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The determinant of individual smoking consumption in Central Java province

Journal of Physics: Conference Series 2019年第2期1321卷

作者： S Subanti A R Hakim H S J N Sriwiyanto I M Hakim Department of Statistics Faculty of Mathematics and Natural Science Universitas Sebelas Maret Institute for Research and Social Services Universitas Sebelas Maret Graduate Program in Economics Faculty of Economics and Business Universitas Indonesia Department of Economic Development Faculty of Economics and Business Universitas Sebelas Maret Department of Industrial Engineering Faculty of Engineering Universitas Indonesia

The paper aims to determine the socio-economic factors that significantly affect the individual smoking consumption and to make smoker profile in Central Java Province. This paper uses national economy social survey (Susenas) based on individual analytical units. The estimation technique with ordinary least squares regression. The findings of the paper is the factors that significantly influence the individual smoking consumption are cigarette prices, income, marriage status, urban-rural, education level, poor status, and living condition. This study suggests that to reduce cigarette consumption, the government needs to increase the price of cigarettes. In addition, the government needs to promote anti-smoking campaigns and smoking bans at work.

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Manifold learning for organizing unstructured sets of process observations

arXiv

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arXiv 2018年

作者： Dietrich, Felix Kooshkbaghi, Mahdi Bollt, Erik M. Kevrekidis, Ioannis G. Department of Chemical and Biomolecular Engineering Department of Applied Mathematics and Statistics Johns Hopkins University BaltimoreMD21218 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Department of Mathematics Department of Electrical and Computer Engineering Clarkson Center for Complex Systems Science Clarkson University PotsdamNY13699-5815 United States

Data mining is routinely used to organize ensembles of short temporal observations so as to reconstruct useful, low-dimensional realizations of an underlying dynamical system. In this paper, we use manifold learning to organize unstructured ensembles of observations ("trials") of a system's response surface. We have no control over where every trial starts;and during each trial operating conditions are varied by turning "agnostic" knobs, which change system parameters in a systematic but unknown way. As one (or more) knobs "turn" we record (possibly partial) observations of the system response. We demonstrate how such partial and disorganized observation ensembles can be integrated into coherent response surfaces whose dimension and parametrization can be systematically recovered in a data-driven fashion. The approach can be justified through the Whitney and Takens embedding theorems, allowing reconstruction of manifolds/attractors through different types of observations. We demonstrate our approach by organizing unstructured observations of response surfaces, including the reconstruction of a cusp bifurcation surface for Hydrogen combustion in a Continuous Stirred Tank Reactor. Finally, we demonstrate how this observation-based reconstruction naturally leads to informative transport maps between input parameter space and output/state variable *** codes 37M20 Copyright © 2018, The Authors. All rights reserved.

关键词： Dynamical systems

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The Influence of the Model Fractal Parameters on the Electromagnetic Response in Environment with Cylindrical Layers

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International Journal of Geosciences 2017年第3期8卷 349-363页

作者： Valcir Joã o da Cunha Farias Brígida Ramati Pereira da Rocha Alice Nabiç a Mores Faculty of Statistics Federal University of Pará Belém Brazil Pos-Graduate Program in Electrical Engineering Federal University of Pará Belém Brazil

The induced polarization response of an environment presenting cylindrical layers was obtained. The fractal model for complex resistivity was employed as an intrinsic property of the polarizable layers. The influence of the model fractal parameters on the electromagnetic response was investigated. The results demonstrated that the fractal parameters dominate the apparent resistivity phase response;measurements of the induced polarization data allow for the determination of the fractal properties of the environment without noticeable electromagnetic coupling effects at frequencies below 104 Hz.

关键词： Fractal Model Induced Polarization Complex Resistivity Well Log

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Evaluation of an Instrument to Identify Factors that Impact the Motivation and Engagement of Undergraduate Students in Computing

Evaluation of an Instrument to Identify Factors that Impact ...

