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Whats the best time to give work? A study on relationship between employee moods and performance at different time intervals
Employees change their behavior many times in a day due to many factors. It is not uncommon to see any employee being agitated over petty issues at work place. This paper aims at identifying meaning, relationships between moods and performance. Employees decision-making abilities depend on mood and his mood depend on his personality, work environment variables such as protocols, procedures, work events, dynamics of formal and informal communication. We equate this daily swing to three-time frames named morning, afternoon and evening. Our attempt has been to try to establish a relationship between moods and emotions and employee performance which can increase the productivity level of the employee. This research intends to establish a more robust relationship and involves better evaluative and interpretive models to cope with the non-linearitys related to the complexity of the model and facilitate better decision-making with more accurate and intricate or comprehensive yet simple approach. Development of such relationship will help managers in dealing with the employees and take measures to increase productivity by adopting suggestions and conclusions from this study. IJSTR2019. -
Under Pressure: Integrating Policy Interventions to Save Distressed Indian SMEs of COVID-19 Aftershocks
The Micro, Small, Medium Enterprises (MSME) sector has one of Indias highest employment Indexes and is the launchpad for all genres and innovators. This sector is inclusive in integrating grass root level workers into tech innovators. There are about 63 million MSMEs in India, employing 110 million individuals. According to 2019 MSME reports, the sector contributed 29% to the overall GDP catalyzing socio-economic development. The Covid-19 pandemics have left world economies and business entities to redefine and rethink policy regulations and business models. The pandemic has created socio-economic displacement across business sectors, and no country is free from the socio-economic exclusions that has triggered. The Indian economy has been badly affected by a projection of over a seven percent decline in quarterly GDP in 2021.The coronavirus pandemic has impacted MSME earnings by 2050 percent, with micro and small organizations being the worst hit due to liquidity crunch. According to the survey conducted by Endurance International Group, many MSMEs have temporarily shut their operations or laid off their staff due to the inability to pay salaries. Further, due to slip in demand and halted production, many had to vacate the rented premises where they were functioning. MSMEs seek government support to tide over the situation with policy interventions on tax discounts or exemptions and loans distributed at cheaper rates or zero interest rates. With the economic slowdown and global restrictions on business outsourcing, and border tensions with China, India revived its Swadeshi (ethnic) dream of Mahatma Gandhi. The Government launched Atmanirbhar Bharat Mission to boost MSMEs and thrust indigenous industries and processes to reduce our foreign nations resilience. Indian government policies are favourable because they have committed $50 billion to help small businesses survive and provide low-income workers with a $266 billion stimulus package of around two percent of Indias annual economic output. Aatmanirbharta which means self-reliance, has been chosen by Oxford Languages as its Hindi word of the year 2020 as it authenticated the everyday achievements of the countless Indians who survived the perils of a pandemic, as stated in one of the popular daily newspaper. The paper focuses on the issues and challenges faced by MSMEs in India due to the pandemic. Further, an analysis of changes in MSME definition presented in the Union Budget 2021 and various policy interventions by the Government and their impact on reviving in the MSME sector is presented. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Optimal Sizing and Placement of Distributed Generation in Eastern Grid of Bhutan Using Genetic Algorithm
Power system has to be stable and reliable for its users. Nevertheless, due to the aging and ignorance, it tends to be unreliable and unstable. Distributed Generation (DG) is a small-scale energy production which are usually connected towards the load. It helps in the reduction of power losses and improvement of profile of voltage in a distribution network. However, if a DG is not optimally placed and sized, it will rather lead to an increase in a power loss and also deteriorates the voltage profile. This report exhibits the importance of DG placement and sizing in a distribution network using Genetic Algorithm (GA). Apart from the optimum DG placement and sizing, different scenarios with numbers of DGs is also being analyzed in this report. On eastern grid of Bhutan, a detailed analysis for its performance is carried out through MATLAB platform to demonstrate and study the effectiveness and reliability of a methodology that is being proposed. 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Influence of alkali treatment on physiochemical and morphological properties of palmyra fibers
