• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.547-552
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• 2015

In this paper, an ARS-EKF based motion counting algorithm for repetitive exercises such as calisthenics is proposed using a smartwatch. Raw sensor signals from accelerometers and gyroscopes are widely used for conventional smartwatch counting algorithms based on pattern recognition. However, generated features from raw data are not intuitive to reflect the movement of motions. The proposed motion counter algorithm is composed of navigation based feature generation and counting with error correction. The candidate features for each activity are velocity and attitude calculated through an ARS-EKF algorithm. In order to select those features which reveal the characteristics of each motion, an exercise frame from the initial sensor frame is introduced. Counting processes are basically based on the zero crossing method, and misdetected counts are eliminated via simple classification algorithms considering the frequency of the counted motions. Experimental results show that the proposed algorithm efficiently and accurately counts the number of exercises.

• Smart Structures and Systems
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• v.31 no.2
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• pp.183-197
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• 2023

For long-span bridges with a structural health monitoring (SHM) system, environmental temperature-driven responses are proved to be a main component in measurements. However, anomalous structural behavior may be hidden incomplicated recorded data. In order to receive reliable assessment of structural performance, it is important to study therelationship between temperature and monitoring data. This paper presents an application of the cointegration based methodology to detect anomalies that may be masked by temperature effects and then forecast the temperature-induced deflection (TID) of long-span suspension bridges. Firstly, temperature effects on girder deflection are analyzed with fieldmeasured data of a suspension bridge. Subsequently, the cointegration testing procedure is conducted. A threshold-based anomaly detection framework that eliminates the influence of environmental temperature is also proposed. The cointegrated residual series is extracted as the index to monitor anomaly events in bridges. Then, wavelet separation method is used to obtain TIDs from recorded data. Combining cointegration theory with autoregressive moving average (ARMA) model, TIDs for longspan bridges are modeled and forecasted. Finally, in-situ measurements of Xihoumen Bridge are adopted as an example to demonstrate the effectiveness of the cointegration based approach. In conclusion, the proposed method is practical for actual structures which ensures the efficient management and maintenance based on monitoring data.

• Smart Structures and Systems
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• v.32 no.6
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• pp.371-382
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• 2023

Box girder bridges are now widely used in bridge construction, and it is necessary to perform load rating regularly to evaluate the load capacity of box girder bridges. Load testing is a common measure for load rating. However, the bridge must be loaded by many trucks under different loading conditions, which is time-consuming and laborious. To solve this problem, this paper proposes a load rating method for box girder bridges based on rapid moving loads testing. The method includes three steps. First, the quasi-influence factors of the bridge are obtained by crossing the bridge with rapidly moving loads, and the structural modal parameters are simultaneously obtained from the dynamic data to supplement. Second, an objective function is constructed, consisting of the quasi-influence factors at several measurement points and structural modal parameters. The finite element model for load rating is then updated based on the Rosenbrock method. Third, on this basis, a load rating method is proposed using the updated model. The load rating method proposed in this paper can considerably reduce the time duration of traditional static load testing and effectively utilize the dynamic and static properties of box girder bridges to obtain an accurate finite element model. The load capacity obtained based on the updated model can avoid the inconsistency of the evaluation results for the different structural members using the adjustment factors specified in codes.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.45-54
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• 2020

This study investigated basic data on walking characteristics, including walking speed and cognitive-response for the elderly, and based on these, the time of walking signal was calculated. The on-site survey examined the actual pedestrian crossing speed using a stopwatch, and the age was divided into groups of ordinary people and the elderly. Analysis of the data showed that the average walking speed for the general public was 1.29 m/s, while the average walking speed for the elderly was 1.13 m/s, higher than that of the general public. In addition, the lower speed of the 15th percentile was analyzed to 1.01 m/s for the general population and 0.85 m/s for the elderly, showing a lower walking speed than the standard for the general area and 0.8 m/s for the protected area. However, for senior citizens who use walking sticks or wheelchairs, the speed of the lower 15th-percentile is 0.73 m/s, which is lower than the current standard of protected areas, according to the analysis.

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.31-39
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• 2012

In this paper, we propose a microprocessor-based automatic voltage regulator(AVR) to reduce consumers' electric energy consumption and to help controlling peak demanding power. Hybrid Switching Automatic Voltage Regulator (HS-AVR) consist of a toroidal core, several tap control switches, display and command control parts. The coil forms an autotransformer which has a serial main winding and four parallel auxiliary windings. It controls the output voltage by changing the combination of the coils and the switches. Relays are adopted as the link switches of the coils to minimize the loss. To make connecting and disconnecting time accurate, relays of the circuit have parallel TRIACs. A software phase locked loop(PLL) has been used to synchronize the timings of the switches to the voltage waveform. The software PLL informs the input voltage zero-crossing and positive/negative peak timing. The traditional voltage transformers and AVRs have a disadvantage of having a large mandatory capacity to accommodate maximum inrush current to avoid the switch contact damage. But we propose a suitable AVR for every purpose in smart grid with reduced size and increased efficiency.

