eChapters

Introduction

The finance sector is undergoing a profound transformation driven by technological advancements, with artificial intelligence (AI) and blockchain technology at the lead of innovation. AI, characterized by its capacity to analyze vast datasets, recognize patterns, and take data-driven decisions has revolutionized various industries, including finance. On the other hand blockchain technology, initially popularized by cryptocurrencies like Bitcoin has arose as a disruptive force in finance, offering decentralized, transparent and secure transactional systems.

The integration of AI and blockchain technology holds immense promise for the finance sector, offering new avenues for efficiency, transparency, and risk management. By combining the analytical power of AI with the security and transparency of blockchain, financial institutions can streamline operations improve customer experiences, and mitigate risks more effectively. However realizing the full potential of this integration requires a nuanced understanding of its complexities, challenges, and opportunities.

Introduction

AI plays a key role in management effectiveness and adaptation, especially in small and medium enterprises (SMEs) facing evolving markets (Lemos S. I. C., et al., 2022). Designing AI-based management frameworks enhances companies’ economic activities through data analysis and informed decision making (Emine, Kalender., 2023). Academic research shows a growing interest in AI in management, with a focus on effective adoption practices and potential areas for development (Jbid, Arsenyan., Anke, Piepenbrink. 2023). Artificial intelligence (AI) significantly influences decision-making processes in management by enhancing rationality, efficiency, and fairness. AI, through machine learning and big data analysis, reduces managerial bounded rationality, enabling a shift from satisficing to optimizing decision making modes (Shtepa, S., et. al., 2023). In human resource management AI-enabled interview analysis improves candidate selection by uncovering hidden patterns and mitigating biases, leading to more objective decisions (Rajneesh, Panwar. 2023). Additionally, by increasing productivity, efficacy and creativity, the incorporation of AI into business strategy transforms decision-making; nonetheless, ethical considerations and human oversight are essential for responsible implementation (Gonesh, C., et. al., 2023).

Introduction

21^st century challenges like climate change, water scarcity, increasing world population, rising food prices, and other socio-economic impacts are expected to generate a great threat to agriculture and food security worldwide, especially for the poorest people who live in arid and sub-arid regions. Millet is one of the oldest foods known to humans and possibly the first cereal grain to be used for domestic purposes. Millet has been used in Africa and India as a staple food for thousands of years. Typical grain texture and hard seed coat of millets increase their keeping quality but make them difficult to process as well as to cook in convenient form. Absence of appropriate primary processing technologies to prepare ready-to-use or ready-to-cook (RTC) products and also the secondary as well as tertiary processing technologies to prepare ready-to-eat value added products from millets are the major limiting factors for their diversified food uses.

Millets have relatively poor digestibility and low bio-availability of minerals due to the presence of inherent anti-nutritional factors. The difficulties in millet grain processing present a challenge but nutritional as well as health benefits and consumer demand for health foods provide opportunities in processing, develop suitable technology for newer products and process mechanization. This change in technology and consumer food preference would help in increasing the area under millets, maintaining ecological balance, ensuring food security, prevent malnutrition and increase the scope for utilization of millet grains on industrial scale.

Introduction

Indian agriculture is in a phase of transition from subsistence to high-tech agribusiness. This has ushered in an era where entrepreneurship is viewed as a strategic intervention in rural development. As a result, promotion of rural enterprises has gained great significance as an instrument for improved farm earnings, employment and women empowerment. It implies development of agriculture through farm diversification, value addition and development of agro-processing industries that provides autonomy, independence and reduced need for social support to the farmers. Improved farm-industry linkages along with great export potential will be added advantages. In this development scenario, agriculture, specifically high value horticultural crops like fruits, vegetables, spices, flowers, plantation crops, medicinal and aromatic plants among others that ensure maximum returns to the growers with multiple scopes for value addition hold great promise. In fact, horticultural crops become a necessary condition for improving the living standards of farmers and ensuring nutritional security of the nation. The concept of nutritional security goes beyond food security to include adequate availability of micronutrients such as vitamins and minerals in addition to calorie and protein needs of the people supplied through food grains. Therefore, the spectacular increase in food grain production and a reasonable overall agricultural performance has failed to eradicate malnutrition as can be inferred from Table 1. It indicates that the Global Hunger Index (GHI), a more comprehensive tool used to measure and track hunger, ranks India (97 out of 118 developing countries) in the category of serious hunger behind Bangladesh (90/118). More disturbing are the rates of growing malnutrition among Indian households. As such, nutritional security becomes a more relevant indicator of food security as we move up the development ladder