As a part of sustainable development in construction, natural fibers are used as reinforcement in cement composites. The degradation of these natural fibers in matrix has led to growing interest among researchers to enhance the fiber properties by adopting suitable treatment techniques. This research focuses on examining the influence of alkali treatment on various aspects, including the physical, chemical, crystallinity, mechanical and surface characteristics of palmyra fibers. Herein, the palmyra fibers were immersed in alkaline solution for different duration (30 minutes, 60 minutes and 120 minutes) to arrive at optimum treatment period. The investigation utilizes XRD, FTIR, SEM and EDS analysis to gain insights into these properties. The findings indicated that the treatment effectively removed excess amorphous components like extractives, hemicellulose and lignin leading to the increase in crystallinity index and surface roughness. The crystallinity index increased by 11 %, 13 % and 23 % for 30 minutes, 60 minutes and 120 minutes treatment respectively. The water absorption of palmyra fibers reduced by 13 %, 14 % and 14 % for 30 minutes, 60 minutes and 120 minutes treatment duration respectively. Additionally, SEM-EDS exhibited best results for 60 min treatment of fibers, with 38 % increase in Oxygen to Carbon ratio of cellulose compared to untreated fibers. Among the different treatment duration, the 60 minutes treatment duration of fibers in 0.5 M sodium hydroxide solution has exhibited considerable enhancement in properties. These enhancements in palmyra fiber properties post-alkali treatment suggests their potential utility in the reinforcement of composites using alkali treated palmyra fibers. 2024 The Authors -
Mechanical strength and water penetration depth of palmyra fibre reinforced concrete
Natural fibre reinforced composites are replacing the conventional fibre reinforced composites for several applications due to natural fibre availability, variety and lesser raw material cost. Using natural fibres in composites also reduces the issue of agricultural residue disposals, which are in abundance. Different natural fibres exhibit unique properties when it is used in composites and hence there is a need to study the behaviour of scarcely used natural fibres. Indian palmyra trees (Borassus flabellifer) are fast growing commonly found trees in Southern India. From the base of these palm tree leaves, palmyra fibres are taken out. Though these fibres are locally available in huge quantities, these are very rarely used as reinforcing material in concrete compared to other natural fibres like coir, sisal, jute etc. Palmyra fibre reinforced cement composite specimens were prepared by varying the fibre content (0.5%, 1% and 2% by weight of cement) and length of fibre (25 mm and 50 mm). Plain concrete and palmyra fibre reinforced concrete specimens of identical size were tested for mechanical strength and also for its depth of water penetration. The work carried out revealed that the water penetration of palmyra fibre reinforced concrete increased with fibre content increase. The compressive strength of palmyra fibre reinforced concrete improved up to 1% of fibre content and further increase in fibre content upto 2% resulted in compressive strength reduction for both the fibre lengths. However, split tensile strength, flexure strength and shear strength increased with fibre content increase in the mix. Based on the mechanical strength properties investigated, increase in shear strength was found to be more significant with the inclusion of palmyra fibres in concrete. 2022 -
Exploring the Impact of Behavioral Biases on Young Investors Portfolio Performance: An Examination through the Lens of Nudging Green: Behavioral Economics for Environmental Sustainability
