International Journal of Computer Science & Network Security
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v.22
no.4
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pp.387-393
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2022
The article reflects short-term perspectives on the use of information and communication technologies in the training of teachers for higher education. Education is characterized by conservatism, so aspects of systematic development of the industry are relevant to this cluster of social activity. Therefore, forecasting the introduction of innovative elements of ICT training is in demand for the educational environment. Forecasting educational trends are most relevant exactly in the issues of training future teachers of higher education because these specialists are actually the first to implement the acquired professional skills in pedagogical activities. The article aims to consider the existing potential of ICT-based learning, its implementation in the coming years, and promising innovative educational elements that may become relevant for the educational space in the future. The tasks of scientific exploration are to show the optimal formats of synergy between traditional and innovative models of learning. Based on already existing experience, extrapolation of conditions of educational process organization with modeling realities of using information and communication technologies in various learning dimensions should be carried out. Educational trends for the next 3 years are a rather tentative forecast because, as demonstrated by the events associated with the COVID-19 pandemic, the socio-cultural space is very changeable. Consequently, the dynamism of the educational environment dictates the need for a value-based awareness of the information society and the practical use of technological advances. Thus, information and communication technologies are a manifestation of innovative educational strategies of today and become an important component along with traditional aspects of educational process organization. Future higher education teachers should develop a training strategy taking into account the expediency of the ICT component.
Purpose - As the U.S.-China trade war has become considerably worse, the Chinese government is considering applying non-tariff barriers to trade, especially local contents rule. The main purpose of this research is to check whether it is suitable for Korean investors to invest in the current Chinese capital market. Design/methodology - In order to check the stability of the recent Chinese capital market, we investigated the behavior of foreign equity investment (including Korean equity investment) in the Chinese capital market after China announced the Shanghai-Hong Kong Stock Connect (SH-HK Connect). In this paper, we researched whether international portfolio investment would or would not contribute to an increase the volatility of an emerging market's stock market (Chinese capital market) when foreign investors make investment decisions based on the objective of short-term gains by rushing into countries whose markets are booming and fleeing from countries whose markets are falling. Findings - The empirical results indicate that foreign investors show strong, negative feedback trading behavior with regard to the stock index of the Shanghai Stock Exchange (SSE), and when the performance of foreign investors in the Chinese stock market was fairly good. Also, we found evidence that the behavior of foreign investors significantly decreased volatility in SSE stock returns. Consequently, the SH-HK Connect brought on a win-win effect for both the Chinese capital market and foreign investors. Originality/value - It appeared that the Chinese capital market was very suitable for Korean investors after the China's declaration of the SH-HK Connect. However, the win-win effect was brought on by the Chinese government's aggressive capital control but the capital controls could possibly cause financial turmoil in the Chinese capital market. Therefore, Chinese reform in industrial structure and the financial sector should keep pace with suitable capital control policies.
Objectives: To investigate current status of randomized controlled clinical trial (RCT) registration for suicide attempters. Methods: The World Health Organization International Clinical Trials Registry Platform (WHO-ICTRP) was used to search for data using 'suicide' as a search term. All registration information of RCTs registered up to April 2023 were collected. Results: Among a total of 68 RCTs registered, the United States ranked the highest in terms of quantity in this field (n=30, 46.15%), whereas Asia had only six (8.82%). A total of 62 (91.18%) RCTs involved individual interventions, while nine (13.24%) RCTs involved group interventions. Among individual interventions, 11 (16.18%) and 54 (79.41%) RCTs were on pharmacotherapy and psychotherapy, respectively. Within psychotherapy, there were a total of 17 (25%) studies utilizing digital media, with cognitive behavioral therapy (CBT) via phone being the most common approach. Among non-digital media-based studies, CBT was used the most frequently (n=11, 16.18%), followed by attempted suicide short intervention program (n=6, 8.82%). There were no studies using interventions from East Asian traditional medicine, including Korean medicine (KM). The most frequently used main outcome was the Beck scale for suicidal ideation. Conclusions: Studies on suicide attempts in Asia, especially in South Korea, are very scarce. Despite vigorous psychotherapeutic research in this field, KM psychotherapy has not been used. Thus, KM clinical trial for suicide attempters might be planned in the future based on our findings.
