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Unleashing human potential: Integrating cognitive behavioral neuroscience into HR strategies
The world of work is transforming, driven by insights from the frontiers of science. Human resource (HR) practices are no longer limited to traditional methods and increasingly incorporate knowledge from disciplines like Cognitive Behavioral Neuroscience (CBN). By understanding how our brains work, we can design HR practices that enhance employee well-being, engagement, and, ultimately, performance. Drawing from neuroscientific research on decision-making, communication, stress, learning, motivation, and workplace design, this chapter delves into the intersection of CBN and HR, offering evidence-based practices that support a thriving workforce. This interdisciplinary approach holds promise for maximizing human potential in the context of the modern workplace. 2024 by IGI Global. All rights reserved. -
Effect of Museum Visit Intervention on Learning and Attitude Towards History
Place-Based Education is an education where learning happens in a place. The place could be museum, garden, palace, library etc. Place-based education is useful for the discipline of History as places are the existing evidence of past historical events. Therefore, students in History discipline can use place-based education for effective learning of history. The study attempts to find out the effect of museum visit intervention on learning and attitude towards newlinehistory. The study brings out how Museums act as an active agency to learn history. The study employed Quasi-experimental model with pre-test, post-test and follow-up post-test. Through purposive random sampling method, the participants were selected from 6th grade students of secondary schools of ICSE board located in the urban area of Kolkata in India. 120 students are included in the study group of the research (control group=60, experimental group=60). For the purpose of measuring museum visit intervention on learning and attitude towards history, researcher made achievement test and attitude scale with 5 point Likert scale was used. newlineThe instruction was provided in accordance with the History Course Curriculum of ICSE newlineboard. Experimental group visited the museum whilst the control group did not visit the newlinemuseum. Data analysis was conducted through SPSS program version 29. The result of the newlinestudy revealed that students of the experimental groups have performed better in comparison to the students of the control groups in learning and attitude towards history. Therefore, there is a recommendation to include museum visits pedagogies in the scope of social studies in History discipline. -
The red terror and a state of uncertainty: United Nations' role In the Indian maoist struggle
In this paper, the authors argue that the long drawn armed conflict between the Maoists and the Indian State has acquired the status of a non-international armed conflict due to the organized nature of the Maoists and the scale of violence arising out of the conflict. The systematic human rights abuses by both parties and forceful displacement of civilians is a tangible threat to international peace and security in the region. In light of the deadlock between the parties, the authors make a case for United Nations' intervention in mediating an end to the conflict and restoring peace and security in the region. Drawing inspiration from the role played by the UN in ending civil wars across the globe, this paper argues for a similar intervention in the non-international armed conflict in India. The authors argue that the UN should venture to exert pressure on the State to eliminate any further abuses of human rights, and remove the impasse between both the parties to facilitate a constructive dialogue. Copyright 2012 De Gruyter. All rights reserved. -
Intelligent Agents System for Vegetable Plant Disease Detection Using MDTW-LSTM Model
When it comes to agricultural output, nation, India, ranks first in the world, and agriculture is unparalleled. The need to categorize and trade agricultural goods is paramount. Manual organization, which is tedious and laborious, is not a choice. When agricultural products are graded automatically, a lot of time is saved. The application of image processing techniques facilitates the examination and evaluation of the products. A technique for identifying diseased vegetables is the focus of this effort. Feature extraction, preprocessing, segmentation, and training the model are all heavily dependent on sequence. Among the preprocessing technologies at disposal are image segmentation and filtering. Using Kapur's thresholding based segmentation method, the image's sick areas can be located during the segmentation process. Use k-means clustering for feature extraction to identify vegetable plant diseases. The training of an MDTW-LSTM model relies heavily on feature selection. In terms of performance, the proposed method surpasses two cutting-edge algorithms: LSTM and DTW. The results showed an accuracy of 97.35 percent, indicating a remarkable improvement. 2024 IEEE. -
Efficient Method for Tomato Leaf Disease Detection and Classification based on Hybrid Model of CNN and Extreme Learning Machine
