta more quickly and display what which is searched precisely. An approach is needed using the VSM method that encourages without complete keywords, and to see the effectiveness of research searches. The results of the VSM method can be applied for the development of prototype applications. The prototype used to facilitate the process of searching or finding the documents and information needed is fast and simple.

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Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Dec, 10.1038/s41467-019-13824-9, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1页

作者： Sieverling, Lina Hong, Chen Koser, Sandra D. Ginsbach, Philip Kleinheinz, Kortine Hutter, Barbara Braun, Delia M. Cortes-Ciriano, Isidro Xi, Ruibin Kabbe, Rolf Park, Peter J. Eils, Roland Schlesner, Matthias Brors, Benedikt Rippe, Karsten Jones, David T. W. Feuerbach, Lars Division of Applied Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Faculty of Biosciences Heidelberg University 69120 Heidelberg Germany Division of Applied Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Biosciences Heidelberg University Heidelberg Germany German Cancer Consortium (DKTK) Heidelberg Germany National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ) Heidelberg Germany Wellcome Sanger Institute Wellcome Genome Campus Hinxton Cambridge CB10 1SA UK Korea Advanced Institute of Science and Technology Daejeon 34141 South Korea Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Korea Advanced Institute of Science and Technology Daejeon South Korea Division of Chromatin Networks German Cancer Research Center (DKFZ) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Department for Bioinformatics and Functional Genomics Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Institute of Pharmacy and Molecular Biotechnology and BioQuant Heidelberg University Heidelberg Germany Heidelberg University Heidelberg Germany New BIH Digital Health Center Berlin Institute of Health (BIH) and Charité - Universitätsmedizin Berlin Berlin Germany Heidelberg Center for Personalized Oncology (DKFZ-HIPO) German Cancer Research Center (DKFZ) Heidelberg Germany Department of Biomedical Informatics Harvard Medical School Boston MA USA Ludwig Center at Harvard Medical School Boston MA USA Department of Biomedical Informatics Harvard Medical School Boston Massachusetts 02115 USA Ludwig Center at Harvard Medical School Boston Massachusetts 02115 USA Broad Institute of MIT and Harvard

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