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Predictive Analytics for Stock Market Trends using Machine Learning
Navigating the intricacies of stock market trends demands a novel approach capable of deciphering the web of financial data and market sentiment. This research embarks on a transformative journey into the realm of machine learning, where we harness the power of data to forecast stock market trends with increased precision and accuracy. Commencing with an exploration of stock market dynamics and the inherent limitations of traditional forecasting techniques, this paper takes a bold step into the future by embracing the potential of machine learning. The study begins with an in-depth analysis of data preprocessing, unraveling the complexity of feature selection and engineering, setting the stage for a data-driven odyssey. As our exploration progresses, we dive into the deployment of diverse machine learning algorithms, including linear regression, decision trees, random forests, and the formidable deep learning models such as recurrent neural networks (RNNs) and long short-term memory networks (LSTMs). These algorithms act as our guiding lights, revealing intricate patterns concealed within historical stock price data. Our journey reaches new heights as we recognize the significance of augmenting predictive models with external data sources. Incorporating elements like news sentiment analysis and macroeconomic indicators enriches our understanding of the market landscape, enhancing the predictive capabilities of our models. We also delve into the crucial aspects of model evaluation, guarding against overfitting, and selecting appropriate performance metrics to ensure robust and reliable predictions. The research reaches its zenith with a meticulous analysis of real-world case studies, providing a comparative perspective between machine learning models and traditional forecasting methods. The results underscore the remarkable potential of machine learning in predicting stock market trends more accurately. 2023 IEEE. -
Digital Forensics Investigation for Attacks on Artificial Intelligence
The new research approaches are needed to be adopted to deal with security threats in AI based systems. This research is aimed at investigating the Artificial Intelligence (AI) attacks that are malicious by design. It also deals with conceptualization of the problem and strategies for attacks on Artificial Intelligence (AI) using Digital Forensic tools. A specific class of problems in Adversarial attacks are tampering of Images for computational processing in applications of Digital Photography, Computer Vision, Pattern Recognition (Facial Mapping algorithms). State-of-the-art developments in forensics such as 1. Application of end-to-end Neural Network Training pipeline for image rendering and provenance analysis, 2. Deep-fake image analysis using frequency methods, wavelet analysis & tools like - Amped Authenticate, 3. Capsule networks for detecting forged images 4. Information transformation for Feature extraction via Image Forensic tools such as EXIF-SC, Splice Radar, Noiseprint 5. Application of generative adversarial Networks (GAN) based models as anti-Image Forensics [8], will be studied in great detail and a new research approach will be designed incorporating these advancements for utility of Digital Forensics. The Electrochemical Society -
Non-destructive classification of diversely stained capsicum annuum seed specimens of different cultivars using near-infrared imaging based optical intensity detection
The non-destructive classification of plant materials using optical inspection techniques has been gaining much recent attention in the field of agriculture research. Among them, a near-infrared (NIR) imaging method called optical coherence tomography (OCT) has become a well-known agricultural inspection tool since the last decade. Here we investigated the non-destructive identification capability of OCT to classify diversely stained (with various staining agents) Capsicum annuum seed specimens of different cultivars. A swept source (SS-OCT) system with a spectral band of 1310 nm was used to image unstained control C. annuum seeds along with diversely stained Capsicum seeds, belonging to different cultivar varieties, such as C. annuum cv. PR Ppareum, C. annuum cv. PR Yeol, and C. annuum cv. Asia Jeombo. The obtained cross-sectional images were further analyzed for the changes in the intensity of back-scattered light (resulting due to dye pigment material and internal morphological variations) using a depth scan profiling technique to identify the difference among each seed category. The graphically acquired depth scan profiling results revealed that the control specimens exhibit less back-scattered light intensity in depth scan profiles when compared to the stained seed specimens. Furthermore, a significant back-scattered light intensity difference among each different cultivar group can be identified as well. Thus, the potential capability of OCT based depth scan profiling technique for non-destructive classification of diversely stained C. annum seed specimens of different cultivars can be sufficiently confirmed through the proposed scheme. Hence, when compared to conventional seed sorting techniques, OCT can offer multipurpose advantages by performing sorting of seeds in respective to the dye staining and provides internal structural images non-destructively. 2018 by the authors. Licensee MDPI, Basel, Switzerland. -
