“…Through a comparison with two benchmark solution approaches (a mathematical programme and a non-dominated archiving ant colony optimization algorithm), the superiority of the heuristic algorithm is shown regarding solution quality and CPU time. Finally, we conduct numerical analyses to present managerial implications.…”
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“…It is observed that all the blocks use same methodology to be the part of a new blockchain network. Moreover, the CPU and memory consumption in the implementation of HCM is always below two percent and about fifty percent respectively as shown in the latency graph. …”
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“…The best algorithm is the one that produces the largest objective function (energy generation) and has the minimum standard deviation (SD), the minimum coefficient of variations (CV), and the shortest time of CPU usage. It was found that the best solution was achieved by the moth swarm algorithm (MSA), with the optimized energy generation of 19,311,535 MW which was 65.088% more than the actual energy generation (11,697,757). …”
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“…RTOS based sfotware event response is bounded within 1 ms while the CPU usage is at 3∼5%. The device is able to work for 50 min with its onboard power. …”
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“…Our study identified a total of 14 single nucleotide polymorphism (SNP) markers associated with the resistance to BW isolates 528, 557, and 597 using mixed linear models (MLMs) in BLINK, FarmCPU, GAPIT, and TASSEL 5. These SNPs were located on chromosomes Phaseolus vulgaris [Pv]02, Pv04, Pv08, and Pv09 for isolate 528; Pv07, Pv10, and Pv11 for isolate 557; and Pv04, Pv08, and Pv10 for isolate 597. …”
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“…This reduced computation time enables the UQ execution with 100 000 predictions in a few minutes on a single CPU core and in less than a minute on a GPU. We performed UQ to predict the risk of cerebral hyperperfusion (CH), a life-threatening condition that can occur after carotid artery stenosis surgery if collateral circulation fails to function appropriately. …”
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“…A total of 20 and 46 marker-trait associations (MTAs) were identified for grain nutrient and agronomic traits, respectively, using FarmCPU and BLINK models. Of which seven SNPs for grain protein, twelve for Fe, and one for Zn content were distributed on chromosomes 1, 4, 6, and 7. …”
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“…Also, the proposed DCNN-IPSCA performs much better than the standard DCNN, with GPU and CPU training times, which are 387.69 and 63.10 times faster, respectively. …”
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“…Compared to antaRNA, aRNAque CPU time is higher but more successful in finding designed sequences that fold correctly into the target structures. …”
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“…The proposed system is also evaluated considering the generational distance, CPU processing time, cohesion, and readability factor, reflecting that the system-generated summaries are readable, concise, relevant, and fast. …”
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“…For practical deployment, we implemented the trained model in edge devices (NCS2) and this has achieved an improvement of 90% in inference speed compared to CPU. This shows that the developed model has the potential to be implemented on the edge, for example in primary care clinics and rural areas which are not well-equipped or do not have access to stable internet connections.…”
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“…Increasing age was significantly associated with reduced odds of daily use of central processing unit (CPU) or tablet. One-third of the participants were undecided about potential participation in PTR. …”
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“…The trusted server will be capable of deploying and running a variety of sequencing analysis hardware, such as GPUs and FPGAs, as well as CPU-based software. We demonstrated that DSGD achieved comparable throughput with and without encryption on the trusted server Therefore, our system is ready to be installed at research institutes and hospitals that make diagnoses based on whole genome sequencing on a daily basis.…”
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“…Meanwhile, the H-Swish activation function is used to optimize the model performance to further improve the model accuracy at a small computational cost. 768 images of pine cones in forest were used as experimental data, and 1536 images were obtained after data expansion, which were divided into training set and test set at the ratio of 8:2. The CPU used in the experiment was Inter Core i9-10885@2.40Ghz, and the GPU was NVIDIA Quadro RTX 5000. …”
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“…The proposed design outperforms the ARM-A9 dual-core CPU implementation with a 92.74% increase and 90.71% saving in computing speed and energy consumption, respectively. …”
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“…Creating the TractoInferno database required approximately 20,000 CPU-hours of processing power, 200 man-hours of manual QC, 3,000 GPU-hours of training baseline models, and 4 Tb of storage, to produce a final database of 350 Gb. …”
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“…Experimental results with a cluster of 10 cheap machines each of which is equipped with Intel Xeon E3-1220 CPU (4-cores at 3.10GHz), 16GB RAM, and 2 SSDs of 1TB show that UniCon is up to 13 times faster than competitors on real-world graphs. …”
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“…The present task validates a new methodology of Monte Carlo simulation based on the Multithreading technique to reduce CPU time to simulate a 6 MV photon beam provided by the Elekta Synergy MLCi2 platform medical linear accelerator treatment head utilizing TOpas version 3.6 Monte Carlo software and the Slurm Marwan cluster. …”
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“…The first pareto solution is 1,869,908.962, 2172.638 and 65.926, and the CPU time is 412 Ms. The results show a rise in the maximum supply risk occurs in the total cost and risk but a reduction in the accountability of the network and also an increase in the disruption period findings in increased total cost and risk of the network, while it first increases and then decreases the accountability.…”
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“…The performance metrics considered for the evaluation of the proposed framework are the sum of squared error (SSE), time complexity with respect to different m values, and storage complexity with CPU utilization. The results have experimented with MATLAB 2018a simulation environment. …”
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