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Machine LearningEnabled NIR Spectroscopy. Part 2: Workflow for Selecting a Subset of Samples from Publicly Accessible Data
Abstract: An increasingly large dataset of pharmaceuticsdisciplines is frequently challenging to comprehend. Since machine learning needs high-quality data sets, the open-source dataset can be a place to start. This work presents a systematic method to choose representative subsamples from the existing research, along with an extensive set of quality measures and a visualization strategy. The preceding article (Muthudoss et al. in AAPS PharmSciTech 23, 2022) describes a workflow for leveraging near infrared (NIR) spectroscopy to obtain reliable and robustdata on pharmaceutical samples. This study describes the systematic and structured procedure for selecting subsamples from the historical data. We offer a wide range of in-depth quality measures, diagnostic tools, and visualization techniques. A real-world, well-researched NIR dataset was employed to demonstrate this approach. This open-source tablet dataset (http://www.models.life.ku.dk/Tablets) consists of different doses in milligrams, different shapes, and sizes of dosage forms, slots in tablets, three different manufacturing scales (lab, pilot, production), coating differences (coated vs uncoated), etc. This sample is appropriate; that is, the model was developed on one scale (in this research, the lab scale), and it can be great to investigate how well the top models are transferable when tested on new data like pilot-scale or production (full) scale. A literature review indicated that the PLS regression models outperform artificial neural network-multilayer perceptron (ANN-MLP). This work demonstrates the selection of appropriate hyperparameters and their impact on ANN-MLP model performance. The hyperparameter tuning approaches and performance with available references are discussed for the data under investigation. Model extension from lab-scale to pilot-scale/production scale is demonstrated. Highlights: We present a comprehensive quality metrics and visualization strategy in selecting subsamples from the existing studies A comprehensive assessment and workflow are demonstrated using historical real-world near-infrared (NIR) data sets Selection of appropriate hyperparameters and their impact on artificial neural network-multilayer perceptron (ANN-MLP) model performance The choice of hyperparameter tuning approaches and performance with available references are discussed for the data under investigation Model extension from lab-scale to pilot-scale successfully demonstrated Graphical Abstract: [Figure not available: see fulltext.]. 2023, The Author(s). -
Machine Transliteration of Handwritten MODI Script to Devanagari using Deep Neural Networks
The transliteration process involves transcribing words from the source language into the target language that uses a different script. Language and scriptural hurdles can be overcome via transliteration systems. There is a demand for automated transliteration systems due to the existence of several languages and the growing number of multilingual speakers. This study focuses on the Machine Transliteration of handwritten MODI script to Devanagari. MODI script was the official script for Marathi till 1950. Although Devanagari has, since then, taken over as the Marathi languages official script, the MODI script has historical significance as large volumes of its manuscripts are preserved in libraries across different parts of India. However, MODI into Devanagari transliteration is a difficult task because MODI script documents are complex in nature and there is no standard dataset available for the experiment. Machine Transliteration can be approached either as a Natural Language Processing task or as a pattern recognition task. In this research work, the transliteration task is carried out using the pattern recognition technique. The transliteration of MODI script to Devanagari is implemented using Convolutional Recurrent Neural Network (CRNN) based Calamari OCR, which is open-source software. An accuracy of 88.14% is achieved in character level matching of each word in the MODI to Devanagari transliteration process. When considering the entire word matching, the accuracy achieved is 61%. Machine Transliteration of MODI script documents results in the retrieval of large repositories of knowledge from ancient MODI manuscripts. (2024), (Research Institute of Intelligent Computer Systems). All rights reserved. -
Machine-Learning Based Sleep Pattern Analysis Using Linear Regression Algorithm
This article is investigating the connection between sleep patterns and concentration spans among university students while exploring the potential influence of MyersBriggs Type Indicator (MBTI) personality types on these aspects. The primary objective is to understand how sleep duration affects students ability to maintain focus and how their personality traits might interact with this relationship. Data was collected from university students aged 1619 using a multiple-choice form. The key variables analyzed were age, MBTI personality types, sleep duration, concentration span, and effective study ranking. Pearson's correlation was employed to examine these relationships. Additionally, a linear regression model was developed to predict concentration span based on sleep hours. The findings revealed a strong positive correlation 0.758 between sleep duration and concentration span, suggesting that increased sleep is associated with longer concentration spans. A moderate positive relationship 0.249 was also observed between concentration span and effective study ranking. However, the analysis showed a negligible relationship ? 