• Title/Summary/Keyword: Mode value

Search Result 1,619, Processing Time 0.027 seconds

A Study on Formative Elements in 3D Animation Character -Focusing on Characters' Visual Recognition Elements of Form through Elements of Form and Formation Method of Form- (3D 애니메이션 캐릭터의 조형성 연구 -<겨울왕국> 캐릭터를 중심으로 조형의 구성요소와 원리를 통한 시각인지요소에 관한 연구-)

  • Kim, Hye Sung;Sung, Re-A
    • Cartoon and Animation Studies
    • /
    • s.36
    • /
    • pp.45-74
    • /
    • 2014
  • We can anticipate that animations will form one of the axes and lead popular culture in our future visual age. Recently, research has been actively conducted, but it mainly focuses on their value in culture industry or technologies and methods of producing animations. Of course, research that deals with animation characters has constantly come out. This study focuses on the 'formative elements' of 3D animation characters and attempts differentiation from other research by inducing new logic theoretically. Being freed from the research on characters that has been merely focused on theoretical grounds, this study intends to figure out how audience that is consumers who actually get to watch and feel animations recognizes them and find out related problems and also solutions for them. In particular, this study intends to examine the formative characteristics of 3D animation characters with the characters appearing in , one of the animations that have achieved artistic value as well as commercial success. And for that, the study conducted not only literature review but various surveys and Delphi method as well. Also, the researcher devised an analysis frame to evaluate the formative elements through in-depth discussion with experts. And with this, the study created the forms such as the Elements of Form, Formation Methods of Form and Visual Recognition Elements of Form, examined how audience recognized 3D characters. The process of recognizing an image is influenced by socio-cultural environment or sex, age, and the level of knowledge differently. This was meant to investigate current visual culture and the public's perspective through characters in that represent the visual mode.

Mode of Action of Several Surfactants on Paraquat Efficacy (Paraquat 활성에 미치는 계면활성제의 작용기구)

  • Choi, Jung-Sup;Hwang, In-Taek;Kim, Jin-Seok;Kim, Tae-Joon;Cho, Kwang-Yun
    • The Korean Journal of Pesticide Science
    • /
    • v.6 no.3
    • /
    • pp.193-201
    • /
    • 2002
  • The effects of 24 ionic and nonionic surfactants on paraquat (1, 1' -dimethyl-4 4'-bipyridinium) efficacy were investigated with several annual plant species under greenhouse conditions. The paraquat efficacy was decreased or even lost when treated with the anionic surfactants tested. However, the efficacy of paraquat was significantly increased by 7 nonionic surfactants such as sorbitan palmitate, sorbitan stearate, polyoxyethylene sorbitan monopalmitate, polyoxyethylene sorbitan monostearate, polyoxyethylene stearyl ether, polyoxyethylene laurylamine ether, and polyoxyethylene stearylamine ether. Among these tested surfactants, 0.08% of polyoxyethylene laurylamine ether most significantly increased the paraquat activity, and the $GR_{50}$ value of paraquat with polyoxyethylene laurylamine ether was 1.6 times lower than the $GR_{50}$ value without polyoxyethylene laurylamine ether. In in vitro experiments, cellular leakage and chlorophyll contents between the application with and without polyoxyethylene laurylamine ether did not show significant changes. The absorption rate of $^{14}C$ paraquat in the treatment with polyoxyethylene laurylamine ether showed an absorption rate of 1.6 times higher than without surfactant. These results suggest that using compatible surfactants would increase the paraquat efficacy, and this increasing are due to improved absorption rate with the surfactant.

