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Speech to text conversion and summarization for effective understanding and documentation
Speech, is the most powerful way of communication with which human beings express their thoughts and feelings through different languages. The features of speech differs with each language. However, even while communicating in the same language, the pace and the dialect varies with each person. This creates difficulty in understanding the conveyed message for some people. Sometimes lengthy speeches are also quite difficult to follow due to reasons such as different pronunciation, pace and so on. Speech recognition which is an inter disciplinary field of computational linguistics aids in developing technologies that empowers the recognition and translation of speech into text. Text summarization extracts the utmost important information from a source which is a text and provides the adequate summary of the same. The research work presented in this paper describes an easy and effective method for speech recognition. The speech is converted to the corresponding text and produces summarized text. This has various applications like lecture notes creation, summarizing catalogues for lengthy documents and so on. Extensive experimentation is performed to validate the efficiency of the proposed method. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
Natural Disaster Prediction by Using Image Based Deep Learning and Machine Learning
In recent years, diseases and disaster have become more unpredictable. The advent of technology has not only making our lives easier but also technology-dependent. Nevertheless, the natural disasters cause great adversity by disrupting considerable human lives. Also, the disasters obstruct and affect many industries and services either directly or indirectly. Hence, it is necessary to study and observe data patterns and warning signs that lead to a natural disaster, its potential risk and its ability to resolve management strategies, which can be implemented immediately to minimize the socio-economic loss. This article reviews the state-of-the-art research works and findings through a technological perspective on data analysis, natural disaster prediction, and the utilization of technology for deploying management strategy. Also, this paper focuses on investigating the today's Industry 4.0 that utilizes cognitive computing. The primary aim of this article is to review the research ideas that leverage big data and data mining to observe and track patterns, which can impelment predictive analysis to anticipate the forthcoming disasters. Furthermore, this research work analyzed the posed predictive models by specifically using ANN (Artificial Neural Networks), sentiment model, and smart disaster prediction application (SDPA) to predict the flash flood. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
United States-South Asia relations: Challenges and opportunities facing the Biden administration
With the passage of time, US interests in the South Asian region have also diversified. South Asia has emerged as a highly strategic and volatile region in the geopolitics of the Indo-Pacific region. The chapter is divided into two sections. One section looks at the prospects in US-South Asia relations, focusing on the scaling up of security and non-security cooperation with the South Asian countries, with reference to US relations with Pakistan, Afghanistan, Sri Lanka, Bangladesh, Maldives and Nepal. The chapter addresses the overall strategic importance of the region and the impact of geopolitical shifts on US-South Asia relations. The second section of the chapter focuses on the evolving strategic ties between India and the United States. This analysis is against the backdrop of China's political, economic, and strategic policies and priorities in the region. Some of the major issues to be addressed in this section include the Chinese reaction to the defence and security cooperation, between India and the United States, the growing Chinese presence in the Indo-Pacific and its impact on the balance of power in the region, the Chinese "String of Pearls" strategy and its impact on India-US relations, the challenges posed by transnational crime, terrorism and piracy and their impact on India-US strategic cooperation, and the need to maintain the safety and security of sea lanes in the Indo-Pacific region. 2024 selection and editorial matter, Adluri Subramanyam Raju and R. Srinivasan. All rights reserved. -
Maulana Abul Kalam Azad
