• Advances in nano research
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• v.16 no.5
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• pp.473-487
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• 2024

The current study employs the nonlocal Timoshenko beam (NTB) theory and von-Kármán's geometric nonlinearity to develop a non-classic beam model for evaluating the nonlinear free vibration of bi-directional functionally-graded (BFG) nanobeams. In order to avoid the stretching-bending coupling in the equations of motion, the problem is formulated based on the physical middle surface. The governing equations of motion and the relevant boundary conditions have been determined using Hamilton's principle, followed by discretization using the differential quadrature method (DQM). To determine the frequencies of nonlinear vibrations in the BFG nanobeams, a direct iterative algorithm is used for solving the discretized underlying equations. The model verification is conducted by making a comparison between the obtained results and benchmark results reported in prior studies. In the present work, the effects of amplitude ratio, nanobeam length, material distribution, nonlocality, and boundary conditions are examined on the nonlinear frequency of BFG nanobeams through a parametric study. As a main result, it is observed that the nonlinear vibration frequencies are greater than the linear vibration frequencies for the same amplitude of the nonlinear oscillator. The study finds that the difference between the dimensionless linear frequency and the nonlinear frequency is smaller for CC nanobeams compared to SS nanobeams, particularly within the α range of 0 to 1.5, where the impact of geometric nonlinearity on CC nanobeams can be disregarded. Furthermore, the nonlinear frequency ratio exhibits an increasing trend as the parameter µ is incremented, with a diminishing dependency on nanobeam length (L). Additionally, it is established that as the nanobeam length increases, a critical point is reached at which a sharp rise in the nonlinear frequency ratio occurs, particularly within the nanobeam length range of 10 nm to 30 nm. These findings collectively contribute to a comprehensive understanding of the nonlinear vibration behavior of BFG nanobeams in relation to various parameters.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.209-218
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• 2012

Recently, the Field Programmable Stateful Logic Array (FPSLA) was proposed as one of the most promising system integration technologies which will extend the life of the Moore's law. This work is the first proposal of the FPSLA design automation flow, and the approaches to logic synthesis, synchronization, physical mapping, and automatic placement of the FPSLA designs. The synchronization at each gate for pipelining determines the x-coordinates of cells, and reduces the placement to 1-dimensional problems. The objective function and its gradients for the non-linear optimization of the net length and placement density have been remodeled for the reduced global placement problem. Also, a recursive algorithm has been proposed to legalize the placement by relaxing the density overflow of bipartite bin groups in a top-down hierarchical fashion. The proposed model and algorithm are implemented, and validated by applying them to the ACM/SIGDA benchmark designs. The output state of a gate in an FPSLA needs to be duplicated so that each fanout gate can be connected to a dedicated copy. This property has been taken into account by merging the duplicated nets into a hyperedge, and then, splitting the hyperedge into edges as the optimization progresses. This yields additional 18.4% of the cell count reduction in the most dense logic stage. The practicality of the FPSLA can be further enhanced primarily by incorporating into the logic synthesis the constraint to avoid the concentrated fains of gates on some logic stages. In addition, an efficient algorithm needs to be devised for the routing problem which is based on a complicated graph. The graph models the nanowire crossbar which is trimmed to be embedded into the FPSLA fabric, and therefore, asymmetric. These CAD tools can be used to evaluate the fabric efficiency during the architecture enhancement as well as automate the design.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.9
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• pp.304-315
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• 2018

Harmony Search (HS) is a recently developed metaheuristic algorithm that is widely known to many researchers. However, due to the increasing complexity of optimization problems, the optimal solution cannot be efficiently found by HS. To overcome this problem, there have been many studies that have improved the performance of HS by modifying the parameter settings and incorporating other metaheuristic algorithms. In this study, Copycat HS (CcHS) is suggested, which improves the parameter setting method and the performance of searching for the optimal solution. To verify the performance of CcHS, the results were compared to those of HS variants with a set of well-known mathematical benchmark problems. The effectiveness of CcHS was proven by finding final solutions that are closer to the global optimum than other algorithms in all problems. To analyze the applicability of CcHS to engineering optimization problems, it was applied to a design problem for Water Distribution Systems (WDS), which is widely applied in previous research. As a result, CcHS proposed the minimum design cost, which was 21.91% cheaper than the cost suggested by simple HS.

