Fragmentation usually occurs when data space of original storage nodes has to be reallocated to new added storage nodes during the scale-out evolution of the large-scale storage *** greatly influences its performance ...
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Fragmentation usually occurs when data space of original storage nodes has to be reallocated to new added storage nodes during the scale-out evolution of the large-scale storage *** greatly influences its performance and becomes a challenge to manage the whole *** present an efficient space management framework,called New Balance,to reduce fragmentation with the minimum data movement while keeping the storage system load *** space management framework has two phases including the collection phase and the allocation *** the collection phase,we propose a novel algorithm,called the greedy bi-direction collector,which collects enough space for the new storage *** the allocation phase,we formally represent it as a variant of the bin packing problem and then utilize some bin packing heuristics including the first fitting and the best fitting to allocate collected intervals to new added storage *** experimental results show that the amount of intervals can be reduced by 20%;5%and our algorithmic optimization improves the data lookup performance by at least 10%and the scale-out performance by 2X;X.
This review article provides a comprehensive analysis of nesting optimization algorithms in the shipbuilding industry,emphasizing their role in improving material utilization,minimizing waste,and enhancing production ...
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This review article provides a comprehensive analysis of nesting optimization algorithms in the shipbuilding industry,emphasizing their role in improving material utilization,minimizing waste,and enhancing production *** shipbuilding process involves the complex cutting and arrangement of steel plates,making the optimization of these operations vital for cost-effectiveness and *** algorithms are broadly classified into four categories:exact,heuristic,metaheuristic,and *** algorithms ensure optimal solutions but are computationally *** contrast,heuristic algorithms deliver quicker results using practical rules,although they may not consistently achieve optimal *** algorithms combine multiple heuristics to effectively explore solution spaces,striking a balance between solution quality and computational *** algorithms integrate the strengths of different approaches to further enhance *** review systematically assesses these algorithms using criteria such as material dimensions,part geometry,component layout,and computational *** findings highlight the significant potential of advanced nesting techniques to improve material utilization,reduce production costs,and promote sustainable practices in *** adopting suitable nesting solutions,shipbuilders can achieve greater efficiency,optimized resource management,and superior overall *** research directions should focus on integrating machine learning and real-time adaptability to further enhance nesting algorithms,paving the way for smarter,more sustainable manufacturing practices in the shipbuilding industry.
The lack of effective evaluation of online education is a worldwide malpractice, and it is impossible to help students improve the correctness of online learning choices through existing reviews. Based on the current ...
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The lack of effective evaluation of online education is a worldwide malpractice, and it is impossible to help students improve the correctness of online learning choices through existing reviews. Based on the current mainstream sentiment lexicon and text sentiment analysis, the authors use machine learning method to analyze the sentiment orientation of the legal course review text, through method that combines PMI and SVM. At the same time, this paper uses LibSVM tool to train and predict data, collect and pre-process data through network data collection, and, based on traditional algorithms, propose improved experimental scheme based on their respective advantages and disadvantages. In addition, the model proposed in this study is used to classify and process the emotional text, and the two methods are combined to obtain the final result. Finally, this paper combines experiments to analyze the performance of the comprehensive model proposed in this study. The research shows that the classification effect of the text sentiment analysis of model is good, it can be applied to practice, and it can provide theoretical reference for subsequent related research.
To address the challenge of detecting adherent seeds in images of dehuller discharge from buckwheat processing, this study proposes an innovative approach using an enhanced YOLOv8n architecture, termed MCG-YOLOv8n. Th...
