• Journal of KSNVE
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• v.8 no.6
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• pp.1121-1129
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• 1998

This research is concerned with the multiple PPF and the modified LQG controller design for active vibration control of intelligent structures. The intelligent structure is defined as the structure equipped with smart actuators and sensors. Various control techniques aimed for the piezoceramic sensors and actuators have been proposed for the active vibration control of smart structures and some of them prove their effectiveness experimentally. In this paper, the multiple PPF controller and the modified LQG controller are developed and applied to the smart grid structure. The multiple PPF control and the modified LQG control can be classified as the classical and the modern control techniques. respectively. The experimental results show that both control techniques are effective in suppressing vibrations. Two control techniques are compared with respect to the design process. the ease of implementation and the effectiveness

• Korean Management Science Review
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• v.11 no.3
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• pp.13-26
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• 1994

In this paper we studied an integration scheme of some simplex algorithms and some efficient techniques to get the stable solution in linear programming code. And we developed a linear programming package (LPAK) by introducing this scheme and techniques. In LPAK three different algorithms were integrated, which were two primal simplex algorithms using Two phase method and big-M method respectively, and the dual simplex algorithm. LPAK introduces several heuristic techniques in each step of simplex method in order to enhance the stability and efficiency. They were new heuristic methods in structuring initial basis, choosing entering variable, choosing dropping variable and performing reinversion. The experimental results on the NETLIB problems showed that LPAK provided the stable solutions.

• Structural Engineering and Mechanics
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• v.32 no.4
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• pp.489-500
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• 2009

The aim of this paper is to compare wavelet, kurtosis and pseudofractal based techniques for structural health monitoring in the presence of measurement noise. A detailed comparison and assessment of these techniques have been carried out in this paper through numerical experiments for the calibration of damage extent of a simply supported beam with an open crack serving as an illustrative example. The numerical experiments are deemed critical due to limited amount of experimental data available in the field of singularity based detection of damage. A continuous detectibility map has been proposed for comparing various techniques qualitatively. Efficiency surfaces have been constructed for wavelet, kurtosis and pseudofractal based calibration of damage extent as a function of damage location and measurement noise level. Levels of noise have been identified for each technique where a sudden drop of calibration efficiency is observed marking the onset of damage masking regime by measurement noise.

• Journal of Computing Science and Engineering
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• v.2 no.2
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• pp.137-160
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• 2008

The increasing availability of personal location data pushed by the widespread use of location-sensing technologies raises concerns with respect to the safeguard of location privacy. To address such concerns location privacy-preserving techniques are being investigated. An important area of application for such techniques is represented by Location Based Services (LBS). Many privacy-preserving techniques designed for LBS are based on the idea of forwarding to the LBS provider obfuscated locations, namely position information at low spatial resolution, in place of actual users' positions. Obfuscation techniques are generally based on the use of geometric methods. In this paper, we argue that such methods can lead to the disclosure of sensitive location information and thus to privacy leaks. We thus propose a novel method which takes into account the semantic context in which users are located. The original contribution of the paper is the introduction of a comprehensive framework consisting of a semantic-aware obfuscation model, a novel algorithm for the generation of obfuscated spaces for which we report results from an experimental evaluation and reference architecture.

• International Journal of CAD/CAM
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• v.3 no.1_2
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• pp.111-117
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• 2003

The paper presents an efficient algorithm based on ROAM for visualization of large scale terrain models in real-time. The quality and smoothness of the terrain data visualization within a 3D interactive environment is preserved, while the complexity of the algorithm is kept on a reasonable level. The main contribution of the paper is an introduction of a number of efficient techniques such as implicit coordinates method within the patch array representing ROAM and the viewpoint dependent triangle rendering method for dynamic level of detail (LOD) updates. In addition, the paper presents experimental comparison of a variety of culling techniques, including a newly introduced method: relational position culling. These techniques are incorporated in the visualization software, which allows to achieve more realistic terrain representation and the real-time level of detail reduction.

