BACKGROUND: The gangue content in coal seriously affects the calorific value produced by its combustion. In practical applications, gangue in coal needs to be completely separated. The pseudo-dual-energy X-ray method ...
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BACKGROUND: The gangue content in coal seriously affects the calorific value produced by its combustion. In practical applications, gangue in coal needs to be completely separated. The pseudo-dual-energy X-ray method does not have high sorting accuracy. OBJECTIVE: This study aims to propose a novel multi-dimensional coal and gangue X-ray sorting algorithm based on CdZnTe photon counting detectors to solve the problem of coal and gangue sorting by X-ray. METHODS: This complete algorithm includes five steps: (1) Preferred energy bins, (2) transmittance sorting, (3) one-dimensional R-value sorting, (4) two-dimensional R-value sorting, and (5) three-dimensional R-value sorting. The output range of each step is determined by prior information from 65 groups of coal and gangue. An additional 110 groups of coal and gangue are employed experimentally to validate the algorithm's accuracy. RESULTS: Compared with the 60% sorting accuracy of the Pseudo-dual-energy method, the new algorithm reached a sorting accuracy of 99%. CONCLUSIONS: Study results demonstrate the superiority of this novel algorithm and its feasibility in practical applications. This novel algorithm can guide other two-substance X-ray sorting applications based on photon counting detectors.
Purpose - The purpose of this study is to present a newly proposed and developed sorting algorithm-based merging weighted fraction Monte Carlo (SAMWFMC) method for solving the population balance equation for the weigh...
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Purpose - The purpose of this study is to present a newly proposed and developed sorting algorithm-based merging weighted fraction Monte Carlo (SAMWFMC) method for solving the population balance equation for the weighted fraction coagulation process in aerosol dynamics with high computational accuracy and efficiency. Design/methodology/approach - In the new SAMWFMC method, the jump Markov process is constructed as the weighted fraction Monte Carlo (WFMC) method (Jiang and Chan, 2021) with a fraction function. Both adjustable and constant fraction functions are used to validate the computational accuracy and efficiency. A new merging scheme is also proposed to ensure a constant-number and constant-volume scheme. Findings - The new SAMWFIMC method is fully validated by comparing with existing analytical solutions for six benchmark test cases. The numerical results obtained from the SAMWFMC method with both adjustable and constant fraction functions show excellent agreement with the analytical solutions and low stochastic errors. Compared with the WFMC method (liang and Chan, 2021), the SAMWFMC method can significantly reduce the stochastic error in the total particle number concentration without increasing the stochastic errors in high-order moments of the particle size distribution at only slightly higher computational cost. Originality/value - The WFMC method (Jiang and Chan, 2021) has a stringent restriction on the fraction functions, making few fraction functions applicable to the WFMC method except for several specifically selected adjustable fraction functions, while the stochastic error in the total particle number concentration is considerably large. The newly developed SAMWFMC method shows significant improvement and advantage in dealing with weighted fraction coagulation process in aerosol dynamics and provides an excellent potential to deal with various fraction functions with higher computational accuracy and efficiency.
A new event-driven sorting algorithm-based merging Monte Carlo (SAMMC) method is proposed and developed for solving the general dynamic equation in aerosol dynamics. A neighbour merging method is proposed to maintain ...
