• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.55-65
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• 2006

Most of fast block motion estimation algorithms reported so far in literatures aim to reduce the computation in terms of the number of search points, thus do not fit well with multimedia processors due to their irregular data flow. For multimedia processors, proper reuse of data is more important than reducing number of absolute difference operations because the execution cycle performance strongly depends on the number of off-chip memory access. Therefore, in this paper, we propose a Hexagon-shape line search (HEXSLS) algorithm using line search pattern which can increase data reuse from on-chip local buffer, and check sub-sampling points in line search pattern to reduce unnecessary SAD operation. Our experimental results show that the prediction error (MAE) performance of the proposed HEXSLS is similar to that of the full search block matching algorithm (FSBMA), while compared with the hexagon-based search (HEXBS), the HEXSLS outperforms. Also the proposed HEXSLS requires much lesser off-chip memory access than the conventional fast motion estimation algorithm such as the hexagon-based search (HEXBS) and the predictive line search (PLS). As a result, the proposed HEXSLS algorithm requires smaller number of execution cycles on media processor.

• Culinary science and hospitality research
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• v.18 no.5
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• pp.63-79
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• 2012

The purpose of this study is to empirically determine the structural relationship between employee constructs such as internal service quality, employee satisfaction, and organization commitment and customer constructs such as perceived value, customer satisfaction, and loyalty to suggest an effective business strategy for restaurant business. To do this, the study consulted with the Korea Restaurant Association, the representative of Korean food service and got the intention of participating in the research from the Daegu branch. As a result, 51 restaurants registered in the Daegu branch who showed their intention to participate were selected as an initial sample. Also, other restaurants were introduced through snow-ball sampling method by the owners of restaurants who finished responding to the survey, and total 100 restaurants were examined. A survey was conducted to external customers who visited restaurants and internal customers working there. For final analysis, 741 questionnaires of internal customers and 970 questionnaires of external customers were used. The result of analysis showed that team-work & communication in internal service quality has a significant effect on employee satisfaction, employee satisfaction on organization commitment, and organization commitment on value perceived by customers. Also, perceived value has a significant effect on customer satisfaction and loyalty, and customer satisfaction on loyalty.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.87-107
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• 2016

Understanding market convergence has became essential for small and mid-size enterprises. Identifying convergence items among heterogeneous markets could lead to product innovation and successful market introduction. Previous researches have two limitations. First, traditional researches focusing on patent databases are suitable for detecting technology convergence, however, they have failed to recognize market demands. Second, most researches concentrate on identifying the relationship between existing products or technology. This study presents a platform to identify the opportunity of market convergence by using product databases from a global B2B marketplace. We also attempt to identify convergence opportunity in different industries by applying Structural Hole theory. This paper shows the mechanisms for market convergence: attributes extraction of products and services using text mining and association analysis among attributes, and network analysis based on structural hole. In order to discover market demand, we analyzed 240,002 e-catalog from January 2013 to July 2016.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1397-1406
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• 1996

In this paper, we propose a discrete model of conveyor systems, which is frequently used in flexible manufacturing systems to transfer work-in-process( WIP) between manipulators. In the case where the time required for transferring WIP's between manipulators are greater than that of manufacturing itself, as in many flexible assembly lines, the quantitative model of the transfer systems is needed to analyze the behavior and productivity of the whole manufacturing system. The proposed model is based upon the assumptions that the length of any unit conveyor component is integer multiple of the length of a pallet and hat the transferring speed of the conveyor is constant. Under these assumptions, the observation moments and the length of the conveyor can be quantized. Hence, the state of a conveyor can be represented by two kinds of Boolean variables: one representing the presence of a pallet on each quantize conveyor length and the other representing the mobility of this pallet. The whole conveyor system can be modeling as a network composed of branches and knots based on these two Boolean variables. The proposed modelling method was tested with various conveyor system configurations and showed that the model can be adopted successfully for the simulation of transfer systems and of the piloting of manufacturing processes.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.4
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• pp.355-362
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• 2012

Remaining useful life(RUL) prediction of a system is important in the prognostics field since it is directly linked with safety and maintenance scheduling. In the physics-based prognostics, accurately estimated model parameters can predict the remaining useful life exactly. It, however, is not a simple task to estimate the model parameters because most real system have multivariate model parameters, also they are correlated each other. This paper presents representative methods to estimate model parameters in the physics-based prognostics and discusses the difference between three methods; the particle filter method(PF), the overall Bayesian method(OBM), and the sequential Bayesian method(SBM). The three methods are based on the same theoretical background, the Bayesian estimation technique, but the methods are distinguished from each other in the sampling methods or uncertainty analysis process. Therefore, a simple physical model as an easy task and the Paris model for crack growth problem are used to discuss the difference between the three methods, and the performance of each method evaluated by using established prognostics metrics is compared.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.703-709
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• 2017

Korea Utility Helicopter(KUH) is a project to replace the aging helicopter presently being operated by the military with a domestic helicopter. The auxiliary power unit is a device that supplies emergency power to the system by an alternator installed when the main generator fails and the start motor converts the electrical energy of the battery into mechanical rotational energy to rotate the auxiliary power unit engine. With continuing power and operation, defects of the starting motor were found and improvements were carried out to solve it. In the failure mode analysis, the causes of possible defects were classified into 5 categories. Analysis of the 5 factors revealed that the main cause of defects is mechanical wear, which was found to be related to spring pressure. 250 tests were conducted through the theoretically determined pressure and regression analysis was performed with 4 sampling.The results showed that pressure was related to wear rate. In conclusion, early wear and breakage due to wear can be controlled through spring force and test showed the prediction of wear and the validity of the result were confirmed.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.871-884
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• 2021