Through India, most people make a living through agriculture or a related industry. Crops and other agricultural output suffer significant quality and quantity losses when plant diseases are present. The solution to preventing losses in the harvest and quantity of agricultural products is the detection of these illnesses. Improving classification accuracy while decreasing computational time is the primary focus of the suggested method for identifying leaf disease in tomato plant. Pests and illnesses wipe off thousands of tons of tomatoes in India's harvest every year. The agricultural industry is in danger from tomato leaf disease, which generates substantial losses for producers. Scientists and engineers can improve their models for detecting tomato leaf diseases if they have a better understanding of how algorithms learn to identify them. This proposed approaches a unique method for detecting diseases on tomato leaves using a five-step procedure that begins with image preprocessing and ends with feature extraction, feature selection, and model classification. Preprocessing is done to improve image quality. That improved K-Means picture segmentation technique proposes segmentation as a key intermediate step. The GLCM feature extraction approach is then used to extract relevant features from the segmented image. Relief feature selection is used to get rid of the categorization results. finally, classification techniques such as CNN and ELM are used to categorize infected leaves. The proposed approach to outperforms other two models such as CNN and ELM. 2023 IEEE. -
Hybrid Subset Feature Selection and Importance Framework
Feature selection algorithms are used in high-dimensional data to remove noise, reduce model overfitting, training and inference time, and get the importance of features. Features subset selection is choosing the subset with the best performance. This research provides a Hybrid subset feature selection and importance (HSFSI) framework that provides a pipeline with customization for choosing feature selection algorithms. The authors propose a hybrid algorithm in the HSFSI framework to select the best possible subset using an efficient exhaustive search. The framework is tested using the Bombay stock exchange IT index's companies' data collected quarterly for 16 years consisting of 71 financial ratios. The experimental results demonstrate that models created using 12 features chosen by the proposed algorithm outperform models with all features with up to 6% accuracy. The importance-based ranks of all features are generated using the framework calculated using 13 implemented feature selection techniques. All selected feature subsets are cross-validated using prediction models such as support vector machine, logistic regression, KNeighbors classffier, random forest, and deep neural network. The HSFSI framework is available as an open-source Python software package named ''feature-selectionpy'' available at GitHub and Python package index. 2023 IEEE. -
Stock Market Prediction Techniques Using Artificial Intelligence: A Systematic Review
This paper systematically reviews the literature related to stock price prediction systems. The reviewers collected 6222 research works from 12 databases. The reviewers reviewed the full-text of 10 studies in preliminary search and 70 studies selected based on PRISMA. This paper uses the PRISMA-based Python framework systematic-reviewpy to conduct this systematic review and browser-automationpy to automate downloading of full-texts. The programming code with comprehensive documentation, citation data, input variables, and reviews spreadsheets is provided, making this review replicable, open-source, and free from human errors in selecting studies. The reviewed literature is categorized based on type of prediction systems to demonstrate the evolution of techniques and research gaps. The reviewed literature is 7 % statistical, 9% machine learning, 23% deep learning, 20% hybrid, 25% combination of machine learning and deep learning, and 14% studies explore multiple categories of techniques. This review provides detailed information on prediction techniques, competitor techniques, performance metrics, input variables, data timing, and research gap to enable researchers to create prediction systems per technique category. The review showed that stock trading data is most used and collected from Yahoo! Finance. Studies showed that sentiment data improved stock prediction, and most papers used tweets from Twitter. Most of the reviewed studies showed significant improvements in predictions to previous systems. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Tuning the output of the higher plants Circadian Clock
The circadian clock is an ascribed regulator found in the cells of creatures, that keeps biological and behavioral processes in stnc with dailt environmental changes throughout the 24-hour ctcles. When the circadian clock in humans malfunctions or is misaligned with environmental signals, the timing of the sleep-wake ctcle is altered and several circadian rhtthm sleep disorders result. Due to the Earth's rotation on its axis, predictable environmental changes are anticipated bt complex processes. The combined term for these ststems is the circadian clock. The circadian rhtthm regulates photostnthesis and photoperiodism, making it the "primart controller of plant life." The circadian clock is made up of post-translational alterations to core oscillators, epigenetic tweaks to DNA and histones, and auto regulatort feedback loops in transcription. In addition, the circadian clock is cell-autonomous and regulates the circadian rhtthms of distinct organs. Biochemical elements such as photostnthetic products, mineral nutrients, calcium ions, and hormones are used bt the core oscillators to communicate with one another. Arabidopsis is utilized to identift clock-related genes that govern plant growth, germination, pollination, flowering, abiotic and biotic stress responses, and more. The biological ctcles of all species, notablt humans, are undoubtedlt impacted bt other elements, including high altitude and changing ecoststems, in addition to the ones alreadt stated. Although it hasn't tet published ant experimental or scientific evidence to support them, the implication that living things have lives does appear inescapable. Hence, the present studt elaborates on the higher plants related to the circadian clock. The Author(s). -
