• Journal of Korean Society of Environmental Engineers
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• v.22 no.12
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• pp.2175-2185
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• 2000

Respiration rate should be a reasonable state variable for the activated sludge and could be used to simulate the performance of the activated sludge process. Toxic materials are classified into three groups, competitive, noncompetitive and uncompetitive. They increase/decrease the half saturation coefficient or specific growth rate. that means decreasing of the substrate removal capacity. In this research, a pilot-scale activated sludge process was operated under extended aeration method, and a representative noncompetitive inhibitor, acidic wastewater was applied to establish a respirometry-based toxicity model. Using this model. the correlation coefficient between measured and calculated respiration rate was 0.96 when acidic wastewater(pH 3.9~5.5) was introduced continuously to the aeration tank. Even though respiration rate was decreased by toxic effect of acidic wastewater, effluent substrate concentration represented to COD was deteriorated just a little bit. It might be caused by the low ratio of readily biodegradable substrate in the input substrate. Reduction of respiration rate by decreasing of input substrate concentration was much lower than that by acidic wastewater, and hence it was estimated that the possibility of false toxic alarm caused by decreasing of substrate concentration should be low.

• Journal of the Korea Society for Simulation
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• v.25 no.2
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• pp.31-40
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• 2016

Wireless sensor networks have been used in many applications such as marine environment, army installation, etc. The sensor data is very important, because all these applications depend on sensor data. The possibility of communication failures becomes high since the surrounding environment of a wireless sense network has an sensitive effect on its communications. In particular, communication failures in underwater communications occur more frequently because of a narrow bandwidth, slow transmission speed, noises from the surrounding environments and so on. In cases of communication failures, the sensor data can be lost in the sensor data delivery process and these kinds of sensor data losses can make critical huge physical damages on human or environments in applications such as fire surveillance systems. For this reason, although a few of studies for storing and compressing sensor data have been proposed, there are lots of difficulties in actual realization of the studies due to none-existence of the framework using network communications. In this paper, we propose a framework for reducing loss of the sensor data and analyze its performance. The our analyzed results in non-framework application show a decreasing data recovery rate, T/t, as t time passes after a network failure, where T is a time period to fill the storage with sensor data after the network failure. Moreover, all the sensor data generated after a network failure are the errors impossible to recover. But, on the other hand, the analyzed results in framework application show 100% data recovery rate with 2~6% data error rate after data recovery.

• Geophysics and Geophysical Exploration
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• v.10 no.1
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• pp.50-59
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• 2007

The advent of towed geo-electrical array surveying on water and land has resulted in datasets of magnitude approaching that of airborne electromagnetic surveying and most suited to 1D inversion. Robustness and complete automation is essential if processing and reliable interpretation of such data is to be viable. Sharp boundaries such as river beds and the top of saline aquifers must be resolved so use of smoothness constraints must be minimised. Suitable inversion algorithms must intelligently handle low signal-to-noise ratio data if conductive basement, that attenuates signal, is not to be misrepresented. A noise-level aware inversion algorithm that operates with one elastic thickness layer per electrode configuration has been coded. The noise-level aware inversion identifies if conductive basement has attenuated signal levels so that they are below noise level, and models conductive basement where appropriate. Layers in the initial models are distributed to span the effective depths of each of the geo-electric array quadrupoles. The algorithm works optimally on data collected using geo-electric arrays with an approximately exponential distribution of quadrupole effective depths. Inversion of data from arrays with linear electrodes, used to reduce contact resistance, and capacitive-line antennae is plausible. This paper demonstrates the effectiveness of the algorithm using theoretical examples and an example from a salt interception scheme on the Murray River, Australia.

• The Journal of Korean Academy of Prosthodontics
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• v.58 no.4
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• pp.328-334
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• 2020

Clinical remounting of complete denture is performed to refine occlusal harmony in maxillo-mandibular relation. It has been reported that patients who used adjusted dentures with clinical remounting felt less complications such as pain and discomfort in mastication. The purpose of this study was to assess effects of clinical remounting with case series. Seven patients with existing complete prosthesis were included. Clinical remounting procedure was done through interocclusal relation recording. In addition, occlusal force was measured with pressure indicating sensor and occlusal contact areas were evaluated with photo occlusion analysis. Occlusal contact areas of prosthesis were enlarged, while bite pressure was not increased. Hit and slide phenomenon of prosthesis was reduced concurrently. Clinical remounting procedure improved denture stability and increased occlusal contact area. Therefore, clinical remounting should be considered.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1A
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• pp.93-98
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• 2004

Serial ATA interface Is inexpensive comparatively and performance is superior. So it is suitable technology in demand that now require data transmission and throughput of high speed. This paper describes a design and implementation of Serial ATA Link layer about error detection and 8b/10b encoder/decoder for DC balance in frequency 150MHz. The 8b/10b Encoder is partitioned into a 5b/6b plus a 3b/4b coder. The logical model of the block is described by using Verilog HDL at register transistor level and the verified HDL is synthesized using standard cell libraries. And it is fabricated with $0.35{\mu}m$ Standard CMOS Cell library and the chip size is about $1500{\mu}m\;*\;1500{\mu}m$. The function of this chip has been verified and tested using testboard with FPGA equipment and IDEC ATS2 test equipment. It is used to frequency of 100MHz in verification processes and supply voltage 3.3V. The result of testing is well on the system clock 100MHz. The designed and verified each blocks may be used IP in the field of high speed serial data communication.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.5
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• pp.38-48
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• 2007

