• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3834-3857
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• 2021

The design of cluster-based routing protocols is necessary for Wireless Sensor Networks (WSN). But, due to the lack of features, the traditional methods face issues, especially on unbalanced energy consumption of routing protocol. This work focuses on enhancing the security and energy efficiency of the system by proposing Energy Efficient Based Secure Routing Protocol (EESRP) which integrates trust management, optimization algorithm and key management. Initially, the locations of the deployed nodes are calculated along with their trust values. Here, packet transfer is maintained securely by compiling a Digital Signature Algorithm (DSA) and Elliptic Curve Cryptography (ECC) approach. Finally, trust, key, location and energy parameters are incorporated in Particle Swarm Optimization (PSO) and meta-heuristic based Harmony Search (HS) method to find the secure shortest path. Our results show that the energy consumption of the proposed approach is 1.06mJ during the transmission mode, and 8.69 mJ during the receive mode which is lower than the existing approaches. The average throughput and the average PDR for the attacks are also high with 72 and 62.5 respectively. The significance of the research is its ability to improve the performance metrics of existing work by combining the advantages of different approaches. After simulating the model, the results have been validated with conventional methods with respect to the number of live nodes, energy efficiency, network lifetime, packet loss rate, scalability, and energy consumption of routing protocol.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.647-650
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• 2006

Low temperature polycrystalline silicon (LTPS) technology using a high power laser have been widely applied to thin film transistors (TFTs) for liquid crystal, organic light emitting diode (OLED) display, driver circuit for system on glass (SOG) and static random access memory (SRAM). Recently, the semiconductor industry is continuing its quest to create even more powerful CPU and memory chips. This requires increasing of individual device speed through the continual reduction of the minimum size of device features and increasing of device density on the chip. Moreover, the flat panel display industry also need to be brighter, with richer more vivid color, wider viewing angle, have faster video capability and be more durable at lower cost. Kornic Systems Co., Ltd. developed the $KORONA^{TM}$ LTP/GLTP series - an innovative production tool for fabricating flat panel displays and semiconductor devices - to meet these growing market demands and advance the volume production capabilities of flat panel displays and semiconductor industry. The $KORONA^{TM}\;LTP/GLTP$ series using DPSS laser and XeCl excimer laser is designed for the new generation of the wafer & FPD glass annealing processing equipment combining advanced low temperature poly-silicon (LTPS) crystallization technology and object-oriented software architecture with a semistandard graphical user interface (GUI). These leading edge systems show the superior annealing ability to the conventional other method. The $KORONA^{TM}\;LTP/GLTP$ series provides technical and economical benefits of advanced annealing solution to semiconductor and FPD production performance with an exceptional level of productivity. High throughput, low cost of ownership and optimized system efficiency brings the highest yield and lowest cost per wafer/glass on the annealing market.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.5
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• pp.19-25
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• 2011

With the issue of a Green IT Technology, studies on a environment-friendly luminous source that can reduce Carbon discharge and increase energy efficiency are actively progressed all over the world. Especially, with the problems of high oil price and environmental pollution, LED has made a great attention as a new luminous source that can replace the existing incandescent bulbs and fluorescent lights. In this paper, the proposed streetlight system becomes more intellectual by combining the low power consuming, high efficient, and high luminous LED module with a complex sensor module with temperature, humidity, illumination and motion sensors. Then, we design and implement the Ad-Hoc based LED-IT-Sensor integrated streetlight system that can maximize the energy savings efficiently with central monitoring system and selective remote dimming control by connecting them to the wireless ubiquitous sensor network(USN) using a Zigbee module.