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To address the challenge of detecting adherent seeds in images of dehuller discharge from buckwheat processing, this study proposes an innovative approach using an enhanced YOLOv8n architecture, termed MCG-YOLOv8n. This model is specifically tailored for precise segmentation of adherent buckwheat seed objects. It incorporates the MobileViT v3 Block into the YOLOv8n-seg backbone network to enhance the feature extraction capability in densely distributed seed areas. At the feature fusion layer, the model incorporates the Generalized Feature Pyramid Network (GFPN) structure for cross-scale feature fusion, coupled with Coordinate Attention (CA) to elevate the detection accuracy of smaller targets. Additionally, the Minimum Point Distance Intersection over Union (MPDIoU) was employed to strengthen the model's generalization ability and mitigate the issue of missed detections caused by dense adherent seeds. Experimental results demonstrate the superior performance of the MCG-YOLOv8n model, achieving high precision (94.70%), recall (93.20%), and mean average precision (mAP@0.5: 95.20%), outperforming other mainstream segmentation models. The analysis of the segmentation results for images, with seed counts ranging from 66 to 435 and a size of 512 x 512 pixels, revealed a weighted error rate of 0.70% in counting, with an average detection time of 0.017 s per image. Consequently, the MCG-YOLOv8n model can accurately and rapidly detect high-throughput adherent buckwheat seeds, providing substantial support for the development of online detection systems and deployment on portable mobile devices.
A collection of techniques is developed in this paper for ray casting free-form deformed-volume objects with high quality and efficiency. The known inverse ray deformation approach is combined with free-form deformati...
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A collection of techniques is developed in this paper for ray casting free-form deformed-volume objects with high quality and efficiency. The known inverse ray deformation approach is combined with free-form deformation to bend the rays to the opposite direction of the deformation, producing an image of the deformed volume without generating a really deformed intermediate volume. The local curvature is estimated and used for the adaptive selection of the length of polyline segments, which approximate the inversely deformed ray trajectories;thus longer polyline segments can be automatically selected in regions with small curvature, reducing deformation calculation without losing the spatial continuity of the simulated deformation. We developed an efficient method for the estimation of the local deformation function. The Jacobian of the local deformation function is used for adjustments of the opacity values and normal vectors computed from the original volume, guaranteeing that the deformed spatial structures are correctly rendered. The popular ray casting acceleration techniques, like early ray termination and space leaping, are incorporated into the deformation procedure, providing a speed-up factor of 2.34-6.56 compared to the nonoptimized case. Copyright (C) 2003 John Wiley Sons, Ltd.
Context: Effort estimation is one of the essential phases that must be accurately predicted in the early stage of software project development. Currently, solving problems that affect the estimation accuracy of Use Ca...
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Context: Effort estimation is one of the essential phases that must be accurately predicted in the early stage of software project development. Currently, solving problems that affect the estimation accuracy of Use Case Points-based methods is still a challenge to be addressed. Objective: This paper proposes a parametric software effort estimation model based on Optimizing Correction Factors and Multiple Regression Models to minimize the estimation error and the influence of unsystematic noise, which has not been considered in previous studies. The proposed method takes advantage of the Least Squared Regression models and Multiple Linear Regression models on the Use Case Points-based elements. Method: We have conducted experimental research to evaluate the estimation accuracy of the proposed method and compare it with three previous related methods, i.e., 1) the baseline estimation method - Use Case Points, 2) Optimizing Correction Factors, and 3) algorithmic optimization Method. Experiments were performed on datasets (Dataset D1, Dataset D2, and Dataset D3). The estimation accuracy of the methods was analysed by applying various unbiased evaluation criteria and statistical tests. Results: The results proved that the proposed method outperformed the other methods in improving estimation accuracy. Statistically, the results proved to be significantly superior to the three compared methods based on all tested datasets. Conclusion: Based on our obtained results, the proposed method has a high estimation capability and is considered a helpful method for project managers during the estimation phase. The correction factors are considered in the estimation process.
In the presence of naturally occurring and man-made public health threats, the feasibility of regional bio-emergency contingency plans plays a crucial role in the mitigation of such emergencies. While the analysis of ...
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In the presence of naturally occurring and man-made public health threats, the feasibility of regional bio-emergency contingency plans plays a crucial role in the mitigation of such emergencies. While the analysis of in-place response scenarios provides a measure of quality for a given plan, it involves human judgment to identify improvements in plans that are otherwise likely to fail. Since resource constraints and government mandates limit the availability of service provided in case of an emergency, computational techniques can determine optimal locations for providing emergency response assuming that the uniform distribution of demand across homogeneous resources will yield an optimal service outcome. This paper presents an algorithm that recursively partitions the geographic space into subregions while equally distributing the population across the partitions. For this method, we have proven the existence of an upper bound on the deviation from the optimal population size for subregions.
