• Tunnel and Underground Space
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• v.33 no.4
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• pp.281-298
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• 2023

Continuous research efforts are being devoted to unmanned mobile platforms for lunar exploration. There is an ongoing demand for real-time information processing to accurately determine the positioning and mapping of areas of interest on the lunar surface. To apply deep learning processing and analysis techniques to practical rovers, research on software integration and optimization is imperative. In this study, a foundational investigation has been conducted on real-time analysis of virtual lunar base construction site images, aimed at automatically quantifying spatial information of key objects. This study involved transitioning from an existing region-based object recognition algorithm to a boundary box-based algorithm, thus enhancing object recognition accuracy and inference speed. To facilitate extensive data-based object matching training, the Batch Hard Triplet Mining technique was introduced, and research was conducted to optimize both training and inference processes. Furthermore, an improved software system for object recognition and identical object matching was integrated, accompanied by the development of visualization software for the automatic matching of identical objects within input images. Leveraging satellite simulative captured video data for training objects and moving object-captured video data for inference, training and inference for identical object matching were successfully executed. The outcomes of this research suggest the feasibility of implementing 3D spatial information based on continuous-capture video data of mobile platforms and utilizing it for positioning objects within regions of interest. As a result, these findings are expected to contribute to the integration of an automated on-site system for video-based construction monitoring and control of significant target objects within future lunar base construction sites.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.139-160
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• 2017

Technology commercialization creates effective economic value by linking the company's R & D processes and outputs to the market. This technology commercialization is important in that a company can retain and maintain a sustained competitive advantage. In order for a specific technology to be commercialized, it goes through the stage of technical planning, technology research and development, and commercialization. This process involves a lot of time and money. Therefore, the duration and cost of technology commercialization are important decision information for determining the market entry strategy. In addition, it is more important information for a technology investor to rationally evaluate the technology value. In this way, it is very important to scientifically estimate the duration and cost of the technology commercialization. However, research on technology commercialization is insufficient and related methodology are lacking. In this study, we propose an evaluation model that can estimate the duration and cost of R & D technology commercialization for small and medium-sized enterprises. To accomplish this, this study collected the public data of the National Science & Technology Information Service (NTIS) and the survey data provided by the Small and Medium Business Administration. Also this study will develop the estimation model of commercialization duration and cost of R&D performance on using these data based on the market approach, one of the technology valuation methods. Specifically, this study defined the process of commercialization as consisting of development planning, development progress, and commercialization. We collected the data from the NTIS database and the survey of SMEs technical statistics of the Small and Medium Business Administration. We derived the key variables such as stage-wise R&D costs and duration, the factors of the technology itself, the factors of the technology development, and the environmental factors. At first, given data, we estimates the costs and duration in each technology readiness level (basic research, applied research, development research, prototype production, commercialization), for each industry classification. Then, we developed and verified the research model of each industry classification. The results of this study can be summarized as follows. Firstly, it is reflected in the technology valuation model and can be used to estimate the objective economic value of technology. The duration and the cost from the technology development stage to the commercialization stage is a critical factor that has a great influence on the amount of money to discount the future sales from the technology. The results of this study can contribute to more reliable technology valuation because it estimates the commercialization duration and cost scientifically based on past data. Secondly, we have verified models of various fields such as statistical model and data mining model. The statistical model helps us to find the important factors to estimate the duration and cost of technology Commercialization, and the data mining model gives us the rules or algorithms to be applied to an advanced technology valuation system. Finally, this study reaffirms the importance of commercialization costs and durations, which has not been actively studied in previous studies. The results confirm the significant factors to affect the commercialization costs and duration, furthermore the factors are different depending on industry classification. Practically, the results of this study can be reflected in the technology valuation system, which can be provided by national research institutes and R & D staff to provide sophisticated technology valuation. The relevant logic or algorithm of the research result can be implemented independently so that it can be directly reflected in the system, so researchers can use it practically immediately. In conclusion, the results of this study can be a great contribution not only to the theoretical contributions but also to the practical ones.

