Browse Items (14421 total)
Sort by:
-
Differential query execution on privacy preserving data distributed over hybrid cloud
Hybrid cloud is proposed as a solution for ensuring security and privacy for data outsourced to cloud. Hybrid cloud uses a mix of both private and public cloud with distribution of sensitive information to private cloud and insensitive information to public cloud. Though data distributed over multi storage provides enhanced security and privacy, query performance is distorted. This work proposes a privacy preserving data distribution with goal of ensuring reduced query latency for data distributed over hybrid clouds without any compromise to the security and privacy. The proposed solution also provides different queries results for the query depending on the access control provided to the users. 2022 Scrivener Publishing LLC. -
Network Security Tools and Applications in Research Perspective
The modern world technology is civilized, globalized and modernized. The technological development of social networks and e-commerce applications produce larger data. This data communication is major task, because device to device communication need network terminal. This data transmission is not safe because of different types of tools and software available to destroy the existing network. In the field of network security during data transfer from one particular node to other node some security vulnerability is happened this is the one of the critical issue in this sector. The reason for this network security is different types of data attacks are happen in day to day life. It is easy to establish a new network but protecting the entire network is a big issue. This network security is generally two parameter first one is communication and second one is data automation. The network security field is directly or indirectly linked with the concept of data encryption. The development in this network security has taken us to a level that from signature again we came back to thumb print. For example maintain the data secure we use the lock system which is a finger print type. This technology helps us to protect the physical data theft, but logical data theft is still problem for data transmission. This article will brief about the network security it also presents the various network security types. Those types are wired and wireless network security. Apart from the network security the following topics is also discussed in this article. Those are network security protocols and simulation tools in network security. The research problems in network security are privacy and vulnerability of data. 2019 IEEE. -
Chitosan stabilized platinum nanoparticles: Synthesis, characterization and cytotoxic impacts on human breast cancer cells
Platinum nanoparticles are widely studied as a nanomedicine against many of the solid tumours. Due to their promising physicochemical properties, chitosan-stabilized platinum nanoparticles may exhibit exceptional cytotoxic effects on cancer cells. This article describes the synthesis and characterization of chitosan-stabilized platinum nanoparticles (Ch-Pt NPs) through a wet chemical method and in vitro studies of their anticancer effect on human breast cancer cells (MCF-7 cell line). Different analytical methods confirmed the formation of chitosan-stabilized platinum nanoparticles. The structural and surface morphological analyses were done using XRD, FTIR, TEM, FESEM, etc. Elemental analysis was done using XPS and EDX. The hydrodynamic diameter and zeta potential were determined using DLS and zeta analyzer. These platinum nanoparticles have a spherical shape and FCC structure with an average particle size of 3.4 nm and an average hydrodynamic diameter of 248 nm. The characteristic FTIR peaks of chitosan in the sample confirmed the capping of chitosan on the surface of the Pt NPs. The surface charge estimation using a zeta potential analyzer showed ?23.8 mV, elucidating the stability and dispersity of the as-synthesized Pt NPs. The in vitro cytotoxicity study using MTT assay revealed a non-toxic behaviour on normal L929 cell lines and a severe anti-proliferative activity on a human breast cancer (MCF-7) cell line with an IC50 value of 35.60 ?g/ml after 24 h of incubation. This result indicates a better anticancer therapeutic application against human breast cancer cells for the as-synthesized chitosan-stabilized platinum nanoparticles. 2024 Elsevier B.V. -
An empirical analysis of ICT tools with gamification for the Indian school education system
Information and communication technologies (ICTs) are used as a part of different fields, for example, training, business, and healthcare. The main objective of this paper is to introduce ICT as a better method to teach and test student's performance so it can become a part of the school curriculum and enhance learner's experience. To accomplish this objective, multiple kinds of literature were studied to get insights into the factors associated with ICT and gamification. Based on the findings, a survey was conducted on teachers to know the favourability of ICT in modern schools. Based on the response, two application prototypes are developed for students to get their performance and results that support the study. Most importantly, similar concepts were taught to students using both, traditional and ICT based approaches. A test was conducted via both methods. It was discovered that the performance of the students increased by 13% when the modern approach was followed to conduct the test. Copyright 2021 Inderscience Enterprises Ltd. -
Bombay High Court (re)assures that copyright registration is not required to remedy infringement
Sanjay Soya Private Limited v. Narayani Trading Company, Interim Application (L) No. 5011 of 2020 and Commercial IP Suit No. 2 of 2021, High Court of Bombay, Maharashtra, judgment of 9 March 2021, by Mr. Justice G.S. Patel The Bombay High Court, in the case of Sanjay Soya Private Limited v. Narayani Trading Company, held that copyright registration is not a prerequisite to claiming relief in copyright infringement cases. The judgment clarifies the dubiety created previously by a contrary judicial opinion and aligns the Indian position with international copyright principles. 2021 The Author(s) 2021. Published by Oxford University Press. All rights reserved. -
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. -
Ethics of Creativity in the Age of AI
