• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.17-23
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• 2016

Wireless sensor-actuator networks (WSANs) enhance the existing wireless sensor networks (WSNs) by equipping sensor nodes with an actuator. The actuators work with the sensor nodes and perform application-specific operations. The WSAN systems have several applications such as disaster relief, intelligent building, military surveillance, health monitoring, and infrastructure security. These applications require capability of reliable data transfer to act responsively and accurately. Biologically inspired modeling techniques have received considerable attention for achieving robustness, scalability, and adaptability, while retaining individual simplicity. In this paper, an epidemic-inspired algorithm for data dissemination with delay constraints while minimizing energy consumption in WSAN is proposed. The steady states and system stability are analyzed using control theory. Also, simulation results indicate that the proposed scheme provides desirable dissemination delay and energy saving.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.689-700
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• 2017

This paper presents an effective approach for wind turbine (WT) condition assessment based on the data collected from wind farm supervisory control and data acquisition (SCADA) system. Three types of assessment indices are determined based on the monitoring parameters obtained from the SCADA system. Neural Networks (NNs) are used to establish prediction models for the assessment indices that are dependent on environmental conditions such as ambient temperature and wind speed. An abnormal level index (ALI) is defined to quantify the abnormal level of the proposed indices. Prediction errors of the prediction models follow a normal distribution. Thus, the ALIs can be calculated based on the probability density function of normal distribution. For other assessment indices, the ALIs are calculated by the nonparametric estimation based cumulative probability density function. A Back-Propagation NN (BPNN) algorithm is used for the overall WT condition assessment. The inputs to the BPNN are the ALIs of the proposed indices. The network structure and the number of nodes in the hidden layer are carefully chosen when the BPNN model is being trained. The condition assessment method has been used for real 1.5 MW WTs with doubly fed induction generators. Results show that the proposed assessment method could effectively predict the change of operating conditions prior to fault occurrences and provide early alarming of the developing faults of WTs.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.1
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• pp.33-40
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• 2003

Radio frequency management system(RFMS) is being operated to facilitate national spectrum management and monitoring in Korea. To improve the engineering analysis function in RFMS, criteria for the automated selection of the propagation model adequate to the radio station service environment considered are proposed. Those criteria are derived from the specified parameters obtained through the analysis of related ITU-R propagation & diffraction loss models which are to be used in RFMS. Then, using criteria acquired, computer program is made to achieve the automated selection of the most appropriate propagation algorithm, among the ones provided in RFMS, to the environment in which the engineering analysis is required. Furthermore, an illustrative example is shown with the proposals fur increasing the efficiency of the engineering analysis in RFMS.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.132-140
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• 2008

Conventional rectal catheters which are used for the measurement of abdominal pressure can cause erroneous result affecting detrusor pressure, and the catheter itself is not comfortable to the patients. To reduce these problems, we invented a new method for measuring abdominal pressure in non invasive manner using surface electromyography (EMG) signals of the rectus abdominis muscle. Our results showed that the correlation coefficient and root mean square error (RMSE) between the measured abdominal pressures by the conventional rectal catheters and the estimated values by our proposed algorithm were $0.79{\pm}0.06$ and $0.10{\pm}0.07$, respectively. These findings suggest that the surface EMG of rectus abdominis muscle might be used indirectly for more convenient measurement of abdominal pressure on ambulatory urodynamic study.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.116-123
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• 2013

In mobile healthcare applications, the reliable transmission of the bio-data is very important. In this article, we present a reliable bio-data transmission technique for mobile healthcare monitoring service at 6LoWPAN multi-hop wireless networks. In particular, we expand IEEE 11073-20601 protocol, and propose the reliable path construction for 6LoWPAN aimed to reliably provide mobile healthcare service over wireless sensor network, using IPv6 network. 6LoWPAN is recognized possibility because it is agree with sensor network by raising Adaptation layer on the MAC layer to transmit IPv6 packets. In this article proposed minimize the algorithm complexity and reliability routing protocol because the 6LoWPAN devices are suitable for low cost, small size and battery that can be used to health care system environment. And detailed procedures and algorithms are presented. We the proposed method to prove the superiority of using NS-3 for compareing with AODV protocol.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.4
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• pp.343-352
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• 2016

A multi-rotor vehicle is an unmanned vehicle consisting of multiple rotors. A multi-rotor vehicle can be categorized as tri-, quad-, hexa-, and octo-rotor depending on the number of the rotors. Multi-rotor vehicles have many advantages due to their agile flight capabilities such as the ability for vertical take-off, landing and hovering. Thus, they can be widely used for various applications including surveillance and monitoring in urban areas. Since multi-rotors are subject to uncertain environments and disturbances, it is required to implement robust attitude stabilization and flight control techniques to compensate for this uncertainty. In this research, an advanced nonlinear control algorithm, i.e. sliding mode control, was implemented. Flight experiments were carried out using an onboard flight control computer and various real-time autonomous attitude adjustments. The feasibility and robustness for flying in uncertain environments were also verified through real-time tests based on disturbances to the multi-rotor vehicle.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.739-752
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• 2018

