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Future of knowledge management in investment banking: Role of personal intelligent assistants
Purpose: The studys objective focuses on investigating the involvement of Personal Intelligent Assistants (PIAs) in the Knowledge Management Process (KMP) in Investment Banking Companies leading to Industrial Revolution 5.0 leading to effective Organizational Knowledge Management. Design/Methodology: A Self-administered Survey Questionnaire was circulated to 695 employees of Investment Banking Companies operating in Bangalore, Mumbai, Delhi, Hyderabad, Chennai, and Pune using the Cluster Sampling method. The Covariance-based Structural Equation Modelling (CB-SEM) and Gradient Boosting Regression technique of Machine Learning were used to validate the hypothesis through JASP V.18 Software. Knowledge Creation, Knowledge Sharing, Knowledge Retrieval, Knowledge Application, and Organizational Knowledge Management are the crucial constructs considered in the study. Findings: The results revealed that Knowledge Application is the most influencing factor in effective organizational Knowledge management among the Investment Banks followed by Knowledge Sharing. It also emphasizes that they have a weak Knowledge retrieval process and minimal efforts taken to create knowledge within these banks. Implications: The PIAs can facilitate effective Data Analysis and research in managing vast data eliminating the repeated tasks in portfolio reconciliation and offering personalized recommendations to manage portfolios. It enables in compliance, risk management, client relationship management, real-time monitoring and leveraged decision-making through predictive analysis. The Author(s) 2024. -
Future perspectives on new innovative technologies comparison against hybrid renewable energy systems
The increase in the dispatchable amount of renewable energy and rural access to the point is proposed. The fuel is used to generate power and electrical energy for the machine. This causes the electricity to manage the single connection point to analyze the hybrid generations. Improving this hybrid generator of renewable power resources can be enabled for the analysis. Photovoltaic power sources have been introduced for converting the power loads and the dumps. The vehicle energy power management technique and the renewable energy system have been used for the analysis. This study shows how vehicle and renewable energy management can help develop geothermal against hydrothermal vents. Hydropower and vehicles can enable bioethanol for vehicle biodiesel. This study allows for the analysis of hydrothermal and biodiesel. In this study, the power of the energy enables the hybrid system, and the combination of the power generator to access the vehicle is proposed. 2023 -
Future search algorithm for optimal integration of distributed generation and electric vehicle fleets in radial distribution networks considering techno-environmental aspects
In this paper, a new nature-inspire meta-heuristic algorithm called future search algorithm (FSA) is proposed for the first time to solve the simultaneous optimal allocation of distribution generation (DG) and electric vehicle (EV) fleets considering techno-environmental aspects in the operation and control of radial distribution networks (RDN). By imitating the human behavior in getting fruitful life, the FSA starts arbitrary search, discovers neighborhood best people in different nations and looks at worldwide best individuals to arrive at an ideal solution. A techno-environmental multi-objective function is formulated using real power loss, voltage stability index. The active and reactive power compensation limits and different operational constraints of RDN are considered while minimizing the proposed objective function. Post optimization, the impact of DGs on conventional energy sources is analyzed by evaluating their greenhouse gas emission. The effectiveness of the proposed methodology is presented using different case studies on Indian practical 106-bus agriculture feeder for DGs and 36-bus rural residential feeder for simultaneous allocation of DGs and EV fleets. Also, the superiority of FSA in terms of global optima, convergence characteristics is compared with various other recent heuristic algorithms. 2021, The Author(s). -
Future Technology and Labour - Are we Heading Towards a Jobless Future?
