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Sustainability In The Built Environment: Are We Doing Enough?
Sustainability is one of the key requirements for any business; however, there exist gaps in recognizing and aligning these sustainable practices with everyday operational activities. With this in mind, this study aims to explore the current awareness level in business leaders and stakeholders about corporate responsibility towards sustainability and reflects on the obstacles encountered by them in diverse built environments, laying the groundwork for addressing these hurdles and contributing towards the overall sustainable development. The study uses a thematic approach to analyzing data with the help of NVIVO12 software. The major findings include Energy Auditing process - not carried out frequently; both sustainability and profitability go hand in hand; absence of technology such as AI and Sensor technology has contributed to the built environment's energy performance gap; there is a knowledge gap that exists among business leaders in understanding the concept of sustainable development. The Electrochemical Society -
Toward sustainability 4.0: A comprehensive analysis of sustainability in corporate environment
Sustainability is one of the key requirements for any business, and continuously changing business requirements and the environment are the main drivers of sustainable business practices. However, there exist gaps in recognizing and aligning these sustainable practices with everyday operational activities. This study's aim is to explore the current awareness level in business leaders and stakeholders about corporate responsibility toward sustainability and reflects on the obstacles encountered by them in diverse built environments, laying the groundwork for addressing these hurdles and contributing toward the overall sustainable development. The study has two major findings: the analysis revealed that there is a paradigm shift in the understanding of sustainability; in contrast to earlier publications, newer publications focus on technological advancements such as the use of "Green Building Information Management" and "Green Internet of Things" illustrating the real-time implications of sustainable practices. Further analysis found a knowledge gap that exists among business leaders in understanding the concept of sustainable development. This, in essence, poses a burden for corporate leaders to keep up with ongoing technological developments. The study concludes that to achieve sustainable growth, leadership in the corporate environment needs a 360-degree view of sustainability, allowing them to assign equal value to the environment, social, and economic pillars of sustainability to address the current issues leveraging from the state-of-the-art technological innovations. The Author(s), under exclusive license to Springer Nature Switzerland AG 2021. All rights reserved. -
Regarding Deeper Properties of the Fractional Order Kundu-Eckhaus Equation and Massive Thirring Model
In this paper, the fractional natural decomposition method (FNDM) is employed to find the solution for the Kundu-Eckhaus equation and coupled fractional differential equations describing the massive Thirring model. The massive Thirring model consists of a system of two nonlinear complex differential equations, and it plays a dynamic role in quantum field theory. The fractional derivative is considered in the Caputo sense, and the projected algorithm is a graceful mixture of Adomian decomposition scheme with natural transform technique. In order to illustrate and validate the efficiency of the future technique, we analyzed projected phenomena in terms of fractional order. Moreover, the behaviour of the obtained solution has been captured for diverse fractional order. The obtained results elucidate that the projected technique is easy to implement and very effective to analyze the behaviour of complex nonlinear differential equations of fractional order arising in the connected areas of science and engineering. 2022 Tech Science Press. All rights reserved. -
Heat and mass transfer of AgH2O nano-thin film flowing over a porous medium: A modified Buongiorno's model
Due to their numerous applications, such as fibre and wire coating, polymer preparation, etc., thin films have recently come into focus in the analysis of heat and mass transport. As a result, the current article's main objective is to investigate how heat and mass are transferred when an AgH2O (sliverwater) thin film flows past a stretching sheet that is subject to thermal and velocity slips. The research takes into account other variables including porosity, thermal radiation, thermophoresis, and Brownian motion, among others, to ensure that the outcomes are consistent with real-world conditions. Along with these parameters, the impact of the nanoparticle volume fraction is also analysed by incorporating the modified model of the existing Buongiorno model. The resulting mathematical model is transformed into ordinary differential equations with the help of appropriate similarity transformation. The system of equations thus obtained is solved by employing the RKF-45 technique and the outcomes are expressed in terms of graphs and tables. The major outcomes indicate that the increase in the mixed convection parameter causes enhancement in the temperature profile while a reduction in the velocity profile. The thermophoresis is found to increase both the temperature and concentration profiles of the thin film. Whereas, the greater values of the volume fraction of the nanoparticles enhance the temperature and diminishes the velocity. 2023 The Physical Society of the Republic of China (Taiwan) -
Microwave assisted structural engineering on efficient eco-friendly natural dye alizarin for dye sensitized solar cells application
