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Is the effect of oil price shock asymmetric on the Indian stock market? Firm-level evidence from energy-intensive companies
Purpose: This paper aims to examine the asymmetric impact of the oil price increase and decrease on stock returns at the firm level. Design/methodology/approach: To ascertain the impact oil price can exert on the stock price at the firm level, this study uses panel structural vector auto regression with various linear and nonlinear measures of oil price shock on a data set, containing 1,168 firms listed in Indian stock markets. This study also considers stock index returns, Fama-French factors and inflation as control variables. Findings: This paper finds evidence that at firm level, net oil price increase and decrease have an asymmetric impact on stock returns. Other oil price shock measures, namely, shock because of oil price increase and decrease, do not show any sign of asymmetric impact on stock returns. Originality/value: The comparison of firm-level return on its response towards oil price fluctuation can give valuable insights into a firms features. 2022, Emerald Publishing Limited. -
Factors affecting the competitive capability of small and medium women entrepreneurs
Small and medium women entrepreneurs have a major contribution in the countrys economic development. After the implication of liberalization, privatization and globalization, all the countries are paying attention to support small and medium women entrepreneurs in order to mobilize maximum resources, generate employment opportunities and to improve competitiveness among them. However, today women entrepreneurs are still facing many problems in terms of finance, human resources, marketing, technology capability etc. These capabilities will result in the development of competitive capability of small and medium women entrepreneurs. Competitive capability is very important in order to sustain not only in the local market but also in the national and international market. Therefore, this study is an attempt to explore the factors affecting the competitive capability of small and medium women entrepreneurs. This study is surveyed 400 women entrepreneurs and obtained complete response from 384women entrepreneurs with 23 questions. The data is collected from November 2019 to January 2020. Simple random sampling technique, Cronbach's alpha and Structural Equation Modelling (SEM) technique are used in the study to obtain the research result. Finally, the study concludes that there are five factors that affect the competitive capability of small and medium women entrepreneurs with significance level 0.05 and the influence of technology capability is more compare to other capabilities on competitiveness of the women entrepreneurs. 2020 SERSC. -
Academic workbench for streetlight powered by solar PV system using internet of everything (IoE)
Renewable energy is one of the growing trend in developing countries. Rapid development of renewable energy leads to the economic benefits and reduce environmental pollution. According to current scenario 20 to 40 percent of the power generated is consumed by streetlights. The problems faced by the current street lighting systems are when there is availability of light there is no proper utilization. Sun intensity shift is not constant all the time, it varies as the climate changes. Real time monitoring and control using intelligent algorithm avoids energy wastage during day time. ZigBee as a communication protocol current and voltage values are sent and received. Base Controller (Single Board Computer) acts as an interphase between the communication protocol and the cloud account. Remote client application is developed to control and monitor streetlight. 2018 IEEE. -
Malpractice Detection in Examination Hall using Deep Learning
Various institutions administer tests at designated examination locations, chosen third-party and approved centers, and have established standards for installing CCTV cameras and conducting frisking under the supervision of designated personnel. Some institutions are using online proctoring, which enables students to take exams from any location. In all of the aforementioned scenarios, human monitoring is conducted, and maintaining a high level of vigilance may be challenging due to administrative oversight or intentional allowance of malpractice for personal gain. The malpractice detection may be attributed to acts like as plagiarism, unauthorized sharing of papers, and non-verbal communication. The study is conducted by capturing the dataset in the classroom of Christ University. The proposed approach is based on the YOLO framework. The movies are processed in real time to identify hand rotation, paper extraction, and classify the motion. The accuracy for the Head_right class is significantly higher than that of the Head_left class. The system is implemented using the programming language Python and has the potential for future expansion to provide real-time monitoring. 2024 IEEE. -
An Advanced and Ideal Method for Tumor Detection and Classification from MRI Image Using Gamma Distribution and Support Vector Machine
As indicated by a measurable report distributed by the registry of central brain tumor at United States (CBTRUS), roughly 59,550 individuals were recently diagnosed to have essential benign and essential harmful brain tumors in 2017. Besides, in excess of 91,000 individuals, in the United States alone, were living with an essential harmful cerebrum tumor and 367,000 were living with an essential kind brain tumor. The task of detecting the position of the tumor in the body of the patient is the starting point for a medical treatment in the diagnosis process. The main aim of this study is to design a computer system, which is able to detect the tumor presence in the digital images of the brain in the patient and to accurately define its borderline. In this proposed model, gamma distribution method is used for training, testing, and for the feature extraction process, while SVM, support vector machine is used for the classification process. Most of the algorithms find it difficult to segment the tumors that were present in the edges. But with the help of gamma distribution along with the use of edge analysis, it is easier to identify those tumor areas that are present in the edges, thus making it easier for the preprocessing process. Gamma distribution also provides us with high accuracy, and it can also point the exact location of the tumor than compared to other algorithms. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A unique adventure - unity based 3D game
