• International conference on construction engineering and project management
• /
• 2009.05a
• /
• pp.890-896
• /
• 2009

In past projects, the main goal has been to enhance efficiency by reducing cost and time. However, considering the current condition of safety management in many construction companies, it can be confirmed that safety management has not been a top priority for a long time. Current safety management, which is based on safety standards and rules, is very ineffective and only emphasizes management after an incident. As well, although fewer accidents occur compared to the past, because construction projects are increasingly large in scale and complex, these accidents tend to be more serious and involve greater monetary loss. Furthermore, as the severity of these accidents increases, so does the possibility of fatalities. Therefore, improving safety management is essential. This study proposes an effective program for safety management, focusing on the processes to connect studies and systems, and the basic techniques required for program development. To realize this program, technical tools are suggested, including systems such as BIM (Building Information Modeling); additionally, the coordination of other systems such as an RTLS, a server, and an alarm system is proposed.

• Journal of Korea Society of Industrial Information Systems
• /
• v.14 no.3
• /
• pp.37-43
• /
• 2009

Steganography conceals the fact that hidden message is being sent on the internet. Steganalysis can be detected the abrupt changes in the statistics of a stego-data. After message embedding, I have analyzed for the statistical significance of the fact the occurrence of differences among the four-neighboring pixels. In this case, when a embedding messages within a images is small, use EC value and chi-square test to determine whether a distribution in an images matches a distribution that shows distortion from stego-data.

• International conference on construction engineering and project management
• /
• 2005.10a
• /
• pp.503-508
• /
• 2005

In the modern, distributed and dynamic construction environment it is important to exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research has demonstrated that (i) a significant percentage of construction data is stored in semi-structured or unstructured data formats (ii) locating and identifying such data that are needed for the important decision making processes is a very hard and time-consuming task. In this paper, an automated methodology for the classification and retrieval of construction images in AEC/FM model based systems will be presented. Specifically, a combination of techniques from the areas of image processing, computer vision, and content-based image retrieval have been deployed to develop a method that can retrieve related construction site image data from components of a project model.

• Annual Conference of KIPS
• /
• 2011.11a
• /
• pp.298-301
• /
• 2011

Edge detection is an base research task in the field of image processing. Edge detection can be regarded as a technique for locating pixels of abrupt gray-level change. So with Gradient method, it can be computed easily. But it can't satisfy human naked eye. so in this paper, new algorithm based on the NLM(Non Local Means) is proposed for good performance for human naked eye.

• International conference on construction engineering and project management
• /
• 2015.10a
• /
• pp.420-424
• /
• 2015

The luffing-tower crane (T/C) is a key facility used in the vertical and horizontal transportation of materials in a tall building construction. Locating the crane in an optimal position is an essential task in the initial stages of construction planning. This paper proposes a new optimization model to locate the luffing T/C in the optimal position to minimize the transportation time. An optimization algorithm, the Harmony Search (HS) algorithm, was used and the results show that HS has high performance characteristics to solve the optimization problem in a short period of time. In a case study, the proposed model offered a better position for T/C than the previous heuristic approach.

• International conference on construction engineering and project management
• /
• 2015.10a
• /
• pp.10-14
• /
• 2015

Unsafe behavior is one of the major causes of construction accidents. Managing the behavior of workers in real-time is difficult and requires huge manpower. In this paper, a new real-time locating framework is proposed to improve safety management by collecting and analyzing data describing the behavior of workers to identify habits that may lead to accidents. The aim of the study is to identify working habits of workers based on their location history. Location data is used to compare with that of other workers and equipment. The results indicate that the reuse of real-time location data can provide extra safety information for safety management and that the proposed system has the potential to prevent struck-by accidents and caught-in between accidents by predicting unwanted interaction between workers and equipment. This adds to current research aimed at automating construction safety to the point where the continuous monitoring, managing and protection of site workers on site is possible.

• Annual Conference of KIPS
• /
• 2023.11a
• /
• pp.563-565
• /
• 2023

Acupuncture and acupressure apply needles or pressure to anatomical points for therapeutic benefit. The over 350 mapped acupuncture points in the human body can each treat various conditions, but anatomical variations make precisely locating these acupoints difficult. We propose a computer vision technique using the real-time hand and face tracking capabilities of the MediaPipe framework to identify acupoint locations. Our model detects anatomical facial and hand landmarks, and then maps these to corresponding acupoint regions. In summary, our proposed model facilitates precise acupoint localization for self-treatment and enhances practitioners' abilities to deliver targeted acupuncture and acupressure therapies.

• Asia pacific journal of information systems
• /
• v.33 no.4
• /
• pp.957-976
• /
• 2023

ChatGPT has had a significant impact on society, business, and academia by influencing individuals and organizations through knowledge generation and supporting users in locating conversational inquiries and answers. It can transform how people seek answers by combining human-like conversational skills with AI. By eradicating the cumbersome process of selecting from multiple options, users can conduct preliminary research or create optimized solutions. The purpose of this research is to investigate how consumers use ChatGPT and digital transformation, specifically in terms of knowledge development, searching and recommending, and optimizing accessible possibilities. Using many linked theories, we address the potential implications and insights that can be gained from ChatGPT's early stages and its integration with other applications such as robotics, service automation, and the metaverse. Finally, the application of ChatGPT has practical, theoretical, and phenomenological impacts, in addition to improving users' experiences.

• International conference on construction engineering and project management
• /
• 2011.02a
• /
• pp.17-22
• /
• 2011

A considerable number of construction disasters occur on pathways. Safety management is usually performed on construction sites to prevent accidents in activity areas. This means that the safety management level of hazards on pathways is relatively minimized. Many researchers have noted that hazard identification is fundamental to safety management. Thus, algorithms for helping safety managers to identify hazardous areas are developed using automated data collection technology. These algorithms primarily search for potential hazardous areas by comparing workers' location logs based on a real-time location system and optimal routes based on BIM. Potential hazardous areas are filtered by identified hazardous areas and activity areas. After that, safety managers are provided with information about potential hazardous areas and can establish proper safety countermeasures. This can help to improve safety on construction sites.

• Journal of the Semiconductor & Display Technology
• /
• v.23 no.2
• /
• pp.38-44
• /
• 2024

This research proposed DBSCAN-D, which is a clustering technique for locating POI based on existing density-based clustering research, such as GPS data, generated by moving objects. This method is designed based on 'staying time' and 'directionality' extracted from the relationship between GPS data. The staying time can be extracted through the difference in the reception time between data using the time at which the GPS data is received. Directionality can be expressed by moving the area of data generated later in the direction of the position of the previously generated data by concentrating on the point where the GPS data is sequentially generated. Through these two properties, it is possible to perform clustering suitable for the data set generated by the moving object.