scholarly journals Improvements in Evaluating Grids for Basic Living Infrastructure: The Case of Gwangjin District in Seoul, South Korea

2021 ◽  
Vol 10 (1) ◽  
pp. 26
Author(s):  
Wooseok Kang ◽  
Narang Park ◽  
Wookjae Heo
Keyword(s):  
South Korea ◽  
Prediction Accuracy ◽  
Urban Policy ◽  
Absolute Error ◽  
Influential Factors ◽  
Current Status ◽  
Minimum Standard ◽  
Squared Error ◽  
Geographic Datasets ◽  
Basic Level

The purpose of this study was to analyze the current status and needs of infrastructure for basic life in Gwangjin district in Seoul, South Korea. In this study, we examined whether the national minimum standard was satisfied in terms of the infrastructure for basic life in the district. Specifically, we employed and compared the empirical utilities of two types of geographic datasets, 100-square-meter grids and 500-square-meter grids. The study compares the prediction accuracy between two types of geographic datasets by employing multivariate linear estimation using influential factors. The evaluation methods for prediction accuracy were to compare the root mean of squared error (RMSE) and mean of absolute error (MAE) from each dataset. The results were as follows: (a) the dataset with 100-square-meter grids showed more significant associations among influential factors and the infrastructure than the dataset with 500-square-meter grids; (b) the 100-square-meter grids showed better prediction accuracy compared with the 500-square-meter grids; and (c) in terms of basic level local government, it was more powerful to use the datasets with 100-square-meter grids for finding blind sides of infrastructure than the datasets with 500-square-meter grids. The results imply that it is necessary to adjust urban policy by using appropriate datasets, such as 100-square-meter grids.

scholarly journals A Novel Computational Intelligence Approach for Coal Consumption Forecasting in Iran

2021 ◽  
Vol 13 (14) ◽  
pp. 7612
Author(s):  
Mahdis sadat Jalaee ◽  
Alireza Shakibaei ◽  
Amin GhasemiNejad ◽  
Sayyed Abdolmajid Jalaee ◽  
Reza Derakhshani
Keyword(s):  
Hybrid Method ◽  
Computational Intelligence ◽  
Energy Demand ◽  
Mean Squared Error ◽  
Absolute Error ◽  
Coal Consumption ◽  
Squared Error ◽  
Artificial Neural ◽  
Socio Economic Variables ◽  
Intelligence Approach

Coal as a fossil and non-renewable fuel is one of the most valuable energy minerals in the world with the largest volume reserves. Artificial neural networks (ANN), despite being one of the highest breakthroughs in the field of computational intelligence, has some significant disadvantages, such as slow training, susceptibility to falling into a local optimal points, sensitivity of initial weights, and bias. To overcome these shortcomings, this study presents an improved ANN structure, that is optimized by a proposed hybrid method. The aim of this study is to propose a novel hybrid method for predicting coal consumption in Iran based on socio-economic variables using the bat and grey wolf optimization algorithm with an artificial neural network (BGWAN). For this purpose, data from 1981 to 2019 have been used for modelling and testing the method. The available data are partly used to find the optimal or near-optimal values of the weighting parameters (1980–2014) and partly to test the model (2015–2019). The performance of the BGWAN is evaluated by mean squared error (MSE), mean absolute error (MAE), root mean squared error (RMSE), standard deviation error (STD), and correlation coefficient (R^2) between the output of the method and the actual dataset. The result of this study showed that BGWAN performance was excellent and proved its efficiency as a useful and reliable tool for monitoring coal consumption or energy demand in Iran.

scholarly journals Estimating Physical Activity Energy Expenditure Using an Ensemble Model-Based Patch-Type Sensor Module

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 861
Author(s):  
Kyeung Ho Kang ◽  
Mingu Kang ◽  
Siho Shin ◽  
Jaehyo Jung ◽  
Meina Li
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Mean Squared Error ◽  
Absolute Error ◽  
Ensemble Model ◽  
Direct Calorimetry ◽  
Patch Type ◽  
Mortality And Morbidity ◽  
Squared Error ◽  
Sensor Module

Chronic diseases, such as coronary artery disease and diabetes, are caused by inadequate physical activity and are the leading cause of increasing mortality and morbidity rates. Direct calorimetry by calorie production and indirect calorimetry by energy expenditure (EE) has been regarded as the best method for estimating the physical activity and EE. However, this method is inconvenient, owing to the use of an oxygen respiration measurement mask. In this study, we propose a model that estimates physical activity EE using an ensemble model that combines artificial neural networks and genetic algorithms using the data acquired from patch-type sensors. The proposed ensemble model achieved an accuracy of more than 92% (Root Mean Squared Error (RMSE) = 0.1893, R2 = 0.91, Mean Squared Error (MSE) = 0.014213, Mean Absolute Error (MAE) = 0.14020) by testing various structures through repeated experiments.

