• Title/Summary/Keyword: 강인 적응 제어

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Harmonic Estimation of Power Signal Based on Time-varying Optimal Finite Impulse Response Filter (시변 최적 유한 임펄스 응답 필터 기반 전력 신호 고조파 검출)

  • Kwon, Bo-Kyu
    • The Journal of Korean Institute of Information Technology
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    • v.16 no.11
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    • pp.97-103
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    • 2018
  • In this paper, the estimation method for the power signal harmonics is proposed by using the time-varying optimal finite impulse response (FIR) filter. To estimate the magnitude and phase-angle of the harmonic components, the time-varying optimal FIR filter is designed for the state space representation of the noisy power signal which the magnitude and phase is considered as a stochastic process. Since the time-varying optimal FIR filter used in the proposed method does not use any priori information of the initial condition and has FIR structure, the proposed method could overcome the demerits of Kalman filter based method such as poor estimation and divergence problem. Due to the FIR structure, the proposed method is more robust against to the model uncertainty than the Kalman filter. Moreover, the proposed method gives more general solution than the time-invariant optimal FIR filter based harmonic estimation method. To verify the performance and robustness of the proposed method, the proposed method is compared with time-varying Kalman filter based method through simulation.

Personal Growth through Spousal Bereavement in Later Life (노년기 배우자 사별 후 적응과정에서의 개인적 성장)

  • Chang, Sujie
    • Korean Journal of Social Welfare
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    • v.65 no.4
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    • pp.165-193
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    • 2013
  • This study purposes to explore the growing process through spousal bereavement in later life, and to develop the theory. A qualitative research was conducted, and the participants were 17 seniors. The analysis according to Strauss and Corbin's grounded theory(1998), resulted in 143 concepts, 43 subcategories, and 19 categories. Range analysis according to paradigm showed that the causal conditions were 'marital relationships', 'independent/dependent tendencies', and 'emotional readiness for the death of a spouse', and the phenomena were 'depression', 'hopelessness', 'daily stress', 'psychological intimidation', 'regret', and 'sense of being freed'. The contextual conditions that affect these phenomena were 'desire for intimate personal relationships' and 'desire to maintain independence'; the action/interaction strategies to manage the phenomena were 'facing reality' and 'efforts for construction of the new life'; and the mediating conditions that promote or suppress these action/interaction strategies were 'social support' and 'spirituality'. The results were 'reconstruction of the meaning in life', 'increase in self-esteem', 'reinforcement of social network' and 'embrace and acceptance'. Furthermore, when personal growth after bereavement of a spouse was analyzed focusing on changes over time, the growth process consisted of three steps: 'sadness and despair', 'embracing and moving forward', and 'personal growth'. The pattern analyses were performed to typify recurring relations by category, and 5 types were derived. The results of our study show that personal growth after spousal loss is an integrative process in life after crisis, and can be conceptualized as the process of overcoming the despair that immediately follows the death of a spouse, seeking a new life by actively taking control, and discovering a strengthened self.

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A Study of Prediction of Daily Water Supply Usion ANFIS (ANFIS를 이용한 상수도 1일 급수량 예측에 관한 연구)

  • Rhee, Kyoung-Hoon;Moon, Byoung-Seok;Kang, Il-Hwan
    • Journal of Korea Water Resources Association
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    • v.31 no.6
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    • pp.821-832
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    • 1998
  • This study investigates the prediction of daily water supply, which is a necessary for the efficient management of water distribution system. Fuzzy neuron, namely artificial intelligence, is a neural network into which fuzzy information is inputted and then processed. In this study, daily water supply was predicted through an adaptive learning method by which a membership function and fuzzy rules were adapted for daily water supply prediction. This study was investigated methods for predicting water supply based on data about the amount of water supplied to the city of Kwangju. For variables choice, four analyses of input data were conducted: correlation analysis, autocorrelation analysis, partial autocorrelation analysis, and cross-correlation analysis. Input variables were (a) the amount of water supplied (b) the mean temperature, and (c)the population of the area supplied with water. Variables were combined in an integrated model. Data of the amount of daily water supply only was modelled and its validity was verified in the case that the meteorological office of weather forecast is not always reliable. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 18.35% and the average error was lower than 2.36%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.

