• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.1-10
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• 2021

The ability to recognize human emotions by computer vision is a very important task, with many potential applications. Therefore the demand for emotion recognition using not only RGB images but also thermal images is increasing. Compared to RGB images, thermal images has the advantage of being less affected by lighting conditions but require a more sophisticated recognition method with low-resolution sources. In this paper, we propose a Divide and Conquer-based CNN training strategy to improve the performance of facial thermal image-based emotion recognition. The proposed method first trains to classify difficult-to-classify similar emotion classes into the same class group by confusion matrix analysis and then divides and solves the problem so that the emotion group classified into the same class group is recognized again as actual emotions. In experiments, the proposed method has improved accuracy in all the tests than when recognizing all the presented emotions with a single CNN model.

• Smart Structures and Systems
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• v.29 no.2
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• pp.267-278
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• 2022

Pre-stressed concrete circular spun piles are widely used in various infrastructure projects around the world and offer an economical deep foundation system with consistent and superior quality compared to cast in-situ and other concrete piles. Conventional methods for measuring the lateral response of piles have been limited to conventional instrumentation, such as electrical based gauges and pressure transducers. The problem with existing technology is that the sensors are not able to assist in recording the lateral stiffness changes of the pile which varies along the length depending on the distribution of the flexural moments and appearance of tensile cracks. This paper describes a full-scale bending test of a 1-m diameter spun pile of 30 m long and instrumented using advanced fibre optic distributed sensor, known as Brillouin Optical Time Domain Analysis (BOTDA). Optical fibre sensors were embedded inside the concrete during the manufacturing stage and attached on the concrete surface in order to measure the pile's full-length flexural behaviour under the prescribed serviceability and ultimate limit state. The relationship between moments-deflections and bending moments-curvatures are examined with respect to the lateral forces. Tensile cracks were measured and compared with the peak strains observed from BOTDA data which corroborated very well. By analysing the moment-curvature response of the pile, the structure can be represented by two bending stiffness parameters, namely the pre-yield (EI) and post-yield (EI_cr), where the cracks reduce the stiffness property by 89%. The pile deflection profile can be attained from optical fibre data through closed-form solutions, which generally matched with the displacements recorded by Linear Voltage Displacement Transducers (LVDTs).

• Geomechanics and Engineering
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• v.28 no.6
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• pp.599-611
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• 2022

Tendon reinforced cemented soil is applied extensively in foundation stabilisation and improvement, especially in areas with soft clay. To solve the deterioration problem led by steel corrosion, the glass fiber-reinforced polymer (GFRP) tendon is introduced to substitute the traditional steel tendon. The interface bond strength between the cemented soil matrix and GFRP tendon demonstrates the outstanding mechanical property of this composite. However, the lack of research between the influence factors and bond strength hinders the application. To evaluate these factors, back propagation neural network (BPNN) is applied to predict the relationship between them and bond strength. Since adjusting BPNN parameters is time-consuming and laborious, the particle swarm optimisation (PSO) algorithm is proposed. This study evaluated the influence of water content, cement content, curing time, and slip distance on the bond performance of GFRP tendon-reinforced cemented soils (GTRCS). The results showed that the ultimate and residual bond strengths were both in positive proportion to cement content and negative to water content. The sample cured for 28 days with 30% water content and 50% cement content had the largest ultimate strength (3879.40 kPa). The PSO-BPNN model was tuned with 3 neurons in the input layer, 10 in the hidden layer, and 1 in the output layer. It showed outstanding performance on a large database comprising 405 testing results. Its higher correlation coefficient (0.908) and lower root-mean-square error (239.11 kPa) were obtained compared to multiple linear regression (MLR) and logistic regression (LR). In addition, a sensitivity analysis was applied to acquire the ranking of the input variables. The results illustrated that the cement content performed the strongest influence on bond strength, followed by the water content and slip displacement.

