• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5491-5505
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• 2017

Use of the Gaussian inverse Wishart PHD (GIW-PHD) filter has demonstrated promise as an approach to track an unknown number of extended targets. However, the partitioning approaches used in the GIW-PHD filter, such as distance partition with sub-partition (DP-SP), prediction partition (PP) and expectation maximization partition (EMP), fails to provided accurate partition results when targets are spaced closely together and performing maneuvers. In order to improve the performance of a GIW-PHD filter, this paper presents a cooperation partitioning (CP) algorithm to solve the partitioning issue when targets are spaced closely together. In the GIW-PHD filter, the DP-SP is insensitive to target maneuvers but sensitive to the differences in target sizes, while EMP is the opposite. The proposed CP algorithm is a fusion approach of DP-SP and EMP, which employs EMP as a sub-partition approach after DP. Therefore, the CP algorithm will be sensitive to neither target maneuvers nor differences in target sizes. The simulation results show that the use of the proposed CP algorithm will improve the performance of the GIW-PHD filter when targets are spaced closely together.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.5
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• pp.139-146
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• 2022

With the recent development of the Internet of Things (IoT) and the convergence of vehicles and IT technologies, high-performance applications such as autonomous driving are emerging, and multi-access edge computing (MEC) has attracted lots of attentions as next-generation technologies. In order to provide service to these computation-intensive tasks in low latency, many methods have been proposed to partition tasks so that they can be performed through cooperation of multiple MEC servers(MECSs). Conventional methods related to task partitioning have proposed methods for partitioning tasks on vehicles as mobile devices and offloading them to multiple MECSs, and methods for offloading them from vehicles to MECSs and then partitioning and migrating them to other MECSs. In this paper, the performance of task partitioning methods using offloading and migration is compared and analyzed in terms of service delay, blocking rate and energy consumption according to the method of selecting partitioning targets and the number of partitioning. As the number of partitioning increases, the performance of the service delay improves, but the performance of the blocking rate and energy consumption decreases.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.3
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• pp.263-269
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• 2003

This paper focuses on lossy medical image compression methods for medical images that operate on three-dimensional(3D) irreversible integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm〔l-3〕to medical images, using a 3-D wavelet decomposition and a 3-D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. As the compression rate increases, the boundaries between adjacent coding units become increasingly visible. Unlike video, the volume image is examined under static condition, and must not exhibit such boundary artifacts. In order to eliminate them, we utilize overlapping at axial boundaries between adjacent coding units. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well. The improvement is visibly manifested as fewer ringing artifacts and noticeably better reconstruction of low contrast.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.6
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• pp.539-543
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• 2006

Lodging is classified as root lodging caused by the loss of supporting force in the root, bending caused by the deformation of the stem and breaking where the stem breaks down as loads exceeding critical elasticity were applied. This research excluded breaking which is not in a state of equilibrium and tried to partition the level of lodging using an algebraic model in root lodging and stem lodging, or bending. When a vertical load was applied, the deformation of the stem of rice plant showed the form of a quadratic equation. The trace of the panicle neck in the process of lodging was an ellipse-shape. When loading was pure root lodging, the trace of the panicle neck became a circle of which culm length is the radius. When it was a pure stem lodging, the trace of the panicle neck is an ellipse of which major axis is culm length and minor axis is 0.64* culm length. When both stem lodging and root lodging occurred in a natural setting, the partitioning of lodging can be calculated by a formula using eccentricity of an ellipse, S=e*100/0.768(S is the ratio of stem lodging in the whole lodging, e is eccentricity of the ellipse). This method is expected to be useful in simple lodging partitioning. We could also calculate the partitioning of stem lodging and root lodging as units of angles as an accuracy method, by using a straight line calculated by differentiating a quadratic equation of stem deformation at the origin of the coordinates. These two methods for dividing root and stem lodging showed different values. However, each of them showed almost same values with different lodging degree in one plant.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.6
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• pp.515-520
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• 2004

Core-based system-on-a-chip (SoC) designs present a number of test challenges. Two major problems that are becoming increasingly important are long application time during manufacturing test and high volume of test data. Highly efficient compression techniques have been proposed to reduce storage and application time for high volume data by exploiting the repetitive nature of test vectors. This paper proposes a new test data compression technique for SoC testing. In the proposed technique, compression is achieved by partitioning the test vector set and removing repeating segment. This process has $O(n^{-2})$ time complexity for compression with a simple hardware decoding circuitry. It is shown that the efficiency of the proposed compression technique is comparable with sophisticated software compression techniques with the advantage of easy and fast decoding.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1480-1483
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• 2009

