• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.17-24
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• 2023

A post-processing technique for the measurement signal of a solenoid-type sensor is introduced. The solenoid-type sensor nondestructively evaluates an external tendon of prestressed concrete using the total flux leakage (TFL) method. The TFL solenoid sensor consists of primary and secondary coils. AC electricity, with the shape of a sinusoidal function, is input in the primary coil. The signal proportional to the differential of the input is induced in the secondary coil. Because the amplitude of the induced signal is proportional to the cross-sectional area of the tendon, sectional loss of the tendon caused by ruptures or corrosion can be identified by the induced signal. Therefore, it is important to extract amplitude information from the measurement signal of the TFL sensor. Previously, the amplitude was extracted using local maxima, which is the simplest way to obtain amplitude information. However, because the sampling rate is dramatically decreased by amplitude extraction using the local maxima, the previous method places many restrictions on the direction of TFL sensor development, such as applying additional signal processing and/or artificial intelligence. Meanwhile, the proposed method uses amplitude demodulation to obtain the signal amplitude from the TFL sensor, and the sampling rate of the amplitude information is same to the raw TFL sensor data. The proposed method using amplitude demodulation provides ample freedom for development by eliminating restrictions on the first coil input frequency of the TFL sensor and the speed of applying the sensor to external tension. It also maintains a high measurement sampling rate, providing advantages for utilizing additional signal processing or artificial intelligence. The proposed method was validated through experiments, and the advantages were verified through comparison with the previous method. For example, in this study the amplitudes extracted by amplitude demodulation provided a sampling rate 100 times greater than those of the previous method. There may be differences depending on the given situation and specific equipment settings; however, in most cases, extracting amplitude information using amplitude demodulation yields more satisfactory results than previous methods.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.24-35
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• 2023

Recently, the Ministry of Land, Infrastructure and Transport presented the '6th Construction Technology Promotion Basic Plan' and 'Smart Construction Revitalization Plan (2022.7.20)'. Off-Site Construction (OSC), which involves construction and production of PC (Precast Concrete) and Modular, etc., has advantages in shortening the construction period, reducing costs, improving quality, reducing construction waste, and reducing safety accidents. However, the construction cost is high compared to the traditional RC construction method, which has hindered its utilization and spread. In this study, OSC utilization was improved. An economic analysis indicator and methodology that can support decision-making in the planning and design stages for multi-unit housing were proposed. The factors used in the economic analysis of OSC (based on the PC method) of apartment houses were reviewed. As for the indicators used in the cost and benefit section, 'Construction Period', 'Disaster Occurrence', 'Waste Generation', and 'Greenhouse gas Emission', which reflect the technical advantages of OSC, were derived. In addition, a scenario analysis was conducted based on actual apartment housing case data for the presented economic analysis indicators and benefit calculation standards. The level of benefit that offsets the difference between the existing RC construction method and the construction cost was reviewed. In future studies, it will be necessary to conduct additional case studies to apply the measurement criteria for detailed indicators and supplement the benefit indicators.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.669-681
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• 2023

Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R²)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm², relative error (RE)≤17.9% and validation of R²≥0.56, RMSE≤1.41 ㎍/cm², RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R²=0.80, RMSE=0.94 ㎍/cm², RE=13.9%, and validation showed R²=0.57, RMSE=1.40 ㎍/cm², RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.31-39
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• 2023

The purpose of this study is to propose a scientific performance evaluation framework for measuring and managing the overall outcome of complex types of projects that are linked to public demand-based commercialization, such as information system projects and public procurement, in integrated national R&D projects. In the case of integrated national R&D projects that involve multiple research institutes to form a single final product, and in the case of demand-based demonstration and commercialization of the project results, the existing evaluation system that evaluates performance based on the short-term outputs of the detailed tasks comprising the R&D project has limitations in evaluating the mid- and long-term effects and practicality of the integrated research products. (Moreover, as the paradigm of national R&D projects is changing to a mission-oriented one that emphasizes efficiency, there is a need to change the performance evaluation of national R&D projects to focus on the effectiveness and practicality of the results.) In this study, we propose a performance evaluation framework from a structural perspective to evaluate the completeness of each national R&D project from a practical perspective, such as its effectiveness, beyond simple short-term output, by utilizing the Hourglass model. In particular, it presents an integrated performance evaluation framework that links the top-down and bottom-up approaches leading to Tool-System-Service-Effect according to the structure of R&D projects. By applying the proposed detailed evaluation indicators and performance evaluation frame to actual national R&D projects, the validity of the indicators and the effectiveness of the proposed performance evaluation frame were verified, and these results are expected to provide academic, policy, and industrial implications for the performance evaluation system of national R&D projects that emphasize efficiency in the future.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1211-1224
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• 2023

