• Journal of Information Processing Systems
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• v.16 no.2
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• pp.329-342
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• 2020

In recent years, emotional text classification is one of the essential research contents in the field of natural language processing. It has been widely used in the sentiment analysis of commodities like hotels, and other commentary corpus. This paper proposes an improved W-LDA (weighted latent Dirichlet allocation) topic model to improve the shortcomings of traditional LDA topic models. In the process of the topic of word sampling and its word distribution expectation calculation of the Gibbs of the W-LDA topic model. An average weighted value is adopted to avoid topic-related words from being submerged by high-frequency words, to improve the distinction of the topic. It further integrates the highest classification of the algorithm of support vector machine based on the extracted high-quality document-topic distribution and topic-word vectors. Finally, an efficient integration method is constructed for the analysis and extraction of emotional words, topic distribution calculations, and sentiment classification. Through tests on real teaching evaluation data and test set of public comment set, the results show that the method proposed in the paper has distinct advantages compared with other two typical algorithms in terms of subject differentiation, classification precision, and F1-measure.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.87-97
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• 2004

In this paper, we propose an algorithm for interlaced-to-progressive conversion by the weighted summation of the information collected from spatial do-interlacing method, in which the weighted edge based line average is applied, and the temporal method in which the motion compensation is employed by using hi-directional BMA (block matching algorithm). We employed time-recursive and motion adaptive processing as motion detection is involved. Also, a median filter is used to deal with limitation of the linear summation in which only an intermediate of values being involved is determined. The main goal of the approach is to overcome the shortcomings of each of the do-interlacing techniques without significant increment of the computational complexity, and the proposed method is apt to implement in hardware for real-time processing.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.2
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• pp.1-10
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• 1993

Frequency response functions(FRF) are the most fundamental data for the frequency domain identifications of structural systems. In this paper, an improved method for estimating FRF's is presented. The new FRF estimator takes the weighted average of two conventional estimators, $H_1$(f) and $H_2$(f), utilizing the fact that $H_2$(f) gives more accurate estimate at resonance, while $H_1$(f) yields better results at antiresonances. Based on the estimated FRF's, the modal parameters of the structures, such as, natural frequencies, damping ratios and mode shapes, are also estimated. The effectiveness of the proposed method is investigated through numerical and experimental studies. The estimated results indicate that the proposed estimator gives more accurate results than other estimators.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.73-76
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• 2018

A Gaussian noise is caused by surrounding environment or channel interference when transmitting image. The noise reduces not only image quality degradation but also high-level image processing performance. The Non-Local Means (NLM) filter finds similarity in the neighboring sets of pixels to remove noise and assigns weights according to similarity. The weighted average is calculated based on the weight. The NLM filter method shows low noise cancellation performance and high complexity in the process of finding the similarity using weight allocation and neighbor set. In order to solve these problems, we propose an algorithm that shows an excellent noise reduction performance by using Summed Square Image (SSI) to reduce the complexity and applying the weighting function based on a cosine Gaussian kernel function. Experimental results demonstrate the effectiveness of the proposed algorithm.

• Design & Manufacturing
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• v.13 no.2
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• pp.1-5
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• 2019

In this study, micro cellular injection molding of automobile head lamp housing with uneven thickness structure was performed to obtain improvement on deformation and light-weight of the part. The thickness of the presented model was uniformly modified to control the deformation of the molded part. In order to maximize the lightweight ratio, the model having an average thickness of 2.0 mm were thinly molded to an average thickness of 1.6 mm. GFM(Gas Free Molding) and CBM(Core Back Molding) technology were applied to improve the problems of the conventional foam molding method. Equal Heat & Cool system was also applied by 3D cooling core and individual flow control system. Warpage of the molded parts with even cooling was minimized. To improve the mechanical properties of foamed products, complex resin containing nano-filler was used and variation of mechanical properties was evaluated. It was shown that the weight reduction ratio of products with light-weighted injection molding was 8.9 % and the deformation of the products was improved from the maximum of 3.6 mm to 2.0 mm by applying Equal Heat & Cool mold cooling system. Also the mechanical strength reduction of foamed product was less than 12% at maximum.