• Management & Information Systems Review
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• v.38 no.4
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• pp.137-157
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• 2019

Companies are trying to use enterprise SNS for collaboration and speedy decision-making. This study verified the mediating effect of communication between enterprise SNS and job performance, and proved the moderating effect of nationality between enterprise SNS and communication. This study collected survey data of 81 Korean and 81 Chinese from employees who have used enterprise SNS in Korea and China. As results of data analysis, first, enterprise SNS improved job performance through speedy information sharing and error reduction. Second, communication mediated the effect of enterprise SNS on job performance. Third, enterprise SNS increased the level of organizational communication through decreasing the burden of offline face-to-face communication. Compared with Chinese corporate organizations, Korean corporate organizations have high power distances, centralized control, and high superior authority. Therefore, in the off-line communication situation, the subordinate feels the social pressure to follow the command of the superior. Thus communication is one-way and closed. In this Korean organizational situation, corporate SNS can be used as a means to bypass rigid offline communication. In the online communication environment of non face-to-face corporate SNS, anxiety and stress of face-to-face communication can be reduced, so communication between the upper and lower sides can flow more smoothly. The contribution of this paper is that it proved that enterprise SNS promotes communication and improve job performance by reducing the anxiety or stress of offline communication, while according to prior research successful adoption of many types of information systems requires the fit between an organization and its organizational culture.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.163-178
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• 2014

Following research proposes "Virtualization of Smart Cards (ViSCa)" which is a security system that aims to provide a multi-device platform for the deployment of services that require a strong security protocol, both for the access & authentication and execution of its applications and focuses on analyzing Virtualization of Smart Cards (ViSCa) platform-based mobile payment service by comparing with other similar cases. At the present day, the appearance of new ICT, the diffusion of new user devices (such as smartphones, tablet PC, and so on) and the growth of internet penetration rate are creating many world-shaking services yet in the most of these applications' private information has to be shared, which means that security breaches and illegal access to that information are real threats that have to be solved. Also mobile payment service is, one of the innovative services, has same issues which are real threats for users because mobile payment service sometimes requires user identification, an authentication procedure and confidential data sharing. Thus, an extra layer of security is needed in their communication and execution protocols. The Virtualization of Smart Cards (ViSCa), concept is a holistic approach and centralized management for a security system that pursues to provide a ubiquitous multi-device platform for the arrangement of mobile payment services that demand a powerful security protocol, both for the access & authentication and execution of its applications. In this sense, Virtualization of Smart Cards (ViSCa) offers full interoperability and full access from any user device without any loss of security. The concept prevents possible attacks by third parties, guaranteeing the confidentiality of personal data, bank accounts or private financial information. The Virtualization of Smart Cards (ViSCa) concept is split in two different phases: the execution of the user authentication protocol on the user device and the cloud architecture that executes the secure application. Thus, the secure service access is guaranteed at anytime, anywhere and through any device supporting previously required security mechanisms. The security level is improved by using virtualization technology in the cloud. This virtualization technology is used terminal virtualization to virtualize smart card hardware and thrive to manage virtualized smart cards as a whole, through mobile cloud technology in Virtualization of Smart Cards (ViSCa) platform-based mobile payment service. This entire process is referred to as Smart Card as a Service (SCaaS). Virtualization of Smart Cards (ViSCa) platform-based mobile payment service virtualizes smart card, which is used as payment mean, and loads it in to the mobile cloud. Authentication takes place through application and helps log on to mobile cloud and chooses one of virtualized smart card as a payment method. To decide the scope of the research, which is comparing Virtualization of Smart Cards (ViSCa) platform-based mobile payment service with other similar cases, we categorized the prior researches' mobile payment service groups into distinct feature and service type. Both groups store credit card's data in the mobile device and settle the payment process at the offline market. By the location where the electronic financial transaction information (data) is stored, the groups can be categorized into two main service types. First is "App Method" which loads the data in the server connected to the application. Second "Mobile Card Method" stores its data in the Integrated Circuit (IC) chip, which holds financial transaction data, which is inbuilt in the mobile device secure element (SE). Through prior researches on accept factors of mobile payment service and its market environment, we came up with six key factors of comparative analysis which are economic, generality, security, convenience(ease of use), applicability and efficiency. Within the chosen group, we compared and analyzed the selected cases and Virtualization of Smart Cards (ViSCa) platform-based mobile payment service.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.55-75
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• 2010