The novel eco-friendly natural dyes, (9E, 10E), ? 9, 10-bis(2-(4-nitrobenzylidene) hydrazono) ? 9,10 dihydroanthracene-1,2-diol (NHA) have been synthesised using the one-pot microwave-assisted solvent evaporation method, and physicochemical characterizations were carried out using 1H NMR, 13C NMR, GC-MS, and FT-IR data. The photophysical properties of NHA dye were determined using experimental and theoretical techniques. The Stoke's shift shows a large bathochromic shift in polar solvents, which is due to the ??? * transition. The ground-state optimization of NHA dye was carried out using density functional theory (DFT) with the B3LYP/631 G level basis set. The HOMO-LUMO and energy band gap values computed from density functional theory and absorption threshold wavelengths are good agreement with each other. Further, the effect of TiO2 nanoparticles on NHA dye has been studied using spectroscopic and electrochemical techniques. It was observed that, NHA dye showed fluorescence quenching in the presence of TiO2 NPs, which is due to the photo induced electron transfer process. The apparent association constant of the interaction between NHA dye and TiO2 nanoparticles is also calculated using the Benesi-Hildebrand model. The Rehm-Weller relation infers that thermodynamically favourable electron transfer takes place between dyes and TiO2 NPs. Further, the solar cell was constructed using NHA dye as a sensitizer, and the photovoltaic conversion efficiency was found to be 1.16%. 2023 Elsevier GmbH -
PEGylated Platinum Nanoparticles: A Comprehensive Study of Their Analgesic and Anti-Inflammatory Effects
Pain and inflammation are common symptoms of a majority of the diseases. Chronic pain and inflammation, as well as related dreadful disorders, remain difficult to control due to a lack of safe and effective medications. In this work, biocompatible platinum nanoparticles with significant analgesic and anti-inflammatory action were synthesized through a wet chemical method using polyethylene glycol-400 as a capping agent and sodium borohydride as a reducing agent. The average particle size of these Pt nanospheres was determined to be 3.26 nm using TEM analysis, and X-ray diffraction confirmed their face-centered cubic crystalline structure. Fourier transform infrared and UV-visible spectroscopy confirm that Pt-NPs are coated with the PEG-400 molecule. The significantly negative zeta potential value (?26.8 mV) indicates the stability of the produced nanoparticles. In vitro cytotoxicity studies on normal cell lines show nontoxic behavior with over 96% cell viability at 100 ?g/mL of the test sample. In vitro assays of inhibition of protein denaturation and DPPH free radical scavenging elucidated the anti-inflammatory and antioxidant properties of PEGylated Pt NPs with promising EC50 values 57.99 and 9.324 ?g/mL, respectively. In vivo animal trials confirmed that PEG-capped Pt-NPs are more effective than conventional medicines. The in vivo hot plate assay for the analgesic study shows a maximum response time of 14.5 1.22 s (92.54% analgesia) at a dosage of 50 mg/kg and 13.8 0.71 s (86.05% analgesia) at a dosage of 25 mg/kg after 180 and 240 min of administration, respectively. In the rat paw edema model for anti-inflammatory activity, the PEG-capped Pt NPs exhibit significant inhibitory action, with the maximum percentage of edema inhibition at a dosage of 50 mg/kg identical to that of the aspirin-based standard medication administered at a higher dosage of 100 mg/kg, resulting in 42% inhibition, suggesting a versatile solution for inflammation and persistent pain. 2025 American Chemical Society. -
Cross-Border Acquisitions and Shareholders Wealth: The Case of the Indian Pharmaceutical Sector
Cross-border acquisitions by Indian companies have increased tremendously, especially during the last two decades, and the pharmaceutical industry is one of the top acquiring industries. This study verifies the relationship between cross-border acquisitions and shareholders wealth in the Indian pharmaceutical sector. For this purpose, the data related to acquisitions were acquired from 2005 to 2019 and the event study methodology was applied along with two parametric tests. The findings of the current research prescribe that cross-border acquisitions have a positive and significant impact on shareholders wealth. Furthermore, the outcomes also indicate higher positive abnormal returns in the short run when the targets are based in the US and the UK as compared to the positive but insignificant abnormal returns when the targets are based in locations other than the US and the UK. 2022 by the authors. -
Performance Analysis of Several CNN Based Models for Brain MRI in Tumor Classification
Classification is one of the primary tasks in data mining and machine learning which is used for categorizing data into classes. In this paper, brain MRI images are used for classification of tumors into three categories namely, Meningioma, Glioma, and Pituitary Tumor. These methodologies used are spatial based, depth based, feature map based and depth based CNN showcasing the power of deep learning in automating the tumor detection process. To evaluate the performance of several deep learning models, data is divided into training and testing data where a generalization method is used for comparison. The experimental results demonstrate promising accuracy, showing that a few techniques are valuable tools for radiologists and physicians, along with further analysis. The best accuracy obtained is 96% using MobileNet and ResNet50 in comparison to other CNN methodologies used in this paper. 2024 IEEE. -
Cuda implementation of non-local means algorithm for GPU processors
