- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Growth, Luminescence and Scintillation Characterization of Disodium Di-tungstate (Na2W2O7) Crystal Scintillator
摘要： A single crystal of Na2W2O7 was grown by using the conventional Czochralski technique. The crystal structure of the grown sample was veri?ed by using a powder X-ray di?raction (XRD) analysis. The luminescence, as well as scintillation, properties of the crystals were evaluated at room temperature. The emission spectra of the crystal were obtained by irradiating the sample with X-ray and proton sources. The trap level of the grown crystal was studied from 325 K to 500 K, and di?erent kinematic parameters were calculated. The scintillation properties such as; energy resolution, light yield, ?uorescence decay time and α/β ratio of the crystal, were studied by using γ- (662 keV from 137Cs) and α- (5.4 MeV from 241Am) sources. The luminescence and the scintillation results revealed that the Na2W2O7 crystal would be a good material for the dark matter search and for high-energy physics experiment.
关键词： Czochralski technique,Na2W2O7,Dark matter search,Luminescence and scintillation
更新于2025-11-14 15:30:11
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Deep structure tensor graph search framework for automated extraction and characterization of retinal layers and fluid pathology in retinal SD-OCT scans
摘要： Maculopathy is a group of retinal disorders that affect macula and cause severe visual impairment if not treated in time. Many computer-aided diagnostic methods have been proposed over the past that automatically detect macular diseases. However, to our best knowledge, no literature is available that provides an end-to-end solution for analyzing healthy and diseased macular pathology. This paper proposes a vendor-independent deep convolutional neural network and structure tensor graph search-based segmentation framework (CNN-STGS) for the extraction and characterization of retinal layers and fluid pathology, along with 3-D retinal profiling. CNN-STGS works by first extracting nine layers from an optical coherence tomography (OCT) scan. Afterward, the extracted layers, combined with a deep CNN model, are used to automatically segment cyst and serous pathology, followed by the autonomous 3-D retinal profiling. CNN-STGS has been validated on publicly available Duke datasets (containing a cumulative of 42,281 scans from 439 subjects) and Armed Forces Institute of Ophthalmology dataset (containing 4,260 OCT scans of 51 subjects), which are acquired through different OCT machinery. The performance of the CNN-STGS framework is validated through the marked annotations, and it significantly outperforms the existing solutions in various metrics. The proposed CNN-STGS framework achieved a mean Dice coefficient of 0.906 for segmenting retinal fluids, along with an accuracy of 98.75% for characterizing cyst and serous fluid from diseased retinal OCT scans.
关键词： convolutional neural network (CNN),Optical coherence tomography (OCT),maculopathy,ophthalmology,graph search
更新于2025-09-23 15:23:52
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Atomic Structures and Electronic Properties of Large-Sized GeN Clusters (N?=?45, 50, 55, 60, 65, 70) by First-Principles Global Search
摘要： A two-step unbiased global search was performed to explore the lowest-energy structures of large GeN clusters with N = 45–70 atoms. It has been revealed that the most stable structures for these large-sized Ge clusters are stuffed cages. Based on the lowest-energy structures, the theoretical results for the size-dependent structural transition, binding energy and ionization potential compare well with the available experimental data. Overall speaking, the structural characteristics and electronic properties of GeN clusters in the considered size range gradually approach the bulk limits, but still with certain deviations.
关键词： Global search,Germanium cluster,Structure
更新于2025-09-23 15:23:52
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Rational Electron Transmission Structure in an Ag <sub/>2</sub> O/TiO <sub/>2</sub> (anatase-B) System for Effective Enhancement of Visible Light Photocatalytic Activity
摘要： Efficient optical flow estimation with high accuracy is a challenging problem in computer vision. In this paper, we present a simple but efficient segmentation-based PatchMatch framework to address this issue. Specifically, it firstly generates sparse seeds without losing important motion information by oversegmentation, and then yields sparse matches by adopting a coarse-to-fine PatchMatch with sparse seeds. Such a scheme enhances the robustness of global regularization and yields better matching results compared with the existing NNF techniques while leading to a significant speed-up due to the sparsity of these seeds. Simultaneously, we introduce an extended nonlocal propagation and adaptive random search to address the basic limitation of traditional coarse-to-fine framework in handing motion details that often vanish at coarser levels. Finally, we obtain dense matches at the finest level through an efficient sparse-to-dense matching according to the cues of oversegmentation. While performing an efficient approximation for oversegmentation, the proposed algorithm runs significantly fast and are robust to large displacements while preserving important motion details. It also achieves good performance on the challenging MPI-Sintel and Kitti flow 2015 datasets.
