Browse Items (14421 total)
Sort by:
-
Natural Language Processing and Information Retrieval: Principles and Applications
This book presents the basics and recent advancements in natural language processing and information retrieval in a single volume. It will serve as an ideal reference text for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology. This text emphasizes the existing problem domains and possible new directions in natural language processing and information retrieval. It discusses the importance of information retrieval with the integration of machine learning, deep learning, and word embedding. This approach supports the quick evaluation of real-time data. It covers important topics including rumor detection techniques, sentiment analysis using graph-based techniques, social media data analysis, and language-independent text mining. Features: Covers aspects of information retrieval in different areas including healthcare, data analysis, and machine translation. Discusses recent advancements in language- and domain-independent information extraction from textual and/or multimodal data. Explains models including decision making, random walk, knowledge graphs, word embedding, n-grams, and frequent pattern mining. Provides integrated approaches of machine learning, deep learning, and word embedding for natural language processing. Covers latest datasets for natural language processing and information retrieval for social media like Twitter. The text is primarily written for graduate students and academic researchers in interdisciplinary areas of electrical engineering, electronics engineering, computer engineering, and information technology. 2024 selection and editorial matter, Muskan Garg, Sandeep Kumar and Abdul Khader Jilani Saudagar chapters. -
Self-assembled free nanocarrier prodrugs based on camptothecin and dihydroartemisinin exhibit accumulation and improved anticancer efficacy
Small molecule targeted inhibitor therapies often have several drawbacks, including limited oral bioavailability, quick metabolism, toxic effects that limit dosage, and poor water solubility. This study aims to develop a nanodrug self-delivery system that does not require a carrier by utilizing the self-assembly of camptothecin (CPT) and dihydroartemisinin (DHA). CPT/DHA nanoparticles (NPs) with varying diameters can be synthesized without requiring further carrier materials or chemical modifications by changing the CPT-to-DHA ratio (10:1, 5:1, 2:1, 1:1). Even more crucially, CPT/DHA NPs generate an AIE impact when they self-assemble. CPT/DHA NPs are used for cell tracking and bioimaging fluorescent probes. We chose CPT/DHA NPs (2:1) with a size of approximately 140nm for the anticancer examinations. The A549 cells were used to assess the cytotoxicity, morphological changes by biochemical staining methods and apoptosis by flow cytometric techniques of CPT/DHA NPs. Finally, in vitro anticancer research proved that CPT/DHA NPs are biocompatible and have strong synergistic anticancer properties. 2024 International Union of Biochemistry and Molecular Biology, Inc. -
Role of international commercial arbitration in resolving WTO disputes
International organizations flourished with the fragrance of effective interactions between parties and reconciliatory measures promoting amicable dispute settlement. In this scenario International Commercial Arbitration comes to the rescue of international organizations resolving multilateral, bilateral, and investment disputes between the parties, promoting sustainable development. The rationale of the article is to promote the parties towards a system of dispute redressal that is opposite to adversarial form of dispute resolution and thereby promoting an arbitration-friendly economy. Arbitration is not considered to be a preferable dispute resolution and the article provides for importance of arbitration in research gap in various research papers by using doctrinal research, analyzing articles and statutes, and providing an answer to the research question "How to promote sustainable development through International Commercial arbitration" and "How to promote arbitration-friendly environment. " This article discusses WTO dispute resolution board's novel approach to promoting arbitration. 2024 Srinesh Thakur, Anvita Electronics, 16-11-762, Vijetha Golden Empire, Hyderabad. -
Sustainable Development- Adopting a Balanced Approach between Development and Development Induced Changes
The emergence of globalization has raised serious concerns and promoted ever increasing dichotomy between development and climate change issues that are borne out of such trade development plans and strategies. The sustainable development goals embark on 17 broad categories that calls upon the nations to achieve them by 2030. In order to achieve these goals the need of the hour is to make a paradigm shift from traditional trade agreements and policies to such agreements that aim to prioritize the attainment of these goals. There has to be uniform environment laws to promote intergeneration and intra-generational equity among the nations and leaving no lacuna for geographical disparity. The Artificial Intelligence can play a pivotal role in achieving sustainability by cross fertilization of technology and sustainable development leading to smart states, effective utilization of resources, green investment policies, use of eff icacious renewable energy resources, analyzing agricultural needs and prior analyses of prospective disasters. The Electrochemical Society -
Energy Efficient Smart Scheduling for Multi-path Routing Using Deep Learning