Clouds cause many difficult problems in observing land surface phenomena using optical satellites, such as national land observation, disaster response, and change detection. In addition, the presence of clouds affects not only the image processing stage but also the final data quality, so it is necessary to identify and remove them. Therefore, in this study, we developed a new cloud detection technique that automatically performs a series of processes to search and extract the pixels closest to the spectral pattern of clouds in satellite images, select the optimal threshold, and produce a cloud mask based on the threshold. The cloud detection technique largely consists of three steps. In the first step, the process of converting the Digital Number (DN) unit image into top-of-atmosphere reflectance units was performed. In the second step, preprocessing such as Hue-Value-Saturation (HSV) transformation, triangle thresholding, and maximum likelihood classification was applied using the top of the atmosphere reflectance image, and the threshold for generating the initial cloud mask was determined for each image. In the third post-processing step, the noise included in the initial cloud mask created was removed and the cloud boundaries and interior were improved. As experimental data for cloud detection, CAS500-1 L2G images acquired in the Korean Peninsula from April to November, which show the diversity of spatial and seasonal distribution of clouds, were used. To verify the performance of the proposed method, the results generated by a simple thresholding method were compared. As a result of the experiment, compared to the existing method, the proposed method was able to detect clouds more accurately by considering the radiometric characteristics of each image through the preprocessing process. In addition, the results showed that the influence of bright objects (panel roofs, concrete roads, sand, etc.) other than cloud objects was minimized. The proposed method showed more than 30% improved results(F1-score) compared to the existing method but showed limitations in certain images containing snow.

• Journal of Venture Innovation
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• v.5 no.4
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• pp.135-156
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• 2022

This study attempted to identify the factors affecting entrepreneurial intention and to confirm the moderating effect of social support that plays a positive role in increasing entrepreneurial intention. The subjects of the study were 419 ordinary people, and data were obtained online and analyzed. The analysis method of this study was based on the SPSS statistical program Ver. 24, and a hierarchical regression analysis method was conducted to analyze the moderating effect. The results of hypothesis verification analysis in this study are as follows. First, innovativeness, risk-taking, self-fulfillment, economic motivation, immersion in a drama, drama role model, and indirect experience, all had a significant positive(+) effect on entrepreneurial intention. Second, among the factors affecting entrepreneurial intention, self-fulfillment was found to have the greatest influence. Third, it was confirmed that the moderating effect of social support between various variables and entrepreneurial intention had a significant effect on innovativeness, self-fulfillment, drama role model, and indirect experience, and entrepreneurial intention. The academic value of this study is to confirm the effect of drama characteristic variables on entrepreneurial intention. In addition, it was possible to confirm the moderating effect of social support, which is the total of individual external support. The implication of this study is that the desire for achievement had the greatest influence on entrepreneurial intention. Therefore, it is necessary to develop a desire to achieve in start-up support policies and start-up education. In addition, in light of the ripple effect of TV dramas, drama role model and indirect experience increase entrepreneurial intention, so it was possible to predict its influence on changes in perception of start-ups and entrepreneurs.

• Journal of Venture Innovation
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• v.6 no.3
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• pp.149-164
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• 2023

Today, when innovation and creativity become increasingly important, management of human resources is a key factor for corporate performance and competitive advantage. Corporate are implementing and introducing various types of support methods for members to achieve goals and improve organizational performance. Organizational culture and organizational trust affect the cognitive and emotional state of members. Furthermore, it can bring about changes in organizational performance such as job stress and job satisfaction. From an institutional point of view, work-life balance is also a major factor affecting organizational performance. The imbalance between work and life leads to a decline in organizational performance, such as decreased morale and dissatisfaction with work. In relation to work-life balance, the low birth rate problem intensified and the importance began to emerge. Therefore, the government has implemented various policy support for workers' work-life balance, and the "52-hour workweek" is a representative example. This study analyzed the effect of organizational culture applying the competitive value model on workers' job stress. In addition, the mediating effects of overtime work per week and organizational trust were analyzed. Job stress corresponds to a prerequisite stage that affects job commitment, job satisfaction, and turnover intention. However, research measuring job stress by organizational performance is insufficient. In addition, there are few studies analyzing the relationship between overtime and organizational performance. Considering this, it is necessary to understand the influence relationship. The results of the study are as follows. First, a hierarchical culture increases the job stress of workers. On the other hand, innovation-oriented, relationship-oriented, and competition-oriented corporate culture reduce job stress. Second, a hierarchical culture has reduced trust in the organization, and other organizational cultures have increased trust in the organization. Third, relationship-oriented and competition-oriented organizational culture reduced overtime. Innovation-oriented, hierarchical-oriented culture increased overtime Fourth, organizational trust and overtime have the effect of mediating organizational culture and job stress. Based on these analysis results, this study presented academic and political implications.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.6
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• pp.697-703
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• 2023

