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Implementation of fuzzy-profile matching in determining drug suitability for hypertensive patients

IOP Conference Series: Materials science and Engineering 2020年第1期857卷

作者： A Wantoro A Syarif K Muludi K Nisa Department of Computer Science Teknokrat Indonesia University Lampung Indonesia Department of Computer Science Faculty of Mathematic and Sciences Lampung University Bandar Lampung Indonesia

Treatments of patients with hypertension can be done in two ways, namely modifying lifestyle and antihypertensive drugs. Generally giving hypertensive drugs depends on age, history of illness, smoking habits, obesity and on diseases such as diabetes, kidney failure, heart failure and ischemic heart disease. Inappropriate use of antihypertensive drugs often causes complaints such as fever, diarrhea, diabetes, mouth breathing, nerve disorders, radiation to the neck and head area. In providing hypertensive drugs that are appropriate to the patient's condition, doctor and medical personnels are required to have high pharmacological knowledge. Not all hospitals have pharmacology experts, therefore this study was conducted to develop a model that can be used as a drug suitability model based on the patient's condition. The method used in this study is Weight Matching Using Fuzzy Logic. Based on the results of comparisons with expert 1 and expert 2, the results of the average system testing are obtained with a value of 100% precision, recall 96.6% and accuracy 96.5%. Tests show that the application with a fuzzy logic approach can increase the efficiency of 9.5% compared to the interpolation weighting method.

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From hotelling to load balancing: Approximation and the principle of minimum differentiation

arXiv

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arXiv 2019年

作者： Feldotto, Matthias Lenzner, Pascal Molitor, Louise Skopalik, Alexander Heinz Nixdorf Institute Departement of Computer Science Paderborn University Paderborn Germany Algorithm Engineering Group Hasso Plattner Institute Potsdam Germany Faculty of Electrical Engineering Mathematic & Computer Science University of Twente Enschede Netherlands

Competing firms tend to select similar locations for their stores. This phenomenon, called the principle of minimum differentiation, was captured by Hotelling with a landmark model of spatial competition but is still the object of an ongoing scientific debate. Although consistently observed in practice, many more realistic variants of Hotellings model fail to support minimum differentiation or do not have pure equilibria at all. In particular, it was recently proven for a generalized model which incorporates negative network externalities and which contains Hotellings model and classical selfish load balancing as special cases, that the unique equilibria do not adhere to minimum differentiation. Furthermore, it was shown that for a significant parameter range pure equilibria do not exist. We derive a sharp contrast to these previous results by investigating Hotellings model with negative network externalities from an entirely new angle: approximate pure subgame perfect equilibria. This approach allows us to prove analytically and via agent-based simulations that approximate equilibria having good approximation guarantees and that adhere to minimum differentiation exist for the full parameter range of the model. Moreover, we show that the obtained approximate equilibria have high social welfare. Copyright © 2019, The Authors. All rights reserved.

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Optimum Index Factor and Cloud Removal on the Landsat Imagery Data Processing 1

Optimum Index Factor and Cloud Removal on the Landsat Imager...

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1st SEMIRATA-International Conference on science and Technology, SEMIRATA-ICST 2018

作者： Ziliwu, M.S. Tulus Sutarman Zarlis, M. Situmorang, Z. Harahap, A.S. Postgraduate School Department of Technical Information Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Mathematics Faculty of Mathematic and Natural Sciences Universitas Sumatera Utara Medan Indonesia Faculty of Computer Science Universitas Katolik Santo Thomas Medan Indonesia

The research by using landsat imagery data which is a remote observation and recording technology equipped with Enhanced Thematic Mapper Plus (ETM +) sensor has been conducted. Landsat-7 has a sensor that produces images with 7 bands of 1, 2, 3, 4, 5, and 7 with spatial resolution of 30×30 m and band 6 with a spatial resolution of 120×120 m. The image processing begins with obtaining the best combination of Optimum Index Factor (OIF) is one of the methods used to get the proper *** data imagery also contains cloud cover which can interfere and hamper in the process of obtaining more accurate landsat image data. Cloud removal by using K-Means Clustering process can separate and clusterize each object in the image based on the closest color and distance so that clouds and other land cover can be clustered and freed from the cloud visually. © Published under licence by IOP Publishing Ltd.