Energy efficiency is a key part of networkingit saves on cost and has an environmental impact. Multi-path routing is a well-known technique used for network traffic management to make it more efficient and reliable. Unfortunately, traditional multi-path routing techniques are oblivious to energy and suffer from poor energy utilization. This paper: An approach to efficient smart scheduling for multi-path routing with deep learning. Employing a deep learning algorithm with relevant network parameters allows us to predict the lightest path for processing in/outbound data. Simulation results demonstrate that our solution guarantees higher energy efficiency than conventional algorithms while enjoying better network performance. This solution proposes the formulation of a green and sustainable networking approach. Thus, it can be better adopted as an innovative security mechanism in many practical scenarios. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Self-assembled free nanocarrier prodrugs based on camptothecin and dihydroartemisinin exhibit accumulation and improved anticancer efficacy
Small molecule targeted inhibitor therapies often have several drawbacks, including limited oral bioavailability, quick metabolism, toxic effects that limit dosage, and poor water solubility. This study aims to develop a nanodrug self-delivery system that does not require a carrier by utilizing the self-assembly of camptothecin (CPT) and dihydroartemisinin (DHA). CPT/DHA nanoparticles (NPs) with varying diameters can be synthesized without requiring further carrier materials or chemical modifications by changing the CPT-to-DHA ratio (10:1, 5:1, 2:1, 1:1). Even more crucially, CPT/DHA NPs generate an AIE impact when they self-assemble. CPT/DHA NPs are used for cell tracking and bioimaging fluorescent probes. We chose CPT/DHA NPs (2:1) with a size of approximately 140nm for the anticancer examinations. The A549 cells were used to assess the cytotoxicity, morphological changes by biochemical staining methods and apoptosis by flow cytometric techniques of CPT/DHA NPs. Finally, in vitro anticancer research proved that CPT/DHA NPs are biocompatible and have strong synergistic anticancer properties. 2024 International Union of Biochemistry and Molecular Biology, Inc. -
On StressStrength Reliability Estimation for the Generalized Inverted Exponential Distribution Under Unified Hybrid Censoring
Stressstrength reliability (SSR) analysis plays a fundamental role in reliability engineering, particularly when lifetime data are subject to censoring due to cost or time limitations. In this article, we study the estimation of the reliability parameter (Formula presented.) when the strength (Formula presented.) and stress (Formula presented.) follow the two-parameter generalized inverted exponential distribution (GIED) under a unified hybrid censoring (UHC) scheme, which ensures both a prespecified number of failures and a bounded test duration. Classical inference is developed via maximum likelihood estimation using the EM algorithm, and the corresponding asymptotic confidence intervals are obtained. Bayesian estimation is carried out using MCMC methods under a generalized entropy loss function, along with HPD credible intervals. The UMVUE of (Formula presented.) is also derived for comparison. A Monte Carlo simulation study is conducted to evaluate the performance of the proposed estimators under different censoring scenarios. The results indicate that Bayesian methods, particularly under informative priors, often provide improved estimation accuracy in heavily censored cases. Two real data sets are analyzed to demonstrate the practical applicability of the proposedmethodology. 2026 John Wiley & Sons Ltd. -
Harnessing the Future: Emerging AI Trends Shaping SME Growth in Emerging Markets
With AI revolutionizing industries, SMEs in emerging markets can tap into its power for sustainable growth, operational efficiency, and enhanced customer experiences. This chapter explores AI- driven automation, predictive analytics, and personalized interactions, addressing challenges like technical skills, data availability, and cost. By adopting AI strategically, SMEs can overcome barriers, compete globally, and drive innovation, ensuring long- term success in the evolving digital economy. 2026 by IGI Global Scientific Publishing. -
Enhancing Cybersecurity: Machine Learning Techniques for Phishing URL Detection
Phishing attacks exploit user vulnerabilities in cybersecurity awareness by tricking them to fake websites designed to steal confidential data. This study proposes a method for detecting phishing URLs using machine learning. The proposed method analyzes various URL characteristics, such as length, subdomain levels, and the presence of suspicious patterns, which are key indicators of phishing attempts. Gradient Boosting was selected due to its robustness in handling complex, non-linear relationships between features, making it particularly effective in distinguishing between legitimate and phishing URLs, by evaluating the Gradient Boosting classifier on a dataset with 10,000 entries and 50 features, the method achieves an accuracy of 99%.This approach has the potential to enhance web browsers with add-ons or middleware that alert users from potential phishing sites which will be based solely on URL. 2024 IEEE. -
Diaspora Experience Between the Creation and the Creator : A Closer Look at the Diaspora Connected Character in Anita Desai's 'Fasting, Feasting'
Quest International Multidisciplinary Research Journal, Vol-1 (2), pp. 83-86. ISSN-2278-4497 -
Exploring silenced subaltern voices of three-fold oppressed dalit women in Akkarmashi by Sharankumar Limbale : A postcolonial reading /
Roots International Journal Of Multidisciplinary Researches, Vol.2, Issue 3, pp.13-15, ISSN No: 2349-8684. -
Indias role in kazakhstans multi-vector foreign policy
