• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.3
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• pp.232-242
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• 2015

For stealth performance consideration, many UAV designs are adopting tailless lambda-shaped configurations which are likely to have unsteady dynamic characteristics. In order to control such UAVs through automatic flight control system, more accurate estimation of dynamic stability derivatives becomes essential. In this paper, dynamic stability derivatives of a tailless lambda-shaped UAV are estimated through numerically simulated forced oscillation method incorporating dynamic mesh technique. First, the methodology is validated by benchmarking the CFD results against previously published experimental results of the Standard Dynamics Model(SDM). The dependency of initial angle of attack, oscillation frequency and oscillation magnitude on the dynamic stability derivatives of a tailless UAV configuration is then studied. The results show reasonable agreements with experimental reference data and prove the validity and efficiency of the concept of using CFD to estimate the dynamic derivatives.

• 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.

• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1295-1300
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• 2004

Although model checking has gained its popularity as one of the most effective approaches to the formal verification, it has to deal with the state explosion problem to be widely used in industry. In order to mitigate the problem, this paper proposes an ion technique to obtain a reduced model M' from a given original model M. Our technique Identifies the set of necessary variables for model checking and projects the state space onto them. The model M' is smaller in both size and behavior than the original model M, written M'$\leq$M. Since the result of reachability analysis with M' is preserved in M, we can do reachability analysis with model checking using M' instead of M. The abstraction technique is applied to Push Push games, and two model checkers - Cadence SMV and NuSMV - are used to solve the games. As a result, most of unsolved games with the usual model checking are solved with the ion technique. In addition, ion shows that there is much of time and space improvement. With Cadence SMV, there is 87% time improvement and 79% space one. And there is 83% time improvement and 56% space one with NuSMV.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.2
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• pp.3-8
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• 2009

The traction system has been mainly used for rehabilitation and correction of patients with spine or gait diseases in orthopedics or at home. Some problems could occur in human body when patients forced their training using the traction system. So it needs to measure a traction force and control the training time. However, most of products on market have no sensor measuring traction force. Thus we designed and made a sensor detecting traction force using strain gauge, amplifier for transition to output signal and experiment devices for performance test. We carried out experiment of a sensor detecting a traction force and measured electric responses of it with respect to traction loads. Maximum error was within about 1% for experiments in static condition and the average error was about 0.7% for experiments in dynamic condition. We concluded that it is possible to use the developed sensor for measurement of traction force since the maximum output variation of a sensor detecting a traction force was about 0.3% in $0^{\circ}C-60^{\circ}C$ temperature condition.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.303-310
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• 2021

This study was conducted to identify the effects of pressure taping between tibia and fibula of High Ankle Sprain athletes on pain, Range of Motion(ROM), and strength and to provide basic data for rehabilitation programs. The subjects of the study were conducted with a total of 10 athletes except for four who gave up who were diagnosed with high ankle sprain, or who were diagnosed with ankle sprain but their physical examinations proved positive. The results showed no significant differences in pain(Visual Analog Scale, VAS). The ROM was significantly increased in inversion(IV) and eversion(EV) in both groups. The Isometric strength was significantly improved in IV(0°, 7°, 14°) and EV(0°) in Taping Group(TG). When taping was applied to athletes with injury to the High Ankle Sprain, ROM and muscle strength improved at the same pain level.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.21-29
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• 2018

In the era of the 4-th industrial revolution, the concept of smart factory is emerging. There are efforts to predict the occurrences of facility errors which have negative effects on the utilization and productivity by using data analysis. Data composed of the situation of a facility error and the type of the error, called the facility error log, is required for the prediction. However, in many manufacturing companies, the types of facility error are not precisely defined and categorized. The worker who operates the facilities writes the type of facility error in the form with unstructured text based on his or her empirical judgement. That makes it impossible to analyze data. Therefore, this paper proposes a framework for constructing a phrase network to support the identification and classification of facility error types by using facility error logs written by operators. Specifically, phrase indicating the types are extracted from text data by using dictionary which classifies terms by their usage. Then, a phrase network is constructed by calculating the similarity between the extracted phrase. The performance of the proposed method was evaluated by using real-world facility error logs. It is expected that the proposed method will contribute to the accurate identification of error types and to the prediction of facility errors.

