Web System Research Articles

Percutaneous coronary intervention of in-stent restenosis: A three-arm analysis from SWEDEHEART

Abstract Background During the last decades, there have been substantial improvements in treatment techniques for percutaneous coronary intervention (PCI). Yet, in-stent restenosis (ISR) continues to pose significant challenges as they account for 10% of all PCI cases and are associated with worse outcome compared to de-novo lesions. When assessing ISR with PCI, balloon angioplasty with drug-coated balloons (DCB) is frequently used. Purpose Despite frequent use of DCB, there is a lack of long-term data ensuring the safety of DCB for ISR as no randomized trial has extended beyond a 3-year follow-up. We aimed to study the long-term outcome and conducted a nationwide three-arm investigation on the outcome of ISR, comparing DCB with drug-eluting stents (DES) or plain old balloon angioplasty (POBA) within a 5-year follow-up. Methods We conducted a nationwide analysis using the SWEDEHEART (Swedish Web System for Enhancement of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies) registry. The SWEDEHEART registry was used to include any ISR undergoing coronary angiography between June 11, 2013, and December 31, 2020. Target lesion revascularization (TLR) was the primary outcome. Secondary outcomes included all-cause mortality, myocardial infarction, and any PCI. The outcomes were analysed using a multivariable Cox regression model. Results A total of 9304 segments from 7987 patients were eligible. Compared to POBA, the use of DCB was associated with lower rates of TLR, hazard ratio (HR) 0.62 (95% confidence interval [CI]: 0.50-0.78), all-cause mortality, HR 0.60 (95% CI: 0.50-0.72), and any PCI, HR 0.78 (95% CI: 0.66-0.93). No difference was observed for myocardial infarction. Compared to DES, the use of DCB was associated with higher rates of TLR, HR 1.24 (95% CI: 1.08-1.42). No difference was observed for all-cause mortality, cardiovascular mortality, myocardial infarction, or any PCI. Conclusions In this nationwide analysis including any ISR undergoing PCI, the use of DCB showed superior outcomes compared to POBA within 5 years but higher rates of repeat revascularizations compared to DES. While DES demonstrated lower TLR rates than DCB, the lack of mortality differences indicates that DCB is a viable option, particularly for patients where DES might not be suitable, but that DES should be considered as the first line strategy.Table 1.5-year outcomeFigure 1.Kaplan-Meier curves

Evaluating the effectiveness of web-based oral health education on enhancing mothers’ awareness: a semi-experimental internet-based intervention

ObjectivesThis study examined the impact of web-based education on enhancing mothers’ awareness of oral health care for children aged 9 and 12 years. It focused on the crucial role of mothers in educating about oral health to prevent dental diseases and reduce long-term healthcare costs.MethodsMothers were divided into three groups: control, intervention with a web system, and intervention with a brochure. Over one month, their knowledge about their children’s oral health was assessed before and after the intervention.ResultsData were analyzed using parametric t-tests and non-parametric Mann-Whitney U tests. The findings indicated a significant increase in parental awareness in both intervention groups.ConclusionIt is recommended that parent education be done using web-based systems or mobile apps, which are better choices due to greater accessibility and interactivity.

Evaluation of 3-year tuberculosis external quality assessment results of public health laboratories.

Background We aimed to evaluate the 3-year participation status of tuberculosis (TB) laboratories in public health laboratories (PHL) tuberculosis external quality assessment (EQA) and EQA results. Method During 2018-2020, PHLs participated in the EQA programme organized annually by the National Tuberculosis Reference Laboratory (NTRL). Five kinds of EQA samples were sent to the participating laboratories on three parameters, including microscopy, culture and phenotypic first-line drug susceptibility testing and they were asked to perform according to the standard protocol. The results were taken over by the Tuberculosis Laboratories Surveillance Network (TULSA) web system and analysed. Results A total of 24 PHLs participated in the EQA in 2018; 30 in 2019 and 23 in 2020. In terms of sensitivity, specificity, accuracy and reproducibility in microscopy, respectively, in 2018, 20 of the laboratories were 100%, 4 of them 80%, and in culture 16 of them were 100% and 2 of them 80%; in 2019, 28 of them were 100%, 2 of them 80%, and in culture 11 of them were 100%, 6 of them 80%, 1 of them 60%; in 2020, 20 of them were 100%, 3 of them 80%, and in culture 13 of them were 100% and 3 of them 80%. Conclusion It is beneficial for laboratories working on TB to participate in EQA in terms of evaluating the accuracy and reliability of the method used.

