World Wide Web Research Articles

Bug Tracker User Guide

ABSTRACT___ The Bug Tracking Tool project addresses the pressing need for efficient bug tracking and management in contemporary software development. By leveraging modern web technologies and agile methodologies, the project aims to develop a comprehensive solution that streamlines bug identification, tracking, and resolution processes. Through a literature survey, key observations and shortcomings in existing bug tracking tools were identified, guiding the proposed work. The project’s methodology encompasses requirements gathering, design, implementation, testing, and deployment, focusing on user-centric design and functionality. Preliminary results demonstrate progress towards achieving project objectives, highlighting the tool’s potential to enhance software quality assurance practices and user satisfaction. Despite encountering challenges such as technical complexity and resource constraints, the project lays a solid foundation for future enhancements and optimizations. Overall, the Bug Tracking Tool project represents a significant step towards improving bug tracking practices and delivering higher-quality software products to end-users INDEX TEARMS – HTML, CSS , JavaScript, Python, Django Framework, SQLlite.

Creating and Evaluating School Exams with Marks Obtained

Abstract— This research paper explores the development of an educational management system leveraging modern web technologies such as React.js for frontend development, Node.js for backend implementation, and MongoDB for database management. The system comprises two main modules: exam creation and result display. The primary focus is on designing a user-friendly interface for teachers to create exams and for students to access their results. Additionally, a leaderboard feature is integrated to showcase students’ rankings based on their performance. This paper discusses the technical architecture, research objectives, and the significance of this system in enhancing educational administration. The module is developed using the MERN stack technology. The ultimate goal of this module is to make the educational system more efficient for both teachers and students. Keywords – Educational Management System, Modern Web Technologies, Exam Creation, Technical Architecture, MERN Stack.

Integrated representation of technical systems with BIM and linked data: TUBES system ontology

Technical systems in the Architecture, Engineering, Construction, and Operations (AECO) industry are complex interconnected structures. To cope with this high complexity, large amounts of data must be processed and exchanged throughout the whole life cycle of these systems. Building Information Modeling (BIM) and Semantic Web Technologies (SWT) offer the possibility to structure and link this data as well as to define common terminology. Semantic Web ontologies describing HVAC systems in the AECO industry have been developed, but an ontology for an integrated representation based on general system theory is missing. Therefore, this study proposes the TUBES System Ontology (TSO) as a knowledge representation for an integrated, explicit representation of linked technical systems, their hierarchical subdivision, structural and functional interconnections, and relationships to spatial entities. The contribution is validated on two example models, and the results are critically discussed, pointing out corresponding limitations as well as the need for further research.

Technique of Government Digital Auditing

The actions that must be taken to consider government digital auditing, given that we all function in the conditions of the “World Wide Web” (www). The use of www reality is essential for the functioning of government digital auditing. It enables the search for ways to solve the challenges of the rational use of budgetary resources and to optimise budgetary relations in a government. This article is about the benefits, challenges and technique of government digital auditing that intended to safeguard public interest and preserve government assets. The goal of this article is to provide a clear and concise representation of the main blocks of the technique for Government Digital Auditing. This technique is based on Author’s insights and practical experience as a government auditor, Chief of accountants, Professor of Accounting and Auditing.

Information System for Operations in an Aviation Company

The work deals with the design and implementation of an information system for the needs of an aviation company based on its requirements as an integral part of its digitization process. In the first part, the authors examine the current trends, but also the development possibilities, of these systems in areas using computerized collection, processing, storage, distribution, as well as display of information for the needs of personnel in an organization operating in the air transport sector. In the second part, the authors discuss the design and implementation of an information system for a company involved in the air transport process. They are based on predefined requirements of the organization. The result is functional online customizable software based on web technologies in accordance with the functional as well as non-functional requirements of the organization, usable not only in air transport.