The number of gamers are increasing day by day and as a result the gaming industry has seen a huge growth. There was a curiosity to get the in-depth detail so as to how a game is developed. The final year project was a great opportunity to explore this field and to make something that would be fun as well as useful. The proposed work gives the detailed description about the entire process of game development. A game is created with three different levels. Each level comes with a particular set of objectives. The objectives of each level need to be attained in order to proceed to the next level. The environment in the game resembles the Christ Kengeri campus. For that, 3D model of Christ Kengeri campus is designed. 3D modeling is done in Unity and Blender software platform. A* is the search algorithm that has been used for pathfinding. The languages that Unity uses to operate with are objectoriented scripting languages. Scripting languages have its own syntax and the primary parts are called functions, variables and classes. Also each level has its own coding and is not linked with any other. In each level a new character is introduced. 2019, Institute of Advanced Scientific Research, Inc. All rights reserved. -
Computerized grading of brain tumors supplemented by artificial intelligence
For effective diagnosis of health conditions, there is a need to process medical images to obtain meaningful information. The diagnosis of brain tumors begins with magnetic resonance imaging (or MRI) scan. This is followed by segmentation of the medical images so obtained which can prove cumbersome if it were to be performed manually. Determining the best approach to do segmentation remains challenge among multiple computerized approaches. This paper combines both the identification and classification of tumors from the MRI results and is backed by a cloud-based framework to provision the same. The phase of extraction of features includes the utilization of a Hadoop framework and Gabor filter along with variations in terms of orientation and scale. Artificial bee colony algorithm and support vector machine classifier have been used to designate the degree of optimal features and categorize the same. The grading of brain tumors from MRI images can be fulfilled by the aforementioned approach. The said approach is believed to deliver promising results in terms of accuracy, which has also been verified experimentally. 2019, Springer-Verlag GmbH Germany, part of Springer Nature. -
An advanced variable temperature refrigerator for preservation and management of food items
All food items will have shelf life period. The main aim of food preservation is to maximize the shelf life period and preservation of nutrients for a long period. One of the preservation methods is refrigeration. Each food item will have its own optimum storage temperature to maximize the shelf life period. Normal refrigerators have fixed temperature. The work proposes a refrigerator with six compartments which is equipped with temperature sensors to maintain the fixed temperature for that compartment and with weighing sensors to monitor the depleting food items with the help of a controller. 2019, Institute of Advanced Scientific Research, Inc. All rights reserved. -
Gender-based spatial segregation: ladies compartments in the Mumbai local trains
The local trains of Mumbai are one of the most crowded means of public transport, but often preferred by many women due to the provision of exclusive ladies compartments reserved for women. While these compartments provide women a space safe from sexual assault, conflicts due to class and religious differences arise among the women who occupy this in-between space. Moreover, the continuous use of ladies compartments leads to the labelling of general compartment as gents, affects the interactions between men and women in different railway spaces, and also configures the public as already segregated according to a binary understanding of gender. Based on the findings from an ethnographic study of womens experiences of using the ladies compartments, I argue that the provision of segregation gives rise to specific mobility practices in the ladies compartments. The logic of segregation spills over to other railway spaces, and these can complicate our understanding of mobility as empowering for women travellers. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Travel time activities Mobility and femininities in the ladies compartments of the Mumbai local trains
Activities undertaken during everyday commutes have often been studied to prove the inherent value of travel time to the commuters. Women commuters using the ladies compartments of the Mumbai local trains use this time to eat and share food, shop, chitchat, and watch sitcoms on their phones. Undertaken in a gender-segregated space, these activities make womens mobility an avenue for the performance of their femininities. Thus, while the association between masculinity and mobility stands questioned, what merits enquiry is whether mobility for women is premised on their effective performance of hegemonic femininities. 2022 The Society for Ethnographic Theory. All rights reserved. -
Estimation of Vehicle Distance Based on Feature Points Using Monocular Vision
