Effectiveness Analysis and Application of Phosphorescent Pavement Markings for Improving Visibility (축광노면표시 시인성 개선에 따른 경제성 분석 및 적용방안)
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- KSCE Journal of Civil and Environmental Engineering Research
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- v.37 no.5
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- pp.815-825
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- 2017
Visibility of lane marking is impaired at night or in the rain, which thereby threatens traffic safety. Recently, various studies and technologies have been developed to improve lane marking visibility, such as the extension of lane marking life expectancy (up to 1.5 times), improvement of lane marking equipment productivity, improvement of lane marking visibility by applying phosphorescent material mixed paint. Cost-benefit analysis was performed with considering various benefit items that can be expected. About 45% of traffic accidents would be prevented by improving lane marking visibility. Additionally, accident reduction benefit and traffic congestion reduction benefit were calculated as much as 246 billion KRW per year and 12 billion KRW per year, respectively, by reducing repaint cycle due to enhanced durability. 45 billion KRW per year is expected to reduced with improved lane detection performance of autonomous vehicle. Meanwhile, total increased cost when introducing phosphorescent material mixed paint to 91,195km of nationwide road is identified as 1922 billion KRW per year. However, economic feasibility could not be secured with 0.16 of cost-benefit ratio when applied to the road network as a whole. In case of "Accident Hot Spot" analyzing section window (400m), one or more fatality or two or more injured (one or more injured in case of less than 2 lanes per direction) per year were caused by pavement marking related accident, economic feasibility was secured. In detail, 3.91 of cost-benefit ratio is estimated with comparison of the installation cost for 5,697 of accident hot spot and accident reduction benefit. Some limitations and future research agenda have also been discussed.
The new medical device technologies for bio-signal information and medical information which developed in various forms have been increasing. Information gathering techniques and the increasing of the bio-signal information device are being used as the main information of the medical service in everyday life. Hence, there is increasing in utilization of the various bio-signals, but it has a problem that does not account for security reasons. Furthermore, the medical image information and bio-signal of the patient in medical field is generated by the individual device, that make the situation cannot be managed and integrated. In order to solve that problem, in this paper we integrated the QR code signal associated with the medial image information including the finding of the doctor and the bio-signal information. bio-signal. System implementation environment for medical imaging devices and bio-signal acquisition was configured through bio-signal measurement, smart device and PC. For the ROI extraction of bio-signal and the receiving of image information that transfer from the medical equipment or bio-signal measurement, .NET Framework was used to operate the QR server module on Window Server 2008 operating system. The main function of the QR server module is to parse the DICOM file generated from the medical imaging device and extract the identified ROI information to store and manage in the database. Additionally, EMR, patient health information such as OCS, extracted ROI information needed for basic information and emergency situation is managed by QR code. QR code and ROI management and the bio-signal information file also store and manage depending on the size of receiving the bio-singnal information case with a PID (patient identification) to be used by the bio-signal device. If the receiving of information is not less than the maximum size to be converted into a QR code, the QR code and the URL information can access the bio-signal information through the server. Likewise, .Net Framework is installed to provide the information in the form of the QR code, so the client can check and find the relevant information through PC and android-based smart device. Finally, the existing medical imaging information, bio-signal information and the health information of the patient are integrated over the result of executing the application service in order to provide a medical information service which is suitable in medical field.
Thermo-responsive polymers that exhibit phase transition in response to temperature change can be used as materials for smart windows because they can control solar light transmission depending on the outside temperature. The development of thermo-responsive polymers for smart windows that can be used over a wide temperature range is desirable. To obtain high performance smart windows materials, three-dimensional thermo-responsive poly(N-isopropylacrylamide) (PNIPAm) gels were prepared by free radical polymerization from monomer N-isopropylacrylamide, N, N'-methylenebis acrylamide (MBAm) as a crosslinking agent, ammonium persulfate (APS) as a strong oxidizing agent/tetramethylene diamine as a catalyst, and a mixture of two solvents (water/glycerol). This study examined the effect of glycerol content on the lower critical solution temperature (LCST), freezing temperature and the solar light transmittance of crosslinked PNIPAm gel films. The LCST and freezing temperature of PNIPAm gel films were found to be significantly decreased from 34.3 and
One of the applications of geomagnetic paleo-secular variation (PSV) is the age dating of archeological remains (i.e., the archeomagnetic dating technique). This application requires the local model of PSV that reflects non-dipole fields with regional differences. Until now, the tentative Korean paleosecular variation (t-KPSV) calculated based on JPSV (SW Japanese PSV) has been applied as a reference curve for individual archeomagnetic directions in Korea. However, it is less reliable due to regional differences in the non-dipole magnetic field. Here, we present PSV curves for AD 1 to 600, corresponding to the Korean Three Kingdoms (including the Proto Three Kingdoms) Period, using the results of archeomagnetic studies in the Korean Peninsula and published research data. Then we compare our PSV with the global geomagnetic prediction model and t-KPSV. A total of 49 reliable archeomagnetic directional data from 16 regions were compiled for our PSV. In detail, each data showed statistical consistency (N > 6, 𝛼95 < 7.8°, and k > 57.8) and had radiocarbon or archeological ages in the range of AD 1 to 600 years with less than ±200 years error range. The compiled PSV for the initial six centuries (KPSV0.6k) showed declination and inclination in the range of 341.7° to 20.1° and 43.5° to 60.3°, respectively. Compared to the t-KPSV, our curve revealed different variation patterns both in declination and inclination. On the other hand, KPSV0.6k and global geomagnetic prediction models (ARCH3K.1, CALS3K.4, and SED3K.1) revealed consistent variation trends during the first six centennials. In particular, the ARCH3K.1 showed the best fitting with our KPSV0.6k. These results indicate that contribution of the non-dipole field to Korea and Japan is quite different, despite their geographical proximity. Moreover, the compilation of archeomagnetic data from the Korea territory is essential to build a reliable PSV curve for an age dating tool. Lastly, we double-check the reliability of our KPSV0.6k by showing a good fitting of newly acquired age-controlled archeomagnetic data on our curve.
Demand for energy consumption reduction is increasing according to the development expectations of future mobility. Lightweight structural materials are known as a method to reduce greenhouse gas emissions and improve energy efficiency. In particular, fiber reinforced polymer composite (FRP) is attracting attention as a material that can replace existing metal alloys due to its excellent mechanical properties and light weight. In this paper, industrial applications and research trends of carbon fiber reinforced composites (CFRP, carbon FRP) and self-reinforced composites (SRC) were reviewed based on the reinforcement, polymer matrix, and manufacturing process. In order to overcome the expensive process cost and long manufacturing time of the epoxy resin-based autoclave method, which is mainly used in the aircraft field, mass production of CFRP-applied electric vehicles has been reported using a high-pressure resin transfer molding process including fast-curing epoxy. In addition, thermoplastic resin-based CFRP and interface enhancement methods to solve the recycling issue of carbon fiber composites were reviewed in terms of materials and processes. To form a perfect matrix-reinforcement interface, which is known as the major factor inducing the excellent mechanical properties of FRP, studies on SRC impregnated with the same matrix in polymer fibers have been reported. The physical and mechanical properties of SRC based on various thermoplastic polymers were reviewed in terms of polymer orientation and composite structure. In addition, a copolymer matrix strategy for extending the processing window of highly drawn polypropylene fiber-based SRC was discussed. The application of CFRP and SRC as lightweight structural materials can provide potential options for improving the energy efficiency of future mobility.
As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70