• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.954-964
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• 2020

In immersive media, the most important factor that provides immersion is depth information. Therefore, it is essential to obtain high quality depth information in order to produce high quality immersive media. In this paper we propose an algorithm to improve depth map, considering the segmentation of images and the relationship between multiple views in multi-view systems. The proposed algorithm uses a super-pixel segmentation technique to divide the depth map of the reference view into several segments, and project each segment into adjacent view. Subsequently, the depth map of the adjacent view is improved using plane estimation using the information of the projected segment, and then reversed to the reference view. This process is repeated for several adjacent views to improve the reference depth map by updating the values of the improved adjacent views and the initial depth map of the reference view. Through simulation, the proposed algorithm is shown to surpass the conventional algorithm subjectively and objectively.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.318-323
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• 2011

Illegal and unethical behaviors of the construction industry affect people's lives and health more than the same problems of the other industries. Among these behaviors, the construction industry is mostly criticized for bribery scandals. According to the survey of the Ministry of Justice in Taiwan over the past years, bribery cases involving public engineering projects and governmental procurements account for a rather large portion of the indicted corruption cases. Transparency International's "Bribe Payer Index" indicates people in construction-related industries are the most likely to pay bribes. Poor construction quality directly and indirectly caused by bribery poses a great threat to public safety, organizational reputation and economic development. However, there is a limited number of existing research on the bribery problem of the construction industry. This study is an empirical attempt to explore bribery intention and its affecting factors among the construction organizations in Taiwan by conducting a questionnaire survey. The theory of planned behavior was used in this study to build its research model (covering elements of attitude, subjective norm, perceived behavior control, and intention). Totally 431 valid samples were returned. To explore the factors affecting bribery intention, this study adopted Pearson's correlation analysis to discuss about the connections among the questionnaire respondents' attitudes to bribery, subjective norms, perceived behavior control, and bribery intention. A multi-regression analysis was then conducted to test if the planned behavior theory can effectively predict bribery intention. The research found (1) according to the results of Pearson's correlation analysis, the respondents' bribery intention, attitudes, subjective norms, and perceived behavior control are positively correlated with one another; (2) according to the results of the multi-regression analysis, bribery intention can be explained through attitudes, subjective norms, and perceived behavior control with an adjusted R² value of 0.591, meaning 59.1% of the bribery intention's variances can be explained through the three dimensions. In addition, each of the three dimensions has a significant influence on the respondents' behavior intentions.

• Advances in Computational Design
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• v.8 no.4
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• pp.309-325
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• 2023

An innovative inertial reactive armor is being developed through a multi-discipline project. Unlike the well-known explosive or non-explosive reactive armour that uses high-energy explosives or bulging effect, the proposed inertial reactive armour uses active disc elements that is set to rotate rapidly upon impact to effectively deflect and disrupt shaped charges and kinetic energy penetrators. The effectiveness of the proposed armour highly depends on the tangential velocity of the impact point on the rotating disc. However,for a single layer armour with an array of high-speed rotating discs, the tangential velocity is relatively low near the center of the disc and is not available between the gap of the discs. Therefore, it is necessary to configure the armor with double layers to increase the tangential velocity at the point of impact. This paper explores a multi-objective geometry design optimization for the double-layered armor using Nelder-Mead optimization algorithm and integration tools of the python programming language. The optimization objectives include maximizing both average tangential velocity and high tangential velocity areas and minimizing low tangential velocity area. The design parameters include the relative position (translation and rotation) of the disc element between two armor layers. The optimized design results in a significant increase of the average tangential velocity (38%), increase of the high tangential velocity area (71.3%), and decrease of the low tangential velocity area (86.2%) as comparing to the single layer armor.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.585-594
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• 2024

In recent years, the construction industry has rapidly adopted offsite-manufacturing and distributed construction methods. This change brings a variety of challenges requiring innovative solutions, such as the utilization of AI-driven and generative design. Numerous studies have explored the concept of multi-objective generative design with genetic algorithms in construction. However, this paper highlights the challenges and proposes a solution for combining generative design with distributed construction to address the need for agility in design. To achieve this goal, the research delves into the development of a multi-objective generative design optimization using a weighted genetic algorithm based on simulated annealing. The specific design case adopted is an educational complex. The proposed process strives for scalable economic viability, environmental comfort, and operational efficiency by optimizing modular configurations of architectural spaces, facilitating affordable, scalable, and optimized construction. Rhino-Grasshopper and Galapagos design tools are used to create a virtual environment capable of generating architectural configurations within defined boundaries. Optimization factors include adherence to urban regulations, acoustic comfort, and sunlight exposure. A normalized scoring approach is also presented to prioritize design preferences, enabling systematic and data-driven design decision-making. Building Information Modeling (BIM) tools are also used to transform the optimization results into tangible architectural elements and visualize the outcome. The resulting process contributes both to practice and academia. Practitioners in AEC industry could gain benefit through adopting and adapting its features with the unique characteristics of various construction projects while educators and future researchers can modify and enhance this process based on new requirements.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1311-1311
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• 2024

