• East Asian Journal of Business Economics (EAJBE)
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• v.10 no.4
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• pp.29-38
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• 2022

Purpose - The present research aims to assess the meaningful association between the extension of sports leisure culture and the spread of wearable devices. The research will discuss the current utilization of wearable devices in sports leisure and the present and future application of wearable devices in sports perspectives. Research design, Data, and methodology - We have investigated and conducted the qualitative content analysis (QCA) to obtain the adequate textual dataset in the current literature and conducted an in-depth analysis of the incorporation of cloud computing in the leisure sports industry by focusing on the development of wearable technologies. Result - From the QCA, it is evident that there is a meaningful connection between the extension of sports leisure culture and the spread of wearable devices, figuring out four kinds of associations as follows: (1) Monitoring the Impact of Sporting Activities, (2) Benefits of Sensor Technology, (3) Reducing Sedentary Behaviors, and (4) Measuring Workload done in Sport Leisure. Conclusion - The present research concludes that wearable devices positively influence individuals to participate in sports and leisure activities. Various technologies are very effective in motivating individuals to adopt sports leisure culture mainly because there is a certain degree of satisfaction that individuals gain in seeing the level of physical activities.

• Smart Structures and Systems
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• v.30 no.3
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• pp.273-286
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• 2022

In recent years, vision-based monitoring has received great attention. However, structural identification using vision-based displacement measurements is far less established. Especially, simultaneous identification of structural systems and unknown excitation using vision-based displacement measurements is still a challenging task since the unknown excitations do not appear directly in the observation equations. Moreover, measurement accuracy deteriorates over a wider field of view by vision-based monitoring, so, only a portion of the structure is measured instead of targeting a whole structure when using monocular vision. In this paper, the identification of structural system and excitations using vision-based displacement measurements is investigated. It is based on substructure identification approach to treat of problem of limited field of view of vision-based monitoring. For the identification of a target substructure, substructure interaction forces are treated as unknown inputs. A smoothing extended Kalman filter with unknown inputs without direct feedthrough is proposed for the simultaneous identification of substructure and unknown inputs using vision-based displacement measurements. The smoothing makes the identification robust to measurement noises. The proposed algorithm is first validated by the identification of a three-span continuous beam bridge under an impact load. Then, it is investigated by the more difficult identification of a frame and unknown wind excitation. Both examples validate the good performances of the proposed method.

• Journal of Sensor Science and Technology
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• v.31 no.1
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• pp.6-11
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• 2022

To date, various techniques have been utilized to assess the contractility of cardiomyocytes and their response to drug-induced toxicity. However, these techniques are either invasive or involve complex fabrication methods and expertise. Here, we introduce the use of video-based analysis software to track the motion of cardiomyocytes and assess their contractility. The software, called "Tracker", is freely available and this is the first attempt at using it for cardiac contractility measurement. We used the software to measure the contractile properties of cells cultured on a rigid substrate and two flexible polydimethylsiloxane (PDMS) substrates having different elastic moduli day-wise up to eight days. Contractility was found to be highest in the most flexible substrate. Subsequently, the cardiotoxicity response of the cells on three different substrates was analyzed with verapamil. It was observed that the cells on rigid substrate were primarily affected by drug-induced toxicity, while the drug had a lesser impact on cells on the more flexible PDMS substrate. Evidently, the flexible substrate aided the maturation of cells and had lower drug toxicity, while the cells on PS could not fully mature. The assessment of cardiomyocytes using "Tracker" proved to be simple and reliable.

• Journal of Sensor Science and Technology
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• v.31 no.1
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• pp.64-68
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• 2022

Herein, we propose a LoRaWAN-based small draft system that can measure the ocean current flow (speed, direction, and distance) in real time at the request of the Coast Guard to develop a device that can promptly find survivors at sea. This system has been implemented and verified in the early stages of rescue after maritime vessel accidents, which are frequent. GPS signals often transmit considerable errors, so correction algorithms using the improved triangulation method algorithm are required to accurately indicate the direction of currents in real time. This paper is structured in the following manner. The introduction section elucidates rescue activities in the case of a maritime accident. Chapter 2 explains the characteristics and main parameters of the GPS surveying technique and LoRaWAN communication, which are related studies. It explains and expands on the critical distance error correction algorithm for GPS signals and its improvement. Chapter 3 discusses the design and analysis of small draft buoys. Chapter 4 presents the testing and validation of the implemented system in both onshore and offshore environments. Finally, Section 5 concludes the study with the expected impact and effects in the future.

• Structural Monitoring and Maintenance
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• v.8 no.4
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• pp.379-402
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• 2021

Traditional approaches for structural health monitoring (SHM) seldom take ambient uncertainty (temperature, humidity, ambient vibration) into consideration, while their impacts on structural responses are substantial, leading to a possibility of raising false alarms. A few predictors model-based approaches deal with these uncertainties through complex numerical models running online, rendering the SHM approach to be compute-intensive, slow, and sometimes not practical. Also, with model-based approaches, the imperative need for a precise understanding of the structure often poses a problem for not so well understood complex systems. The present study employs a data-based approach coupled with Empirical mode decomposition (EMD) to correlate recorded response time histories under varying temperature conditions to corresponding damage scenarios. EMD decomposes the response signal into a finite set of intrinsic mode functions (IMFs). A two-dimensional Convolutional Neural Network (2DCNN) is further trained to associate these IMFs to the respective damage cases. The use of IMFs in place of raw signals helps to reduce the impact of sensor noise while preserving the essential spatio-temporal information less-sensitive to thermal effects and thereby stands as a better damage-sensitive feature than the raw signal itself. The proposed algorithm is numerically tested on a single span bridge under varying temperature conditions for different damage severities. The dynamic strain is recorded as the response since they are frame-invariant and cheaper to install. The proposed algorithm has been observed to be damage sensitive as well as sufficiently robust against measurement noise.