• KNOM Review
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• v.24 no.1
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• pp.20-28
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• 2021

Extensive use of social media applications and mobile devices continues to increase data traffic. Social media applications generate an endless and massive amount of multimedia traffic, specifically video traffic. Many social media platforms such as YouTube, Daily Motion, and Netflix generate endless video traffic. On these platforms, only a few popular videos are requested many times as compared to other videos. These popular videos should be cached in the user vicinity to meet continuous user demands. MEC has emerged as an essential paradigm for handling consistent user demand and caching videos in user proximity. The problem is to understand how user demand pattern varies with time. This paper analyzes three publicly available datasets, MovieLens 20M, MovieLens 100K, and The Movies Dataset, to find the user request pattern over time. We find hourly, daily, monthly, and yearly trends of all the datasets. Our resulted pattern could be used in other research while generating and analyzing the user request pattern in MEC-based video caching scenarios.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.183-188
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• 2022

Recently, more and more researches aimed at the development of automated and autonomous ships are appearing in the scientific environment. One of the main reason is the need to solve the problems of safe navigation and reducing accidents due to human factor, as well as the ever-increasing problem associated with the lack of qualified maritime personnel. Development of technologies based on application of artificial intelligence also plays important role, after all for realization of autonomous navigation concept and enhancement of ship automatic maneuvering processes, advancement of maneuvering functions and elaboration of specific algorithms on prevention of close quarter situations and dangerous approach of ships will be required. The purpose of this work is the review of preconditions of occurrence of the autonomous ship navigation conception, overview of introduction stages and prospects for ship remote control based on unmanned technologies, analysis of technical and intellectual decisions of autonomous surface ships, main research tendencies. The research revealed that the technology of autonomous ship navigation requires further development and improvement, especially in terms of the data transmission protocols upgrading, sensors of navigation information and automatic control systems modernization, which allows to perform monitoring of equipment with the aim of improving the functions of control over the autonomous surface ship operation.

• Environmental and Resource Economics Review
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• v.31 no.3
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• pp.319-342
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• 2022

This study analyzed the effect of pay-as-you-throw bag prices on domestic waste through the natural experiment difference in difference with synthetic control method using cases of price cuts in some districts in Busan in 2019. In order to consider the endogenous problem when estimating demand and price elasticity, the price-invariant district was set as a synthetic control group and the price-cutting district was set as a treatment group. As a result of the analysis, the price elasticity of demand was 0.05~0.11, and the price of the pay-as-you-throw bag had little effect in sales. This seems to be because pay-as-you-throw bag is necessities and account for a very small proportion of household income. This suggests that a policy that can shift the demand curve will be more effective than a price policy to achieve the waste reduction goal because the demand curve is almost vertical.

• Structural Engineering and Mechanics
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• v.83 no.5
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• pp.627-644
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• 2022

In past major earthquakes (1994 Northridge, 1995 Kobe, Chi-Chi 1999, Kocaeli 1999), significant damages occurred in the liquid storage tanks. The basic failure patterns were observed to be the buckling of the tank wall and uplift of the anchorage system. The damages in the industrial facilities and nuclear power plants have caused the spread of toxic substances to the environment and significant fires. Seismic isolation can be used in liquid storage tanks to decouple the structure and decrease the structural demand in the superstructure in case of ground shaking. Previous studies on the use of seismic isolation systems on liquid storage tanks show that an isolation system reduces the impulsive response but might slightly increase the convective one. There is still a lack of understanding of the seismic response of seismically isolated liquid storage tanks considering the fluid-structure interaction. In this study, one broad tank, one medium tank, and one slender tank are selected and designed. Two- and three-dimensional elastomeric bearings are used as seismic isolation systems. The seismic performance of the tanks is then investigated through nonlinear dynamic time-history analyses. The effectiveness of each seismic isolation system on tanks' performance was investigated. Isolator tension forces, modal analysis results, hydrodynamic stresses, strains, sloshing heights and base shear forces of the tanks are compared. The results show that the total base shear is lower in 3D-isolators compared to 2D-isolators. Even though the tank wall stresses, and strains are slightly higher in 3D-isolators, they are more efficient to prevent the tension problem.

