• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.143-154
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• 2021

In this paper, we propose a method of compressing digital hologram standardized data provided by JPEG Pleno. In numerical reconstruction of digital holograms, the addition of random phases for visualization reduces speckle noise due to interference and doubles the compression efficiency of holograms. Holograms are composed of completely complex floating point data, and due to ultra-high resolution and speckle noise, it is essential to develop a compression technology tailored to the characteristics of the hologram. First, frequency characteristics of hologram data are analyzed using various wavelet filters to analyze energy concentration according to filter types. Second, we introduce the subband selection algorithm using energy concentration. Finally, the JPEG2000, SPIHT, H.264 results using the Daubechies 9/7 wavelet filter of JPEG2000 and the proposed method are used to compress and restore, and the efficiency is analyzed through quantitative quality evaluation compared to the compression rate.

• Journal of the Korea Computer Graphics Society
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• v.24 no.5
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• pp.21-30
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• 2018

In this paper, we use Sound-tracing, a 3D sound technology based on ray-tracing that uses geometric method as auditory technology to enhance realism. The Sound-tracing is costly in the sound propagation stage. In order to reduce the sound propagation cost, we propose a method to calculate the average effective frame number of previous frames using the frame coherence property and to adjust the depth according to the space based on the calculated number. Experimental results show that the path loss rate is 0.72% and the traversal & Intersection test calculation amount is decreased by 85.13% and the frame rate is increased by 4.48% when the sound source is indoors, compared with the result of the case without depth control. When the sound source was outdoors, the path loss was 0% and the traversal & Intersection test calculation amount is decreased by 25.01% and the frame rate increased by 7.85%. This allowed the rendering performance to be increased while minimizing the path loss rate.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.3
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• pp.267-275
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• 2019

Currently, due to the widespread use of a smartphone, QR codes allow users to access a variety of added services. However, the QR codes posted on curved surfaces tend to be non-uniformly illuminated and bring about the decline of recognition rate. So, in this paper, the block-adaptive binarization policy is adopted to find an optimal threshold appropriate for bimodal image like QR codes. For a large block, its histogram distribution is found to get an initial threshold and then the block is partitioned to reflect the local characteristics of small blocks. Also, morphological operation is applied to their neighboring boundary at the discontinuous at the QR code junction. This paper proposes an authentication method based on the color code, uniquely painted within QR code. Through a variety of practical experiments, it is shown that the proposed algorithm outperforms the conventional method in detecting QR code and also maintains good recognition rate up to 40 degrees on curved surfaces.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.11
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• pp.69-78
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• 2019

The purpose of this study is to propose a modeling methodology through the exchange of coordinate data of a three-dimensional custom curtain wall panel between Rhino and Revit, and to examine the validity of the model implemented in the drawing. Although the modeling means and method are different, a fundamental principle is that all three-dimensional modeling begins by defining the position of the points, the most primitive element of geometry, in the XYZ coordinate space. For the BIM modeling methodology proposal based on this geometry basic concept, the functions and characteristics associated with the points of Rhino and Revit programs are identified, and then BIM implementation process model is organized and systemized through the setting of the interoperability process algorithm. The BIM implementation process model proposed in this study is (1) Modeling and panelizing surface into individual panels using Rhino and Grasshopper; (2) Extraction of vertex coordinate data from individual panels and create CSV file; (3) Curtain wall modeling through Adaptive Component Family in Revit and (4) Automatic creation of Revit curtain wall panels through API. The proposed process model is expected to help reduce design errors and improve component and construction quality by automatically converting general elements into architectural meaningful information, automating a set of processes that build them into BIM data, and enabling consistent and integrated design management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.714-720
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• 2021

The ITL (information theoretic learning) based on the kernel density estimation method that has successfully been applied to machine learning and signal processing applications has a drawback of severe sensitiveness in choosing proper kernel sizes. For the maximization of correntropy criterion (MCC) as one of the ITL-type criteria, several methods of adapting the remaining kernel size ( ) after removing the term have been studied. In this paper, it is shown that the main cause of sensitivity in choosing the kernel size derives from the term and that the adaptive adjustment of in the remaining terms leads to approach the absolute value of error, which prevents the weight adjustment from continuing. Thus, it is proposed that choosing an appropriate constant as the kernel size for the remaining terms is more effective. In addition, the experiment results when compared to the conventional algorithm show that the proposed method enhances learning performance by about 2dB of steady state MSE with the same convergence rate. In an experiment for channel models, the proposed method enhances performance by 4 dB so that the proposed method is more suitable for more complex or inferior conditions.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.11
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• pp.155-162
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• 2019

