scholarly journals Recognition of Emotion According to the Physical Elements of the Video

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 649 ◽  
Author(s):  
Jing Zhang ◽  
Xingyu Wen ◽  
Mincheol Whang
Keyword(s):  
Video Production ◽  
Support Vector ◽  
Two Dimensional ◽  
K Nearest Neighbors ◽  
Four Dimensions ◽  
Emotion Elicitation ◽  
Neural Processes ◽  
Physical Elements ◽  
The Impact ◽  
The Relationship

The increasing interest in the effects of emotion on cognitive, social, and neural processes creates a constant need for efficient and reliable techniques for emotion elicitation. Emotions are important in many areas, especially in advertising design and video production. The impact of emotions on the audience plays an important role. This paper analyzes the physical elements in a two-dimensional emotion map by extracting the physical elements of a video (color, light intensity, sound, etc.). We used k-nearest neighbors (K-NN), support vector machine (SVM), and multilayer perceptron (MLP) classifiers in the machine learning method to accurately predict the four dimensions that express emotions, as well as summarize the relationship between the two-dimensional emotion space and physical elements when designing and producing video.

scholarly journals Impact of Transformational Leadership on the Affective Commitment of Employees in the Service Sector

2019 ◽  
Vol 8 (4) ◽  
pp. 1388-1393
Keyword(s):  
Transformational Leadership ◽  
Service Sector ◽  
Affective Commitment ◽  
Positive Impact ◽  
Multifactor Leadership Questionnaire ◽  
Intellectual Stimulation ◽  
Four Dimensions ◽  
Multifactor Leadership ◽  
The Impact ◽  
The Relationship

Purpose – There are few studies that have studied the relationship between Transformational leadership (TL) and organisation commitment (OC), but there are very few studies on the service sector especially in the Indian context. This study aims to fill the gap in literature by empirically examining the impact of four dimensions of TL using Multifactor Leadership Questionnaire (MLQ) on the Affective Commitment (AC) of the employees, within the context of the service sector in Bengaluru. Design/methodology/approach – A total of two hypotheses were proposed for testing transformational leadership using Multifactor Leadership Questionnaire (MLQ) questionnaire, (Bass and Avolio, 1997) and five items of affective organization commitment developed by Allen and Meyer (1996) was used for affective commitment. The questionnaire was administered to 210 employees working in various industries in the service sector in Bengaluru to measure the impact of TL on the AC of the respondents. Findings – The analysis of the data collected shows that TL has a positive impact on the affective commitment of the employees. In particular, the results of an empirical investigation revealed that individualized influence and individual consideration by the transformational leader had a significant impact on the affective commitment level of the employees. The employees in the hospitality industry had a difference in opinion compared to IT, Banking & education sector employees on the intellectual stimulation by the leader and their affective commitment towards the organization. Originality/value – This paper contributes to the existing literature of leadership and OC by providing practical evidence leading to the improvement of information and the understanding of the relationship between TL and AC.

scholarly journals Green Intellectual Capital and Firm Competitive Advantage: Evidence from Malaysian Manufacturing Firms

2019 ◽  
pp. 463-471
Author(s):  
Naimah Ahmad Yahya ◽  
Roshayani Arshad ◽  
Amrizah Kamaluddin ◽  
Rahayu Abdul Rahman
Keyword(s):  
Competitive Advantage ◽  
Intellectual Capital ◽  
Manufacturing Firms ◽  
Relational Capital ◽  
Organizational Capital ◽  
Green Innovation ◽  
Four Dimensions ◽  
The Impact ◽  
The Relationship ◽  
Innovation Capital

The purpose of this study is to investigate the relationship between green intellectual capital and firms’ competitive advantage in Malaysia. More specifically this study examines the impact of four dimensions of green intellectual capital; green human capital, green innovation capital, green organisational capital and green relational capital on firms’ competitive advantage. Using survey as a method to collect data from 224 managers of manufacturing firms in Malaysia, the result shows that green intellectual capital and its dimensions, specifically the green innovation capital, green organizational capital and green relational capital have significant and positive relationship with firms’ competitive advantage. Overall, the findings highlight the importance of green intellectual capital as a valuable business resource which in turn enhances firm performance and competitiveness.

scholarly journals The Effect of Emotional Intelligence on Four Dimensions of knowledge Conversion in Selected Industrial Organizational