The Effect of Prediction on Employee Engagement Organizational Commitment and Employee Performance Using Denoised Auto Encoder and SVM Based Model
The purpose of human resources is to ensure that the appropriate people are hired for open positions at appropriate times, that the system receive the necessary training, and that their performance is monitored and their perspective skills are secure through the use of evaluation methods. Despite the importance of this data to decision-makers, it can be difficult to glean useful insights from large datasets. Data mining has made it possible for human resources experts to automate the hitherto tedious task of manually processing enormous data sets. Finding almost perfect outcomes is the main goal of data mining, which is to discover hidden knowledge in data patterns and trends. The proposed method goes as follows: preprocessing is done by data cleaning and data normalization, feature selection using correlation and information theoretic ranking criteria. The last step in training and evaluating the model is using AE-SVM, which stands for Auto Encoder Support Vector Machine. The suggested model is more effective and performs better than two existing models: Support Vector Machine and AE-CNN. The suggested approach attains an accuracy rate of 94%. 2024 IEEE. -
Understanding the emerging integrated marketing communication strategies used in marketing Tamil films /
IOSR Journal Of Humanities And Social Science, Vol.21, Issue 2, Ver. V, pp.33-37, ISSN: e-ISSN: 2279-0837, p-ISSN: 2279-0845. -
An analogical study of the narrative techniques used in the film Paradesi (2013) an adaptation of Tamil translation (Yerium Panikkadu) of the novel 'Red Tea' /
International Journal Of Humanities and Social Science Invention, Vol.5, Issue 3, pp.1-6, ISSN: 2319-7722 (Online) 2319-7714 (Print). -
Review on Emerging Internet of Things Technologies to Fight the COVID-19
The Internet of Things (IoT) has been gaining attention in various disciplines ranging from agriculture, health, industries and home automation. When a pandemic first breaks out early detection, isolating the infected, and tracing the contacts are the most important challenges. IoT protocols like Radio-frequency identification (RFID), Wireless Fidelity (WiFi), Global Positioning System (GPS) are gaining popularity for providing solutions to these challenges. IoT based applications in the health sector are benefitting COVID-19 (coronavirus disease of 2019) patients during this pandemic situation. This article explores and reviews the various Internet of Things enabled technologies and applications used in screening, contact tracing, and surveillance. IoT based telemedicine processes are very useful during the pandemic COVID-19. The purpose of this paper is to deliver an overall understanding of the existing and proposed technologies of IoT based solutions to make the situations better during COVID-19. 2020 IEEE. -
Quasar catalogue for the astrometric calibration of the forthcoming ILMT survey
Quasars are ideal targets to use for astrometric calibration of large scale astronomical surveys as they have negligible proper motion and parallax.The forthcoming 4-m International Liquid Mirror Telescope (ILMT) will survey the sky that covers a width of about 27?. To carry out astrometric calibration of the ILMT observations, we aimed to compile a list of quasars with accurate equatorial coordinates and falling in the ILMT stripe. Towards this, we cross-correlated all the quasars that are known till the present date with the sources in the Gaia-DR2 catalogue, as the Gaia-DR2 sources have position uncertainties as small as a few milli arcsec (mas). We present here the results of this cross-correlation which is a catalogue of 6738 quasars that is suitable for astrometric calibration of the ILMT fields. In this work, we present this quasar catalogue. This catalogue of quasars can also be used to study quasar variability over diverse time scales when the ILMT starts its observations. While preparing this catalogue, we also confirmed that quasars in the ILMT stripe have proper motion and parallax lesser than 20 masyr- 1 and 10 mas, respectively. 2020, Indian Academy of Sciences. -
