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The increased use of data analytics and machine learning algorithms enables better prediction of land values based on various factors such as soil quality, climate, and historical performance by processing large datasets. The primary objective of this paper is to underscore the significance of addressing the topic concerning the evaluation process of agricultural land. Concurrently, it seeks to accentuate the interconnectedness across various domains of study, encompassing strategic management, agronomy, ecology, agricultural practices, and agricultural policies. Advanced technologies such as satellite imagery, remote sensing, and Geographic Information System (GIS) tools are being integrated for more accurate and efficient land valuation. In the present study, a retrospective and descriptive bibliometric analysis using the Web of Science platform was conducted, identifying 1,630 papers on the "valuation of agricultural land" from the year 2000 to 2023, which were then analyzed with VOSviewer and Microsoft Excel to generate visual representations of keyword frequency over time. The paper reveals a notable increase in published articles, emphasizing their relevance due to their economic and financial impact, with a focus on environmental sciences and economics, confirming the topic's importance and its association with ecosystem services, land use change, and willingness to pay. The results demonstrate that this theme is increasingly addressed by researchers. [ABSTRACT FROM AUTHOR]

The ParlaMint project, a CLARIN flagship initiative, seeks to standardize the representation of parliamentary data across diverse languages and regions. Version 3.0 of ParlaMint encompasses corpora from 26 European countries and autonomous regions, available for download and search under the CC-BY license. These corpora adhere to a common XML encoding schema, ensuring interoperability. This study evaluates the feasibility of applying the ParlaMint schema to the proceedings of the Parliament of the Republic of South Africa. Through the conversion of a randomly selected parliamentary session, we scrutinize how various elements are modelled, delineating the steps required to initiate a comprehensive encoding endeavour. The experiment starts with data retrieval by downloading Hansard records from the South African Parliament website. An English session was selected to streamline processing for non-South African researchers. The original format consisted of session headers, metadata, introductory messages, and debate records. Speeches were identified by uppercase headers and segmented into paragraphs. Transcript conversion entailed extracting data from the PDF, eliminating technical elements, and ensuring continuity of utterances. Speaker names and functionswere identified, and the sessionwas transformed into ParlaMint-compliant TEI XML format. Meta-comments, including applause, laughter, and interruptions, were categorized based on typical phrases. Quotations, marked with indentation in the original transcript, were manually encoded as TEI elements. Foreign-language fragments were treated as gaps, with English translations provided. Multiparagraph foreign utterances were encoded paragraph by paragraph. Speaker metadata was stored in separate XML files, listing organizations and individual speakers. Speaker names and roles were converted into XML IDs, and web pages were linked for additional information. Speaker type was designated based on metadata, distinguishing between chairs, guests, and regular speakers. The encoded session comprised 95 utterances, with varying distributions among speakers. The proposed conversion process serves as a starting point for the larger endeavour of encoding South African parliamentary data in the ParlaMint schema. While not exhaustive, this study lays the groundwork for expanding the ParlaMint dataset to include African parliamentary records. [ABSTRACT FROM AUTHOR]

Accurately assigning the document type of review articles in citation index databases like Web of Science(WoS) and Scopus is important. This study aims to investigate the document type assignation of review articles in Web of Science, Scopus and Publisher's websites on a large scale. 27,616 papers from 160 journals from 10 review journal series indexed in SCI are analyzed. The document types of these papers labeled on journals' websites, and assigned by WoS and Scopus are retrieved and compared to determine the assigning accuracy and identify the possible reasons for wrongly assigning. For the document type labeled on the website, we further differentiate them into explicit review and implicit review based on whether the website directly indicates it is a review or not. Overall, WoS and Scopus performed similarly, with an average precision of about 99% and recall of about 80%. However, there were some differences between WoS and Scopus across different journal series and within the same journal series. The assigning accuracy of WoS and Scopus for implicit reviews dropped significantly, especially for Scopus. The document types we used as the gold standard were based on the journal websites' labeling which were not manually validated one by one. We only studied the labeling performance for review articles published during 2017-2018 in review journals. Whether this conclusion can be extended to review articles published in non-review journals and most current situation is not very clear. This study provides a reference for the accuracy of document type assigning of review articles in WoS and Scopus, and the identified pattern for assigning implicit reviews may be helpful to better labeling on websites, WoS and Scopus. This study investigated the assigning accuracy of document type of reviews and identified the some patterns of wrong assignments. [ABSTRACT FROM AUTHOR]

