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Face Detection-Based Border Security System Using Haar-Cascade and LBPH Algorithm
Border security is a process which measures the border management ideas by a country or set of countries to wage against unspecific and unauthorized travel or trade across the country borders, to bound non-legal deport, various crimes combat, and foreclose dangerous criminals from entering in the country. A system will help in keeping a check on those personnels who forge with the legal document with an intension to cross the border. This article discusses about border security of whole Indian context, and there are various such systems which have been built since 2010 as wireless sensor network system named Panchendriya. Remote and instruction manual switch mode arm system using ultrasonic sensor for security of border. This article we have made use of Haar-Cascadian along with LBPH algorithm with their functioning. The result and discussion section we compare most recent face recognition techniques that have been used in the last ten years. The proposed prototype is discussed and shown through simulation model, it provide better result compare to existing model. The proposed Haar-Cascade and LBPH algorithm provide 10% better performance. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Facebook as a Socialising Agent and its Impact on Academic Achievements on an Individual
Golden Research Thoughts Vol.2,Issue 9,pp.1-3 ISSN No. 2231-5063 -
Facebook post analysis for a celebrity page
Social Media is a subject that is large and extremely talked about in the present day. The expanding accessibility of the web and the development of social media brought in a necessity for the analysis of data based on a Facebook page. The number of information generated by social media platforms are expanding exponentially. The best approach to understand data of this magnitude lies in mining and analysis of such big data. The present focus is on the analysis of a Facebook Fan Page. This research work concentrates on the examination of the number of likes, post shares and correlation of posts and comments on various topics, fields or areas of a Facebook page. 'Like' is not the only way of rating a post nowadays. There are also recently added features like emoticons which display emotions such as 'love', 'wow', 'angry', 'sad', etc., to rate a post. The objective of this paper is to extract the data available and to perform analysis on a cricket fan page. Python is used to extract and analyse the information. IAEME Publication. -
Facial Emotion Detection Using Deep Learning: A Survey
The long history of facial expression analysis has influenced current research and public interest. The scientific study and comprehension of emotion are credited to Charles Darwin's 19th-century publication The Representation of the Sentiment in Man and Animals (originally published in 1872). As Recognition of human emotions from images is one of the utmost important and difficult societal connection study assignments. One advantage of using a deep learning strategy is its independence from human intervention while undertaking feature engineering. This approach involves an algorithm that scans the data for features that connect, then combines them to promote quicker learning without being explicitly told to. Deep learning (DL) based emotion detection outperforms traditional image processing methods in terms of performance. In this analytical study, the creation of an artificial intelligence (AI) system that can recognize emotions from facial expressions is presented. It discusses the various techniques for doing so, which generally involve three steps: face uncovering, feature extraction, and sentiment categorization. This study describes the various existing solutions and methodologies used by the researchers to build facial landmark interpretation. The Significance of this survey paper is to analyze the recent works on facial expression detection and distribute better insights to novice researchers for the upgradation in this domain. 2023 IEEE. -
Facial emotion recognition using convolutional neural networks