Sistema de Recomendación de Cursos en Línea basado en el Perfil de Competencias TIC del Docente

Digital transformation in education has created the need to train teachers and improve their digital competencies. However, training processes are often ineffective due to the lack of personalization in the proposals and the variety in teacher profiles. Given this, this article addresses the development of a web tool designed to diagnose teachers’ digital competencies and provide personalized recommendations for MOOCs to support the development of their skills. To achieve this, a system that uses Natural Language Processing (NLP) techniques and a content-based recommendation model is proposed. Course data is obtained through web scraping and processed with NLP techniques, using an advanced language model (BERT) to generate vector representations of the courses and competencies. The web system allows teachers to self-assess their competencies, visualize the results, and receive personalized recommendations for MOOCs. The implementation of this system has proven effective in identifying teachers’ areas for improvement and suggesting relevant courses for their professional development. The results suggest that the use of this system can be an effective solution for training teachers in digital competencies.

Optimization of Data Management through a Web System based on Business Intelligence and Agile Kanban Methodology

The collection of information through a questionnaire for planning purposes played an important role in defining the requirements of the web system, functioning as a fundamental basis for the next step in the software development phase. The application of the Kanban way of thinking has proven to be effective in managing work, supported by greater openness during the system creation phase. The surveys and interviews carried out show that the initiative is important and necessary to improve decision-making and processes. The incorporation of Kanban principles is based on an exhaustive analysis using tools such as PHP, Bootstrap and MySQL to facilitate the process and achieve maximum efficiency. Through the web-based system, it is possible to centralize information, allowing its access and management in real time. Business intelligence is also used to perform in-depth analysis, helping to identify patterns and potential opportunities for improvement. It was considered appropriate to choose the Kanban methodology due to its collaborative and incremental approach, ideal for adapting to change and providing constant value. The results confirm the solidity of our methodology and the relevance of the choices made in the development of this web application based on Business Intelligence and Agile Kanban Methodology.

Improving reuse during the development process for web systems

Software reuse has emerged as a crucial practice in the software industry, offering significant benefits in time-to-market, and resources management. This is particularly pertinent in web systems development, where the integration of diverse technologies and the varied backgrounds of technical teams pose substantial challenges. The rapid expansion of web systems underscores the urgent need to adopt best practices and methodologies for web system reuse to streamline the development process, reducing effort, cost, and time. This paper aims to identify the key challenges of web system reuse in the context of small and medium-sized software companies in Egypt and Saudi Arabia. Using qualitative research methods, including interviews, focus groups, and participant observations, an empirical study was conducted to examine current reuse practices and understand the root causes of common challenges. Based on the results of the empirical study, a systematic approach was developed to enhance web system reuse during the development process in the context of small and medium-sized software companies in Egypt and Saudi Arabia. The proposed approach addresses critical gaps in current practices, offering practical guidelines to improve efficiency, reduce development time, and enhance overall software quality. This research contributes to the broader discourse on software reuse by providing context-specific insights and adaptable solutions that are relevant to similar markets worldwide.

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.

Empowering decentralized identity systems for Web 3.0 in complex spherical fuzzy knowledge

The Web 3.0 network system, the next generation of the world wide web, incorporates new technologies and algorithms to enhance accessibility, decentralization, and security, mimicking human comprehension and enabling more personalized user interactions. The key component of this environment is decentralized identity management (DIM), embracing an identity and access management strategy that empowers computing devices and individuals to manage their digital personas. Aggregation operators (AOs) are valuable techniques that facilitate combining and summarizing a finite set of imprecise data. It is imperative to employ such operators to effectively address multicriteria decision-making (MCDM) issues. Yager operators have a significant extent of adaptability in managing operational environments and exhibit excellent effectiveness in addressing decision-making (DM) uncertainties. The complex spherical fuzzy (CSF) model is more effective in capturing and reflecting the known unpredictability in a DM application. This research endeavors to enhance the DM scenario of the Web 3.0 environment using Yager aggregation operators within the CSF environment. We present two innovative aggregation operators, namely complex spherical fuzzy Yager-ordered weighted averaging (CSFYOWA) and complex spherical fuzzy Yager-ordered weighted geometric (CSFYOWG) operators. We elucidate some structural characteristics of these operators and come up with an updated score function to rectify the drawbacks of the existing score function in the CSF framework. By utilizing newly proposed operators under CSF knowledge, we develop an algorithm for MCDM problems. In addition, we adeptly employ these strategies to handle the MCDM scenario, aiming to identify the optimal approach for ensuring the privacy of digital identity or data in the evolving landscape of the Web 3.0 era. Moreover, we undertake a comparative study to highlight the veracity and proficiency of the proposed techniques compared to the previously designed approaches.