Analyzing the Non-compositionality of Conceptual Combinations

Objectives: This research is first of its kind to investigate the application of quantum mechanics and related mathematical models to cognitive science, specifically focusing on the challenge of modeling how the human mind assigns meaning to combinations of words. The primary objective is to classify whether given word combinations are compositional or non-compositional. Methods: The author introduces the "WWW method," which leverages the World Wide Web (WWW) as an experimental tool in place of human subjects, which makes this method cheaper and handy in comparison to the earlier methods which used human subjects for spoken and sign language studies and robots as non-human subjects. The "WWW method" involves checking the adherence to Bell inequalities and marginal selectivity. The term "meaning bound" is introduced to quantify the extent to which two words influence each other's meaning within a combination. This concept proves instrumental in devising a method for assessing compositionality using the WWW method. Findings: When the WWW serves as the information space, the verification of whether a word combination adheres to Bell inequalities entails determining if the meaning bound for the word combination (AB & C) exceeds that of its constituent parts (A & C, B & C) within the conceptual combination AB. Marginal selectivity is evaluated by establishing a vector model for grammatically framed word combinations, utilizing the WWW to collect data. If the word combination 'A then B' yields an equivalent number of hits as 'B then A,' it signifies that the word combination AB satisfies marginal selectivity. Novelty: Consequently, this research presents an accessible approach to identifying entangled pairs of word combinations using the WWW method, eliminating the need for human subject experiments. The earlier studies which include human subjects are costly and cannot be replicated anytime-anywhere, for obvious reasons. Keywords: Quantum cognition, Marginal selectivity, Compositionality, WWW method, CHSH inequality

ОСОБЕННОСТИ РЕЧЕВОГО ПОВЕДЕНИЯ ВИДЕОБЛОГЕРОВ НА ПРИМЕРЕ ОБЗОРОВ ТРАНСПОРТНЫХ СРЕДСТВ

The aim of this article is to identify the features of speech behavior of video bloggers from the point of view of pragmalinguistics, where the main object of the research is the communicant’s conscious and unconscious choice of speech means. The method of traditional content analysis is used to study the conscious choice of language means by a video blogger, while the method of modified content analysis is used to study the unconscious choice. Fragments of speech of videoblogers, whose videos are devoted to retro vehicles reviews were taken as a research material. This article defines such concepts as Internet discourse, blog and video blog, and also identifies and shows on examples the common linguistic features that are found among video bloggers in the field of retro transport. These features will allow to further form speech portraits of video bloggers and determine their personal traits. These traits show what norms of culture, behavior, communication, even the psychology of people’s thinking are formed among representatives of different generations under the influence of the World Wide Web.

Cloud inversion analysis of surrounding rock parameters for underground powerhouse based on PSO-BP optimized neural network and web technology

Aiming at the shortcomings of the BP neural network in practical applications, such as easy to fall into local extremum and slow convergence speed, we optimized the initial weights and thresholds of the BP neural network using the particle swarm optimization (PSO). Additionally, cloud computing service, web technology, cloud database and numerical simulation were integrated to construct an intelligent feedback analysis cloud program for underground engineering safety monitoring based on the PSO-BP algorithm. The program could conveniently, quickly, and intelligently carry out numerical analysis of underground engineering and dynamic feedback analysis of surrounding rock parameters. The program was applied to the cloud inversion analysis of the surrounding rock parameters for the underground powerhouse of the Shuangjiangkou Hydropower Station. The calculated displacement simulated with the back-analyzed parameters matches the measured displacement very well. The posterior variance evaluation shows that the posterior error ratio is 0.045 and the small error probability is 0.999. The evaluation results indicate that the intelligent feedback analysis cloud program has high accuracy and can be applied to engineering practice.

WCA: Integration of Natural Language Processing Methods and Machine Learning Model for Effective Analysis of Web Content to Classify Malicious Webpages

Malicious websites have become a pervasive concern in the digital realm, targeting careless users as well as organizations. It may result in substantial financial losses, identity theft, data intrusions, and damage to reputation. In order to create efficient countermeasures, it is crucial to comprehend the effects of interacting with such websites. There are several ways to classify malicious webpages. Web content analysis is one such way for protecting internet users from malicious activities. It entails analysing websites to identify potential hazards, such as phishing attempts, malware distribution, and fraudulent activities. Traditional methods relied on rule-based systems, but recent advances in natural language processing and machine learning have opened up new avenues for increasing the precision and scalability of web content analysis to classify malicious webpages. Most of the exciting research work focuses more on URL alone for risk free processing. This paper introduces novel method for analysing web contents especially textual contents of the webpages for classification. Among various tags in web technology, proposed method focuses on div, paragraph and meta tags. The textual contents of these tags are extracted and vectorized using three different vectorizers in natural language processing and classify the webpages using machine learning models. Seven different machine learning models are used for performance evaluation. The result shows that a combined textual content of three distinct tags with count vectorizer + random forest achieves the higher accuracy of 93.46% with 1000 features.