Emotional expressivity has always been a simple job for people, but computer programming is much harder to accomplish. Image emotions may be recognised by recent developments in computer vision and machine learning. In this article, we present a new method to detect face emotion. Use neural networks convolutionary (FERC). The FERC is based on a CNN network of two parts: the first portion removed the backdrop of the image, the second part removed the face vector. The expressional vector (EV) is utilised in the FERC model to detect the fve different kinds of regular facial expressions. The double-level CNN is continuous and the weights and exponent values of the final perception layer vary with each iteration. In that it improves accuracy, FERC varies from widely utilised CNN single-level technology. Moreover, EV generation prevents the development of a number of issues before a new background removal process is used (for example distance from the camera). 2021 -
Facial Expression Recognition Using Pre-trained Architectures
In the area of computer vision, one of the most difficult and challenging tasks is facial emotion recognition. Facial expression recognition (FER) stands out as a pivotal focus within computer vision research, with applications in various domains such as emotion analysis, mental health assessment, and humancomputer interaction. In this study, we explore the effectiveness of ensemble methods that combine pre-trained deep learning architectures, specifically AlexNet, ResNet50, and Inception V3, to enhance FER performance on the FER2013 dataset. The results from this study offer insights into the potential advantages of ensemble-based approaches for FER, demonstrating that combining pre-trained architectures can yield superior recognition outcomes. 2024 by the authors. -
Facial Expression Recognition with Transfer Learning: A Deep Dive
In the realm of affective computing, where the nuanced interpretation of facial expressions plays a pivotal role, this research presents a comprehensive methodology aimed at refining the precision of facial expression recognition on the CK+ (Cohn-Kanade Extended) dataset. Our method uses the robust DenseNet121 architecture that has been pretrained on the 'imagenet' dataset, and it leverages transfer learning on the foundational CK+ dataset. The model deftly handles issues with overfitting, normalization, and feature extraction that are present in facial expression detection on CK+. Our approach not only achieves an overall accuracy of 98%, with a 5.86% accuracy enhancement over the base paper on the CK+ dataset, but also shows remarkable precision, recall, and F1-score values for individual emotion classes. It is noteworthy that emotions such as anger, contempt, and disgust have precision rates that reach 100%. The study highlights the model's noteworthy input to affective computing and presents its possible real-world uses in emotion analysis on CK+ and human-computer interaction. 2024 IEEE. -
Facial pain expression recognition in real-time videos
Recognition of pain in patients who are incapable of expressing themselves allows for several possibilities of improved diagnosis and treatment. Despite the advancements that have already been made in this field, research is still lacking with respect to the detection of pain in live videos, especially under unfavourable conditions. To address this gap in existing research, the current study proposed a hybrid model that allowed for efficient pain recognition. The hybrid, which consisted of a combination of the Constrained Local Model (CLM), Active Appearance Model (AAM), and Patch-Based Model, was applied in conjunction with image algebra. This contributed to a system that enabled the successful detection of pain from a live stream, even with poor lighting and a low-resolution recording device. The final process and output allowed for memory for storage that was reduced up to 40%-55% and an improved processing time of 20%-25%. The experimental system met with success and was able to detect pain for the 22 analysed videos with an accuracy of 55.75%-100.00%. To increase the fidelity of the proposed technique, the hybrid model was tested on UNBC-McMaster Shoulder Pain Database as well. 2018 Pranti Dutta and Nachamai M. -
Facial Recognition Model Using Custom Designed Deep Learning Architecture
