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Investigation of Risk Factors of Students' Healthy Lifestyle Using correlation and regression analysis and Prospects of Artificial Intelligence Application 17

Investigation of Risk Factors of Students' Healthy Lifestyle...

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17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering, TCSET 2024

作者： Ilkanych, Kateryna Lototska, Lesia Maikher, Viktoria Riznychok, Svitlana Kolach, Tetyana Chaban, Olesia Danylo Halytsky Lviv National Medical University Medical Informatics Department Lviv Ukraine Lviv Polytechnic National University Software Department Lviv Ukraine

ISBN: (纸本)9798331520564

This study aims to investigate the main important points related to students' healthy lifestyle behaviours and self-rated health of medical students. In this paper, the factors that directly or indirectly determine the health status of the respondents are investigated using correlation and regression analysis. the proposed model will make it possible to predict the score in the self-assessment of the health of each individual student and determine the most significant risk factors for him. The designed model can be used to develop predictive models with the further aim of continuing research using artificial intelligence technologies. © 2024 IEEE.

关键词： artificial intelligence correlation and regression analysis healthy lifestyle factors

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The influence of atmospheric circulation on the water level on the southern coast of the Baltic Sea

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INTERNATIONAL JOURNAL OF CLIMATOLOGY 2016年第14期36卷 4534-4547页

作者： Girjatowicz, Jozef P. Swiatek, Malgorzata Wolski, Tomasz Univ Szczecin Hydrog & Water Management Unit Ul Mickiewicza 16 PL-70383 Szczecin Poland Univ Szczecin Coastal Marine Hydrol Unit Szczecin Poland

The research focused on the relationships between atmospheric circulation patterns and the water level on the southern coast of the Baltic Sea. Monthly values of water levels were used, recorded between 1961 and 2010 in Wismar, Warnemunde, Sassnitz, winoujcie, Koobrzeg, Ustka and Wadysawowo. To establish and examine the relationships between the water levels (dependent variable) and the number of days of atmospheric circulation patterns (independent variable), the correlation and regression analysis were conducted. The strongest relationships occur in the months of the cold season (November-March), especially in January, February and March, with the statistical significance of =0.01 (usually =0.001), mainly due to considerable atmospheric circulation activity. Relationships with the onshore circulation (W+NW+N) are slightly stronger than with the seaward circulation (E+SE+S). The intensity of these relationships grows eastwards (Ustka, Wadysawowo), where the water levels are higher, their amplitudes and standard deviations are larger and the coastal exposure is more favourable. It is where in winter (December-February) the correlation coefficients exceed |0.80|. The relationships in the months of the warm season (April-October) are visibly weaker, especially with the E+SE+S circulation in the west part of the southern coast of the Baltic Sea (Wismar, Warnemunde), where they are statistically insignificant. The asynchronous relationships of water levels with atmospheric circulation are usually weaker than the synchronous ones. However, on the west coast (Wismar, Warnemunde), the asynchronous relationships, especially with the E+SE+S circulation with 1-month delay, are usually stronger than the synchronous ones. They may have a prognostic value. The longer the intervals between the studied variables are, the weaker the relationships become.

关键词： circulation patterns sea level correlation and regression analysis southern Baltic Sea

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A Sparse regression Method for Group-Wise Feature Selection with False Discovery Rate Control

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2018年第4期15卷 1066-1078页

作者： Gossmann, Alexej Cao, Shaolong Brzyski, Damian Zhao, Lan-Juan Deng, Hong-Wen Wang, Yu-Ping Tulane Univ Bioinnovat PhD Program New Orleans LA 70118 USA Tulane Univ Ctr Bioinformat & Genom New Orleans LA 70118 USA Univ Texas MD Anderson Canc Ctr Dept Bioinformat & Computat Biol Houston TX 77004 USA Indiana Univ Dept Epidemiol & Biostat Bloomington IN USA Jagiellonian Univ Inst Math PL-31007 Krakow Poland Tulane Univ Dept Global Biostat & Data Sci New Orleans LA 70118 USA Tulane Univ Dept Biomed Engn New Orleans LA 70118 USA

