World Wide Web Research Articles

Semantic Web-Based Image Super-Resolution for Enhanced Steel Surface Defect Detection

This study addresses the challenges of steel surface defect detection by introducing the ATG-SRGAN model, which integrates Semantic Web technologies with an Adaptive Transformer and Generation module. By leveraging self-attention mechanisms and residual convolution within the SRGAN framework, the model enhances image resolution, reduces noise, and uncovers finer details, achieving superior PSNR (37.17) and SSIM (0.9590) metrics. Integrated with an improved YOLOv8-ghost-p2 framework, the model also attains a mean Average Precision (mAP) of 81.2 and a recall rate of 76 in defect detection. These results demonstrate the model's potential to significantly improve automated quality control in industrial settings, highlighting the importance of Semantic Web technologies in advancing defect detection methods.

Ontology-based Data Integration Framework for Smart Pig Farms

Semantic web technology is known to enhance data for the connection of information using a network that can be easily read by machines. This work applies an ontology to integrate data involved in swine farm management towards the development of smart farm for swine. To realize environmental data, IoT devices including sensors, camera, and RFID readers were deployed in a pig farm. Despite differences in data format from different sources, an ontology was crafted to provide semantic annotations that could unify the data and enhance them with tangible relationships based on the domain knowledge. The core concepts of this ontology were sensing data with temporal information and identifiable data to represent relationship between real-time environmental features and the pigs within the pen to improve pig management. The semantically enhanced data can thus be applied with semantic-based queries and inference reasoner. Smart services including monitoring, decision support, alerting, and automatic executing based on the deployed IoT devices are thus enabled to support farm managements towards smart farm for swine. From the results, we found that the integrated sensing information from sensors and knowledge given in the developed ontology with inference rules assists the task of interpretation of monitored information and decision-making to improve swine farm management. The data gathered could be extended by combining two or more factors such as temperature and humidity into heat index using knowledge inference to precisely understand environmental information and activate the relevant machine automatically.

Crowdsourcing as a Pedagogical Tool in Computer Science Higher Education: a Case Study

The approach used and the insights gained from employing crowdsourcing techniques in a computer science homework assignment for higher education students are described in this paper. Making use of a platform that supports crowdsourcing in the cultural heritage domain, students were solicited to enrich the metadata associated with a selection of music tracks. The results of the campaign were further analyzed and exploited by students through the use of semantic web technologies. In total, 98 students participated in the campaign, contributing more than 6400 annotations concerning 854 tracks. The process also led to the creation of an openly available annotated dataset, which can be useful for machine learning models for music tagging. The outcomes of the campaign and the feedback collected via an online questionnaire allow us to draw useful insights about the challenges and benefits of incorporating crowdsourcing techniques into computer science curricula and the educational gains for students.

BIM-based search and selection of construction material suppliers: a dedicated framework and prototype

Purpose This study aims to address the key issues concerning supplier selection in traditional construction procurement by proposing an innovative, novel, state-of-the-art prototype plugin building information modelling – supplier search and ranking (BIM-SSR) and an associated conceptual framework. It enhances building information modelling (BIM) capabilities through web crawling and analytical hierarchy processes (AHP). It uses the World Wide Web to procure construction material suppliers. Design/methodology/approach Prevalent issues in traditional procurement of material suppliers have been identified through a rigorous literature review. Field experts vetted these issues. A framework has been presented to address these issues based on integrated web crawling and AHP as a multi-criteria decision-making (MCDM) method. A BIM prototype (BIM-SSR) has been developed using Python and plugged into Autodesk Revit to automate the search and evaluation of material suppliers based on precise material specifications from the BIM design. The BIM-SSR prototype is tested through a case study and validated by field professionals for its efficiency in tackling the identified issues. Findings Thirteen key issues have been identified concerning traditional construction procurement pertinent to supplier selection. Best-value procurement was encouraged by identifying supplier selection criteria such as cost, delivery time, experience, compliance with quality management standards, warranties, and claim period. The presented BIM-SSR prototype has an efficiency of 80%–95% in addressing the issues identified in this study and 97.5% effectiveness in improving the overall procurement management process. Originality/value The BIM-SSR prototype developed in this study is a novel and innovative addition to the body of knowledge that has been integrated into Autodesk Revit as a Plugin. Automation of supplier search and selection through digital technologies, including web crawling and integration of traditionally accepted MCDM methods such as AHP in BIM, is another innovation in the current study. Overall, this study presents a holistic, innovative system, from conceptual design to practical implementation and demonstration. This is one of the steps to help the traditional construction procurement process evolve into a more modern and digital procurement.

