Research on Efficient Association Analysis Algorithm towards Production Process Data

2014 ◽  
Vol 556-562 ◽  
pp. 3827-3830
Author(s):  
Ming Hui Wang ◽  
Wen Li Shang ◽  
Fu Cheng Pan
Keyword(s):  
Correlation Analysis ◽  
Production Process ◽  
Association Analysis ◽  
Industrial Production ◽  
Process Data ◽  
Performance Improvements ◽  
New Process ◽  
Significant Performance ◽  
Efficient Data ◽  
The Many

Association analysis of the production process data (PPD) can be discoveried on the quality relevant parameters with great impact, however, it’s different from correlation analysis of other fields, Huge amount of data due to the production process, and the many parameters involved in the production process, the existing association analysis algorithms as they deal with inefficiency, can not meet the practical application. This paper proposes a new process for the industrial production of efficient data association algorithm-AprioriMask, after the actual production process of association analysis verification, AprioriMask algorithm has significant performance improvements to meet the industrial production process data for correlation analysis.

scholarly journals Bioinformatics Performance Comparison of Many-core Tile64 vs. Multi-core Intel Xeon

2014 ◽  
Vol 17 (1) ◽  
Author(s):  
Myriam Kurtz ◽  
Francisco J. Esteban ◽  
Pilar Hernández ◽  
Juan Antonio Caballero ◽  
Antonio Guevara ◽  
...  
Keyword(s):  
Parallel Implementation ◽  
Protein Sequences ◽  
Performance Comparison ◽  
Xeon Phi ◽  
Performance Improvements ◽  
Dna And Rna ◽  
Significant Performance ◽  
The Many ◽  
Many Core ◽  
Intel Xeon

The performance of the many-core Tile64 versus the multi-core Xeon x86 architecture on bioinformatics has been compared. We have used the pairwise algorithm MC64-NW/SW that we have previously developed to align nucleic acid (DNA and RNA) and peptide (protein) sequences for the benchmarking, being an enhanced and parallel implementation of the Needleman-Wunsch and Smith-Waterman algorithms. We have ported the MC64-NW/SW (originally developed for the Tile64 processor), to the x86 architecture (Intel Xeon Quad Core and Intel i7 Quad Core processors) with excellent results. Hence, the evolution of the x86-based architectures towards coprocessors like the Xeon Phi should represent significant performance improvements for bioinformatics.

scholarly journals An Attention-Based Multilayer GRU Model for Multistep-Ahead Short-Term Load Forecasting

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1639
Author(s):  
Seungmin Jung ◽  
Jihoon Moon ◽  
Sungwoo Park ◽  
Eenjun Hwang
Keyword(s):  
Power Consumption ◽  
Prediction Models ◽  
Short Term Memory ◽  
Load Forecasting ◽  
Input Sequence ◽  
Short Term ◽  
Performance Improvements ◽  
Short Term Load Forecasting ◽  
Significant Performance ◽  
Input Variables

Recently, multistep-ahead prediction has attracted much attention in electric load forecasting because it can deal with sudden changes in power consumption caused by various events such as fire and heat wave for a day from the present time. On the other hand, recurrent neural networks (RNNs), including long short-term memory and gated recurrent unit (GRU) networks, can reflect the previous point well to predict the current point. Due to this property, they have been widely used for multistep-ahead prediction. The GRU model is simple and easy to implement; however, its prediction performance is limited because it considers all input variables equally. In this paper, we propose a short-term load forecasting model using an attention based GRU to focus more on the crucial variables and demonstrate that this can achieve significant performance improvements, especially when the input sequence of RNN is long. Through extensive experiments, we show that the proposed model outperforms other recent multistep-ahead prediction models in the building-level power consumption forecasting.

scholarly journals Selecting Optimal Combination of Data Channels for Semantic Segmentation in City Information Modelling (CIM)

2021 ◽  
Vol 13 (7) ◽  
pp. 1367
Author(s):  
Yuanzhi Cai ◽  
Hong Huang ◽  
Kaiyang Wang ◽  
Cheng Zhang ◽  
Lei Fan ◽  
...  
Keyword(s):  
Large Scale ◽  
Semantic Segmentation ◽  
Optimal Combination ◽  
Reconstruction Technique ◽  
Process Data ◽  
Redundant Data ◽  
Multiple Data ◽  
Information Models ◽  
Efficient Data