The accelerated development of generative artificial intelligence has challenged the principles of creative practice and has laid down them as the established assumptions about the originality, intentions, and cultural significance of humans. This chapter critically discusses the intersection of AI- generated creativity with psychological theories of the agency of humans, social and cultural structures of meaning- making and emerging ethical issues of authorship, ownership and cultural representation. With reference to past and present studies, empirical results and technological advances, the chapter aims to point out the two- sided character of AI as the accelerant of creative possibility and the de- disturbing factor in artistic, economic and cultural ecosystems. It assesses the most notable risks, such as bias, cultural homogenization, deepfakes, labour displacement, and environmental costs, besidesacknowledging the opportunities to democratize, make it more accessible and allow human- machine collaboration. 2026 by IGI Global Scientific Publishing. All rights reserved. -
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 -
Early Detection of Cyber Threats in EVCS Using Machine Learning: A Focus on Reconnaissance Attacks
There is a significant rise in electric vehicle adoption and robust and secure electric vehicle charging station infrastructure to meet this increasing demand. However, advanced technology is vulnerable to several cyber threats. Primarily starting with reconnaissance attacks, attackers gather information about the system to plan greater attacks. This can further lead to several kinds of attacks such as Denial of Service and Host Attacks where the attacker can bypass firewalls, create false traffic and disrupt service for the users. Thus, it is important to detect and prevent these attacks at an early stage. This paper presents a robust machine learning model in order to detect reconnaissance attacks. To the best of our knowledge, there have not been enough studies that focus on specific attack categories for early detection of cyber threats. The ensemble model used in the study demonstrates an impressive accuracy of 97.71% with a good balance between precision and recall. Moreover, variables related to power consumption which are harder to manipulate are used as features. This approach contributes towards more secure EVCS, fosters user trust and promotes adoption of electric vehicles at large. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Assessing the Impact of E-learning through Usage and Preference of E-resources
Aims: Any electronic device that delivers a collection of data, whether it be text referring to full text databases, electronic journals, photographs, other multimedia goods, or quantitative, visualizations, or time-based, is referred to as an electronic resource. These could be transmitted over the internet, tape, CD-ROM, tablets, smartphones, smart watches or another medium, these are now the basis of e-learning. Online searching has made it possible to get patent information more quickly, affordably, and conveniently than the traditional manual or CD-ROM based searching method. The ability to create and distribute documents in electronic form is now made possible by a number of established procedures and standards. So, in order to address the current problems, librarians are utilizing new media, particularly electronic resources, in their collection expansion makes the documentation of users better. As we can see, utilizing online resources is important in the modern world for a multitude of purposes. Because of this, it's important to understand the preferences, motives and usage of various e- resources used by students who use online learning. The aim of the present research paper was to examine the impact of e-resources using its usage and reading preferences. In this study, reasons such as time saving, more information, and busy schedule at college are considered. Methodology: Primary data was gathered from 250 students from Mumbai and Navi Mumbai who are using e-resources through the pre-structured questionnaire. The responses collected were recorded using the SPSS software for data analysis. In order to examine the link between causes, preferences, and the use of e-resources, a theoretical construct was developed grounded on a few assumptions. Statistical techniques like the chi-square test were used and data analysis was done using SPSS version 20 to examine the proposed construct. When doing the data analysis, the demographic profile, objectives, and hypothesis were all taken into consideration. Results: The average for each component that is time saving, more informative, and busy schedule at college was computed and was determined as 0.004, 0.004, and 0.000, correspondingly, for time saving, more informative content, and busy college schedule. As all of these values for all of the preferences under consideration are less than 0.05, it is clear that there is a connection between the usage of electronic resources and their underlying reasons and preferences. Conclusion: Hence, there is a substantial correlation between the reasons for using electronic resources and the different reading preferences, as well as between the two. Only three reasons namely time saving, more informative, and busy schedule at college are considered during this study. Data collection is done from Mumbai and Navi Mumbai region only. 2025 Bentham Science Publishers. -
Analysing the Relationship Between FDI and the Dimensions of Sustainable Development in India
After dominating international development policy for more than 20years, sustainability and sustainable development have attracted more and more attention in policy and scholarly discourse. Significantly, recent events have emphasised the significance of pursuing sustainability and sustainable development even more. These include the adoption of a circular economy strategy, the move to renewable energy sources, the fight against climate change, and attempts to reduce emissions from fossil fuels. Foreign direct investment is one method of achieving sustainable development. Therefore, a sustainable relationship between FDI and sustainable development in India has been established in the subsequent pages of this paper and this causal relationship has been analysed. This causal relationship has been established via the vector error correction model. Through the findings, this paper doubles down on the idea that FDI is a great source for the introduction of sustainable development. However, it is also found that policymakers should focus on the implementation of those policies that utilise the benefits of FDI while simultaneously working against the negative environmental impacts and promoting the need for human development. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. -
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. -
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 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. -
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 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. -
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. -
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. -
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. -
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.