• Nuclear Engineering and Technology
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• v.52 no.1
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• pp.164-169
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• 2020

Use of SiPM has been considered as an alternative to PMT, because of its compact size, low-operating voltage, non-sensitive to electromagnetic, low costs and so on. The main limitation for the use of SiPM is due to its small sensitive area compared to PMT that limits the light collection, and therefore the sensor energy resolution. In this article we studied the effect of increasing the number of SiPM by connecting them in parallel to increase the active detection area. This allowed us to compare the different energy resolution measurements. ¹³⁷Cs has been selected as reference to study the energy resolution for 662 keV gamma-rays. Another investigation was to compare the minimum detectable gamma energy under various SiPM configurations. It has been found that the use of 4 SiPM arrays can greatly improve the energy resolution up to 4% than only one SiPM array, meanwhile use of more than 2 SiPM arrays does not increase the energy resolution significantly. Thus we can conclude that for a large area of cylindrical scintillator (3 × 3 inches), the use of SiPMs are limited to a certain number or certai active area depending on the commercial SiPMs, and its cost should be less than traditional PMT for the cost-effective and compact size considerations. It is well known that the gain of SiPM varies with temperature. In this article, we also calibrated gain to guarantee the same position of photoelectric peak in response of different temperatures.

• Korean Journal of Materials Research
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• v.22 no.10
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• pp.562-568
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• 2012

Metal nanowires can be coated on various substrates to create transparent conducting films that can potentially replace the dominant transparent conductor, indium tin oxide, in displays, solar cells, organic light-emitting diodes, and electrochromic windows. One issue with these metal nanowire based transparent conductive films is that the resistance between the nanowires is still high because of their low aspect ratio. Here, we demonstrate high-performance transparent conductive films with silver nanofiber networks synthesized by a low-cost and scalable electrospinning process followed by two-step sequential thermal treatments. First, the PVP/$AgNO_3$ precursor nanofibers, which have an average diameter of 208 nm and are several thousands of micrometers in length, were synthesized by the electrospinning process. The thermal behavior and the phase and morphology evolution in the thermal treatment processes were systematically investigated to determine the thermal treatment atmosphere and temperature. PVP/$AgNO_3$ nanofibers were transformed stepwise into PVP/Ag and Ag nanofibers by two-step sequential thermal treatments (i.e., $150^{\circ}C$ in $H_2$ for 0.5 h and $300^{\circ}C$ in Ar for 3 h); however, the fibrous shape was perfectly maintained. The silver nanofibers have ultrahigh aspect ratios of up to 10000 and a small average diameter of 142 nm; they also have fused crossing points with ultra-low junction resistances, which result in high transmittance at low sheet resistance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5135-5142
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• 2011

A flexible mechanism is proposed in this paper to improve the dynamic response performance of a traffic flow control system in an urban area. The roads, vehicles, and traffic control systems are all modeled as intelligent systems, wherein a wireless communication network is used as the medium of communication between the vehicles and the roads. The necessary sensor networks are installed in the roads and on the roadside upon which reinforcement learning is adopted as the core algorithm for this mechanism. A traffic policy can be planned online according to the updated situations on the roads, based on all the information from the vehicles and the roads. This improves the flexibility of traffic flow and offers a much more efficient use of the roads over a traditional traffic control system. The optimum intersection signals can be learned automatically online. An intersection control system is studied as an example of the mechanism using Q-learning based algorithm, and simulation results showed that the proposed mechanism can improve the traffic efficiency and the waiting time at the signal light by more than 30% in various conditions compare to the traditional signaling system.

• Proceedings of the KAIS Fall Conference
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• 2008.05a
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• pp.248-250
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• 2008

This paper proposes a prediction method to prevent traffic accident and reduce to vehicle waiting time using neural network. Computer simulation results proved reducing average vehicle waiting time which proposed coordinating green time better than electro-sensitive traffic light system dose not consider coordinating green time. Moreover, we present neural network approach for traffic accident prediction with unnormalized (actual or original collected) data. This approach is not consider the maximum value of data and possible use the network without normalizing but the predictive accuracy is better. Also, the unnormalized method shows better predictive accuracy than the normalized method given by maximum value. Therefore, we can make the best use of this model in software reliability prediction using unnormalized data. Computer simulation results proved reducing traffic accident waiting time which proposed neural network better than conventional system dosen't consider neural network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.985-990
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• 2007

The method of enhancing visibility in optical fiber sensor was investigated by improving coherence length of light source. The optical feedback technique is used to enhance coherence length in fiber laser which generates laser in near infrared wavelength region and utilizes low loss characteristics of optical communication grade fiber. In this paper, the effect to coherence length by short and long optical feedback paths are investigated by using Mach-Zehnder interferometer technique. The effect to coherence length by changing optical feedback power and optical modulation are investigated. The spectral drift was calculated by measuring the degree of phase perturbation in unbalanced Mach-Zehnder interferometer having loom path difference. The short optical feedback path was effective to reduce spectral drift to 450kHz/sec and the long optical feedback path in combination with short optical feedback path was found to further reduce spectral drift to 50kHz/sec.