Sequential pattern mining aims to discover interesting sequential patterns in a sequence database, and it is one of the essential data mining tasks widely used in various application fields such as Web access pattern analysis, customer purchase pattern analysis, and DNA sequence analysis. In general sequential pattern mining, only the generation order of data element in a sequence is considered, so that it can easily find simple sequential patterns, but has a limit to find more interesting sequential patterns being widely used in real world applications. One of the essential research topics to compensate the limit is a topic of weighted sequential pattern mining. In weighted sequential pattern mining, not only the generation order of data element but also its weight is considered to get more interesting sequential patterns. In recent, data has been increasingly taking the form of continuous data streams rather than finite stored data sets in various application fields, the database research community has begun focusing its attention on processing over data streams. The data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. In data stream processing, each data element should be examined at most once to analyze the data stream, and the memory usage for data stream analysis should be restricted finitely although new data elements are continuously generated in a data stream. Moreover, newly generated data elements should be processed as fast as possible to produce the up-to-date analysis result of a data stream, so that it can be instantly utilized upon request. To satisfy these requirements, data stream processing sacrifices the correctness of its analysis result by allowing some error. Considering the changes in the form of data generated in real world application fields, many researches have been actively performed to find various kinds of knowledge embedded in data streams. They mainly focus on efficient mining of frequent itemsets and sequential patterns over data streams, which have been proven to be useful in conventional data mining for a finite data set. In addition, mining algorithms have also been proposed to efficiently reflect the changes of data streams over time into their mining results. However, they have been targeting on finding naively interesting patterns such as frequent patterns and simple sequential patterns, which are found intuitively, taking no interest in mining novel interesting patterns that express the characteristics of target data streams better. Therefore, it can be a valuable research topic in the field of mining data streams to define novel interesting patterns and develop a mining method finding the novel patterns, which will be effectively used to analyze recent data streams. This paper proposes a gap-based weighting approach for a sequential pattern and amining method of weighted sequential patterns over sequence data streams via the weighting approach. A gap-based weight of a sequential pattern can be computed from the gaps of data elements in the sequential pattern without any pre-defined weight information. That is, in the approach, the gaps of data elements in each sequential pattern as well as their generation orders are used to get the weight of the sequential pattern, therefore it can help to get more interesting and useful sequential patterns. Recently most of computer application fields generate data as a form of data streams rather than a finite data set. Considering the change of data, the proposed method is mainly focus on sequence data streams.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.8
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• pp.223-230
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• 2021

The lightweight block cipher PIPO announced at ICISC'20 has been effectively implemented by applying the bit slice technique. In this paper, we propose a parallel optimal implementation of PIPO for ARM processors. The proposed implementation enables parallel encryption of 8-plaintexts and 16-plaintexts. The implementation targets the A10x fusion processor. On the target processor, the existing reference PIPO code has performance of 34.6 cpb and 44.7 cpb in 64/128 and 64/256 standards. Among the proposed methods, the general implementation has a performance of 12.0 cpb and 15.6 cpb in the 8-plaintexts 64/128 and 64/256 standards, and 6.3 cpb and 8.1 cpb in the 16-plaintexts 64/128 and 64/256 standards. Compared to the existing reference code implementation, the 8-plaintexts parallel implementation for each standard has about 65.3%, 66.4%, and the 16-plaintexts parallel implementation, about 81.8%, and 82.1% better performance. The register minimum alignment implementation shows performance of 8.2 cpb and 10.2 cpb in the 8-plaintexts 64/128 and 64/256 specifications, and 3.9 cpb and 4.8 cpb in the 16-plaintexts 64/128 and 64/256 specifications. Compared to the existing reference code implementation, the 8-plaintexts parallel implementation has improved performance by about 76.3% and 77.2%, and the 16-plaintext parallel implementation is about 88.7% and 89.3% higher for each standard.

• Korean Journal of Environment and Ecology
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• v.24 no.4
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• pp.395-405
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• 2010

