Traditional Web Research Articles

Implementation of PWA in Scholarship Application Using Microservices Architecture for Enhancing User Engagement

The shortage of traditional web development makes researchers turn to web development using Progressive Web App (PWA) in developing a web, which has been increasingly done. PWA has the ability to function even with a low internet connection, maintain interactive user and access speeds, and provide real-time notifications. In modern web development, where the demand for data, features, and users can increase rapidly, an architecture is required to handle this problem. Microservices architecture can answer this. This research will develop a scholarship application using PWA and microservices architecture. The scholarship application was developed using Veu.js for the front end of the client application, MySQL for the application database, and the SLIM framework for microservices implementation. Furthermore, we utilized RAbbitMQ to develop a message broker and Docker for microservices contaner. The scholarship application developed using PWA technology and microservices in this research has been tested by conducting a User Acceptance Test. The results are the implementation of PWA in the scholarship application using microservice architecture has worked well, and the application performance has been able to overcome problems in terms of scalability, speed, and reliability.

Design and Implementation of a Web Attack Analysis System Based on Honeypot Technology

Nowadays, with an increasing number of Web services being deployed in university network systems, Web attacks have become a significant threat due to the inherent vulnerabilities in Web services and the diverse forms of these attacks. Traditional Web attack defenses can only react passively, resulting in a lag in protection. Therefore, to enhance the security of Web systems, this paper develops a Web attack analysis system based on honeypot technology. Firstly, the system captures Web attack information through simulated honeypots. Secondly, it extracts and integrates effective data from the attack information to analyze hackers' attack methods and intentions. Thirdly, the analysis results are visualized through charts, providing data support for system maintenance. Finally, the feasibility of the system is verified through experiments.

Face Detection and Recognition for Criminal Identification System

This project showcases a powerful Face Detection and Recognition system intended to improve law enforcement skills by speeding up the identification of suspects in criminal cases. The system uses scalable databases and real-time computation, however instead of using traditional web sources for face detection. Accuracy and dependability are ensured by using the LBPH algorithm for face recognition and the Haar-cascade classifier for feature detection. The smtplib library allows the system to send a Gmail notification when it finds a matching face. The system that has been built contributes to public safety initiatives by improving law enforcement operations and demonstrating versatility for different face detection circumstances. The outcomes show how successfully the system can detect faces in real-time circumstances. The system achieves great performance by creating dynamic datasets and integrating algorithms. Integrating Gmail improves law enforcement response by facilitating prompt contact of identified suspects. This study highlights the role that surveillance technology plays in public safety and crime prevention, and it provides law enforcement authorities with useful solutions. Furthermore, the uses of this facial recognition and detection technology go beyond police enforcement. It can expedite attendance tracking and improve security in access control systems. Because of its adaptability, it can be used in a variety of industries and is expected to have a significant impact.

Social Network Forensics Analysis Model Based on Network Representation Learning.

The rapid evolution of computer technology and social networks has led to massive data generation through interpersonal communications, necessitating improved methods for information mining and relational analysis in areas such as criminal activity. This paper introduces a Social Network Forensic Analysis model that employs network representation learning to identify and analyze key figures within criminal networks, including leadership structures. The model incorporates traditional web forensics and community algorithms, utilizing concepts such as centrality and similarity measures and integrating the Deepwalk, Line, and Node2vec algorithms to map criminal networks into vector spaces. This maintains node features and structural information that are crucial for the relational analysis. The model refines node relationships through modified random walk sampling, using BFS and DFS, and employs a Continuous Bag-of-Words with Hierarchical Softmax for node vectorization, optimizing the value distribution via the Huffman tree. Hierarchical clustering and distance measures (cosine and Euclidean) were used to identify the key nodes and establish a hierarchy of influence. The findings demonstrate the effectiveness of the model in accurately vectorizing nodes, enhancing inter-node relationship precision, and optimizing clustering, thereby advancing the tools for combating complex criminal networks.

