• Journal of Practical Engineering Education
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• v.11 no.2
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• pp.283-289
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• 2019

Recently, product mobility, data compatibility and communication connectivity have become very important to the control system, depending on the application of smart manufacturing. Accordingly, embedded systems are essential in all industries including home appliances, telecommunication, and national defense. Therefore, the demand for embedded system development personnel is increasing further, and education and training programs are needed to combine the practical skills of industrial sites, including programming skills and hardware. Currently, embedded system education offers a variety of education centered on Aduino, but this is mostly for beginners and is not sufficient for majors. In addition, while various prototype studies related to embedded systems are active, the training and training programs for working-level human resources needed at industrial sites are very scarce. Therefore, in order to foster the working personnel of the embedded system for the application of smart manufacturing, this paper selected the capability unit through in-depth interviews and survey analysis of 10 experts based on NCS, and developed education and training programs and contents.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.5
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• pp.35-45
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• 2011

The Salsa20/12 stream cipher selected for the final eSTREAM portfolio has a better performance than software implementation of AES using an 8-bit microprocessor with restricted memory space, In the theoretical approach, the evaluation of exploitable timing vulnerability was 'none' and the complexity of side-channel analysis was 'low', but there is no literature of the practical result of power analysis attack. Thus we propose the correlation power analysis attack method and prove the feasibility of our proposed method by practical experiments, We used an 8-bit RISC AVR microprocessor (ATmegal128L chip) to implement Salsa20/12 stream cipher without any countermeasures, and performed the experiments of power analysis based on Hamming weight model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.600-602
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• 2021

With the development of the mobile industry and growing interest in artificial intelligence (AI) technology, a lot of research for AI processors which applicable to embedded systems is under study. When implementing AI to embedded systems, the design should be considered the restriction of resource and power consumption. Moreover, it is efficient to include a dedicated hardware accelerator in order to complement the low computational performance of the embedded system. In this paper, we propose an stand-alone embedded AI processor. The proposed AI processor includes a hardware accelerator that is dedicated to the distance-based AI algorithm and a general-purpose MCU that supports flexible programmability for application to various embedded systems. The AI processor was designed with Verilog HDL and verified by implementing on Field Programmable Gate Array (FPGA).

• Journal of Bio-Environment Control
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• v.23 no.1
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• pp.26-30
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• 2014

Purpose of this study was a development of a sprayer arm auto control system that could be operated according to distance from pear trees for automation of pest control. Auto control system included two parts, hardware and software. First, controller was made with an MCU and relay switches. Two types of ultra-sonic sensors were installed to measure distance from pear trees: one on/off type that detect up to 3 m, and the other continuous type providing 0~5 V output corresponding to distance of 0~3 m. Second, an auto control algorithm was developed to control. Each spraying arm was controlled according to the sensor-based distance from the pear trees. And it could dodge obstacles to protect itself. Max and min signal values were eliminated, when five sensor signals was collected, and then signals were averaged to reduce sensor's noises. According to results of field experiment, auto control test result was better than non auto control test result. Spraying rates were 69.25% (left line) and 98.09% (right line) under non auto control mode, because pear trees were not planted uniformly. But, auto control test's results were 92.66% (left line) and 94.64% (right line). Spraying rate was increased by maintaining distance from tree.