• Journal of the Korean Recycled Construction Resources Institute
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• v.2 no.4
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• pp.314-320
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• 2014

Although the cement industry serves as the cornerstone of the construction industry by supplying one of its fundamental materials, it confronts new environmental challenges due to the problem of the $CO_2$ generated from raw materials and fuel used in the cement manufacturing process. Also, concrete structures can be decomposed and reused as construction materials. Simply in terms of the cyclic processing of $CO_2$, recycling waste concrete to manufacture recycled aggregate or recycling waste concrete powder, which is the material for cement can be considered optimally environment-friendly practices. This study contributes to the aim of manufacturing high value added materials that exploits the chemical properties of the waste concrete powder. From the research results, waste concrete powder is feasible to use to produce low carbon type recycled cement.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.455-462
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• 2024

In the construction industry, known for its dynamic and hazardous environments, there exists a crucial demand for effective safety incident prevention. Traditional approaches to monitoring on-site safety, despite their importance, suffer from being laborious and heavily reliant on subjective, paper-based reports, which results in inefficiencies and fragmented data. Additionally, the incorporation of computer vision technologies for automated safety monitoring encounters a significant obstacle due to the lack of suitable training datasets. This challenge is due to the rare availability of safety accident images or videos and concerns over security and privacy violations. Consequently, this paper explores an innovative method to address the shortage of safety-related datasets in the construction sector by employing generative artificial intelligence (AI), specifically focusing on the Stable Diffusion model. Utilizing real-world construction accident scenarios, this method aims to generate photorealistic images to enrich training datasets for safety surveillance applications using computer vision. By systematically generating accident prompts, employing static prompts in empirical experiments, and compiling datasets with Stable Diffusion, this research bypasses the constraints of conventional data collection techniques in construction safety. The diversity and realism of the produced images hold considerable promise for tasks such as object detection and action recognition, thus improving safety measures. This study proposes future avenues for broadening scenario coverage, refining the prompt generation process, and merging artificial datasets with machine learning models for superior safety monitoring.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.916-923
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• 2023

Purpose: Looking at the status of fatal accidents in the construction industry in the 2022 Industrial Accident Status Supplementary Statistics, 27.8% of all fatal accidents in the construction industry are caused by construction equipment. In order to overcome the limitations of tours and inspections caused by the enlargement of sites and high-rise buildings, we plan to build a model that can extract construction equipment using computer vision technology and analyze the model's accuracy and field applicability. Method: In this study, deep learning is used to learn image data from excavators, dump trucks, and mobile cranes among construction equipment, and then the learning results are evaluated and analyzed and applied to construction sites. Result: At site 'A', objects of excavators and dump trucks were extracted, and the average extraction accuracy was 81.42% for excavators and 78.23% for dump trucks. The mobile crane at site 'B' showed an average accuracy of 78.14%. Conclusion: It is believed that the efficiency of on-site safety management can be increased and the risk factors for disaster occurrence can be minimized. In addition, based on this study, it can be used as basic data on the introduction of smart construction technology at construction sites.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.1
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• pp.53-60
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• 2000

In this paper, we developed a character recognition system which could be applied to the automation of construction assembling, and testing process of components by the recognition of characters on the components used in industry department. In this system the image information of each component was caught by the CCD camera and then characters on the images were recognized automatically. If we apply the system to the industrial field it will meet the various requirements such as high productivity, low cost and high qualify products and factory automation.

• The Journal of Economics, Marketing and Management
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• v.6 no.4
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• pp.1-16
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• 2018

Purpose - This study will investigate and identify the relationship between brand image, brand attitude and intent to purchase based on subjects that have remembered or watched more than one storytelling marketing ad related to airlines. The purpose of the project is to secure market competitiveness by presenting the basis for and use of the marketing strategy using storytelling, which can capture the goodwill of the aerospace competition market in the future. Research, design, data, and methodology - Prior to the research model and hypothesis testing phase, a verification factor analysis was conducted to assess internal consistency among each measurement item and to ensure reliability and validity of the measurement tool. Further, the organization was assessed for validity by calculating the mean variance estimation (AVE) and the construction concept reliability (CCR) through a positive factor analysis. Hypothesis verification was analyzed through a structural equation model, and each concept set in the hypothesis was entered as a potential variable, and each measurement item was entered as an observation variable. Results - Airline's storytelling marketing has a significant impact on the brand image and two emotional and cognitive responses have been shown to influence the brand image. In addition, airline storytelling marketing has a significant impact on brand attitudes and airline storytelling marketing derived from factor analysis has shown two emotional and cognitive responses to brand attitudes. Conclusions - The parts derived based on the research results show that storytelling marketing has a strong influence on the airline's brand image and attitude, and that it is necessary for airlines to have a brand image and attitude. Also, forming a favorable brand image has a significant impact on brand attitudes. We believe that by presenting basic data to the aviation industry in future research on airline storytelling, we will be able to increase understanding and contribution to development of storytelling marketing in aviation.

