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Enhancement of Reflected Faces on Semi-reflecting Surfaces
Face recognition is interesting research area in computer vision. This paper proposes to enhance faces reflected on semi reflecting surfaces such as glass window, glass screens or any other mirror like surfaces. Visibility or clarity of reflected image is depending on the reflecting ability of material surface on which reflection occurs. Other than mirror surfaces, majority of reflected images are less visibility. So recognition of reflected face is a challenge in the proposed method. This paper addresses enhancement of reflected face image. Estimating atmospheric light and medium transmission map, recover haze free image. Apply CLAHE i.e., adaptive histogram equalization by limiting contrast to obtain enhanced reflected face image. 2019 IEEE. -
Enhancement of resilience an quality of life using strength based counselling and the mediating role of parental bonding in adolescents with type 1 diabetes
The current study was an attempt to understand the socio-demographic profile of newlineadolescents with type 1diabetes, the relationship between variables such as resilience, quality of life, parental bonding and the mediating role of parental bonding. It was also aimed to understand parent s perception of the adolescent s resilience and quality of life and their newlineexperiences. In phase 1, 100 adolescents/ newlinechildren (M=40, F=60, Age 10-18years) with an newlineexisting diagnosis of type 1 diabetes and their parents were enrolled from two hospitals and one clinic in Bangalore. The adolescents were administered Paediatric Quality Of Life for Diabetics (PedsQL) (Child and Adolescent Form), The Resilience Scale for Youth (CYRM), The Parental Bonding Instrument PBI (Father and Mother Form ). Parents were administered the consent form, demographic data sheet and parent version of resilience and quality of life.All scales were translated and back translated. In Phase 2 of the study, an intervention model based on the principles of strength newlinebased counselling to enhance resilience and quality of life (SBCTD1) was developed and newlineused. Qualitative interviews were conducted to understand the experiences of parents of newlinechildren/adolescents having type 1 diabetes. These interviews were tape recorded. 50 newlineadolescents from Phase1, were randomly assigned to the intervention group (n=25) and the control group (n=25). For the intervention group after going through the sessions the Resilience Scales and The Paediatric Quality of Life scales were administered after one and three months respectively. HbA1c values were also collected again after three months of newlineintervention. Control group received regular care and treatment at the center and were not newlineexposed to the model developed for the study. -
Enhancement of substitution voices using F1 formant deviation analysis and DTW based template matching
Speech is the best way to express the thoughts and feelings among the human beings. But for many reasons the sound produced by human beings becomes disordered voice and termed with many names based on the cause as stammering, dys-theria, apraxia and so on. In the above mentioned few examples, the voice becomes disordered because of the underperformance of body's organ. The larynx is removed in some human beings because of cancer. For them an artificial larynx transducer (ALT) is used to produce the sounds. The above all sounds are categorized as disordered voice and the sound produced by ALT is also called as Substitution voice. In this paper, a method is used to improve the quality of substitution voice produced by ALT. Algorithm is developed to estimate undesired audio components from the device output and remove the same using Non Linear Spectral Subtraction (NLSS) technique. Further, Fundamental (F0) contour and novel parameter F1 formant deviation of healthy speech (HE) and ALT speech are determined. The above two parameters are estimated and stored during the training phase of the system. In the test phase, the above mentioned parameters are estimated and they are used to scale down the database to reduce overall enhancement time. Next step is template matching done by mapping test data with training data using Dynamic Time Warping (DTW) Technique. The data base with least distance estimation is recognized as the utterance and the same is played back. 2017 IEEE. -
Enhancement of tensile strength and elastic modulus using bio-waste based carbon nanospheres doped polymer nanocomposites
