• Journal of applied mathematics & informatics
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• v.40 no.5_6
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• pp.1151-1165
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• 2022

Key drive of information quarrying is to digest liked information starting possible information. With the colossal amount of realities kept in documents, information bases, and stores, in the medical care area, it's inexorably significant, assuming excessive, arising compelling resources aimed at examination besides comprehension like information on behalf of the withdrawal of gen that might assistance in independent direction. Classification is method in information mining; it's characterized as per private, passing on item toward a specific course established happening it is likeness toward past instances of different substances trendy the data collection. In pre-owned recycled four Classification algorithm that incorporate Multi-Layer perception, KSTAR, Bayesian Network and PART to fabricate the grouping replicas arranged the malaria data collection and analyze the replicas, degree their exhibition through Waikato Environment for Knowledge Analysis introduced to Java Development Kit 8, then utilizations outfit's technique trendy promoting presentation of the arrangement methodology. The outcome perceived that Bayesian Network return most elevated exactness of 50.05% when working on followed by Multi-Layer perception, with 49.9% when helping is half, then, at that point, Kstar with precision of 49.44%, 49.5% when supporting individually and PART have lesser precision of 48.1% when helping, The exploration recommended that Bayesian Network is awesome toward remain utilized on Malaria data collection in our sanatoriums.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.319-331
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• 2022

The latest global COVID-19 pandemic has made the use of facial masks an important aspect of our lives. People are advised to cover their faces in public spaces to discourage illness from spreading. Using these face masks posed a significant concern about the exactness of the face identification method used to search and unlock telephones at the school/office. Many companies have already built the requisite data in-house to incorporate such a scheme, using face recognition as an authentication. Unfortunately, veiled faces hinder the detection and acknowledgment of these facial identity schemes and seek to invalidate the internal data collection. Biometric systems that use the face as authentication cause problems with detection or recognition (face or persons). In this research, a novel model has been developed to detect and recognize faces and persons for authentication using scale invariant features (SIFT) for the whole segmented face with an efficient local binary texture features (DLBP) in region of eyes in the masked face. The Fuzzy C means is utilized to segment the image. These mixed features are trained significantly in a convolution neural network (CNN) model. The main advantage of this model is that can detect and recognizing faces by assigning weights to the selected features aimed to grant or provoke permissions with high accuracy.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.99-106
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• 2023

Recently, many studies on crop yield prediction using deep learning technology have been conducted. These algorithms have difficulty constructing a linear map between input data sets and crop prediction results. Furthermore, implementation of these algorithms positively depends on the rate of acquired attributes. Deep reinforcement learning can overcome these limitations. This paper analyzes the performance of DQN, Double DQN and Dueling DQN to improve crop yield prediction. The DQN algorithm retains the overestimation problem. Whereas, Double DQN declines the over-estimations and leads to getting better results. The proposed models achieves these by reducing the falsehood and increasing the prediction exactness.

• Computers and Concrete
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• v.32 no.1
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• pp.87-97
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• 2023

The bending of a porous FG plate is discussed in this study using a novel higher quasi-3D hyperbolic shear deformation theory with four unknowns. The proposed theory takes into consideration the normal and transverse shear deformation effect and ensures the parabolic distribution of the transverse stresses through the thickness direction with zero-traction at the top and the bottom surfaces of the structure. Innovative porous functionally graded materials (FGM) have through-thickness porosity as a unique attribute that gradually varies with their qualities. An analytical solution of the static response of the perfect and imperfect FG plate was derived based on the virtual work principle and solved using Navier's procedure. The validity and the efficiency of the current model is confirmed by comparing the results with those obtained by others solutions. The comparisons showed that the present model is very efficient and simple in terms of computation time and exactness. The impact of the porosity parameter, aspect ratio, and thickness ratio on the bending of porous FG plate is shown through a discussion of several numerical results.

• The Journal of the Acoustical Society of Korea
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• v.25 no.2
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• pp.72-77
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• 2006

British acoustics in the nineteenth century is important as a foundation for modern acoustics in the history of acoustics. The Purpose and objective of acoustics was different from those in modern age. and musical motivation was distinguished among them. This study intends to clarify various aspects of interaction between music and acoustics in nineteenth-century Britain by examining related materials in both published and unpublished forms. Then music Provided acoustics with instruments, subjects, and personnel, and acoustics did much as musical science in helping to improve and develop musical scales and enhancing the exactness of measurement of absolute pitches. Music played an essential role in developing acoustics to a modern discipline in Europe, especially in Britain. all through the nineteenth century.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.1
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• pp.97-103
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• 2009

