• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.316-324
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• 2005

e-Learning has been mushrooming with wide range of teaming groups from pedagogy to andragogy As e-teaming opportunities increase, many people raise question about whether e-teaming show positive teaming effects. The related research emphasized that e-learning would be a failure in terms of understanding of e-Learners and activating intuitive teaming activities from learner's long-term memory span. The e-teaming strategies based on the traditional classroom and resulted boring and ineffective teaming outcomes, should be changed to provide authentic and effective teaming results. This paper analyzed that how learners have received e-Learning for the last few years from the research and explained what could be the failing aspects in e-Learning. To be successful, e-loaming should consider the e-learner's individualized teaming style and thinking patterns. When considering of various e-Learning components, the quality of e-teaming should not be focused on any specific single factor, but develop every individual factor to be integrated into high level of quality. In conclusion, this paper suggest that it is needed new understandings of e-Loaming and e-Learner. Also the e-Learning strategies should be examined throughly whether they are on the side of learners and realized how they learn from e-Learning. Finally, we should add enormous imagination into e-loaming for next generation because new generation's teaming patterns significantly differ from their parent's generation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.8-15
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• 2020

A forecasting method using deep learning does not have consistent results due to the differences in the characteristics of the dataset, even though they have the same forecasting models and parameters. For example, the forecasting model X optimized with dataset A would not produce the optimized result with another dataset B. The forecasting model with the characteristics of the dataset needs to be optimized to increase the accuracy of the forecasting model. Therefore, this paper proposes novel optimization steps for outlier removal, dataset classification, and a CNN-LSTM-based hyperparameter tuning process to forecast the daily power usage of a university campus based on the hourly interval. The proposing model produces high forecasting accuracy with a 2% of MAPE with a single power input variable. The proposing model can be used in EMS to suggest improved strategies to users and consequently to improve the power efficiency.

• Journal of Navigation and Port Research
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• v.29 no.1 s.97
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• pp.91-96
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• 2005

The National Marine Electronics Association(NMEA) is nonprofit-making cooperation composed with manufacturers, distributors, wholesalers and educational institutions. We use the basic port of equipment in order to process the signal from NMEA signal using equipment. When we don't have enough one, we use the multi-port for processing. However, we need to have module development simulation which could multiplex and provide NMEA related signal that we could solve the problems in multi-port application and exclusive equipment generation for a number of signal. For now, we don't have any case or product using NMEA multiplexer so that we import expensive foreign equipment or embody NMEA signal transmission program like software, using multi-port. These have problems since we have to pay lots ci money and build separate processing part for every application programs. Besides, every equipment generating NMEA signal are from different manufactures and have different platform so that it could cause double waste and loss of recourse. For making up for it, I suggest the NMEA multiplexer embodiment, which could independently move by reliable process and high performance single hardware module, improve the memory efficiency of module by designing the optimized Queue, and keep having reliability for realtime communication among the equipment such as main input sensor equipment Gyrocompass, Echo-sound, and GPS.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.363-363
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• 2014

Ruthenium (Ru) has attractive material properties due to its promising characteristics such as a low resistivity ($7.1{\mu}{\Omega}{\cdot}cm$ in the bulk), a high work function of 4.7 eV, and feasibility for the dry etch process. These properties make Ru films appropriate for various applications in the state-of-art semiconductor device technologies. Thus, it has been widely investigated as an electrode for capacitor in the dynamic random access memory (DRAM), a metal gate for metal-oxide semiconductor field effect transistor (MOSFET), and a seed layer for Cu metallization. Due to the continuous shrinkage of microelectronic devices, better deposition processes for Ru thin films are critically required with excellent step coverages in high aspect ratio (AR) structures. In these respects, atomic layer deposition (ALD) is a viable solution for preparing Ru thin films because it enables atomic-scale control of the film thickness with excellent conformality. A recent investigation reported that the nucleation of ALD-Ru film was enhanced considerably by using a zero-valent metallorganic precursor, compared to the utilization of precursors with higher metal valences. In this study, we will present our research results on the synthesis and characterization of novel ruthenium complexes. The ruthenium compounds were easy synthesized by the reaction of ruthenium halide with appropriate organic ligands in protic solvent, and characterized by NMR, elemental analysis and thermogravimetric analysis. The molecular structures of the complexes were studied by single crystal diffraction. ALD of Ru film was demonstrated using the new Ru metallorganic precursor and O2 as the Ru source and reactant, respectively, at the deposition temperatures of $300-350^{\circ}C$. Self-limited reaction behavior was observed as increasing Ru precursor and O2 pulse time, suggesting that newly developed Ru precursor is applicable for ALD process. Detailed discussions on the chemical and structural properties of Ru thin films as well as its growth behavior using new Ru precursor will be also presented.