Development of Defect Inspection System for Polygonal Containers (다각형 용기의 결함 검사 시스템 개발)

  • Yoon, Suk-Moon;Lee, Seung-Ho
    • Journal of IKEEE
    • /
    • v.25 no.3
    • /
    • pp.485-492
    • /
    • 2021
  • In this paper, we propose the development of a defect inspection system for polygonal containers. Embedded board consists of main part, communication part, input/output part, etc. The main unit is a main arithmetic unit, and the operating system that drives the embedded board is ported to control input/output for external communication, sensors and control. The input/output unit converts the electrical signals of the sensors installed in the field into digital and transmits them to the main module and plays the role of controlling the external stepper motor. The communication unit performs a role of setting an image capturing camera trigger and driving setting of the control device. The input/output unit converts the electrical signals of the control switches and sensors into digital and transmits them to the main module. In the input circuit for receiving the pulse input related to the operation mode, etc., a photocoupler is designed for each input port in order to minimize the interference of external noise. In order to objectively evaluate the accuracy of the development of the proposed polygonal container defect inspection system, comparison with other machine vision inspection systems is required, but it is impossible because there is currently no machine vision inspection system for polygonal containers. Therefore, by measuring the operation timing with an oscilloscope, it was confirmed that waveforms such as Test Time, One Angle Pulse Value, One Pulse Time, Camera Trigger Pulse, and BLU brightness control were accurately output.

Risk Analysis for the Rotorcraft Landing System Using Comparative Models Based on Fuzzy (퍼지 기반 다양한 모델을 이용한 회전익 항공기 착륙장치의 위험 우선순위 평가)

  • Na, Seong Hyeon;Lee, Gwang Eun;Koo, Jeong Mo
    • Journal of the Korean Society of Safety
    • /
    • v.36 no.2
    • /
    • pp.49-57
    • /
    • 2021
  • In the case of military supplies, any potential failure and causes of failures must be considered. This study is aimed at examining the failure modes of a rotorcraft landing system to identify the priority items. Failure mode and effects analysis (FMEA) is applied to the rotorcraft landing system. In general, the FMEA is used to evaluate the reliability in engineering fields. Three elements, specifically, the severity, occurrence, and detectability are used to evaluate the failure modes. The risk priority number (RPN) can be obtained by multiplying the scores or the risk levels pertaining to severity, occurrence, and detectability. In this study, different weights of the three elements are considered for the RPN assessment to implement the FMEA. Furthermore, the FMEA is implemented using a fuzzy rule base, similarity aggregation model (SAM), and grey theory model (GTM) to perform a comparative analysis. The same input data are used for all models to enable a fair comparison. The FMEA is applied to military supplies by considering methodological issues. In general, the fuzzy theory is based on a hypothesis regarding the likelihood of the conversion of the crisp value to the fuzzy input. Fuzzy FMEA is the basic method to obtain the fuzzy RPN. The three elements of the FMEA are used as five linguistic terms. The membership functions as triangular fuzzy sets are the simplest models defined by the three elements. In addition, a fuzzy set is described using a membership function mapping the elements to the intervals 0 and 1. The fuzzy rule base is designed to identify the failure modes according to the expert knowledge. The IF-THEN criterion of the fuzzy rule base is formulated to convert a fuzzy input into a fuzzy output. The total number of rules is 125 in the fuzzy rule base. The SAM expresses the judgment corresponding to the individual experiences of the experts performing FMEA as weights. Implementing the SAM is of significance when operating fuzzy sets regarding the expert opinion and can confirm the concurrence of expert opinion. The GTM can perform defuzzification to obtain a crisp value from a fuzzy membership function and determine the priorities by considering the degree of relation and the form of a matrix and weights for the severity, occurrence, and detectability. The proposed models prioritize the failure modes of the rotorcraft landing system. The conventional FMEA and fuzzy rule base can set the same priorities. SAM and GTM can set different priorities with objectivity through weight setting.

