• The Journal of Engineering Geology
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• v.33 no.1
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• pp.39-49
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• 2023

Soil contaminants measured and managed in Korea include those of geologic origin such as arsenic, cadmium, copper, lead, zinc, nickel, mercury, and fluoride. This study identifies the distribution of these contaminants using GIS modeling to analyze the spatial probability of soil contamination originating from geology. The modeling found that cadmium, copper, lead, nickel, and mercury often exceed the regulated standard by <1%. Concentrations of arsenic and zinc greatly exceeded the standard in the vicinity of mines and industrial complexes: mining and industry seemed to have substantial effects on the concentrations of these metals. Although fluoride was sampled at the lowest number of points, its frequency of exceeding the standard was the highest. No obvious source of artificial contamination has been identified, and fluoride's distribution characteristics showed continuity over a wide area, suggesting a strong correlation between geological characteristics and fluoride concentration. The highest frequencies of fluoride exceeding the standard were in Jurassic granite (40.00%) and Precambrian banded gneiss (34.12%). As these rocks contributed to the formation of soil through their weathering, high fluoride concentrations can be expected in soil in areas where these rocks are distributed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.281-290
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• 2022

In Korea, the number of national facilities for which a safety inspection is mandatory is increasing, and a safer safety inspection method is needed. This study aimed to increase the efficiency of the bridge safety inspection by enabling rapid exterior inspection while securing the safety of inspectors by using drones to perform the safety inspections of bridges, which had mainly relied on visual inspections. For the research, the Youngjong Grand Bridge in Incheon was selected as a test bed and was divided into four parts: the warren truss, suspension bridge main cable, main tower, and pier. It was possible to establish a five-step standard procedure for drone safety inspections. The step-by-step contents of the standard procedure obtained as a result of this research are: Step 1, facility information collection and analysis, Step 2, analysis of vulnerable parts and drone flight planning, Step 3, drone photography and data processing, Step 4, condition evaluation by external inspection, Step 5, building of external inspection diagram and database. Therefore, if the safety inspections of civil engineering facilities including bridges are performed according to this standard procedure, it is expected that these inspection can be carried out more systematically and efficiently.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5C
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• pp.293-301
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• 2008

Soil profiling is one of the most important work among geotehnical engineering practice. Generally, soil profile is estimated from the observation of soil samples during subsurface exploration but such estimation also includes some experiencing aspects such as flushed water from the borehole, slime colour, boring speed and so on. In addition, since the capacity of hydraulic drill rig is significantly increased, thin layers might be easily missed. So, continuous soil profile is almost impossible over all depth to be bored from conventional subsurface exploration. While CPT or CPTu can serve continuous soil profile information over all depth generally in 5cm interval. Many charts or methods for soil profile from CPT result have been proposed during last several decades over the world. However they have not been verified in local ground condition in Korea. In this research, CPT results and soil classification results based on USCS were compiled from 17 sites over the Korea. Soil classification results by using 7 CPT soil classification charts were compared with those of USCS for the compiled database. Most proper CPT soil classification chart for Korean soil characteristics was evaluated and effective parameters for the soil classification from CPT were discussed. Finally interrelationship between CPT soil classification chart and USCS soil classification was evaluated.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2021.11a
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• pp.78-80
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• 2021

This study is based on Degree of Recognition and AHP surveys for experts, this study investigates changes in the demand of seafarers in response to changes in the shipping industry environment in which Maritime Autonomous Surface Ships(MASS) emerge according to the application of the fourth industrial revolution technology to ships, and it looks into changes in seafarers' skills. It also analyzes and proposes a plan for cultivating seafarers accordingly. As a result of Degree of Recognition and AHP analysis, it is analyzed that a new training system is required because the current training and education system may cover the job competencies of emergency response, caution and danger navigation, general sailing, cargo handling, seaworthiness maintenance, emergency response, and ship maintenance and management, but jobs such as remote control, monitoring diagnosis, device management capability, and big data analysis require competency for unmanned and shore based control.By evaluating the importance of change factors in the duties of seafarers in Maritime Autonomous Surface Ships, this study provides information on seafarers educational institutions response strategies for nurturing seafarers and prioritization of resource allocation, etc. The importance of factors was compared and evaluated to suggest changes in the duties of seafarers and methods of nurturing seafarers according to the introduction of Maritime Autonomous Surface Ships.It is expected that this study is meaningful as it systematically derived the duties and competency factors of seafarers of Maritime Autonomous Surface Ships from a practical point of view and analyzed the perception level of each relevant expert to diagnose expert-level responses to the introduction of Maritime Autonomous Surface Ships.