• Korean Journal of Construction Engineering and Management
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• v.22 no.5
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• pp.73-85
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• 2021

This study proposes an efficient management direction for Korean construction accident cases through a deep learning-based text data classification model. A deep learning model was developed, which categorizes five categories of construction accidents: fall, electric shock, flying object, collapse, and narrowness, which are representative accident types of KOSHA. After initial model tests, the classification accuracy of fall disasters was relatively high, while other types were classified as fall disasters. Through these results, it was analyzed that 1) specific accident-causing behavior, 2) similar sentence structure, and 3) complex accidents corresponding to multiple types affect the results. Two accuracy improvement experiments were then conducted: 1) reclassification, 2) elimination. As a result, the classification performance improved with 185.7% when eliminating complex accidents. Through this, the multicollinearity of complex accidents, including the contents of multiple accident types, was resolved. In conclusion, this study suggests the necessity to independently manage complex accidents while preparing a system to describe the situation of future accidents in detail.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.105-112
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• 2021

In the era of big data, interest in data is exploding. In particular, the development of the Internet and social media has led to the creation of new data, enabling the realization of the era of big data and artificial intelligence and opening a new chapter in convergence technology. Also, in the past, there are many demands for analysis of data that could not be handled by programs. In this paper, an analysis model was designed and verified for classification of unstructured data, which is often required in the era of big data. Data crawled DBPia's thesis summary, main words, and sub-keyword, and created a database using KoNLP's data dictionary, and tokenized words through morpheme analysis. In addition, nouns were extracted using KAIST's 9 part-of-speech classification system, TF-IDF values were generated, and an analysis dataset was created by combining training data and Y values. Finally, The adequacy of classification was measured by applying three analysis algorithms(random forest, SVM, decision tree) to the generated analysis dataset. The classification model technique proposed in this paper can be usefully used in various fields such as civil complaint classification analysis and text-related analysis in addition to thesis classification.

• Journal of Industrial Convergence
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• v.21 no.7
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• pp.51-63
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• 2023

This study aimed to verify the effects of a 4-week program of ankle-strengthening exercise and toe-taping walk exercise on the basic lower body strength and walking to examine the benefits of the two exercises. The subjects involved 30 women in their 20s enrolled in university A. The subjects were equally divided into three groups - ankle-strengthening exercise group, toe-taping walk exercise group, and control group. The subjects were instructed to massage and do ankle-strengthening exercises using a towel, massage ball, and CRT, for 60 minutes, 3 times a week. They also taped their hallux valgus using a kinesiology tape and walked for 20 minutes with white tape applied. To sum up, the 4-week ankle-strengthening exercise and toe-taping walk exercise were identified to have a partial statistical significance on the basic lower body strength (muscular strength, power, and balance) and walking (length of gait line, plantar pressure, and COP) of women in their 20s. Therefore, the study confirmed the effects of ankle-strengthening exercises and toe-taping walk exercise on the lower body exercise function, and it is considered that further studies should be conducted on more various effects of the exercises by subdividing them into different pain locations and orthomechanic findings.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.3
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• pp.155-163
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• 2023

Real-time monitoring technology is critical for ensuring the safety and reliability of nuclear power plant structures. However, the current seismic monitoring system has limited system identification capabilities such as modal parameter estimation. To obtain global behavior data and dynamic characteristics, multiple sensors must be optimally placed. Although several studies on optimal sensor placement have been conducted, they have primarily focused on civil and mechanical structures. Nuclear power plant structures require robust signals, even at low signal-to-noise ratios, and the robustness of each mode must be assessed separately. This is because the mode contributions of nuclear power plant containment buildings are concentrated in low-order modes. Therefore, this study proposes an optimal sensor placement methodology that can evaluate robustness against noise and the effects of each mode. Indicators, such as auto modal assurance criterion (MAC), cross MAC, and mode shape distribution by node were analyzed, and the suitability of the methodology was verified through numerical analysis.