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Frontiers in Education (FIE) Conference

作者： Pablo Schoeffel Raul Sidnei Wazlawick Vinicius Faria Culmant Ramos Adilson Vahldick Marcelo de Souza Graduate Program in Computer Science Federal University of Santa Catarina Florianópolis Brazil Department of Informatics and Statistics Federal University of Santa Catarina Florianópolis Brazil Department of Information and Communication Technologies Federal University of Santa Catarina Araranguá Brazil Departament of Software Engineering University of Santa Catarina State Ibirama Brazil

ISBN: (纸本)9781538611753;9781538611746

This Research Paper presents the evaluation of an instrument to identify the impact of motivation and engagement factors in undergraduate students in computing. Although researches indicate a direct impact of motivation and engagement on student performance and retention, few studies have been found that address which factors are relevant in this process. The instrument is a questionnaire based on the compilation of several works of the literature containing 48 items divided into 6 groups: personal and demographic data, general perception about motivation, perception about the university, student behavior, perception about program and perception about classes/teachers. The questionnaire evaluation is based on a case study with 112 undergraduate students in Software engineering. As a result, we found that the questionnaire can be considered reliable (Cronbach's alpha = .8904). Considering the validity of constructs, we found an acceptable degree of correlation between the most pair of items in each group (averaging 63%). We also found that the item-total correlation coefficient was only not adequate for one factor group, indicating satisfactory correlation for all other items. Finally, we found that the number of factors is coherent, but there are several items from different groups strongly correlated, indicating the need for a reorganization.

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Identification of Pre-University Factors that Affect the Initial Motivation of Students in Computing programs: A multi-institutional case study

Identification of Pre-University Factors that Affect the Ini...

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Frontiers in Education (FIE) Conference

ISBN: (纸本)9781538611753;9781538611746

This Research to Practice Paper presents the results of the evaluation of pre-university factors that impact the initial motivation of undergraduate students in computing. Although there are studies in the literature that have investigated some previous factors, this paper replicates a previous work that aims to consolidate several pre-university factors and, as the main differential, uses the AMS (Academic Motivation Scale), a scale already consolidated in the literature to measure students' initial motivation, and evaluate the relation between motivation and candidate factors. We applied a questionnaire to 159 students from different computing programs in ten universities, which evaluates 20 factors divided into 4 groups: personal and demographic data, taste and knowledge of the program and area, computing experience, and school performance. To evaluate the correlation between factors and motivation, we used Spearman's coefficient, t-student test, and ANOVA to evaluate the correlation between factors and motivation. As main results, we found significant variation in the initial motivation according to following factors: taste for programming and technology, knowledge about the undergraduate program content, correct perception about computing professionals, knowledge and experience in computer programming, and general school performance.

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CEMRACS 2017: numerical probabilistic approach to MFG

arXiv

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arXiv 2018年

作者： Angiuli, Andrea Graves, Christy V. Li, Houzhi Chassagneux, Jean-François Delarue, François Carmona, René Department of Statistics and Applied Probability University of California Santa Barbara Program in Applied and Computational Mathematics Princeton University Laboratoire de Probabilités Modélisation et Statistiques Université Paris Diderot Laboratoire Jean-Alexandre Dieudonné Université de Nice Sophia-Antipolis Operations Research and Financial Engineering Bendheim Center for Finance Princeton University

This project investigates numerical methods for solving fully coupled forward-backward stochastic differential equations (FBSDEs) of McKean-Vlasov type. Having numerical solvers for such mean field FBSDEs is of interest because of the potential application of these equations to optimization problems over a large population, say for instance mean field games (MFG) and optimal mean field control problems. Theory for this kind of problems has met with great success since the early works on mean field games by Lasry and Lions, see [27], and by Huang, Caines, and Malhamé, see [24]. Generally speaking, the purpose is to understand the continuum limit of optimizers or of equilibria (say in Nash sense) as the number of underlying players tends to infinity. When approached from the probabilistic viewpoint, solutions to these control problems (or games) can be described by coupled mean field FBSDEs, meaning that the coefficients depend upon the own marginal laws of the solution. In this note, we detail two methods for solving such FBSDEs which we implement and apply to five benchmark problems. The first method uses a tree structure to represent the pathwise laws of the solution, whereas the second method uses a grid discretization to represent the time marginal laws of the solutions. Both are based on a Picard scheme;importantly, we combine each of them with a generic continuation method that permits to extend the time horizon (or equivalently the coupling strength between the two equations) for which the Picard iteration converges. Copyright © 2018, The Authors. All rights reserved.

