• 전력전자학회논문지
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• 제24권2호
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• pp.71-77
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• 2019

This study proposes a circulating current reduction method that uses high-frequency voltage compensation when carrier phase difference occurs between two inverters in MSIS. In MSIS, inverters are configured in parallel to increase power capacity and to increase efficiency by using inverters only as needed. However, in the parallel inverter structure, circulating current is inevitably generated. Circulating current increases the stress on the switch, adversely affects the current control performance, and renders load sharing difficult. The proposed method compensates for the output voltage reference of the slave module by using the high-frequency voltage so that the switching pattern of each module is matched even in asynchronous carriers. The validity of the proposed method is verified by simulations and experiments with 600 W IPMSM.

• Tribology and Lubricants
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• 제37권1호
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• pp.1-6
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• 2021

This paper presents the experimental results of hydrophobic surfaces developed using a stereolithography-based additive-manufacturing technique. The additive manufacturing technique can be used to manufacture objects with complex geometries from computer-aided design data. Several additive manufacturing methods, such as selective laser sintering, fused deposition modeling, stereolithography apparatus (SLA), and inkjet-based system, have been developed. The SLA is a form of three-dimensional printing technology used to create prototypes, patterns, and production parts in successive layers through photochemical processes. Light causes chemical monomers and oligomers to cross-link together to form objects composed of polymers. Moreover, this method is economical for fabricating surfaces with high output resolution and quality. Here, we fabricate various surfaces using different shapes using an SLA. The surfaces with micro-patterns are fabricated for 10 cases, including the biomimetic surface. The fabricated surfaces with various micro-patterns are evaluated for hydrophobicity performance based on the static contact angle. The contact angle is measured three times for each case, and the averaged value is used. The results indicate that the arrangements in a staggered structure have a larger contact angle than those in a line when the same micro-pattern is applied. Moreover, the mimetic surfaces exhibit more hydrophobic characteristics than those of artificial micro-patterns.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권10호
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• pp.3355-3372
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• 2022

Composing music is an inspired yet challenging task, in that the process involves many considerations such as assigning pitches, determining rhythm, and arranging accompaniment. Algorithmic composition aims to develop algorithms for music composition. Recently, algorithmic composition using artificial intelligence technologies received considerable attention. In particular, computational intelligence is widely used and achieves promising results in the creation of music. This paper attempts to provide a survey on the music generation based on the Monte Carlo (MC) algorithm. First, transform the MIDI music format files to digital data. Among these data, use the logistic fitting method to fit the time series, obtain the time distribution regular pattern. Except for time series, the converted data also includes duration, pitch, and velocity. Second, using MC simulation to deal with them summed up their distribution law respectively. The two main control parameters are the value of discrete sampling and standard deviation. Processing the above parameters and converting the data to MIDI file, then compared with the output generated by LSTM neural network, evaluate the music comprehensively.

• Smart Structures and Systems
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• 제29권1호
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• pp.53-62
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• 2022

The deployment of advanced structural health monitoring (SHM) systems in large-scale civil structures collects large amounts of data. Note that these data may contain multiple types of anomalies (e.g., missing, minor, outlier, etc.) caused by harsh environment, sensor faults, transfer omission and other factors. These anomalies seriously affect the evaluation of structural performance. Therefore, the effective analysis and mining of SHM data is an extremely important task. Inspired by the deep learning paradigm, this study develops a novel generative adversarial network (GAN) and convolutional neural network (CNN)-based data anomaly detection approach for SHM. The framework of the proposed approach includes three modules : (a) A three-channel input is established based on fast Fourier transform (FFT) and Gramian angular field (GAF) method; (b) A GANomaly is introduced and trained to extract features from normal samples alone for class-imbalanced problems; (c) Based on the output of GANomaly, a CNN is employed to distinguish the types of anomalies. In addition, a dataset-oriented method (i.e., multistage sampling) is adopted to obtain the optimal sampling ratios between all different samples. The proposed approach is tested with acceleration data from an SHM system of a long-span bridge. The results show that the proposed approach has a higher accuracy in detecting the multi-pattern anomalies of SHM data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권12호
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• pp.4567-4583
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• 2021

This study proposes an analytical approximation algorithm based on extreme value theory (EVT) for the inverse of the power of the incomplete Gamma function. First, the Gumbel function is used to approximate the power of the incomplete Gamma function, and the corresponding inverse problem is transformed into the inversion of an exponential function. Then, using the tail equivalence theorem, the normalized coefficient of the general Weibull distribution function is employed to replace the normalized coefficient of the random variable following a Gamma distribution, and the approximate closed form solution is obtained. The effects of equation parameters on the algorithm performance are evaluated through simulation analysis under various conditions, and the performance of this algorithm is compared to those of the Newton iterative algorithm and other existing approximate analytical algorithms. The proposed algorithm exhibits good approximation performance under appropriate parameter settings. Finally, the performance of this method is evaluated by calculating the thresholds of space-time block coding and space-frequency block coding pattern recognition in multiple-input and multiple-output orthogonal frequency division multiplexing. The analytical approximation method can be applied to other related situations involving the maximum statistics of independent and identically distributed random variables following Gamma distributions.

