• Title/Summary/Keyword: ALiDAR

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CENTRALIZING AND COMMUTING INVOLUTION IN RINGS WITH DERIVATIONS

  • Khan, Abdul Nadim
    • Communications of the Korean Mathematical Society
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    • v.34 no.4
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    • pp.1099-1104
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    • 2019
  • In [1], Ali and Dar proved the ${\ast}$-version of classical theorem due to Posner [15, Theorem] with involution of the second kind. The main objective of this paper is to improve the above mentioned result without the condition of the second kind involution. Moreover, a related result has been discussed.

Task Balancing Scheme of MPI Gridding for Large-scale LiDAR Data Interpolation (대용량 LiDAR 데이터 보간을 위한 MPI 격자처리 과정의 작업량 발란싱 기법)

  • Kim, Seon-Young;Lee, Hee-Zin;Park, Seung-Kyu;Oh, Sang-Yoon
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.9
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    • pp.1-10
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    • 2014
  • In this paper, we propose MPI gridding algorithm of LiDAR data that minimizes the communication between the cores. The LiDAR data collected from aircraft is a 3D spatial information which is used in various applications. Since there are many cases where the LiDAR data has too high resolution than actually required or non-surface information is included in the data, filtering the raw LiDAR data is required. In order to use the filtered data, the interpolation using the data structure to search adjacent locations is conducted to reconstruct the data. Since the processing time of LiDAR data is directly proportional to the size of it, there have been many studies on the high performance parallel processing system using MPI. However, previously proposed methods in parallel approach possess possible performance degradations such as imbalanced data size among cores or communication overhead for resolving boundary condition inconsistency. We conduct empirical experiments to verify the effectiveness of our proposed algorithm. The results show that the total execution time of the proposed method decreased up to 4.2 times than that of the conventional method on heterogeneous clusters.

Algorithm of Common Solutions to the Cayley Inclusion and Fixed Point Problems

  • Dar, Aadil Hussain;Ahmad, Mohammad Kalimuddin;Iqbal, Javid;Mir, Waseem Ali
    • Kyungpook Mathematical Journal
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    • v.61 no.2
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    • pp.257-267
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    • 2021
  • In this paper, we develop an iterative algorithm for obtaining common solutions to the Cayley inclusion problem and the set of fixed points of a non-expansive mapping in Hilbert spaces. A numerical example is given for the justification of our claim.

Rockfall Source Identification Using a Hybrid Gaussian Mixture-Ensemble Machine Learning Model and LiDAR Data

  • Fanos, Ali Mutar;Pradhan, Biswajeet;Mansor, Shattri;Yusoff, Zainuddin Md;Abdullah, Ahmad Fikri bin;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.35 no.1
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    • pp.93-115
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    • 2019
  • The availability of high-resolution laser scanning data and advanced machine learning algorithms has enabled an accurate potential rockfall source identification. However, the presence of other mass movements, such as landslides within the same region of interest, poses additional challenges to this task. Thus, this research presents a method based on an integration of Gaussian mixture model (GMM) and ensemble artificial neural network (bagging ANN [BANN]) for automatic detection of potential rockfall sources at Kinta Valley area, Malaysia. The GMM was utilised to determine slope angle thresholds of various geomorphological units. Different algorithms(ANN, support vector machine [SVM] and k nearest neighbour [kNN]) were individually tested with various ensemble models (bagging, voting and boosting). Grid search method was adopted to optimise the hyperparameters of the investigated base models. The proposed model achieves excellent results with success and prediction accuracies at 95% and 94%, respectively. In addition, this technique has achieved excellent accuracies (ROC = 95%) over other methods used. Moreover, the proposed model has achieved the optimal prediction accuracies (92%) on the basis of testing data, thereby indicating that the model can be generalised and replicated in different regions, and the proposed method can be applied to various landslide studies.

Collision-free local planner for unknown subterranean navigation

  • Jung, Sunggoo;Lee, Hanseob;Shim, David Hyunchul;Agha-mohammadi, Ali-akbar
    • ETRI Journal
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    • v.43 no.4
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    • pp.580-593
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    • 2021
  • When operating in confined spaces or near obstacles, collision-free path planning is an essential requirement for autonomous exploration in unknown environments. This study presents an autonomous exploration technique using a carefully designed collision-free local planner. Using LiDAR range measurements, a local end-point selection method is designed, and the path is generated from the current position to the selected end-point. The generated path showed the consistent collision-free path in real-time by adopting the Euclidean signed distance field-based grid-search method. The results consistently demonstrated the safety and reliability of the proposed path-planning method. Real-world experiments are conducted in three different mines, demonstrating successful autonomous exploration flights in environment with various structural conditions. The results showed the high capability of the proposed flight autonomy framework for lightweight aerial robot systems. In addition, our drone performed an autonomous mission in the tunnel circuit competition (Phase 1) of the DARPA Subterranean Challenge.

Multipath Ghosts in Through-the-Wall Radar Imaging: Challenges and Solutions

  • Abdalla, Abdi T.;Alkhodary, Mohammad T.;Muqaibel, Ali H.
    • ETRI Journal
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    • v.40 no.3
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    • pp.376-388
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    • 2018
  • In through-the-wall radar imaging (TWRI), the presence of front and side walls causes multipath propagation, which creates fake targets called multipath ghosts. They populate the scene and reduce the probability of correct target detection, classification, and localization. In modern TWRI, specular multipath exploitation has received considerable attention for reducing the effects of multipath ghosts. However, this exploitation is challenged by the requirements of the reflecting geometry, which is not always available. Currently, the demand for a high radar image resolution dictates the use of a large aperture and wide bandwidth. This results in a large amount of data. To tackle this problem, compressive sensing (CS) is applied to TWRI. With CS, only a fraction of the data are used to produce a high-quality image, provided that the scene is sparse. However, owing to multipath ghosts, the scene sparsity is highly deteriorated; hence, the performance of the CS algorithms is compromised. This paper presents and discusses the adverse effects of multipath ghosts in TWRI. It describes the physical formation of ghosts, their challenges, and existing suppression techniques.