关键词： K-means clustering

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Authentication of Piper betle L. folium and quantification of their antifungal-activity

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Journal of Traditional and Complementary Medicine 2017年第3期7卷 288-295页

作者： Wirasuta, I Made Agus Gelgel Srinadi, I Gusti Ayu Made Dwidasmara, Ida Bagus Gede Ardiyanti, Ni Luh Putu Putri Trisnadewi, I Gusti Ayu Arya Paramita, Ni Luh Putu Vidya Pharmacy Department Faculty of Mathematic and Natural Science Udayana University Indonesia Mathematic Department Faculty of Mathematic and Natural Science Udayana University Indonesia Computer Science Department Faculty of Mathematic and Natural Science Udayana University Indonesia

The TLC profiles of intra- and inter-day precision for Piper betle L. (PBL) folium methanol extract was studied for their peak marker recognition and identification. The Numerical chromatographic parameters (NCPs) of the peak markers, the hierarchical clustering analysis (HCA) and the principal component analysis (PCA) were applied to authenticate the PBL. folium extract from other Piper species folium extract and to ensure the antifungal activity quality of the PBL essential oil. The spotted extract was developed with the mobile phase of toluene: ethyl acetate;93:7, (v/v). The eluted plate was viewed with the TLC-Visualizer, scanned under absorption and fluorescent mode detection, and on each sample the in-situ UV spectra were recorded between 190 to 400 nm. The NCPs profiles of intra- and inter-day precision results offered multi-dimensional chromatogram fingerprints for better marker peak pattern recognition and identification. Using the r-value fingerprints data series generated with this method allowed more precise discrimination the PBL. from other Piper species compared to the marker peak area fingerprint method. The cosine pair comparison was a simple method for authentication of two different fingerprints. The ward linkage clustering and the pair cross-correlation comparison were better chemometric methods to determine the consistency peak area ratio between fingerprints. The first component PCA-loading values of peak marker area fingerprints were correlated linearly to both the bio-marker concentration as well as the antifungal activity. This relationship could be used to control the quality and pharmacological potency. This simple method was developed for the authentication and quantification of herbal medicine. © 2017 Center for Food and Biomolecules, National Taiwan University

关键词： Antifungal Authentication Piper betle Quantification TLC multi-dimensional fingerprint

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Bresse-Timoshenko type systems with thermodiffusion effects: Well-possedness, stability and numerical results

arXiv

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arXiv 2020年

作者： Elhindi, Mohammad Zennir, Khaled Ouchenane, Djamel Choucha, Abdelbaki Arwadi, Toufic E.L. Department of Mathematics and Computer Science Faculty of Science Beirut Arab University Beirut Lebanon Department of Mathematics College of Sciences and Arts Qassim University Ar-Rass Saudi Arabia Laboratoire de Mathématiques Appliquées et de Modélisation Université 8 Mai 1945 Guelma. B.P. 401 Guelma24000 Algeria Laboratory of pure and applied mathematic Laghouat University Algeria Department of Mathematics Faculty of Exact Sciences University of El Oued B.P. 789 El Oued39000 Algeria

Bresse-Timoshenko beam model with thermal, mass diffusion and theormoelastic effects is studied. We state and prove the well-posedness of problem. The global existence and uniqueness of the solution is proved by using the classical Faedo-Galerkin approximations along with two a priori estimates. We prove an exponential stability estimate for problem under an unusual assumption, and by using a multiplier technique in two different cases, with frictional damping in the angular rotation and with frictional damping in the vertical displacement. In numerical parts, we first obtained a numerical scheme for problem by P1-finite element method for space discretization and implicit Euler scheme for time discretization. Then, we showed that the discrete energy decays, later a priori error estimates are established. Finally, some numerical simulations are presented. Copyright © 2020, The Authors. All rights reserved.

关键词： Damping

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Brain Tumour Detection using Fine-Tuning Mechanism for Magnetic Resonance Imaging

Brain Tumour Detection using Fine-Tuning Mechanism for Magne...

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2017 Malaysian Technical Universities Conference on Engineering and Technology, MUCET 2017

作者： Al-Tamimi, Mohammed S.H. Ghazali, Nur Hafizah Mahrom, Norfadila Ghazali, Nurulhuda Sulong, Ghazali University of Baghdad College of Science Department of Computer Science Baghdad Iraq Universiti Malaysia Perlis School of Computer and Communication Engineering Perlis Malaysia Universiti Teknologi Mara Faculty of Computer and Mathematic Sciences Melaka Malaysia Universiti Teknologi Malaysia Faculty of Computing Johor Malaysia Universiti Malaysia Terengganu School of Informatics and Applied Mathematics Terengganu Malaysia

In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments. © The Authors, published by EDP sciences, 2018.

关键词： Magnetic resonance imaging

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Comparative Analysis of Efficient Image Segmentation Technique for Text Recognition and Human Skin Recognition

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IOP Conference Series: Materials science and Engineering 2019年第1期621卷

作者： Septian Cahyadi Febri Damatraseta Victor Ilyas Sugara Faculty of Mathematic and Natural Science Pakuan University of Bogor Indonesia Department of Computer Science Faculty of Master Budi Luhur Universit Jakarta Indonesia

computer Vision and Pattern Recognition is one of the most interesting research subject on computer science, especially in case of reading or recognition of objects in real-time from the camera device. Object detection has wide range of segments, in this study we will try to find where the better methodologies for detecting a text and human skin. This study aims to develop a computer vision technology that will be used to help people with disabilities, especially illiterate (tuna aksara) and deaf (penyandang tuli) to recognize and learn the letters of the alphabet (A-Z). Based on our research, it is found that the best method and technique used for text recognition is Convolutional Neural Network with achievement accuracy reaches 93%, the next best achievement obtained OCR method, which reached 98% on the reading plate number. And also OCR method are 88% with stable image reading and good lighting conditions as well as the standard font type of a book. Mean while, best method and technique to detect human skin is by using Skin Color Segmentation: CIELab color space with accuracy of 96.87%. While the algorithm for classification using Convolutional Neural Network (CNN), the accuracy rate of 98%.