A Study on the Development of IoT Inspection System for Gas Leakage Inspection in Kitchen Gas Range Built-in Method (주방 가스레인지 빌트인 방식에서 가스 누출검사를 위한 IoT 검사 시스템 개발에 관한 연구)

  • Kang, Dae Guk;Choi, Young Gyu
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.15 no.4
    • /
    • pp.283-290
    • /
    • 2022
  • In this study, an IoT inspection system that can be linked with a server was developed using a gas timer and ESP-01 Wi-Fi module installed on a gas valve in the home. The server environment of the gas leak IoT inspection system was installed with APM (Apache, PHP, MySQL) to collect gas pressure data by generation so that leakage checks could be performed. In order to control the gas leak IoT inspection system, the app inventory was used to manage the gas leak check value in real time. In addition, user convenience has been enhanced so that membership management, WiFi settings, and leakage check values can be checked through mobile apps. In order to manage subscribers by region, the user list was checked by logging in in in the administrator mode so that the information on whether or not the leak test was conducted and the results could be provided. In addition, when the user presses the gas leak check button, the pressure is automatically checked, and the measured value is stored in the server, and when a gas leak occurs, the leakage check is performed after alarm and repair so that it can be used if normal. In addition, in order to prevent overlapping membership, membership management can be performed based on MAC addresses.

Big Data Management in Structured Storage Based on Fintech Models for IoMT using Machine Learning Techniques (기계학습법을 이용한 IoMT 핀테크 모델을 기반으로 한 구조화 스토리지에서의 빅데이터 관리 연구)

  • Kim, Kyung-Sil
    • Advanced Industrial SCIence
    • /
    • v.1 no.1
    • /
    • pp.7-15
    • /
    • 2022
  • To adopt the development in the medical scenario IoT developed towards the advancement with the processing of a large amount of medical data defined as an Internet of Medical Things (IoMT). The vast range of collected medical data is stored in the cloud in the structured manner to process the collected healthcare data. However, it is difficult to handle the huge volume of the healthcare data so it is necessary to develop an appropriate scheme for the healthcare structured data. In this paper, a machine learning mode for processing the structured heath care data collected from the IoMT is suggested. To process the vast range of healthcare data, this paper proposed an MTGPLSTM model for the processing of the medical data. The proposed model integrates the linear regression model for the processing of healthcare information. With the developed model outlier model is implemented based on the FinTech model for the evaluation and prediction of the COVID-19 healthcare dataset collected from the IoMT. The proposed MTGPLSTM model comprises of the regression model to predict and evaluate the planning scheme for the prevention of the infection spreading. The developed model performance is evaluated based on the consideration of the different classifiers such as LR, SVR, RFR, LSTM and the proposed MTGPLSTM model and the different size of data as 1GB, 2GB and 3GB is mainly concerned. The comparative analysis expressed that the proposed MTGPLSTM model achieves ~4% reduced MAPE and RMSE value for the worldwide data; in case of china minimal MAPE value of 0.97 is achieved which is ~ 6% minimal than the existing classifier leads.

