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Non-destructive silkworm pupa gender classification with X-ray images using ensemble learning
Sericulture is the process of cultivating silkworms for the production of silk. High-quality production of silk without mixing with low quality is a great challenge faced in the silk production centers. One of the possibilities to overcome this issue is by separating male and female cocoons before extracting silk fibers from the cocoons as male cocoon silk fibers are finer than females. This study proposes a method for the classification of male and female cocoons with the help of X-ray images without destructing the cocoon. The study used popular single hybrid varieties FC1 and FC2 mulberry silkworm cocoons. The shape features of the pupa are considered for the classification process and were obtained without cutting the cocoon. A novel point interpolation method is used for the computation of the width and height of the cocoon. Different dimensionality reduction methods are employed to enhance the performance of the model. The preprocessed features are fed to the powerful ensemble learning method AdaBoost and used logistic regression as the base learner. This model attained a mean accuracy of 96.3% for FC1 and FC2 in cross-validation and 95.3% in FC1 and 95.1% in FC2 for external validation. 2022 The Authors -
Nondestructive and cost-effective silkworm, Bombyx mori (Lepidoptera: Bombycidae) cocoon sex classification using machine learning
Sericulture is the process of cultivating silkworm cocoons for the production of silks. The quality silk production requires quality seed production which in turn requires accurate classification of male and female pupa in grainage centers. The challenges in the current methods of silkworm cocoon sex classification using manual observation lie in the time-consuming nature of the process, potential human error, and difficulties in accurately discerning subtle morphological differences between male and female cocoons. FC1 and FC2 single hybrid variety breed pupa are commonly used in south India for the production of high yielding double hybrid bivoltine silkworm seeds. In this study, 1579 FC1 and 1669 FC2 variety samples were used for the classification process. To overcome the challenges of present physical observation by expert employees, camera images of FC1 and FC2 cocoons were used in this study for sex classification. The proposed model used Histogram Oriented Gradient (HOG) feature descriptor of cocoon samples. Linear Discriminant Analysis (LDA) was applied on the feature vector to reduce the dimension and this feature matrix was given to the classical machine learning algorithms support vector machine (SVM), k-nearest neighbors (kNN), and gaussian nae bayes for classification with stratified 10-fold cross validation. The results showed that for FC1 data HOG + LDA + Nae Bayes performed better with a mean accuracy of 95.3% and for FC2 data HOG + LDA + KNN attained a mean accuracy of 96.2%. Our results suggest that this camera imaging method can be used efficiently in the classification based on the cocoon size and shape of different breeds. African Association of Insect Scientists 2024. -
An optimized method for mulberry silkworm, Bombyx mori (Bombycidae:Lepidoptera) sex classification using TLBPSGA-RFEXGBoost
Silkworm seed production is vital for silk farming, requiring precise breeding techniques to optimize yields. In silkworm seed production, precise sex classification is crucial for optimizing breeding and boosting silk yields. A non-destructive approach for sex classification addresses these challenges, offering an efficient alternative that enhances both yield and environmental responsibility. Southern India is a hub for mulberry silk and cocoon farming, with the high-yielding double-hybrid varieties FC1 (foundation cross 1) and FC2 (foundation cross 2) being popular. Traditional methods of silkworm pupae sex classification involve manual sorting by experts, necessitating the cutting of cocoons a practice with a high risk of damaging the cocoon and affecting yield. To address this issue, this study introduces an accelerated histogram of oriented gradients (HOG) feature extraction technique that is enhanced by block-level dimensionality reduction. This non-destructive method allows for efficient and accurate silkworm pupae classification. The modified HOG features are then fused with weight features and processed through a machine learning classification model that incorporates recursive feature elimination (RFE). Performance evaluation shows that an RFE-hybridized XGBoost model attained the highest classification accuracy, achieving 97.2% for FC1 and 97.1% for FC2. The model further optimized with a novel teaching learning-based population selection genetic algorithm (TLBPSGA) achieved a remarkable accuracy of 98.5% for FC1 and 98.2% for FC2. These findings have far-reaching implications for improving both the ecological sustainability and economic efficiency of silkworm seed production. 2024. Published by The Company of Biologists Ltd. -
