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Analysis of Market Behavior Using Popular Digital Design Technical Indicators and Neural Network
Forecasting the future price movements and the market trend with combinations of technical indicators and machine learning techniques has been a broad area of study and it is important to identify those models which produce results with accuracy. Technical analysis of stock movements considers the price and volume of stocks for prediction. Technical indicators such as Relative Strength Index (RSI), Stochastic Oscillator, Bollinger bands, and Moving Averages are used to find out the buy and sell signals along with the chart patterns which determine the price movements and trend of the market. In this article, the various technical indicator signals are considered as inputs and they are trained and tested through machine learning techniques to develop a model that predicts the movements accurately. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Hybrid Evolutionary Deep Learning Model Integrating Multi-Modal Data for Optimizing Ovarian Cancer Diagnosis
This research intends to enhance ovarian cancer detection by the combination of state-of-the-art machine learning algorithms with extensive multi-modal datasets. The Convolutional Neural Network (CNN), K-Nearest Neighbors (KNN), and VGG16 models were thoroughly assessed, displaying remarkable precision, recall, F1 scores, and overall accuracy. Notably, VGG16 emerged as a strong performance with a precision of 0.97, recall of 0.96, F1 score of 0.97, and accuracy reaching 98.65%. The addition of confusion matrices enables a thorough insight on each model's classification performance. Leveraging multiple datasets, spanning CT and MRI scans with demographic and biographical facts, promotes the holistic knowledge of ovarian cancer features. While the suggested Hybrid Evolutionary Deep Learning Model was not deployed in this work, the results underscore the potential for its development in future research. These discoveries signify a huge leap forward in early detection capabilities and individualized treatment techniques for ovarian cancer patients. As technology and medicine combine, this study tracks a road for breakthrough diagnostic approaches, empowering clinicians and encouraging favourable results in the continuing struggle against ovarian cancer. 2024 IEEE. -
Improving Groundwater Forecasting Accuracy with a Hybrid ARIMA-XGBoost Approach.
In addressing the critical challenge of accurate groundwater level prediction, this study explores the comparative performance of various machine learning models. We implement a novel hybrid model combining ARIMA and Extreme Gradient Boosting (XGB) for the prediction of groundwater levels, and compare it against traditional models including ARIMA, XGBoost, LightGBM, Random Forest, and Decision Trees. Traditional approaches often rely on single models; however, our research seeks to delve into the intricacies of hybrid model architectures. Combining the strengths of ARIMA and XGB, we aim to build a highly accurate and efficient groundwater level prediction system. Comprehensive evaluations were conducted using metrics such as Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE), The future scope of machine learning in water resource management includes integrating such models with real-time monitoring systems and expanding their applications to diverse environmental conditions and regions. 2024 IEEE. -
Bacillus velezensis-synthesized silver nanoparticles and its efficacy in controlling the Aedes aegypti
Abstract: Dengue fever and dengue haemorrhagic fever are diseases that do not have any potential medications. The severity of these diseases is fatal and thus poses a severe threat to mankind. Aedes aegypti is the vector that carries and spreads the dengue virus. Therefore, controlling the development and population of mosquitoes is crucial. Many insecticides and other strategies of control have not become successful in their purpose. Therefore, establishing potential compounds that are environmentally safe and productive in inhibiting the growth of mosquitoes is still to be acquired. Bacillus velezensis (MW219533) was utilized in the synthesis of silver nanoparticles with silver nitrate as the metal ion source. The silver nanoparticles were characterized and confirmed using UVvisible spectrometry that indicated a peak at 421 nm. Further analytical measurements such as X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy and energy dispersive X-ray analysis confirmed the presence of crystalline, cylindrical-shaped silver nanoparticles of size 5659 nm. The LC50 was found to be 581.39, 616.37, 760.93, 801.94 and 867.66 g l?1 when tested against the five developmental stages of Aedes aegypti, such as first instar, second instar, third instar, fourth instar stages of larvae and pupae, respectively. The predatory efficacy of Poecilia reticulata was calculated with exposure to silver nanoparticles. Our study aims on developing an environmentally safe and economical approach to reduce the development of mosquitoes in the environment. The work signifies the biological method towards controlling the larvae and pupae stages of A. aegypti as well as to mark its safety at the aquatic level of the life cycle that leaves no traces of pollution on the environment. Graphical abstract: [Figure not available: see fulltext.] 2023, Indian Academy of Sciences. -
