• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.2
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• pp.17-24
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• 2023

A post-processing technique for the measurement signal of a solenoid-type sensor is introduced. The solenoid-type sensor nondestructively evaluates an external tendon of prestressed concrete using the total flux leakage (TFL) method. The TFL solenoid sensor consists of primary and secondary coils. AC electricity, with the shape of a sinusoidal function, is input in the primary coil. The signal proportional to the differential of the input is induced in the secondary coil. Because the amplitude of the induced signal is proportional to the cross-sectional area of the tendon, sectional loss of the tendon caused by ruptures or corrosion can be identified by the induced signal. Therefore, it is important to extract amplitude information from the measurement signal of the TFL sensor. Previously, the amplitude was extracted using local maxima, which is the simplest way to obtain amplitude information. However, because the sampling rate is dramatically decreased by amplitude extraction using the local maxima, the previous method places many restrictions on the direction of TFL sensor development, such as applying additional signal processing and/or artificial intelligence. Meanwhile, the proposed method uses amplitude demodulation to obtain the signal amplitude from the TFL sensor, and the sampling rate of the amplitude information is same to the raw TFL sensor data. The proposed method using amplitude demodulation provides ample freedom for development by eliminating restrictions on the first coil input frequency of the TFL sensor and the speed of applying the sensor to external tension. It also maintains a high measurement sampling rate, providing advantages for utilizing additional signal processing or artificial intelligence. The proposed method was validated through experiments, and the advantages were verified through comparison with the previous method. For example, in this study the amplitudes extracted by amplitude demodulation provided a sampling rate 100 times greater than those of the previous method. There may be differences depending on the given situation and specific equipment settings; however, in most cases, extracting amplitude information using amplitude demodulation yields more satisfactory results than previous methods.

• The korean journal of orthodontics
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• v.27 no.5 s.64
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• pp.791-800
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• 1997

Sixty premolars extracted for orthodontic treatment were divided into four groups, and the residual resin was removed with four different rotary finishing instruments at a fixed speed of $18,500{\pm}300 rpm$ on the low speed handpiece. The instruments were G1; No.169L carbide fissure bur, G2: No.2 round bur, G3; No.4 round bur, G4: No.8 round bur. Then, the enamel received a S-second polishing with a rubber cup and a pumice. To find the extent of loss on the enamel at this point, prophylaxis was done with the rubber cup and pumice prior to bonding of the bracket(P1) and removal of residual resin by means of appropriate procedure applicable to each respective group(P2) followed. The final polishing was done with the rubber cup and pumice(P3), and the enamel surface roughness was measured each by the surface measuring instrument. The whole process was observed under a scanning electron microscope to gain the following results: At P2, the enamel surface roughness in G1 showed most smoothly with $2.60{\pm}0.55{\mu}m;\;in\;G2,\;3.24{\pm}0.80{\mu}m;\;in\;G3,\;3.44{\pm}0.94{\mu}m;\;in\;G4,\;3.89{\pm}0.54{\mu}m$, the roughest. G2 and G3 showed no statistical significance(P>0.05). At P3, the enamel surface roughness in G1 showed most smoothly with $2.29{\pm}0.47{\mu}m;\;in\;G2,\;2.44{\pm}0.56{\mu}m;\;in\;G3,\;2.44{\pm}0.56{\mu}m;\;in\;G4,\;2.92{\pm}0.43{\mu}m$, the roughest. G1 vs G2, G3, and G2 vs G3 had no statistical significances(p>0.05). In all groups, P2 and P3 showed rougher in surface roughness than P1, and P2 rougher than P3(p<0.01). In a case of 5-second prophylaxis with the rubber cup and the pumice on a virgin, normal enamel, fine scratches were found under the scanning electron microscope. In all four groups, unremovable gouges remained even after polishing with the ubber and pumice; residual resin was not observed with naked eye when finished with the rubber and pumice, but the resin debris was observed under the scanning electron microscope.

