• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.12
• /
• pp.2859-2864
• /
• 2013

Recently, a great attention has been paid to a car black box device in the automobile markets besides it provides an accident re-construction based on the data which contains audio, video, and some meaningful driving information. Also, it is expected that the device will get to promote around public transit and the market will greatly grow within a few years. Thus, this research conducted of preference the influencing factors in decisions purchase of auto black box. Factors influencing in decisions purchase of black box were divided safety, functionality, differentiation, economics. A questionnaire survey was conducted to those who worked in a black box company. This study suggests practical and theoretical implications of factors influencing purchase decisions based on the results.

• Advances in concrete construction
• /
• v.16 no.1
• /
• pp.69-78
• /
• 2023

This investigation delves into the adverse repercussions stemming from the impact of arsenic on steel pipes concealed within soil designated for rice cultivation. Simultaneously, the study aims to ascertain effective techniques for detecting arsenic in the soil and to provide strategies for mitigating the corrosion of steel pipes. The realm of nanotechnology presents promising avenues for addressing the intricate intersection of renewable energy, oil, and environmental pollution from a novel perspective. Nanostructured materials, characterized by distinct chemical and physical attributes, unveil novel pathways for pioneering materials that exert a substantial impact across diverse realms of food production, storage, packaging, and quality control. Within the scope of the food industry, the scope of nanotechnology encompasses processes, storage methodologies, packaging paradigms, and safeguards to ensure the safety of consumables. Of particular note, silver nanoparticles, in addition to their commendable antibacterial efficacy, boast anti-fungal and anti-inflammatory prowess, environmental compatibility, minimal irritability and allergenicity, resilience to microbial antagonism, thermal stability, and robustness. Confronting the pressing issue of arsenic contamination within both environmental settings and the food supply is of paramount importance to preserve public health and ecological equilibrium. In response, this study introduces detection kits predicated upon silver nanoparticles, providing an expeditious and economically feasible avenue for identifying arsenic concentrations ranging from 0.5 to 3 ppm within rice. Subsequent quantification employs Hydride Atomic Absorption Spectroscopy (HG-AAS), which features a detection threshold of 0.05 ㎍/l. A salient advantage inherent in the HG-AAS methodology lies in its capacity to segregate analytes from the sample matrix, thereby significantly reducing instances of spectral interference. Importantly, the presence of arsenic in the soil beneath rice cultivation establishes a causative link to steel pipe corrosion, with potential consequences extending to food contamination-an intricate facet embedded within the broader tapestry of renewable energy, oil, and environmental pollution.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.37 no.2
• /
• pp.427-435
• /
• 2017

Korea's overseas construction awards reached US $750 bn for more than 50 years since it first entered the market in 1966. In particular, the company won US $540 bn over 10 years from 2007, achieving 72% of the total contracts. However, in recent two years, awarded amounts have decreased by 40% each year. The most significant decline is due to the impact of international oil prices, which have plummeted since end of 2014, as oil-producing nations, which are Korea's major target countries, are struggling to cancel or postpone infrastructure orders. In order to lessen the impact of raw material price fluctuations, the recent trend is that even countries with relatively loose government financing conditions are rapidly changing their ordering methods to investment development forms such as PPP. The Korean government and companies have been already preparing for this for several years, but they are still not doing so well. The main reason is the lack of understanding about the investment development type project, especially financing methods and the aggravated fear of exposing it to various risks due to the characteristics of the development project, which takes a long time to collect the investment. In this paper, I propose a more systematic solution to financial process and risk management, which is recognized as a obstructive factor for Korean companies, in line with the recent government-led establishment of overseas infrastructure development support organizations. I would like to serve as a investment guide.

