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Novel hybrid metamaterial to improve the performance of a beamforming antenna
This paper investigates the design and implementation of a novel hybrid metamaterial unit cell to improve a beamforming Wi-Fi antenna's performance. The proposed metamaterial unit cell is created on an FR-4 substrate (?? = 4.4) and a thickness of 1.6 mm. The metallization height of the unit cell is maintained at 0.035 mm. The designed metamaterial unit cell is simulated using HFSS Ver. 18.2 to verify the double negative behaviour. The unit cell consists of five Split Ring Resonators (SRR's) at the bottom and a hexagonal ring of six triangles. Initially, a conventional inset fed microstrip patch antenna is designed then an array of the proposed unit cell is created and used as a superstrate to study the performance. A Three Element Antenna Array (TEAA) is designed to operate at 2.4 GHz Wi-Fi band, and the superstrate created out of the proposed unit cell is used to study its effect. Metamaterial superstrate improved the conventional Single Element Antenna (SEA) gain by approximately 2 dB. Superstrate with TEAA exhibited an improved gain of 1 dB over TEAA. Published under licence by IOP Publishing Ltd. -
Antenna Array Miniaturization using a Defected Ground Structure
A novel Defected Ground Structure (DGS) is proposed to miniaturize a 2 Modified Corporate Feed Planar Antenna Array (M-CFPA) with a modified corporate feeding network. The DGS altered the surface current distribution and shifted the resonance frequency to the lower side. After running a parametric sweep of length and width of the patch antenna element, achieved the miniaturized antenna array resonating at 2.4 GHz frequency. The proposed antenna array is designed using Rogers/RT Duroid 5,880 (2.2) substrate with a thickness of 1.6 mm. The overall dimensions of the proposed Planar Array with DGS (PA-DGS) is 25.2723 % lesser than M-CFPA. The M-CFPA has a peak gain of 11.53 dB with a-10 dB reflection coefficient bandwidth of 118 MHz. The proposed PA-DGS array exhibits a peak gain of 9.51 dB with 100 MHz-10 dB bandwidth. 2022, Walailak University. All rights reserved. -
High Gain Miniature Antenna Arrays for 2.4 GHz Applications
In this paper, miniature corporate feed Four Element Array (FEA), Eight Element Array (EEA) and Sixteen Element Array (SEA) are presented. The proposed antenna arrays are created on Rogers Duroid 5880 substrate with permittivity 2.2 and thickness of 0.782 mm. Initially, a single element antenna was created, then it was used in a corporate feed network designed for the 4-element array. As an extension, the 4-element array was used as a template and created an 8-element array and 16-element array to achieve high gain and directivity at 2.4 GHz. The proposed FEA, EEA, and SEA exhibit reflection coefficients of -25.55 dB, -37.14 dB, and -30.61 dB respectively. The peak gains obtained are 11.5 dB, 13.67 dB, and 16.76 dB respectively for FEA, EEA, and SEA. Also, the directivity has improved corresponding to the increase in the number of elements. Therefore, it can be a suitable candidate for applicationswhere extended range and coverage with better signal quality and higher data transfer rates is a priority. 2024 IEEE. -
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Green synthesis of zirconium phosphate by combustion method: photocatalytic application and microwave-assisted catalytic conversion of aldehyde to nitriles
Water pollution has increased swiftly, especially the dyes from industries that have disturbed aquatic eco-system. Photocatalytic degradation (PCD) is one of the attractive methods to eliminate dyes from industrial effluents. Zirconium phosphate (ZP) nanoparticles were synthesized by combustion method using zirconyl nitrate and phosphorous pentoxide as precursors. The obtained ZP was characterized by powder X-ray diffractogram, Fourier transform infrared, scanning electron microscopy, high-resolution transmission electron microscopy, Raman spectroscopy, photoluminescence spectroscopy, BrunauerEmmettTeller surface area. PCD was carried out using methylene blue as a model pollutant in aqueous medium in the presence of UV light irradiation with different concentrations of dye, catalyst and pH. Higher degradation efficiency was observed in basic medium. ZP is employed as a catalyst to form nitrides from aldehydes using different solvents with different aldehydes. Graphic abstract: [Figure not available: see fulltext.]. 2021, Indian Academy of Sciences. -
Mediating role of teacher confidence between support system and satisfaction
Online education in India has witnessed a shift due to the ongoing pandemic, compelling the Indian education sector to adapt to new advancements. The study's main purpose has been to find the relationship between the support systems of institutions, teachers support and students, leading to instructors' satisfaction. It further analyses the mediating role of educators' confidence in linking support systems and leading to teachers' satisfaction. The sample for our research consisted of 129 teachers from Higher Educational Institutions (HEIs). We found that there is a significant relationship between support systems and teacher satisfaction. Among the three support systems, institutions support had a significant influence. On the other hand, teachers' confidence had a partially mediating effect on their satisfaction, even though they could translate to higher effectiveness in online teaching. Further, this study inferred that educational institutions are quick to adapt to online teaching due to the ongoing pandemic. Copyright 2022 Inderscience Enterprises Ltd. -