Maulana Abul Kalam Azad was a profound and rare Islamic scholar, writer, thinker, freedom fighter who promoted the idea of 'universal humanism'. He was well versed in poetry, art and music besides having a flair for writing. He was a multi-faceted personality with a progressive outlook. Though he had a rationalist outlook, he was very well versed in Islamic lore and history. His view of Islam did not necessarily come into conflict with territorial nationalism, Pan-Islamism and anti-imperialism. In this sense, he had interpreted Islam from a rationalist perspective. Maulana Azad had given a clarion call to the Muslims to join hands with the Hindus to achieve the common goal of ending British rule and domination in India. In fact, he considered this as the duty of the Indian Muslims, because according to him Muslims were created not for despondency but for 'hope'. As a revolutionary journalist the Maulana heralded a new era in Urdu journalism. His weekly 'Al-Hilal' grew in readership to such an extent that ultimately the British Government had to ban it. This chapter will analyse the thoughts, ideas and contribution of Maulana Azad to the freedom movement and nation-building in the post-independent India. Springer Nature Singapore Pte Ltd. 2022. All rights reserved. -
Cooperative Federalism in South Asia and Europe: Contemporary Issues and Trends
This book explores the challenges, opportunities, and trends impacting the working of federations in South Asia and Europe. It deliberates on the changing socio-economic realities, challenges facing the existing structures of governance, degrees of consociationalism, and the growing aspirations of people in South Asia and Europe.Through case studies from Greece, Germany, Austria, Switzerland, Spain, France, Sri Lanka, Pakistan, Nepal, Maldives, Bhutan, and India, the volume focuses on critical issues relating to cooperative federalism its complexities, institutional dilemmas, and trends in South Asia and Europe. It discusses a variety of themes relevant to Cooperative Federalism including federal-state relations; cooperative governance; constitution; multiculturalism, fiscal relations, democratization, devolution of powers, consociationalism, and global citizenship in South Asia and Europe. The book further emphasizes the need to strike a balance between the federal government and the constituent units in these two regions. Topical and lucid, this book will be of interest to teachers, scholars, and researchers of political science, comparative government and politics, federalism, South Asian politics, European politics, governance studies, and political studies. 2024 selection and editorial matter, M.J. Vinod, Stefy V Joseph, Joseph Chacko Chennatuserry and Dimitris N. Chryssochoou; individual chapters, the contributors. -
INTRODUCTION
The twenty-first century has been witnessing a global federal resurgence, distinguished by conversations focusing on interdependencies, multiculturalism, overlapping jurisdictions, multilateralism, multiple centres of policy-making and multiple notions of citizenship. Any assessment of cooperative federalism needs to go beyond institutional structures by incorporating images of diversity, pluralism, identity, issues of empowerment and democratization. Cooperative federalism facilitates cooperation among the national, state and local governments. It perceives the federation and the states as complementary parts of an arrangement where sovereignty is shared. 2024 selection and editorial matter, M.J. Vinod, Stefy V Joseph, Joseph Chacko Chennatuserry and Dimitris N. Chryssochoou; individual chapters, the contributors. -
THE FEDERAL DYNAMICS OF INDIAN FOREIGN POLICY: Issues, Concerns and Trends
Participation of regional governments in foreign policy is a global phenomenon, which has been described as constituent diplomacy or Para diplomacy. It is a phenomenon that includes a cocktail of factors like globalisation, economic liberalisation, diffusion of technology and the decentralisation of political power. Dependence of coalition governments on regional parties in India has resulted in a subtle power shift when it comes to foreign policy prioritisation and perceptions. There is a new activism in the making and implementation of Indian foreign policy. The chapter analyses the domestic imperatives impacting on India's foreign policy. The assertion and expectations of regional parties have been contingent on the leverage they have within a coalition like the NDA and the UPA. States are now even bringing foreign and security issues to the bargaining table, thereby providing the regional parties a variety of participatory opportunities. Conduct of India's foreign policy is no longer the exclusive domain of the federal government in India. At any given time, domestic compulsions influence how states act and react to various foreign policy issues and events, and hence engaging state governments in foreign affairs can be a force multiplier for Indian foreign policy. 2024 selection and editorial matter, M.J. Vinod, Stefy V Joseph, Joseph Chacko Chennatuserry and Dimitris N. Chryssochoou; individual chapters, the contributors. -
