• Title/Summary/Keyword: sigmoid

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Air Pollution Risk Prediction System Utilizing Deep Learning Focused on Cardiovascular Disease

  • Lee, Jisu;Moon, Yoo-Jin
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.12
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    • pp.267-275
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    • 2022
  • This paper proposed a Deep Neural Network Model system utilizing Keras for predicting air pollution risk of the cardiovascular disease through the effect of each component of air on the harmful virus using past air information, with analyzing 18,000 data sets of the Seoul Open Data Plaza. By experiments, the model performed tasks with higher accuracy when using methods of sigmoid, binary_crossentropy, adam, and accuracy through 3 hidden layers with each 8 nodes, resulting in 88.92% accuracy. It is meaningful in that any respiratory disease can utilize the risk prediction system if there are data on the effects of each component of air pollution and fine dust on oil-borne diseases. It can be further developed to provide useful information to companies that produce masks and air purification products.

A study on activation functions of Artificial Neural Network model suitable for prediction of the groundwater level in the mid-mountainous area of eastern Jeju island (제주도 동부 중산간지역 지하수위 예측에 적합한 인공신경망 모델의 활성화함수 연구)

  • Mun-Ju Shin;Jeong-Hun Kim;Su-Yeon Kang;Jeong-Han Lee;Kyung Goo Kang
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.520-520
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    • 2023
  • 제주도 동부 중산간 지역은 화산암으로 구성된 지하지질로 인해 지하수위의 변동폭이 크고 변동양상이 복잡하여 인공신경망(Artificial Neural Network, ANN) 모델 등을 활용한 지하수위의 예측이 어렵다. ANN에 적용되는 활성화함수에 따라 지하수의 예측성능은 달라질 수 있으므로 활성화함수의 비교분석 후 적절한 활성화함수의 사용이 반드시 필요하다. 본 연구에서는 5개 활성화함수(sigmoid, hyperbolic tangent(tanh), Rectified Linear Unit(ReLU), Leaky Rectified Linear Unit(Leaky ReLU), Exponential Linear Unit(ELU))를 제주도 동부 중산간지역에 위치한 2개 지하수 관정에 대해 비교분석하여 최적 활성화함수 도출을 목표로 한다. 또한 최적 활성화함수를 활용한 ANN의 적용성을 평가하기 위해 최근 널리 사용되고 있는 순환신경망 모델인 Long Short-Term Memory(LSTM) 모델과 비교분석 하였다. 그 결과, 2개 관정 중 지하수위 변동폭이 상대적으로 큰 관정은 ELU 함수, 상대적으로 작은 관정은 Leaky ReLU 함수가 지하수위 예측에 적절하였다. 예측성능이 가장 낮은 활성화함수는 sigmoid 함수로 나타나 첨두 및 최저 지하수위 예측 시 사용을 지양해야 할 것으로 판단된다. 도출된 최적 활성화함수를 사용한 ANN-ELU 모델 및 ANN-Leaky ReLU 모델을 LSTM 모델과 비교분석한 결과 대등한 지하수위 예측성능을 나타내었다. 이것은 feed-forward 방식인 ANN 모델을 사용하더라도 적절한 활성화함수를 사용하면 최신 순환신경망과 대등한 결과를 도출하여 활용 가능성이 충분히 있다는 것을 의미한다. 마지막으로 LSTM 모델은 가장 적절한 예측성능을 나타내어 다양한 인공지능 모델의 예측성능 비교를 위한 기준이 되는 참고모델로 활용 가능하다. 본 연구에서 제시한 방법은 지하수위 예측과 더불어 하천수위 예측 등 다양한 시계열예측 및 분석연구에 유용하게 사용될 수 있다.

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Estimation and Adjustment of Time Point in Manifestation of Gas Safety Project Effects using Sigmoid Functions (시그모이드 함수를 이용한 가스안전사업 효과의 발현시점 추정과 조정)

  • Hyeon Kyo Lim;Geon Yeong Bak
    • Journal of the Korean Society of Safety
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    • v.38 no.1
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    • pp.70-77
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    • 2023
  • Gas has replaced coal or petroleum as primary fuel because of its convenience. However, gas has risk of fire, explosion, or poisoning. To reduce gas-related accidents, many strategic projects have been being carried based on 'Gas Safety Management Basic Plans' on a domestic scale. In spite of those projects, the gas-related accident rate did not decrease over past decades. Thus, this study was conducted to analyze the effectiveness of ongoing projects, and to find out ways to make improvements. Conventional statistical analyses on accident data published by gas-related institutions were not useful to determine meaningful attributes to predict future. Whereas, accident case analyses adopted in the present study discovered differences in the type of people and their unsafe acts for each gas type. Meanwhile, the overall average priority of projects was not high in the aspect of System Safety Precedence. If the current trend is maintained, with sigmoid functions, it can be estimated that mean annual accident rate will decrease by only 2.0% in the next two decades. To improve the current trend, the present study made conclusions as followings: (1) safety projects should be designed with careful consideration of accident traits including gas type, unsafe acts, and persons involved and (2) alternative strategies should include system considerations such as minimum hazard design and safety devices prior to mere education or training. To summarize briefly, the present state related with gas accidents highlights the necessity of a system-based multidisciplinary approach.