• Journal of East-West Nursing Research
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• v.28 no.2
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• pp.100-108
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• 2022

Korean medicine has traditionally provided a lot of medical care for the treatment of infertility. The combination treatment of Korean medicine and Western medicine can be effective for infertility to improve the problems caused by the extremely low fertility rate and the aging of pregnant women. In relation to female infertility, we reviewed the evidence for Korean medicine treatment for polycystic ovary syndrome, which has recently been increasing interest in female infertility, and the evidence for the collaboration between Korean and Western medicine in the treatment of polycystic ovary syndrome and infertility. Because polycystic ovary syndrome is closely related to metabolic diseases related to endocrine abnormalities, hormone treatment alone has limited therapeutic effects and has side effects. In domestic and international research, herbal medicine and acupuncture in the treatment of infertility have shown good clinical effects based on the hypothesis of various mechanisms of effect, and many cases of successful pregnancy have been reported. Although continuous research through large-scale randomized clinical studies is needed to prove efficacy, the importance of combined treatment of Korean medicine and Western medicine in infertility treatment is increasing in order to solve the extremely low fertility rate. Combining artificial insemination or in vitro fertilization with Korean medicine treatment is highly likely to be effective in increasing pregnancy success and fertility rates. In women with polycystic ovary syndrome, which is recognized as a metabolic disease due to endocrine abnormalities among the causes of female infertility, Korean medicine treatment can increase the pregnancy rate with herbal medicines and acupuncture, etc. Although well-designed large-scale clinical studies are currently lacking and meta-analysis has not provided sufficient evidence, the combination treatment of Korean medicine and Western medicine is more active to increase the pregnancy rate for solving the problem of low fertility.

• PNF and Movement
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• v.20 no.3
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• pp.451-459
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• 2022

Purpose: Temporomandibular disorder (TMD) is a common musculoskeletal problem that causes pain in and disability of masticatory muscles, the temporo-mandibular joint (TMJ), and related structures. The purpose of this study was to compare pressure pain thresholds (PPTs) of masticatory muscles, cervical ranges of motion (ROM), and pelvic mobility during gait of subjects with or without TMD. Methods: In this study, pain thresholds and changes in the mobility of the cervical vertebrae and pelvis were measured in 25 patients with TMD and 25 healthy controls. Using a pressure algometer, the pressure pain thresholds (PPTs) of the masseter and temporalis muscles were measured in both groups. A gyroscope sensor with a mobile application was used to determine cervical ROM in the frontal and sagittal planes. A 3D-motion analysis system was used to evaluate pelvic mobility in the sagittal, frontal, and transverse planes during gait. Results: The TMD group showed significantly decreased PPTs of masseter and temporalis muscles compared with the control group (p < 0.05). Cervical ROM in flexion, extension, and lateral bending were significantly decreased in the TMD group compared with the control group (p < 0.05). In addition, antero-posterior pelvic tilt was significantly decreased in the TMD group (p < 0.05). Conclusion: The results of the current study suggest that there are close anatomical and functional relationships between TMD and muscle chains related to the cervical spine and pelvis. Therefore, more comprehensive body posture assessments, especially of painful areas, should be undertaken when studying TMD patients.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.905-910
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• 2022

Drowsy driving requires a lot of social attention because it increases the incidence of traffic accidents and leads to fatal accidents. The number of accidents caused by drowsy driving is increasing every year. Therefore, in order to solve this problem all over the world, research for measuring various biosignals is being conducted. Among them, this paper focuses on non-contact biosignal analysis. Various noises such as engine, tire, and body vibrations are generated in a running vehicle. To measure the driver's heart rate and respiration rate in a driving vehicle with a piezoelectric sensor, a sensor plate that can cushion vehicle vibrations was designed and noise generated from the vehicle was reduced. In addition, we developed a system for classifying whether the driver is sleeping or not by extracting the model using the CNN-LSTM ensemble learning technique based on the signal of the piezoelectric sensor. In order to learn the sleep state, the subject's biosignals were acquired every 30 seconds, and 797 pieces of data were comparatively analyzed.