It’s time to celebrate! Linking genetic resources to the Mexican National Biological Collections custodied by the Institute of Biology of the National Autonomous University of Mexico

The Instituto de Biología of the Universidad Nacional Autónoma de México (IBUNAM) celebrates 95 years as a leading institution on biodiversity research. Besides developing frontier research, training of human resources, and public science communication, IBUNAM houses 10 National Zoological Collections and the National Herbarium of Mexico (MEXU). The specimens deposited in these collections are the foundation of numerous biological studies, from which ample genetic resources have been generated. Here we present an initial effort to link the specimens deposited at the National Biological Collections housed at IBUNAM to their public genetic resources, using MEXU’s Collection of Types of Vascular Plants as proof of concept. First, a list of the type specimens was retrieved from IBdata, the web system for consulting the records of the biological collections housed at IBUNAM. Then, the interface Entrez Programming Utilities of GenBank was used to search for the available genetic resources associated with the type specimens. New fields were incorporated into IBdata to facilitate access to the identified genetic resources. Future initiatives should promote access to the public metadata (e.g., molecular, morphological) associated to specimens of the biological collections housed at IBUNAM.

AI-Based Learning Model for Sociocybernetic Systems in Web of Things: An Efficient and Accurate Decision-Making Procedure

AI-Based Learning Model for Sociocybernetic Systems in Web of Things: An Efficient and Accurate Decision-Making Procedure

Magazine Identification on SS1-V1 Assault Rifle using Web-based HX711 Load Cell Sensor

The SS1-V1 is an assault rifle model equipped with a magazine as one of its main components. The magazine plays a crucial role in storing and loading ammunition. However, magazines must be stored separately from the weapon as their integrated storage can pose a risk to a country’s security. Therefore, this research proposes a web-based system capable of identifying the presence of magazines in weapons in real-time. This system is supported by various hardware components, including a load cell sensor, HX711 sensor module, Arduino UNO R3, and an Ethernet shield for network connectivity. In addition, API is used for data management, which is then stored in the database. The results of this research indicate that the average response time for each rack within a cabinet is between 2.7s to 3.3s, while for racks serving as slaves, it ranges from 14.16s to 15.01s. Based on the results of the weight-based weapon identification testing, there is a weight difference of 0.1kg to 0.2kg. These results state that all tests were successfully identified by the web system according to the conditions of the weapons on the rack.

Web system in the management of Preprofessional internship in students at the Private University of Trujillo [Sistema web en la gestión de Prácticas Pre Profesionales en los estudiantes de la Universidad Privada de Trujillo

The objective of this study is to improve the management of preprofessional internships for students at the Private University of Trujillo. The Directorate of Professional Development and Job Board, in charge of connecting students with companies for their pre-professional internships, carries out a series of manual processes for this purpose and disseminates them through printed publications in the university's wall newspapers, where on many occasions they go unnoticed. In addition to this, students do not necessarily have classes scheduled every day of the week, losing the opportunity to apply for a job offer that has been recently published and whose time for submitting the file is in a short period of time. As these are printed publications, there is minimal risk of them being lost, damaged or intentionally tampered with, without the management being aware of it. With the arrival of the COVID-19 pandemic and everything that this entailed, since the current government declared a state of national emergency, the Directorate saw a decrease in the population of students eligible for pre-professional internships. The study corresponds to the cross-sectional correlational type, with a variant population for each identified indicator. For statistical analysis, the SPSS Static 21 program was used and the Kolgomorov-Smirnov normality test, Student's t test and Wilcoxon for related samples were used to test the hypotheses. The results showed that the time spent searching for information before the implementation of the web system is greater than the time spent searching after the implementation of the web system (p=0.00). The Rational Unified Process software development methodology was used, supported by the unified modeling language (UML). On the other hand, the time to register pre-professional internship advertisements before the implementation of the web system is greater than the time to search after the implementation of the web system (p=0.00). Also the degree of user satisfaction before the implementation of the web system is lower than the degree of user satisfaction after the implementation of the web system (p=0.00). It concludes with a decrease of 83.02% in the time spent searching for ads; a 57.40% decrease in the time to publish ads, and a 45.51% increase in the level of user satisfaction. All this leads to the conclusion that the implementation of a web system improves the management of pre-professional internships of students at the Private University of Trujillo.

