• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.1021-1026
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• 2016

The graph-based SLAM (Simultaneous Localization and Mapping) approach has been gaining much attention in SLAM research recently thanks to its ability to provide better maps and full trajectory estimations when compared to the filtering-based SLAM approach. Even though graph-based SLAM requires batch processing causing it to be computationally heavy, recent advancements in optimization and computing power enable it to run fast enough to be used in real-time. However, data association problems still require large amount of computation when building a pose graph. For example, to find loop closures it is necessary to consider the whole history of the robot trajectory and sensor data within the confident range. As a pose graph grows, the number of candidates to be searched also grows. It makes searching the loop closures a bottleneck when solving the SLAM problem. Our approach to alleviate this bottleneck is to sample a limited number of pose nodes in which loop closures are searched. We propose a heuristic for sampling pose nodes that are most advantageous to closing loops by providing a way of ranking pose nodes in order of usefulness for closing loops.

• Journal of Integrative Natural Science
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• v.11 no.4
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• pp.167-183
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• 2018

Electroencephalogram (EEG) recording provides a new way to support human-machine communication. It gives us an opportunity to analyze the neuro-dynamics of human cognition. Machine learning is a powerful for the EEG classification. In addition, machine learning can compensate for high variability of EEG when analyzing data in real time. However, the optimal EEG electrode location must be prioritized in order to extract the most relevant features from brain wave data. In this paper, we propose an intelligent system model for the extraction of EEG data by training the optimal electrode location of EEG in a specific problem. The proposed system is basically a fuzzy system and uses a neural network structurally. The fuzzy clustering method is used to determine the optimal number of fuzzy rules using the features extracted from the EEG data. The parameters and weight values found in the process of determining the number of rules determined here must be tuned for optimization in the learning process. Genetic algorithms are used to obtain optimized parameters. We present useful results by using optimal rule numbers and non - symmetric membership function using EEG data for four movements with the right arm through various experiments.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.781-787
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• 2009

Training and process analysis in the construction industry has not taken full advantage of new technologies such as building information modeling(BIM). The purpose of this research is to develop a framework for the virtual interactive construction education system using three dimensional technologies. The modules will simulate the construction process for a facility from start to finish using information drawn from real projects in the built environment. These modules can be used as training tools for new employees where they attempt to optimize time and cost in a virtual environment given a limited number of equipment, time and employee options. They can also be used as a process analysis tool for new construction where a number of situational variables can change leading to exposure of potential risk. These modules would be particularly useful for repetitive construction where the initial project is analyzed for optimization and risk mitigation. This paper describes the framework and shows a residential construction example using a 900 square foot wood frame single family house designed for the United States.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.942-956
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• 2014

This paper proposes a real-time hand pose tracking method using a monocular RGB camera. Hand tracking has high ambiguity since a hand has a number of degrees of freedom. Thus, to reduce the ambiguity the proposed method adopts the step-by-step estimation scheme: a palm pose estimation, a finger yaw motion estimation, and a finger pitch motion estimation, which are performed in consecutive order. Assuming a hand to be a plane, the proposed method utilizes a planar hand model, which facilitates a hand model regeneration. The hand model regeneration modifies the hand model to fit a current user's hand, and improves robustness and accuracy of the tracking results. The proposed method can work in real-time and does not require GPU-based processing. Thus, it can be applied to various platforms including mobile devices such as Google Glass. The effectiveness and performance of the proposed method will be verified through various experiments.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.1
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• pp.61-67
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• 2000

Digital controllers found in many industrial real-time systems consist of a number of interacting periodic tasks. To sustain the required control quality, these tasks possess the maximum activation periods as performance constraints. An essential step in developing a real-time system is thus to assign each of these tasks a constant period such that the maximum activation requirements are met while the system utilization is minimized [1]. Given a task graph design allowing producer/consumer relationships among tasks [2], resource demands of tasks, and range constraints on periods, the period assignment problem falls into a class of nonlinear optimization problems. This paper proposes a ploynomial time approximation algorithm which produces a solution whose utilization does not exceed twice the optimal utilization. Our experimental analysis shows that the proposed algorithm finds solutions which are very close to the optimal ones in most cases of practical interest.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.249-256
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• 2022

Various studies are being actively conducted to show that the real-time visualization technology that combines BIM (Building Information Modeling) and AR (Augmented Reality) helps to increase construction management decision-making and processing efficiency. However, when large-capacity BIM data is projected into AR, there are various limitations such as data transmission and connection problems and the image cut-off issue. To improve the high efficiency of visualizing, a mesh optimization algorithm based on the k-nearest neighbors (KNN) classification framework to reconstruct BIM data is proposed in place of existing mesh optimization methods that are complicated and cannot adequately handle meshes with numerous boundaries of the 3D models. In the proposed algorithm, our target BIM model is optimized with the Unity C# code based on triangle centroid concepts and classified using the KNN. As a result, the algorithm can check the number of mesh vertices and triangles before and after optimization of the entire model and each structure. In addition, it is able to optimize the mesh vertices of the original model by approximately 56 % and the triangles by about 42 %. Moreover, compared to the original model, the optimized model shows no visual differences in the model elements and information, meaning that high-performance visualization can be expected when using AR devices.