The image distortion model (IDM) is a deformation model that is used for computing the (dis-)similarity between images. Therefore it evaluates displacements of individual pixels between two images within a so-called w...
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The image distortion model (IDM) is a deformation model that is used for computing the (dis-)similarity between images. Therefore it evaluates displacements of individual pixels between two images within a so-called warp range and also takes into account the surrounding pixels (local context). It can be used with a kNN classifier and has shown good retrieval quality in handwritten character recognition as well as in past runs of the medical automatic annotation task of ImageCLEF workshops. However, one of its limitations is computational complexity and the resulting long query response times, that may limit its use for a wider range of applications and for modifications to further improve retrieval quality. In particular an enlarged local context and warp range are candidates for such improvements, but would even further increase computational complexity. In our approach, we therefore apply several optimizations that reduce the retrieval time without degrading the result quality. First, we use an early termination strategy for the individual distance computations which contribute a speedup of a factor of 4.3-4.9. Second, we make efficient use of multithreading. With these extensions, we are able to perform the IDM in less than 1.5 s per query on an 8-way server and 16 s on a standard Pentium 4 PC without any degradation of retrieval quality compared to the non-optimized version. We extend the possible displacements to an area of 7 x 7 pixels, using a local context of either 5 x 5 or 7 x 7 pixels. The results of the extended IDM have been submitted to the medical automatic annotation task of ImageCLEF 2007 and were ranked in the upper third. More importantly, the used techniques for reducing the execution time are not limited strictly to IDM but are also applicable to other expensive distance measures. (C) 2008 Elsevier B.V. All rights reserved.
GROMACS 3.0 is the latest release of a versatile and very well optimized package for molecular simulation. Much effort has been devoted to achieving extremely high performance on both workstations and parallel compute...
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GROMACS 3.0 is the latest release of a versatile and very well optimized package for molecular simulation. Much effort has been devoted to achieving extremely high performance on both workstations and parallel computers. The design includes an extraction of virial and periodic boundary conditions from the loops over pairwise interactions, and special software routines to enable rapid calculation of x(-1/2). Inner loops are generated automatically in C or Fortran at compile time, with optimizations adapted to each architecture. Assembly loops using SSE and 3DNow! Multimedia instructions are provided for x86 processors, resulting in exceptional performance on inexpensive PC workstations. The interface is simple and easy to use (no scripting language), based on standard command line arguments with self-explanatory functionality and integrated documentation. All binary files are independent of hardware endian and can be read by versions of GROMACS compiled using different floating-point precision. A large collection of flexible tools for trajectory analysis is included, with output in the form of finished Xmgr/Grace graphs. A basic trajectory viewer is included, and several external visualization tools can read the GROMACS trajectory format. Starting with version 3.0, GROMACS is available under the GNU General Public License from http://***.
With the continuous progress of aerospace, military technology, and marine development, the MEMS resonance pressure sensor puts forward the requirements of not only a wide range but also high sensitivity. However, tra...
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With the continuous progress of aerospace, military technology, and marine development, the MEMS resonance pressure sensor puts forward the requirements of not only a wide range but also high sensitivity. However, traditional resonators are hardly compatible with both. In response, we propose a new sensor structure. By arranging the resonant beam and the sensitive diaphragm vertically in space, the new structure improves the rigidity of the diaphragm without changing the thickness of the diaphragm and achieves the purpose of increasing the range without affecting the sensitivity. To find the optimal structural parameters for the sensor sensitivity and range, and to prevent the effects of modal disturbances, we propose a multi-objective optimization design scheme based on the BP and NSGA-II algorithms. The optimization of the structure parameters not only improved the sensitivity but also increased the interference frequency to solve the issue of mode interference. The optimized structure achieves a sensitivity and range of 4.23 Hz/kPa and 1-10 MPa, respectively. Its linear influence factor is 38.07, significantly higher than that of most resonant pressure sensors. The structural and algorithmic optimizations proposed in this paper provide a new method for designing resonant pressure sensors compatible with a wide range and high sensitivity.
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