The method of Sorted L-One Penalized Estimation, or SLOPE, is a sparse regression method recently introduced by Bogdan et. al. [1]. It can be used to identify significant predictor variables in a linear model that may have more unknown parameters than observations. When the correlations between predictor variables are small, the SLOPE method is shown to successfully control the false discovery rate (the expected proportion of the irrelevant among all selected predictors) at a user specified level. However, the requirement for nearly uncorrelated predictors is too restrictive for genomic data, as demonstrated in our recent study [2] by an application of SLOPE to realistic simulated DNA sequence data. A possible solution is to divide the predictor variables into nearly uncorrelated groups, and to modify the procedure to select entire groups with an overall significant group effect, rather than individual predictors. Following this motivation, we extend SLOPE in the spirit of Group LASSO to Group SLOPE, a method that can handle group structures between the predictor variables, which are ubiquitous in real genomic data. Our theoretical results show that Group SLOPE controls the group-wise false discovery rate (gFDR), when groups are orthogonal to each other. For use in non-orthogonal settings, we propose two types of Monte Carlo based heuristics, which lead to gFDR control with Group SLOPE in simulations based on real SNP data. As an illustration of the merits of this method, an application of Group SLOPE to a dataset from the Framingham Heart Study results in the identification of some known DNA sequence regions associated with bone health, as well as some new candidate regions.

关键词： Probability and statistics correlation and regression analysis statistical computing machine learning mathematics and statistics biology and genetics

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Changes of air temperature and precipitation in Poland in the period 1951-2000 and their relationship to atmospheric circulation

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INTERNATIONAL JOURNAL OF CLIMATOLOGY 2004年第3期24卷 291-310页

作者： Degirmendzic, J Kozuchowski, K Zmudzka, E Univ Lodz Dept Environm Dynam & Bioclimatol PL-90139 Lodz Poland Warsaw Univ Dept Climatol PL-00927 Warsaw Poland

An analysis of trends of mean monthly temperature and precipitation totals in Poland in the period 1951-2000 was carried out. Areal means of temperature and precipitation were used, averaged for 51 meteorological stations evenly distributed within Poland's borders. Sensitivity of air temperature and precipitation variations towards circulation was assessed. Circulation variations were expressed by sea-level pressure in the 52.5 degreesN, 20 degreesE grid point and geostrophic wind calculated from meridional (45-60 degreesN) and latitudinal (10-30 degreesE) pressure gradients. It was shown that the circulation factor explains up to 77% and 44% of temperature and precipitation variance respectively. Significant upward trends of temperature in March and May were detected. Also, the precipitation total in March was on the increase. The last decade of the 20th century was slightly 'too warm' in comparison with the circulation-induced temperature level, as well as with the temperature change scenario according to HadCM2 GS model. An attempt was made to evaluate the contribution of the frequency of snow cover occurrence to the temperature increase in winter, i.e. the temperature-albedo feedback. Copyright (C) 2004 Royal Meteorological Society.

关键词： Poland correlation and regression analysis air temperature precipitation atmospheric circulation snow cover

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Integration of life cycle assessment and statistical analysis to understand the influence of rainfall on WWTPs with combined sewer systems

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JOURNAL OF CLEANER PRODUCTION 2018年 172卷 2521-2530页

作者： Li, Yi Hou, Xing Zhang, Wenlong Xiong, Wei Wang, Longfei Zhang, Shanxue Wang, Peifang Wang, Chao Hohai Univ Coll Environm Key Lab Integrated Regulat & Resource Dev Shallow Minist Educ Nanjing 210098 Jiangsu Peoples R China