• Korean Journal of Remote Sensing
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• v.25 no.6
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• pp.547-557
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• 2009

LIDAR (LIght Detection And Ranging) is an active remote sensing technology which provides 3D coordinates of the Earth's surface by performing range measurements from the sensor. Early small footprint LIDAR systems recorded multiple discrete returns from the back-scattered energy. Recent advances in LIDAR hardware now make it possible to record full digital waveforms of the returned energy. LIDAR waveform decomposition involves separating the return waveform into a mixture of components which are then used to characterize the original data. The most common statistical mixture model used for this process is the Gaussian mixture. Waveform decomposition plays an important role in LIDAR waveform processing, since the resulting components are expected to represent reflection surfaces within waveform footprints. Hence the decomposition results ultimately affect the interpretation of LIDAR waveform data. Computational requirements in the waveform decomposition process result from two factors; (1) estimation of the number of components in a mixture and the resulting parameter estimates, which are inter-related and cannot be solved separately, and (2) parameter optimization does not have a closed form solution, and thus needs to be solved iteratively. The current state-of-the-art airborne LIDAR system acquires more than 50,000 waveforms per second, so decomposing the enormous number of waveforms is challenging using traditional single processor architecture. To tackle this issue, four parallel LIDAR waveform decomposition algorithms with different work load balancing schemes - (1) no weighting, (2) a decomposition results-based linear weighting, (3) a decomposition results-based squared weighting, and (4) a decomposition time-based linear weighting - were developed and tested with varying number of processors (8-256). The results were compared in terms of efficiency. Overall, the decomposition time-based linear weighting work load balancing approach yielded the best performance among four approaches.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2013.11a
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• pp.28-29
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• 2013

We have been measuring $CH_4$ flux in a rice paddy in Gimje using the eddy covariance method since July 2011. In order to measure the fast fluctuations of $CH_4$ concentration, an innovative LI-7700 open-path laser spectrometer is used. This high-precision, low power, light weight, low maintenance sensor enables us to operate it on a continuous and long-term basis. One particular feature, among other things, is the self-cleaning lower mirror which decreases maintenance requirements while ensuring more robust, continuous, high-quality dataset. Its cleaning is initiated at user-specified time intervals or a signal strength threshold, and its status is recorded as a diagnostic index. We have noticed that the operation of LI-7700 at Gimje site is quite challenging particularly due to its frequent mirror cleaning requirement and the associated sensitivity of the instrument. In this presentation, we present some field observation data regarding the mirror cleaning and their analysis, thereby suggesting the pertinent operation options for high-quality, maximum data retrieval in the field.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.778-783
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• 2018

With the rapid advancement of information and communication technology and industrial technologies, a hyper-connected society is being realized to connect human beings, all programs and things via the Internet. IoT (Internet of Thing), which connects a thing and another thing, and things and human beings, gathers information to realize the hyper-connected society. MQTT (Message Queuing Telemetry Transport) is a push-technology-based light message transmission protocol that was developed to be optimized to the limited communication environment such as IoT. In pursuing the hyper-connected society, IoT's sensor environment information is now being used as a wide range of information on people's diseases and health management. Thus, security problems of such MQTT include not only the leak of environmental information but also the personal information infringement. To resolve such MQTT security problems, we have designed a new security MQTT communication by applying the initial-value sensitivity and pseudorandomness of the chaotic system to the integrity and confidentiality. The encryption method using our proposed chaotic system offers a simple structure and a small amount of calculation, and it is deemed to be suitable to the limited communication environment such as IoT.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.942-943
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• 2016

Stereo gamma ray detection system generates a two-dimensional image of the gamma ray by using the position values and the gamma ray signal. And the device will overlap with the visible light image shows the actual distribution of the gamma-ray space. The gamma ray detection device is a stereo configuration to a motion controller for controlling the signal measurement unit and the position detection portion for detecting the detection portion and the gamma-ray signal comprising a gamma-ray detection sensor. In this paper, we developed a system operation management algorithm for each module individually configured efficiently. We confirmed the imaged and distribution information output for the gamma rays from gamma-ray irradiation test site by using these results.