scholarly journals A hybrid recommender system based-on link prediction for movie baskets analysis

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mohammadsadegh Vahidi Farashah ◽  
Akbar Etebarian ◽  
Reza Azmi ◽  
Reza Ebrahimzadeh Dastjerdi
Keyword(s):  
Recommender System ◽  
Link Prediction ◽  
Mean Squared Error ◽  
Spatial Clustering ◽  
Randomized Algorithm ◽  
Similarity Criterion ◽  
Absolute Error ◽  
Similarity Criteria ◽  
Online Systems ◽  
Squared Error

AbstractOver the past decade, recommendation systems have been one of the most sought after by various researchers. Basket analysis of online systems’ customers and recommending attractive products (movies) to them is very important. Providing an attractive and favorite movie to the customer will increase the sales rate and ultimately improve the system. Various methods have been proposed so far to analyze customer baskets and offer entertaining movies but each of the proposed methods has challenges, such as lack of accuracy and high error of recommendations. In this paper, a link prediction-based method is used to meet the challenges of other methods. The proposed method in this paper consists of four phases: (1) Running the CBRS that in this phase, all users are clustered using Density-based spatial clustering of applications with noise algorithm (DBScan), and classification of new users using Deep Neural Network (DNN) algorithm. (2) Collaborative Recommender System (CRS) Based on Hybrid Similarity Criterion through which similarities are calculated based on a threshold (lambda) between the new user and the users in the selected category. Similarity criteria are determined based on age, gender, and occupation. The collaborative recommender system extracts users who are the most similar to the new user. Then, the higher-rated movie services are suggested to the new user based on the adjacency matrix. (3) Running improved Friendlink algorithm on the dataset to calculate the similarity between users who are connected through the link. (4) This phase is related to the combination of collaborative recommender system’s output and improved Friendlink algorithm. The results show that the Mean Squared Error (MSE) of the proposed model has decreased respectively 8.59%, 8.67%, 8.45% and 8.15% compared to the basic models such as Naive Bayes, multi-attribute decision tree and randomized algorithm. In addition, Mean Absolute Error (MAE) of the proposed method decreased by 4.5% compared to SVD and approximately 4.4% compared to ApproSVD and Root Mean Squared Error (RMSE) of the proposed method decreased by 6.05 % compared to SVD and approximately 6.02 % compared to ApproSVD.

Mismatches Between the Number of Installed Automated External Defibrillators and the Annual Rate of Automated External Defibrillator Use Among Places

2021 ◽  
pp. 1-6
Author(s):  
Je Hyeok Oh ◽  
Gyu Chong Cho ◽  
Seung Mok Ryoo ◽  
So Hyun Han ◽  
Seon Hee Woo ◽  
...  
Keyword(s):  
South Korea ◽  
Medical Center ◽  
Annual Rate ◽  
Current Status ◽  
Automated External Defibrillator ◽  
Automated External Defibrillators ◽  
The Law ◽  
National Emergency ◽  
Apartment Complexes ◽  
External Defibrillator

Abstract Aim: In South Korea, the law concerning automated external defibrillators (AEDs) states that they should be installed in specific places including apartment complexes. This study was conducted to investigate the current status and effectiveness of installation and usage of AEDs in South Korea. Methods: Installation and usage of AEDs in South Korea is registered in the National Emergency Medical Center (NEMC) database. Compared were the installed number, usage, and annual rate of AED use according to places of installation. All data were obtained from the NEMC database. Results: After excluding AEDs installed in ambulances or fire engines (n = 2,003), 36,498 AEDs were registered in South Korea from 1998 through 2018. A higher number of AEDs were installed in places required by the law compared with those not required by the law (20,678 [56.7%] vs. 15,820 [43.3%]; P <.001). Among them, 11,318 (31.0%) AEDs were installed in apartment complexes. The overall annual rate of AED use was 0.38% (95% CI, 0.33-0.44). The annual rate of AED use was significantly higher in places not required by the law (0.62% [95% CI, 0.52-0.72] versus 0.21% [95% CI, 0.16-0.25]; P <.001). The annual rate of AED use in apartment complexes was 0.13% (95% CI, 0.08-0.17). Conclusion: There were significant mismatches between the number of installed AEDs and the annual rate of AED use among places. To optimize the benefit of AEDs in South Korea, changes in the policy for selecting AED placement are needed.