Effect of sonication in enhancing the uniformity of MWCNT distribution in aluminium alloy AA2219 matrix
The present paper investigates the effect of premixing process on the distribution of 0, 0.5, 0.75, 1 and 2 wt.% multiwall carbon nanotubes (MWCNTs) and resultant properties of aluminium alloy AA2219 matrix. Premixing process consists of ultrasonication, magnetic stirring and mechanical stirring. FESEM was used for characterizing the distribution of reinforcement in the matrix. Ball milling with premixing was found to be effective in achieving better uniform distribution of the reinforcement than mere ball milling. Hardness testing of the composite revealed reinforcement of MWCNT enhances the matrix hardness. The thermal stability of composite as evidenced by DTA analysis proved the presence of MWCNT without any structural damages. 2019 Elsevier Ltd. All rights reserved. -
A novel image compression method using wavelet coefficients and Huffman coding
Compressing medical images to reduce their size while maintaining their clinical and diagnostic information is crucial. Because medical images can be large and demand a lot of storage and transmission capacity, effective compression methods aid medical institutions in better storing and transmitting medical images, reducing costs, speeding up data transfer, and simplifying managing image databases. However, it is essential to note that image compression in medical imaging can also introduce drawbacks, such as loss of information and poor output image quality. Therefore, a suitable compression algorithm and parameter must be chosen to balance file size and visual fidelity. This paper suggests an effective image compression method employing the Discrete Wavelet Transform (DWT), followed by a reduction operation and Huffman coding to produce a mere lossless encoding to transmit the images over a channel. The extracted DWT coefficients are mapped to the nearest integral value. All four sub-bands of DWT are joined, and then a window of 3 3 is selected for reduction operation by choosing the origin as the pivot element. The Huffman coding algorithm is used to compress the processed image. The pivot origin element is used in the reversible reduction while uncompressing the image. When sending compressed data across an unreliable route, the window size and pivot element selection keep the compressed data secure. Standard measures such as bits per pixel (BPP) and compression ratio (CR) are used to assess the suggested approach. The efficiency of the suggested course of action is supported by the research's findings, which use a peak signal-to-noise ratio (PSNR) of 54.66 dB. 2023 The Authors -
Impulse noise recuperation from grayscale and medical images using supervised curve fitting linear regression and mean filter
Acquisition of images from electronic devices or Transmission of the image through any medium will cause an additional commotion. This study aims to investigate a framework for eliminating impulse noise from grayscale and medical images by utilizing linear regression and a mean filter. Linear regression is a supervised machine learning algorithm that computes the value of a dependent variable based on an independent variable. The value of the recuperating pixel is measured using a curve-fitting, direction-based linear regression approach or applying a mean filter to the noise-free pixels. The efficiency of the proposed technique experiments with benchmark test images and the images of the USC-SIPI and TESTIMAGES data sets. Peak signal-to-noise ratio (PSNR) and structural similarity index metrics (SSIM) are determined to prove the performance of the proposed method. The results, when compared with the seven recent state-of-the-art techniques, show the superiority of the proposed method in terms of visual quality and accuracy. The proposed model achieves an average PSNR value of 65.21dB and an SSIM value of 0.999 for the reconstruction of medical images, proving its accuracy and efficiency. The impulse noise restoration process helps the radiologist get a clear visual clarity of the medical image for diagnosis purposes. 2022 Institute of Advanced Engineering and Science. All rights reserved. -
Securing grayscale image using improved Arnold transform and ElGamal encryption