• Journal of the Korean Institute of Gas
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• v.23 no.6
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• pp.90-96
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• 2019

Natural gas has been regarded as one of major alternative fuels, because of the increment of mining shale gas and supplying PNG(Pipeline Natural Gas) from Russia. Thus, it needs to broaden the usage of natural gas as the increasing its supplement. In this situation, application of natural gas on the transport area is a good suggestion to reduce exhaust emissions such as CO₂(carbon dioxides) and soot from vehicles. For this reason, natural gas can be applied to SI(spark ignition) engines due to its anti-knocking and low auto-ignitibility characteristics. Recently, since turbocharged SI engine has been widely used, it needs to apply natural gas on the turbocharged SI engine. However, there is a major challenge for using natural gas on turbocharged SI engine, because it is hard to make natural gas direct injection in the cylinder, while gasoline is possible. As a result, there is a loss of fresh air when natural gas is injected by MPI (multi-point injection) method under the same intake pressure with gasoline-fueled condition. It brings the power reduction. Therefore, in this research, intake pressure was increased by controling the turbocharger system under natural gas-fueled condition to improve power output. The goal of improved power is the same level with that of gasoline-fueled condition under the maximum torque condition of each engine speed. As a result, the maximum power levels, which are the same with those of gasoline-fueled conditions, with improved brake thermal efficiency could be achieved for each engine speed (from 2,000 to 6,000 rpm) by increasing intake pressure 5-27 % compared to those of gasoline-fueled conditions.

• Journal of Bio-Environment Control
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• v.21 no.2
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• pp.95-101
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• 2012

This study was conducted to investigate the effect of climate conditions during cultivation and harvesting on the quality and storability of fresh bulb cabbage (Brassica oleracea L. var. capitata). Plug seedlings of six cabbage cultivars were transplanted to Gangneung-Wonju University high elevation research station in Gangwon province (780 m above sea level, lat. $37.5^{\circ}N$.) and harvested with four different harvest times like August 3 ($1^{st}$), August 13 ($2^{nd}$), August 23 ($3^{rd}$), and September 10 ($4^{th}$), respectively from 50 days after transplanting. Weight loss, Hunter color factors, firmness, and soluble solids content (SSC) of the cabbage bulbs were investigated during storage at $3^{\circ}C$ (85% RH) and $25^{\circ}C$ (60% RH). Decreased bulb weight and poor quality cabbages were apparent at the late transplanting (July 14) and harvest (September 10) respectively. Quality index such as firmness and SSC at August 23 ($3^{rd}$) harvested cabbage was better than August 3 ($1^{st}$) and August 13 ($2^{nd}$) cabbages due to the good weather condition just before harvesting. The cv. 'Speed king' and 'Minix 40' showed good qualities among the cultivars, especially when the bulbs were harvested during sunny day conditions from one week before harvesting. Also SSC was influenced by weather condition before harvesting rather than transplanting date, while firmness was influenced by transplanting and harvest date. However, the differences among the cultivars were not significant. The potential of storage as maintaining the quality was different, depending on weather conditions at harvest time. Generally the storage periods of six cultivars were around 3~5 days and 9~10 days at room and low temperature, respectively. However, the August 3 ($1^{st}$) harvested cabbage lost their marketable quality very fast because of rainy and cloudy weather condition before harvesting and also storability of bulbs was 2 days and 4 days at room temperature and $3^{\circ}C$, respectively. Quality index was also not significant difference among cultivars.

• Journal of the Korean Institute of Gas
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• v.24 no.2
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• pp.1-8
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• 2020

Centrifugal pump is a facility that transfers energy to fluid through centrifugal force, which is usually generated by rotating the impeller at high speed, and is a major process facility used in many LNG production bases such as vaporization seawater pump, industrial water and fire extinguishing pump using seawater. to be. Currently, pumps in LNG plant sites are subject to operating conditions that vary depending on the amount of supply desired by the customer for a long period of time. Pumps in particular occupy a large part of the consumption strategy at the plant site, and if the optimum operation condition is not available, it can incur enormous energy loss in long term plant operation. In order to solve this problem, it is necessary to identify the performance deterioration factor through the flow analysis and the result analysis according to the fluctuations of the pump's operating conditions and to determine the optimal operation efficiency. In order to evaluate operation efficiency through experimental techniques, considerable time and cost are incurred, such as on-site operating conditions and manufacturing of experimental equipment. If the performance of the pump is not suitable for the site, and the performance of the pump needs to be reduced, a method of changing the rotation speed or using a special liquid containing high viscosity or solids is used. Especially, in order to prevent disruptions in the operation of LNG production bases, a technology is required to satisfy the required performance conditions by processing the existing impeller of the pump within a short time. Therefore, in this study, the rotation difference of the pump was applied to the ANSYS CFX program by applying the modified 3D modeling shape. In addition, the results obtained from the flow analysis and the curve fitting toolbox of the MATLAB program were analyzed numerically to verify the outer diameter correction theory.