Purpose: This systematic literature review aims to explore the adoption, global acceptance and implementation of human resources (HR) analytics (HRA) by reviewing literature on the subject. HRA adoption can assist HR professionals in managing complex procedures and making strategic human resource management (SHRM) decisions more effectively. The study also aims to identify the applications of analytics in various disciplines of management. Design/methodology/approach: The review is conducted using a domain-based structured literature review (SLR), emphasizing the diffusion of innovative thinking and the adoption process of HRA among early adopters. The philosophical stances are analyzed with the combination of research onion model and PRISMA protocol. Secondary data are gathered from published journals, books, case studies, conference proceedings, web pages and media stories as the primary source of information. Findings: The study finds that skilled professionals and management assistance can significantly impact adoption intentions, enabling professionals to deal with analytics. The examples and analytical models provided by early adopters allow managers to manage complex processes and make SHRM decisions. Research limitations/implications: The study suggests that the lack of use of quantitative techniques is a key limitation and should be considered in future studies. Despite the rise in the number of research papers on HRA, its application in the workplace remains limited. Practical implications: This research can assist managers in implementing HRA and help resolve complex and inefficient processes, making SHRM decisions. Originality/value: This study adds to the existing body of knowledge on how HRA can aid a company's efficacy and performance and can be considered one of the first to link adoption and HRA. [ABSTRACT FROM AUTHOR]

Featured Application: The model is primarily utilized for the task of entity relationship extraction during the construction process of an aquatic disease knowledge graph. Entity–relationship extraction plays a pivotal role in the construction of domain knowledge graphs. For the aquatic disease domain, however, this relationship extraction is a formidable task because of overlapping relationships, data specialization, limited feature fusion, and imbalanced data samples, which significantly weaken the extraction's performance. To tackle these challenges, this study leverages published books and aquatic disease websites as data sources to compile a text corpus, establish datasets, and then propose the Fd-CasBGRel model specifically tailored to the aquatic disease domain. The model uses the Casrel cascading binary tagging framework to address relationship overlap; utilizes task fine-tuning for better performance on aquatic disease data; trains on specialized aquatic disease corpora to improve adaptability; and integrates the BRC feature fusion module—which incorporates self-attention mechanisms, BiLSTM, relative position encoding, and conditional layer normalization—to leverage entity position and context for enhanced fusion. Further, it replaces the traditional cross-entropy loss function with the GHM loss function to mitigate category imbalance issues. The experimental results indicate that the F1 score of the Fd-CasBGRel on the aquatic disease dataset reached 84.71%, significantly outperforming several benchmark models. This model effectively addresses the challenges of ternary extraction's low performance caused by high data specialization, insufficient feature integration, and data imbalances. The model achieved the highest F1 score of 86.52% on the overlapping relationship category dataset, demonstrating its robust capability in extracting overlapping data. Furthermore, We also conducted comparative experiments on the publicly available dataset WebNLG, and the model in this paper obtained the best performance metrics compared to the rest of the comparative models, indicating that the model has good generalization ability. [ABSTRACT FROM AUTHOR]