Evaluation of potential larvicidal and pupicidal activity of Cassia fistula L. synthesized silver nanoparticles against Aedes aegypti
Dengue Fever (DF) and Dengue Hemorrhagic Fever (DHF) are fatal and are spread primarily by Aedes aegypti. Control measures against vector causing disease have still not been well documented. The fatality of these diseases has alarmed a need for the development of promising methods to control A. aegypti. Nanotechnology offers the utilization of nanosized particles to target specific disease causing vectors such as mosquitoes. In the present study, an attempt was designed to synthesize silver nanoparticles from Cassia fistula leaf extract and to test its efficacy in vector control. The synthesized silver nanoparticles were sized in the range of 59-62 nm. The silver nanoparticles were tested for their capability in larvicidal and pupicidal activity against all the larval stages and pupal stages of A. aegypti. The LC50 values demonstrated the lethal effect of the nano material against all the stages of A. aegypti. The study draws attention towards the usage of plant parts in nano product synthesis that can act as a potential insecticide. 2023, Indian journals. All rights reserved. -
A review on metal nanoparticles from medicinal plants: Synthesis, characterization and applications
Plant extracts contain secondary metabolites which have the potential to act as reducing and stabilizing agents contributing to a greener and more efficient method to synthesize nanoparticles. Rapid growth of Nanotechnology has led to an increased demand in various fields. This review summarizes the use of potent medicinal plant extracts to synthesize metal nanoparticles, methods employed to characterize the properties of the nanoparticles and its application. Characterization of the nanoparticle based on its shape, size, chemical bonds, surface properties, hydrodynamic diameter and crystalline structure using techniques such as UV-Visible Spectroscopy, XRD (X-ray Diffraction), TEM (Transmission Electron Microscopy), SEM (Scanning Electron Microscopy), EDS (X-ray energy dispersive spectroscopy), DLS (Dynamic Light Scattering), Zeta Potential and FTIR (Fourier Transform-Infrared Spectroscopy) are elaborated. The synthesized metal nanoparticles have wide ranges of applications such as antimicrobial activity, antioxidative capability, anticancer effect, antidiabetic properties, plant growth enhancement, dye degradation effects and anti-larval properties. Recent advances in nanotechnology with special emphasis on plant metabolites provide an insight into their usage as plant-derived edible nanoparticles (PDNPs). Applications, limitations and future prospects of this technology have also been briefly discussed. 2021 Bentham Science Publishers. -
Biocontrol of Aedes aegypti using Talaromyces islandicus Synthesized Silver Nanoparticles
Aedes aegypti is the vector that spreads the dengue virus, causing dengue fever and dengue hemorrhagic fever. With more than half the worlds population at the risk of acquiring this infection, controlling the Aedes mosquitoes is the only path to limit the spread of the fatal disease. The emergence of insect resistance in mosquitoes raised the need for developing novel insecticides. Present research is focused on using fungus (Talaromyces islandicus) as the biosystem in the synthesis of nanoparticles. Myco-synthesized silver nanoparticles were characterized using UV-visible spectrometry that exhibited a peak at 429 nm. The XRD spectral peaks were in the range of 27.83, 32.27, 38.23and 65.01. The FTIR spectrum showed peaks corresponding to O-H, N-O, S=O, etc. representing the silver nanoparticles. SEM and EDAX represent the formation of silver ions that are spherical in shape with a size range of 23 to 26 nm. The antioxidant activity of silver nanoparticles and the extract of Talaromyces islandicus were assessed by DPPH assay, reducing power assay and hydrogen peroxide assay. The nanoparticles studied for its bio efficacy against the larval stages of Aedes aegypti indicated the LC50 value of 352.03, 389.86, 397.72 and 443.50 when tested against first, second, third and fourth instar larvae. respectively. The LC50 value of 540.41 was determined against the pupae of Aedes. The predatory efficiency of P. reticulata indicated the positive feeding behaviour of the fish when exposed to the silver nanoparticles. The cell toxicity assay was conducted against C6/36 insect cell lines and the cell viability inhibition was calculated. A toxic free, environmentally acceptable approach for controlling the mosquito vector by utilizing fungal nanoparticles was assessed and their efficacy in vector control was analyzed in this study. 2022 Chemical Publishing Co.. All rights reserved. -
