• Journal of the Society of Naval Architects of Korea
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• v.35 no.2
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• pp.51-62
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• 1998

In this paper, a CAD/CAM system for 5-axis machining of model propeller is introduced. This system has been developed under the environment of personal computer and Windows NT. In order to enhance the productivity, existing text-based design S/W was integrated into this graphic-based system. Non-Uniform Rational B-Spline method is used to represent the sculptured surface of propeller blades and hub using point data, and surface blending between blade and hub is realized in this system. For 5-axis machining of sculptured surface, tool/work collision and interference are checked and inverse kinematic analysis is performed to make NC data. In addition, tool and workpiece are animated on the PC monitor by preparing NC verification module. Finally, optimal cutting conditions are determined empirically and those cutting conditions are integrated into this S/W so that the whole process from design to machining can be done automatically.

• Journal of Broadcast Engineering
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• v.9 no.4 s.25
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• pp.345-356
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• 2004

In this paper, we present a design and implementation of a personalized broadcasting system using TV-Anytime metadata for providing personalized services. The TV-Anytime specifies metadata schema, metadata coding and delivery, and provides service models to provide personalized broadcasting content services at anytime when users want to consume using metadata, which includes ECG (Electronic Content Guide) and content descriptive information in a PDR (Personal Digital Recorder)-centric environment. The proposed personalized broadcasting system consists of a server that provides metadata binary-coding, encapsulation and multiplexing, and a client terminal that takes charge of de-multiplexing, metadata decoding, and metadata processing for personalized content accessing and consumption. This paper presents the details of the design of each functional module, and the evaluation results with a set of service scenarios in an end-to-end broadcasting test-bed.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.10
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• pp.31-38
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• 2008

This paper describes sensor network system implementation for the IEEE 1451.2 standard which guarantees compatibilities between various wired sensors. The proposed system consists of the Network Capable Application Processor(NCAP) in the IEEE 1451.0, the Transducer Independent Interface(TII) in the IEEE 1451.2, the Transducer Electronic Data Sheet(TEDS) and sensors. The research goal of this study is to minimize and optimize system complexity for IC design. The NCAP is implemented using C language in personal computer environment. TII is used in the parallel port between PC and an FPGA application board. Transducer is implemented using Verilog on the FPGA application board. We verified the proposed system architecture based on the standards.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.23-34
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• 2023

Wearable technology for military applications has received considerable attention as a means of personal status check and monitoring. Among many, an implementation to recognize specific motion states of a human is promising in that allows active management of troops by immediately collecting the operational status and movement status of individual soldiers. In this study, as an extension of military wearable application research, a new ankle wearable device is proposed that can glean the information of a soldier on the battlefield on which action he/she takes in which environment. Presuming a virtual situation, the soldier's upper limbs are easily exposed to uncertainties about circumstances. Therefore, a sensing module is attached to the ankle of the soldier that may always interact with the ground. The obtained data comprises 3-axis accelerations and 3-axis rotational velocities, which cannot be interpreted by hand-made algorithms. In this study, to discern the behavioral characteristics of a human using these dynamic data, a data-driven model is introduced; four features extracted from sliced data (minimum, maximum, mean, and standard deviation) are utilized as an input of the model to learn and classify eight primary military movements (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). As a result, the proposed device could recognize a movement status of a solider with 95.16% accuracy in an arbitrary test situation. This research is meaningful since an effective way of motion recognition has been introduced that can be furtherly extended to various military applications by incorporating wearable technology and artificial intelligence.