2015 ◽  
Vol 9 (12) ◽  
pp. 134
Author(s):  
Peyman Akhavan ◽  
Saeid Samiee ◽  
Mahdi Abasaltian ◽  
Ehsan Samimi ◽  
Ali Abasaltian
Keyword(s):  
Emotional Intelligence ◽  
Organizational Culture ◽  
Social Skill ◽  
Research Data ◽  
Four Dimensions ◽  
Knowledge Conversion ◽  
Five Factors ◽  
Different Dimensions ◽  
The Impact ◽  
The Relationship

<p class="zhengwen"><span lang="EN-GB">There is a relation between Emotional intelligence, knowledge management and culture of each organization. In this research the impact of organizational cultures have been studied. The methodology has been used for this research was descriptive. According to type and size of their projects, organizational culture was estimated as bureaucratic in seven organizations. The Quinn organizational culture questionnaire along with several interviews with managers verified the bureaucratic culture in four organizations. The applied tool for data collection was a questionnaire consisting of 33 questions. Moreover, the sample size was 344 employees in four organizations. To investigate the reliability of the questionnaire the Cronbach’s alpha value has been measured and the validity has been confirmed by the field. Moreover, according to Goleman’s emotional intelligence model the five factors have been measured in the selected organizations. Also the knowledge management‘s Model presented by Nonaka and Takeuchi has been used by considering four presented elements. </span></p><p class="zhengwen"><span lang="EN-GB">The results demonstrated that in the bureaucratic cultures, externalization and combination are in a proper status. Analyzing the research data depicted the relationship between different dimensions of emotional intelligence and the ability of individuals in different aspects of converting the knowledge. For example Social skill and empathy ability of individuals have a positive and significant relationship with socialization. </span></p>

scholarly journals The Classification of Profiles of Financial Catastrophe Caused by Out-of-Pocket Payments: A Methodological Approach

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1170
Author(s):  
Maria-Carmen García-Centeno ◽  
Román Mínguez-Salido ◽  
Raúl del Pozo-Rubio
Keyword(s):  
Methodological Approach ◽  
Penalized Regression ◽  
Multivariate Adaptive Regression Splines ◽  
Machine Learning Techniques ◽  
Vulnerable Groups ◽  
Support Vector ◽  
K Nearest Neighbors ◽  
Term Care ◽  
Out Of Pocket Payments ◽  
The Impact

The financial catastrophe resulting from the out-of-pocket payments necessary to access and use healthcare systems has been widely studied in the literature. The aim of this work is to predict the impact of the financial catastrophe a household will face as a result of out-of-pocket payments in long-term care in Spain. These predictions were made using machine learning techniques such as LASSO (Least Absolute Shrinkage and Selection Operator) penalized regression and elastic-net, as well as algorithms like k-nearest neighbors (KNN), MARS (Multivariate Adaptive Regression Splines), random forest, boosted trees and SVM (Support Vector Machine). The results reveal that all the classification methods performed well, with the complex models performing better than the simpler ones and showing no evidence of overfitting. Detecting and defining the profiles of individuals and families most likely to suffer from financial catastrophe is crucial in enabling the design of financial policies aimed at protecting vulnerable groups.

scholarly journals The Impact of Truck Proportion on Traffic Safety Using Surrogate Safety Measures in China

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Shengdi Chen ◽  
Shiwen Zhang ◽  
Yingying Xing ◽  
Jian Lu ◽  
Yichuan Peng ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Traffic Flow ◽  
Traffic Safety ◽  
Variation Coefficient ◽  
Support Vector ◽  
Safety Measures ◽  
Speed Variation ◽  
Surrogate Safety Measures ◽  
The Impact ◽  
The Relationship

The purpose of this study is to investigate the impact of the truck proportion on surrogate safety measures to explore the relationship between truck proportion and traffic safety. The relationship between truck proportion and traffic flow parameters was analyzed by correlation and partial correlation analysis, and the value of the 85th percentile speed minus the 15th percentile speed (85%V–15%V) and the speed variation coefficient were selected as surrogate safety measures to explore the impact of truck proportion on traffic status. The k-means algorithm and the support vector machine were employed to evaluate traffic status on a freeway under different truck proportions in different periods. The major results are that the relationship between truck proportion and the value of 85%V–15%V and the speed variation coefficient is consistent in different aggregation periods. With increasing truck proportion, the value of 85%V–15%V, as well as the speed variation coefficient, increases initially and then decreases. In addition, the traffic flow status tends to be dangerous when the truck proportion ranges from 0.4 to 0.6 and when the value of 85%V–15%V and the speed variation coefficient are above 42 km/h and 0.223, respectively. While the truck proportion is from 0.1 to 0.3 and from 0.7 to 0.9, the traffic flow is relatively safe on the condition that the value of 85%V–15%V and the speed variation coefficient were under 42 km/h and 0.223, respectively. Therefore, the relationship between truck proportion and traffic safety could be well revealed by two surrogate safety measures, that is, the value of 85%V–15%V and the speed variation coefficient. In addition, the k-means algorithm and the support vector machine can well reveal the impact of truck proportion on traffic safety in different periods. The findings of this study indicate a need for decreasing the disturbance of mixed traffic and the impact of the truck proportion on traffic safety status.