Monetary policy announcement and stock price behaviour: An event study with respect to India
Monetary policy in a developing country plays a significant role in achieving the objectives of macroeconomic policies. The Central Bank formulates and implements the monetary policy in a country which in turn facilitates the increase in growth rate, manages interest rates, and money supply in the economy. The primary objective of this paper is to test the semi-strong form of Efficient Market Hypothesis in the Indian Stock Market with respect to financial services industry by conducting an event study. The monetary policy announcements made from 11th March 2016 to 30th August 2019 are taken as the events. The event study methodology is conducted on 13 financial service companies listed in NSE Financial Services Index. The Average Abnormal Return (AAR) and Cumulative Average Abnormal Return (CAAR) are estimated using the daily closing price of the sample companies and Nifty. Two sample T-statistics are used to find the significance of the returns generated. The t-values of a majority of AARs and CAARs are significant suggesting that there is a scope for generating abnormal return by the investors on the event of the monetary policy announcement. It is found that the investors are able to earn abnormal profits which indicate that the Indian stock market is not efficient in the semi-strong form due to the slow absorption of information. IJSTR 2020. -
Inorganic Nanoparticles in Cosmetics
Inorganic nanomaterials of different chemical compositions and morphologies have been applied in cosmetic products due to their size- and shape-dependent properties which can improve the performance of the products. This chapter discusses the application of inorganic nanoparticles in cosmetic products with an emphasis on the characteristic features of nanoparticles suitable for cosmetic applications. In particular, applications of inorganic nanoparticles as UV filters and antimicrobial materials are discussed in detail with a basic overview of the fundamental scientific basis related to these applications. Types of nanoparticles used in commercial cosmetic products are enlisted, reflecting the range of applications and property modifications. Applications of inorganic nanoparticles in cosmetic formulations as active components and nanocarriers are also discussed along with relevant examples. Springer Nature Switzerland AG 2019. -
A study on the role of academic web application among children an analysis through parents /
The education systems in today’s world have greatly changed with the emergence of new technologies. With the advent of digital media, variety of applications are developed which aid the children to step into their primary education. This research paper aims at finding out the role of such academic web applications among children. -
India's Role as a Net Security Provider in the Indian Ocean Region: Issues, Challenges, and Trends
Since former US Defense Secretary Robert Gates introduced the term 'net security provider' at the Shangri La Dialogue in 2008, India's role as a net security provider in the Indian Ocean Region (IOR) has been much discussed and deliberated. The chapter tries to specify and elaborate on what this entails for India and the countries in the IOR. India's strategic location in the IOR provides distinct advantages and challenges. India cannot remain indifferent to the evolving maritime geopolitics of the region, as well as its geoeconomic interests. Over the years, India's aspiration to be a net security provider in the IOR has been much debated. It reflects India's desire to enhance its strategic presence and reach in the IOR and beyond. An assessment of India's maritime doctrine and strategy is also imperative to understand India's role in the IOR. India's intent to be a net security provider in the IOR has to be backed up by a clear strategy as well as intent. It will also be circumscribed by regional security constraints. The chapter looks at many issues, events, and developments that impact India's role as a net security provider in the IOR, viz., capacity building and enhancement, maritime diplomacy and engagement, maritime security operations, deployment of maritime forces, humanitarian assistance, and disaster relief. 2025 Adluri Subramanyam Raju and R. Srinivasan. All rights reserved. -
Vimana /
Patent Number: 202241030155, Applicant: Ramesh Chandra Poonia.