Personalized and adaptive e-learning systems for semantic Web: a systematic review and roadmap

Purpose The purpose of this study is to present a systematic and comprehensive review of personalized, adaptive and semantic e-learning systems. Design/methodology/approach Preferred reporting items of systematic reviews and meta-analyses guidelines have been used for a thorough insight into associated aspects of e-learning that complement the e-learning pedagogies and processes. The aspects of e-learning systems have been reviewed comprehensively such as personalization and adaptivity, e-learning and semantics, learner profiling and learner categorization, which are handy in intelligent content recommendations for learners. Findings The adoption of semantic Web based technologies would complement the learner’s performance in terms of learning outcomes. Research limitations/implications The evaluation of the proposed framework depends upon the yearly batch of learners and recording is a cumbersome/tedious process. Social implications E-Learning systems may have diverse and positive impact on society including democratized learning and inclusivity regardless of socio-economic or geographic status. Originality/value A preliminary framework of an ontology-based e-learning system has been proposed at a modular level of granularity for implementation, along with evaluation metrics followed by a future roadmap.

Modeling and supporting adaptive Complex Data-Intensive Web Systems via XML and the O-O paradigm: The OO-XAHM model

The data model is a critical component of an Adaptive Web System (AWS). The major goals of such a data model are describing the application domain of the AWS and capturing data about the user in order to support the “adaptation effect”. There have been many proposals for data models, principally based on knowledge representation, machine learning, logic and reasoning, and, recently, ontologies. These models are focused on the implementation of the core layer of AWS, that is realizing the adaptation of contents and presentations of the system, but sometimes they are poor with respect to the application domain design. In this paper, we present an extension of the state-of-the-art XML Adaptive Hypermedia Model (XAHM), Object-Oriented XAHM (OO-XAHM) that supports the application domain modeling using an object-oriented approach. We also provide the formal definition of the model, its description via Unified Modeling Language (UML), and its implementation using XML Schema. Finally, we provide a complete case study that focuses the attention on the well-known Italian archaeological site Pompeii.

Advanced hybrid malware identification framework for the Internet of Medical Things, driven by deep learning

AbstractThe Internet of Things (IoT) effortlessly enables communication between items on the World Wide Web and other systems. This extensive use of IoTs has created new services and automation in numerous industries, enhancing the standard of living, especially in healthcare. Internet of Medical Things (IoMT) adoption has been beneficial during pandemic conditions by enabling remote patient monitoring and therapy. Nevertheless, the excessive use of IoMT has raised security concerns as it can compromise critical data. This breach in security can result in an inaccurate diagnosis or violate privacy. This research presents a novel approach to hybrid deep learning‐based detection of malware solutions for the IoT. This study uses RNN‐Bi‐LSTM to detect and extract significant features related to an already existing dataset. The proposed model exhibits a detection accuracy of 98.38% when evaluated using these existing datasets. Statistical tests like Mathew co‐relation and Log Loss also indicated reliability of proposed framework. The distinguished feature of our framework is its ability to combine complex deep learning models for IoMT security, which is of economic and scientific importance. It certainly offers a reliable solution for healthcare applications that rely on real‐time functionality and dependency on IoMT systems.

Optimization of diagnostic processes using decision trees in ECG data analysis - lets web system analysis engine

The article presents the capabilities of the LETS Web system, which uses Internet of Things (IoT) technology to analyze medical data to optimize diagnostic processes. The article focuses on implementing decision tree algorithms that analyze electrocardiogram (ECG) data to identify cardiac conditions. The study used three variants of decision trees that differed in structure and ECG parameters. Each variant was tested for its ability to accurately classify cardiac health conditions ranging from simple arrhythmias to complex arrhythmic changes. The study showed that modifications to the structure of the decision trees significantly affected their effectiveness. The most advanced variant of the tree, using multivariate data analysis, showed the highest efficiency in diagnosing complex conditions. The effectiveness of the different variants of decision trees varied, confirming the importance of selecting the suitable diagnostic model for the specifics of the data and clinical goals.

Web application of an integrated simulation for aquatic environment assessment in coastal and estuarine areas

This paper introduces the web application-type Graphical User Interface that has been developed and also presents an application example. The introduced simulator conducts hydrodynamics and ecosystems in coastal and estuarine areas. It consists of (1) a hydrodynamic model that can simulate the current velocity, water temperature, salinity, and water level; (2) an ecosystem model that can simulate dissolved oxygen, phytoplankton, zooplankton, nutrients, fish, and bivalves; and (3) a benthic ecosystem model that can simulate elution. Web GUI is the first web system of aquatic environment simulation system that can both prepare calculation conditions and visualize them. Another significant feature is that it requires no installation and can be easily used by anyone to perform calculations. Thus, the proposed system helps fill the expertise gap experienced by potential users of the model. The use of standard systems, such as those discussed in this study, will facilitate evidence-based policymaking (EBPM).

