• Journal of Navigation and Port Research
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• v.32 no.6
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• pp.459-464
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• 2008

In this paper, we present the model-based fuzzy controller for container cranes which effectively performs set-point tracking control of trolley and anti-swaying control under system parameter and disturbance changes. The first part of this paper focuses on the development of Takagi-Sugeno (T-S) fuzzy modeling in a nonlinear container crane system. Parameters of the membership functions are adjusted by a RCGA to have same dynamic characteristics with nonlinear model of a container crane. In the second part, we present a design methodology of the model-based fuzzy controller. Sub-controllers are designed using LQ control theory for each subsystem in fuzzy model and then the proposed controller is performed with the combination of these sub-controllers by fuzzy IF-THEN rules. In the results of simulation, the fuzzy model showed almost similar dynamic characteristics compared to the outputs of the nonlinear container crane model. Also, the model-based fuzzy controller showed not only the fast settling time for the change in parameter and disturbance, but also stable and robust control performances without any steady-state error.

• Journal of Yeungnam Medical Science
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• v.18 no.1
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• pp.30-38
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• 2001

Background: The purpose of this study was to evaluate the usefulness of diffusion-weighted magnetic resonance imaging for monitoring the response to radiation therapy in metastatic bone marrow of the spines. Materials and Methods: Twenty-one patients with metastatic bone marrow of the spines were examined with MRI. Diffusion-weighted and spin-echo MRI were performed in 10 patients before and after radiation therapy with or without systemic chemotherapy, and performed in 11 patients after radiation therapy alone. Follow up spin-echo and diffusion-weighted MRI were obtained at 1 to 6 months after radiation therapy according to patients' condition. The diffusion-weighted imaging sequence was based on reversed fast imaging with steady-state precession (PSIF). Signal intensity changes of the metastatic bone marrows before and after radiation therapy on conventional spin-echo sequence MRI and diffusion-weighted MRI were evaluated. Bone marrow contrast ratios and signal-to-noise ratios before and after radiation therapy of diffusion- weighted MRI were analyzed. Results: All metastatic bone marrow of the spinal bodies were hyperintense to normal bone marrow of the spinal bodies on pretreatment diffusion-weighted MRI and positive bone marrow contrast ratios(p<0.001), and hypointense to normal spinal bodies on posttreatment diffusion-weighted MRI and negative bone marrow contrast ratios(p<0.001). The signal to noise ratios after treatment decreased comparing with those of pretreatment. Decreased signal intensity of the metastatic bone marrows on diffusion-weighted MRI began to be observed at average more than one month after the initiation of the radiation therapy. Conclusion: These results suggest that diffusion-weighted MRI would be an excellent method for monitoring the response to therapy of metastatic bone marrow of the spinal bodies, however, must be investigated in a larger series of patients with longer follow up period.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1845-1852
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• 2008

The key elements of inter prediction are motion estimation(ME) and motion compensation(MC). Motion estimation is to find the optimum motion vectors, not only by using a distance criteria like the SAD, but also by taking into account the resulting number of 비트s in the 비트 stream. Motion compensation is compensate for movement of blocks of current frame. Inter-prediction Encoding is always the main bottleneck in high-quality streaming applications. Therefore, in real-time streaming applications, dedicated hardware for executing Inter-prediction is required. In this paper, we studied a motion estimator(ME) for H.264/AVC. The designed motion estimator is based on 2-D systolic array and it connects processing elements for fast SAD(Sum of Absolute Difference) calculation in parallel. By providing different path for the upper and lower lesion of each reference data and adjusting the input sequence, consecutive calculation for motion estimation is executed without pipeline stall. With data reuse technique, it reduces memory access, and there is no extra delay for finding optimal partitions and motion vectors. The motion estimator supports variable-block size and takes 328 cycles for macro-block calculation. The proposed architecture is local memory-free different from paper [6] using local memory. This motion estimation encoder can be applicable to real-time video processing.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.6
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• pp.127-138
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• 2019