?fter the disintegration of the Soviet Union, Kazakhstans economy was weak since most of the industrial en-terprises were located in Russia. To attain economic growth, Kazakhstan crafted a unique foreign policy known as the multi-vec-tor foreign policy, which facilitated an easy inflow of direct foreign investments into the state economy. After economic liberalization in 1991, India took a serious interest in Cen- tral Asia, and since then the two nations have come a long way marked by complex interde-pendence in the international arena. They have demonstrated a successful and sus-tained upward trend in their bilateral relationship through soft power, trade and long-standing historical connections. Thus, the prospects of mutual cooperation between Central Asia, particularly Kazakhstan, and India are quite promising in the near future. 2021, CA and C Press AB. All rights reserved. -
Precision Corn Price Prediction with Advanced ML Techniques
In the ever-evolving corn market, accurate price prediction is imperative for informed decision-making. This research introduces an innovative predictive model that integrates and external factors to enhance forecasting accuracy in the corn market. By exploring historical trends, comparing machine learning algorithms, and employing advanced feature selection methods, the study addresses the complexities of the corn market, emphasizing economic indicators, geopolitical events, and demand-supply dynamics. Informed by a literature review, the research underscores the necessity of dynamic models in corn price forecasting. Utilizing machine learning models such as linear regression, random forest, SVM, Adaboost, and ARIMA, coupled with the interpretability of SHAP values, the study aims to improve prediction accuracy in the corn market. With a robust methodology and comprehensive evaluation metrics (MAE, RMSE, MAPE), the research contributes valuable insights into corn market dynamics, providing a variable dictionary for clarity and emphasizing the strategic implications of the superior random forest model for stakeholders in the corn sector. 2024 IEEE. -
Technology Transfer, Innovation, and Equitable Development: A Business-Centric Approach
In an era of rapid technological innovation, significant global disparities in access persist, impeding sustainable development. This chapter examines technology transferthe dissemination of knowledge and tools across bordersas a catalyst for equitable growth. Analyzing mechanisms such as licensing, joint ventures, and FDI, it elucidates how businesses can utilize these strategies for market expansion addressing barriers including restrictive intellectual property regimes, cultural incongruities, and regulatory fragmentation. Case studies, encompassing Kenya's M-Pesa mobile payments and COVID-19 vaccine inequities, underscore the dual potential for empowerment and exploitation. The chapter posits the necessity for ethical frameworks that balance profit and equity, urging stakeholdersgovernments, corporations, and international bodiesto implement tiered pricing, reform IP laws, and invest in local capacity. Prioritizing inclusive innovation, technology transfer can mitigate disparities, unlock $12 trillion in market opportunities by 2030, ensuring progress benefits to humanity. 2025 by IGI Global Scientific Publishing. All rights reserved. -
ESG Narrative Quality in Green Bond Disclosures: Implications for Risk Perception, Transparency, and Market Trust
This research evaluates the extent to which firms green bond disclosures create and convey a meaningful representation of their Environmental, Social, and Governance (ESG) commitments. Additionally, this research explores how investors distinguish between disclosures that represent genuine commitment to sustainability and those that may be indicative of greenwashing, and how such distinctions impact their assessment of an issuers credibility as well as the issuers performance subsequent to the issuance of a green bond. The methodology employed in this research employs a convergent mixed-methods approach that combines quantitative methods (Natural Language Processing (NLP), financial modeling, etc.) with qualitative methodologies (case studies, interviews). The NLP methodology employed in this research includes sentiment analysis, topic modeling, and ambiguity measurement in order to determine the tone, thematic content, and linguistic clarity of the disclosure texts. Subsequently, the results of the NLP methodologies are correlated with firm level outcomes using cross validated partial least squares regression (PLS-R), event study methodologies, and one way ANOVA to test for temporal and industrial variability. Finally, the results of the computational and financial methodologies are supplemented by qualitative case studies and interviews to provide context for the patterns identified in the computational and financial methodologies. In summary, the results of this research demonstrate that firms that communicate in a clear, balanced, and verifiable manner experience better market reaction and more favorable accounting results subsequent to the issuance of a green bond than do firms whose communications are vague, overly optimistic, or lacking in consistency. Conversely, the findings suggest that investors have become increasingly sensitive to potential greenwashing and therefore are less likely to respond favorably to communications characterized by the aforementioned characteristics. 2025 by the authors. -
Intelligent Manufacturing Components, Challenges, and Opportunities