Интерактивная геоинформационная система динамической визуализации характеристик аврорального овала на основе паттернов компонентно-ориентированного программирования

The practical need for operational monitoring of the position dynamics of the auroral oval is due to the negative technospheric manifestations of space weather effects observed in this spatial region. However, the well-known software tools for modeling the auroral oval solve this problem inefficiently from the point of view of informativeness and ergonomics. The paper proposes an approach to dynamic visualization of the characteristics of the auroral oval, which is available at the program level in the form of a traditional web application with the ability to render visual elements in the browser, as well as in the format of a standalone service like RESTful-API. The developed solution provides visualization of the following parameters: the probability of observing the glow of the upper layers of the atmosphere with the naked eye, the electric and magnetic potentials of the field in the region of the northern auroral belt, as well as various types of auroral precipitation. It is assumed that the proposed approach will make it possible to significantly increase the efficiency of the study of parameters in the auroral oval region by specialists and scientists in the relevant fields. At the same time, the high internal and low external connectivity of the developed software modules allow them to be integrated into third-party applications of various profiles and purposes.

Evaluating the Accuracy and Utility of Large Language Models in Answering Common Contraception Questions [ID 2683633

INTRODUCTION: Traditional web resources that provide information on contraception produce varied results demanding user synthesis. However, direct answers provided by large language models (LLMs) can offer accessible contraception counseling. This study examines the efficacy of four LLMs, OpenAI's ChatGPT 4.0, OpenAI's ChatGPT 3.5, Google Bard, and Microsoft Bing, in answering common contraception questions. METHODS: Contraception questions and responses in a recent American Academy of Family Physicians (AAFP) review were used as reference text. We presented GPT-4.0, GPT-3.5, Bard, and Bing with six contraception questions from the AAFP text, ensuring no prior chat bias. Response formatting was standardized for analysis. Two ob-gyn physician reviewers (S.J. and A.A.), blinded to the source LLM, assessed responses via a 5-point Likert scale on the following criteria: response specificity, evidence basis, completeness, referrals to outside resources, and avoiding speaking in absolutes. Responses were analyzed using the Kruskal–Wallis test (SAS 9.4). RESULTS: The AAFP review scored highest in response specificity, evidence basis, and completeness. Large language models differed significantly on whether responses were evidence based (P<.0001), made referrals to outside resources (P<.001), or spoke in absolutes (P<.05). Notably, GPT-3.5 and Bard consistently provided referrals across all six questions, outperforming the AAFP text on this criteria. No significant differences were found across LLMs in response specificity or response completeness. CONCLUSION: Despite promising LLM-generated responses, the AAFP review outperformed LLMs in critical areas including evidence basis and completeness. Nonetheless, LLMs, especially GPT-3.5 and Bard, demonstrated strong potential as supplementary resources for reproductive health education.

Serverless Architectures and Their Influence on Web Development

In recent years, serverless computing has emerged as a transformative technology in the field of web development, offering a new paradigm that eliminates the need for server management and promotes a more efficient deployment model. This computing model enables developers to focus solely on writing code, while the underlying infrastructure scaling, provisioning, and maintenance is handled by cloud service providers. The key attraction of serverless computing lies in its promise to increase operational efficiency, reduce costs, and simplify scalability challenges inherent in traditional web development practices.

Dynamic switching of psychological test questions and design of scalable database: A study of web page data visualization and front-end interaction