Over the last decade, a 3D reconstruction technique has been developed to present the latest as-is information for various objects and build the city information models. Meanwhile, deep learning based approaches are employed to add semantic information to the models. Studies have proved that the accuracy of the model could be improved by combining multiple data channels (e.g., XYZ, Intensity, D, and RGB). Nevertheless, the redundant data channels in large-scale datasets may cause high computation cost and time during data processing. Few researchers have addressed the question of which combination of channels is optimal in terms of overall accuracy (OA) and mean intersection over union (mIoU). Therefore, a framework is proposed to explore an efficient data fusion approach for semantic segmentation by selecting an optimal combination of data channels. In the framework, a total of 13 channel combinations are investigated to pre-process data and the encoder-to-decoder structure is utilized for network permutations. A case study is carried out to investigate the efficiency of the proposed approach by adopting a city-level benchmark dataset and applying nine networks. It is found that the combination of IRGB channels provide the best OA performance, while IRGBD channels provide the best mIoU performance.

scholarly journals Data Downlink System in the Vast IOT Node Condition Assisted by UAV, Large Intelligent Surface, and Power and Data Beacon

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5748
Author(s):  
Zhibo Zhang ◽  
Qing Chang ◽  
Na Zhao ◽  
Chen Li ◽  
Tianrun Li
Keyword(s):  
Communication Systems ◽  
Optimization Problems ◽  
Minimum Energy ◽  
Numerical Algorithms ◽  
Flight Trajectory ◽  
Performance Improvements ◽  
Minimum Energy Consumption ◽  
Significant Performance ◽  
Downlink System ◽  
The Internet Of Things

The future development of communication systems will create a great demand for the internet of things (IOT), where the overall control of all IOT nodes will become an important problem. Considering the essential issues of miniaturization and energy conservation, in this study, a new data downlink system is designed in which all IOT nodes harvest energy first and then receive data. To avoid the unsolvable problem of pre-locating all positions of vast IOT nodes, a device called the power and data beacon (PDB) is proposed. This acts as a relay station for energy and data. In addition, we model future scenes in which a communication system is assisted by unmanned aerial vehicles (UAVs), large intelligent surfaces (LISs), and PDBs. In this paper, we propose and solve the problem of determining the optimal flight trajectory to reach the minimum energy consumption or minimum time consumption. Four future feasible scenes are analyzed and then the optimization problems are solved based on numerical algorithms. Simulation results show that there are significant performance improvements in energy/time with the deployment of LISs and reasonable UAV trajectory planning.

VESTA 3for three-dimensional visualization of crystal, volumetric and morphology data

2011 ◽  
Vol 44 (6) ◽  
pp. 1272-1276 ◽  
Author(s):  
Koichi Momma ◽  
Fujio Izumi
Keyword(s):  
Search Algorithm ◽  
Voronoi Tessellation ◽  
Three Dimensional ◽  
Structure Parameters ◽  
Volumetric Data ◽  
Complex Molecules ◽  
Visualization System ◽  
Performance Improvements ◽  
Significant Performance

VESTAis a three-dimensional visualization system for crystallographic studies and electronic state calculations. It has been upgraded to the latest version,VESTA 3, implementing new features including drawing the external morphology of crystals; superimposing multiple structural models, volumetric data and crystal faces; calculation of electron and nuclear densities from structure parameters; calculation of Patterson functions from structure parameters or volumetric data; integration of electron and nuclear densities by Voronoi tessellation; visualization of isosurfaces with multiple levels; determination of the best plane for selected atoms; an extended bond-search algorithm to enable more sophisticated searches in complex molecules and cage-like structures; undo and redo in graphical user interface operations; and significant performance improvements in rendering isosurfaces and calculating slices.

Fräsen partikelverstärkter Titanmatrix-Verbundwerkstoffe*/Milling of particle-reinforced titanium metal matrix composites

2017 ◽  
Vol 107 (04) ◽  
pp. 301-305
Author(s):  
E. Prof. Uhlmann ◽  
F. Kaulfersch
Keyword(s):  
High Performance ◽  
High Wear Resistance ◽  
Tool Geometry ◽  
Matrix Composites ◽  
Titanium Matrix ◽  
Titanium Matrix Composites ◽  
Performance Improvements ◽  
Significant Performance ◽  
High Temperature Components ◽  
Process Strategy

