Volume 9 | Issue 3 | March-2021

 Abstract

Ongoing advances of innovation in digital imaging and digital storage gadgets make it conceivable to effectively produce, transmit, control and store substantial number of digital images and documents. The term CBIR can be characterized as to recover the image from low level features like texture, shape spatial data or color. In early period of this developing recorded the image was retrieved by text depiction called as Text Based Image Retrieval [TBIR]. The combination of these content-based features is needed for better retrieval of image according to the application. The main test of CBIR framework is to decide the specific/surmised matching image of database to the query image. Over the most recent two decades, CBIR frameworks have been enhanced a lot. In any case, there still stay a few issues which have not been addressed agreeably. In this study we will represent the CBIR and also represent the existing techniques with results by various authors.

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 Keywords

Digital, Image, Text, Database, query.

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Creative Commons Attribution 4.0 and The Open Definition

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Surface modelling and design have embraced subdivision surfaces as a compelling representation. They solve some of the major drawbacks of classic spline-based approaches, such as the inability to accommodate arbitrary topologies and the lack of flexibility. To allow multiscale editing procedures to be supported in this article.Methods of subdivision-based modelling with a focus on interactive tools for 3D model style and embellishment.We complete and unite two sets of surface developments that utilize polynomial bits of degree (3,3) to partner a smooth surface with a lattice. The two sets complete one another in that one broadens the subdivisionmodelling worldview, the other the NURBS fix approach to freestyle displaying. Both Catmull-Clark and polar development generalize the bi-cubic spline region. Together, they structure a powerful blend for a smooth item plan: while the CatmullClark region is more appropriate where not many aspects join,polar development pleasantly models areas where numerous aspectsjoin, as while covering expelled highlights. We tell the best way toeffectively join the cross-sections of these two speculations ofbi-cubic spline development.A related however unique speculation of bi-cubic splinesis to demonstrate non-tensor-item designs by a limitedset of flawlessly associated bi-cubic patches. PCCM does as such for designs where Catmull-Clark would apply. Weshow that a solitary NURBS fix can be utilized where polar development would be applied. This spline is independentlyparametrized, yet, utilizing a clever strategy, that's what we showthe surface is C1 and has limited shapes. Modelling non-tensor-product setups using a finite collection of smoothly linked bi-cubic patches is a related but distinct generalization of bi-cubic splines. PCCMdoes so in cases when Catmull-Clark would be appropriate. Wedemonstrate that a single NURBS patch may be utilized in place of a polar subdivision. This spline is unique.parametrized, but we demonstrate using a unique method thatThe surface has restricted curvatures and is C1.

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 Keywords

Catmull Clark region, subdivision-based modelling, bi-cubic spline region, NURBS.

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Creative Commons Attribution 4.0 and The Open Definition

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In this paper, we suggest using a serverclient framework model that makes use of Internet of Things (IoT) technology to manage Pap smear imaging data obtained from a high-resolution magnifying lens and to categorise those images.by learning using an Artificial Neural Network (ANN)server-side computation The Internet of Things (IoT) has the potential to enhance those magnifying tools. To communicate with one another while the ANN empowers a new generationmethod for high-precision imaging grouping. We make use ofAs a contribution to our proposed plan, 917 high-goal photographs were submitted.The technique achieves a 0.8834 root mean square error and0.6643 is the connection coefficient.Cervicography, another analytic tool, provides long-term, objective documenting of both common and atypical cervical cases. To coordinate visual colposcopy amplification and aim, the projected cervicogram is nearly same. An expert can get a cervicogram and send it to a professional for evaluation. The demonstrative precision of coloscopic, cytological, and cervicographic findings was investigated in a study of 700 women. A total of 136 cases of dysplasia or cancer were investigated by coordinated biopsy in 296 women who had a typical cytologic findings. Both colposcopy and cervicographic findings were suspected in 91.1 percent of the cases; cervicography was used only in 2.9 percent of the cases, and colposcopy was used exclusively in 5.9 percent of the cases. Nine instances (2.2 percent) of dysplasia were found in 404 routinely tested individuals who had no previous odd cytologic results.

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 Keywords

Cervicogram, Colposcopic, Cervicography, Artificial Neural Network, Cytologic.

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Creative Commons Attribution 4.0 and The Open Definition

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A Content Management System (CMS) is an application which licenses to fitting, control, adjust, erase and change content in a compelling and dynamic manner. Content Management Software (CMS) is a program that grants you to manage the substance on your site. A Content Management Software consistently has two sections: a Content Management Application (CMA) and a Content Delivery Application (CDA). The Content Management System is a sort of web application that has actually obtained reputation (CMS). Model-Driven Engineering (MDE) techniques, of course, hope to speed up the headway connection by focusing in on models and thoughts as opposed to acquiring code.CMS structures might potentially transform into the new standard for web application designing. The main aim of this study is to assess the Web Application Development And Cms Model-Driven Transformations. We have present a couple of techniques for making demonstrating dialects, similarly as specific points that displaying language organizers should ponder. Regardless, it is crazy to expect that metamodels - and models - don't change for a really long time.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Content, Management, Software, CMS, program, Application, data, etc.

