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Parallel organizations and subversion of the grass-roots democracy in Andhra Pradesh
[No abstract available] -
On Automatic Target Recognition (ATR) using Inverse Synthetic Aperture Radar Images
Inverse Synthetic Aperture Radar (ISAR) is used to image sea surface targets during day/night and all-weather capabilities for applications such as coastal surveillance, ship self-defense, suppression of drug trafficking etc. Hence automating classification of ships by means of machine learning methods has become more significant. Typical classification approaches consist of pre-processing, feature extraction and processing by classifiers. Image processing techniques are applied for pre-processing ISAR images. Transformation invariant features are then extracted to which classifiers such as SVM, Neural Networks (NNs) are applied. The performance of these algorithms depend on the manually chosen features and is trained to perform well for different target profiles. The target image (profile of target) varies depending on the target type, aspect angle and motion introduced due to different sea states. In addition, Deep learning methods are also being explored for classification of ships. The challenge is to classify ships for different sea conditions and image acquisition parameters with limited database and processing resource. 2023 IEEE. -
GeneRiskCalc: a web-based tool for genetic risk association analysis in casecontrol studies
Background: Genetic association studies play a pivotal role in identifying disease-associated variants, but researchers face challenges in performing essential calculations like HardyWeinberg equilibrium testing, odds ratios, and confidence intervals due to reliance on manual methods or multiple software tools. We aimed to develop GeneRiskCalc, an integrated web-based platform that simplifies genetic association analysis by automating HardyWeinberg equilibrium assessment, odds ratios with confidence interval calculation, and visual data presentation in casecontrol studies. Using an HTML/CSS/JavaScript framework, we developed online software with three core functionalities: (1) automated HWE evaluation, (2) odds ratio with 95% confidence interval computation with statistical validation, and (3) dynamic Forest Plot generation for data visualization. The tool was designed with an intuitive interface to minimize prerequisite statistical expertise. Results: The tool, named the Genetic Risk Association Calculator (GeneRiskCalc), demonstrated high computational accuracy in HWE testing (?2 validation) and association metrics (odds ratio and confidence interval). The results were cross-validated against established statistical methods, confirming their reliability. Furthermore, the integrated Forest Plotter enabled immediate visualization of effect sizes across multiple genetic models, facilitating a comprehensive interpretation of genetic associations. Conclusion: By integrating essential analytical steps into a single platform, the GeneRiskCalc, streamlines genetic epidemiology workflows, addressing key challenges in data analysis. Its user-friendly interface enhances accessibility, promotes reproducibility, and accelerates research in genetic association studies. The tool is freely available at GeneRiskCalc (https://sites.google.com/view/GeneRiskCalc/home?authuser=0). The Author(s) 2025. -
Some new results on equitable coloring parameters of graphs
An equitable coloring of a graph G is a proper vertex coloring C of G such that the cardinalities of any two color classes in G with respect to C differ by at most one. Coloring the vertices of a graph G subject to given conditions can be considered as a random experiment. In this context, a discrete random variable X can be defined as the color of a vertex chosen at random, with respect to the given type of coloring of G and a probability mass function for this random variable can be defined accordingly. In this paper, we discuss two statistical parameters of the powers of certain graph classes with respect to their equitable colorings. 2019, Univerzita Komenskeho. All rights reserved. -
The sparing number of certain graph powers
Let N0 be the set of all non-negative integers and P(N0) be its power set. Then, an integer additive set-indexer (IASI) of a given graph G is an injective function f : V(G) ! P(N0) such that the induced function f+ : E(G) ! P(N0) deffned by f+(uv) = f(u) + f(v) is also injective. An IASI f is said to be a weak IASI if jf+(uv)j = max(jf(u)j; jf(v)j) for all u; v 2 V(G). A graph which admits a weak IASI may be called a weak IASI graph. The set-indexing number of an element of a graph G, a vertex or an edge, is the cardinality of its set-labels. The sparing number of a graph G is the minimum number of edges with singleton set-labels, required for a graph G to admit a weak IASI. In this paper, we study the admissibility of weak IASI by certain graph powers and their corresponding sparing numbers. 2019 Sciendo. All rights reserved. -
The sparing number of the powers of certain Mycielski graphs
In this paper, we discuss the sparing number of the power graphs of the Mycielski graphs of certain graph classes. Journal Algebra and Discrete Mathematics. -
