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Malayalam kavi Kumaranasan ka yug bodh /
International Journal of Hindi Research, Vol.4, Issue 4, pp.56-58, ISSN No: 2455-2232. -
Malicious node detection using heterogeneous cluster based secure routing protocol (HCBS) in wireless adhoc sensor networks
In wireless, every device can moves anywhere without any infrastructure also the information can be maintained constantly for routing the traffic. The open issues of wireless Adhoc network the attacks which are chosen the forwarding attack that is dropped by malicious node to corrupt the network performance then the information integrity exposure. Aim of the problem that existing methods in Adhoc network for malicious node detection which cannot assure the traceability of the node as well as the fairness of node detection. In this paper, the proposed heterogeneous cluster based secure routing scheme provides trust based secure network for detection of attacks such as wormhole and black hole caused by malicious nodes presence in wireless Adhoc network. The simulation result shows that the proposed model is detect the malicious nodes effectively in wireless Adhoc networks. The malicious node detection efficiency can be achieved 96% also energy consumption also 10% better than existing method. 2020, Springer-Verlag GmbH Germany, part of Springer Nature. -
Malicious Traffic Classification in WSN using Deep Learning Approaches
Classifying malicious traffic in Wireless Sensor Networks (WSNs) is crucial for maintaining the network's security and dependability. Traditional security techniques are challenging to deploy in WSNs because they comprise tiny, resourceconstrained components with limited processing and energy capabilities. On the other hand, machine learning-based techniques, such as Deep Learning (DL) models like LSTMs, may be used to detect and categorize fraudulent traffic accurately. The classification of malicious traffic in WSNs is crucial because of security. To protect the network's integrity, data, and performance and ensure the system functions properly and securely for its intended use, hostile traffic categorization in WSNs is essential. Classifying malicious communication in a WSN using a Long Short-Term Memory (LSTM) is efficient. WSNs are susceptible to several security risks, such as malicious nodes or traffic that can impair network performance or endanger data integrity. In sequential data processing, LSTM is a Recurrent Neural Network (RNN) appropriate for identifying patterns in network traffic data. 2023 IEEE. -
Malicious URL Detection Using Machine Learning Techniques
Cyber security is a very important requirement for users. With the rise in Internet usage in recent years, cyber security has become a serious concern for computer systems. When a user accesses a malicious Web site, it initiates a malicious behavior that has been pre-programmed. As a result, there are numerous methods for locating potentially hazardous URLs on the Internet. Traditionally, detection was based heavily on the usage of blacklists. Blacklists, on the other hand, are not exhaustive and cannot detect newly created harmful URLs. Recently, machine learning methods have received a lot of importance as a way to improve the majority of malicious URL detectors. The main goal of this research is to compile a list of significant features that can be utilized to detect and classify the majority of malicious URLs. To increase the effectiveness of classifiers for detecting malicious URLs, this study recommends utilizing host-based and lexical aspects of the URLs. Malicious and benign URLs were classified using machine learning classifiers such as AdaBoost and Random Forest algorithms. The experiment shows that Random Forest performs really well when checked using voting classifier on AdaBoost and Random Forest Algorithms. The Random Forest achieves about 99% accuracy. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
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. -
Mamaearth: from a mothers dilemma to a multi-crore brand
Learning outcomes: The case study has several objectives: to gauge the evaluation of the direct-to-consumer industry in the economy of India, to analyse the competition of the brands, to ascertain the evolution of smaller direct-to-consumer (DTC) brands on the purchasing capacity of consumers, to analyse challenges in branding in Tier 2 and 3 cities and to evaluate the strategic branding decisions of Mamaearth. Case overview/synopsis: During her pregnancy, Ghazal Alagh and her husband Varun Alagh, the co-founders of Mamaearth, were looking for some good and natural products for their babys skincare. However, she could not find products that were 100% safe. Hence, as a concerned mother, she started using a few hands-on home remedies for her baby, which were 100% organic, and then the idea clicked to her to start a baby care brand named Mamaearth, which later also included personal care products. The company started as a DTC/internet-first brand in 2016, which only used to sell products online without any intermediaries when it was still trying to make its way in the market and was aware of the stiff competition by giants such as Hindustan Unilever and Proctor & Gamble, who