Facial Recognition is widely used in some applications such as attendance tracking, phone unlocking, and security systems. An extensive study of methodologies and techniques used in face recognition systems has already been suggested, but it doesn't remain easy in the real-world domain. Preprocessing steps are mentioned in this, including data collection, normalization, and feature extraction. Different classification algorithms such as Support Vector Machines (SVM), Nae Bayes, and Convolutional Neural Networks (CNN) are examined deeply, along with their implementation in different research studies. Moreover, encryption schemes and custom-designed deep learning architecture, particularly designed for face recognition, are also covered. A methodology involving training data preprocessing, dimensionality reduction using Principal Component Analysis, and training multiple classifiers is further proposed in this paper. It has been analyzed that a recognition accuracy of 91% is achieved after thorough experimentation. The performance of the trained models on the test dataset is evaluated using metrics such as accuracy and confusion matrix. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Facile combustion synthesis of highly active Mo doped BiVO4 for photocatalytic dye degradation, photo-oxidation of alcohols, antifungal and antioxidant activities
This work represents the facile and green synthesis of Molybdenum (Mo)-doped bismuth vanadate (BiVO4). Green synthesis of Mo-doped BiVO4 was done using combustion technique using Mangifera indica (Mango) leaf extract as the fuel for combustion. The material synthesised was pure and characterised using X-ray diffraction, scanning electron microscopy, high resolution transmission electron microscopy, ultravioletvisible diffuse reflectance spectroscopy, Fourier transform infrared spectroscopy and photoluminescence (PL). It was found that Mo-doped BiVO4 had monoclinic scheelite phase, with a bandgap of 3.71eV. Various application was possible from the synthesised material like photodegradation of Malachite Green, a typical organic which showed excellent degradation efficiency of 99% under 120minutes. The catalyst also gave up to 95% yields in the light-assisted oxidation of aromatic alcohols to corresponding aldehydes. The material also showed excellent antioxidant properties showing 6.7g of ascorbic acid equivalence (AAE). It gave an excellent minimum lethal dosage (MLD) of 500g against Penicillium and Trichoderma fungal strains and showed maximum of 32 mm zone of inhibition. These applications show the versatility of the material to be used in various fields. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Facile construction of gefitinib-loaded zeolitic imidazolate framework nanocomposites for the treatment of different lung cancer cells
Gefitinib (GET) is a revolutionary targeted treatment inhibiting the epidermal growth factor receptor's tyrosine kinase action by competitively inhibiting the ATP binding site. In preclinical trials, several lung cancer cell lines and xenografts have demonstrated potential activity with GET. Response rates neared 25% in preclinical trials for non-small cell lung cancer. Here, we describe the one-pot synthesis of GET@ZIF-8 nanocomposites (NCs) in pure water, encapsulating zeolitic imidazolate framework 8 (ZIF-8). This method developed NCs with consistent morphology and a loading efficiency of 9%, resulting in a loading capacity of 20wt%. Cell proliferation assay assessed the anticancer effect of GET@ZIF-8 NCs on A549 and H1299 cells. The different biochemical staining (Calcein-AM and PI and 4?,6-Diamidino-2-phenylindole nuclear staining) assays assessed the cell death and morphological examination. Additionally, the mode of apoptosis was evaluated by mitochondrial membrane potential (??m) and reactive oxygen species. Therefore, the study concludes that GET@ZIF-8 NCs are pledged to treat lung cancer cells. 2024 International Union of Biochemistry and Molecular Biology, Inc. -
Facile engineering of aptamer-coupled silk fibroin encapsulated myogenic gold nanocomposites: investigation of antiproliferative activity and apoptosis induction
Nanocomposites selectively induce cancer cell death, holding potential for precise liver cancer treatment breakthroughs. This study assessed the cytotoxicity of gold nanocomposites (Au NCs) enclosed within silk fibroin (SF), aptamer (Ap), and the myogenic Talaromyces purpureogenus (TP) against a human liver cancer cell (HepG2). The ultimate product, Ap-SF-TP@Au NCs, results from a three-step process. This process involves the myogenic synthesis of TP@Au NCs derived from TP mycelial extract, encapsulation of SF on TP@Au NCs (SF-TP@Au NCs), and the conjugation of Ap within SF-TP@Au NCs. The synthesized NCs are analyzed by various characteristic techniques. Ap-SF-TP@Au NCs induced potential cell death in HepG2 cells but exhibited no cytotoxicity in non-cancerous cells (NIH3T3). The morphological changes in cells were examined through various biochemical staining methods. Thus, Ap-SF-TP@Au NCs emerge as a promising nanocomposite for treating diverse cancer cells. The Author(s), under exclusive licence to Springer Nature B.V. 2024. -