The data response speed is a critical issue of cloud services because it directly related to the user experience. As such, the in-memory database is widely adopted in many cloud-based applications for achieving fast data response. However, the current implementation of the in-memory database is mostly based on the linked list-based hash table which cannot guarantee the constant data response time. Thus, cuckoo hashing was introduced as an alternative solution, however, there is a disadvantage that only half of the allocated memory can be used for storing data. Subsequently, bucketized cuckoo hashing (BCH) improved the performance of cuckoo hashing in terms of memory efficiency but still cannot overcome the limitation that the insert overhead. In this paper, we propose a data management solution called Wall Cuckoo which aims to improve not only the insert performance but also lookup performance of BCH. The key idea of Wall Cuckoo is that separates the data among a bucket according to the different hash function be used. By doing so, the searching range among the bucket is narrowed down, thereby the amount of slot accesses required for the data lookup can be reduced. At the same time, the insert performance will be improved because the insert is following up the operation of the lookup. According to analysis, the expected value of slot access required for our Wall Cuckoo is less than that of BCH. We conducted experiments to show that Wall Cuckoo outperforms the BCH and Sorting Cuckoo in terms of the amount of slot access in lookup and insert operations and in different load factor (i.e., 10%-95%).

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.28 no.4
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• pp.382-392
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• 2018

Objective: Allergic diseases such as asthma due to fungal exposure in houses have increased, and proper management is urgent. Mold can grow in the air, floor, walls, and other areas according to environmental conditions, and there are many limitations to the conventional methodology for examining fungal exposure. For this reason, the degree of fungal contamination is being evaluated by ERMI (Environmental Relative Moldiness Index), a quantitative analysis method proposed by the EPA. In this study, we compared ERMI values between water-damaged dwellings and non-damaged ones to evaluate the effectiveness of Korean ERMI values. We also explored the association of ERMI values with the level of airborne mold and characteristics of dwellings. Methods: Floor dust was collected after installing a Dustream collector on the suction port of a vacuum cleaner. The collected samples were filtered to remove only 5 mg of dust, and DNA was extracted using the FastDNA SPIN KIT protocol. Results: The ERMI values were found to be 19.6 (-6.9-58.8) for flooded houses, 7.5 (-29.2-48.3) for leaks/condensation, and 0.8 (-29.2-37.9) for non-damaged dwellings. The airborne concentration of mold for flooded, leakage or condensed, and non-damaged houses were $684CFU/m^3$, $566CFU/m^3$, and $378CFU/m^3$, respectively. The correlation between ERMI values and the levels of airborne mold was low (R = 0.038), but a weakly significant association of the ERMI values with the concentration of particulate matter ($PM_{10}$) was observed as well(R=0.231,P<0.05). Conclusions: Our findings show that the reference value using ERMI can be used to distinguish water-damaged and non-damaged dwellings. It is believed that ERMI values could be a promising tool for assessing long-term fungal exposure in dwellings.

• Explosives and Blasting
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• v.37 no.3
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• pp.13-24
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• 2019

This paper was prepared to investigate the behavior of fragments in underwater torpedo explosion beneath a frigate or surface ship by using an explicit finite element analysis. In this study, a fluid-structure interaction (FSI) methodology, called the multi-material arbitrary Lagrangian-Eulerian (MM-ALE) approach in LS-DYNA, was employed to obtain the responses of the torpedo fragments and frigate hull to the explosion. The Euler models for the analysis were comprised of air, water, and explosive, while the Lagrange models consisted of the fragment and the hull. The focus of this modeling was to examine whether a worst-case fragment could penetrate the frigate hull located close (4.5 m) to the exploding torpedo. The simulation was performed in two separate steps. At first, with the assumption that the expanding skin of the torpedo had been torn apart by consuming 30% of the explosive energy, the initial velocity of the worst-case fragment was sought based on a well-known experimental result concerning the fragment velocity in underwater bomb explosion. Then, the terminal velocity of the worst-case fragment that is expected to occur before the fragment hit the frigate hull was sought in the second step. Under the given conditions, the possible initial velocities of the worst-case fragment were found to be very fast (400 and 1000 m/s). But, the velocity difference between the fragment and the hull was merely 4 m/s at the instant of collision. This result was likely to be due to both the tremendous drag force exerted by the water and the non-failure condition given to the frigate hull. Anyway, at least under the given conditions, it is thought that the worst-case fragment seldom penetrate the frigate hull because there is no significant velocity difference between them.

