• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.1
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• pp.31-36
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• 2009

Micro-machining technology has been adopted for shape accuracy of micrometer and sub-micrometer scale, surface roughness of tens nanometer in industries. In micro-machining process the quality of machined surface is derived from machining condition and tooling. This paper investigates AE(acoustic emission) and cutting force signals according to machined surface quality related to machining condition. Machined surface quality was analyzed by the AE and cutting force parameter which reflect surface morphology. The characteristics of signal were extracted for process optimization by monitoring both the tool condition and the machined surface texture in micro end milling process.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.15-18
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• 2015

Front end planning is arguably the most impactful process in the successful delivery of capital projects. Organizations expend substantial effort in this planning process, intending to minimize risk and promote project success. This process has been well documented, including critical technical components, as well as the importance of team collaborative components. As organizations continue to pursue large projects with multi-national participation from sponsors, designers, contractors and suppliers, the importance of collaboration on a global scale during front end planning becomes more important, not less. This paper will outline research performed over the past two decades giving the basic components of the process and the value of global collaboration. It will provide guidance to project participants in pursuing successful planning.

• Journal of Environmental Health Sciences
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• v.39 no.3
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• pp.289-299
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• 2013

Objectives: For the field application of the dielectric barrier discharge plasma reactor, scale-up of the plasma reactor is needed. This study investigated the possibility of inactivation of microorganisms in sewage using pilot multi-plasma reactor. We also considered the possibility of degradation of total organic carbon (TOC) and nonbiodegradable matter ($UV_{254}$) in sewage. Methods: The pilot plasma reactor consists of plasma reactor with three plasma modules (discharge electrode and quartz dielectric tube), liquid-gas mixer, high voltage transformers, gas supply equipment and a liquid circulation system. In order to determine the operating conditions of the pilot plasma reactor, we performed experiments on the operation parameters such as gas and liquid flow rate and electric discharge voltage. Results: The experimental results showed that optimum operation conditions for the pilot plasma reactor in batch experiments were 1 L/min air flow rate), 4 L/min liquid circulation rate, and 13 kV electric discharge voltage, respectively. The main operation factor of the pilot plasma process was the high voltage. In continuous operation of the air plasma process, residual microorganisms, $UV_{254}$ absorbance and TOC removal rate at optimal condition of 13 kV were $10^{2.24}$ CFU/mL, 56.5% and 8.6%, respectively, while in oxygen plasma process at 10 kV, residual microorganisms, $UV_{254}$ absorbance and TOC removal rate at optimal conditions were $10^{1.0}$ CFU/mL, 73.3% and 24.4%, respectively. Electric power was increased exponentially with the increase in high voltage ($R^2$ = 0.9964). Electric power = $0.0492{\times}\exp^{(0.6027{\times}lectric\;discharge\;voltage)}$ Conclusions: Inactivation of microorganisms in sewage effluent using the pilot plasma process was done. The performance of oxygen plasma process was superior to air plasma process. The power consumption of oxygen plasma process was less than that of air plasma process. However, it was considered that the final evaluation of air and oxygen plasma must be evaluated by considering low power consumption, high process performance, operating costs and facility expenses of an oxygen generator.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.7
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• pp.669-679
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• 2008

With the increasing demands of information sharing and searches via the web, the web search engine has drawn much attention. Although many researches have been done to solve technical challenges to build the web search engine, the issue regarding its query processing system is rarely dealt with. Since the software architecture and operational schemes of the query processing system are hard to elaborate, we here present related techniques implemented on a commercial system. The implemented system is a very large-scale system that can process 5-million user queries per day by using index files built on about 65-million web pages. We implement a multi-level cache scheme to save already returned query results for performance considerations, and the multi-level cache is managed in 4-level cache storage areas. Using the multi-level cache, we can improve the system throughput by a factor of 4, thereby reducing around 70% of the server cost.

• 유체기계공업학회:학술대회논문집
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• 2006.08a
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• pp.33-36
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• 2006

As the computing environment is rapidly improved, the interests of CFD are gradually focused on large-scale computation over complex geometry. Keeping pace with the trend, essential computational tools to obtain solutions of complex aerospace flow analysis and design problems are examined. An accurate and efficient flow analysis and design codes for large-scale aerospace problem are presented in this work. With regard to original numerical schemes for flow analysis, high-fidelity flux schemes such as RoeM, AUSMPW+ and higher order interpolation schemes such as MLP (Multi-dimensional Limiting Process) are presented. Concerning the grid representation method, a general-purpose basis code which can handle multi-block system and overset grid system simultaneously is constructed. In respect to design optimization, the importance of turbulent sensitivity is investigated. And design tools to predict highly turbulent flows and its sensitivity accurately by fully differentiating turbulent transport equations are presented. Especially, a new sensitivity analysis treatment and geometric representation method to resolve the basic flow characteristics are presented. Exploiting these tools, the capability of the proposed approach to handle complex aerospace simulation and design problems is tested by computing several flow analysis and design problems.

