• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.23-34
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• 2023

Wearable technology for military applications has received considerable attention as a means of personal status check and monitoring. Among many, an implementation to recognize specific motion states of a human is promising in that allows active management of troops by immediately collecting the operational status and movement status of individual soldiers. In this study, as an extension of military wearable application research, a new ankle wearable device is proposed that can glean the information of a soldier on the battlefield on which action he/she takes in which environment. Presuming a virtual situation, the soldier's upper limbs are easily exposed to uncertainties about circumstances. Therefore, a sensing module is attached to the ankle of the soldier that may always interact with the ground. The obtained data comprises 3-axis accelerations and 3-axis rotational velocities, which cannot be interpreted by hand-made algorithms. In this study, to discern the behavioral characteristics of a human using these dynamic data, a data-driven model is introduced; four features extracted from sliced data (minimum, maximum, mean, and standard deviation) are utilized as an input of the model to learn and classify eight primary military movements (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). As a result, the proposed device could recognize a movement status of a solider with 95.16% accuracy in an arbitrary test situation. This research is meaningful since an effective way of motion recognition has been introduced that can be furtherly extended to various military applications by incorporating wearable technology and artificial intelligence.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2A
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• pp.163-169
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• 2009

The research performed a test concerning the fluidity and strength of concrete manufactured by combining lime stone power, fly ash, and blast furnace slag into two and three component systems, aiming at evaluating rheological and dynamic properties of concrete by manufacturing High Flowing Self-Compacting according to the strength changes of three levels. As a result of the research, for High Flowing Self-Compacting of 30 MPa, the combination of lime stone power 20% and fly ash 30% for securing quality and strength and adjusting viscosity satisfied the required performance. For High Flowing Self-Compacting of 50 MPa, the combination of blast furnace slag 10% and fly ash 20% satisfied the fluidity and strength of the requirement performance. Also, for 70 MPa that has many power contents, the combination of blast furnace slag 20% and fly ash 10% for the increase of fluidity and the reduction of viscosity satisfied the required performance. It is judged that fly ash in all combinations can be used to secure viscosity and reduce concrete amount. In addition, it is judged that for High Flowing Self-Compacting according to the levels of compressive strength the combination of three component system including fly ash is more appropriate than the combination of two component system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2B
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• pp.163-171
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• 2009

Classical linear models have been generally used to analyze and forecast hydrologic time series. However, there is growing evidence of nonlinear structure in natural phenomena and hydrologic time series associated with their patterns and fluctuations. Therefore, the classical linear techniques for time series analysis and forecasting may not be appropriate for nonlinear processes. In recent, the BDS (Brock-Dechert-Scheinkman) statistic instead of conventional techniques has been used for detecting nonlinearity of time series. The BDS statistic was derived from the statistical properties of the correlation integral which is used to analyze chaotic system and has been effectively used for distinguishing nonlinear structure in dynamic system from random structures. DVS (Deterministic Versus Stochastic) algorithm has been used for detecting chaos and stochastic systems and for forecasting of chaotic system. This study showed the DVS algorithm can be also used for detecting nonlinearity of the time series. In this study, the stochastic and hydrologic time series are analyzed to detect their nonlinearity. The linear and nonlinear stochastic time series generated from ARMA and TAR (Threshold Auto Regressive) models, a daily streamflow at St. Johns river near Cocoa, Florida, USA and Great Salt Lake Volume (GSL) data, Utah, USA are analyzed, daily inflow series of Soyang dam and the results are compared. The results showed the BDS statistic is a powerful tool for distinguishing between linearity and nonlinearity of the time series and DVS plot can be also effectively used for distinguishing the nonlinearity of the time series.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.279-289
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• 2006

The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.

• Journal of the Korean neurological association
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• v.35 no.1
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• pp.8-15
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• 2017

