• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.4
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• pp.331-335
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• 2020

In this study, through the accumulated technologies such as real-time monitoring of power consumption using power line communication (PLC) method, power control, and automatic blocking of standby power, to commercialize them, we developed the hardware design, algorithm, protocol and module along with data transmission using PLC. We conducted the study to develop advanced products. We also proposed cloud-based smart outlet products with a novel type of outlet. These products can measure the internal power consumption through the H/W modules and the modules that control the power of household appliances connected to the smart outlets and smart plugs. Subsequently, they transmit the measurements to the energy saving system server via a communication module. This system can control the terminal device connected to the Gateway (G/W) server through a mobile phone. This will allow the customer to check the power consumption of the building at any given time, to turn the terminal on/off, and to maximize the energy efficiency during the construction of new apartments or multi-family housing in an area.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1445-1456
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• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.69-77
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• 2019

Today, most of elevators have an emergency call facility for emergency situations. However, if the network installed in the elevator is also out of power, it cannot be used for the elevator remote monitoring and management. So, we develop an integrated and unified emergency call system, which can transmit not only telephone call but also data signals using PSTN(Public Switched Telephone Network) in order to remote monitoring and management of elevators, even though a power outage occurs. The proposed integrated emergency call system to process multiple data such as voice and operational information is a multi-channel board system which is composed of an emergency phone signal processing module and an operational information processing module in the control box of elevator. In addition, the RMS(remote management server) systems based on the Web consist of a dial-up server and a remote monitoring server where manages the elevator's operating information, status records, and operational faults received via the proposed integrated and unified emergency call system in real time. So even if there's a catastrophic emergency, the proposed RMS systems shall ensure and maintain the safety of passengers inside the elevator. Also, remote control of the elevator by this system should be more efficient and secure. In near future, all elevator emergency call system need to support multifunctional capabilities to transmit operational data as well as phone calls for the safety of passengers. In addition, for safer elevators, it is necessary to improve them more efficiently by combining them with high-tech technologies such as the Internet of Things and artificial intelligence.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1563-1570
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• 2023

In this study, a DeCART/MIG uncertainty quantification (UQ) analysis code system with a multicorrelated cross section stochastic sampling (S.S.) module was established and verified through the UAM (Uncertainty Analysis in Modeling) and the BEAVRS (Benchmark for Evaluation And Validation of Reactor Simulations) benchmark calculations. For the S.S. calculations, a sample of 500 DeCART multigroup cross section sets for two major actinides, i.e., ²³⁵U and ²³⁸U, were generated by the MIG code and covariance data from the ENDF/B-VII.1 evaluated nuclear data library. In the three pin problems (i.e. TMI-1, PB2, and Koz-6) from the UAM benchmark, the uncertainties in k_inf by the DeCART/MIG S.S. calculations agreed very well with the sensitivity and uncertainty (S/U) perturbation results by DeCART/MUSAD and the S/U direct subtraction (S/U-DS) results by the DeCART/MIG. From these results, it was concluded that the multi-group cross section sampling module of the MIG code works correctly and accurately. In the BEAVRS whole benchmark problems, the uncertainties in the control rod bank worth, isothermal temperature coefficient, power distribution, and critical boron concentration due to cross section uncertainties were calculated by the DeCART/MIG code system. Overall, the uncertainties in these design parameters were less than the general design review criteria of a typical pressurized water reactor start-up case. This newly-developed DeCART/MIG UQ analysis code system by the S.S. method can be widely utilized as uncertainty analysis and margin estimation tools for developing and designing new advanced nuclear reactors.

• Korean Journal of Construction Engineering and Management
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• v.15 no.1
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• pp.11-19
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• 2014

The Construction industry is a labor-intensive industry that its labor cost takes up about 30~40% out of the whole construction cost. However, due to a stereotype that on-site work is a 3D job there is a shortage of the labor forces. Modular construction method is to produce modular units in the plant so that workers could work stably. Also, after delivering the module from plant to the site, there will be only installment to be required that shortens construction duration. Even though the modular market is currently expanding based on military facilities in Korea, its best strengths are not demonstrated well which are shortened construction period and low cost. It also causes labor problem of production due to minimum utilization of the modular construction method. Multi-skilled labor means a technician that is able to perform more than two kinds of work with more than two techniques. Multi-skilled labor can proceed smoothly by figuring out the connectivity between the precedent and following operations. Therefore, this research is to apply the concept of Multi-skilled labors, suggest solutions and allocate manpowers efficiently. As a result, it helps to decrease idle manpowers during the operation and the total labor forces can be saved. Low cost is the original strength of the modular which can stand out so the modular market is expected to expand.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.6
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• pp.613-624
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• 2011

