Algorithms and Performance Results for Dynamic HSDPA Resource Allocation

2006 ◽  
Author(s):  
Klaus Pedersen ◽  
Per Michaelsen
Keyword(s):  
Resource Allocation ◽  
And Performance ◽  
Performance Results

The Relation Between Financial Incentives, Motivation, and Performance

2017 ◽  
Vol 16 (2) ◽  
pp. 61-76 ◽  
Author(s):  
Anaïs Thibault Landry ◽  
Marylène Gagné ◽  
Jacques Forest ◽  
Sylvie Guerrero ◽  
Michel Séguin ◽  
...  
Keyword(s):  
Financial Incentives ◽  
Work Performance ◽  
Autonomous Motivation ◽  
Compensation Plans ◽  
Work Settings ◽  
Path Analyses ◽  
Three Samples ◽  
And Performance ◽  
Performance Results

Abstract. To this day, researchers are debating the adequacy of using financial incentives to bolster performance in work settings. Our goal was to contribute to current understanding by considering the moderating role of distributive justice in the relation between financial incentives, motivation, and performance. Based on self-determination theory, we hypothesized that when bonuses are fairly distributed, using financial incentives makes employees feel more competent and autonomous, which in turn fosters greater autonomous motivation and lower controlled motivation, and better work performance. Results from path analyses in three samples supported our hypotheses, suggesting that the effect of financial incentives is contextual, and that compensation plans using financial incentives and bonuses can be effective when properly managed.

scholarly journals Two Sides of the Same Coin. University-Industry Collaboration and Open Innovation as Enhancers of Firm Performance

2021 ◽  
Vol 13 (7) ◽  
pp. 3866
Author(s):  
Joana Costa ◽  
Ana Rita Neves ◽  
João Reis
Keyword(s):  
Firm Performance ◽  
Open Innovation ◽  
Primary Data ◽  
Company Performance ◽  
Innovation Ecosystem ◽  
Industry Collaboration ◽  
And Performance ◽  
Performance Results ◽  
The Impact ◽  
University Industry

Open innovation is proved to be determinant in the rationalization of sustainable innovation ecosystems. Firms, universities, governments, user communities and the overall environment are called to contribute to this dynamic process. This study aims to contribute to a better understanding of the impact of open innovation on firms’ performance and to empirically assess whether university-industry collaborations are complementary or substitutes for this activity. Primary data were collected from a survey encompassing 908 firms, and then combined with performance indicators from SABI (Spanish and Portuguese business information). Econometric estimations were run to evaluate the role of open innovation and university-industry collaboration in the firm innovative propensity and performance. Results highlight the importance of diversity in collaborations with the academia and inbound open innovation strategy as enhancers of firm performance. The two activities reinforce each other. By testing the impact of open innovation practices on company performance, the need for heterogeneity in terms of contact type and university is also demonstrated. Findings cast light on the need to reformulate existing policy packages, reinforcing the ties with academia as well as the promotion of open innovation strategies. The connection to the innovation ecosystem needs to be further encouraged as well as the promotion of persistent connections with the knowledge sources in an open and multilateral framework.

DESIGN, PREPRODUCTION, AND PERFORMANCE OF THE CDF RUN IIB SILICON DETECTOR

2005 ◽  
Vol 20 (16) ◽  
pp. 3811-3814
Author(s):  
◽  
PAUL LUJAN
Keyword(s):  
Building Block ◽  
Silicon Detector ◽  
Radiation Hardness ◽  
Control Signals ◽  
Lightweight Structure ◽  
And Performance ◽  
Performance Results ◽  
And Control ◽  
Radiation Hard ◽  
Detector Design

A new silicon detector was designed by the CDF collaboration for Run IIb of the Tevatron at Fermilab. The main building block of the new detector is a "supermodule" or "stave", an innovative, compact and lightweight structure of several readout hybrids and sensors with a bus cable running directly underneath the sensors to carry power, data, and control signals to and from the hybrids. The hybrids use a new, radiation-hard readout chip, the SVX4 chip. A number of SVX4 chips, readout hybrids, sensors, and supermodules were produced and tested in preproduction. The performance (including radiation-hardness) and yield of these components met or exceeded all design goals. The detector design goals, solutions, and performance results are presented.

