• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.89-101
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• 2007

This paper investigates the effects of the fusion of multifrequency (C and L bands) polarimetric SAR data in land-cover classification. NASA JPL AIRSAR C and L bands data were used to supervised classification in an agricultural area to simulate the integration of ALOS PALSAR and Radarsat-2 SAR data to be available. Several scattering features derived from target decomposition based on eigen value/vector analysis were used as input for a support vector machines classifier and then the posteriori probabilities for each frequency SAR data were integrated by applying a probabilistic ratio model as a decision level fusion methodology. From the case study results, L band data had the proper amount of penetration power and showed better classification accuracy improvement (about 22%) over C band data which did not have enough penetration. When all frequency data were fused for the classification, a significant improvement of about 10% in overall classification accuracy was achieved thanks to an increase of discrimination capability for each class, compared with the case of L band Shh data.

• Korean Journal of Remote Sensing
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• v.20 no.4
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• pp.235-244
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• 2004

This study focuses on the assessment for proposed algorithm to discriminate cloudy pixels from snowy pixels through use of visible, near infrared, and short wave infrared channel data in VEGETATION-1 sensor embarked on SPOT-4 satellite. Traditional threshold algorithms for cloud and snow masks did not show very good accuracy. Instead of these independent masking procedures, K-Means clustering scheme is employed for cloud/snow discrimination in this study. The pixels used in clustering were selected through an integration of two threshold algorithms, which group ensemble the snow and cloud pixels. This may give a opportunity to simplify the clustering procedure and to improve the accuracy as compared with full image clustering. This paper also compared the results with threshold methods of snow cover and clouds, and assesses discrimination capability in VEGETATION channels. The quality of the cloud and snow mask even more improved when present algorithm is implemented. The discrimination errors were considerably reduced by 19.4% and 9.7% for cloud mask and snow mask as compared with traditional methods, respectively.

• Journal of Korean Society for Quality Management
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• v.47 no.1
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• pp.17-32
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• 2019

Purpose: CMMI is a process model used to assess or improve an organization's software development capabilities. This paper deals with the quality indicators when using CMMI and their priorities for possible improvement. Methods: The 22 process areas and 167 practices of CMMI are matched with 60 indicators of Quality Scorecard(QSC) first to analyze the balance of CMMI in terms of prevention, appraisal, and final result categories and second to isolate a set of key areas for quality focused performance measures. Results: A total of 86.2% (144 out of 167) CMMI practices were mapped to QSC. According to the CMMI level of maturity, level 2 and 3 accounted for more than 75% of the total. The practices at the maturity level of 4 and 5 were mapped to more than 52% of the final result's measurements. It has been observed that CMMI practices need further elaboration at higher levels to consider prevention, appraisal, and final results simultaneously. Conclusion: In order to improve the quality performance of the organization by applying CMMI, the final result measures should be refined in metrics, cycles, and methods, and then corrective actions could be conducted to improve the performance of CMMI practices. This strategy would help the practitioners benefit from CMMI in fostering the overall quality level of key activities for the organization's business goals.

• Journal of Information Science Theory and Practice
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• v.9 no.2
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• pp.66-82
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• 2021

Recommender Systems have gained immense popularity due to their capability of dealing with a massive amount of information in various domains. They are considered information filtering systems that make predictions or recommendations to users based on their interests and preferences. The more recent technology, Linked Open Data (LOD), has been introduced, and a vast amount of Resource Description Framework data have been published in freely accessible datasets. These datasets are connected to form the so-called LOD cloud. The need for semantic data representation has been identified as one of the next challenges in Recommender Systems. In a LOD-enabled recommendation framework where domain awareness plays a key role, the semantic information provided in the LOD can be exploited. However, dealing with a big chunk of the data from the LOD cloud and its integration with any domain datasets remains a challenge due to various issues, such as resource constraints and broken links. This paper presents the challenges of interconnecting and extracting the DBpedia data with the MovieLens 1 Million dataset. This study demonstrates how LOD can be a vital yet rich source of content knowledge that helps recommender systems address the issues of data sparsity and insufficient content analysis. Based on the challenges, we proposed a few alternatives and solutions to some of the challenges.

• Advances in aircraft and spacecraft science
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• v.9 no.3
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• pp.195-215
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• 2022

The increasing interest in CubeSat platforms ant their capability of enlarging the frontier of possible missions impose technology improvements. Miniaturized electrical propulsion (EP) systems enable new mission for multi-unit CubeSats (6U+). While electric propulsion systems have achieved important level of knowledge at equipment level, the investigation of the mutual impact between EP system and CubeSat technology at system level can provide a decisive improvement for both the technologies. The interaction between CubeSat and EP system should be assessed in terms of electromagnetic emissions (both radiated and conducted), thermal gradients, high electrical power management, surface chemical deposition, and quick and reliable data exchanges. This paper shows how a versatile CubeSat Test Platform (CTP), together with standardized procedures and specialized facilities enable the acquisition fundamental and unprecedented information. Measurements can be taken both by specific ground support equipment placed inside the vacuum facility and by dedicated sensors and subsystems installed on the CTP, providing a completely new set of data never obtained before. CTP is constituted of a 6U primary structure hosting the EP system, representative CubeSat avionics and batteries. For the first test campaign, CTP hosts the ambipolar plasma propulsion system, called Regulus and developed by T4I. After the integration and the functional test in laboratory environment, CTP + Regulus performed a Test campaign in relevant environment in the vacuum chamber at CISAS, University of Padua. This paper is focused on the test campaign description and the main results achieved at different power levels for different duration of the firings.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.6
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• pp.395-402
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• 2016

Recently, firms confront to rapid environmental changes due to scientific development and demand change. Firms are trying to improve supply chain capability to react these environmental changes. Being in these improvement processes, it is important to collaborate with other partners in the supply chain. Firms have tried to outsource their in-house activity to other partners and have eliminated wasteful factors in their process and the supply chain is getting leaner. This study investigates the effect of waste factor degree on supply chain performance under external risks. Test results in this paper show that waste level has negative relationship with supply chain performance. The effect of waste level on the supply chain performance is influenced by external risk. As waste level increases, risk has moderating effect between waste level and supply chain performance. That means it is important to focus on utilization, productivity or integration properly for managing the external risk in order to improve the supply chain performance.

