• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1516-1539
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• 2022

This article shows a set of physical information fusion IoT systems that we designed for smart buildings. Its essence is a computer system that combines physical quantities in buildings with quantitative analysis and control. In the part of the Internet of Things, its mechanism is controlled by a monitoring system based on sensor networks and computer-based algorithms. Based on the design idea of the agent, we have realized human-machine interaction (HMI) and machine-machine interaction (MMI). Among them, HMI is realized through human-machine interaction, while MMI is realized through embedded computing, sensors, controllers, and execution. Device and wireless communication network. This article mainly focuses on the function of wireless sensor networks and MMI in environmental monitoring. This function plays a fundamental role in building security, environmental control, HVAC, and other smart building control systems. The article not only discusses various network applications and their implementation based on agent design but also demonstrates our collaborative information fusion strategy. This strategy can provide a stable incentive method for the system through collaborative information fusion when the sensor system is unstable in the physical measurements, thereby preventing system jitter and unstable response caused by uncertain disturbances and environmental factors. This article also gives the results of the system test. The results show that through the CPS interaction of HMI and MMI, the intelligent building IoT system can achieve comprehensive monitoring, thereby providing support and expansion for advanced automation management.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.633-640
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• 2001

In this paper we examine the machine learning issues raised by the domain of the Intrusion Detection Systems(IDS), which have difficulty successfully classifying intruders. There systems also require a significant amount of computational overhead making it difficult to create robust real-time IDS. Machine learning techniques can reduce the human effort required to build these systems and can improve their performance. Genetic algorithms are used to improve the performance of search problems, while data mining has been used for data analysis. Data Mining is the exploration and analysis of large quantities of data to discover meaningful patterns and rules. Among the tasks for data mining, we concentrate the classification task. Since classification is the basic element of human way of thinking, it is a well-studied problem in a wide variety of application. In this paper, we propose a classifier system based on genetic algorithm, and the proposed system is evaluated by applying it to IDS problem related to classification task in data mining. We report our experiments in using these method on KDD audit data.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.193-198
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• 2001

In the large scale B2B transaction like buying Express-Train or selling Daewoo Motor, a tremendous amount of variables and factors of chaos functionate in it directly or indirectly. To get effective information processing on the so called complex system like this, it should be possible to unite the global insight power of the human being and the local computing power of the machine. In this paper, we suggested a union model of human being and machine using Hugent concept. Hugent is defined as an agent model which allows us to chemically unite the human's component and the machine's component in terms of information processing. In this paper, we showed that some typical problems contained in the complex system can be treated more easily through the suggested Hugent concept.

• Journal of the Ergonomics Society of Korea
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• v.34 no.3
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• pp.235-245
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• 2015

Objective: The purpose of this study is to develop visual complexity metrics based on theoretical bases. Background: With the development of IT technologies, drivers process a large amount of information caused by automotive human-machine interface (HMI), such as a cluster, a head-up display, and a center-fascia. In other words, these systems are becoming more complex and dynamic than traditional driving systems. Especially, these changes can lead to the increase of visual demands. Thus, a concept and tool is required to evaluate the complicated systems. Method: We reviewed prior studies in order to analyze the visual complexity. Based on complexity studies and human perceptual characteristics, the dimensions characterizing the visual complexity were determined and defined. Results: Based on a framework and complexity dimensions, a set of metrics for quantifying the visual complexity was developed. Conclusion: We suggest metrics in terms of perceived visual complexity that can evaluate the in-vehicle displays. Application: This study can provide the theoretical bases in order to evaluate complicated systems. In addition, it can quantitatively measure the visual complexity of In-vehicle information system and be helpful to design in terms of preventing risks, such as human error and distraction.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.145-150
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• 2005