Extracting geoscientific dataset names from the literature is crucial for building a literature–data association network, which can help readers access the data quickly through the Internet. However, the existing named-entity extraction methods have low accuracy in extracting geoscientific dataset names from unstructured text because geoscientific dataset names are a complex combination of multiple elements, such as geospatial coverage, temporal coverage, scale or resolution, theme content, and version. This paper proposes a new method based on the hierarchical temporal memory (HTM) model, a brain-inspired neural network with superior performance in high-level cognitive tasks, to accurately extract geoscientific dataset names from unstructured text. First, a word-encoding method based on the Unicode values of characters for the HTM model was proposed. Then, over 12,000 dataset names were collected from geoscience data-sharing websites and encoded into binary vectors to train the HTM model. We conceived a new classifier scheme for the HTM model that decodes the predictive vector for the encoder of the next word so that the similarity of the encoders of the predictive next word and the real next word can be computed. If the similarity is greater than a specified threshold, the real next word can be regarded as part of the name, and a successive word set forms the full geoscientific dataset name. We used the trained HTM model to extract geoscientific dataset names from 100 papers. Our method achieved an F1-score of 0.727, outperforming the GPT-4- and Claude-3-based few-shot learning (FSL) method, with F1-scores of 0.698 and 0.72, respectively. [ABSTRACT FROM AUTHOR]

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The blockchain technology can become a solution in data privacy and protection, being considered a public and decentralized database, in which the identity of a user is masked in the form of an address. Based on this technology, several decentralized protocols such as Bitcoin or Ethereum have been created, with the help of which decentralized applications can be created. In this article, we examine how these technologies can be used to ensure the transparency of a software application, but also the privacy and protection of user data. Other facilities like Non-Fungible Token - NFT and Smart Contract are used. The paper proposes the design and the implementation (including the source code) of a web platform for education / courses incorporating blockchain technology. The results and conclusions are showed. Finally, the contributions of the paper, the limitations and future works are also highlighted. [ABSTRACT FROM AUTHOR]

Trauma-informed design and technology have been an important topic of discussion in the last 5 years in user experience. However, little exists to offer practical direction for practitioners applying trauma-informed approaches to websites, apps, and other digital tools. This paper shares an example of applying trauma-informed (TI) principles to a social service agency website in the United States using wellknown usability heuristics, which are principles used in interaction design to ensure usability. There appears to be a significant overlap between usability heuristics and TI principles; practitioners can use usability heuristics as a familiar foundation to make any design more traumainformed. This paper describes specific ways TI principles can be operationalized using usability heuristics to develop more user-friendly and trauma-informed websites. A case study in design shows how user experience professionals can be more trauma-informed in their work to better serve the general public or users who have experienced trauma. [ABSTRACT FROM AUTHOR]

Copyright of Environmental & Social Management Journal / Revista de Gestão Social e Ambiental is the property of Environmental & Social Management Journal and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

One way of exposing predatory journals is to submit a spoof article to see if it gets accepted. We investigate one journal, looking at how it has performed since a spoof paper it accepted came to light. We find that it has published almost 20% more papers following the acceptance of the spoof paper. The journal has a new web site, which appears to show that it did not publish its first paper until 2018. However, there is an old web site that lists 321 papers dating back to 2012. The editors said that this is due to a new workflow system, which meant that previously published papers could not be listed on the new web site. Moreover, the number of papers could be not accommodated, as a high configuration server would be required to provide a responsive web site. We found some plagiarism, which looks quite serious. We conclude that the spoof paper had little effect on the journal, which continues to operate, seven years after the spoof paper was accepted. [ABSTRACT FROM AUTHOR]

The incidence and nature of sexual violence at UK universities has been aligned with a 'rape culture', where sexual violence is taken-for-granted. Calls to change such a culture permeate literature from government, charities, regulatory bodies, and academia. This paper pulls out of the literature the strategies called to change rape culture. Focusing on three overarching strategies: naming sexual violence, reporting sexual violence, and preventing sexual violence. We carried out a website analysis of all UK universities that focused on gathering data along these three themes to ascertain the extent to which their websites supported changing the culture of sexual violence at their university. Many universities' websites had an online reporting tool and defined sexual violence, but many universities' websites did not have information about bystander initiatives (the prevention strategy we focused on). The research raises implications for universities to enhance their website pages for in-person bystander initiatives and to standardise definitions of sexual violence used in online reporting tools. Consequently, more research is needed into what definitions of sexual violence are used, the type of language used and the efficacy of online reporting tools. [ABSTRACT FROM AUTHOR]

