Statistical Analysis & Survey of Research Work in Opinion Mining

2019 ◽  
Author(s):  
Ankur Ratmele ◽  
Ramesh Thakur
Keyword(s):  
Statistical Analysis ◽  
Opinion Mining ◽  
Research Work

scholarly journals Load Model Verification, Validation and Calibration Framework by Statistical Analysis on Field Data

2017 ◽  
Vol 18 (6) ◽  
Author(s):  
Xiangqing Jiao ◽  
Yuan Liao ◽  
Thai Nguyen
Keyword(s):  
Statistical Analysis ◽  
System Analysis ◽  
Research Work ◽  
Field Measurements ◽  
Model Verification ◽  
Verification And Validation ◽  
Load Model ◽  
Load Models ◽  
Utility System ◽  
Model Verification And Validation

AbstractAccurate load models are critical for power system analysis and operation. A large amount of research work has been done on load modeling. Most of the existing research focuses on developing load models, while little has been done on developing formal load model verification and validation (V&V) methodologies or procedures. Most of the existing load model validation is based on qualitative rather than quantitative analysis. In addition, not all aspects of model V&V problem have been addressed by the existing approaches. To complement the existing methods, this paper proposes a novel load model verification and validation framework that can systematically and more comprehensively examine load model’s effectiveness and accuracy. Statistical analysis, instead of visual check, quantifies the load model’s accuracy, and provides a confidence level of the developed load model for model users. The analysis results can also be used to calibrate load models. The proposed framework can be used as a guidance to systematically examine load models for utility engineers and researchers. The proposed method is demonstrated through analysis of field measurements collected from a utility system.

scholarly journals Application of Time and Motion study for Brickwork activity in Residential building

2021 ◽  
Vol 1197 (1) ◽  
pp. 012038
Author(s):  
G Vinod Kumar Reddy ◽  
K Shyam Chambrelin
Keyword(s):  
Statistical Analysis ◽  
Labor Productivity ◽  
Work Experience ◽  
Residential Buildings ◽  
Research Work ◽  
Residential Building ◽  
Vital Role ◽  
Time And Motion Study ◽  
Time And Motion ◽  
Motion Study

Abstract Construction industry is one of the largest industries in any economy whether gauged in currency volume or workforce quantity but still it is not attentive in appealing it. Human resource plays a vital role in increasing economy and enhancing productivity. Labor productivity is the key driving factor in burgeoning thrift. Various labors possess distinct productivity levels, thus ultimately affects time and profit of construction. Construction activities performed by workers are usually repetitive and demands physical attention, which can be examined by time and motion study followed by evaluation through statistical analysis. A time and motion study are a work measurement technique that involves recording the time spent on a specific job. A time keeping system can be used to record time, while a motion study can be used to eliminate waste. In this research work, a total of seven residential building sites were selected for performing time and motion study considering brick masonry work as main domain where vision-based approach is followed to collect data, i.e., video record study followed by statistical analysis applied to the observed and collected data on site to determine the time parameters, work efficiency and labor productivity construing to the hassles and its reasons. This study focused on only residential buildings limiting the crew designation to mason and helpers aged 25-35 years with 10-16 years of work experience working under traditional method with conditioned tools like hand trowel, mason square, spirit level, plumb rule, etc.

scholarly journals Swarm Optimized Opinion Classification Model for Policy Assessment

2020 ◽  
Vol 9 (4) ◽  
pp. 2345-2354
Keyword(s):  
Government Policy ◽  
Opinion Mining ◽  
Research Work ◽  
Substantial Reduction ◽  
Feature Subset Selection ◽  
Advanced Technology ◽  
Classification Model ◽  
Feature Subset ◽  
The Government ◽  
The Impact

