A Comparative Study of HARR Feature Extraction and Machine Learning Algorithms for Covid-19 X-Ray Image Classification

In this study, we investigated how effectively COVID-19 image categorization using Harr feature extraction and machine learning algorithms. We were particularly interested in the effectiveness of these algorithms. A dataset of 500 X-ray scans, equally split between 250 COVID-19-positive cases and 250 healthy controls, served as the basis for our study.  K-nearest neighbors,decision tree,  Linear regression, support vector machine, regression, classification, naive Bayes,random forest,  as well as linear discriminant analysis were among the seven machine-learning approaches used to categorize the photos. With the use of Harr feature extraction, the features of the pictures were extracted. We studied the efficacy of COVID-19 X-ray images for classification utilizing the combination of machine learning as well as the Harr feature extraction methods in the present investigation due to their effectiveness. We searched a database of 500 X-rays for this investigation, dividing them equally between groups of 250 patients with COVID-19-positive cases and 250 healthy people. Following that, the images were examined using seven various machine learning approaches for recognition. These methods included naive Bayes, linear discriminant analysis, random forests, classification,k-nearest neighbors,  and regression trees. The information from the photos was gathered using the Harr feature extraction method. The effectiveness of the algorithms was evaluated with the help of a variety of metrics, such asF1 score, precision,accuracy, recall, the area under the ROC curve, and the region of interest curve. According to our research, the Support Vector Machine algorithm had the highest accuracy, at 77%, while the Naive Bayes approach had the lowest accuracy, at 58%. By using machine learning and Harr feature extraction approaches, the Random Forest method yields the best results, based on our research. The development of future COVID-19 X-ray image-based automated diagnostic systems may be influenced by these findings. Results from the suggested model were comparable to those of cutting-edge models trained using transfer learning techniques. The proposed model's main advantage is that it has ten times fewer parameters than the most advanced models.A receiver operating characteristic (ROC) curve's F1 score, and the algorithms' accuracy, precision, the area under the curve,  and recall were all used as metrics. According to our findings, the Naive Bayes method gained the least accuracy (58%) and the Support Vector Machine method produced the highest accuracy (77%) when used. Our results reveal that employing Harr feature extraction and machine learning techniques, the Random Forest strategy is the most successful way to recognize COVID-19 X-ray pictures. These findings may be pertinent to the development of automated COVID-19 diagnosis tools relying on X-ray images. The recommended model produced results that were competitive when measured against cutting-edge models trained using transfer learning techniques. The suggested model employs 10 times fewer parameters than the most advanced models, which is its key selling point.&nbsp

Probing IC/CMB Interpretation for the X-ray knots of AGN through VHE observations

Detection of hard X-ray spectrum from the kilo-parsec scale jet of active galactic nuclei cannot be accounted to the synchrotron emission mechanism from the electron distribution responsible for the radio/optical emission. Alternate explanations are the inverse Compton scattering of cosmic microwave background photons (IC/CMB) or synchrotron emission from a second electron population. When the X-ray emission is interpreted as IC/CMB process, the Compton spectrum peak at GeV energy and were predicted to be the Fermi candidate sources. The non-detection of significant gamma ray flux from these galaxies by Fermi disfavoured the IC/CMB interpretation of the high energy emission. We extend this study to predict the very high energy (VHE) gamma ray emission due to IC/CMB model which can be investigated by Cherenkov Telescope Array(CTA). The model parameters deciding the broadband spectral energy distribution are estimated using analytical approximation of the emissivity functions. The emission model is extrapolated to VHE energy and then compared with the CTAO sensitivity. Particularly, we selected the sources for which the IC/CMB model is not ruled out by initial Fermi observations.Comment: Submitted to MNRAS Main Joura

Controlled delivery of Imatinib mesylate from collagen coated poly(lactic acid) microspheres: In vitro release studies

The development of injectable microspheres for controlled drug delivery to the desired site is a major challenge. We demonstrated the possibility of entrapping an anticancer drug, Imatinib mesylate, in collagen coated biodegradable poly (lactic acid) microspheres with a mean diameter of 10-20 µm. The collagen coating on polymeric matrix surfaces through various surface modification techniques was the current scenario to improve bio-integration of the polymers with the in-vivo system. Here protein adsorption principle is used and various characterization techniques like FTIR, DSC and SEM analysis are used to confirm collagen coating. The reduction in burst release of the Imatinib from the PLA microspheres further confirms its presence and role in controlled release.  This collagen coated PLA microspheres may have potential for the targeted delivery of Imatinib mesylate to treat gastrointestinal stromal tumors, chronic myeloid leukemia cancer