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A hybrid data mining model for Indonesian telematics SMEs empowerment

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IOP Conference Series: Materials science and Engineering 2019年第1期567卷

作者： E T Tosida F Andria I Wahyudin R Widianto M Ganda R R Lathif Computer Science Department Faculty of Mathematic & Natural Science Universitas Pakuan Bogor Indonesia Management Department Faculty of Economy Universitas Pakuan Bogor Indonesia

The power of information technology and communication (telematics) is one of the vital forces for every country. In the Industrial Revolution 4.0 era, the development of telematics was one of the priorities of the Indonesian government nawacitas. The development of the field of telematics in Indonesia for a decade is inseparable from the role of SMEs. The role of telematics SMEs in the strength of national development can be mapped through the optimization of National Economic Census data (Susenas). The detailed 2016 Susenas data has not been released by BPS. Therefore, this research still uses 2006 Susenas data. The 2016 Susenas recapitalization shows that Indonesian telematics has a very large power, consisting of 2.6 million players. This great strength needs to be optimized to have high competitiveness so as to be able to support Indonesia's development. The purpose of this study was to conduct hybrid data mining modeling to be used as a decision model in mapping the classification of Indonesian telematics SMEs. The classification map includes the feasibility of assistance for the empowerment of Indonesian telematics SMEs, business prospects and development plans for Indonesian telematics SMEs. The hybrid data mining model with K-Medoids & C4.5 technique shows better performance compared to other models, with an average accuracy rate of 71.87%. This model validation test also involves K-fold cross validations.

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Incremental maintenance of discovered association rules and approximate dependencies

Incremental maintenance of discovered association rules and ...

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作者： Pérez-Alonso, Alain Medina, Ignacio J. Blanco González-González, Luisa M. Serrano Chica, José M. Center for Informatics Studies Department of Computer Science Faculty of Mathematic Physic and Computer Science University 'Marta Abreu' of Las Villas Villa-Clara Cuba Department of Computer Science and Artificial Intelligence University of Granada Granada Spain

Association Rules (ARs) and Approximate Dependencies (ADs) are significant fields in data mining and the focus of many research efforts. This knowledge, extracted by traditional mining algorithms becomes inexact when new data operations are executed, a common problem in real-world applications. Incremental mining methods arise to avoid re-runs of those algorithms from scratch by re-using information that is systematically maintained. These methods are useful to extract knowledge in dynamic environments. However, the implementation of algorithms only to maintain previously discovered information creates inefficiencies. In this paper, two active algorithms are proposed for incremental maintenance of previous discovered ARs and ADs, inspired by efficient computation of changes. These algorithms operate over a generic form of measures to efficiently maintain a wide range of rule metrics simultaneously. We also propose to compute data operations at real-time, in order to create a reduced relevant instance set. The algorithms presented do not discover new knowledge;they are just created to efficiently maintain previously extracted valuable information. Experimental results in real education data and repository datasets show that our methods achieve a good performance. In fact, they can significantly improve traditional mining, incremental mining, and a naïve approach. © 2017 - IOS Press and the authors. All rights reserved.

关键词： Association rules

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Thank You to Our 2021 Peer Reviewers

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GeoHealth 2022年第5期6卷 e2022GH000639页

作者： Gabriel Filippelli Rita Colwell Susan Anenberg John Balbus Daniela Ceccarelli Karen Hudson-Edwards Antarpreet Jutla Chiyuan Miao Paul Sandifer Avner Vengosh Department of Earth Sciences and Center of Urban Health Indiana University-Purdue University Indianapolis Indianapolis IN USA. Institute for Advanced Computer Studies University of Maryland College Park MD USA. Milken Institute School of Public Health George Washington University Washington DC USA. National Institute of Environmental Health Sciences Bethesda MD USA. Research Executive Agency of the European Commission Brussels Belgium. Camborne School of Mines and Environment and Sustainability Institute University of Exeter Exeter UK. Department of Environmental Engineering Sciences University of Florida Gainesville FL USA. Faculty of Geographical Science Beijing Normal University Beijing China. Center for Coastal Environmental and Human Health College of Charleston School of Sciences & Mathematic Charleston SC USA. Nicholas School of the Environment Division of Earth and Ocean Sciences Duke University Durham NC USA.

The editors thank the 2021 peer reviewersIn 2021, GeoHealth benefited from 365 reviews provided by 241 of our peersA number of individuals submitted multiple reviews for GeoHealth in 2021.

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