Machine Learning-Driven Energy Management for Electric Vehicles in Renewable Microgrids
The surge in demand for sustainable transportation has accelerated the adoption of electric vehicles (EVs). Despite their benefits, EVs face challenges such as limited driving range and frequent recharging needs. Addressing these issues, innovative energy optimization techniques have emerged, prominently featuring machine learning-driven solutions. This paper reviews work in the areas of Smart EV energy optimization systems that leverage machine learning to analyse historical driving data. By understanding driving patterns, road conditions, weather, and traffic, these systems can predict and optimize EV energy consumption, thereby minimizing waste and extending driving range. Concurrently, renewable microgrids present a promising avenue for bolstering power system security, reliability, and operation. Incorporating diverse renewable sources, these microgrids play a pivotal role in curbing greenhouse gas emissions and enhancing efficiency. The review also delves into machine learning-based energy management in renewable microgrids with a focus on reconfigurable structures. Advanced techniques, such as support vector machines, are employed to model and estimate the charging demand of hybrid electric vehicles (HEVs). Through strategic charging scenarios and innovative optimization methods, these approaches demonstrate significant improvements in microgrid operation costs and charging demand prediction accuracy. The Authors, published by EDP Sciences, 2024. -
The Various Challenges Involved in Sensor Based Cloud System to Protect the Data and to Avoid Attacks: A Technical Review
In these studies, we introduce a unique protection framework for the integration of Wireless Sensor Networks (WSN) with cloud computing, aimed closer to enhancing statistics-centric programs consisting of far-flung healthcare structures. The framework's cornerstone is a robust, bendy safety version that ensures immoderate-degree information confidentiality, integrity, and terrific-grained get proper of access to control, addressing the important protection demanding situations in WSN-Cloud integration. By the use of a hybrid encryption mechanism that mixes the strengths of symmetric and uneven encryption techniques, our method gives a entire safety answer that protects information during transmission and garage. Furthermore, the version includes an efficient key manipulate gadget, facilitating the dynamic era and relaxed distribution of encryption keys. This contemporary framework is designed to mitigate common safety threats, such as Man-in-the-Middle (MITM) and Denial of Service (DoS) attacks, even as preserving the overall performance and standard performance of the blanketed gadget. Our research offers a massive contribution to securing statistics-centric packages in WSN-Cloud ecosystems, making sure dependable and comfortable facts verbal exchange and get right of entry to for a way off healthcare programs and past. 2024 IEEE. -
Weighted Mask Recurrent-Convolutional Neural Network based Plant Disease Detection using Leaf Images
Large losses in output, money, and quality/quantity of agricultural goods are incurred due to plant diseases. Seventy percent of India's GDP is tied to the agricultural sector, thus protecting plants from diseases is crucial. For this reason, it is important to keep an eye on plants from the moment they sprout. The usual approach for this omission is naked eye inspection, which is more time-consuming, costly, and requires significant skill. Thus, automating the method for detecting diseases is necessary to speed up this process. It is imperative that image processing methods be used in the creation of the illness detection system. Disease detection involves a number of processes, including Weighted Mask R-CNN, GLCM feature extraction, Multi-thresholding image pre-processing, and K means image segmentation classification. The weighted Mask R-CNN outperforms the standard RNN, the Mask R-CNN, and the CNN in terms of accuracy and recall in analytical trials by a significant margin. 2023 IEEE. -
Orhan pamuks the white castle as a text on secular discourse
The impact of religious thought and practice on literature and culture was very evident till the latter part of the nineteenth century. But with the publication of Darwins Origin of Species, voices of dissent were heard from the scientific and literary world. Writers strongly felt that the objective of literature was not to be dogmatic, but to provide the necessary ingredients that would contribute to a healthy and secular society. The emergence of postmodernism saw religion once again taking center stage. This paper seeks to understand what secularism is, and the evolution in meaning this term has undergone over the ages. In this process, the theories and ideas of religious and political thinkers are examined to understand the essence of the term secularism. In an era when religious fundamentalism is on the rise and literature is censured on religious or cultural grounds, the paper analyzes Orhan Pamuks The White Castle and concludes with the contention that the text can definitely be a source of secular discourse (which indeed is the essence of religious texts) that nations can emulate, contrary to the idea of narrow secular nationalism currently being propagated by States. IUP Publications. All rights reserved. -
An empirical study on the clients perspective in decision making with regard to lawyer selection for trial courts: Does grey hair matter?