The construction industry is the highest safety accident causing industry as 28.55% portion of all industries' accidents in Korea. In particular, falling is the highest accidents type composed of 60.16% among the construction field accidents. Therefore, we analyzed the factors of major disaster affecting the fall accident and then derived feature importances by considering various variables. We used data collected from Korea Occupational Safety & Health Agency (KOSHA) for learning and predicting in the proposed model. We have an effort to predict the degree of occupational fall accidents by using the machine learning model, i.e., Adaboost, short for Adaptive Boosting. Adaboost is a machine learning meta-algorithm which can be used in conjunction with many other types of learning algorithms to improve performance. Decision trees were combined with AdaBoost in this model to predict and classify the degree of occupational fall accidents. HyOperpt was also used to optimize hyperparameters and to combine k-fold cross validation by hierarchy. We extracted and analyzed feature importances and affecting fall disaster by permutation technique. In this study, we verified the degree of fall accidents with predictive accuracy. The machine learning model was also confirmed to be applicable to the safety accident analysis in construction site. In the future, if the safety accident data is accumulated automatically in the network system using IoT(Internet of things) technology in real time in the construction site, it will be possible to analyze the factors and types of accidents according to the site conditions from the real time data.

• Journal of Biomedical Engineering Research
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• v.42 no.3
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• pp.80-85
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• 2021

We developed a model to classify the absence of cervical cancer using deep learning from the cervical image to which the histogram equalization algorithm was applied, and to compare the performance of each model. A total of 4259 images were used for this study, of which 1852 images were normal and 2407 were abnormal. And this paper applied Image Sharpening(IS), Histogram Equalization(HE), and Contrast Limited Adaptive Histogram Equalization(CLAHE) to the original image. Peak Signal-to-Noise Ratio(PSNR) and Structural Similarity index for Measuring image quality(SSIM) were used to assess the quality of images objectively. As a result of assessment, IS showed 81.75dB of PSNR and 0.96 of SSIM, showing the best image quality. CLAHE and HE showed the PSNR of 62.67dB and 62.60dB respectively, while SSIM of CLAHE was shown as 0.86, which is closer to 1 than HE of 0.75. Using ResNet-50 model with transfer learning, digital image-processed images are classified into normal and abnormal each. In conclusion, the classification accuracy of each model is as follows. 90.77% for IS, which shows the highest, 90.26% for CLAHE and 87.60% for HE. As this study shows, applying proper digital image processing which is for cervical images to Computer Aided Diagnosis(CAD) can help both screening and diagnosing.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.9-18
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• 2021

The 5G communication system employs the millimeter wave with the extremely high frequency. Since the high frequency signal has the strong straightness, the beamforming technology based on the multiple base stations is required for services covering wide range. The beamformer needs the angle-of-arrival(AOA) information of the signal incident to the antenna, and it is generally estimated through the high resolution AOA estimation algorithm such as Multiple Signal Classification (MUSIC) or Estimation of Signal Parameters via Rotational Invariacne Technique (ESPRIT). Although various antenna array shapes can be employed for the beamformer, a single shape (square, circle, or hexagonal) is typically utilized. In this paper, we introduce a transmitting/receiving beamforming system based on the combined array antenna with square and circular shapes, which is proper to various frequency signals, and evaluate its performance. For evaluating the performance of the proposed beamforming system based on the combined array antenna, we implement the computer simulation employing various scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1892-1912
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• 2022

With the massive demand and growth of cloud computing, virtualization plays an important role in providing services to end-users efficiently. However, with the increase in services over Cloud Computing, it is becoming more challenging to manage and run multiple Virtual Machines (VMs) in Cloud Computing because of excessive power consumption. It is thus important to overcome these challenges by adopting an efficient technique to manage and monitor the status of VMs in a cloud environment. Reduction of power/energy consumption can be done by managing VMs more effectively in the datacenters of the cloud environment by switching between the active and inactive states of a VM. As a result, energy consumption reduces carbon emissions, leading to green cloud computing. The proposed Efficient Dynamic VM Scheduling approach minimizes Service Level Agreement (SLA) violations and manages VM migration by lowering the energy consumption effectively along with the balanced load. In the proposed work, VM Scheduling for Efficient Dynamically Migrated VM (VMS-EDMVM) approach first detects the over-utilized host using the Modified Weighted Linear Regression (MWLR) algorithm and along with the dynamic utilization model for an underutilized host. Maximum Power Reduction and Reduced Time (MPRRT) approach has been developed for the VM selection followed by a two-phase Best-Fit CPU, BW (BFCB) VM Scheduling mechanism which is simulated in CloudSim based on the adaptive utilization threshold base. The proposed work achieved a Power consumption of 108.45 kWh, and the total SLA violation was 0.1%. The VM migration count was reduced to 2,202 times, revealing better performance as compared to other methods mentioned in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.9
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• pp.1405-1411
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• 2022

Power management is still an important issue in embedded environments as hardware advances like high-performance processors. Power management methods such as DVFS control CPU frequencies in an adaptive manner for efficient power management in polling-based I/O programs such as network communication. This paper presents the problems of the existing power management method and proposes a new power management method. Through this, it is possible to reduce electric consumption by increasing the polling cycle in situations where the frequency of data reception is low, and on the contrary, in situations where data reception is frequent, it can operate at the maximum frequency without performance degradation. After implementing this as a code layer on the embedded board and observing it through Atmel's Power Debugger, the proposed method showed a performance improvement of up to 30% in energy consumption compared to the existing power management method.