• Journal of the Korean Society for Marine Environment & Energy
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• v.17 no.1
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• pp.27-35
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• 2014

The headspace solid-phase microextraction (HS-SPME) followed by gas chromatography/mass spectrometry procedure has been developed for the simultaneous determination of petroleum aromatic hydrocarbons such as benzene, toluene, ethylbenzene and xylene isomers (BTEX) and polycyclic aromatic hydrocarbons (PAHs) in seawater. The advantages of SPME compared to traditional methods of sample preparation are ease of operation, reuse of fiber, portable system, minimal contamination and loss of the sample during transport and storage. SPME fiber, extraction time, temperature, stirring speed, and GC desorption time were key extraction parameters considered in this study. Among three kinds of SPME fibers, i.e., PDMS ($100{\mu}m$), CAR/PDMS ($75{\mu}m$), and PDMS/DVB ($65{\mu}m$), a $65{\mu}m$ PDMS/DVB fiber showed the most optimal extraction efficiencies covering molecular weight ranging from 78 to 202. Other extraction parameters were set up using $65{\mu}m$ PDMS/DVB. The final optimized extraction conditions were extraction time (60 min), extraction temperature (50), stirring speed (750 rpm) and GC desorption time (3 min). When applied to artificially contaminated seawater like water accommodated fraction, our optimized HS-SPME-GC/MS showed comparable performances with other conventional method. The proposed protocol can be an attractive alternative to analysis of BTEX and PAHs in seawater.

• Journal of agriculture & life science
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• v.53 no.5
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• pp.137-143
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• 2019

To manufacturing of solid fuel by reuse of the wastes, the drying unit which have 500 kg/hr of drying capacity was developed and experimentally evaluate the performance. The spinach grown in Nam-hae island were used for the experiments and investigated of the heated-air drying characteristics as the inlet amount of raw materials, raw material stirring status, conveying type and drying time. The drying air heated by the energy derived from the steam which is supplied from the incineration plant. The moisture contents of raw materials were measured 85.65%. The inlet flow rate of drying air made a difference as the depth of the raw materials loaded on the drying unit and temperature has showed 108~144℃. The drying speed of the mixed drying more than doubled as that of non mixed drying under the same drying type, inlet amount, drying time and drying air temperature. In each experiment, the drying capacity have showed over 500 kg/hr. A drying efficiency of the ratio of drying consumption energy to input energy was 33.46%, lower than the average of 57.76% for the 157 conventional dryers. Because developed dryer must have a drying time of less than one hour, it is considered that the dry efficiency has been reduced due to the loss of wind volume during drying. If waste heat from incineration plant is used as a direct heat source, the dry air temperature is expected to be at least 160℃, greatly improving the drying capacity.

• Journal of Bio-Environment Control
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• v.33 no.1
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• pp.30-36
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• 2024