In higher courts, statutory interpretation and persuasion of the court with new perspectives on legal principles are critical. Whereas, the main focus of the subordinate courts is on evidential underpinnings. Hence, the lawyers in all courts are an indispensable part of the judicial process and play a seminal role in the dispensation of justice. The existing literature demonstrates that engaging a senior lawyer increases the chances of winning cases. However, young lawyers today make their mark by establishing their own offices, succeeding in the profession, while some remain the dark horses of their incumbent seniors. Against this backdrop, the authors explore the clients perception of the lawyer selection process and the significance of lawyers age using a mixed methods approach. The data for this study was gathered from trial court clients using a convenient sampling method. The qualitative data were collected by conducting semi-structured interviews with clients. Interviews were analysed at a thematic level and broad themes were identified and used as constructs for a quantitative survey questionnaire. The quantitative data were analysed through Pearson correlation, regression analysis, and factor analysis. The study determined that lawyers efficiency is a key factor considered by trial court clients in selecting their lawyers. The results also revealed that there exists a significant positive correlation between the age of the lawyer and the clients decision making when choosing their lawyers. In the end, the implications of the findings are discussed. 2022, The Author(s), under exclusive licence to O.P. Jindal Global University (JGU). -
Image Processing and Artificial Intelligence for Precision Agriculture
Precision agriculture is a novel approach to increase the productivity of crops that employs recent technologies such as Artificial Intelligence, WSN, cloud computing, Machine Learning, and IoT. This paper reviews the development of different techniques effectively used in precision agriculture. The paper details the technological impact on precision agriculture followed by the different image processing schemes such as Satellite imagery and unmanned aerial vehicle (UAV). The role of precision agriculture is disease detection, weed detection from UAV images, and detection of trees and contaminated soils from satellite imagery is discussed. It reviews the impact of artificial intelligence (AI) namely machine learning &deep learning in precision agriculture. The performance of the recent image processing schemes in precision agriculture is analyzed. The paper also discusses the challenges that exist in implementing the precision agriculture system. 2022 IEEE. -
Digital Soil Texture Classification Using Machine Learning Approaches
The texture of the soil is an important factor to consider during cultivation. The water transmission property is being regulated by the texture of the soil. To determine sand, silt and clays percentage present in a soil sample, a conventional laboratory method is used, which consumes more time. Digitization in agriculture has given a new direction of innovative research in agriculture domain. In this paper, based on image processing an efficient model has been developed for soil texture classification. Eight different image preprocessing techniques were used for the image enhancement. Out of that, the linear contrast adjustment found to be best in image enhancement. A feature vector was calculated by extracting six different features from the enhanced image. The feature vector of an image is input to the machine learning classifier. The various classifiers used in this research work are SVM, KNN, ANN and PNN. The accuracy of the classifiers was SVM (0.98), KNN (0.89), ANN (0.89) and PNN (0.86). From the result, it is found SVM model has higher rate in classification of soil. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
A Systematic Literature Review on Image Preprocessing and Feature Extraction Techniques in Precision Agriculture
Revolutions in information technology have been helping agriculturists to increase the productivity of the cultivation. Many techniques exist for farming, but precision agriculture (PAg) is one technique that has gained popularity and has become a valuable tool for agriculture. Nowadays, farmers find it difficult to get expert advice regarding crops on time. As a solution, image processing techniques (IPTs) embedded PAg applications are developed to support farmers for the benefit of agriculture. In recent years, IPT has contributed a lot to provide a significant solution in PAg. This systematic review provides an understanding on preprocessing and feature extraction in PAg applications along with limitations. Preprocessing and feature extraction are the major steps of any application using IPTs. This study gives an overall view of the different preprocessing, feature extraction, and classification methods proposed by the researchers for PAg. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Soil classification using active contour model for efficient texture feature extraction