In this digital era safety and security have the highest precedence, the advanced driver assistance system is the latest trend and where many challenges are open for researchers. Vehicle to vehicle distance estimation is one of the most important challenges to provide the security and safety alerts for the driver. In order to achieve this, image of the front vehicle is captured using the single camera under monocular vision to estimate the vehicle distance. Then three key steps are designed to estimate the vehicle distance: extracting and locating the key features of the vehicle, characteristic triangle is drawn between those features to calculate pixel area and develop the measuring formula to calculate the distance. For efficient feature extraction and localizing of the feature position, conventional AdaBoost algorithm is utilized to find the strong features for scalable samples. Distance measurement formulation is used to derive the correlation between the pixel area and distance by considering the different parameters from the prototype of pinhole camera, camera standardization and plotting of area. Formula is developed to estimate the optimum moving distance between vehicles to vehicle. After the experimental analysis, the accuracy rate is improved and time complexity satisfies the precision. 2019 IEEE. -
Classification of Vehicle Make Based on Geometric Features and Appearance-Based Attributes Under Complex Background
Vehicle detection and recognition is an important task in the area of advanced infrastructure and movement administration. Many researchers are working on this area with different approaches to solve the problem since it has a many challenge. Every vehicle has its on own unique features for recognition. This paper focus on identifying the vehicle brand based on its geometrical features and diverse appearance-based attributes like colour, occlusion, shadow and illumination. These attributes will make the problem very challenging. In the proposed work, system will be trained with different samples of vehicles belongs to the different make. Classify those samples into different classes of models belongs to same make using Neural Network Classifier. Exploratory outcomes display promising possibilities efficiently. 2019, Springer Nature Singapore Pte Ltd. -
Classification of Vehicle Type on Indian Road Scene Based on Deep Learning
In Recent days an intelligent traffic system [ITS] is implemented on indian traffic sytem. Different applications are widely used to improvies the performance of the system. To improve the intelligence of the system deep learning can used to classify the vehicles into three different classes. The combination of Faster RCNN classifier and RPN can used to detect the objects and classify those objects into different classes. Analysis of the experimental results shows the improved accuracy and efficiency in classifying the vehicles on indian roads into different categories. 2021, Springer Nature Singapore Pte Ltd. -
Smart Vehicle Recognition System on Indian Roads Under Rainy Conditions
Recognition of vehicles under the different weather condition is very challenging. This work aims to recognize vehicles on Indian road in accordance with their visibility. It is important to recognize the surround roadside objects, particularly front and rare vehicles to avoid the accidents. Especially in raining conditions vehicle recognition is rate traffic surveillance cameras get decreases due to water droplets. Hence, we proposed a method for recognition of vehicles on road in rainy condition using image processing in computer vision techniques to improve the recognition rate. In the proposed method, an instance segmentation technique is used to segment the vehicles in Indian road scene and the visual noise and texture features are analysed and computed in the segmented images to recognize the vehicles more accurately in rainy conditions. By integrating the visual noise features with the texture feature and instance segmentation, the accuracy of vehicle recognition is improved. The experimental findings demonstrated that the suggested approach could more accurately predict the visibility of vehicles in rainy weather conditions. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
ESG efficiency analysis in the IT industry: a DEA-based approach
Unlocking the power of sustainable growth, Environmental, Social, and Governance (ESG) principles are redefining the future of responsible investment and corporate excellence. ESG regulations ensure that organizations maintain sustainable development and improve non-monetary metrics, such as stakeholders engagement, customer satisfaction, market acceptability, societal ethics, and values. Higher ESG scores demonstrate commitment towards responsible business practices and indicate higher market value for companies, which are valid for all sectors, including IT. However, existing literature reveals that IT sector companies pay less attention to planning their operations to make them more sustainable. Therefore, IT firms must identify methods and practices to maintain high ESG scores to achieve sustainable growth. The current study leads the readers into a new area of ESG through the help of an advanced method, DEA. DEA (Data Envelopment Analysis) methodology has been used to identify the decision units relative efficiency scores and helps identify peers and followers based on ESG scores. The study reveals that among the selected IT firms using the output-oriented strategy, 56.25% experience increasing returns to scale, 18.75 per cent experience decreasing returns to scale, and the remaining 25.00 per cent report constant returns to scale. This indicates that most IT industry firms can generate greater output change in proportion to the input change. 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
PMFRO: Personalized Mens Fashion Recommendation Using Dynamic Ontological Models