0.008 between MBTI personality types and concentration span, indicating that within the context of this study, personality type does not significantly influence concentration span. This research emphasizes the critical role of sleep in academic settings and challenges the assumption that personality types significantly impact concentration span and sleep patterns. The linear regression model developed provides a predictive tool for understanding the impact of sleep on concentration, underscoring the importance of adequate sleep for academic success. This research is contributing to the broader understanding of factors influencing student performance and offers practical insights for optimizing study habits and educational strategies. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025. -
Machining Characteristics Evaluation of Al7075TiB2 In Situ Composite Using Abrasive Water Jet Machining with Varied Test Parameters
The study delves into the abrasive water jet (AWJ) cutting of an Al7075TiB2 metal matrix composite that was synthesized in situ. The primary goal is to investigate how variations in three key process parameters, namely, stand-off distance (SOD) ranging from 0.5 to 2.5mm, abrasive flow rate (100 to 300gmin), and traverse speed (100 to 500mmmin), affect three critical performance metrics: volumetric material removal rate (VMRR), dimensional accuracy, and surface roughness (SR). The study's findings were represented graphically, highlighting the relationships between these responses and the aforementioned process parameters. Scanning electron microscopy (SEM) was also used to examine the machined surfaces. It was discovered that increasing traverse speed resulted in significant increases in surface roughness, VMRR, and dimensional errors. An increase in the SOD, on the other hand, resulted in an increase in surface roughness, VMRR, and a decrease in dimensional accuracy. Furthermore, increasing the abrasive flow rate resulted in lower surface roughness and dimensional accuracy while achieving a higher VMRR. 2023, The Institution of Engineers (India). -
Machining Characteristics Evaluation of Al7075TiB2 In Situ Composite Using Abrasive Water Jet Machining with Varied Test Parameters
The study delves into the abrasive water jet (AWJ) cutting of an Al7075TiB2 metal matrix composite that was synthesized in situ. The primary goal is to investigate how variations in three key process parameters, namely, stand-off distance (SOD) ranging from 0.5 to 2.5 mm, abrasive flow rate (100 to 300 g min), and traverse speed (100 to 500 mm min), affect three critical performance metrics: volumetric material removal rate (VMRR), dimensional accuracy, and surface roughness (SR). The studys findings were represented graphically, highlighting the relationships between these responses and the aforementioned process parameters. Scanning electron microscopy (SEM) was also used to examine the machined surfaces. It was discovered that increasing traverse speed resulted in significant increases in surface roughness, VMRR, and dimensional errors. An increase in the SOD, on the other hand, resulted in an increase in surface roughness, VMRR, and a decrease in dimensional accuracy. Furthermore, increasing the abrasive flow rate resulted in lower surface roughness and dimensional accuracy while achieving a higher VMRR. The Institution of Engineers (India) 2023. -
MADeGen: Multi-Agent based Deep Reinforcement Learning for Sequential Keyphrase Generation
Keyphrase generation is an essential tool in the field of natural language processing for information retrieval, document summarization, and text recommendation applications, extracting succinct and representative phrases from the text document. Traditional keyphrase extraction methods applied the supervised or unsupervised learning fail to capture the sequential keyphrase generation in a dynamic environment. The keyphrase generation approaches lack focus on explicitly discriminating the present and absent keyphrases, leading to the inadequate generation of semantically rich absent keyphrases. Hence, this work utilizes the potential benefits of reinforcement learning with the design of a distinguished reward function for present and absent keyphrases for sequential decision-making in the keyphrase generation. Thus, this work presents a novel keyphrase generation system, MADeGen, utilizing Multi- Agent Deep Reinforcement Learning (MADRL). In particular, a multi-agent reinforcement system collaboratively enables the generation of representative and coherent keyphrases by the evaluation metric-aware cooperative reward function analysis and adaptively training the agents. The proposed MADeGen incorporates two major phases, such as multi-agent modelling and actor critic-based policy optimization towards accurate keyphrase generation. In the first phase, the proposed approach designs two learning agents, including the extraction agent and generation agent, with the incorporation of a pre-trained language model. In the multi-agent system, the generation agent is the finetuned version of the extraction agent with the integration of the Wikipedia source. Secondly, the evaluation-aware adaptive reward function is designed to evaluate each agent's generated keyphrases with reference to ground-truth keyphrases. In subsequence, the cooperative reward analysis triggers the actor critic-based policy optimization for the generation agent in the multi-agent system to precisely generate the semantically relevant keyphrases with the assistance of an external web source. Experimental results on several benchmark datasets, such as Inspec, PubMed, and wiki20, illustrate the effectiveness of the proposed MADeGen compared to the existing keyphrase extraction models, yielding state-of-the-art performance in keyphrase extraction tasks. The proposed MADeGen proves its higher performance in the present as well as absent keyphrase extraction as 0.367 and 0.438 F1-score, respectively, while testing on the Inspec dataset. (2024), (Intelligent Network and Systems Society). All Rights Reserved. -