AUTOMATION OF TEST CASE PRIORITIZATION: A SYSTEMATIC LITERATURE REVIEW AND CURRENT TRENDS
An Important stage in software testing is designing a test suite [18]. The test case repository consists of a large number of test cases. However, only a portion of these test cases would be relevant and can find bugs. Test case prioritization(TCP) is one such technique that can substantially increase the cost-effectiveness of the testing activity. Using test case prioritization, more relevant test cases can be captured and tested in the earlier stages of the testing phase. The objective of the study is to understand different techniques used and a systemic study on the effectiveness of these approaches. The Literature consists of a few relevant articles introducing novel techniques for test case prioritization between 2008 and 2022. Studies show that parameters that are considered for test case prioritization are important. Hence, the current article also focuses on the parameters considered in the literature. 40% of the articles used in the literature review use different test case information as parameters. A systemic review and analysis of data sets involved in the literature are evaluated in the study. The review also focuses on the different approaches used for comparing the newly introduced approach and reveals a novel approach for prioritization. 2023 Little Lion Scientific. All rights reserved. -
Predictors of compassion competence among nurses working in the non-profit healthcare sector in India
Objectives: For many years, the non-profit healthcare sector in India has been able to instil a sense of goodwill in the society through the provision of healthcare services, which are not only affordable and accessible, but also deliver compassionate care. This study was an attempt to evaluate the compassionate care and competence of the nurses working in India's non-profit healthcare sector, and to identify the predictive factors associated with their work environment and engagement. Methods: A cross-sectional survey of nurses working in the medical college hospitals managed by private trusts in the non-profit sector in India was conducted using an online questionnaire. The study was conducted in April 2021 after the second wave of the Covid-19 pandemic. Socio-demographic factors, compassion competence, nurse practice environment, and nurse engagement were assessed. Linear regression analysis was conducted to identify the variance and the predictors of compassion competence among Indian nurses. Results: We found that nurses practice environment (?=0.982, p=< .001) and engagement (?=0.842, p=< .001) predicted compassion competence during the Covid-19 pandemic. Moreover, nurse practice environment and engagement positively influenced compassion competence. Conclusion: There was a considerably high level of compassion competence among nurses working in the non-profit healthcare sector during the Covid-19 pandemic. The compassion phenomenon was statistically significantly impacted by the nurses practice environment and their level of engagement. Consequently, not only does competent compassion behaviour require positive work environments and engaged nurses, but also nurses compassion competence and its relationship with practice environment factors and engagement are critical in the non-profit healthcare sector in India. These findings support previous reviews that a high degree of compassion competence increases healthcare quality. 2024 Jismon, M. G., Rofin T. M., Thekkekkara, J. V., Asha K. C., & Vijesh P. V. -
Time series forecasting for understanding potential buyer behavior with ecommerce
Ecommerce is a platform for e-business Companies and hawkers for dynamically responding consumer demand and supply. Furthermore, responses to the consumer include blot-from-blue service with great quality of appurtenances. Moreover, the Indian retail industry is currently ranking in the world's top five concerning the growth. Thus, data is a new oil for this era of digitization. Henceforth, Cluster and distance classifier plays an important role in data-related findings. Besides, the cluster will give an identical pattern of data with the inclusion of centroid for finding out useful information. Furthermore, an already formed identical cluster pattern will be useful for mapping with another cluster. Thus, in this way cluster mapping done. Mapped cluster pattern will be useful in establishing the customer relationship with products. Moreover, it leads to the profitability of the e-commerce platform. Thereafter, cluster mapping is align with the new RFM model for getting more clarity about the consumer-buying pattern. Besides, it helps in identifying the potential buyer consumer. Moreover, time series results obtained are positive for potential buyer behavior. Thus, when time series forecasting is used on the RFM model it gives rise potential buyer loyalty with an e-commerce platform. 2020 Ecological Society of India. All rights reserved. -