The security of sensitive data is critical, and it opens up a wide area of research to find efficient and effective methods to prevent unauthorized access. Our study provides a secure framework for sending visual information over an untrusted channel, such as a social networking site. The proposed framework is a combination of scrambling and encryption techniques. Initially, a hybrid block-wise and pixel-wise scrambling approach is administered to the grayscale image, followed by the Arnold transform, which causes all pixel points to move within the image. Finally, to improve the efficiency of the diffusion process, the asymmetric encryption ElGamal algorithm has been mastered. Peak-signal-To-noise ratio (PSNR), structural similarity index metric (SSIM), number of pixels change rate (NPCR), and unified average changing intensity (UACI) are the metrics utilized to evaluate the efficiency of the proposed scheme. The efficiency of the suggested scheme validates the low-Average PSNR value of <9 dB and the SSIM average value of <0.01 for the encrypted images. The NPCR and UACI values achieved in our study are above the threshold values of 99.6% and 33.33%, respectively, exhibiting the strength of the proposed framework. 2022 SPIE and IS&T. -
An improved compocasting technique for uniformly dispersed multi-walled carbon nanotube in AA2219 Alloy Melt
Technology transfer for economic bulk production is the greatest challenge of the era. Production of high strength lightweight materials with nanocarbon reinforcement has attained its importance among the researchers. Property enhancement with multi-walled carbon nanotube (MWCNT) reinforcement is reported by all researchers. But effective utilization of its property remains a challenge even though it is the strongest material in the world. Achieving homogeneous dispersion especially in molten metal is a complex task. To address the same, a new approach was tried which could trigger de-bundling and make a uniform dispersion. Various metallurgical and mechanical characterizations were done. Grain refinement and the structure were studied with an optical microscope, MWCNT dispersion and structural damage was studied using field emission scanning microscope, Phase change and reactions during casting was done with XRD scan. The method remarkably facilitated 23.7% and 69.75% improvement in hardness and ultimate compressive strength respectively with the addition of MWCNT. Faculty of Mechanical Engineering, Belgrade. -
Risk Behavior Among Emerging Adults: The Role of Adverse Childhood Experiences (ACE), Perceived Family and Interpersonal Environment
Background: Evidence demonstrates that ambiance provided during childhood and the interactions of children with different social agents during childhood have an impact on their adult behaviour. Objective: The current research tries to explore the role of adverse childhood experiences and perceived family and interpersonal interactions in their resultant adult risk behaviour. Method: Around 613 emerging adults (1824 years; Male 343 and Female 270) from the northern districts of Kerala, India took part in the study. The participants were selected using multistage sampling techniques. A Semi-structured Questionnaire was used to understand the perceived family and interpersonal environment. In addition, a checklist (adopted from the risk behaviour scale and youth risk behaviour survey) was also employed. The checklist assisted to understand the presence of actual risk behaviours. Results: Hierarchical Logistic Regression analysis is used to test the hypotheses. The results revealed that 87.2 % of the participants were engaged in at least one type of risk behaviour. Socio-demographic variables (gender and family type) and items of perceived family and interpersonal relationships and adverse childhood experiences were found to be significant predictors of emerging adult risk behaviour. Conclusion: The results further highlight the significance of childhood experiences and the current family environment of emerging adults in understanding their behaviour, and in designing evidence-based intervention program for emerging adults. 2023 The Author(s). -
Child friendly schools: Challenges and issues in creating a positive and protective school environment
Schools are considered to be one of the safest places where children are seen on a daily basis and are under the supervision of teachers who are trained and equipped caregivers. Children are victims of all forms of abuse, punishment, neglect, discrimination, and ill-treatment within the school setting. Though there are various policies and programmes at international and national levels, addressing child protection has been a serious challenge for every community. Children need to be protected and any acts that hamper their well-being and safety need to be curbed. The objective of this chapter is to critically evaluate school-based child-protection programmes and suggest a model of child protection through positive schooling. Positive schooling is an approach to create a healthier and safer school environment. Positive schooling emphasises inclusiveness, strength-based education, developing character strengths, creating least restrictive environments, and fostering well-being among the school community, including students and teachers. It aims at creating a positive culture where every learner gets equal opportunities to learn and develop. It gives value to overall well-being of the individual and happiness within the learning environment. It promotes positive teaching strategies without the use of punishment and pressure. The positive culture within the school environment would promote peer support and collaboration, preventing bullying and abuse. Learners and facilitators would respect and support each other, focusing on strengths rather than weakness, which would, in turn, create an inclusive environment accommodating everyone. The chapter also highlights the need for: trained professionals, like counsellors, in school settings; stronger school-based polices; and the need for collaboration among school administrators, counsellors, teachers, and parents. Springer Nature Singapore Pte Ltd. 2018. -
