• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.139-147
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• 2023

The metal bush assembling process is a process of inserting and compressing a metal bush that serves to reduce the occurrence of noise and stable compression in the rotating section. In the metal bush assembly process, the head diameter defect and placement defect of the metal bush occur due to metal bush omission, non-pressing, and poor press-fitting. Among these causes of defects, it is intended to prevent defects due to omission of the metal bush by using signals from sensors attached to the facility. In particular, a metal bush omission is predicted through various data mining techniques using left load cell value, right load cell value, current, and voltage as independent variables. In the case of metal bush omission defect, it is difficult to get defect data, resulting in data imbalance. Data imbalance refers to a case where there is a large difference in the number of data belonging to each class, which can be a problem when performing classification prediction. In order to solve the problem caused by data imbalance, oversampling and composite sampling techniques were applied in this study. In addition, simulated annealing was applied for optimization of parameters related to sampling and hyper-parameters of data mining techniques used for bush omission prediction. In this study, the metal bush omission was predicted using the actual data of M manufacturing company, and the classification performance was examined. All applied techniques showed excellent results, and in particular, the proposed methods, the method of mixing Random Forest and SA, and the method of mixing MLP and SA, showed better results.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.811-827
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• 2018

The purpose of this study is to compare machine learning algorithm and deep learning algorithm in crop classification using multi-temporal remote sensing data. For this, impacts of machine learning and deep learning algorithms on (a) hyper-parameter and (2) training sample size were compared and analyzed for Haenam-gun, Korea and Illinois State, USA. In the comparison experiment, support vector machine (SVM) was applied as machine learning algorithm and convolutional neural network (CNN) was applied as deep learning algorithm. In particular, 2D-CNN considering 2-dimensional spatial information and 3D-CNN with extended time dimension from 2D-CNN were applied as CNN. As a result of the experiment, it was found that the hyper-parameter values of CNN, considering various hyper-parameter, defined in the two study areas were similar compared with SVM. Based on this result, although it takes much time to optimize the model in CNN, it is considered that it is possible to apply transfer learning that can extend optimized CNN model to other regions. Then, in the experiment results with various training sample size, the impact of that on CNN was larger than SVM. In particular, this impact was exaggerated in Illinois State with heterogeneous spatial patterns. In addition, the lowest classification performance of 3D-CNN was presented in Illinois State, which is considered to be due to over-fitting as complexity of the model. That is, the classification performance was relatively degraded due to heterogeneous patterns and noise effect of input data, although the training accuracy of 3D-CNN model was high. This result simply that a proper classification algorithms should be selected considering spatial characteristics of study areas. Also, a large amount of training samples is necessary to guarantee higher classification performance in CNN, particularly in 3D-CNN.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.616-621
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• 2006

A began of this study is to verify Spontaneous Acoustic Field Reproduction System(SAFRS), developed as an embodiment of creating agreeable sound environment, with evaluation on the field application. SAFRS is a system to sense changes of surroundings and produce sounds, which can go well with environment elements sensed by the system in to the space. The sound which can go well with environment elements is sound which judged by individual evaluation to be so, the classification of the preferred sounds according to the mood of the space was suggested in the former study. So, SAFRS was applied into the Square of D University to evaluate effectiveness of the system. The executed evaluations were 1) evaluation on sounds perception, frequency, volume and matchability with the space, 2) image evaluation on the square and sound environment and 3) evaluation on sound environment with existing sounds, fountains sound, sound produced by SAFRS, and both fountains sound and sound produced by SAFRS. Verifying SAPRS of field application was deduced from those evaluations. Theresultsofthestudyarefollowing: Though the system was applied into the space, the volume of the sounds shouldn't be too high. And with visual surroundings, the effectiveness of the system would be increased. At the results of four evaluations, the result of day evaluation is; both fountains sound and sound produced by SAFRS>fountains sound>sound produced by SAFRS>existing sounds, the result of night evaluation is; sound produced by SAFRS>both fountains sound and sound produced by SAFRS>fountains sound>existing sounds and these results pointed out that sounds environment produced by the system was highly evaluated due to less background sounds.

• Journal of Oral Medicine and Pain
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• v.16 no.1
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• pp.85-93
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• 1991

In this study, 88 dental students were examined to evaluate the relationship between occlusal states and TM disorders for the epidemiologic study of TM disorders. The clinical evaluation were composed of mandibular movement, TMJ noise, occlusal states and muscle palpation. The following results were disclosed. 1. The frequencies of pain on mandibular movement were 3.4% on maximum opening, 1.13% on protrusion and no pain on laterotrusion. 2. The frequencies on TMJ sound were 21.6% in click, 1.13% in crepitus. 3. The frequency of tenderness on palpation was 12.5% on extra oral, intraoral and neck muscles, tenderness on palpation of TMJ capsule were reported 5 cases, and 4 of them were female. 4. The distribution of Angle's classification was found 79.5% in class I, 4.5% in clasII-div.1 and 15.9% in class III. There was no significant differences on TM disorders between Angles classifications. 5. There was no significant differences on TM disorders between the subjects of canine guided occlusion and group function occlusion, and also for the differences between the subjects of nonworking side interferences and no interferences on laterotrusion. 6. There was no significant differences on TM disorders between the subjects of anterior teeth trauma in C.C. and no anterior teeth trauma, but there were significant differences between the subjects of posterior protrusive contact and no posterior protrusive contact.