• International journal of advanced smart convergence
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• v.4 no.1
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• pp.137-144
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• 2015

Development of the yarn sorting equipment (khonhook) by slide way due to the principle of engineering that cause of workers on the long of motion time. The data was collected from the weaving group Ban Nongkok village, Nakornratchasima Province, THAILAND. According to the study, the step of yarn sorting (konhook) was one of the steps that affect long of motion time. The problem was the inadequate capacity equipment. The objective of research was to study and develop the yarn sorting equipment (konhook). The fabric used in the study was 64 meters in length and 1 meter in width. Researchers studied the processes the yarn sorting (konhook) which it consists of seven sub steps, 1) the thread tube setting, 2) yarn bunching, 3) tying a knot at the end of yarn, 4) looping the yarn into a pillar, 5) sorting the yarn (konhook), 6) crossing pillars and 7) taking out the yarn. Researchers focused on studying yarn sorting process (konhook) by designing and creating a device for yarn sorting (konhook) for reducing yarn sorting (konhook) time by the original method performance indicators. The results found that the developed yarn sorting equipment (konhook) ) by slide way could reduce working time from 7.24 minutes to 6.08 minutes of the original equipment yarn sorting (konhook). This means it could make the process 16.02 % faster. This also helps reducing the distance of workers' movement from 2,234 meters to 8 meters. This is 99.64 % shorter.

• The KIPS Transactions:PartC
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• v.18C no.1
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• pp.7-14
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• 2011

Power analysis attack on low-power consumed security devices such as smart cards is very powerful, but it is required that the correlation between the measured power signal and the mid-term estimated signal should be consistent in a time instant while running encryption algorithm. The power signals measured from the security device applying the random clock do not match the timing point of analysis, therefore random clock is used as counter measures against power analysis attacks. This paper propose a new constant pitch based time alignment for power analysis with random clock power trace. The proposed method neutralize the effects of random clock used to counter measure by aligning the irregular power signals with the time location and size using the constant pitch. Finally, we apply the proposed one to AES algorithm within randomly clocked environments to evaluate our method.

• Smart Structures and Systems
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• v.13 no.6
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• pp.1015-1039
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• 2014

The widening project on Freeway No.1 in Taiwan has a total length of roughly 14 kilometers, and includes three special bridges, namely a 216 m long-span bridge crossing the original freeway, an F-bent double decked bridge in a co-constructed section, and a steel and prestressed concrete composite bridge. This study employed in-situ monitoring in conjunction with numerical modeling to establish a real-time monitoring system for the three bridges. In order to determine the initial static and dynamic behavior of the real bridges, forced vibration experiments, in-situ static load experiments, and dynamic load experiments were first carried out on the newly-constructed bridges before they went into use. Structural models of the bridges were then established using the finite element method, and in-situ vehicle load weight, arrangement, and speed were taken into consideration when performing comparisons employing data obtained from experimental measurements. The results showed consistency between the analytical simulations and experimental data. After determining a bridge's initial state, the proposed in-situ monitoring system, which is employed in conjunction with the established finite element model, can be utilized to assess the safety of a bridge's members, providing useful reference information to bridge management agencies.

• Korean Journal of Health Education and Promotion
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• v.28 no.5
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• pp.145-160
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• 2011

Objectives: This study attempted to apply the Intervention mapping and Transtheoretical models to develop a program to promote moderate alcohol drinking in university students. Methods: Surveyed data from 1,137 university students were analyzed to identify personal and environmental determinants for alcohol drinking. Based on these determinants, program objectives were established. Crossing the objectives with related important determinants resulted in matrices of learning objectives for which educational strategies were developed. Subsequently, an intervention program were designed to achieve those objectives. Results: Identified personal determinants included awareness, attitudes, self-efficacy and behavioral skills. Environmental determinants were binge drinking behaviors of family members and peers, and social pressure for drinking. Program, impact and learning objectives were developed to change the identified determinants. Program activities included provision of information on positive and negative consequences of binge drinking, opportunities for assessing one's drinking pattern, increasing outcome expectancies of and skill building for monitoring drinking, resisting peer pressure and managing stress. To facilitate adoption and maintenance of the program, an intervention diffusion plan was suggested. An evaluation plan was developed by utilizing RE-AIM framework. Conclusions: In order to expand evidence bases for effective theory-based programs, the developed program should be tested in diverse university settings.

• Smart Structures and Systems
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• v.31 no.3
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• pp.247-257
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• 2023

In structural health monitoring of large-scale structures, optimal sensor placement plays an important role because of the high cost of sensors and their supporting instruments, as well as the burden of data transmission and storage. In this study, a vibration sensor placement algorithm based on deep reinforcement learning (DRL) is proposed, which can effectively solve non-convex, high-dimensional, and discrete combinatorial sensor placement optimization problems. An objective function is constructed to estimate the quality of a specific vibration sensor placement scheme according to the modal assurance criterion (MAC). Using this objective function, a DRL-based algorithm is presented to determine the optimal vibration sensor placement scheme. Subsequently, we transform the sensor optimal placement process into a Markov decision process and employ a DRL-based optimization algorithm to maximize the objective function for optimal sensor placement. To illustrate the applicability of the proposed method, two examples are presented: a 10-story braced frame and a sea-crossing bridge model. A comparison study is also performed with a genetic algorithm and particle swarm algorithm. The proposed DRL-based algorithm can effectively solve the discrete combinatorial optimization problem for vibration sensor placements and can produce superior performance compared with the other two existing methods.