Arithmetic integer additive set-valued graphs: A creative review
For a non-empty ground set X, finite or infinite, the set-valuation or set-labeling of a given graph G is an injective function f: V (G) ? P(X), where P(X) is the power set of the set X. A set-indexer of a graph G is an injective set-valued function f: V (G) ? P(X) such that the function f?: E(G) ? P(X) ? { defined by f? (uv) = f (u)? f (v) for every uv?E(G) is also injective, where ? is a binary operation on sets. Let N0 be the set of all non-negative integers and P(N0) is its power set. An integer additive set-labeling (IASL) of a graph G is an injective function f: V (G) ? P(N0) such that the induced function f+: E(G) ? P(N0) is defined by f+ (uv) = f (u) + f (v), where f (u) + f (v) is the sumset of the sets f (u) and f (v). An IASL f of a graph G is said to be an integer additive set-indexer (IASI) of G if the induced function f+ is also injective. In this paper, we critically and creatively review the concepts and properties of a particular type integer additive set-valuation, called arithmetic integer additive set-valuation of graphs. 2020 the author(s). -
On the rainbow neighbourhood number of Mycielski type graphs
A rainbow neighbourhood of a graph G is the closed neighbourhood N[v] of a vertex v ? V (G) which contains at least one colored vertex of each color in the chromatic coloring C of G. Let G be a graph with a chromatic coloring C defined on it. The number of vertices in G yielding rainbow neighbourhoods is called the rainbow neighbourhood number of the graph G, denoted by rX(G). In this paper, we discuss the rainbow neighbourhood number of the Mycielski type graphs of graphs. 2018 Academic Publications. -
A Review of Smart Grid Management Systems Using Machine Learning Algorithms for Efficient Energy Distribution
The smart grid is an intelligent electricity network that uses digital technology to improve the efficiency, reliability, and sustainability of power delivery. Machine learning is a type of artificial intelligence that can be used to analyze data and learn from it. This makes it a valuable tool for the smart grid, as it can be used to solve a variety of problems, such asorecasting energy demand, detecting, and preventing outages, optimizing power flows, managing distributed energy resources, ensuring grid security.In this article, we will review the use of machine learning in the smart grid. We will discuss the different machine learning algorithms that are being used, the challenges that need to be addressed, and the future of machine learning in the smart grid.. The Authors, published by EDP Sciences, 2024. -
A Secure Data Encryption Mechanism in Cloud Using Elliptic Curve Cryptography
Cloud computing is undergoing continuous evolution and is widely regarded as the next generation architecture for computing. Cloud computing technology allows users to store their data and applications on a remote server infrastructure known as the cloud. Cloud service providers, such Amazon, Rackspace, VMware, iCloud, Dropbox, Google's Application, and Microsoft Azure, provide customers the opportunity to create and deploy their own applications inside a cloud-based environment. These providers also grant users the ability to access and use these applications from any location worldwide. The subject of security poses significant challenges in contemporary times. The primary objective of cloud security is to establish a sense of confidence between cloud service providers and data owners inside the cloud environment. The cloud service provider is responsible for ensuring user data's security and integrity. Therefore, the use of several encryption techniques may effectively ensure cloud security. Data encryption is a commonly used procedure utilised to ensure the security of data. This study analyses the Elliptic Curve Cryptography method, focusing on its implementation in the context of encryption and digital signature processes. The objective is to enhance the security of cloud applications. Elliptic curve cryptography is a very effective and robust encryption system due to its ability to provide reduced key sizes, decreased CPU time requirements, and lower memory utilisation. 2024 IEEE. -
Designing a Precision Seed Sowing Machine for Enhanced Crop Productivity
A seed sowing machine is a valuable agricultural device that facilitates the precise and efficient sowing of seeds in fields. When designing and optimizing such a machine, several crucial factors need consideration including seed size, seed rate, soil type, and field conditions. The primary objective is to achieve uniform seed distribution and optimal seed-to-soil contact, which can be accomplished by incorporating a seed metering mechanism to control the seed rate accurately. Versatility is another important aspect of the machine's design, as it should be able to handle different seed sizes, types, soil conditions, and field variations. To achieve this, utilizing advanced technologies such as sensors, automation, and precision farming techniques can significantly enhance the machine's performance and efficiency while also reducing costs and minimizing environmental impact. The optimization of a seed sowing machine plays a crucial role in ensuring successful crop production. By implementing cutting-edge technologies and precision farming techniques, farmers can increase their yields and decrease the amount of seed and fertilizer needed for a specific area. Ultimately, this leads to improved productivity, increased profitability, and a more sustainable approach to agriculture. 2024 E3S Web of Conferences -