Effect of a novel sintering technique: hot coining on microstructure and mechanical properties of MWCNT reinforced Al metal matrix nanocomposite
Fabrication of MWCNT-reinforced nanocomposites with uniform distribution is still remaining as a challenge. Even for researchers who achieved uniform distribution in powder, boundary agglomerations are observed after sintering. Hot coining (HC) a novel technique for bulk sampling can achieve uniform distribution during sintering. Several mechanical testing and characterisation methods are applied closely to explore the mechanical properties and structural features of the hot coined AA2219-MWCNT composites. Hot coining results in significant improvement of mechanical properties when reinforced with 0.75wt.% MWCNT shows 38.8 % (Rockwell hardness), 106% (UTS), 183 % (impact strength) and 76% (radial crushing strength). But retardation in mechanical properties was observed above 0.75wt. %. During HC particle rearrangement and pushing of MWCNT towards particle boundary is not taking place as in other conventional and advanced sintering technology. The fracture surface of HC tensile specimen shows uniform dispersion and MWCNT alignment in the matrix. The fracture surface shows the mixed mode of fracture (ductile-brittle), and ductility is found to be decreasing with increased MWCNT concentration. 2021 Informa UK Limited, trading as Taylor & Francis Group. -
Antibacterial performance of GOAg nanocomposite prepared via ecologically safe protocols
Control and extinction of the rising problem of antimicrobial resistance makes a multidisciplinary approach for the advancement of novel disinfectant agents imperative. Although graphene-based nanomaterials display high bacterial toxicity, their cytotoxicity to mammalian cells is found to be very low. Herein, a simple green approach for the synthesis of graphene oxidesilver composite using Syzgium cumini (Indian black plum) fruit extract was reported. Physicochemical properties and antibacterial activities of the composite were subsequently studied comparing with silver nanoparticles and pure graphene oxide. We demonstrate the influence of precursor materials in dictating the antibacterial properties of nanosystems. The antibacterial study conducted on selected gram-negative and gram-positive bacteria reveals that composite is more effective against gram-negative bacteria. The microbicidal activity of composite against bacteria Pseudomonas aeruginosa and E. coli, was higher than the control drug cephalexin (CE control). Test compounds against L929 cell lines by MTT assay reveal the low cytotoxicity of samples. From the statistical analysis, it is inferred that the cell viability is dependent on the concentration. Fruit extract-based graphenesilver composite could be an excellent environment-friendly replacement for harsh disinfectants. 2020, King Abdulaziz City for Science and Technology. -
Electrochemical efficacies of coal derived nanocarbons
Carbon based nanomaterials are acknowledged for their admirable optical, electrical, mechanical characteristics and broad class of applications. Choice of precursor and simple synthesis techniques have decisive roles in viable production and commercialization of carbon produce. The intense demand to develop high purity carbon nanomaterials through inexpensive techniques has promoted usage of fossil derivatives as feasible source of carbon. Coal serves as a naturally available, abundant and cheap feedstock for carbon materials. From the crystalline clusters of aromatic hydrocarbons in a cross-linked network, carbon nanostructures can easily be extracted through green synthesis routes. It promotes a potent alternative for the cost effective and scaled up production of nanocarbon. The well-developed pores distribution, presence of numerous active sites and appropriate migration channels for ions enhance the electrochemical parameters necessary for the fabrication of supercapacitors, batteries and electrochemical sensors. The metallic impurities contained in coal contribute towards faradic redox reactions required for an efficient electrode modification. In this review, the potential uses of coal based carbon nanomaterials in energy storage and environmental sectors are discussed in detail. 2020, The Author(s). -