As a part of the global industrial efforts to reduce environmental pollution owing to air pollution, regulations have been established by the International Maritime Organization (IMO). The IMO has implemented various regulations such as EEXI, EEDI, and CII to reduce air pollution emissions from ships. They are also promoting measures to decrease the power consumption in ships, aiming to conserve energy. Most of the power used in ships is consumed by electric motors. Among the motors installed on ships, the engine room blower that takes up a significant load, operates at a constant irrespective of demand. Therefore, energy savings can be expected through frequency control. In this study, we demonstrated the efficacy of energy savings by controlling the frequency of the electric motor of the generator blower that supplies combustion air to the generator's turbocharger. The system was modeled based on the output data of the turboharger outlet temperature in response to the blower frequency inpu. A PI control system was established to control the frequency with the target being the turbocharger outlet temperature. By maintaining the turbocharger design standard outlet temperature and controlling the blower frequency, we achieved an annual energy saving of 15,552kW in power consumption. The effectiveness of energy savings through frequency control of blower fans was verified during the summer (April to September) and winter (March to October) periods. Based on this, we achieved annual fuel cost savings of 6,091 thousand won and reduction of 8.5 tons of carbon dioxide, 2.4 kg of SOx, and 7.8 kg of NOx air pollutants on the training ship.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.77-90
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• 2023

This study aims to investigate the potential of alternative credit assessment through Social Networking Sites (SNS) as a complementary tool to conventional loan review processes. It seeks to discern the impact of SNS usage characteristics and loan product attributes on credit loan repayment. To achieve this objective, we conducted a binomial logistic regression analysis examining the influence of SNS usage patterns, loan characteristics, and personal attributes on credit loan conditions, utilizing data from Company A's credit loan program, which integrates SNS data into its actual loan review processes. Our findings reveal several noteworthy insights. Firstly, with respect to profile photos that reflect users' personalities and individual characteristics, individuals who choose to upload photos directly connected to their personal lives, such as images of themselves, their private circles (e.g., family and friends), and photos depicting social activities like hobbies, which tend to be favored by individuals with extroverted tendencies, as well as character and humor-themed photos, which are typically favored by individuals with conscientious traits, demonstrate a higher propensity for diligently repaying credit loans. Conversely, the utilization of photos like landscapes or images concealing one's identity did not exhibit a statistically significant causal relationship with loan repayment. Furthermore, a positive correlation was observed between the extent of SNS usage and the likelihood of loan repayment. However, the level of SNS interaction did not exert a significant effect on the probability of loan repayment. This observation may be attributed to the passive nature of the interaction variable, which primarily involves expressing sympathy for other users' comments rather than generating original content. The study also unveiled the statistical significance of loan duration and the number of loans, representing key characteristics of loan portfolios, in influencing credit loan repayment. This underscores the importance of considering loan duration and the quantity of loans as crucial determinants in the design of microcredit products. Among the personal characteristic variables examined, only gender emerged as a significant factor. This implies that the loan program scrutinized in this analysis does not exhibit substantial discrimination based on age and credit scores, as its customer base predominantly consists of individuals in their twenties and thirties with low credit scores, who encounter challenges in securing loans from traditional financial institutions. This research stands out from prior studies by empirically exploring the relationship between SNS usage and credit loan repayment while incorporating variables not typically addressed in existing credit rating research, such as profile pictures. It underscores the significance of harnessing subjective, unstructured information from SNS for loan screening, offering the potential to mitigate the financial disadvantages faced by borrowers with low credit scores or those ensnared in short-term liquidity constraints due to limited credit history a group often referred to as "thin filers." By utilizing such information, these individuals can potentially reduce their credit costs, whereas they are supposed to accrue a more substantial financial history through credit transactions under conventional credit assessment system.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.15-31
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• 2022

This study was conducted to suggest a start-up policy that includes start-up education and support for active seniors with various careers who try to change their careers before and after retirement. From this point of view, this study divided the factors affecting the entrepreneurial will of active seniors into entrepreneurship organizational and functional competency and identified the effect of these competencies on entrepreneurial efficacy and entrepreneurial intention. In the proposed model, start-up competency is divided into organizational competency (leadership, creativity problem-solving, communication, decision-making) and functional competency (management strategy, marketing, business plan). And this study examined the mediating role of entrepreneurial efficacy in the relationship between entrepreneurial competency factors and entrepreneurial intention. Meanwhile, PLS-POS analysis was performed to uncover the heterogeneity and pattern in the proposed structural model. The survey was conducted with the help of an online survey company from November 27 to December 15, 2020 for the active senior age group from 40 to under 65 years old. Data were collected from a total of 433 panelists and analyzed using SPSS 22.0 and SmartPLS 3.3.7 programs. The findings are as follows. First, the finding shows that the entrepreneurial organizational and functional competencies of active seniors had significant positive(+) effects on entrepreneurial efficacy. Second, the result shows that entrepreneurial organizational and functional competencies of active seniors had significant positive(+) effects on entrepreneurial intention. Third, the findings show that entrepreneurship efficacy had a significantly positive(+) effect on entrepreneurial intention. The findings of PLS-POS show that entrepreneurship education needs to be carried out by identifying the needs that require entrepreneurial organizational and functional competency when training for entrepreneurship competency. In summary, the findings of the current study are to determine what the competency factors are for the government (local government) to increase the policy direction necessary for establishing and implementing entrepreneurship education and training programs to develop policies to enhance the economic activity participation rate of active seniors.