Influence of Coronavirus Disease 2019 on human biological timekeeping
To stay in sync with environmental cues, the body's metabolic activities must be rhythmic, and these rhythmic functions are known as circadian rhythms, which repeat every 24 h. People's sleep-wake and eating patterns were interrupted as a result of house confinement, making them more vulnerable to noncommunicable chronic diseases during the coronavirus disease 2019 (COVID-19) period. During the epidemic, there was a greater degree of misalignment with this synchronization. The effects of severe acute respiratory syndrome coronavirus 2 (COVID-19) on the human circadian clock are studied in depth. The literature review was conducted fully online, with the website utilized to collect all of the papers from PubMed, and duplicates were handled only in the first phase. Researchers found that individuals of all ages who are pushed to adjust their daily routines shift to the later chronotype, resulting in lifestyle modifications and an altered biological timing system that contributes to noncommunicable chronic illnesses. Chronic illnesses have bidirectional conductance, which means they can be caused by both environmental and self-modification in daily activity, as was the case during the COVID-19 outbreak, which forced people to stay at home. This review comes to the conclusion that fighting the pandemic may be best done by changing medications and focusing on immune health. 2023 Wolters Kluwer Medknow Publications. All rights reserved. -
Intelligent Manufacturing and Industry 4.0: Impact, Trends, and Opportunities
The use of intelligence in manufacturing has emerged as a fascinating subject for academics and businesses everywhere. This book focuses on various manufacturing operations and services which are provided to customers to achieve greater manufacturing flexibility, as well as widespread customization and improved quality with the help of advanced and smart technologies. It describes cyber-physical systems and the whole product life cycle along with a variety of smart sensors, adaptive decision models, high-end materials, smart devices, and data analytics. Intelligent Manufacturing and Industry 4.0: Impact, Trends, and Opportunities focuses on Intelligent Manufacturing and the design of smart devices and products that meet the demand of Industry 4.0, manufacturing and cyber-physical systems, along with real-time data analytics for Intelligent Manufacturing. The usage of advanced smart and sensing technologies in Intelligent Manufacturing for healthcare solutions is discussed as well. Popular use cases and case studies related to Intelligent Manufacturing are addressed to provide a better understanding of this topic. This publication is ideally designed for use by technology development practitioners, academicians, data scientists, industry professionals, researchers, and students interested in uncovering the latest innovations in the field of Intelligent Manufacturing. Features: Presents cutting-edge manufacturing technologies and information to maximise product exchanges and production Discusses the improvement in service quality, product quality, and production effectiveness Conveys how a manufacturing companys competitiveness can increase if it can manage the turbulence and changes in the global market Presents how intelligence production is essential in Industry 4.0 and how Industry 4.0 offers greater manufacturing flexibility, as well as widespread customisation, improved quality, and increased productivity Covers the ways businesses handle the challenges of generating an increasing number of customised items with quick time to market and greater quality Includes popular use cases and case studies related to intelligent manufacturing to provide a better understanding of this discipline. 2025 selection and editorial matter, Alka Chaudhary, Vandana Sharma, and Ahmed Alkhayyat individual chapters, the contributors. -
An Assessment of Farmers' Perception and Adaptive Capacity for Climate Change
In the past decades, various regions in U.P. had experienced severe floods. The effects of climate change also affected agricultural production. This study investigated the farmers' perception of climate change and suggested strategies for mitigating its effects using a primary survey with the help of a pre-structured schedule. Change in rainfall pattern, problems in seed quality, the emergence of new pests and diseases, changes in the crop cycle were the few effects that farmers' perceived due to climate change. Even the most mitigation efforts by the farmers cannot prevent some of the impacts of climate change within the following decades. It makes adaptation a must-have for addressing these impacts. 2022, The Society of Economics and Development. All rights reserved. -
Studies on phase transitions and dielectric properties of biowaste synthesized porous carbon nanoparticlesferroelectric liquid crystal mixture
Ferroelectric liquid crystals(FLCs), an exciting class of liquid crystals(LCs), found potential applications in the display as well as non-display regimes due to their fast response, low driving voltage and nonvolatile memory. The amalgamation of nanoparticles into FLCs has opened up new avenues in the LCs research field by alterations/modification of the existing properties of LCs. In this work, porous carbon nanoparticles (PCNPs) were dispersed into FLC mixture (W206E) and investigated their doping effect on FLCs textural, phase transition temperatures and dielectric studies in planar-aligned cells. Dielectric spectroscopy was carried out in the frequency range of 20 Hz to 10 MHz to explore the frequency as well as the temperature dependent of FLC in the entire SmC* region. The transition temperature of FLC mixture is increased by 4 C in PCNPs doped FLC sample then undoped FLC sample. Nearly 8.42% increase in permittivity is observed. A Gold stone relaxation mode at ?627 Hz was observed at lower frequency. 2024 Taylor & Francis Group, LLC. -
