• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2480-2487
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• 2011

As sensor technology grows up in fields such as environmental hazards detecting system, ubiquitous sensor network, intelligent robot, the sensing and detecting system for sensor is increasing. The sensor data is measured by change of chemical and physical status. Because of decrepit sensor or various sensing environment, it is problem that sensor data is inaccurate result. So the reliability of sensor data is essential. In this paper, we proposes a reliable sensor signal processing platform for various sensor. To improve reliability, we use same sensors in multiple array structure. As sensor data is corrected by spatial and temporal relation signal processing algorithm for measured sensor data, reliability of sensor data can be improved. The exclusive protocol between platform components is designed in order to verify sensor data and sensor state in various environment.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.1
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• pp.255-259
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• 2016

Background: Reliable and validated instruments are needed in order to study the quality of life in myeloma patients. This study aimed to translate and explore the psychometric properties of the European Organisation for Research and Treatment of Cancer (EORTC) myeloma module (QLQ-MY20) in Iranian patients. Materials and Methods: Two hundred and fifteen patients with multiple myeloma (MM) were recruited from Imam Khomeini Hospital, Tehran. A standard forward-backward translation procedure was implemented. Participating patients were asked to complete the EORTC QLQ-C30 and the QLQ-MY20 three times, at study entry, after two weeks, and again after three months. Data were tested for the range of measurement, internal consistency, test-retest reliability, known group comparison, responsiveness and factor structure. Results: Mean age of the patients was 60.7 years. No floor and ceiling effects were seen for the QLQ-MY20. Cronbach's ${\alpha}$ was greater than 0.80 for all three multi-item scales (ranging from 0.82 to 0.93). All four scales had test-retest reliability of 0.85 or greater. Results of the confirmatory factor analysis that the hypothesized 3-scale measurement model of the QLQ-MY20. Moreover, the Persian version for the QLQ-MY20 differentiated between subgroups of the patients in terms of beta-2 microglobulin, fracture and performance status. The responsiveness of the QLQ-MY20 to change over time was confirmed within 3 months. Conclusions: the results of our study indicate that our Iranian version of the QLQ-MY20 is a feasible, reliable and valid questionnaire for assessing the condition-specific quality of life of patients with MM.

• Journal of Biomedical Engineering Research
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• v.25 no.5
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• pp.351-359
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• 2004

Velocity-type repisratory air flow transducer measures dynamic pressure converted from air velocity based on the we1l-known Bernoulli's principle. It requires multiple velocity sampling holes on the flow plane. Measurement error theoretica1ly estimated by computer simulation was demonstrated to significantly reduce by unequally locating the velocity sampling holes. The flow plane was divided into multiple equi-area rings and the sampling holes were located on the circles also equally dividing each ring's area, which decreased measurement error down to 1/5 of the simple equi-radius ring division method. Also, less than 1 ％ relative error was estimated with 4 or more sampling holes. The present technique was less sensitive by <1/2 to the velocity profile change compared to the euqi-radius sampling. Therefore, the present unequal distance velocity sampling technique should be of great use to design the structure of the velocity-type respiratory air flow transducer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1210-1220
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• 2016

As modern warfare has changed into network centered, the ability to share situational awareness among allies become a core competency for performing operational missions. In an airborne environment, it uses a tactical data link such as Link-16 for shared situational awareness. There exist problems when it shares situational awareness over the existing data link that can not allocate slots dynamically or that can not change the number of a slot to be allocated. In addition, there was a problem that can not share this failure so that failed to improves situation awareness because of finite time slot resources. In this paper, we accommodate dynamic slot allocation and changes of slot allocation with mixed structure of TDMA (time division multiple access) and random access. We propose a technique that can be used when available slots are exhausted, and a load balancing method to prevent slot allocation delay when slot requesting or message sending is concentrated on a single subframe.

• Journal of radiological science and technology
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• v.44 no.4
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• pp.327-333
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• 2021

Magnetic resonance imaging(MRI) uses strong magnetic field to image the cross-section of human body and has excellent image quality with no risk of radiation exposure. Because of above-mentioned advantages, MRI has been widely used in clinical fields. However, the noise generated in MRI degrades the quality of medical images and has a negative effect on quick and accurate diagnosis. In particular, examining a object with a detailed structure such as brain, image quality degradation becomes a problem for diagnosis. Therefore, in this study, we acquired T2 weighted 3D data of multiple sclerosis disease using BrainWeb simulation program, and used quantitative evaluation factors to find appropriate slice thickness among 1, 3, 5, and 7 mm. Coefficient of variation and contrast to noise ratio were calculated to evaluate the noise level, and root mean square error and peak signal to noise ratio were used to evaluate the similarity with the reference image. As a result, the noise level decreased as the slice thickness increased, while the similarity decreased after 5 mm. In conclusion, as the slice thickness increases, the noise is reduced and the image quality is improved. However, since the edge signal is lost due to overlapped signal, it is considered that selecting appropriate slice thickness is necessary.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1256-1263
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• 2022

