• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.109-120
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• 2024

For successful waterproofing construction, it is very important to secure construction quality as well as material performance of waterproofing materials used in construction. Due to the long-term cost reduction policy following the economic downturn in the construction market, most construction companies are using general low-priced waterproof materials rather than high-quality waterproof materials without clear quality control standards. Without clear education on construction, construction is being carried out with meaning only on construction activities. In addition, the waterproofing method applied in combination is a situation where water leakage occurs due to waterproofing failure due to insufficient construction quality because the construction method is complicated. Therefore, it is necessary to review the quality control measures(design, materials, construction) for successful waterproofing work and improve problems that are derived so that stable waterproofing work can be done. In order to expect the leakage prevention effect of a building, first, it is required to select appropriate materials for each part of the building and environment in the design stage, and the selected materials must satisfy all items of the Korean Industrial Standard(KS). Second, to secure the quality of waterproofing construction, sincere construction by workers is required. In this paper, we tried to describe "review of waterproof design", "constructor education", "site inspection", and "criticism(correction/supplementation)" as quality control measures after material selection.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.375-375
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• 2010

CdTe as an absorber material is widely used in thin film solar cells with the heterostructure due to its almost ideal band gap energy of 1.45 eV, high photovoltaic conversion efficiency, low cost and stable performance. The deposition methods and preparation conditions for the fabrication of CdTe are very important for the achievement of high solar cell conversion efficiency. There are some rearranged reports about the deposition methods available for the preparation of CdTe thin films such as close spaced sublimation (CSS), physical vapor deposition (PVD), vacuum evaporation, vapor transport deposition (VTD), closed space vapor transport, electrodeposition, screen printing, spray pyrolysis, metalorganic chemical vapor deposition (MOCVD), and RF sputtering. The RF sputtering method for the preparation of CdTe thin films has important advantages in that the thin films can be prepared at low growth temperatures with large-area deposition suitable for mass-production. The authors reported that the optical and electrical properties of CdTe thin film were closely connected by the thickness-uniformity of the film in the previous study [1], which means that the better optical absorbance and the higher carrier concentration could be obtained in the better condition of thickness-uniformity for CdTe thin film. The thickness-uniformity could be controlled and improved by the some process parameters such as vacuum level and RF power in the sputtering process of CdTe thin films. However, there is a limitation to improve the thickness-uniformity only in the preparation process [1]. So it is necessary to introduce the external or additional method for improving the thickness-uniformity of CdTe thin film because the cell size of thin film solar cell will be enlarged. Therefore, the authors firstly applied the chemical mechanical polishing (CMP) process to improving the thickness-uniformity of CdTe thin films with a G&P POLI-450 CMP polisher [2]. CMP process is the most important process in semiconductor manufacturing processes in order to planarize the surface of the wafer even over 300 mm and to form the copper interconnects with damascene process. Some important CMP characteristics for CdTe were obtained including removal rate (RR), WIWNU%, RMS roughness, and peak-to-valley roughness [2]. With these important results, the CMP process for CdTe thin films was performed to improve the thickness-uniformity of the sputtering-deposited CdTe thin film which had the worst two thickness-uniformities of them. Some optical properties including optical transmittance and absorbance of the CdTe thin films were measured by using a UV-Visible spectrophotometer (Varian Techtron, Cary500scan) in the range of 400 - 800 nm. After CMP process, the thickness-uniformities became better than that of the best condition in the previous sputtering process of CdTe thin films. Consequently, the optical properties were directly affected by the thickness-uniformity of CdTe thin film. The absorbance of CdTe thin films was improved although the thickness of CdTe thin film was not changed.

• Asia pacific journal of information systems
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• v.20 no.3
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• pp.139-166
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• 2010