Precision farming is a systematic approach in agriculture that aims in improving economic and environment status of the farmers. It is achieved by having prior knowledge on soil texture, nutrient, pH and other climatic conditions. Hence this paper proposes a soil classification for crop prediction approach that uses an active contour algorithm for band estimation in Fourier domain for efficient texture feature extraction. This approach initially segments the soil sample and extracts into the color and texture features. The approach proposes a texture feature extraction where the image is initially transformed to Fourier domain of a 2D-discrete Fourier transform. The image in the Fourier domain is classified into high and low-frequency bands. The cut off frequency is decided by final contour of active contour method, where initial circular contour is used for estimating final contours on Fourier coefficients. This leads to the estimation of an irregular-shaped cut off frequency along with the 2D Fourier coefficients, instead of using a circular-shaped cut off frequency. A local binary pattern (LBP) from the high-frequency band image extracts texture feature. The extracted texture and color features are trained using a fully connected network. Active contour-based proposed model was evaluated by metrics F1-score, accuracy, specificity, sensitivity, and precision on soil datasets of Kaggle and IRSID. The accuracy, F1-score, specificity, precision, and sensitivity of proposed approach active contour-based were estimated as 97.89%, 97.87%, 99.46%, 98.11 and 97.94% respectively when evaluated in the Kaggle dataset. The evaluation results of proposed active contour model based soil classification outperform other traditional approaches. 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management. -
Rhetoric as an instrument for manipulation and distortion of truth an analysis of Orwell's 1984
Aristotle, in his Rhetoric, points out that all individuals indulge in rhetoric to demonstrate the truth or righteousness in what one wants to say. Problems arise only when rhetoric is used to appeal to emotions, rather than reason. In the current times, when rhetoric is used by leaders for propaganda, to whip up emotions in terms of nationalism and racism, George Orwell's remark that "political language is designed to make lies sound truthful and murder respectable,"6 sounds relevant. The author examines Orwell's 1984 to demonstrate how rhetoric is a powerful tool in the hands of political leaders that can control the thoughts of individuals, to the extent of reducing them to non-entities. In an era where manufacture of consent is possible, the paper highlights how the quality of rhetoric has vitiated over time and the concern that the abuse of language prevalent in fascist regimes of Hitler and Stalin is slowly creeping into democracies too. A peaceful and harmonious existence is possible only when political leaders engage in responsible rhetoric and are willing to dialogue with dissenting voices. 2017 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore). -
Impact of pharmacy industries growth on India economy during covid 19 /
Patent Number: 202241050891, Applicant: Deepha V.
Impact of Pharmacy Industries growth on India Economy during COVID 19 Abstract Pharmacy is an industry that can continue to function without being affected by economic fluctuations. This industry is socially respected by people. Whether people have food to eat or not, everyone wants to preserve the health of the body. In particular, the demand for medicines is more than ever in today's era. -
Visual propaganda through social media: A case study of Arab - Israeli crisis /
A picture is worth a thousand words, uploading images immediately attract attention a comments or tweets. Images are able to trigger multiple emotions and are effectively used for propaganda. Visual propaganda stands for usage of images to fulfil propaganda goals. These images carry meaning, emotion and a purpose. -
Artificial intelligence based system and method for management, recommendation, mapping of skill /
Patent Number: 202111054501, Applicant: Durgansh Sharma.
Artificial intelligence based system (100) and method for management, recommendation, mapping of skill comprising EmpNet (101), recommender system (102), automated machine learning system (103), skillset dataset (104), optimization system (105), industry interface system (106). The method for management, recommendation, mapping of skill comprising the steps of: a) capturing the required skillset personal data by the panchayat system (701); b) verify the skillset (702). -
An Optimal Load Balancing Framework for Fog-Assisted Smart Grid Applications
The growth of the Internet of Things (IoT) causes a significant amount of data to come in from physical devices and sensors, which adds to the latency and processing delays in smart grid applications. The pay-per-model method of transmitting gathered data that cloud computing offers improves scalability and functionality for end devices, which increases smart grid efficiency. Milliseconds matter in the crucial realms of load balancing, resource usage, and distribution systems, where any latency or jitter is unacceptable. By strategically positioning processing, networking, storage, and communication capabilities at the network edge, fog computing, an outgrowth of cloud technology, successfully addresses current issues in service groups. This paper introduces a unique hybrid framework on a highly virtualized platform and proposes three potential load balancing algorithms: throttled, Round Robin, and a novel Equilibrium Optimizer with Simulated Annealing (EO-SA). The article provides a comprehensive investigation on several load balancing techniques for obtaining optimized services in a smart grid environment thereby focusing on better utilization of network resources and reduction of costs. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.