• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.326-354
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• 2014

In this paper, a new green clustering algorithm is proposed to be as a first approach in the framework of an energy efficient strategy for centralized enterprise high-density WLANs. Traditionally, in order to maintain the network coverage, all the APs within the WLAN have to be powered-on. Nevertheless, the new algorithm can power-off a large proportion of APs while the coverage is maintained as its always-on counterpart. The two main components of the new approach are the faster procedure based on K-means and the more accurate procedure based on Evolutionary Algorithm (EA), respectively. The two procedures are processes in parallel for different designed requirements and there is information interaction in between. In order to implement the new algorithm, EA is applied to handle the optimization of multiple objectives. Moreover, we adapt the method for selection and recombination, and then introduce a new operator for mutation. This paper also presents simulations in scenarios modeled with ray-tracing method and FDTD technique, and the results show that about 67% to 90% of energy consumption can be saved while it is able to maintain the original network coverage during periods when few users are online or the traffic load is low.

• ETRI Journal
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• v.37 no.2
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• pp.317-327
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• 2015

A reliable analysis of consumer preference from a large amount of purchase data acquired in real time and an accurate customer characterization technique are essential for successful direct marketing campaigns. In this study, an optimal segmentation of post office customers in Korea is performed using a subspace projection-based clustering method to generate an accurate customer characterization from a high-dimensional census dataset. Moreover, a traditional temporal mining method is extended to an algorithm using the MapReduce framework for a consumer preference analysis. The experimental results show that it is possible to use parallel mining through a MapReduce-based algorithm and that the execution time of the algorithm is faster than that of a traditional method.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.45-48
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• 2003

We can easily buy network system for high performance micro-processor, progress computer architecture is caused of high bandwidth and low delay time. Coupling PC-based commodity technology with distributed computing methodologies provides an important advance in the development of single-user dedicated systems. Lately Network is joined PC or workstation by computers of high performance and low cost. Than it make intensive that Cluster system is resembled supercomputer. Unix, Linux, BSD, NT(Windows series) can use Cluster system OS(operating system). I'm chosen linux gain low cost, high performance and open technical documentation. This paper is benchmark performance of Beowulf clustering by UltraSPARC-1K(64bit-RISC processor). Benchmark tools use MPI(Message Passing Interface) and NetPIPE. Beowulf is a class of experimental parallel workstations developed to evaluate and characterize the design space of this new operating point in price-performance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.7 s.238
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• pp.1013-1021
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• 2005

In this paper, we developed an automatic design optimization system for parametric shape optimization of cooling passages inside axial turbine blades. A parallel three-dimensional thermoelasticity finite element analysis code from an open source system was used to perform automatic thermal and stress analysis of different blade configuration. The developed code was connected to an evolutionary optimizer and built in a design optimization system. Using the optimization system, 279 feasible and optimal solutions were searched. It is provided not only one best solution of the searched solutions, but also information of variation structure and correlation of the 279 solutions in function, variable, and real design spaces. To explore design information, it is proposed a new interpretation approach based on evolutionary clustering and principal component analysis. The interpretation approach might be applicable to the increasing demands in the general area of design optimization.

• ETRI Journal
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• v.40 no.6
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• pp.788-793
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• 2018

3D reconstruction of urban architecture, land, and roads is an important part of building a "digital city." Unmanned aerial vehicles (UAVs) are gradually replacing other platforms, such as satellites and aircraft, in geographical image collection; the reason for this is not only lower cost and higher efficiency, but also higher data accuracy and a larger amount of obtained information. Recent 3D reconstruction algorithms have a high degree of automation, but their computation time is long and the reconstruction models may have many voids. This paper decomposes the object into multiple regional parallel reconstructions using the clustering principle, to reduce the computation time and improve the model quality. It is proposed to detect the planar area under low resolution, and then reduce the number of point clouds in the complex area.