Enhancing Data Security Through Semi-parametric Shrinkage Estimation of Shannon and Past Entropy in Geometric Distributions
The concept of entropy has been introduced in statistical methods to measure the amount of information contained in a random observation, and it plays a crucial role in various fields, especially in data security. This paper focuses on the semi-parametric shrinkage estimation of Shannon entropy and past entropy measures of the geometric distribution under complete, right, and time-censored sampling procedures. Shannon entropy, a key measure of uncertainty, along with past entropy (or min-entropy), which assesses the least predictable outcomes, plays a crucial role in ensuring strong data security, particularly in cryptographic systems and secure communications. While most existing literature addresses estimating these entropy measures for continuous distributions, this paper evaluates shrinkage estimators to enhance the efficiency of the ordinary semi-parametric least squares estimator for geometric distributions. This study explores the constant shrinkage factor and modified Thomson-type estimators, evaluating their effectiveness against traditional methods such as maximum likelihood estimators. Empirical investigations conducted with simulated samples indicate that shrinkage estimators consistently outperform maximum likelihood estimators, showcasing better relative efficiency. These results emphasize the potential of shrinkage estimators to enhance entropy-based measures in data security applications, which can lead to more robust cryptographic key generation, password strength analysis, and intrusion detection. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Artificial Intelligence Driven Drug Delivery Systems: Recent Advances and Emerging Trends
Drug Delivery Systems (DDS) play a critical role in ensuring the therapeutic efficacy and safety of pharmaceutical agents. Conventional drug delivery approaches often suffer from limitations such as poor bioavailability, non-specific targeting, and systemic toxicity. Recent advancements in Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) have revolutionized the design and optimization of drug delivery platforms. AI-driven methods enable predictive modeling, intelligent nanocarrier design, and personalized therapeutic strategies by analyzing large biomedical datasets. These technologies facilitate optimized drug formulation, controlled release mechanisms, and targeted delivery, thereby improving treatment outcomes. AI algorithms such as Support Vector Machines (SVM), random forests, Convolutional Neural Networks (CNN), and reinforcement learning are increasingly applied in nanoparticle design, pharmacokinetic modeling, and clinical decision support systems. Additionally, emerging concepts such as self-driving laboratories, autonomous drug delivery systems, and AI-guided nanomedicine are reshaping pharmaceutical research. This review provides a comprehensive analysis of recent advances in AI-driven drug delivery systems, covering computational techniques, nanocarrier optimization, clinical applications, and emerging research trends. Comparative analysis tables summarize key algorithms, delivery platforms, and research developments reported in the literature. Finally, major challenges including data quality, regulatory issues, and interpretability of AI models are discussed along with future directions for the integration of AI in precision medicine and smart therapeutics. 2026, Dr. Yashwant Research Labs Pvt. Ltd. All rights reserved. -
Green synthesis and electrochemical characterization of rGOCuO nanocomposites for supercapacitor applications
Reduced graphene oxide (rGO) were prepared from graphene oxide (GO) by using piperine as a green reducing agent extracted from Piper nigrum. The obtained rGO had few defects and lacked connectivity between the layers. To overcome these defects, copper oxide (CuO) nanoparticles were synthesized ultrasonically and nanocomposites of rGOCuO were prepared. The conductivities of the rGO, CuO and rGOCuO nanocomposites were determined by AC impedance spectroscopy in different electrolytes. Morphology, composition and electronic structure of CuO, rGO and rGOCuO nanocomposites were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photon spectroscopy (XPS) and electrochemical techniques. Transmission electron microscopy (TEM) images portrait CuO as a fish caught in the net of rGO layers. The rGOCuO nanocomposite exhibiting lower resistance and higher capacitance was used in fabrication of supercapacitor electrodes. The specific capacitance of the fabricated supercapacitor was found to be 137Fg?1. The supercapacitor performance of the nanocomposite electrode is attributed to the synergistic effect of double-layer capacitance of rGO and redox capacitance of CuO nanoparticles. [Figure not available: see fulltext.] 2016, Springer-Verlag Berlin Heidelberg. -