THE USE OF NEAR INFRARED REFLECTANCE SPECTROSCOPY(NIRS) TO PREDICT CHEMICAL COMPOSITION ON MAIZE SILAGE

  • D.Cozzolino;Fassio, A.;Mieres, J.;Y.Acosta
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
    • /
    • 2001.06a
    • /
    • pp.1610-1610
    • /
    • 2001
  • Microbiological examination of silage is of little value in gauging the outcome of silage, and so chemical analysis is more reliable and meaningful indicator of quality. On the other hand chemical assessments of the principal fermentation products provide an unequivocal basis on which to judge quality. Livestock require energy, protein, minerals and vitamins from their food. While fresh forages provide these essential items, conserved forages on the other hand may be deficient in one or more of them. The aim of the conservation process is to preserve as many of the original nutrients as possible, particularly energy and protein components (Woolford, 1984). Silage fermentation is important to preservation of forage with respect of feeding value and animal performance. Chemical and bacteriological changes in the silo during the fermentation process can affect adversely nutrient yield and quality (Moe and Carr, 1984). Many of the important chemical components of silage must be assayed in fresh or by extraction of the fresh material, since drying either by heat or lyophilisation, volatilises components such as acids or nitrogenous components, or effects conversion to other compounds (Abrams et al., 1987). Maize silage dorms the basis of winter rations for the vast majority of dairy and beef cattle production in Uruguay. Since nutrient intake, particularly energy, from forages is influenced by both voluntary dry matter intake and digestibility; there is a need for a rapid technique for predicting these parameters in farm advisory systems. Near Infrared Reflectance Spectroscopy (NIRS) is increasingly used as a rapid, accurate method of evaluating chemical constituents in cereals and dried forages. For many years NIRS was applied to assess chemical composition in dry materials (Norris et al., 1976, Flinn et al., 1992; Murray, 1993, De Boever et al., 1996, De la Roza et al., 1998). The objectives of this study were (1) to determine the potential of NIRS to assess the chemical composition of dried maize samples and (2) to attempt calibrations on undried samples either for farm advisory systems or for animal nutrition research purposes in Uruguay. NIRS were used to assess the chemical composition of whole - plant maize silage samples (Zea mays, L). A representative population of samples (n = 350) covering a wide distribution in chemical characteristics were used. Samples were scanned at 2 nm intervals over the wavelength range 400-2500 nm in a NIRS 6500 (NIRSystems, Silver Spring, MD, USA) in reflectance mode. Cross validation was used to avoid overfitting of the equations. The optimum calibrations were selected on the basis of minimizing the standard error of cross validation (SECV). The calibration statistics were R$^2$ 0. 86 (SECV: 11.4), 0.90 (SECV: 5.7), 0.90 (SECV: 16.9) for dry matter (DM), crude protein (CP), acid detergent fiber (ADF) in g kg$\^$-1/ on dry matter, respectively for maize silage samples. This work demonstrates the potential of NIRS to analyse whole - maize silage in a wide range of chemical characteristics for both advisory farm and nutritive evaluation.

  • PDF

The Study on Determination of Benefit Factor as Constructing Traffic Facilities Using ANP (ANP기법을 이용한 교통시설 건설사업의 편익항목 선정에 관한 연구)

  • Kim, Man Kyeong;Jung, Hun Young;Lee, Sang Yong
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.26 no.1D
    • /
    • pp.41-47
    • /
    • 2006
  • The construction of traffic facilities has generated a variety of problems in the equality and efficiency when it would be planed and evaluated. One of the reasons for these phenomena isn't the definition of an objective standard about benefit items. Thus, results of evaluation couldn't give a demonstration of confidence. But, the traffic facility construction and its operation costs are securely appeared. Therefor, it will be demonstrated to decide the benefit items in this study. Before deciding the items, user's satisfaction evaluation and economic analysis would be carried. We find out subway user's satisfaction higher than load traffic mode user in satisfaction evaluation, while subway's economic feasibility is lower than load facility, as a result of B/C analysis. In this inconsistent results, we found out that the benefit value is a little lower because of indefinite standard of it's items as comparing Busan Metropolitan City's population with subway's modal split ratio. Accordingly, we enumerate some benefit items in the case of feasibility evaluation as constructing traffic facility. And each of evaluation items' weight is estimated by using ANP. We found out that the weight value of accessibility has the highest one, that of punctuality has second, that of travel time has third, and benefit items according to improvement of user's traffic condition have much more important than those which were considered in the existence economic analysis.

