• Title/Summary/Keyword: 효율 향상

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Business Incubator Manager's Competency Characteristics Affect Organizational Commitment and Work Performance : Focused on the Manager's Self-Efficacy (창업보육센터 매니저의 역량 특성이 조직몰입과 업무성과에 미치는 영향 : 매니저의 자기효능감을 중심으로)

  • Park, Sang-Ho;Kang, Shin-Cheol
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.16 no.1
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    • pp.71-85
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    • 2021
  • Representative domestic start-up support organizations include the Business Incubator(BI), Korea Institute of Startup & Entrepreneurship Development(KISED), Techno Park(TP), and Center of Creative Economy Innovation(CCEI), and there are about 260 Business incubator nationwide. The Business incubator is operated by universities, research institutes, and private foundations or associations. The organization consists of the center director and the incubating professionals (hereinafter referred to as "manager"), etc., and performs tasks such as center operation management and incubation support services for tenant companies. Until now, research on the operation of Business Incubator has been mainly focused on the performance of tenant companies. Studies on whether the manager's competency characteristics directly or indirectly affect the performance of the tenant companies through psychological mediators such as self-efficacy and organizational commitment were very scarce. The purpose of this study is to explore various factors influencing organizational commitment and job performance by the competence characteristics of Business incubator managers, and to explain the causal relationship among those factors. In particular, the difference in perception was investigated by a manager's survey that influences organizational commitment and work performance at the Business incubator. Through this, we intend to present practical implications for the role of managers in the operation of Business incubators. This study is an exploratory study, and the subject of the study was a survey of about 600 managers working at Business incubator nationwide, of which 116 responses were analyzed. Data analysis included descriptive statistics, exploratory factor analysis, and reliability. Structural equation model analysis was performed for hypothesis tests. As a result of the analysis, it was found that the cognitive characteristics of the Business incubator manager, communication, and situational response as the behavioral characteristics had a positive effect on the manager's self-efficacy, and the behavioral characteristics had a greater effect on the self-efficacy. It was also found that the manager's cognitive and behavioral characteristics, and self-efficacy had a positive effect on organizational commitment and work performance. In particular, a manager's self-efficacy has a positive effect on organizational commitment and work performance. This result showed that the manager's competency characteristics increase the manager's self-efficacy as a mediating factor rather than directly affecting organizational commitment and work performance. This study explains that the manager's competency characteristics are transferred to organizational commitment and work performance. The results of the study are expected to reflect the job standard of the National Competency Standards (NCS) and basic vocational competency to the job competency of managers, and it also provides a guideline for the effective business incubator operation in terms of human resource management. In practice, it is expected that the results of the study can reflect the vocational basic skills of the Business Incubator manager's job competency in the National Competency Standards(NCS) section, and suggest directions for the operation of the Business Incubator and the manager's education and training.

Development of the forecasting model for import volume by item of major countries based on economic, industrial structural and cultural factors: Focusing on the cultural factors of Korea (경제적, 산업구조적, 문화적 요인을 기반으로 한 주요 국가의 한국 품목별 수입액 예측 모형 개발: 한국의, 한국에 대한 문화적 요인을 중심으로)

  • Jun, Seung-pyo;Seo, Bong-Goon;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.27 no.4
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    • pp.23-48
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    • 2021
  • The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

A Study on Evaluating the Possibility of Monitoring Ships of CAS500-1 Images Based on YOLO Algorithm: A Case Study of a Busan New Port and an Oakland Port in California (YOLO 알고리즘 기반 국토위성영상의 선박 모니터링 가능성 평가 연구: 부산 신항과 캘리포니아 오클랜드항을 대상으로)

