• Wind and Structures
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• v.12 no.1
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• pp.1-19
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• 2009

In this paper, the airflow around an ideal thin plate (hereafter referred to as ITP) with various ratios of central slot is simulated by using the finite-difference-method (FDM)-based Arbitrary-Lagrangian-Eulerian descriptions for the rigid oscillating body. The numerical procedure employs the second-order projection scheme to decouple the governing equations, and the multigrid algorithm with three levels to improve the computational efficiency in evaluating of the pressure equation. The present CFD method is validated through comparing the computed flutter derivatives of the ITP without slot to Theodorsen analytical solutions. Then, the unsteady aerodynamics of the ITP with and without central slot is investigated. It is found that even a smaller ratio of central slot of the ITP has notable effects on pressure distributions of the downstream section, and the pressure distributions on the downstream section will further be significantly affected by the slot ratio and the reduced wind speeds. Continuous increase of $A_2^*$ with the increase of central slot may be the key feature of the slotted ITP. Finally, flutter analyses based on the flutter derivatives of the slotted ITP are performed, and moreover, flutter instabilities of a scaled sectional model of a twin-deck bridge with various ratios of deck slot are investigated. The results confirm that the central slot is effective to improve bridge flutter stabilities, and that the flutter critical wind speeds increase with the increase of slot ratio.

• Journal of Power Electronics
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• v.12 no.4
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• pp.664-676
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• 2012

A phase shift algorithm based on the closed-loop control of dc-link voltage implemented on a series active voltage quality regulator (AVQR) is proposed in this paper. To avoid pumping-up the dc-link voltage, a general phase shift compensation strategy is applied. The relationships among the operation variables are discussed in detail, which is very important for guiding the design of both the main circuit and the control system. Then on the basis of an investigation of the dc-link voltage pumping-up from viewpoint of the active power flow, a novel phase shift control method based on the closed-loop of the dc-link voltage is proposed. This method can adjust the phase of the output voltage gradually and automatically according to the dc-link voltage variation without introducing a phase jump. The effectiveness of the proposed strategy is verified through simulations of a single-phase 5kVA prototype and laboratory experiments on both a single-phase 5kVA and a three-phase 15kVA prototype.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.1984-2002
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• 2020

With the appearance of wireless spectrum crisis in traditional cellular network, device-to-device (D2D) communication has been regarded as a promising solution to ease heavy traffic burden by enabling precise content delivery among mobile users. However, due to the channel sharing, the interference between D2D and cellular users can affect the transmission rate and narrow the throughput in the network. In this paper, we firstly present a weighted interference minimization cluster formation model involving both social attribute and physical closeness. The weighted-interference, which is evaluated under the susceptible-infected(SI) model, is utilized to gather user in social and physical proximity. Then, we address the cluster formation problem via spectrum clustering with iterative operation. Finally, we propose the stable matching theory algorithm in order to maximize rate oriented to accomplish the one-to-one resource allocation. Numerical results show that our proposed scheme acquires quite well clustering effect and increases the accumulative transmission rate compared with the other two advanced schemes.

• Smart Structures and Systems
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• v.26 no.1
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• pp.49-61
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• 2020

This paper proposes a novel high performance vibration control device, multiple tuned mass dampers-inerters (MTMDI), to suppress the oscillatory motions of structures. The MTMDI, similar to the MTMD, involves multiple tuned mass damper-inerter (TMDI) units. In order to reveal the basic performance of the MTMDI, it is installed on a single degree-of-freedom (SDOF) structure excited by the ground acceleration, and the dynamic magnification factors (DMF) of the structure-MTMDI system are formulated. The optimization criterion is determined as the minimization of maximum values of the relative displacement's DMF for the controlled structure. Based on the particle swarm optimization (PSO) algorithm to tune the optimum parameters of the MTMDI, its performance has been investigated and evaluated in terms of control effectiveness, strokes, stiffness and damping coefficient, inerter element force, and robustness in frequency domain. Meanwhile, further comparison between the MTMDI with MTMD has been conducted. Numerical results clearly demonstrate the MTMDI outperforms the MTMD in control effectiveness and strokes of mass blocks. Additionally, in the aspects of frequency perturbations on both earthquake excitations and structures, the robustness of the MTMDI is also better than the MTMD.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.109-134
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• 2018

Collaborative Filtering (CF) is widely used in recommendation field, which can be divided into rating-based CF and learning-to-rank based CF. Although many methods have been proposed based on these two kinds of CF, there still be room for improvement. Firstly, the data sparsity problem still remains a big challenge for CF algorithms. Secondly, the malicious rating given by some illegal users may affect the recommendation accuracy. Existing CF algorithms seldom took both of the two observations into consideration. In this paper, we propose a recommendation method based on listwise learning-to-rank by incorporating users' social information. By taking both ratings and order of items into consideration, the Plackett-Luce model is presented to find more accurate similar users. In order to alleviate the data sparsity problem, the improved matrix factorization model by integrating the influence of similar users is proposed to predict the rating. On the basis of exploring the trust relationship between users according to their social information, a listwise learning-to-rank algorithm is proposed to learn an optimal ranking model, which can output the recommendation list more consistent with the user preference. Comprehensive experiments conducted on two public real-world datasets show that our approach not only achieves high recommendation accuracy in relatively short runtime, but also is able to reduce the impact of malicious ratings.

