• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.3
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• pp.1-11
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• 2010

Traffic broadcasting is using a usual traffic information announcement when giving its information to users on the road and for the provision of information useful to drivers, a clear criteria of how to judge with information from informers needs to be established from the perspective of users. In this study, to give some available criteria for current announcement which often causes confusion, cognitive characteristics were investigated and analyzed based on judgment criteria which are commonly felt by correspondents, participants in traffic broadcasting and drivers. The result requires the provision of information that is relied on an average speed where drivers feel little cognitive difference and found a classification where a smooth traffic flow is more than 60km/h, going slow 40~60km/h and congested state less than 40km/h respectively. And from the study of 35 traffic information announcement for different traffic situations, 8 cases of smooth state and 9 cases of congested state were clearly classified but the rest 18 cases of comment were ambiguously perceived by drivers and which requires the necessity of a announcement that uses directly the word of 'smooth', 'slow', and 'congestion' in the actual expression of slow driving. The future study should be focused on the establishment of more definite criteria by representation of nearly real traffic flow, provision of traffic information announcement and the analysis of cognitive response through car dynamic simulators and the kinds.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.111-117
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• 2017

The purpose of forecasting the traffic accident is to reduce the traffic accident. Therefore, the goal of this study is to provide severity of the accident by Forecasting of Probability of Accident. In Korea, accident data are distributed to the public via internet that includes numbers of accident and fatality as well. And crude level of accident severity in accordance with weather information for metropolitan city level are available by weekly. However, It can not reflect personal needs at specific origin of the travel for a certain traveller. This study aims to consider 68 major intersections with precipitation data, and eventually introduces link based accident severity. In estimating the accident severity both dynamic data such as drivers' characteristics, driving conditions and static data such as geometry of road, intersection characteristics are considered. Also, we identifies accident severity according to the accident type - 'vehicle to vehicle,' 'vehicle to person.' Finally, the outcomes of this study suggests taylor-made accident severity information for a specific traveller for a certain route.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.266-274
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• 2020

This paper reports a means of improving the abnormal noise of light tactical vehicles (LTVs) by applying a vehicle fitting type generator (hereinafter called generator). LTVs are classified as having generators, and there are no differences in the noise level. On the other hand, quality improvement was performed in response to unpleasant noise felt by the user (hereinafter called abnormal noise) during vehicle operation. To improve the quality, the generator mounting structure and the phenomenon of the vehicle in the problem were identified. Through this, it was confirmed that the noise caused by the generator installation was the rattle noise. Rattle noise at the engine driving system is normally caused by the transfer of irregular torque generated by the engine power stroke and the backlash by the spline-serration fitting structure between the engine coupler and rotor assembly in a generator. Therefore, this study established an improvement plan to apply a damper coupler to solve the cause of the abnormal noise. Regarding the improved establishment method, the improvement effect was confirmed from the influence of the irregular torque of the engine, noise level, dynamic characteristics analysis, and the endurance test of the parts.

• Journal of Korea Technology Innovation Society
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• v.20 no.1
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• pp.175-204
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• 2017

The existing innovation policies and strategies mainly focused on the influencing factors for improvement of innovation outcome. However, these strategies were not always successful in driving innovative activities that make technology innovation disseminated. In this regard, innovation ecosystems approach has recently been coming to the force to establish a successful innovation strategy. The innovation ecosystems concept describes that innovation processes are evolved through collaborative networks of economic actors. In an innovation ecosystem, different organizations collaborate for technology development and its use. They interact for value co-creation by sharing mutual resources. The organizational networks are re-organized by dynamic changes of actors' interactions, which drive innovation mechanism of the networks. Recent studies on innovation ecosystems mostly have paid attention on developing theoretical frameworks to describe dynamics of an innovation ecosystem. There have hardly been empirical tests on the theoretical ecosystem models. In this vein, we investigated dynamics of an innovation ecosystem by analyzing structural characteristics of a collaborative network among organizations which are involved in the use of innovative technologies. Particularly, we examined the longitudinal changes of the interaction patterns among the organizations. This test was performed by an analysis of structural equivalence on the network dataset transformed from the organizational interactions. This result provides a guideline for an organization in developing an innovation strategy under a systemic perspective.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.18-25
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• 2020