Punctured Turbo Codes for Bandwidth-efficient Transmission

Turbo codes are the error-coding schemes applied nowadays in wireless networks. In navalapplications, the information is mostly sent through wireless networks and the data is moreprone to noise. Since very important data has to be communicated, it is necessary to get backthe original data in the receiver. In military applications also, the soldiers wear electronic jacketswhich are connected by wireless networks. In such applications, the data loss is not affordableand there is also a need to utilise the bandwidth efficiently through puncturing by means ofwhich certain bits are deleted before transmission from the output of encoder. By means of thispunctured turbo codes, bandwidth-efficient coding is achieved. Hence, it is necessary to designturbo codes with an efficient puncturing pattern so that the performance of the punctured codeis also improved in spite of deletion of few bits before transmission. This paper deals in choosingthe puncturing patterns that lead to systematic rate-compatible punctured turbo codes (RCPTCs)which also give a reduction in bit-error rate. The design criterion for choosing the best puncturingpatterns is based on the minimum weight of code words and their multiplicities. The best puncturingpattern chosen is tested for its performance by simulating turbo codes for an additive whiteGaussian noise (AWGN ) channel. Compared with the existing puncturing pattern, the patternproposed is able to achieve a gain of 0.5 dB at a bit-error rate of 10-3

A New Generalization of Power Garima Distribution with Applications in Blood Cancer and Relief Times

The present study deals with the weighted version of power Garima distribution and its various statistical properties have been obtained. For estimating its parameters, the technique of maximum likelihood estimation have been used and also observed its Fisher’s information matrix. Finally, the two real lifetime data sets from medical sciences have been used to discuss the superiority of new distribution

Cognitive Power of Women

For ages together, men and women were considered to be different in biological and social terms due to which men enjoyed superiority over women. In the current scenario, this idea is fading due to the sense of equality. However, it is a controversial issue regarding whether differing or equal that made people research about the innate aspects of both the genders. It is ironical that though men and women are the same species they differ in their perceptions and deeds. This paper restricts to the discussion of mere cognition processes of both the genders. It compares and contrasts the thought processes of woman to that of men and the gender brain myths. In this paper, woman’s brain power is identified and the impact of physiological and sociological factors on woman is highlighte

Quantification and expert evaluation of evidence for chemopredictive biomarkers to personalize cancer treatment.

Predictive biomarkers have the potential to facilitate cancer precision medicine by guiding the optimal choice of therapies for patients. However, clinicians are faced with an enormous volume of often-contradictory evidence regarding the therapeutic context of chemopredictive biomarkers.We extensively surveyed public literature to systematically review the predictive effect of 7 biomarkers claimed to predict response to various chemotherapy drugs: ERCC1-platinums, RRM1-gemcitabine, TYMS-5-fluorouracil/Capecitabine, TUBB3-taxanes, MGMT-temozolomide, TOP1-irinotecan/topotecan, and TOP2A-anthracyclines. We focused on studies that investigated changes in gene or protein expression as predictors of drug sensitivity or resistance. We considered an evidence framework that ranked studies from high level I evidence for randomized controlled trials to low level IV evidence for pre-clinical studies and patient case studies.We found that further in-depth analysis will be required to explore methodological issues, inconsistencies between studies, and tumor specific effects present even within high evidence level studies. Some of these nuances will lend themselves to automation, others will require manual curation. However, the comprehensive cataloging and analysis of dispersed public data utilizing an evidence framework provides a high level perspective on clinical actionability of these protein biomarkers. This framework and perspective will ultimately facilitate clinical trial design as well as therapeutic decision-making for individual patients

Photorefractive polymeric solitons

We show the existence of photorefractive polymeric solitons in a bulk photorefractive polymer. We also show the existence of incoherently coupled two dimensional soliton pairs under steady state condition. The soliton pairs can exist under the condition that the two beams are mutually incoherent and have the same wavelength and polarization. The system was studied using the variational method and the result so obtained was analyzed using the finite-difference Beam Propagation method. Stable propagation of the soliton beam through the medium was observed

Sustainable solid waste management through ecological footprint analysis – a solution to Kochi city, India

Kochi, the commercial capital of Kerala, South India and second most important city next to Mumbai on the Western coast is a land having a wide variety of residential environments. Due to rapid population growth, changing lifestyles, food habits and living standards, institutional weaknesses, improper choice of technology and public apathy, the present pattern of the city can be classified as that of haphazard growth with typical problems characteristics of unplanned urban development especially in the case of solid waste management. To have a better living condition for us and our future generations, we must know where we are now and how far we need to go. We, each individual must calculate how much nature we use and compare it to how much nature we have available. This can be achieved by applying the concept of ecological footprint. Ecological footprint analysis (EFA) is a quantitative tool that represents the ecological load imposed on earth by humans in spatial terms. The aim of applying EFA to Kochi city is to quantify the consumption and waste generation of a population and to compare it with the existing biocapacity. By quantifying the ecological footprint we can formulate strategies to reduce the footprint and there by having a sustainable living. The paper discusses the various footprint components of Kochi city and in detail analyses the waste footprint of the residential areas using waste footprint analyzer. An attempt is also made to suggest some waste foot print reduction strategies thereby making the city sustainable as far as solid waste management is concerned

Synthesis and Characterization of Co (Ii) And Ni (Ii) Complexes of 2, 5- Substituted 1, 3, 4-Oxadiazole Derivatives

Abstract Eight new Co(II