Image compression using discrete cosine transform and wavelet transform and performance comparison

Image compression deals with reducing the size of image which is performed with the help of transforms. In this project we have taken the Input image and applied wavelet techniques for image compression and have compared the result with the popular DCT image compression. WT provided better result as far as properties like RMS error, image intensity and execution time is concerned. Now a days wavelet theory based technique has emerged in different signal and image processing application including speech, image processing and computer vision. In particular Wavelet Transform is of interest for the analysis of non-stationary signals. In the WT at high frequencies short windows and at low frequencies long windows are used. Since discrete wavelet is essentially sub band–coding system, sub band coders have been quit successful in speech and image compression. It is clear that DWT has potential application in compression problem

Spread Complexity in free fermion models

We study spread complexity and the statistics of work done for quenches in the three-spin interacting Ising model, the XY spin chain, and the Su-Schrieffer-Heeger model. We study these models without quench and for different schemes of quenches, such as sudden quench and multiple sudden quenches. We employ the Floquet operator technique to investigate all three models in the presence of time-dependent periodic driving of parameters. In contrast to the sudden quenched cases, the periodically varying parameter case clearly shows non-analytical behaviour near the critical point. We also elucidate the relation between work done and the Lanczos coefficient and how the statistics of work done behave near critical points.Comment: 23 pages, 18 figure

Complexity and quenches in models with three and four spin interactions

We study information theoretic quantities in models with three and four spin interactions. These models show distinctive characteristics compared to their nearest neighbour counterparts. Here, we quantify these in terms of the Nielsen complexity in static and quench scenarios, the Fubini-Study complexity, and the entanglement entropy. The models that we study have a rich phase structure, and we show how the difference in the nature of phase transitions in these, compared to ones with nearest neighbour interactions, result in different behaviour of information theoretic quantities, from ones known in the literature. For example, the derivative of the Nielsen complexity does not diverge but shows a discontinuity near continuous phase transitions, and the Fubini-Study complexity may be regular and continuous across such transitions. The entanglement entropy shows a novel discontinuity both at first and second order quantum phase transitions. We also study multiple quench scenarios in these models and contrast these with quenches in the transverse XY model.Comment: 12 Pages, 11 Figure

Auditing Gender Analyzers on Text Data

AI models have become extremely popular and accessible to the general public. However, they are continuously under the scanner due to their demonstrable biases toward various sections of the society like people of color and non-binary people. In this study, we audit three existing gender analyzers -- uClassify, Readable and HackerFactor, for biases against non-binary individuals. These tools are designed to predict only the cisgender binary labels, which leads to discrimination against non-binary members of the society. We curate two datasets -- Reddit comments (660k) and, Tumblr posts (2.05M) and our experimental evaluation shows that the tools are highly inaccurate with the overall accuracy being ~50% on all platforms. Predictions for non-binary comments on all platforms are mostly female, thus propagating the societal bias that non-binary individuals are effeminate. To address this, we fine-tune a BERT multi-label classifier on the two datasets in multiple combinations, observe an overall performance of ~77% on the most realistically deployable setting and a surprisingly higher performance of 90% for the non-binary class. We also audit ChatGPT using zero-shot prompts on a small dataset (due to high pricing) and observe an average accuracy of 58% for Reddit and Tumblr combined (with overall better results for Reddit). Thus, we show that existing systems, including highly advanced ones like ChatGPT are biased, and need better audits and moderation and, that such societal biases can be addressed and alleviated through simple off-the-shelf models like BERT trained on more gender inclusive datasets.Comment: This work has been accepted at IEEE/ACM ASONAM 2023. Please cite the version appearing in the ASONAM proceeding