In this paper, the hardware(HW) and software(SW) co-design methodology of H.264/AVC decoder using ARM-Excalibur is proposed. The SoC consists of embedded processor, memory, peripheral device and logic circuits. Recently, the co-design method which designs simultaneously HW and SW part is a new paradigm in SoC design. Because the optimization for partitioning the SoC system is very difficult, the verification must be performed earlier in design flow. We designed the H.264 and AVC Decoder using co-design method. It is shown that, for the proposed co-design method, the performance improvements can be obtained.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.378-384
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• 2013

In this paper, we propose the fuzzy neural networks based on fuzzy c-means clustering algorithm. Typically, the generation of fuzzy rules have the problem that the number of fuzzy rules exponentially increases when the dimension increases. To solve this problem, the fuzzy rules of the proposed networks are generated by partitioning the input space in the scatter form using FCM clustering algorithm. The premise parameters of the fuzzy rules are determined by membership matrix by means of FCM clustering algorithm. The consequence part of the rules is expressed in the form of polynomial functions and the learning of fuzzy neural networks is realized by adjusting connections of the neurons, and it follows a back-propagation algorithm. The proposed networks are evaluated through the application to nonlinear process.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5379-5388
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• 2012

In fuzzy modeling for nonlinear process, the fuzzy rules are typically formed by selection of the input variables, the number of space division and membership functions. The Generation of fuzzy rules for nonlinear processes have the problem that the number of fuzzy rules exponentially increases. To solve this problem, complex nonlinear process can be modeled by generating the fuzzy rules by means of fuzzy division of input space. Therefore, in this paper, rules of non-fuzzy inference systems are generated by partitioning the input space in the scatter form using HCM clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of HCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the consequence parameters of each rule are identified by the standard least-squares method. And lastly, we evaluate the performance and the nonlinear characteristics using the data widely used in nonlinear process. Through this experiment, we showed that high-dimensional nonlinear systems can be modeled by a very small number of rules.

• Journal of Communications and Networks
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• v.5 no.1
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• pp.43-54
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• 2003

Due to insufficient available bandwidth resources and the continuously growing demand for cellular communication services, the channel assignment problem has become increasingly important. To trace the optimal assignment, several heuristic strategies have been proposed. So far, most of them focus on the small-scale systems containing no more than 25 cells and they use an anachronistic cost model, which does not satisfy the requirements ity. Solving the small-scale channel assignment problems could not be applied into existing large scale cellular networks' practice. This article proposes a decomposition approach to solve the fixed channel assignment problem (FCAP) for large-scale cellular networks through partitioning the whole cellular network into several smaller sub-networks and then designing a sequential branch-and-bound algorithm that is made to solve the FCAP for them sequentially. The key issue of partition is to minimize the dependences of the sub-networks so that the proposed heuristics for solving smaller problems will suffer fewer constraints in searching for better assignments. The proposed algorithms perform well based on experimental results and they were applied to the Taiwan Cellular Cooperation (TCC) in ChungLi city to find better assignments for its network.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.110-117
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• 2017

In the construction of high-rise residential buildings in which the finishing works are done repetitively in each housing unit, the construction period and cost can be reduced, while maintaining the quality, if the work process is properly managed in order for the resources to be input continuously. Time management methods such as the Bar Chart, CPM and LOB are not appropriate, due to the difficulties involved in the diagraming of repetitive works and applying them to the project. The Tact method also has difficulties in maintaining a constant work flow and needs significant effort and cooperation from the subcontractors to allocate the resources consistently. Partitioning, base works for finishing, floor mortar plastering and the final finishing work are done sequentially in residential buildings projects, and there are many repetitive activities which differ in terms of the work method, work area and productivity. If these repetitive activities are synchronized or converged toward the last work area, the goal of process management can be achieved effectively. Therefore, a process planning method for the finishing works of residential building projects is proposed, which takes into consideration elements, such as the sequential relation between the activities in each housing unit and classification of repetitive works in terms of their management method, work area and production rate, for the continuous input of resources into the housing units.