Technological innovations and the invention of machines powered by Artificial intelligence2have changed the way we work, interact and carry on our everyday lives. Automation wave has revolutionized the manner in which the traditional manufacturing and service-oriented industries are functioning today. The first industrial revolution was triggered with the invention of steam engine and also led to mechanical production. The invention of electricity and assembly lines resulted in the second industrial revolution where mass production became feasible. The third industrial revolution was driven by computer, digital technology and the internet. The future technologies have resulted in the fourth industrial revolution. The new age technological innovations and inventions such as the automated robots; big data and analytics; augmented reality; the cloud; cyber security; additive manufacturing; horizontal and vertical integration; the internet of things are transforming industrial production and labour relations. There is a drastic improvement in the entire chain of production ranging from design up to productivity, the speed and the quality at which the goods are produced. As a result of the new age technologies various concerns are raised especially its impact on the employment. Many labourers are rendered unemployed and redundant due to automation. The question that arises is whether we are approaching a jobless future?? The job market in India is also undergoing a transformation and posing many social, economic, legal and ethical challenges. Job structure is changing and the workers need to equip themselves with new skills to fit into the new jobs that are emerging as a result of technological innovation. The education system in any country plays a pivotal role in the overall development of an economy as it caters to the needs of the trained and skilled manpower. It is vital for the education system in the country to re-orient itself to cater to the needs of the students to fit into the changing paradigm. The focus of the education needs to be on imparting life-skills and to improve the thinking, problem-solving and decision-making ability of the individuals in a society. In the light of the above, it is also important to address and discuss the various changes, issues and challenges that are taking place in the labour market including the impact of these technologies on the working hours, wages, the working environment and the labour relations amongst others. 2019, Department of Law, University of North Bengal. All rights reserved. -
FUZZY MODULARITY AND FUZZY COMPLEMENTS IN FUZZY LATTICES
In this paper, we study the concept of fuzzy modularity in fuzzy lattices. We also define a fuzzy Birkhoff lattice and study fuzzy complements in fuzzy lattices. We prove that the notions of a right and a left complement coincide in a fuzzy lattice I??k University, Department of Mathematics, 2022; all rights reserved -
FUZZY SEMI-ESSENTIAL SUBMODULES AND FUZZY SEMI-CLOSED SUBMODULES
In this paper, we prove some properties of fuzzy semi-essential submodules and fuzzy semi-closed submodules I??k University, Department of Mathematics, 2023; all rights reserved -
GaitRec-Net: A Deep Neural Network for Gait Disorder Detection Using Ground Reaction Force
Walking (gait) irregularities and abnormalities are predictors and symptoms of disorder and disability. In the past, elaborate video (camera-based) systems, pressure mats, or a mix of the two has been used in clinical settings to monitor and evaluate gait. This article presents an artificial intelligence-based comprehensive investigation of ground reaction force (GRF) pattern to classify the healthy control and gait disorders using the large-scale ground reaction force. The used dataset comprised GRF measurements from different patients. The article includes machine learning- and deep learning-based models to classify healthy and gait disorder patients using ground reaction force. A deep learning-based architecture GaitRec-Net is proposed for this classification. The classification results were evaluated using various metrics, and each experiment was analysed using a fivefold cross-validation approach. Compared to machine learning classifiers, the proposed deep learning model is found better for feature extraction resulting in high accuracy of classification. As a result, the proposed framework presents a promising step in the direction of automatic categorization of abnormal gait pattern. 2022 Chandrasen Pandey et al. -
Galerkin finite element analysis of magneto-hydrodynamic natural convection of Cu-water nanoliquid in a baffled U-shaped enclosure
In this paper, single-phase homogeneous nanofluid model is proposed to investigate the natural convection of magneto-hydrodynamic (MHD) flow of Newtonian CuH2O nanoliquid in a baffled U-shaped enclosure. The Brinkman model and Wasp model are considered to measure the effective dynamic viscosity and effective thermal conductivity of the nanoliquid correspondingly. Nanoliquid's effective properties such as specific heat, density and thermal expansion coefficient are modeled using mixture theory. The complicated PDS (partial differential system) is treated for numeric solutions via the Galerkin ?nite element method. The pertinent parameters Hartmann number (1 ? Ha ? 60), Rayleigh number (103 ? Ra ? 106) and nanoparticles volume fraction (0% ? ? ? 4%) are taken for the parametric analysis, and it is conducted via streamlines and isotherms. Excellent agreement between numerical results and open literature. It is ascertained that heat transfer rate enhances with Rayleigh number Ra and volume fraction ?, however it is diminished for larger Hartmann number Ha. 2020 Beihang University -
Gamma irradiation effects in InBi0.8Te0.2 crystals grown by horizontal directional freezing
The high-energy gamma-ray irradiation treatment using Co-60 isotope offers the possibility of engineering mechanical and optoelectronic properties of InBi0.8Te0.2 crystals. Tellurium-doped indium bismuthide (InBi) crystals were prepared by horizontal directional freezing technique. Dose-dependent modifications in structure, composition and surface topographical features have been analyzed by X-ray powder diffraction, X-ray energy-dispersive analysis, transmission electron and atomic force microscopy, respectively. Dielectric constant and dielectric loss were found to increase with the cumulative dose of radiation, and a shift in the ferroelectric transition temperature (T0c0) from 405 to 410 K was observed for 25 kGy. Upon irradiation, there is an enhancement in microhardness (H0V0), yield stress (sigma; 0y0) and stiffness constant (C0110). The optical transmittance was decreased by 12.45%, resulting in a reduction in the optical band gap from 0.210 eV to 0.198 eV. These results indicate the suitability of InBi00.80Sb00.20 crystals for low-wavelength infrared applications. The Chinese Society for Metals and Springer-Verlag Berlin Heidelberg 2015. -
Gammaless gamma-ray bursts?
