• Smart Structures and Systems
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• v.16 no.3
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• pp.383-399
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• 2015

Today, as railways increase their capacity and speeds, it is more important than ever to be completely aware of the state of vehicles fleet's condition to ensure the highest quality and safety standards, as well as being able to maintain the costs as low as possible. Operation of a modern, dynamic and efficient railway demands a real time, accurate and reliable evaluation of the infrastructure assets, including signal networks and diagnostic systems able to acquire functional parameters. In the conventional system, measurement data are reliably collected using coaxial wires for communication between sensors and the repository. As sensors grow in size, the cost of the monitoring system can grow. Recently, auto-powered wireless sensor has been considered as an alternative tool for economical and accurate realization of structural health monitoring system, being provided by the following essential features: on-board micro-processor, sensing capability, wireless communication, auto-powered battery, and low cost. In this work, an original harvester device is designed to supply wireless sensor system battery using train bogie energy. Piezoelectric materials have in here considered due to their established ability to directly convert applied strain energy into usable electric energy and their relatively simple modelling into an integrated system. The mechanical and electrical properties of the system are studied according to the project specifications. The numerical formulation is implemented with in-house code using commercial software tool and then experimentally validated through a proof of concept setup using an excitation signal by a real application scenario.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.147-154
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• 2015

Recently agile development process became increasing effectiveness, quality, attention to experts in customer satisfaction, as evidenced in this methodology when selecting projects promoting productive efficiency. With regard to contemporary needs and user requirements on the methodology selected to meet this paper is the product based Cross functional team suggested methodology Feature Team model to solve problems of this model, and organizing the Cross functional team, this team but this outcome (product) basis, were examined for the model that points to progress the development across multiple product as a functional unit, value-driven agile project through the Skills-based model and proposed a difference. And it examined the Agile Maturity metrics. PRINCE2 Agile Health-check entries future development direction of Agile techniques is a requirement of the project outset has studied the subject objective evaluation by the assumption that they can be changed at any time, not fixed this way and for the project team through research The proposed.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1215-1220
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• 2003

People's Republic of China is one of the most rapidly developing countries in the world today. There is a great demand on highly actual and accurate spatial information of the whole country, especially of West China which becomes the focus of development of the Chinese government right now and in the next years, but where still not enough topographic maps are available. This raises great challenges to the surveying and mapping community in China. Facing the new challenges the Chinese Academy of Surveying and Mapping (CASM) started its pioneer work early 2002 to explore new techniques and technologies available today toward increasing the map productivity. With import of a CCNS/AEROcontrol system in November 2002 the first DGPS/IMU-based photogrammetric project in China was successfully accomplished jointly by CASM and the Germany-based companies IGI and Techedge. Two photogrammetric blocks of 1:4,000 and 1:20,000 photo scale, respectively, were flown in Anyang, China. Direct georeferencing and integrated sensor orientation were conducted. Results achieved were proven by using ground check points and compared with those of aerial triangulation. Orthophotos generated based on direct georeferencing shows the high efficiency and quality, and thus proved the promise of the new technology. Furthermore several DGPS/IMU-based photogammetric projects was accomplished one by one and a big project of more than 100,000 km2 in the Inner Mongolia will be started in August 2003. The paper presents experiences with DGPS/IMU-based photogrammetry in China. Results achieved in concrete projects are shown and evaluated. Politic and technical specialties in China are discussed. Conclusions outline the potential of DGPS/IMU-based photogrammetric production in China.