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A new event-driven sorting algorithm-based merging Monte Carlo (SAMMC) method is proposed and developed for solving the general dynamic equation in aerosol dynamics. A neighbour merging method is proposed to maintain a constant-volume and constant -number scheme with minimal interference to the numerical particle population, where ab-solute volume difference (AVD) and relative volume difference (RVD) are used as the cru-cial merging criteria. The SAMMC method can be used for simulating all aerosol dynamic processes with very high computational accuracy, especially effective in those aerosol dy-namic processes generating additional numerical particles. In the present study, compre-hensive computational conditions are used to study their impacts on computational accu-racy and efficiency by comparing the SAMMC method to previous MC methods and ana-lytical solutions. Numerical results show that the SAMMC method has excellent agreement with analytical solutions for all specified cases of different aerosol dynamic processes and shows higher computational accuracy than equal-weight-based MC methods. In addition, the computational accuracy of the SAMMC method in the total particle number concen-tration is much higher than those of the weighted fraction Monte Carlo (WFMC) method and sorting algorithm-based merging weighted fraction Monte Carlo (SAMWFMC) method in non-homogeneous coagulation. The SAMMC method can also achieve the same compu-tational precision as the multi-Monte Carlo (MMC) method at only slightly higher com-putational cost in homogeneous coagulation. More importantly, the SAMMC method can deal with breakage-related processes and simultaneous coagulation and nucleation with very high computational accuracy and efficiency, while the numerical results of the MMC method may significantly deviate from analytical solutions due to the introduction of sys-tematic errors. Furthermore, the RVD can achieve higher computational accuracy in multi -breakage modelling than
Non-volatile memory (NVM) has emerged as an alternative of the next-generation memory due to its non-volatility, byte addressability, high storage-density, and low-energy consumption. However, NVM also has some limita...
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Non-volatile memory (NVM) has emerged as an alternative of the next-generation memory due to its non-volatility, byte addressability, high storage-density, and low-energy consumption. However, NVM also has some limitations, e.g. asymmetric read and write latency. Therefore, at present, it is not realistic to completely replace DRAM with NVM in computer systems. A more feasible scheme is to adopt the hybrid memory architecture composed of NVM and DRAM. Following the assumption of hybrid memory architecture, in this paper, we propose an NVM-friendly sorting algorithm called NVMsorting. Particularly, we introduce a new concept called Natural Run to improve the existing MONTRES algorithm. Further, we apply the proposed NVMsorting to database join algorithms to improve the performance of the existing sort-merge join. To verify the performance of our proposal, we implement six existing sorting algorithms as baselines, including the MONTRES algorithm, and conduct comparative experiments on real Intel Optane DC persistent memory. The results show that NVMsorting outperforms other sorting algorithms in terms of execution time and NVM writes. In addition, the results of the join experiment show that the NVMsorting algorithm achieves the highest performance among all schemes. Especially, in the partially ordered data, the execution time of NVMsorting is 2.9%, 2.7%, and 4.2% less than MONTRES, external sort, and quick sort, respectively. Also, the amount of NVM writes of the NVMsorting is 26.1%, 43.6%, 96.2% less than MONTRES, external sort, and quick sort, respectively.
Among the comparison-based algorithms, INSERTIONSORT is recognized as one of the fastest methods to sort relatively small data sets, or when the elements are relatively ordered. However, due to not offering good asymp...
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Among the comparison-based algorithms, INSERTIONSORT is recognized as one of the fastest methods to sort relatively small data sets, or when the elements are relatively ordered. However, due to not offering good asymptotic complexity in its runtime, it performs very poorly both in the worst case and in the average case for most large data collections. In this article we offer a new sorting algorithm based on orderer block insertions with worst case optimal time. At the cost of an additional memory space of nk words, for any constant k, our algorithm is able to easily transform it into an in-place algorithm with a time of symbolscript in the worst case. Empirically, our method outperforms symbolscript in all the different cases tested, even for small input collections. Furthermore, our experiments show that, for small or large datasets from either of the two main probability distributions-Uniform and Normal;our algorithms also outperform any traditional method like symbolscript symbolscript or symbolscript and even better than the efficient hybrid algorithm symbolscript symbolscript method provided by the GNU C++ Standard Library.
Drones are used for post-flood disaster management and delivering relief goods to flood-affected areas. Autonomous drones are an alternative means of prioritizing assistance due to the lack of available technology and...
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In the work described in this paper, we experimentally demonstrate an efficient method to improve reconstruction of objects embedded in turbid media. The method combines multiple polarized speckle projections and a fu...
