• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.32-43
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• 1999

Adaptive robust control scheme is introduced for flexible joint manipulator with nonlinearities and uncertainties. The system does not satisfy the matching condition due to insufficient actuators for each node. The control only relies on the assumption that the bound of uncertainty exists. Thus, the bounded value does not need to be known a prior. The control utilizes the update law by estimating the bound of the uncertainties. The control scheme uses the backstepping method and constructs a state transformation. Also, stability analysis is done for both transformed system and original system.

• Research in Community and Public Health Nursing
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• v.31 no.spc
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• pp.534-548
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• 2020

Purpose: This study was conducted to evaluate the prevalence and lifestyle habits of cardiovascular disease (CVD) according to the type of disability in Korean adults compared to adults without disability. Methods: This study was secondary data analysis using the National Health check-up database from 2010 to 2013. Among the total 395,627 adults aged 30~80, the physically disabled (n=21,614) and the mentally disabled (n=1,448) who met the diagnosis criteria were extracted and compared with non-disabled (n=372,565) through 1:2 propensity score matching for nine characteristics. Results: Prior to matching, the prevalence of CVD was 34.4% in individuals without disabilities, accounting for 53.8% in those with physical disabilities and 22.4% in those with mental disabilities, showing significant differences between groups (p<.001). After matching, compared to the individuals without disability, those with physically disabled had significantly higher prevalence of CVD and the average number of CVD (p<.001). The prevalence of hypertension, diabetes, and vascular disease was significantly higher in the physically disabled (p<.05). Drinking was significantly higher in the non-disabled than in the physically and mentally disabled, and smoking was more in the non-disabled than in the mentally disabled. Physical activity was found to be significantly less in both the physically and mentally disabled than in the non-disabled (p<.01). Conclusion: It is necessary to confirm the differences in the prevalence of CVD risk factors and lifestyle according to the type of disability, suggesting the development and verification of health promotion programs including physical activity for CVD prevention in the disabled with CVD risk factors.

• Smart Structures and Systems
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• v.25 no.2
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• pp.123-133
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• 2020

Compressive sensing (CS) is a newly developed data acquisition and processing technique that takes advantage of the sparse structure in signals. Normally signals in their primitive space or format are reconstructed from their compressed measurements for further treatments, such as modal analysis for vibration data. This approach causes problems such as leakage, loss of fidelity, etc., and the computation of reconstruction itself is costly as well. Therefore, it is appealing to directly work on the compressed data without prior reconstruction of the original data. In this paper, a direct approach for modal analysis of damped systems is proposed by decomposing the compressed measurements with an appropriate dictionary. The damped free vibration function is adopted to form atoms in the dictionary for the following sparse decomposition. Compared with the normally used Fourier bases, the damped free vibration function spans a space with both the frequency and damping as the control variables. In order to efficiently search the enormous two-dimension dictionary with frequency and damping as variables, a two-step strategy is implemented combined with the Orthogonal Matching Pursuit (OMP) to determine the optimal atom in the dictionary, which greatly reduces the computation of the sparse decomposition. The performance of the proposed method is demonstrated by a numerical and an experimental example, and advantages of the method are revealed by comparison with another such kind method using POD technique.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.4
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• pp.437-446
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• 2018

This paper describes the real-time logic implementation of orthogonal matching pursuit(OMP) algorithm for compressive sensing digital receiver. OMP contains various complex-valued linear algebra operations, such as matrix multiplication and matrix inversion, in an iterative manner. Xilinx Vivado high-level synthesis(HLS) is introduced to design the digital logic more efficiently. The real-time signal processing is realized by applying dataflow architecture allowing functions and loops to execute concurrently. Compared with the prior works, the proposed design requires 2.5 times more DSP resources, but 10 times less signal reconstruction time of $1.024{\mu}s$ with a vector of length 48 with 2 non-zero elements.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1087-1101
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• 2018

As cloud computing has become a widespread technology, malicious attackers can obtain the private information of users that has leaked from the service provider in the outsourced databases. To resolve the problem, it is necessary to encrypt the database prior to outsourcing it to the service provider. However, the most existing data encryption schemes cannot process a query without decrypting the encrypted databases. Moreover, because the amount of the data is large, it takes too much time to decrypt all the data. For this, Programmable Order-Preserving Secure Index Scheme (POPIS) was proposed to hide the original data while performing query processing without decryption. However, POPIS is weak to both order matching attacks and data count attacks. To overcome the limitations, we propose a group order-preserving data encryption scheme (GOPES) that can support efficient query processing over the encrypted data. Since GOPES can preserve the order of each data group by generating the signatures of the encrypted data, it can provide a high degree of data privacy protection. Finally, it is shown that GOPES is better than the existing POPIS, with respect to both order matching attacks and data count attacks.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.6
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• pp.606-611
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• 2014

The understanding of another's behavior is a fundamental cognitive ability for primates including humans. Recent neuro-physiological studies suggested that there is a direct matching algorithm from visual observation onto an individual's own motor repertories for interpreting cognitive ability. The mirror neurons are known as core regions and are handled as a functionality of intent recognition on the basis of imitative learning of an observed action which is acquired from visual-information of a goal-directed action. In this paper, we addressed previous works used to model the function and mechanisms of mirror neurons and proposed a computational model of a mirror neuron system which can be used in human-robot interaction environments. The major focus of the computation model is the reproduction of an individual's motor repertory with different embodiments. The model's aim is the design of a continuous process which combines sensory evidence, prior task knowledge and a goal-directed matching of action observation and execution. We also propose a biologically inspired plausible equation model.