• Journal of the Korea Institute of Building Construction
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• v.23 no.5
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• pp.595-605
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• 2023

With the escalating prevalence of modular construction projects, there is a concurrent surge in scholarly and industrial intrigue in this domain, leading to a broadened spectrum of its applications. Modular construction, inherently facilitated by controlled factory settings, boasts the capability to consistently deliver edifices of superior quality. To optimize this advantage, the judicious integration of quality assurance methodologies during the site-specific phases of lifting and assembly is non-negotiable. This research embarked on a survey directed at project stakeholders, aiming to gauge the perceived significance and efficaciousness of prevailing quality preservation and oversight protocols during the aforementioned site stages, subsequently employing the Importance-Performance Analysis(IPA) for data interpretation. The findings elucidated that, while a majority of quality assurance procedures were adeptly executed, perceptual disparities existed among stakeholders regarding certain aspects, prompting recommendations for enhancement. This investigative endeavor lays a foundation, aiding future studies in amplifying the quality assurance cognizance among professionals during modular construction's site-assembly phase.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.275-287
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• 2024

Research on the integration of Knowledge Graphs (KGs) and Language Models (LMs) has been consistently explored over the years. However, studies focusing on the automatic generation of text using the structured knowledge from KGs have not been as widely developed. In this study, we propose a methodology for automatically generating specific domain-related research items (Related Work) at a level comparable to existing papers. This methodology involves: 1) selecting optimal prompts, 2) extracting triples through a four-step refinement process, 3) constructing a knowledge graph, and 4) automatically generating related research. The proposed approach utilizes GPT-4, one of the large language models (LLMs), and is desigend to automatically generate related research by applying the four-step refinement process. The model demonstrated performance metrics of 17.3, 14.1, and 4.2 in Triple extraction across #Supp, #Cont, and Fluency, respectively. According to the GPT-4 automatic evaluation criteria, the model's performamce improved from 88.5 points vefore refinement to 96.5 points agter refinement out of 100, indicating a significant capability to automatically generate related research at a level similar to that of existing papers.

• Information Systems Review
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• v.12 no.1
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• pp.165-188
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• 2010

Recently public and finance SI (system integration) industry is called as 4D (difficult, dangerous, dirty, dreamless) industry because of low profit, overtime works and poor motivation of employees. Even some people think at SI industry to be a labor intensive industry instead of a high technology industry. The current study considers outside environmental change of SI industry as well as inside capability enhancement of SI companies. The study adopted action research method with the author's expertise and experiences as a head of a major SI company in Korea. The current research framework suggests 5 areas of profitability enhancement that offers propositions and implications. 5 areas of profitability enhancement are (1) policy improvement, (2) business portfolio innovation (3) sales capability reinforcement, (4) delivery capability reinforcement, and (5) cost management innovation. The five areas include 11 propositional factors and 21 implementation plans which were chosen from the profitability perspectives of SI companies.In order to successfully execute propositions and implementation plans of the framework, 3 years is needed and after 3 years profitability are expected to increase 10% higher than the current level. The framework, propositions and suggestions in this study are expected to offer a real contribution for SI companies that want to enhance competitiveness and profitability. Future extension of the current study to benchmarking the competitiveness and profitability between local companies and global companieswill bring a solid attention from industry and academics.

• Korean Journal of Construction Engineering and Management
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• v.10 no.5
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• pp.37-46
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• 2009

This research will focus on the public agencies, designers, supervisors, building cooperation, and contractor who involved in urban development plan. By understanding the complexity and the priorities in urban development process, all problems of the urban development projects can be solved or improved. These priorities are specified using AHP (Analytic Hierarchy Process). A questionnaire survey is employed to identify the problems of urban development process and the methods of revitalizing urban in this research. Through the survey, 35 issues are drawn out. Factor analysis technique is applied to extract the underlying interrelationships possibly existing. Using latent root criterion and varimax rotation method, 9 factors are extracted(by using 34 issues after deleting 1 issue less than 0.4 of factor loading) These 9 factors named as PIF (Problem Improvement Factor) consist of integration estimation (PIF1), cooperation operation capability (PIF2), contractor corporation capability (PIF3), capital for infrastructure investment (PIF4), misunderstanding of effective land use (PIF5), financial capability (PIF6), obscure goal of project (PIF7), shortage of cooperation expertise (PIFS), administrative procedures (PIF9). PIF 6 is the most important factor and PIF 1 is the most widely effective factor to succeed urban land development projects. It is recognized that administrative office is most responsible for PIF1 cooperation is most responsible for PIF2, 7, 8 and 9; contractors is most responsible for PIF3 and PIF6; administrative agencies is most responsible for PIF4; cooperation and consultants are responsible for PIF5. From findings in this study, some suggestions are proposed for the revitalization methods of urban development projects through the land readjustment method.