A case study of the antibiotics-associated Pseudomembranous Colitis treated with Yijoong-tang (Lizhong-tang) (항생제로 유발된 Pseudomembranous Colitis환자의 이중탕(理中湯) 치료 1례)

  • Choi, Won-woo;Kim, Mi-young;Kim, Young-jee;Lee, Seung-yeop;Min, In-kyu;Hong, Jin-woo;Na, Byong-jo;Jung, Woo-sang
    • The Journal of the Society of Stroke on Korean Medicine
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    • v.8 no.1
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    • pp.58-62
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    • 2007
  • Objective : Stroke patients tend to take antibiotics due to infection resulting from complication. One of many side effects from using antibiotics is diarrhea, which infact causes anaerobic organism dysfunction resulting Pseudo-Membranous Colitis (P.M.C). To treat P.M.C, antibiotics and antibacterial agents are usually used. But they may cause other side effects, therefore extreme caution must be taken. Methods : We treated an antibiotic induced P.M.C patient who diagnosed by sigmoid scopy with only Yijoong-tang (Lizhong-tang) without antibiotics and observed patients stool aspects. Results and Conclusion : Patiensts symptom was improved after 7days, and we can see the improvement by follow-up sigmoid scopy. This case may give us a possibility of that oriental medical treatments as complementary and alternative medicine to standard antibiotic treatment.

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Performance Evaluation for ECG Signal Prediction Using Digital IIR Filter and Deep Learning (디지털 IIR Filter와 Deep Learning을 이용한 ECG 신호 예측을 위한 성능 평가)

  • Uei-Joong Yoon
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.4
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    • pp.611-616
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    • 2023
  • ECG(electrocardiogram) is a test used to measure the rate and regularity of heartbeats, as well as the size and position of the chambers, the presence of any damage to the heart, and the cause of all heart diseases can be found. Because the ECG signal obtained using the ECG-KIT includes noise in the ECG signal, noise must be removed from the ECG signal to apply to the deep learning. In this paper, the noise of the ECG signal was removed using the digital IIR Butterworth low-pass filter. When the performance evaluation of the three activation functions, sigmoid(), ReLU(), and tanh() functions, was compared using the deep learning model of LSTM, it was confirmed that the activation function with the smallest error was the tanh() function. Also, When the performance evaluation and elapsed time were compared for LSTM and GRU models, it was confirmed that the GRU model was superior to the LSTM model.

Predicton and Elapsed time of ECG Signal Using Digital FIR Filter and Deep Learning (디지털 FIR 필터와 Deep Learning을 이용한 ECG 신호 예측 및 경과시간)

  • Uei-Joong Yoon
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.4
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    • pp.563-568
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    • 2023
  • ECG(electrocardiogram) is used to measure the rate and regularity of heartbeats, as well as the size and position of the chambers, the presence of any damage to the heart, and the cause of all heart diseases can be found. Because the ECG signal obtained using the ECG-KIT includes noise in the ECG signal, noise must be removed from the ECG signal to apply to the deep learning. In this paper, Noise included in the ECG signal was removed by using a lowpass filter of the Digital FIR Hamming window function. When the performance evaluation of the three activation functions, sigmoid(), ReLU(), and tanh() functions, which was confirmed that the activation function with the smallest error was the tanh() function, the elapsed time was longer when the batch size was small than large. Also, it was confirmed that result of the performance evaluation for the GRU model was superior to that of the LSTM model.

