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Blockchain abetted supply chain management /
Patent Number: 202241004710, Applicant: Ghanesh Gunaseelan.
The invention block chain abetted'supply chain management comprising, a physical product receiver gets the information by a smart label through accessing a block of a blockchain stored on a computer system, a cold chain requirement for a product, wherein the smart label is associated with a package containing the product, the cold chain requirement ' for the product is stored in the block of the blockchain. -
Blockchain abetted supply chain management /
Patent Number: 202241004710, Applicant: Ghanesh Gunaseelan.
The invention block chain abetted'supply chain management comprising, a physical product receiver gets the information by a smart label through accessing a block of a blockchain stored on a computer system, a cold chain requirement for a product, wherein the smart label is associated with a package containing the product, the cold chain requirement ' for the product is stored in the block of the blockchain. -
Block chain-based security and authentication for forensics application using consensus proof of work and zero knowledge protocol
The technique that checks the origin, integrity, Zero-Knowledge authenticity of photographs is known as image authentication. Numerous studies on image authentication have revealed numerous trade-offs between four desirable features, namely robustness, security, flexibility, and efficiency. This study demonstrated a high-security Forensic Image (FI) as well as an authentication mechanism. Initially, the FI considered image registration with features for the Consensus method (CM) to generate blocks on each feature using a hypothesis test-based similarity measure. Because Proof-of-Work (PoW) blockchain technology is widely used, maintaining the Consensus PoW(CPoW) requires a massive amount of computing power. ZKP authentication is a critical cryptographic mechanism that authenticates network nodes without revealing the users identity or any other data given by the user. The blockchain stores the secret information, as well as the hash value of the original FI. This allows for the tracking of all medical pictures exchanged through the proposed blockchain network. The blockchain stores the private information as well as the hash value of the original medical image. The experimental results indicate the utility of the proposed approach with performance measures in contrast to established security analysis methods. Bharati Vidyapeeth's Institute of Computer Applications and Management 2024. -
Block chain-based security and authentication for forensics application using consensus proof of work and zero knowledge protocol
The technique that checks the origin, integrity, Zero-Knowledge authenticity of photographs is known as image authentication. Numerous studies on image authentication have revealed numerous trade-offs between four desirable features, namely robustness, security, flexibility, and efficiency. This study demonstrated a high-security Forensic Image (FI) as well as an authentication mechanism. Initially, the FI considered image registration with features for the Consensus method (CM) to generate blocks on each feature using a hypothesis test-based similarity measure. Because Proof-of-Work (PoW) blockchain technology is widely used, maintaining the Consensus PoW(CPoW) requires a massive amount of computing power. ZKP authentication is a critical cryptographic mechanism that authenticates network nodes without revealing the users identity or any other data given by the user. The blockchain stores the secret information, as well as the hash value of the original FI. This allows for the tracking of all medical pictures exchanged through the proposed blockchain network. The blockchain stores the private information as well as the hash value of the original medical image. The experimental results indicate the utility of the proposed approach with performance measures in contrast to established security analysis methods. Bharati Vidyapeeth's Institute of Computer Applications and Management 2024. -
Blind separation of speech from aortic regurgitation signals using Dhoulaths method
Conducting auscultation of traumatically distressed patients has always been demanding for medical professionals. The challenge calls for an innovative solution enabling doctors to conduct precise diagnoses despite other sound interference. This suggested study presents an entirely non-invasive and convenient method designed to aid doctors in routine diagnostic procedures. This study is centred on the segregation of aortic regurgitation heart sounds from speech. The mixture utilised for the study is a combination of speech and aortic regurgitation signals. The method applied for the study is a revised procedure of Blind Source component separation utilising a solo sensor method. With this technique, doctors are not compelled to prevent patients from articulating their pain or discomfort while diagnosing heart sounds. Doctors can offer a consoling word to patients while the auscultation is in progress without worrying about how the speech sounds affect the diagnosis. For babies, timely detection of heart-related issues can be life-saving. With Dhoulaths method, the distressing sounds of a babys cries can be effectively separated, thereby offering doctors clear audio of heartbeats. The study was conducted to ascertain if heartbeats can be segregated from the signals of speech or cries. This segregation procedure has succeeded in arriving at an enhanced level of clarity. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Blending the old with the new through technology- sanskrit and e-learning /
Internation Journal Of English Language, Vol.5(10), pp.57-64. -
Blending of Knowledge Management with Industry 4.0: A New Formula for Success!