This study was carried out to offer basic data to minimize the indiscreet development and damage of coastal wetlands through an evaluation from an ecological standpoint highlighting the importance of the coastal wetland in South Gyeongsang Province, Korea. The result of the macrobenthos survey for the coastal wetland assessment showed that Dongdal and Hwasan-ri, Yongnam-myeon, and Tongyeong city had the largest species number; Oegan-ri and Naegan-ri, Geoje-myeon, and Geoje city had the largest population and biomass; and Miryong-ri, Samsan-myeon, Goseong-gun had the highest species diversity. In the halophytes survey, Imyeong-ri, Jinjeon-myeon, Masan city and Oegan-ri and Naegan-ri, Geoje-myeon, Geoje city had the large character species and companion species. The evaluation results of the ecological values of the coastal wetlands were categorized into five grades based on the field surveys, and the sedimentary environment factor in the case of Danghang-ri, Hoehwa-myeon, and Goseong-gun; Miryong-ri, Samsan-myeon, Goseong-gun; Guho-ri, Gonyang-myeon, Sacheon city; Sulsang-ri Yangpo-ri, Jingyo-myeon, Hadong-gun; and Seokpyeong-ri, Idong-myeon, Namhae-gun, were appraised at the highest rating of grade II. The halophytes factor in the case of Imyeong-ri, Jinjeon-myeon, Masan city, Dongdal-ri and Hwasan-ri, Yongnam-myeon, Tongyeong city and Oegan-ri and Naegan-ri, Geoje-myeon, Geoje city, were highly evaluated as grade II. The macrobenthos factor in the case of Imyeong-ri, Jinjeon-myeon, Masan city and Oegan-ri and Naegan-ri, Geoje-myeon, Geoje city was highly evaluated as grade II. The final evaluation grade was calculated by the mean values of three evaluation factors, and Imyeong-ri, Jinjeon-myeon, Masan city and Oegan-ri and Naegan-ri, Geoje-myeon, and Geoje city had the highest rating of II. On the other hand, Seokpyeong-ri, Idong-myeon, Namhae-gun had the lowest rating of IV. These locations will require future research to survey and monitor the coastal wetland ecosystems by season, in addition to the construction of the GIS-based wetland information system with a view to manage the coastal wetlands.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.903-916
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• 2021

An area's topography refers to the shape of the earth's surface, described by its elevation, slope, and aspect, among other features. The topographical conditions determine energy flowsthat move water and energy from higher to lower elevations, such as how much solar energy will be received and how much wind or rain will affect it. Another common factor, the topographic wetness index (TWI), is a calculation in digital elevation models of the tendency to accumulate water per slope and unit area, and is one of the most widely referenced hydrologic topographic factors, which helps explain the location of forest vegetation. Analyses of topographical factors can be calculated using a geographic information system (GIS) program based on digital elevation model (DEM) data. Recently, a large number of free open source software (FOSS) GIS programs are available and developed for researchers, industries, and governments. FOSS GIS programs provide opportunitiesfor flexible algorithms customized forspecific user needs. The majority of biodiversity in island areas exists at about 20% higher elevations than in land ecosystems, playing an important role in ecological processes and therefore of high ecological value. However, island areas are vulnerable to disturbances and damage, such as through climate change, environmental pollution, development, and human intervention, and lacks systematic investigation due to geographical limitations (e.g. remoteness; difficulty to access). More than 4,000 of Korea's islands are within a few hours of its coast, and 88% are uninhabited, with 52% of them forested. The forest ecosystems of islands have fewer encounters with human interaction than on land, and therefore most of the topographical conditions are formed naturally and affected more directly by weather conditions or the environment. Therefore, the analysis of forest topography in island areas can be done more precisely than on its land counterparts, and therefore has become a major focus of attention in Korea. This study is focused on calculating the performance of different topographical factors using FOSS GIS programs. The test area is the island forests in Korea's south and the DEM of the target area was processed with GRASS GIS and SAGA GIS. The final slopes and TWI maps were produced as comparisons of the differences between topographic factor calculations of each respective FOSS GIS program. Finally, the merits of each FOSS GIS program used to calculate the topographic factors is discussed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.853-865
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• 2022

