• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.182-186
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• 1997

This paper presents a mathematical approach to implementing distributed optimal power flow (OPF), wherein a regional decomposition technique is adopted to parallelize the OPF. Three mathematical decomposition coordination methods are introduced firs to implement the proposed distributed scheme: the Auxiliary Problem Principle (APP), the Predictor-Corrector Proximal Multiplier Method (PCPM), and the Alternating Direction Method (ADM). Then two alternative schemes for modeling distributed OPF are introduced; the Dummy Generator-Dummy Generator (DGDG) scheme and Dummy Generator-Dummy Load (DGDL) scheme. We present the mathematical analyses of the proposed approach, and demonstrate the approach on several test, systems, including IEEE Reliability Test Systems and parts of the ERCOT (Electric Reliability Council of Texas) system.

• Structural Engineering and Mechanics
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• v.75 no.2
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• pp.239-246
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• 2020

In this paper, a novel analytical method, Max-Min Approach (MMA), has been presented and applied to consider the nonlinear vibration of dry cask storage systems. The nonlinear governing equation of the structure has been developed using the shell theory. The MMA results are compared with numerical solutions derived by Runge-Kutta's Method (RKM). The results indicate a satisfying agreement between MMA and numerical solutions. Parametric studies have been conducted on the nonlinear frequency of dry casks. The phase-plan of the problem is also presented and discussed. The proposed approach can potentially ca be extended to highly nonlinear problems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1118-1133
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• 2017

Computer vision-based human activity recognition (HAR) has become very famous these days due to its applications in various fields such as smart home healthcare for elderly people. A video-based activity recognition system basically has many goals such as to react based on people's behavior that allows the systems to proactively assist them with their tasks. A novel approach is proposed in this work for depth video based human activity recognition using joint-based motion features of depth body shapes and Deep Belief Network (DBN). From depth video, different body parts of human activities are segmented first by means of a trained random forest. The motion features representing the magnitude and direction of each joint in next frame are extracted. Finally, the features are applied for training a DBN to be used for recognition later. The proposed HAR approach showed superior performance over conventional approaches on private and public datasets, indicating a prominent approach for practical applications in smartly controlled environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2173-2193
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• 2013

In order to reduce the distribution cost of sensor nodes, a mobile sensor deployment has been proposed. The mobile sensor deployment can be solved by finding the optimal layout and planning the movement of sensor nodes with minimum energy consumption. However, previous studies have not sufficiently addressed these issues with an efficient way. Therefore, we propose a new deployment approach satisfying these features, namely a tree-based approach. In the tree-based approach, we propose three matching schemes. These matching schemes match each sensor node to a vertex in a rake tree, which can be trivially transformed to the target layout. In our experiments, the tree-based approach successfully deploys the sensor nodes in the optimal layout and consumes less energy than previous works.

• Korean Journal of Computational Design and Engineering
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• v.6 no.4
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• pp.254-262
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• 2001

It is not possible to exchange parametric information of CAD (Computer Aided Design) models based on the current version of STEP (Standard leer the Exchange of Product model data). The design intent can be lost during the STEP transfer of CAD models. The ISO Parametrics Group has proposed the SMCH (Solid Model Construction History) schema in June 2000 that includes structures fur exchange of parametric information. This paper proposes the macro parametric approach that is intended to provide capabilities to transfer parametric information. In this approach, CAD models are exchanged in the form of macro files. The macro file contains user commands which are used in the modeling phase. To exchange CAD models using the macro parametric approach, modeling commands of commercial CAD systems are analyzed. Those commands are classified by the grouping method suggested by Bill Anderson. As a neutral file format, a standard modeling commands set has been defined. Mapping relations between the standard modeling commands set and the native modeling commands set of commercial CAD systems are defined.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10A
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• pp.980-986
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• 2008

Spatial multiuser access is investigated for the reverse link of multiuser multiple-input multiple-output (MIMO) systems. In particular, we consider two alternative a aches to spatial multiuser access that adopt the same detection algorithm at the base station: one is a closed-loop approach based on singular value decomposition (SVD) of the channel matrix, whereas the other is an open-loop approach based in space-time block coding (STBC). We develop multiuser detection algorithms for these two spatial multiuser access schemes based on the minimum mean square error (MMSE) criterion. Then, we compare the bit error rate (BER) performance of the two schemes and a single-user MIMO scheme. Interestingly, it is found that the STBC approach can provide much better BER performance than the SVD approach as well as than a single-user MIMO scheme.

• International Journal of CAD/CAM
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• v.2 no.1
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• pp.13-21
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• 2002

It is not possible to exchange parametric information of CAD models based on the current version of STEP. The design intent can be lost during the STEP transfer of CAD models. The Parametrics Group of ISO/TC184/SC4 has proposed the SMCH schema, which includes constructs for exchange of parametric information. This paper proposes a macro-parametric approach that is intended to provide capabilities to transfer parametric information including design intents. In this approach, CAD models are exchanged in the form of macro files. The macro file contains the history of user commands, which are used in the modeling phase. To exchange CAD models using the macro-parametric approach, the modeling commands of several commercial CAD systems are analyzed. Those commands are classified and a set of standard modeling commands has been defined. Mapping relations between the standard modeling commands and the native modeling commands of commercial CAD systems are defined. The scope of the current version is limited to parts modeling, not assemblies.

• Smart Structures and Systems
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• v.12 no.2
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• pp.157-179
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• 2013

We present an approach, based on the state dependent Riccati equation, for designing non-collocated seismic response control strategies for buildings accounting for physical constraints, with particular attention to force saturation. We consider both cases of active control using general actuators and semi-active control using magnetorheological dampers. The formulation includes multi control devices, acceleration feedback and time delay compensation. In the active case, the proposed approach is a generalization of the classic linear quadratic regulator, while, in the semi-active case, it represents a novel generalization of the well-established modified clipped optimal approach. As discussed in the paper, the main advantage of the proposed approach with respect to existing strategies is that it allows to naturally handle a broad class of non-linearities as well as different types of control constraints, not limited to force saturation but also including, for instance, displacement limitations. Numerical results on a typical building benchmark problem demonstrate that these additional features are achieved with essentially the same control effectiveness of existing saturation control strategies.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.6
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• pp.277-283
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• 2021

This paper addresses the problem of vision-based mask filter inspection for mask production systems. Machine learning-based approaches can be considered to solve the problem, but they may not be applicable to mask filter inspection if normal and anomaly mask filter data are not sufficient. In such cases, handcrafted image processing methods have to be considered to solve the problem. In this paper, we propose a hierarchical correlation-based approach that combines handcrafted image processing methods to detect anomaly mask filters. The proposed approach combines image rotation, cropping and resizing, edge detection of mask filter parts, average blurring, and correlation-based decision. The proposed approach was tested and analyzed with real mask filters. The results showed that the proposed approach was able to successfully detect anomalies in mask filters.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.214-222
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• 2021

Recently, the growth of e-commerce in Saudi Arabia has been exponential, bringing new remarkable challenges. A naive approach for product matching and categorization is needed to help consumers choose the right store to purchase a product. This paper presents a machine learning approach for product matching that combines deep learning techniques with standard artificial neural networks (ANNs). Existing methods focused on product matching, whereas our model compares products based on unstructured descriptions. We evaluated our electronics dataset model from three business-to-consumer (B2C) online stores by putting the match products collectively in one dataset. The performance evaluation based on k-mean classifier prediction from three real-world online stores demonstrates that the proposed algorithm outperforms the benchmarked approach by 80% on average F1-measure.