Young women’s perception of safety can influence their mode choice. This study sets out to understand and quantify the factors that influence young women’s perception of safety while commuting in public buses in Ban...
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Young women’s perception of safety can influence their mode choice. This study sets out to understand and quantify the factors that influence young women’s perception of safety while commuting in public buses in Bangalore and Ahmedabad in India. To investigate the research question, surveys were done using a structured questionnaire comprising questions about respondents’ socio-demographic information, perceptions of safety (at the bus stop, inside the bus and while boarding and alighting), bus usage, and other miscellaneous aspects. A total of 192 and 422 valid responses from Ahmedabad and Bangalore respectively, were used for the investigation. Factor analysis reveals that both cities have safety at bus stop, anxiety while travelling in bus and bus stop facilities as common underlying safety-influential factors, except trust (which is extracted for Ahmedabad). The study also attempts to explore the relationship between young women’s perception of safety and extracted factors after controlling for socio-demographics attributes of the respondents. The empirical models reveal that in Ahmedabad, respondents with higher educational qualification are more likely to perceive themselves safer while travelling in buses than those with lower educational qualification. In Bangalore, it was found that respondents who perceive bus stops to be safe are more likely to perceive themselves safer while commuting in bus than those who feel unsafe at bus stops. These results imply that travel experience and the condition of physical infrastructures can influence the overall safety perception of women in the study cities.
The growth in the number of sellers in both the offline and online markets has necessitated the development of analytic tools that may assist assess whether a company is reaching its sales targets. Our proposal Sales ...
The growth in the number of sellers in both the offline and online markets has necessitated the development of analytic tools that may assist assess whether a company is reaching its sales targets. Our proposal Sales Upsurge System explains the requirement for a system to evaluate the product offered utilising Machine learning, data mining approaches, and algorithms such as Affinity analysis, Association rule learning- Apriori. Our proposed system idea for this project is to create a system (website) that takes the input of sold products, categories the data obtained, analyses the data, and extracts the sales trend, and then optimizes the data based on market requirements, thereby maximize the value of sales and merchandise planning and increasing the organization's overall sales and profits.
Pulmonary Tuberculosis (TB) one of the transmissible diseases, which is one of the top ten causes of death worldwide. The need to strengthen the treatment and screening in TB affected countries. In this paper, a syste...
Pulmonary Tuberculosis (TB) one of the transmissible diseases, which is one of the top ten causes of death worldwide. The need to strengthen the treatment and screening in TB affected countries. In this paper, a systematic review is carried on deep learning-based computer-aided diagnostic (CAD) systems that are used to analyze chest X-rays for diagnosing pulmonary tuberculosis (TB). Deep learning has recently become one of the most successful techniques, particularly in the analysis of medical images. In Deep learning Convolutional Neural Networks (CNNs) are widely used for TB detection. A CNN model is commonly comprised of convolutional layers, sub-sampling / pooling layers, and fully connected layers. This paper also presents a comprehensive survey on the CNN models for the detection of TB. The progression of computer-aided diagnostic (CAD) systems has sped up the early diagnosis of TB.
Balancing equations for excitation system is very basic and fundamental concept and in some cases it becomes more difficult so that a mathematical treatment is needed in order to make it easy for AC and DC Regulators ...
Balancing equations for excitation system is very basic and fundamental concept and in some cases it becomes more difficult so that a mathematical treatment is needed in order to make it easy for AC and DC Regulators Excitation Systems (ES). This research paper mainly focuses on an excellent application of The power generating units and higher power motors are majority included by wound field synchronous machines because of it has flexible field excitation, flux intrinsic weakening capacity and high efficiency. It can be also used in low to medium power range for high end solutions in a wide range. This paper is analyzing a study of modern methods and technologies of excitation system for AC and DC regulators.
作者：
Sudhani SrikanthA. ParthibanResearch Scholar
Department of Mechanical Engineering School of Engineering Vels Institute of Science Technology and Advanced Studies Chennai 600117 India Associate Professor
Department of Mechanical Engineering School of Engineering Vels Institute of Science Technology and Advanced Studies Chennai 600117 India
Nd:YAG Laser welding is the widely used in the welding process in which quality of micro welded area for assembly of small components mainly depends on the input parameters are Laser beam power, Welding speed and Freq...
Nd:YAG Laser welding is the widely used in the welding process in which quality of micro welded area for assembly of small components mainly depends on the input parameters are Laser beam power, Welding speed and Frequency. By considering responses are microstructure for pre and post heat treated welding samples of the Inconel 625 alloy material. These work we are mainly focused on the microstructural analysis for before and post heated for welding samples, after post heat treatment of welding samples the welding area, parent metal and Heat affected zone are Slightly changes occurs on the microstructures of welded area and Heat affected zone for before post heat treatment of welding samples.
Previous work examined the usage of an advanced technique for control of a tandem cold rolling mill. This paper expands on the previous work by applying improvements to this technique as developed in subsequent work f...
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Bioelectrical interfaces represent a significant evolution in the intersection of nanotechnology and biophysics, oRering new strategies for probing and influencing cellular processes. These systems capitalize on the s...
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People put their opinions or views on various events happening in the society or world. Twitter is one of the best social networking sites where a huge amount of data generates on the daily basis. These data can be us...
People put their opinions or views on various events happening in the society or world. Twitter is one of the best social networking sites where a huge amount of data generates on the daily basis. These data can be used to classify their tweets based on various sentiments attached to them. Numerous technologies are applied to analyse the sentiments of users. Sentiment analysis needs a very efficient method to manage long arrangement data and their drawn-out dependencies. In this paper, we have applied a deep learning technique to perform Twitter sentiment analysis. Simple Neural Network, Long Short-Term Memory (LSTM), and Convolutional Neural Network (CNN) methods are applied for the sentiment analysis and their performances are evaluated. The LSTM is the best among all proposed techniques with the highest accuracy of 87%. We have collected a Twitter dataset from Kaggle to perform our experiment. The future improvement of the proposed research should include REST APIs and web crawling-based solutions to get live tweets to perform real-time analytics. We have analysed 1.6 million tweets in our research work.
This study makes a speciality of a way to use the Statistical Analysis for Data science approach to a real-international commercial enterprise scenario. Through this paper, the prominence of the Statistical Learning i...
This study makes a speciality of a way to use the Statistical Analysis for Data science approach to a real-international commercial enterprise scenario. Through this paper, the prominence of the Statistical Learning is known. Statistical Learning helps us, locating out the answer for a statistical inferential trouble through which it is easy to discover a predictive characteristic primarily based on the information we have. Statistical learning performs a distinguished position in the various fields like computer Vision, Speech Recognition, Emotion and Gender identification of Data science.
Skin diseases are hazardous and often contagious, especially melanoma, eczema, and impetigo. These skin diseases can be cured if detected early. The fundamental problem with it is, only an expert dermatologist is able...
Skin diseases are hazardous and often contagious, especially melanoma, eczema, and impetigo. These skin diseases can be cured if detected early. The fundamental problem with it is, only an expert dermatologist is able to detect and classify such disease. Sometimes, the doctors also fail to correctly classify the disease and hence provide inappropriate medications to the patient. Our project proposes a skin disease detection method based on Image Processing and Deep Learning Techniques. Our system is Personal computer based so can be used even in remote areas. The patient needs to provide the image of the infected area and it is given as an input to the application. Image Processing and Deep Learning techniques process it and deliver the accurate output. The output is used to get the best medical cure for the disease with nearest hospital details. In this project, we present a comparison of two different approaches for real-time skin disease detection algorithm based on accuracy.
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