• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.73-84
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• 2005

Highway design criteria are considering roadway safety and smooth driving maneuver. However, a certain highway alignment within design criteria often leads drivers to undesirable situation due to the differences between the original intention of design criteria and the unintended result of drivers' cognition. The differences between them often result in traffic accidents. In order to reduce accident process, highway safety facilities are installed on those roadway sections. However, the relationship between highway environments and human factors has not been deeply studied in Korea. In this study. vertical roadway sections are constructed with 3-D graphical tools. This vertical roadway sections are simulated on a driving simulator in order to identify the differences of drivers' cognition on different roadway environments. Based upon the collected data from the driving simulator, canonical correlation analysis and canonical discriminant analysis of quantification theory II have been performed in order to figure out impacting factors on the degree of roadway safety. Also, based upon quantification theory I. the relationship between roadway safety facilities and the degree of safety has been analyzed.

• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.113-118
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• 2023

Maintenance of semiconductor equipment processes is crucial for the continuous growth of the semiconductor market. The process must always be upheld in optimal condition to ensure a smooth supply of numerous parts. Additionally, it is imperative to monitor the status of the robots that play a central role in the process. Just as many senses of organs judge a person's body condition, robots also have numerous sensors that play a role, and like human joints, they can detect the condition first in the joints, which are the driving parts of the robot. Therefore, a normal state test bed and an abnormal state test bed using an aging reducer were constructed by simulating the joint, which is the driving part of the robot. Various sensors such as vibration, torque, encoder, and temperature were attached to accurately diagnose the robot's failure, and the test bed was built with an integrated system to collect and control data simultaneously in real-time. After configuring the user screen and building a database based on the collected data, the characteristic values of normal and abnormal data were analyzed, and machine learning was performed using the KNN (K-Nearest Neighbors) machine learning algorithm. This approach yielded an impressive 94% accuracy in failure diagnosis, underscoring the reliability of both the test bed and the data it produced.

• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.2
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• pp.132-140
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• 2002

A momentum backpropagation neural network is prepared to carry out real-time dynamics simulations of a passenger car. A full-car model of fifteen degrees of freedom was constructed for vehicle dynamics analysis. Human body dynamics analysis was performed for a male driver(50 percentile Korean adult) restrained by a three point seatbelt system. The trained data using the neural network were obtained using a dynamic solver, ADAMS . The neural network were formed based on the dynamics of the simulator. The optimized hidden layer was obtained by selecting the optimal number of hidden layers. The driving scenario including bump passing and lane changing has been used for the estimation of the proposed neural network. A comparison between the trained data and neural network outputs is found to be satisfactory to show the applicability of the suggested approach.

• Electronics and Telecommunications Trends
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• v.38 no.4
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• pp.70-80
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• 2023

In recent years, our society has shifted from an information society to an intelligent information society, in which computing has become a key factor in shaping and driving social development. In this new era of digital civilization powered by the Internet of Things, traditional data-based computing is no longer sufficient to meet the growing demand for higher levels of intelligence. Therefore, intelligent computing has emerged, reshaping traditional computing and forming new computing paradigms to promote the digital revolution in the era of the Internet of Things, big data, and artificial intelligence. Intelligent computing has greatly expanded the scope of computing through new computing theories, architectures, methodologies, systems, and applications, and it is expanding into diverse computing paradigms such as perceptual intelligence, cognitive intelligence, autonomous intelligence, and human-computer fusion intelligence. This paper introduces the concept and main features of intelligent computing and describes trends in standardization for intelligent computing within the ISO/IEC JTC 1, focusing on the technical trend report on intelligent computing that is currently under development within ISO/ IEC JTC 1/AG 2.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.169-179
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• 2020

This study examines the drivers and implementation of intrapreneurship strategy in a property service company. Using a qualitative case study approach, the study interviewed four managers involved in related intrapreneurship initiatives. The data was validated by an expert and a practitioner from a different company. The implementation of the company's intrapreneurship strategy is limited to improving new ways of working and developing products and services. However, business development and the creation of new business models are still limited. From several intrapreneurship driving factors, it was observed that the company practices are considered adequate with regard to top management support, leadership, flexibility in carrying out work, as well as in fairly harmonious arrangements for ongoing business relationships with the intrapreneurship projects. On the other hand, human resources with entrepreneurial behavior are still minimal. Similarly, the driving factors in reward and training that promote entrepreneurial behavior are also considered to be insufficient. The application of intrapreneurship as a strategy requires understanding and commitment from all parties in the organization. This study provides insight into the Indonesian context and proposes that intrapreneurship initiatives are less likely to succeed if they are not supported by developing a more systematic entrepreneurial mindset, behavior, and culture.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.6
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• pp.703-709
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• 2019