PurposeThis research paper delves into identification of interaction and relationship among numerous factors like investors behavior, psychological factors of investors, specific biases, financial knowledge and literacy, and portfolio value of young investors. Through this research paper we can conclude that investors are increasingly affected by the biases that exist. These biases act as a hindrance in their process of decision making. Design/methodology/approachIn this research paper a survey was conducted and the poll consisted of various questions. In this research paper, a convenience sampling technique was used and responses from 295 investors were collected for analysis of the data. In this paper we have used descriptive analysis and regression correlation for the purpose of analysis which ultimately unfolds the relationship between biases and investors portfolios. FindingsThis paper unfolds the various behavioral factors and other factors that shape the investment portfolio of youth. The paper dwells into the intricate study of behavioral factors that affect youth and determines their investment pattern. Research limitation/implicationsLimited samples have been collected for this paper and that is the limitation of this paper. As the sample size is limited there is a high probability that with a larger group of investors, the behaviour pattern and biases may differ. As most of the investors are young their knowledge about trading market and investment market is quite limited which ultimately generates hindrances in analysis. Maximum number of investors are quite young which increases the probability of biases in the decision making process. Practical implicationsThis paper will help scholars, analysts, academicians, practitioners, policymakers, brokers, and investors to frame better strategies in order to deal with behavioural biases and other behavioural factors. In order to not get influenced with behavioral biases and other behavioral factors, young people can plan out their investments in a better way. The youth of our country can have greater understanding regarding investments if they are given enough wisdom regarding the same through workshops, webinars, seminars, lectures, curriculum. Originality/valueIn this paper investors behavior, psychological factors, specific biases, financial knowledge and literacy are factors that influence the investment portfolio of young investors. Young investors can keep these factors in mind in order to increase their portfolios value which will ultimately lead to better investment decisions among them. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Investigating structure and spectral energy distribution of galaxies using uvit and multi-wavelength archival data
This thesis deals with the multi-wavelength investigation of the different aspects of galaxy formation and evolution. The first part of this thesis deals with the studies on the characteristics of the in-orbit performance of the Ultraviolet Imaging Telescope (UVIT) on-board AstroSat. We have written a UVIT pipeline (JUDE ) to convert the Level 1 data from the Indian Space Science Data Centre (ISSDC) into scientifically useful photon lists and images. We have also performed an independent calibration of the FUV and NUV channels of the UVIT using JUDE. We found that the photometric sensitivity is about 35% that of the Galaxy Evolution Explorer (GALEX ) in the FUV broadband filter, and about the same as GALEX in the NUV broadband filter. The point spread function (PSF) of the instrument is of the order of 1.2 1.6and#8242;and#8242;. We found that the performance is close to that expected from the ground-based calibrations. We studied the recent star formation in the nearby face-on spiral galaxy NGC 2336 using the UVIT imaging. We have identified 78 bright star-forming complexes in the disk and derived their positions and estimated their properties such as luminosities, sizes, star formation rates (SFRs), colors, and ages. The FUV-NUV colors of the complexes are found to be redder in the inner region of the galaxy and become progressively bluer as the radius increases. The last part of this thesis is devoted to a model-based study of galaxies using physically motivated Code Investigating Galaxy Emission (CIGALE) package. We have studied 10,000 galaxies from GALEX SDSS merged catalog using CIGALE and estimated their properties such as stellar masses, SFRs, stellar populations, dust luminosities etc. We have classified this set of galaxies into the star-forming, intermediate and quiescent type of galaxies based on their specific SFR. We also studied the properties of dust-lane spheroidal galaxies (DLSGs) drawn from the multi-wavelength archival data in 18 bands from FUV to FIR using GALEX, SDSS, 2MASS, WISE, and AKARI surveys. -
Investigating the in-flight performance of the UVIT payload on AstroSat
We have studied the performance of the Ultraviolet Imaging Telescope payload on AstroSat and derived a calibration of the far-ultraviolet (FUV) and near-ultraviolet (NUV) instruments on board. We find that the sensitivity of both the FUV and NUV channels is as expected from ground calibrations, with the FUV effective area about 35 per cent and the NUV effective area about the same as that of GALEX. The point spread function of the instrument is on the order of 1.2-1.6". We have found that pixel-to-pixel variations in the sensitivity are less than 10 per cent with spacecraft motion compensating for most of the flat-field variations. We derived a distortion correction but recommend that it be applied post-processing as part of an astrometric solution. 2018 The Author(s). -