In this study, from August to October 2019, we conducted a survey of the spatial distribution and dominant species of macrobenthos on the rocky intertidal zones of 38 specified islands distributed along the southern coast of Korea. On the basis of observation made using 50 × 50 cm quadrats, we identified a total of 80 species, among which, Mollusca were the most abundant fauna, with 54 species that accounted for 67.4% of the total, followed by Crustacea with 15 species (18.7%). The recorded numbers of Cnidaria, Porifera, and Echinodermata species ranged from 1 to 6. In terms of the regional patterns of species richness, specified islands in Yeosu were found to be the most species rich, supporting 61 species, whereas islands in Hadong, Namhae, and Chujado were found to have a similar level of species richness, ranging from 42 to 46 species. Islands in Boseong and Goheung were home to the fewest species, with only 29 species being recorded. At the sampling station scale, we noted a considerable difference in faunal richness, ranging from 6 (St. 6) to 33 (St. 20) species. Among the recorded species, Echinolittorina radiata was identified as the dominant species on 15 specified islands, with the next most abundant species being Tetraclita japonica, considered an indicator species of climate change, which was recorded on 11 islands. In terms of frequency, E. radiata, found on 36 islands, was identified as the most frequently occurring species, followed by Reishia clavigera (30 islands), Mytilisepta virgata (29), Nerita japonica (28), Ligia. exotica (27), and Littorina brevicula (26). Of the 80 species identified, 9, 4, and 2 species of Mollusca, Crustacea, and Cnidaria, respectively, are classified as Marine fauna of accepted foreign export, whereas 50 are Red List species, 44 are species of Least Concern, 3 are Data Deficient species, and 1 species was not evaluated. However, during the survey, we found no Near Threatened or Not Applicable species. On the basis of the findings of this survey, it would appear that the abundance and richness of macrobenthic fauna inhabiting the rocky intertidal zones of specified islands along the southern coast of Korea differ according to different habitat conditions, particularly with respect to the duration of exposure and the extent and properties of the substrata. The findings of this study will provide baseline data for future monitoring and management of specified islands in Korea.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.1-21
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• 2021

As the global business environment changes, uncertainties in technology development and market needs increase, and competition among companies intensifies, interests and demands for R&D activities of individual companies are increasing. In order to cope with these environmental changes, R&D companies are strengthening R&D investment as one of the means to enhance the qualitative competitiveness of R&D while paying more attention to facility investment. As a result, facilities or R&D investment elements are inevitably a burden for R&D companies to bear future uncertainties. It is true that the management strategy of increasing investment in R&D as a means of enhancing R&D capability is highly uncertain in terms of corporate performance. In this study, the structural factors that influence the R&D capabilities of companies are explored in terms of technology management capabilities, R&D capabilities, and corporate classification attributes by utilizing data mining techniques, and the characteristics these individual factors present according to the level of R&D capabilities are analyzed. This study also showed cluster analysis and experimental results based on evidence data for all domestic R&D companies, and is expected to provide important implications for corporate management strategies to enhance R&D capabilities of individual companies. For each of the three viewpoints, detailed evaluation indexes were composed of 7, 2, and 4, respectively, to quantitatively measure individual levels in the corresponding area. In the case of technology management capability and R&D capability, the sub-item evaluation indexes that are being used by current domestic technology evaluation agencies were referenced, and the final detailed evaluation index was newly constructed in consideration of whether data could be obtained quantitatively. In the case of corporate classification attributes, the most basic corporate classification profile information is considered. In particular, in order to grasp the homogeneity of the R&D competency level, a comprehensive score for each company was given using detailed evaluation indicators of technology management capability and R&D capability, and the competency level was classified into five grades and compared with the cluster analysis results. In order to give the meaning according to the comparative evaluation between the analyzed cluster and the competency level grade, the clusters with high and low trends in R&D competency level were searched for each cluster. Afterwards, characteristics according to detailed evaluation indicators were analyzed in the cluster. Through this method of conducting research, two groups with high R&D competency and one with low level of R&D competency were analyzed, and the remaining two clusters were similar with almost high incidence. As a result, in this study, individual characteristics according to detailed evaluation indexes were analyzed for two clusters with high competency level and one cluster with low competency level. The implications of the results of this study are that the faster the replacement cycle of professional managers who can effectively respond to changes in technology and market demand, the more likely they will contribute to enhancing R&D capabilities. In the case of a private company, it is necessary to increase the intensity of input of R&D capabilities by enhancing the sense of belonging of R&D personnel to the company through conversion to a corporate company, and to provide the accuracy of responsibility and authority through the organization of the team unit. Since the number of technical commercialization achievements and technology certifications are occurring both in the case of contributing to capacity improvement and in case of not, it was confirmed that there is a limit in reviewing it as an important factor for enhancing R&D capacity from the perspective of management. Lastly, the experience of utility model filing was identified as a factor that has an important influence on R&D capability, and it was confirmed the need to provide motivation to encourage utility model filings in order to enhance R&D capability. As such, the results of this study are expected to provide important implications for corporate management strategies to enhance individual companies' R&D capabilities.