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In the work described in this paper, we experimentally demonstrate an efficient method to improve reconstruction of objects embedded in turbid media. The method combines multiple polarized speckle projections and a fully automated sorting algorithm. In the experimental setup, the medium was illuminated with a polarized laser beam and multiple polarized images of the object were obtained from different viewing perspectives using a lens array and captured by a camera. In offline image processing, each sub-image was digitally cropped, extracted from the array, and qualitatively evaluated by contrast-to-noise ratio (CNR) and entropy metrics. Subimages were sorted based on quality as determined by CNR and entropy values, with high CNR and low entropy considered as highest quality with the best resolution and contrast. The images were then shifted to a common center and then summed with other sub-images to form a single average image. Experiments to demonstrate the effectiveness of the proposed algorithm were carried out on targets with different geometrical shapes embedded within scattering media in transmission configuration. Analysis of image metrics indicated improvement in object reconstruction by using circular polarization as compared to the use of linear polarization or nonpolarization states. The overall experimental results obtained in this work illustrate effective performance of the proposed method.
sorting is one of the most fundamental algorithms in Computer Science and a common operation in databases not just for sorting query results but also as part of joins (i.e., sort-merge-join) or indexing. In this work,...
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ISBN:
(纸本)9781450367356
sorting is one of the most fundamental algorithms in Computer Science and a common operation in databases not just for sorting query results but also as part of joins (i.e., sort-merge-join) or indexing. In this work, we introduce a new type of distribution sort that leverages a learned model of the empirical CDF of the data. Our algorithm uses a model to efficiently get an approximation of the scaled empirical CDF for each record key and map it to the corresponding position in the output array. We then apply a deterministic sorting algorithm that works well on nearly-sorted arrays (e.g., Insertion Sort) to establish a totally sorted order. We compared this algorithm against common sorting approaches and measured its performance for up to 1 billion normally-distributed double-precision keys. The results show that our approach yields an average 3.38x performance improvement over C++ STL sort, which is an optimized Quicksort hybrid, 1.49x improvement over sequential Radix Sort, and 5.54x improvement over a C++ implementation of Timsort, which is the default sorting function for Java and Python.
One important characteristic of modular multilevel converter (MMC) is the existence of circulating current, which consists of a dc component and a series of undesirable even-order (predominantly second-order) harmonic...
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One important characteristic of modular multilevel converter (MMC) is the existence of circulating current, which consists of a dc component and a series of undesirable even-order (predominantly second-order) harmonics. However, only the dc part of the circulating current is required for power balance, the ac harmonics are unwanted. These undesirable harmonics should he suppressed to reduce device stress and power losses. Most state-of-the-art circulating current suppression techniques employ separate controllers to generate the arm reference voltage for circulating current suppression. This paper proposes an alternate approach, eliminating the need of any additional control loop. Generation of undesirable circulating current is prevented inherently in the modulation stage. Reduced switching frequency sorting algorithm based modulation framework is employed to ensure reduced switching loss. Suitability of the proposed method is validated by experiments performed on a three-phase laboratory prototype of MMC. Steady state and transient operation of the MMC in grid-connected condition is studied.
This paper proposes a new carrier-based modulation strategy for symmetrical cascaded multilevel converters denominated phase dispositionwith sorting (PDS). It deals with the issue of irregular distribution of PWM sign...
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This paper proposes a new carrier-based modulation strategy for symmetrical cascaded multilevel converters denominated phase dispositionwith sorting (PDS). It deals with the issue of irregular distribution of PWM signals and power for each converter cell that occurs when using the conventional phase disposition (PD) modulation. Although some alternatives have been proposed in the literature for overcoming these problems, most of them do not consider operation of the converter under fault conditions on the power cells. Therefore, one of the contributions of the proposed PDS modulation strategy is the ability to evenly distribute the pulse signals for the converter semiconductor switches, resulting in the same power being processed by all cells, maintaining the good quality of the synthesized output voltages, even with faults in one or more power cells. In addition, it allows implementation in commercial digital signal processors, not requiring additional hardware. The good performance of the proposed modulation strategy is validated through experimental results for a three-phase symmetrical cascaded multilevel converter with three cells per phase, considering normal and faulty conditions on the power cells.
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