The supply chain management (SCM) systems have emerged as strong managerial tools for manufacturing firms in enhancing competitive strength. Despite of large investments in the SCM systems, many companies are not fully realizing the promised benefits from the systems. A review of literature on adoption, implementation and success factor of IOS (inter-organization systems), EDI (electronic data interchange) systems, shows that this issue has been examined from multiple theoretic perspectives. And many researchers have attempted to identify the factors which influence the success of system implementation. However, the existing studies have two drawbacks in revealing the determinants of systems implementation success. First, previous researches raise questions as to the appropriateness of research subjects selected. Most SCM systems are operating in the form of private industrial networks, where the participants of the systems consist of two distinct groups: focus companies and vendors. The focus companies are the primary actors in developing and operating the systems, while vendors are passive participants which are connected to the system in order to supply raw materials and parts to the focus companies. Under the circumstance, there are three ways in selecting the research subjects; focus companies only, vendors only, or two parties grouped together. It is hard to find researches that use the focus companies exclusively as the subjects probably due to the insufficient sample size for statistic analysis. Most researches have been conducted using the data collected from both groups. We argue that the SCM success factors cannot be correctly indentified in this case. The focus companies and the vendors are in different positions in many areas regarding the system implementation: firm size, managerial resources, bargaining power, organizational maturity, and etc. There are no obvious reasons to believe that the success factors of the two groups are identical. Grouping the two groups also raises questions on measuring the system success. The benefits from utilizing the systems may not be commonly distributed to the two groups. One group's benefits might be realized at the expenses of the other group considering the situation where vendors participating in SCM systems are under continuous pressures from the focus companies with respect to prices, quality, and delivery time. Therefore, by combining the system outcomes of both groups we cannot measure the system benefits obtained by each group correctly. Second, the measures of system success adopted in the previous researches have shortcoming in measuring the SCM success. User satisfaction, system utilization, and user attitudes toward the systems are most commonly used success measures in the existing studies. These measures have been developed as proxy variables in the studies of decision support systems (DSS) where the contribution of the systems to the organization performance is very difficult to measure. Unlike the DSS, the SCM systems have more specific goals, such as cost saving, inventory reduction, quality improvement, rapid time, and higher customer service. We maintain that more specific measures can be developed instead of proxy variables in order to measure the system benefits correctly. The purpose of this study is to find the determinants of SCM systems success in the perspective of vendor companies. In developing the research model, we have focused on selecting the success factors appropriate for the vendors through reviewing past researches and on developing more accurate success measures. The variables can be classified into following: technological, organizational, and environmental factors on the basis of TOE (Technology-Organization-Environment) framework. The model consists of three independent variables (competition intensity, top management support, and information system maturity), one mediating variable (collaboration), one moderating variable (government support), and a dependent variable (system success). The systems success measures have been developed to reflect the operational benefits of the SCM systems; improvement in planning and analysis capabilities, faster throughput, cost reduction, task integration, and improved product and customer service. The model has been validated using the survey data collected from 122 vendors participating in the SCM systems in Korea. To test for mediation, one should estimate the hierarchical regression analysis on the collaboration. And moderating effect analysis should estimate the moderated multiple regression, examines the effect of the government support. The result shows that information system maturity and top management support are the most important determinants of SCM system success. Supply chain technologies that standardize data formats and enhance information sharing may be adopted by supply chain leader organization because of the influence of focal company in the private industrial networks in order to streamline transactions and improve inter-organization communication. Specially, the need to develop and sustain an information system maturity will provide the focus and purpose to successfully overcome information system obstacles and resistance to innovation diffusion within the supply chain network organization. The support of top management will help focus efforts toward the realization of inter-organizational benefits and lend credibility to functional managers responsible for its implementation. The active involvement, vision, and direction of high level executives provide the impetus needed to sustain the implementation of SCM. The quality of collaboration relationships also is positively related to outcome variable. Collaboration variable is found to have a mediation effect between on influencing factors and implementation success. Higher levels of inter-organizational collaboration behaviors such as shared planning and flexibility in coordinating activities were found to be strongly linked to the vendors trust in the supply chain network. Government support moderates the effect of the IS maturity, competitive intensity, top management support on collaboration and implementation success of SCM. In general, the vendor companies face substantially greater risks in SCM implementation than the larger companies do because of severe constraints on financial and human resources and limited education on SCM systems. Besides resources, Vendors generally lack computer experience and do not have sufficient internal SCM expertise. For these reasons, government supports may establish requirements for firms doing business with the government or provide incentives to adopt, implementation SCM or practices. Government support provides significant improvements in implementation success of SCM when IS maturity, competitive intensity, top management support and collaboration are low. The environmental characteristic of competition intensity has no direct effect on vendor perspective of SCM system success. But, vendors facing above average competition intensity will have a greater need for changing technology. This suggests that companies trying to implement SCM systems should set up compatible supply chain networks and a high-quality collaboration relationship for implementation and performance.

