• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.41 no.3
• /
• pp.154-161
• /
• 2018

This study conducted to predict the stock market prices based on the assumption that internet news articles might have an impact and effect on the rise and fall of stock market prices. The internet news articles were tested to evaluate the accuracy by comparing predicted values of the actual stock index and the forecasting models of the companies. This paper collected stock news from the internet, and analyzed and identified the relationship with the stock price index. Since the internet news contents consist mainly of unstructured texts, this study used text mining technique and multiple regression analysis technique to analyze news articles. A company H as a representative automobile manufacturing company was selected, and prediction models for the stock price index of company H was presented. Thus two prediction models for forecasting the upturn and decline of H stock index is derived and presented. Among the two prediction models, the error value of the prediction model (1) is low, and so the prediction performance of the model (1) is relatively better than that of the prediction model (2). As the further research, if the contents of this study are supplemented by real artificial intelligent investment decision system and applied to real investment, more practical research results will be able to be developed.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.12
• /
• pp.819-829
• /
• 2020

This empirical research is aimed at testing the relationship of the big five personality traits namely openness to experience, extraversion, consciousness, agreeableness, neuroticism, and risk aversion with the investment intention of individual investors belonging to Balochistan, Pakistan. The primary data is collected through a self-administered questionnaire (a structured form that consists of a series of closed-ended and open-ended questions) from a sample of 397 active individual investors belonging to different districts of the province. The data is empirically analyzed by applying the Partial Least Square (PLS) path modeling technique by using the estimation package available in Smart-PLS. The findings of this study suggest that all the variables are statistically significant with investors' investment intention with risk aversion as the strongest predictor. Moreover, openness to experience, extraversion, consciousness, agreeableness, and risk are significantly and positively related to an investor's investment intention, whereas neuroticism is negatively related to an investor's investment intention. The results extended by this study can be used by financial planners and investment bankers to channelize the available financial resources in diversified portfolios. The results will help financial planners to make available diverse investment alternatives for investors in Balochistan, thus catering to their unique needs. Academia must offer courses on contemporary finance paradigm based on behavioral finance to enable future business graduates to make wise financial decisions.

• Smart Media Journal
• /
• v.11 no.4
• /
• pp.9-18
• /
• 2022

Recently, research and system using AI is rapidly increasing in various fields. Smart farm using artificial intelligence and information communication technology is also being studied in agriculture. In addition, data-based precision agriculture is being commercialized by convergence various advanced technology such as autonomous driving, satellites, and big data. In Korea, the number of commercialization cases of facility agriculture among smart agriculture is increasing. However, research and investment are being biased in the field of facility agriculture. The gap between research and investment in facility agriculture and open-air agriculture continues to increase. The fields of fruit trees and plant factories have low research and investment. There is a problem that the big data collection and utilization system is insufficient. In this paper, we are proposed the system for determining the fruit tree growth stage using a deep learning-based object detection model. The system was proposed as a hybrid app for use in agricultural sites. In addition, we are implemented an object detection function for the fruit tree growth stage determine.

• Korean Journal of Construction Engineering and Management
• /
• v.18 no.6
• /
• pp.13-25
• /
• 2017

Apartments are a major type of residence and their number has continuously increased. Apartments have multiple meanings in that for public they are not only for residence purpose but for investment, a major commodity for construction firms and a critical policy measure of public well-fare for the government. Therefore, it is critical to understand and analyze trends in apartments demand for pro-active actions. The objective of the study is to analyze and identify key trends in apartments demand based on big data drawn from articles of major daily newspapers. The study identifies 17 major trends from seven themes including development, trade, sale in lots, location requirements, policy, residential environment, and investment and profit. The research methods in the study can be usefully applied to further studies for various issues in relation to the construction industry.

• International Journal of Aerospace System Engineering
• /
• v.5 no.2
• /
• pp.1-7
• /
• 2018

This study examines the history of Korean aviation industry and presents the investment strategy based on the evidence and the 4th industrial revolution. Looking at the evolution of the Korean aviation industry and its technological development will be a great help to support industrial and technological innovation in the future. The modern aviation industry is divided into stages of development, focusing on maintenance of equipment introduced in advanced countries, localization through license assembly, production of products based on technology, and international joint development. The development of aeronautics technology has been progressing towards a general improvement of economic efficiency, aircraft safety efficiency through environmental-friendliness, unmanned operation, and downsizing. The Korea Aerospace Research Institute has secured key technologies through development of several aircrafts such as Experimental Aircraft Kachi, EXPO Unmanned Airship, Twin-engine Composite Aircraft, Canard Aircraft, Multi-Purpose Stratosphere unmanned-airship, Medium Aerostats, Smart UAV, Surion, EAV-2H, KC-100, and OPV. The development strategy is discussed at the level of the evidence-based investment strategy that is currently being discussed, and so the investment priorities in aircraft is high. Current drone usage and development direction are not only producing parts using 3D printer, but also autonomous flight, communication (IoT, 5G), information processing (big data, machine learning). Therefore, the aviation industry is expected to lead the fourth industrial revolution.