Crypto-Spatial: A New Direction in Geospatial Data

Abstract. Geospatial technology involves the use of maps, satellite imagery, and spatial databases to collect, analyze, and visualize geographic data. Understanding the link between blockchain and geospatial technology is crucial as it opens the door to innovation and progress in both fields. “The use of Blockchain as a system for managing and verifying geospatial data necessitates accuracy, integrity, and trustworthiness”(Pengxiang et al 2022). Improving data integrity, promoting collaboration, and revolutionizing applications in the geospatial domain are all possible through the combination of these two technologies. The World Wide Web (WWW) has expanded connections worldwide, but it also makes networks susceptible to multiple attacks from various anonymous sources. Packets of fixed or variable sizes are used for transmitting data across nodes. Data is encrypted using secure algorithms at the application level, then packetized and sent at lower levels in the OSI architecture. The encrypted data can be obtained by an intruder by organizing the data contents of each packet once they have access to all the packets. Intruders may also attempt to break the secured algorithm used by the sender. This sophisticated approach to Data Security is the content and order of data, ensuring that unauthorized individuals are unable to discern sensitive information during data transmission. The primary objective of this paper is to introduce a novel spatial encryption technique designed to enhance the security of data transfers within networks. This paper, founded on a comprehensive literature review, endeavors to propose a research project focused on exploring futuristic solutions, particularly within the post-quantum era.

Analytical Evaluation of the WebSocket and WebTransport Protocols for the Class of SCADA Systems Operating Within the Intranet

The purpose of research. In recent years, web technologies have been actively used in many process control systems, including SCADA. Such systems allow continuous monitoring of the test object in real time. In this regard, there is a need for frequent data transmission for their further display. To solve this problem, network protocols are used, which continue to develop rapidly to this day.Materials and methods. SCADA systems are used in many industries: aviation, ground transportation, rocket and space technology, systems for receiving and processing telemetry information. Among them, a class of SCADA systems operating within the intranet stands out. This can be an internal network of the enterprise, a hangar or a small test stand for tracking the indexes of measuring equipment. Therefore, today, more than ever, open and publicly available materials are important for understanding modern network solutions that reduce the time spent on data transmission and their further visualization. Such information will be of particular value to students studying network and web technologies.Results. As a result of the research, taking into account the limitations of the SCADA system and network being developed, the time characteristics for the WebSocket and WebTransport protocols have been determined, and the most optimal solution for a typical load is proposed. In the presented paper, the issues of data transfer between the client and server parts for a class of SCADA systems operating within an intranet are considered. In this regard, it is proposed to consider the two most suitable solutions for this task. These are application layer network protocols of the OSI model: WebSocket and WebTransport. In addition, transport layer protocols (TCP and QUIC) are taken into account, since they can also affect time characteristics. Data transmission issues are considered in the context of the SCADA data display and monitoring system. The server part is developed using C#, and the client is developed using JavaScript. A number of experiments are carried out for boundary cases and typical loads, on the basis of which the dependence of data transmission time on their volume is determined.Conclusion. The approach given in the paper on collecting network traffic and analyzing time characteristics will also be useful as part of the educational process for teaching students in the courses “Computer Networks” and “Internet Technologies”.

Newsmaking Criminology in the 21st Century: Forming the Public Opinion under the New Reality

Objective: to study the concept of newsmaking criminology and its relevance in the current conditions of mass media development.Methods: the methodological basis of the work consists of general scientific, social, and special-legal methods of cognition. The conducted research is based on the dialectical method (in determining the general direction of the study), methods of formal logic (analysis, synthesis, induction, deduction, analogy), system method (in comparing and generalizing the information collected for the research).Results: the functions of newsmaking criminology in its classical manifestation, as well as its additional functions in the study of mass media in the Internet, were revealed. It is suggested that with the emergence of the World Wide Web, the relevance of newsmaking criminology has increased: social networks, blogs and video hosting as alternative media have a strong influence on public opinion, while an unlimited number of people have access to content generation, contrary to traditional media. Many states understand the importance of interaction between mass media and law enforcement agencies and are actively implementing their methods of promoting newsmaking criminology online. This article points out the risks that arise in media coverage of law enforcement and crime. One of such risks is the cancel culture, which is spontaneous, unpredictable in nature, and may jeopardize the quality of life of the victim or business reputation and activity of organizations.Scientific novelty: the functions performed by newsmaking criminology in the study of traditional and alternative media were identified. So far, such doctrine has not been sufficiently researched taking into account modern forms of mass communication. Examples of interaction between law enforcement agencies of different states and the media were analyzed.Practical significance: the study contributes to understanding the correlation between criminological phenomena and modern media platforms. The Internet and social networks provide new channels of information exchange that differ significantly from traditional media such as printed media or television.

