• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.75-83
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• 2024

This study examined the causes and remedies of bid-rigging in the construction industry through a survey of procurement practitioners. The study identified potential problems from the business, construction, and bidding environments, and proposed improvements to the procurement and bidding systems to address these problems. The study found that transparency, fairness, and diversity are important factors in reducing bid-rigging. These factors can be achieved through a variety of measures, such as expanding bidding systems, strengthening fairness standards, and increasing the diversity of participating companies. The study also found that unfair subcontracting regulations are a problem that needs to be addressed. There were differences in the perceptions of the causes of bid-rigging between the general and specialized construction groups. However, there was no difference in the perceptions of improvements to the procurement system between the two groups. This suggests that a consistent solution to bid-rigging can be found. The study's findings are expected to contribute to the resolution and prevention of bid-rigging in the construction industry.

• Smart Media Journal
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• v.13 no.5
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• pp.52-61
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• 2024

The onset of the COVID-19 pandemic has accelerated social transformations across various nations. These changes, particularly prominent in the corporate and industrial sectors, have necessitated a shift towards increased remote activities, fundamentally altering societal structures. Within this context, the concept of the Metaverse, a virtual world existing since the early 2000s but previously underrecognized, began to gain widespread recognition. In South Korea, major tech companies such as Naver, Kakao, and Coupang have long normalized remote working, with new employee orientations also taking place on Metaverse platforms. Beyond the IT sector, institutions requiring large gatherings, such as schools, have adopted the Metaverse for hosting major events like welcome ceremonies and informational sessions. This phenomenon suggests that the Metaverse is not merely a transient social trend but is gradually integrating into the daily lives of the general populace, serving as a significant social connector. This study explores the potential of Metaverse-enabled design thinking and methodologies to address the Environmental, Social, and Governance (ESG) challenges faced by Korean society. Specifically, the research focuses on developing solutions for social issues related to pets in Korea.

• Smart Media Journal
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• v.12 no.11
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• pp.27-35
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• 2023

Fourth Industrial Revolution and COVID-19 pandemic have boosted the use of Government 24 app for public service complaints in the era of non-face-to-face interactions. there has been a growing influx of complaints and improvement demands from users of public apps. Furthermore, systematic management of public apps is deemed necessary. The aim of this study is to analyze the grievances of Government 24 app users, understand the current dissatisfaction among citizens, and propose potential improvements. Data were collected from the Google Play Store from May 2, 2013, to June 30, 2023, comprising a total of 6,344 records. Among these, 1,199 records with a rating of 1 and at least one 'thumbs-up' were used for topic modeling analysis. The analysis revealed seven topics: 'Issues with certificate issuance,' 'Website functionality and UI problems,' 'User ID-related issues,' 'Update problems,' 'Government employee app management issues,' 'Budget wastage concerns ((It's not worth even a single star) or (It's a waste of taxpayers' money)),' and 'Password-related problems.' Furthermore, the overall trend of these topics showed an increase until 2021, a slight decrease in 2022, but a resurgence in 2023, underscoring the urgency of updates and management. We hope that the results of this study will contribute to the development and management of public apps that satisfy citizens in the future.

• Annals of Occupational and Environmental Medicine
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• v.35
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• pp.39.1-39.14
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• 2023

Background: Diseases affecting the lungs and airways contribute significantly to the global burden of disease. The problem in low- and middle-income countries appears to be exacerbated by a shift in global manufacturing base to these countries and inadequate enforcement of environmental and safety standards. In Ghana, the potential adverse effects on respiratory function associated with occupational wood dust exposure have not been thoroughly investigated. Methods: Sixty-four male sawmill workers and 64 non-woodworkers participated in this study. The concentration of wood dust exposure, prevalence and likelihood of association of respiratory symptoms with wood dust exposure and changes in pulmonary function test (PFT) parameters in association with wood dust exposure were determined from dust concentration measurements, symptoms questionnaire and lung function test parameters. Results: Sawmill workers were exposed to inhalable dust concentration of 3.09 ± 0.04 mg/m³ but did not use respirators and engaged in personal grooming habits that are known to increase dust inhalation. The sawmill operators also showed higher prevalence and likelihoods of association with respiratory symptoms, a significant cross-shift decline in some PFT parameters and a shift towards a restrictive pattern of lung dysfunction by end of daily shift. The before-shift PFT parameters of woodworkers were comparable to those of non-woodworkers, indicating a lack of chronic effects of wood dust exposure. Conclusions: Wood dust exposure at the study site was associated with acute respiratory symptoms and acute changes in some PFT parameters. This calls for institution and enforcement of workplace and environmental safety policies to minimise exposure at sawmill operating sites, and ultimately, decrease the burden of respiratory diseases.

