• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.349-353
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• 2004

A study on optimal placement of constrained layer damping treatment for vibration control of automotive panels is presented. The effectiveness of damping treatment depends upon design parameters such as choice of damping materials, locations and size of the treatment. This paper proposes a CAE (Computer Aided Engineering) methodology based on finite element analysis to optimize damping treatment. From the equivalent modeling technique, it is found that the best damping performance occurs as the viscoelstic patch is placed by means of the modal strain energy method of bare structural panels to identify flexible regions, which in turn facilitates optimizations of damping treatment with respect to location and size. Different configurations of partially applied damping layer treatment have been analyzed for their effectiveness in realizing maximum system damping with minimum mass of the applied damping material. Moreover, simulated frequency response function of the automotive roof with and without damping treatments are compared, which show the benefits of applying damping treatment. Finally, the optimized damping treatment configuration is validated by comparing the locations and the size of the treatment with that of an experimental modal test conducted on roof compartment.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1310-1319
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• 2016

Face detection is the first step in a wide range of face applications. However, detecting faces in the wild is still a challenging task due to the wide range of variations in pose, scale, and occlusions. Recently, many deep learning methods have been proposed for face detection. However, further improvements are required in the wild. Another important issue to be considered in the face detection is the computational complexity. Current state-of-the-art deep learning methods require a large number of patches to deal with varying scales and the arbitrary image sizes, which result in an increased computational complexity. To reduce the complexity while achieving better detection accuracy, we propose a fully convolutional network-based face detection that can take arbitrarily-sized input and produce feature maps (heat maps) corresponding to the input image size. To deal with the various face scales, a multi-scale network architecture that utilizes the facial components when learning the feature maps is proposed. On top of it, we design multi-task learning technique to improve detection performance. Extensive experiments have been conducted on the FDDB dataset. The experimental results show that the proposed method outperforms state-of-the-art methods with the accuracy of 82.33% at 517 false alarms, while improving computational efficiency significantly.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1391-1401
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• 2017

In this paper, a secondary resonance half-bridge dc-dc converter with an inductive output filter is presented. The primary side of such a converter utilizes asymmetric pulse width modulation (APWM) to achieve zero-voltage switching (ZVS) of the switches, and clamps the voltage of the switch to the input voltage. In addition, zero current switching (ZCS) of the output diode is achieved by a half-wave rectifier circuit with a filter inductor and a resonant branch in the secondary side of the proposed converter. Thus, the switching losses and diode reverse-recovery losses are eliminated, and the performance of the converter can be improved. Furthermore, an inductive output filter exists in the converter reduce the output current ripple. The operational principle, performance analysis and design equation of this converter are given in this paper. The analysis results show that the output diode voltage stress is independent of the duty cycle, and that the voltage gain is almost linear, similar to that of the isolation Buck-type converter. Finally, a 200V~380V input, 24V/2A output experimental prototype is built to verify the theoretical analysis.

• International Journal of Air-Conditioning and Refrigeration
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• v.13 no.4
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• pp.196-205
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• 2005

In this paper, recent research trend on heat transfer in impinging jet is reviewed. We focused on submerged jet that air issued into air or liquid issued into liquid. To control and enhance the heat transfer in single jet, researchers have performed a lot of experiments by considering the nozzle geometry, impinging surface and active method such as jet vibration, secondary injection and suction flow. The studies on multiple jet have been mainly focused on finding out the optimum condition and on investigating many different factors concerned with application condition (crossflow, rotation and geometry etc.) and combined techniques (rib turbulator, pin fin, dimple and effusion hole etc.). All most experiments showed the detailed heat transfer data by using liquid crystal method, infrared camera technique and naphthalene sublimation method. Many numerical calculations have been performed to investigate the flow and heat transfer characteristics in laminar jet region. Various turbulence models such as $k-\varepsilon-\bar{\nu^2}$, modified $k-\varepsilon-f_{\mu}$ were applied to the calculation for turbulent jet and the predicted results showed a good agreement with the experimental data. Although a lot of studies on impinging jet have performed consistently up to recently, further studies are still required to understand the flow and heat transfer characteristics more accurately, and to give a guideline for optimum impinging jet design in various applications.

• Journal of Magnetics
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• v.20 no.1
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• pp.79-85
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• 2015

This paper presents a comparative study of a Tubular Linear Machine (TLM) with an Axially Magnetized Single-sided Permanent Magnet (AMSPM) and an Axially Magnetized Double-sided Permanent Magnet (AMDPM) based on analytical field calculations. Using a two-dimensional (2-D) polar coordinate system and a magnetic vector potential, analytical solutions for the flux density produced by the stator windings are derived. This technique is significant for the design and control implementation of electromagnetic machines. The field solution is obtained by solving Maxwell's equations in the simplified boundary value problem consisting of the air gap and coil. These analytical solutions are then used to estimate the self and mutual inductances. Two different types of machine are used to verify the validity of these model simplifications, and the analytical results are compared to results obtained using the finite element method (FEM) and experimental measurement.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.54 no.5
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• pp.798-807
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• 2021