were ruling the market for decades. When the COVID-19 pandemic hit, the market saw a shift in consumer buying patterns. There was greater use of e-commerce touch points for shopping, as various digital platforms such as the official site of products, social media and mobile platforms were used by consumers during the pandemic, leading to digitalization in buying and digitalization of consumer shopping journey. These technology platforms were expected to play a substantial role in reaching and creating consumer awareness, transaction and retention post-COVID according to reports by Deloitte 2020. Moreover, such a shift in behaviour amidst the COVID-19 pandemic shot up sales of this DTC brand and made itself the big shot it is today, where they were looking to get into an initial public offering in just seven years of its launch. They re-evaluated their strategy, which helped them become the biggest brand in no time. Complexity academic level: This case study is suitable for Doctor of Philosophy students. Supplementary material: Teaching notes are available for educators only. Subject code: CSS 8: Marketing. 2023, Emerald Publishing Limited. -
Management and Sales Forecasting of an E-commerce Information System Using Data Mining and Convolutional Neural Networks
The exponential development of e-commerce in recent decades has enhanced convenience for individuals. Compared to the conventional business environment, e-commerce is characterized by increased dynamism and complexity, resulting in several obstacles. Data mining assists individuals in effectively addressing these difficulties. Traditional data mining cannot efficiently use big data in the power provider industry. It heavily relies on time-consuming and labor-intensive feature engineering, and the resulting model could be more easily scalable. Convolutional Neural Networks (CNN) can efficiently use vast amounts of data and autonomously extract valuable elements from the original input, resulting in increased effectiveness. This article utilizes a CNN to extract valuable insights from e-commerce information to forecast commodities sales accurately and proposes a CNN-based Sales Forecasting Model (CNN-SFM). The findings indicate that using data mining and CNN yields a high level of precision in forecasting forthcoming people buying capacity data. The correlation variable between actual usage information and projected usage information was 0.98, and the highest mean error was just 1.78%. Data mining can effectively extract hidden relevant information and forecast future consumption habits for e-commerce systems. CNN demonstrates proficiency in accurately predicting forthcoming consumption power and trends. The Research Publication. -
Management practices on execution effectiveness of strategies based on Thirukkural
Thirukkural by Thiruvalluvar contains couplets that speak about the morale necessary for an individual based on the roles played in various circumstances of life. These are applied to various fields including management even today. In this chapter, the authors conduct a narrative analysis on two major aspects of management skills to be inculcated in managers for successful progression of the organization. Execution is one such important aspect of management which plays a significant role in constructing effective doable strategies and executing the strategies without delay after proper analysis, thus sustaining the motivation level of the team and progress. 2024, IGI Global. All rights reserved. -
Managing change, growth and transformation: Case studies of organizations in an emerging economy
Purpose: In view of dynamic and widespread economic transformation in emerging economies, managing organizational change and growth in this context deserves more research attention. The purpose of this paper is to examine how three organizations in different industries manage change, growth and transformation in their organizational ecosystem. Design/methodology/approach: The authors conducted in-depth interviews with the leadership of three organizations in different economic sectors in India, a country representing an emerging economy. The authors also reviewed historical data from these organizations. Three case studies illustrating the evolution of these organizations were developed from the data collected. Findings: Lessons and implications from the three case studies suggest the following key elements of effective organizational change mechanisms in an emerging economy: visionary entrepreneurial leadership; program quality excellence; scale growth and scope expansion; network capabilities; and sustainable stakeholders engagement. At the same time, this study also shows how these organizations manage change, growth and transformation in the context of a society with strong traditions and cultural norms. Research limitations/implications: Results and conclusions may be limited by the fact that the study is based on three case studies. Additional studies from a variety of industries with large numbers of participants will be helpful in more fully understanding the ways in which change, growth and transformation can best be developed and deployed in different organizational settings. Practical implications: The proposed model of organizational change in an emerging economy may assist organizational leadership in designing and sustaining their change efforts. Social implications: This study highlights the role of visionary entrepreneurial leadership and the impact of organizational growth mechanisms on organizational value delivery capabilities and organizational reputation. Originality/value: Lessons and implications of five growth steps of outstanding organizations in an emerging economy context provide valuable insight for organizational change, growth and transformation in other emerging contexts. 2019, Emerald Publishing Limited. -
