SU-F-P-64: The Impact of Plan Complexity Parameters On the Plan Quality and Deliverability of Volumetric Modulated Arc Therapy with Canonical Correlation Analysis

2016 ◽  
Vol 43 (6Part6) ◽  
pp. 3372-3372
Author(s):  
X Jin ◽  
J Yi ◽  
C Xie
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Volumetric Modulated Arc Therapy ◽  
Plan Quality ◽  
Arc Therapy ◽  
The Impact

scholarly journals Canonical Correlation Analysis and a New Composite Index on Digitalization and Labor Force in the Context of the Industrial Revolution 4.0

2020 ◽  
Vol 12 (17) ◽  
pp. 6812
Author(s):  
Ane-Mari Androniceanu ◽  
Irina Georgescu ◽  
Manuela Tvaronavičienė ◽  
Armenia Androniceanu
Keyword(s):  
Correlation Analysis ◽  
Labor Force ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Structural Changes ◽  
Industrial Revolution ◽  
Composite Index ◽  
Developed Countries ◽  
World Economic ◽  
The Impact

The current phenomenon of the economy-accelerated digitalization, known as the “Industry 4.0”, will generate both an increased productivity, connectivity and several transformations on the labor force skills. Our research objectives are to determine the influence that digitalization has had on the workforce in several developed countries and to propose a new composite indicator that reflects these dynamics over time. We have used the Canonical Correlation Analysis (CCA) in order to identify and analyze the correlations between two sets of variables, an independent one and a dependent one. Data were collected from the World Bank and World Economic Forum for the years 2018–2019. Based on the results of our research we have determined and made a consistent analysis of the new composite index of digitalization and labor force in 19 countries. The results of our research are relevant and show not only the impact of digitalization on the labor force in different countries, but also the structural changes required by the new economic and social models. Our research can help decision-makers get in advance the necessary measures in the field of labor force in order to ensure a proper integration of these measures into the new economic model based on digitalization.

Canonical correlation analysis of the impact of ICT on the diversification performance

2020 ◽  
Vol 19 (2/3) ◽  
pp. 202
Author(s):  
Omar Alexánder León García ◽  
Juan Ignacio Igartua Lopez ◽  
Jaione Ganzarain Epelde
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
The Impact

Real-time damage detection of degrading systems

2019 ◽  
Vol 19 (3) ◽  
pp. 810-837 ◽  
Author(s):  
Tapas Tripura ◽  
Basuraj Bhowmik ◽  
Vikram Pakrashi ◽  
Budhaditya Hazra
Keyword(s):  
Correlation Analysis ◽  
Damage Detection ◽  
Real Time ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Degree Of Freedom ◽  
Time Varying ◽  
Analysis Algorithm ◽  
Stiffness Reduction ◽  
The Impact

In this article, a robust output-only real-time damage detection technique for multi-degree-of-freedom degrading systems using recursive canonical correlation analysis is presented. It has been observed that the impact of damage to a vibrating system gradually advances with time that sustains until the system degrades up to a considerable extent. Of significant interest is the effect of sudden damage in presence of continuous degradation in real-time, which is studied in the form of a sudden stiffness reduction in a separate floor. The proposed recursive canonical correlation analysis algorithm estimates the iterative update of eigenspace at each instant from the response data, thereby capturing the features of a time varying degrading structure in an online framework. Furthermore, recursive canonical correlation analysis algorithm is shown to reduce the computational cost by updating the eigenspace at each instant of time. This article explores newly developed recursive condition indicators: recursive Mahalanobis distance and recursive Itakura distance that elicit damage information from the eigenspace. In order to model degradation, simulations aimed at successfully capturing the behavior of the process in real-time becomes imperative. A general stochastic formulation of the coupled response-degradation problem accounting for the evolution of degradation is presented in the light of stiffness degradation problems. The evolution of time varying system responses is generated using a newly proposed Ito–Taylor expansion-based stochastic numerical integration formulation. Numerically simulated structural vibrating systems, namely, 2-degree-of-freedom base-isolated and 4-degree-of-freedom linear systems, have been used to check the performance of the recursive canonical correlation analysis method. The spatial damage detectability of the algorithm in real-time is explored through identifying crack location on a beam traversed by a vehicle. Finally, an experimental case study has been carried out to verify the robustness of the proposed algorithm. The identification results for both numerical and experimental cases demonstrate the efficacy of the proposed algorithm in identification of nonlinear and time varying behavior associated with degrading structural systems.

The Impact of Channel Leadership Behavior on Intrachannel Conflict

1983 ◽  
Vol 47 (3) ◽  
pp. 21-34 ◽  
Author(s):  
Patrick L. Schul ◽  
William M. Pride ◽  
Taylor L. Little
Keyword(s):  
Factor Analysis ◽  
Correlation Analysis ◽  
Leadership Style ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Leadership Behavior ◽  
Distribution Channel ◽  
Product Service ◽  
Different Types ◽  
The Impact

This study examines the impact of different types of channel leadership behavior on channel members' perceptions of intrachannel conflict in a franchise distribution channel. Factor analysis and canonical correlation analysis are used to explore the relationships between participative, supportive and directive leadership behavior and dependent measures of intrachannel conflict. The results indicate that conflict arising from both administrative and product-service issues diminishes when the franchisor is perceived to exhibit a leadership style emphasizing participation, support and direction in carrying out channel activities.