Prior researches have highlighted challenges and variations arising from the requirements of research ethics committees and ethics governance systems across diverse research fields. This emphasizes the need to investigate how universities convey and implement research ethical practices. Research ethics plays a pivotal role in guiding the integration of ethical principles throughout all stages of research starting from its inception and planning to its completion and the dissemination of results. These practices encompass a range of considerations, reviews, guidelines, and processes aimed at safeguarding the rights, dignity, health, safety, and privacy of research participants. Using the content analysis technique, this paper aims to analyse research ethical practices information on universities' websites from three developed countries and developing countries respectively using the isomorphism conception. The findings suggest that the coercive, normative, and mimetic isomorphic pressures explain the research ethics governance practices. The ethical practices information was disclosed more on university websites of the developed countries. Suggestions to improve the university's research ethics governance system for the post-COVID-19 era were provided in the paper. [ABSTRACT FROM AUTHOR]

To shed light on the conservation and management of canal cultural heritage worldwide, this paper examines the relevant experience and implications acquired from the US Erie Canal and Canadian Rideau Canal from the perspective of public participation in terms of four dimensions: subject, concept, content, and horizon. The study findings are fourfold: first, the factors such as residents of the Heritage Corridor, non-governmental organizations, non-profit enterprises, private forces, tourists, and individual volunteers constitute the subject of public participation. Second, both sides concur that extensive public involvement is the driving force behind the success of cultural heritage conservation and management. This wide involvement is conducive to promoting education and shaping national identity. Third, for both sides, public participation is integral to the Heritage Corridor project management plan, spanning the entire process of drafting, revising, implementing, and evaluating. Finally, both sides have been leveraging modern information technology and social media, such as web home pages, databases, virtual discussions, Facebook, Twitter, and Instagram, to promote public participation, and achieving double the results with half the effort. The implications of the findings lie in four aspects: first, the canal community committees assume leadership responsibilities with relevant laws and regulations in place as legal backup; second, both the US and Canadian sides take effective measures to organize, recognize, and appreciate participants; third, they demonstrate the spirit of democratic participation and exemplary deliberation throughout the cultural heritage canal conservation and management process; and finally, both sides maximize the use of modern information technologies for efficient conservation and management of their respective Canal Cultural Heritage Corridors. [ABSTRACT FROM AUTHOR]

In a recent paper titled Expert range maps of global mammal distributions harmonised to three taxonomic authorities , Marsh et al. (2022) introduced a series of new geographic range maps for all extant species of mammals and made these maps available on the Map of Life (MoL) website (www.mol.org). The title of the paper and inclusion of over 140 prominent mammalogists and biogeographers as coauthors strongly suggested that these new range maps were carefully vetted. However, when examining the maps of Marsh et al. (2022) on the MoL web platform, we found a variety of serious problems, including, but not limited to: range exaggerations (inclusion of substantial geographic areas not represented by specimen records or verified observations); range maps that are geographically shifted so that species are shown as occurring in areas in which they do not, and not occurring in areas in which they do (and in some cases, these new maps do not even encompass the type locality of a species); range maps that simply omit peripheral populations of conservation concern; and range maps for fully marine mammals (i.e. those that do not spend any time on land) that include large swaths of both insular and continental landmasses. Overall, we evaluated the new "expert" mammal range maps on the MoL platform for 78 species (retrieved between 31 March 2022 and 1 April 2023) and show that there are serious, systemic problems with these maps, and that these problems are both geographically and taxonomically widespread. As such, we caution researchers to carefully review and evaluate the range maps of Marsh et al. (2022) on the MoL before using them for any research purpose—including conservation, biogeographical, and macroecological analyses of mammals. [ABSTRACT FROM AUTHOR]