• Korean Chemical Engineering Research
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• v.52 no.5
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• pp.657-666
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• 2014

Coal gasification technology is considered as next generation clean coal technology even though it uses coal as fuel which releases huge amount of greenhouse gas because it has many advantages for carbon capture. Coal or pet-coke slurry gasification is very attractive technology at present and in the future because of its low construction cost and flexibility of slurry feeding system in spite of lower efficiency compared to dry feeding technology. In this study, we carried out gasification experiment using bituminous coal slurry sample by integrating coal slurry feeding facility and slurry burner into existing dry feeding compact gasifier. Especially, our experiment was conducted under fairly lower operation temperature than that of existing entrained-bed gasifier, resulting in partial slagging operation mode in which only part of ash was converted to slag and the rest of ash was released as fly ash. Carbon conversion rate was calculated from data analysis of collected slag and ash, and then cold gas efficiency, which is the most important indicator of gasifier performance, was estimated by carbon mass balance method. Fairly high performance considering pilot-scale experiment, 98.5% of carbon conversion and 60.4% of cold gas efficiency, was achieved. In addition, soundness of experimental result was verified from the comparison with chemical equilibrium composition and energy balance calculations.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.6
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• pp.69-80
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• 2015

This can be promoted collaboration environment for the system and the system is very important for competitiveness, it is equipped. If so, could work in collaboration with members of the organization to promote collaboration what factors? Organizational collaboration and cooperation of many people working, or worth pursuing common goals by sharing information and processes to improve labor productivity, defined as collaboration. Factors that promote collaboration are shared visions, the organization's principles and rules that reflect the visions, on-line system developments, and communication methods. First, it embodies the vision shared by the more sympathetic members are active and voluntary participation in the activities of the organization can be achieved. Second, the members are aware of all the rules and principles of a united whole is accepted and leads to good performance. In addition, the ability to share sensitive business activities for self-development and also lead to work to make this a regular activity to create a team that can collaborate to help the environment and the atmosphere. Third, a systematic construction of the online collaboration system is made efficient and rapid task. According to Student team and A corporation we knew that Cloud services and social media, low-cost, high-efficiency services could achieve. The introduction of the latest information technology changes, the members of the organization's systems and active participation can take advantage of continuing education must be made. Fourth, the company to inform people both inside and outside of the organization to communicate actively to change the image of the company activities, the creation of corporate performance is very important to figure. Reflects the latest trend to actively use social media to communicate the effort is needed. For development of systematic collaboration promoting model steps to meet the organizational role. First, the Chief Executive Officer to make a firm and clear vision of the organization members to propagate the faith, empathy gives a sense of belonging should be able to have. Second, middle managers, CEO's vision is to systematically propagate the organizers rules and principles to establish a system would create. Third, general operatives internalize the vision of the company stating that the role of outside companies must adhere. The purpose of this study was well done in collaboration organizations promoting factors for strategic alignment model based on the golden circle and collaboration to understand and reflect the latest trends in information technology tools to take advantage of smart work and business know how student teams through case analysis will derive the success factors. This is the foundation for future empirical studies are expected to be present.

• Korean Journal of Poultry Science
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• v.18 no.1
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• pp.9-31
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• 1991

The purpose of this study was to investigate the effects of dietary methionine and lysine levels on laying hen performance. The level of protein was fixed 15% during whole experiment period, but the levels of methionine and lysine were 0.30% and 0.58% (Low), 0.32% and 0.64% (Medium), 0.35% and 0 70% (High), respectively. Total 288 laying pullets of 22 weeks age were reared from January 28, 1989 to March 23, 1990 for 60weeks. The results obtained were summarized as follows : 1. The e99 Productions were highest in medium treatment in phase I (22~42weeks of age), phase II (42~62 weeks of age) and phase III (62~82weeks of age) and especially, there was significant difference among treatments during phase II (P＜0.05). 2. Egg weight was significantly increased as the levels of methionine and lysine were increased up to methionine and lysine were 0.32% and 0.64%, respectively(P＜0.01). 3. Daily egg mass was highest when the levels of methionine and lysine were 0.32% and 0.64%, respectively and there were significant differences among treatments during phase I and phase II (P＜0.01) 4. Daily feed intake was increased as the levels of methionine and lysine were increased, and there was significant difference among treatments during phase III (P＜0.05). 5. Feed efficiency was best in medium treatment in phase I and phase II (P＜0.01) 6, Viability was highest in medium treatment, but there was no significant difference among treatments. 7. Nutrient utilizability of experimental diets was not significantly different among treatments. 8. Eviscerated yield was highest and abdominal fat accumulation was lowest in medium treatment, but there was no significant difference among treatments. 9. Egg shell quality and chemical composition of egg content were not different among treatments. 10. The feed cost per kg egg mass was lowest in medium treatment and there were significant differences among treatments in phase I, phase II and whole egg laying period(P＜0.05)