Managing change, growth and transformation: Case studies of organizations in an emerging economy /
Journal of Management Development, Vol.38, Issue 4, pp. 298-311, ISSN No. 0262-1711. -
Managing coworker conflict: investigating the effect of workplace phubbing and mindfulness on employee deviant and negligent behavior
Purpose: This study aims to examine the influence of workplace phubbing on employee deviant behavior and negligence, while also investigating the mediating role of coworker conflict. Additionally, the study explores the moderating effect of workplace mindfulness on the relationship between workplace phubbing, the mediators and employee deviant behavior and negligence. Design/methodology/approach: Data were gathered from employees in the service sector in the UAE using an online survey questionnaire. A total of 374 participants submitted complete responses. The studys hypotheses were tested through regression-based moderated path analysis, incorporating conditional process modeling and nonlinear bootstrapping. Findings: The study indicates that experiencing phubbing at work contributes to feelings of coworker conflict, which subsequently leads to increased interpersonal deviance and employee negligence. Moreover, workplace mindfulness weakens the positive influence of being phubbed on coworker conflict, interpersonal deviance and employee negligence. Originality/value: To the best of the authors knowledge, no previous studies have examined the negative impact of being phubbed at the individual employee level within the service industry. This study aims to contribute to both theory and practice by elucidating the mediating mechanism of coworker conflict and exploring the moderating effects of workplace mindfulness. 2024, Emerald Publishing Limited. -
Managing individual and orgnizational challenges with respect to diversity perceptions and social capital among members of virtual teams,
Diversity encompasses complex differences and similarities in perspectives, identities, and points of view among members of an institution as well as among individuals who make up the wider community. Diversity includes important and interrelated dimensions of human identity such as race, ethnicity, gender, gender identity and newlineexpression, socio-economic status, nationality, citizenship, religion, newlinesexual orientation, ability and age. These differences are important to understand but they cannot be used to predict any individual s values, choices or responses. Organizations with diverse employees are better suited to serve diverse external customers in an increasingly global market. Such organizations have a better understanding of the requirements of the legal, political, social, economic, and cultural environments. Organizations that manage diversity are recipients of more commitment, and better satisfied as well newlineas better performing employees (Patrick and Kumar,2012). newlineEnsuring better social relations among team members has become complex. The nature of teams is not how they used to be, organizations have spread across geographically which has led to the birth of virtual teams. Virtual team members are been separated by time and space this makes it even more difficult to ensure that social capital is being maintained among virtual team members, as only when there is a trust, newlinereciprocity and cooperation among virtual team members they will be better connected individuals who obtain greater advantages, this ensures that groups and organizations improve performance and obtain sustainable competitive advantage (Tsai and Ghoshal, 1998). newlineThe present investigation was focused on understanding the perception of members of virtual teams towards diversity at workplace. newlineThis study newlineassists us to find out how virtual team members can overcome Individual newlineand Organizational Challenges towards diversity and to find out the social newlinerelations among virtual team members, how much trust exists among them. -
Managing stress, traumatic experiences, life skill training, and leading with a purpose
This chapter examines the obstacles encountered by minority women pursuing leadership positions in K-12 education, focusing on the interconnectedness of gender and ethnicity. This work explores the intricate terrain of stress and trauma, examining particular obstacles such as marginalization and microaggressions, thereby emphasizing the necessity for specialized assistance. The chapter delivers valuable insights regarding stress management and purposeful leadership, including Mindfulness, life skill training, tension reduction, professional assistance, mentorship, and peer support. The text highlights the significance of effective stress management in cultivating a supportive educational environment. The text culminates in an appeal for empowerment, emphasizing the capacity of obstacles to be catalysts for change in the direction of inclusivity and diversity for minority women leaders who strive to shape a diverse and progressive future. 2024, IGI Global. All rights reserved. -