The directivity characteristics of acoustic transducers for conventional single-beam echo sounders considerably limit the detection of fish-size information in acoustic field surveys. To overcome this limitation, using the split-aperture technique to estimate the direction of arrival of single-echo signals from individual fish distributed within the sound beam represents the most reliable method for fish-size classification. For this purpose, we design and develop a split-beam data acquisition and processing system to obtain fish-size information in conjunction with a 50-kHz single-beam echo sounder. This split-beam data acquisition and processing system consists of a notebook PC, a field-programmable gate array board, an external single-transmitter module with a matching network, and four-channel receiver modules operating at a frequency of 50-kHz. The functionality of the developed split-beam data processor is tested and evaluated. Acoustic measurements in an experimental water tank showed that the developed data acquisition and processing system can be used as a fish-sizing echo sounder to estimate the size distribution of individual fish, although an external single-transmitter module with a matching network is required.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.341-349
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• 2021

Many emerging mobile ad-hoc network application communications are group-oriented. Multicast supports group-oriented applications efficiently, particularly in a mobile environment that has a limited bandwidth and limited power. Energy effectiveness along with safety are 2 key problem in MANET design. Within this paper, MANET is presented with a stable, energy-efficient clustering technique. In this proposed work advanced clustering in the networks with ticket ID cluster manager (TID-CMGR) has formed in MANET. The proposed routing scheme makes secure networking the shortest route possible. In this article, we propose a Cluster manager approach based on TICKET-ID to address energy consumption issues and reduce CH workload. TID-CMGR includes two mechanism including ticket ID controller, ticketing pool, route planning and other components. The CA (cluster agent) shall control and supervise the functions of nodes and inform to TID-CMGR. The CH conducts and transfers packets to the network nodes. As the CH energy level is depleted, CA elects the corresponding node with elevated energy values, and all new and old operations are simultaneously stored by CA at this time. A simulation trial for 20 to 100 nodes was performed to show the proposed scheme performance. The suggested approach is used to do experimental work using the NS- simulator. TIDCMGR is compared with TID BRM and PSO to calculate the utility of the work proposed. The assessment shows that the proposed TICKET-ID scheme achieves 90 percent more than other current systems.

• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.3966-3978
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• 2021

ISFRA (Integrated SFR Analysis Program for PSA) computer program has been developed for simulating the response of the PGSFR pool design with metal fuel during a severe accident. This paper describes validation of the ISFRA aerosol model against the Aerosol Behavior Code Validation and Evaluation (ABCOVE) experiments undertaken in 1980s for radionuclide transport within a SFR containment. ABCOVE AB5, AB6, and AB7 tests are simulated using the ISFRA aerosol model and the results are compared against the measured data as well as with the simulation results of the MELCOR severe accident code. It is revealed that the ISFRA prediction of single-component aerosols inside a vessel (AB5) is in good agreement with the experimental data as well as with the results of the aerosol model in MELCOR. Moreover, the ISFRA aerosol model can predict the "washout" phenomenon due to the interaction between two aerosol species (AB6) and two-component aerosols without strong mutual interference (AB7). Based on the theory review of the aerosol correlation technique, it is concluded that the ISFRA aerosol model can provide fast, stable calculations with reasonable accuracy for most of the cases unless the aerosol size distribution is strongly deformed from log-normal distribution.

• Structural Engineering and Mechanics
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• v.68 no.6
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• pp.691-700
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• 2018

Ground granulated blast furnace slag (GGBS) is a by product obtained from iron and steel industries, useful in the design and development of high quality cement paste/mortar and concrete. This paper investigates the applicability of relevance vector machine (RVM) based regression model to predict the compressive strength of various GGBS based concrete mixes. Compressive strength data for various GGBS based concrete mixes has been obtained by considering the effect of water binder ratio and steel fibres. RVM is a machine learning technique which employs Bayesian inference to obtain parsimonious solutions for regression and classification. The RVM is an extension of support vector machine which couples probabilistic classification and regression. RVM is established based on a Bayesian formulation of a linear model with an appropriate prior that results in a sparse representation. Compressive strength model has been developed by using MATLAB software for training and prediction. About 70% of the data has been used for development of RVM model and 30% of the data is used for validation. The predicted compressive strength for GGBS based concrete mixes is found to be in very good agreement with those of the corresponding experimental observations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2042-2059
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• 2019

Digital shadow puppet has traditionally relied on expensive motion capture equipments and complex design. In this paper, a low-cost driven technique is presented, that captures human pose estimation data with simple camera from real scenarios, and use them to drive virtual Chinese shadow play in a 2.5D scene. We propose a special method for extracting human pose data for driving virtual Chinese shadow play, which is called 2.5D human pose estimation. Firstly, we use the 3D human pose estimation method to obtain the initial data. In the process of the following transformation, we treat the depth feature as an implicit feature, and map body joints to the range of constraints. We call the obtain pose data as 2.5D pose data. However, the 2.5D pose data can not better control the shadow puppet directly, due to the difference in motion pattern and composition structure between real pose and shadow puppet. To this end, the 2.5D pose data transformation is carried out in the implicit pose mapping space based on self-network and the final 2.5D pose expression data is produced for animating shadow puppets. Experimental results have demonstrated the effectiveness of our new method.