scholarly journals Machine Learning And Statistical Theory Enabled Real Time People Analytics Framework Based On Emotional Quotient Intelligence And Self Efficacy

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3454-3459
Keyword(s):  
Machine Learning ◽  
Emotional Intelligence ◽  
Statistical Theory ◽  
Real Time ◽  
Self Efficacy ◽  
General Public ◽  
T Test ◽  
The Other ◽  
The Public ◽  
Common Association

The motivation behind the examination was to concentrate the connection between Emotional Intelligence (E.I.) and Self-Efficacy (S.E.) with statistic factors in the Public members in Madurai and Dindigul. This review was illustrative. The general public comprised of thousand ranges and the example was 120 who were haphazardly chosen. Enthusiastic Intelligence Inventory was utilized as an tool. Relationship, t-test and relapse were utilized to examination of information. Comes about demonstrated that there was critical connection between E.I. also, S.E emphatically. There were not discovered noteworthy contrasts amongst operational and authoritative; and prepared and untrained persons in Emotional Intelligence and Self-Efficacy. Plus, Emotional Intelligence was anticipated by statistic factors and Self-Efficacy and the other way around. Passionate Intelligence and Self-Efficacy have common association with each other.

The Relationship between Emotional Intelligence and Rh Type

2014 ◽  
Vol 1 (1) ◽  
pp. 7-9
Author(s):  
Sepideh Iranfar
Keyword(s):  
Emotional Intelligence ◽  
Blood Groups ◽  
T Test ◽  
The Other ◽  
Significance Level ◽  
The Relationship ◽  
Positive Groups

This study has been aimed to find out the correlation emotional intelligence and Rhtype. The simple sizes were 35 undergraduate and graduate of Abadan Oil College with the cluster sampling.The correlation between emotional intelligence and P/N blood groups was 0.085 and it does not accept by standard statistics. We enter the other variable as emotional intelligence groups. The correlation between Rh type and emotional intelligence groups was 0.136 and this correlation in 0/2 significance level had been reported significant.The result was tested by t test, and analysis shown significance difference.it was found that scattering of Rh type was not equal on EI.As well as positive groups can receive upper scores of EI than negative ones and negatives groups have less scores of EI the other. In fact most positives have scores between "114-148", means that they can perch in the medium and high groups of EI.

Public Space, Common Space, and the Spaces In–Between: A Case Study of Philadelphia's LOVE Park

2020 ◽  
Vol 19 (3) ◽  
pp. 676-703
Author(s):  
Luke M. Cianciotto
Keyword(s):  
Public Space ◽  
General Public ◽  
Urban Landscape ◽  
Public Spaces ◽  
The Other ◽  
The Public ◽  
Common Space ◽  
The Common

This study concerns the struggle for Philadelphia's LOVE Park, which involved the general public and its functionaries on one side and skateboarders on the other. This paper argues LOVE Park was one place composed of two distinct spaces: the public space the public engendered and the common space the skateboarders produced. This case demonstrates that public and common space must be understood as distinct, for they entail different understandings of publicly accessible space. Additionally, public and common spaces often exist simultaneously as “public–common spaces,” which emphasizes how they reciprocally shape one another. This sheds light on the emergence of “anti–common public space,” which is evident in LOVE Park's 2016 redesign. This concept considers how common spaces are increasingly negated in public spaces. The introduction of common space to the study of public spaces is significant as it allows for more nuanced understandings of transformations in the urban landscape.

scholarly journals A Real-Time Machine Learning Based Public Transport Bus-Passenger Information System

2021 ◽  
Author(s):  
Menzi Skhosana ◽  
Absalom Ezugwu
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Public Transport ◽  
Public Transportation ◽  
Web Application ◽  
Predictive Analytics ◽  
Current Status ◽  
Transport Sector ◽  
The Public ◽  
Cost Efficient