Assessing the impact of business uncertainty on supply chain integration

2016 ◽  
Vol 27 (2) ◽  
pp. 463-485 ◽  
Author(s):  
Minkyun Kim ◽  
Sangmi Chai
Keyword(s):  
Supply Chain ◽  
Supply Chain Integration ◽  
Content Type ◽  
Four Dimensions ◽  
Purchasing Managers ◽  
And Performance ◽  
Push And Pull ◽  
The Impact ◽  
The Relationship

Purpose – The purpose of this paper is to investigate how business uncertainty affects the implementation of supply chain integration (SCI). More importantly, this research divides business uncertainty into four dimensions and SCI into three dimensions to examine the role of each dimension. In addition, it investigates the moderating effects of manufacturing approaches, such as push and pull, in the relationship between SCI and performance. Design/methodology/approach – Through a structured survey, this study collected 259 responses from supply executives, and supply and purchasing managers of US manufacturing firms. The empirical data analysis was done by using the partial least squares technique. Findings – The results empirically support the findings that business uncertainty positively affects implementation of SCI. Among the four dimensions of business uncertainty, dynamism and hostility significantly affect implementation of internal integration, integration with suppliers, and integration with customers. In addition, manufacturing approaches, such as push and pull, have a moderating effect on the relationship between SCI and performance. Practical implications – This study collected survey responses from a manufacturing firm in the supply chain to assist managers to find a solution while dealing with business uncertainty through the implementation of SCI. It also emphasizes manufacturing approaches, such as push and pull, in implementing SCI to improve performance. Thus, supply and purchasing managers should consider the business uncertainty that they are dealing with while developing their supply chain strategy. Originality/value – To the best of the authors’ knowledge, this study is the first to provide meaningful insights on the effects of SCI toward dealing with business uncertainty. More importantly, by dividing the dimensions of business uncertainty and SCI, this study presents empirical evidence of the significant role of supply chain practices in uncertain business conditions. In addition, this study addresses the gap in extant literature and shows that managers need to consider their manufacturing approach in SCI to improve business performance.

scholarly journals The Impact of Feature Selection Methods for Classifying Arabic Textual Data

2019 ◽  
Vol 8 (4) ◽  
pp. 1333-1338
Keyword(s):  
Feature Selection ◽  
Text Classification ◽  
Information Gain ◽  
Feature Space ◽  
Support Vector ◽  
Selection Methods ◽  
K Nearest Neighbors ◽  
Chi Square ◽  
Selection Algorithms ◽  
The Impact

Text classification is a vital process due to the large volume of electronic articles. One of the drawbacks of text classification is the high dimensionality of feature space. Scholars developed several algorithms to choose relevant features from article text such as Chi-square (x2 ), Information Gain (IG), and Correlation (CFS). These algorithms have been investigated widely for English text, while studies for Arabic text are still limited. In this paper, we investigated four well-known algorithms: Support Vector Machines (SVMs), Naïve Bayes (NB), K-Nearest Neighbors (KNN), and Decision Tree against benchmark Arabic textual datasets, called Saudi Press Agency (SPA) to evaluate the impact of feature selection methods. Using the WEKA tool, we have experimented the application of the four mentioned classification algorithms with and without feature selection algorithms. The results provided clear evidence that the three feature selection methods often improves classification accuracy by eliminating irrelevant features.