• Journal of Families and Better Life
• /
• v.28 no.6
• /
• pp.35-46
• /
• 2010

The purpose of the study was to identify the potential buyers' consciousness of single-family housing to provide useful data to help future single-family housing supplies in Ulsan. The study selected residents in Ulsan, who were over twenty and had an interest in living in a single-family housing. A survey was conducted from September 11, 2008 to September 25, 2008. The sample consisted of 364 persons who are currently live in Ulsan metropolitan area. The results are as following. About two thirds of the sample had the desire to live in a single-family housing. Moving into a single-family housing had financial preparation as the greatest issue. When moving into a single-family housing, the convenience of the residential district was the greatest consideration, whether or not it is a green environment, pollution level, etc. The potential buyers valued environment-friendly features and also had a very strong desire to own their own house. Many of them wanted to design and build their own single-family housing within a budget of 100-200 million KRW. In terms of the location, there was a higher preference for the riverside or lakeside rural areas outside the city. In terms of size, the preference was less than $330m^2$, which includes $99-132m^2$ for residential. When considering a single-family housing the direction was the most important feature, along with eco-friendly and safer materials and equipments. When building the single-family housing the potential buyers considered the community spaces first with a preference for having three bedrooms and two bathrooms. For the exterior, they wanted a unique shape of roof and there were high preferences for brown and beige colors. In terms of housing complexes, the potential buyers preferred individual unit types over complexes. If they preferred housing complexes, they wanted the cluster form complex with about 10-30 units. The complex also required a park-like setting with a guard system, which shows that convenience and safety were the most important features. In terms of complex management, they considered environmental management as the most important feature. The potential buyers were willing to pay belw 200,000 KRW, which showed their desire to minimize financial burdens.

• Journal of Intelligence and Information Systems
• /
• v.25 no.2
• /
• pp.99-122
• /
• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Korean Journal of Construction Engineering and Management
• /
• v.16 no.1
• /
• pp.52-63
• /
• 2015

Business facilities among domestic architectures have rapidly been constructed along with domestic economic development. It is an important facility taking the second largest proportion next to apartment buildings among current 31 building types of fire department classification of 2012 year for urban architectures. The expected service life of business facilities is 15 years, but 70% of those in urban areas have surpassed the 15 year service life as of the present 2014. Thus, the demand for urgent rehabilitation of such facilities is constantly increasing due to the aging and performance deterioration of the facilities'main finishing materials. Especially, the business facilities are being used for the lease of company office or private office, and such problems as aging and performance deterioration of the facilities could cause less competitive edge for leasing and real estate value depreciation for the O&M (Operation & Management) agent and the owner, respectively. Therefore, an effective planned rehabilitation as a preventive measure according to the standardized repair rate by the number of years after the construction is in need in order to prevent the aging and performance deterioration of the facilities(La et al. 2001). Nonetheless, domestic repair/rehabilitation standards based on the repair rate are mainly limited to apartment buildings and pubic institutions, resulting in impractical application of such standards to business facilities. It has been investigated and analyzed that annual repair rate data for each finishing material are required for examination of the applicability of the repair rate standard for the purpose of establishment of a repair plan. Hence, this study aimed at developing a repair rate computation model for finishing materials of the facilities and verifying the appropriateness of the annual repair rate for each finishing material through a case study after collecting and analyzing the repair history data of six business facilities. The results of this study are expected to contribute to the planning and implementation of more efficient repair/rehabilitation budget by preventing the waste of unpredicted repair cost and opportunity cost for the sake of the business facilities' owners and O&M agents.

• Journal of Intelligence and Information Systems
• /
• v.29 no.3
• /
• pp.79-101
• /
• 2023

The current status of local road pavement management in Jeollabuk-do only relies on the accomplishments of the site construction company's pavement repair and is only managed through Microsoft Excel and word documents. Furthermore, the budget is irregular each year. Accordingly, a systematic maintenance plan for local roads is necessary. In this paper, data related to road damage and road environment were collected and processed to derive possible areas which could suffer from road damage. The effectiveness of the methodology was reviewed through the on-site inspection of the area. According to the Ministry of Land, Infrastructure and Transport, in 2018, the number of damages on general national roads were about 47,000. In 2019, it reached around 38,000. Furthermore, the number of lawsuits regarding the road damages were about 93 in 2018 and it increased to 119 in 2019. In the case of national roads, the number of damages decreased compared to 2018 due to pavement repairs. To measure the priorities in maintenance of local roads at Jeollabuk-do, data on maintenance history, local port hole occurrence site, overlapping business section, and emergency maintenance section were transformed into data. Eventually, it led to improvements in maintenance of local roads. Furthermore, spatial data were constructed using various current status data related to roads, and finally the data was processed into a new form that could be utilized in machine learning and predictions. Using the spatial data, areas requiring maintenance on pavement were predicted and the results were used to establish new budgets and policies on road management.