Investigating wave propagation in sigmoid-FGM imperfect plates with accurate Quasi-3D HSDTs

  • Mokhtar Nebab;Hassen Ait Atmane;Riadh Bennai
    • Steel and Composite Structures
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    • v.51 no.2
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    • pp.185-202
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    • 2024
  • In this research paper, and for the first time, wave propagations in sigmoidal imperfect functionally graded material plates are investigated using a simplified quasi-three-dimensionally higher shear deformation theory (Quasi-3D HSDTs). By employing an indeterminate integral for the transverse displacement in the shear components, the number of unknowns and governing equations in the current theory is reduced, thereby simplifying its application. Consequently, the present theories exhibit five fewer unknown variables compared to other Quasi-3D theories documented in the literature, eliminating the need for any correction coefficients as seen in the first shear deformation theory. The material properties of the functionally graded plates smoothly vary across the cross-section according to a sigmoid power law. The plates are considered imperfect, indicating a pore distribution throughout their thickness. The distribution of porosities is categorized into two types: even or uneven, with linear (L)-Type, exponential (E)-Type, logarithmic (Log)-Type, and Sinus (S)-Type distributions. The current quasi-3D shear deformation theories are applied to formulate governing equations for determining wave frequencies, and phase velocities are derived using Hamilton's principle. Dispersion relations are assumed as an analytical solution, and they are applied to obtain wave frequencies and phase velocities. A comprehensive parametric study is conducted to elucidate the influences of wavenumber, volume fraction, thickness ratio, and types of porosity distributions on wave propagation and phase velocities of the S-FGM plate. The findings of this investigation hold potential utility for studying and designing techniques for ultrasonic inspection and structural health monitoring.

Comparative analysis of activation functions of artificial neural network for prediction of optimal groundwater level in the middle mountainous area of Pyoseon watershed in Jeju Island (제주도 표선유역 중산간지역의 최적 지하수위 예측을 위한 인공신경망의 활성화함수 비교분석)

  • Shin, Mun-Ju;Kim, Jin-Woo;Moon, Duk-Chul;Lee, Jeong-Han;Kang, Kyung Goo
    • Journal of Korea Water Resources Association
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    • v.54 no.spc1
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    • pp.1143-1154
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    • 2021
  • The selection of activation function has a great influence on the groundwater level prediction performance of artificial neural network (ANN) model. In this study, five activation functions were applied to ANN model for two groundwater level observation wells in the middle mountainous area of the Pyoseon watershed in Jeju Island. The results of the prediction of the groundwater level were compared and analyzed, and the optimal activation function was derived. In addition, the results of LSTM model, which is a widely used recurrent neural network model, were compared and analyzed with the results of the ANN models with each activation function. As a result, ELU and Leaky ReLU functions were derived as the optimal activation functions for the prediction of the groundwater level for observation well with relatively large fluctuations in groundwater level and for observation well with relatively small fluctuations, respectively. On the other hand, sigmoid function had the lowest predictive performance among the five activation functions for training period, and produced inappropriate results in peak and lowest groundwater level prediction. The ANN-ELU and ANN-Leaky ReLU models showed groundwater level prediction performance comparable to that of the LSTM model, and thus had sufficient potential for application. The methods and results of this study can be usefully used in other studies.

Laparoscopic Primary Endorectal Pull-through Procedure for Hirschsprung's Disease (선천성 거대결장에서 복강경하 일기적 Boley씨 수술)

  • Kwon, Soo-In
    • Advances in pediatric surgery
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    • v.4 no.2
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    • pp.172-175
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    • 1998
  • With the recent advances in instruments and techniques, laparoscopic procedure have extended to neonates with congenital anomalies. The author reports a 6-day-old boy with Hirschsprung's disease, treated successfully by the laparoscopic endorectall pull-through procedure. The technique and its potential role in the treatment of Hirschsprung's disease are described. One camera port and three working ports were used for access to the peritoneal cavity. The descending and sigmoid colon were mobilized laparoscopically. The submucosal dissection was done transanally. The colon was then pulled down in continuity, divided above the transition zone, and secured to the anal mucosa about 10 mm above the pectinate line. Author concluded that endorectal pull-through can be performed safety with the laparoscope.

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Prediction of plasma etching using genetic-algorithm controlled backpropagation neural network

  • Kim, Sung-Mo;Kim, Byung-Whan
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1305-1308
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    • 2003
  • A new technique is presented to construct a predictive model of plasma etch process. This was accomplished by combining a backpropagation neural network (BPNN) and a genetic algorithm (GA). The predictive model constructed in this way is referred to as a GA-BPNN. The GA played a role of controlling training factors simultaneously. The training factors to be optimized are the hidden neuron, training tolerance, initial weight magnitude, and two gradients of bipolar sigmoid and linear functions. Each etch response was optimized separately. The proposed scheme was evaluated with a set of experimental plasma etch data. The etch process was characterized by a $2^3$ full factorial experiment. The etch responses modeled are aluminum (A1) etch rate, silica profile angle, A1 selectivity, and dc bias. Additional test data were prepared to evaluate model appropriateness. The GA-BPNN was compared to a conventional BPNN. Compared to the BPNN, the GA-BPNN demonstrated an improvement of more than 20% for all etch responses. The improvement was significant in the case of A1 etch rate.

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