  • Park, Sangchul;Park, Yeongbin;Jang, Soyeong;Kim, Tae-Ho
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1463-1478
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    • 2022
  • Maritime transport accounts for 99.7% of the exports and imports of the Republic of Korea; therefore, developing a vessel monitoring system for efficient operation is of significant interest. Several studies have focused on tracking and monitoring vessel movements based on automatic identification system (AIS) data; however, ships without AIS have limited monitoring and tracking ability. High-resolution optical satellite images can provide the missing layer of information in AIS-based monitoring systems because they can identify non-AIS vessels and small ships over a wide range. Therefore, it is necessary to investigate vessel monitoring and small vessel classification systems using high-resolution optical satellite images. This study examined the possibility of developing ship monitoring systems using Compact Advanced Satellite 500-1 (CAS500-1) satellite images by first training a deep learning model using satellite image data and then performing detection in other images. To determine the effectiveness of the proposed method, the learning data was acquired from ships in the Yellow Sea and its major ports, and the detection model was established using the You Only Look Once (YOLO) algorithm. The ship detection performance was evaluated for a domestic and an international port. The results obtained using the detection model in ships in the anchorage and berth areas were compared with the ship classification information obtained using AIS, and an accuracy of 85.5% and 70% was achieved using domestic and international classification models, respectively. The results indicate that high-resolution satellite images can be used in mooring ships for vessel monitoring. The developed approach can potentially be used in vessel tracking and monitoring systems at major ports around the world if the accuracy of the detection model is improved through continuous learning data construction.

Evaluating Global Container Ports' Performance Considering the Port Calls' Attractiveness (기항 매력도를 고려한 세계 컨테이너 항만의 성과 평가)

  • Park, Byungin
    • Journal of Korea Port Economic Association
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    • v.38 no.3
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    • pp.105-131
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    • 2022
  • Even after the improvement in 2019, UNCTAD's Liner Shipping Connectivity Index (LSCI), which evaluates the performance of the global container port market, has limited use. In particular, since the liner shipping connectivity index evaluates the performance based only on the distance of the relationship, the performance index combining the port attractiveness of calling would be more efficient. This study used the modified Huff model, the hub-authority algorithm and the eigenvector centrality of social network analysis, and correlation analysis for 2007, 2017, and 2019 data of Ocean-Commerce, Japan. The findings are as follows: Firstly, the port attractiveness of calling and the overall performance of the port did not always match. However, according to the analysis of the attractiveness of a port calling, Busan remained within the top 10. Still, the attractiveness among other Korean ports improved slowly from the low level during the study period. Secondly, Global container ports are generally specialized for long-term specialized inbound and outbound ports by the route and grow while maintaining professionalism throughout the entire period. The Korean ports continue to change roles from analysis period to period. Lastly, the volume of cargo by period and the extended port connectivity index (EPCI) presented in this study showed a correlation from 0.77 to 0.85. Even though the Atlantic data is excluded from the analysis and the ship's operable capacity is used instead of the port throughput volume, it shows a high correlation. The study result would help evaluate and analyze global ports. According to the study, Korean ports need a long-term strategy to improve performance while maintaining professionalism. In order to maintain and develop the port's desirable role, it is necessary to utilize cooperation and partnerships with the complimentary port and attract shipping companies' services calling to the complementary port. Although this study carried out a complex analysis using a lot of data and methodologies for an extended period, it is necessary to conduct a study covering ports around the world, a long-term panel analysis, and a scientific parameter estimation study of the attractiveness analysis.

Effect of Gastric Cancer Screening on Patients with Gastric Cancer: A Nationwide Population-based Study (위암 환자에서 국가암검진의 효과)

  • Cho, Young Suk;Lee, Sang Hoon;So, Hyun Ju;Kim, Dong Wook;Choi, Yoon Jung;Jeon, Han Ho
    • Journal of Digestive Cancer Reports
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    • v.8 no.2
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    • pp.102-108
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    • 2020
  • Background: This study was performed to evaluate the effect of gastric cancer screening through analysis of screening-related data. Methods: We investigated claims data of gastric cancer from 2009 to 2015. We evaluated whether the screening was performed to prior to registration as patients with gastric cancer. The effect of gastric cancer screening was also analyzed by gender. Results: We collected total 196,293 patients with gastric cancer. 74% of them had previous experience of gastric cancer screening. In patients with screening, early gastric cancer was 33.4% and advanced gastric cancer was 17.3%. 22,548 (15.5%) patients were diagnosed with gastric cancer within 2 years after screening. In the case of patients without screening, early gastric cancer was 15.1% and advanced gastric cancer was 25.3%. In case of men, 76% of them confirmed gastric cancer through screening, and 70.2% of women confirmed the gastric cancer. In both men and women, the rate of early gastric cancer was higher among those with screening than those without screening. Conclusion: In this study, we were able to indirectly confirm the stage shift of gastric cancer screening. However, within 2 years after screening, not a few patients with gastric cancer were diagnosed. Therefore, more studies are warranted to in the future.