As the need for efficient and user-friendly web applications in the field of psychological assessment continues to grow, traditional web development approaches are challenged to provide a dynamic and adaptive user experience. This study focuses on addressing these challenges through a comprehensive study that provides insight into the current state of psychological assessment web development, highlighting the shortcomings of traditional approaches, including the static limitations of Hyper Text Markup Language (HTML) and limited client-side scripting. The result is a user experience that lacks the responsiveness and flexibility that modern users expect. To tackle these problems, the intended solution suggested in this work combines a strong and scalable database design with a dynamic switching mechanism for psychological exam questions. Features-rich, aesthetically pleasing, and functioning client-server Web applications are created using technologies such as Servlets and Java Server Pages (JSP). The research contains practical case studies that demonstrate how Java-based user interface design can be successfully applied in real-world scenarios. The advantages of modularity, code reusability, and maintainability are demonstrated in these case studies. The study examines how selected technologies affect the performance, security, and accessibility of web UI, while also addressing load times, data integrity, and user inclusion issues. To summarize, this investigation underscores the crucial role of dynamic and scalable databases and Java-based technologies in enhancing the design of psychological assessment Web UIs.Developers can create web applications that exceed user expectations and provide superior user experience in the evolving digital landscape by using the proposed frameworks comprehensive toolkit.

Decentralization of Webhosting Using Blockchain

Abstract: This paper introduces a ground breaking approach to web hosting, leveraging the decentralized infrastructure of the Interplanetary File System (IPFS) and the secure framework of the Ethereum blockchain. In this novel model, Ethereum smart contracts govern the IPFS network and hosting services, ensuring robust management and reliability. IPFS serves as the backbone for data storage and website hosting, with storage miner nodes providing essential pinning services to maintain the longevity of stored content. Additionally, these nodes facilitate the Interplanetary Name Space (IPNS) service, enabling the creation and maintenance of mutable links to IPFS contents, thus enhancing accessibility and ease of updates. DNS TXT records are employed to seamlessly map domain names to IPNS addresses, seamlessly integrating decentralized hosting with traditional web infrastructure. To safeguard user privacy and data integrity, websites deploy advanced encryption algorithms, ensuring confidentiality in the decentralized environment. The proposed model represents a fusion of IPFS and blockchain networks, creating a robust platform for decentralized web hosting. Through experimental validation, the efficacy of this approach is demonstrated, showcasing its ability to surpass traditional web hosting models in terms of confidentiality, integrity, and availability. This innovative solution not only addresses existing challenges in web hosting but also heralds a new era of decentralized, secure, and accessible internet infrastructure

SoK: Analysis Techniques for WebAssembly

WebAssembly is a low-level bytecode language that enables high-level languages like C, C++, and Rust to be executed in the browser at near-native performance. In recent years, WebAssembly has gained widespread adoption and is now natively supported by all modern browsers. Despite its benefits, WebAssembly has introduced significant security challenges, primarily due to vulnerabilities inherited from memory-unsafe source languages. Moreover, the use of WebAssembly extends beyond traditional web applications to smart contracts on blockchain platforms, where vulnerabilities have led to significant financial losses. WebAssembly has also been used for malicious purposes, like cryptojacking, where website visitors’ hardware resources are used for crypto mining without their consent. To address these issues, several analysis techniques for WebAssembly binaries have been proposed. This paper presents a systematic review of these analysis techniques, focusing on vulnerability analysis, cryptojacking detection, and smart contract security. The analysis techniques are categorized into static, dynamic, and hybrid methods, evaluating their strengths and weaknesses based on quantitative data. Our findings reveal that static techniques are efficient but may struggle with complex binaries, while dynamic techniques offer better detection at the cost of increased overhead. Hybrid approaches, which merge the strengths of static and dynamic methods, are not extensively used in the literature and emerge as a promising direction for future research. Lastly, this paper identifies potential future research directions based on the state of the current literature.

ChatGPT vs. web search for patient questions: what does ChatGPT do better?