关键词： extended nonlocal propagation,adaptive random search,Optical flow,PatchMatch,oversegmentation
更新于2025-09-23 15:23:52
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Automated Method for Retinal Artery/Vein Separation via Graph Search Metaheuristic Approach
摘要： Separation of the vascular tree into arteries and veins is a fundamental prerequisite in the automatic diagnosis of retinal biomarkers associated with systemic and neurodegenerative diseases. In this paper, we present a novel graph search metaheuristic approach for automatic separation of arteries/veins (A/V) from color fundus images. Our method exploits local information to disentangle the complex vascular tree into multiple subtrees, and global information to label these vessel subtrees into arteries and veins. Given a binary vessel map, a graph representation of the vascular network is constructed representing the topological and spatial connectivity of the vascular structures. Based on the anatomical uniqueness at vessel crossing and branching points, the vascular tree is split into multiple subtrees containing arteries and veins. Finally, the identified vessel subtrees are labeled with A/V based on a set of hand-crafted features trained with random forest classifier. The proposed method has been tested on four different publicly available retinal datasets with an average accuracy of 94.7%, 93.2%, 96.8% and 90.2% across AV-DRIVE, CT-DRIVE, INSPIRE-AVR and WIDE datasets, respectively. These results demonstrate the superiority of our proposed approach in outperforming state-of-the-art methods for A/V separation.
关键词： Graph search,Vessel keypoints,Artery/Vein classification,Retinal image
更新于2025-09-23 15:23:52
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Research on feature point extraction and matching machine learning method based on light field imaging
摘要： At present, there are many methods to realize the matching of specified images with features, and the basic components include image feature point detection, feature description, and image matching. Based on this background, this article has done different research and exploration around these three aspects. The image feature point detection method is firstly studied, which commonly include image edge information-based feature detection method, corner information-based detection method, and various interest operators. However, all of the traditional detection methods are involved in problems of large computation burden and time consumption. In order to solve this problem, a feature detection method based on image grayscale information-FAST operator is used in this paper, which is combined with decision tree theory to effectively improve the speed of extracting image feature points. Then, the feature point description method BRIEF operator is studied, which is a local expression of detected image feature points based on descriptors. Since the descriptor does not have rotation invariance, the detection operator is endowed by a direction that is proposed in this paper, and then the local feature description is conducted on the feature descriptor to generate a binary string array containing direction information. Finally, the feature matching machine learning method is analyzed, and the nearest search method is used to find the nearest feature point pair in Euclidean distance, of which the calculation burden is small. The simulation results show that the proposed nearest neighbor search and matching machine learning algorithm has higher matching accuracy and faster calculation speed compared with the classical feature matching algorithm, which has great advantages in processing a large number of array images captured by the light field camera.
关键词： Nearest neighbor search,Light field imaging,Image matching,Machine learning
更新于2025-09-23 15:23:52
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[IEEE 2018 IEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC) - Hanoi (2018.9.12-2018.9.14)] 2018 IEEE 12th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC) - Designing Compact Convolutional Neural Network for Embedded Stereo Vision Systems
摘要： Autonomous systems are used in a wide range of domains from indoor utensils to autonomous robot surgeries and self-driving cars. Stereo vision cameras probably are the most flexible sensing way in these systems since they can extract depth, luminance, color, and shape information. However, stereo vision based applications suffer from huge image sizes and computational complexity leading system to higher power consumption. To tackle these challenges, in the first step, GIMME2 stereo vision system [1] is employed. GIMME2 is a high-throughput and cost efficient FPGA-based stereo vision embedded system. In the next step, we present a framework for designing an optimized Deep Convolutional Neural Network (DCNN) for time constraint applications and/or limited resource budget platforms. Our framework tries to automatically generate a highly robust DCNN architecture for image data receiving from stereo vision cameras. Our proposed framework takes advantage of a multi-objective evolutionary optimization approach to design a near-optimal network architecture for both the accuracy and network size objectives. Unlike recent works aiming to generate a highly accurate network, we also considered the network size parameters to build a highly compact architecture. After designing a robust network, our proposed framework maps generated network on a multi/many core heterogeneous System-on-Chip (SoC). In addition, we have integrated our framework to the GIMME2 processing pipeline such that it can also estimate the distance of detected objects. The generated network by our framework offers up to 24x compression rate while losing only 5% accuracy compare to the best result on the CIFAR-10 dataset.
