• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5782-5799
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• 2018

With the development of GPS and the popularity of mobile devices with positioning capability, collecting massive amounts of trajectory data is feasible and easy. The daily trajectories of moving objects convey a concise overview of their behaviors. Different social roles have different trajectory patterns. Therefore, we can identify users or groups based on similar trajectory patterns by mining implicit life patterns. However, most existing daily trajectories mining studies mainly focus on the spatial and temporal analysis of raw trajectory data but missing the essential semantic information or behaviors. In this paper, we propose a novel trajectory semantics calculation method to identify groups that have similar behaviors. In our model, we first propose a fast and efficient approach for stay regions extraction from daily trajectories, then generate semantic trajectories by enriching the stay regions with semantic labels. To measure the similarity between semantic trajectories, we design a semantic similarity measure model based on spatial and temporal similarity factor. Furthermore, a pruning strategy is proposed to lighten tedious calculations and comparisons. We have conducted extensive experiments on real trajectory dataset of Geolife project, and the experimental results show our proposed method is both effective and efficient.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.43-54
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• 2021

The study evaluates India's technological advancement, which has created a range of opportunities for consumers to enter into digital payment space. Demonetization in India has forced all consumers and companies to embrace and create cashless digital payment platforms. The cashless economy scenario involves various factors for its adoption such as reach, availability and awareness. This study considers factors responsible for adopting new digital payment technologies in India's different regions across various consumers. The study includes descriptive statistics and variance analysis (ANOVA) to identify elements to achieve maximum satisfaction. The research collects data from 250 respondents living in India, experiencing digital payments and online transactions. The data is collected through a structured questionnaire and critically analyzed using statistical analysis. The data has been analyzed with no sectorial biases and tracked by creating real-time indications. The study uses various hypotheses after taking responses from a sample of respondents. Cronbach's Alpha analysis is also used to determine the validity and reliability of the data. The study illustrates the complete shift of consumer behavior from cash to a cashless economy. A certain number of factors are shown to directly influence the rate of such a shift toward digital transactions in India.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.16 no.2
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• pp.18-24
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• 2020

When a damage occurs in the nuclear fuel burning in the reactor, fission products that should be in the nuclear fuel rod are released into the reactor coolant. In this case, sipping test, a series of non-destructive inspection methods, are used to find leakage in nuclear fuel assemblies during the power plant overhaul period. In addition, the sipping test is also used to check the integrity of the spent fuel for moving to an intermediate dry storage, which is carried out as the first step of nuclear decommissioning, . In this paper, the principle and characteristics of the sipping test are described. The structure of the sipping inspection equipment is largely divided into a suction device that collects fissile material emitted from a damaged assembly and an analysis device that analyzes their nuclides. In order to make good use of the sipping technology, the radioactive level behavior of the primary system coolant and major damage mechanisms in the event of nuclear fuel damage are also introduced. This will be a reference for selecting an appropriate sipping method when dismantling a nuclear power plant in the future.

• Journal of IKEEE
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• v.25 no.2
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• pp.337-343
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• 2021

Deep reinforcement learning is an artificial intelligence algorithm that enables learners to select optimal behavior based on raw and, high-dimensional input data. A lot of research using this is being conducted to create an optimal movement path of a mobile robot in an environment in which obstacles exist. In this paper, we selected the Dueling Double DQN (D3QN) algorithm that uses the prioritized experience replay to create the moving path of mobile robot from the image of the complex surrounding environment. The virtual environment is implemented using Webots, a robot simulator, and through simulation, it is confirmed that the mobile robot grasped the position of the obstacle in real time and avoided it to reach the destination.

• Advances in nano research
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• v.11 no.6
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• pp.657-665
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• 2021

The present work aimed to explore green approach via aqueous leaves extract of Murraya koenigii (ALEMk) for the synthesis of silver nanoparticles (AgNPsMk) in single step. The synthesis process was visualized with a color change and monitored by employing UV/Visible spectroscopy and a clear peak attained at 420 nm confirming the synthesis of AgNPsMk. The possible functional groups present in the extract which participated in the synthesis of AgNPsMk were identified with the help of FTIR spectroscopy. Further characterization using TEM images revealed the spherical shape of AgNPsMk with average particle size of 20 nm displaying well dispersion throughout the solution. Pronounced antioxidant activities of AgNPsMk at increased concentrations observed which evidencing strong radical scavenging ability. Moreover, AgNPsMk exhibited strong antibacterial behavior when tested against bacterial strains of Escherichia coli and Bacillus subtilis. Moving ahead, in vitro cytotoxicity work revealed potent cell viability loss appearing in AU565 and HeLa cancer cell lines on exposure to AgNPsMk at increased concentration. Finally, in vivo assessment carried out inside male Wistar rats indicated non toxic effect on examined liver tissues besides biochemical analysis including bilirubin, alkaline phosphtase (ALP) and serum glutamate pyruvate transaminase (SGPT) which found within the normal range when compared with control. The prior research work profoundly apprises the potential of green synthesized AgNPsMk to play a significant role in biomedical applications and formulations.

