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Data Structure Based Loss-less Image Compression Algorithm
Working capital in any organizations has a significant role in driving the business forward. Hence, there is an imminent need for the management of the working capital. The efficiency with which working capital is managed in a business or organization determines the health of the business or the organization. On having an effective working capital management firms tend to be successful and while ineffective working management leads to the failure of the business. Hence, the management of working capital is of great importance. The research study is to evaluate the effectiveness of working capital management in maximizing the profitability of construction companies in Bangalore. The research will analyze the construction companies to establish an understanding of the significance of effective WCM for maximizing the profitability. The working capital is the life blood of a business and an important function of finance that defines and deals with the liquidity of the firm. Also, profitability of firms is another major aspect of business. The research explores the correlation between the working capital and profitability to understand the effectiveness of working capital management in maximizing the profitability. The construction industry is the second largest industry of the country after agriculture. Construction activity is an integral part of a countrys infrastructure and industrial development. It includes hospitals, schools, townships, offices, houses and other buildings; urban infrastructure (including water supply, sewerage, drainage); highways, roads, ports, railways, airports; power systems; irrigation and agriculture systems; telecommunications etc. Covering as it does such a wide spectrum, construction becomes the basic input for socio-economic development. The construction industry generates substantial employment and provides a growth impetus to other sectors through backward and forward linkages. It is, essential therefore, that, this vital activity is nurtured for the healthy growth of the economy. With the present emphasis on creating physical infrastructure, massive investment is planned during the Tenth Plan. The construction industry would play a crucial role in this regard and has to gear itself to meet the challenges. In order to meet the intended investment targets in time, the current capacity of the domestic construction industry would need considerable strengthening. The construction sector has major linkages with the building material industry since construction material accounts for sizeable share of the construction costs these include cement, steel, bricks/tiles, sand/aggregates, fixtures/fittings, paints and chemicals, construction equipment, petro-products, timber, mineral products, aluminum, glass and plastics. The construction sector is one of the largest employers in the country. In 1999-2000, it employed 17.62 million workers, a rise of 6 million over 1993-94. The sector also recorded the highest growth rate in generation of jobs in the last two decades, doubling its share in total employment. -
Data visualization and toss related analysis of IPL teams and batsmen performances
Sports play a very significant role in the development of the human persona. Getting involved in games like Cricket and other various sports help us to build character, discipline, confidence and physical fitness. Indian Premier League, IPL provides the most successful form of cricket as it gives opportunities to young and talented players to show case their talents on various pitch. Decision-makers are the utmost customers for all fundamentals in the sports analytics framework. Sports analytics has been a smash hit in shaping success for many players and teams in various sports. Sports analytics and data visualization can play a crucial role in selecting the best players for a team. This paper is about the Toss Related analysis and the breadth of data visualization in supporting the decision makers for identifying inherent players for their teams. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
Data visualization: Experiment to impose ddos attack and its recovery on software-defined networks
The entire network is doing paradigm shift towards the software-defined networks by separating forwarding plane from control plane. This gives a clear call to researchers for joining the ocean of software-defined networks for doing research considering its security aspects. The biggest advantage of SDN is programmability of the forwarding plane. By making the switches programmable, it can take live instructions from controllers. The versions of OpenFlow protocol and the compatibility of programmable switches with OpenFlow were the stepping stone making software-defined networks thrashed towards reality. The control plane has come up with multiple options of controllers such as NOX [2], Ryu [3], Floodlight [4], Open- DayLight [6], ONOS [7] and the list is big. The major players are Java based which keeps the doors open for enhancement of features by the contributors. However, more is expected from the practicality of P4Lang programmed switches by bringing skilled people to the industry who can actually implement programmable switches with ease. The obvious reason for delayed progress in the area of software-defined