Madhavrao Babasaheb Ghorpade (19262019)
This chapter highlights the significant contributions of M.B. Ghorpade to the field of psychology in India, emphasizing his foresight and dedication to documenting the evolution of this discipline. Ghorpades work included the publication of essential reading materials on psychological testing and abnormal psychology, along with numerous research papers and articles in various journals. His influential publications include An Introduction to Experimental Psychology, Essentials of Psychological Testing, Essentials of Psychology, Essentials of Social Psychology, Industrial Psychology, and Introduction to Modern Psychotherapy. Through his scholarly endeavours, Ghorpade ensured that future generations have access to a well-grounded understanding of psychological principles and practices. 2025 selection and editorial matter, Braj Bhushan; individual chapters, the contributors. -
Madhubala
Madhubala stamp was originally issued on 18 March, 2008. The Department of Posts issued the commemorative stamp on Madhubala, one of the most enduring legends of Indian cinematic history. -
MADTRAS: Dataset for aspect-based sentiment analysis of movie reviews in Tamil
The rise of online platforms has led to a growing trend of people expressing their thoughts and emotions in their native languages. Movies have been a predominant topic of discussion on online platforms where people reflect on various aspects of movies. Aspect-based Sentiment Analysis (ABSA), a computational technique, assists in examining the sentiments hidden in these discussions. Two challenges arise when attempting to use ABSA to identify sentiments in movie reviews written in the Indian regional language Tamil; the former being the unavailability of potential Tamil movie review datasets and the latter being the difficulty that arises due to the agglutinative nature of Tamil Language. This work addresses the first challenge by curating an annotated movie review dataset in Tamil, MADTRAS (Dataset for Aspect-based Sentiment Analysis of Movie Reviews in Tamil). The quality of the dataset is ensured through content and annotation evaluation. To prove the efficiency of the dataset, the multilingual BERT (mBERT) was used, and the performance was compared with other Deep Learning(DL) models. 2025 The Authors -
MAGAZINE COVER: AN ARTISTIC EXPRESSION AND A METHOD TO COMMUNICATE WITH THE READERS
The dissertation aims at going deeper than what meets the eyes, in terms of design and creativity with the help of semiotic analysis. The researcher conducted semiotic analysis of eight issues of Bloomberg Businessweek and Wired magazine??s cover pages, in an attempt to decode and deconstruct the nuances of the cover page. Stylistically all the cover pages considered for the semiotic analysis are covers that have several connotations and denotations. These aspects are generally neglected by the readers and there has been a constant need to decipher the underlying meaning. A lot of creative thought that goes into the creation of these cover pages as it involves a combined effort of the editorial and the design team with best of creative minds coming together. Here the attempt by the researcher is too look into that aspect of the cover which goes beyond the obvious. -
MAGIC AND TERROR IN EASTERINE KIRES ECOLOGICAL FICTION: Indigenous Naga Ecofeminism and Conservation Ethics
Indigenous women across the globe are front-line environmental activists implementing sustainable living practices and conservation through their activism and narratives. Indigenous women writers from Nagaland dominate published creative work from the region, making creative writing a space of resistance and representation. Native or Indigenous knowledge systems revolve around ecocultural practices of sustainability and conservation ethics. The Tenyimia worldview of the Angami Nagas of Nagaland opens up possibilities of ecological ethics and sustainable living through its knowledge systems. A minority Indigenous community in the Northeast region of India, the Angami Nagas represent a worldview that offers sustainable living practices and means of forest conservation through narratives that incorporate magic and terror. Easterine Kire, a renowned writer from Nagaland, has revived the eco-culture of the community through her representation of the Tenyimia worldview, offering insights into Indigenous ecofeminist views through her narratives, which she terms Peoplestories.' The present chapter investigates how magic and terror in Easterine Kires fiction represent forms of Indigenous knowledge that help define ecological ethics. The study applies an Indigenous ecofeminist approach to Easterine Kires work which invokes magic and terror through forest spirits, river spirits, and environmental legends such as the Tekhumevi, or were-tiger, to offer a re-imagination of the ecological spaces traditionally reflected through the communitys oral narratives. 2025 selection and editorial matter, Ina C. Seethaler and Tripthi Pillai; individual chapters, the contributors. -