Intelligent Manufacturing shows transformative paradigms in the manufacturing industry; leveraging advanced technologies such as Artificial Intelligence (AI), Internet of Things (IoT), and robotics, to develop highly automated and adaptive production systems. This chapter outlines the Intelligent Manufacturing process, including its key principles, components, challenges, and opportunities. The combination of Machine Learning (ML) techniques and AI enables decision-making, real-time optimisation, and predictive analytics of manufacturing processes, productivity, and quality of products. Robotics and IoT devices play critical roles in enabling automation, data collection, and connectivity within Intelligent Manufacturing environments. Additionally, Digital Twin technology facilitates virtual simulation, modelling, and optimisation of production systems. While Intelligent Manufacturing offers significant benefits, it also presents challenges viz. high investments, integration complexity, and workforce reskilling requirements. Overcoming the challenges requires a holistic approach involving collaboration between industry stakeholders, government agencies, academia, and technology providers. Overall, Intelligent Manufacturing represents a promising future for the manufacturing industry, offering opportunities for innovation, competitiveness, and sustainable growth in a rapidly evolving global economy. 2025 selection and editorial matter, Alka Chaudhary, Vandana Sharma, and Ahmed Alkhayyat individual chapters, the contributors. -
Capitalizing on diversity: Role of entrepreneurial and firm attributes in rural MSMEs financial accessibility
Consistent access to credit from formal financial institutions has been a significant challenge for micro-, small, and medium-sized enterprises (MSMEs) in rural areas. Despite contributing to a majority of the workforce in the economy, their failure rates continue to rise. These often indicate an inadequacy in internal determinants, such as limited access to infrastructure, inefficient managerial competencies, low entrepreneurial orientation, and other firm-related attributes. This article investigates how entrepreneurial and firm-specific traits influence the financial accessibility of rural MSMEs in the northeastern state of Assam in India while also considering the role of credit rationing. The current study data were collected from MSME entrepreneurs and analyzed using thematic analysis to explore the variables impacting credit accessibility. The results reveal that entrepreneurial (motivation, education, entrepreneurial orientation) and firm characteristics (firm size, infrastructure, technical know-how) are critical in assessing lenders perception toward borrowers in the complex loan processes. 2025 International Council for Small Business. -
Taxonomic revision and molecular phylogeny of flemingia subgenus rhynchosioides (Leguminosae)
A taxonomic revision of Flemingia subg. Rhynchosioides based on morphology and molecular information (matK and ITS) is presented. The subgenus comprises six herbaceous taxa (F. gracilis, F. mukerjeeana, F. nilgheriensis, F. rollae, F. tuberosa and F. vestita). All species except F. vestita are endemic to India. Morphological evidence and molecular phylogeny revealed that the subgenus is monophyletic. Nevertheless, the systematic position of F. tuberosa remains unclear on account of its unique ecology and inflorescence. A new species, F. mukerjeeana, is described and four binomials, namely F. gracilis, F. nilgheriensis, F. tuberosa and F. vestita have been lectotypified. Furthermore, all species have been described, illustrated and their ecology discussed. A taxonomic key including the recently described species from Thailand, F. sirindhorniae, is also provided for easy identification. 2019 Naturalis Biodiversity Center. -
Defluoridation of Drinking WaterFluoride Wars
Fluorine is also known as two-edged sword. At lower doses, it influences tooth by inhibiting tooth caries, while in high doses, it causes dental and skeletal fluorosis. It is known that some quantity of fluoride is important for the formation of tooth enamel and mineralization in tissues. The present work aims at providing safe and potable water to rural areas where this element has created a menace. This work also suggests the use of few adsorbents such as paddy husk and coir pith which are affordable and removes fluorine to greater extent. The study concludes that materials which are used as adsorbents and can be safely inculcated as fluorine removal adsorbents which help people to have safe potable water. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Removal of Struvite in Wastewater Using Anammox Bacteria
Struvite precipitation in wastewater has proved to be an effective method in treating wastewater and has helped in the recovery of ammonia nitrogen and phosphate phosphorus. Nutrient recovery from wastewater has become a new trend attracting the interests of several researchers. Extraction of the nutrients based on struvite crystals as nutrition sources from wastewater has been acknowledged as a need of the hour solution to tackle the water pollution issue. This review focuses on the featured characteristics of struvite as a chemical fertilizer for plant and the struvite formation process related to physiochemical conditions in wastewaters. In the present work, struvite precipitation in the actual swine wastewater is studied by strategically controlling aeration, pH, and mixing of anammox bacteria. The effect of organic solids in the wastewater has also been studied. Laboratory experiments were conducted by optimizing pH value. pH was found to be an important parameter in the simultaneous removals of ammonium nitrogen and orthophosphate. This work reveals that the struvite removal from wastewater can be reduced to 80% using anammox bacteria. Springer Nature Singapore Pte Ltd. 2022.