• Journal of the Earthquake Engineering Society of Korea
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• v.8 no.3
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• pp.63-76
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• 2004

This paper presents LRB-based hybrid base isolation systems employing additional active/semiactive control devices for mitigating earthquake-induced vibration of a cable-stayed 29 bridge. Hybrid base isolation systems could improve the control performance compared with the passive type-base isolation system such as LRB-installed bridge system due to multiple control devices are operating. In this paper, the additional response reduction by the two typical additional control devices, such as active type hydraulic actuators controlled by LQG algorithm and semiactive-type magnetorheological dampers controlled by clipped-optimal algorithm, have been evaluated bypreliminarily investigating the slightly modified version of the ASCE phase I benchmark cable-stayed bridge problem (i.e., the installation of LRBs to the nominal cable-stayed bridge model of the problem). It shows from the numerical simulation results that all the LRB based hybrid seismic isolation systems considered are quite effective to mitigate the structural responses. In addition, the numerical results demonstrate that the LRB based hybrid seismic isolation systems employing MR dampers have the robustness to some degree of the stiffness uncertainty of in the structure, whereas the hybrid system employing hydraulic actuators does not. Therefore, the feasibility of the hybrid base isolation systems employing semiactive additional control devices could be more appropriate in realfor full-scale civil infrastructure applications is clearly verified due to their efficacy and robustness.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.139-153
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• 2017

Corporate bankruptcy can cause great losses not only to stakeholders but also to many related sectors in society. Through the economic crises, bankruptcy have increased and bankruptcy prediction models have become more and more important. Therefore, corporate bankruptcy has been regarded as one of the major topics of research in business management. Also, many studies in the industry are in progress and important. Previous studies attempted to utilize various methodologies to improve the bankruptcy prediction accuracy and to resolve the overfitting problem, such as Multivariate Discriminant Analysis (MDA), Generalized Linear Model (GLM). These methods are based on statistics. Recently, researchers have used machine learning methodologies such as Support Vector Machine (SVM), Artificial Neural Network (ANN). Furthermore, fuzzy theory and genetic algorithms were used. Because of this change, many of bankruptcy models are developed. Also, performance has been improved. In general, the company's financial and accounting information will change over time. Likewise, the market situation also changes, so there are many difficulties in predicting bankruptcy only with information at a certain point in time. However, even though traditional research has problems that don't take into account the time effect, dynamic model has not been studied much. When we ignore the time effect, we get the biased results. So the static model may not be suitable for predicting bankruptcy. Thus, using the dynamic model, there is a possibility that bankruptcy prediction model is improved. In this paper, we propose RNN (Recurrent Neural Network) which is one of the deep learning methodologies. The RNN learns time series data and the performance is known to be good. Prior to experiment, we selected non-financial firms listed on the KOSPI, KOSDAQ and KONEX markets from 2010 to 2016 for the estimation of the bankruptcy prediction model and the comparison of forecasting performance. In order to prevent a mistake of predicting bankruptcy by using the financial information already reflected in the deterioration of the financial condition of the company, the financial information was collected with a lag of two years, and the default period was defined from January to December of the year. Then we defined the bankruptcy. The bankruptcy we defined is the abolition of the listing due to sluggish earnings. We confirmed abolition of the list at KIND that is corporate stock information website. Then we selected variables at previous papers. The first set of variables are Z-score variables. These variables have become traditional variables in predicting bankruptcy. The second set of variables are dynamic variable set. Finally we selected 240 normal companies and 226 bankrupt companies at the first variable set. Likewise, we selected 229 normal companies and 226 bankrupt companies at the second variable set. We created a model that reflects dynamic changes in time-series financial data and by comparing the suggested model with the analysis of existing bankruptcy predictive models, we found that the suggested model could help to improve the accuracy of bankruptcy predictions. We used financial data in KIS Value (Financial database) and selected Multivariate Discriminant Analysis (MDA), Generalized Linear Model called logistic regression (GLM), Support Vector Machine (SVM), Artificial Neural Network (ANN) model as benchmark. The result of the experiment proved that RNN's performance was better than comparative model. The accuracy of RNN was high in both sets of variables and the Area Under the Curve (AUC) value was also high. Also when we saw the hit-ratio table, the ratio of RNNs that predicted a poor company to be bankrupt was higher than that of other comparative models. However the limitation of this paper is that an overfitting problem occurs during RNN learning. But we expect to be able to solve the overfitting problem by selecting more learning data and appropriate variables. From these result, it is expected that this research will contribute to the development of a bankruptcy prediction by proposing a new dynamic model.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.5
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• pp.225-230
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• 2015

In this paper, we propose an effective real-time visual loop closure detector, VILODE, which makes use of key frames and bag of visual words (BoW) based on SURF feature points. In order to determine whether the camera has re-visited one of the previously visited places, a loop closure detector has to compare an incoming new image with all previous images collected at every visited place. As the camera passes through new places or locations, the amount of images to be compared continues growing. For this reason, it is difficult for a visual loop closure detector to meet both real-time constraint and high detection accuracy. To address the problem, the proposed system adopts an effective key frame selection strategy which selects and compares only distinct meaningful ones from continuously incoming images during navigation, and so it can reduce greatly image comparisons for loop detection. Moreover, in order to improve detection accuracy and efficiency, the system represents each key frame image as a bag of visual words, and maintains indexes for them using DBoW database system. The experiments with TUM benchmark datasets demonstrates high performance of the proposed visual loop closure detector.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2176-2183
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• 2017