Chat generative pretrained transformer (ChatGPT) has the potential to significantly impact how patients acquire medical information online. Here, we characterize the readability and appropriateness of ChatGPT responses to a range of patient questions compared to results from traditional web searches. Patient questions related to the published Clinical Practice Guidelines by the American Academy of Otolaryngology-Head and Neck Surgery were sourced from existing online posts. Questions were categorized using a modified Rothwell classification system into (1) fact, (2) policy, and (3) diagnosis and recommendations. These were queried using ChatGPT and traditional web search. All results were evaluated on readability (Flesch Reading Ease and Flesch-Kinkaid Grade Level) and understandability (Patient Education Materials Assessment Tool). Accuracy was assessed by two blinded clinical evaluators using a three-point ordinal scale. 54 questions were organized into fact (37.0%), policy (37.0%), and diagnosis (25.8%). The average readability for ChatGPT responses was lower than traditional web search (FRE: 42.3 ± 13.1 vs. 55.6 ± 10.5, p < 0.001), while the PEMAT understandability was equivalent (93.8% vs. 93.5%, p = 0.17). ChatGPT scored higher than web search for questions the 'Diagnosis' category (p < 0.01); there was no difference in questions categorized as 'Fact' (p = 0.15) or 'Policy' (p = 0.22). Additional prompting improved ChatGPT response readability (FRE 55.6 ± 13.6, p < 0.01). ChatGPT outperforms web search in answering patient questions related to symptom-based diagnoses and is equivalent in providing medical facts and established policy. Appropriate prompting can further improve readability while maintaining accuracy. Further patient education is needed to relay the benefits and limitations of this technology as a source of medial information.

Enhancing Web Application Security: A Deep Learning and NLP-based Approach for Accurate Attack Detection

Abstract— Nowadays, web attacks have become more complicated, leading to the difficulty of traditional web application firewalls (WAFs) in recognizing those threats, especially when dealing with new attacks. Hence, machine learning/deep learning (ML/DL) approaches have been applied to the field of web attack detection with proven success. However, most existing ML/DL-based web attack detectors focus on a specific type of attack due to the difference in the payload of various attacks, which sets a border to the capability of those solutions in detecting new attack types. In this paper, we propose a novel DL-based solution for web attack detection, named DL-WAD, leveraging deep learning and natural language processing techniques. Moreover, DL-WAD is designed with a data preprocessing mechanism aimed at differentiating between regular web requests and malicious ones that carry attack payloads encompassing multiple types of web attacks. The experiment results indicate the effectiveness of our solution in protecting the target web services from a wide range of attacks with high accuracy.

Worship Rights and Gender Parity: Analyzing the Sabarimala Issue in India

This research paper critically examines the complex interplay between the right to worship and gender parity, with a specific focus on the Sabarimala issue in India. The study investigates the dual aspects of Sabarimala, considering it both as a sacred tradition and a locus of constitutional rights. Through an analysis of the historical and cultural foundations of the Sabarimala pilgrimage, the research explores the tension between religious customs and the constitutional imperative of gender equality. The judicial pronouncement, particularly the Supreme Court's verdict allowing the entry of women of all ages, is scrutinized to understand its implications on the broader discourse of religious rights and gender justice. Additionally, the paper investigates the post-judgment scenario in Kerala, examining how the legal transformation has affected societal attitudes, religious practices, and the overall dynamics at the pilgrimage site. By navigating the intricate web of tradition, constitutional principles, and post-judgment realities, this research contributes nuanced insights to the ongoing global dialogue on worship rights and gender parity.

Housing development, land values and the decentred state: Traditions and dilemmas in House of Commons planning debates

ABSTRACT The paper examines the narratives and traditions that converged in the debates that raged in the House of Commons in response to the UK government’s controversial proposals for planning reform in 2020. Using decentred theory, it is argued that planning is essentially decentred in that it has no essence, no fixed core beyond a general concern with the relationships between town and country, central and local government, economic development and the environment, private property and community, individual freedom and state power. This means that English planning comprises a web of contradictory traditions that can be articulated in service of various agendas. The analysis explores how the traditions in planning were interpreted through and reframed by various ideological traditions in the Conservative Party to legitimise different arguments concerning the desirability, or otherwise, of housebuilding and how planning should govern new housing development.