Large-Scale Knowledge Graphs as a Tool for Enhanced Robotic Perception

Autonomous robotic systems depend on their perception and understanding of their environment for informed decision-making. One of the goals of the Semantic Web is to make knowledge on the Web machine-readable, which can significantly aid robots by providing background knowledge, and thereby support their understanding. In this paper, we present a reasoning system that uses the Ontology for Robotic Knowledge Acquisition (ORKA) to integrate the sensory data and perception algorithms of the robot, thereby enhancing its autonomous capabilities. This reasoning system is subsequently employed to retrieve and integrate information from the Semantic Web, thereby improving the robot's comprehension of its environment. To achieve this, the system employs a Perceived-Entity Linking (PEL) pipeline that associates regions in the sensory data of the robotic agent with concepts in a target knowledge graph. As a use-case for the linking process, the Perceived-Entity Typing task is used to determine the more fine-grained subclass of the perceived entities. Specifically, we provide an analysis of the performance of different knowledge graph embedding methods on the task using a annotated observations and WikiData as a target knowledge graph. The experiments indicate that relying on pre-trained embedding methods results in an increased performance when using TransE as the embedding method for the observations of the robot. This contribution advances the field by demonstrating the potential of integrating Semantic Web technologies with robotic perception, thereby enabling more nuanced and context-aware decision-making in autonomous systems.

Digitalisation in European regions: unravelling the impact of relatedness and complexity on digital technology adoption and productivity growth

ABSTRACT Digital technologies are the cornerstone of platform, knowledge, and network economies, driving the interconnectedness, innovation, and efficiency that define these economic models. Consequently, digitalisation has recently become a key policy objective for regional economies. This paper provides empirical evidence on how the adoption of new digital web technologies is shaped by previous regional digital capabilities. The analysis is based upon an economic complexity and relatedness framework using novel data on digital web technologies’ adoption for 278 European NUTS-2 regions between the years 2000 and 2022. Results show that regions tend to adopt new digital web technologies when they already master related digital capabilities. This paper also shows how digital complexity is associated with labour productivity gains at the regional level. Conclusions shed light on how regions adopt digital web technologies and serve as a tool for policymakers.

Is It True That More Than Half of Web Contents Are in English? Not If Multilingualism Is Paid Due Attention!

The belief that English is and will remain largely dominant as the first language of the Internet in terms of content and is the natural lingua franca in cyberspace plays against the mobilization of human and funding resources to incorporate minority languages. We sustain that this belief stands on biased data and that multilingualism is more and more the nature of the Internet and translation its lingua franca. We challenge the validity of a source widely used, since 2011, to state that English represents a steady percentage of web contents over 50%. This business source, W3Techs, is well-famed and considered reliable for its surveys on web technologies, exploring a large sample of the Web. However, languages differ from other web technologies, in the fact than more than one language could be used on a website. Not taking into account the multilingual nature of the Web is a serious bias that leads to major errors. The study of the rate of multilingualism of the sample of websites used by W3Techs concludes that the percentage of English contents on the Web is within a 20%–30% range, a value coherent with the results from three referenced alternative methods. We plan for 2025 to create a tool for measurement of languages and rate of multilingualism in a series of websites, with thorough attention to list all the languages used within a website, a complex matter. This tool will be applied to the same sampling and should close definitively this matter.

The Evolution of EFL and ELL (2000-2024): Impact of Culture, Technology, and Innovative Pedagogies on Language Learning

For nearly a century, English language has consistently remained a global phenomenon with a continued business relevance; the mandatory inclusion of English Language Learning (ELL) in Asian, African and other non-native English-speaking countries is proof of the same. Consequently, research about English as a Foreign Language (EFL) has continued too. Despite ample empirical studies in the past that have examined the role of culture, linguistics, technology or digital tools in EFL, there are limited studied that holistically investigate and review the learning and successful implementation of EFL and its influencing factors. The current study is an attempt to systematically synthesize the findings from empirical studies undertaken between early 2000 and 2024 in the domains of EFL and ELL for a sample of 53 journal articles. The research also aims to draw a scientific relationship between the most relevant concepts surrounding ELL and EFL. To achieve this, the study conducted a systematic literature review coupled with Bibliometric mapping analysis. The study concluded that the upward surge of technological advancements and World Wide Web has transformed learning EFL. Cultural diversity, and technological or digital tools are key influencing factors and innovative teaching/learning pedagogies in EFL and ELL that can enhance the success rates in EFL and ELL in non-native English-speaking countries.