Simulation modeling for heart attack patient by mapping cholesterol level
Cholesterol is a complex structural material made up of four-fused hydrocarbon rings. There is a hydrocarbon tail linked at one end of the structure, while the hydroxyl group linked to each other on the other end. To one end of the structure, a hydrocarbon tail linked and to the other end, a hydroxyl group linked to each other. High cholesterol level is one among the major risk factors of a heart attack. It is feasible to compute and control the cholesterol level of a cardiovascular patient by making use of intended Mathematical modeling in System Dynamics (S.D.). Moreover, by simulating proposed set of equations for a heart attack patient, recovery accomplished at a faster pace. Because of S.D., a substantial amount of reduction in the patient's Cardiovascular Disease achieved by control over the sterol level of the heart patient. This simulation modeling is an attempt made in translational research domain and is useful in the healthcare industry health care industry. It will minimize the risk of heart stroke and maintain a healthy life. Copyright 2020 Institute of Advanced Engineering and Science. All rights reserved. -
An efficient 2-Step DNA symmetric cryptography algorithm based on dynamic data structures
The security of text has become highly demanding in today's fast growing networking world. DNA computing is one of the emerging technologies in the arena of huge data storage and parallel computation. A single gram of DNA holds 5.5 petabytes of data. This leads to the increased risk in data communication. DNA in computers is mapped to human genome. Thus, the sequence of nucleotide base constructs the foundation of uniqueness. In this paper, a new scheme acronymed as -'Cryptography on DNA Storage'-CDS is provided. It performs the DNA data encryption in just two-step by using random private key for each letter in the plaintext and parallel swapping of the resultant text in small clusters. It is discussed keeping the time and space complexity of the algorithm in concern. 2018 Authors. -
Asset productivity in organisations at the intersection of big data analytics and supply chain management
A close investigation is required on the fundamental instruments of an establishments big data analytics usage. This research paper mainly addresses how is an organizations value creation affected due to big data analytics usage, what is big data analytics, and what are its key antecedents in an organization to understand the aspects that influence the actual usage of big data analytics. Hence, the technology, organization, and environment framework are used. The review data collected from Indian founded corporations confirm that: organizational value creation is significantly affected by big data analytics usage in that organization; organizational BDA usage is indirectly influenced by environmental factors, technological factors, and organizational factors through top management support. Collectively, this research study will guide the business managers on the usage of big data analytics, and a theory-based comprehensive analysis of big data analytics usage and its key antecedents. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. -
Mobile in learning: Enhancement of information and communication technologies
The technological advancement in the world has changed the people's life. The people view point towards the usage of technologies in different fields like business, tourism, communication, education etc. has changed. Mobile learning can give flexible learning environ-ment for the user. It can also increase the participant number in the online teaching learning process. This paper discusses about the ef-fectiveness of the current technologies used in higher education system. It profiles the advantages of using mobile in accessing the uni-versity central system for teaching and learning. It also discusses about mobile digital book with augmentation, which can be used to improve the teaching and learning process of the different departments in the university. 2018 Authors. -
Development of efficient biometric recognition algorithms based on fingerprint and face /