Purpose: The purpose of this study was to investigate the relationship between kiln processing parameters and NOx emissions that occur in the sintering and calcination steps of the cement manufacturing process and to derive the main factors responsible for producing emissions outside emission limit criteria, as determined by category models and classification rules, using data mining techniques. The results from this study are expected to be useful as guidelines for NOx emission control standards. Methods: Data were collected from Precalciner Kiln No.3 used in one of the domestic cement plants in Korea. Thirty-four independent variables affecting NOx generation and dependent variables that exceeded or were below the NOx emiision limit (>1 and <0, respectively) were examined during kiln processing. These data were used to construct a detection model of NOx emission, in which emissions exceeded or were below the set limits. The model was validated using SPSS MODELER 18.0, artificial neural network, decision treee (C5.0), and logistic regression analysis data mining techniques. Results: The decision tree (C5.0) algorithm best represented NOx emission behavior and was used to identify 10 processing variables that resulted in NOx emissions outside limit criteria. Conclusion: The results of this study indicate that the decision tree (C5.0) can be applied for real-time monitoring and management of NOx emissions during the cement firing process to satisfy NOx emission control standards and to provide for a more eco-friendly cement product.

• Korean Journal of Remote Sensing
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• v.27 no.6
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• pp.637-651
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• 2011

This study presents a rule-based urban image classification method for time series analysis of changes in the vicinity of Asan-si and Cheonan-si in Chungcheongnam-do, using Landsat satellite images (1991-2006). The area has been highly developed through the relocation of industrial facilities, land development, construction of a high-speed railroad, and an extension of the subway. To determine the yearly changing pattern of the urban area, eleven classes were made depending on the trend of development. An algorithm was generalized for the rules to be applied as an unsupervised classification, without the need of training area. The analysis results show that the urban zone of the research area has increased by about 1.53 times, and each correlation graph confirmed the distribution of the Built Up Index (BUI) values for each class. To evaluate the rule-based classification, coverage and accuracy were assessed. When Optimal allowable factor=0.36, the coverage of the rule was 98.4%, and for the test using ground data from 1991 to 2006, overall accuracy was 99.49%. It was confirmed that the method suggested to determine the maximum allowable factor correlates to the accuracy test results using ground data. Among the multiple images, available data was used as best as possible and classification accuracy could be improved since optimal classification to suit objectives was possible. The rule-based urban image classification method is expected to be applied to time series image analyses such as thematic mapping for urban development, urban development, and monitoring of environmental changes.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.147-151
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• 2005

CAN(Controller Area Network) is a simple and efficient network system for real time control and measurement. As it is not only good at error detection but also strong in electromagnetic interference, CAN has been widely used all over the industries. Basically, CAN needs a master node in charge of sensor data collection, node scheduling for data transmission to a monitoring system and error detection. According to the number of mater nodes, the CAN system is classified into two type of master system. One is a single master system that has only one master node and the other is a multi-master system where any sensor node can become a master node depending on the system's conditions. While it has the advantage of its fault tolerance, the multi-master system will suffer form the overall performance degradation when a defect is found in the master node. It is because all sensor nodes pertaining to a defective master node lose their position. Moreover, it is difficult and expensive to implement. For a single master system, the whole system will be broken down when a problem happens to a single master. In this paper, a dynamic master system is presented that there are several sub-master nodes of which basic functions are those of other sensor nodes at ordinary times but dynamically changed to replace the failing master node. An effective scheduling algorithm is also proposed to choose an appropriate node among sub-master nodes, where each sub-master node has its precedence value. The performance of the dynamic master system is experimented and analyzed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.917-927
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• 2018

High blood pressure causes various cardiovascular diseases and is associated with mortality. Periodic self-monitoring and recording of blood pressure is very helpful in preventing the occurrence of secondary diseases caused by hypertension. However, existing cuff-type blood pressure monitors have many limitations. As an alternative of that, a method of estimating the blood pressure by measuring the velocity change of the blood flow using the photo plethysmography is widely known. However, photo plethysmography have a low correlation with blood flow. So, we will propose an algorithm for estimating blood pressure using the relationship between velocity change of blood flow measured by magnetic field instead of photo plethysmography and electrocardiogram. For this purpose, First, we analyzed the correlation between photo plethysmography and magneto plethysmography. the correlation between MPG and PPG was r = 0.9449. Second, we compared estimated blood pressure and measured blood pressure. In the four experiment each result was r = 0.5737, r = 0.7863, r = 0.5669, and r = 0.7445.