The convergence of Industry 4.0 and knowledge management presents a transformative opportunity for organizations seeking enhanced efficiency and sustainable growth. In the context of organizational processes, the amalgamation of technological advancements and effective knowledge management practices can lead to a reduction in costs and an overall improvement in operational efficiency. Understanding the intricacies of knowledge management procedures is crucial, encompassing the production, transfer, acquisition, storage, and utilization of knowledge resources across the organizational spectrum. The advent of the fourth industrial revolution, commonly referred to as Industry 4.0, has significantly reshaped traditional knowledge management systems. Industry 4.0 introduces the interconnectivity of machines and their autonomous capacity to learn and share data. While both knowledge management and Industry 4.0 offer distinct benefits individually, a strategic approach that combines the strengths of both can unlock new opportunities for efficient business growth and success in the external environment. This article delves into the symbiotic relationship between Industry 4.0 and knowledge management, emphasizing their combined potential. Industry 4.0 generates vast volumes of data, and by leveraging knowledge management, organizations can derive valuable insights to inform decision-making processes. Historical data and best practices, accessible through knowledge management, contribute to process optimization. Integration with Industry 4.0 technologies, such as automation and the Internet of Things, further enhances process efficiency. The marriage of knowledge management and Industry 4.0 extends beyond process optimization to workforce development. Recognizing employees as the building blocks of an organization, this integration enables better management by upgrading knowledge and skills. Consequently, it enhances the overall productivity of the workforce, contributing to organizational success. In the dynamic landscape of globalization, technology, and competition, this chapter serves as a guide for organizations aiming to harness the collective power of knowledge management and Industry 4.0. By exploring their complementary benefits, it seeks to facilitate the informed utilization of these tools for the betterment and sustainability of businesses in the contemporary world. 2024 Scrivener Publishing LLC. -
Blended Learning and Its Impact on Cognition and Emotion
A lot of research has been conducted to improvise learning by means of smart incorporation of technology and multimedia. There exists a complex relationship between cognition and emotions; technology is used to elicit emotional responses to create an emotional state which people learn best. Given the increasing attention to the important relationship between learning and emotions, this chapter is about blended learning and the emotion experienced by the students. The blended learning model focuses on the learners freedom in the way that they learn and engross in their education. The cognitive goals are the achieved by maintaining learners interest throughout the course. This chapter also explores the intrinsic differences, such as individual characteristics and contextual motivational factors which influence learning. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020, Corrected Publication 2020. -
Blast resistance of steel plate shear walls designed for seismic loading
Since a blast loading or explosion can create nonlinear wave action and impact pressure on a structure, it necessary to construct a structure to resist blast loading as like other loads. In this study the nonlinear behaviour of a blast loading is simulated by calculating the pressure diagram with respect to time under the guidance of IS 4991-1968, code for "Criteria for Blast Resistant Design of Structures for Explosions above Ground". The study carried out for different charge weight (100kg TNT, 200kg TNT and 400kg TNT) and standoff distances of 20metre. Nonlinear behaviour of a Blast loading to steel structures with shear plates of thickness 6 mm, 8 mm and 10 mm are modelled in ETABS and the analysis is carried out to obtain base shear, story displacement, story deformation pattern, column forces, etc. Published under licence by IOP Publishing Ltd. -
Blackberry gel-assisted combustion modified MgO: Sm3+ nanoparticles for photocatalytic, battery, sensor and antibacterial applications