Near-infrared spectroscopy (NIRS), a noninvasive optical method, utilizes the characteristic absorption spectra of hemoglobin in the near-infrared range to provide information on cerebral hemodynamic changes in various clinical situations. NIRS monitoring have been used mainly to detect reduced perfusion of the brain during orthostatic stress for three common forms of orthostatic intolerance (OI); orthostatic hypotension, neurally mediated syncope, and postural orthostatic tachycardia syndrome. Autonomic function testing is an important diagnostic test to assess their autonomic nervous systems for patients with symptom of OI. However, these techniques cannot measure dynamic changes in cerebral blood flow. There are many experimentations about study of NIRS to reveal the pathophysiology of patients with OI. Research using NIRS in other neurologic diseases (stroke, epilepsy and migraine) are ongoing. NIRS have been experimentally used in all stages of stroke and may complement the established diagnostic and monitoring tools. NIRS also provide pathophysiological approach during rehabilitation and secondary prevention of stroke. The hemodynamic response to seizure has long been a topic for discussion in association with the neuronal damage resulting from convulsion. One critical issue when unpredictable events are to be detected is how continuous NIRS data are analyzed. Besides, NIRS studies targeting pathophysiological aspects of migraine may contribute to a deeper understanding of mechanisms relating to aura of migraine. NIRS monitoring may play an important role to trend regional hemodynamic distribution of flow in real time and also highlights the pathophysiology and management of not only patients with OI symptoms but also those with various neurologic diseases.

• Journal of The Korean Association For Science Education
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• v.29 no.4
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• pp.423-436
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• 2009

This study aims to develop an analytic framework that can be used to classify scientific models in science textbooks according to modes and attributes of representation and to investigate types of scientific models presented in the biology section of science textbooks for the $7^{th}$ to $10^{th}$ grades. The results showed that modes of representation of scientific models are related to the nature of sub-areas of biology sections. Generally, the iconic model and symbolic model were in dominant use, including drawings of organs and explanations of working of systems. However, the chapters on 'The Organization of Life' and 'The Continuity of Life' showed a relatively high frequency in use of the actual model. The theoretical model was presented in a part of 'The Continuity of Life', due to its highly abstract characteristics. Moreover, the gestural model and analogical model showed very low frequency. From the perspective of attributes of representation, frequency of the static model was very high, while one of the dynamic models was very low. Therefore, efforts to recognize the properties of scientific concepts more clearly and to develop diverse types of models that can represent the concepts adequately are required. Analysis of these types of scientific models can offer recognition of the usefulness and limitations of models in representing the concepts or phenomena, and can help us to design adequate models depicting particular properties of given concepts. Also, this type of analysis may motivate researchers to strive to reveal correct methods for and limits of using the scientific models that are presented in existing science textbooks, as well as to provide useful information to organize the science textbooks according to the revised $7^{th}$ national science curriculum.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.1
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• pp.70-81
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• 2024

In this study, Tridimensional Hybrid Isolation System(THIS) was proposed as a vibration isolator for traffic loads, combining vertical and horizontal isolation systems. Its efficacy in improving serviceability for vertical vibration was analytically evaluated. Firstly, for the analysis, the major vibration modes of the existing apartment were identified through eigenvalue analysis for the system and pulse response analysis for the bedroom slab using commercial structural analysis software. Subsequently, a 16-story model with horizontal, vertical and rotational degrees of freedom for each slab was numerically organized to represent the achieved modes. The dynamic analysis for the measured acceleration from an adjacent ground to high-speed railway was performed by state-space equations with the stiffness and damping ratio of THIS as variables. The result indicated that as the vertical period ratio increased, the threshold period ratio where the slab response started to be suppressed varied. Specifically, when the period ratio is greater than or equal to 5, the acceleration levels of all slabs decreased to approximately 70% or less compared to the non-isolated condition. On the other hand, it was ascertained that the influence of damping ratios on the response control of THIS is inconsequential in the analysis. Finally, the improvement in vertical vibration performance of THIS was evaluated according to design guidelines for floor vibration of AIJ, SCI and AISC. It was confirmed that, after the application of THIS, the residential performance criteria were met, whereas the non-isolated structure failed to satisfy them.

• Journal of Korean Foot and Ankle Society
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• v.28 no.1
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• pp.21-26
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• 2024