One of the possible resolutions of the compactness problem in gamma-ray bursts (GRBs) is by invoking the Lorentz factors associated with the relativistic bulk motion. This model applies to GRBs where sufficient energy is converted to accelerate the ejected matter to relativistic speeds. In some situations, this may not be a possible mechanism, and as a result, the gamma rays are trapped in the region. In this work, we look at such possible scenarios and where the neutrino pair production process can dominate. As a result, the neutrinos can escape freely. This could give rise to a scenario where the release of neutrinos precedes the gamma-ray emission that is much attenuated. This model can thus possibly explain why fewer GRBs are observed than what is expected. 2023, Indian Association for the Cultivation of Science. -
Gandhiji and RSS: The Cultural Grounding of Social Representations
Exploring the cordial relationship and mutual respect between Gandhiji and the Rashtriya Swayamsevak Sangh (RSS), this article critically examines the political rhetoric against the RSS and its implications. As a nationalist cultural organisation, the RSS had been well aligned with most of the social and cultural programmes initiated by Gandhiji. When critics of the RSS like Jawaharlal Nehru were keen on crushing the RSS, the truth-seeking political philosopher Gandhiji applauded its discipline, annihilation of untouchability and the rigorous simplicity. This article demonstrates how the serious charges against the RSS that were brought to the notice of Gandhiji by a section of Congress leaders further cemented the cultural grounding of social representations between the two, instead of making Gandhiji be the stranger of the RSS. 2023 ICHR. -
Ganga and Yamuna Rivers: Through the Lens of the National Green Tribunal
Despite the country's extensive environmental jurisprudence and many historic rulings in which the courts have rescued worsening environmental situations, river (Ganga and Yamuna) water does not match the mandated minimum "bathing quality." Rivers like the Ganga and Yamuna, which flow through numerous states and towns, would be in a different situation. Without strict monitoring and enforcement of the measures, no action plan can work. Punishment of defaulters can serve as deterrence while also instilling fear in other non-compliant enterprises. In comparison to environmental legislation, the NGT Act allows for substantially harsher fines and penalties. River rejuvenation plans must be carefully monitored to ensure that they do not suffer the same fate. Making action plans will not improve river water quality unless they are implemented with sincerity and consistency, as well as continuous monitoring and severe enforcement. 2022 Technoscience Publications. All rights reserved. -
Garcinia indica Leaf Extract Derived Ag-Zn Nanocomposites: A Sustainable Approach for Textile Dyes Photodegradation
The recent advancements for the biosynthesis of nanoparticles from plant biomass offer a promising avenue for the sustainable and environmentally friendly production of nanomaterials. The utilization of plant extracts as bioreductants and capping agents leverages naturally occurring biomolecules for the controlled synthesis of nanoparticles, minimizing environmental impacts and promoting a more sustainable nanotechnology landscape. This study explores the biofabrication of silver-zinc nanocomposites (Ag-Zn NCs) using Garcinia indica leaf extract, offering a green and sustainable alternative to conventional methods. The synthesized nanocomposites were characterized using UV-vis, FTIR, XRD and TEM analyses. The UV-vis spectra confirmed the formation of nanocomposites with distinct surface plasmon resonance peaks (355 nm and 408 nm). FTIR identified functional groups involved in the bioreduction, while XRD indicated a crystalline size of 6.26 nm. TEM images revealed a mixture of hexagonal, spherical and rod-shaped nanocomposites with an average size of 40.37 nm. Furthermore, the study evaluated the photocatalytic activity of the Ag-Zn NCs against various reactive textile dyes (RY-86, RY-145, RB-220 and RB-222). Remarkably, the nanoparticles achieved an impressive 87-100% degradation of these dyes within 160-320 min under UV irradiation. This highlights the potential of biofabricated Ag-Zn NCs for environmental remediation, particularly in treating dye contaminated industrial effluents. This work demonstrates the feasibility of using G. indica leaf extract for the sustainable synthesis of Ag-Zn NCs with efficient dye degradation capabilities. 2024 Asian Publication Corporation. All rights reserved. -
Garlic peel based mesoporous carbon nanospheres for an effective removal of malachite green dye from aqueous solutions: Detailed isotherms and kinetics