Non-Local Means algorithm (NLM) is a prominent image denoising algorithm. One of the major limitations of NLM algorithm and its variants is the time requirement. In this era of high performance computing, an efficient alternative to reduce the time complexity of any algorithm is its parallelization. In this paper, a parallelized version of basic NLM algorithm using CUDA architecture is proposed. The algorithm is developed on NVIDIA GeForce 940M GPU which follows Maxwell architecture with 3 SMs and 384 CUDA cores. Experiments are carried out using selected set of natural and medical images of various sizes. Our proposed parallelized version of NLM algorithm reduces the time requirement approximately by 50% in comparison to its basic version and also achieves comparable denoising performance in terms of PSNR, SSIM and FSIM evaluation metrics. The proposal is a model which can be customized for newer GPU architectures. 2020, Engg Journals Publications. All rights reserved. -
A Fusion Based Approach for Blood Vessel Segmentation from Fundus Images by Separating Brighter Optic Disc
Abstract: In ophthalmology, blood vessel segmentation from fundus images plays a significant role in automated retinal disease screening systems. Several research papers on blood vessel segmentation suggest enhancing fundus images before segmentation significantly to improve performance. The brightness of the optic disc region in a fundus image negatively influences the enhancement of relatively darker vessel pixels. Segregation of brighter optic disc from fundus images before its enhancement is the fundamental idea behind developing the proposed framework. Initially, the optic disc is extracted from the input fundus image to form two images, one containing optical disc and the other, fundus image without optical disk. In the second stage, both the images are enhanced independently, followed by blood vessel segmentation. Finally, the segmented blood vessels from the images are fused to obtain a single image. Experiments conducted with fundus images from DRIVE, STARE, and CHASE_DB1 databases show improvement in the identification of blood vessel pixels. 2021, Pleiades Publishing, Ltd. -
A Novel Fuzzy-Based Thresholding Approach for Blood Vessel Segmentation from Fundus Image
Retinal vessel segmentation is a vital part of pathological analysis in Fundus imaging. The automatic detection of blood vessels resolves several issues in the manual segmentation process. Most unsupervised segmentation methods depend on conventional thresholding techniques for final vessel extraction. It may lead to the loss of some vessel pixels, leading to inaccurate analysis of retinal diseases. In this work, we incorporate fuzzy concepts into two threshold-based vessel detection methods, namely mean-c thresholding and Iso-Data thresholding, which results in a mask consisting of membership values rather than binary values. The two fuzzy-based thresholding algorithms are applied independently on each image, and the resultant membership image (mask) is fused to get a single membership mask. The fusion is performed using fuzzy union operation. Experiments are carried out with Fundus images from DRIVE, STARE and CHASE_DB1 databases.ses. The proposed fusion framework gives a 3%, 6%, and 5% increase in sensitivity compared to traditional thresholding methods when applied to the DRIVE, STARE, and CHASE_DB1 databases, respectively. The accuracy obtained for the datasets is 96.02%, 94.57%, and 94.34%, respectively. 2023 by the authors. -
An Efficient Preprocessing Step for Retinal Vessel Segmentation via Optic Nerve Head Exclusion
Retinal vessel segmentation plays a significant role for accurate diagnostics of ophthalmic diseases. In this paper, a novel preprocessing step for retinal vessel segmentation via optic nerve head exclusion is proposed. The idea relies in the fact that the exclusion of brighter optic nerve head prior to contrast enhancement process can better enhance the blood vessels for accurate segmentation. A histogram based intensity thresholding scheme is introduced in order to extract the optic nerve head which is then replaced by its surrounding background pixels. The efficacy of the proposed preprocessing step is established by segmenting the retinal vessels from the optic nerve head excluded image enhanced using CLAHE algorithm. Experimental works are carried out with fundus images from DRIVE database. It shows that 1%3% of improvement in terms of TPR measure is achieved. 2019, Springer Nature Singapore Pte Ltd. -
A Dual Step Strategy for Retinal Thin Vessel Enhancement/Extraction
Blood vessel extraction from retinal images is a challenging and fundamental step in pathological analysis. Most of the vessel extraction algorithms face difficulty in the extraction of thin vessels. In this paper, a dual step strategy for retinal thin vessel enhancement/extraction is proposed. Since thin vessel pixels have intensities closer to the background non-vessel pixels, the first level enhancement algorithms usually suffers in its accurate extraction. This led to explore a novel idea of eliminating the effects of thick vessel pixels in a reference image, via replacing it with neighboring non-vessel pixels. By applying second level enhancement on the vessel subtracted image, thin vessels are projected and improvement in extraction is attained subjectively as well as objectively. 2019 IEEE. -
Diabetic retinopathy detection using convolutional neural networka study