• Proceedings of the KSR Conference
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• 2009.05a
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• pp.91-98
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• 2009

For maintaining railroad, accumulated passing tonnage is a determinant factor of appropriate rail replacement time. Recently, Seoul Metro's rail maintaining system and technology is being improved from previous years, which increasing a standard of rail replacement. Thus, this brings importance of estimating and managing for accumulated passing tonnage. In case of light weighted train such as subway, current method of calculating accumulated passing tonnage has defaults of misrepresenting accumulated passing tonnage data. Because current method is based on the weight of passengers and train., and operation data. In addition, currently there is no mechanical and electronic system that could represent and support the accurate data between heavy and non-heavy traffic area, and accumulated passing tonnage is calculated inaccurately by estimating average value each line. The current method of calculating accumulated passing tonnage misleads to unpredictable data that represent inappropriate rail replacement period, which leads to under or over analyzed replacement period. If accumulated passing tonnage is over estimated, rail replacement leads to waste of budget. Hence, it is necessary to construct reliable actual measurement system to manage rail's life safely and efficiently, and in this study the accumulated passing tonnage measurement device is installed with using rail pad of optical fiber sensors and its effect is analyzed.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1291-1298
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• 2023

Surveillance reconnaissance sensor network is used for surveillance in wartime and area of operation. In this paper, we propose a target localization method using the detection signal strength of seismic sensors. Relay equipment calculates the target location using coordinate information and detection signal strength of the seismic sensors. Target localization error deviation due to environmental factors was minimized by subtracting the dynamic offset when calculating the target location. Field test shows improvement of target localization through reduction of errors. The average error was decreased to 3.62m. Up to 62% improved result was obtained compared to weighted centroid localization method.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.49-54
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• 2017

Pathfinding for pedestrians provided by various navigation programs is based on a shortest path search algorithm. There is no big difference in their guide results, which makes the path quality more important. Multiple criteria should be included in the search cost to calculate the path quality, which is called a multi-criteria pathfinding. In this paper we propose a user adaptive pathfinding algorithm in which the cost function for a multi-criteria pathfinding is defined as a weighted sum of multiple criteria and the weights are learned automatically by Perceptron learning. Weight learning is implemented in two ways: short-term weight learning that reflects weight changes in real time as the user moves and long-term weight learning that updates the weights by the average value of the entire path after completing the movement. We use the weight update method with momentum for long-term weight learning, so that learning speed is improved and the learned weight can be stabilized. The proposed method is implemented as an app and is applied to various movement situations. The results show that customized pathfinding based on user preference can be obtained.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.92-98
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• 2017

Generally, image contains geometrical and radiometric errors. Census transform can solve the stereo mismatching problem caused by the radiometric distortion. Since the general census transform compares center of window pixel value with neighbor pixel value, it is hard to obtain an accurate matching result when the difference of pixel value is not large. To solve that problem, we propose a census transform method that applies different 4-step weight for each pixel value difference by applying an assistance window inside the window kernel. If the current pixel value is larger than the average of assistance window pixel value, a high weight value is given. Otherwise, a low weight value is assigned to perform a differential census transform. After generating an initial disparity map using a weighted census transform and input images, the gradient information is additionally used to model a cost function for generating a final disparity map. In order to find an optimal cost value, we use guided filtering. Since the filtering is performed using the input image and the disparity image, the object boundary region can be preserved. From the experimental results, we confirm that the performance of the proposed stereo matching method is improved compare to the conventional method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2414-2434
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• 2015

Among numerous localization schemes proposed specifically for Wireless Sensor Network (WSN), the range-free localization algorithms based on the received signal strength indication (RSSI) have attracted considerable research interest for their simplicity and low cost. As a typical range-free algorithm, Approximate Point In Triangulation test (APIT) suffers from significant estimation errors due to its theoretical defects and RSSI inaccuracy. To address these problems, a novel localization method called FIAPIT, which is a combination of an improved APIT (IAPIT) and a fuzzy logic system, is proposed. The proposed IAPIT addresses the theoretical defects of APIT in near (it's defined as a point adjacent to a sensor is closer to three vertexes of a triangle area where the sensor resides simultaneously) and far (the opposite case of the near case) cases partly. To compensate for negative effects of RSSI inaccuracy, a fuzzy system, whose logic inference is based on IAPIT, is applied. Finally, the sensor's coordinates are estimated as the weighted average of centers of gravity (COGs) of triangles' intersection areas. Each COG has a different weight inferred by FIAPIT. Numerical simulations were performed to compare four algorithms with varying system parameters. The results show that IAPIT corrects the defects of APIT when adjacent nodes are enough, and FIAPIT is better than others when RSSI is inaccuracy.