Biowaste based nanoadsorbents have gained much attention in the recent times for wastewater decolourization owing to their low cost, high surface area and high adsorption capacities. In the present research, garlic peel based nanoparticles (GCNP) were synthesized at different temperatures by a one step pyrolytic green approach for the effective removal of cationic dye, malachite green from the aqueous medium. The surface properties of Garlic nanoparticles were elucidated by N2 adsorption- desorption and all the GCNP samples were found to exhibit Type IV(a) isotherm indicating the presence of mesopores in carbon matrix. Using BET calculations, highest surface area (380 m2/g) was obtained for GCNP synthesized at 1000 ?C. Characterization of nanoparticles was done by XRD, EDAX, SEM and FTIR studies before and after the dye treatment. Adsorption studies conducted using different parameters like contact time, concentration and pH and dosage of adsorbent showed removal efficiency above 90% for the contact time of 70 min. Best adsorption experimental results were obtained for GCNP synthesized at 1000 C ascribable to its high surface area, higher total pore volume (0.26 cm2/g) and higher carbon content. Four adsorption isotherm models were used to validate batch equillibrium studies and the results showed data in good agreement with Langmuir and Freundlich isotherms with maximum Langmuir adsorbtion capactiy to be 373.7 mg/g. Kinetic modelling of the data showed best fit with the Pseudo second order model with rate constant value of 48.726 g mg?1 min?1. Regenerative studies were conducted conducted upto 6 cycles. Also the GC nanoparticles were tested for their compatibility in membrane form wherein, removal efficiency results were obtained for GCNP anchored in polyvinyl difluoride (PVDF) and polysulfone (PSF) membrane matrix for dye adsorption. 2022 Elsevier B.V. -
Gas Kinematics and Dynamics of Carina Pillars: A Case Study of G287.76-0.87
We study the kinematics of a pillar, namely G287.76-0.87, using three rotational lines of 12CO(5-4), 12CO(8-7), 12CO(11-10), and a fine structure line of [O i] 63 ?m in southern Carina observed by SOFIA/GREAT. This pillar is irradiated by the associated massive star cluster Trumpler 16, which includes ? Carina. Our analysis shows that the relative velocity of the pillar with respect to this ionization source is small, ?1 km s?1, and the gas motion in the tail is more turbulent than in the head. We also performed analytical calculations to estimate the gas column density in local thermal equilibrium (LTE) conditions, which yields N CO as (?0.2-5) 1017 cm?2. We further constrain the gass physical properties in non-LTE conditions using RADEX. The non-LTE estimations result in n H 2 ? 10 5 cm ? 3 and N CO ? 1016 cm?2. We found that the thermal pressure within the G287.76-0.87 pillar is sufficiently high to make it stable for the surrounding hot gas and radiation feedback if the winds are not active. While they are active, stellar winds from the clustered stars sculpt the surrounding molecular cloud into pillars within the giant bubble around ? Carina. 2024. The Author(s). Published by the American Astronomical Society. -
GASP XVIII: Star formation quenching due to AGN feedback in the central region of a jellyfish galaxy
We report evidence for star formation quenching in the central 8.6 kpc region of the jellyfish galaxy JO201 that hosts an active galactic nucleus (AGN), while undergoing strong ram-pressure stripping. The ultraviolet imaging data of the galaxy disc reveal a region with reduced flux around the centre of the galaxy and a horse-shoe-shaped region with enhanced flux in the outer disc. The characterization of the ionization regions based on emission line diagnostic diagrams shows that the region of reduced flux seen in the ultraviolet is within the AGN-dominated area. The CO J2-1 map of the galaxy disc reveals a cavity in the central region. The image of the galaxy disc at redder wavelengths (9050-9250 reveals the presence of a stellar bar. The star formation rate map of the galaxy disc shows that the star formation suppression in the cavity occurred in the last few 108 yr. We present several lines of evidence supporting the scenario that suppression of star formation in the central region of the disc is most likely due to the feedback from the AGN. The observations reported here make JO201 a unique case of AGN feedback and environmental effects suppressing star formation in a spiral galaxy. 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. -
GASP XXIII: A Jellyfish Galaxy as an Astrophysical Laboratory of the Baryonic Cycle
With MUSE, Chandra, VLA, ALMA, and UVIT data from the GASP program, we study the multiphase baryonic components in a jellyfish galaxy (JW100) with a stellar mass 3.2 1011 M o hosting an active galactic nucleus (AGN). We present its spectacular extraplanar tails of ionized and molecular gas, UV stellar light, and X-ray and radio continuum emission. This galaxy represents an excellent laboratory to study the interplay between different gas phases and star formation and the influence of gas stripping, gas heating, and AGNs. We analyze the physical origin of the emission at different wavelengths in the tail, in particular in situ star formation (related to H?, CO, and UV emission), synchrotron emission from relativistic electrons (producing the radio continuum), and heating of the stripped interstellar medium (ISM; responsible for the X-ray emission). We show the similarities and differences of the spatial distributions of ionized gas, molecular gas, and UV light and argue that the mismatch on small scales (1 kpc) is due to different stages of the star formation process. We present the relation H?