This paper proposes a framework (OSEC-p model) for the evaluation of health communication, through websites, aimed at breast and cervical cancer screening adherence. For identification of the set of indicators of the model, content analysis of websites was adopted with coding based on both data-driven and theoretically-driven approaches. The proposed model comprises factors on multiple levels (macro-items, items, and micro-items), referring to the strategic orientation aimed at prevention, the organizational structure, corporate tools and stakeholder engagement, content on screening initiatives, compliance with communication principles, and website ergonomics. A pilot study on a sample of websites of Italian local health organizations confirms the applicability of the model and the usefulness of results and indications it offers. The OSEC-p can be considered the first step in a line of research not yet been investigated in the academic field, and aims to be a guideline for managers of healthcare organizations as it allows evaluation (and improvement) of communication via websites aimed at adhering to cancer prevention programs. [ABSTRACT FROM AUTHOR]

The Web has become an essential resource but is not yet accessible to everyone. Assistive technologies and innovative, intelligent frameworks, for example, those using conversational AI, help overcome some exclusions. However, some users still experience barriers. This paper shows how a human-centered approach can shed light on technology limitations and gaps. It reports on a three-step process (focus group, co-design, and preliminary validation) that we adopted to investigate how people with speech impairments, e.g., dysarthria, browse the Web and how barriers can be reduced. The methodology helped us identify challenges and create new solutions, i.e., patterns for Web browsing, by combining voice-based conversational AI, customized for impaired speech, with techniques for the visual augmentation of web pages. While current trends in AI research focus on more and more powerful large models, participants remarked how current conversational systems do not meet their needs, and how it is important to consider each one's specificity for a technology to be called inclusive. [ABSTRACT FROM AUTHOR]

Copyright of Pasado y Memoria. Revista de Historia Contemporánea is the property of Pasado y Memoria and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The continuous improvement in the seaworthiness of Arctic shipping routes has caused an urgent international demand for meteorological and sea ice information. In view of the diversity of Arctic meteorological and sea ice information websites and the uneven service levels of the websites, and to assist Arctic navigation ships in selecting timely, stable, and reliable meteorological and sea ice information, this paper summarizes the websites providing Arctic meteorological and sea ice information. Constructing an evaluation indicator system for the service level of the Arctic meteorological and sea ice information websites from the two dimensions of data quality and browsing experience, this system integrates the cloud model, the Dempster–Shafer (D-S) evidence theory, and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to construct a corresponding service-level evaluation and decision optimization process of Arctic meteorological and sea ice information websites. Finally, through case analysis, the feasibility of this research method is demonstrated. [ABSTRACT FROM AUTHOR]

Collecting data from users is a frequent practice for websites to improve various aspects of their products and services, such as performance, usability, and security. Monitoring user activity on websites helps to comprehend visitor behavior and assess the impact of the site. Numerous applications involve the collection of user data by websites, enabling the prediction of user preferences. This, in turn, facilitates personalized content recommendations. Recommender systems serve as a mechanism to propose analogous items and concepts tailored to an individual's unique mindset. Fundamentally, there are two categories of recommender systems: Collaborative Filtering and Content-Based Filtering. This paper provides a comparative study of collaborative filtering and content-based filtering. [ABSTRACT FROM AUTHOR]

URL stands for uniform resource locator are the addresses of the unique resources on the internet. We all need URLs to access any type of resource on the internet, such as any web page, and document. Sometimes URLs can be long, irrelative and unattractive and unable to send sometimes via email. So, for this, we proposed a URL shortener web application based on the Python-Django platform which is fast and makes your long URLs in the shortest form which you can share on social media platforms. It makes all the messy, unattractive URLs short and shareable. Writing paper proposed a premium section in our application that gives access to the customizable URLs and analytics of your shorten URLs. Customizable URLs are the URLs you create by your own keywords. By creating a premium profile with the application, you can create your own URLs by using your own keywords. We have considered security a major part of the application that prevents the short URLs from being hacked or redirected to any advertising website or content. We store all the data related to the URL to show you the best view of your analytics and update it regularly. Main contribution in this field that for web application that provides users with a fast, secure and shortest URL for their using long URLs. Comparatively to other services that are currently available, the application provides superior security, availability, and confidentiality. [ABSTRACT FROM AUTHOR]