• Journal of Korean Academy of Nursing
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• v.49 no.5
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• pp.538-549
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• 2019

Purpose: This study aimed to explore and compare the knowledge structure of pain management nursing research, between Korea and other countries, applying a text network analysis. Methods: 321 Korean and 6,685 international study abstracts of pain management, published from 2004 to 2017, were collected. Keywords and meaningful morphemes from the abstracts were analyzed and refined, and their co-occurrence matrix was generated. Two networks of 140 and 424 keywords, respectively, of domestic and international studies were analyzed using NetMiner 4.3 software for degree centrality, closeness centrality, betweenness centrality, and eigenvector community analysis. Results: In both Korean and international studies, the most important, core-keywords were "pain," "patient," "pain management," "registered nurses," "care," "cancer," "need," "analgesia," "assessment," and "surgery." While some keywords like "education," "knowledge," and "patient-controlled analgesia" found to be important in Korean studies; "treatment," "hospice palliative care," and "children" were critical keywords in international studies. Three common sub-topic groups found in Korean and international studies were "pain and accompanying symptoms," "target groups of pain management," and "RNs' performance of pain management." It is only in recent years (2016~17), that keywords such as "performance," "attitude," "depression," and "sleep" have become more important in Korean studies than, while keywords such as "assessment," "intervention," "analgesia," and "chronic pain" have become important in international studies. Conclusion: It is suggested that Korean pain-management researchers should expand their concerns to children and adolescents, the elderly, patients with chronic pain, patients in diverse healthcare settings, and patients' use of opioid analgesia. Moreover, researchers need to approach pain-management with a quality of life perspective rather than a mere focus on individual symptoms.

• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.335-343
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• 2019

Healthy living is an essential element of human happiness. Quality eating provides the basis for life, and the health of livestock, which provides meat and dairy products, has a direct impact on human health. In the case of calves, diarrhea is the cause of all diseases.In this paper, we use a sensor to measure calf 's biometric data to diagnose calf diarrhea. The collected biometric data is subjected to a preprocessing process for use as meaningful information. We measure calf birth history and calf biometrics. The ontology is constructed by inputting environmental information of housing and biochemistry, immunity, and measurement information of human body for disease management. We will build a knowledge base for predicting calf diarrhea by predicting calf diarrhea through logical reasoning. Predict diarrhea with the knowledge base on the name of the disease, cause, timing and symptoms of livestock diseases. These knowledge bases can be expressed as domain ontologies for parent ontology and prediction, and as a result, treatment and prevention methods can be suggested.

• Journal of Radiation Protection and Research
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• v.36 no.1
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• pp.28-34
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• 2011

The measurement-based verification for intensity modulated radiation therapy (IMRT) is a time-and labor-consuming procedure. Instead, this study aims to develop a MU fluence reconstruction method for IMRT QA. Total actual fluences from treatment planning system (TPS, Eclipse 8.6, Varian) were selected as a reference. Delivered leaf positions according to MU were extracted by the dynalog file generated after IMRT delivery. An in-house software was develop to reconstruct MU fluence from the acquired delivered leaf position data using MATLAB. We investigated five patient's plans delivered by both step-and-shoot IMRT and sliding window technologies. The total actual fluence was compared with the MU fluence reconstructed by using commercial software (Verisoft 3.1, PTW) and gamma analysis method (criteria: 3%/3 mm and 2%/1 mm). Gamma pass rates were $97.8{\pm}1.33$% and the reconstructed fluence was shown good agreement with RTP-based actual fluence. The fluence from step and shoot IMRT was shown slightly higher agreement with the actual fluence than that from sliding window IMRT. If moving from IMRT QA measurements toward independent computer calculations, the developed method can be used for IMRT QA. A point dose calculation method from reconstructed fluences is under development for the routine IMRT QA purpose.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.12
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• pp.489-498
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• 2022

Recently, the textile industry, which is labor-intensive, is attempting to reduce process costs and optimize quality through artificial intelligence. However, the fiber spinning process has a high cost for data collection and lacks a systematic data collection and processing system, so the amount of accumulated data is small. In addition, data imbalance occurs by preferentially collecting only data with changes in specific variables according to the purpose of fiber spinning, and there is an error even between samples collected under the same fiber spinning conditions due to difference in the measurement environment of physical properties. If these data characteristics are not taken into account and used for AI models, problems such as overfitting and performance degradation may occur. Therefore, in this paper, we propose an outlier handling technique and data augmentation technique considering the characteristics of the spinning process data. And, by comparing it with the existing outlier handling technique and data augmentation technique, it is shown that the proposed technique is more suitable for spinning process data. In addition, by comparing the original data and the data processed with the proposed method to various models, it is shown that the performance of the tensile tenacity and elongation prediction model is improved in the models using the proposed methods compared to the models not using the proposed methods.

