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Challenges and Strategies for Women Empowerment in India: Facts and Realities
Full text linkIn today’s world women empowerment is an important issue of discussion because in every sector we find women which constitute half of the total population in the world are lacking behind. If about half of the nation\u27s human resources are neglected, the overall progress of the country would obviously be hampered. Women empowerment has become one of the most central concerns and need of the hour but in reality, the situation is not good enough. In the traditional patriarchal society, women have been given a secondary status which is reflected in the economic, social and political spheres. However, women equality and empowerment has always remained a priority area and has been taken utmost care by stake holders. Gender mainstreaming propels progress towards the ultimate goal of attaining gender equality and women empowerment. In this direction policies and programmes at different levels to cover various proportions and strategies of gender development have been framed by the government of India. The paper critically examines women empowerment in India, various challenges and strategies. The paper discusses constitutional safe guards as well as plans and programmes by the government and their implementation, indicators of women empowerment in India. Finally, this paper is an attempt to examine the status of women in India and provides some policy suggestions for women empowerment
Effective Secure Data Agreement Approach-based cloud storage for a healthcare organization
Full text linkIn recent days, there has been a significant development in the field of computers as they need to handle the vast resource using cloud computing and performing various cloud services. The cloud helps to manage the resource dynamically based on the user demand and is transmitted to multiple users in healthcare organizations. Mainly the cloud helps to reduce the performance cost and enhance data scalability & flexibility. The main challenges faced by the existing technologies integrated with the cloud need to be solved in managing the data and the problem of data heterogeneity. As the above challenges, mitigation makes the services more data stable should the healthcare organization identify the malware. Developed countries are utilizing the services through the cloud as it needs more security. In this work, a secure data agreement approach is proposed as it is associated with feature extraction with cloud computing for healthcare to examine and enhance the user parties to make effective decisions. The proposed method classifies into two components. The first component deals with the modified data formulation algorithm, used to identify the relationship among variables, i.e., data correlation, and validate the data using trained data. It helps to achieve data reduction and data scale development. In the second component, Feature selection is used to validate the model using subset selection to determine the model fitness based on the data. It is necessary to have more samples of different Android applications to examine the framework using factors like data correctness and the F-measure. As feature selection is a concern, this study focuses on Chi-square, gain ratio, information gain, logistic regression analysis, OneR, and PCA
Dr. Anubha Walia
No full textDr. Anubha Walia is the Founder Director of Prism Philosophy, Chairperson with Indian Society for Training & Development Delhi chapter, has played a pioneering role in setting up one of India’s best Corporate training, Executive Coaching & Wellness firms which has grown to leading people & development of an organizations.
She herself is a prolific Learning & Development professional with a rich dossier of more than two decades of experience after working with Honeywell & ICICI Bank, engaged in various Human Process Intervention at National & International level . She has empowered more than 100000 professionals, has 30 research papers & case studies to her credit. She has authored two books \u27Fundamentals of Research’ and ‘500 Powerful Coaching Questions’ and became the first lady in India to do research followed by a PhD in Followership styles & Leadership styles.
She was honored with Best Executive Coach Award by Coach Awards Singapore, BML Munjal Awards for attaining Business Excellence in Learning and Development\u27, Female Entrepreneur Achievers Award by Delhi Management Association, Global Famine Entrepreneur Award by Dr Kalam’s International Foundation, Emerging HRD thinker award (Gold Medalist thrice) for 5 consecutive years by ISTD and many more. Presently she is training & coaching in 23 countries creating an experience by empowering women ensuring that everyone\u27s voice is heard, opinions are considered, creating a very close-knit group of team who treats one another like family.https://www.interscience.in/mentors/1095/thumbnail.jp
Food emergency dispatching method based on optimized fireworks algorithm
Full text linkIn order to solve the problem of food emergency dispatching under emergencies, a food emergency dispatching method based on the optimal fireworks algorithm was proposed. The fitness function was used to measure the individual merits of fireworks, the tabu table was set to avoid the fireworks algorithm falling into the local optimal, and the tournament strategy was adopted as the iterative strategy of fireworks population. The goal of the fitness function is to maximize the satisfaction of demand points and minimize the vehicle travel time.In order to accurately predict the amount of food required at the point of demand, an infectious disease model (SEIR) was used.By comparing with the basic fireworks algorithm and genetic algorithm, the simulation results show that the proposed algorithm has higher computational efficiency and can be used in food emergency dispatching
DATA_SPHERE
Full text linkThis paper presents a comprehensive overview of Database Management Systems (DBMS) and their significance in modern information management. DBMS technology plays a crucial role in the storage, organisation, retrieval, and manipulation of vast amounts of data in various domains, ranging from business operations to scientific research. This abstract highlights the key aspects covered in the paper, including the evolution of DBMS, its architectural components, and the challenges and advancements in the field.
The paper begins by discussing the historical development of DBMS, tracing its origins from file-based systems to the emergence of relational databases and the subsequent rise of object-oriented and NoSQL databases. We explore the motivations behind these advancements and their impact on data management.
Next, we delve into the fundamental architectural components of a DBMS. We examine the storage layer, which encompasses data structures and access methods, and discuss different indexing techniques for efficient data retrieval. The query processing and optimization module are explored, focusing on query execution plans and cost-based optimization strategies. Additionally, we analyse the transaction management component, highlighting concepts such as ACID properties, concurrency control, and recovery mechanisms.