Facile fabrication of 3D-?-Fe2O3@2D-g-C3N4 heterojunction composite materials: Effect of iron oxide loading on the electrochemical performance
Designing heterojunction nanocomposites is crucial for optimizing supercapacitor electrodes. This study addresses the challenge by introducing a facile synthesis method for creating 3D-?-Fe2O3@2D-g-C3N4 heterojunctions through a bulk carbon nitride-assisted hydrothermal process. During this process, the growth of ferric oxide particles coincides with the exfoliation and deposition of carbon nitride, leading to simultaneous structural changes in both iron oxide and carbon nitride phases. The resulting composite's properties strongly correlate with the iron oxide loading. Comprehensive characterization using XRD, FTIR, SEM-EDAX, XPS and TEM identified three distinct structures for ?-Fe2O3/g-C3N4 composites based on iron oxide loading: low, medium, and high. The medium-loaded sample demonstrated superior electrochemical performance, attributed to better interfacial contact and the formation of 3D-Fe2O3@2D-g-C3N4 heterojunctions. This composite, with an optimized 22 wt% iron oxide loading, exhibited a maximum specific capacitance of 925.1 Fg?1 at 5 mVs?1 and 498.6 Fg?1 at 6 Ag?1 in charge-discharge analysis, with stable performance over 2000 cycles. Overall, this research presents an enhanced hydrothermal method for facile preparation of effective ?-Fe2O3/g-C3N4 heterojunction materials. 2024 Elsevier B.V. -
Facile fabrication of dasatinib laden multifunctional polymeric micelles: Evaluation of anti-proliferative and apoptotic activities in human cancer cells
Dasatinib (DAS) has recently gained significant interest for its anticancer potential. Yet, the lipophilicity inherent in DAS limited its potential use as a chemotherapeutic drug. This study aimed to examine the effectiveness of polyethylene glycol-polycaprolactone (PEG-PCL) as a nanocarrier for DAS to increase its anticancer capabilities. The DAS-loaded PEG-PCL nanoparticles (termed as DAS@PEG-PCL NPs) were characterized using Fourier transform infrared (FTIR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and dynamic light scattering (DLS). Morphological staining and MTT tests were employed to investigate drug-loaded nanoparticles' apoptotic and anti-proliferative effects. The MTT assay demonstrated that incorporating DAS onto PEG-PCL NPs resulted in a dose-dependent increase in cytotoxicity in A549 (lung cancer) and HeLa (cervical cancer) cells. The A549 cancer cells were analyzed for their morphology using the acridine orange/ethidium bromide (AO/EB) and DAPI staining techniques. Overall, these findings demonstrate that the polymeric PEG-PCL nanoparticle systems hold great potential as a novel therapeutic strategy for cancer treatment. 2024 Wiley Periodicals LLC. -
Facile Fabrication of Nano carbon Derivatives for Optical and Electro chemical Applications
From synthesis of novel materials to their end-use applications, the prime objective of the material science community is to address the burgeoning social issues across the world. Noxious emissions from fossil fuel combustion, increased incidence of skin cancer, drug misuse, and ever-increasing demand for energy are some of the global concerns that require urgent consideration. This drives a relentless quest for a multifunctional material with broad applicability that can directly and constructively impact the quality of life, environment, and economic progress. However, materials of this kind should embrace versatile characteristics, improved competency, plausibility, and lower cost. In light of this, the current doctoral research emphasizes the development of trailblazing graphene-based materials with manifold usages derived from a naturally abundant carbonaceous fossil fuel coke to discover scientific solutions to the aforesaid trials and tribulations. Fossil fuel coal, mainly used for energy purposes, is often discouraged from industrial and domestic consumption due to its contribution to global warming. Despite the fact that coal is a non-renewable resource and a source of greenhouse gas emissions, it is one of the world's bountiful carbon resources. Therefore, it can be exploited as a potent substitute for conventional graphite, enabling the extraction of value-added graphene derivatives along with the sustainable utilization of coal. However, the purity of the precursor is a vital criterion to guarantee the quality and supply of graphene materials. In this doctoral work, coal-coke