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Derivative Free Levenberg-Marquardt Method for Solving Fuzzy Nonlinear Equation

IOP Conference Series: Materials Science and engineering 2021年第1期1115卷

作者： A U Omesa I M Sulaiman M Mamat M Y Waziri A Shadi M A Zaini Kalfin I Sumiati Department of Mathematics College of Agriculture Zuru Kebbi Nigeria Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus Kuala Nerus 22200 Terengganu Malaysia Department of Mathematics Bayero University Kano Nigeria Institute of Engineering Mathematics Universiti Malaysia Perlis Kangar Malaysia Doctor Program of Mathematics Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Indonesia Master Program in Mathematics Faculty of Mathematics and Natural Science Universitas Padjadjaran Indonesia

In this paper, we present a derivative-free computational method for solving fuzzy nonlinear equation. Derivative-free technique avoids computing the derivative by generating an estimate to the derivative. This is made possible by inserting the estimate of in Levenberg-Marquardt's method. Numerical experiments are carried out which shows that, the method is efficient.

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Applying mobility business intelligence concept in analyzing oil palm plantation productivity

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AIP Conference Proceedings 2024年第1期3026卷

作者： Andreas Wahyu Krisdiarto Irya Wisnubhadra Anzaludin Samsinga Perbangsa Teddy Suparyanto Bens Pardamean Faculty of Agricultural Technology STIPER Institute of Agriculture Yogyakarta Indonesia Informatics Engineering Department Atma Jaya Yogyakarta University Yogyakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia BDSRC Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia

The palm oil business employs almost 20 million people, generates USD 21 billion in revenue, and plays a vital role in Indonesia’s social economy. The Fresh Fruit Bunches (FFB) to Palm Oil Mills (POM) distribution system is one important aspect of fruit quality. Three steps are involved in getting Oil Palm FFB from the plantation to the POM. The first part of the procedure involves cutting FFB from the tree, the second stage involves gathering the fruit at a fruit collection point (FCP), and the third stage involves transporting the fruit to the palm oil mill (POM). As of now, the cost of the FFB transportation is still considerable, accounting for roughly 15% to 20% of the FFB pricing. The use of the Business Intelligence (BI) idea in the oil palm harvesting system is presented in this study as a foundation for creating web-based applications.

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Performance Analysis of a Modified Conjugate Gradient Algorithm for Optimization Models

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IOP Conference Series: Materials Science and engineering 2021年第1期1115卷

作者： S E Olowo I M Sulaiman M Mamat A E Owoyemi M A Zaini Kalfin S H Yuningsih Department of Mathematics Kano University of science and Technology Kano Nigeria Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus Kuala Nerus 22200 Terengganu Malaysia Department of General Studies. Federal College of Agricultural Produce Technology Kano Nigeria Institute of Engineering Mathematics Universiti Malaysia Perlis Kangar Malaysia Doctor Program of Mathematics Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Indonesia Master Program of Mathematics Faculty of Mathematics and Natural Sciences Universitas Padjadjaran Indonesia

The Conjugate gradient (CG) algorithms is very important and widely used in solving optimization models. This is due to its simplicity as well as global convergence properties. Various line search procedures as usually employ in the analysis of the CG methods. Recently, many studies have been done aimed at improving the CG method. In this paper, an alternative formula for conjugate gradient coefficient has been proposed which possesses the global convergence properties under exact minimization condition. The result of the numerical computation has shown that this new coefficient performs better than the existing CG methods.

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Analysis of plant pattern using water balance and cimogram based on oldeman climate type

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IOP Conference Series: Earth and Environmental Science 2018年第1期195卷

作者： R E Caraka M Tahmid R M Putra A Iskandar M A Mauludin Hermansah N E Goldameir H Rohayani B Pardamean Bioinformatics and Data Science Research Center (BDSRC) Bina Nusantara University Jakarta Indonesia 11480 Indonesia Agency for Meteorology Climatology and Geophysics Indonesia Informatics Engineering STMIK AKBA Makassar Laboratory of Sociology and Extension Universitas Padjadjaran Universitas Riau Kepulauan Riau University Universitas Adiwangsa Jambi Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