A government policy is a scheme launched by the governing body of a nation for the welfare of a particular section of the society or the entire public in general. The impact of such a policy can hence only be determined by the response from its target group. The evaluation of these schemes is often challenging, due to the inability of the government body or organization to collect unfiltered and unbiased feedback from the entire population. The aforementioned task may require a large amount of effort, considerable time and in-depth knowledge of advanced technology. However, with the advent of the information era, it is possible to analyze the sentiments of the public using negligible resources. The internet is rich in freely available unused and unstructured data that can be exploited efficiently for various purposes. One such application is opinion mining which allows the user to extract data from social media websites and categorize it into pre-defined classes. This paper is an attempt to assess one of the most important and current government initiatives- “Digital India”, through public sentiments. Digital India is a program launched by the Prime Minister of India to transform the country into a technologically advanced and digitally connected nation. This research work corroborates the use of swarm intelligence or nature-inspired algorithms for feature subset selection during opinion mining, as it results in a substantial reduction in the number of features (and consequently a lesser computation time for model training) and increase in the classification accuracy of the model. Therefore, the aim of this study is to analyze public opinion on “Digital India” campaign to ascertain the success (or failure) of the mission, while at the same time, determine the most suited model for automated evaluation of any government policy in the future

scholarly journals CORRELAÇÕES GENÉTICAS, FENOTÍPICAS E DE AMBIENTE ENTRE OS PESOS DE VÁRIAS IDADES EM BOVINOS DA RAÇA GUZERÁ NO ESTADO DE SÃO PAULO

2002 ◽  
Vol 7 (1) ◽  
Author(s):  
C. H. M. MALHADO ◽  
J. C. SOUZA ◽  
L. O. C. SILVA ◽  
P. B. FERRAZ FILHO
Keyword(s):  
Statistical Analysis ◽  
Statistical Model ◽  
Fixed Effects ◽  
Research Work ◽  
Genetic Correlations ◽  
Sao Paulo ◽  
Mixing Models ◽  
São Paulo ◽  
Environmental Correlation ◽  
Environmental Correlations

Este trabalho tem como finalidade estudar as correlações genéticas, fenotípicas e de ambientes sobre os pesos de animais da raça Guzerá, criados no estado de São Paulo, aos 205 (P205), 365 (P365) e 550 (P550) dias de idade. Para realização das análises estatísticas, utilizouse da metodologia de modelos mistos, programa MTDFREML. O modelo estatístico continha os efeitos aleatórios de animal, touro, vaca e o erro; e, como efeitos fixos de grupo contemporâneo (fazenda, sexo, estação: (água e seca), mês e ano de nascimento do bezerro) e a covariável idade da vaca ao parto (quadrática). As correlações genética foram iguais a 0,75, entre os P205 e P365; 0,61, entre os P205 e P550 e 0,65, entre os P365 e P550. A correlação de ambiente entre os P205 e P365 foi 0,44; para o P205 e P550 foi 0,49; entre P365 e P550 foi 0,66. Os valores obtidos para as correlações fenotípica foram 0,59, 0,42 e 0,65 entre os P205 e P365; P205 e P550; P365 e P550; respectivamente. Os valores obtidos para as correlações genéticas indicam que a seleção para peso em idades jovens deverá promover mudanças nos pesos posteriores de um mesmo animal, apontando que a seleção poderá ser realizada em idades mais jovens. Genetic, phenotypical and environmental correlations between weight and age in the State of Paulo bovines from the guzera breed Abstract The main purpose of the present research work is centered in the study of genetic, phenotypical and environmental correlations regarding the weight of Guzera breed bovines at 205, 365 and 550 days of age. Statistical analysis was carried out by the methodology of mixing models, programs MTDFREML, the statistical model containing the aleatory effects of the animal, sire, cow and the error, and as fixed effects of contemporary group - farm, sex, season, water and drought, the year of birth of the calf, and the covariable age of dam. The genetic correlations was found to be equal do 0.75, 0.61 and 0.65, between P295 and P365. P205 and P550, and P365 and P550, respectively. The environmental correlation between P205 and P365, P205 and P550, and P365 and P550 was 0.44, 0.49 and 0.66, respectively. The phenotypical correlation between P205 and P365, P205 and P550, and P365 and P550 was of 0.59, 0.42, and 0.65, respectively. The values found for the genetic correlations indicate the possibility to select the animals, taking their weight as a parameter, earlier during their life.