Effect of a Deep Learning Framework-Based Computer-Aided Diagnosis System on the Diagnostic Performance of Radiologists in Differentiating between Malignant and Benign Masses on Breast Ultrasonography

  • Ji Soo Choi;Boo-Kyung Han;Eun Sook Ko;Jung Min Bae;Eun Young Ko;So Hee Song;Mi-ri Kwon;Jung Hee Shin;Soo Yeon Hahn
    • Korean Journal of Radiology
    • /
    • v.20 no.5
    • /
    • pp.749-758
    • /
    • 2019
  • Objective: To investigate whether a computer-aided diagnosis (CAD) system based on a deep learning framework (deep learning-based CAD) improves the diagnostic performance of radiologists in differentiating between malignant and benign masses on breast ultrasound (US). Materials and Methods: B-mode US images were prospectively obtained for 253 breast masses (173 benign, 80 malignant) in 226 consecutive patients. Breast mass US findings were retrospectively analyzed by deep learning-based CAD and four radiologists. In predicting malignancy, the CAD results were dichotomized (possibly benign vs. possibly malignant). The radiologists independently assessed Breast Imaging Reporting and Data System final assessments for two datasets (US images alone or with CAD). For each dataset, the radiologists' final assessments were classified as positive (category 4a or higher) and negative (category 3 or lower). The diagnostic performances of the radiologists for the two datasets (US alone vs. US with CAD) were compared Results: When the CAD results were added to the US images, the radiologists showed significant improvement in specificity (range of all radiologists for US alone vs. US with CAD: 72.8-92.5% vs. 82.1-93.1%; p < 0.001), accuracy (77.9-88.9% vs. 86.2-90.9%; p = 0.038), and positive predictive value (PPV) (60.2-83.3% vs. 70.4-85.2%; p = 0.001). However, there were no significant changes in sensitivity (81.3-88.8% vs. 86.3-95.0%; p = 0.120) and negative predictive value (91.4-93.5% vs. 92.9-97.3%; p = 0.259). Conclusion: Deep learning-based CAD could improve radiologists' diagnostic performance by increasing their specificity, accuracy, and PPV in differentiating between malignant and benign masses on breast US.

Experimental and numerical study on the structural behavior of Multi-Cell Beams reinforced with metallic and non-metallic materials

  • Yousry B.I. Shaheen;Ghada M. Hekal;Ahmed K. Fadel;Ashraf M. Mahmoud
    • Structural Engineering and Mechanics
    • /
    • v.90 no.6
    • /
    • pp.611-633
    • /
    • 2024
  • This study intends to investigate the response of multi-cell (MC) beams to flexural loads in which the primary reinforcement is composed of both metallic and non-metallic materials. "Multi-cell" describes beam sections with multiple longitudinal voids separated by thin webs. Seven reinforced concrete MC beams measuring 300×200×1800 mm were tested under flexural loadings until failure. Two series of beams are formed, depending on the type of main reinforcement that is being used. A control RC beam with no openings and six MC beams are found in these two series. Series one and two are reinforced with metallic and non-metallic main reinforcement, respectively, in order to maintain a constant reinforcement ratio. The first crack, ultimate load, deflection, ductility index, energy absorption, strain characteristics, crack pattern, and failure mode were among the structural parameters of the beams under investigation that were documented. The primary variables that vary are the kind of reinforcing materials that are utilized, as well as the kind and quantity of mesh layers. The outcomes of this study that looked at the experimental and numerical performance of ferrocement reinforced concrete MC beams are presented in this article. Nonlinear finite element analysis (NLFEA) was performed with ANSYS-16.0 software to demonstrate the behavior of composite MC beams with holes. A parametric study is also carried out to investigate the factors, such as opening size, that can most strongly affect the mechanical behavior of the suggested model. The experimental and numerical results obtained demonstrate that the FE simulations generated an acceptable degree of experimental value estimation. It's also important to demonstrate that, when compared to the control beam, the MC beam reinforced with geogrid mesh (MCGB) decreases its strength capacity by a maximum of 73.33%. In contrast, the minimum strength reduction value of 16.71% is observed in the MC beams reinforced with carbon reinforcing bars (MCCR). The findings of the experiments on MC beams with openings demonstrate that the presence of openings has a significant impact on the behavior of the beams, as there is a decrease in both the ultimate load and maximum deflection.