Green synthetic methods are currently preferred in industry over other physicochemical methods. Herein, we present a facile, environmentally friendly, non-toxic approach for the fabrication of MgO using jamun fruit extract. The phytochemicals present in the fruit extract, such as kaemferol, glucoside, anthocyanins, ellagic acid, myricetin, and isoquercetin, facilitate the bio-reduction of Mg(NO3)2. Pure and Sm3+ (17 mol %) doped MgO nanomaterials were synthesized using this bio-mediated synthetic method. The structural and morphological properties of the synthesized nanomaterials were studied using Powder X-ray diffraction (PXRD), Field Emission Scanning Electron Microscopy (FE-SEM), Energy Dispersive Spectroscopy (EDS), and Diffused Reflectance Spectroscopy (DRS) techniques. The effect of Sm3+ ions on the host matrix for the photo-catalytic oxidation of Fast Orange-Red (FOR) dye was investigated under UV light irradiation. MgO: Sm3+(3 mol %) exhibited superior (94 %) degradation of the dye compared to pristine and other doped catalysts, attributed to the maximum migration of charge carriers at the catalyst's surface. Additionally, the 3 mol % Sm3+ doped MgO electrode demonstrated a smaller charge transfer resistance, indicating superior capacitive properties compared to pristine and other doped electrodes. The synthesized materials also exhibited effective bacterial activity against pathogens. This research demonstrates the potential of the synthesized nanomaterials for environmental pollution purification, as well as their utility as electrode materials for supercapacitors, batteries, sensors, and antibacterial applications. 2024 The Author(s) -
Bivariate iterated FarlieGumbelMorgenstern stressstrength reliability model for Rayleigh margins: Properties and estimation
In this paper, we propose bivariate iterated FarlieGumbelMorgenstern (FGM) due to[Huang and Kotz (1984). Correlation structure in iterated Farlie-Gumbel-Morgenstern distributions. Biometrika 71(3), 633636. https://doi.org/10.2307/2336577] with Rayleigh marginals. The dependence stressstrength reliability function is derived with its important reliability characteristics. Estimates of dependence reliability parameters are obtained. We analyse the effects of dependence parameters on the reliability function. We found that the upper bound of the positive correlation coefficient is attaining to 0.41 under a single iteration with Rayleigh marginals. A comprehensive comparison between classical FGM with iterated FGM copulas is graphically examined to assess the over or under estimation of reliability with respect to ? and ?. We propose a two-phase estimation procedure for estimating the reliability parameters. A Monte-Carlo simulation study is conducted to assess the finite sample behaviour of the proposed reliability estimators. Finally, the proposed estimators are examined and validated with real data sets. 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. -
Bivariate Cointegrated Model with Gamma Innovations
The nature of time-bound data is its non-stationarity, that is, the constant presence of factors such as trend, seasonality, or both. Adopting mechanisms such as the method of differencing or ordinary least squares results in a loss of information or overestimation or underestimation of the parameters, respectively. A cointegration study reflects the notion of a long-run equilibrium, which is a concept of sensitivity in macroecometrics. Thus, cointegration can be defined as the onset of a longterm equilibrium between two or more time series that evolve under the influence of time, with the potential advantage of establishing a dynamic relationship using standard methods. Thus, this study explores the theoretical approach of estimating an error correction model for a cointegrated bivariate VAR (2) model with gamma innovation. To obtain the parameter estimates of the proposed model, we employ the conditional maximum likelihood estimation, implemented through the NewtonRaphson algorithm, because of the gamma distributions non-closed form nature. A theoretical study is strengthened by artificial simulations that support mathematical derivations. 2025 Scrivener Publishing LLC. -
Bithiophene and 3,4-Ethylenedioxythiophene Copolymers with Biphenyl and Bis-[octyloxy]benzene acceptors for NLO Application
Two groups of thiophene-based donoracceptor (DA) type conjugated copolymers with low band gaps were designed and synthesized through direct arylation. Biphenyl and bis(octyloxy)benzene were incorporated as electron-deficient units to effectively lower the band gaps. The HOMOLUMO energy levels of the resulting copolymers were theoretically determined using DFT calculations at the HSE06 and B3LYP levels with a 631G(d,p) basis set. The copolymers were characterized by UVVis, FT-IR, fluorescence, and H NMR spectroscopy. Their thermal stability was assessed using thermogravimetric analysis, which confirmed that the bithiophene-based copolymers P(BT-BP) and P(BT-DOB) were highly thermally stable. Additionally, P(BT-DOB) and P(EDOT-DOB) exhibited solvatochromic behavior in varying toluene/acetonitrile solvent mixtures. Third-order nonlinear optical properties of P(BT-BP), P(EDOT-BP), P(BT-DOB), and P(EDOT-DOB) were studied using an open-aperture Z-scan method at 532 nm in DMSO. These copolymers showed reverse saturable absorption with low optical threshold values. 2025 Elsevier B.V. -
Bismuth ferrite nanoparticles decorated CR2C MXENE: A highly efficient electrocatalyst for hydrogen evolution /
Patent Number: 202241040877, Applicant: B Shalini Reghunath.