The era of Big Data and the Internet of Things is upon us, and it is time for developing countries to take advantage of and pragmatically apply these ideas to solve real-world problems. Many problems faced daily by the public transportation sector can be resolved or mitigated through the collection of appropriate data and application of predictive analytics. In this body of work, we are primarily focused on problems affecting public transport buses. These include the unavailability of real-time information to commuters about the current status of a given bus or travel route; and the inability of bus operators to efficiently assign available buses to routes for a given day based on expected demand for a particular route. A cloud-based system was developed to address the aforementioned. This system is composed of two subsystems, namely a mobile application for commuters to provide the current location and availability of a given bus and other related information, which can also be used by drivers so that the bus can be tracked in real-time and collect ridership information throughout the day, and a web application that serves as a dashboard for bus operators to gain insights from the collected ridership data. These were integrated with a machine learning model trained on collected ridership data to predict the daily ridership for a given route. Our novel system provides a holistic solution to problems in the public transport sector, as it is highly scalable, cost-efficient and takes full advantage of the currently available technologies in comparison with other previous work in this topic.

A Virtual Reality Drumkit Simulator System with a Kinect Device

2015 ◽  
Vol 6 (1) ◽  
pp. 72-86 ◽  
Author(s):  
Alejandro Rosa-Pujazón ◽  
Isabel Barbancho ◽  
Lorenzo J. Tardón ◽  
Ana M. Barbancho
Keyword(s):  
Machine Learning ◽  
Virtual Reality ◽  
Real Time ◽  
User Experience ◽  
The Other ◽  
Wiener Filtering ◽  
Detection Model ◽  
Time Interaction ◽  
Kinect Camera ◽  
Drumkit Simulator

In this paper, an implementation of a virtual reality based application for drumkit simulation is presented. The system tracks user motion through the use of a Kinect camera sensor, and recognizes and detects user-generated drum-hitting gestures in real-time. In order to compensate the effects of latency in the sensing stage and provide real-time interaction, the system uses a gesture detection model to predict user movements. The paper discusses the use of two different machine learning based solutions to this problem: the first one is based on the analysis of velocity and acceleration peaks, the other solution is based on Wiener filtering. This gesture detector was tested and integrated into a full implementation of a drumkit simulator, capable of discriminating up to 3, 5 or 7 different drum sounds. An experiment with 14 participants was conducted to assess the system's viability and impact on user experience and satisfaction.

Humor Analysis Of Ideological Discussion In Twitter Account Interactions @NUgarislucu and @MuhammadiyinGL

2021 ◽  
Vol 1 (1) ◽  
pp. 19-25
Author(s):  
Ahmad Efendi
Keyword(s):  
Social Media ◽  
General Public ◽  
Indirect Interactions ◽  
The Other ◽  
The Public ◽  
Twitter Account

This study aims to analyze the humorous interaction of ideological discourses between twitter account @NUgarislucu and @MuhammadiyinGL. In social media twitter because they often interact with organizational ideological issues in a joke. Researchers cite 5 direct and indirect interactions between the @NUgarislucu and @MuhammadiyinGL twitter accounts during January-February 2021 with different interaction backgrounds. In the interaction between the two accounts above, there are actually ideologies of their respective organizations that want to be conveyed to the public. However, the two accounts also show the general public that conveying beliefs, religious doctrines can actually be done with jokes and humor. You don't have to think that one group is right and the other is wrong.

How Measurable Is Success?

1969 ◽  
Vol 15 (4) ◽  
pp. 519-524
Author(s):  
Chester H. Bartoo
Keyword(s):  
General Public ◽  
The Other ◽  
Physical Sciences ◽  
Is Success ◽  
The Public ◽  
Clear Cut ◽  
Other Hand

The general public wants "success" or "failure" defined in black or white terms. The physical sciences offer universally clear-cut definitions, formulas, and criteria by which their "suc cess" can be appraised; on the other hand, the behavioral sci ences are equivocal and the public, bewildered, questions the truth of the claimed "successes." Correction, in particular, must embark on research that will formalize and measure the authen ticity of its "successes."

scholarly journals Unmasking People’s Opinions behind Mask-Wearing during COVID-19 Pandemic—A Twitter Stance Analysis

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1995
Author(s):  
Liviu-Adrian Cotfas ◽  
Camelia Delcea ◽  
Rareș Gherai ◽  
Ioan Roxin
Keyword(s):  
Machine Learning ◽  
General Public ◽  
Protective Measure ◽  
Public Authorities ◽  
Public Places ◽  
The Public ◽  
Public Perspective ◽  
Mixed Messages ◽  
One Year ◽  
The One