This study was conducted to determine the optimal working conditions when a recently developed blower-type onion stem cutter is utilized for cutting onion leaves at harvest time. The June 20 leaf cutting treatment group had the highest leaf dryness among the treatment groups (leaf dryness: 66.3%; leaf moisture content: 50.5%); the residual leaf length was 6.7 ± 3.5 cm. It is considered to have the best mechanical leaf cutting performance among the treatment groups because it is included in the optimal range of 4-10 cm. The average working speed of mechanical onion leaf cutting using the stem cutter was 0.17 m·s^-1, which is approximately 3.4 times faster than the average working speed of 0.05 m·s^-1 in the human leaf cutting treatment group. This is expected to save approximately 2.6 hours compared to human labor (based on one person) when working on a 10a area using this machine. In addition, the incidence of damaged bulbs in the machine leaf cutting treatment group was 1.3%, compared to 0.0% in the manual leaf cutting treatment group. This suggests that the mechanical leaf cutting treatment group had a higher average onion bulb decay rate during storage than the manual leaf cutting treatment group. When the storage characteristics of each treatment group were examined, the decay rate by bulb part (leaf connected or root connected) after 8 months of storage was higher in the treatment group with a residual leaf length of less than 5.0 cm after mechanical leaf cutting than in the treatment with a residual leaf length of more than 5.0 cm. This is thought to be due to the fact that treatments with a residual leaf length of less than 5.0 cm are more susceptible to infection by pathogens that cause decay during storage than treatments with a residual leaf length of 5.0 cm or more. Based on the results of this experiment, performance target of the experimental machine (residual leaf length after operation: 5 cm), and existing research on the optimal residual leaf length for onion harvesting, it is recommended to cut onion leaves so that the residual leaf length is 5-10 cm when using the stem cutter.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.147-157
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• 2013

With the advent of the digital environment that can be accessed anytime, anywhere with the introduction of high-speed network, the free distribution and use of digital content were made possible. Ironically this environment is raising a variety of copyright infringement, and product images used in the online shopping mall are pirated frequently. There are many controversial issues whether shopping mall images are creative works or not. According to Supreme Court's decision in 2001, to ad pictures taken with ham products is simply a clone of the appearance of objects to deliver nothing but the decision was not only creative expression. But for the photographer's losses recognized in the advertising photo shoot takes the typical cost was estimated damages. According to Seoul District Court precedents in 2003, if there are the photographer's personality and creativity in the selection of the subject, the composition of the set, the direction and amount of light control, set the angle of the camera, shutter speed, shutter chance, other shooting methods for capturing, developing and printing process, the works should be protected by copyright law by the Court's sentence. In order to receive copyright protection of the shopping mall images by the law, it is simply not to convey the status of the product, the photographer's personality and creativity can be recognized that it requires effort. Accordingly, the cost of making the mall image increases, and the necessity for copyright protection becomes higher. The product images of the online shopping mall have a very unique configuration unlike the general pictures such as portraits and landscape photos and, therefore, the general image watermarking technique can not satisfy the requirements of the image watermarking. Because background of product images commonly used in shopping malls is white or black, or gray scale (gradient) color, it is difficult to utilize the space to embed a watermark and the area is very sensitive even a slight change. In this paper, the characteristics of images used in shopping malls are analyzed and a watermarking technology which is suitable to the shopping mall images is proposed. The proposed image watermarking technology divide a product image into smaller blocks, and the corresponding blocks are transformed by DCT (Discrete Cosine Transform), and then the watermark information was inserted into images using quantization of DCT coefficients. Because uniform treatment of the DCT coefficients for quantization cause visual blocking artifacts, the proposed algorithm used weighted mask which quantizes finely the coefficients located block boundaries and coarsely the coefficients located center area of the block. This mask improves subjective visual quality as well as the objective quality of the images. In addition, in order to improve the safety of the algorithm, the blocks which is embedded the watermark are randomly selected and the turbo code is used to reduce the BER when extracting the watermark. The PSNR(Peak Signal to Noise Ratio) of the shopping mall image watermarked by the proposed algorithm is 40.7~48.5[dB] and BER(Bit Error Rate) after JPEG with QF = 70 is 0. This means the watermarked image is high quality and the algorithm is robust to JPEG compression that is used generally at the online shopping malls. Also, for 40% change in size and 40 degrees of rotation, the BER is 0. In general, the shopping malls are used compressed images with QF which is higher than 90. Because the pirated image is used to replicate from original image, the proposed algorithm can identify the copyright infringement in the most cases. As shown the experimental results, the proposed algorithm is suitable to the shopping mall images with simple background. However, the future study should be carried out to enhance the robustness of the proposed algorithm because the robustness loss is occurred after mask process.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.