With the advent of the Fourth Industrial Revolution, the amount of energy used in buildings has been increasing due to changes in the energy use structure caused by the massive spread of information-oriented equipment, climate change and greenhouse gas emissions. For the efficient use of energy, it is necessary to have a plan that can predict and reduce the amount of energy use according to the type of energy source and the use of buildings. To address such issues, this study presents a model embedded in a digital twin that predicts energy use in buildings. The digital twin is a system that can support a solution of urban problems through the process of simulations and analyses based on the data collected via sensors in real-time. To develop the energy use prediction model, energy-related data such as actual room use, power use and gas use were collected. Factors that significantly affect energy use were identified through a correlation analysis and multiple regression analysis based on the collected data. The proof-of-concept prototype was developed with an exhibition facility for performance evaluation and validation. The test results confirm that the error rate of the energy consumption prediction model decreases, and the prediction performance improves as the data is accumulated by comparing the error rates of the model. The energy use prediction model thus predicts future energy use and supports formulating a systematic energy management plan in consideration of characteristics of building spaces such as the purpose and the occupancy time of each room. It is suggested to collect and analyze data from other facilities in the future to develop a general-purpose energy use prediction model.

• Convergence Security Journal
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• v.23 no.5
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• pp.135-142
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• 2023

In addressing the prominent issues of climate change, resource scarcity, and environmental pollution associated with household waste, extensive research has been conducted on intelligent waste classification methods. These efforts range from traditional classification algorithms to machine learning and neural networks. However, challenges persist in effectively classifying waste in diverse environments and conditions due to insufficient datasets, increased complexity in neural network architectures, and performance limitations for real-world applications. Therefore, this paper proposes i-YOLOX as a solution for rapid classification and improved accuracy. The proposed model is evaluated based on network parameters, detection speed, and accuracy. To achieve this, a dataset comprising 10,000 samples of household waste, spanning 17 waste categories, is created. The i-YOLOX architecture is constructed by introducing the Involution channel convolution operator and the Convolution Branch Attention Module (CBAM) into the YOLOX structure. A comparative analysis is conducted with the performance of the existing YOLO architecture. Experimental results demonstrate that i-YOLOX enhances the detection speed and accuracy of waste objects in complex scenes compared to conventional neural networks. This confirms the effectiveness of the proposed i-YOLOX architecture in the detection and classification of multiple household waste objects.

• The Journal of the Acoustical Society of Korea
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• v.31 no.1
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• pp.51-61
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• 2012

In this research, we have analyzed the trend of radiation pattern variation in relation to the change of design variables such as source interval and source number for conformal array transducers arranged in equi-angle, equi-interval, and geodesic dome forms. Through statistical multiple regression analysis of the results, we derived functional forms of the side lobe level and the beamwidth in terms of the design variables. Futhermore, the structure of the array transducer was optimized to achieve the smallest side lobe level while satisfying the requirements on beam width by the GA (genetic algorithm) method. Based on the optimized results, we have determined the equi-interval form as the optimal array geometry among the three conformal array geometries.

• Bulletin of the Korean Chemical Society
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• v.35 no.3
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• pp.905-907
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• 2014

The plasma and microwave surface treatments of carbon nanotubes that loaded on plastic substrates were carried out with expecting a change of carbon nanotube dispersion by increasing treatment time. The microwave treatment process was undergone by commercial microwave oven (800 W). The electrical property was measured by hall measurement and resistance was increased by increasing $O_2$ flow rate of plasma, suggesting an improvement of carbon nanotube dispersion and a possibility of controlling the resistances of carbon nanotubes by plasma surface treatment. The resistance was increased in both polyethylene terephthalate and polyimide substrates by increasing $O_2$ flow rate. Resistance changes only slightly with different $O_2$ flow treatment in measure rho for all polyimide samples. Sheet resistance is lowest in polyimide substrate not due to high carbon nanotube loading but due to tendency to remain in elongated structure. $O_2$ or $N_2$ plasma treatments on both polyethylene terephthalate and polyimide substrates lead to increase in sheet resistance.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.3
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• pp.457-464
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• 2020

ROK Forces operate Link-11, Link-16 and Korean Tactical Data Link System with Link-K(JTDLS: Joint Tactical Data Link System). As the change from Link-11 to Link-22 approaches, in the JTDLS Completed Business will be added tactical data link processing such as Link-22. In this paper, we propose the data management structure for data from multiple tactical data links. Also, we simulate to find ways to process a lot of data quickly using Shared Memory, In-Memory DB, Self Development DB in DLP, and then we confirm the result.