Systemic Functional Linguistic Based on Semantic Web

This research aims to combine a functional and systematic linguistic approach with Semantic Web technology. The main aim of this research is to develop a framework that can facilitate systematized analysis and language modeling in the context of the semantic web. The research method used is a qualitative approach with focused data analysis. The data collected will involve text and web content relevant to the Semantic Web framework. The analysis was carried out using the principles and tools of systematic functional linguistic analysis to identify language structure, communicative function, and meaning in web content. The results of this research are expected to provide new insights into the understanding of how language can be organized and analyzed regularly in the context of the semantic web. Apart from that, this research is also expected to contribute to the development of Semantic Web technology by using a functional linguistic approach. It is hoped that the conclusions of this research will provide a deeper understanding of the role of language in the context of the semantic web and provide a basis for the development of more sophisticated and effective Semantic Web-based applications and systems.

Implementation of Sports Science and Technology Integration Infrastructure: A Case Study of Speed Skating Utilizing Web and Mobile Applications, and Information Visualization Technologies

In the field of sports, there is an active discussion on and an attempt to apply technologies that integrate sports with cutting-edge science and technology for the purpose of enhancing athletic performance. In line with this trend, South Korea is supporting research on the fusion of sports and science technology at an interdepartmental level. For the improvement of performance in elite sports, it is important to consider the athlete’s skills, the coach’s information analysis, the scientification of equipment, and the environmental optimization. Accordingly, this study aims to propose web and mobile app technologies to establish an integrated infrastructure of sports science and technology for the three factors of athletes, equipment, and environment to improve the performance of speed skating. Furthermore, it aims to make policy recommendations to activate this integration. The application of such technologies and policy recommendations can be transferred and organically integrated into other sports, including track and field, which are time-based competitions. Additionally, it is expected that this approach will lead to the formation of new theories that consider the emotional aspects occurring in sports situations.

A Study on Functional Requirements and Inspection Items for AI System Change Management and Model Improvement on the Web Platform

The rapid adoption of artificial intelligence (AI) on the web platform across multiple sectors has highlighted not only its inherent technical hurdles, such as unpredictability and lack of transparency, but also significant societal concerns. These include the misuse of AI technology, invasions of privacy, discrimination fueled by biased data, and infringements of copyright. Such challenges jeopardize the sustainable growth of AI and risk the erosion of societal trust, industry adoption and financial investment. This analysis explores the AI system’s lifecycle, emphasizing the essential continuous monitoring and the need for creating trustworthy AI technologies. It advocates for an ethically oriented development process to mitigate adverse effects and support sustainable progress. The dynamic and unpredictable nature of AI, compounded by variable data inputs and evolving distributions, requires consistent model updates and retraining to preserve the integrity of services. Addressing the ethical aspects, this paper outlines specific guidelines and evaluation criteria for AI development, proposing an adaptable feedback loop for model improvement. This method aims to detect and rectify performance declines through prompt retraining, thereby cultivating robust, ethically sound AI systems. Such systems are expected to maintain performance while ensuring user trust and adhering to data science and web technology standards. Ultimately, the study seeks to balance AI’s technological advancements with societal ethics and values, ensuring its role as a positive, reliable force across different industries. This balance is crucial for harmonizing innovation with the ethical use of data and science, thereby facilitating a future where AI contributes significantly and responsibly to societal well-being.

A Semantic Augmented Approach to FEMA P-58 based Dynamic Regional Seismic Loss Estimation Application

Regional seismic loss estimation (RSLE) is a crucial process in both immediate post-earthquake emergency response and long-term reconstruction endeavors. Over the years, significant progress has been made in RSLE: sensing approaches such as field investigation and remote sensing offers a comprehensive overview necessary for real-time disaster response, while simulation techniques such as the methodology proposed in Federal Emergency Management Agency (FEMA) P-58 series provide insights into the mechanism of disaster development and its potential long-term impacts on urban assets. Nonetheless, challenges persist in the realm of practical RSLE applications. Firstly, a dynamic understanding of a disaster event and its influence is deemed important for effective emergency responses while challenging to achieve in current approaches. Secondly, stakeholders with varying roles, including administrators, rescue teams and ordinary citizens have distinct information requirements for RSLE. Thirdly, the complexity of seismic loss estimation, involving diverse data sources such as building information models, performance models, fragility data and sensor observations, poses interoperability issue. To tackle these issues, this article introduces a dynamic, multi-granularity, ontological representation scheme tailored for RSLE decision-supporting systems. This scheme operates across various scales, from individual building components to broader regional scales by synergistically employing FEMA P-58 guidelines and Semantic Web technologies. Upon the corresponding semantics, a question-and-answer agent powered by large language model is further developed to facilitate interaction requirements within the RSLE process via FEMA P-58 pipeline. The practical efficacy of this approach is validated through a prototype deployed under a real earthquake event, demonstrating its value in real-world scenarios.

