• Title/Summary/Keyword: Ranging Algorithms

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Multi-resolution Lossless Image Compression for Progressive Transmission and Multiple Decoding Using an Enhanced Edge Adaptive Hierarchical Interpolation

  • Biadgie, Yenewondim;Kim, Min-sung;Sohn, Kyung-Ah
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.12
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    • pp.6017-6037
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    • 2017
  • In a multi-resolution image encoding system, the image is encoded into a single file as a layer of bit streams, and then it is transmitted layer by layer progressively to reduce the transmission time across a low bandwidth connection. This encoding scheme is also suitable for multiple decoders, each with different capabilities ranging from a handheld device to a PC. In our previous work, we proposed an edge adaptive hierarchical interpolation algorithm for multi-resolution image coding system. In this paper, we enhanced its compression efficiency by adding three major components. First, its prediction accuracy is improved using context adaptive error modeling as a feedback. Second, the conditional probability of prediction errors is sharpened by removing the sign redundancy among local prediction errors by applying sign flipping. Third, the conditional probability is sharpened further by reducing the number of distinct error symbols using error remapping function. Experimental results on benchmark data sets reveal that the enhanced algorithm achieves a better compression bit rate than our previous algorithm and other algorithms. It is shown that compression bit rate is much better for images that are rich in directional edges and textures. The enhanced algorithm also shows better rate-distortion performance and visual quality at the intermediate stages of progressive image transmission.

Development of LiDAR Simulator for Backpack-mounted Mobile Indoor Mapping System

  • Chung, Minkyung;Kim, Changjae;Choi, Kanghyeok;Chung, DongKi;Kim, Yongil
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.2
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    • pp.91-102
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    • 2017
  • Backpack-mounted mapping system is firstly introduced for flexible movement in indoor spaces where satellite-based localization is not available. With the achieved advances in miniaturization and weight reduction, use of LiDAR (Light Detection and Ranging) sensors in mobile platforms has been increasing, and indeed, they have provided high-precision information on indoor environments and their surroundings. Previous research on the development of backpack-mounted mapping systems, has concentrated mostly on the improvement of data processing methods or algorithms, whereas practical system components have been determined empirically. Thus, in the present study, a simulator for a LiDAR sensor (Velodyne VLP-16), was developed for comparison of the effects of diverse conditions on the backpack system and its operation. The simulated data was analyzed by visual inspection and comparison of the data sets' statistics, which differed according to the LiDAR arrangement and moving speed. Also, the data was used as input to a point-cloud registration algorithm, ICP (Iterative Closest Point), to validate its applicability as pre-analysis data. In fact, the results indicated centimeter-level accuracy, thus demonstrating the potentials of simulation data to be utilized as a tool for performance comparison of pointdata processing methods.

A Study on the Quantitative Analysis of Scientific Communication (학술 커뮤니케이션의 수량학적 분석에 관한 연구)

  • Kim Hyun-hee
    • Journal of the Korean Society for Library and Information Science
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    • v.14
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    • pp.93-130
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    • 1987
  • Scientific communication is an information exchange activity between scientists. Scientific communication is carried out in a variety of informal and formal ways. Basically, informal communication takes place by word of mouth, whereas formal communication occurs via the written word. Science is a highly interdependent activity in which each scientist builds upon the work of colleagues past and present. Consequently, science depends heavily on scientific communication. In this study, three mathematical models, namly Brillouin measure, logistic equation, and Markov chain are examined. These models provide one with a means of describing and predicting the behavior of scientific communication process. These mathematical models can be applied to construct quality filtering algorithms for subject literature which identify synthesized elements (authors, papers, and journals). Each suggests a different type of application. Quality filtering for authors can be useful to funding agencies in terms of identifying individuals doing the best work in a given area or subarea. Quality filtering with respect to papers can be useful in constructing information retrieval and dissemination systems for the community of scientists interested m the field. The quality filtering of journals can be a basis for the establishment of small quality libraries based on local interests in a variety of situations, ranging from the collection of an individual scientist or physician to research centers to developing countries. The objective of this study is to establish the theoretical framework for informetrics which is defined as the quantitative analysis of scientific communication, by investigating mathematical models of scientific communication.