The transfer of land has an impact on the decreasing of the agricultural land area, so it is necessary to plan the right cropping pattern as an effort to increase the productivity of agricultural cultivation. Also, Climate is one of the factors influencing the determination of cropping pattern in a region. Analysis of climatic characteristics in the determination of cropping pattern not only based on oldeman climatic classification. At the same time, the study of groundwater availability for plants and climogram of climatic elements is needed in determining planting schedule which is suitable for planting and determination of irrigation water supply, either the right amount of time. This study aims to identify and build spatial of the oldeman climate classification. It also determines the cropping pattern for seasonal crops based on the calculation of water balance and climogram (rainfall and air temperature) in each type of climate oldeman district of Cirebon and surrounding areas. Data used monthly rainfall data period 1981-2010 from BMKG Jatiwangi station and air temperature data, plant coefficient and the base map of Cirebon region. The analysis method includes classification of Oldeman climate type, spatial data processing, water balance calculation by Thorntwaite & Matter method and making climogram (rainfall and temperature) with: k = p0 + p1/FC; p0 = 1.000412351; p1 = -1.073807306 and determination of planting pattern of each type of oldeman

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Rainfall forecasting using PSPline and rice production with ocean-atmosphere interaction

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IOP Conference Series: Earth and Environmental Science 2018年第1期195卷

作者： Rezzy Eko Caraka Budi Darmawan Supatmanto Muhammad Tahmid Joko Soebagyo M Ali Mauludin Akbar Iskandar Bens Pardamean Bioinformatics and Data Science Research Center (BDSRC) Bina Nusantara University Jakarta Indonesia 11480 Weather Modification Technology Center Agency for the Assessment and Application of Technology (BPPT Indonesia Agency for Meteorology Climatology and Geophysics Indonesia College of Technology Wastukancana Purwakarta Laboratory of Sociology and Extension Padjadjaran University Informatics Engineering STMIK AKBA Makassar Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

The role of climate can be affected by plants. The weather can accelerate and multiply the existence of various plant pests and diseases, accelerate the growth and development of grass among plants, and encourage the emergence of infection and significant damage to plants. The elements of climate that affect the growth of plants are one of them is rainfall. In this paper, we performed the simulation using the non-parametric penalized spline (PSPLINE) method and studied the effect on rice production in Lampung. It can be concluded that the increasing fluctuation, frequency, and intensity of climate anomalies in the last decade caused by the ENSO phenomenon have an impact on changes in distribution patterns, intensity, and period of the wet season so that the start of the rainy season and the dry season becomes too late. As a result, there is a seasonal shift from normal average conditions that can ultimately have severe implications for food crops. In a nutshell penalized spline gives high accuracy with R 2 = 96.227% and MAPE = 1.62%.

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Identification of gene expression signatures for psoriasis classification using machine learning techniques

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Medicine in Omics 2021年 1卷

作者： Nguyen Quoc Khanh Le Duyen Thi Do Trinh-Trung-Duong Nguyen Ngan Thi Kim Nguyen Truong Nguyen Khanh Hung Nguyen Thi Thu Trang Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei City 106 Taiwan Research Center for Artificial Intelligence in Medicine Taipei Medical University Taipei City 106 Taiwan Graduate Institute of Biomedical Informatics Taipei Medical University Taipei City 106 Taiwan Department of Computer Science and Engineering Yuan Ze University Chung-Li 32003 Taiwan School of Nutrition and Health Sciences Taipei Medical University Taipei City 110 Taiwan International Master/Ph.D. Program in Medicine College of Medicine Taipei Medical University Taipei City 110 Taiwan Orthopedic and Trauma Department Cho Ray Hospital Ho Chi Minh City Viet Nam International PhD Program for Cell Therapy and Regeneration Medicine College of Medicine Taipei Medical University Taipei City 110 Taiwan

Psoriasis classification requires the accurate identification of the lesional types for the early and effective diagnosis and it is worth interesting that the normal and psoriasis cell tissues exhibit different gene expression. Therefore, gene expression data is an effective source for psoriasis classification and there is a challenge regarding the selection of suitable gene signatures for its purpose. In this present study, the gene expression-based microarray data were used and 35 expression features linked with psoriasis were utilized to feed into our machine learning model. Overall, the performance of our model based on 35 mentioned-above features surpassed that of other state-of-the-art classifiers with an average accuracy of 98.3%, recall of 98.6%, and precision of 98% in 5-fold cross-validation tests. We also validate our model on two different sets of psoriasis and the performance results are significant. These results have suggested that our 35 expression signatures have been identified as key features for classifying samples between lesion and non-lesion. More specifically, the expression levels of few genes i.e., FABP5 , TGM1 , or BCAR3 are discovered as newly potential biomarkers for psoriasis classification and treatment with high confidence. This study, therefore, could shed light on developing the prediction models for psoriasis classification and treatment using gene expression profiles.