• Journal of KIISE
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• v.43 no.10
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• pp.1115-1123
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• 2016

Assumption-based truth maintenance system (ATMS) is a tool that maintains the reasoning process of inference engine. It also supports non-monotonic reasoning based on dependency-directed backtracking. Bookkeeping all the reasoning processes allows it to quickly check and retract beliefs and efficiently provide solutions for problems with large search space. However, the amount of data has been exponentially grown recently, making it impossible to use a single machine for solving large-scale problems. The maintaining process for solving such problems can lead to high computation cost due to large memory overhead. To overcome this drawback, this paper presents an approach towards incrementally maintaining the reasoning process of inference engine on cluster using Spark. It maintains data dependencies such as assumption, label, environment and justification on a cluster of machines in parallel and efficiently updates changes in a large amount of inferred datasets. We deployed the proposed ATMS on a cluster with 5 machines, conducted OWL/RDFS reasoning over University benchmark data (LUBM) and evaluated our system in terms of its performance and functionalities such as assertion, explanation and retraction. In our experiments, the proposed system performed the operations in a reasonably short period of time for over 80GB inferred LUBM2000 dataset.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.9
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• pp.691-698
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• 2006

TCP/IP Offload Engine (TOE) is a technology that processes TCP/IP on a network adapter instead of a host CPU to reduce protocol processing overhead from the host CPU. There have been some approaches to implementing TOE: software TOE based on an embedded processor; hardware TOE based on ASIC implementation; and hybrid TOE in which software and hardware functions are combined. In this paper, we designed software modules and hardware modules for a hybrid TOE on an FPGA that had two processor cores. Software modules are based on the embedded Linux. Hardware modules are for data transmission (TX) and reception (RX). One core controls the TX path and the other controls the RX path of the Linux. This TX/RX path separation mechanism can reduce task switching overheads between processes and overcome poor performance of single embedded processor. Hardware modules deal with creating headers for outgoing packets, processing headers of incoming packets, and fetching or storing data from or to the host memory by DMA. These can make it possible to improve the performance of data transmission and reception. We proved performance of the TOE with separated transmission and reception paths by performing experiments with a TOE network adapter that was equipped with the FPGA having processor cores.

• Journal of Sensor Science and Technology
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• v.8 no.4
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• pp.341-346
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• 1999

In general cases, compared with glass electrode, FET type electrolyte sensors have many advantages. But the drift, memory effect and the poor reproducibility of the FET type electrolyte sensor cause the decrease of the reliability in the measurement system. To improve the reliability, an ion-measuring system using FET type electrolyte sensor array with 8 sensors has been developed. Developed system employed the electronic switchs to connect a signal detecting circuit with 8 sensor array and the system can measure ion concentration of 4 different type electrolyte($H^+$, $Na^+$, $K^+$, $Ca^{2+}$). The signal processing algorithm with insertion sorting method was adopted to enhance the reliability. We measured 3 different ion($H^+$, $Na^+$, $K^+$) to evaluate the performance of developed system. The results show that the designed signal processing algorithm can reduce the error range in comparison with a simple arithmetic mean and the developed system has a good reliability over the previous single channel sensor system.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.156-162
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• 2007

The parallel beam SPECT system acquires projection data by using collimators in conjunction with photon detectors. The projection data of the parallel beam SPECT system is, however, blurred by the point response function of the collimator that is used to define the range of directions where photons can be detected. By increasing the number of parallel holes per unit area in collimator, one can reduce such blurring effect. This approach also, however, has the blurring problem if the distance between the object and the collimator becomes large. In this paper we consider correction methods for artifacts caused by non-circular orbit of parallel beam SPECT with many parallel holes per detector cell. To do so, we model the relationship between the object and its projection data as a linear system, and propose an iterative reconstruction method including artifacts correction. We compute the projector and the backprojector, which are required in iterative method, as a sum of convolutions with distance-dependent point response functions instead of matrix form, where those functions are analytically computed from a single function. By doing so, we dramatically reduce the computation time and memory required for the generation of the projector and the backprojector. We conducted several simulation studies to compare the performance of the proposed method with that of conventional Fourier method. The result shows that the proposed method outperforms Fourier methods objectively and subjectively.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.8
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• pp.56-63
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• 2010

This work proposes a 12b 100MS/s 0.13um CMOS pipeline ADC for battery-powered mobile video applications such as DVB-Handheld (DVB-H), DVB-Terrestrial (DVB-T), Satellite DMB (SDMB), and Terrestrial DMB (TDMB) requiring high resolution, low power, and small size at high speed. The proposed ADC employs a three-step pipeline architecture to optimize power consumption and chip area at the target resolution and sampling rate. A single shared and switched op-amp for two MDACs removes a memory effect and a switching time delay, resulting in a fast signal settling. A two-step reference selection scheme for the last-stage 6b FLASH ADC reduces power consumption and chip area by 50%. The prototype ADC in a 0.13um 1P7M CMOS technology demonstrates a measured DNL and INL within 0.40LSB and 1.79LSB, respectively. The ADC shows a maximum SNDR of 60.0dB and a maximum SFDR of 72.4dB at 100MS/s, respectively. The ADC with an active die area of 0.92 $mm^2$ consumes 24mW at 1.0V and 100MS/s. The FOM, power/($f_s{\times}2^{ENOB}$), of 0.29pJ/conv. is the lowest of ever reported 12b 100MS/s ADCs.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1593-1601
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• 2017

In a big data platform, association rule mining applications could bring some benefits. For instance, in a agricultural big data platform, the association rule mining application could recommend specific products for farmers to grow, which could increase income. The key process of the association rule mining is the frequent itemsets mining, which finds sets of products accompanying together frequently. Former researches about this issue, e.g. Apriori, are not satisfying enough because huge possible sets can cause memory to be overloaded. In order to deal with it, SON algorithm has been proposed, which divides the considered set into many smaller ones and handles them sequently. But in a single machine, SON algorithm cause heavy time consuming. In this paper, we present a method to find association rules in our Hadoop based big data platform, by parallelling SON algorithm. The entire process of association rule mining including pre-processing, SON algorithm based frequent itemset mining, and association rule finding is implemented on Hadoop based big data platform. Through the experiment with real dataset, it is conformed that the proposed method outperforms a brute force method.