with 99% carbon content was used for the production of high-quality oxidized multilayer graphene derivatives by employing an environmentally-benign synthesis technique. The obtained graphene structure exhibited a multi-emissive fluorescence property having emissions ranging from blue to green-yellow. In addition, it also possessed remarkable electrochemical performance, good rate capability, and durability, signifying its expediency in energy storage devices. In an attempt to further enhance the scope of as-synthesized coke-based graphene derivatives, heteroatoms such as nitrogen and phosphorus were introduced into the graphene lattice via substitutional doping. It was perceived that nitrogen doping impressively amended the photophysical properties, especially in terms of quantum yield and fluorescence lifetime. Therefore, the as-synthesized nitrogen-doped multilayer graphene derivative was used as a fluorescent biomarker for imaging melanoma skin cancer cells with the purpose of early detection. Wherein co-doping of nitrogen and phosphorus endorsed excellent electrochemical characteristics and sensing performance, owing to the synergistic effect from heteroatoms and the imparted structural corrugations. Thus, by utilizing the as-synthesized nitrogen, phosphorus co- doped heteroatom derivative, oxytocin, a high-risk abused drug, was electrochemically detected in an nM range and validated the possibility of real-time surveillance over its mishandling in edibles and biological models. The coke-based graphene derivatives were further refashioned to obtain optimum textural and surface chemistry characteristics beneficial for energy storage characteristics. Accordingly, simultaneous heteroatom-doping and activation of graphene derivative were achieved. The obtained sample had a high surface area, hierarchical porous structure, increased defect densities, and co-active heteroatom enriched graphene network, suggesting its potential as an electrode material for supercapacitor applications. It was observed that the as-synthesized simultaneously heteroatom-doped and activated samples demonstrated high capacitance value, appreciable cyclic stability, and lower charge-transfer resistance. Henceforth, such enhanced supercapacitive performance points toward the cradle-to-gate transformation of fossil fuel, i.e., the conversion of sluggish black coal to green energy. -
Facile fabrication of stable wettability gradients on elastomeric surfaces for applications in water collection and controlled cell adhesion
We have developed a simple and effective method to prepare stable wettability gradients on an elastomeric soft substrate, polydimethylsiloxane (PDMS). In our method, a partially cured PDMS film composed of a definite ratio of elastomer and crosslinking agent was heated over a hot surface with a temperature gradient. This causes differential thermal curing of the PDMS film and the water contact angle (wettability) of the resultant surface showed gradual variation across the length. This method allows us to design and fabricate wettability gradients with rationally controlled directionality and shapes (e.g., linear and radial gradients). The stability of the wettability gradients was studied and a chemical treatment method was developed to enhance the stability at room temperature. Stable wettability gradients prepared through this method can find applications as reliable platforms and scaffolds offering controlled or directional wetting and adhesion. We have demonstrated the practical applications of the wettability gradients in directional water collection, controlled crystallization of materials, and controlled cell adhesion of HeLa cells, osteoblasts and NIH/3T3 cells. The multi-functional characteristics of these wettable gradients are expected to be handy in other domains using soft materials and interfaces also. 2023 The Royal Society of Chemistry. -
Facile green synthesis of semiconductive ZnO nanoparticles for photocatalytic degradation of dyes from the textile industry: A kinetic approach