Optimized Implementation of Block Cipher PIPO in Parallel-Way on 64-bit ARM Processors (64-bit ARM 프로세서 상에서의 블록암호 PIPO 병렬 최적 구현)

  • Eum, Si Woo;Kwon, Hyeok Dong;Kim, Hyun Jun;Jang, Kyoung Bae;Kim, Hyun Ji;Park, Jae Hoon;Song, Gyeung Ju;Sim, Min Joo;Seo, Hwa Jeong
    • 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.

Monitoring of Concrete Deterioration Caused by Steel Corrosion using Electrochemical Impedance Spectroscopy(EIS) (EIS를 활용한 철근 부식에 따른 콘크리트 손상 모니터링)

  • Woo, Seong-Yeop;Kim, Je-Kyoung;Yee, Jurng-Jae;Kee, Seong-Hoon
    • Journal of the Korea Institute of Building Construction
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    • v.22 no.6
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    • pp.651-662
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    • 2022
  • The electrochemical impedance spectroscopy(EIS) method was used to evaluate the concrete deterioration process related to chloride-induced steel corrosion with various corrosion levels(initiation, rust propagation and acceleration periods). The impressed current technique, with four total current levels of 0C, 13C, 65C and 130C, was used to accelerate steel corrosion in concrete cylinder samples with w/c ratio of 0.4, 0.5, and 0.6, immersed in a 0.5M NaCl solution. A series of EIS measurements was performed to monitor concrete deterioration during the accelerated corrosion test in this study. Some critical parameters of the equivalent circuit were obtained through the EIS analysis. It was observed that the charge transfer resistance(Rc) dropped sharply as the impressed current increased from 0C to 13C, indicating a value of approximately 10kΩcm2. However, the sensitivity of Rc significantly decreased when the impressed current was further increased from 13C to 130C after corrosion of steel had been initiated. Meanwhile, the double-layer capacitance value(Cdl) linearly increased from 50×10-6μF/cm2 to 250×10-6μF/cm2 as the impressed current in creased from 0C to 130C. The results in this study showed that monitoring Cdl is an effective measurement parameter for evaluating the progress of internal concrete damages(de-bonding between steel and concrete, micro-cracks, and surface-breaking cracks) induced by steel corrosion. The findings of this study provide a fundamental basis for developing an embedded sensor and signal interpretation method for monitoring concrete deterioration due to steel corrosion at various corrosion levels.

Priority Analysis of Cause Factors of Safety Valve Failure Mode Using Analytical Hierarchy Process (AHP를 활용한 안전밸브(PSV) 고장모드의 Cause Factors 우선순위 분석)

  • Kim, Myung Chul;Lee, Mi Jeong;Lee, Dong Geon;Baek, Jong-Bae
    • Korean Chemical Engineering Research
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    • v.60 no.3
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    • pp.347-355
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    • 2022
  • The safety valve (PSV) is a safety device that automatically releases a spring when the pressure generated by various causes reaches the set pressure, and is restored to a normal state when the pressure falls below a certain level. Periodic inspection and monitoring of safety valves are essential so that they can operate normally in abnormal conditions such as pressure rise. However, as the current safety inspection is performed only at a set period, it is difficult to ensure the safety of normal operation. Therefore, evaluation items were developed by finding failure modes and causative factors of safety valves required for safety management. In addition, it is intended to provide decision-making information for securing safety by deriving the priority of items. To this end, a Delphi survey was conducted three times to derive evaluation factors that were judged to be important in relation to the Failure Mode Cause Factor (FMCFs) of the safety valve (PSV) targeting 15 experts. As a result, 6 failure modes of the safety valve and 22 evaluation factors of its sub-factors were selected. In order to analyze the priorities of the evaluation factors selected in this way, the hierarchical structure was schematized, and the hierarchical decision-making method (AHP) was applied to the priority calculation. As a result of the analysis, the failure mode priorities of FMCFs were 'Leakage' (0.226), 'Fail to open' (0.201), 'Fail to relieve req'd capacity' (0.152), 'Open above set pressure' (0.149), 'Spuriously' 'open' (0.146) and 'Stuck open' (0.127) were confirmed in the order. The lower priority of FMCFs is 'PSV component rupture' (0.109), 'Fail to PSV size calculation' (0.068), 'PSV Spring aging' (0.065), 'Erratic opening' (0.059), 'Damage caused by improper installation and handling' (0.058), 'Fail to spring' (0.053), etc. were checked in the order. It is expected that through efficient management of FMCFs that have been prioritized, it will be possible to identify vulnerabilities of safety valves and contribute to improving safety.