• The Korean Journal of Air & Space Law and Policy
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• v.33 no.2
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• pp.3-34
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• 2018

Korea's air transport industry has a 70-year history since Korea National Airline was establishment in October 1948. Korea has 9 airlines which have international air transport business licenses, and as of 2017, air transport performance(Domestic & International) is ranked 8th in the world. Through analysis of Korea's air transport industry, this paper examines the essential problems of the domestic air transport industry and what policies and laws should be supplemented, and presents an "Policy Directions for the Air Transport Industry" that can continue to grow into a global aviation leading country in the future. Analysis of aviation statistics shows that the nation's air transport industry has a very high growth rate, and national airlines continue to invest in sustainable growth. Furthermore, new companies are also trying to enter the market. As of November 2018, four companies applied for licenses for international air transport business, one for international air transport business (cargo) license, and the Ministry of Land, Infrastructure and Transport is expected to decide whether to issue the license by first quarter of 2019. While some expect price reductions and consumer benefits through competition promotion, others worry about worsening airline financial structures and reducing safety investment due to competition. To sum up the problems of the nation's air transport industry, first, low-cost airlines focus only on attracting domestic demand, and thus have a weak foundation for continued growth. Second, the rapid growth in recent years has led to the lack of aviation professionals such as pilots and technicians and the saturation of slots at major airports. Third, since the financial soundness of airlines is not systematically managed, the financial situation of airlines can quickly deteriorate and the damage can be attributed to consumers. In order for the national airlines to continue to develop, the first is to focus on the endless demand of the global aviation market and to secure international competitiveness. Second, the government should support the airline infrastructure according to the size of the air transport industry, third, we will systematically nurture aviation experts who will lead the future of the nation's air transport industry, and finally, the government will have to continuously manage the financial status of airlines to prevent consumer damage in advance. Nowadays the air transport industry has become very competitive. Not only do airlines have to work hard for the sustainable development of national airlines, but all government agencies must support our airline companies in policy to win international competition.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.11
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• pp.1007-1018
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• 2009

Hydrocyclone is widely used in industry, because of its simplicity in design, high capacity, low maintenance and operational cost. The separation action of a hydrocyclone treating particulate slurry is a consequence of the swirling flow that produces a centrifugal force on the fluid and suspended particles. In spite of hydrocyclone have many advantage, the application for treatment of urban stormwater case study were rare. We conducted a laboratory scale study on treatable potential of micro particles using hydrocyclone filter (HCF) that was a combined modified hydrocyclone with perlite filter cartridge. Since it was not easy to use actual storm water in the scaled-down hydraulic model investigations, it was necessary to reproduce ranges of particles sizes with synthetic materials. The synthesized storm runoff was made with water and addition of particles; ion exchange resin, road sediment, commercial area manhole sediment, and silica gel particles. Experimental studies have been carried out about the particle separation performance of HCF-open system and HCF-closed system. The principal structural differences of these HCFs are underflow zone structure and vortex finder. HCF was made of acryl resin with 120 mm of diameter hydrocyclone and 250 mm of diameter filter chamber and overall height of 800 mm. To determine the removal efficiency for various influent concentrations of suspended solids (SS) and chemical oxygen demand (COD), tests were performed with different operational conditions. The operated maximum of surface loading rate was about 700 $m^3/m^2$/day for HCF-open system, and 1,200 $m^3/m^2$/day for HCF-closed system. It was found that particle removal efficiency for the HCF-closed system is better than the HCF-open system under same surface loading rate. Results showed that SS removal efficiency with the HCF-closed system improved by about 8~20% compared with HCF-open system. The average removal efficiency difference for HCF-closed system between measurement and CFD particle tracking simulation was about 4%.