EXPLORING THE EFFICACY OF ARTIFICIAL INTELLIGENCE IN DELIVERING HOSPICE INFORMATION

Abstract Background Artificial Intelligence Chatbots (AIC) are swiftly gaining popularity due to their language model capability to address user queries by analyzing extensive amounts of available data and generating human-like responses. Objective: To analyze the accuracy of AIC in responding to inquiries related to hospice services and benefits. Additionally, the goal is to assess the user-friendliness of AIC in comparison to traditional web search engines. Methods AICs, namely ChatGPT and Bard, were subjected to testing through a series of questions and scenarios pertinent to hospice services (such as its definition, eligibility criteria, types of provided services, and specific care scenarios). Recorded responses from the AICs were subsequently evaluated for accuracy and quality by experts in geriatric palliative care. Results Both ChatGPT and Bard provided mostly accurate responses to fundamental questions and uncomplicated scenarios regarding hospice. These encompassed explanations about prognosis, interdisciplinary teams, and basic services offered. While ChatGPT did not furnish articles or source references, it did offer occasional medical advice. On the other hand, Bard issued medical information warnings and occasionally included visual aids like pictures, diagrams, and website links. When faced with the same set of questions, conventional web search engines often supplied links to webpages that did not invariably contain specific answers to the queries. Conclusions The AICs can deliver predominantly accurate, generic information about hospice in a conversational and comprehensible manner. Future research could delve into how AICs would respond to more personalized and specific inquiries that could be posed by patients or caregivers.

Numerical investigation of steel beams with web openings obtained from topology optimisation

The use of web openings in I-section beams has become increasingly common in recent years, and these elements can be observed in various civil engineering applications. This design approach results in an improved weight-to-stiffness ratio in steel beams, enabling their use over longer spans without a significant increase in material cost and deflections due to self-weight. It also avoids the cutting of holes in inappropriate locations for electrical, hydraulic, and air conditioning installations. Steel beams fabricated with web openings also represent an important solution when height constraints are imposed on multi-story buildings due to design regulations and economic considerations. It is recognised that the use of the traditional web opening shapes - namely, circular, rectangular, and hexagonal - in civil structures can lead to issues associated with high stress concentration. The presence of these web openings can induce local instability or yielding due to inadequate shear force transfer across the openings, allowing plastic hinge formations, also known as Vierendeel mechanism, for instance. In this sense, researchers have investigated novel shapes to mitigate the impacts of the web openings in both structural and economic terms. In this sense, this work has been developed aiming to evaluate the structural performance of I-section beams obtained using structural optimisation, for a reference distributed load and different boundary conditions, compared with the cellular beams. An evaluation of the structural potential of the obtained topologies has been performed by linear elastic, buckling and complete nonlinear analyses. Results were obtained in terms of stresses, displacements, and ultimate loads for all investigated cases. It was found that when compared to a cellular beam, the optimised beams increased the ultimate resistance with superior stiffness resulting in lower displacements and presented a more adequate stress distribution with lower stress concentration. However, in some cases a poor structural performance was observed due to large zones with holes obtained from the optimisation process. Based on these results and on the work of Tsavdaridis et al., authors proposed a configuration for the openings, and its structural performance proved it to be a promising solution to be employed on beams with web openings, especially when the expected failure mode is lateral-torsional buckling. A parametric study was conducted to assess the efficiency of the proposed configuration for different steel profiles and span lengths; results indicated equivalent or superior load capacity when compared to the reference cellular beam. The configuration suggested by the authors can be easily fabricated, and, considering the constant patterns along the length, finding an expression to determine its design load is possible, like what is usually done for other shapes (circular, hexagonal).