networks is the lack of awareness towards data visualization options existing as of now. The purpose of writing this chapter is to throw light upon the existing options available for data visualization in the area of SDN especially addressing the security aspect by analyzing the experiment of distributed denial of service (DDoS) attack on SDN with clarity on its usage, features, applicability and scopes for its adaptabilities in the world of networks which is going towards SDN. This chapter is a call to network researchers to join the train of SDN and push forward the SDN technology by proved results of data visualization of network and security matrices. The sections and subsections show clearly the experimental steps to implement DDoS attack on SDN and further provide solution to overcome the attack. Springer Nature Singapore Pte Ltd. 2020. -
Data-driven behaviour finance for mutual fund investment decision making
When it comes to money and investing funds, the individual portfolio investor isn't always as logical as he feels he is, which is why there's a whole school of thought dedicated to explaining why people behave in irrational and weird ways. The primary objective of this research is to investigate the effects of five major behavioural biases on individual investor decisions in a metro city India, with a focus on mutual funds, as well as to examine how individuals make decisions to ensure that their investments generate greater returns for a better future. The statistical evidence shows that a variety of behavioural elements have a significant part in people' investment decision-making patterns, which has an impact on the population's economic situation. The purpose of this study is to illustrate how an individual's perspective, attitude, and conduct affect mutual fund investments. 2023, IGI Global. -
Data-Driven Decision Making
This book delves into contemporary business analytics techniques across sectors for critical decision-making. It combines data, mathematical and statistical models, and information technology to present alternatives for decision evaluation. Offering systematic mechanisms, it explores business contexts, factors, and relationships to foster competitiveness. Beyond managerial perspectives, it includes contributions from professionals, academics, and scholars worldwide, delivering comprehensive knowledge and skills through diverse viewpoints, cases, and applications of analytical tools. As an international business science reference, it targets professionals, academics, researchers, doctoral scholars, postgraduate students, and research organizations seeking a nuanced understanding of modern business analytics. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Data-Driven Decision Making in the VUCA Context: Harnessing Data for Informed Decisions
Data-driven decision making (DDDM) has evolved from being a strategic advantage to a necessity for organizations aiming to thrive in the dynamic business contexts. It is about using data as a tool to enhance strategic thinking, scenario planning, and adaptation in rapidly changing environments. It involves leveraging data and analytics to navigate the challenges of volatility, uncertainty, complexity, and ambiguity. By embracing DDDM, organizations can enhance their decision-making processes, gain a competitive edge, and navigate the challenges of volatility, uncertainty, complexity, and ambiguity with greater confidence. However, successful implementation requires addressing challenges, fostering a data-driven culture, and continually adapting best practices to meet the evolving demands of the VUCA environment. This chapter discusses how organizations leverage DDDM in VUCA context to support effective and rapid decision making aligned with organizations vision. Particularly, it would offer insights to transit from volatility to vision, uncertainty to understanding, complexity to clarity, and ambiguity to agility. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Data: A Key to HR Analytics for Talent Management
The past few years have witnessed a significant rise in job openings across various industries worldwide. This trend has highlighted the need for companies to plan and recruit better talent to keep up with the demand for skilled employees. As a result, Human Resource (HR) professionals are now using workforce planning and HR analytics to address the challenges of finding and retaining the right employees. With the help of technological advancements in HR systems, businesses are leveraging data and insights to understand workplace dynamics better. Workforce planning has thus become crucial for organizations of all sizes to ensure they have the necessary talent to achieve their goals in the present and future. This chapter delves deeper and examines the importance of workforce planning and how HR analytics can help companies achieve their strategic objectives. Talent Management is about analyzing the workforce skill requirements of the organization. It needs a strategic plan to ensure the appropriate people are in the right roles at the right times. Talent Management is a crucial element of every businesss performance. In this process, data play a pivotal role in evaluating the existing workforce and planning for future workforce needs. Based on this, a strategy is developed to fill gaps or prospective shortages. Organizations can achieve their goals by using talent planning and collecting data about upcoming projects and skill requirements based on market needs. For example, talent planning is essential in the healthcare sector to guarantee that hospitals and clinics have enough doctors, nurses, and other healthcare workers to fulfill the rising demand for healthcare services. HR analytics is the key to talent management, enabling organizations to stay competitive, enhance productivity, and achieve long-term strategic objectives. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Data: An Anchor for Decision- Making to Build the Future Workforce Management System
