447 research outputs found
The role of part structure in the perceptual localization of a shape
No full textThe process of object localization may be accomplished with respect to a particularreference location, such as the center of gravity, COG (eg Vishwanath and Kowler, 2003 VisionResearch 43 1637-1653). Here, we investigated how part structure affects an object's referencelocation. The reference location was evaluated with a measure of the illusory displacement of an internal target element embedded within a larger object (Morgan et al, 1990 Vision Research 30 1793-1810). To examine whether the reference location is different for shapes with part structure, two shapes were tested: circle (small and large; no part structure) and bell (shape with two parts, one larger than the other). Results were examined with respect to two predictions: either the location of an object is based on its shape as a whole, disregarding part structure (ie a single, overall COG), or the parts are processed separately (different COGs).With the circles, the results showed a systematic illusory displacement of the internal target toward the COG. With the bell, the illusion was significantly weaker than with both circles--even though the main part of the bell had the same size as the small circle, and its horizontal axis had the same extent as the large circle. Moreover, the distance judgments for the bell were consistent with a (weaker) reference point being located at the COG of the larger part, rather than at the COG of the entire bell. These results show that the part structure of a shape plays a role in the representation of its location, and that for complex shapes the perceived location of an embedded element depends more on the parts within which it is embedded, rather than on the whole shape.Supported by the Air Force Office of Scientific Research, Grant AF 49620- 02-1-0112, Life Sciences Directorate to Eileen Kowler, and by NSF, Grant BCS-0216944 to Manish Singh.AF 29620-02-1-0112; to Eileen KowlerNSF BCS-0216944; to Manish SinghDenisova, Kristina, Manish Singh, Eileen Kowler, 2006. The definitive, peer-reviewed and edited version of this article is published in Perception, 35, 1073-1087, DOI:10.1068/p5518
A Global focus on family::Experiences in diverse continents from an Indian diplomat optic
No full textA Global focus on family: Experiences in diverse continents from an Indian diplomat opticv. Rashmi Singla & Simon Warren On Thursday, 27th March 2025, Global Humanities program students at Roskilde University shared firsthand experiences of family life and related practices in diverse countries such as Ivory Coast, Sweden, Mongolia, USA and India, covering the four continents of the world. It was through the guest -speaker Anil Trigunayat, former Indian Ambassador of India, Jordan, Libya and Malta, accompanied by the current Indian ambassador Manish Prabhat to Denmark, who also participated in the discussion about the family life and practices under the module course session theme: Family life beyond ethnocentric belief: Developmental psychological perspective. Trigunayat has been a career diplomat for more than three decades, along with writing articles and books about foreign policy matters. The theme about family beyond ethnocentrism was a challenge for him, which he took up under the following title: " Family is the cornerstone for a good citizen experience in diverse continents from an Indian diplomat optic”.<br/
Fabrication of Langmuir-Blodgett film from Polyvinylpyrrolidone stabilized NiCo alloy nanoparticles
No full textThe fabrication of monolayer/multilayer films of Polyvinylpyrrolidone (PVP) stabilized NiCo alloy nanoparticles with an average particle size 7 nm via Langmuir–Blodgett method is presented in this paper. The NiCo alloy nanoparticles were synthesized in ethanol using hydrazine hydrate as reducing agent at 60 °C in the presence of PVP and washed with a mixture of chloroform–methanol (1:1) solution to get pure PVP capped alloy nanoparticles. The NiCo alloy suspension was spread to the interface of air/water and transferred to the glass surface. The formation of a Langmuir monolayer/multilayer of PVP stabilized NiCo particles at air/water interface were revealed with the pressure-area isotherm curve. The transfer of nanoparticles on the glass surface was found to be efficient for the first six layers as exhibited by the pressure-area isotherm and increases in absorption intensity in the UV–Vis range. The atomic force microscopy results show that this film has a cubic symmetry in a two dimensional (2D) array.