FOTOC complexity in an extended Lipkin-Meshkov-Glick model

We study fidelity out-of-time-order correlators (FOTOCs) in an extended Lipkin-Meshkov-Glick model and demonstrate that these exhibit distinctive behaviour at quantum phase transitions in both the ground and the excited states. We show that the dynamics of the FOTOC have different behaviour in the symmetric and broken-symmetry phases, and as one approaches phase transition. If we rescale the FOTOC operator with time, then for small times, we establish that it is identical to the Loschmidt echo. We also compute the Nielsen complexity of the FOTOC operator in both phases, and apply this operator on the ground and excited states to obtain the quasi-scrambled state of the model. The FOTOC operator introduces a small perturbation on the original ground and excited states. For this perturbed state, we compute the quantum information metric to first order in perturbation, in the thermodynamic limit. We find that the associated Ricci scalar diverges at the phase transition on the broken-symmetry phase side, in contrast to the zeroth order result. Finally, we comment upon the Fubini-Study complexity in this model.Comment: Minor corrections. 10 Pages, 5 Figure

RFID Based Automatic Shopping Cart

Large grocery stores are nowadays used by millions of people for the acquisition of an enlarging number of products. Product acquisition represents a complex process that comprises time spent in corridors, product location and checkout queues. On the other hand, it is becoming increasingly difficult for retailers to keep their clients loyal and to predict their needs due to the influence of competition and the lack of tools that discriminate consumption patterns. In this article it is presented the proposal of an architecture and solution of an innovative system for the acquisition of products in grocery stores (Intelligent Cart). The Intelligent Cart explores emerging mobile technologies and automatic identification technologies (such as RFID) as a way to improve the quality of services provided by retailers and to augment the consumer value thus allowing to save time and money. Keywords: Automatic Product Identification; Electronic Services; Grocery Stores, RFID, Intelligent car

CORRELATION AND HEAT SUSCEPTIBILITY INDEX ANALYSIS FOR TERMINAL HEAT TOLERANCE IN BREAD WHEAT

Six generations namely, P1, P2, F2, F3, BC1s and BC2s (2006-07) and P1, P2, F3, F4, BC1ss and BC2ss (2007-08) developed from four parental genotypes viz. DBW 14 (heat tolerant), NP 846 (heat and drought tolerant), WH 147 and Raj 4014 (heat susceptible for late sown). All the six generations from four crosses were evaluated during Rabi 2006-07 and Rabi 2007-08 in a compact family block design with three replications on two sowing dates. Heat susceptibility index values revealed reduction in grain yield in both the years for all the generations of the four crosses. Significant estimates of correlation of grain yield with days to heading, days to anthesis and days to maturity were recorded in late sown condition during first year. While under timely sown condition spike length has high estimate correlation with grain yield in first year itself. Significant estimated were recorded for tillers per plant in both the environments in second year. Lowest yield loss was reported in backcross populations of Cross I in both years and among segregating populations of Cross IV observed to be least affected and therefore suggested to be forwarded to further generations and further selection of heat tolerant genotypes

Sperm centriole assessment identifies male factor infertility in couples with unexplained infertility - a pilot study

Unexplained infertility affects about one-third of infertile couples and is defined as the failure to identify the cause of infertility despite extensive evaluation of the male and female partners. Therefore, there is a need for a multiparametric approach to study sperm function. Recently, we developed a Fluorescence-Based Ratiometric Analysis of Sperm Centrioles (FRAC) assay to determine sperm centriole quality. Here, we perform a pilot study of sperm from 10 fertile men and 10 men in couples with unexplained infertility, using three centriolar biomarkers measured at three sperm locations from two sperm fractions, representing high and low sperm quality. We found that FRAC can identify men from couples with unexplained infertility as the likely source of infertility. Higher quality fractions from 10 fertile individuals were the reference population. All 180 studied FRAC values in the 10 fertile individuals fell within the reference population range. Eleven of the 180 studied FRAC values in the 10 infertile patients were outliers beyond the 95% confidence intervals (P = 0.0008). Three men with unexplained infertility had outlier FRAC values in their higher quality sperm fraction, while four had outlier FRAC values in their lower quality sperm fraction (3/10 and 4/10, P = 0.060 and P = 0.025, respectively), suggesting that these four individuals are infertile due, in part, to centriolar defects. We propose that a larger scale study should be performed to determine the ability of FRAC to identify male factor infertility and its potential contribution to sperm multiparametric analysis