The reliable verification systems are required to verify and confirm the identity of an individual requesting their service. Secure access to the buildings, laptops, cellular phones, ATM etc. is an example of such applications. In the absence of robust verification systems, these systems are vulnerable to the wiles of an impostor. The traditional ways of authentications are passwords (knowledge ?? based security) and the ID Cards (token ?? based security). These methods can be easily breached due to the chance of stolen, lost or forget. The development and progress of biometrics technology, the fear of stolen, lost or forget can be eliminated. Biometrics refers to the automatic identification (or verification) of an individual (or a claimed identity) by using certain physiological or behavioral traits associated with the person. The biometrics identifies the person based on features vector derived from physiological or behavioural characteristics such as uniqueness, permanence, accessibility, collectability with minimum cost. The physiological biometrics are Fingerprint, Hand Scan, Iris Scan, Facial Scan and Retina Scan etc., and behavioural biometric are Voice, Keystroke, Gait, Signature etc., The physiological biometrics measures the specific part of the structure or shape of a portion of a subjects body. But the behavioural biometric are more concerned with mood and environment. Chapter one presents the introduction to biometrics and its various traits. Further description like structure of the biometric system, different approaches are discussed. Also the design issues in biometric system such as universality, collectability, distinctiveness, permanence, acceptability, uniqueness, performance, circumvention etc., are discussed. Chapter two gives a detailed survey of biometric techniques. It includes the literature survey of fingerprint and face biometric traits and various approaches. In Chapter three, the algorithm of Fingerprint Verification based on Dual Tree Complex Wavelet Transformation (DTCWT) is proposed. The original fingerprint is cropped and resized to apply the DTCWT. The features of Fingerprint are obtained by applying different levels of DTCWT. Performance analysis is discussed with the FRR, FAR and TSR. Chapter four discusses another highly recommended source of authentication such as face recognition. In this chapter, the algorithm of Performance Comparison of Face Recognition using Transform Domain Techniques (PCFTD) is proposed. The face databases L ?? Spacek, JAFFE and NIR are considered. The features of face are generated using wavelet families such as Haar, Symelt and DB1 by considering approximation band only. The face features are also generated using magnitudes of FFTs. The test image features are compared with database features using Euclidian Distance (ED). The performance parameters such as FAR, FRR, TSR and EER computed using wavelet families and FFT. The methodology described in this paper is accurate, simple, fast and better than the existing algorithms. Chapter five presents conclusion and future work. -
Dissecting star formation in the "atoms-for-Peace" galaxy: UVIT observations of the post-merger galaxy NGC7252
Context. The tidal tails of post-merger galaxies exhibit ongoing star formation far from their disks. The study of such systems can be useful for our understanding of gas condensation in diverse environments. Aims. The ongoing star formation in the tidal tails of post-merger galaxies can be directly studied from ultraviolet (UV) imaging observations. Methods. The post merger galaxy NGC7252 ("Atoms-for-Peace" galaxy) is observed with the Astrosat UV imaging telescope (UVIT) in broadband NUV and FUV filters to isolate the star-forming regions in the tidal tails and study the spatial variation in star formation rates. Results. Based on ultraviolet imaging observations, we discuss star-forming regions of ages <200 Myr in the tidal tails. We measure star formation rates in these regions and in the main body of the galaxy. The integrated star formation rate (SFR) of NGC7252 (i.e., that in the galaxy and tidal tails combined) without correcting for extinction is found to be 0.81 0.01 M yr-1. We show that the integrated SFR can change by an order of magnitude if the extinction correction used in SFR derived from other proxies are taken into consideration. The star formation rates in the associated tidal dwarf galaxies (NGC7252E, SFR = 0.02 M yr-1 and NGC7252NW, SFR = 0.03 M yr-1) are typical of dwarf galaxies in the local Universe. The spatial resolution of the UV images reveals a gradient in star formation within the tidal dwarf galaxy. The star formation rates show a dependence on the distance from the centre of the galaxy. This can be due to the different initial conditions responsible for the triggering of star formation in the gas reservoir that was expelled during the recent merger in NGC7252. 2018 ESO. -