• Journal of Korea Multimedia Society
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• v.7 no.10
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• pp.1378-1388
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• 2004

This paper proposes method to improve the image quality degradation that show when reconstructing compressed images at low bit rate by using wavelet transform. The image quality distortion is blocking artifacts and noise in DCT's compression but blocking artifacts of wavelet transform does not appear and ringing artifacts was appeared near the edge. This proposed technique is classified to part which is ringing artifacts of the edge vicinity appears which is not, apply adaptive filter to each region improved image. A edge region which is harsh to the eye is applied by Canny mask and finding strong edge region, search the neighborhood classify the flat region and the texture region, and apply to each region suitable filter, As experiment result, PSNR value of method that is proposed in that low bit rate compression image that ringing artifact appears became low about 0.05db, but 0.023db degree rose strong edge region and nat region's image. Also, showed picture quality improved more than ringing artifacts in nat region when see from subjective viewpoint of human.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2283-2288
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• 2006

As development in technology of bioinformatics recently makes it possible to operate micro-level experiments, we can observe the expression pattern of total genome through on chip and analyze the interactions of thousands of genes at the same time. Thus, DNA microarray technology presents the new directions of understandings for complex organisms. Therefore, it is required how to analyze the enormous gene information obtained through this technology effectively. In this thesis, We used sample data of bioinformatics core group in harvard university. It designed and implemented system that evaluate accuracy after dividing in class of two using Bayesian algorithm, ASA, of feature extraction method through normalization process, reducing or removing of noise that occupy by various factor in microarray experiment. It was represented accuracy of 98.23% after Lowess normalization.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.7 s.124
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• pp.572-578
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• 2007

Two stroke low speed diesel engines are widely used for marine propulsion or as power plant prime mover. These engines have many merits which includes higher thermal efficiency, mobility and durability. Yet various annoying vibrations occur sometimes in ships or at the plant itself. Of these vibrations, torsional vibration is very important and dictates a careful investigation during the engme's initial design stage for safe operation. With the rule and limit on torsional vibration in place, shaft strength fatigue due to torsional vibration however demands further analysis which possibly can be incorporated in the classification societies' rule and limit. In addition, the shaft's torsional vibration stresses can be calculated equivalently from accumulated fatigue cycles number due to transient torsional vibration in time domain. In this paper, authors suggest a new estimation method combined with Palmgren-Miner equation. A 6S70MC-C ($25,320ps{\times}91rpm$) engine for ship propulsion was selected as a case study. Angular velocity was measured, instead of shaft's strain, for simplified measurement and it was converted to torsional vibration stress for accumulated fatigue cycle numbers in shafting life time. Likewise, the accumulated fatigue calculation was compared with shaft fatigue strength limit. This new method can be further realized and confirmed in ship with two stroke low speed diesel engine.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.515-518
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• 2007

SAFRS(Spontaneous Acoustic Field Reproduction System) is a system to sense changes of surroundings and produce sounds which can go well with environment elements sensed by the system in to the space. The sounds were judged by individual evaluation and, the classification of the preferred sounds according to the mood of the space was suggested in the former study. Effectiveness of SAFRS with field application was validated by prior studies which dealt with researching acoustic environment, evaluating images of sounds, and rating environment with existence and nonexistence of sound resources such as fountains and the system after applied in D university. In this study, for more effective field application of SAFRS, research for the acoustic environment around sound resources and subjective evaluation of the preference of the sounds from the resources were made and it was considered that the results of the experiments should be primary information to propose proper sound level to be offered by the system. The results of the study are as follows; 1) It was considered that the ambience of the center road was dependent upon produced sounds by the system and water sounds of the fountain and that of walk way was mostly dependent upon produced sounds. 2) The results of the subjective evaluation showed that the distance from sound resources was suggestive; the more distant from produced sounds the less full and clear the sounds, the less distant from the sounds of water the more delight and idyllic ambience, and the less distant from the forest the more idyllic ambient and diversity. 3) The results upwards were telling that an average value of six elements for the evaluation was even at the place set back 10.2m from center road and walk way. And harmony of all sounds of the place should be considered to propose suitable sound level of SAFRS.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.11
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• pp.997-1004
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• 2011

A fault detection algorithm of a charge and discharge system to ensure the safe use of hybrid electric vehicle is proposed in this paper. This algorithm can be used as a complementary way to existing fault detection technique for a charge and discharge system. The proposed algorithm uses a SVDD technique, which additionally utilizes two methods for learning a large amount of data; one is to incrementally learn a large amount of data, the other one is to remove the data that does not affect the next learning using a new data reduction technique. Removal of data is selected by using lines connecting support vectors. In the proposed method, the data processing speed is drastically improved and the storage space used is remarkably reduced than the conventional methods using the SVDD technique only. A battery data and speed data of a commercial hybrid electrical vehicle are utilized in this study. A fault boundary is produced via SVDD techniques using the input and output in normal operation of the system without using mathematical modeling. A fault detection simulation is performed using both an artificial fault data and the obtained fault boundary via SVDD techniques. In the fault detection simulation, fault detection time via proposed algorithm is compared with that of the peak-peak method. Also the proposed algorithm is revealed to detect fault in the region where conventional peak-peak method is never able to do.

• Journal of Advanced Navigation Technology
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• v.24 no.5
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• pp.393-407
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• 2020

In order to reduce the threat by illegal unmanned aerial vehicles, a tracking system based on sound was implemented. There are three main points to the drone acoustic tracking method. First, it scans the space through variable beam formation to find a sound source and records the sound using a microphone array. Second, it classifies it into a hidden Markov model (HMM) to find out whether the sound source exists or not, and finally, the sound source is In the case of a drone, a sound source recorded and stored as a tracking reference signal based on an adaptive beam pattern is used. The simulation was performed in both the ideal condition without background noise and interference sound and the non-ideal condition with background noise and interference sound, and evaluated the tracking performance of illegal drones. The drone tracking system designed the criteria for determining the presence or absence of a drone according to the improvement of the search distance performance according to the microphone array performance and the degree of sound pattern matching, and reflected in the design of the speech reading circuit.