There is a thriving need for an expert intelligent system for recommending fashion especially focusing on mens fashion. As it is an area which is neglected both in terms of fashion and modelling intelligent systems. So, in this paper the PMFRO framework for mens recommendation has been put forth which indicates the semantic similarity schemes with auxiliary knowledge and machine intelligence in a very systematic manner. The framework intelligently creates mapping of the preprocessed preferences and the user records and clicks with that of the items in the profile. So, this model aggregates community user profiles and also maps the mens fashion ontology using strategic semantic similarity schemes. Semantic similarity is evaluated using Lesk similarity and NPMI measures at several stages and instances with differential set thresholds and the dataset is classified using the feature control, machine learning bagging classifier which is an ensemble model in order to recommend the mens fashion. The PMFRO framework is an intelligent amalgamation and integration of auxiliary knowledge, strategic knowledge, user profile preferences as well as machine learning paradigms and semantic similarity models for recommending mens fashion and overall precision of 94.68% and FDR of 0.06 was achieved using the PMFRO model. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Consumption of antibiotics as self-medication from over-the-counter purchase: An empirical study
Objective: The primary objective of this study is to find the reasons behind the practice of self-medication (SM) by the people with over-the-counter (OTC) drugs which are usually available in all medical stores. Methods: This article presents an empirical view of SM practice with OTC drugs. The research design of the study is descriptive, and the population of the study is customers who buy OTC drugs. The target population of this research is the common public who are all having the possibility to consume OTC drugs ever. The sampling technique used for this study is a systematic random sampling, and the sample size is 144. An instrument used for collecting data is a self-administered questionnaire and personal interview with the pharmacists. The data were analyzed using descriptive statistics. Results: The study results that most of the OTC customers consider SM is not a good practice, even though they practice SM of antibiotics in certain circumstances, due to reasons such as time-saving, convenience, cost saving, avoid waiting time to consult a doctor, easy and quick availability of antibiotics in neighbourhood drug stores, etc. Conclusion: The study concludes the reasons behind the SM practice and some remedies to overcome OTC drug-related problems from SM. 2017 The Authors. Published by Innovare Academic Sciences Pvt Ltd. -
Impact of Social Networking Sites on Academic Performance and Career through Collaborative Learning (with Reference to Students of Self-financing Engineering Colleges in Tiruchirappalli)
Use of Social Networking Sites (SNSs) is having a growing importance among students in their everyday life. It acts as an essential tool for them in higher level education. Among the social networking sites Facebook, WhatsApp, Twitter, LinkedIn is gaining more support from the student community. It helps the students to communicate each other directly like face to face interaction. SNSs are having an ability to induce students decision making capability. Based on this, the study tries to emphasize the ability of the SNSs to induce the students academic performance using collaborative learning among various groups in which they belong. The result reveals that collaborative learning will have a major impact on academic performance, i.e. 49.6% of the respondents stated that they are using SNSs for academic purpose. They use SNSs for sharing of information and study materials with their peers. SNSs help them to be interacting with their peers and teachers. Serials Publications Pvt. Ltd. -
Occupants perspective on building maintenance and workers maintenance performance in residential buildings - An empirical study
The entire life cycle of a building involves planning, design, construction, occupancy, operation, maintenance, demolition and removal of wastes. Maintenance is a never ending process in the life cycle of buildings which plays an essential role in building operation. To meet the changing needs of building construction, environment and technology, building maintenance is essential for improving the performance of buildings and for retaining the value and service life of buildings. The main purpose of this study is to establish a sound maintenance strategy for improving the building maintenance services in the areas of Tanjore district, Tamil Nadu which helps to improve occupants satisfaction to a desired level. The present study focuses on the factors influencing building maintenance and assessment of performance of building maintenance service providers. This study attempts to identify the parameters that strengthens and weakens the performance of building maintenance from the occupants perspective. An extensive survey has been conducted with 104 occupants who are residing in pertinent areas of Tanjore in order to determine the predominant factors that have causation effect on building maintenance and workers performance from the perspective of occupants. The research findings indicated that there exists a positive significant correlation exists statistically between performance of maintenance workers and effective functioning of residential buildings for comfort living of occupants. Serials Publications Pvt. Ltd. -
Arming Farmers with Smart Farming: The Future of Agriculture
Internet of Things (IoT) innovation is currently one of the growing fields across a diversity of industries, together with agriculture. IoT enhances our lives by making and promoting developments in a wide range of actions to encourage them to become more appropriate, practicality, and enhanced using suitable man-made recognition. Smart agricultural frameworks recognize a social trade toward more helpful, lower-cost agribusiness because of this innovation. The proposed work is to use IoT in the agriculture industry to collect real-time data (soil moisture, temperature, and so on) to help one look at a few climate scenarios from afar, efficiently, and greatly increase production. A global solution for monitoring and managing the agricultural field remotely has been proposed. Implementation of a local stand-alone field control unit that includes detection and activation capabilities. Developed a cloud solution for data storage, real-time monitoring, and historical data visualization based on the ThingSpeak cloud platform. Remote managing and control functions have been realized in both the local unit and the cloud using IoT infrastructure. 2022 IEEE.