• International Journal of Fluid Machinery and Systems
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• v.2 no.2
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• pp.179-188
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• 2009

Recent development of high speed computers and use of optimization techniques have given a big momentum of turbomachinery design replacing expensive experimental cost as well as trial and error approaches. The surrogate based optimization techniques being used for aerodynamic turbomachinery designs coupled with Reynolds-averaged Navier-Stokes equations analysis involve single- and multi-objective optimization methods. The objectives commonly tried to improve were adiabatic efficiency, pressure ratio, weight etc. Presently coupling the fluid flow and structural analysis is being tried to find better design in terms of weight, flutter and vibration, and turbine life. The present article reviews the surrogate based optimization techniques used recently in turbomachinery shape optimizations.

• Journal of the Korean Society for information Management
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• v.1 no.1
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• pp.43-62
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• 1984

The present study has two main objectives. The first objective is to devise a new term weighting technique which can be used to weight the significance value of each word stem in a test collection of documents on the subject of "enteral hyperalimentation." The next objective is to evaluate retrieval performance of proposed term weighting technique, together with four other term weighting techniques, by conducting a set of experiments. The experimental results have shown that the performance of Sparck Jones's inverse document frequency weighting and the proposed term significance weighting techniques produced better recall and precision ratios than the other three complex weighting techniques.

• Speech Sciences
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• v.11 no.4
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• pp.17-28
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• 2004

In this paper, we propose a statistical approach to improve the performance of spectral quantization of speech coders. The proposed techniques compensate for the distortion in a decoded line spectrum pairs (LSP) vector based on a statistical mapping function between a decoded LSP vector and its corresponding original LSP vector. We first develop two codebook-based probabilistic matching (CBPM) methods based on linear mapping functions according to different assumption of distribution of LSP vectors. In addition, we propose an iterative procedure for the two CBPMs. We apply the proposed techniques to a predictive vector quantizer used for the IS-641 speech coder. The experimental results show that the proposed techniques reduce average spectral distortion by around 0.064dB.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.107-112
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• 2024

Nowadays the deadly virus famous as COVID-19 spread all over the world starts from the Wuhan China in 2019. This disease COVID-19 Virus effect millions of people in very short time. There are so many symptoms of COVID19 perhaps the Identification of a person infected with COVID-19 virus is really a difficult task. Moreover it's a challenging task to identify whether a person or individual have covid test positive or negative. We are developing a framework in which we used machine learning techniques..The proposed method uses DecisionTree, KNearestNeighbors, GaussianNB, LogisticRegression, BernoulliNB , RandomForest , Machine Learning methods as the classifier for diagnosis of covid ,however, 5-fold and 10-fold cross-validations were applied through the classification process. The experimental results showed that the best accuracy obtained from Decision Tree classifiers. The data preprocessing techniques have been applied for improving the classification performance. Recall, accuracy, precision, and F-score metrics were used to evaluate the classification performance. In future we will improve model accuracy more than we achieved now that is 93 percent by applying different techniques

• BMB Reports
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• v.57 no.3
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• pp.135-142
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• 2024

DNA methylation is one of the most extensively studied epigenetic regulatory mechanisms, known to play crucial roles in various organisms. It has been implicated in the regulation of gene expression and chromatin changes, ranging from global alterations during cell state transitions to locus-specific modifications. 5-hydroxymethylcytosine (5hmC) is produced by a major oxidation, from 5-methylcytosine (5mC), catalyzed by the ten-eleven translocation (TET) enzymes, and is gradually being recognized for its significant role in genome regulation. With the development of state-of-the-art experimental techniques, it has become possible to detect and distinguish 5mC and 5hmC at base resolution. Various techniques have evolved, encompassing chemical and enzymatic approaches, as well as third-generation sequencing techniques. These advancements have paved the way for a thorough exploration of the role of 5hmC across a diverse array of cell types, from embryonic stem cells (ESCs) to various differentiated cells. This review aims to comprehensively report on recent techniques and discuss the emerging roles of 5hmC.