Managing Sustainability in Perishable Food Supply Chains : A Case of Mango From Farm-to-Table
This research explores the significant role of India in the global food production sector, with a specific focus on perishable goods. It examines how this sector contributes to rural income and overall economic growth, while also addressing issues like post-harvest losses and inefficiencies in the perishable sector. The study highlights the necessity of a sustainable and efficient perishable sector for the progression of the Indian economy. By utilizing insights from resource-based view theory, stakeholders theory and systems theory, the research delves into the challenges and opportunities present in India's perishable food supply chain, emphasizing the crucial role of farmers in ensuring quality and effectiveness in India. Additionally, the study explores the broader context of Indian agriculture, with a specific focus on the perishable and horticulture sectors, their economic importance, and challenges such as post-harvest losses and the impacts of climate change. The research advocates for a strategic collaborative approach involving governments, businesses and communities to secure the sustainability and resilience of the perishable food supply chain in light of current and future challenges. The existing literature on the perishable food supply chain is evaluated to find the research gaps. This evaluation is conducted through a bibliometric analysis, shedding light on areas that have been neglected or inadequately explored in prior research. The identified gaps serve as the foundation for the research objectives of the study, aiming to fill these voids with fresh insights and discoveries. To establish the groundwork for the investigation, this research also initiates an in-depth discourse on each hypothesis, ensuring that the research design presented is both transparent and logical. The ultimate objective is to enhance comprehension of the perishable foodsupply chain, paving the way for future studies to build upon this foundational work. Then the research seeks to elucidate the research methods utilized to meticulously validate the researchmodel, employing stringent techniques and measures to guarantee the integrity and dependability of the findings. This framework aims to encapsulate the entire research process succinctly, from its fundamental objectives to the eventual implications of its findings, guiding readers through the investigative journey undertaken in the study. To achieve these objectives, a research model is presented that examines the interrelationships between quality, efficiency, sustainability and technological capabilities within the perishable food supply chain. The research methodology employed in this study combines both quantitative and qualitative techniques. It encompasses a detailed description of the sampling procedure and data collection methods, including the utilization of probability sampling techniques and surveys. Furthermore, the statistical tools and techniques employed in the study is Partial Least Square Structural Equation Modelling (PLS-SEM). The study formulates a comprehensive model that takes into account quality, efficiency and sustainability within the perishable food supply chain, with a specific focus on the moderating impact of technological capabilities. It identifiespositive connections between quality and sustainability, efficiency and sustainability, as well as the combined influence of quality and efficiency on sustainability. Technological capabilities are revealed to bolster these connections, underscoring the significance of circularity in the supply chain to minimize waste and align with sustainability objectives. The research concludes by providing insights on the challenges and prospective pathways towards more sustainable, efficient, and quality-driven practices in the perishable sector, particularly in light of technological advancements and the global trend towards circularity. -
Managing with Machines: A Comprehensive Assessment on the Use of Artificial Intelligence in Organizational Perspectives
This complete study, delves into the multifaceted impacts of artificial Intelligence (AI) inside organizational settings, highlighting its ability and demanding situations. The investigation spans numerous aspects along with AI-driven customer relationship management (CRM), employee productivity, and overall performance enhancement thru AI. By analyzing distinct AI applications and methodologies across different organizational functions, this studies presents insights into how AI can transform industries, decorate CRM, improve employee productiveness, and foster sustainable development. Despite the promising programs, the study also addresses the pitfalls and enormous hesitancy in AI adoption due to disasters in some high-profile AI projects. The paper underscores the significance of strategic AI integration, context-consciousness, and the want for organizational readiness to leverage AI's full capability whilst aligning with the Sustainable improvement goals (SDGs). 2024 IEEE. -