• Structural Monitoring and Maintenance
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• v.4 no.4
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• pp.331-350
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• 2017

Based on the alternative stabilization diagram by varying the time lag parameter in the stochastic subspace identification analysis, this study aims to investigate the measurements from several cases of civil structures for extending the applicability of a recently noticed criterion to ensure stable identification results. Such a criterion demands the time lag parameter to be no less than a critical threshold determined by the ratio of the sampling rate to the fundamental system frequency and is firstly validated for its applications with single measurements from stay cables, bridge decks, and buildings. As for multiple measurements, it is found that the predicted threshold works well for the cases of stay cables and buildings, but makes an evident overestimation for the case of bridge decks. This discrepancy is further explained by the fact that the deck vibrations are induced by multiple excitations independently coming from the passing traffic. The cable vibration signals covering the sensor locations close to both the deck and pylon ends of a cable-stayed bridge provide convincing evidences to testify this important discovery.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.71-73
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• 2000

Recently researches have been made on the client-side Web GIS, which can lessen the load of a server and provide users with intheractive geographic information. Howwever, the initial delay is the main drawback because of a high volume of geographic data and becausr the server does not associate spatial features with the map scale. Even when a complex spatial object is too small to be distinguished from a point by the naked eyes, it's complete data will be transmitted. This paper proposes a new effcient schema to reduce the response time and increase transmission effciency. Briefly speaking, "Transmit what can be seen" is the main idea. By exploiting the generalization algorithm, the proposed method allows the server to extract readable features from objects according to the display scale. Meanwhile, increasingly detailed map will be cached on the client. Therefore this method will contribute to the transmission efficiency of Web GISs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.288-301
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• 2017

In this paper, we propose an optimized algorithm for texture classification by computing a completed modeling of the local binary pattern (CLBP) instead of the traditional LBP of a scalable block size in an image. First, we show that the CLBP descriptor is a better representative than LBP by extracting more information from an image. Second, the CLBP features of scalable block size of an image has an adaptive capability in representing both gross and detailed features of an image and thus it is suitable for image texture classification. This paper successfully implements a machine learning scheme by applying the CLBP features of a scalable size to the Support Vector Machine (SVM) classifier. The proposed scheme has been evaluated on Outex and CUReT databases, and the evaluation result shows that the proposed approach achieves an improved recognition rate compared to the previous research results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.466-483
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• 2017

Zen Cart is an open-source online store management system. It is used all over the world because of its stability and safety. Today, Zen Cart's session security mechanism is mainly used to verify user agents and check IP addresses. However, the security in verifying the user agent is lower and checking the IP address can affect the user's experience. This paper, which is based on the idea of session protection as proposed by Ben Adida, takes advantage of the HTML5's sessionStorage property to store the shared keys that are used in HMAC-SHA256 encryption. Moreover, the request path, current timestamp, and parameter are encrypted by using HMAC-SHA256 in the client. The client then submits the result to the web server as per request. Finally, the web server recalculates the HMAC-SHA256 value to validate the request by comparing it with the submitted value. In this way, the Zen Cart's open-source system is reinforced. Owing to the security and integrity of the HMAC-SHA256 algorithm, it can effectively protect the session security. Analysis and experimental results show that this mechanism can effectively protect the session security of Zen Cart without affecting the original performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3203-3215
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• 2015

Due to the high growth of SNS population, service scalability is one of the critical issues to be addressed. The cloud environment provides the flexible computing and storage resources for services deployment, which fits the characteristics of scalable SNS deployment. However, if the SNS related information is not properly placed, it will cause unbalance load and heavy transmission cost on the storage virtual machine (VM) and cloud data center (CDC) network. In this paper, we characterize the SNS into a graph model based on the users' associations and interest correlations. The node weight represents the degree of associations, which can be indexed by the number of friends or data sources, and the link weight denotes the correlation between users/data sources. Then, based on the SNS graph, the two-step algorithm is proposed in this paper to determine the placement of SNS related data among VMs. Two k-means based clustering schemes are proposed to allocate social data in proper VM and physical servers for pre-configured VM and dynamic VM environment, respectively. The experimental example was conducted and to illustrate and compare the performance of the proposed schemes.