• Journal of KIISE
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• v.43 no.1
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• pp.61-70
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• 2016

In recent years, there has been a need for techniques for large-scale ontology inference in order to infer new knowledge from existing knowledge at a high speed, and for a diversity of semantic services. With the recent advances in distributed computing, developments of ontology inference engines have mostly been studied based on Hadoop or Spark frameworks on large clusters. Parallel programming techniques using GPGPU, which utilizes many cores when compared with CPU, is also used for ontology inference. In this paper, by combining the advantages of both techniques, we propose a new method for reasoning large RDFS ontology data using a Spark in-memory framework and inferencing distributed data at a high speed using GPGPU. Using GPGPU, ontology reasoning over high-capacity data can be performed as a low cost with higher efficiency over conventional inference methods. In addition, we show that GPGPU can reduce the data workload on each node through the Spark cluster. In order to evaluate our approach, we used LUBM ranging from 10 to 120. Our experimental results showed that our proposed reasoning engine performs 7 times faster than a conventional approach which uses a Spark in-memory inference engine.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.36-48
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• 2022

As a valid numerical method to obtain a high-resolution result of a flow field, computational fluid dynamics (CFD) have been widely used to study coolant flow and heat transfer characteristics in fuel rod bundles. However, the time-consuming, iterative calculation of Navier-Stokes equations makes CFD unsuitable for the scenarios that require efficient simulation such as sensitivity analysis and uncertainty quantification. To solve this problem, a reduced-order model (ROM) based on proper orthogonal decomposition (POD) and machine learning (ML) is proposed to simulate the flow field efficiently. Firstly, a validated CFD model to output the flow field data set of the rod bundle is established. Secondly, based on the POD method, the modes and corresponding coefficients of the flow field were extracted. Then, an deep feed-forward neural network, due to its efficiency in approximating arbitrary functions and its ability to handle high-dimensional and strong nonlinear problems, is selected to build a model that maps the non-linear relationship between the mode coefficients and the boundary conditions. A trained surrogate model for modes coefficients prediction is obtained after a certain number of training iterations. Finally, the flow field is reconstructed by combining the product of the POD basis and coefficients. Based on the test dataset, an evaluation of the ROM is carried out. The evaluation results show that the proposed POD-ROM accurately describe the flow status of the fluid field in rod bundles with high resolution in only a few milliseconds.

• Smart Structures and Systems
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• v.32 no.5
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• pp.319-338
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• 2023

The study presents a new hybrid data-driven method by combining radial basis functions neural networks (RBF-NN) with the Jaya algorithm (JA) to provide effective structural health monitoring of arch dams. The novelty of this approach lies in that only one user-defined parameter is required and thus can increase its effectiveness and efficiency, as compared to other machine learning techniques that often require processing a large amount of training and testing model parameters and hyper-parameters, with high time-consuming. This approach seeks rapid damage detection in arch dams under dynamic conditions, to prevent potential disasters, by utilizing the RBF-NNN to seamlessly integrate the dynamic elastic modulus (DEM) and modal parameters (such as natural frequency and mode shape) as damage indicators. To determine the dynamic characteristics of the arch dam, the JA sequentially optimizes an objective function rooted in vibration-based data sets. Two case studies of hyperbolic concrete arch dams were carefully designed using finite element simulation to demonstrate the effectiveness of the RBF-NN model, in conjunction with the Jaya algorithm. The testing results demonstrated that the proposed methods could exhibit significant computational time-savings, while effectively detecting damage in arch dam structures with complex nonlinearities. Furthermore, despite training data contaminated with a high level of noise, the RBF-NN and JA fusion remained the robustness, with high accuracy.

• Korean Chemical Engineering Research
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• v.47 no.1
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• pp.133-140
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• 2009