• Journal of Ecology and Environment
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• v.48 no.1
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• pp.17-23
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• 2024

Background: Honey bees play a crucial role in pollination and ecological balance. Apis mellifera L. colonies, especially those located in specific geographic regions, such as the palm garden in Eastern Thailand, are susceptible to potential threats from microbial contaminants. Understanding and detecting microbial organisms in these beehives is essential for the preservation of bee health, honey production, and the broader ecosystem. However, the problem of microbial infection and antibiotic-resistant bacteria is more severe and continuously increasing, resulting in a health, economic, and social crisis. The purpose of this study is to determine the prevalence of microorganisms in A. mellifera beehives in palm gardens in Rayong province, Eastern Thailand. Results: Ten swabs in transport media were swabbed and obtained from different parts of each beehive (1 swab per beehive), for a total of 10 hives. Traditional microbial culture-based methods, biochemical tests, and antimicrobial susceptibility (disc-diffusion) tests were used to detect microbial organisms and antibiotic resistance in bacteria. The swab tests from nine beehives resulted in the detection of Gram-positive bacteria (63.64%), Gram-negative bacteria (27.27%), and fungi/yeast (9.09%). These microorganisms are classified as a group of coagulase-negative Staphylococcus spp. and made up 40.91% of the bacteria discovered. Other bacteria found were Coryneform bacteria (13.64%), Pantoea spp. (13.64%), Bacillus spp. (9.09%), yeast (9.09%), glucose non-fermentative Gram-negative bacilli (9.09%), and Pseudomonas spp. (4.55%). However, due to the traditional culture-based and 0biochemical tests usually used to identify the microbial organisms in clinical specimens and the limitation of identifying some environmental microbial species, the results of the antimicrobial susceptibility test cannot reveal if the organism is resistant or susceptible to the drug. Nevertheless, drug-sensitive inhibition zones were formed with each antibiotic agent. Conclusions: Overall, the study supports prevention, healthcare, and public health systems. The contamination of microorganisms in the beehives may affect the quality of honey and other bee products or even the health of the beekeeper. To avoid this kind of contamination, it is therefore necessary to wear personal protective equipment while harvesting honey and other bee products.

• Journal of Service Research and Studies
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• v.14 no.3
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• pp.231-250
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• 2024

This research aims to enhance donor engagement by increasing the transparency of nonprofit donation platforms. Donations are primarily based on social trust, and a lack of transparency on these platforms can significantly reduce donor motivation. To address this issue, the study analyzes the user experience of existing donation platforms, identifies problems, and explores potential improvements. The research began with a literature review to examine the social need for donations and their effectiveness. The findings indicate that donors place a high value on transparency and are less willing to donate when this element is lacking. Specifically, when donors can clearly see how their contributions are being utilized, they experience greater psychological satisfaction and are more likely to continue donating. The study analyzed various platforms to identify issues causing user discomfort and compared elements aimed at enhancing transparency. By employing the KJ affinity method and the Double Diamond process, the study aimed to understand the problem's nature and propose solutions considering the interactions between donors and nonprofits. A key conclusion is the critical importance of making information more accessible and intuitive. The findings suggest that greater transparency can help build donor trust, improve nonprofit efficiency, and contribute to a more robust giving ecosystem. Additionally, platforms with increased transparency facilitate ongoing communication between donors and nonprofits, fostering an environment where donors become more actively engaged in their giving. This strategy is expected to play a vital role in promoting a sustainable culture of giving based on mutual trust.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1326-1327
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• 2024