• Journal of Korea Society of Industrial Information Systems
• /
• v.23 no.3
• /
• pp.87-95
• /
• 2018

Recently, with the technological development of artificial intelligence, related market is expanding rapidly. In the artificial intelligence technology field, which is still in the early stage but still expanding, it is important to reduce uncertainty about research direction and investment field. Therefore, this study examined technology trends using text mining and topic modeling among big data analysis methods and suggested trends of core technology and future growth potential. We hope that the results of this study will provide researchers with an understanding of artificial intelligence technology trends and new implications for future research directions.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.1
• /
• pp.301-311
• /
• 2020

With the recent global urban issues such as climate change, urbanization, and energy problems, the smart city was proposed as one of the solutions in urban planning. This study introduces the smart city initiatives of South Korea by examining the recent history of smart city policies and their limitations. This case study reflects the experience of one of the countries which thrived to building smart cities as their national key industries to drive economic growth. It also analyzes the trends of the smart city using big data analysis techniques. Although there are obstacles such as economic recession, failing to differentiate from the U-city, low service level than expected smart functionality, We could recognize the current status of the smart city policies in South Korea such as 1) Korean smart city development projects are actively implemented, 2) public consensus suggests that applying advanced technology and the active role of government need, 3) a comprehensive and strategic approach with the integration and application of advanced technologies is required as well, 4) investment by both private and public sectors need to deliver social improvements. This study suggests future direction of smart city polity in South Korea in the conclusion.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2014.07a
• /
• pp.93-94
• /
• 2014

Enterprises or public organizations have invested in development of their information systems and operated them repeatedly. Since these information systems projects have unique characteristics such as technology sensitiveness, network effectiveness, embeddedness, and externality, these investment projects have been not taken care of in the field of administration and evaluation. And then, it is difficult to manage and monitor them. In this research, we propose a evaluation life cycle management model on the basis of result to evaluate information systems. This life cycle model with ten stages would furnish a guide to introduction of total evaluation systems.

• Korean small business review
• /
• v.40 no.3
• /
• pp.1-24
• /
• 2018

The purpose of this study is verifying with corporate financial data that the required investment amount flow shows a similar pattern as times passed, in new product development by start-up company. In the previous paper, the same authors proposed the required investment amount flow as a 'New Product Investment Curve (NPIC)'. In this study, we have studied further in various types of companies. The samples used are accounting data of 462 companies selected from 5,873 Korean companies which were finished external audit in 2015. The results of this study are as follows; The average investment period was 3 years for the listed companies, while 6 years for the unlisted companies. The investment payback period was 6 years for listed companies, while 17 years for unlisted companies. The investment payback period of the company supported by big affiliate company (We call 'greenhouse company') was 14~15 years, while 17 years for real venture companies. When we divide all companies into 4 groups in terms of R&D cost and variable cost ratio, NPIC explanatory power of 'high R&D and high variable cost ratio group (Automobile Assembly Business) is best. Among the eight investment cost indexes proposed to estimate the investment amount, the 'cash 1' (operating cash flow+fixed asset excluding land & building+intangible asset, deferred asset change)/year-end total assets) turned out to be the most effective index to estimate the investment flow patterns. The conclusion is that NPIC explanatory power is somewhat reduced when we estimate all companies together. However, if we estimate the sample companies by characteristics such as listed, unlisted, greenhouse, and venture company, the proposed NPIC was verified to be effective by showing the required investment amount pattern.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.20 no.2
• /
• pp.58-71
• /
• 2021

The number of elderly people worldwide is rapidly increasing and the mobility handicapped suffering from inconvenient public transportation service is also increasing. In Korea and abroad, various policies are being implemented to provide high-quality transportation services for the mobility handicapped, and budget support and investment related to mobility facilities are being expanded. The mobility handicapped spends more time for transit transfer than normal users and their satisfaction with transit service is also lower. There exist transfer inconvenience points of the mobility handicapped due to various factors such as long transfer distances, absence of transportation facilities like elevators, escalators, etc. The purpose of this study is to find transfer inconvenience points for convenient transit transfer of the mobility handicapped using Smart card Big data. This study process traffic card transaction data and construct transfer travel data by user groups using smart card big data and analysis of the transfer characteristics for each user group ; normal, children, elderly, etc. Finally, find transfer inconveniences points by comparing transfer patterns between normal users and the mobility handicapped. This study is significant in that it can find transfer inconvenience points for convenient transit transfer of the mobility handicapped using Smart card Big data. In addition, it can be applicated of Smart card Big data for developing public transportation polices in the future. It is expected that the result of this study be used to improve the accessibility of transit transportation for mobility handicapped.