Data Security and Cryptography Substitution Techniques Algorithms implementation

Cryptography and data security have been usedto make data more secure for many years, militarycommunications are having a major impact on growingcryptography field. Although the internet have been invitedin the ends 1960's, but it is not appear to public until inventthe World Wide Web (www) in 1989. The World Wide Weballows people to e-mail each other and transfer data. Thisappeared as one reason in growing use of computer. Inaddition needs to make e-commerce more secure.Cryptography understanding helps to find better ways orprotocols to make transfer data faster and more efficient.This paper starts with a brief background about securityand cryptography. It provides central concepts ofcryptography. Also provides an account of substitutiontechniques algorithms and their implementation. Theimplementation will be as an application in c# language thatreads a text, encodes it by a specified algorithm and decodesthe encrypted text. In addition explaining the mathematicalfunctions used in the algorithms

SISTEM PAKAR DIAGNOSA PENYAKIT SAPI

In the livestock industry, the health of cattle is crucial because diseases can lead to a decrease in production, animal deaths, and economic losses. The high incidence of these diseases is due to ignorance and lack of knowledge about them. Therefore, an expert system was developed to diagnose diseases in cattle. The method used in creating this expert system is forward chaining using the PHP programming language and MySQL database. The result of this research is an expert system application for diagnosing diseases in cattle using forward chaining method, which can be accessed by the public, especially farmers and traders, to identify diseases in cattle, with the hope of improving the efficiency of diagnosis. This system can speed up the disease detection process, minimize human errors, and enable faster and more accurate decision-making by combining artificial intelligence with web technology.

Development of Models by Energy Expended and Age Classifications for Diet Recommendation System

People today are more conscious of their health and constantly looking for methods to improve their health status. Due to the unavailability and inaccessibility of dieticians to recommend diet, people do not know how to plan their diet well, thereby people’s health are compromised because of unbalanced diet and misappropriation of diet. There is need to develop models that recommend diet on various classifications on the basis of energy expended daily and age. The models are mathematically represented using arithmetic expressions on different classifications: Energy expended or job/activities, health status, family size and age. The models use the rule-based statements to proffer solution to diet problems. In employing the technology, the models were implemented using a programming tool like PhP etc The DRS can be deployed on the World Wide Web and be allowed to be used by the general public for a healthy diet. The Diet Recommendation System (DRS) creates and increases people's awareness and assist them in receiving appropriate counsel as to the quantity of food, food types, time to take food, the appropriate food for certain age group, the balanced diet for a family size, the kind of food type according to the activities a person engages in.

Networking Aspects of the Electronic Health Records: Hypertext Transfer Protocol Version 2 (HTTP/2) vs HTTP/3.

The rapid development of the digital healthcare and the electronic health records (EHR) requires smooth networking infrastructure to access data using Hypertext Transfer Protocol (HTTP)-based applications. The new HTTP/3 standard should provide performance and security improvements over HTTP/2. The goal of our work was to test the performance of HTTP/2 and HTTP/3 in the context of the EHRs. We used 45,000 test FHIR Patient resources downloaded and uploaded using 20, 50, 100 and 200 resources per Bundle, which resulted in 2251, 901, 451 and 226 HTTP GET and POST requests respectively. The first test downloading 20 resources per Bundle showed that HTTP/3 outperformed HTTP/2 in the local (mean request time 16.57 ms ± 7.2 standard deviation [SD]) and in the remote network (71.45 ms ± 43.5 SD) which is almost 3 times faster. In the 50 and 100 resources per Bundle test the HTTP/3 protocol demonstrated again more than two times gain in downloading performance for remote requests with mean request time 91.13 ms ± 34.54 SD and 88.09 ms ± 21.66 SD respectively. Furthermore, HTTP/3 outperformed HTTP/2 in the constructed clinical dataset remote transfer. In the upload tests HTTP/3 showed only a slight gain in performance merely in the remote network. The HTTP/3 protocol is a relatively new development and a major improvement for the worldwide web. This new technology is still missing in the digital health and EHRs. Its use could offer a major performance gain in situations where data is gathered from multiple remote locations.