Causal inference of server- and client-side code smells in web apps evolution

ContextCode smells (CS) are symptoms of poor design and implementation choices that may lead to increased defect incidence, decreased code comprehension, and longer times to release. Web applications and systems are seldom studied, probably due to the heterogeneity of platforms (server and client-side) and languages, and to study web code smells, we need to consider CS covering that diversity. Furthermore, the literature provides little evidence for the claim that CS are a symptom of poor design, leading to future problems in web apps.ObjectiveTo study the quantitative evolution and inner relationship of CS in web apps on the server- and client-sides, and their impact on maintainability and app time-to-release (TTR).MethodWe collected and analyzed 18 server-side, and 12 client-side code smells, aka web smells, from consecutive official releases of 12 PHP typical web apps, i.e., with server- and client-code in the same code base, summing 811 releases. Additionally, we collected metrics, maintenance issues, reported bugs, and release dates. We used several methodologies to devise causality relationships among the considered irregular time series, such as Granger-causality and Information Transfer Entropy(TE) with CS from previous one to four releases (lag 1 to 4).ResultsThe CS typically evolve the same way inside their group and its possible to analyze them as groups. The CS group trends are: Server, slowly decreasing; Client-side embed, decreasing and JavaScript,increasing. Studying the relationship between CS groups we found that the "lack of code quality", measured with CS density proxies, propagates from client code to server code and JavaScript in half of the applications. We found causality relationships between CS and issues. We also found causality from CS groups to bugs in Lag 1, decreasing in the subsequent lags. The values are 15% (lag1), 10% (lag2), and then decrease. The group of client-side embed CS still impacts up to 3 releases before. In group analysis, server-side CS and JavaScript contribute more to bugs. There are causality relationships from individual CS to TTR on lag 1, decreasing on lag 2, and from all CS groups to TTR in lag1, decreasing in the other lags, except for client CS.ConclusionsThere is statistical inference between CS groups. There is also evidence of statistical inference from the CS to web applications’ issues, bugs, and TTR. Client and server-side CS contribute globally to the quality of web applications, this contribution is low, but significant. Depending on the outcome variable (issues, bugs, time-to-release), the contribution quantity from CS is between 10% and 20%.

OFL-W3: A One-Shot Federated Learning System on Web 3.0

Federated Learning (FL) addresses the challenges posed by data silos, which arise from privacy, security regulations, and ownership concerns. Despite these barriers, FL enables these isolated data repositories to participate in collaborative learning without compromising privacy or security. Concurrently, the advancement of blockchain technology and decentralized applications (DApps) within Web 3.0 heralds a new era of transformative possibilities in web development. As such, incorporating FL into Web 3.0 paves the path for overcoming the limitations of data silos through collaborative learning. However, given the transaction speed constraints of core blockchains such as Ethereum (ETH) and the latency in smart contracts, employing one-shot FL, which minimizes client-server interactions in traditional FL to a single exchange, is considered more apt for Web 3.0 environments. This paper presents a practical one-shot FL system for Web 3.0, termed OFL-W3. OFL-W3 capitalizes on blockchain technology by utilizing smart contracts for managing transactions. Meanwhile, OFL-W3 utilizes the Inter-Planetary File System (IPFS) coupled with Flask communication, to facilitate backend server operations to use existing one-shot FL algorithms. With the integration of the incentive mechanism, OFL-W3 showcases an effective implementation of one-shot FL on Web 3.0, offering valuable insights and future directions for AI combined with Web 3.0 studies.

Rancang Bangun Aplikasi Penerimaan Siswa Baru di SMA Gerardus Mayella Kalembu Weri

Gerardus Mayella Kalembu Weri High School is a school that operates in the field of educational institutions which currently still has problems with the process of admitting new students requiring quite a long time in filling out paper forms and student data still using the main book as a medium for storing student data. Then the committee will input or copy student data on the computer, which is a problem regarding new student registration which is still manual, which of course keeps the committee busy in terms of new student registration. And the data could be lost because it is still in the form of sheets of paper. System This can be more efficient in terms of costs, energy and time, so that it is effective in achieving goals. In accessing the current system, we sometimes experience obstacles in implementing information, such as accepting new students. For this reason, a special information system is needed to overcome this problem, namely an online registration information system. This system was developed using web engineering methods. The method is used to create a web-based application system using engineering science, management principles and a systematic approach so that high quality web systems and applications can be obtained.