The abstract also highlights the challenges faced by modern DBMS. With the proliferation of big data and the advent of cloud computing, scalability, availability, and performance have become critical concerns. We examine techniques such as parallel and distributed databases, replication, and sharding to address these challenges. Furthermore, we discuss the integration of DBMS with emerging technologies like machine learning and blockchain to leverage their capabilities in data analytics and secure data transactions.
Lastly, the abstract touches upon recent advancements in DBMS, including the rise of graph databases for managing interconnected data, the adoption of in-memory databases for high-performance applications, and the exploration of new database models to handle unstructured and semi-structured data.
In conclusion, this paper provides a comprehensive overview of DBMS, covering its historical evolution, architectural components, challenges, and recent advancements. By understanding the principles and advancements in DBMS, researchers and practitioners can effectively harness the power of data management systems to tackle the complexities of modern data-driven applications
Cloud Computing for Supply Chain Management and Warehouse Automation: A Case Study of Azure Cloud
Full text linkIn recent times, organizations are examining the art training situation to improve the operation efficiency and the cost of warehouse retail distribution and supply chain management. Microsoft Azure emerges as an expressive technology that leads optimization by giving infrastructure, software, and platform resolutions for the whole warehouse retail distribution and supply chain management. Using Microsoft Azure as a cloud computing tool in retail warehouse distribution and supply manacle management contributes to active and monetary benefits. At the same time, potential limitations and risks should be considered by the retail warehouse distribution and the supply chain administration investors. In this research summary of the cloud figuring tool, both public and hybrid in supply chain administration and retail, warehouse distribution is addressed. A brief introduction to the use of Microsoft Azure technology is provided. This is followed by the application of cloud computing to warehouse retail distribution and supply chain management activities. At the same time, the negative and positive aspects of familiarizing this Microsoft Azure technology in the modern supply chain and retail distribution are debated. Also, the circumstance for the third-party logistics services suppliers has indicated respect for automation and cybersecurity solutions in a cloud environment. Lastly, the upcoming research practices and following technological trends are offered as the conclusion
Perceptions of Men and Women on Respect in Workplace Relationships
Full text linkThis study looks into how men and women perceive professional relationships based on respect for one another. The study generated responses from 113 employees belonging to the private and public organizations in India. The main statistical tools used for the survey are multiple dichotomy analysis and the interclass correlation coefficient. The study revealed that the perspective of men on the subject of respect in the workplace differs from that of women. Thus, where men primarily associate respect with recognition, women, on the other hand, associate respect with fairness in terms of equal access to opportunities at the workplace. The policy implications of this study draw a parity line for men and women at the workplace to appreciate each other, as such relations purport to be indices for the growth and development of organizations. In view of this, elements that promote respect among the organizational workforce should be prioritized when formulating company policies
Credit Card Fraud Detection Using Logistic Regression and Synthetic Minority Oversampling Technique (SMOTE) Approach
Full text linkFinancial fraud is a serious threat that is expanding effects on the financial sector. The use of credit cards is growing as digitization and internet transactions advance daily. The most common issues in today\u27s culture are credit card scams. This kind of fraud typically happens when someone uses someone else\u27s credit card details. Credit card fraud detection uses transaction data attributes to identify credit card fraud, which can save significant financial losses and affluence the burden on the police. The detection of credit card fraud has three difficulties: uneven data, an abundance of unseen variables, and the selection of an appropriate threshold to improve the models\u27 reliability. This study employs a modified Logistic Regression (LR) model to detect credit card fraud in order to get over the preceding difficulties. The dataset sampling strategy, variable choice, and detection methods employed all have a significant impact on the effectiveness of fraud detection in credit card transactions. The effectiveness of naive bayes, k-nearest neighbour, and logistic regression on highly skewed credit card fraud data is examined in this research. The accuracy of the logistic regression technique will be closer to 0.98%; with this accuracy, frauds may be easily detected. The fact that LR receives the highest classifier score illustrates how well LR predicts credit card theft
Analysis of Mental Health Problems Among Higher Education Students using Machine Learning
Full text linkCurrently, mental health concerns pose a significant issue in Odisha. Generally, mental health problems affect a person\u27s thoughts, feelings, actions, and communication. As per the 2017 National Health and Morbidity Survey (NHMS), one in five individuals in Odisha suffer from depression, two have anxiety, and one out of ten experiences stress. Additionally, students in higher education are at an elevated risk of developing mental health problems. However, helping a person with mental health concerns can be challenging due to difficulties in identifying the root causes of their condition. The main objectives of this study are to: 1. Explore mental health issues among higher education students. 2. Investigate the factors that contribute to these issues. 3. Assess the effectiveness of machine learning techniques in analyzing and predicting mental health problems among higher education students. Using computational modeling, this paper\u27s findings will contribute to the ongoing discussion on mental health concerns in future research
Dr. Arindam Mondal
No full textDr. Arindam Mondal is currently working as Associate Professor in the Strategic Management Area at XLRI-Xavier School of Management, Jamshedpur (XLRI). He has a PhD in Strategic Management from the Indian Institute of Management (IIM), Calcutta. He also holds a B. E (Electrical Engineering, with Honours) from IIEST, Shibpur. He has been researching in the broader area of multinationals from emerging economies and their business strategies for the last ten years. He has published his research work in many reputed international journals such as, Global Strategy Journal, Management International Review, Journal of Business Research, International Journal of Entrepreneurial Behavior & Research etc. He has presented his research work at multiple international management conferences in India, the USA, Canada, Mexico, Italy, and Denmark. His teaching interest lies in the fields of Strategic Management, Entrepreneurship and New Venture creation, Emerging Market Strategy, and Family Business Strategy.https://www.interscience.in/mentors/1115/thumbnail.jp