• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.690-693
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• 2022

In this study, we used wine data to perform correlation analysis on factors that affect wine quality, and predicted wine quality standards based on the results. The dataset used in this study used data from 1599 red wines and 4898 white wines produced in Vinho verde, Portugal, for a total of 6497. The variable items are 12 kinds of component variables that represent wine components through physical and chemical analysis tests, a total of 1599 observations, and a total of one of the representative wines of the three major wine producing regions in the world (France, Italy, Spain). Added 3 pieces. Analysis was made by applying national climate change data.

• Geomechanics and Engineering
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• v.33 no.6
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• pp.611-624
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• 2023

Soil properties make it attractive as a building material due to its mechanical strength, aesthetically appearance, plasticity, and low cost. However, it is frequently necessary to improve and stabilize the soil mechanical properties with binders. Soil-cement is applied for purposes ranging from housing to dams, roads and foundations. Unconfined compression strength (UCS) and split tensile strength (CD) are essential mechanical parameters for ascertaining the aptitude of soil-cement for a given application. However, quantifying these parameters requires specimen preparation, testing, and several weeks. Methodologies that allowed accurate estimation of mechanical parameters in shorter time would represent an important advance in order to ensure shorter deliverable timeline and reduce the amount of laboratory work. In this work, an extensive campaign of UCS and CD tests was carried out in a sandy soil from the Leiria region (Portugal). Then, using the machine learning tool Neural Pattern Recognition of the MATLAB software, a prediction of these two parameters based on six input parameters was made. The results, especially those obtained with resource to a Bayesian regularization-backpropagation algorithm, are frankly positive, with a forecast success percentage over 90% and very low root mean square error (RMSE).

• Iberoamérica
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• v.12 no.1
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• pp.241-265
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• 2010

The main purpose of this study is to reveal the historical origins of Latin American economic underdevelopment, by answering two research questions; 1)'Why is Latin America underdeveloped?' and 2)'How has colonial experience impacted on the economic growth in Latin America?' First, this essay analyzes long-term tendency of growth domestic product(GDP) per capita data. The data verify that current underdevelopment of Latin American economy is the result of economic stagnation during the eighteenth and nineteenth centuries, when Latin America suffered political and economic instability before and after the independence from Spain and Portugal. It elucidates that colonial experience affected on the economic growth in Latin America. Second, this essay reviews key independent variables of the relationship between colonial experience and economic growth in Latin America. To do so, the study categorizes extant literature into two groups according to the type of its independent variables: 1)internal factor and 2)external factor. Finally, the essay surveys the role of institutions in Latin American economic growth and development. The survey confirms that the importance of institutions in the study of Latin American economic history. In addition, the essay suggests some tasks for further research in Latin American economic history; 1)the construction of basic economic data, 2)the substantialization of the role and characteristics of institutions, and 3)the expansion of research on institutions which overcomes ideological rigidity of existing institutional approach.

• Journal of Korean Clinical Health Science
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• v.11 no.1
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• pp.1632-1638
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• 2023

Purpose: The aim of this study was to determine the distribution of the cornea thickness and intra ocular pressure Korean adult of 20 to 24 year old using the Pentacam and tonometer. Methods: The subjects of this study were 43 Korean adults with healthy eyes. Corneal thickness was measured with Pentacam device. The intra ocular pressure was measured with tonometer. Data was analyzed by means of the Pearson's correlation cofficient. P-values<0.001 were considered statistically significant. Results: Mean age of subjects was 20.41±0.86 years. The mean +/- intra ocular pressure of the right eye and left eye were 16.236±2.523mmHg and 16.971±1.992mmHg, respectively. The mean central corneal thickness of the right eye and left eye was 545.324±38.682㎛ and 547.442±33.778㎛, respectively. No significant difference in central corneal thickness was found between the right and left eyes. But, there was a statistically significant difference between central cornea thickness and peripheral cornea thickness around 4 mm of central cornea(p<0.001, Pearson's correlation). However there was no statistically significant difference between central cornea thickness and intra ocular pressure. Conclusion: The results of this study could be used as a clinical reference data for diagnosis and treatment of cornea in Korean adult.

• The korean journal of orthodontics
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• v.54 no.5
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• pp.274-283
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• 2024

Objective: To determine the correlation between dentoskeletal parameters related to craniofacial morphology and the upper airway (UA) volume. Methods: Cone-beam computed tomography images of 106 randomly selected orthodontic patients were analyzed using NemoFab Ortho software. The dentoskeletal variables assessed were anterior facial height (AFH), posterior facial height (PFH), PFH/AFH ratio, hyoid position, maxillary width (MW), and palatal depth. The UA volume (evaluation in anatomical regions and as a whole) was also assessed using the same software. We also evaluated potential differences in UA variables between age and sex groups. The correlation between the dentoskeletal parameters and UA volume was calculated using the Pearson correlation coefficient (R). Analysis of variance and Student's t test were performed to assess differences between age and sex for UA variables. Statistical analyses were performed using SPSS software (version 26 for Windows). Results: This study found that PFH, AFH, and MW were the dentoskeletal parameters most strongly correlated with UA volume. However, the ANB angle did not show any significant correlation with UA volume. Additionally, differences in UA volumes were observed between age groups. Sex differences were found in both the "8-12" and "≥ 16" age groups for oropharyngeal and pharyngeal volumes. Conclusions: In conclusion, our findings indicate a significant correlation between UA volume and dentoskeletal parameters, particularly those related to facial height and MW.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.5
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• pp.51-58
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• 2012