In this digital era, the change in business environments and the nature of work lead to skill gaps. Training the workforce on desired skill sets must fill these skill gaps. Data play a crucial role in identifying the skills needed and helping organizations to plan the future workforce. Data is essential for any organizations growth and success in the dynamic market. Knowing the skill set in advance allows organizations and individuals to plan the business and skill requirements well. The way work is done may be impacted by these structural changes as the world is changing swiftly. Building the abilities necessary for the uncertain environments of the present and future environments is also crucial for training the employees. However, such skills must first be acknowledged and appreciated before being developed. Empirical data must support the methodology for valuing such abilities and skills. This chapter outlines the significance of data in skill identification for individuals to be future-ready. Finding the most relevant abilities in a given environment is the first step toward their formalization and acceptance at the systems level. It also presents the importance of creating skill matrices for students and organizations. The skill matrix objectively quantifies skill value for specific occupations and the possible trajectories to acquire those skill sets. This metric will allow policymakers to navigate this fast-changing workforce landscape and focus resources to ensure that skills are needed as students transition into the workforce and have skills that enable them to transition. 2024 selection and editorial matter, Alex Khang, Sita Rani, Rashmi Gujrati, Hayri Uygun, and Shashi Kant Gupta; individual chapters, the contributors. -
Database aware memory reconstruction for object oriented programming paradigm
Data storage is a big challenge in front of industries and researchers when its growing enormously. Traditional data storage strategy was fulfilling the business needs till the data was in structured format. But now due to Internet of Things (IoT) compatible devices unstructured data is more than structured one. In such cases traditional data storage strategy won't work efficiently. Initially data storage devices used to store the data irrespective of its logical storage. It means the record was stored either in array format or block format. Such type of storage was not matching physical and logical structure. Logically, structured data is generated as an attribute of particular entity, but physically it gets stored in a sequential memory storage either as file or as memory block. Object Based Storage pattern(OBS) stores the data in the way object gets generated by the programmer and accordingly memory is allocated for that object. Object contains all the data related to that particular entity which makes it easy to retrieve it back. Current study includes comparative advantages, operations and study of different service providers of object-based storage. We also focused on the current need of object-based storage structure for big data analysis and cloud computing. International Journal of Scientific and Technology Research. All rights reserved. -
Dataset exploring organizational culture of K-12 schools
Culture can be understood as an explicit social product arising from social interaction as an intentional or unintentional consequence of behavior. Educational Institutions culture differs from other organizational cultures as it impacts teachers' performance and students' learning. In this survey the definition of organizational culture used is given by Schein, The deeper level of basic assumptions and beliefs that are, learned responses to the group's problems of survival in its external environment and its problems of internal integration; are shared by members of an organization; that operate unconsciously; and that define in a basic taken -for-granted fashion in an organization's view of itself and its environment [1]. The data contains 1158 cases collected from K-12 School teachers on their perception of values and beliefs of their organizational culture using the OCTAPACE scale. Convenience sampling is used to obtain the data from teachers. The questionnaire was administered personally to teachers from sixty-five Private aided, Private unaided and Government schools. The eight dimensions measuring values and beliefs of Educational Institutions organizational culture are Pro-action, Authenticity, Openness, Collaboration, Experimenting, Trust, Confrontation and Autonomy. Descriptive statistics are computed from the dataset. The dataset can be used by researchers for meta analysis on organizational culture and school management can explore in depth the need for an organizational culture of autonomy, experimenting, collaboration and openness among teachers. 2022 The Authors -