Objectives
• Understand the concept and structure of analogy-based questions.
• Recognize different types of analogies used in reasoning.
• Develop strategies to approach analogy questions effectively.
• Enhance critical thinking and problem-solving skills through practice.
Introduction
An analogy is a comparison between two things that highlights a relationship or similarity between them. Analogical reasoning is frequently used in verbal reasoning sections of competitive exams, as well as in day-to-day problemsolving.
In analogy-based questions, pairs of words are given, and the goal is to identifythe relationship between them and apply the same  relationship to another pair. Analogies test your ability to comprehend relationships, draw logical inferences, and think critically.
Structure of an Analogy Question
Typically, an analogy question follows this format:

Objectives
• Understand the concept and structure of analogy-based questions.
• Recognize different types of analogies used in reasoning.
• Develop strategies to approach analogy questions effectively.
• Enhance critical thinking and problem-solving skills through practice.
Introduction
An analogy is a comparison between two things that highlights a relationship or similarity between them. Analogical reasoning is frequently used in verbal reasoning sections of competitive exams, as well as in day-to-day problemsolving.
In analogy-based questions, pairs of words are given, and the goal is to identify the relationship between them and apply the same relationship to another pair. Analogies test your ability to comprehend relationships, draw logical inferences, and think critically.

ABSTRACT

Women are vital human resources and play a significant role in agricultural and allied sectors undertaking both on-farm and off- farm activities. Yet their contribution has not been recognized and they are considered as invisible workers. Considering this, the present study has been conducted to analysis the constraints faced by farm women in agriculture and allied sectors. A total of 100 farm women were selected as respondents through proportionate random sampling. The selected respondents were interviewed personally using pre-tested well structured interview schedule. The finding showed that the major constraints that farm women faced were limited access to productive resources like land, credit, input, extension services, storage and technical assistance, their absence from decision-making process, less wages and their illiteracy also hindered their progress. Women perform all un-mechanized agricultural tasks and perform multiple tasks, which add more burden to them.

Introduction

India has shaped its economic growth and transformed through information technology and digitalisation/ The Digital India initiative has tremendously improved its economic development. India’s efforts to revolutionize its information technology have taken the road ahead among the developed countries/ The contribution in the digital payment system has shifted in the banking and financial services sector. The emergence of technology upgradation through the internet has gained momentum in shifting towards internet and mobile banking technologies. The advent of technology has revolutionized the banking system through the evolution of financial technology with sustainable technological architecture through artificial intelligence which has enhanced ease of access for customers in the banking and financial sector. Artificial intelligence revolutionized various industries especially in the banking sector which has enhanced the way for interact the customers. The AI technology helps in reducing the cost for the Financial Sector. The Banks are welcoming the new age technology to serve betterment of the modern banking services.

Statistics is a branch of science which deals with the collection, classification, description and interpretation of data obtained by conducting surveys and experiments. The essential purpose of it is to describe and draw valid inferences about numerical properties of populations” (Ferguson 1966). The experience in statistics application indicates that a single statistical method can be used in different research areas for dealing with different types of problems. Various possibilities which application of a statistical method provides in certain research areas should be considered as an adequate way of dealing with a problem of the research. However, it should be noted that statistics is not a method by which it is possible to solve all the problems in a research. Nachmias and Nachmias (2009) stated that there are basically two types of statistics which include descriptive and inferential statistics. Descriptive statistics enable the researcher to summarize and organize data in an effective and meaningful way. It involves the use of tables, charts, graphs, mean, modes, median, standard scores and correlation to treat collected data. Inferential statistics is concerned with making inferences from a unit of a population. Inferential statistics is concerned with making inferences from a unit of a population. Inferential statistics allow the researcher to make decisions or inferences by interpreting data patterns. Researchers use inferential statistics to determine whether an expected pattern designated by the theory and hypotheses is actually found in the observations. To decide whether this hypothesis is true, researchers might survey the respondents and then use descriptive statistics to make comparison between these groups and would employ inferential statistics to determine whether the differences between the groups are significant or not.

All human beings are prone to a state of anger, which affects their performance during their day-to-day life. Anger and aggression are the same, although they are often experienced at the same time. Anger is an emotion, whereas aggression is a behavior or form of intervention. Whereas anger is internal, aggression is external. But both are typically associated with physiological arousal.

A person who perceives that wrong has occurred, which should be corrected, usually feels anger. Anger is a reaction against somebody, a person, an event, or an object. It is resentment to some injustice which has been perceived to have been meted out. The emotion of anger leads to aggressive behavior, especially among adolescents and teenagers. Aggression further causes pain to individuals.