Synthesis of bent-shaped azobenzene main-chain polymers for photo-switching properties
This work presents the synthesis of the new bent-core polymers with siloxane units connected to the one side of azobenzene units. The structure of siloxane-based azobenzene bent-core polymers, 7ac, was elucidated by spectral analysis (nuclear magnetic resonance and Fourier-transform infrared spectroscopy). The results of gel permeation chromatography suggested that all polymers (7ac) showed polydisperse (polydispersity index >1). Besides, the extent of polymerization in the following order: 7a > 7b > 7c, where the degree of polymerization values were 7, 8 and 11, respectively. Polarizing optical microscopy revealed that the bent-core liquid crystal (BCLC) monomers, 6a and 6b, displayed the smectic A phase, whereas BCLC monomer 6c and all siloxane-based main-chain polymers (MCPs) (7ac) were crystalline in nature. The result of ultraviolet-visible spectroscopy demonstrated that all MCPs (7ac) exhibited strong photoisomerization behavior in solution. All polymers (7ac) showed trans to cis isomerization in about 200 s, whereas the reverse process required much longer times ranging from 400 to 520 min in solution. The photo-switching study on azobenzene containing polymers stated that the effect of alkyl chain length and type of central core units on trans to cis isomerization were negligible. In contrast, both parameters influence the cis to trans process in which the photo-switching behavior of these materials may be primarily suitably exploited in the field of photo-induced phenomenon. 2023 Taylor & Francis Group, LLC. -
An Examination of the Challenges Associated with Applying Artificial Intelligence Techniques to Specific Management Problems
Artificial intelligence (AI) holds immense promise in revolutionizing management practices across various sectors, offering solutions to complex problems and optimizing decision-making processes. However, the application of AI techniques to management problems is not without its challenges. This examination delves into the multifaceted hurdles encountered when integrating AI into management frameworks, highlighting key obstacles and potential avenues for overcoming them.AI algorithms heavily rely on large volumes of high-quality data for effective training and decision-making. Yet, many management domains grapple with disparate data sources, inconsistencies, and incomplete datasets, hindering the performance and reliability of AI systems. Furthermore, the dynamic nature of management problems poses a significant challenge to AI implementation. Management environments are characterized by evolving trends, uncertainties, and unforeseen disruptions, rendering static AI models inadequate in adapting to changing conditions. Hence, the development of agile AI systems capable of continuous learning and adaptation becomes essential for addressing the dynamic nature of management challenges. 2024, Collegium Basilea. All rights reserved. -
An Efficient Face Recognition System using Deep Transfer Learning
Face recognition is an AI-based innovation used to find and recognize human appearances in videos and images. Organizations can apply face recognition to many different kinds of fields which may include biometrics, regulation of law, security and individual wellbeing; so as to take observation of individuals in any scenario. Face recognition has advanced from simple vision methods to progress in ML; and further to progressively refined neural networks (ANN) and related advances. It currently assumes an indispensable part as the initial phase in numerous basic applications, including the task of tracking a face. Face recognition is utilized to focus cameras or count the number of individuals present in a particular region. The innovation likewise has showcasing applications, for instance, showing recommended promotions when a specific user is detected. 2022 IEEE. -
An Analysis of Machine Learning and Deep Learning to Predict Breast Cancer
According to the report published by American Cancer Society, breast cancer is currently the most prevalent cancer in women. In addition, it is the second leading cause of death. It needs to be taken into serious consideration. Earlier and faster detection can help in the earlier and easier cure. Normally, medical practitioners take a large amount of time to understand and identify the presence of cancer cells in the human body. This can lead to serious complications even to the death of the individual. Hence there is a need to identify and detect the presence of this disease very accurately and in a shorter span of time. Like every other industry, the medical industry is shifting its paradigm to automation giving excellent results having high accuracy and efficiency, which is achieved using Artificial Intelligence. There are two sets of models developed