An MMIC multi-function chip for an X-band active phased array radar system has been designed and fabricated using a 0.5 ${\mu}m$ GaAs p-HEMT commercial process. A digital serial-to-parallel converter is included in this chip in order to reduce the number of the control interface. The multi-function chip provides several functions: 6-bit phase shifting, 6-bit attenuation, transmit/receive switching, and signal amplification. The fabricated multi-function chip with a relative compact size of 24 $mm^2$(6 mm${\times}$4 mm) exhibits a transmit/receive gain of 24/15 dB and a P1dB of 21 dBm from 8.5 GHz to 10.5 GHz. The RMS errors for the 64 states of the 6-bit phase shift and attenuation were measured to $7^{\circ}$ and 0.3 dB, respectively over the frequency.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.45-51
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• 2021

With the development of deep learning, semantic segmentation methods are being studied in various fields. There is a problem that segmenation accuracy drops in fields that require accuracy such as medical image analysis. In this paper, we improved PSPNet, which is a deep learning based segmentation method to minimized the loss of features during semantic segmentation. Conventional deep learning based segmentation methods result in lower resolution and loss of object features during feature extraction and compression. Due to these losses, the edge and the internal information of the object are lost, and there is a problem that the accuracy at the time of object segmentation is lowered. To solve these problems, we improved PSPNet, which is a semantic segmentation model. The multi-scale attention proposed to the conventional PSPNet was added to prevent feature loss of objects. The feature purification process was performed by applying the attention method to the conventional PPM module. By suppressing unnecessary feature information, eadg and texture information was improved. The proposed method trained on the Cityscapes dataset and use the segmentation index MIoU for quantitative evaluation. As a result of the experiment, the segmentation accuracy was improved by about 1.5% compared to the conventional PSPNet.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.274-286
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• 2022

Multi-object tracking has been studied for a long time under computer vision and plays a critical role in applications such as autonomous driving and driving assistance. Multi-object tracking techniques generally consist of a detector that detects objects and a tracker that tracks the detected objects. Various publicly available datasets allow us to train a detector model without much effort. However, there are relatively few publicly available datasets for training a tracker model, and configuring own tracker datasets takes a long time compared to configuring detector datasets. Hence, the detector is often developed separately with a tracker module. However, the separated tracker should be adjusted whenever the former detector model is changed. This study proposes a system that can train a model that performs detection and tracking simultaneously using only the detector training datasets. In particular, a Siam network with augmentation is used to compose the detector and tracker. Experiments are conducted on public datasets to verify that the proposed algorithm can formulate a real-time multi-object tracker comparable to the state-of-the-art tracker models.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.3
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• pp.277-284
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• 2012

In this study, a heat-transfer performance analysis is carried out for a multi-channel volumetric air receiver for a solar power tower. On the basis of a series of reviews regarding the relevant literature, a calculation process is proposed for the prediction of the wall- and air- temperature distributions of a single channel at given geometric and input conditions. Furthermore, a unique mathematical model of the receiver effectiveness is presented through analysis of the temperature profile. The receiver is made of silicon carbide. A total of 225 square straight channels per module are molded to induce the air flow, and each channel has the dimensions of $2mm(W){\times}2mm(H){\times}0.2mm(t){\times}320mm(L)$. The heat-transfer rate, temperature distribution and effectiveness are presented according to the variation of the channel and module number under uniform irradiation and mass flow rate. The available air outlet temperature applied to the solar power tower should be over $700^{\circ}C$. This numerical model was actually used in the design of a 200 kW-level commercial solar air receiver, and the required number of modules satisfying the thermal performance could be obtained for the specified geometric and input conditions.

• The KIPS Transactions:PartA
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• v.17A no.3
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• pp.127-136
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• 2010

A wireless sensor network(WSN) which roles as a mediator between living environment and computers in ubiquitous computing is very essential research area. Due to the constraint that sensor nodes should work in very resource-restricted circumstances, an operating system that can manage resources effectively is demanded. Also, a sensor network should be able to deal with many events quickly and simultaneously in order to respond to various physical changes in outer environment. The Sensor Network Operating System such as TinyOS, MANTIS and NanoQplus is much designed so that it can satisfy such requirement. But, for programmers who develop application program for sensor networks, they have lack of frameworks which the development is easily possible from restricted development environment. In this paper for this, we implemented a state machine framework apt for responsive systems in NanoQplus which is multi-thread-based sensor network operating system. In addition we propose an event broker module(EBM) for effective event dispatching, a message data structure for message sharing among state machines, and an execution module that handles messages and their queue and performs state transition of the machines. Furthermore, we could do the development more easily an application program with a state-based framework by developing CASE tools.