• Journal of the Korean Society of Earth Science Education
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• v.14 no.3
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• pp.248-256
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• 2021

The purpose of this study is to investigate the perception of pre-service elementary teachers on the educational approach to metaverse. Questions about metaverse were asked to 71 pre-service elementary teachers who were taking the course 'Study of Textbooks in Elementary Science II'. The results of analyzing the contents of the questions are as follows. The results and conclusions were presented through numerical analysis and static analysis based on the responses to questions presented using the university's LMS system. First, the level of understanding of the metaverse of pre-service elementary teachers is very high. Pre-service elementary teachers, as the MZ generation, are already living in a very fast IT environment that can be the basis of the metaverse, so it would have been helpful to understand the metaverse. Second, the need for the metaverse of pre-service elementary teachers is very high. There was a tendency to think that the perception of pre-service elementary teachers is because the metaverse has many factors that can provide higher quality education beyond the current educational environment. Third, in the question of applicability exploration in the 'Earth and Space' domain of Pre-service elementary teachers, there have been few cases in which instructional design was planned based on instructional design principles. Based on these results, if the possibility of metaverse application is proposed in the 'Earth and Space' domain, educational contents using virtual space that can transcend time and space will be very necessary. Based on these results, suggestions are made as follows. First, educational content incorporating the metaverse technique based on instructional design should be developed and utilized. Second, financial support should be provided so that the metaverse can be implemented in the educational environment. Third, it is necessary to provide training opportunities for teachers (including Pre-service elementary teachers) to give lectures on metaverse.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.300-307
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• 2022

Time-resolved serial femtosecond crystallography (TR-SFX) is a powerful technique for determining temporal variations in the structural properties of biomacromolecules on ultra-short time scales without causing structure damage by employing femtosecond X-ray laser pulses generated by an X-ray free electron laser (XFEL). The mixing rate of reactants and biomolecule samples, as well as the hit rate between crystal samples and x-ray pulses, are critical factors determining TR-SFX performance, such as accurate image acquisition and efficient sample consumption. We here develop two distinct sample delivery systems that enable ultra-fast mixing and on-demand droplet injecting via pneumatic application with a square pulse signal. The first strategy relies on inertial mixing, which is caused by the high-speed collision and subsequent coalescence of droplets ejected through a double nozzle, while the second relies on on-demand pneumatic jetting embedded with a 3D-printed micromixer. First, the colliding behaviors of the droplets ejected through the double nozzle, as well as the inertial mixing within the coalesced droplets, are investigated experimentally and numerically. The mixing performance of the pneumatic jetting system with an integrated micromixer is then evaluated by using similar approaches. The sample delivery system devised in this work is very valuable for three-dimensional biomolecular structure analysis, which is critical for elucidating the mechanisms by which certain proteins cause disease, as well as searching for antibody drugs and new drug candidates.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.7
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• pp.233-240
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• 2022

Most of the recent AI researches has focused on developing AI models. However, recently, artificial intelligence research has gradually changed from model-centric to data-centric, and the importance of learning data is getting a lot of attention based on this trend. However, it takes a lot of time and effort because the preparation of learning data takes up a significant part of the entire process, and the generation of labeling data also differs depending on the purpose of development. Therefore, it is need to develop a tool with various labeling functions to solve the existing unmetneeds. In this paper, we describe a labeling system for creating precise and fast labeling data of medical images. To implement this, a semi-automatic method using Back Projection, Grabcut techniques and an automatic method predicted through a machine learning model were implemented. We not only showed the advantage of running time for the generation of labeling data of the proposed system, but also showed superiority through comparative evaluation of accuracy. In addition, by analyzing the image data set of about 1,000 patients, meaningful diagnostic indexes were presented for men and women in the diagnosis of sarcopenia.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1015-1023
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• 2022

The Entry-Descent-Landing process of a lander involves many environmental and technical challenges. To solve these problems, recently, terrestrial relative navigation (TRN) technology has been essential for landers. TRN is a technology for estimating the position and attitude of a lander by comparing Inertial Measurement Unit (IMU) data and image data collected from a descending lander with pre-built reference data. In this paper, we present a method for generating descent dataset and extracting landmarks, which are key elements for developing TRN technologies to be used on Mars. The proposed method generates IMU data of a descending lander using a simulated Mars landing trajectory and generates descent images from high-resolution ortho-map and digital elevation map through a ray tracing technique. Landmark extraction is performed by an area-based extraction method due to the low-textured surfaces on Mars. In addition, search area reduction is carried out to improve matching accuracy and speed. The performance evaluation result for the descent dataset generation method showed that the proposed method can generate images that satisfy the imaging geometry. The performance evaluation result for the landmark extraction method showed that the proposed method ensures several meters of positioning accuracy while ensuring processing speed as fast as the feature-based methods.