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A Parametric Voice Activity Detection Based on the SPD-TE for Nonstationary Noises (비정체성 잡음을 위한 SPD-TE 기반 계수형 음성 활동 탐지)

  • Koo, Boneung
    • The Journal of the Acoustical Society of Korea
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    • v.34 no.4
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    • pp.310-315
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    • 2015
  • A single channel VAD (Voice Activity Detection) algorithm for nonstationary noise environment is proposed in this paper. Threshold values of the feature parameter for VAD decision are updated adaptively based on estimates of means and standard deviations of past non-speech frames. The feature parameter, SPD-TE (Spectral Power Difference-Teager Energy), is obtained by applying the Teager energy to the WPD (Wavelet Packet Decomposition) coefficients. It was reported previously that the SPD-TE is robust to noise as a feature for VAD. Experimental results by using TIMIT speech and NOISEX-92 noise databases show that decision accuracy of the proposed algorithm is comparable to several typical VAD algorithms including standards for SNR values ranging from 10 to -10 dB.

Requirements Analysis of Image-Based Positioning Algorithm for Vehicles

  • Lee, Yong;Kwon, Jay Hyoun
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.5
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    • pp.397-402
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    • 2019
  • Recently, with the emergence of autonomous vehicles and the increasing interest in safety, a variety of research has been being actively conducted to precisely estimate the position of a vehicle by fusing sensors. Previously, researches were conducted to determine the location of moving objects using GNSS (Global Navigation Satellite Systems) and/or IMU (Inertial Measurement Unit). However, precise positioning of a moving vehicle has lately been performed by fusing data obtained from various sensors, such as LiDAR (Light Detection and Ranging), on-board vehicle sensors, and cameras. This study is designed to enhance kinematic vehicle positioning performance by using feature-based recognition. Therefore, an analysis of the required precision of the observations obtained from the images has carried out in this study. Velocity and attitude observations, which are assumed to be obtained from images, were generated by simulation. Various magnitudes of errors were added to the generated velocities and attitudes. By applying these observations to the positioning algorithm, the effects of the additional velocity and attitude information on positioning accuracy in GNSS signal blockages were analyzed based on Kalman filter. The results have shown that yaw information with a precision smaller than 0.5 degrees should be used to improve existing positioning algorithms by more than 10%.

Algorithmic approach to the lymphatic leak after vascular reconstruction: a systematic review

  • Nicksic, Peter John;Condit, Kevin Michael;Nayar, Harry Siva;Michelotti, Brett Foster
    • Archives of Plastic Surgery
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    • v.48 no.4
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    • pp.404-409
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    • 2021
  • Background To date, there are no consensus guidelines for management of lymphatic leak in groin vascular reconstruction patients. The goal of this study is to review the relevant literature to determine alternatives for treatment and to design an evidence-based algorithm to minimize cost and morbidity and maximize efficacy. Methods A systematic review of the literature was conducted per Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. Two independent reviewers applied agreed-upon inclusion and exclusion criteria to eligible records. Studies that included patients who underwent groin dissection for oncologic diagnoses and level 5 data were excluded. Interventions were then categorized by efficacy using predetermined criteria. Results Our search yielded 333 records, of which eight studies were included. In four studies, the success of lymphatic ligation ranged from 75% to 100%, with average days to resolution ranging from 0 to 9. Conservative management in the form of elevation, compression, and bedrest may prolong time to resolution of lymphatic leak (14-24 days) and therefore cost. Conclusions The majority of patients should be offered early operative intervention in the form of lymphatic ligation with or without a primary muscle flap. If the patient is not an operative candidate, a trial of conservative management should be attempted before other nonsurgical interventions.

A Multi-Scale Parallel Convolutional Neural Network Based Intelligent Human Identification Using Face Information

  • Li, Chen;Liang, Mengti;Song, Wei;Xiao, Ke
    • Journal of Information Processing Systems
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    • v.14 no.6
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    • pp.1494-1507
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    • 2018
  • Intelligent human identification using face information has been the research hotspot ranging from Internet of Things (IoT) application, intelligent self-service bank, intelligent surveillance to public safety and intelligent access control. Since 2D face images are usually captured from a long distance in an unconstrained environment, to fully exploit this advantage and make human recognition appropriate for wider intelligent applications with higher security and convenience, the key difficulties here include gray scale change caused by illumination variance, occlusion caused by glasses, hair or scarf, self-occlusion and deformation caused by pose or expression variation. To conquer these, many solutions have been proposed. However, most of them only improve recognition performance under one influence factor, which still cannot meet the real face recognition scenario. In this paper we propose a multi-scale parallel convolutional neural network architecture to extract deep robust facial features with high discriminative ability. Abundant experiments are conducted on CMU-PIE, extended FERET and AR database. And the experiment results show that the proposed algorithm exhibits excellent discriminative ability compared with other existing algorithms.