Determination of the size of the dust torus in H0507+164 through optical and infrared monitoring
The time delay between flux variations in different wavelength bands can be used to probe the inner regions of active galactic nuclei (AGNs). Here, we present the first measurements of the time delay between optical and near-infrared (NIR) flux variations in H0507+164, a nearby Seyfert 1.5 galaxy at z = 0.018. The observations in the optical V-band and NIR J, H, and Ks bands carried over 35 epochs during the period 2016 October to 2017 April were used to estimate the inner radius of the dusty torus. From a careful reduction and analysis of the data using cross-correlation techniques, we found delayed responses of the J, H, and Ks light curves to the V-band light curve. In the rest frame of the source, the lags between optical and NIR bands are found to be 27.1-12.0 +13.5 d (V versus J), 30.4-12.0 +13.9 d (V versus H) and 34.6-9.6 +12.1 d (V versus Ks). The lags between the optical and different NIR bands are thus consistent with each other. The measured lags indicate that the inner edge of dust torus is located at a distance of 0.029 pc from the central ultraviolet/optical AGN continuum. This is larger than the radius of the broad line region of this object determined from spectroscopic monitoring observations thereby supporting the unification model of AGN. The location of H0507+164 in the ?-MV plane indicates that our results are in excellent agreement with the now known lag-luminosity scaling relationship for dust in AGN. 2018 The Author(s). -
REMAP: Determination of the inner edge of the dust torus in AGN by measuring time delays
Active galactic nuclei (AGN) are high luminosity sources powered by accretion of matter onto super-massive black holes (SMBHs) located at the centres of galaxies. According to the Unification model of AGN, the SMBH is surrounded by a broad emission line region (BLR) and a dusty torus. It is difficult to study the extent of the dusty torus as the central region of AGN is not resolvable using any conventional imaging techniques available today. Though, current IR interferometric techniques could in principle resolve the torus in nearby AGN, it is very expensive and limited to few bright and nearby AGN. A more feasible alternative to the interferometric technique to find the extent of the dusty torus in AGN is the technique of reverberation mapping (RM). REMAP (REverberation Mapping of AGN Program) is a long term photometric monitoring program being carried out using the 2 m Himalayan Chandra Telescope (HCT) operated by the Indian Institute of Astrophysics, Bangalore, aimed at measuring the torus size in many AGN using the technique of RM. It involves accumulation of suitably long and well sampled light curves in the optical and near-infrared bands to measure the time delays between the light curves in different wavebands. These delays are used to determine the radius of the inner edge of the dust torus. REMAP was initiated in the year 2016 and since then about one hour of observing time once every five days (weather permitting) has been allocated at the HCT. Our initial sample carefully selected for this program consists of a total of 8 sources observable using the HCT. REMAP has resulted in the determination of the extent of the inner edge of the dusty torus in one AGN namely H0507+164. Data accumulation for the second source is completed and observations on the third source are going on. We will outline the motivation of this observational program, the observational strategy that is followed, the analysis procedures adopted for this work and the results obtained from this program till now. 2019 Societe Royale des Sciences de Liege. All rights reserved. -
Estimation of the size and structure of the broad line region using Bayesian approach
Understanding the geometry and kinematics of the broad line region (BLR) of active galactic nuclei (AGN) is important to estimate black hole masses in AGN and study the accretion process. The technique of reverberation mapping (RM) has provided estimates of BLR size for more than 100 AGN now; however, the structure of the BLR has been studied for only a handful number of objects. Towards this, we investigated the geometry of the BLR for a large sample of 57 AGN using archival RM data. We performed systematic modelling of the continuum and emission line light curves using a Markov chain Monte Carlo method based on Bayesian statistics implemented in PBMAP (Parallel Bayesian code for reverberation-MAPping data) code to constrain BLR geometrical parameters and recover velocity integrated transfer function. We found that the recovered transfer functions have various shapes such as single-peaked, double-peaked, and top-hat suggesting that AGN have very different BLR geometries. Our model lags are in general consistent with that estimated using the conventional cross-correlation methods. The BLR sizes obtained from our modelling approach is related to the luminosity with a slope of 0.583 0.026 and 0.471 0.084 based on H ? and H ? lines, respectively. We found a non-linear response of emission line fluxes to the ionizing optical continuum for 93 per cent objects. The estimated virial factors for the AGN studied in this work range from 0.79 to 4.94 having a mean at 1.78 1.77 consistent with the values found in the literature. 2021 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