Dielectric performance of graphene nanostructures prepared from naturally sourced material
Cost-effective and environmentally benign approach was adopted for the synthesis of oxidized graphene nanostructures from the precursor coke via Improved Hummers' method. The surface states of oxygen functional groups provided strong polarization for enhanced dielectric properties. Occurrence of dipole and interfacial polarizations in the low frequency region contributed to the dispersive behaviour of ?', ?", and tand.The relaxation phenomenon of the structure lead to an augmented electrical conductivity with increase in frequency. Our finding reveals the advantageous fabrication of graphene nanostructure having high dielectric constant (1 0 5) but with low loss which can be used in advanced nanodielectrics. 2020 Elsevier Ltd. All rights reserved. -
Application of Nanomaterials in Fuel Cell and Photovoltaic System
The emerging appliances and components of nanotechnology facilitate pioneering and cost-efficient strategies to meet the ever-growing energy demands. Employment of nanomaterials fetched innovative approaches for processing, storing, and exchange of energy owing to its nanosized and well-defined structure. This review presents an overview of the involvement of nanomaterials that made breakthroughs in the field of fuel cell and photovoltaic technologies. While the morphologies and unique dimensions of nanostructures offered novel electrolytes and high surface area for fuel cell catalysts; the probability of quick separation and collection of photogenerated charge carriers was enhanced in solar cells. This book chapter will focus on the recent research and developments for improving efficiency and lower device fabrication cost in nano-enabled fuel and solar cells. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Opto-electric property relationship in phosphorus embedded nanocarbon
Graphene, due to its zero band gap, has an excellent combination of the important features such as ballistic transport, tensile strength and chemical tuning, which are practically hindered in opto-electric applications. The precursors used in the production of nanocarbon are relatively costlier; however, that their production processes include difficulties is a harder problem. It is possible to control the size, structure and properties of the produced nanocarbon matrix by tuning sp2 domains in the matrix. In this respect, the coal, being a potential candidate for the synthesis of nanocarbon which holds promising applications, has attracted remarkable interest. The nanocarbon structure reported in this paper was synthesized from bituminous coal and then phosphorus atoms were added into the produced structure in order to obtain resultant composite structure, whose structural properties were illustrated here in detail by using the X-ray, IR and UVVisible spectroscopy techniques. A systematical analysis of the optical and electrical properties of the produced composite has revealed that a composite structure to be produced in the ratio 1:2 of nanocarbon + phosphorus has better optical and electrical properties. We report here that the composite produced in this study from nanocarbon by adding phosphorous atoms shows unique photoluminescent property in particular due to the dominance of quantum confinement and oxygen functionalities. The observed increase in the dielectric strength, which results from interfacial polarization and its frequency independent nature, is desirable for the fields such as supercapacitor, sensor, stealth applications etc. 2018 The Authors -
Luminescence and energy storage characteristics of coke-based graphite oxide
The substantial escalation in both energy consumption and ecological crisis prompts the utilization of conventional pollution-causing energy resources towards a proficient mode of energy production and storage. The most polluting fossil fuel like coal possesses a highly ordered sp2 carbon clusters, that can be easily tailored into graphene derivatives promising for energy-related applications. However, the impact of crystallinity and quality of the precursor coke on the physicochemical characteristics of extracted carbon nanostructures need to be identified. Herein, we have prepared graphite oxide structures (GrO) from high-quality coal, coke via Improved Hummers' method eliminating the need for toxic NaNO3. The inherent defect states own by coke are also of high significance as it performs the role of various photoluminescence emission centers. The sp2 domains and different surface defects promote excitation independent and dependent luminescence substantiating the distinct multi-emission property of GrO. The extent of functionalization during the oxidation process has also significantly affected the thermal stability of the carbogenic structure. The symmetric galvanostatic charge-discharge curves and lower internal resistance present superior stability and fatser ion transport of as-synthesized GrO. A specific capacitance of 193F/g was obtained at 0.2A/g with excellent capacitance retention over 2500 cycles. The versatile attributes of the coke derived GrO validate its realizable optoelectronics and energy storage applications. 2020 Elsevier B.V. -