• Analytical Science and Technology
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• v.28 no.1
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• pp.40-46
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• 2015

Hydrochar has been generated from food waste via hydrothermal carbonization (HTC) reaction. As a solid product of HTC reaction, hydrochar has a great potential as an adsorbent of pollutants from the various media. The surface area and pore volumes are very important parameters to be served as an adsorbent. It requires an expensive equipment and consumes time to measure those parameter. Therefore, titration methods including iodine and methylene blue adsorption were evaluated to be correlated with that of BET analysis. Even though the absolute values of the computed surface area and pore volumes were not able to be matched directly, the patterns of change were successfully correlated. Among the reaction conditions, the reaction time and temperature at $230^{\circ}C$ for 4 h was determined as an optimization condition, which confirmed by titration method and BET analysis. Titration method for surface area and pore volumes computed by combination of iodine and methylene blue adsorbing values would be a simple and fast way of determining the optimization condition for hydrochar as an adsorbent produced by HTC reaction.

• Journal of the Korea Computer Graphics Society
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• v.17 no.3
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• pp.43-50
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• 2011

We present a trade-off technique for fast but qualitative planar shape deformation using a layered mesh. We construct a layered mesh that is embedding a planar input shape; the upper-layer is denoted as a control mesh and the other lower-layer as a shape mesh that is defined by mean value coordinates relative to the control mesh. First, we try to preserve some shape properties including user constraints for the control mesh by means of a known existing nonlinear least square optimization technique, which produces deformed positions of the control mesh vertices. Then, we compute the deformed positions of the shape mesh vertices indirectly from the deformed control mesh by means of simple coordinates computation. The control mesh consists of a small number of vertices while the shape layer contains relatively a large number of vertices in order to embed the input shape as tightly as possible. Since the time-consuming optimization technique is applied only to the control mesh, the overall execution is extremely fast; however, the quality of deformation is sacrificed due to the sacrificed quality of the control mesh and its relativity to the shape mesh. In order to change the deformation behavior and consequently to compensate the quality sacrifice, we present a method to control the deformation stiffness by incorporating the orientation into the user constraints. According to our experiments, the proposed technique produces a planar shape deformation fast enough for real-time applications on limited embedded systems such as cell phones and tablet PCs.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.23-32
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• 2004

The query optimizer's important task while a query is invoked is to estimate the fraction of records in the databases that satisfy the given query condition. The query result size estimation in spatial databases, like relational databases, proceeds to partition the whole input into a small number of subsets called “buckets” and then estimate the fraction of the input in the buckets. The accuracy of estimation is determined by the difference between the real data counts and approximations in the buckets, and is dependent on how to partition the buckets. Existing techniques for spatial databases are equi-area and equi-count techniques, which are respectively analogous in relation databases to equi-height histogram that divides the input value range into buckets of equal size and equi-depth histogram that is equal to the number of records within each bucket. In this paper we propose a new partitioning technique that determines buckets according to the maximal difference of area which is defined as the product of data ranges End frequencies of input. In this new technique we consider both data values and frequencies of input data simultaneously, and thus achieve substantial improvements in accuracy over existing approaches. We present a detailed experimental study of the accuracy of query result size estimation comparing the proposed technique and the existing techniques using synthetic as well as real-life datasets. Experiments confirm that our proposed techniques offer better accuracy in query result size estimation than the existing techniques for space query size, bucket number, data number and data size.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12B
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• pp.1103-1111
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• 2008

Internet routers forward an incoming packet to an output port toward its final destination through IP address lookup. Since each incoming packet should be forwarded in wire-speed, it is essential to provide the high-speed search performance. In this paper, IP address lookup algorithms using binary search are studied. Most of the binary search algorithms do not provide a balanced search, and hence the required number of memory access is excessive so that the search performance is poor. On the other hand, binary-search-on-range algorithm provides high-speed search performance, but it requires a large amount of memory. This paper shows an optimized binary-search-on-range structure which reduces the memory requirement by deleting unnecessary entries and an entry field. By this optimization, it is shown that the binary-search-on-range can be performed in a routing table with a similar or lesser number of entries than the number of prefixes. Using real backbone routing data, the optimized structure is compared with the original binary-search-on-range algorithm in terms of search performance. The performance comparison with various binary search algorithms is also provided.