This paper presents the experimental study to analyze the pressure and production behavior using depressurization and thermal methods in order to evaluate the hydrate productivity in the 2-D multi-well, plate-type apparatus which has 80 md permeability and 30% hydrate saturation. Injecting methane gas through multi-well allowed to set up the highly saturated hydrate system and combining two different sorts of sands made possible to build up the low permeability system. In this system, both depressurization and electric stimulation methods were applied. When operating pressure was low, according to the depressurization experiments results, the gas recovery was high, however strong pulses which appeared at initial stage of production would damage the operation system. Moreover, cases that hydrate reformed have occurred by endothermic reaction. We have conducted experiments four and six times for the depressurization magnitudes of 140 psi and 320 psi, respectively, to analyze production behavior for the method more in detail. For the cases that the depressurization magnitude was set as 140 psi, the unstable period appears in the results, but stabilized soon. In the experiment results for 320 psi the discontinuous and intermittent behavior has been observed. Thermal stimulation experiments was conducted with depressurizing 80 psi which is the case that shows stable behavior and low recovery. In the results, the gas recovery was high and the energy efficiency was low for long stimulating time. The energy efficiency and gas recovery increased for the soaking time of 1 minute after 2 minute-preheating. In the cases of which the soaking time exceeds 1 minute, energy loss by long soaking time caused low gas recovery and poor energy efficiency.

• Journal of Oriental Neuropsychiatry
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• v.26 no.4
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• pp.337-348
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• 2015

Objectives: The purpose of this study was to review previous clinical studies on underlying mechanisms of sleep-related type-specific pathophysiological symptoms among the Sasang types. Methods and Procedure: We reviewed seven research databases from December 2003 to August 2015 with the keywords Sasang typology, constitution and sleep. The Sasang type-specific sleep-related symptoms were analyzed based on seven categories, including subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleep medications and daytime dysfunction. Results: Total of twelve studies were included in the analysis. The Tae-Yang type showed low subjective sleep quality, long sleep latency and frequent awakening, and the So-Yang type showed long sleep latency. The Tae-Eum type presented high subjective sleep quality, short sleep duration, frequent snore, toss and turn during the sleep, and insomnia and low frequency of dream. The So-Eum type showed long sleep latency in male and high frequency of dream. The Eum type combining Tae-Eum and So-Eum types had higher subjective sleep quality, longer sleep duration and higher frequency of dream than the Yang type combining Tae-Yang and So-Yang types.Conclusions This study reviewed type-specific sleep-related characteristics and discussed possible pathophysiological mechanisms involved. Differences in sleep characteristics among the Sasang types might stem from type-specific temperaments and require further study.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.21-27
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• 2013

In this paper, we propose a low-complexity Turbo coded BICM-ID (bit-interleaved coded modulation with iterative decoding) system. A Turbo code is a powerful error correcting code with a BER (bit error rate) performance very close to the Shannon limit. In order to increase spectral efficiency of the Turbo code, a coded modulation combining Turbo code with high order modulation is used. The BER performance of Turbo-BICM can be improved by Turbo-BICM-ID using iterative demodulation and decoding algorithm. However, compared with Turbo-BICM, the decoding complexity of Turbo-BICM-ID is increased by exchanging information between decoder and demodulator. To reduce the decoding complexity of Turbo-BICM-ID, we propose a low-complexity Turbo-BICM-ID system. When compared with conventional Turbo-BICM-ID, the proposed scheme not only show similar BER performance but also reduce the decoding complexity.

• Bulletin of the Korean Chemical Society
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• v.26 no.3
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• pp.440-446
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• 2005

A method is described for the determination of dibutyltin (DBT) in sediment by isotope dilution using liquid chromatography inductively-coupled plasma/mass spectrometry (LC-ICP/MS). To achieve the highest accuracy and precision, special attentions are paid in optimization and evaluation of overall processes of the analysis including extraction of analytes, characterization of the standards used for calibration and LC-ICP/MS conditions. An approach for characterization of natural abundance DBT standard has been developed by combining inductively-coupled plasma/optical emission spectrometry (ICP/OES) and LC-ICP/MS for the total Sn assay and the analysis of Sn species present as impurities, respectively. An excellent LC condition for separation of organotin species was found, which is suitable for simultaneous DBT and tributyltin (TBT) analysis as well as impurity analysis of DBT standards. Microwave extraction condition was also optimized for high efficiency while preventing species transformation. The present method determines the amount contents of DBT in sediments with expanded uncertainty of less than 5% and its result shows high degree of equivalence with reference values of an international inter-comparison and a certified reference material (CRM) within stated uncertainties.