Date Palm: Genomic Designing for Improved Nutritional Quality
Date palm (Phoenix dactylifera L.) is one of the oldest fruit trees known where a significant amount of breeding has been carried out to improve various agronomic and nutritional characteristics. Numerous studies have been done to improve the nutritional composition and quality of the fruit due to its significant biological properties. Various strategies have been formulated for improving the agronomic characters through biofortification as well as preserving through postharvesting techniques. Modern breeding practices using molecular markers have significantly helped to identify the phenotypic, as well as genotypic, diversity for the selection of superior date palm cultivars, advanced agronomic characters like nutritional quality, disease resistance, and yield. Availability of the whole genome sequence, organellar sequence, and genetic map of date palm has helped breeders in modification and improvement of the characteristics. With the availability of bioinformatic tools and gene editing knowledge, the nutritional composition of date palm can be effectively manipulated to develop better crops along with good agronomic characters and resistance to diseases. The authors have compiled the nutritional composition of date palm fruits and detail the strategies to edit the genome and improve nutritional quality. Springer Nature Singapore Pte Ltd. 2023. -
DATING APPS, FORMS OF ABUSE AND PERSONALITY TYPE
[No abstract available] -
DAWM: Cost-Aware Asset Claim Analysis Approach on Big Data Analytic Computation Model for Cloud Data Centre
The heterogeneous resource-required application tasks increase the cloud service provider (CSP) energy cost and revenue by providing demand resources. Enhancing CSP profit and preserving energy cost is a challenging task. Most of the existing approaches consider task deadline violation rate rather than performance cost and server size ratio during profit estimation, which impacts CSP revenue and causes high service cost. To address this issue, we develop two algorithms for profit maximization and adequate service reliability. First, a belief propagation-influenced cost-aware asset scheduling approach is derived based on the data analytic weight measurement (DAWM) model for effective performance and server size optimization. Second, the multiobjective heuristic user service demand (MHUSD) approach is formulated based on the CPS profit estimation model and the user service demand (USD) model with dynamic acyclic graph (DAG) phenomena for adequate service reliability. The DAWM model classifies prominent servers to preserve the server resource usage and cost during an effective resource slicing process by considering each machine execution factor (remaining energy, energy and service cost, workload execution rate, service deadline violation rate, cloud server configuration (CSC), service requirement rate, and service level agreement violation (SLAV) penalty rate). The MHUSD algorithm measures the user demand service rate and cost based on the USD and CSP profit estimation models by considering service demand weight, tenant cost, and energy cost. The simulation results show that the proposed system has accomplished the average revenue gain of 35%, cost of 51%, and profit of 39% than the state-of-the-art approaches. 2021 M. S. Mekala et al. -
DDoS Intrusions Detection in Low Power SD-IoT Devices Leveraging Effective Machine Learning
Security and privacy are significant concerns in software-defined networking (SDN)-applied Internet of Things (IoT) environments, due to the proliferation of connected devices and the potential for cyberattacks. Hence, robust security mechanisms need to be developed, including authentication, encryption, and distributed denial of service (DDoS) attack detection, tailored to the constraints of low-power IoT devices. Selecting a suitable tiny machine learning (TinyML) algorithm for low-power IoT devices for DDoS attack detection involves considering various factors such as computational complexity, robustness in dealing with heterogeneous data, accuracy, and the specific constraints of the target IoT device. In this paper, we present a two-fold approach for the optimal TinyML algorithm selection leveraging the hybrid analytical network process (HANP). First, we make a comparative analysis (qualitative) of the machine learning algorithm in the context of suitability for TinyML in the domain of SD-IoT devices and generate the weights of suitability for TinyML applications in SD-IoT. Then we evaluate the performance of the machine learning algorithms and validate the results of the model to demonstrate the effectiveness of the proposed method. Finally, we see the effect of dimensionality reduction with respect to features and how it affects the precision, recall, accuracy, and F1 score. The results demonstrate the effectiveness of the scheme. 1975-2011 IEEE. -
De novo synthesis of 2,2-bis(dimethylamino)-3-alkyl or benzyl 2,3-dihydroquinazolin-4(1H)-one compounds
A new versatile and efficient strategy for the synthesis of 2,2-bis(dimethylamino)-3-alkyl or benzyl 2,3-dihydroquinazoline-4(1H)-one compounds has been developed by one-pot multicomponent reaction with isatoic anhydride, amines followed by in situ-generated Vilsmeier reagent. The reaction has also been studied with different amines and solvents. 2017 Taylor & Francis. -