• Journal of Intelligence and Information Systems
• /
• v.16 no.3
• /
• pp.99-120
• /
• 2010

Due to the wide spread of customers' frequent access of non face-to-face services, there have been many attempts to improve customer satisfaction using huge amounts of data accumulated throughnon face-to-face channels. Usually, a call center is regarded to be one of the most representative non-faced channels. Therefore, it is important that a call center has enough agents to offer high level customer satisfaction. However, managing too many agents would increase the operational costs of a call center by increasing labor costs. Therefore, predicting and calculating the appropriate size of human resources of a call center is one of the most critical success factors of call center management. For this reason, most call centers are currently establishing a department of WFM(Work Force Management) to estimate the appropriate number of agents and to direct much effort to predict the volume of inbound calls. In real world applications, inbound call prediction is usually performed based on the intuition and experience of a domain expert. In other words, a domain expert usually predicts the volume of calls by calculating the average call of some periods and adjusting the average according tohis/her subjective estimation. However, this kind of approach has radical limitations in that the result of prediction might be strongly affected by the expert's personal experience and competence. It is often the case that a domain expert may predict inbound calls quite differently from anotherif the two experts have mutually different opinions on selecting influential variables and priorities among the variables. Moreover, it is almost impossible to logically clarify the process of expert's subjective prediction. Currently, to overcome the limitations of subjective call prediction, most call centers are adopting a WFMS(Workforce Management System) package in which expert's best practices are systemized. With WFMS, a user can predict the volume of calls by calculating the average call of each day of the week, excluding some eventful days. However, WFMS costs too much capital during the early stage of system establishment. Moreover, it is hard to reflect new information ontothe system when some factors affecting the amount of calls have been changed. In this paper, we attempt to devise a new model for predicting inbound calls that is not only based on theoretical background but also easily applicable to real world applications. Our model was mainly developed by the interactive decision tree technique, one of the most popular techniques in data mining. Therefore, we expect that our model can predict inbound calls automatically based on historical data, and it can utilize expert's domain knowledge during the process of tree construction. To analyze the accuracy of our model, we performed intensive experiments on a real case of one of the largest car insurance companies in Korea. In the case study, the prediction accuracy of the devised two models and traditional WFMS are analyzed with respect to the various error rates allowable. The experiments reveal that our data mining-based two models outperform WFMS in terms of predicting the amount of accident calls and fault calls in most experimental situations examined.

• Korean Journal of Health Education and Promotion
• /
• v.24 no.5
• /
• pp.87-101
• /
• 2007

Objectives: This study identified the labor union associates' perception and participation status on SHEW and analyzed these two Constructs correlations with Safety and health education at work(SHEW) in manufacture and construction industries. Methods: Self-administered survey was successfully finished by 103 labor union associates (91 employed in 78 manufacturing companies and 12 employed in 12 constructing companies over 12 areas). Two questionnaires, survey direction slip, the official letter to ask survey participation from Korea Ministry of Labor, and a posted envelop to return were delivered to each workplace labor union office in conveniently selected companies. Most participants' companies were at least medium to large in manufacturing industry and most associates were men and married. A survey questionnaire examined demographic characteristics, SHEW status (participation status included), and perceptions of SHEW. Results: Overall, manufacturing companies had better infrastructures for SHEW, employer support for SHEW, and current educators' competencies than constructing companies. These infrastructures for SHEW were closely correlated with company labor union participation on SHEW and the correlation coefficients were greater than any other expectations or needs variables for SHEW. Conclusions: The primary strategies for better participation and support from labor union need to be developed in supporting for organizational infrastructures related to SHEW and strengthening safety and health education training programs for supervisors or educators at work.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.16 no.2
• /
• pp.81-89
• /
• 2002

The Battery Energy Storage System (BESS) has lots of advantages such as load leveling, quick response emergency power (spinning reserve), frequency and voltage control, improvement of reliability, and deferred generation and transmission construction. However, it is very critical that economic feasibility requires justification from the customer side of meter to promoting the dissemination of BESS in nation widely. In this paper, we proposed the economic assessment model of customer owned BESS which is complemented and improved the existing model. The proposed model is applied to the typical customer types, i.e. light industrial, commercial, and residential, which are taken from the statistical analysis on the load profile survey of Korea Electric Power COmpany (KEPCO). The economic viability performed for each customer load type to justifying their economic feasibility of BESS installation from the economic measures such as payback period, Net Present Worth (NPW), Rate Of Return (ROR). The results show that the BESS has economic benefits to the specific customer type, i.e. residential customer. Therefore, the government and the energy agency should be committing the support program, such as tax incentive, financial support, to disseminate the BESS nation widely. The results of this paper are useful to the customer investment decision-making and the national energy policy & strategy in Korea.