Let us try to understand what we mean by anger, aggression, and pain, and how to manage them.

Anthropometry is the study of the measurement of the human body in terms of the dimensions of bone, muscle, and adipose (fat) tissue. It is a branch of anthropology dealing with measurements of human body to determine difference in groups and individuals. The word “anthropometry” is derived from the Greek word “anthropo” meaning “human” and the Greek word “metron” meaning “measure” (Ulajaszek, 1994).

Beekeeping symbolizes the biological interdependence between insects, pollination and production of seed. Honey bees have been tirelessly rendering this yeoman service to benefit human-kind since time immemorial. Beekeeping is defined as “the science and art of rearing honey bees for man’s economic benefits”. Since, honey producing bees are restricted to the genus Apis beekeeping is also called ‘Apiculture’. A suitable place selected for housing honey bee hives, equipments and related accessories is referred to as an “apiary”. The invention of movable hive with separable frames in 1851 by L.L. Langstroth gave beekeeping the impetus to flourish. Further fine-tuning of scientific rearing techniques in these movable hives helped in spreading beekeeping to the newer areas.

Honey Producing Species of Bee

About 20,000 bee species are found worldwide. However, only four species viz. the European honey bee (Apis mellifera Linnaeus), the oriental bee (A. cerana Fabricius), the dwarf bee (A. florae Fabricius), and the giant or rock bee (A. dorsata Fabricius) are commonly recognized as honey producing. Amongst these two, only A. cerana and A. mellifera are hived because these build multiple-combs in dark cavities. The other two build single comb nests in the open (Akratnakul 1987a, Ruttner 1987).

Introduction

Gamhian concept of development gained inspiration from villages where local resources met the optimum needs of the poorest of the poor. Gandhiji was of the view that the process of development of the Nation must begin from its villages. In a country like India, where villages are in the majority the prosperity of the Nation can only be ensured when fanners are considered as development managers. The economic liberty of individuals and villages in effect will lead to the prosperity of the Nation. The anomaly in this regard in our country can be seen in the overcrowded cities and desolated a village that is indicative of major gaps in our approach. Acute migration has created a dearth of strong hands in the villages resulting in overcrowded cities, putting tremendous strains on its infrastructure. Thus economy and-ecology of most regions in the country, both rural as well as the urban areas are threatened.

The Independence has been attained by the nation 65 years ago but Economic Slavery is pervasive everywhere in the Rural India. There must be an Economic Independence drive in the country. This will check rising Economic inequity between rural urban regions.

The Acceptance Quality Limit, commonly called AQL, is a statistical sampling system used to determine whether a production lot satisfies a predetermined level of quality. Inspectors examine a randomly selected sample and accept or reject the entire lot according to the number and seriousness of defects found. AQL does not require absolute freedom from defects; instead, it establishes an acceptable threshold based on the product, buyer expectations and defect criticality. It provides an efficient and objective alternative when complete inspection is impractical. Textile and apparel inspections commonly follow ISO 2859-1 or ANSI/ASQ Z1.4, which prescribe inspection levels, sample sizes and acceptance-rejection criteria.

Introduction

Global economies have witnessed very deepened financial integration in past decade and have more room for leverage. However, these integrations have also witnessed various turmoil in the economy in the form of Russian- Brazil debt crisis, Asian financial crisis, Dot com bubble, Argentina debt crisis, Global financial crisis and many more since 1990s. Due to the existence of globalization, these crises have impacted not only a particular economy but has extended its scope.

The previous studies have found the credit growth and asset prices as a leading indicator. Some studies also showed that the foreign exchange reserve, broad money supply and trade as variables were also statistically significant. These studies have used either the Signal Extraction Approach used by Kaminsky and Reinhart (1999) which used a threshold value as a limit for multiple variables beyond which a crisis signal is given. Bucharest Stock Exchange (BSE)in Romania (Brezinski and Stephen, 2011) lost its attractiveness among foreign investors. However, there are not enough resources which focuses on Asian economies or India. The emergence of novel technologies, including artificial intelligence (AI), blockchain, cloud computing, big data analytics, machine learning (ML), internet of things (IoT), and 3-D printing, commonly known as Industrial Revolution 4.0 (IR4.0), offers developing nations like India both significant opportunities and challenges. IR4.0 technologies, sometimes referred to as the “digital revolution,” have numerous uses in the industries of services, industry, and agriculture.