Dealing with missing values in a relation dataset using the DROPNA function in python
Python provides a rich data structure library called PANDAS, which provides fast and efficient data transformation and analysis. The word PANDAS is an abbreviation of Python Data Analysis Library. PANDAS facilitate optimized and dynamic data structure designs work with "relational" or "labeled" data. Python's approach is meant to provide a high-level, high-performance building block that can be used to do real-world analysis of data. PANDAS Library is allowing users to import data from different file formats, such as CSV, SQL, Microsoft Excel etc. [1]. It helps in data preparation, as well as in data modeling, for those projects, which aims data analysis for the extraction of information. Python's future will be built on this layer for statistical computing. In addition to discussing future areas of work and growth opportunities for statistics and data analytics applications built on Python, the study provides details about the language's design and features [2]. In this research paper, we intend to solve the problem of missing values in a dataset using the DROPNA function in Python using PANDAS library. 2023 Scrivener Publishing LLC. -
Death of Vernaculars and Language Hegemony: An ethnography of the higher education sector in 21st century India
The paper examines how new age pedagogies and neoliberal policies consciously work towards naturalizing English languages hegemony in institutions of Higher Education (IHE) in India. An ethnographic study the paper foregrounds the precarious positioning of non-English Indian languages vis-vis the pervading discourses of internationalization and education as job/skill oriented. Hegemony of English in the present is coupled with a restructuring of language departments as well as fleeting market demands for human capital. The paper also brings into question the role of the Internet and related technologies in reorganizing the linguistic dynamics of HE. Instead of democratizing, the Internet produces new monopolies in knowledge production, controls knowledge traffic from global North to South and further legitimizes the language hegemony. The paper argues that, in the last two decades, the neoliberal rupture has been leading HE institutions to a death of vernaculars within their physical, cultural and academic spaces. 2024, Hiroshima University,Research Institute for Higher Education,. All rights reserved. -
Death Rituals and Change Among Hindu Nadars in a South Indian Village
This article examines changes in the death rituals performed among Hindu Nadars in a South Indian village. It emphasises the importance of understanding ritual changes within their specific micro-level local contextual framework, including changing social structures at household and village level. This empirical evidence showcases how changing rituals connected to death reflect various adaptations through imitation, substitution and alteration of specific ritual elements and performants. It also identifies emerging class distinctions among Nadars and their connection with changes in rituals associated with death. This analysis of the changes depicts how Nadars use ritual actions in pragmatic ways, symbolically expressing and realising their aspirations for status enhancement through such ritual performances. 2021 SAGE Publications. -
Death-worlds, Necropolitics and Decoloniality Colonial Negotiations in Mah
The boundaries of sovereignty are mostly relegated to modern and late modern political thoughts that focus on biopolitical and democratic theories. This paper marks a shift of sovereign subjectivity to the interstitial spaces of life and death of the colonial subjects. Through the study of the necropolitics of colonial control in the erstwhile French colony of Mah as narrated in the novel On the Banks of the Mayyazhi, this paper argues that colonial subjectivity and the idea of sovereignty have decentred itself from the traditional notions of political control and violence to newer avenues of life and death. The perusal of the decolonial approach to necropolitics will examine how colonial logic has shaped the idea of sovereignty. 2024 Economic and Political Weekly. All rights reserved. -
Decent Work Deficit: A Challenge on the Women Empowerment in Indian Agricultural Sector
Women play a crucial role in Indian agriculture, but they also confront several obstacles that reduce their productivity and prevent them from fully engaging in the sectors development. The majority of women in India are employed in agriculture, which is one of the sectors that contributes most to the GDP and is essential to the economic development of the nation. Although women continue to have a significant and recognized role in agriculture, their function is frequently overlooked. Women make up about 75% of the full-time labor force on Indian farms. The nation wont develop unless its women farmers are empowered. Only through decent work labour the agriculture sector will be developed which will help in the empowermentof women agricultural Labourers in India. So the government should take all steps to implement the decent work concept of ILO in the Indian agricultural sector. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.