• Ocean Systems Engineering
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• v.11 no.4
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• pp.353-371
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• 2021

Sloshing behavior of liquid within containers represents one of the most fundamental fluid-structure interactions. Liquid in partially filled tanks tends to slosh when subjected to external disturbances. Sloshing is a vicious resonant fluid motion in a moving tank. To understand the effect of baffle positioned at L/3 and 2L/3 location, a shake table experiments was conducted for different fill volumes of aspect ratio 0.163, 0.325 and 0.488. For a fixed amplitude of 7.5 mm, the excitation frequencies are varied between 0.457 Hz to 1.976 Hz. Wave probes have been located at both tank ends to capture the surface elevation. The experimental parameters such as sloshing oscillation and energy dissipation are discussed here. Comparison is done for with baffles and without baffles conditions. For both conditions, the results showed that aspect ratio of 0.163 gives better surface elevation and energy dissipation than obtained for aspect ratio 0.325 and 0.488. Good agreement is observed when numerical analysis is compared with the experiments results.

• 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.

• Geomechanics and Engineering
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• v.28 no.2
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• pp.107-116
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• 2022

The steady state of unsaturated soil takes a long time to achieve. The soil seepage behaviours and hydraulic properties depend highly on the wetting/drying rate. It is observed that the soil-water characteristic curve (SWCC) is dependent on the wetting/drying rate, which is known as the dynamic effect. The dynamic effect apparently influences the scanning curves and will substantially affect the seepage behavior. However, the previous models commonly ignore the dynamic effect and cannot quantitatively describe the hysteresis scanning loops under dynamic conditions. In this study, a dynamic hysteresis model for SWCC is proposed considering the dynamic change of contact angle and the moving of the contact line. The drying contact angle under dynamic condition is smaller than that under static condition, while the wetting contact angle under dynamic condition is larger than that under static condition. The dynamic contact angle is expressed as a function of the saturation rate according to the Laplace equation. The model is given by a differential equation, in which the slope of the scanning curve is related to the slope of the boundary curve by means of contact angle. Empirical models can simulate the boundary curves. Given the two boundary curves, the scanning curve can be well predicted. In this model, only two parameters are introduced to describe the dynamic effect. They can be easily obtained from the experiment, which facilitates the calibration of the model. The proposed model is verified by the experimental data recorded in the literature and is proved to be more convenient and effective.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.141-143
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• 2021

The Activity patterns of animal species are difficult to access and the behavior of freely moving individuals can not be assessed by direct observation. As it has become large challenge to understand the activity pattern of animals such as dogs, and cats etc. One approach for monitoring these behaviors is the continuous collection of data by human observers. Therefore, in this study we assess the activity patterns of dog using the wearable sensors data such as accelerometer and gyroscope. A wearable, sensor -based system is suitable for such ends, and it will be able to monitor the dogs in real-time. The basic purpose of this study was to develop a system that can detect the activities based on the accelerometer and gyroscope signals. Therefore, we purpose a method which is based on the data collected from 10 dogs, including different nine breeds of different sizes and ages, and both genders. We applied six different state-of-the-art classifiers such as Random forests (RF), Support vector machine (SVM), Gradient boosting machine (GBM), XGBoost, k-nearest neighbors (KNN), and Decision tree classifier, respectively. The Random Forest showed a good classification result. We achieved an accuracy 86.73% while the detecting the activity.

• Structural Engineering and Mechanics
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• v.88 no.3
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• pp.239-249
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• 2023

The Radial Point Interpolation Method (RPIM) has been proposed to overcome the difficulties associated with the use of the Radial Basis Functions (RBFs). The RPIM has the following properties: Simple implementation in terms of boundary conditions as in the Finite Element Method (FEM). A less expensive CPU time compared to other collocation meshless methods such as the Moving Least Square (MLS) collocation method. In this work, we propose an adaptive high-order numerical algorithm based on RPIM to simulate the thermoviscoplastic behavior of a material mixing observed in the Friction Stir Welding (FSW) process. The proposed adaptive meshfree RPIM algorithm adapts well to the geometric and physical data by choosing a good shape parameter with a good precision. Our numerical approach combines the RPIM and the Asymptotic Numerical Method (ANM). A numerical procedure is also proposed in this work to automatically determine an improved shape parameter for the RBFs. The efficiency of the proposed algorithm is analyzed in comparison with an iterative algorithm.