Over the years the number of research publications per year is growing exponentially. Finding research papers of quality from the massive literature of relevant articles is a challenging and time-consuming task. The approaches in the latest literature address citation recommendation by utilizing large bibliographic information and use machine learning and deep learning methods for the task. These techniques clearly require a large amount of training data as well as machines with high processing power. To overcome these issues, we propose a novel method by modifying the popular hyperlink induced topic search (HITS), a web page ranking algorithm, as citation recommendation using hyperlink induced topic search (CR-HITS) that works on a directed and weighted heterogeneous bibliographic network containing diverse types of nodes and edges. We define effective scoring schemes for nodes and edges based on basic bibliographic information like citations of papers, number of publications of an author, etc. Given a few seed papers, the citation recommendation algorithm CR-HITS is run on small neighborhoods of the seed papers and hence the time taken by the execution is very small to yield the final recommendations. To the best of our knowledge, HITS has been used for the first time for the citation recommendation problem. We perform extensive experimentation on DBLP (version-11) and ACM (version-9) datasets and compare the results with many baseline methods in terms of MAP, MRR, and recall@N measures. The performance of the proposed algorithms is superior with respect to the MAP metric and matches the second best for the other two metrics. Since the top two algorithms use deep learning methods and use much larger bibliographic information including abstracts of the papers, we claim that our approach utilizes very low resources, yet yields recommendations that are very close to the top recommendations. [ABSTRACT FROM AUTHOR]

The article describes the revolutionary new ways of communicating the written word when moving from the Medieval to Modern period in Europe, primarily the use of paper and moveable typeface printing and how these catalysed important cultural developments. A similar revolution has taken place in the last 50 years with the development of the internet. The article looks at how scientific publishing has changed with electronic publishing, including the development of Open Access. The journal Heritage Science is placed into this context. Especially important for scientific journals in an era when anyone can post anything on a webpage, is maintaining standards through high quality refereeing which distinguishes formal scientific literature from informal websites. [ABSTRACT FROM AUTHOR]

This paper aimed to conserve and digitise indigenous games, making them accessible online, in order to harmonise cultural traditions with modernity. The majority of contemporary youth are exposed to Western entertainment that contradicts African values and traditions. Certain games have had a detrimental impact on society, leading young people to engage in acts of violence, sexual promiscuity, and even self-harm. African youth in pre-colonial times acquired moral principles through instruction from communal elders, who imparted these lessons through the use of moral games. This study contends that the process of digitization can be employed in conjunction with conventional means of knowledge dissemination and conservation to address the void in a societal context where cultural customs are diminishing. The significance of elders, relationships, and the corpus remains paramount. The study aimed to find an Afro-centric approach to digitise traditional games for educational entertainment. The study centred on the Sankofa and Diffusion of Innovation theories. The study employed qualitative case study research methodology to achieve its objective. Information was collected through a document survey. The data underwent thematic analysis. The paper investigated decolonial approaches to safeguard games via social media, applications, and websites. The study concluded that qualitative methodologies are necessary for determining the optimal and economically efficient technologies. Additionally, it emphasised that decolonization necessitates the establishment of alternative knowledge systems to challenge the dominance of Western and Eurocentric epistemology. [ABSTRACT FROM AUTHOR]

Identifying owners of devices on the Internet can enable numerous network security applications. For example, accurate Owner Name Entity Recognition (ONER) of websites is critical to find influenced owners in light of new security threats. In this situation, as a specific task of Multimodal Named Entity Recognition (MNER), ONER is essential and helpful for network security. Currently, most existing MNER models only use texts and images, so they cannot effectively utilize the multimodal data of devices to achieve ONER accurately. Also, most of the existing MNER models separately use information in each modality and between modalities. Thus, the fusion is inconsistent, so the effect is not satisfied. Therefore, the paper proposes HDGT: A heterogeneous and Dynamic Graph Transformer, to improve the performance of ONER. The core components in HDGT to realize MNER are a dynamic graph and two-stream mechanism, which could learn the relationship between different modalities during training and the graph's structure well. The paper manually labels a multimodal dataset containing texts, images, and domains to prove the performance of HDGT. Also, the paper conducts experiments on existing and public MNER datasets. The results show that HDGT achieves 84.88% F1 scores on the recognition of owner entities, 75.21% F1 on Twitter2015, and 87.03% F1 on Twitter2017, which outperforms other existing MNER models. [ABSTRACT FROM AUTHOR]

