• Journal of KIISE:Computing Practices and Letters
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• v.9 no.6
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• pp.674-682
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• 2003

Ship autonomous navigation is designated as what computerizes mental faculties possessed of navigation experts, which are building navigation plans, grasping the situation, forecasting the fluctuation, and coping with the situation. An autonomous navigation system, which consists of several subsystems such as navigation system, a collision avoidance system, several data fusion systems, and a motion control system, is based on an intelligent control architecture for the sake of integrating the systems. The motion control system, which is one of the most essential system in autonomous navigation system, controls its propulsion and steering gears to move the ship satisfying its hydrodynamic characteristics. This paper is the study on the ship movement control system and its implementation which are totally developed and run on virtual-world system. Receiving the high-level control values such as a waypoint presented from the collision avoidance system, the motion control system generates them to low-level control values for propulsion and steering devices. In the paper, we develop a ship motion controller using Oldenburger's theory based on mathematical fundamentals, and simulate it with various scenarios in order to verify its performance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.81-90
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• 2016

As an autonomous driving vehicle (AV) need to cope with external road conditions by itself, its perception performance for road environment should be better than that of a human driver. A vision sensor, one of AV sensors, performs lane detection function to percept road environment for performing safe vehicle steering, which relates to define vehicle heading and lane departure prevention. Performance standards for a vision sensor in an ADAS(Advanced Driver Assistance System) focus on the function of 'driver assistance', not on the perception of 'independent situation'. So the performance requirements for a vision sensor in AV may different from those in an ADAS. In assuming that an AV keep previous steering due to lane detection failure, this study calculated lane departure distances between the AV location following curved road alignment and the other one driving to the straight in a curved section. We analysed lane departure distance and time with respect to the allowance of lane detection malfunction of an AV vision sensor. With the results, we found that an AV would encounter a critical lane departure situation if a vision sensor loses lane detection over 1 second. Therefore, it is concluded that the performance standards for an AV should contain more severe lane departure situations than those of an ADAS.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.55-66
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• 2020

This study developed four algorithms and their associated indices that can quantify and qualify road hazards along roadways. Initially, relevant raw data can be collected from commercial vehicles by camera and DTG. Well-processed data, such as potholes, road freezing, and fog, can be generated from the Integrated management system. Road hazard algorithms combine these data with road inventory data in the Data Sharing Platform. Depending on well-processed data, four different road hazard algorithms and their associated indices were developed. To test the algorithms, an experimental plan based on passive DTG attached in probe vehicles was performed at two different test locations. Selection of the test routes was based on historical data. Although there were limitations using random data for commercial vehicles, hazardous roadways sections, such as fog, road freezing, and potholes, were generated based on actual historical data. As a result, no algorithm error was found in the entire test. Because this study provides road hazard information according to a section, not a point, it can be practically helpful to road users as well as road agencies.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.462-469
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• 2014

As a basic study on both engineering applications and representation methods of synesthesia, this paper aims at building basic system which converts a muscular sense into both visual and auditory elements. As for the building method, data of the muscular sense can be acquired through roll and pitch signals which are calculated from both three-axis acceleration sensor and the two-axis gyro sensor. The roll and pitch signals are then converted into both visual and auditory information as outputs. The roll signals are converted into both intensity elements of the HSI color model and octaves as one of auditory elements. In addition, the pitch signals are converted into both hue elements of the HSI color model and scales as another one of auditory elements. Each of the extracted elements of the HSI color model is converted into each of the three elements of the RGB color model respectively, so that the real-time output color signals can be obtained. Octaves and scales are also converted and synthesized into MIDI signals, so that the real-time sound signals can be obtained as anther one of output signals. In experiments, the results revealed that normal color and sound output signals were successfully obtained from roll and pitch values that represent muscular senses or physical movements, depending on the conversion relationship based on the similarity between color and sound.