The purpose of this study was to determine ways to increase efficiency in constructing and verifying artificial intelligence learning data on land cover using aerial and satellite images, and in applying the data to AI learning algorithms. To this end, multi-resolution datasets of 0.51 m and 10 m each for 8 categories of land cover were constructed using high-resolution aerial images and satellite images obtained from Sentinel-2 satellites. Furthermore, fine data (a total of 17,000 pieces) and coarse data (a total of 33,000 pieces) were simultaneously constructed to achieve the following two goals: precise detection of land cover changes and the establishment of large-scale learning datasets. To secure the accuracy of the learning data, the verification was performed in three steps, which included data refining, annotation, and sampling. The learning data that wasfinally verified was applied to the semantic segmentation algorithms U-Net and DeeplabV3+, and the results were analyzed. Based on the analysis, the average accuracy for land cover based on aerial imagery was 77.8% for U-Net and 76.3% for Deeplab V3+, while for land cover based on satellite imagery it was 91.4% for U-Net and 85.8% for Deeplab V3+. The artificial intelligence learning datasets on land cover constructed using high-resolution aerial and satellite images in this study can be used as reference data to help classify land cover and identify relevant changes. Therefore, it is expected that this study's findings can be used in the future in various fields of artificial intelligence studying land cover in constructing an artificial intelligence learning dataset on land cover of the whole of Korea.

• Journal of the Korean Geosynthetics Society
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• v.17 no.4
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• pp.225-238
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• 2018

In this paper, to investigate the influence of installation damage, a variety of full-scale field installation tests with 15 geosynthetics reinforcements and fill materials of various grain size distribution have been performed. The full-scale field installation test was conducted with reference to the FHWA (2009) guidelines. The tensile strength tests were performed by sampling up to 20 specimens randomly from the excavated geosynthetics reinforcements after compaction of fill material, and the degree of decrease in tensile strength of reinforcements due to compaction was analyzed based on the experiment results. It was found that the degree of tensile strength reduction of geosynthetics reinforcements due to the compaction of fill material is greatly influenced by the type of reinforcement and the maximum diameter of fill material. In addition, it was found that the strength reduction ratio of PET geogrid (PVC coating) with relatively small stiffness was greatest, and that the larger the maximum grain size of the fill material, the greater the strength reduction ratio. And also, a more reasonable evaluation method for the installation damage reduction factor of geosynthetics reinforcements is proposed based on the results of full-scale field installation tests in present study and the existing test results.

• Journal of IKEEE
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• v.22 no.4
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• pp.1012-1018
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• 2018

In this paper, CMOS SAR (Successive Approximation Register) A/D converter with 1.8V supply voltage is designed for IoT sensor processing. This paper proposes design of a 12-bit SAR A/D converter with two A / D converters in parallel to improve the sampling rate. A/D converter1 of the two A/D converters determines all the 12-bit bits, and another A/D converter2 uses the upper six bits of the other A/D converters to minimize power consumption and switching energy. Since the second A/D converter2 does not determine the upper 6 bits, the control circuits and SAR Logic are not needed and the area is minimized. In addition, the switching energy increases as the large capacitor capacity and the large voltage change in the C-DAC, and the second A/D converter does not determine the upper 6 bits, thereby reducing the switching energy. It is also possible to reduce the process variation in the C-DAC by proposed structure by the split capacitor capacity in the C-DAC equals the unit capacitor capacity. The proposed SAR A/D converter was designed using 0.18um CMOS process, and the supply voltage of 1.8V, the conversion speed of 10MS/s, and the Effective Number of Bit (ENOB) of 10.2 bits were measured. The area of core block is $600{\times}900um^2$, the total power consumption is $79.58{\mu}W$, and the FOM (Figure of Merit) is 6.716fJ / step.

• Tunnel and Underground Space
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• v.29 no.4
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• pp.230-242
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• 2019

While various automatic rock fracture survey methods have been researched, the evaluation of the accuracy of these methods raises issues due to the absence of a metric which fully expresses the similarity between automatic and manual fracture maps. Therefore, this paper proposes a geometry similarity metric which is especially designed to determine the overall similarity of fracture maps and to evaluate the accuracy of rock fracture survey methods by a single number. The proposed metric, Scanline Intersection Similarity (SIS), is derived by conducting a large number of scanline surveys upon two fracture maps using Python code. By comparing the frequency of intersections over a large number of scanlines, SIS is able to express the overall similarity between two fracture maps. The proposed metric was compared with Intersection Over Union (IoU) which is a widely used evaluation metric in computer vision. Results showed that IoU is inappropriate for evaluating the geometry similarity of fracture maps because it is overly sensitive to minor geometry differences of thin elongated objects. The proposed metric, on the other hand, reflected macro-geometry differences rather than micro-geometry differences, showing good agreement with human perception. The metric was further applied to evaluate the accuracy of a deep learning-based automatic fracture surveying method which resulted as 0.674 (SIS). However, the proposed metric is currently limited to 2D fracture maps and requires comparison with rock joint parameters such as RQD.