• 복식문화연구
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• 제31권2호
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• pp.213-227
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• 2023

To analyze the status and needs of the small- and medium-sized garment manufacturing industry in Busan, this study comprised an online survey of companies and interviews with 14 representatives of the 98 companies. The results are as follows: Approximately 34.7% of the garment manufacturers were located in Geumjeong-gu, Busan. The most common type of work was the contracting factory type. Daily production output was between 100pcs and 300pcs. Production materials comprised 42.9% woven and 24.8% knitted fabrics. Main products were menswear, uniforms, womenswear, casual wear, sports and leisure wear, protective clothes, and children's clothing. The main clients were uniform companies, main factories, wholesale markets, online shopping malls and promotion companies, exporters, and department stores. As a result of a survey on industrial needs with company representatives, their satisfaction with company employees was 57.2%, and the most important factor when hiring employees was job-related competencies, among which the ability to understand the sewing process was the most necessary. In terms of computer software literacy, illustrations and pattern CAD/CAM are required. They thought industry-university cooperation is crucial for advantage for advantage research and product development, as it allows for the sharing knowledge, resources, and especially human resources. The greatest administrative issue were human resources and funding.

• 한국정밀공학회지
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• 제11권1호
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• pp.138-149
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• 1994

This paper introduces a new monitoring technique which utilizes an adaptive signal processing for feature generation, coupled with a multilayered merual network for pattern recognition. The cutting force signal in face milling operation was modeled by a low order discrete autoregressive model, shere parameters were estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(recursive least square) method with discounted measurements. The influences of the adaptation algorithm parameters as well as some considerations for modeling on the estimation results are discussed. The sensitivity of the extimated model parameters to the tool state(new and worn tool)is presented, and the application of a multilayered neural network to tool state monitoring using the previously generated features is also demonstrated with a high success rate. The methodology turned out to be quite suitable for in-process tool wear monitoring in the sense that the model parameters are effective as tool state features in milling operation and that the classifier successfully maps the sensors data to correct output decision.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2008년도 춘계학술발표대회
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• pp.231-234
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• 2008

Currently an automated methodology based on data mining techniques is presented for the prediction of customer load patterns in load demand data. The main aim of our work is to forecast customers' contract information from capacity of daily power consumption patterns. According to the result, we try to evaluate the contract information's suitability. The proposed our approach consists of three stages: (i) data preprocessing: noise or outlier is detected and removed (ii) cluster analysis: SOMs clustering is used to create load patterns and the representative load profiles and (iii) classification: we applied the K-NNs classifier in order to predict the customers' contract information base on power consumption patterns. According to the our proposed methodology, power load measured from AMR(automatic meter reading) system, as well as customer indexes, were used as inputs. The output was the classification of representative load profiles (or classes). Lastly, in order to evaluate KNN classification technique, the proposed methodology was applied on a set of high voltage customers of the Korea power system and the results of our experiments was presented.

• 전자공학회논문지S
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• 제35S권12호
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• pp.17-26
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• 1998

초음파센서는 저렴성, 단순한 구조, 기계적 강인성, 사용상의 적은 제약 등의 이점 때문에 실제 다양한 응용 분야에 적용되지만 물체의 인식에 초음파센서를 사용하기에는 낮은 분해능을 초래하는 불량한 방향성과 측정오류를 유발하는 반사성의 어려움을 내재하고 있다. 일반적인 거리계에 사용되는 TOF(time of flight) 방법은 작은 물체의 형태, 즉 평면, 코너, 에지의 구별이 불가능하므로 많은 수의 센서를 배열형태로 사용하거나, 일정수의 센서를 사용할 경우에는 센서의 배열을 기계적으로 이동시키는 방법, 그리고 초음파 반사신호의 물리적인 특징을 해석하여 물체를 구별 인식한다. 본 논문에서는 간단하게 구성된 전자회로를 부가하여 초음파센서의 송출전압을 여러 단계로 변경시켜 가면서 송출음파를 조절하고, 물체의 패턴인식에 있어서 가장 기본적인 거리뿐만 아니라 물체크기, 물체각도, 물체이동 값을 위해 센서 데이터의 조합을 이용한 보간법과 제안한 뉴로퍼지 기반의 지능적 게산 알고리즘을 적용하여 물체의 패턴 인식을 개선한다.

• 천문학회지
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• 제48권2호
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• pp.125-137
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• 2015

We report results of the performance evaluation of a new hardware correlator in Korea, the Daejeon correlator, developed by the Korea Astronomy and Space Science Institute (KASI) and the National Astronomical Observatory of Japan (NAOJ). We conduct Very Long Baseline Interferometry (VLBI) observations at 22 GHz with the Korean VLBI Network (KVN) in Korea and the VLBI Exploration of Radio Astrometry (VERA) in Japan, and correlated the aquired data with the Daejeon correlator. For evaluating the performance of the new hardware correlator, we compare the correlation outputs from the Daejeon correlator for KVN observations with those from a software correlator, the Distributed FX (DiFX). We investigate the correlated flux densities and brightness distributions of extragalactic compact radio sources. The comparison of the two correlator outputs shows that they are consistent with each other within < 8%, which is comparable with the amplitude calibration uncertainties of KVN observations at 22 GHz. We also find that the 8% difference in flux density is caused mainly by (a) the difference in the way of fringe phase tracking between the DiFX software correlator and the Daejeon hardware correlator, and (b) an unusual pattern (a double-layer pattern) of the amplitude correlation output from the Daejeon correlator. The visibility amplitude loss by the double-layer pattern is as small as 3%. We conclude that the new hardware correlator produces reasonable correlation outputs for continuum observations, which are consistent with the outputs from the DiFX software correlator.