scholarly journals Hadoop Configuration Tuning for Performance Optimization

2017 ◽  
Vol 4 (1) ◽  
pp. 31-40
Author(s):  
Christian Christian ◽  
Kho I Eng ◽  
Heru Purnomo Ipung
Keyword(s):  
Performance Optimization ◽  
Parameter Tuning ◽  
Performance Gain ◽  
Performance Improvements ◽  
Configuration Parameter ◽  
Cpu Utilization ◽  
Cluster Configuration ◽  
Significant Performance ◽  
Hadoop Clusters ◽  
The Impact

Configuration parameter tuning is an essential part of the implementation of Hadoop clusters. Each parameter in a configuration plays a role that impacts the ov erall performance of the cluster. Therefore, we need to learn the characteristics of said parameter and understand the impact in hardware utilization in order to achieve optimal configuration. In this paper, we conducted experiments that includes modifying configuration and performed benchmark to find out if there is any performance gain. TeraSort is the program that runs the benchmark, we measure the time needed to complete the sort of the set of data and the CPU utilization during the benchmark. We conclu de that from our experiments we can see significant performance improvements by tuning with the configurations. However, the results may vary between different cluster configuration.

scholarly journals The Introduction of Academy Schools to England's Education

2019 ◽  
Vol 17 (4) ◽  
pp. 1107-1146 ◽  
Author(s):  
Andrew Eyles ◽  
Stephen Machin
Keyword(s):  
School Reform ◽  
Secondary School ◽  
English Education ◽  
Independent State ◽  
Performance Improvements ◽  
Authority Control ◽  
Significant Performance ◽  
Almost All ◽  
The Impact ◽  
State Schools

Abstract This paper studies the origins of what has become one of the most radical and encompassing programmes of school reform seen in the recent past in advanced countries—the introduction of academy schools to English education. Academies are independent state funded schools that are allowed to run in an autonomous manner outside of local authority control. Almost all academies are conversions from already existent state schools and so are school takeovers that enable more autonomy in operation than was permitted in their predecessor state. Studying the first round of conversions that took place in the 2000s, where poorly performing schools were converted to academies, a focus is placed on legacy enrolled pupils who were already attending the school prior to conversion. The impact on end of secondary school pupil performance is shown to be positive and significant. Performance improvements are stronger for pupils in urban academies and for those converting from schools that gained relatively more autonomy as a result of conversion.

Multilingual Distant Supervised Relation Extractors Combining Multiple Feature Types

2014 ◽  
Vol 08 (04) ◽  
pp. 441-459
Author(s):  
Thiago Nunes ◽  
Daniel Schwabe
Keyword(s):  
Semantic Relation ◽  
Semantic Features ◽  
Data Filtering ◽  
Performance Improvements ◽  
Distant Supervision ◽  
Multiple Feature ◽  
Different Types ◽  
Significant Performance ◽  
The Impact ◽  
Multiple Languages

A well-known drawback in building machine learning semantic relation detectors for natural language is the lack of a large number of qualified training instances for the target relations in multiple languages. Even when good results are achieved, the datasets used by the state-of-the-art approaches are rarely published. In order to address these problems, this work presents an automatic approach to build multilingual semantic relation detectors through distant supervision combining two of the largest resources of structured and unstructured content available on the Web, DBpedia and Wikipedia. We map the DBpedia ontology back to the Wikipedia text to extract more than 100.000 training instances for more than 90 DBpedia relations for English and Portuguese languages without human intervention. First, we mine Wikipedia articles to find candidate instances for relations described in the DBpedia ontology. Second, we preprocess and normalize the data filtering out irrelevant instances. Finally, we use the normalized data to construct regularized logistic regression detectors that achieve an F-Measure above 80% for both English and Portuguese languages. In this paper, we also compare the impact of different types of features on the accuracy of the trained detector, demonstrating significant performance improvements when combining lexical, syntactic and semantic features. Both the datasets and the code used in this research are available online.

scholarly journals Inlining External Sources in Answer Set Programs

2019 ◽  
Vol 19 (3) ◽  
pp. 360-411
Author(s):  
CHRISTOPH REDL
Keyword(s):  
External Source ◽  
Performance Gain ◽  
Alternative Evaluation ◽  
Performance Improvements ◽  
Evaluation Approach ◽  
Special Cases ◽  
Evaluation Algorithm ◽  
Significant Performance ◽  
External Sources ◽  
Answer Set

Abstracthex-programs are an extension of answer set programs (ASP) with external sources. To this end, external atoms provide a bidirectional interface between the program and an external source. The traditional evaluation algorithm for hex-programs is based on guessing truth values of external atoms and verifying them by explicit calls of the external source. The approach was optimized by techniques that reduce the number of necessary verification calls or speed them up, but the remaining external calls are still expensive. In this paper, we present an alternative evaluation approach based on inlining of external atoms, motivated by existing but less general approaches for specialized formalisms such as DL-programs. External atoms are then compiled away such that no verification calls are necessary. The approach is implemented in the dlvhex reasoner. Experiments show a significant performance gain. Besides performance improvements, we further exploit inlining for extending previous (semantic) characterizations of program equivalence from ASP to hex-programs, including those of strong equivalence, uniform equivalence, and $\langle\mathcal{H},\mathcal{B}\rangle$- equivalence. Finally, based on these equivalence criteria, we characterize also inconsistency of programs w.r.t. extensions. Since well-known ASP extensions (such as constraint ASP) are special cases of hex, the results are interesting beyond the particular formalism.