This paper presents an Electrotactile Display System (ETCS). One of the most important human sensory systems for human computer interaction is the sense of touch, which can be displayed to human through tactile output devices. To realize the sense of touch, electrotactile display produces controlled, localized touch sensation on the skin by passing small electric current. In electrotactile stimulation, the mechanoreceptors in the skin may be stimulated individually in order to display the sense of vibration, touch, itch, tingle, pressure etc. on the finger, palm, arm or any suitable location of the body by using appropriate electrodes and waveforms. We developed an ETCS and investigated effectiveness of the proposed system in terms of the perception of roughness of a surface by stimulating the palmar side of hand with different waveforms and the perception of direction and location information through forearm. Positive and negative pulse trains were tested with different current intensities and electrode switching times on the forearm or finger of the user with an electrode-embedded armband in order to investigate how subjects recognize displayed patterns and directions of stimulation.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.394-397
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• 1987

This paper presents an analysis of the man-machine control system. A man-machine system depends on the performance of a human operator for proper operation. The analysis method is based upon the assumption that human operator will act in a near optimal controller. Optimal control theory and its associated state space representation is used as the basis for the analytic procedure. The computer simulation for a given plant shows that plant parameters have limited range by the human operator.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.22
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• pp.71-78
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• 1990

Some problems to assess the safety of automated man-machine system are studied in many ways. The difficulty occurred in this system is the vagueness of human behavior. Fuzzy set theory is used to assess the human behavior in safety analysis. The unsafe behavior listed top 10 in accident statistics would be explained as the factors of human vagueness. Three cases are considered, which consist of man-machine system as man-man, man-machine, machine-machine types. For the design of safe task, using characteristics of work performance, each motion cycle time is required to know the rate of learning. Approach of human behavior to the standard motion means more safe motion. It is important to design the works as to minimize the time performance to the standard motion's, which utilize the control of risk potential with easy. In that process, use of fuzzy set theory is appropriate to analyze the human behavior to identify its vagueness.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.34-42
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• 2015

Modeling and control of human-involved manufacturing systems poses a huge challenge on how to model all possible interactions among system components within the time and space dimensions. As the manufacturing environment are getting complicated, the importance of human in the manufacturing system is getting more and more spotlighted to incorporate the manufacturing flexibility. This paper presents a formal modeling methodology of affordance-based MPSG (Message-based Part State Graph) for a human-machine collaboration system incorporating supervisory control scheme for flexible manufacturing systems in automotive industry. Basically, we intend to extend the existing model of affordance-based MPSG to the real industrial application of humanmachine cooperative environments. The suggested extension with the real industrial example is illustrated in three steps; first, the manufacturing process and relevant data are analyzed in perspectives of MABA-MABA and the supervisory control; second, the manufacturing processes and task allocation between human and machine are mapped onto the concept of MABA-MABA; and the last, the affordance-based MPSG of humanmachine collaboration for the manufacturing process is presented with UMLs for verification.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.8
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• pp.870-877
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• 2013

There has been much recent research interest in developing numerous kinds of human-machine interface. This field currently requires more accurate and reliable sensing systems to detect the intended human motion. Most conventional human-machine interface use electromyography (EMG) sensors to detect the intended motion. However, EMG sensors have a number of disadvantages and, as a consequence, the human-machine interface is difficult to use. This study describes a muscle volume sensor (MVS) that has been developed to measure variation in the outline of a muscle, for use as a human-machine interface. We developed an algorithm to calibrate the system, and the feasibility of using MVS for detecting muscular activity was demonstrated experimentally. We evaluated the performance of the MVS via isotonic contraction using the KIN-COM$^{(R)}$ equipment at torques of 5, 10, and 15 Nm.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.373-380
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• 2008

So far there have been many researches on machine-based recognition of handwritten digit. But we have not yet attained the level of performance that can be satisfactory to men. The dissatisfaction with the performance of machine comes from not only the low accuracy of recognition but also the dissimilarity of the recognition results between man and machine. To reduce the difference of machine from man we first made an experiment with the human recognition of handwritten digits and then inquiry into the way of the human recognition that makes the results of men different from that of machine. We found out the attributes that play an important role in the human recognition process through the analysis of the experimental results like uni- and bi-directional confused pairs of digits, several ones unmixed up with another and the redundancy of mis-recognition, and proposed the approach direction to be able to improve the accuracy of the machine-based recognition, and furthermore the similarity in the recognition results of men and machine on the basis of the found facts above.