Partikelverstärkte Titanmatrix-Verbundwerkstoffe erlauben erhebliche Leistungssteigerungen im Bereich hochtemperaturbeanspruchter Struktur- und Funktionsbauteile. Die durch die Partikelverstärkung gesteigerte Verschleißbeständigkeit, Festigkeit und Härte bedeuten eine große Herausforderung an die spanende Bearbeitung derartiger Hochleistungswerkstoffe. Mittels Zerspanuntersuchungen beim Fräsen konnten unter Variation der Werkzeuggeometrie, der Schneidstoffe und der Prozessstrategie Parameterbeiche identifiziert werden, mit denen die prozesssichere Zerspanung partikelverstärkter Titanmatrix-Verbundwerkstoffe möglich ist.   Particle-reinforced titanium matrix composites ensure significant performance improvements of structural and functional high-temperature components. However, the high wear resistance, toughness and hardness due to particle reinforcement is a major challenge in machining these high performance materials. By conducting milling experiments with a variation of tool geometry, cutting material and process strategy, process parameters could be identified that enable efficient machining of particle-reinforced titanium matrix composites.

scholarly journals A Robust Cooperative Modulation Classification Scheme with Intra sensor Fusion for the Time correlated Flat Fading Channels

2020 ◽  
Vol 70 (1) ◽  
pp. 60-65 ◽  
Author(s):  
Goran Marković ◽  
Vlada Sokolović
Keyword(s):  
Fading Channels ◽  
Sensor Fusion ◽  
Large Scale ◽  
Negative Influence ◽  
Modulation Classification ◽  
Distributed Sensors ◽  
Performance Improvements ◽  
Flat Fading ◽  
Significant Performance ◽  
Single Sensor

Networks with distributed sensors, e.g. cognitive radio networks or wireless sensor networks enable large-scale deployments of cooperative automatic modulation classification (AMC). Existing cooperative AMC schemes with centralised fusion offer considerable performance increase in comparison to single sensor reception. Previous studies were generally focused on AMC scenarios in which multipath channel is assumed to be static during a signal reception. However, in practical mobile environments, time-correlated multipath channels occur, which induce large negative influence on the existing cooperative AMC solutions. In this paper, we propose two novel cooperative AMC schemes with the additional intra-sensor fusion, and show that these offer significant performance improvements over the existing ones under given conditions.

scholarly journals A Parallel Event System for Large-Scale Cloud Simulations in DISSECT-CF

2021 ◽  
Author(s):  
Dilshad Hassan Sallo ◽  
Gabor Kecskemeti
Keyword(s):  
Time Management ◽  
Large Scale ◽  
Discrete Event ◽  
Parallel Execution ◽  
Management Scenarios ◽  
Performance Improvements ◽  
Event Simulation ◽  
Independent Events ◽  
Event System ◽  
Significant Performance

Discrete Event Simulation (DES) frameworks gained significant popularity to support and evaluate cloud computing environments. They support decision-making for complex scenarios, saving time and effort. The majority of these frameworks lack parallel execution. In spite being a sequential framework, DISSECT-CF introduced significant performance improvements when simulating Infrastructure as a Service (IaaS) clouds. Even with these improvements over the state of the art sequential simulators, there are several scenarios (e.g., large scale Internet of Things or serverless computing systems) which DISSECT-CF would not simulate in a timely fashion. To remedy such scenarios this paper introduces parallel execution to its most abstract subsystem: the event system. The new event subsystem detects when multiple events occur at a specific time instance of the simulation and decides to execute them either on a parallel or a sequential fashion. This decision is mainly based on the number of independent events and the expected workload of a particular event. In our evaluation, we focused exclusively on time management scenarios. While we did so, we ensured the behaviour of the events should be equivalent to realistic, larger-scale simulation scenarios. This allowed us to understand the effects of parallelism on the whole framework, while we also shown the gains of the new system compared to the old sequential one. With regards to scaling, we observed it to be proportional to the number of cores in the utilised SMP host.

Experiment Study on Novel Precision Cropping Machinery Using Rotary Striking Action

2013 ◽  
Vol 281 ◽  
pp. 287-292 ◽  
Author(s):  
Ren Feng Zhao ◽  
Sheng Dun Zhao ◽  
Bin Zhong
Keyword(s):  
Industrial Production ◽  
Experimental Results ◽  
Control Mode ◽  
Experiment Study ◽  
New Process ◽  
Different Types ◽  
New Type ◽  
Working Principle ◽  
Process Method

This paper illuminates a new type of precision cropping process method with rotary striking action. The new process makes use of a controllable circumferential strike on a metal bar with a V-shaped notch. The working principle of the machine is described. Different types of metal bars have been tested, and both bad results and successful results were stated in the paper. The most ideal control mode has been obtained. The experimental results show that the new cropping process can crop bars with different materials and diameters. In some cases, it can be directly used in the subsequent industrial production.

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