• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.1-10
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• 2014

The cloud computing paradigm introduced pay-per-use models in which IT services can be created and scaled on-demand. However, service providers are still concerned about the constraints imposed by their physical infrastructures. In order to keep the required QoS and achieve the goal of upholding the SLA, virtualized resources must be efficiently consolidated to maximize system throughput while keeping energy consumption at a minimum. Using ANN, we propose a predictive SLA-aware approach for consolidating virtualized resources in a cloud environment. To maintain the QoS and to establish an optimal trade-off between performance and energy efficiency, the server's utilization threshold dynamically adapts to the physical machine's resource consumption. Furthermore, resource-intensive VMs are prevented from getting underprovisioned by assigning them to hosts that are both capable and reputable. To verify the performance of our proposed approach, we compare it with non-optimized conventional approaches as well as with other previously proposed techniques in a heterogeneous cloud environment setup.

• Korean Journal of Applied Biomechanics
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• v.24 no.1
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• pp.35-42
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• 2014

Tendon elasticity is an important factor affecting muscle function and thus human movements. It has been reported that the mechanical properties of tendon are adaptable to external loading condition. Based on the adaptability of muscle and tendon to external loading conditions, one can assume that there might be an optimum ratio between muscle strength and tendon stiffness. The present study aimed to investigate whether there is correlation between plantar flexor muscle strength and stiffness of the achilles tendon (AT). Twenty two male subjects (age: $23.2{\pm}1.5yrs$, height: $175.5{\pm}6.2cm$, weight: $75.4{\pm}9.8kg$) performed maximum voluntary isometric plantarflexion on a custom-built dynamometer and muscle-tendon junction of the medial gastrocnemius muscle was simultaneously monitored using a real-time ultrasound imaging machine. The averages of muscle force and tendon stiffness were $366.38{\pm}79.37N$, $35.34{\pm}10.42N/mm$, respectively. Significant positive correlation was observed between muscle strength and tendon stiffness (r=0.8507), indicating that the muscle force is proportional to tendon stiffness. The results might have been used in computational modeling and criterion of training progress level in the fields of training and rehabilitation.

• Journal of the Korean Institute of Gas
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• v.16 no.6
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• pp.115-122
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• 2012

Polyurethane foams were synthesized with different contents and kinds of catalysts to know change of properties under various NCO index. UTM(universal testing machine), DSC(differential scanning calorimetry), SEM(scanning electron microscope) and FT-IR(Fourier transform spectroscopy) were used for studying the PUF's physical properties change. Compressive strength of PUF increased with increasing contents of catalyst. Glass transition temperature(Tg) and compressive strength of PUF using PC-8 and 33LV catalyst, increased with increasing NCO index at the aging. According to the results of Infrared spectral analysis, reduction of NCO peak was found in gelling catalyst, because unreacted NCO reacted with polyurethane. Although Tg and compressive strength of PUF using TMR-2, unchanged with increasing NCO index at the aging, because trimerization of isocyanate.

• Journal of KIISE
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• v.42 no.3
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• pp.295-306
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• 2015

MOnCa2 is a framework for building intelligent smartphone applications based on smartphone sensors and ontology reasoning. In previous studies, MOnCa determined and inferred user situations based on sensor values represented by ontology instances. When this approach is applied, recognizing user space information or objects in user surroundings is possible, whereas determining the user's physical context (travel behavior, travel destination) is impossible. In this paper, MOnCa2 is used to build recognition models for travel behavior and routes using smartphone sensors to analyze the user's physical context, infer basic context regarding the user's travel behavior and routes by adapting these models, and generate high-level context by applying ontology reasoning to the basic context for creating intelligent applications. This paper is focused on approaches that are able to recognize the user's travel behavior using smartphone accelerometers, predict personal routes and destinations using GPS signals, and infer high-level context by applying realization.

• Journal of Korean Physical Therapy Science
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• v.16 no.3
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• pp.11-17
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• 2009

Background: The purpose of this study was designed to find out the effectiveness of reposition sense, muscle fatigue response on lumbar spine after apply lumbosacral stabilization exercise program to 4 patients with chronic low back pain and for 12 weeks. Method: In this study the reposition sense was measured in 3 angle(60, 30, 12) of the lumbar spine motion with blind by MedX test machine and the difference of instability to lumbar vertebra segments in flexion, extension test of standing position and spinal load test Mattress Test by Spinal Mouse. The stabilization exercise program was applied 2 times a week for 12 weeks in hospital and 2 times a day for 20 minutes at home. Result: The results of the present study were that the repositioning sense was appeared the most error in 12 angles of lumbar flexion and Men was appeared to decrease an error more than female in average value of 4 angles after 12 weeks. And average error of male was decrease more than female. Thus the effects of lumbosacral stabilization exercise was improved repositioning sense of prorioceptor. Fatigue response test(FRT) results, in male, was raised muscle fatigue rate during increase weight, on the other hand female appeared lower than male. Conclusion: As a results, lumbosacral stabilization exercise was aided to improvement of lumbar spine repositioning sense and vertebra segments stabilization. It was showed the rate of decrease in typically 12 degree angle point of each 3 angle(60, 36, 12). Especially, that spine instability patients will have a risk when in lifting a load or working with slight flexion posture around 12 degree during the daily of living life and it is probably to increase recurrence rate. Thus, not only lumbar extension muscle strength but also stability of vertebra segments in lumbar spine may be very important.