关键词： Deep Convolutional Neural Network,Stereo Vision Systems,Neural Processing Unit,Neural Network Architecture Search
更新于2025-09-23 15:22:29
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Semiconducting B<sub>13</sub>C<sub>2</sub> system: Structure search and DFT-based analysis
摘要： DFT calculation on Boron Carbide in B13C2 stoichiometry using a 15-atom unit cell necessarily results in metallic ground state regardless of the crystal structure. This is because such a unit cell consists of odd number of electrons, and hence complete filling of the top most band(s) of nonzero occupancy is impossible. This is in contrast to the observed semiconducting nature. If the crystal structure of B13C2 is made of a 30-atom unit cell which cannot be reduced to a 15 atom cell, there is a possibility of obtaining either a metallic or a semiconducting state as such a cell consists of an even number of electrons. In this work the evolutionary algorithm based structure search using 30-atom unit cells has yielded a previously unreported semiconducting system of B13C2 with unique bonding pattern. The mechanical and dynamical stability of the system have been properly established through the computation of elastic constants and phonon spectra. Its bond lengths, elastic moduli, hardness and infrared spectrum are in good agreement with experimental data.
关键词： Boron Carbide,elastic constants,evolutionary algorithm,DFT,phonon spectra,semiconducting,structure search,B13C2
更新于2025-09-23 15:22:29
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Fractional Order Based Modeling and Identification of Coupled Creep and Hysteresis Effects in Piezoelectric Actuators
摘要： In this paper, Monte Carlo tree search (MCTS) is introduced for controlling the Pac-Man character in the real-time game Ms Pac-Man. MCTS is used to find an optimal path for an agent at each turn, determining the move to make based on the results of numerous randomized simulations. Several enhancements are introduced in order to adapt MCTS to the real-time domain. Ms Pac-Man is an arcade game, in which the protagonist has several goals but no conclusive terminal state. Unlike games such as Chess or Go there is no state in which the player wins the game. Instead, the game has two subgoals, 1) surviving and 2) scoring as many points as possible. Decisions must be made in a strict time constraint of 40 ms. The Pac-Man agent has to compete with a range of different ghost teams, hence limited assumptions can be made about their behavior. In order to expand the capabilities of existing MCTS agents, four enhancements are discussed: 1) a variable-depth tree; 2) simulation strategies for the ghost team and Pac-Man; 3) including long-term goals in scoring; and 4) reusing the search tree for several moves with a decay factor. The agent described in this paper was entered in both the 2012 World Congress on Computational Intelligence (WCCI’12, Brisbane, Qld., Australia) and the 2012 IEEE Conference on Computational Intelligence and Games (CIG’12, Granada, Spain) Pac-Man Versus Ghost Team competitions, where it achieved second and first places, respectively. In the experiments, we show that using MCTS is a viable technique for the Pac-Man agent. Moreover, the enhancements improve overall performance against four different ghost teams.
关键词： real time,Monte Carlo tree search (MCTS),Pac-Man,Monte Carlo
更新于2025-09-23 15:21:01
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Controlled Dynamic Search for a Mobile Object with Minimum Cost of Light Energy
摘要： We consider the optimal control problem for the spatial motion of a dynamic object in order to search for a moving object that performs simple motion in a rectangular region on a plane. As the optimality criterion, we consider a functional that takes into account the energy consumption of a light source located on the searching object. The object in question is considered to be detected when it reaches the light square with a given illumination. We propose a method for controlling the movement of a searching object, as well as the corresponding law of variation of the electric current in the light source circuit, which ensure the detection of the desired object under a guaranteed search time with minimal light energy consumption.
关键词： dynamic search,light energy consumption,moving object,optimal control
更新于2025-09-23 15:21:01