The status and the property of a tongue are the important indicators to diagnose one's health like physiological and clinicopathological changes of inner organs. However, the tongue diagnosis is affected by examination circumstances like a light source, patient's posture, and doctor's condition. To develop an automatic tongue diagnosis system for an objective and standardized diagnosis, classifying tongue coating is inevitable but difficult since the features like color and texture of the tongue coatings and substance have little difference, especially in the neighborhood on the tongue surface. The proposed method has two procedures; the first is to acquire the color table to classify tongue coatings and substance by automatically separating coating regions marked by oriental medical doctors, decomposing the color components of the region into hue, saturation and brightness and obtaining the 2nd order discriminant with statistical data of hue and saturation corresponding to each kind of tongue coatings, and the other is to apply the tongue region in an input image to the color table, resulting in separating the regions of tongue coatings and classifying them automatically. As a result, kinds of tongue coatings and substance were segmented from a face image corresponding to regions marked by oriental medical doctors and the color table for classification took hue and saturation values as inputs and produced the classification of the values into white coating, yellow coating and substance in a digital tongue diagnosis system. The coating regions classified by the proposed method were almost the same to the marked regions. The exactness of classification was 83%, which is the degree of correspondence between what Oriental medical doctors diagnosed and what the proposed method classified. Since the classified regions provide effective information, the proposed method can be used to make an objective and standardized diagnosis and applied to an ubiquitous healthcare system. Therefore, the method will be able to be widely used in Oriental medicine.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.119-124
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• 2009

In this paper, AMR-WB+ audio coder is implemented, in real-time, using Intel 400MHz Xscale PXA250 with 32bit RISC processor ARM9E-J(R)core. The assembly code for ARM9E-J(R)core is developed through the serial process of C code optimization, cross compile, assembly code manual optimization and adjusting the optimized code to Embedded Visual C++ platform. C code is trimmed on Visual C++ platform. Cross compile and assembly code manual optimization are performed on CodeWarrior with ARM compiler. Through these stages the code for both ARM EVM board and PDA is implemented. The average complexities of the code are 160.75MHz on encoder and 33.05MHz on decoder. In case of static link library(SLL), the required memories are 65.21Kbyte, 32.01Kbyte and 279.81Kbyte on encoder, decoder and common sources, respectively. The implemented coder is evaluated using 16 test vectors given by 3GPP to verify the bit-exactness of the coder.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.3
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• pp.224-230
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• 2002

In this paper, a counting algorithm hybridized with an adaptive automatic thresholding method based on Otsu's method and the algorithm that elongates markers obtained by the well-known watershed algorithm is proposed to enhance the exactness of the microcell counting in microscopic images. The proposed counting algorithm can be stated as follows. The transformed full image captured by CCD camera set up at microscope is divided into cropped images of m$\times$n blocks with an appropriate size. The thresholding value of the cropped image is obtained by Otsu's method and the image is transformed into binary image. The microbial cell images below prespecified pixels are regarded as noise and are removed in tile binary image. The smoothing procedure is done by the area opening and the morphological filter. Watershed algorithm and the elongating marker algorithm are applied. By repeating the above stated procedure for m$\times$n blocks, the m$\times$n segmented images are obtained. A superposed image with the size of 640$\times$480 pixels as same as original image is obtained from the m$\times$n segmented block images. By labeling the superposed image, the counting result on the image of microbial cells is achieved. To prove the effectiveness of the proposed mettled in counting the microbial cell on the image, we used Acinetobacter sp., a kind of ammonia-oxidizing bacteria, and compared the proposed method with the global Otsu's method the traditional watershed algorithm based on global thresholding value and human visual method. The result counted by the proposed method shows more approximated result to the human visual counting method than the result counted by any other method.

• The Transactions of the Korea Information Processing Society
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• v.3 no.1
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• pp.211-224
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• 1996

In the research area of estimation of the software development efforts, a number of researches have been accomplished in order to control the costs and to make software more competitive. However, most of them were restricted to the functional algorithm models or the statistic models. Moreover, since they are dealing with the cases of foreign countries, the results are hard to apply directly to the domestic environment for the efficient project management because of lack of accuracy, fitness, flexibility and portability. Therefore, it is appropriate to suggest and propose a new approach supported by artificial neural network which is composed of back propagation and feel-forward algorithms to improve the exactness of the efforts estimation and to advance practical uses. In this study, the artificial neural network approach is used to model the software cost estimation and the results are compared with the revised COCOMO and the multiregression model in order to validate the superiority of the model.

• Tribology and Lubricants
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• v.35 no.6
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• pp.369-375
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• 2019

This paper presents a new method on how to calculate the thrust forces acting on an auto-leveling device in headlamps for passenger vehicles. The leveling device is used to lower the angle of lights when a load in the trunk of the vehicle lifts it. In the process of the headlamp design, it is imperative to predict the external forces so that the designers can decide whether to proceed or not. The device is composed of three pivot joints with no reaction moment, a plate that holds the lamp, and a leveling motor that changes rotation to linear motion. In this study, force balance, moment balance, and geometric compatibility are applied to the leveling device system so that a nonlinear system of equations can be derived; the multi-dimensional Newton-Raphson algorithm is then used to solve these. A sensitivity analysis is carried out to verify which design variables affect the system the most: the mass of the lamp and the height between the pivot and leveling device affect the thrust forces the most. Then, considering the friction forces between the moving parts, the hysteresis of the forces are derived. An experimental apparatus, designed and developed in this study, is used to verify the exactness of the derived equations. The results from experiments coincide well with the calculated results. The friction hysteresis, in particular, proves this upon analysis.