Recent advances in artificial intelligence technology have led to active research aimed at systematically managing the productivity and environmental impact of major management targets such as heavy equipment at construction sites. However, challenges arise due to phenomena like partial occlusions, resulting from the dynamic working environment of construction sites (e.g., equipment overlapping, obstruction by structures), which impose practical constraints on precisely monitoring heavy equipment. To address these challenges, this study aims to enhance automated multi-object tracking (MOT) in scenarios involving long-term occlusions across consecutive frames for heavy construction equipment. To achieve this, two methodologies are employed to address long-term occlusions at construction sites: (i) tracking-by-detection and (ii) video inpainting with generative adversarial networks (GANs). Firstly, this study proposes integrating FairMOT with a tracking-by-detection algorithm like ByteTrack or SMILEtrack, demonstrating the robustness of re-identification (Re-ID) in occlusion scenarios. This method maintains previously assigned IDs when heavy equipment is temporarily obscured and then reappears, analyzing location, appearance, or motion characteristics across consecutive frames. Secondly, adopting video inpainting with GAN algorithms such as ProPainter is proposed, demonstrating robustness in removing objects other than the target object (e.g., excavator) during the video preprocessing and filling removed areas using information from surrounding pixels or other frames. This approach addresses long-term occlusion issues by focusing on a single object rather than multiple objects. Through these proposed approaches, improvements in the efficiency and accuracy of detection, tracking, and activity recognition for multiple heavy equipment are expected, mitigating MOT challenges caused by occlusions in dynamic construction site environments. Consequently, these approaches are anticipated to play a significant role in systematically managing heavy equipment productivity, environmental impact, and worker safety through the development of advanced construction and management systems.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.125-140
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• 2018

Due to rapid development of semiconductor technology, embedded systems have been developed from single-functional system to the multi-functional system. The system composed of software that has different criticality level is called Mixed-Criticality System. Currently, the project related to the Mixed-Criticality System is accelerating the efforts to seek the development direction and take technical initiatives led by EU and USA where the related industry has developed, but the movement in Korea is yet insignificant. Therefore, it is urgent to perform the research and project of various basic technologies to occupy the initiative for the related technology and market. In this paper, we analyze the trends of major project researches and developments related to the MCS. First, after defining the definition of the MCS and system model, we analyze the underlying technology constituting the MCS. In addition, we analyze the project trends of each country researching MCS and discuss the future research areas. Through this study, it is possible to grasp the research trends of the world in order to establish the research direction of the MCS and to lay the foundation for the integration into the military system.

• Journal of Wetlands Research
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• v.16 no.4
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• pp.463-476
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• 2014

The riverine wetlands located in the riverside bring about social conflicts through confrontation between flood control value through flood control project and ecological preservation value of riverine wetland. In this study, we identified the importance of both values through analysis of economic feasibility of flood control and ecological values of riverine wetland, and tried to suggest management plans for riverine wetland considering both of flood control safety and ecological preservation through these results. For this, we calculated the expected annual flood damage of Imjin River using the multi-dimensional flood damage analysis(MD-FDA), and calculated the total value of riverine wetland using the contingent valuation method(CVM) to estimate preservation value of riverine wetland. The result of the analysis shows that the Imjin River needs flood control project and the ecological preservation of riverine wetland is also important. Therefore, the establishment of the management plan for protecting riverine wetland is also needed. As a result, the Imjin riverine wetland was classified as the area where sedimentation continues to take place, and the flood water level to rise. On the basis of the analyzed results, it is judged that the Imjin River needs flood control for public safety and ecological consideration for ecosystem preservation in the river improvement project. So, the stepwise river improvement is desirable to protect riverine wetland and minimize ecosystem disturbance. The results is expected to be made good use as the basic study for establishment of institutional river management plans considering flood control project and riverine wetland preservation in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.301-310
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• 2006

Typically, we needs enormous national budget for the flood control project and so the project usually has big influence on the national economy. Therefore, the reliable estimation of flood damage is the key issue for the economic analysis of the flood control project. This study aims to provide a GIS based technique for distributed flood damage estimation. We consider two aspects of engineering and economic sides, which are the inundation analysis and MD-FDA (Multi-Dimensional Flood Damage Analysis), for the flood damage assessment. We propose the analysis framework and data processing using GIS for assessing flood damages. The proposed methodology is applied to the flood control channel project for flood disaster prevention in Mokgamcheon/Dorimcheon streams and this study presents the detailed GIS database and the assessment results of flood damages. This study may have the worth in improving practical usability of MD-FDA and also providing research direction for combining economic side with the engineering aspect. Also this distributed technique will help decision-making in evaluating the feasibility of flood damage reduction programs for structural and nonstructural measures.

• Journal of the Korea Society of Computer and Information
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• v.28 no.10
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• pp.123-132
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• 2023

Git's commit messages manage the history of source changes during project progress or operation. By utilizing this historical data, project risks and project status can be identified, thereby reducing costs and improving time efficiency. A lot of research related to this is in progress, and among these research areas, there is research that classifies commit messages as a type of software maintenance. Among published studies, the maximum classification accuracy is reported to be 95%. In this paper, we began research with the purpose of utilizing solutions using the commit classification model, and conducted research to remove the limitation that the model with the highest accuracy among existing studies can only be applied to programs written in the JAVA language. To this end, we designed and implemented an additional step to standardize source change data into natural language using GPT. This text explains the process of extracting commit messages and source change data from Git, standardizing the source change data with GPT, and the learning process using the DistilBERT model. As a result of verification, an accuracy of 91% was measured. The proposed model was implemented and verified to ensure accuracy and to be able to classify without being dependent on a specific program. In the future, we plan to study a classification model using Bard and a management tool model helpful to the project using the proposed classification model.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.100-103
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• 2008

Recently Development of construction system that subjective operators share and control information efficiently based on the three-dimensional space and design information throughout life cycle of construction project is progressing dynamically. In case of civil structures which are infrastructure, Demand for structure of complex system which has multi-functions such as super and smart bridges and express rails is increasing and system development which computerizes and integrates process of structure design is in need. For that, research about link way between three dimensional modeling data and structure analysis programs should be preceded. In this research, therefore, research about interface design between three dimensional virtual modeling data to automate efficient civil-structure-design and nonlinear finite element analysis program which is made up of reinforced concrete material model that express material's character clearly.