Rainfall plays a vital role in the operation phase of wastewater treatment plants (WWTPs) when receiving wastewater from combined sewers in rainy days. The aim of this study is to investigate how, and to what extent, the life cycle assessment (LCA) impacts of the WWTP with a combined sewer system could be influenced by the rainfall. Comprehensive correlation and regression analyses were preliminarily conducted to understand the statistical correlation among monthly rainfall precipitation, wastewater indicators (wastewater quality and quantity) and environmental burden contributors (resource consumptions and pollution emissions) in a case-study WWTP in eastern China. A dynamic LCA was then performed to quantify monthly CML2001 environmental impacts (including Abiotic Depletion Potential (ADP), Acidification Potential (AP), Eutrophication Potential (EP), Global Warming Potential (GWP), and Photochemical Ozone Creation Potential (POCP)) under different monthly rainfall precipitations. Finally, a regression analysis based on the preceding work was performed and five best fitting curves were obtained to model the relationship between monthly rainfall precipitations and CML2001 environmental impacts. It was found that monthly inflow rate had a linear relation with monthly rainfall precipitation below 193.2 mm and both of them had a moderate to strong correlation (vertical bar r vertical bar > 0.5) with all wastewater indicators. Most of the variations in environmental burden contributors can be interpreted by wastewater quality and quantity variations except for the discharge of effluent NH3-N. All environmental impacts show a rising trend with monthly rainfall precipitation below the threshold value for different reasons and then remain stable. The result indicates that the total environmental impacts of the WWTPs might be highly dependent on the capabilities of sewer systems and the WWTP. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Rainfall precipitation Wastewater treatment plant Combined sewer system Dynamic life cycle assessment correlation and regression analysis

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correlation analysis on GPU systems using NVIDIA's CUDA

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JOURNAL OF REAL-TIME IMAGE PROCESSING 2011年第4期6卷 275-280页

作者： Gembris, Daniel Neeb, Markus Gipp, Markus Kugel, Andreas Maenner, Reinhard Sci Instrument Mfg Bruker BioSpin MRI GmbH D-76275 Ettlingen Germany Univ Heidelberg Inst Comp Engn Mannheim D-68131 Mannheim Germany

Functional magnetic resonance imaging allows non-invasive measurements of brain dynamics and has already been used for neurofeedback experiments, which relies on real time data processing. The limited computational resources that are typically available for this have hindered the use of connectivity analysis in this context. A basic, but already computationally demanding analysis method of neural connectivity is correlation analysis that computes all pairwise correlations coefficients between the measured time series. The parallel nature of the problem predestines it for an implementation on massive parallel architectures as realized by GPUs and FPGAs. We show what performance benefits can be achieved when compared with current desktop CPUs. The use of correlation analysis is not limited to brain research, but is also relevant in other fields of image processing, e.g. for the analysis of video streams.

关键词： correlation and regression analysis Graphics processing unit (GPU) FPGA Time series analysis fMRI BOLD

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Investigation of the variables effects on fuelwood consumption as an energy source in forest villages of Turkey

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ENERGY CONVERSION AND MANAGEMENT 2001年第10期42卷 1215-1227页

作者： Türker, MF Kaygusuz, K Karadeniz Tech Univ Dept Forest Engn TR-61080 Trabzon Turkey Karadeniz Tech Univ Dept Chem TR-61080 Trabzon Turkey

It is a fact that the existing forests of Turkey have been insufficient, both in quality and quantity. The people living in and around the state forests in Turkey have been illegally using the wood raw material as fuelwood because of social, economic and geographic problems. As a result of this process, the state forests in Turkey cannot realize their social and economic functions. The main objective of this research is to define the social, economic, cultural and geographic factors effects on fuelwood consumption. The Macka State Forest Enterprise with 70 villages was chosen as the research area. In order to perform this study, the face to face question method and statistical tests were used. This research showed that there was a statistically positive relation between the fuelwood consumption and the altitudes of villages, the distances between forest and town center, the number of wooden houses and cows, whereas a statistically negative relation was shown between the fuelwood consumption and the amounts of liquid gas consumption, the numbers of new houses, the distances between forest and villages and the unit forest area per person. (C) 2001 Elsevier Science Ltd. All rights reserved.