Magical mushroom Ganoderma-A Promising treatment for cancer
[No abstract available] -
Magnetic coupling across the antiferromagnetic-antiferromagnetic interface
We investigate the magnetic coupling across the antiferromagnetic-antiferromagnetic (AFM-AFM) interface for the prototypical CoO-NiO bilayer system where the bulk Nl temperature (T N ) of NiO is higher than that of CoO. Using the temperature-dependent exchange-scattered electron intensities from the surface AFM lattice, the surface T N of CoO was estimated as a function of the CoO/NiO film thicknesses. Our results show that the surface T N of CoO layers is enhanced significantly from its bulk T N value and approaching the T N of the NiO layers, as the thickness of the CoO layers is reduced to the monolayer limit. Thus, thinner CoO layers are found to have higher T N than thicker layers on NiO, contrasting with the expected finite-size behavior. In addition to the short-range magnetic exchange coupling at the CoO-NiO interface, we observe the existence of a longer-range magnetic coupling across the interface, mediated by the magnetic correlations. Thus, the magnetic proximity effect is attributed to a combination of a short-range and a weaker long-range magnetic coupling, explaining the long AFM order propagation length in AFM-AFM superlattices and bilayers. Further, our results indicate a new approach to tune the AFM Nl temperature by varying the individual layer thickness of the bilayer system through the magnetic proximity effect. 2021 IOP Publishing Ltd. -
Magnetic field and light dependant supercapacitor behaviours of Mn3O4-rGO hybrid nanocomposites
Recently, hybrid nanostructures have been very promising candidates for energy generation and storage applications in nanotechnology. Here, Manganese Oxide (Mn3O4) decorated reduced graphene oxide (rGO) nanosheets hybrid composite was synthesised in chemical methods. The hybrid nanocomposite shows supercapacitance performance under a magnetic field and light irradiation. The magnetoelectrochemistry behaviour of the material was studied by varying external magnetic fields and the charge storage behaviours depending on the magnetic field. Additionally, the charge storage behaviour also changes under visible light irradiation. Interestingly, 82% enhancement is obtained under visible light. Therefore the present work gives a new pathway to understand the charge storage behaviour under light and magnetic fields. Qatar University and Springer Nature Switzerland AG 2024. -
Magnetic iron oxide nanoparticles immobilized on microporous molecular sieves as efficient porous catalyst for photodegradation, transesterification and esterification reactions
Magnetic iron oxide nanoparticles were immobilized on microporous molecular sieves (13X) via a plant extract mediated green synthesis method. The prepared material was then characterized using XRD, FTIR, TGA, FESEM, and TEM techniques. The synthesized iron oxide nanoparticles-molecular sieves (Fe2O3/MS) composite showed excellent photodegradation of methylene blue (MB) at 99% efficiency. Enhanced photocatalytic properties were observed in comparison with the pure iron oxide (Fe2O3) nanoparticles synthesized. Catalytic conversion of triglycerides to fatty-acid ethyl esters (FAEE) was carried out using sunflower oil, and the reaction showed very good catalytic activity in the transesterification of sunflower oil, converting 84% of the sunflower oil to FAEE. The catalyst was also used in the esterification reaction and found to have excellent applicability. The catalyst showed excellent reusability, and easy separation from the reaction mixture using an external magnet. This enables the synthesized material to act as a promising photocatalyst in degradation and organic synthesis. Very few reports are available on the synthesis of magnetic iron oxide coated on molecular sieves and used for photodegradation, transesterification, and esterification catalysis. 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
Magnetic property applications of microwave method prepared zinc ion modified CoAl2O4 nanoparticles
Employing Microwave combustion technique and utilizing L-arginine as fuel pure Cobalt Aluminate and Zn doped Cobalt Aluminate nanoparticles (NPs) were prepared. XRD, DRS-UV, HRSEM and VSM techniques were used to investigate the structural, optical, morphological, and magnetic properties. The average crystallite size is found in the range of 15-24 nm. Elemental confirmation is done by aid of EDX spectra. The band gap values of the produced samples were discovered to be between 2.57 and 2.45 eV. At room temperature, the prepared samples showed diamagnetic magnetic characteristics, which were corroborated by MagnetizationField (MH) hysteresis curves. 2021, S.C. Virtual Company of Phisics S.R.L. All rights reserved. -
Magnetically retractable tea extract stabilized palladium nanoparticles for denitrogenative cross-coupling of aryl bromides with arylhydrazines under green conditions: An alternate route for the biaryls synthesis