关键词： Numerical methods

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CellLENS enables cross-domain information fusion for enhanced cell population delineation in single-cell spatial omics data

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Nature immunology 2025年 2025 May 22页

作者： Bokai Zhu Sheng Gao Shuxiao Chen Yuchen Wang Jason Yeung Yunhao Bai Amy Y Huang Yao Yu Yeo Guanrui Liao Shulin Mao Zhenghui G Jiang Scott J Rodig Ka-Chun Wong Alex K Shalek Garry P Nolan Sizun Jiang Zongming Ma Ragon Institute of MGH MIT and Harvard Cambridge MA USA. Broad Institute of MIT and Harvard Cambridge MA USA. Massachusetts Institute of Technology Cambridge MA USA. Department of Statistics and Data Science The Wharton School University of Pennsylvania Philadelphia PA USA. Center for Virology and Vaccine Research Beth Israel Deaconess Medical Center Harvard Medical School Boston MA USA. Department of Computer Science City University of Hong Kong Hong Kong People's Republic of China. Dana-Farber Cancer Institute Boston MA USA. Center of Hepato-Pancreato-Biliary Surgery The First Affiliated Hospital of Sun Yat-sen University Guangzhou People's Republic of China. Division of Genetics and Genomics Boston Children's Hospital Harvard Medical School Boston MA USA. Program in Biological and Biomedical Sciences Harvard Medical School Boston MA USA. Division of Gastroenterology/Liver Center Beth Israel Deaconess Medical Center Harvard Medical School Boston MA USA. Department of Pathology Brigham and Women's Hospital Harvard Medical School Boston MA USA. Institute for Medical Engineering and Science Massachusetts Institute of Technology Cambridge MA USA. Department of Chemistry Massachusetts Institute of Technology Cambridge MA USA. Koch Institute for Integrative Cancer Research Massachusetts Institute of Technology Cambridge MA USA. Department of Pathology Stanford University Stanford CA USA. gnolan@stanford.edu. Broad Institute of MIT and Harvard Cambridge MA USA. sjiang3@bidmc.harvard.edu. Center for Virology and Vaccine Research Beth Israel Deaconess Medical Center Harvard Medical School Boston MA USA. sjiang3@bidmc.harvard.edu. Dana-Farber Cancer Institute Boston MA USA. sjiang3@bidmc.harvard.edu. Department of Pathology Brigham and Women's Hospital Harvard Medical School Boston MA USA. sjiang3@bidmc.harvard.edu. Department of Statistics and Data Science Yale University New Haven CT USA. zongming.ma@yale.edu.

Delineating cell populations is crucial for understanding immune function in health and disease. Spatial omics technologies offer insights by capturing three complementary domains: single-cell molecular biomarker expression, cellular spatial relationships and tissue architecture. However, current computational methods often fail to fully integrate these multidimensional data, particularly for immune cell populations and intrinsic functional states. We introduce Cell Local Environment and Neighborhood Scan (CellLENS), a self-supervised computational method that learns cellular representations by fusing information across three spatial omics domains (expression, neighborhood and image). CellLENS markedly enhances de novo discovery of biologically relevant immune cell populations at fine granularity by integrating individual cells' molecular profiles with their neighborhood context and tissue localization. By applying CellLENS to diverse spatial proteomic and transcriptomic datasets across multiple tissue types and disease settings, we uncover unique immune cell populations functionally stratified according to their spatial contexts. Our work demonstrates the power of multi-domain data integration in spatial omics to reveal insights into immune cell heterogeneity and tissue-specific functions.