Detection and classification of Diabetic Retinopathy (DR) is a challenging task. Automation of the detection is an active research area in image processing and machine learning. Conventional preprocessing and feature extraction methods followed by classification of a suitable classifier algorithm are the common approaches followed by DR detection. With the advancement in deep learning and the evolution of Convolutional Neural Network (CNN), conventional preprocessing and feature extraction steps are rapidly being replaced by CNN. This paper reviews some of the recent contributions in diabetic retinopathy detection using deep architectures. Further, two architectures are implemented with minor modifications. Experiments are carried out with different sample sizes, and the detection accuracies of the two architectures are compared. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. -
A Novel Threshold based Method for Vessel Intensity Detection and Extraction from Retinal Images
Retinal vessel segmentation is an active research area in medical image processing. Several research outcomes on retinal vessel segmentation have emerged in recent years. Each method has its own pros and cons, either in the vessel detection stage or in its extraction. Based on a detailed empirical investigation, a novel retinal vessel extraction architecture is proposed, which makes use of a couple of existing algorithms. In the proposed algorithm, vessel detection is carried out using a cumulative distribution function-based thresholding scheme. The resultant vessel intensities are extracted based on the hysteresis thresholding scheme. Experiments are carried out with retinal images from DRIVE and STARE databases. The results in terms of Sensitivity, Specificity, and Accuracy are compared with five standard methods. The proposed method outperforms all methods in terms of Sensitivity and Accuracy for the DRIVE data set, whereas for STARE, the performance is comparable with the best method. 2021. All Rights Reserved. -
Shifting trends in bollywood's representation of subculture -A mise-en-scene perspective /
Indian Cinema today is an outcome of the continuous shifts and transferals, focusing on certain popular culture, narrative structures and styles, genres and most importantly visual culture. Bollywood which is the custodian of Hindi Cinema has come a long way from the depiction of as a prototype of any part of the country, identified and experienced by everyone irrespective of time and space has narrowed itself into more specific forms, focusing on the sub-cultures as perceived or understood from the innumerable films produced in the recent years. -
Employee performance prediction model /
With the dominance of knowledge power in the success of an organization, competent human resource has become crucial for realization of organizational objectives. Human Resource Management, HRM is a set of tasks to maintain and develop a proficient human resource. A performance appraisal process helps the HRM in identifying the strengths and weaknesses of an employee. This evaluation of employee is based on several different parameters according to the work domain and organizational objectives. This activity of employee evaluation has a high significance in making strategic decisions of manpower planning than just salary reviews. The objective of the prediction model constructed in the study is to assist HR personnel in decision making by predicting the performance of an employee. -
Atendo: The portable attendence recorder /
Patent Number: 202241019881, Applicant: Kevin Benny.
Attendance is the fact of being present or absent at a place or an event. One of the most basic things to understand and analyse the response of an event is by recording the attendance of the event. By tracking the sessions attended by the attendees and how long the attendees stay in the event, it is possible to derive a clear picture of how engaged the event was. Attendance monitoring is very important for examining the success or failure of an event. Tracking session attendance is an easy and accurate way to gather attendee feedback and translate this information into useful data. -
Knowing Discovery from Legal Documents Dataset using Text Mining Techniques
International Journal of Computer Applications Vol.66, No.23, pp. 32-34 ISSN No. 0975-8887 -
Assessment of microsatellite instability for screening bladder cancer in high-risk population
Aims: This study aims to determine the diagnostic efficacy of microsatellite markers for screening bladder cancer in population at high risk. Materials and Methods: A population of 200 people was screened for bladder cancer using a set of microsatellite markers. Urine samples were obtained from four different types of population groups - Group 1 (healthy population group), Group 2 (current smokers with a smoking history of more than 10 years), Group 3 (bladder cancer group), and Group 4 (bladder cancer group who were former smokers with a history of more than 10 years). Polymerase chain reaction (PCR) was performed to amplify microsatellite sequences at D9S63, D9S156, and D9S283. PCR products were separated on 1.8% agarose gel and were scanned using ultraviolet transilluminator. Results: In Group 2 (high-risk population group, mainly current smokers with a history of more than 10 years), microsatellite alterations were found in 36 out of 50 people. We observed microsatellite alterations in 38 out of 50 people in Group 3 (bladder cancer group) and in 39 out of 50 people in Group 4 (bladder cancer group, mainly former smokers with a history of more than 10 years). The sensitivity of this test in Group 2, Group 3, and Group 4 was found to be 72%, 76% and 78%, respectively. The specificity of this test in each group was found to be 90%. Conclusion: Using these set of microsatellite markers, medium sensitivity and high specificity were reported for this test. The current findings suggest that a set of microsatellite markers (D9S63, D9S156, and D9S283) can be used to detect bladder cancer in high-risk population. 2018 Medknow Publications. All Rights Reserved.