Drone navigation works by building a map of its surroundings while tracking its position within the map. This allows the drone to demonstrate positional accuracy (the global average URE (User error rate) across all satellites) of < 0.643 m (2.1 ft.) 95% of the lime using the Global Positioning System (GPS). The problem with this technology is twofold. It deploys only L band communication in practice. -
Framework based on IoT, AI, and blockchain for smart access to government agricultural schemes
Agriculture plays an important part in most countries, such as India. A survey says that 54.6% of the total labor force of India is engaged in agriculture and its connected activities. The government is announcing many schemes to facilitate agriculture and support farmers. But most of the farmers are from poor families and are not able to reach the government schemes when they are really in need. Also, it is required to observe and measure the inter and intra-field variability in crops to enjoy the complete benefits of government schemes. This can be done with the advancements in the field of the Internet of Things. Information related to the impact of natural calamities on the agricultural field, malfunctions in the machinery used for cropping, yielding level, and health status of crops can be measured using the technology of IoT (Internet of Things) and analyzed using AI (Artificial Intelligence). Blockchain plays a critical role in replacing traditional means of data storage and exchanging agricultural data with a more trustworthy, immutable, transparent, and decentralized approach. By keeping all the transactions related to government schemes in blockchain, the possible crimes in the form of false data by the intermediate dealers acting between the farmers and the government can be addressed. This, in turn, allows useful government schemes to reach the farmer in time. We propose to develop a theoretical model using IoT, AI, and blockchain, which can assist the farmers in benefitting from the appropriate schemes announced by the government in time and achieving precise agriculture. 2024 Bentham Science Publishers. All rights reserved. -
Theoretical Framework for Blockchain Secured Predictive Maintenance Learning Model Using Digital Twin
The automotive sector benefits from Digital Twins (DTs), software replicas of physical assets or processes. DTs enable engineers and data scientists to obtain deeper insights into the system and solve the most difficult problems faster and more affordably. Blockchain technology is a developing and exciting technology that has the potential to offer DTs monitoring capabilities, strengthening security and enhancing DTs transparency, dependability, and immutability. Intelligent behavior can be integrated into blockchain-based DTs to foresee important maintenance tasks and successfully manage machine functions. Our research involves creating a theoretical framework that leverages emerging technologies such as blockchain, artificial intelligence and DTs to facilitate resolution in the predictive maintenance of industry machines with minimised governing cost. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Integrity assured multi-functional multi-application secure data aggregation in wireless sensor networks (IAMFMA-SDA)
Industrial revolutions and demand of novel applications drive the development of sensors which offer continuous monitoring of remote hostile areas by collecting accurate measurement of physical phenomena. Data aggregation is considered as one of the significant energy-saving mechanism of resource constraint Wireless Sensor Networks (WSNs) which reduces bandwidth consumption by eliminating redundant data. Novel applications demand WSN to provide information about the monitoring region in multiple aspects in large scale. To meet this requirement, different kinds of sensors of different parameters are deployed in the same region which in turn demands the aggregator node to integrate diverse data in a smooth and secure manner. Novelty in applications also requires Base station (BS) to apply multiple statistical functions. Hence, we propose to develop a novel secure cost-efficient data aggregation scheme based on asymmetric privacy homomorphism to aggregate data of multiple parameters and facilitate the BS to compute multiple functions in one round of data collection by providing elaborated view of monitoring region. To meet the claim of large scale WSN which requires dynamic change in size, vector-based data collection method is adopted in our proposed scheme. The security aspect is strengthened by allowing BS to verify the authenticity of source node and validity of data received. The performance of the system is analyzed in terms of computation and communication overhead using the mathematical model and simulation results. 2023 - IOS Press. All rights reserved. -
Discrete Integrity Assuring Slice-Based Secured Data Aggregation Scheme for Wireless Sensor Network (DIA-SSDAS)