The Carbon Nano Spheres (CNS) derived from areca nuts were synthesized from pyrolysis process and were used as fillers for fabrication of polymer nano composite materials. The filler materials are loaded in 0.05%, 0.1% and 0.5% loading percentages. The optimum sample was subjected to heat treatment. The tensile strength, elastic modulus and % of elongation were investigated for all samples. The Scanning Electron Microscope (SEM) images revealed the morphological features of optimum samples and hence the uniform dispersion of CNS in polymer matrix. The 0.1% samples showed 10% improvement in Ultimate Tensile Strength (UTS) and 24% improvement in Elastic modulus compared to bare epoxy material. When 0.1% samplewas subjected to heat treatment under 200C the UTS improved by 23%. Hence, CNS reinforced composite materials exhibited unique properties like high strength, less weight and low cost making them suitable for various structural applications such as aerospace, automotive, construction, and electronics industries. The Polymer Society, Taipei 2024. -
Enhancement of the Electrochemical behaviour of Carbon Black via a defect induced approach
In order to address the rising global concern of energy storage, carbon-based materials have established themselves due to their distinct features. Despite the demand for the fabrication of supercapacitors from natural, inexpensive carbonaceous materials is on the rise, the intrinsic disorders present in such materials hinder their performance, and hence, tuning these defects can aid in the improvement of their electrochemical performance. In this study, carbon black is introduced with defects in the form of oxygen functional groups via oxidation and thermal exfoliation and the impact on its electrochemical performance is studied. Careful tuning of the type of oxygen functional moieties at the basal plane of the carbon lattice is observed to be the contributing factor for the electrochemical behaviour. The distortion in the graphitic lattice caused by the epoxy and hydroxyl groups alters the specific surface area, porosity, and thermal stability, facilitating easier ion diffusion rates and enhanced faradaic reactions. The obtained specific capacitance of the thermally exfoliated carbon black is as high as 246.49 Fg?1 in a three-electrode system and 82.85 F/g in a two-electrode setup, owing to an energy density of 5.63 Whkg?1 and a power density of 189.75 Wkg?1. It has also exhibited excellent cyclic stability and capacitance retention up to 4000 cycles. The equivalent series resistance is found to decrease from 5.67 to 4.96 ? making the material conductive. As a result, the electrochemical properties of carbon black can be enhanced by tuning the oxygen functional groups, making it a promising supercapacitive material. Graphical Abstract: (Figure presented.). Qatar University and Springer Nature Switzerland AG 2024. -
Enhancement of the thermal conductivity of a near room temperature magnetocaloric composite using graphene-like hybrid nanosheets derived from organic waste
Polymer matrix composites, fabricated to counter the inherent brittleness of magnetocaloric Heusler alloys, suffer from low thermal conductivity. Here, we demonstrate a low-cost, scalable route towards developing thermally conductive, mechanically robust near-room-temperature magnetocaloric composites by incorporating graphene-like hybrid nanostructures chemically synthesized from discarded sugarcane. Micron-sized particles obtained by manually grinding Ni50.2Mn36.7Sn13 ribbons possessing a strong magnetostructural transformation near room-temperature were chosen as the active magnetocaloric fillers. Both the functional fillers were incorporated into a polysulfone matrix by solution casting. Large values of isothermal entropy change ? 0.43 and -0.46 J/kg.K were observed for a ?H = 2T, driven by two successive first and second-order transformations within the alloy fillers. Additionally, an enhanced value of the in-plane thermal conductivity ? 3.06 0.4 W/m.K was observed in the composites owing to the formation of efficient thermal bridges/pathways by the graphene-like hybrid nanostructures, rendering them promising candidates for magnetic refrigeration applications. 2023 Acta Materialia Inc. -
Enhancement of thermoelectric efficiency in vapor deposited Sb 2Te3 and Sb1.8In0.2Te3 crystals