Dust reverberation mapping of Z229-15
We report results of the dust reverberation mapping (DRM) on the Seyfert 1 galaxy Z229-15 at z = 0.0273. Quasi-simultaneous photometric observations for a total of 48 epochs were acquired during the period 2017 July to 2018 December in B, V, J, H and Ks bands. The calculated spectral index (?) between B and V bands for each epoch was used to correct for the accretion disc (AD) component present in the infrared light curves. The observed ? ranges between -0.99 and 1.03. Using cross-correlation function analysis we found significant time delays between the optical V and the AD corrected J, H and Ks light curves. The lags in the rest frame of the source are 12.52+10.00 -9.55 d (between V and J), 15.63+5.05 -5.11 d (between V and H) and 20.36+5.82 -5.68 d (between V and Ks). Given the large error bars, these lags are consistent with each other. However, considering the lag between V and Ks bands to represent the inner edge of the dust torus, the torus in Z229-15 lies at a distance of 0.017 pc from the central ionizing continuum. This is smaller than that expected from the radius luminosity (R-L) relationship known from DRM. Using a constant ? = 0.1 to account for theADcomponent, as is normally done in DRM, the deduced radius (0.025 pc) lies close to the expected R-L relation. However, usage of constant ? in DRM is disfavoured as the ? of the ionizing continuum changes with the flux of the source. 2021 Oxford University Press. All rights reserved. -
Changing look AGN Mrk 590: Broad-line region and black hole mass from photometric reverberation mapping
We present the results of photometric reverberation mapping observations on the changing look active galactic nucleus Mrk 590 at z = 0.026. The observations were carried out from 2018 July to December using broad-bandB-,R-, and narrow-band H ? and S ii filters. The B band traces the continuum emission from the accretion disc, the R band encompasses both the continuum emission from the accretion disc and the redshifted H ? line from the broad-line region (BLR), the S ii band contains the redshifted H ? emission and the H ? band traces the continuum emission underneath the S ii band. All the light curves showed strong variation with a fractional root-mean-square variation of 0.132 0.001 in the B band and 0.321 0.001 in H ? line. From cross-correlation function analysis, we obtained a delayed response of H ? line emission to the opticalB-band continuum emission of $21.44^{+1.49}_{-2.11}$ d in the rest frame of the source, corresponding to a linear size of the BLR of 0.018 pc. This is consistent with previous estimates using H ?. By combining the BLR size with the H ? line full width at half-maximum of 6478 240 km s-1 measured from a single-epoch spectrum obtained with the Subaru telescope, we derived a black hole mass of $1.96^{+0.15}_{-0.21}\times 10^8 {\rm M}_{\odot }$. 2021 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
Optical Resonator-Enhanced Random Lasing using Atomically Thin Aluminium-based Multicomponent Quasicrystals
Photon trapping inside a gain medium using a dispersed two-dimensional (2D) passive scatterer is an impetus to obtain incoherent random lasing (ic-RL) emission due to non-resonant feedback. An optical resonator (OR) can be used to influence such lasing thresholds. Non-noble nanomaterials-based quasicrystals (QCs) are an intriguing research prospect due to their potential surface plasmon resonance (SPR) property and ability to be exfoliated into 2D. In this work, an aluminium-based multicomponent alloy (Al70Co10Fe5Ni10Cu5) has been synthesized via the arc melting method. Thereafter, ultrasonication-based liquid phase exfoliation was used to obtain 2D quasicrystals (2D-QCs). The SPR-induced light scattering properties of synthesized 2D-QCs were exploited to obtain ic-RL from DCM dye gain medium under 532 nm, 10 ns, 10 Hz pulsed laser pumping. The plasmonic field enhancement property of 2D-QCs which enables the gain medium to absorb photons outside its peak absorption band has been demonstrated. The transition from ic-RL to OR-enhanced ic-RL and vice versa in the presence of resonator walls has been achieved by tweaking the device architecture. In this way, the ability of 2D-QCs to be potential passive scatterers and the controllability of lasing thresholds in the presence of an OR has been demonstrated. 2024 Elsevier Ltd -