9.1. Introduction

The human population of the world will reach nearly 10 billion by 2050, boosting agricultural order-in a situation of humble financial development (FAO, 2017). At present, approximately 37.7% of total land surface is being utilized for crop production. From employment generation to contribution to National Income, agriculture sector is contributing a significant role in economic prosperity of the developed nations and is playing an active part in the economy of the developing countries as well. The growth of agriculture has resulted in a significant increase in the per-capita income of the rural community. Thus, a greater emphasis on agricultural sector is the need of the hour. For countries, like India, the agricultural sector accounts for 18% of GDP and provides employment to 50% of the country’s workforce. Development in the agricultural sector will enrich the rural development which will lead toward rural transformation and ultimately the desired structural transformation (Mogili and Deepak, 2018; Shah et al., 2019). The role of Artificial Intelligence (AI) has been obvious in the agricultural sector recently. The sector needs the impetus from AI based technology to maximize its yield including improper soil treatment, disease and pest infestation, big data requirements, low output, and knowledge gap between farmers and technology.

Introduction

The term "artificial intelligence" was originally coined in 1956 at a conference hosted by Dartmouth College. While the aspirations and dreams of the attendees were sky-high, the reality was sobering. The thought of citizens in space or self-driving cars within a decade was ancient science fiction. The building blocks of the required computing infrastructure, as well as AI, notably deep learning and statistical machine learning methods, were not even in the distant future. The aim was to create an artificial brain for a machine, where the "brain" is the so-called "expert system", a software program that can integrate a large knowledge base and use it to solve problems in the same manner that a human expert could. The intellectual merits and achievements of a few AI systems designed solely to narrowly excel in a specific problem became the actual problem of the nascent field.

What is Artificial Intelligence

‘Artificial’ is taken to mean a property of a human-made machine. ‘Intelligence’ will be that when something is able to perform a new action or change its state to achieve the optimal response it could perform given external inputs. This term is coined by- John McCarthy (American computer and cognitive scientist) during 1956 So, AI is basically a machine able to mimic human intelligence by having the ability to predict, classify, learn, plan, reason and perceive.

AI is an emerging technology in the field of agriculture. AI-based equipment and machines, has taken today’s agriculture system to a different level. This technology has enhanced crop production and improved real-time monitoring, harvesting, processing and marketing . The latest technologies of automated systems using agricultural robots and drones have made a tremendous contribution in the agro-based sector. Various hi-tech computer-based systems are designed to determine various important parameters like weed detection, yield detection and crop quality and many other techniques.

12.1. Introduction

Artificial Neural Networks (ANNs) are computational models inspired by the way biological neural networks in the human brain process information. They consist of interconnected nodes or “neurons” arranged in layers: an input layer, one or more hidden layers, and an output layer. Each neuron in the network processes data and passes the results to the next layer. ANNs are designed to recognize patterns, learn from data, and make predictions or classifications based on that learning.

In an ANN, the connections between neurons are weighted, meaning each connection has a strength or value that determines the influence of one neuron on another. Through a process called training, the network adjusts these weights to minimize errors in its predictions. This is typically done using techniques like backpropagation, where the error is propagated backward through the network to update the weights (Abiodunet al., 2018).

ANNs are highly versatile and have been applied across various domains, including image and speech recognition, natural language processing, and decision-making systems. Their ability to model complex relationships in large datasets makes them a crucial component in the field of machine learning and artificial intelligence (Ahmed et al., 2023).

ABSTRACT

Assessment of technical and financial feasibility of two resource conservation technologies suitable for rice establishment1. Zero Tillage Machine (ZTM) for direct seeded rice (DSR) and; 2. Paddy transplanter machine (PTM) for mechanical transplanted rice(MTR) in Rohtas district was carried out at the demonstration farm of Krishi Vigyan Kendra (KVK), Rohtas during Kharif-2012 and 2013 in a view to reduce the drudgery and cost of cultivation. An eight row self-propelled PTM (Model 2ZT-238-8) and 9 tined National Make ZTM were used for the purpose. Technical performance of these resource conservation technologies was found satisfactory. The field capacity, field efficiency, fuel consumption and cost of establishment of rice by these technologies were evaluated for the purpose. For the assessment of financial feasibility; benefit-cost ratio, internal rate of return, pay-back period and net present worth of these technologies were evaluated and demonstrated to rural youths for their quick adoption and get rid of labour-shortage and delayed transplanting of rice crop and hence saving of significant loss of Rabi crops that happens due to delayed harvesting of rice crop.