Pure and indium doped antimony telluride (Sb2Te3) crystals find applications in high performance room temperature thermoelectric devices. Owing to the meagre physical properties exhibited on the cleavage faces of melt grown samples, an attempt was made to explore the thermoelectric parameters of p-type crystals grown by the physical vapor deposition (PVD) method. The crystal structure of the grown platelets (9 mm8 mm2 mm) was identified as rhombohedral by x-ray powder diffraction method. The energy dispersive analysis confirmed the elemental composition of the crystals. The electron microscopic and scanning probe image studies revealed that the crystals were grown by layer growth mechanism with low surface roughness. At room temperature (300 K), the values of Seebeck coefficient S (c) and power factor were observed to be higher for Sb1.8In0.2Te 3 crystals (155 ?VK-1, 2.669 10-3 W/mK2) than those of pure ones. Upon doping, the thermal conductivity ? (c) was decreased by 37.14% and thus thermoelectric efficiency was improved. The increased figure of merit, Z = 1.23 10-3 K -1 for vapour grown Sb1.8In0.2Te3 platelets indicates that it could be used as a potential thermoelectric candidate. Pure and indium doped antimony telluride (Sb2Te 3) crystals were grown by the physical vapor deposition (PVD) method. Incorporation of indium atoms into the antimony sub lattice improved Seebeck coefficient and reduced thermal conductivity. The increased figure of merit, Z = 1.23 10-3K-1 for vapor grown Sb 1.8In0.2Te3 platelets indicates that it could be used as a potential thermoelectric candidate. 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. -
Enhancement of thermoelectric efficiency in vapor deposited Sb2Te3 and Sb1.8In0.2Te3 crystals
Crystal Research & Technology, Vol-49 (4), pp. 212-219. ISSN-0232-1300 -
Enhancements in anomaly detection in body sensor networks
Anomaly detection in Body Sensor Networks (BSNs), have recently received much attention from the healthcare community. This is partly due to the development of sensor based real-time tracking and monitoring networks. These networks have been responsible not only for ensuring critical medical treatment at times of emergency, but have also made it easier for health-care personnel to administer critical treatment. In this paper we consider improvements to existing machine learning methods that detect anomalous sensor measurements. The improved methods are a step in the right direction in ensuring unduly overheads due to faulty sensors don't interfere while administering life-critical treatment in a limited resources scenario. 2019 IEEE. -
Enhancements of women's entrepreneurship: A theme-based study
Woman entrepreneurs are defined as a group of women who initiate, organize, and run a business concern, from a situation where a woman was not even allowed to get out of their home, to today, running most of the successful brands of the world, contributing a major part to the economic growth, and breaking the stereotypes by providing a reality check to the male dominance. There has been a wide range of public policies enrolled out to facilitate and encourage the growth of women's entrepreneurship. A few such policies from India have proved to be successful, which will be outlined in this book chapter. From the past times of not gaining adequate recognition for their support, women have emerged successful in overcoming hardships such as lack of visibility, lack of training and educative support about public policies provided by governments to women entrepreneurs, fewer opportunities, and walking out of the social stigma. 2023, IGI Global. All rights reserved. -
Enhancements to Content Caching Using Weighted Greedy Caching Algorithm in Information Centric Networking
Information-Centric Networks (ICN) or Future Internet is the revolutionary concept for the existing infrastructure of the internet that changes the paradigm from host-centric networks to data-centric networks. Caching in Information-Centric Networks (ICN) has become one of the most critical research areas in today's world, especially for the leading in content delivery over Internet companies like Netflix, Facebook, Google, etc. This paper is intended to propose a novel Caching strategy called Weighted Greedy Dual Size Frequency for caching in Information-Centric networks. In this paper, the WGDSF considers multiple critical factors for maintaining the Web Content efficiently in ICN Caching Router. Simulation is done for the various performance metrics like Cache Hit ratio, Link load, Path Stretch, and Latency for WGDSF cache replacement algorithm, and results shown that WGDSF outperforms well compared with LRU, LFU, and RAND Caching Strategies. 2020 The Authors. Published by Elsevier B.V. -
Enhancements to greedy web proxy caching algorithms using data mining method and weight assignment policy
A Web proxy caching system is an intermediary between the users and servers that tries to alleviate the loads on the servers by caching selective Web objects and behaves as the proxy for the server and service the requests that are made to the servers by the users. In this paper the performance of a proxy system is measured by the number of hits at the proxy. A higher number of hits at the proxy server reflects the effectiveness of the proxy system. The number of hits is determined by the replacement policies chosen by the proxy systems. Traditional replacement policies that are based on time and size are reactive and do not consider the events that will possibly happen in the future. The outcomes of the paper are proactive strategies that augment the traditional replacement policies with data mining techniques. In this paper, the performances of the greedy replacement policies such as GDS, GDSF and GD* are adapted by the data mining method and weight assignment policy. Experiments were conducted on various data sets. Hit ratio and byte hit ratio were chosen as parameters for performance. 2018 ISSN. -