• The Journal of Korean Academy of Prosthodontics
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• v.32 no.2
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• pp.249-267
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• 1994

The purpose of this study was to compare the fatigue, physical properties, flexibility and surface roughness of titanium used in removable partial dentures with those of a type IV and alloy and a cobalt- chromium alloy. Fatigue testing subjected the test specimen to rapid cycling at a given stress until failure occurred by using a small-sized, electrodynamic type bending fatigue testing machine. The S-N curves for the framework materials were generated. For tensile testing, a tensile bar as described in the ADA Specification No.14 was subjected to tensile loading until failure occurred. Load-displacement curves were generated for 18 gauge round specimen and tapered half round specimen. Then the flexibilities were calculated. The surface roughnesses were compared by analyzer. Through analyses of the data, the following conclusions were obtained. 1. The fatigue property of titanium was higher than that of a type IV gold alloy$(p\leq0.05)$, but there was no significant difference between titanium and a cobalt-chromium alloy $(p\geq0.05)$. 2. The yield strength, the ultimate tensile strength and Victors hardness of titanium were higher than those of a type IV gold alloy but lower than those of a coalt-chromium alloy$(p\leq0.05)$. 3. The percentage of elongation and reduction of area of titanium were the highest $(p\leq0.05)$. 4. The surface roughness of titanium was the greatest$(p\leq0.05)$. 5. The flexibility of titanium was lower than that of a type IV gold alloy but higher than that of a cobalt-chromium alloy$(p\leq0.05)$.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.2
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• pp.227-234
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• 2020

This paper introduces the state definition and diagnostic algorithm for autonomic control of manufacturing facilities. Smart factory systems through cyber-physical systems and digital twin technology are increasing the productivity and stability of existing manufacturing plants, which has become an issue recently. A Smart factory system is one of the key technologies that make up a smart factory system, to improve productivity, enable workers to make better decisions, and to control abnormal process flows. However, performing an autonomic control process based on large number of integrated plat data requires significant advance work. Therefore, in this paper, we define an abstracted facility state for manufacturing facility autonomic control and propose an algorithm to diagnose the current state. This makes the autonomic control process simpler by autonomic control based on the facility status rather then integrated facility data.

• Applied Chemistry for Engineering
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• v.29 no.2
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• pp.168-175
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• 2018

In order to investigate the effect of the chemical treatment of bamboo fiber on physical properties of polypropylene (PP)/bamboo fiber (BF) composites, silane coupling agents such as ${\gamma}$-aminopropyltriethoxysilane (APS), ${\gamma}$-glycidoxypropyl-trimethoxysilane (GPS) and ${\gamma}$-mercaptopropyltrimethoxysilane (MRPS) were applied to BF and alkaline treated BF. Morphological properties of the chemically treated BF were confirmed by optical microscope and SEM measurements, and chemical structure changes were confirmed by FT-IR and EDS. TGA results showed that the thermal stability of silane treated BF increased. Based on the analysis of a universal testing machine and an Izod impact test, the flexural and impact properties of PP/silane treated BF composites showed higher values than those of PP/BF composites. The enhancement of interfacial adhesion properties of the PP/BF composite was checked from SEM images of the fracture of specimens after the tensile test.

• The Journal of Korean Academy of Prosthodontics
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• v.37 no.6
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• pp.767-775
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• 1999

The purpose of this study was to evaluate the effect of wattage and curing time on surface hard-ness, three-point bending strength and internal porosity of microwave curing denture base resin. Two sizes of resin specimens were made of Acron $MC^{(R)}\;;\;3.5{\times}10{\times}60mm$ for surface hardness and three-point bending strength measurement and $5{\times}12{\times}60mm$ for internal porosity measurement. They were cured by microwave energy at varing wattages(500W, 700W) and curing times(2min., 3min., 4min.) to determine if a certain wattage/curing time combination would improve physical properties. Surface hardness was measured with Vikers hardness tester, three-point bend-ing strength with universal testing machine and internal porosity was calculated by measuring the weight in air and in water. The results obtained were as follows: 1. There was no significant difference in percent porosity among experimental groups(p>0.05). 2. 500W/3min. group showed the higher surface hardness than 700W/2, 3, 4min. groups(p<0.05), and 700W/4 min. group showed the lower surface hardness than 500W/2, 3, 4min. groups(p<0.05), but there was no significant difference among others(p>0.05). 3. 500W/3min. group yielded the higher value of bending strength than 500W/2min., 700W/3, 4min. groups(p<0.05), but there was no significant difference among others(p>0.05).