Jaehyun Park;Yonghun Jang;Bok-Dong Lee;Myung-Sub Lee
Journal of the Korea Society of Computer and Information
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v.28
no.11
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pp.43-52
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2023
Rubber produced by rubber companies is subjected to quality suitability inspection through rheometer test, followed by secondary processing for automobile parts. However, rheometer test is being conducted by humans and has the disadvantage of being very dependent on experts. In order to solve this problem, this paper proposes a deep learning-based rheometer quality inspection system. The proposed system combines LSTM(Long Short-Term Memory) and CNN(Convolutional Neural Network) to take advantage of temporal and spatial characteristics from the rheometer. Next, combination materials of each rubber was used as an auxiliary input to enable quality conformity inspection of various rubber products in one model. The proposed method examined its performance with 30,000 validation datasets. As a result, an F1-score of 0.9940 was achieved on average, and its excellence was proved.
The amount of wave propagation through a rubber concrete construction is the subject of the current investigation. Rubber tire waste was used to make two different types of cement mixtures. One type contains sand substitute in amounts ranging from 15% to 60% of the total volume, while the other has gravel with diameters of 3/8 and 8/15 and 15% sand in the same mixture. A wide variety of concrete forms and compositions were created, and their viscous and solid state characteristics were assessed, along with their short-, medium-, and long-term strengths. Diffusion, density, mechanical strength resistance to compressive force, and ultrasound wave propagation were also assessed. The water-to-cement ratio and plasticizer were used in this investigation. In the second part of the study, an analytical model is presented that simulates the experimental model in predicting the speed of waves and the frequencies accompanying them for this type of mixture. Higher order shear deformation beam theory for wave propagation in the rubberized concrete beam is developed, considering the bidirectional distribution, which is primarily expressed by the density, the Poisson coefficient, and Young's modulus. Hamilton's concept is used to determine the governing equations of the wave propagation in the rubberized concrete beam structure. When the analytical and experimental results for rubber concrete beams were compared, the outcomes were very comparable. The addition of rubber gravel and sandy rubber to the mixture both resulted in a discernible drop in velocities and frequencies, according to the data.
This study applied deep convolution neural network based on U-Net and SegNet using long period weather radar data to very short-term rainfall prediction. And the results were compared and evaluated with the translation model. For training and validation of deep neural network, Mt. Gwanak and Mt. Gwangdeoksan radar data were collected from 2010 to 2016 and converted to a gray-scale image file in an HDF5 format with a 1km spatial resolution. The deep neural network model was trained to predict precipitation after 10 minutes by using the four consecutive radar image data, and the recursive method of repeating forecasts was applied to carry out lead time 60 minutes with the pretrained deep neural network model. To evaluate the performance of deep neural network prediction model, 24 rain cases in 2017 were forecast for rainfall up to 60 minutes in advance. As a result of evaluating the predicted performance by calculating the mean absolute error (MAE) and critical success index (CSI) at the threshold of 0.1, 1, and 5 mm/hr, the deep neural network model showed better performance in the case of rainfall threshold of 0.1, 1 mm/hr in terms of MAE, and showed better performance than the translation model for lead time 50 minutes in terms of CSI. In particular, although the deep neural network prediction model performed generally better than the translation model for weak rainfall of 5 mm/hr or less, the deep neural network prediction model had limitations in predicting distinct precipitation characteristics of high intensity as a result of the evaluation of threshold of 5 mm/hr. The longer lead time, the spatial smoothness increase with lead time thereby reducing the accuracy of rainfall prediction The translation model turned out to be superior in predicting the exceedance of higher intensity thresholds (> 5 mm/hr) because it preserves distinct precipitation characteristics, but the rainfall position tends to shift incorrectly. This study are expected to be helpful for the improvement of radar rainfall prediction model using deep neural networks in the future. In addition, the massive weather radar data established in this study will be provided through open repositories for future use in subsequent studies.
With the globalization of the world economy, international trade networks are expanding beyond geographical proximity, and the expansion of such trade networks is playing a role in promoting globalization. Korea has established itself as a strong FTA for the past 13 years, starting with the Korea-Chile FTA. Successful establishment of a short-term FTA network has shown positive economic effects such as increased trade volume with partner countries and market share in overseas markets. Other countries are also turning to the paradigm of economic development through the formation of a regional economic integration and a bilateral trade agreement network, and it is time to investigate new opportunities through understanding the entire RTA and FTA network. In this study, we analyzed the status of RTA and FTA from the 1960s to 2010s, analyzed network structure and centrality through SNA(social network analysis). The results of the study show that the structure of the FTA network is gradually expanding, and the FTA network, which has been expanding to the center of the early European countries, is changing toward the Asian countries such as Korea, China and Japan. As a result of the analysis of the degree of centrality, Korea was ranked as the top in all the degree of centrality(Degree, Betweenness, Closeness and Eigenvector) indicators for a short period of time and it means that Korea's FTA strategy was evaluated as very successful. This study examines the FTA among the global RTAs, assesses the structure of the FTAs and evaluates Korea's FTA strategies and the FTA network from a network perspective.