Heteroatom engineered graphene-based electrochemical assay for the quantification of high-risk abused drug oxytocin in edibles and biological samples
The naive detection of scheduled H drug oxytocin is a vital requisite, owing to its deleterious impact on societal affluence prompted by unconstrained usage. Therefore, a reliable, cost-effective, and quick-to-respond analytic technique for this drug is in ample demand. In this work, we report electrochemical detection of oxytocin employing novel nitrogen, phosphorus co-doped coke-derived graphene (NPG) modified electrode. The electro-oxidation behavior of oxytocin was investigated on the NPG modified electrode by square wave stripping voltammetry (SWSV) in 0.1 M phosphate buffer of pH 7. The oxidation peak current was linear in two ranges, spanning from 0.1 nM to 10 nM and 15 nM to 95 nM. The limit of detection at the NPG electrode was calculated to be 40 pM. The practical application of developed sensor for the determination of oxytocin was examined in edible products and body fluids, hence signifying the possibility of having real-time surveillance over its misusage. 2022 Elsevier Ltd -
Doable production of highly fluorescent, heteroatom-doped graphene material from fuel coke for cellular bioimaging: An eco-sustainable cradle-to-gate approach
The manifold usage of fluorescent materials and their pliable association with optical imaging techniques have made great strides in unfolding the incredible potential of biotechnological research, particularly in cancer treatment, from point-of-care assay to clinical applications. Enlarged nuclei or numerous counts often indicate tumor growth activity, and these expressions can be visualized with the aid of fluorescence imaging. Therefore, developing highly fluorescent, biocompatible, and sustainable biomarkers for imaging is a vital necessity for their extensive application in cancer diagnosis and therapy. In this work, we have demonstrated the cradle-to-gate transformation of abundant and cheap fossil fuel coke into a fluorescent probe for bioimaging. Herein, for the first time, a facile strategy for modulating the emission characteristics of coke-derived graphene system via doping of heteroatoms has been reported. It is found that the doping of nitrogen atoms could strongly influence photophysical properties, giving rise to increased quantum yield (16%), extended fluorescence lifetime (8.51 ns), and higher photostability (92%). Moreover, the as-synthesized nitrogen-doped graphene derivative is used as a potential labelling agent for the cellular imaging of cancerous cells, as well as normal cells, at concentrations ranging from 0 to 100 ?g/mL. For 24h incubation, the cells cultured with a concentration of 25 ?g/mL were observed to have an appreciable fluorescence accompanied by significant biocompatibility, with a viability value of ?85%. Considering the heteroatom-induced emission characteristics and bioanalytical acuities, it is prospective that the coke-derived graphene system can be further explored to elucidate its significance in biomedical applications, without compromising on economic and environmental sustainability. 2022 Elsevier Ltd -
Fuel coke derived nitrogen and phosphorus co-doped porous graphene structures for high-performance supercapacitors: The trail towards a brown-to-green transition
As the looming crisis of global energy market exponentially intensifies, the scientific community prompts the use of supercapacitors as a sustainable energy production/storage model and emission reduction strategy. Therefore, in this work, we present a cutting-edge approach for the high-value utilization of fossil fuel-derived materials in supercapacitor applications, promoting an integrated brown-to-green transition for energy, ecology, and the environment. Herein, nitrogen and phosphorus co-doped porous graphene sheets (a-NPGO) have been prepared from fuel coke, which exhibits outstanding electrochemical performance as a supercapacitor electrode material. The a-NPGO shows a high specific capacitance (322 F/g at 1 A/g) almost 11 times greater than the undoped coke-based graphene derivative. Furthermore, the symmetric supercapacitor assembled with a-NPGO-modified electrodes delivered an exceptional power density of 812 W/kg at energy density of 14 Wh/kg and an excellent capacitance retention of 90 % after 5000 charge-discharge cycles. This impression of coke-derived material in high-performance supercapacitors may broaden the horizon of the current electrochemical energy storage paradigm and afford the eco-conscious implementation of fossil fuel resources. 2023 Elsevier Ltd