This paper proposes a monitoring and remote control system, an essential part of In Vehicle Infotainment (IVI) and Human Vehicle Interface (HVI) to provide safety and convenience to a driver. The system utilizes Bluetooth for a short range communication and utilizes WCDMA for a long range communication to enhance efficiency. In this paper, an integrated controller, which integrates a CAN communication module, a Bluetooth communication module, a WCDMA communication module, is designed to control a car. Also, a remote server for managing data is designed to provide real-time monitoring and remote control for a user via smart devices. Experiment results show that all the proposed remote control, driving log, real-time monitoring, and diagnostics functions are working properly. With the proposed system, a driver can drive safely by monitoring and inspecting a car before driving via smart devices, and control conveniently by controlling a car remotely.

• Journal of Multimedia Information System
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• v.9 no.1
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• pp.11-20
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• 2022

In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

• Journal of Multimedia Information System
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• v.9 no.1
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• pp.33-42
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• 2022

In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

• Journal of the Ergonomics Society of Korea
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• v.31 no.5
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• pp.647-655
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• 2012

Objective: The purpose of this study was to confirm difference between angular foot movement time and existing foot Fitts' law predicting times, and to develop the angular foot Fitts' law in the foot tapping task. Background: Existing studies of foot Fitts' law focused on horizontal movement to predict the movement time. However, when driving a car, humans move their foot from the accelerator to the brake with a fixed heel. Therefore, we examined the experiment to measure angular foot movement time in reciprocal foot tapping task and compared to conventional foot Fitts' law predicting time. And, we developed the angular foot Fitts' law. Method: In this study, we compared the angular foot movement time in foot tapping task and the predicted time of four conventional linear foot Fitts' law models - Drury's foot Fitts' law, Drury's ballistic, Hoffmann's ballistic, Hoffmann's visually-controlled. 11 subjects participated in this experiment to get a movement time and three target degrees of 20, 40, and 60 were used. And, conventional models were calculated for the prediction time. To analyze the movement time, linear and arc distance between targets were used for variables of model. Finally, the angular foot Fitts' law was developed from experimental data. Results: The average movement times for each experiment were 412.2ms, 474.9ms, and 526.6ms for the 89mm, 172mm, and 253mm linear distance conditions. The results also showed significant differences in performance time between different angle level. However, all of conventional linear foot Fitts' laws ranged 135.6ms to 401.2ms. On the other hand, the angular foot Fitts' law predicted the angular movement time well. Conclusion: Conventional linear foot Fitts' laws were underestimated and have a limitation to predict the foot movement time in the real task related angular foot movement. Application: This study is useful when considering the human behavior of angular foot movement such as driving or foot input device.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.145-152
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• 2021

In the Recent times, various technological enhancements in the field of artificial intelligence and big data has been noticed. This advancement coupled with the evolution of the 5G communication and Internet of Things technologies, has helped in the development in the domain of smart mine construction. The development of unmanned vehicles with enhanced and smart scheduling system for open-pit mine transportation is one such much needed application. Traditional open-pit mining systems, which often cause vehicle delays and congestion, are controlled by human authority. The number of sensors has been used to operate unmanned cars in an open-pit mine. The sensors haves been used to prove the real-time data in large quantity. Using this data, we analyses and create an improved transportation scheduling mechanism so as to optimize the paths for the vehicles. Considering the huge amount the data received and aggregated through various sensors or sources like, the GPS data of the unmanned vehicle, the equipment information, an intelligent, and multi-target, open-pit mine unmanned vehicle schedules model was developed. It is also matched with real open-pit mine product to reduce transport costs, overall unmanned vehicle wait times and fluctuation in ore quality. To resolve the issue of scheduling the transportation, we prefer to use algorithms based on artificial intelligence. To improve the convergence, distribution, and diversity of the classic, rapidly non-dominated genetic trial algorithm, to solve limited high-dimensional multi-objective problems, we propose a decomposition-based restricted genetic algorithm for dominance (DBCDP-NSGA-II).