• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.620-623
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• 2003

The material processing by using ultrashort pulse laser, in recently, is actively applying into the micro machining and nano-machining technology since ultrashort pulse has so faster than the time which the electrons energy absorbing photon energy is transmitted to surrounding lattice-phonon that it has many advantages in point of machining. The micro machining of metallic thin film on the plain glass is widely used in the fields such as mask repairing for semiconductor, fabrication of photonic crystal, MEMS devices and data storage devices. Therefore, it is important to secure the machining technology of the sub-micron size. In this research, we set up the machining system by using ultrashort pulse laser and conduct on the Cr 200nm thin film ablation experiments of spot and line with the variables such as energy, pulse number, speed, and so on. And we observed the characteristics of surrounding heat-affected zone and by-products appeared in critical energy density and higher energy density through SEM, and also examined the machining features between in He gas atmosphere which make pulse change minimized by nonlinear effect and in the air. Finally, the pit size of 0.8${\mu}{\textrm}{m}$ diameter and the line width of 1${\mu}{\textrm}{m}$ could be obtained.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.2
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• pp.38-47
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• 2001

In this paper, a new scheme of adaptive-neuro control system is presented to implement real-time control of robot manipulator using Digital Signal Processors. Digital signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of therir prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust perfor-mance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for the implementation of real-time control of robot system by the simulation and experi-ment.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.162-169
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• 1999

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital Signal Processors. Digital signal processors DSPs. are micro-processors that are particularly developed for variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In addition, DSPs are as fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a biable computatinal tool in digital implementation of sophisticated controllers. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be a efficient control scheme for implementation of real-time control of robot system by the simulation and experiment.

• 한국연소학회:학술대회논문집
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• 2006.04a
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• pp.213-217
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• 2006

Recent advances in energetic materials modeling and high-resolution hydrocode simulation enable enhanced computational analysis of bio-medical treatments that utilize high-pressure shock waves. Of particular interest is in designing devices that use such technology in medical treatments. For example, the generated micro shock waves with peak pressure on orders of 10 GPa can be used for treatments such as kidney stone removal, trans-dermal micro-particle delivery. and cancer cell removal. In this work, we present a new computational methodology for applying the high explosive dynamics to bio-medical treatments by making use of high pressure shock physics and multi-material wave interactions. The preliminary calculations conducted by the in-house code, GIBBS2D, captures various features that are observed from the actual experiments under the similar test conditions. We expect to gain novel insights in applying explosive shock wave physics to the bio-medical science involving drug injection. Our forthcoming papers will illustrate the quantitative comparison of the modeled results against the experimental data.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.4
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• pp.3-7
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• 2006

Confocal scanning microscopy is a measurement technique used to observe micrometer and sub-micrometer features due to its high resolution, nondestructive properties, and 3D surface profiling capabilities. The design, implementation, and performance test of a confocal scanning microscopy system are presented in this paper. A short-wavelength laser (405 nm) and an objective lens with a high numerical aperture (0.95) were used to achieve the desired high resolution, while the x- and y-axis scans were implemented using an acousto-optic deflector and galvanomirror, respectively. An objective lens with a piezo-actuator was used to scan the z-axis. A spatial resolution of less than 138 nm was achieved, along with successful 3D surface reconstructions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.176-183
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• 2005

Laser heat treatment technology is used for improving the feature of fatigue resistance and wear resistance in mobile parts. The purpose of this study is to compare the characteristics of laser heat treatment and high frequency heat treatment, which is commonly used in industrial place. For the preemptive experiment, the distribution, depth and size of hardening and its micro-structural features were compared between surface heat treatment case by defocusing and variables of each process for heat treatment by exclusively manufactured heat treatment optical system. As a result, high frequency heat treatment has wide distribution of hardening depth and width about 3 times larger than laser heat treatment, however, its average hardness showed 621.4Hv which is smaller than the average hardness of laser heat treatment with 691Hv.

• Journal of the Korean Magnetic Resonance Society
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• v.23 no.3
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• pp.61-66
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• 2019

RNAs exhibit distinct structural and dynamic features required for proper function. The hydrogen-bonded imino protons of RNAs are a probe of the conformational transition and dynamic feature. MicroRNAs originate from primary transcripts containing hairpin structures. The levels of mature miR156 influence the flowering time of plants. To understand the molecular mechanism of biological function of $miR156:miR156^*$ duplex, we performed hydrogen exchange study on the model RNAs mimicking two phenotypes of $miR156:miR156^*$, $miR156:miR156^*$ (m-miR156a) and $miR156:miR156^*$ (m-miR156g) duplexes. This study found that the internal bulge of m-miR156a destabilized the neighboring base-pairs, whereas the bulge structure of m-miR156g did not affect the thermal stabilities of the neighboring base-pairs.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.256-266
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• 2021

The Convolutional Neural Network (CNN) has recently made potential improvements in face verification applications. In fact, different models based on the CNN have attained commendable progress in the classification rate using a massive amount of data in an uncontrolled environment. However, the enormous computation costs and the considerable use of storage causes a noticeable problem during training. To address these challenges, we focus on relevant data trained within the CNN model by integrating a lifting method for a better tradeoff between the data size and the computational efficiency. Our approach is characterized by the advantage that it does not need any additional space to store the features. Indeed, it makes the model much faster during the training and classification steps. The experimental results on Labeled Faces in the Wild and YouTube Faces datasets confirm that the proposed CNN framework improves performance in terms of precision. Obviously, our model deliberately designs to achieve significant speedup and reduce computational complexity in deep CNNs without any accuracy loss. Compared to the existing architectures, the proposed model achieves competitive results in face recognition tasks

• Applied Chemistry for Engineering
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• v.33 no.3
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• pp.258-271
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• 2022

Ferrate (VI) [Fe(VI)] has multi-functional features, which include potential oxidant, coagulant, and disinfectant. Because of these distinctive properties, numerous studies on the synthesis of ferrate (VI) and its possible applications in a wide research areas have been investigated. This review highlights the recent development made on different synthesis methods for ferrate including wet chemical, electrochemical, and thermal methods. The recent advancements achieved in ferrate (VI) oxidation and the synergistic effect of the oxidative properties of ferrate (VI) in the presence of various compounds or materials are also included. Moreover, this review discusses the applications of ferrate (VI) for degrading various types of water pollutants and its reaction mechanism. The optimized experimental conditions and interaction mechanisms of ferrate (VI) with micro-pollutants, dyes, and other organic compounds are also elaborated upon to provide greater insight for future studies. Lastly, the limitations and prospects of the ferrate use in the treatment of polluted water are described.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.375-382
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• 2022

This paper proposes a multi-core cooperative computing structure considering the heterogeneous features of automotive embedded on-chip software. The automotive embedded software has the heterogeneous execution flow properties for various hardware drives. Software developed with a homogeneous execution flow without considering these properties will incur inefficient overhead due to core latency and load. The proposed method was evaluated on an target board on which a automotive MCU (micro-controller unit) with built-in multi-cores was mounted. We demonstrate an overhead reduction when software including common embedded system tasks, such as ADC sampling, DSP operations, and communication interfaces, are implemented in a heterogeneous execution flow. When we used the proposed method, embedded software was able to take advantage of idle states that occur between heterogeneous tasks to make efficient use of the resources on the board. As a result of the experiments, the power consumption of the board decreased by 42.11% compared to the baseline. Furthermore, the time required to process the same amount of sampling data was reduced by 27.09%. Experimental results validate the efficiency of the proposed multi-core cooperative heterogeneous embedded software execution technique.