scholarly journals Methodological Approaches to Assessing the Impact of Information Technologies on Economic Growth in the Regions of Russia

2020 ◽  
pp. 23-34
Author(s):  
Elena Petrova ◽  
Petr Bondarenko ◽  
Alla Shipileva
Keyword(s):  
Economic Growth ◽  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Russian Federation ◽  
Canonical Correlation ◽  
Methodological Approach ◽  
Assessment Tools ◽  
Broadband Internet ◽  
The Russian Federation ◽  
The Impact

In this work, the authors propose a methodological approach to study the impact of using NBICtechnologies on the economic growth of the regions of the Russian Federation. The authors show that among NBIC-technologies they are ICT that have the greatest impact on economic growth. The assessment tools are integrated empirical analysis methods. At the first stage, a cluster analysis was carried out using the k-means method according to the per-capita GRP, the level of population income and the level of ICT use, under which three groups of Russian regions were distinguished, characterized by low, medium and high dynamics of economic growth. At the second stage, a canonical correlation analysis was carried out and analytical expressions of the interconnections of economic growth indicators and a set of indicators characterizing the development and use of ICT in the regions of the Russian Federation were obtained. The study proves the relationship between ICT and economic growth in the regions of the Russian Federation. The greatest influence is exerted by indicators such as the number of mobile cell phones and broadband Internet subscribers. The canonical correlation analysis for the selected groups of regions did not give positive results, the results for the first cluster, which is characterized by low dynamics of economic growth, turned out to be statistically significant. Most likely, this is due to the fact that in this group using ICT gives the greatest effect. However, the substantiation of this hypothesis requires the expansion of the statistical base of the study, both in time and in terms of expanding the composition of indicators that reflect not only economic, but also social aspects of the processes under study.

scholarly journals Sinc-Windowing and Multiple Correlation Coefficients Improve SSVEP Recognition Based on Canonical Correlation Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Valeria Mondini ◽  
Anna Lisa Mangia ◽  
Luca Talevi ◽  
Angelo Cappello
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Classification Accuracy ◽  
Canonical Correlation ◽  
Positive Impact ◽  
Low Cost ◽  
Correlation Coefficients ◽  
Canonical Correlations ◽  
User Training ◽  
The Impact

Canonical Correlation Analysis (CCA) is an increasingly used approach in the field of Steady-State Visually Evoked Potential (SSVEP) recognition. The efficacy of the method has been widely proven, and several variations have been proposed. However, most CCA variations tend to complicate the method, usually requiring additional user training or increasing computational load. Taking simple procedures and low computational costs may be, however, a relevant aspect, especially in view of low-cost and high-portability devices. In addition, it would be desirable that the proposed variations are as general and modular as possible to facilitate the translation of results to different algorithms and setups. In this work, we evaluated the impact of two simple, modular variations of the classical CCA method. The variations involved (i) the number of canonical correlations used for classification and (ii) the inclusion of a prefiltering step by means of sinc-windowing. We tested ten volunteers in a 4-class SSVEP setup. Both variations significantly improved classification accuracy when they were used separately or in conjunction and led to accuracy increments up to 7-8% on average and peak of 25–30%. Additionally, variations had no (variation (i)) or minimal (variation (ii)) impact on the number of algorithm steps required for each classification. Given the modular nature of the proposed variations and their positive impact on classification accuracy, they might be easily included in the design of CCA-based algorithms that are even different from ours.

scholarly journals Seasonal Prediction of Winter Precipitation Anomalies over Central Southwest Asia: A Canonical Correlation Analysis Approach

2018 ◽  
Vol 31 (2) ◽  
pp. 727-741 ◽  
Author(s):  
Sapna Rana ◽  
James Renwick ◽  
James McGregor ◽  
Ankita Singh
Keyword(s):  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Southern Oscillation ◽  
Winter Precipitation ◽  
Southwest Asia ◽  
Potential Predictability ◽  
The Pacific ◽  
Precipitation Anomalies ◽  
The Impact

Central southwest Asia (CSWA; 20°–47°N, 40°–85°E) is a water-stressed region prone to significant variations in precipitation during its winter precipitation season of November–April. Wintertime precipitation is crucial for regional water resources, agriculture, and livelihood; however, in recent years droughts have been a notable feature of CSWA interannual variability. Here, the predictability of CSWA wintertime precipitation is explored based on its time-lagged relationship with the preceding months’ (September–October) sea surface temperature (SST), using a canonical correlation analysis (CCA) approach. For both periods, results indicate that for CSWA much of the seasonal predictability arises from SST variations in the Pacific related to El Niño–Southern Oscillation (ENSO) and the Pacific decadal oscillation (PDO). Additional sources of skill that play a weaker predictive role include long-term SST trends, North Atlantic variability, and regional teleconnections. CCA cross-validation skill shows that the regional potential predictability has a strong dependency on the ENSO phenomenon, and the strengthening (weakening) of this relationship yields forecasts with higher (lower) predictive skill. This finding is validated by the mean cross-validated correlation skill of 0.71 and 0.38 obtained for the 1980/81–2014/15 and 1950/51–2014/15 CCA analyses, respectively. The development of cold (warm) ENSO conditions during September–October, in combination with cold (warm) PDO conditions, is associated with a northward (southward) shift of the jet stream and a strong tendency of negative (positive) winter precipitation anomalies; other sources of predictability influence the regional precipitation directly during non-ENSO years or by modulating the impact of ENSO teleconnection based on their relative strengths.

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