关键词： correlation and regression analysis forest villages fuelwood consumption socio-economic factors biomass energy

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Training-Free, Generic Object Detection Using Locally Adaptive regression Kernels

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IEEE TRANSACTIONS ON PATTERN analysis AND MACHINE INTELLIGENCE 2010年第9期32卷 1688-1704页

作者： Seo, Hae Jong Milanfar, Peyman Univ Calif Santa Cruz Santa Cruz CA 95064 USA

We present a generic detection/localization algorithm capable of searching for a visual object of interest without training. The proposed method operates using a single example of an object of interest to find similar matches, does not require prior knowledge (learning) about objects being sought, and does not require any preprocessing step or segmentation of a target image. Our method is based on the computation of local regression kernels as descriptors from a query, which measure the likeness of a pixel to its surroundings. Salient features are extracted from said descriptors and compared against analogous features from the target image. This comparison is done using a matrix generalization of the cosine similarity measure. We illustrate optimality properties of the algorithm using a naive-Bayes framework. The algorithm yields a scalar resemblance map, indicating the likelihood of similarity between the query and all patches in the target image. By employing nonparametric significance tests and nonmaxima suppression, we detect the presence and location of objects similar to the given query. The approach is extended to account for large variations in scale and rotation. High performance is demonstrated on several challenging data sets, indicating successful detection of objects in diverse contexts and under different imaging conditions.

关键词： Object detection image representation correlation and regression analysis

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Measuring Effects of Technology-Enabled Mirroring Scaffolds on Self-Regulated Learning

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IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES 2020年第1期13卷 150-163页

作者： Milikic, Nikola Gasevic, Dragan Jovanovic, Jelena Univ Belgrade Fac Org Sci Belgrade 11000 Serbia Monash Univ Fac Educ Clayton Vic 3800 Australia Monash Univ Fac Informat Technol Clayton Vic 3800 Australia

Learning design in a massive open online course (MOOC) intends to promote creativity, autonomy, and social networked learning, amongst other things. Students in a MOOC are required to self-regulate their learning to properly self-monitor their learning process and effectiveness of the adopted learning strategies. This paper presents the results of a study among 279 students enrolled in a MOOC that was enriched with a set of scaffolding interventions for social mirroring. The mirroring interventions supported social awareness and social embeddedness of learners. Associations between the use of the interventions and microlevel self-regulated learning processes were measured and analyzed. The extent to which those associations are affected by learner demographics and motivational characteristics was also investigated. Findings show that interventions that provide students, throughout the course, with learning updates and progress of peers are associated with the students' engagement with learning tasks and applying changes in strategies for completing those tasks. Social awareness scaffold influenced more students low in need for cognition, with a higher education degree, high in performance-approach orientation and low in grit, to engage with their learning tasks, while its effect on the change in learning strategies was higher with those early and towards the end of their careers and high in performance-approach strategy. The social comparison scaffold affected more students low in mastery goal orientation and high in grit to work on their learning tasks.

关键词： correlation and regression analysis education learning management systems learning technologies scaffolding mirroring scaffolds social technologies

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Using Incomplete Information for Complete Weight Annotation of Road Networks

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2014年第5期26卷 1267-1279页

作者： Yang, Bin Kaul, Manohar Jensen, Christian S. Aarhus Univ Dept Comp Sci DK-8200 Aarhus Denmark Aalborg Univ Dept Comp Sci DK-9220 Aalborg Denmark

We are witnessing increasing interests in the effective use of road networks. For example, to enable effective vehicle routing, weighted-graph models of transportation networks are used, where the weight of an edge captures some cost associated with traversing the edge, e. g., greenhouse gas (GHG) emissions or travel time. It is a precondition to using a graph model for routing that all edges have weights. Weights that capture travel times and GHG emissions can be extracted from GPS trajectory data collected from the network. However, GPS trajectory data typically lack the coverage needed to assign weights to all edges. This paper formulates and addresses the problem of annotating all edges in a road network with travel cost based weights from a set of trips in the network that cover only a small fraction of the edges, each with an associated ground-truth travel cost. A general framework is proposed to solve the problem. Specifically, the problem is modeled as a regression problem and solved by minimizing a judiciously designed objective function that takes into account the topology of the road network. In particular, the use of weighted PageRank values of edges is explored for assigning appropriate weights to all edges, and the property of directional adjacency of edges is also taken into account to assign weights. Empirical studies with weights capturing travel time and GHG emissions on two road networks (Skagen, Denmark, and North Jutland, Denmark) offer insight into the design properties of the proposed techniques and offer evidence that the techniques are effective.

关键词： Spatial databases and GIS correlation and regression analysis

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