Current Status and Future Prospects for Harvesting and Resource Management of the Agarophyte in Japan

1976 ◽  
Vol 33 (4) ◽  
pp. 1024-1030 ◽  
Author(s):  
Nobuo Yamada
Keyword(s):  
Resource Management ◽  
South Korea ◽  
Conservation Management ◽  
Resource Conservation ◽  
Current Status ◽  
Future Prospects ◽  
Annual Output ◽  
The Usa

Agar-agar manufacturing was Japan’s monopoly for about 300 yr from 1644 until about 1920, when its production was initiated in the USA by introducing techniques from Japan, and then was begun in South Korea, Indonesia, and many other countries. Today the average annual output of agar-agar of over 20 countries amounts to 6000 tons, half of which is produced in Japan.Agarophytes are harvested in many countries and traded among them. In Japan, nearly 14,000 tons are consumed in a year, two thirds of which are imported from about 20 countries.Under these circumstances, there is a worldwide demand for appropriate measures for resource conservation, effective harvesting, and utilization of agarophytes.This paper presents the results of basic and applied investigations on the agarophytes and the existing state of harvesting and resource-conservation management in Japan.

The Profession of Family Therapy in South Korea: Current Status and Future Directions

2013 ◽  
Vol 35 (2) ◽  
pp. 388-399 ◽  
Author(s):  
Sun Hae Lee ◽  
Young Ju Chun ◽  
Hyejeong Chung ◽  
Sun In Shin ◽  
Insoo Lee ◽  
...  
Keyword(s):  
Family Therapy ◽  
South Korea ◽  
Current Status ◽  
Future Directions

Current status of design basis earthquake level for nuclear power plant sites in several countries

2021 ◽  
Author(s):  
Hoseon Choi ◽  
Seung Gyu Hyun
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
South Korea ◽  
Seismic Activity ◽  
Nuclear Power ◽  
Current Status ◽  
Seismic Safety ◽  
Design Basis ◽  
Design Earthquake ◽  
Design Construction

&lt;p&gt;According to strict criteria step by step for site selection, design, construction and operation, the seismic safety of nuclear power plant (NPP) sites in South Korea are secured by considering design basis earthquake (DBE) level capable of withstanding the maximum ground motions that can occur on the site. Therefore, it is intended to summarize DBE level and its evaluation details for NPP sites in several countries.&lt;/p&gt;&lt;p&gt;Similar but different terms are used for DBE from country to country, i.e. safe shutdown earthquake (SSE), design earthquake (DE), SL2, Ss, and maximum calculated earthquake (MCE). They may differ when applied to actual seismic design process, and only refer to approximate comparisons. This script used DBE as a representative term, and DBE level was based on horizontal values.&lt;/p&gt;&lt;p&gt;The DBE level of NPP sites depends on seismic activity of the area. Japan and Western United States, where earthquakes occur more frequently than South Korea, have high DBE values. The DBE level of NPP sites in South Korea has been confirmed to be similar or higher compared to that of Central and Eastern Unites Sates and Europe, which have similar seismic activity.&lt;/p&gt;

Measuring The Tensile Strain of Wood By Visible And Near-Infrared Spatially Resolved Spectroscopy

2021 ◽  
Author(s):  
Ma Te ◽  
Tetsuya Inagaki ◽  
Masato Yoshida ◽  
Mayumi Ichino ◽  
Satoru Tsuchikawa
Keyword(s):  
Light Scattering ◽  
Prediction Accuracy ◽  
Tensile Strain ◽  
Near Infrared ◽  
Mean Squared Error ◽  
Calibration Model ◽  
Spatially Resolved ◽  
Squared Error ◽  
Stiffness Evaluation ◽  
Spatially Resolved Spectroscopy

Abstract Wood has various mechanical properties, so stiffness evaluation is critical for quality management. Using conventional strain gauges constantly is high cost, also challenging to measure precious wood materials due to the use of strong adhesive. This study demonstrates the correlation between light scattering changes inside the wood cell walls and tensile strain. A multifiber-based visible-near-infrared (Vis–NIR) spatially resolved spectroscopy (SRS) system was designed to rapidly and conventiently acquire such light scattering changes. For the preliminary experiment, samples with different thicknesses were measured to evaluate the influence of thickness. The differences in Vis–NIR SRS spectral data diminish with an increase in sample thickness, which suggests that the SRS method can successfully measure the whole strain (i.e., surface and inside) of wood samples. Then, for the primary experiment, 18 wood samples with the same thickness (2 mm) were tested to construct a strain calibration model. The prediction accuracy was characterized by a determination coefficient (R2) of 0.86 with a root mean squared error (RMSE) of 297.89 με for five-fold cross-validation; for test validation, The prediction accuracy was characterized by an R2 of 0.82 and an RMSE of 345.44 με.

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