Accurate transmission and estimation of the channel statistics affected by high Doppler spread is one of the main issues of concern for the latest and future mobile communication systems. Therefore, it is important to research in novel channel estimation techniques that overcome the limitations of conventional methods. In this paper, we propose a novel channel estimation method that, after a simple estimation in the first OFDM symbol, uses Kalman filter to predict the channel in the rest of OFDM symbols with pilot subcarriers. Our method is designed considering the lattice-type arrangement of pilot subcarriers in LTE-Advanced, since most of the studies so far focus on block-type or comb-type pilot arrangements. In addition, to optimize the results, we use the filtering of channel impulse response and Wiener Filter for the estimation of the channel frequency response in the rest of the subcarriers.

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.7
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• pp.1108-1114
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• 2007

Twenty eight non-lactating and non-pregnant adult Serra da Estrela ewes, ranging in body condition score (BCS) from 1 to 4 were used to study the relationships between BCS, live weight (LW), body composition and fat partition. Ewes were slaughtered and their kidney knob and channel fat (KKCF), sternal fat (STF) and omental plus mesenteric fat (OMF) were separated and weighed. Left sides of carcasses as well as the respective lumbar joints were then dissected into muscle, bone and subcutaneous (SCF) and intermuscular fat (IMF). The relationship between LW and BCS was studied using data from 1,396 observations on 63 ewes from the same flock and it was found to be linear. Regression analysis was also used to describe the relationships among BCS and/or LW and weights (kg) and percentages in empty body weight (EBW) of dissected tissues. The prediction of weights and percentages in EBW of total fat (TF) and of all fat depots afforded by BCS was better than that provided by LW. Only the weight of muscle and the percentage of bone in the EBW were more efficiently predicted by LW than by BCS. IMF represented the largest fat depot with a BCS of 1 and 2, whereas SCF was the most important site of fat deposition with a BCS of 3 and 4. Allometric coefficients for each fat depot in TF suggest that the fat deposition order in ewes from this breed is: IMF, OMF, SCF and KKCF. Results demonstrate that BCS is a better predictor than LW of body reserves in this breed and that LJ is a suitable anatomical region to evaluate BCS.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.3
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• pp.13-18
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• 2011

Sphere Decoding (SD) is a decoding technique able to achieve the Maximum Likelihood (ML) performance in fading environments; nevertheless, the main disadvantage of this technique is its high complexity, especially in poor channel conditions. In this paper, we present an adaptive hybrid algorithm which reduces the conventional Sphere Decoder's complexity and keeps the ML performance. The system called Adaptive OSIC-SD modifies its operation based on Signal to Noise Ratio (SNR) information and achieves an optimal performance in terms of Bit Error Rate (BER) and complexity. Through simulations, we probe that the proposed system maintains almost the same bit error rate performance of the conventional SD, and exhibits a lower, quasi-constant complexity.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.5 no.1
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• pp.17-22
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• 1972

This results concerning the growth of transplanting of the oyster seed, Crassostrea angulata and Ostrea Iurida, which were transplanted from Japan by air, and cultivated by the raft suspended method at the coast of Yeongoo-Ri, Koje-Goon, located on the southern coast of Korea from January to December 1970, are as follows, 1. The mean shell height of O. lurida was 36.4mm, and the shape of the shell was round and small. On the other hand, the mean shell height of C. angulata was 87.4mm and the shell length was 52.3mm, and the shape of the shell was oval and large, 2. O. lurida and C. angulata oysters grew well when the water temperature was above $16^{\circ}C$ and the specific gravity ranged from 1.0171 to 1.0236 from June to July. 3. There was a little difference in relative valiance between shell length and height of O, lurida but significant difference was shown in C. angulata from July to November. 4. The mortality rate of O. lurida was $35.2\%$ and that of C. angulata was $21.7\%$ respectively.

• Journal of KIISE
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• v.44 no.7
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• pp.686-691
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• 2017

Telemarketing has become the center of marketing action of the industry in the information society. Recently, machine learning has emerged in many areas, especially, financial prediction. Financial data consists of lots of unlabeled data in most parts, and therefore, it is difficult for humans to perform their labeling. In this paper, we propose a fusion method of semi-supervised learning for automatic labeling of unlabeled data to predict telemarketing. Specifically, we integrate labeling results of label propagation and co-training with a decision tree. The data with lower reliabilities are removed, and the data are extracted that have consistent label from two labeling methods. After adding them to the training set, a decision tree is learned with all of them. To confirm the usefulness of the proposed method, we conduct the experiments with a real telemarketing dataset in a Portugal bank. Accuracy of the proposed method is 83.39%, which is 1.82% higher than that of the conventional method, and precision of the proposed method is 19.37%, which is 2.67% higher than that of the conventional method. As a result, we have shown that the proposed method has a better performance as assessed by the t-test.