Electronic structure and intrinsic dielectric polarization of defect-engineered rutile TiO2
Experimental realization of colossal permittivity associated with intrinsic dielectric polarization of defect-engineered (Nb, In) co-doped rutile TiO2 appears to be most suitable for microelectronics and solid-state device applications. Combining resonant photoemission spectroscopy, X-ray absorption spectroscopy, and density functional theory calculations, we here present a coherent understanding of electronic structure, in-gap defect states, doped electron localization, and their connection with macroscopic polarization for various doping configurations. Most often, conventional sample preparation conditions introduce in-gap states of Ti3+? character, limiting the maximum achievable intrinsic polarization value. Our understanding provides a pathway to enhance intrinsic polarization and minimize dielectric loss through suitable defect-engineering. The Royal Society of Chemistry. -
Echo mapping of active galactic nuclei
Active galactic nuclei (AGN) are the persistent high luminosity sources powered by accretion of matter onto super massive black holes (SMBHs) at their centres. They are known to show flux variation and this property can be used as an effective tool to map the extent of the broad line region (BLR) and the dusty torus that surrounds the central SMBH. Though the mass of the SMBH (MBH) can be directly measured using the dynamics
of stars that are close to the SMBH, this method is limited to objects in the low redshift Universe (z < 0.1). On the other hand, the technique of reverberation mapping (RM) can provide MBH estimate over a range of redshifts. RM is based on the light travel time delayed response of the line emitting gas as well as the re-processed torus emission to changes in the continuum emission from the accretion disk. As of now, MBH measurements are available for more than 100 sources based on RM. The obtained
BLR sizes (RBLR) are found to be correlated with the optical luminosity (L5100) at wavelength 5100 Å. This relationship is obtained based on measurements of AGN available over a limited range of luminosity. Moreover, many of these measurements also have larger error bars. Therefore, there
is an urgent need to increase RM measurements with small errors on more AGN covering a wide range of redshifts to better constrain the RBLR − L5100 relation. -
Echo mapping of active galacticn nuclei
Active galactic nuclei (AGN) are the persistent high luminosity sources powered by accretion of matter onto super massive black holes (SMBHs) at their centres. They are known to show flux variation and this property can be used as an effective tool to map the extent of the broad line region (BLR) and the dusty torus that surrounds the central SMBH. Though the mass of the SMBH (MBH) can be directly measured using the dynamics of stars that are close to the SMBH, this method is limited to objects in the low redshift Universe (z < 0.1). On the other hand, the technique of reverberation mapping (RM) can provide MBH estimate over a range of redshifts. RM is based on the light travel time delayed response of the line emitting gas as well as the re-processed torus emission to changes in the continuum emission from the accretion disk. As of now, MBH measure-ments are available for more than 100 sources based on RM. The obtained BLR sizes (RBLR) are found to be correlated with the optical luminosity (L5100) at wavelength 5100 This relationship is obtained based on mea-surements of AGN available over a limited range of luminosity. Moreover, many of these measurements also have larger error bars. Therefore, there is an urgent need to increase RM measurements with small errors on more AGN covering a wide range of redshifts to better constrain the RBLR ? L5100 relation. We have carried out photometric reverberation observa- tions on the AGN Mrk 590. Using both broad band (that overlaps with the continuum) and narrow band (that overlaps with the H? emission line) observations, we found the BLR size to be 21.44+1.49 ?2.11 days, which is equiv- alent to 0.018+0.001 ?0.002 pc. Using this measured BLR size and the full width at half maximum of the H? line measured from the newly acquired Subaru spectrum we found a black hole mass of 1.96+0.15 ?0.21 108 M , using virial relationship and adopting a scale factor of 1.12. Similar to BLR reverberation mapping, the extent of the dusty torus in AGN can also be measured using dust reverberation mapping (DRM) based on the delayed response of the near infrared (NIR) flux from the torus