PulseGuard: Health Monitoring and Analysis System

Abstract: The use of wearable devices such as smart watches has led to a major change in the way a person is able to manage their health. In this paper, health monitoring system construction based on a smartwatch is designed which is capable of Health parameters like heartbeat monitoring, counting steps and their physical activity levels at continuous intervals. The system is built on modern web technologies and cloud services for data processing in a real-time manner, thus ensuring that alert messages are delivered immediately in case health parameters go beyond the normal ranges. The goal is to improve personal health management by providing expansion, dependability and availability to the users in areas where there is poor or no health care provision. The paper discusses system architecture, implementation, and the prospect of the system in enhancing preventive medicine and its practice for better health.

Bridging the Gap: An Analysis of Cybersecurity in Web Technologies for Cyber Diplomacy

Bridging the Gap: An Analysis of Cybersecurity in Web Technologies for Cyber Diplomacy

Arabic word tokenization system using the maximum matching model

Word tokenization is the first stage for higher-order Natural Language Processing (NLP) tasks like Part-of-Speech (PoS) tagging, parsing, and named entity recognition. The amount of text on the World Wide Web is growing daily in the present era of technology, necessitating the use of advanced instruments. Since more and more people speak Arabic around the world, Arabic language processing systems must be improved. Due to the writing style of Arabic with a lack of support for capitalization features and the use of compound words, it is difficult to perform word tokenization. This research paper proposes a novel Arabic word tokenization system based on the knowledge. To develop this system, a maximum matching model with its two variations, namely forward and reverse maximum matching is used. The proposed system is implemented in Python. The results produced during system evaluation report high performance.

Online Marketing and Advertising in Nigeria: Prospects and Challenges

The study was guided by three research objectives and underpinned by two theories: Technological Determinism and Social Presence Theories. The study was tilted toward qualitative methodology while library research design was adopted in studying secondary data obtained from books, journals, and newspapers which were analysed. Among other findings, the study ascertained that the Internet and other communication technology channels are generally changing many aspects of consumers’ buying behaviour all over the world, including Nigeria, to new goods and services and that the Internet and the World Wide Web have transformed how goods are bought and the way businesses are conducted. The study also found that despite the prospect of online marketing and advertising, unpredictable fixed line networks in Nigeria and unstable electricity supply, pose serious challenges to online marketing and advertising in Nigeria. The study concluded that these situations pose challenges to sustainable marketing communication in Nigeria. Given these findings, the study recommended among others that, the government and all the relevant stakeholders should improve on internet infrastructure in Nigeria, constant electricity supply, and make data subscription affordable and that online advertising messages need to be compelling and engaging to be able to capture and retain audience attention, to achieve the desired result.

Optimizing Test Data Management Strategies in Banking Domain Projects

The steady rise in processing power over the past 20 years has resulted in an enormous volume of data. Furthermore, anybody may now easily create and consume material in any format thanks to recent advancements in Web technology. Large volumes of data are regularly gathered by banking systems, including trade finance data, SWIFT and telex communications, client information, details about transactions, risk profiles, credit card details, limit and collateral details, the compliance or Anti Money Laundering (AML)-related data, and limit and collateral details. Every day, thousands of choices are made at banks. These choices pertain to credit, default, beginning a relationship, investments, AML, and illicit funding, among other things. To make these crucial choices, one must rely on a variety of data and drill down capabilities offered by the banking systems. We created a set of specifications for the kinds of data that should be included in a product catalogue. We ascertained what data the departments need by using a survey and questionnaire of the retailer's staff. We ensured that there was no one standard for the information organisation and then put out our own plan. This enormous amount of data may be mined for information and intriguing patterns, which can then be used to the decision-making process. This article examines and summarises a number of data mining methods that have applications in the banking industry. An overview of data mining methods and procedures is given. It also sheds light on how these methods may be applied in the banking industry to facilitate and enhance decision-making.