based on the numerical dataset Wisconsin and image dataset BreakHis. Machine Learning algorithms and Deep Learning algorithms were applied on the Wisconsin dataset. Meanwhile, Deep Learning models were used for analysis of the Breakhis dataset. Machine Learning models- Logistic Regression, K Neighbors, Naive Bayes, Decision tree, Random Forest and Support vector classifiers were used. Deep Learning models- normal deep learning models, Convolutional Neural Network (CNN), VGG16 & VGG19 models. All the models have provided a very good accuracy ranging between 75% and 100%. Since medical research has a requirement for higher accuracy, these models can be considered and embedded into several applications. Grenze Scientific Society, 2022. -
Changing equations: Empowerment, entrepreneurship and the welfare of women
The world is a melange of varied cultures and norms. Some are similar, while others are strikingly different from the rest. However, every society has something in common: suppression of their women although the degree and extent may vary. It is not that women are incapable of playing those roles in society which have been dominated by men, but consistent and strategic oppression of the female sex has led many women to consider themselves as weak, powerless and a step below their male counterparts. The waves of feminism and movements to emancipate women have, to a notable extent, changed this perception. However, the world still associates women with the domestic sphere which includes rearing, nurturing and caring for children. While, this is important, this must seldom be the only role played by women. This paper while highlighting the importance of the role of women in the economic and public sphere, shall also explore the various means and steps that have been taken and further measures that can be taken to empower women and encourage entrepreneurship in developing economies such as India. The capability approach and welfare economics by Amartya Sen shall also be explored to understand how best such approaches could benefit the rural women and their empowerment. Developing economies simply cannot ignore even a fraction of their demography. This paper would thus like to bring to the fore that empowerment of women is as important to an economy as it is for their individual well-being, and ultimately their liberation. 2018 Journal of International Women's Studies. -
Synthesis of Quinoxalin-2(1 H)-ones and Hexahydroquinoxalin-2(1 H)-ones via Oxidative Amidation-Heterocycloannulation
A metal-catalyst-free synthesis of substituted quinoxalin-2-ones from 2,2-dibromo-1-arylethanone by employing an oxidative amidation-heterocycloannulation protocol is reported. The substrate scope of the reaction has been demonstrated and a possible mechanism for this reaction has also been proposed. 2020 GeorgThieme. All Rights Reserved. -
Classification of epileptic seizures using wavelet packet log energy and norm entropies with recurrent Elman neural network classifier
Electroencephalogram shortly termed as EEG is considered as the fundamental segment for the assessment of the neural activities in the brain. In cognitive neuroscience domain, EEG-based assessment method is found to be superior due to its non-invasive ability to detect deep brain structure while exhibiting superior spatial resolutions. Especially for studying the neurodynamic behavior of epileptic seizures, EEG recordings reflect the neuronal activity of the brain and thus provide required clinical diagnostic information for the neurologist. This specific proposed study makes use of wavelet packet based log and norm entropies with a recurrent Elman neural network (REN) for the automated detection of epileptic seizures. Three conditions, normal, pre-ictal and epileptic EEG recordings were considered for the proposed study. An adaptive Weiner filter was initially applied to remove the power line noise of 50Hz from raw EEG recordings. Raw EEGs were segmented into 1s patterns to ensure stationarity of the signal. Then wavelet packet using Haar wavelet with a five level decomposition was introduced and two entropies, log and norm were estimated and were applied to REN classifier to perform binary classification. The non-linear Wilcoxon statistical test was applied to observe the variation in the features under these conditions. The effect of log energy entropy (without wavelets) was also studied. It was found from the simulation results that the wavelet packet log entropy with REN classifier yielded a classification accuracy of 99.70% for normal-pre-ictal, 99.70% for normal-epileptic and 99.85% for pre-ictal-epileptic. 2016, Springer Science+Business Media Dordrecht. -
Phytochemical Analysis and Antibacterial Potential of Stevia rebaudiana (Bertoni, 1899) Leaf Extracts against Aeromonas Species: Influence of Extraction Methods and Solvents in Aquaculture Applications