With the development of water internet technology, data communication between objects is expanding. Research related to data communication technology between vehicles that incorporates related technologies into vehicles has been actively conducted. For data communication between mobile terminals, data stability, reliability, and real-time performance must be guaranteed. The 5 GHz Wi-Fi band, which is advantageous in bandwidth, communications speed, and wireless saturation of the wireless network, was selected as the data communications network between vehicles. This study analyzes how to design and implement a 5 GHz Wi-Fi network in a vehicle network. Considering the characteristics of the mobile communication terminal device, a continuous variable communications structure is proposed to enable high-speed data switching. We simplify the access point access procedure to reduce the latency between wireless terminals. By limiting the Transmission Control Protocol Internet Protocol (TCP/IP)-based Dynamic Host Configuration Protocol (DHCP) server function and implementing it in a broadcast transmission protocol method, communication delay between terminal devices is improved. Compared to the general commercial Wi-Fi communication method, the connection operation and response speed have been improved by five seconds or more. Utilizing this method can be applied to various types of event data communication between vehicles. It can also be extended to wireless data-based intelligent road networks and systems for autonomous driving.

• Journal of Korean Society of Transportation
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• v.21 no.1
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• pp.103-113
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• 2003

This paper shows alternative route search and preference route search for the traffic route search, and proposes the use of the fuzzy non-additive controller by the application of AHP(analytic hierarchy process). It is different from classical route search and notices thinking method of human. Appraisal element, weight of route is extracted from basic of the opinion gathering for the driving expert and example of route model was used for the finding of practice utility. Model evaluation was performed attribute membership function making of estimate element, estimate value setting, weight define by the AHP, non additive presentation of weight according to $\lambda$-fuzzy measure and Choquet fuzzy integral. Finally, alternative route search was possible to real time traffic route search for the well variable traffic environment, and preference route search showed reflection of traffic route search disposition for the driver individual. This paper has five important meaning. (1)The approach is similar to the driver's route selection decision process. (2)The approach is able to control of route appraisal criteria for the multiple attribute. (3)The approach makes subjective judgement objective by a non additive. (4)The approach shows dynamic route search for the alternative route search. (5)The approach is able to consider characteristics of individual drivers attributed for the preference route search.

• Tuberculosis and Respiratory Diseases
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• v.82 no.3
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• pp.251-260
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• 2019

Background: Beyond its current function as a rescue therapy in acute respiratory distress syndrome (ARDS), extracorporeal membrane oxygenation (ECMO) may be applied in ARDS patients with less severe hypoxemia to facilitate lung protective ventilation. The purpose of this study was to evaluate the efficacy of extended ECMO use in ARDS patients. Methods: This study reviewed 223 adult patients who had been admitted to the intensive care units of 11 hospitals in Korea and subsequently treated using ECMO. Among them, the 62 who required ECMO for ARDS were analyzed. The patients were divided into two groups according to pre-ECMO arterial blood gas: an extended group (n=14) and a conventional group (n=48). Results: Baseline characteristics were not different between the groups. The median arterial carbon dioxide tension/fraction of inspired oxygen ($FiO_2$) ratio was higher (97 vs. 61, p<0.001) while the median $FiO_2$ was lower (0.8 vs. 1.0, p<0.001) in the extended compared to the conventional group. The 60-day mortality was 21% in the extended group and 54% in the conventional group (p=0.03). Multivariate analysis indicated that the extended use of ECMO was independently associated with reduced 60-day mortality (odds ratio, 0.10; 95% confidence interval, 0.02-0.64; p=0.02). Lower median peak inspiratory pressure and median dynamic driving pressure were observed in the extended group 24 hours after ECMO support. Conclusion: Extended indications of ECMO implementation coupled with protective ventilator settings may improve the clinical outcome of patients with ARDS.

• Smart Media Journal
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• v.13 no.3
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• pp.18-26
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• 2024

Road surface monitoring is essential for maintaining road environment safety through managing risk factors like rutting and crack detection. Using autonomous driving-based UGVs with high-performance 2D laser sensors enables more precise measurements. However, the increased energy consumption of these sensors is limited by constrained battery capacity. In this paper, we propose a fusion sensor system for efficient surface monitoring with UGVs. The proposed system combines color information from cameras and depth information from line laser sensors to accurately detect surface displacement. Furthermore, a dynamic sampling algorithm is applied to control the scanning frequency of line laser sensors based on the detection status of monitoring targets using camera sensors, reducing unnecessary energy consumption. A power consumption model of the fusion sensor system analyzes its energy efficiency considering various crack distributions and sensor characteristics in different mission environments. Performance analysis demonstrates that setting the power consumption of the line laser sensor to twice that of the saving state when in the active state increases power consumption efficiency by 13.3% compared to fixed sampling under the condition of λ=10, µ=10.

• 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.