Occupational Exposure to Cooking Oil Fumes : Biochemical, Cytogenetic and Molecular Signatures
Occupational exposure to Cooking Oil Fumes (COFs) is a widespread concern in the newlineculinary industry, and it has raised significant health apprehensions due to its potential adverse effects on individuals working in kitchens. This current research presents a comprehensive analysis of the biochemical, cytogenetic, and molecular analysis observed in individuals exposed to COFs in their workplace. The study employed a cross-sectional approach, involving a cohort of kitchen personnel working in diverse culinary settings. Biochemical assessments focused on analyzing blood parameters, such as lipid profiles, liver enzymes, and markers of oxidative stress, to gauge the impact of COFs on the participants systemic health. Cytogenetic investigations encompassed the assessment of chromosomal aberrations and micronuclei frequency in peripheral blood lymphocytes, shedding light on potential genotoxicity associated with COF exposure. Moreover, molecular analyses involved the examination of ApoE and BMAL1 gene expression patterns related to inflammation, oxidative stress response, and detoxification pathways also this aspect aimed to uncover the newlineunderlying molecular mechanisms influenced by COFs. Preliminary results suggest a significant association between COF exposure and alterations in biochemical parameters, newlineparticularly an increase in oxidative stress markers and changes in lipid profiles, indicative of potential cardiovascular risks. Cytogenetic assessments revealed an elevated frequency of chromosomal aberrations and micronuclei formation, highlighting genotoxic effects linked to COF exposure. Molecular investigations demonstrated differential expression patterns of ApoE and BMAL1 genes involved in inflammation and oxidative stress responses, further corroborating the adverse effects of COFs on cellular processes. The findings of this research underscore the importance of addressing occupational exposure to COFs and implementing appropriate safety measures in cooking area. -
Financing for SDGs in India in Post Pandemic era - Challenges & Way forward
In 2015, a resolution known as Agenda 2030 was passed by United Nations General Assembly in which seventeen goals for Sustainable Development were laid down for global dignity, peace and prosperity. The post- pandemic era became full of uncertainties in pursuing those Sustainable Development Goals (SDGs) and its implementation became a challenge especially for the developing economies like India. The country is facing a tremendous gap in arranging for resources to meet the climatic changes and attaining the SDGs. India requires 170 billion dollars per year from 2015-2030 to fulfill the Sustainable Development Goals as per the estimation done by National Determined Contribution, a body setup after Paris agreement 2015 to monitor the efforts of the country towards reducing national emissions and adapting to climate change. There is a huge concern amongst the various agencies on exploring the ways to fill this financing gap especially after the economic slowdown seen in the post pandemic era. This research paper analyses the challenges imposed by the COVID 19 pandemic on financing for SDGs and also explores the options to mitigate them. The articles and research papers related to SDG financing are reviewed by the researchers to arrive at the above mentioned statements. This paper is an attempt to draw the attention of worldwide authorities towards this grim situation as sustainable finance is far from reality in India and requires immediate up scaling. The Electrochemical Society -
A smart attendance system and method for permission inventory during the class /
Patent Number: 202111060922, Applicant: Shivani Chaudhry.A smart attendance system (1). The system (1) comprises a smart lecture stand (2), which having an electronic unit (2A) which is connected to the other smart door, smart bench, and smart chair of the system; a smart bench (3), which having an electronic unit (3A), which is connected to the other smart door, smart stand, and smart chair of the system; a smart chair (4) comprises which having an electronic unit (4A); which is connected to the other smart door, smart bench, and smart stand of the system; a smart door (5) comprises a electronic unit (5A), which is connected to the other smart door, smart bench, and smart chair of the system. -
Method of enhancing quality of services in cloud computing environment using load balancer /
Patent Number: 202211006218, Applicant: Dr. Pratibha Giri. -
CSR as an agent of financial stability: A use case of banking industry
The study was undertaken to examine the importance of corporate social responsibility (CSR) as an agent to improve the firm's performance and financial stability by enhancing goodwill and competitive advantage in the Indian banking industry. In the study, it has been hypothesized that CSR expenses have a positive relationship with financial stability. A correlation study has also been undertaken to determine any relationship among these variables, followed by a dependency regression test to show the levels of dependency of financial stability on CSR expenses and the Granger Causality test to find their causal relationship. The study has revealed a significant relationship between the financial stability variables and CSR expenses, and the Granger Causality level supports the findings. 2021 Ecological Society of India. All rights reserved. -
A system for measuring mediating effect of globalization on income distribution in emerging economies /
Patent Number: 202231033186, Applicant: Shruti Mohapatra.