In a wireless sensor network, data privacy with a minimum network bandwidth usage is addressed using homomorphic-based data aggregation schemes. Most of the schemes which ensure the end-to-end privacy provide collective integrity verification of aggregated data at the receiver end. The presence of corrupted values affects the integrity of the aggregated data and results in the rejection of the whole data by the base station (BS) thereby leading to the wastage of bandwidth and other resources of energy constraint wireless sensor network. In this paper, we propose a secured data aggregation scheme by slicing the data generated by each sensor node deployed in layered topology and enabling en route aggregation. Novel encoding of data and hash slices based on child order is proposed to enable concatenation-based additive aggregation and smooth extraction of slices from the aggregate by the BS. Elliptic curve-based homomorphic encryption is adopted to ensure end-to-end confidentiality. To the best of our knowledge, the proposed scheme is the first which facilitates the BS to perform node-wise integrity verification, filter out only the corrupted portion, and implement dynamic query over the received data. Communication- and computation-based performance analysis shows the efficiency of the proposed scheme for varied network sizes. The scheme can resist eavesdropping attack, node compromising attack, replay attack, malleability attack, selective dropping attack, and collusion attack. 2021 D. Vinodha and E. A. Mary Anita. -
A novel multi functional multi parameter concealed cluster based data aggregation scheme for wireless sensor networks (NMFMP-CDA)
Data aggregation is a promising solution for minimizing the communication overhead by merging redundant data thereby prolonging the lifetime of energy starving Wireless Sensor Network (WSN). Deployment of heterogeneous sensors for measuring different kinds of physical parameter requires the aggregator to combine diverse data in a smooth and secure manner. Supporting multi functional data aggregation can reduce the transmission cost wherein the base station can compute multiple statistical operations in one query. In this paper, we propose a novel secure energy efficient scheme for aggregating data of diverse parameters by representing sensed data as number of occurrences of different range value using binary encoded form thereby enabling the base station to compute multiple statistical functions over the obtained aggregate of each single parameter in one query. This also facilitates aggregation at every hop with less communication overhead and allows the network size to grow dynamically which in turn meets the need of large scale WSN. To support the recovery of parameter wise elaborated view from the multi parameter aggregate a novelty is employed in additive aggregation. End to end confidentiality of the data is secured by adopting elliptic curve based homomorphic encryption scheme. In addition, signature is attached with the cipher text to preserve the data integrity and authenticity of the node both at the base station and the aggregator which filters out false data at the earliest there by saving bandwidth. The efficiency of the proposed scheme is analyzed in terms of computation and communication overhead with respect to various schemes for various network sizes. This scheme is also validated against various attacks and proved to be efficient for aggregating more number of parameters. To the best of our understanding, our proposed scheme is the first to meet all of the above stated quality measures with a good performance. 2020, Springer Science+Business Media, LLC, part of Springer Nature. -
Blockchain-Based Digital Twin for Predictive Maintenance of Machines Using Machine Learning
Digital Twin (DT) is a software replica of the physical asset or process that serves the automobile industry by empowering engineers and data scientists to gain a deeper insight into the system and solve the biggest challenges with less time and cost. Blockchain technology is an evolving and promising technology that foresees providing surveil -lance facilities for DTs, resulting in firming up security and improving the openness, reliability, and unchangeability of DTs. By incorporating intellectual behavior in blockchain-based DTs, the functions of machines can be governed parallelly, and the major maintenance activities can be predicted effectively. This chapter explores the design of various frameworks using recent technologies. Some of them are DTs, blockchain, artificial intelligence, and the Internet of Things which drive resolution in the industry to minimize the governing cost of machines. 2025 by Apple Academic Press, Inc. -
Data Driven Emergency Response Management for UAV-Based Future Transportation A Case Study
The transportation sector plays a vital role and is heavily involved in emergency response and disaster relief because of the necessity for quick deployment, evacuation and rescue operations, supply chain support, infrastructure restoration, aerial support and surveillance, traffic management, and route optimization, among other things. All of these are areas that can greatly benefit from the use of drones. The capabilities of drones provide an efficient and speedy option for surveying impacted regions, spotting possible dangers, finding survivors, accessing dangerous or inaccessible locations, delivering supplies, and generally facilitating relief efforts with speed and minimal human risk. UAV (Unmanned aerial vehicle)-based transportation can become a precise substitute for time-sensitive items, emergency relief, medical supplies, and more by overcoming obstacles like traffic and geographical accessibility. The success of emergency response management for UAV-based transportation is dependent upon the quality of the data collected and the effectiveness of its analysis and interpretation. Hence, in this chapter, we propose to analyze and explore the challenges and issues involved in the design and implementation of a data-driven emergency response management system for UAV-based future transportation and its applications. 2026 Scrivener Publishing LLC.