• Journal of Digital Contents Society
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• v.14 no.1
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• pp.65-72
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• 2013

Current and future parallel computing model has been suggested for running and solving large-scale application problems such as climate, bio, cryptology, and astronomy, etc. Parallel computing is a form of computation in which many calculations are carried out simultaneously. And we are able to shorten the execution time of the program, as well as can extend the scale of the problem that can be solved. In this paper, we perform the actual cryptographic algorithms through parallel processing and evaluate its efficiency. Length of the key, which is stable criterion of cryptographic algorithm, judged according to the amount of complete enumeration computation. So we present a detailed procedure of DES key search cryptographic algorithms for executing of enumeration computation in parallel processing environment. And then, we did the simulation through applying to clustering system. As a result, we can measure the safety and solidity of cryptographic algorithm.

• Food Science of Animal Resources
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• v.42 no.5
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• pp.874-888
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• 2022

This study aimed to compare the similarities, physicochemical properties, and muscle fiber characteristics of porcine skeletal muscles. Fourteen types of muscles were collected from nine pig carcasses at 24 h post-mortem and classified by muscle architecture into two main groups, namely parallel and pennate. The muscles were further differentiated into three subtypes per group. These included fan-shaped, fusiform, and strap for the parallel group, and unipennate, bipennate, and multipennate for the pennate group. Parallel-fibered muscles, which were composed of larger I, IIA, IIX, and IIXB fibers and a lower density of IIA fibers, showed higher redness and yellowness values than pennate-fibered muscles (p<0.05). However, the relative fiber area was not significantly different between the parallel and pennate groups (p>0.05). In the subtypes of parallel architecture, the strap group showed lower moisture content and higher redness values than the other subtypes and had considerably higher amounts of oxidative fibers (I and IIA; 72.3%) than the fan-shaped and fusiform groups (p<0.05). In the pennate group, unipennate showed comparatively lower moisture content and higher lightness than other pennate subtypes and was composed of smaller I, IIA, and IIX fibers than the bipennate and multipennate groups (p<0.05). Finally, a different trend of muscle clustering by hierarchical cluster analysis was found between physicochemical properties and muscle fiber characteristics. These results suggest that the physicochemical properties and muscle fiber characteristics of porcine skeletal muscles are not significantly dependent on morphological properties but are rather related to the intrinsic properties of the individual muscles.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.430-438
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• 2004

Among the optimization method, GA (genetic algorithm) is a very powerful searching method enough to compete with design sensitivity analysis method. GA is very easy to apply, since it dose not require any design sensitivity information. However, GA has been computationally not efficient due to huge repetitive computation. In this study, parallel computation is adopted to Improve computational efficiency, Paralleled GA is introduced on a clustered LINUX based personal computer system.

• The Journal of the Korea Contents Association
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• v.2 no.2
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• pp.103-111
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• 2002

In parallel application programs with a localized communication, even if the MINs have lour diameters, overall system performance degrades when compared to the hypercube and tree structure. The reason is that it is impossible for MINs to provide some mechanisms for clustering to exploit the locality of reference. However proposed MIN can be constructed suitable for localized communication by providing the shortcut path and multiple paths inside the processor-memory duster which has frequent data communications. Therefore proposed MIN achieves enhanced performance in parallel application program with a localized communication.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.252-257
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• 2001

With the help of newly arrived technology such as PC clustering, molecular dynamics (MD) seems to be promising for large-scale materials simulations. A cost-effective cluster is set up using commodity PCs connected over Ethernet with fast switching devices and free software Linux. Executing MD simulations in the parallel sessions makes it possible to carry out large-scale materials simulations at acceptable computation time and costs. In this study, the MD computer code for fracture simulation is modified to comply with MPI (Message Passing Interface) specification, and runs on the PC cluster in parallel mode flawlessly. It is noted that PC clusters can provide a rather inexpensive high-performance computing environment comparing to supercomputers, if properly arranged.