scholarly journals Mineração de Dados Educacionais Visando a Identificação da Evasão no Ensino Superior

2020 ◽  
Author(s):  
Guilherme Carminati ◽  
Roberto Augusto ◽  
Norberto Dallabrida ◽  
Raimundo Teive
Keyword(s):  
Data Mining ◽  
Large Scale ◽  
Engineering Students ◽  
Educational Data Mining ◽  
Private University ◽  
Mean Value ◽  
Educational Settings ◽  
Preliminary Results ◽  
The Mean

This paper tackles the problem of dropout of undergraduate studentsin a private university, by using Educational Data Mining(EDM) techniques. The EDM is an emerging area, concerned withdeveloping methods for exploring the increasingly large-scale datathat come from educational settings and using those methods tobetter understand students and the settings which they learn in. Inthis work, EDM is used to identify profiles of students who withdrawfrom their engineering courses. The considered dataset iscomposed of 53 attributes, involving financial and academic aspectsof 2,925 engineering students. Preliminary results have identifiedsome attributes that are related to the dropout in engineering courses,such as: the semester of the year (students are more prone todropout in the first half of the year), attendance, grades (in thiscase median is more important than the mean value) and numberof credits in the previous semester, and the current semester thestudent is enrolled (students bellow the 5th semester have a highertendency to dropout).

Synchronous Issue of IR-Based Large Scale Volume Localization System

2014 ◽  
Vol 496-500 ◽  
pp. 1643-1647
Author(s):  
Ying Feng Wu ◽  
Gang Yan Li
Keyword(s):  
Standard Deviation ◽  
Mobile Robot ◽  
Large Volume ◽  
Large Scale ◽  
Image Acquisition ◽  
Mean Value ◽  
Network Synchronization ◽  
Localization System ◽  
Localization Performance ◽  
The Mean

IR-based large scale volume localization system (LSVLS) can localize the mobile robot working in large volume, which is constituted referring to the MSCMS-II. Hundreds cameras in LSVLS must be connected to the control station (PC) through network. Synchronization of cameras which are mounted on different control stations is significant, because the image acquisition of the target must be synchronous to ensure that the target is localized precisely. Software synchronization method is adopted to ensure the synchronization of camera. The mean value of standard deviation of eight cameras mounted on two workstations is 12.53ms, the localization performance of LSVLS is enhanced.

Analysis of Synergies among the Ecological Factors of Farmland in a Township

2014 ◽  
Vol 556-562 ◽  
pp. 916-920
Author(s):  
Yu Huan Li ◽  
Deng Qiu Li ◽  
Jie Wu
Keyword(s):  
Large Scale ◽  
Ecological Factors ◽  
Mean Value ◽  
Small Scale ◽  
Medium Scale ◽  
Factorial Kriging ◽  
Spherical Models ◽  
Scale Range ◽  
The Mean ◽  
High Coordination

The spatial variability of single ecological factors of the farmland and the synergies among the ecological factors were studied by using geostatistical analysis and factorial kriging analysis (FKA).The results show that all of the spherical models of the co-variogram can be grouped into four parts: the nugget part, the small-scale part, the medium-scale part, and the large-scale part. The mean value of the small-scale range (1.12-1.85 km) is approximately 1.50 km, that of the medium-scale range (3.40-4.10 km) is approximately 3.8 km, and that of the large-scale range (9.35-10.10 km) is approximately 9.8 km. The correlations between each factor on the four scales vary, and the correlation between each factor on the medium scale is the strongest. In this paper, the ecological factors of the farmland on the medium scale have relatively consistent variability and sources, indicating that all of the factors on that scale have a high coordination.

scholarly journals Assessment of sagittal spinopelvic alignment in asymptomatic Chinese juveniles and adolescents: a large cohort study and comparative meta-analysis

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Canglong Hou ◽  
Kai Chen ◽  
Yu Chen ◽  
Tianjunke Zhou ◽  
Mingyuan Yang ◽  
...  
Keyword(s):  
Cohort Study ◽  
Large Scale ◽  
Meta Analysis ◽  
Mean Value ◽  
Large Cohort ◽  
Mean Values ◽  
Spinopelvic Alignment ◽  
Large Cohort Study ◽  
Sagittal Parameters ◽  
The Mean

Abstract Study design Retrospective study and comparative meta-analysis. Objective To document the sagittal spinopelvic alignment in a large cohort study in asymptomatic Chinese juveniles and adolescents, and to explore whether these parameters were different from various regions using meta-analysis. Methods Medical records of 656 asymptomatic Chinese juveniles and adolescents were reviewed, whose mean age was 13.14 ± 3.41 years old, including 254 male and 402 female volunteers. Demographic and lateral radiological parameters were evaluated. Furthermore, a systematic online search was performed to identify eligible studies. Weight mean difference (WMD) with 95% confidence interval (CI) were used to evaluate whether these sagittal parameters were different from various regions. Results The mean value of sagittal spinopelvic alignment in this study was calculated and analyzed respectively. Significant differences of PI (34.20 ± 4.00 vs. 43.18 ± 7.12, P < 0.001) and PT (3.99 ± 6.04 vs. 8.42 ± 7.08, P < 0.001) were found between juveniles and adolescents. A total of 17 studies were recruited for meta-analysis. For juvenile populations, TK, PI and SS of Caucasians were significantly larger than those of our study (all P < 0.001). As for adolescent populations, PI (P = 0.017), TK (P = 0.017) and SS (P < 0.001) of Caucasians was found to be greater when compared with that of our study. All in all, TK, PI and SS in Chinese pre-adult populations were significantly smaller than those populations in Caucasian regions (all P < 0.001). Conclusion Our study was the first large-scale study that reported the mean values of sagittal parameters in asymptomatic Chinese juveniles and adolescents. There were significant differences in TK, PI and SS between our study and other previous reported populations, which reminded us for using specific mean values in different populations when restoring a relatively normal sagittal spinopelvic balance in spinal deformity.