The value of Big-Data which is a main factor of the fourth Industrial Revolution enhances industrial productivity in private sector and provides administrative services for nations and corporates in public sector. ICT-developed countries are coming up with Big-Data application in public sector rapidly. Especially, when it comes to social crisis management, they are equipped with pre-forcasting system. Korean Government also emphasizes Big-Data application in public sector for the social crisis management. But the reality where the overall infrastructure vulnerability reveals requires preparation and operation of measurement for social problems. Accordingly, we need to analyze Big-Data application problem and benchmark the precedented cases, thereby, direct policy diversity. Hence, this paper proposes the roles and rules of E-government analyzing problems from Big-Data application. The following policy proposes open Information and legal&institutional improvement, Big-Data service considerations threatening privacy issues in Big-Data ecosystem, necessity of operational and analytical technology for Big-Data and related technology in technical implication of Big-Data.

• Journal of the Earthquake Engineering Society of Korea
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• v.3 no.3
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• pp.63-74
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• 1999

A sliding mode fuzzy control (SMFC) algorithm is presented for vibration of large structures. Rule-base of the fuzzy inference engine is constructed based on the sliding mode control, which is one of the nonlinear control algorithms. Fuzziness of the controller makes the control system robust against the uncertainties in the system parameters and the input excitation. Non-linearity of the control rule makes the controller more effective than linear controllers. Design procedure based on the present fuzzy control is more convenient than those of the conventional algorithms based on complex mathematical analysis, such as linear quadratic regulator and sliding mode control(SMC). Robustness of presented controller is illustrated by examining the loop transfer function. For verification of the present algorithm, a numerical study is carried out on the benchmark problem initiated by the ASCE Committee on Structural Control. To achieve a high level of realism, various aspects are considered such as actuator-structure interaction, modeling error, sensor noise, actuator time delay, precision of the A/D and D/A converters, magnitude of control force, and order of control model. Performance of the SMFC is examined in comparison with those of other control algorithms such as $H_{mixed 2/{\infty}}$ optimal polynomial control, neural networks control, and SMC, which were reported by other researchers. The results indicate that the present SMFC is an efficient and attractive control method, since the vibration responses of the structure can be reduced very effectively and the design procedure is simple and convenient.

• Convergence Security Journal
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• v.17 no.4
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• pp.69-78
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• 2017

Since the September 11, 2001, transnational crimes and terrorism have increased, the importance of border security has been emphasized and integrated CIQ capability has been required. The U.S., Canada, and Australia are consolidating CIQ to strengthen border security, focusing on strengthening travelers and goods immigration control and airports, ports and land border security. In 2003, the U.S. established the Customs and Border Protection(CBP) under the Department of Homeland Security. Canada also established the Canada Border Services Agency(CBSA) under the Public Safety Canada in 2003. The Australian Customs and Border Protection Service was integrated with the Department of Immigration and Border Protection(DIBP) and the Australian Border Force was established in 2015. However, Korea operates a distributed border management system for each CIQ task which is unable to respond to complex border threats such as illegal immigration, entry of terrorists, smuggling of drugs, and gun trade in the airports, ports and land borders. In order to solve this problem, it is possible to consider integrating sequentially the customs and quarantine services which have high similarities, and to integrate the entire CIQ tasks with the Korea Customs Service delegated to the immigration control duties in the mid to long term. There is also a plan to benchmark the CIQ single accountability agencies in the U.S., Canada, and Australia in accordance with the Korean situation and to establish a new integrated border security organization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.707-716
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• 2017

The advances in image display devices necessitate display images suitable for the user's purpose. The display devices should be able to provide object-based image information when a depthmap is required. In this paper, we represent the algorithm using a histogram-based image segmentation method for depthmap generation. In the conventional K-means clustering algorithm, the number of centroids is parameterized, so existing K-means algorithms cannot adaptively determine the number of clusters. Further, the problem of K-means algorithm tends to sink into the local minima, which causes over-segmentation. On the other hand, the proposed algorithm is adaptively able to select centroids and can stand on the basis of the histogram-based algorithm considering the amount of computational complexity. It is designed to show object-based results by preventing the existing algorithm from falling into the local minimum point. Finally, we remove the over-segmentation components through connected-component labeling algorithm. The results of proposed algorithm show object-based results and better segmentation results of 0.017 and 0.051, compared to the benchmark method in terms of Probabilistic Rand Index(PRI) and Segmentation Covering(SC), respectively.