Investigation of blasting impact on limestone of varying quality using FEA

  • Dimitraki, Lamprini S.;Christaras, Basile G.;Arampelos, Nikolas D.
    • Geomechanics and Engineering
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    • v.25 no.2
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    • pp.111-121
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    • 2021
  • Large deformation and rapid pressure propagation take place inside the rock mass under the dynamic loads caused by the explosives, on quarry faces in order to extract aggregate material. The complexity of the science of rock blasting is due to a number of factors that affect the phenomenon. However, blasting engineering computations could be facilitated by innovative software algorithms in order to determine the results of the violent explosion, since field experiments are particularly difficult to be conducted. The present research focuses on the design of a Finite Element Analysis (FEA) code, for investigating in detail the behavior of limestone under the blasting effect of Ammonium Nitrate & Fuel Oil (ANFO). Specifically, the manuscript presents the FEA models and the relevant transient analysis results, simulating the blasting process for three types of limestone, ranging from poor to very good quality. The Finite Element code was developed by applying the Jones-Wilkins-Lee (JWL) equation of state to describe the thermodynamic state of ANFO and the pressure dependent Drucker-Prager failure criterion to define the limestone plasticity behavior, under blasting induced, high rate stress. A progressive damage model was also used in order to define the stiffness degradation and destruction of the material. This paper performs a comparative analysis and quantifies the phenomena regarding pressure, stress distribution and energy balance, for three types of limestone. The ultimate goal of this research is to provide an answer for a number of scientific questions, considering various phenomena taking place during the explosion event, using advanced computational tools.

Forecasting River Water Levels in the Bac Hung Hai Irrigation System of Vietnam Using an Artificial Neural Network Model

  • Hung Viet Ho
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.37-37
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    • 2023
  • There is currently a high-accuracy modern forecasting method that uses machine learning algorithms or artificial neural network models to forecast river water levels or flowrate. As a result, this study aims to develop a mathematical model based on artificial neural networks to effectively forecast river water levels upstream of Tranh Culvert in North Vietnam's Bac Hung Hai irrigation system. The mathematical model was thoroughly studied and evaluated by using hydrological data from six gauge stations over a period of twenty-two years between 2000 and 2022. Furthermore, the results of the developed model were also compared to those of the long-short-term memory neural networks model. This study performs four predictions, with a forecast time ranging from 6 to 24 hours and a time step of 6 hours. To validate and test the model's performance, the Nash-Sutcliffe efficiency coefficient (NSE), mean absolute error, and root mean squared error were calculated. During the testing phase, the NSE of the model varies from 0.981 to 0.879, corresponding to forecast cases from one to four time steps ahead. The forecast results from the model are very reasonable, indicating that the model performed excellently. Therefore, the proposed model can be used to forecast water levels in North Vietnam's irrigation system or rivers impacted by tides.

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REAL-TIME 3D MODELING FOR ACCELERATED AND SAFER CONSTRUCTION USING EMERGING TECHNOLOGY

  • Jochen Teizer;Changwan Kim;Frederic Bosche;Carlos H. Caldas;Carl T. Haas
    • International conference on construction engineering and project management
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    • 2005.10a
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    • pp.539-543
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    • 2005
  • The research presented in this paper enables real-time 3D modeling to help make construction processes ultimately faster, more predictable and safer. Initial research efforts used an emerging sensor technology and proved its usefulness in the acquisition of range information for the detection and efficient representation of static and moving objects. Based on the time-of-flight principle, the sensor acquires range and intensity information of each image pixel within the entire sensor's field-of-view in real-time with frequencies of up to 30 Hz. However, real-time working range data processing algorithms need to be developed to rapidly process range information into meaningful 3D computer models. This research ultimately focuses on the application of safer heavy equipment operation. The paper compares (a) a previous research effort in convex hull modeling using sparse range point clouds from a single laser beam range finder, to (b) high-frame rate update Flash LADAR (Laser Detection and Ranging) scanning for complete scene modeling. The presented research will demonstrate if the FlashLADAR technology can play an important role in real-time modeling of infrastructure assets in the near future.

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