• Journal of Communications and Networks
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• v.13 no.2
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• pp.187-200
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• 2011

We present the design and implementation of a novel anti-malware system called SplitScreen. SplitScreen performs an additional screening step prior to the signature matching phase found in existing approaches. The screening step filters out most non-infected files (90%) and also identifiesmalware signatures that are not of interest (99%). The screening step significantly improves end-to-end performance because safe files are quickly identified and are not processed further, and malware files can subsequently be scanned using only the signatures that are necessary. Our approach naturally leads to a network-based anti-malware solution in which clients only receive signatures they needed, not every malware signature ever created as with current approaches. We have implemented SplitScreen as an extension to ClamAV, the most popular open source anti-malware software. For the current number of signatures, our implementation is $2{\times}$ faster and requires $2{\times}$ less memory than the original ClamAV. These gaps widen as the number of signatures grows.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.4
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• pp.127-133
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• 2018

Corporate social responsibility (CSR) is one of the strategies for managing firms' business activities but may have heterogeneity depending on ownership structures. This study investigates the association between group-affiliation and CSR activities. Drawing on a theory from the prior research, this study predicts that group-affiliated firms are less likely to invest on CSR activities. For instance, prior research finds that controlling shareholders expropriate the values of minority shareholders. As one of the motivations of investing on CSR activities is the harmonization among the stakeholders, it leads to the prediction that firms controlled by large shareholders are less likely to engage in CSR activities. Second, group-affiliated firms under poor financial performance benefit from other group members through sharing their financial resources. Thus, there is less incentive for managers of group-affiliated firms to increase their financial performance by conducting CSR. By leveraging firms listed in Korean stock market and CSR score from Korea Economic Justice Institute, the result shows that the group-affiliation is negatively related to CSR activities. The result is consistent in case of applying propensity score-matched sample. Based on the findings of this study, this paper contributes to the related literature by showing the significant association between group-affiliation and CSR decisions.

• Journal of Veterinary Clinics
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• v.34 no.3
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• pp.197-199
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• 2017

A 14-year-old castrated male ShihTzu diagnosed with chronic kidney disease (CKD) 6 months prior was referred to our clinic. The patient had been experiencing symptoms such as vomiting, poor appetite and hind limbs weakness. Hematology tests showed that he had a non-regenerative anemia. With aggressive treatment, the patient's state had gotten worse. He showed ragged breath, vomiting blood and loss of consciousness temporarily. Hematocrit maintained low level. Gastric hemorrhage was strongly suspected by hematemesis. Whole blood transfusion was performed and heparin was used as an anticoagulant. Prior to transfusion, the blood cross matching between donor and patient was performed and the result was compatible. After the transfusion was stabilized, 1 mg of protamine sulfate for each 100 units of heparin was prepared and given intravenously over 3 minutes to reverse the effects of heparin. Immediately after protamine injection, the patient conducted severe anaphylactic shock. Protamine sulfate is used to reverse the anticoagulant action of heparin in dogs and humans. The adverse reaction of protamine sulfate range from mild reaction to fetal cardiac arrest. When using protamine sulfate as heparin neutralization, it can lead to the death of a patient cause of anaphylactic shock. For this reason, the protamine sulfate should be injected slowly with antihistamine and the clinician should carefully monitor patients.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.516-525
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• 2005

Case-based reasoning (CBR) has been widely used in various areas due to its convenience and strength in complex problem solving. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However, designing a good matching and retrieval mechanism for CBR systems is still a controversial research issue. Most prior studies have tried to optimize the weights of the features or selection process of appropriate instances. But, these approaches have been performed independently until now. Simultaneous optimization of these components may lead to better performance than in naive models. In particular, there have been few attempts to simultaneously optimize the weight of the features and selection of the instances for CBR. Here we suggest a simultaneous optimization model of these components using a genetic algorithm (GA). We apply it to a customer classification model which utilizes demographic characteristics of customers as inputs to predict their buying behavior for a specific product. Experimental results show that simultaneously optimized CBR may improve the classification accuracy and outperform various optimized models of CBR as well as other classification models including logistic regression, multiple discriminant analysis, artificial neural networks and support vector machines.