• ETRI Journal
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• v.39 no.3
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• pp.326-335
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• 2017

In the uplink transmission of massive (or large-scale) multi-input multi-output (MIMO) systems, large dimensional signal detection and its hardware design are challenging issues owing to the high computational complexity. In this paper, we propose low-complexity hardware architectures of Richardson iterative method-based massive MIMO detectors. We present two types of massive MIMO detectors, directly mapped (type1) and reformulated (type2) Richardson iterative methods. In the proposed Richardson method (type2), the matrix-by-matrix multiplications are reformulated to matrix-vector multiplications, thus reducing the computational complexity from $O(U^2)$ to O(U). Both massive MIMO detectors are implemented using a 65 nm CMOS process and compared in terms of detection performance under different channel conditions (high-mobility and flat fading channels). The hardware implementation results confirm that the proposed type1 Richardson method-based detector demonstrates up to 50% power savings over the proposed type2 detector under a flat fading channel. The type2 detector indicates a 37% power savings compared to the type1 under a high-mobility channel.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.467-472
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• 2005

The principal objective of enhancement methods is to process an image so that the output image is more suitable than the original image lot a specific application. Images taken in the night can be low-contrast images because of poor environments. In this paper, we compared the performance of Image Contrast Enhancement Technique Using Clustering Algorithm(ICECA) with those of color adjustment methods such as Histogram Equalization(HE), Brightness Preserving Bi-Histogram Equalization(BBHE), and the Multi-Scale Refiner(MSR). We compared these methods by applying the image enhancement methods to a set of diverse images.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.36.2-36.2
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• 2021

In the outskirts of galaxy clusters, weak shocks with M_s < ~3 appear as radio relics where the synchrotron radiation is emitted from cosmic-ray (CR) electrons. To understand the production of CR electrons through the so-called diffusive shock acceleration (DSA), the electron injection into the DSA process at shocks in the hot intracluster medium (ICM) has to be described. However, the injection remains as an unsolved, outstanding problem. To explore this problem, 2D Particle-in-Cell (PIC) simulations were performed. In this talk, we present the electron preacceleration mechanism mediated by multi-scale plasma waves in the shock transition zone. In particular, we find that the electron preacceleration is effective only in the supercritical shocks, which have the sonic Mach number M_s > M_crit ≈ 2.3 in the high-beta (β~100) plasma of the ICM, because the Alfven ion cyclotron instability operates and hence multi-scale plasma waves are induced only in such supercritical shocks. Our findings will help to understand the nature of radio relics in galaxy clusters.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.393-394
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• 2010

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4439-4455
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• 2021

Compared with two-stage object detection algorithms, one-stage algorithms provide a better trade-off between real-time performance and accuracy. However, these methods treat the intermediate features equally, which lacks the flexibility to emphasize meaningful information for classification and location. Besides, they ignore the interaction of contextual information from different scales, which is important for medium and small objects detection. To tackle these problems, we propose an image pyramid network based on dual attention mechanism (DAIPNet), which builds an image pyramid to enrich the spatial information while emphasizing multi-scale informative features based on dual attention mechanisms for one-stage object detection. Our framework utilizes a pre-trained backbone as standard detection network, where the designed image pyramid network (IPN) is used as auxiliary network to provide complementary information. Here, the dual attention mechanism is composed of the adaptive feature fusion module (AFFM) and the progressive attention fusion module (PAFM). AFFM is designed to automatically pay attention to the feature maps with different importance from the backbone and auxiliary network, while PAFM is utilized to adaptively learn the channel attentive information in the context transfer process. Furthermore, in the IPN, we build an image pyramid to extract scale-wise features from downsampled images of different scales, where the features are further fused at different states to enrich scale-wise information and learn more comprehensive feature representations. Experimental results are shown on MS COCO dataset. Our proposed detector with a 300 × 300 input achieves superior performance of 32.6% mAP on the MS COCO test-dev compared with state-of-the-art methods.