Citizens as Environmental Sensors: Noise Mapping and Assessment on Lemnos Island, Greece, Using VGI and Web Technologies

Noise caused by industrial activities, urban life and traffic has a negative impact on people's health and quality of life. Environmental noise mapping is an important tool to study and address this problem. Through specialized measurement and analysis techniques, it is possible to identify areas at high risk of noise and under-stand the extent of the problem. This information can be used to develop strategies to protect the population exposed to high noise levels. In this paper, a method for collecting, processing, managing and mapping spatial noise data based on Volunteered Geographic Information (VGI) and web mapping technologies is present-ed. The proposed method uses noise pollution data collected from citizens using mobile devices. This includes both on-site measurements and information on users' subjective perceptions, providing a comprehensive picture of the problem. This enables authorities to take into account the individual perceptions and needs of citizens when planning noise mitigation measures, which has not been the case in the inter-national literature to date. To achieve this goal, a prototype of a free and open-source tool called "Noise Pollution" was developed. The proposed methodology and the resulting system are intended to help improve the quality of life in noisy environments and protect the health of citizens. They provide a practical tool for collecting and analyzing noise data and enable the development of noise mitigation strategies for the benefit of the population exposed to high noise levels.

Exploring the Importance of Fiori in Application Development

Fiori web apps represent the blend of beauty and practicality reshaping user experiences in the era. Stemming from SAPs dedication to user design Fiori apps focus on simplicity, ease of use and responsiveness. By emphasizing role interactions they deliver personalized experiences catered to users requirements. Using web technologies Fiori apps enable users to seamlessly access business functions and insights enhancing efficiency and fostering innovation. Covering a range of business operations they streamline processes. Enhance decision making. Through their design and smooth operation Fiori apps pave the way, for a phase of enterprise software that harmoniously combines usability, with functionality. Index Terms—Fiori apps, design principles, sap ux strategy and the sap fiori ux

Website for Online Election System

The goal of this article is to present the design and execution of an online voting system that will improve the election process's accessibility, security, and efficiency. The integrity and confidentiality of votes cast are guaranteed by the proposed system, which makes use of secure web technologies and contemporary cryptography techniques. Real-time result tabulation, end-to-end encryption, and user authentication are important features. Regardless of their level of technical expertise, voters may easily traverse the platform thanks to the user-friendly design of the system. Strong safeguards are also put in place to guard against fraud and guarantee voters' confidentiality, answering worries about the possibility of cyberattacks and illegal access. The online voting system has undergone extensive testing and review, and the results show that it significantly outperforms traditional voting systems in terms of voter participation rates, convenience, and accuracy.

Specifics of YouTube Functioning as a Popular Video Hosting Platform in the Modern Internet Space

The purpose of the article is to study the main aspects of the development of YouTube video hosting in the modern Internet space and to analyse the strategy for improvement and competitiveness of YouTube as a popular media platform. Research methods. The methodology is based on applying analytical, systemic, empirical, comparative and functional methods. In particular, the author analyses the features of the Internet space as a multi-component integral system, where a high degree of interactivity and consumption of Internet resources can be traced through video hosting; determines that YouTube is the key video hosting; summarises the advantages of YouTube among other video hosting; identifies the problems and contradictions which have caused the platform to be criticised; identifies the main factors contributing to the growth of competitiveness since the creation of the website, as well as the algorithms of YouTube’s functioning in the modern Internet space and the ways to improve it. The scientific novelty is to clarify the specifics of the fundamental properties of the functioning and competitiveness of YouTube video hosting; to predict algorithms for improving the platform, and to identify some technological innovations and tools that will contribute to YouTube’s leadership on the World Wide Web. Conclusions. Today, the Internet is a powerful platform that consumers are actively using. Video hosting services are quite popular among Internet formats, as they experiment with various content in specific market conditions. This very web service is a platform for the potential representation of content, which is updated through active requests and views of recipients. In the context of war, modern machine learning algorithms make it possible to create a regression model that is best suited to choosing a strategy for creating and promoting Ukrainian-language content on video hosting services. YouTube is a powerful online video hosting platform that is constantly improving and experimenting with various content in specific market conditions. While maintaining its leadership position, YouTube is expanding its interaction with other social networks, streaming platforms and services and is confidently competing with many video hosts. YouTube is not just a project, but an empirical reality that is dynamically developing and reflects new high-quality content driven by specific communicative functions, forming a value basis in the process of functioning.