• Smart Structures and Systems
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• v.28 no.6
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• pp.827-838
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• 2021

The dynamic displacement is considered to be an important indicator of structural safety, and becomes an indispensable part of Structural Health Monitoring (SHM) system for high-speed railway bridges. This paper proposes an indirect strain based dynamic displacement reconstruction methodology for high-speed railway box girders. For the typical box girders under eccentric train load, the plane section assumption and elementary beam theory is no longer applicable due to the bend-torsion coupling effects. The monitored strain was decoupled into bend and torsion induced strain, pre-trained multi-output support vector regression (M-SVR) model was employed for such decoupling process considering the sensor layout cost and reconstruction accuracy. The decoupled strained based displacement could be reconstructed respectively using box girder plate element analysis and mode superposition principle. For the transformation modal matrix has a significant impact on the reconstructed displacement accuracy, the modal order would be optimized using particle swarm algorithm (PSO), aiming to minimize the ill conditioned degree of transformation modal matrix and the displacement reconstruction error. Numerical simulation and dynamic load testing results show that the reconstructed displacement was in good agreement with the simulated or measured results, which verifies the validity and accuracy of the algorithm proposed in this paper.

• Journal of Information Technology Applications and Management
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• v.29 no.1
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• pp.1-28
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• 2022

To realize the vision of internet of things (IoT), where it is expected to bring significant impact to the global economy in the future, consideration of business models in the IoT context is necessary. This research attempts to build an enhanced artifact business model framework based on the definitions of IoT and literature on business models for analysis of IoT businesses. The framework is used to analyze four different types of players: the owner of things, vendors of devices, providers of connectivity and providers of IoT application services. The findings suggest that the owners of things tend to partner with ICT players to complement their weakness, and it tends to be connectivity providers. The device vendors leverage their strength of devices and device platforms to attract and enable 3rd party sensor/devices to interconnect, while the service providers are aiming to penetrate into customer premise. These lead to the following recommendations for non-IT players to consider in expanding into IoT business: 1) take into account differences in product development process between IT and non-IT businesses in expanding into IoT market; 2) collaborate with ICT players that acknowledge and understand the differences.

• Korean Journal of Remote Sensing
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• v.39 no.4
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• pp.459-466
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• 2023

In the last decade, artificial intelligence's dramatic advancement with the development of various deep learning techniques has significantly contributed to remote sensing fields and satellite image applications. Among many prominent areas, super-resolution research has seen substantial growth with the release of several benchmark datasets and the rise of generative adversarial network-based studies. However, most previously published remote sensing benchmark datasets represent spatial resolution within approximately 10 meters, imposing limitations when directly applying for super-resolution of small objects with cm unit spatial resolution. Furthermore, if the dataset lacks a global spatial distribution and is specialized in particular land covers, the consequent lack of feature diversity can directly impact the quantitative performance and prevent the formation of robust foundation models. To overcome these issues, this paper proposes a method to generate benchmark datasets by simulating the modulation transfer functions of the sensor. The proposed approach leverages the simulation method with a solid theoretical foundation, notably recognized in image fusion. Additionally, the generated benchmark dataset is applied to state-of-the-art super-resolution base models for quantitative and visual analysis and discusses the shortcomings of the existing datasets. Through these efforts, we anticipate that the proposed benchmark dataset will facilitate various super-resolution research shortly in Korea.

• Advanced Industrial SCIence
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• v.2 no.1
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• pp.1-7
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• 2023

The use of Internet of Things(IoT) in smart cities and smart homes is essential. The security of the sensor nodes, which are the core of the IoT, is weak and hacking attacks are severe enough to have a fatal impact on real life. This research is conducted to improve the security of the Internet of Things by developing a lightweight secure communication protocol for the Internet of Things, and to build a safe Internet of Things environment suitable for the era of the 4th Industrial Revolution. It contributes to building a safe and convenient smart city and smart home by proposing key management and identifier development to increase the confidentiality of communication and the establishment of an Internet authentication system.

• ETRI Journal
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• v.45 no.6
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• pp.1022-1034
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• 2023

In this study, the impact of varying lighting conditions on recognition and decision-making was considered. The luminosity approach was presented to increase gesture recognition performance under varied lighting. An efficient framework was proposed for sensor-based sign language gesture identification, including picture acquisition, preparing data, obtaining features, and recognition. The depth images were collected using multiple Microsoft Kinect devices, and data were acquired by varying resolutions to demonstrate the idea. A case study was designed to attain acceptable accuracy in gesture recognition under variant lighting. Using American Sign Language (ASL), the dataset was created and analyzed under various lighting conditions. In ASL-based images, significant feature points were selected using the scale-invariant feature transformation (SIFT). Finally, an artificial neural network (ANN) classified hand gestures using specified characteristics for validation. The suggested method was successful across a variety of illumination conditions and different image sizes. The total effectiveness of NN architecture was shown by the 97.6% recognition accuracy rate of 26 alphabets dataset with just a 2.4% error rate.