• International Journal of Highway Engineering
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• v.6 no.4 s.22
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• pp.75-89
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• 2004

Long term performance of concrete pavement significantly depends on the given construction and environmental condition. It means that random cracks and extreme crack width due to inappropriate quality control at the early age might lead to decreasing the pavement service life. The temperature and moisture during the construction, cement and aggregate types, curing condition are major components to affect the quality of the concrete pavement at the early age. First of all, the high temperature differential, that is made by increasing air temperature and the heat of cement hydration, is known as the major contributor to severe cracks. In this study, tent covering was used for controlling temperature of the concrete slab. The field measurement data indicates that the effect of the tent covering is very significant to decrease possibilities of random crack occurrence and curling stress and enhance the long-term concrete strength. HIPERPAV(High PERformance PAVing software), a program predicting the strength and stress of an earty-age concrete pavement (72 hour after placement), is used for simulating the effects of tent covering. The HIPERPAVE results showed that the section with the tent covering has higher reliability than the section without the tent covering by 22.5%. In details, reliability is increased 72.5% (without the tent covering) to 95% (with the tent covering).

• Journal of radiological science and technology
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• v.21 no.1
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• pp.35-39
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• 1998

We analyzed image factors to determine the characteristic factors that need for intelligent replenishment system of the auto film processor. We processed the serial 300 sheets of radiographic films of chest phantom without replenishment of developing and fixation replenisher. We took the digital data by using film digitizer which scaned the films and automatically summed up the pixel values of the films. We analyzed characteristic curves, average gradients and relative speeds of individual film using densitometer and step densitometry. We also evaluated the pH of developer, fixer, and washer fluid with digital pH meter. Fixer residual rate and washing effect were measured by densitometer using the reagent methods. There was no significant reduction of the digital density numbers of the serial films without replenishment of developer and fixer. The average gradients were gradually decreased by 0.02 and relative speeds were also gradually decreased by 6.96% relative to initial standard step-densitometric measurement. The pHs of developer and fixer were reflected the inactivation of each fluid. The fixer residual rates and washing effects after processing each 25 sheets of films were in the normal range. We suggest that the digital data are not reliable due to limitation of the hardware and software of the film digitizer. We conclude that average gradient and relative speed which mean the film's contrast and sensitivity respectively are reliable factors for determining the need for the replenishment of the auto film processor. We need more study of simpler equations and programming for more intelligent replenishment system of the auto film processor.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.13-20
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• 2022

IEEE 802.11ay Wi-Fi is the next generation wireless technology and operates in mmWave band. It supports the MU-MIMO (Multiple User Multiple Input Multiple Output) transmission in which an AP (Access Point) can transmit multiple data streams simultaneously to multiple STAs (Stations). To this end, the AP should perform MU-MIMO beamforming training with the STAs. For efficient MU-MIMO beamforming training, it is important for the AP to estimate signal strength measured at each STA at which multiple beams are used simultaneously. Therefore, in the paper, we propose a deep learning-based link quality estimation scheme. Our proposed scheme estimates the signal strength with high accuracy by utilizing a deep learning model pre-trained for a certain indoor or outdoor propagation scenario. Specifically, to estimate the signal strength of the multiple concurrent beams, our scheme uses the signal strengths of the respective single beams, which can be obtained without additional signaling overhead, as the input of the deep learning model. For performance evaluation, we utilized a Q-D (Quasi-Deterministic) Channel Realization open source software and extensive channel measurement campaigns were conducted with NIST (National Institute of Standards and Technology) to implement the millimeter wave (mmWave) channel. Our simulation results demonstrate that our proposed scheme outperforms comparison schemes in terms of the accuracy of the signal strength estimation.