Enhancements to greedy web proxy caching algorithms using data mining method and weight assignment policy /
International Journal of Innovative Computing, Information And Control, Vol.14, Issue 4, pp.1311-1326, ISSN No. 1349-4198. -
Enhancements to randomized web proxy caching algorithms using data mining classifier model
Web proxy caching system is an intermediary between the users and servers that tries to alleviate the loads on the servers by caching selective web pages, behaves as the proxy for the server, and services the requests that are made to the servers by the users. In this paper, the performance of a proxy system is measured by the number of hits at the proxy. The higher number of hits at the proxy server reflects the effectiveness of the proxy system. The number of hits is determined by the replacement policies chosen by the proxy systems. Traditional replacement policies that are based on time and size are reactive and do not consider the events that will possibly happen in the future. The outcomes of the paper are proactive strategies that augment the traditional replacement policies with data mining techniques. In this work, the performance of the randomized replacement policies such as LRU-C, LRU-S, HARM, and RRGVF are adapted by the data mining classifier based on the weight assignment policy. Experiments were conducted on various data sets. Hit ratio and byte hit ratio were chosen as parameters for performance. Springer Nature Singapore Pte Ltd. 2019. -
Enhanching the Performance Metrics of Overlay Network for QoS in Media Transfer Using Genetic Algorithm
Quality of Service (QoS) of real time video applications is difficult to realize in wireless mobile networks because of the limited resource availability. Software-Defined Networking (SDN) Overlay networks are becoming popular to solve routing, traffic engineering and QoS due to the rapid increase in the adoption and investment in SDN. The SDN market size is projected to grow by a double-digit CAGR within the next decade and reached the low tens of billions USD in 2023, which shows a positive adoption of the industry. Real-time streaming and live content demand have also risen to an all-time high - the live-streaming market is growing at an average rate of about -20-23% CAGR through 2030, and the role of QoS in high-volume media is becoming more and more relevant. 2025 IEEE. -
Enhancing academic credential verification through blockchain technology adoption in university academic management systems
Blockchain technology has emerged as promising solution in various sectors, including higher education. This research investigates the impact of usage of blockchain technology in student credential verification within university academic management system. This study employs a descriptive research through quantitative analysis of data collected from universities that have integrated or planning to integrate blockchain technology into their academic management systems. Key parameters examined include awareness and familiarity with blockchain, extent of blockchain usage, user experience and satisfaction, the perceived impact and benefits. The findings suggest that blockchain technology positively influences academic credential verification process, streamlining data sharing and reducing administrative burdens. As blockchain continues to transform the academic management landscape, this study offers timely guidance for stakeholders navigating the intersection of technology and education. 2024, IGI Global. All rights reserved. -
Enhancing Angle Modulation Using Fractional Calculus: Theory and Performance Analysis