• Journal of the Korea Institute of Building Construction
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• v.10 no.5
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• pp.45-54
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• 2010

Recently more and more construction projects have become high-rise, complex and intelligent. Accordingly, such projects require an integrated management system for tasks, with a lean approach to construction with work processes for management and productivity. In particular, Construction Information Technology (CIT) fields are concerned with Building Information Modeling (BIM), which represents the process of generating and managing building data during its life cycle. Constructability research has progressed for the project goal which is a cost-time-quality of optimization by integrated construction knowledge and experience. However, the current constructability process has not been performed efficiently, as the existing 2D drawings and papers lack consistent and accurate information, it is difficult to share the contents of work, and the use of information is inefficient. This study proposes that the reformation and enhancement of BIM-based constructability work process can lead to brilliant performance in the framework of the construction phase through achieving collaboration between the design team and the workers at the site.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.365-373
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• 1999

Recently, numerous studies have demonstrated that artificial intelligence such as neural networks can be an alternative methodology for classification problems to which traditional statistical methods have long been applied. In building neural network model, the selection of independent and dependent variables should be approached with great care and should be treated as a model construction process. Irrespective of the efficiency of a learning procedure in terms of convergence, generalization and stability, the ultimate performance of the estimator will depend on the relevance of the selected input variables and the quality of the data used. Approaches developed in statistical methods such as correlation analysis and stepwise selection method are often very useful. These methods, however, may not be the optimal ones for the development of neural network models. In this paper, we propose a genetic algorithms approach to find an optimal or near optimal input variables for neural network modeling. The proposed approach is demonstrated by applications to bankruptcy prediction modeling. Our experimental results show that this approach increases overall classification accuracy rate significantly.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.355-361
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• 1999

An application of case-based reasoning is proposed to build an influence diagram for identifying successful new ventures. The decision to invest in new ventures in characterized by incomplete information and uncertainty, where some measures of firm performance are quantitative, while some others are substituted by qualitative indicators. Influence diagrams are used as a model for representing investment decision problems based on incomplete and uncertain information from a variety of sources. The building of influence diagrams needs much time and efforts and the resulting model such as a decision model is applicable to only one specific problem. However, some prior knowledge from the experience to build decision model can be utilized to resolve other similar decision problems. The basic idea of case-based reasoning is that humans reuse the problem solving experience to solve a new decision. In this paper, we suggest a case-based reasoning approach to build an influence diagram for the class of investment decision problems. This is composed of a retrieval procedure and an adaptation procedure. The retrieval procedure use two suggested measures, the fitting ratio and the garbage ratio. An adaptation procedure is based on a decision-analytic knowledge and decision participants knowledge. Each step of procedure is explained step by step, and it is applied to the investment decision problem in new ventures.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.167-175
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• 2006

Building accurate corporate bankruptcy prediction models has been one of the most important research issues in finance. Recently, support vector machines (SVMs) are popularly applied to bankruptcy prediction because of its many strong points. However, in order to use SVM, a modeler should determine several factors by heuristics, which hinders from obtaining accurate prediction results by using SVM. As a result, some researchers have tried to optimize these factors, especially the feature subset and kernel parameters of SVM But, there have been no studies that have attempted to determine appropriate instance subset of SVM, although it may improve the performance by eliminating distorted cases. Thus in the study, we propose the simultaneous optimization of the instance selection as well as the parameters of a kernel function of SVM by using genetic algorithms (GAs). Experimental results show that our model outperforms not only conventional SVM, but also prior approaches for optimizing SVM.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.846-847
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• 2016

LED lighting is energy in lighting control based on had developed into a human-centered / multi-functional lighting systems from simple one trillion people thereby using environmental change by combining IT technology and software, including a variety of sensor functions and communication functions, depending on the evolution of the IT Convergence Era the reduction, and the strength and the color tone customized illumination of the user-section of light has been desired. For this intelligent lighting system is applied to the sensor and the control center of the user should be possible, and it is necessary for this artist platform of the communication module. In this paper, we propose a communication platform that utilizes Bluetooth BLE module for LED lighting control.

• Steel and Composite Structures
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• v.42 no.5
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• pp.591-598
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• 2022

The article deals with the possibilities of vibration stimulation. Based on the stability analysis, a multi-scale approach with a modified whole-building model is implemented. The motion equation is configured for a controlled bridge with a MDOF (multiple dynamic degrees of freedom) Tuned Mass Damper (M-TMD) system, and a combination of welding, excitation, and control effects is used with its advanced packages and commercial software submodel. Because the design of high-performance and efficient structural systems has been of interest to practical engineers, systematic methods of structural and functional synthesis of control systems must be used in many applications. The smart method can be stabilized by properly controlling the high frequency injection limits. The simulation results illustrate that the multiple modeling method used is consistent with the accuracy and high computational efficiency. The M-TMD system, even with moderate reductions in critical pressure, can significantly suppress overall feedback on an unregulated design.