As part of the SPVS (Short-Period Variability Survey) which is a wide-field $(90'{\times}60')$ photometric monitering program at Bohyunsan Optical Astronomy (BOAO), we performed V band time-series CCD photometric observations ofthe young open cluster NGC 129 for 11 nights between October 12, 2004 and November 3, 2005 using the 155mm refractor equipped with $3K{\times}2K$ CCD camera. From the observation we obtained 2400 V band CCD frames and color-magnitude diagram of the cluster. To transform instrumental magnitude to standard magnitude, we applied ensemble normalization technique to all observed time-series data. After the photometric reduction process, we examined variations of 9537 stars. As a result, sixty six of the new variable stars were discovered. To determine the periods of the sevariables, we used DFT(Discrete Fourier Transform) and phase-matching technique. According to light curve shape, period, amplitude and the position on a C-M diagram, we classified these variables as 9 SPB type, 9 ${\delta}$ Scuti type, 29 eclipsing, 17 long term variables. However, two of them were not classified. From this study, we learned that small telescopes could be a very useful tool to observe variable stars in the open cluster in survey program.
Journal of Korean Society of Coastal and Ocean Engineers
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v.24
no.4
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pp.269-276
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2012
Salinity distribution in estuary and tidal river is presented by many parameters including tidal forcing, river discharge and geographical effect. Understanding the characteristics of salinity structure is very important in the aspect of water-quality, ecological, and engineering viewpoint. Field measurement was carried out to study the distribution of salinity structure at 2 surface stations at Yeomha channel in the Han River estuary. The results of short- and long-term salinity change according to short and long tidal variability is investigated. For analyzing the axial salinity distribution at Yeomha channel, the salinity data from NFRDI is used in this study. The relationship between freshwater discharge and salinity distribution is represented through the nonlinear regression equation. The empirical equation for salt intrusion length scale, including tide, river discharge, and topographical effect is presented. As the comparison of empirical equation and existing data collected in study area, the characteristic of salt intrusion length and salinity distribution is changed by tide, fresh water, and geographical effect.
Urbanization of the world's population has given rise to more than 450 cities around the world with populations in excess of 1 million (megacity) and more than 25 so-called metacities with populations over 10 million (Brinkhoff, 2010). The United States today has a total resident population of more than 308,500,000 people, with 81 percent residing in cities and suburbs as of mid - 2005 (UN, 2008). Urban meteorology is the study of the physics, dynamics, and chemistry of the interactions of Earth's atmosphere and the urban built environment, and the provision of meteorological services to the populations and institutions of metropolitan areas. While the details of such services are dependent on the location and the synoptic climatology of each city, there are common themes, such as enhancing quality of life and responding to emergencies. Experience elsewhere (e.g., Shanghai, Helsinki, Tokyo, Seoul, etc.) shows urban meteorological support is a key part of an integrated or multi-hazard warning system that considers the full range of environmental challenges and provides a unified response from municipal leaders. Urban meteorology has come to require much more than observing and forecasting the weather of our cities and metropolitan areas. Forecast improvement as a function of more and better observations of various kinds and as a function of model resolution, larger ensembles, predicted probability distributions; Responses of emergency managers, government officials, and users to improved and probabilistic forecasts; Benefits of improved forecasts in reduction of loss of life, property damage, and other adverse effects. A national initiative to enhance urban meteorological services is a high-priority need for a wide variety of stakeholders, including the general, commerce and industry, and all levels of government. Some of the activities of such an initiative include: conducting basic research and development; prototyping and other activities to enable very--short and short range predictions; supporting and improving productivity and efficiency in commercial and industrial sectors; and urban planning for long term sustainability. In addition urban test-beds are an effective means for developing, testing, and fostering the necessary basic and applied meteorological and socioeconomic research, and transitioning research findings to operations. An extended, multi-year period of continuous effort, punctuated with intensive observing and forecasting periods, is envisioned.
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