UVIT observations of the star-forming ring in NGC 7252: Evidence of possible AGN feedback suppressing central star formation
Context. Some post-merger galaxies are known to undergo a starburst phase that quickly depletes the gas reservoir and turns it into a red-sequence galaxy, though the details are still unclear. Aims. Here we explore the pattern of recent star formation in the central region of the post-merger galaxy NGC 7252 using high-resolution ultraviolet (UV) images from the UVIT on ASTROSAT. Methods. The UVIT images with 1.2 and 1.4 arcsec resolution in the FUV and NUV are used to construct a FUV-NUV colour map of the central region. Results. The FUV-NUV pixel colour map for this canonical post-merger galaxy reveals a blue circumnuclear ring of diameter ?10?? (3.2 kpc) with bluer patches located over the ring. Based on a comparison to single stellar population models, we show that the ring is comprised of stellar populations with ages ? 300 Myr, with embedded star-forming clumps of younger age (? 150Myr). Conclusions. The suppressed star formation in the central region, along with the recent finding of a large amount of ionised gas, leads us to speculate that this ring may be connected to past feedback from a central super-massive black hole that has ionised the hydrogen gas in the central ?4?? ?1.3 kpc. ESO 2018. -
More insights into bar quenching: Multi-wavelength analysis of four barred galaxies
The underlying nature of the process of star formation quenching in the central regions of barred disc galaxies that is due to the action of stellar bar is not fully understood. We present a multi-wavelength study of four barred galaxies using the archival data from optical, ultraviolet, infrared, CO, and HI imaging data on star formation progression and stellar and gas distribution to better understand the process of bar quenching. We found that for three galaxies, the region between the nuclear or central sub-kiloparsec region and the end of the bar (bar region) is devoid of neutral and molecular hydrogen. While the detected neutral hydrogen is very negligible, we note that molecular hydrogen is present abundantly in the nuclear or central sub-kiloparsec regions of all four galaxies. The bar co-rotation radius is also devoid of recent star formation for three out of four galaxies. One galaxy shows significant molecular hydrogen along the bar, which might mean that the gas is still being funnelled to the centre by the action of the stellar bar. Significant star formation is also present along the bar co-rotation radius of this galaxy. The study presented here supports a scenario in which gas redistribution as a result of the action of stellar bar clears the bar region of fuel for further star formation and eventually leads to star formation quenching in the bar region. 2020 ESO. -
Insights on bar quenching from a multiwavelength analysis: The case of Messier 95
The physical processes related to the eect of bars in the quenching of star formation in the region between the nuclear/central subkiloparsec region and the ends of the bar (bar region) of spiral galaxies is not fully understood. It is hypothesized that the bar can either stabilize the gas against collapse, inhibiting star formation, or eciently consume all the available gas, leaving no fuel for further star formation.We present a multiwavelength study using the archival data of an early-type barred spiral galaxy, Messier 95, which shows signatures of suppressed star formation in the bar region. Using optical, ultraviolet (UV), infrared, CO, and HI imaging data we study the pattern of star formation progression and stellar/gas distribution, and try to provide insights into the process responsible for the observed pattern. The FUV NUV pixel colour map reveals a cavity devoid of UV flux in the bar region that matches the length of the bar, which is 4.2 kpc. The central nuclear region of the galaxy shows a blue colour clump and along the major axis of the stellar bar the colour progressively becomes redder. Based on a comparison to single stellar population models, we show that the region of galaxy along the major axis of the bar, unlike the region outside the bar, is comprised of stellar populations with ages 350 Myr; there is a star-forming clump in the centre of younger ages of 150 Myr. Interestingly the bar region is also devoid of neutral and molecular hydrogen but has an abundant molecular hydrogen present at the nuclear region of the galaxy. Our results are consistent with a picture in which the stellar bar in Messier 95 is redistributing the gas by funnelling gas inflows to nuclear region, thus making the bar region devoid of fuel for star formation. ESO 2019. -
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.