• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.87-92
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• 2013

In this paper, we developed a digital and integrated PA(Public Address) system with speech recognition and sensor connection based on IP with an ID using agent. It has facilities such as an external input, a microphone and a radio for a PA system and has speech recognition. If "fire" is spoken to the PA system then it can recognize the emergency situation and will broadcast information to the appropriate agency immediately. In addition to that, many sensors, such as temperature, humidity, and infrared, etc., can be connected to the PA system and can be integrated with the context awareness which contains many types of information about internal statuses using inference agent. Also, developed the digital integrated PA system will make it possible to broadcast the message to adaptable places using network IP based on IDs. Finally, the digital PA system is designed for operation from a PC, which makes installation and setting of operating parameters very simple and user-friendly. For implementation details, we implemented thread based concurrent processing for the events which occur concurrently from many sensors or users.

• Journal of Korean Academy of Nursing Administration
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• v.14 no.3
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• pp.241-248
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• 2008

Purpose: The purpose of this study was to examine the effects of preceptor preparation education on the preceptor's role recognition, role conflict and professional self-concept. Method: A Quasi-experimental design with non-equivalant control group was used. The subjects included 39 nurses, 19 in experimental group, and 20 in the control group. The program consisted of introduction of preceptor education program & curriculum, change of hospital management environment, the newest trend of nursing course, concept of preceptorship, steps of preceptorship, role of preceptor, attitude of preceptor, role of education, etiquette in nursing situation, policy of clinical education ability improvement, communication, conflict management, nursing ethics, contents concerned nursing professionalist, cardiopulmonary resuscitation, and medication. The data was collected from September 29 to November 17, 2007 using a structured questionnaire. Result: Preceptor's role recognition was increased significantly in the experimental group. However, role conflict and professional self-concept weren't significantly changed in the experimental group, compared to the control group. Conclusion: This study provides evidence for potential and beneficial effect of preceptor preparation education program on nurses.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.12
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• pp.2313-2321
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• 2008

In order to develop reliable on-site partial discharge(PD) pattern recognition algorithm, the fuzzy neural network based on fuzzy set(FNN) and the polynomial network pattern classifier based on fuzzy Inference(PNC) were investigated and designed. Using PD data measured from laboratory defect models, these algorithms were learned and tested. Considering on-site situation where it is not easy to obtain voltage phases in PRPDA(Phase Resolved Partial Discharge Analysis), the measured PD data were artificially changed with shifted voltage phases for the test of the proposed algorithms. As input vectors of the algorithms, PRPD data themselves were adopted instead of using statistical parameters such as skewness and kurtotis, to improve uncertainty of statistical parameters, even though the number of input vectors were considerably increased. Also, results of the proposed neuro-fuzzy algorithms were compared with that of conventional BP-NN(Back Propagation Neural Networks) algorithm using the same data. The FNN and PNC algorithms proposed in this study were appeared to have better performance than BP-NN algorithm.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.06a
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• pp.517-518
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• 2007

A method to recognize unpaved road region using a 3D depth measurement system is proposed for mobile robots. For autonomous maneuvering of mobile robots, recognition of obstacles or recognition of road region is the essential task. In this paper, the 3D depth measurement system which is composed of a rotating mirror, a line laser and mono-camera is employed to detect depth, where the laser light is reflected by the mirror and projected to the scene objects whose locations are to be determined. The obtained depth information is converted into an image. Such depth images of the road region represent even and plane while that of off-road region is irregular or textured. Therefore, the problem falls into a texture identification problem. Road region is detected employing a simple spatial differentiation technique to detect the plain textured area. Identification results of the diverse situation of Nonlinear trail are included in this paper.