Grid Resource Allocation with Genetic Algorithm Using Population Based on Multisets

2017 ◽  
Vol 26 (1) ◽  
pp. 169-184 ◽  
Author(s):  
Absalom E. Ezugwu ◽  
Nneoma A. Okoroafor ◽  
Seyed M. Buhari ◽  
Marc E. Frincu ◽  
Sahalu B. Junaidu
Keyword(s):  
Genetic Algorithm ◽  
Resource Allocation ◽  
Grid Computing ◽  
Resource Selection ◽  
Computing System ◽  
Population Based ◽  
Fine Tuning ◽  
Grid Resource ◽  
Performance Results ◽  
Grid Resources

AbstractThe operational efficacy of the grid computing system depends mainly on the proper management of grid resources to carry out the various jobs that users send to the grid. The paper explores an alternative way of efficiently searching, matching, and allocating distributed grid resources to jobs in such a way that the resource demand of each grid user job is met. A proposal of resource selection method that is based on the concept of genetic algorithm (GA) using populations based on multisets is made. Furthermore, the paper presents a hybrid GA-based scheduling framework that efficiently searches for the best available resources for user jobs in a typical grid computing environment. For the proposed resource allocation method, additional mechanisms (populations based on multiset and adaptive matching) are introduced into the GA components to enhance their search capability in a large problem space. Empirical study is presented in order to demonstrate the importance of operator improvement on traditional GA. The preliminary performance results show that the proposed introduction of an additional operator fine-tuning is efficient in both speed and accuracy and can keep up with high job arrival rates.

scholarly journals Popularity and performance of bioinformatics software: the case of gene set analysis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Chengshu Xie ◽  
Shaurya Jauhari ◽  
Antonio Mora
Keyword(s):  
Comprehensive Evaluation ◽  
Gene Set Analysis ◽  
Tool Selection ◽  
Functional Interpretation ◽  
Selection Procedures ◽  
Gene Set ◽  
And Performance ◽  
Reported Data ◽  
Performance Results

Abstract Background Gene Set Analysis (GSA) is arguably the method of choice for the functional interpretation of omics results. The following paper explores the popularity and the performance of all the GSA methodologies and software published during the 20 years since its inception. "Popularity" is estimated according to each paper's citation counts, while "performance" is based on a comprehensive evaluation of the validation strategies used by papers in the field, as well as the consolidated results from the existing benchmark studies. Results Regarding popularity, data is collected into an online open database ("GSARefDB") which allows browsing bibliographic and method-descriptive information from 503 GSA paper references; regarding performance, we introduce a repository of jupyter workflows and shiny apps for automated benchmarking of GSA methods (“GSA-BenchmarKING”). After comparing popularity versus performance, results show discrepancies between the most popular and the best performing GSA methods. Conclusions The above-mentioned results call our attention towards the nature of the tool selection procedures followed by researchers and raise doubts regarding the quality of the functional interpretation of biological datasets in current biomedical studies. Suggestions for the future of the functional interpretation field are made, including strategies for education and discussion of GSA tools, better validation and benchmarking practices, reproducibility, and functional re-analysis of previously reported data.

On improving the training of aircraft engineers

2021 ◽  
Vol 20 (5) ◽  
pp. 865-885
Author(s):  
Leonid B. SOBOLEV
Keyword(s):  
Aviation Industry ◽  
Information Protection ◽  
Global Trends ◽  
Space Industry ◽  
The Poor ◽  
Military Aviation ◽  
And Performance ◽  
Performance Results ◽  
The Military ◽  
The U.S

Subject. The article continues the discussion about the method of training aircraft engineers to work in the military and civil segments of aviation and rocket-and-space industry. Objectives. The purpose is to improve the training of Russian engineers to work in the competitive market environment, on the basis of the analysis of experience in training the aviation engineers in leading foreign technical universities. Methods. The study rests on the comparative analysis of implementation of major projects in the military and civil segments of aviation in the U.S. and Russia, as well as programs for training aircraft engineers in both countries. Results. The analysis shows that the duration of modern large military aviation projects in both countries is the same (the comparison of cost is impossible, due to information protection in Russia), while in the civil segment of the aviation industry, Russia's lagging behind is significant both in terms of the duration of projects and performance results. One of the reasons is in the poor training of aircraft engineers to work in the competitive environment. Conclusions. It is crucial to reform Russian aviation universities in terms of conformity to global trends in multidisciplinarity and differentiation of financing and research base.

Secretly Pruned Convolutional Codes: Security Analysis and Performance Results

2016 ◽  
Vol 11 (7) ◽  
pp. 1500-1514 ◽  
Author(s):  
Nicholas Kolokotronis ◽  
Alexandros Katsiotis ◽  
Nicholas Kalouptsidis
Keyword(s):  
Security Analysis ◽  
Convolutional Codes ◽  
And Performance ◽  
Performance Results
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