Blockchain Based Decentralized Web Hosting System

Abstract: In today’s digital era, the internet heavily depends on a centralized framework where powerful servers support content on well-known platforms such as Facebook and Twitter. Although this centralization is proficient in content delivery, it comes with significant drawbacks, including a single point of failure and vulnerability to censorship. The need for a decentralized web hosting structure is growing due to its promise of content accessibility regardless of a user’s geographical location, while still maintaining the speed and reliability of conventional web services. Currently, the internet’s structure is defined by centralization, introducing risks related to cyber-attacks and service disturbances. For example, even a brief disruption to a large platform like Facebook can leave millions without internet access. Additionally, large corporations and government bodies possess significant control over the internet, enabling them to alter and censor content. To confront these problems, it becomes essential to develop a decentralized web structure that is publicly owned. This study delves into the issues arising from the centralized internet and investigates potential solutions by utilizing blockchain technology to decentralize web structure, subsequently improving traditional web services and fortifying the internet’s robustness and accessibility

Research on the Identification of a Winter Olympic Multi-Intent Chinese Problem Based on Multi-Model Fusion

Aiming at addressing the inability of traditional web technologies to effectively respond to Winter-Olympics-related user questions containing multiple intentions, this paper explores a multi-model fusion-based multi-intention recognition model BCNBLMATT to solve this problem. The model is proposed to address the characteristics of complex semantics, strong contextual relevance, and a large number of informative features of the Chinese problem text related to the Winter Olympics, as well as the limitations of the traditional word vector model, such as insufficient expression in the textual representation and the relative concern mechanism of feature expression. The BCNBLMATT model first obtains a comprehensive feature vector representation of the problem text through BERT. Then, a multi-scale text convolutional neural network model and a BiLSTM-Multi-heads attention model (a joint model combining a bidirectional long- and short-term attention network with a multi-head attention mechanism) are used to capture local features at more scales and contextually critical information features at more levels. Finally, the two obtained kinds of features are concatenated and fused to obtain richer and more comprehensive information about the problem text features, which improves the model’s performance in the multi-attention recognition task. Comparative experiments on the Winter Olympics Chinese question dataset and the MixATIS question dataset show that the BCNBLMATT model significantly improves the three metrics of macro-averaged precision, macro-averaged recall, and macro-averaged F1 value and exhibits better generalization. This study provides an effective solution to the multi-intent recognition task for Winter Olympic problems, overcomes the limitations of traditional models, and provides new ideas for improving the performance of multi-intent recognition.

Selling myself: Anthropomorphic products in electronic commerce

What if a product was able to sell itself? Suppose a product could display itself in the form of an animated caricature that walked, talked, and described itself to potential buyers. Such a display may trigger anthropomorphism, the automatic process of attributing human characteristics to a non-human object, but past research suggests that the nature of the product may influence this process. We argue that displaying a product as an animated caricature is more likely to trigger anthropomorphism when the underlying product itself has some human-like features than when the product does not (e.g., appearance, movement, speech, behavior). We tested this form of presentation with a laptop, a camera, and a TV, theorizing that the effects would be stronger for the laptop than either the TV or the camera because the computer has more human-like features. Our results show that participants bid 20% more for a computer when it was presented in the form of an animated caricature compared to when it was presented on a traditional Web page, and as theorized, there were no differences for the TV or camera when presented in this form. Electroencephalogram (EEG) results show that participants engaged in similar cognitive activities for the computer displayed on Web pages and as an animated caricature. However, there was a significant difference in results between the two display formats for the camera and TV, which we interpret as the cognitive conflict that occurs when the animated product display does not fit the underlying nature of the product.

Li-Ion Battery Electrode Manufacturing Control System in Winding Process: Tension Control in Industrial Complex Roll-to-Roll Winding Machine Via SMC-FLC Hybrid Control Method

Abstract This paper introduces a new control method for web tension control on a complex roll-to-roll winding machine used in battery production. A traditional web tension control method cannot perform well enough under high winding speed: the parameter tuning process is time-consuming, the disturbance rejection performance is not satisfying, and the control performance is not stable. A hybrid control method is proposed, and it is easy to be implemented on common programming platform for commercial winding machines with an easy tuning process, while providing superior control performance to the traditional control method. The system modeling used in the control method is much simpler than the modeling in most of the tension control researches, providing better feasibility for industrial application.