Recent studies have explored Stevia rebaudiana Bertoni leaf extracts for their antibacterial potential and phytochemical content. However, the impact of extraction methods and solvents on aquaculture bacteria remains understudied. This research aimed to evaluate the antibacterial, radical scavenging, and phytochemical properties of S. rebaudiana extracts against Aeromonas species. Dried S. rebaudiana leaves were extracted using methanol (Mt) and ethanol (Et) through Soxhlet and maceration methods (SMt, SEt, MMt and MEt respectively). Soxhlet extraction yielded higher amounts (36.29% for Mt, 23.87% for Et) compared to maceration. Phytochemical analysis identified phenolics, flavonoids, alkaloids, saponin, tannin, and steroids in all extracts. Notably, MEt had elevated phenolic and flavonoid content, while SEt contained more tannins. MEt exhibited the strongest antioxidant activity (IC50 = 67.95g/mL), aligning with its high phenolic and flavonoid levels. In antibacterial assays against Aeromonas strains, ethanol extract showed the largest zone of inhibition (ZOI) of 16.67mm for A. salmonicida, followed by methanol extract (15mm) at 250 mg/mL, using maceration and Soxhlet methods, respectively. However, none of the extracts displayed activity against A. hydrophila. This suggests that cold maceration is a cost-effective method that preserves heat-sensitive secondary metabolites within a shorter extraction time. In conclusion, this study highlights the significance of extraction techniques and solvents in obtaining potent antibacterial and antioxidant extracts from S. rebaudiana leaves. The findings emphasize the potential of these extracts in aquaculture practices and open avenues for further research in utilizing natural compounds for sustainable aquaculture strategies. The Author(s) 2023. -
Augmented reality for history education
Augmented Reality is live, direct or indirect view of a physical real world environment whose elements are augmented by personal computers (PC) that produces the information such as sound, video, designs or GPS data. This paper shows an instructive mobi le application based system model on Augmented Reality which is used to learn subjects like history through augmented videos. The objective of development of this system model is to make the learning interesting for the young generation. Unity 3D and Vufo ria Augmented Reality Software Development Kit (SDK) is used for the development of this model. The prime purpose of this application model is to enhance the learning process with digital technologies. This paper has step by step implementation instructions for the development of augmented reality modeling that can supplement the current teaching-learning environment to generate interest among young generation in less interesting subjects such as History, Geography, etc. 2018 Authors. -
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Analysing the market for digital payments in India using the predator-prey model
Technology has revolutionized the way transactions are carried out in economies across the world. India too has witnessed the introduction of numerous modes of electronic payment in the past couple of decades, including e-banking services, National Electronic Fund Transfer (NEFT), Real Time Gross Settlement (RTGS) and most recently the Unified Payments Interface (UPI). While other payment mechanisms have witnessed a gradual and consistent increase in the volume of transactions, UPI has witnessed an exponential increase in usage and is almost on par with pre-existing technologies in the volume of transactions. This study aims to employ a modified Lotka-Volterra (LV) equations (also known as the Predator-Prey Model) to study the competition among different payment mechanisms. The market share of each platform is estimated using the LV equations and combined with the estimates of the total market size obtained using the Auto-Regressive Integrated Moving Average (ARIMA) technique. The result of the model predicts that UPI will eventually overtake the conventional digital payment mechanism in terms of market share as well as volume. Thus, the model indicates a scenario where both payment mechanisms would coexist with UPI being the dominant (or more preferred) mode of payment. 2023 Balikesir University. All rights reserved. -
Recognition of Signature Using Neural Network and Euclidean Distance for Bank Cheque Automation
Handwritten signature recognition plays significant role in automatic document verification system in particularly bank cheque authorization. The proposed method focuses on A novel technique for offline signature recognition approach for bank cheque based on zonal features and regional features. These combined features are used to find genuinety of signature using Euclidean distance as a metric. Extensive experiments are carried out to exhibit the success of the recommended approach. 2019, Springer Nature Singapore Pte Ltd.