The current invention demonstrates the efficiency of bismuth ferrite/Cr2C MXene binary composite as a highly efficient electrocatalyst for hydrogen evolution reaction in alkaline media. The methodology for preparing O2C MXene is by etching the O2AIC MAX phase with hydrofluoric acid for 30 min at room temperature. Cr2C MXene and bismuth ferrite nanoparticles are mixed under solvothermal conditions to obtain the bismuth ferrite/Cr2C-MXene binary composite. -
Bismuth ferrite nanoparticles decorated CR2C MXENE: A highly efficient electrocatalyst for hydrogen evolution /
Patent Number: 202241040877, Applicant: B Shalini Reghunath.
The current invention demonstrates the efficiency of bismuth ferrite/Cr2C MXene binary composite as a highly efficient electrocatalyst for hydrogen evolution reaction in alkaline media. The methodology for preparing O2C MXene is by etching the O2AIC MAX phase with hydrofluoric acid for 30 min at room temperature. Cr2C MXene and bismuth ferrite nanoparticles are mixed under solvothermal conditions to obtain the bismuth ferrite/Cr2C-MXene binary composite. -
Bismuth (III) oxide decorated graphene oxide filled epoxy nanocomposites: thermo-mechanical and photon attenuation properties
In this study, bismuth (III) oxide (Bi2O3) decorated graphene oxide (GO) nanocomposites were employed as novel radioprotective fillers in the epoxy matrix. Decoration of GO with Bi2O3 would transform it as carrier for Bi2O3 particles, thereby enhancing the thermo-mechanical and radiation shielding properties of the epoxy composites through effective filler distribution. Structural and compositional studies confirmed the successful decoration of Bi2O3 on the surface of GO. Thereupon, epoxy composites containing decorated fillers at different loadings (5, 10 and 15 wt%) were synthesized using solution casting technique. The correlation between surface decoration and filler loading was systematically examined as function of thermo-mechanical, viscoelastic and radiation shielding properties of the composites. These nanocomposites displayed good thermal resistance (~ 450 C), high glass transition temperature (~ 136 C), elastic modulus (~ 4.36 GPa) and storage modulus, thereby confirming the improved dispersion and better interfacial adhesion in the composites. The formation of continuous filler network across epoxy matrix formed by decorated fillers significantly improved X-ray and ?-ray shielding properties of epoxy composites in the wide energy range of medical interest (301332 keV). Shielding efficiency of these lowly loaded BGO/epoxy composites were comparable with the composites containing Bi2O3 nanoparticles alone and highly loaded microcomposites. 2022 Japan Society for Composite Materials, Korean Society for Composite Materials and Informa UK Limited, trading as Taylor & Francis Group. -
Bishwa Nath Mukherjee (19331997)
Bishwa Nath Mukherjee was a pioneering figure in psychology, notable for his extensive contributions to psychometrics, statistics, and education. His career included significant research roles, particularly at the B.M. Institute of Psychology and Child Development in Ahmedabad, where he led studies on learning efficiency and adapted the Wechsler Intelligence Scale for Children into Gujarati. His work in the USA involved groundbreaking projects on learning patterns, achievement motivation, and womens status, supported by institutions such as the Graduate School of Indiana University and the UNs Division of Human Rights. In India, he directed a project on industrial shift work and engaged in various studies on settlement planning, social attitudes, and mass communication. As a prolific author, Mukherjee wrote extensively on multivariate analysis, addressing topics such as self-concept, job-related needs, and educational assessment. His legacy encompasses diverse specializations, including advanced statistics, personality assessment, environmental psychology, and the evaluation of social programmes, making him a key contributor to contemporary psychology and social sciences. 2025 selection and editorial matter, Braj Bhushan; individual chapters, the contributors. -
Bipolar Disease Data Prediction Using Adaptive Structure Convolutional Neuron Classifier Using Deep Learning