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Creative Commons Attribution 4.0 and The Open Definition

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SPI exercises in programming affiliations are as frequently as conceivable acted considering all around portrayed reference models distinguishing issues is a crucial part in all product cycle improvement. A lot of variable accepts huge part in programming process. The rule reason for this work is to establish the framework for SPI by discussing the piece of programming, the changes in programming advancement systems and programming improvement process models, and the quality turn of events. The main aim of this study is to discuss the Successful Process Management in Organizations by Using SPI Approach. In addition, SPI experiences are analyzed. This designing exploration technique gives a practical method for managing SPI strategy headway research, as a result of its in-manufactured considered constant turn of events and change. Moreover, it slowly makes and evaluates SPI a strategy, intertwining means to achieve the recently referenced essential accomplishment factors. The investigation relies upon a couple of modern context oriented examinations.

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 Keywords

Management, SPI, Software, Programs, Organization etc.

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Creative Commons Attribution 4.0 and The Open Definition

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The Semantic Web is actually apt to demand knowledge and energy certain. This's pricey, and so it might well be restricted to certain domains on the internet which see a powerful edge in the use of its, though over time as the expertise gets much more commonplace it must get more inexpensive. Furthermore, the' network effect' could work as both an incentive as well as a screen. One of the primary benefits of supplying Semantic Web annotation is actually that's could be discussed and can easily get use to others, consequently when there's little details to share, then there's very little motivation to take the excess cost of sharing; however, after the ball begins to roll, there's an exponential benefit in merging the personal data of yours with others. The main aim of this study is to discuss the Semantic Web Reasoning and Answer Set Programming with Finite and Infinite Set Programming. It is concluded that the chance to exchange knowledge with outside energy sources in a completely declarative framework like ASP is particularly crucial in view of applications of the Semantic Web region.

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Semantic Web, Answer Set Programming, finite, infinite, programming, Description Logics etc.

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Agent, Misuse, Mobile, Intrusion, Detection, Wireless.

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Creative Commons Attribution 4.0 and The Open Definition

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In agriculture, imageprocessingis becoming more and more significant as it enables farmers to make quicker, more informed, and more precise decisions. Without spending many hours in the field, farmers may assess crop health, identify diseases, track soil conditions, and calculate yields using photos from satellites, drones, and ground- based cameras. Machine learning can be used to automatically evaluate these photos and identify issues like pest assaults, nutritional shortages, or water stress early on. Productivity is increased, resources are saved, and prompt action is made possible. Additionally, image processing promotes environmentally responsible farming by spraying pesticides, fertilizers, and water only when necessary. With workforce shortages, climate change, and rising food demand, this technology provides a useful means of enhancing as well as agriculturalsustainability

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Creative Commons Attribution 4.0 and The Open Definition

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Machine learning, sustainable farming, crop health monitoring, image processing, and precision agriculture.

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Creative Commons Attribution 4.0 and The Open Definition

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The rapid integration of Artificial Intelligence (AI) into the healthcare sector has revolutionised medical diagnostics, patient care, and hospital administration. However, this digital transformation has also made the sector a prime target for cybercriminals aiming to exploit sensitive patient data. This paper investigates the dual role of AI, as both a tool for enhancing healthcare data security and a potential vulnerability exploited by malicious actors. Through a detailed analysis of recent cyberattacks, AI-driven security frameworks, and emerging threat vectors, the study reveals how AI can bolster defences through threat detection, predictive analytics, and automated incident response. The research also highlights the ethical and technical challenges in implementing AI-based cybersecurity systems, especially in resource-constrained healthcare environments. The study concludes with strategic recommendations for developing a robust AI-integrated cybersecurity ecosystem aimed at preserving the integrity, confidentiality, and availability of healthcare data. This paper serves as a call to action for policymakers, healthcare administrators, and cybersecurity professionals to recognize AI's pivotal role in countering cybercrime and safeguarding digital healthcare infrastructure.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI in cybersecurity, healthcare data integrity, cybercrime in healthcare, AI-powered threat detection, data protection, digital health security, patient privacy, intelligent security systems, predictive analytics, cyber defence strategies

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Creative Commons Attribution 4.0 and The Open Definition

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Data quality poses a significant challenge for organizations deploying Customer Relationship Management (CRM) systems like Salesforce. Despite progress in data cleansing techniques, existing methodologies are prone to be dependent heavily on manual intervention or rule-based systems lacking the flexibility to learn from changing data patterns. Past research has focused mainly on static algorithms and traditional machine learning models for cleansing, which lack the ability to generalize to the dynamic and complex datasets prevalent in Salesforce environments. This limitation highlights the need for intelligent, autonomous agents with continuous learning and real-time adaptation. Autonomous AI agents with reinforcement learning and adaptive feedback capabilities hold immense potential to address these limitations by cleansing data autonomously with little or no human intervention. However, utilization of such agents specifically for Salesforce datasets has remained under-explored. This paper attempts to bridge this gap by developing a new framework where AI agents systematically find, fix, and remove data anomalies leveraging contextual knowledge of Salesforce data structures and business rules. The framework employs unsupervised learning to detect inconsistencies and reinforcement learning to improve cleansing strategies based on outcomes, promoting scalability and robustness in complex CRM datasets. Experimental testing with real-world Salesforce datasets shows spectacular improvements in accuracy, efficiency, and minimized manual effort compared to existing methodologies. This research makes contributions towards the development of autonomous data management for CRM systems towards more intelligent, self-sustaining data ecosystems that fuel decision-making and operational efficiency.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Autonomous self-learning AI agents, automated data cleaning, Salesforce data sets, reinforcement learning, data quality, CRM data handling, unsupervised anomaly detection, adaptive data correction.

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Creative Commons Attribution 4.0 and The Open Definition