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Robust Speech Recognition Algorithm of Voice Activated Powered Wheelchair for Severely Disabled Person (중증 장애우용 음성구동 휠체어를 위한 강인한 음성인식 알고리즘)

  • Suk, Soo-Young;Chung, Hyun-Yeol
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.6
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    • pp.250-258
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    • 2007
  • Current speech recognition technology s achieved high performance with the development of hardware devices, however it is insufficient for some applications where high reliability is required, such as voice control of powered wheelchairs for disabled persons. For the system which aims to operate powered wheelchairs safely by voice in real environment, we need to consider that non-voice commands such as user s coughing, breathing, and spark-like mechanical noise should be rejected and the wheelchair system need to recognize the speech commands affected by disability, which contains specific pronunciation speed and frequency. In this paper, we propose non-voice rejection method to perform voice/non-voice classification using both YIN based fundamental frequency(F0) extraction and reliability in preprocessing. We adopted a multi-template dictionary and acoustic modeling based speaker adaptation to cope with the pronunciation variation of inarticulately uttered speech. From the recognition tests conducted with the data collected in real environment, proposed YIN based fundamental extraction showed recall-precision rate of 95.1% better than that of 62% by cepstrum based method. Recognition test by a new system applied with multi-template dictionary and MAP adaptation also showed much higher accuracy of 99.5% than that of 78.6% by baseline system.

Adjuvant Postoperative Radiation Therapy for Carcinoma of the Uterine Cervix (자궁경부암의 수술 후 방사선치료)

  • Lee Kyung-Ja;Moon Hye Seong;Kim Seung Cheol;Kim Chong Il;Ahn Jung Ja
    • Radiation Oncology Journal
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    • v.21 no.3
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    • pp.199-206
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    • 2003
  • Purpose: This study was undertaken to evaluate the efficacy of postoperative radiotherapy, and to investigate the prognostic factors for FIGO stages IB-IIB cervical cancer patients who were treated with simple hysterectomy, or who had high-risk factors following radical hysterectomy and pelvic lymph node dissection. Materials and Methods: Between March 1986 and December 1998, 58 patients, with FIGO stages IB-IIB cervical cancer were included in this study. The indications for postoperative radiation therapy were based on the pathological findings, including lymph node metastasis, positive surgical margin, parametrial extension, lymphovascular invasion, invasion of more than half the cervical stroma, uterine extension and the incidental finding of cervix cancer fellowing simple hysterectomy. All patients received external pelvic radiotherapy, and 5 patients, received an additional intracavitary radiation therapy. The radiation dose from the external beam to the whole pelvis was $40\~50$ Gy. Vagina cuff Irradiation was peformed, after completion of the external beam irradiation, at a low-dose rate of Cs-137, with the total dose of $4488\~4932$ chy (median: 4500 chy) at 5 mm depth from the vagina surface. The median follow-up period was 44 months ($15\~108$ months). Results: The 5-yr actuarial local control rate, distant free survival and disease-free survival rate were $98\%,\;95\%\;and\;94\%$, respectively. A univariate analysis of the clinical and pathological parameters revealed that the clinical stage (p=0.0145), status of vaginal resection margin (p=0.0002) and parametrial extension (p=0.0001) affected the disease-free survival. From a multivariate analysis, only a parametrial extension independently influenced the disease-free survival. Five patients ($9\%$) experienced Grade 2 late treatment-related complications, such as radiation proctitis (1 patient), cystitis (3 patients) and lymphedema of the leg (1 patient). No patient had grade 3 or 4 complications. Conclusion: Our results indicate that postoperative radiation therapy can achieve good local control and survival rates for patients with stages IB-IIB cervical cancer, treated with a simple hysterectomy, as well as for those treated with a radical hysterectomy, and with unfavorable pathological findings. The prognostic factor for disease-free survival was invasion of the parametrium. The prognosic factor identified in this study for treatment failure can be used as a selection criterion for the combined treatment of radiation and che motherapy.

The Flood Water Stage Prediction based on Neural Networks Method in Stream Gauge Station (하천수위표지점에서 신경망기법을 이용한 홍수위의 예측)

  • Kim, Seong-Won;Salas, Jose-D.
    • Journal of Korea Water Resources Association
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    • v.33 no.2
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    • pp.247-262
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    • 2000
  • In this paper, the WSANN(Water Stage Analysis with Neural Network) model was presented so as to predict flood water stage at Jindong which has been the major stream gauging station in Nakdong river basin. The WSANN model used the improved backpropagation training algorithm which was complemented by the momentum method, improvement of initial condition and adaptive-learning rate and the data which were used for this study were classified into training and testing data sets. An empirical equation was derived to determine optimal hidden layer node between the hidden layer node and threshold iteration number. And, the calibration of the WSANN model was performed by the four training data sets. As a result of calibration, the WSANN22 and WSANN32 model were selected for the optimal models which would be used for model verification. The model verification was carried out so as to evaluate model fitness with the two-untrained testing data sets. And, flood water stages were reasonably predicted through the results of statistical analysis. As results of this study, further research activities are needed for the construction of a real-time warning of the impending flood and for the control of flood water stage with neural network method in river basin. basin.

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