关键词： Psoriasis classification Random forest Gene expression Feature selection Machine learning FABP5 Dermatology

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Optimization of production processes using predictive analytics apparatus in synthesis of systems of industrial Internet of Things

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AIP Conference Proceedings 2021年第1期2402卷

作者： A. L. Zolkin V. D. Munister V. A. Tikhonov I. V. Slabodenuk N. E. Amirov 1Computer and Information Sciences Department Povolzhskiy State University of Telecommunications and Informatics L.Tolstogo 23 Samara Russia 2Department of Mathematical Methods and Computer-Aided Design Private educational institution "Donetsk Academy of Transport" Dzerzhinsky Street 7 Donetsk Ukraine 3Department of chemical engineering and ecology Berezniki branch of the Perm National Research Polytechnic University TelmanaStreet 7 Perm region Berezniki Russia 4Chemical engineering of inorganic substances Master program Berezniki branch of the Perm National Research Polytechnic University TelmanaStreet 7 Perm region Berezniki Russia

The article presents an analysis of the optimal criterion. The role and significance of certain properties of fuzzy logic in predictive analytics of technical systems to support the functioning of the optimal level of production processes are considered. The role of calculation of the degree of inclusion of fuzzy sets is justified by the example of transfer characteristic functions in the generalized case. The author's research on the optimization value of the investigated mathematical apparatus is presented on the example of the synthesis of the industrial Internet of Things system within the framework of the model of automatic control of the air temperature in the greenhouse.

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Metadata Correction: Importance-Performance Analysis of Personal Health Records in Taiwan: A Web-Based Survey

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Journal of medical Internet research 2017年第6期19卷 e209页

作者： Hsiao-Hsien Rau Yi-Syuan Wu Chi-Ming Chu Fu-Chung Wang Min-Huei Hsu Chi-Wen Chang Kang-Hua Chen Yen-Liang Lee Senyeong Kao Yu-Lung Chiu Hsyien-Chia Wen Anis Fuad Chien-Yeh Hsu Hung-Wen Chiu Graduate Institute of Biomedical Informatics Taipei Medical University Taipei Taiwan. Administration Department Healthconn Corp Taipei Taiwan. Institute of Medical Informatics Department of Computer Science of Information Engineering National Cheng Kung University Tainan Taiwan. School Of Public Health National Defense Medical Center Taiepi Taiwan. National Health Insurance Administration Ministry of Health and Welfare Taiepi Taiwan. School of Nursing College of Medicine Chang Gung University Linkou Taiwan. Division of Endocrinology Department of Pediatrics Linkou Chang Gung Memorial Hospital Linkou Taiwan. Internet of Things Laboratory Chunghwa Telecom Laboratories TaoYuen Taiwan. School of Health Care Administration Taipei Medical University Taipei Taiwan. Department of Biostatistics Epidemiology and Population Health Faculty of Medicine Universitas Gadjah Mada Yogyakarta Indonesia. Department of Information Management National Taipei University of Nursing and Health Sciences Taipei Taiwan. Master Program in Global Health and Development Taipei Medical University Taipei Taiwan.

[This corrects the article DOI: .].

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Author Correction: Single-cell transcriptomics uncovers EGFR signaling-mediated gastric progenitor cell differentiation in stomach homeostasis

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Nature communications 2023年第1期14卷 6540页

作者： Hitomi Takada Yohei Sasagawa Mika Yoshimura Kaori Tanaka Yoshimi Iwayama Tetsutaro Hayashi Ayako Isomura-Matoba Itoshi Nikaido Akira Kurisaki Laboratory of Stem Cell Technologies Graduate School of Science and Technology Nara Institute of Science and Technology Takayama-cho Ikoma Nara Japan. Laboratory for Bioinformatics Research RIKEN Center for Biosystems Dynamics Research Wako Saitama Japan. Department of Functional Genome Informatics Biological Data Science Medical Research Institute Tokyo Medical and Dental University Bunkyo Tokyo Japan. Laboratory for Bioinformatics Research RIKEN Center for Biosystems Dynamics Research Wako Saitama Japan. itoshi.nikaido@riken.jp. Department of Functional Genome Informatics Biological Data Science Medical Research Institute Tokyo Medical and Dental University Bunkyo Tokyo Japan. itoshi.nikaido@riken.jp. Master's/Doctoral Program in Life Science Innovation (Bioinformatics) Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Tsukuba Ibaraki Japan. itoshi.nikaido@riken.jp. Laboratory of Stem Cell Technologies Graduate School of Science and Technology Nara Institute of Science and Technology Takayama-cho Ikoma Nara Japan. akikuri@bs.naist.jp.

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