to the ionizing UV/optical continuum coming from the accretion disk. From these observations too, a strong correlation is known to exist between the torus size (Rdust) and the optical luminosity (LV). Based on the Rdust ?LV relation, it is also possible to use AGN as standard candle to con- strain the Hubble constant (H0) and other cosmological parameters. But for that, a large number of DRM observations are needed at different red- shifts. As of today, very few NIR interferometric observations are avail-able, but measurements of the torus size via such direct imaging observa-tions are again limited to very near and bright AGN. Moreover, there is a large discrepancy in the size of the torus obtained via the direct imaging method through interferometry and that obtained from DRM. From long term monitoring in the optical and infra-red, we found the inner edge of the dust torus in H0507+164 and Z229?15 to lie at a distance of 0.029+0.010 ?0.008 pc and 0.017+0.005 ?0.005 pc, respectively, from the central optical continuum source. These two new measurements are also found to lie closely on the known Rdust ? LV relation line. Also, by modeling the available BLR RM data in the literature, it is possible to constrain the size, structure and kinemat-ics of the BLR using Bayesian approach. This approach is adopted several times to study the BLR morphology by different ways but is not applied to a large number of sources in an homogeneous manner. From an analysis of the RM data for a total of 57 sources following a Bayesian approach, we could constrain the structure of the BLR in them as well as derive other properties of BLR. -
An Integrated Reinforcement DQNN Algorithm to Detect Crime Anomaly Objects in Smart Cities
In olden days it is difficult to identify the unsusceptible forces happening in the society but with the advancement of smart devices, government has started constructing smart cities with the help of IoT devices, to capture the susceptible events happening in and around the surroundings to reduce the crime rate. But, unfortunately hackers or criminals are accessing these devices to protect themselves by remotely stopping these devices. So, the society need strong security environment, this can be achieved with the usage of reinforcement algorithms, which can detect the anomaly activities. The main reason for choosing the reinforcement algorithms is it efficiently handles a sequence of decisions based on the input captured from the videos. In the proposed system, the major objective is defined as minimum identification time from each frame by defining if then decision rules. It is a sort of autonomous system, where the system tries to learn from the penalties posed on it during the training phase. The proposed system has obtained an accuracy of 98.34% and the time to encrypt the attributes is also less. 2021. All Rights Reserved. -
A Critical Review of Applications of Artificial Intelligence (AI) and its Powered Technologies in the Financial Industry
The present research shed light on the applications of AI technologies for the financial industry of the UK. The research has also investigated the different types of powered technologies of AI and their impact on finance operations and activities. This research possesses the tools and techniques used by the researcher in gathering the research evidence for the proper completion of the research work. 2022 IEEE. -
Aggression Behaviour and Physical Fitness of National Handball Girls Players
Aggression is one of the significant types of feeling and emotion, which is exceptionally fundamental for sports execution. It is ordinarily propelled conduct at any rate for that specific purpose of time in the genuine play, which drives a player brimming with his energies towards his point. 150 School National Handball female players aged 14-17 years who were concentrated in higher optional schools of Andhra Pradesh Rural and Urban were haphazardly chosen as subjects. An aggression scale is used to contemplate the degree of aggression in any age gathering (over 14 years). The scale comprises 55 articulations. It is a Likert type 5-guide scale toward locating the aggressive conduct among Handball players. The premise of the discoveries is that the shooters have phenomenal aggression conduct than the all-rounders and defenders and shooters have more physical fitness than the all-rounders and defenders. In the examination, the Shooter would have a more aggressive inclination and physical fitness when contrasted with all-rounders and defenders. It is very different on the grounds that the Shooter alone for example independently will confront the adversary gathering of players because of body contact and the battle for greatness will lead the shooter to more aggressive than others. 2022 by authors, all rights reserved.