-X-ray surface brightness, which is steeper for star-forming regions than for diffuse ionized gas regions with a high [O i]/H? ratio. We propose that ISM heating due to interaction with the intracluster medium (either for mixing, thermal conduction, or shocks) is responsible for the X-ray tail, observed [O i] excess, and lack of star formation in the northern part of the tail. We also report the tentative discovery in the tail of the most distant (and among the brightest) currently known ULX, a pointlike ultraluminous X-ray source commonly originating in a binary stellar system powered by either an intermediate-mass black hole or a magnetized neutron star. 2019. The American Astronomical Society. All rights reserved. -
GASP. XV. A MUSE view of extreme ram-pressure stripping along the line of sight: Physical properties of the jellyfish galaxy JO201
We present a study of the physical properties of JO201, a unique disc galaxy with extended tails undergoing extreme ram-pressure stripping (RPS) as it moves through the massive cluster Abell 85 at supersonic speeds mostly along the line of sight. JO201 was observed with multi-unit spectroscopic explorer as part of the GASP programme. In a previous paper (GASP II) we studied the stellar and gas kinematics. In this paper we present emission-line ratios, gas-phase metallicities, and ages of the stellar populations across the galaxy disc and tails. We find that while the emission at the core of the galaxy is dominated by an active galactic nucleus (AGN), the disc is composed of star-forming knots surrounded by excited diffuse gas. The collection of star-forming knots presents a metallicity gradient steadily decreasing from the centre of the galaxy outwards, and the ages of the stars across the galaxy show that the tails formed ? 109 yr ago. This result is consistent with an estimate of the stripping time-scale (?1 Gyr), obtained from a toy orbital model. Overall, our results independently and consistently support a scenario in which a recent or ongoing event of intense RPS acting from the outer disc inwards, causes removal and compression of gas, thus altering the AGN and star formation activity within and around the galaxy. 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society. -
Gastronomic delights for community growth: unravelling the impact of sustainable tourism in Sikkim, India
Community development (CD) and sustainable gastronomy tourism development (SGTD) are mutually beneficial. Therefore, this study calls for a thorough investigation and interpretation of the phenomenon. In the context of Sikkim, India, this study examines the effects of SGTD on CD. The research question of whether sustainable gastronomy tourism (SGT) influences CD is addressed through a narrative analysis. The stories of ten local food vendors are gathered and examined using the categorical-content approach. However, the narratives indicate that local food vendors do believe that SGTD can act as a catalyst for local development, and that using traditional food as an alternative source of income can offer them a number of benefits. Other facets of gastronomic tourism are identified in the stories that may have unfavourable effects. Several ways to promote SGTD are suggested. The paper concludes that, to endorse gastronomic tourism (GT), local community involvement and strict policies are crucial. Copyright 2024 Inderscience Enterprises Ltd. -
Gaussian MutationSpider Monkey Optimization (GM-SMO) Model for Remote Sensing Scene Classification
Scene classification aims to classify various objects and land use classes such as farms, highways, rivers, and airplanes in the remote sensing images. In recent times, the Convolutional Neural Network (CNN) based models have been widely applied in scene classification, due to their efficiency in feature representation. The CNN based models have the limitation of overfitting problems, due to the generation of more features in the convolutional layer and imbalanced data problems. This study proposed Gaussian MutationSpider Monkey Optimization (GM-SMO) model for feature selection to solve overfitting and imbalanced data problems in scene classification. The Gaussian mutation changes the position of the solution after exploration to increase the exploitation in feature selection. The GM-SMO model maintains better tradeoff between exploration and exploitation to select relevant features for superior classification. The GM-SMO model selects unique features to overcome overfitting and imbalanced data problems. In this manuscript, the Generative Adversarial Network (GAN) is used for generating the augmented images, and the AlexNet and Visual Geometry Group (VGG) 19 models are applied to extract the features from the augmented images. Then, the GM-SMO model selects unique features, which are given to the Long Short-Term Memory (LSTM) network for classification. In the resulting phase, the GM-SMO model achieves 99.46% of accuracy, where the existing transformer-CNN has achieved only 98.76% on the UCM dataset. 2022 by the authors.