Purpose: Foot pressure measurement devices are used widely in clinical settings for plantar pressure assessments. Despite the availability of various devices, studies evaluating the inter-device reliability are limited. This study compared plantar pressure measurements obtained from HR Mat (Tekscan Inc.) and EMED-n50 (Novel GmbH). Materials and Methods: The study involved 38 healthy male volunteers. The participants were categorized into two groups based on the Meary's angle in standing foot lateral radiographs: those with normal feet (angles ranging from -4° to 4°) and those with mild flatfeet (angles from -8° to -15°). The static and dynamic plantar pressures of the participants were measured using HR Mat and EMED-n50. The reliability of the contact area and mean force was assessed using the interclass correlation coefficient (ICC). Furthermore, the differences in measurements between the two devices were examined, considering the presence of mild flatfoot. Results: The ICC values for the contact area and mean force ranged from 0.703 to 0.947, indicating good-to-excellent reliability across all areas. EMED-n50 tended to record higher contact areas than HR Mat. The mean force was significantly higher in the forefoot region when measured with EMED-n50, whereas, in the hindfoot region, this difference was observed only during static measurements with HR Mat. Participants with mild flatfeet exhibited significantly higher contact areas in the midfoot region for both devices, with no consistent differences in the other parameters. Conclusion: The contact area and mean force measurements of the HR Mat and EMED-n50 showed high reliability. On the other hand, EMED-n50 tended to record higher contact areas than HR Mat. In cases of mild flatfoot, an increase in contact area within the midfoot region was observed, but no consistent impact on the differences between the two devices was evident.

• Information Systems Review
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• v.17 no.2
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• pp.77-100
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• 2015

This study examined the factors that influence the smartphone user's decision to accept the personalized mobile advertisement. As a theoretical basis, we applied the privacy calculus model (PCM) that illustrates how consumers are engaged in a dynamic adjustment process in which privacy risks are weighted against benefits of information disclosure. In particular, we investigated how smartphone users make a risk-benefit assessment under which personalized service as benefit-side factor and information privacy risks as a risk-side factor accompanying their acceptance of advertisements. Further, we extend the current PCM by considering advertisement fatigue as a new factor that may influence the user's acceptance. The research model with five (5) hypotheses was tested using data gathered from 215 respondents through a quasi-experimental survey method. During the survey, each participant was asked to navigate the website where the experimental simulation of a mobile advertisement service was provided. The results showed that three (3) out of five (5) hypotheses were supported. First, we found that the intention to accept advertisements is positively and significantly influenced by the perceived value of personalization. Second, perceived advertisement fatigue was also found to be a strong predictor of the intention to accept advertisements. However, we did not find any evidence of direct influence of privacy risks. Finally, we found that the significant moderating effect between the perceived value of personalization and advertisement fatigue. This suggests that the firms should provide effective tailored advertisement that can increase the perceived value of personalization to mitigate the negative impacts of advertisement fatigue.

• Journal of Plant Biotechnology
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• v.33 no.1
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• pp.1-9
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• 2006

Peroxiredoxins (Prxs) are ubiquitously distributed and play important functions in diverse cellular signaling systems. The proteins are largely classified into three groups, such as typical 2-Cys Prx, atypical 2-Cys Prx, and 1-Cys Prx, that are distinguished by their catalytic mechanisms and number of Cys residues. From the three classes of Prxs, the typical 2-Cys Prx containing the two-conserved Cys residues at its N-terminus and C-terminus catalyzes $H_2O_2$ with the use of thioredoxin (Trx) as an electron donor. During the catalytic cycle, the N-terminal Cys residue undergoes a peroxide-dependent oxidation to sulfenic acid, which can be further oxidized to sulfinic acid at the presence of high concentrations of $H_2O_2$ and a Trx system containing Trx, Trx reductase, and NADPH. The sulfinic acid form of 2-Cys Prx is reduced by the action of sulfiredoxin which requires ATP as an energy source. Under the strong oxidative or heat shock stress conditions, 2-Cys Prx in eukaryotes rapidly switches its protein structure from low-molecular-weight species to high-molecular-weight protein structures. In accordance with its structural changes, the protein concomitantly triggers functional switching from a peroxidase to a molecular chaperone, which can protect its substrate denaturation from external stress. In addition to its N-terminal active site, the C-terminal domain including 'YF-motif' of 2-Cys Prx plays a critical role in the structural changes. Therefore, the C-terminal truncated 2-Cys Prxs are not able to regulate their protein structures and highly resistant to $H_2O_2$-dependent hyperoxidation, suggesting that the reaction is guided by the peroxidatic Cys residue. Based on the results, it may be concluded that the peroxidatic Cys of 2-Cys Prx acts as an '$H_2O_2$-sensor' in the cells. The oxidative stress-dependent regulation of 2-Cys Prx provides a means of defense systems in cells to adapt stress conditions by activating intracellular defense signaling pathways. Particularly, 2-Cys Prxs in plants are localized in chloroplasts with a dynamic protein structure. The protein undergoes conformational changes again oxidative stress. Depending on a redox-potential of the chloroplasts, the plant 2-Cys Prx forms super-molecular weight protein structures, which attach to the thylakoid membranes in a reversible manner.