Angle modulation originally forms part of the backbone of the telecommunication and signal processing, where current studies are being carried out to improve its susceptibility to noise interference. This paper aims to analyze the possibility of the application of fractional calculus for optimization of angle modulation, as a requirement for development of enhanced and flexible communication networks. The main purpose of this study is to design and model new angle modulation technique which are Fractional Phase Modulation (FPM) and Fractional Frequency Modulation (FFM) by using fractional calculus. A generalized form of angle modulation and an introduction to the use of fractional calculus was proposed and a mathematical analysis of FM and FFM detectors was done. In evaluating the findings, the interaction between the fractional order of ? and some performance parameters like Signal-to-Noise Ratio (SNR) and Figure of Merit (FoM) was also considered. It has been shown that FPM and FFM detectors also show high SNR and FOM performance, and when ? is replaced. The FPM detector demonstrated a steady trend and increased from SNR 0 to 1 when the ? was diverse, while the FFM detector had a huge increase in SNR from ?=-0.9 to 0. These results indicate that the angle provides additional benefits in partial stones, signaling purity and system flexibility for the modulation technique. Thus, the ability to achieve better stability in communication for modulation techniques indicates the ability to achieve better stone purity and system flexibility for modulation techniques. Since partial order ? can be adjusted to fit the application, the proposed method shows interesting applications in many communication settings, especially when the signal is noisy or dynamic. 2025, School of Electrical Engineering and Informatics. All rights reserved. -
Enhancing authentication in blockchain bridges: A smart contract-based approach leveraging polynomial interpolation
This work focuses on the integration of blockchain for enhancing the security, privacy, and trust management within Vehicle Ad Hoc Networks (VANETs). In the context of smart transportation, VANETs offer essential safety but the open and dynamic nature of these networks makes secure, anonymous authentication a major challenge. Blockchain's decentralized nature can provide a secure, tamper- resistant ledger for managing data across the network nodes, helping address these security concerns. Cross- chain bridges enable the transfer of data, money and assets across blockchains. It has thus become important to enhance existing authentication mechanisms in blockchain bridges. In this research, we analyze existing authentication approaches, highlighting their limitations, such as reliance on centralized entities, private key leaks and weakness in smart contract functions. We then propose a novel approach to strengthen existing authentication mechanisms with the combined capabilities of Smart Contracts and Polynomial Interpolation, to establish a secure authentication layer. 2025, IGI Global Scientific Publishing. All rights reserved. -
Enhancing authenticity and trust in social media: an automated approach for detecting fake profiles
Fake profile detection on social media is a critical task intended for detecting and alleviating the existence of deceptive or fraudulent user profiles. These fake profiles, frequently generated with malicious intent, could engage in different forms of spreading disinformation, online fraud, or spamming. A range of techniques is employed to solve these problems such as natural language processing (NLP), machine learning (ML), and behavioural analysis, to examine engagement patterns, user-generated content, and profile characteristics. This paper proposes an automated fake profile detection using the coyote optimization algorithm with deep learning (FPD-COADL) method on social media. This multifaceted approach scrutinizes user-generated content, engagement patterns, and profile attributes to differentiate genuine user accounts from deceptive ones, ultimately reinforcing the authenticity and trustworthiness of social networking platforms. The presented FPD-COADL method uses robust data pre-processing methods to enhance the uniformness and quality of data. Besides, the FPD-COADL method applies deep belief network (DBN) for the recognition and classification of fake accounts. Extensive experiments and evaluations on own collected social media datasets underscore the effectiveness of the approach, showcasing its potential to identify fake profiles with high scalability and precision. 2024 Institute of Advanced Engineering and Science. All rights reserved. -
Enhancing Banana Cultivation: Disease Identification through CNN and SVM Analysis for Optimal Plant Health
Detection and effective remedies play a crucial role in revolutionizing banana crop health. The banana industry faces numerous challenges, including the prevalence of diseases and pests that can lead to significant yield losses. This paper explores the potential impact of detection techniques and remedies on improving banana crop management. Disease detection models based on machine learning, image processing and deep learning offer high accuracy in identifying diseases like Fusarium Wilt, Yellow Sigatoka, and Black Sigatoka. Implementing detection and targeted treatments can enhance crop productivity, reduce pesticide usage, and ensure sustainable banana production. 2024 IEEE.