In ubiquitous environment, sensor networks that sense and transmit surrounding data without human intervention will become more important. If sensors are installed for detecting vehicles and measuring their speed in the road and that real-time information is given to drivers, it will be very effective for enhancing safety and controlling traffic in the road. In this paper, we proposed a new reliable and real-time sensor MAC protocol between AP and sensor nodes in order to provide real-time traffic flow information based on ubiquitous sensor networks. The proposed MAC allocates one TDMA slot for each sensor node on the IEEE 802.15.4 based channel structure, introduces relayed communication for distant sensors, and adopts a frame structure that supports retransmission for the case of errors. In addition, the proposed MAC synchronizes with AP by using beacon and adopts a hybrid tracking mode that supports economic power consumption according to various traffic situations, We implemented a simulator for the proposed MAC by using sim++ and evaluated various performances. The simulation results show that the proposed MAC reduces the power consumption and reveals excellent performance in real-time application systems.

• Journal of the Korean Geographical Society
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• v.43 no.1
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• pp.154-169
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• 2008

Geography textbooks often have treated the world as a collection of independent nations. Also, many scholars have warned of ethnocentric bias in geography textbooks. Global education that emphasizes world interdependence and pursues global perspectives offers some possibilities to go beyond the status quo of current World Geography textbooks. The primary objective of this study is to analyze current US World Geography textbooks in terms of global education. A secondary objective is to explore a framework for rereading World Geography textbooks critically. This interpretive qualitative case study indicates that US World Geography textbooks maintain an imperialist and American-centered perspective. Especially, the case of Korea shows that other places and people are underrepresented through dichotomy, negative attitude and exclusion, misconception and stereotyping, and simplification in textbooks. Therefore, we need to detect conscious and unconscious fallacy and bias, to understand the world view and experiences of underrepresented people, and to deal with controversial global issues from diverse perspectives through global perspectives and post-colonial perspectives of global education.

• Geophysics and Geophysical Exploration
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• v.1 no.3
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• pp.176-182
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• 1998

The borehole radar reflection survey can image the underground structure with high resolution, however, we cannot get any information on the orientation of the reflectors with dipole antenna alone. The direction-finding antenna system is commonly used to give the solution to the problem. However, the interpretation of the data from direction- finding antenna may be time-consuming, and sometimes have ambiguities in the sense of precise determination of the azimuth. To solve the problem, we developed the automatic azimuth finding scheme of reflectors in borehole radar reflection data using direction-finding antenna. The algorithm is based on finding the azimuthal angle possibly showing the maximum reflection amplitude in the least-squared error sense. The developed algorithm was applied to the field data acquired in quarry mine. It was possible to locate nearly all of the reflectors in three dimensional fashion, which coincide with the known geological structures and man-made discontinuities.

• Journal of Energy Engineering
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• v.27 no.4
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• pp.103-110
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• 2018

In this paper, we introduce evaluation method of time series prediction model with new approach of Mean Absolute Percentage Error(hereafter MAPE) and Symmetric Mean Absolute Percentage Error(hereafter sMAPE). There are some problems using MAPE and sMAPE. First MAPE can't evaluate Zero observation of dataset. Moreover, when the observed value is very close to zero it evaluate heavier than other methods. Finally it evaluate different measure even same error between observations and predicted values. And sMAPE does different evaluations are made depending on whether the same error value is over-predicted or under-predicted. And it has different measurement according to the each sign, even if error is the same distance. These problems were solved by Maximum Mean Absolute Percentage Error(hereafter mMAPE). we used the absolute maximum of observed value as denominator instead of the observed value in MAPE, when the value is less than 1, removed denominator then solved the problem that the zero value is not defined. and were able to prevent heavier measurement problem. Also, if the absolute maximum of observed value is greater than 1, the evaluation values of mMAPE were compared with those of the other evaluations. With Beijing PM2.5 temperature data and our simulation data, we compared the evaluation values of mMAPE with other evaluations. And we proved that mMAPE can solve the problems that we mentioned.

• Journal of Appropriate Technology
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• v.5 no.2
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• pp.70-81
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• 2019

The garment industry is one of the most labor-intensive manufacturing industries, with its sewing process relying almost entirely on manual labor. Its costs highly depend on the efficiency of this production line and thus is crucial to determine the production rate in real-time for line balancing. However, current production tracking methods are costly and make it difficult for many Small and Medium-sized Enterprises (SMEs) to implement them. As a result, their reliance on manual counting of finished products is both time consuming and prone to error, leading to high manufacturing costs and inefficiencies. In this paper, a production tracking system that uses the sewing machines' energy consumption data to track and count the total number of sewing tasks completed through Convolutional Neural Network (CNN) classifiers is proposed. This system was tested on two target sewing tasks, with a resulting maximum classification accuracy of 98.6%; all sewing tasks were detected. In the developing countries, the garment sewing industry is a very important industry, but the use of a lot of capital is very limited, such as applying expensive high technology to solve the above problem. Applied with the appropriate technology, this system is expected to be of great help to the garment industry in developing countries.