• Korean Journal of Plant Resources
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• v.37 no.2
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• pp.171-202
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• 2024

If the plant genetic resources and information-sharing systems held by arboretums worldwide are effectively utilized, it is believed that a conservation system for plant diversity in the currently inaccessible North Korean region could be established. This study was conducted to review the scientific names of plants native to North Korea but not to South Korea and to assess the status of genetic resources held in domestic and international arboretums. To compile a list and status of North Korean plant's genetic resources, updated checklists of vascular plants in Korean Peninsula and online plant information databases were consulted to compile synonym, distribution range, and other related information. A total of 486 taxa (449 species, 13 subspecies, 21 varieties, 1 forma and 2 hybrids) from 236 genera and 64 families, representing 12.34% of the total native flora of the Korean Peninsular were presented in the North Korea plant list, and the presence of rare, endemic and northern lineage species was confirmed. It was found that 384 taxa from 190 genera, 53 families of North Korean plants are held as genetic resources in 333 arboretums and plant research institutions across 46 countries and 5 continents worldwide. This study is expected to contribute to the construction and application of a species list for plants native to the Korean Peninsula.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.71-90
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• 2020

Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.

• Korean Security Journal
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• no.13
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• pp.145-168
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• 2007

Like to change to the information-oriented society, the guard service needs to be changed. The communication and hardware technology develop rapidly and according to the internet environment change from cable to wireless, modern person can approach every kinds of information service using wireless communication machinery which can be moved such as laptop, computer, PDA, mobile phone and so on, LBS field which presents the needing information and service at anytime, anywhere, and which kinds of device expands it's territory all the more together with the appearance of ubiquitous concept. LBS use the chip in the mobile phone and make to confirm the position of the joining member anytime within several tens centimeters to hundreds meters. LBS can be divided by the service method which use mobile communication base station and apply satellite. Also each service type can be divided by location chase service, public safe service, location based information service and so on, and it is the part which will plan with guard service development. It will be prospected 8.460 hundred million in 2005 years and 16.561 hundred million in 2007 years scale of market. Like this situation, it can be guessed that the guard service has to change rapidly according to the LBS application. Study method chooses documentary review basically, and at first theory method mainly uses the second documentary examination which depends on learned journal and independent volume which published in the inside and the outside of the country, internet searching, other kinds of all study report, statute book, thesis which published at public order research institute of the Regional Police Headquarter, police operation data, data which related with statute, documents and statistical data which depend on private guard company and so on. So the purpose of the study gropes in accordance with the LBS application, and present the problems and improvement method to analyze indirect of manager side of operate guard adaptation service of LBS, government side which has to activate LBS, systematical, operation management, manpower management and education training which related with guard course side which has to study and educate in accordance with application of the new guard service, as well as intents to excellent quality service of guard.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.2
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• pp.1-20
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• 2020

The purpose of this study was to analyze the distribution characteristics of spatial and temporal PM_2.5 in urban areas of Changwon-si, and to identify the causes of PM_2.5 by comparing the characteristics of land-use, and to suggest the direction of reduction measures. As the basic data, the every hour average from September 2017 to August 2018 of Airpro data, which has measurement points in kindergartens, elementary schools, and some middle and high schools in Changwon-si was used. Also, by using IDW method among spatial interpolation methods of GIS, monthly and time-slot distribution maps were constructed, and based on this, spatial and temporal PM_2.5 distribution characteristics were confirmed. First, to verify the accuracy of the Airpro data, the correlation with AirKorea data managed by the Ministry of Environment was confirmed. As a result of the analysis, R² was 0.75~0.86, showing a very high correlation and the data was judged that it was suitable for the study. In the monthly analysis, January was the highest year, and August was the lowest. As a result of analysis by time-slot, The clock-in time at 06-09 was the highest, and the activity time at 09-18 was the lowest. By administrative district, Sangnam-dong, Happo-dong, and Myeonggok-dong were the most severe regions of PM_2.5 and Hoeseong-dong was the lowest. As a result of analyzing the land-use characteristics by administrative area, it was confirmed that the ratio of traffic area and commercial area is high in the serious area of PM_2.5. In conclusion, the results of this study will be used as basic data to grasp the characteristics of PM_2.5 distribution in Changwon-si. Also, it is thought that the severe regions and the direction of establishing reduction measures derived from this study can be used to prepare more effective policies than before.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.