The Impact of Leadership Changes on Expectations of Organizational Performance

2015 ◽  
Vol 29 (5) ◽  
pp. 485-497 ◽  
Author(s):  
Brian P. Soebbing ◽  
Pamela Wicker ◽  
Daniel Weimar
Keyword(s):  
Organizational Performance ◽  
Performance Expectations ◽  
Upper Management ◽  
Performance Improvements ◽  
Positive Effects ◽  
Expected Performance ◽  
Management Positions ◽  
Significant Performance ◽  
Leadership Changes ◽  
The Impact

Previous research has examined the effect of changes in upper management positions on actual organizational performance; however, the influence of leadership changes on performance expectations has been largely neglected. This gap in the literature is surprising given that failure to meet expectations leads to dismissal. The purpose of the present research is to analyze how coaching changes affect expectations of a sports team’s performance. Betting lines are used as performance expectations because they are unbiased forecasts of game outcomes. This study uses data from 13 seasons of the German Football Bundesliga. Significant positive timelagged effects on performance expectations are evident when examining underlying expected performance. These positive effects are evident 8 weeks after the leadership change, indicating that new leaders are expected to need some time before significant performance improvements are expected to occur.

Labyrinth Seal Technology Within the Dutch Aero Engine Cluster

2010 ◽  
Author(s):  
Gerrit Kool ◽  
Arjen Kloosterman ◽  
Bambang Soemarwoto ◽  
Joris Versluis ◽  
Robert Janssen
Keyword(s):  
Performance Optimization ◽  
Flow Simulation ◽  
Labyrinth Seal ◽  
Knife Edge ◽  
Performance Improvements ◽  
Seal Design ◽  
Aero Engine ◽  
Improved Performance ◽  
Cfd Analyses ◽  
The Impact

Labyrinth honeycomb seals are regarded as very mature technology and seal flow performance improvements seem to be hardly achievable. However, since computational fluid dynamics have been successfully applied on the flow simulation through these seals, further seal performance optimization becomes within reach against acceptable development costs. This paper describes a staggered labyrinth seal design and is referenced against a two-knife edge stepped seal. Both seals have been evaluated with 3D CFD and tested in an advanced seal test rig facility under realistic conditions. The work described was done by the Dutch Aero Engine Cluster DAEC within the IMPACT-project for Improved Performance by Advanced Compressor Technology. The staggered seal has been selected initially based on potential performance gains, insensitive to axial excursion, good manufacturability, and robust design at acceptable development and manufacturing costs. The staggered labyrinth seal showed a performance improvement of over 30% compared with the baseline two knife edge stepped labyrinth seal. This was demonstrated by both, CFD-analyses and rig testing. In addition, the CFD and test data are consistent with each other.

scholarly journals Performance Evaluation of Java Programming Strategies

2021 ◽  
Vol 10 (4) ◽  
pp. 146-159
Author(s):  
Qusay Idrees Sarhan
Keyword(s):  
Programming Languages ◽  
Web Applications ◽  
Experimental Studies ◽  
Experimental Tests ◽  
Performance Improvements ◽  
Java Programming ◽  
Software Applications ◽  
Wide Range ◽  
Significant Performance ◽  
The Impact

Java is one of the most demanding programming languages nowadays and it is used for developing a wide range of software applications including desktop, mobile, embedded, and web applications. Writing efficient Java codes for those various types of applications (which some are critical and time-sensitive) is crucial and recommended best practices that every Java developer should consider. To date, there is a lack of in-depth experimental studies in the literature that evaluate the impact of writing efficient Java programming strategies on the performance of desktop applications in terms of runtime. Thus, this paper aims to perform a variety of experimental tests that have been carefully chosen and implemented to evaluate the most important aspects of desktop efficient Java programming in terms of runtime. The results of this study show that significant performance improvements can be achieved by applying different programming strategies.

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 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.

Impact of Sustainable Structural Systems Undergraduate Research on Education and Program Development at MSU Denver

2015 ◽  
Vol 1762 ◽  
Author(s):  
Jeno Balogh ◽  
Sandra Haynes ◽  
Aaron Brown
Keyword(s):  
Program Development ◽  
Systems Engineering ◽  
Performance Optimization ◽  
Structural Engineering ◽  
Undergraduate Research ◽  
Solar Furnace ◽  
Direct Access ◽  
Faculty Research ◽  
Research Activities ◽  
The Impact

ABSTRACTThis paper presents the impact of three undergraduate research projects focusing on constructability assessment of adhesive-based wood-concrete composite structural members, on a solar heating technology that can be utilized in conjunction with this system and how these projects relate to engineering education and program development at Metropolitan State University of Denver (MSU Denver). The sustainable structures topic was pursued within senior project classes offered in summer 2013 and 2014 at MSU Denver. The first project addressed new members, while the second dealt with retrofits. These projects were motivated by faculty research in developing new sustainable construction systems using composites. Since underlining faculty research is on an international scale, students had direct access to researchers world-wide. Such research was used as an instrument in the “Experimental Methods in Structural Engineering” course. The students were also exposed to a broader-range of diverse ideas within the field of research by attending an international conference on timber bridges. The solar furnace project was run in parallel, providing students an opportunity to conduct research targeted at design and performance optimization of the heating units with the intention to assess the benefits of incorporating these devices into future buildings using the sustainable structural system technology. Experiences gained through the undergraduate research activities were applied in the design of a proposed Sustainable Systems Engineering degree program.

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.

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