Studies on the Search for Varieties of higher Sulfur-Containing Protein with Lower Lipoxygenase Activity and their Inheritance and Selection Efficiency for the Breeding of Good Quality Soybean Cultivar 1. Search for Varieties with Higher Sulfur-Containing Amino Acids and their Inheritance and Selection Efficiency (양질콩 품종육성을 위한 고함황단백질 및 Iopoxygenase 저활성도 품종의 탐색과 그의 유전 및 선발효과 1. 고함황 아미노산 품종의 탐색과 그의 유전 및 선발효과)

  • Lee, Hong-Suk;Park, Eui-Ho;Ku, Ja-Hwan;Shim, Jae-Wook
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.38 no.6
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    • pp.499-506
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    • 1993
  • The contents of sulfur, sulfur-containing protein and amino acids of soybean seeds of 518 genotypes as well as their inheritance and selection efficiency in early breeding generation were measured to facilitate breeding for soybean with high sulfur-containing amino acids. Average seed sulfur content of 518 cultivars was 0.33%, and ranged from 0.20 to 0.45%, and that of 30 wild soybeans was 0.35%, and ranged form 0.19 to 0.62%. Correlation coefficients between seed sulfur content and sulfur-containing protein and amino acids were 0.924$^{**}$ and 0.974$^{**}$, respectively. Seed sulfur content was tended to be high in soybean genotypes with late maturity, seed coat bloom, or green cotyledon. Sulfur content had -0.312$^{**}$ correlation coeficient with sugar content and -0.384$^{**}$ with 100 seed weight. Seed sulfur content was inherited quantitatively, in which additive effect was greater than dominant one, and proportion of genes with positive effects was similar to those with negative ones. Estimated narrow- and broad-sense heritabilities were 0.75 and 0.88 for seed sulfur content, respectively. Heritability measured from selection in early breeding lines for high or low seed sulfur content was 60~62.5% or 50~62,5%, respectively. And selection for high sulfur content increased by 14.7~18.8%, whereas that for low one decreased by 8.8~15.6%, when compared to that of random population. Therefore selection in early generation seemed to be clearly effective.

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Analysis of the impact of mathematics education research using explainable AI (설명가능한 인공지능을 활용한 수학교육 연구의 영향력 분석)

  • Oh, Se Jun
    • The Mathematical Education
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    • v.62 no.3
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    • pp.435-455
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    • 2023
  • This study primarily focused on the development of an Explainable Artificial Intelligence (XAI) model to discern and analyze papers with significant impact in the field of mathematics education. To achieve this, meta-information from 29 domestic and international mathematics education journals was utilized to construct a comprehensive academic research network in mathematics education. This academic network was built by integrating five sub-networks: 'paper and its citation network', 'paper and author network', 'paper and journal network', 'co-authorship network', and 'author and affiliation network'. The Random Forest machine learning model was employed to evaluate the impact of individual papers within the mathematics education research network. The SHAP, an XAI model, was used to analyze the reasons behind the AI's assessment of impactful papers. Key features identified for determining impactful papers in the field of mathematics education through the XAI included 'paper network PageRank', 'changes in citations per paper', 'total citations', 'changes in the author's h-index', and 'citations per paper of the journal'. It became evident that papers, authors, and journals play significant roles when evaluating individual papers. When analyzing and comparing domestic and international mathematics education research, variations in these discernment patterns were observed. Notably, the significance of 'co-authorship network PageRank' was emphasized in domestic mathematics education research. The XAI model proposed in this study serves as a tool for determining the impact of papers using AI, providing researchers with strategic direction when writing papers. For instance, expanding the paper network, presenting at academic conferences, and activating the author network through co-authorship were identified as major elements enhancing the impact of a paper. Based on these findings, researchers can have a clear understanding of how their work is perceived and evaluated in academia and identify the key factors influencing these evaluations. This study offers a novel approach to evaluating the impact of mathematics education papers using an explainable AI model, traditionally a process that consumed significant time and resources. This approach not only presents a new paradigm that can be applied to evaluations in various academic fields beyond mathematics education but also is expected to substantially enhance the efficiency and effectiveness of research activities.