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Exchange rate volatility and exports: a panel data analysis for 5 ASEAN countries

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Journal of Physics: Conference Series 2019年第1期1217卷 012089-012089页

作者： Subanti, S Hakim, A R Riani, A L Hakim, I M Nasir, M S Department of Statistics Universitas Sebelas Maret Institute for Research and Social Services Universitas Sebelas Maret Graduate Program in Economics Universitas Indonesia Institute for Research and Social Services Universitas Sebelas Maret Department of Management Universitas Sebelas Maret Department of Industrial Engineering Universitas Indonesia Department of Development Economics Universitas Ahmad Dahlan

The study of the effects of exchange rate volatility has still attracted the attention among economist, especially international economist. Because, if the exchange rate is unpredictable, it makes uncertainty about the profits to be gained, so this conditions may diminish the gain from international trade. In addition, some empirical literature provides various findings, where the exchange rate volatility has a positive effect on exports and can also negatively effect on exports. This paper wants to provide empirical evidence on both of these. It uses panel data involving five ASEAN countries with a period of 2000 – 2016. We also apply some analysis in panel data, such as the pooled least squares method, the fixed effect method, and the random effect method. The findings show that the exchange rate volatility has negative impact on exports. This paper suggests that each of central bank should pursue sustainable and stable exchange rate policy measures to promote greater exchange rate stability that would help to enhance the real exports of the economy.

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Publisher Correction: Comprehensive molecular characterization of mitochondrial genomes in human cancers

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Nature genetics 2023年第5期55卷 893页

作者： Yuan Yuan Young Seok Ju Youngwook Kim Jun Li Yumeng Wang Christopher J Yoon Yang Yang Inigo Martincorena Chad J Creighton John N Weinstein Yanxun Xu Leng Han Hyung-Lae Kim Hidewaki Nakagawa Keunchil Park Peter J Campbell Han Liang Department of Bioinformatics and Computational Biology The University of Texas MD Anderson Cancer Center Houston TX USA. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK. Graduate School of Medical Science and Engineering Korea Advanced Institute of Science and Technology Daejeon Korea. Department of Health Science and Technology Samsung Advanced Institute for Health Science and Technology Sungkyunkwan University School of Medicine Seoul Korea. Quantitative and Computational Biosciences Graduate Program Baylor College of Medicine Houston TX USA. Division of Biostatistics The University of Texas Health Science Center at Houston School of Public Health Houston TX USA. Department of Medicine and Dan L. Duncan Cancer Center Division of Biostatistics Baylor College of Medicine Houston TX USA. Department of Systems Biology The University of Texas MD Anderson Cancer Center Houston TX USA. Department of Applied Mathematics and Statistics Johns Hopkins University Baltimore MD USA. Department of Biochemistry and Molecular Biology The University of Texas Health Science Center at Houston McGovern Medical School Houston TX USA. Department of Biochemistry Ewha Womans University School of Medicine Seoul Korea. Laboratory for Cancer Genomics RIKEN Center for Integrative Medical Sciences Yokohama Japan. Division of Hematology/Oncology Samsung Medical Center Sungkyunkwan University School of Medicine Seoul Korea. kpark@skku.edu. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK. pc8@sanger.ac.uk. Cambridge University Hospitals NHS Foundation Trust Cambridge UK. pc8@sanger.ac.uk. Department of Bioinformatics and Computational Biology The University of Texas MD Anderson Cancer Center Houston TX USA. hliang1@***. Quantitative and Computational Biosciences Graduate Program Baylor College of Medicine Houston TX USA. hliang1@***. Department of Systems Biology The University of Texas MD Anderson Cancer Center Houston TX USA. hliang1@mdanderson

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An expanded study to assess the effect of online homework on student learning in a first circuits course 123

An expanded study to assess the effect of online homework on...

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123rd ASEE Annual Conference and Exposition

作者： Evans, Katie Hummel, Paul Gates, Miguel Louisiana Tech. University Department of Mathematics and Statistics United States Cyber Engineering Program United States

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