• International Journal of Computer Science & Network Security
• /
• v.22 no.10
• /
• pp.246-256
• /
• 2022

Recently, parents and teachers consider physical education as a minor subject for students in elementary and secondary schools. Physical education performance has become increasingly significant as parents and schools pay more attention to physical schooling. The sports mining with distribution analysis model considers different factors, including the games, comments, conversations, and connection made on numerous sports interests. Using different machine learning/deep learning approach, children's athletic and academic interests can be tracked over the course of their academic lives. There have been a number of studies that have focused on predicting the success of students in higher education. Sports interest prediction research at the secondary level is uncommon, but the secondary level is often used as a benchmark to describe students' educational development at higher levels. An Automated Student Interest Prediction on Sports Mining using DL Based Bi-directional Long Short-Term Memory model (BiLSTM) is presented in this article. Pre-processing of data, interest classification, and parameter tweaking are all the essential operations of the proposed model. Initially, data augmentation is used to expand the dataset's size. Secondly, a BiLSTM model is used to predict and classify user interests. Adagrad optimizer is employed for hyperparameter optimization. In order to test the model's performance, a dataset is used and the results are analysed using precision, recall, accuracy and F-measure. The proposed model achieved 95% accuracy on 400^th instances, where the existing techniques achieved 93.20% accuracy for the same. The proposed model achieved 95% of accuracy and precision for 60%-40% data, where the existing models achieved 93% for accuracy and precision.

• International Commerce and Information Review
• /
• v.11 no.3
• /
• pp.363-390
• /
• 2009

This study investigates the role of private participation in FTA Negotiation in case of US, Mexico and Japan. We utilize Putnam(1988)'s two stage negotiation model, Schelling Conjecture and Principal-Agent(P-A) theory to understand the role of private sector in FTA Negotiation. Those theories are useful to understand the behavior and interaction of key players such as private sector, congress and government in FTA negotiation. Putnam(1988)'s two stage negotiation model divides the FTA negotiation process into two processes: the external negotiation with foreign country and domestic negotiation with domestic interest group. Principal-Agent(P-A) theory provides the theoretical foundation of Putnam's two stage negotiation model, which is that principal's interest is not identical to the interest of Agent. We showed that the private sector and congress play an important role in FTA negotiation in United States. In case of Mexico, the private sector and government occupy the dominant position in FTA negotiation. In particular, the cooperation of industry and government has been successfully established via COECE in Mexico. In contrast to these countries, the role of private participation in trade policy is relatively low in Japan and Korea.

• International journal of advanced smart convergence
• /
• v.10 no.3
• /
• pp.72-80
• /
• 2021

Metaverse is an immersive 3D virtual environment, a true virtual artificial community in which avatars act as the user's alter ego and interact with each other. If we do not manage the hype for the metaverse, which has recently been receiving a surge in interest, the metaverse will fail to cross the chasm. In this study, to provide stakeholders with insights for the successful introduction and growth of the 3D immersive next-generation virtual world, metaverse, we analyzed user-side interest, media-side interest, and research-side interest. For this purpose, in this study, search traffic, news frequency and topic, and research article frequency and topic were analyzed. The methodology and results of this study are expected to provide insight for the stable success of metaverse transformation and the coexistence of the real world and the virtual world through hyper-connection and hyper-convergence.

• Management & Information Systems Review
• /
• v.3
• /
• pp.77-97
• /
• 1999

The purpose of this paper is to measure the international competitiveness of insurance business and to analyze its determinants empirically. I have attempted to use Revealed Comparative Advantage(RCA) index to measure domestic competitiveness. confining to OECD countries only. Among domestic competitiveness advantage countries in the insurance, there are Austria, Denmark, France. Japan, Korea... etc. The factors of domestic competitiveness determinants were found out through multivariate regression analysis with panel data$(1990{\sim}1995)$. In insurance industry, statistically significant variables are employee's per capita premium of insurance company (Pro), stock market capitalization/GDP(MVESR), saving rate (SAV) and real interest(RMMR), while they are Pro, MVESR, and real interest in Korea insurance industry.