The construction industry is renowned for its dynamic and intricate characteristics, which demand proficient leadership skills for successful project management. However, the existing training platforms within this sector often overlook the significance of soft skills in leadership development. These platforms primarily focus on safety, work processes, and technical modules, leaving a noticeable gap in preparing future leaders, especially students in the construction domain, for the complex challenges they will encounter in their professional careers. It is crucial to recognize that effective leadership in construction projects requires not only technical expertise but also the ability to communicate effectively, collaborate with diverse stakeholders, and navigate complex relationships. These soft skills are critical for managing teams, resolving conflicts, and driving successful project outcomes. In addition, the construction sector has been slow in adopting and harnessing the potential of advanced emerging technologies such as virtual reality, artificial intelligence, to enhance the soft skills of future leaders. Therefore, there is a need for a platform where students can practice complex situations and conversations in a safe and repeatable training environment. To address these challenges, this study proposes a pioneering approach by integrating conversational AI techniques using large language models (LLMs) within virtual worlds. Although LLMs like ChatGPT possess extensive knowledge across various domains, their responses may lack relevance in specific contexts. Prompt engineering techniques are utilized to ensure more accurate and effective responses, tailored to the specific requirements of the targeted users. This involves designing and refining the input prompts given to the language model to guide its response generation. By carefully crafting the prompts and providing context-specific instructions, the model can generate responses that are more relevant and aligned with the desired outcomes of the training program. The proposed system offers interactive engagement to students by simulating diverse construction site roles through conversational AI based agents. Students can face realistic challenges that test and enhance their soft skills in a practical context. They can engage in conversations with AI-based avatars representing different construction site roles, such as machine operators, laborers, and site managers. These avatars are equipped with AI capabilities to respond dynamically to user interactions, allowing students to practice their communication and negotiation skills in realistic scenarios. Additionally, the introduction of AI instructors can provide guidance, feedback, and coaching tailored to the individual needs of each student, enhancing the effectiveness of the training program. The AI instructors can provide immediate feedback and guidance, helping students improve their decision-making and problem-solving abilities. The proposed immersive learning environment is expected to significantly enhance leadership competencies of students, such as communication, decision-making and conflict resolution in the practical context. This study highlights the benefits of utilizing conversational AI in educational settings to prepare construction students for real-world leadership roles. By providing hands-on, practical experience in dealing with site-specific challenges, students can develop the necessary skills and confidence to excel in their future roles.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• The KIPS Transactions:PartC
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• v.10C no.5
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• pp.625-634
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• 2003

More than a decade after its initial proposal, deployment of IP Multicast has been limited due to the problem of traffic control in multicast routing, multicast address allocation in global internet, reliable multicast transport techniques etc. Lately, according to increase of multicast application service such as internet broadcast, real time security information service etc., overlay multicast is developed as a new internet multicast technology. In this paper, we describe an overlay multicast protocol and propose fast join mechanism that considers switching of the tree. To find a potential parent, an existing search algorithm descends the tree from the root by one level at a time, and it causes long joining latency. Also, it is try to select the nearest node as a potential parent. However, it can't select the nearest node by the degree limit of the node. As a result, the generated tree has low efficiency. To reduce long joining latency and improve the efficiency of the tree, we propose searching two levels of the tree at a time. This method forwards joining request message to own children node. So, at ordinary times, there is no overhead to keep the tree. But the joining request came, the increasing number of searching messages will reduce a long joining latency. Also searching more nodes will be helpful to construct more efficient trees. In order to evaluate the performance of our fast join mechanism, we measure the metrics such as the search latency and the number of searched node and the number of switching by the number of members and degree limit. The simulation results show that the performance of our mechanism is superior to that of the existing mechanism.

• Korean Security Journal
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• no.48
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• pp.147-176
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• 2016

Korean Peninsula is surrounded by ocean on three sides. Because of this geographical quality over 97% of export and import volumes are exchange by sea. Foreign ship and international passenger vessels carries foreign tourist and globalization and internationalization increases this trends. Leisure population grows with national income increase and interest of ocean. And accidents and incidents rates are also increases. Korea Coast Guard's jurisdiction area is 4.5 times bigger than our country. The length of coastline is 14,963km including islands. One patrol vessel is responsible for 24,068km and one coast guard substation is responsible for 94km. Efficient patrol activities can not be provided. This research focus on this problem. Analyze the status and trends of maritime crime and suggest efficient patrol activities. To deal with increasing maritime crime rate this study suggest to use geographical profile method which developed early 1900s in USA. This geographical profile analyse the spatial characteristic and mapping this result. With this result potential crime zone can be predicted. One of the result is hot spot management which gives data about habitual crime zone. In Korea National Police Agency adopt this method in 2008 and apply on patrol and crime prevention activity by analysis of different criteria. Korea National Police Agency analyse the crime rate with crime type, crime zone and potential crime zone, and hourly, regionally criteria. Korea Coast Guard need to adopt this method and apply on maritime to make maritime crime map, which shows type of crime with regional, periodical result. With this geographical profiling we can set a Criminal Point which shows the place where the crime often occurs. The Criminal Points are set with the data of numerous rates such as homicide, robbery, burglary, missing, collision which happened in ocean. Set this crime as the major crime and manage the data more thoroughly. I expect to enhance the reinforcement of marine crime using this Criminal Points. Because this points will give us efficient way to prevent the maritime crime by placing the patrol vessel where they needed most.