Novel palladium based magnetic nanocatalyst was synthesized by the co-precipitation method and coated with silica and tea extract as stabilizing agent. Palladation onto the prepared nanocomposite was done to get ION-SiO2/TE-Pd(0) catalyst. Our study is one of the limited number of studies reported for the catalytic denitrogenative coupling of arylbromide and arylhydrazine. This led to the construction of important substituted biaryls bearing various substituents with 8292% yields. The synthesized nanocatalyst was characterized using structural and morphological characterization techniques. It was also observed that only 2 mol% of ION-SiO2/TE-Pd(0) catalyst was sufficient for the catalysis and reusable upto six cycles. 2024 The Authors -
Magnetization induced skyrmion dynamics of a spin-orbit-coupled spinor condensate under sinusoidally varying magnetic field
We explore the spin texture dynamics of a harmonically trapped spin-1 BoseEinstein condensate with Rashba spinorbit coupling and ferromagnetic spin-exchange interactions under a sinusoidally varying magnetic field along the x-direction. This interplay yields an intrinsic spin texture in the ground state, forming a linear chain of alternating skyrmions at the saddle points of the magnetic field. Our study analyzes the spin-mixing dynamics for both a freely evolving and a controlled longitudinal magnetization. The spin-1 system exhibits the Einsteinde Haas effect for the first case, for which an exchange between the total orbital angular momentum and the spin angular momentum is observed, resulting in minimal oscillations about the initial position of the skyrmion chain. However, for the fixed magnetization dynamics, the skyrmion chain exhibits ample angular oscillations about the equilibrium position, with the temporary formation of new skyrmions to facilitate the oscillatory motion. For the case of fixed magnetization, this contrast now stems from the exchange between the canonical and spin-dependent contribution to the orbital angular momentum. The variation in canonical angular momentum is linked to the angular oscillations, while the spin-dependent angular momentum accounts for the creation or annihilation of skyrmions. We confirm the presence of scissors mode excitations in the spin texture due to the angular skyrmion oscillations. 2025 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft. -
Magneto convective flow of casson nanofluid due to Stefan blowing in the presence of bio-active mixers
The induced magnetic field for three-dimensional bio-convective flow of Casson nanofluid containing gyrotactic microorganisms along a vertical stretching sheet is investigated. The movement of these microorganisms cause bioconvection and they act as bio-active mixers that help in stabilising the nanoparticles in the suspension. The two forces, Thermophoresis and Brownian motion are incorporated in the Mathematical model along with Stefan blowing. The resulting model is transformed to ordinary differential equations using similarity transformations and are solved using (Formula presented.) method. The Velocity, Induced Magnetic field, Temperature, Concentration of Nanoparticles, and Motile density profiles are interpreted graphically. It is observed that the Casson parameter decreases the flow velocity and enhances the temperature, concentration, and motile density profiles and also it is noticed that the blowing enhances the nanofluid profiles whereas, suction diminishes the nanofluid profiles. On the other hand, it is perceived that the rate of heat conduction is enhanced with Thermophoresis and Brownian motion. IMechE 2021. -
Magneto-thermal-convection stability in an inclined cylindrical annulus filled with a molten metal
Purpose: Metal-cooled reactors generally use molten metals such as sodium, potassium or a combination of sodium and potassium because of their excellent heat transfer properties so that the reactor can operate at much lower pressures and higher temperatures. The purpose of this paper is to investigate the stability of natural convection in an inclined ring filled with molten potassium under the influence of a radial magnetism. Design/methodology/approach: A numerical simulation of electrically conductive fluid natural convection stability is performed on an inclined cylindrical annulus under the influence of a radial magnetism. The upper and lower walls are adiabatic, while the internal and external cylinders are kept at even temperatures. The equations governing this fluid system are solved numerically using finite volume method. The SIMPLER algorithm is used for pressure-speed coupling in the momentum equation. Findings: Numerical results for various effective parameters that solve the problem in the initial oscillatory state are discussed in terms of isobars, isotherms and flow lines in the annulus for a wide range of Hartmann numbers (0 ? Ha ? 80), inclination angles (0 ? ? ? 90) and radii ratios ? ? 6. The dependency stability diagrams between complicated situations with the critical value of the Rayleigh number RaCr and the corresponding frequency FrCr are established on the basis of the numeric data of this investigation. The angle of inclination and the radii ratio of the annulus have a significant effect on the stabilization of the magneto-convective flux and show that the best stabilization of the natural oscillatory convection is obtained by the intensity of the strongest magnetic field, the high radii ratio and inclination of the annulus at ? = 30. Practical implications: This numerical model is selected for its various applications in technology and industry. Originality/value: To the best of the authors knowledge, the influence of the inclination of the cylindrical annulus (ring), with various radii ratio, on natural oscillatory convection under a radial magnetism has never been investigated. 2020, Emerald Publishing Limited.