scholarly journals Advanced Scholastic Analytics by Implementing Data Mining Techniques

2019 ◽  
Vol 8 (12S) ◽  
pp. 95-98
Keyword(s):  
Data Mining ◽  
Association Rule ◽  
Teaching And Learning ◽  
Large Scale ◽  
Educational Data Mining ◽  
New Techniques ◽  
Job Information ◽  
Educational Environments ◽  
And Performance ◽  
Work Type

Over the past few years, the adaption of Edification management System in the sector of education has increased. Mining, clustering of essential data and finding out unique patterns from the field of education to research student’s behaviors and performance is widely recognized as Educational Data Mining (EDM) and it is a progressing profession involved with the production of new techniques for discovering distinctive and progressively large-scale information from educational environments and employing those techniques for deeper comprehend learning. It also provides an inherent understanding of teaching and learning processes for the efficient scheduling of education. This paper recommends the use of two information mining techniques in educational data. First, in admittance information, the association rule was implemented to discover some knowledge to support admission schedules. Second, a decision tree was implemented in grades and graduate student job information to estimate work type after graduation. The findings of this research provide an excellent understanding of admittance scheduling and work prediction.

scholarly journals Long-term studies of MLT summer length definitions based on mean zonal wind features observed for more than one solar cycle at mid- and high-latitudes in the northern hemisphere

2021 ◽  
Author(s):  
Juliana Jaen ◽  
Toralf Renkwitz ◽  
Jorge L. Chau ◽  
Maosheng He ◽  
Peter Hoffmann ◽  
...  
Keyword(s):  
Solar Cycle ◽  
Zonal Wind ◽  
Large Scale ◽  
Southern Oscillation ◽  
Lower Thermosphere ◽  
Polar Vortex ◽  
Mean Value ◽  
High Latitudes ◽  
The Mean

Abstract. Specular meteor radars (SMRs) and partial reflection radars (PRRs) have been observing mesospheric winds for more than a solar cycle over Germany (~54 °N) and northern Norway (~69 °N). This work investigates the mesospheric mean zonal wind and the zonal mean geostrophic zonal wind from the Microwave Limb Sounder (MLS) over these two regions between 2004 and 2020. Our study focuses on the summer when strong planetary waves are absent and the stratospheric and tropospheric conditions are relatively stable. We establish two definitions of the summer length according to the zonal wind reversals: (1) the mesosphere and lower thermosphere summer length (MLT-SL) using SMR and PRR winds, and (2) the mesosphere summer length (M-SL) using PRR and MLS. Under both definitions, the summer begins around April and ends around mid-September. The largest year to year variability is found in the summer beginning in both definitions, particularly at high-latitudes, possibly due to the influence of the polar vortex. At high-latitudes, the year 2004 has a longer summer length compared to the mean value for MLT-SL, as well as 2012 for both definitions. The M-SL exhibits an increasing trend over the years, while MLT-SL does not have a well-defined trend. We explore a possible influence of solar activity, as well as large-scale atmospheric influences (e.g. quasi-biennial oscillations (QBO), El Niño-southern oscillation (ENSO), major sudden stratospheric warming events). We complement our work with an extended time series of 31 years at mid-latitudes using only PRR winds. In this case, the summer length shows a breakpoint, suggesting a non-uniform trend, and periods similar to those known for ENSO and QBO.

Material content of the Universe: meeting summary

1986 ◽  
Vol 320 (1556) ◽  
pp. 609-611
Keyword(s):  
Cosmological Model ◽  
Mass Distribution ◽  
Large Scale ◽  
Mean Value ◽  
De Sitter ◽  
Cosmic Evolution ◽  
Broad Variety ◽  
The Mean ◽  
The Universe ◽  
General Synthesis

We have considered what might be said about the large-scale distribution of mass in the Universe and in particular whether the mean value might agree with the Einstein-de Sitter cosmological model; what might be said about the composition of the mass as a function of position, and in particular whether we can convince ourselves that exotic matter plays a significant role in some regions; and what might be said about the cosmic evolution of the mass distribution and composition. The present state of our debate is notable for the broad variety of interesting-looking clues and the lack of general agreement on how they might fit together in some general synthesis.

Learning Analytics and Education Data Mining in Higher Education

2021 ◽  
pp. 108-126
Author(s):  
Samira ElAtia ◽  
Donald Ipperciel
Keyword(s):  
Higher Education ◽  
Data Mining ◽  
Big Data ◽  
Learning Analytics ◽  
Large Scale ◽  
Educational Data Mining ◽  
Current Situation ◽  
Research Perspective ◽  
Education Data ◽  
The Impact

In this chapter, the authors propose an overview on the use of learning analytics (LA) and educational data mining (EDM) in addressing issues related to its uses and applications in higher education. They aim to provide meaningful and substantial answers to how both LA and EDM can advance higher education from a large scale, big data educational research perspective. They present various tasks and applications that already exist in the field of EDM and LA in higher education. They categorize them based on their purposes, their uses, and their impact on various stakeholders. They conclude the chapter by critically analyzing various forecasts regarding the impact that EDM will have on future educational setting, especially in light of the current situation that shifted education worldwide into some form of eLearning models. They also discuss and raise issues regarding fundamentals consideration on ethics and privacy in using EDM and LA in higher education.

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