Manish Kumara, Anjali Pathaka, Mandeep Singhb, M.L. Singlaa
Application of levenberg marquardt algorithm for short term load forecasting: a theoretical investigation
No full textDynamic modeling and forecasting algorithms for financial data systems
No full textIt is a valid question that why a Control Systems Engineer would be interested in dealing with financial instruments. Financial instruments involving option theory are very elegant, math oriented and practical. These mathematical tools have created a new industry known as 'Derivative Industry' or 'Hedge-Fund Industry' or so called 'Risk-Management Industry'. This thesis is aimed at developing investment strategies involving the decision making needs via control system techniques. The problem, in general, is computationally challenging particularly when investment of many securities is involved resulting in a high dimensional computational framework. Furthermore, complications may arise due to realistic restrictions and non-linearities. The various areas of financial engineering are very fertile for the application of the system methodology and control theory techniques. Modeling, optimization, identification and computational methods used in the Systems Engineering can be successfully applied to the financial instruments. The ideas developed in this thesis are more about the scientific reasoning involving financial instruments rather than specific situations alone. Major contribution of this thesis is the time series optimal prediction filter and the development of the Dynamic Modeling and Forecasting Algorithm (DMFA). The proposed algorithm predicts the next data point of the financial time series while dynamically computing the parameters from existing data. The computation of the parameters is optimized by use of the recursive matrix inversion algorithm. The system is solved via an innovative technique of inversion such that it avoids explicit inversion of more than a 2 X 2 matrix and computation of higher dimensional determinants and co-factors. This results in new contributions to computation finance and numerical methodology along with arbitrage decision and hedging strategies under market uncertainties as well as robust control applications. The minimum mean-square algorithm used assures system stability via poles within the unit circle. The DMFA method is a superior auto regression (AR) model as a general system of time-series realizations in-order to calculate the coefficients that fit the model for a better prediction. Theoretical modeling and market specific volatility models, updated volatility computation are derived from the observation data.Ph.D.Includes bibliographical referencesIncludes vitaby Manish Mahaja
Speaker Indentification using Labview
No full textNow days, Biometrics is being used extensively for the purpose of security.
Biometrics deals with identifying individuals with their physiological such as fingerprint
DNA, ECG etc or behavioral traits i.e. rhythm, gait, voice etc. Voice is a most natural way
of communication and non-intrusive as a biometric, Voice biometric has characteristic of
acceptability, cost, easy to implement as no special equipment is required. Also Voice
based biometric system can be easily combined with other biometric systems to enhance
the reliability and security of the system.
In the present work a speaker identification system has been developed. The
developed system uses the LabVIEW (Laboratory Virtual Instrument Engineering
Workbench) 8.5 platform. Speaker Identification involves features extraction,
preprocessing, pattern matching, decision-making. Silence removing of voice signal is key
factor to improve the identification. In feature extraction stage, Mel frequency cepstrum
coefficients (MFCC) have been calculated which provides a better measure of Speaker
Identification than the other features. Speaker identification can be done by various
methods but in this thesis vector quantization based recognition system using LabVIEW
has been developed and tested. The developed system is user friendly and provides the
results in real time. A database of 20 person having 5 samples per person including male
and female has been created. The experiments conducted on the above database suggest
that an accuracy of 90% has been achieved with the developed system.Thapar University: Department of Electrical and Instrumentation Engineerin
Load Forecasting Using Artificial Neural Network
No full textThe key role of load forecasting is the power system energy management system. Load forecasting helps to diminish the production cost, spinning reserve capacity and enhance the reliability of the power system. Load forecasting is tremendously essential for financial institutions, power suppliers and other participants in electric energy market i.e. transmission, generation and distribution. The economic allotment of generation is a vital purpose of short term load forecasting.
This thesis presents a solution methodology using an artificial neural network for short term load forecasting. The inputs using for forecasting the load, i.e. Dry bulb temperature, Dew point temperature, humidity and load data. The load data is taken from the 66kv substation, Bhai Roopa, Bathinda and weather data from weather stations “IMD” Pune. The data are taken from the year 2015 and 2016. The back propagation algorithm has been implemented to minimize the error function derived on the basis of computed load and actual load. The effectiveness is also checked through its implemented under the MATLAB environment. Where, the Levenberg Marquardt algorithm is used and the performance is investigated under Multilayer Neural Network
The relationship between spatial pooling and attention in saccadic and perceptual tasks
No full textAbstractSaccades aimed at spatially extended targets land reliably at central locations determined by pooling information across the target shape [Melcher, D., & Kowler, E. (1999). Shape, surfaces and saccades. Vision Research, 39, 2929–2946; Vishwanath, D., & Kowler, E. (2003). Localization of shapes: Eye movements and perception compared. Vision Research, 43, 1637–1653]. Previous findings of saccadic errors when attempting to look at a target in the midst of distractors encouraged suggestions that pooling occurs indiscriminately, with little or no influence of a selective filter to eliminate the influence of nearby distractors. To determine the effectiveness of filtering, saccadic localization was studied for saccades made to a set of target elements (discs) interleaved with an equivalent set of distractors of a different color. With such interleaved elements, selection and spatial pooling are constrained to occur over the same spatial region. The results showed that filtering was effective and saccadic landing position was determined mainly by the target elements. Concurrent perceptual judgments made about the same stimuli (estimating the mean size of either target or distractor discs) showed better performance for the target discs than distractors, confirming that perceptual attention was allocated to the set of target elements. These results: (1) support the role of attention in setting the input to the spatial pooling process that guides saccades to spatially extended targets, and (2) show that perceptual judgments of mean value, often thought to impose modest attentional demands, are not immune to the constraints of this pre-saccadic filter
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