Wearing a mask by the general public has been a controversial issue from the beginning of the COVID-19 pandemic as the public authorities have had mixed messages, either advising people not to wear masks if uninfected, to wear as a protective measure, to wear them only when inside a building/room with insufficient air flow or to wear them in all the public places. To date, the governments have had different policies regarding mask-wearing by the general public depending on the COVID-19 pandemic evolution. In this context, the paper analyzes the general public’s opinion regarding mask-wearing for the one-year period starting from 9 January 2020, when the first tweet regarding mask-wearing in the COVID-19 context has been posted. Classical machine learning and deep learning algorithms have been considered in analyzing the 8,795,633 tweets extracted. A random sample of 29,613 tweets has been extracted and annotated. The tweets containing news and information related to mask-wearing have been included in the neutral category, while the ones containing people’s opinions (for or against) have been marked using a symmetrical approach into in favor and against categories. Based on the analysis, it has been determined that most of the mask tweets are in the area of in favor or neutral, while a smaller percentage of tweets and retweets are in the against category. The evolution of the opinions expressed through tweets can be further monitored for extracting the public perspective on mask-wearing in times of COVID-19.

scholarly journals Misconceptions about emotional intelligence: Deploying emotional intelligence in one’s life dimensions

2007 ◽  
Vol 7 (1) ◽  
pp. 1-10
Author(s):  
Anobé Badenhorst ◽  
Dawie Smith
Keyword(s):  
Emotional Intelligence ◽  
General Public ◽  
Scientific Community ◽  
The Other ◽  
Emotional Life ◽  
The Past

Emotional intelligence (EI) has become a buzz-word over the past ten years, yet misconceptions with regard to the concept abound. This leads to confusion among the general public, the scientific community, as well as to unfounded claims being made as to what the development of EI can accomplish in a person’s life. In this article the aim is to clarify the concept EI by making a sharper demarcation between the Emotional Life Dimension and the other life dimensions. Based on this clarification, the conceptualisation of EI in the literature is reviewed in more depth.

Current Trends in Deep Learning Frameworks With Opportunities and Future Prospectus

2020 ◽  
pp. 63-77
Author(s):  
Chitra A. Dhawale ◽  
Krtika Dhawale
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Real Time ◽  
End Users ◽  
The Other ◽  
Qualitative Review ◽  
Current Trends ◽  
Real Time Applications ◽  
Learning Frameworks

Artificial Intelligence (AI) is going through its golden era by playing an important role in various real-time applications. Most AI applications are using Machine learning and it represents the most promising path to strong AI. On the other hand, Deep Learning (DL), which is itself a kind of Machine Learning (ML), is becoming more and more popular and successful at different use cases, and is at the peak of developments. Hence, DL is becoming a leader in this domain. To foster the growth of the DL community to a greater extent, many open source frameworks are available which implemented DL algorithms. Each framework is based on an algorithm with specific applications. This chapter provides a brief qualitative review of the most popular and comprehensive DL frameworks, and informs end users of trends in DL Frameworks. This helps them make an informed decision to choose the best DL framework that suits their needs, resources, and applications so they choose a proper career.

scholarly journals Kan lovspråk temmes?

2014 ◽  
Vol 15 (7) ◽  
Author(s):  
Sissel C. Motzfeldt
Keyword(s):  
Knowledge Base ◽  
General Public ◽  
Civil Servants ◽  
The Other ◽  
Legislative Process ◽  
The Public ◽  
Work Health ◽  
The Right ◽  
Laws And Regulations

In the Plain Legal project we started our work by establishing a knowledge base. We conducted two surveys—one directed at the general public and the other at civil servants from ministries and agencies. The surveyors found that 54 percent of the public said they had read a law or regulation in the previous year concerning work, health, welfare, housing or the economy. This showed that clear legislation was important for the general public too. The survey directed at civil servants showed that linguists were seldom used in the legislative process and that draft laws were almost never user-tested. Our knowledge base has proved very useful in our work, and has helped us work systematically in the right direction. We are on our way, but we still have a long way to go. Working with improving the language in laws and regulations is a never-ending story!

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