• Journal of Korean Society of Rural Planning
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• v.22 no.2
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• pp.99-107
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• 2016

Forest service government has been prepared a Forest welfare voucher service system base on published law on th Promotion Welfare Forest. The purpose of this research is study on domestic situation and set on direction of voucher service before started it. In particular, voucher service will be implemented to Forest service government's recreation facilities area, awareness of voucher service system of its users and operators need to be reveal, and also other government's similar voucher operator's opinions also investigate. From those results, it find out introduction factors of forest welfare services voucher system. Recognition investigating survey result shows that the ordinary people are interested in programs, the forest recreation experts are interested in 'Construction and utilization of forest infrastructure', other voucher's experts are interested in 'Training', and ordinary people are interested in 'voucher programs'. So each respondents' results are different in important factors of introducing welfare service voucher system.

• Journal of The Korean Association of Information Education
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• v.23 no.5
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• pp.491-497
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• 2019

As the world develops into a global society, more and more people want to speak foreign languages fluently. To speak fluently, you must have sufficient training in speaking, which requires a dialogue partner. Recently, it is expected that the development of voice recognition information technology will enable the development of a system for conducting foreign language speaking training without human beings from the other party. In this study, a test bed system for foreign language speaking training was developed and applied to elementary school classes. Elementary school students were asked to present their English conversation situation and conduct speaking training. Then, satisfaction with the system and potential for continuous utilization were surveyed. The system developed in this study has been identified as helpful for the training of learning to speak a foreign language.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.667-670
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• 2014

Recently, Domestic situation have been occurred lots of accidents related with disaster and safety including Sewolho Accident. Nevertheless there is insufficient about IoT recognition service technics. Furthermore mosf of people aware of M2M and IoT technics, but there is no service system at a whole perspective. Goverment have been discuss about that disaster and saftey but it is hard to construct that service system. In this paper, we suggest a process and technology about IoT recognition service on disaster and safety.

• Journal of Drive and Control
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• v.18 no.4
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• pp.9-18
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• 2021

This study proposes a method for creating learning datasets to recognize obstacles using deep learning algorithms in automated construction machinery or an autonomous vehicle. Recently, many researchers and engineers have developed various recognition algorithms based on deep learning following an increase in computing power. In particular, the image classification technology and image segmentation technology represent deep learning recognition algorithms. They are used to identify obstacles that interfere with the driving situation of an autonomous vehicle. Therefore, various organizations and companies have started distributing open datasets, but there is a remote possibility that they will perfectly match the user's desired environment. In this study, we created an interface of the virtual simulator such that users can easily create their desired training dataset. In addition, the customized dataset was further advanced by using the RDBMS system, and the recognition rate was improved.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.255-263
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• 2022

3D object detection pipelines often incorporate RGB-based object detection methods such as YOLO, which detects the object classes and bounding boxes from the RGB image. However, in complex environments where objects are heavily cluttered, bounding box approaches may show degraded performance due to the overlapping bounding boxes. Mask based methods such as Mask R-CNN can handle such situation better thanks to their detailed object masks, but they require much longer time for data preparation compared to bounding box-based approaches. In this paper, we present a 3D object recognition pipeline which uses either the YOLO or Mask R-CNN real-time object detection algorithm, K-nearest clustering algorithm, mask reduction algorithm and finally Principal Component Analysis (PCA) alg orithm to efficiently detect 3D poses of objects in a complex environment. Furthermore, we also present an improved YOLO based 3D object detection algorithm that uses a prioritized heightmap clustering algorithm to handle overlapping bounding boxes. The suggested algorithms have successfully been used at the Artificial-Intelligence Robot Challenge (ARC) 2021 competition with excellent results.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.445-446
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• 2022

In this paper, in order to improve port work preparation and berth scheduling efficiency in an artificial intelligence-based berthing monitoring system that can monitor the ship's berthing process, we develop a mooring line recognition model to check an exact berthing time. By improving the pre-designed AI model, it is possible to segment the mooring line from the input image, and to recognize when the mooring line arrives or falls on the berth, thereby providing the correct ship's berthing time. The proposed AI model confirmed by the results that mooring line recognition is possible with evaluation data about the actual berthing situation.