Investigations on thermo-mechanical properties of organically modified polymer clay nanocomposites for packaging application
Eco-friendly packing polymer materials are in the spotlight but, lack of new biodegradable polymers either natural or synthetic is yet to establish the market more competitively. So, in the present work, clay as a nano-filler is embedded and organically modified in some synthetic and natural polymers which are well established commercially to enhance their biodegradability. The impact of clay on the properties of synthetic polymers namely, poly(methyl methacrylate) (PMMA), poly(vinyl chloride) (PVC), poly(vinyl acetate) (PVAc) and natural polymer cellulose acetate butyrate (CAB) was studied. Results from differential scanning calorimetric (DSC) showed a decrease in the glass transition temperature of organically modified polymer clay nanocomposites (PCC) than pure polymers. Scanning electron microscopy (SEM) displayed a uniform surface with small-sized crystallites distributed on the polymer surface. X-ray diffraction (XRD) spectra revealed the formation of enhanced intercalated structures in PCC. Furthermore, FTIR studies showed that the interlayer bonding (SiO bands) of pure clay is deformed in PCCs. The tensile strength of PCC increased with an increase in organo-clay loading. This unique mechanical behavior is due to the agglomeration of organo-clay particles. Finally, the biodegradation studies revealed enhanced hydrolytic degradation in PCC than pure polymers. Hence, these PCCs are environmentally friendlier than their pure synthetic polymers without significant compromise in their properties, which makes it suitable for packaging industries. The Author(s) 2020. -
Supercapacitor studies of activated carbon functionalized with poly(ethylene dioxythiophene): Effects of surfactants, electrolyte concentration on electrochemical properties
Electropolymerization of poly(ethylene dioxythiophene) (PEDOT) on activated carbon (AC) was performed using different surfactants such as anionic surfactant (sodium dodecyl sulfate), protonic surfactant (camphor sulphonic acid) and non-ionic surfactant (Triton) in 0.1 M H2SO4. The effects of concentration of different surfactants for electrodeposition of PEDOT on AC were analyzed using electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and SEM techniques. Supercapacitors (SC) were fabricated using AC/PEDOT composite electrodes and 0.1 M H2SO4 as an electrolyte. The specific capacitance (Cs) values were calculated using CV at different concentrations of surfactants, electrolytes and variation of potential. The electrolyte containing 0.1 M H2SO4 and 0.02 M camphor sulphonic acid showed to have the highest specific capacitance value of 240 Fg?1 than other surfactant based SCs. Galvanostatic charge/discharge at varying current density were performed on SCs containing different surfactant based electrodes to study their cyclic stability. 2020 -
Emerging Cyber Threats in 5G and Beyond: A Wireless Communication Perspective
There are digital age threats to cybersecurity that cost organizations and businesses their infrastructure, operations, and even sensitive data. Cybersecurity risk management is important to ensure that organizational assets are not subjected to cyberattacks, data breaches, and any other vulnerability. This paper also looks at other significant risk-reduction strategies, including threat intelligence, models of risk assessment, encryption, access control systems. It also talks about how machine learning and artificial intelligence can help improve the way threats are detected and handled. Organizations should take a proactive and layered approach to security that integrates leading-edge security methods, with regulatory compliance processes and employee awareness programs. Also, regular security checking, incident response plans and consistent monitoring help in reducing risks and business continuity. Organisations must continue to adjust as cyber threats change, utilizing cutting-edge cybersecurity solutions to fortify their defenses. Organisations may create robust security structures in a continuously linked and threatprone digital environment by using the perspectives this research offers on efficient risk management techniques. 2025 IEEE. -
Green synthesis and electrochemical characterization of rGO–CuO nanocomposites for supercapacitor applications /
Lonics, Vol.23, Issue 5, pp.1267–1276, ISSN: 9477047. -
Deconstruction of representation of working women in Indian femvertisements /
Femvertisements are advertisements wherein brands use the concepts of feminism, women empowerment etc. These advertisements talk about breaking the stereotypes that women are confined to in our society. The irony comes when these empowering advertisements themselves have hidden stereotypes that invariably end up doing more harm than good. -
Revisiting television in India: Mapping the portrayal of women in soap operas /
Sociological Bulletin, Vol.67, Issue 2, pp. 204-219.