Managing workplace diversity: Issues and challenges
Sage Open pp.1-5 DoI No. 10.1177/2158244012444615 -
Managing workplace diversity: Issues and challenges
Diversity management is a process intended to create and maintain a positive work environment where the similarities and differences of individuals are valued. The literature on diversity management has mostly emphasized on organization culture; its impact on diversity openness; human resource management practices; institutional environments and organizational contexts to diversity-related pressures, expectations, requirements, and incentives; perceived practices and organizational outcomes related to managing employee diversity; and several other issues. The current study examines the potential barriers to workplace diversity and suggests strategies to enhance workplace diversity and inclusiveness. It is based on a survey of 300 IT employees. The study concludes that successfully managing diversity can lead to more committed, better satisfied, better performing employees and potentially better financial performance for an organization. The Author(s) 2012. -
Manipur: the British legacy
[No abstract available] -
Manta Ray Foraging Optimizer with Deep Learning based Malicious Activity Detection for Privacy Protection in Social Networks
Malicious activity detection is a vital component of ensuring privacy protection in social media networks. As users engage in online interactions, protecting their sensitive information becomes paramount. Social networks can proactively identify and mitigate malicious behaviors, such as cyberbullying, data breaches, and phishing attacks by applying advanced AI and machine learning (ML) technologies. This detection system analyzes user behavior patterns, content, and network traffic to flag suspicious activities, thus safeguarding user privacy and fostering a safer online environment. The incorporation of robust malicious activity detection mechanisms helps maintain trust in social networks and reinforces the commitment to preserving user privacy in an increasingly interconnected digital landscape. This article introduces a novel Manta Ray Foraging Optimizer with Deep Learning based Malicious Activity Detection (MRFODLMAD) technique for privacy protection in social networks. The drive of the MRFODL-MAD technique is to detect and classify malicious activities in the social network. To accomplish this, the MRFODL-MAD technique preprocesses the input data. For malicious activity detection, the MRFODL-MAD technique employs long short term memory (LSTM) system. The MRFO algorithm has been executed to hyperparameter tuning process to improve the performance of the LSTM network. The experimental outcomes of the MRFODL-MAD algorithm can be tested on social networking database and the results inferred the improved performance of the MRFODL-MAD algorithm under various different measures. 2023 IEEE. -
Mapping Cityscapes : Interrogating the Cultural Spaces in the Select Novels of Bapsi Sidhwa
Bapsi Sidhwa (1939) a well-known Pakistani Zoroastrian novelist in English offers the cityscapes of Lahore that provide the settings for her fictional works. The select newlinenovels for the study include The Crow Eaters (1978), The Pakistani Bride (1983), IceCandy Man (1988) and An American Brat (1993). Fascinated by the cityscapes of Lahore, the novelist personalizes the cityscapes and the personalized cityscapes are fictionalized. The novelist is aided by imagination. However, the imagined cityscapes in the select novels become illegible with a growing sense of alienation from the city. The cityscapes are cityspaces that are shape shifting. The metaphorical cityscapes in newlinethe select novels are woven with imagination, memory and nostalgia. The thesis examines the fictional representation of the cityscapes of Lahore and the relationship between the novelist and the imagined cityscapes. The study adopts the method of qualitative textual analysis in an attempt to examine the cityscapes. This illumines the in-between status of the cityscapes connecting the factual and fictional images of the city. The study unveils a layered construction of heterogeneous cityscapes which are selective and subjective. The urban cultural spaces are interrogated through the fictional characters who experience the city like fleurs and contribute to the making of the spatial stories. The acts of walking in the city offer knowledge of the city which enables the fictional characters to attain self-awareness. The awareness helps in achieving autonomy in the movements of the fictional characters. However, only a few fictional characters are perfect fleurs and the others view the city as voyeurs. Since the imagined cityscapes of Lahore are guided by the sense of place, the legibility of the cityscapes declines with the acts of alienation from the city. However, the novelist attempts to recover the palimpsest cityscapes from memory through cognitive mapping.