• International Journal of Advanced Culture Technology
• /
• v.7 no.1
• /
• pp.84-88
• /
• 2019

This paper examines whether the exchange rate respond differently to monetary policy shocks in Korea using regression model. We find an asymmetric response of the monetary policy shocks to the monetary policy shocks in the context of Korea. Over the whole period sample, we do not find the effect of an actual interest rate on exchange rate. But we find that the estimated coefficient on the expected and unexpected change in the policy rate are negative and statistically significant. In the period of monetary policy easing, the estimated coefficient on the expected and unexpected change in the policy rate are negative but not statistically significant. In contrast, the period of monetary policy tightening, the estimated coefficient on the expected and unexpected change in the policy rate are negative and statistically significant.

• International Journal of Computer Science & Network Security
• /
• v.22 no.3
• /
• pp.45-52
• /
• 2022

To make the research and development in IoT networks witness a significant improvement and last for a long period, it is always important to attract new researchers to work on this area and be a part of it. The best way to attract researchers to work in any research area and have their interest is to give them a clear background and roadmap about it. In this way, researchers can easily find a deep point to start their research based on their interest. This paper presents an overview and roadmap about IoT technologies from the most five vital aspects: IoT architecture, communication technologies, type of IoT applications, IoT applications protocols and IoT challenges.

• International Journal of Computer Science & Network Security
• /
• v.22 no.5
• /
• pp.1-4
• /
• 2022

The growth in global population and industrialization has led to an increasing demand for electricity. Accordingly, the electricity providers need to increase the electricity generation. Due to the economical and environmental concerns associated with the generation of electricity from fossil fuels. Alternative power recourses that can potentially mitigate the economical and environmental are of interest. Renewable energy resources are promising recourses that can participate in producing power. Among renewable power resources, solar energy is an abundant resource and is currently a field of research interest. Photovoltaic solar power is a promising renewable energy resource. The power output of PV systems is mainly affected by the solar irradiation and ambient temperature. this paper investigates the utilization of machine learning unsupervised neural network techniques that potentially improves the reliability of PV solar power systems during integration into the electrical grid.

• International Journal of Contents
• /
• v.2 no.1
• /
• pp.5-8
• /
• 2006

This paper describes a new mechanism of detecting object of interest from a noisy image, without using any a-priori knowledge about the target. It employs a parallel set of filters inspired upon biological findings of mammalian vision. In our proposed system, several basic features are extracted directly from original input visual stimuli, and these features are integrated based on their local competitive relations and statistical information. Through integration process, unnecessary features for detecting the target are spontaneously decreased, while useful features are enhanced. Experiments have been performed on a set of computer generated and real images corrupted with noise.

• The Journal of Asian Finance, Economics and Business
• /
• v.6 no.3
• /
• pp.103-113
• /
• 2019

The effectiveness of monetary policy critically depends upon how well the transmission mechanism functions, so that the desired impact on output and inflation is achieved. The purpose of this paper is to study the transmission mechanism of monetary policy by analyzing the impact on inflation and output during multiple indicator regime (1998-99 to 2014) in an emerging economy-India. The Inflation Targeting Regime is also briefly outlined alongwith the impact on output and inflation. Using quarterly data for the period 1997 to 2017, the paper uses weighted average call money market rate as a proxy for the policy rate and evaluates the strength of the interest rate channel. We use a conventional Structural vector auto regression (SVAR) methodology to evaluate the efficacy and show the impluse response functions. Our results find that changes in the policy rate impact output growth steeply with a lag of about two quarters and the impact on inflation is maximized after three quarters. The study concludes that the monetary policy in India has a significant impact on output and inflation in the short-to-medium-run. After the policy shock, the fall in the output growth rate is of greater magnitude than the fall in inflation.

• Journal of Environmental Science International
• /
• v.23 no.12
• /
• pp.1977-1985
• /
• 2014

Many countries around the world are amplifying interest and studies on irrigation, flood control and environment with concern on serious water problems. Especially for irrigation in water supply vulnerable areas such as coastal areas - islands, business on underwater resource security facilities are promoted to secure stable water resources due to development of society and increase of life quality. Also, various policies such as reuse of leaking underwater, utilization of underwater at waterfront, and artificial recharge, etc are planned and designed. In order to develop small sized underwater resource secure technology, verification of seawater-freshwater interface is executed and how the balance between these will develop is a great interest of coastal areas - islands. In this study, seawater-freshwater interface behavior analysis experiment was conducted while reflecting properties of coastal areas - islands and executed hydraulic similitude of saltwater intrusion form control technology on abstraction.