Impact of Project Management Offices on Knowledge Management

2020 ◽  
pp. 166-195
Author(s):  
César Hernando Rincón-González ◽  
Flor Nancy Díaz-Piraquive
Keyword(s):  
Knowledge Management ◽  
Project Management ◽  
Statistical Analysis ◽  
Literature Review ◽  
Research Work ◽  
Theoretical Framework ◽  
Information Gathering ◽  
Scientific Publications ◽  
Detailed Statistical Analysis ◽  
The Impact

This applied research work identifies the impact of the project management offices (PMO) on knowledge management among 502 organizations from Colombian enterprises. First, a literature review about PMOs and knowledge management within the project perspective was conducted. Then, a bibliometric analysis was conducted in order to establish the link between this type of offices and the knowledge management on scientific publications about project management. Afterwards, a comprehensive theoretical framework about the matter of study was build. Subsequently, an information gathering instrument was developed in order to collect data for the research. Next, a nation-wide fieldwork was undertaken by analyzing the organizations. Successively, a detailed statistical analysis was conducted in order to identify the impact of the project management offices on knowledge management within the objects of study. Finally, results and conclusions were documented, and future lines of research were established.

The Influence of Plasticizer Content and Type on the Rheological Behaviour of Plastisol Used in Coated Fabrics

2000 ◽  
Vol 30 (1) ◽  
pp. 50-50
Author(s):  
A. Zadhoush ◽  
M. A. Alsharif
Keyword(s):  
Statistical Analysis ◽  
Power Law ◽  
Research Work ◽  
Rheological Behaviour ◽  
Flow Properties ◽  
Newtonian Flow ◽  
Plasticizer Content ◽  
Rheological Measurements ◽  
Coated Fabrics ◽  
Power Law Index

Coating pastes need to have very specific rheological properties because of the methods in which they are applied. Composition of the paste can be formulated in such a manner to achieve the desired rheological behaviour. In this research work rheological measurements of paste with nine various plasticizer content using DOP and DOA, and PVC-E with three k-values (69, 70, 75) were studied. The results indicate that pastes are characterized by a non-Newtonian pseudoplastic flow under the studied conditions. The power-law index ( n) values of the pastes show that the flow properties of pastes change to Newtonian flow above 50 phr plasticizer content. It was also found that the consistency index (k) of the pastes were decreased with increasing plasticizer content. Statistical analysis carried out show very good correlation between the studied parameters.

scholarly journals Robustious Feature Selection Based Genetic Algorithm (RFS-GA) For Cross Domain Opinion Mining

2019 ◽  
Vol 8 (2) ◽  
pp. 6267-6279
Keyword(s):  
Genetic Algorithm ◽  
Feature Selection ◽  
Sentiment Analysis ◽  
Opinion Mining ◽  
Performance Metrics ◽  
Research Work ◽  
Features Selection ◽  
Cross Domain ◽  
Multiple Challenges ◽  
Day By Day

Day by day the requirement of information for processing the sentiment analysis is getting increased multiple times. For these kind of reasons, feature selection is utilized to detect the opinion among different reviews and comments. Sentiment analysis is becoming like phenomenon due to increase of social media’s popularity. Currently, significant advancements are shown in this research domain, but still multiple challenges are to be solved – i.e., sentiment analysis in cross domains. In this paper rumbustious feature selection based genetic algorithm is proposed to address the problem of analyzing the sentiments in cross domain. It performs classification based optimistic-class and pessimistic-class. The dataset used to this research work includes books, DVDs, gadgets and kitchen appliances. Initially the features selection is performed and opinion mining is performed by Genetic Algorithm. Benchmark performance metrics are selected for measuring the performance of proposed work against existing method. Results depict that the proposed work has better performance than that of the existing work as far as chosen performance metrics.

scholarly journals A Inspection on Sentiment Research of Big Data: Techniques, Open Challenges

2019 ◽  
Vol 8 (6S4) ◽  
pp. 362-365
Keyword(s):  
Social Networking ◽  
Sentiment Analysis ◽  
Social Networking Sites ◽  
Opinion Mining ◽  
Service Industry ◽  
Research Work ◽  
Educational Institutions ◽  
Business Organizations ◽  
The Public ◽  
Day By Day