The present invention discloses a system that is configured to receive from a user an income range and a geographical scope of interest in a predefined set of income distribution and aggregating prediction data from the income range and geographical scope from one or more of the asset classes selected from the group consisting of currency, bond, commodity, and stock. Further, automatically determining changes over time within the income range of one or more statistical analysis values of the aggregated prediction data selected from the group consisting of mean, median, mode, difference of means, standard deviation, variance, tolerance levels, skewness, kurtosis, inflection points and Bayesian analysis. -
CONTRARIAN AND MOMENTUM STRATEGIES IN THE INDIAN STOCK FUTURES MARKET: A STUDY ON BANKING SECTOR
This thesis tries to investigate the contrarian and momentum strategy can help the investors to lay down the major guidelines for undertaking any derivative transaction. Contrarian strategies are based on the reversal pattern in stock returns and imply buying past losers and selling past winners. On the contrary, Momentum strategies are based on the continuation pattern in stock returns and imply buying past winners and selling past losers. For the purpose of analysis, the stock returns for the Indian stock futures market segment for Indian banking sector for the period from July 1, 2005 to June 30 2011 by using the Fama and French multifactor model. The Fama-French model involves the use of three factors for explaining common stock returns: the market factor proposed by the CAPM, and factors relating to size and value. The company used in this research consists of 16 Banks which were ranked in an ascending order based on their average returns. The ranked securities are then used to form five equal portfolios. While portfolio P1 contains the bottom 20 per cent securities and is called "losers' portfolio," portfolio P5 contains the top 20 per cent securities and is termed as "winners' portfolio." The findings suggests that the stock-return behavior in banking sector for short-term momentum profits and long term contrarian profits exist in this case. Further, the contrarian trading strategy based on long term returns provides moderately positive payoffs and short-term returns show a continuation pattern and the investment strategy based on momentum effect provides significantly high returns. Finally, the study generally supportive of the Fama-French model applied to Indian futures stock market related to banking sector. Keywords: Contrarian, Momentum, Stock Returns, CAPM, Fama-French Model JEL Classification: C12, C22, E43, G11 -
An effective face recognition system based on Cloud based IoT with a deep learning model
As of late, the Internet of Things (IoT) innovation has been utilized in applications, for example, transportation, medical care, video observation, and so on. The quick appropriation and development of IoT in these segments are producing an enormous measure of information. For instance, IoT gadgets, for example, cameras produce various pictures when utilized in medical clinic reconnaissance sees. Here, face acknowledgement is one of the most significant instruments that can be utilized for clinic affirmations, enthusiastic discovery, and identification of patients, location of fake gadgets. patient, and test clinic models. Programmed and shrewd face acknowledgement frameworks are profoundly precise in an overseen climate; notwithstanding, they are less exact in an unmanaged climate. Additionally, frameworks must keep on running on numerous occasions in different applications, for example, insightful wellbeing. This work presents a tree-based profound framework for programmed face acknowledgement in a cloud climate. The inside and out pattern have been proposed to cost less for the PC without focusing on unwavering quality. In the model, the additional size is isolated into a few sections, and a stick is made for each part. The tree is characterized by its branch area and stature. The branches are spoken to by a leftover capacity, which comprises of a twofold layer, a stack game plan, and a non-direct capacity. The proposed technique is assessed in an assortment of generally accessible information bases. An examination of the method is likewise finished with top to bottom craftsmanship models for the eye to eye connection. The aftereffects of the tests indicated that the example was considered to have accomplished a precision of 98.65%, 99.19%, and 95.84%. 2020