The symptoms of bipolar disorder include extreme mood swings. It is the most common mental health disorder and is often overlooked in all age groups. Bipolar disorder is often inherited, but not all siblings in a family will have bipolar disorder. In recent years, bipolar disorder has been characterised by unsatisfactory clinical diagnosis and treatment. Relapse rates and misdiagnosis are persistent problems with the disease. Bipolar disorder has yet to be precisely determined. To overcome this issue, the proposed work Adaptive Structure Convolutional Neuron Classifier (ASCNC) method to identify bipolar disorder. The Imbalanced Subclass Feature Filtering (ISF2) for visualising bipolar data was originally intended to extract and communicate meaningful information from complex bipolar datasets in order to predict and improve day-to-day analytics. Using the Scaled Features Chi-square Testing (SFCsT), extract the maximum dimensional features in the bipolar dataset and assign weights. In order to select features that have the largest Chi-square score, the Chi-square value for each feature should be calculated between it and the target. Before extracting features for the training and testing method, evaluate the Softmax neural activation function to compute the average weight of the features before the feature weights. Diagnostic criteria for bipolar disorder are discussed as an assessment strategy that helps diagnose the disorder. It then discusses appropriate treatments for children and their families. Finally, it presents some conclusions about managing people with bipolar disorder. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Biowaste-Derived, Highly Efficient, Reusable Carbon Nanospheres for Speedy Removal of Organic Dyes from Aqueous Solutions
The current work explores the adsorptive efficiency of carbon nanospheres (CNSs) derived from oil palm leaves (OPL) that are a source of biowaste. CNSs were synthesized at 400, 600, 800 and 1000 C, and those obtained at 1000 C demonstrated maximum removal efficiency of ~91% for malachite green (MG). Physicochemical and microscopic characteristics were analysed by FESEM, TEM, FTIR, Raman, TGA and XPS studies. The presence of surface oxygen sites and the porosity of CNSs synergistically influenced the speed of removal of MG, brilliant green (BG) and Congo red (CR) dyes. With a minimal adsorbent dosage (1 mg) and minimum contact time (10 min), and under different pH conditions, adsorption was efficient and cost-effective (nearly 99, 91 and 88% for BG, MG and CR, respectively). The maximum adsorption capacities of OPL-based CNSs for BG were 500 and 104.16 mg/g for MG and 25.77 mg/g for CR. Adsorption isotherms (Freundlich, Langmuir and Temkin) and kinetics models (pseudo-first-order, pseudo-second-order and Elovich) for the adsorption processes of all three dyes on the CNSs were explored in detail. BG and CR adsorption the Freundlich isotherm best, while MG showed a best fit to the Temkin model. Adsorption kinetics of all three dyes followed a pseudo-second-order model. A reusability study was conducted to evaluate the effectiveness of CNSs in removing the MG dye and showed ~92% efficiency even after several cycles. Highly efficient CNSs with surface oxygen groups and speedy removal of organic dyes within 10 min by CNSs are highlighted in this paper. 2022 by the authors. -
Biowaste-derived hierarchical activated porous carbon with heteroatom-doping (N/S) for efficient symmetrical supercapacitors: A cow urine approach
The continuous accumulation of biowaste in the environment over extended periods can pose considerable ecological challenges. Hence, the conversion of natural biowaste into value-added products is essential. In this study, for the first time, carbon materials derived from cow urine, an animal waste, were explored as potential electrode materials for supercapacitors (SCs). Hierarchical, highly porous carbonaceous materials containing heteroatoms such as N and S were synthesized using a simple, template-free pyrolysis method, involving the direct carbonization of cow urine as a single precursor at 700 C (CCUR-700) and pre-KOH activation of the resulting cow urine deposit pyrolyzed at 700 C (A-CCUR-700) with a removal of inherent mineral salts. The resulting porous carbon materials were then employed as electrode materials for SC applications. The A-CCUR-700 electrode, with its abundant surface functionalities, high specific surface area (2651.7 m2/g), high porosity, good conductivity, and self-doped heteroatoms (N and S), demonstrated better charge storage performance compared to the CCUR-700 electrode. Notably, a two-electrode symmetric SC assembled using the A-CCUR-700 electrode demonstrated an excellent specific capacitance of 165 F/g at a current density of 0.5 A g?1. Furthermore, the A-CCUR-700 symmetric SC device achieved a high energy and power density of 22.9 Wh/kg and 5100 W/kg, respectively, with a capacitance retention of 95.3 % over 5000 cycles. Overall, the results of this study suggest that the synthesis of functionalized carbonaceous materials from cow urine may open up new possibilities for producing inexpensive electrode materials for electrochemical value-added applications. 2025