Due to the invention of Web 2.0, the users have become more interest to share their content day by day. The emergence of various social networking sites has added to a greater extent to these activities. These provide a very good platform for the users to share the opinions of the persons across the globe. The opinions shared by the customers on the web can have the prevalent over the service industry. Many industries such as educational institutions, researchers, business organizations are concentrating opinion mining which is also called as sentiment analysis (SA) to retrieve the views and opinions posted by the public. This paper made a survey on Sentiment Analysis (SA) which aims to discusses technical aspects of SA (techniques, types) .This paper further highlights the main challenges faced by SA. These challenges present a lot of scope for research work in the future

scholarly journals EFEITOS DA TEMPERATURA AMBIENTE E DA VELOCIDADE DO VENTO NO DESEMPENHO DE MÓDULOS SOLARES FOTOVOLTAICOS

2019 ◽  
Vol 4 (15) ◽  
pp. 362
Author(s):  
Amaury De Souza ◽  
Ana Paula Garcia Oliveira ◽  
Flavio Aristone ◽  
Vanise Dos Santos Rodrigues ◽  
Gabriel Ozório Linhares Mello
Keyword(s):  
Statistical Analysis ◽  
Wind Speed ◽  
Ambient Temperature ◽  
Environmental Temperature ◽  
Research Work ◽  
Photovoltaic Module ◽  
Solar Photovoltaic ◽  
Positive Linear Relationship ◽  
Module Prediction ◽  
Positive Linear Relation

EFFECTS OF ENVIRONMENTAL TEMPERATURE AND WIND SPEED IN THE PERFORMANCE OF PHOTOVOLTAIC SOLAR MODULESEFECTOS DE LA TEMPERATURA AMBIENTAL Y LA VELOCIDAD DEL VIENTO EN EL DESEMPEÑO DE LOS MÓDULOS SOLARES FOTOVOLTAICOSRESUMOOs efeitos da temperatura ambiente e da velocidade dos ventos na análise de desempenho de um módulo fotovoltaico solar de silício monocristalino foram analisados em Campo Grande, MS, para o período janeiro a dezembro de 2017. O trabalho de pesquisa foi realizado monitorando a variação da eficiência do módulo em função desses parâmetros. Uma análise estatística é apresentada e o resultado indica que os valores do coeficiente de correlação são 96% e 68% para a temperatura ambiente e para velocidade dos ventos, respectivamente, considerando o nível de confiança de 95%. Os resultados mostram que existe uma forte relação linear positiva entre a eficiência do módulo e a temperatura ambiente, e uma relação linear positiva moderada com a velocidade dos ventos.Palavras-chave: Módulo Fotovoltaico; Predição de Eficiência; Condições Climáticas.ABSTRACTThe effects of ambient temperature and wind velocity on the performance analysis of a monocrystalline silicon solar photovoltaic module were analyzed in Campo Grande, MS, from January to December 2017. The research work was carried out by monitoring the efficiency variation of the module according to these parameters. A statistical analysis is presented and the result indicates that the values of the correlation coefficient are 96% and 68% for the ambient temperature and for wind speed, respectively, considering the 95% confidence level. The results show that there is a strong positive linear relationship between the modulus efficiency and the ambient temperature, and a moderate positive linear relation with the velocity of the winds.Keywords: Photovoltaic Module; Prediction of Efficiency; Climate Conditions.RESUMENLos efectos de la temperatura ambiente y de la velocidad de los vientos en el análisis de desempeño de un módulo fotovoltaico solar de silicio monocristalino fueron analizados en Campo Grande, MS, para el período enero a diciembre de 2017. El trabajo de investigación fue realizado monitoreando la variación de la eficiencia del módulo en función de estos parámetros. Se presenta un análisis estadístico y el resultado indica que los valores del coeficiente de correlación son 96% y 68% para la temperatura ambiente y para la velocidad de los vientos, respectivamente, considerando el nivel de confianza del 95%. Los resultados muestran que existe una fuerte relación lineal positiva entre la eficiencia del módulo y la temperatura ambiente, y una relación lineal positiva moderada con la velocidad de los vientos.Palabras clave: Módulo Fotovoltaico; Predicción de Eficiencia; Condiciones Climáticas.

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