Integration of Building Information Modeling (BIM) and Geographic Information System (GIS): a new approach for IFC to CityJSON conversion

Within the contemporary urban development discourse, the paradigm of smart cities has gained prominence over the past two decades. Ensuring sustainability in smart cities requires coherent orchestration of processes that span design, construction, operations, and management. Central to this orchestration are technologies such as Building Information Modeling (BIM), which provides detailed architectural data, and Geographic Information Systems (GIS), which provide comprehensive geographic intelligence. However, a significant challenge remains: data degradation during BIM-GIS integration. This data inconsistency, exacerbated by the different data structures of BIM and GIS, is a barrier to true interoperability. One promising solution to this conundrum is the use of Semantic Web technologies. In this study, we leverage Semantic Linked Data and geometric conversion tools to develop an algorithm that mitigates the loss of semantic information during the BIM-to-GIS conversion process. The effectiveness of this approach is underscored by a 95% accuracy rate of the converted semantic information.

Towards a semantic blockchain: A behaviouristic approach to modelling Ethereum

Decentralised ledgers are gaining momentum following the interest of industries and people in smart contracts. Major attention is paid to blockchain applications intended for trading assets that exploit digital cryptographic certificates called tokens. Particularly relevant tokens are the non-fungible tokens (NFTs), namely, unique and non-replicable tokens used to represent the cryptographic counterpart of assets ranging from pieces of art through to licenses and certifications. A relevant consequence of the hard-coded nature of blockchains is the hardness of probing, in particular when advanced searchers involving the capabilities of the smart contracts or the assets digitised by NFTs are required. For this purpose, a formal representation for the operational semantics of smart contracts and of tokens has become particularly urgent, especially in economy and finance, where blockchains become increasingly relevant. Hence, we feel the need to tailor Semantic Web technologies to achieve that semantic representation at least for NFTS. This article reports on an ontology that leverages the Ontology for Agents, Systems, and Integration of Services (“OASIS”) towards the semantic representation of smart contracts responsible for managing ERC721-compliant NFTs and running on the Ethereum blockchain. Called Ether-OASIS, the proposed ontology adopts OASIS and tailors its behaviouristic approach to the Ethereum blockchain by conceiving smart contracts as agents running on the blockchain and, consequently, smart contract interactions as agent commitments. Smart contracts are represented in terms of their actions, purposes and tokens that they manage, thus realising a blockchain that is more usable both by users and automated applications. The ontology is evaluated using standard ontological metrics and applied on a case study concerning the minting and transferring of NFTs that digitise batches of wheat.

Uniqueness meets Semantics: A Novel Semantically Meaningful Bag-of-Words Approach for Matching Resumes to Job Profiles

In an increasingly competitive world, automated screening of resumes of candidates is the need of the hour given the large numbers of such resumes in career portals on the World Wide Web. Resume classification is a subset of the document classification problem in which the keywords extracted from the resume play a significant role in determining the job profile. In this paper, we explore the novel combination of uniqueness in terms of the number of occurrences of a keyword in a resume class as compared to the other resume classes, and the concept of semantics by representing the filtered keywords using word embeddings that can be used to find semantic similarities between resume documents. The principle of maximum entropy partitioning is used to find the keywords unique to a particular class. The aim is to use semantic representations of only those keywords that occur more frequently in one class more than in any other class; these are then passed as input to a Bidirectional long short-term memory (LSTM) for classification. Our experiments on a benchmark dataset proves that the proposed approach outperforms the state of the art in text classification by a significant margin proving the efficacy of our approach.