One-pot, facile and green synthesis of zinc oxide nanoparticles are synthesized using cow dung as fuel by combustion procedure. The synthesized material is characterized by using various techniques such as XRD, FTIR, UV, FESEM, and EDX. To assess the photocatalytic efficacy of the as-synthesized material, harmful cationic and anionic dyes such as methylene blue (MB) and alizarin red S (AZ) dyes, respectively, are selected as benchmark dyes. The influence of light source, dye concentration, photocatalyst dosage, and pH value on the efficiency of photocatalyst and kinetics of photodegradation are systematically studied. The photodegradation results revealed that the synthesized ZnO NPs exhibited removal efficiency of MB and AZ dyes upon irradiation with UV light. Concisely, the removal efficacy of the ZnO NPs under UV light irradiation exhibited an MB and AZ degradation of 99.9% and 96.8%, respectively. A reasonable photo-catalytic mechanism for the high photodegradation efficacy of MB and AZ dyes by the prepared photocatalyst is also proposed. The green fabricated photocatalyst is promising material and could be applied for waste-water remediation and other ecological applications. 2022 -
Facile synthesis of aluminum oxyhydroxide-PVA films and its adsorptive evaluation for the removal of methylene blue dye from water: kinetics, optimization studies and mechanism
Aluminum oxyhydroxide-polyvinyl alcohol films were synthesized by the solgel method with varying metal-polymer ratios. The results of the characterization confirmed the formation of aluminum oxyhydroxideand the incorporation of metal into the polymer. The adsorption isotherms of the film exhibited type IV isotherms indicating the mesoporous nature with a non-uniform pore size distribution. The optical profilometric studies confirmed the surface roughness of the film. The adsorptive nature of the film was tested for the removal of methylene blue dye from the aqueous solution. Optimization studies were conducted to investigate the effect of various parameters on the adsorption process. The adsorption isotherms of methylene blue fit with the Langmuir isotherm model and follow a pseudo-second-order equation. A suitable reaction mechanism was proposed, which confirms the adsorptive nature of the film is due to the electrostatic attraction. The synergetic effect of the metal-polymer blend, surface roughness and pore size of the film, which ranges from 0.01 to 0.025nm,enhances the adsorption of methylene blue. The comparison of results obtained in the current study with earlier reports confirms that the aluminum oxyhydroxide-polyvinyl alcohol films can be considered an eco-friendly, cost-effective adsorbent for removing methylene blue. 2023, The Polymer Society, Taipei. -
Facile synthesis of Bi2WO6-NiO nanocomposite for supercapacitor application
In order to prepare for future high-power storage-related applications, a tremendous amount of studies have been conducted on the manufacturing of high-performance supercapacitor electrodes. The hydrothermal technique was used to synthesize Bi2WO6NiO nanocomposite (NC), which was examined using FTIR, XRD, HR-TEM, EDX, FESEM, and XPS techniques. Furthermore, the Bi2WO6-NiO NC performs with an elevated specific capacity of 398.2C/g at 10 mV/s. The charge transfer resistance (Rct) and solution resistance (Rs) of Bi2WO6-NiO NC were determined as 0.81 and 0.23 ? using electrochemical impedance spectra (EIS). Bi2WO6-NiO NC extended the chargedischarge time and rate capacities, as shown by the galvanostatic chargedischarge (GCD) analysis. Even after 2000 cycles, Bi2WO6-NiO NC cyclic stability was superior with a capacitive retention of 89.3 %. A power density of 6750 W/kg resulted from the constructed asymmetric supercapacitor (ASC) device based on Bi2WO6-NiO/AC, exhibiting an energy density of 32.5 Wh/kg. Additionally, the ASC maintains high cyclic stability with 90.8 % of initial capacity, even after 2000 chargedischarge cycles in a row. 2024 Elsevier B.V. -
Facile Synthesis of Few-Layer Graphene Oxide from Cinnamomum camphora
Abstract: This study presents a facile synthesis technique to produce few-layer graphene oxide from Cinnamomum camphora (Camphor L.). Camphor upon carbonization and chemical oxidation leads to the formation of few-layer graphene oxide sheets of around ten layers with a lateral size of 4.14 nm and stacking height of 3.10 nm. AFM and SEM analysis results reveal the wrinkled morphology of the graphene oxide sheets formed. The sharp G band and the relative intensity of the defect to the graphitic band in the Raman spectrum indicate the formation of nanocrystalline graphene oxide sheets with fewer defects. The FTIR spectrum and the deconvoluted C 1s XPS spectrum of graphene oxide synthesized reveal the presence of predominant sp2 hybridized carbon along with carbon bound to various oxygen functionalities. In brief, the formation of high-quality few-layer graphene oxide from an abundant, low-cost, and readily available botanical precursor is herein reported. 2021, Pleiades Publishing, Ltd.