• Ceramist
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• v.22 no.2
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• pp.198-214
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• 2019

The possibility of economic exchange with North Korea is increasing, but there is still a shortage of information of cement industry, which occupies the largest proportion of North Korean construction material industry. Therefore, this study researched the status of cement production facility management using satellite photographs of 16 cement factories in North Korea, and examined the operating status of North Korean cement industry by observing smoke discharged from the chimneys of the cement production facilities. When the satellite photographs were analyzed, it was observed that the monthly stack fog ratio of the North Korean cement factories was 55% in 2016, 60% in 2017 and nearly 65% in 2018. This demonstrates that the average operating ratio has been increasing continuously. However, the operation rate of the five major cement factories reaches the limit, actual cement production is estimated to have maintained the previous level or small increased.

• Journal of Information Technology Services
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• v.1 no.1
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• pp.67-80
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• 2002

This study aims to explore the ways of reinforcing the competitive edge and substance of company through e-business in furniture industry by presenting the e-business model of furniture industry which faces the opportunity of challenge in the course of industrial restructuring. e-business model can take various types depending on the environment, feature and competitive edge that each company faces. For example, it is general in the fields of manufacturing company to study the model by dividing into Sell Side for sales to the customers, and Buy Side for purchase of raw materials, Integrating both sides. In furniture industry, Sell Side has the feature of giving a priority in the quality and price rather than brand image in the purchase type of consumer. Especially, it shall not be overlooked that majority of furniture is delivered to the consumer indirectly through the construction company. As such, e-business should be promoted in a way to expand the point of contact for consumers, rather than to construct its own point of contact for consumers. The percentage of importation of raw lumber is high and the standardization was insufficient in Buy Side.

• Proceedings of the Technology Innovation Conference
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• 1997.12a
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• pp.177-196
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• 1997

The engineering industry plays an important role for national competitive, since it has an high impact on other industries. With its importance, the engineering industry development largely depends on its technical manpower ather than capital factor. This study aims at estimating the additional requirement on technical manpower based on the forecasted market size which represents the structure change corresponding to economic growth in related industry. Research scope includes the twelve of fifteen field except three with insufficient historical data and technical manpower above bachelor degree. Specialty, we forecast market size with determinants resulted from historical data analysis on each field. The demand on technical manpower is derived from the forecasted market. We also estimate an additional requirement with the supply analysis. The research results show different patterns over time period. The relative ratio on chemical and construction to total market will steadily grow over short term, while applied, environment, electronic and information will rapidly grow This pattern will be stabilized over mid or long term. The additional requirement on technical manpower represents the similar pattern to market growth. The research result implies manpower policy for having high inflow of technical engineer from educational institute and the related industries through the image improvement.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.2
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• pp.168-174
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• 2008

Diagnosis on setteability based on human operator's experimental knowledge, which could be established by long term operation, is a limit factor to construction of automation control system in wastewater treatment plant. On-line SVI(Sludge Volume Index) analyzer was developed which can measure SV30 automatically by image capture and image analysis method. In this paper, information got by settling process was studied using On-line SVI analyzer for better operation & management of WWTPs. First, SV30 detection algorithm was developed using image capture and image analysis for settling test and it showed that automatic detection is feasible even if deflocculation and bulking was occurred. Second, turbidity assessment model was developed using image analysis.

• ETRI Journal
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• v.27 no.4
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• pp.385-393
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• 2005

This paper presents an application of digital signal processing to data acquired by the radio imaging method (RIM) that was adopted to measure moisture distribution inside the human body. RIM was originally developed for the mining industry; we are applying the method to a biomedical measurement because of its simplicity, economy, and safety. When a two-dimensional image was constructed from the measured data, the method provided insufficient resolution because the wavelength of the measurement medium, a weak electromagnetic wave in a VHF band, was longer than human tissues. We built and measured a phantom, a model simulating the human body, consisting of two water tanks representing large internal organs. A digital equalizer was applied to the measured values as a weight function, and images were reconstructed that corresponded to the original shape of the two water tanks. As a result, a two-dimensional image containing two individual peaks corresponding to the original two small water tanks was constructed. The result suggests the method was applicable to biomedical measurement by the assistance of digital signal processing. This technique may be applicable to home-based medical care and other situations in which safety, simplicity, and economy are important.