Strategic alignment and its impact on decision effectiveness: a comprehensive model

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohamed A. Ghonim ◽  
Nagi M. Khashaba ◽  
Hameda M. Al-Najaar ◽  
Mohamed A. Khashan
Keyword(s):  
Strategic Alignment ◽  
Developed Countries ◽  
Primary Data ◽  
Comprehensive Model ◽  
Content Type ◽  
Strategic Performance ◽  
Four Dimensions ◽  
The Public ◽  
The Impact ◽  
The Relationship

PurposeIn recent decades, the concept of strategic alignment has been a center of concern for researchers and practitioners. This alignment is associated with the process of strategic planning to achieve high strategic performance and competitiveness. This study aims to investigate the impact of strategic alignment on decision effectiveness.Design/methodology/approachPrimary data were collected from 383 employees of the Directorate of Health Affairs in the Dakahlia Governorate in Egypt, through a self-administered questionnaire. The PLS-SEM approach was used to analyze the collected data.FindingsThe results revealed that strategic alignment significantly and positively affects decision effectiveness and its dimensions, emphasizing the importance of considering all four dimensions of strategic alignment in an integrated model to achieve the greatest impact on the decision effectiveness.Research limitations/implicationsThis study is applied to a developing country, so a comparative study between both developing and developed countries may be needed. Second, the study was restricted to the nonprofit organization, so further research may examine the profit organizations.Originality/valueDespite the existence of several studies on the relationship between strategic alignment and decision effectiveness in developed countries, studies conducted in the developing countries are still few. This is one of the earliest studies that adopt the multidimensional approach of strategic alignment in the public sector in emerging economies, which could help directors understand the interdependencies and different roles of strategic alignment dimensions in a novel comprehensive model.

scholarly journals The Impact of Context-Based Capabilities on the Type of Communication of Spaces

2018 ◽  
Vol 4 (6) ◽  
pp. 1415
Author(s):  
Mojgan Khakpour ◽  
Guilda Daghighi Masoule ◽  
Mehrdad Amirnejad Mojdehi
Keyword(s):  
Research Method ◽  
Research Question ◽  
The Body ◽  
Traditional Architecture ◽  
Spatial Continuity ◽  
Behavioural Patterns ◽  
Analytical Research ◽  
Physical Elements ◽  
The Impact ◽  
The Relationship

Perceiving an architectural work requires a comprehensive understanding of its context, since the context has a direct impact on both the body and the activities. This recognition can be examined from two aspects: the study of natural and geographical conditions and human-based conditions which include the symbolic, religious-cultural, historical, social, and economic values. What has been considered through this article was the effect of these factors on the type of communication between the spaces. Due to the climate and cultural characteristics across Guilan province, it seems that the spaces from their public realm- that is from the neighbourhood spaces to their most exclusive parts- include rooms and closed spaces that have such continuity which was created by the elements of the boundary between these spaces. These elements link the spaces together and lead to a hierarchy of activities. The research question is whether the relationship between spaces and spatial continuity in traditional architecture of Rasht is influenced by the capabilities of the context or not? This is a descriptive-analytical research, which used a qualitative research method. Data collection was carried out by using desk research method   and field observations. The data was analysed through content analysis and independent of numerical documentation within an analogy process. With respect to the effect of filed capabilities on the traditional architecture in Rasht city, first a sample of buildings was selected and the physical elements contributing to continuity of the space have been studied. Then, the effect of the context-based capabilities on them was considered. It was found that these capabilities contributed to formation of the physical elements and behavioural patterns which itself can affect the type of relationship between space and its continuity within old urban tissues of Rasht, including the sensory continuity and the physical continuity between the spaces.

scholarly journals Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2016 ◽  
Author(s):  
Aleksandra Dorochowicz ◽  
Adam Kurowski ◽  
Bożena Kostek
Keyword(s):  
Personality Trait ◽  
Internet Survey ◽  
Support Vector ◽  
Svm Classifier ◽  
K Nearest Neighbors ◽  
Low Level ◽  
Music Genres ◽  
Subjective Tests ◽  
Musical Excerpt ◽  
The Relationship

The purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks. First, an Internet survey was built, in which the respondents identify themselves as extraverts or introverts according to the given definitions. Their task was to listen to music excerpts that belong to several music genres and choose the ones they like. Next, music samples were parameterized. Two parametrization schemes were employed for that purpose, i.e., low-level MIRtoolbox parameters (MIRTbx) and variational autoencoder neural network-based, which automatically extract parameters of musical excerpts. The prediction of a personality type was performed employing four baseline algorithms, i.e., support vector machine (SVM), k-nearest neighbors (k-NN), random forest (RF), and naïve Bayes (NB). The best results were obtained by the SVM classifier. The results of these analyses led to the conclusion that musical excerpt features derived from the autoencoder were, in general, more likely to carry useful information associated with the personality of the listeners than the low-level parameters derived from the signal analysis. We also found that training of the autoencoders on sets of musical pieces which contain genres other than ones employed in the subjective tests did not affect the accuracy of the classifiers predicting the personalities of the survey participants.

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