The prevalence of phishing as a cybercrime continues to escalate, posing significant threats to individuals' sensitive information. This paper addresses the urgent need for effective phishing detection methods, considering the limitations of existing approaches. The study employs Artificial Neural Networks, specifically Multilayer Perceptrons (MLP), trained using the backpropogation algorithm. The study also highlights MLP's advantages in handling complex and noisy data. Through a comprehensive review of related works, the paper identifies gaps in current research and establishes the groundwork for an innovative phishing website classification framework. The proposed solution utilizes MLPs, offering a detailed explanation of the methodology, dataset, model architecture, and training processes. The research concludes by summarizing key findings, emphasizing the solution's contributions to cybersecurity, and outlining potential avenues for future research. [ABSTRACT FROM AUTHOR]

Bei der gesetzlichen Pflichtablieferung von Netzpublikationen kooperiert die Badische Landesbibliothek mit der Württembergischen Landesbibliothek, dem Bibliotheksservice-Zentrum Baden-Württemberg und der Deutschen Nationalbibliothek. Entstanden sind dabei fünf innovative Dienste zur Archivierung von Amtsdruckschriften, E-Books, E-Journals, E-Papers und Websites. Diese ermöglichen es, wesentliche Teile des textbasierten digitalen Kulturerbes aus Baden zu sichern – wir berichten hier über den aktuellen Stand unserer Sammlung. The legal deposit of online publications is handled through a cooperation by the Baden State Library, the State Library of Württemberg, the Library Service Centre Baden-Württemberg and the German National Library. The joint project has developed five innovative services for archiving government documents, e-books, electronic journals and papers, as well as websites. These services facilitate the protection of substantial parts of our text-based, digital cultural heritage in Baden. We present a short report on the collection and progress to date. [ABSTRACT FROM AUTHOR]

Academic publishing has faced numerous ethical challenges, but reviewer conflict of interest (COI) and potential associated coercive citation requests present an under-explored area of concern. Although we expect most reviewers to act ethically, the drive for academics to increase their citation counts creates a potential incentive for reviewers to seek citations of their own work, presenting a potential reviewer COI. With citation counts serving as an important part of most university and journal rankings, the integrity of the research review process has far-reaching implications. This study analyzes journals' communication to reviewers regarding coercive citation requests and COIs in general, with 205 survey responses from editors of major management or marketing journals, and an assessment of a randomly selected subset of 30 leading journal websites. The majority of journals did not discuss reviewer coercive citation requests or COIs, nor have any obvious processes to screen for it. We discuss the factors that foster an environment conducive to coercive citation requests and identify easily adoptable changes to review formats to address the problem. We also discuss the need to examine the triad of relationships among authors, reviewers, and editors, taking a systems approach. We encourage attention to balance of power and cocreation. [ABSTRACT FROM AUTHOR]

Water quality monitoring serves diverse purposes, such as assessing water safety for drinking or agriculture. However, traditional methods are often time-consuming and costly. Additionally, assessing water quality on demand is not always feasible, and parameter variations are not consistently documented. With the advent of affordable equipment capable of efficient performance with minimal resources, remote monitoring sans physical access to the environment has become viable. This has led to reduced inspection and control costs. Understanding the applications, characteristics, and limitations of these devices is crucial for maximizing their benefits. Rainwater quality remains understudied in many areas, leaving its physical, chemical, and microbiological conditions unknown. These conditions are influenced by various atmospheric factors, including both human and natural activities. This research paper develops monitoring stations employing low-cost technology to assess rainwater quality in Morelia City. A prototype was developed based on low-cost technology implementation. Additionally, basic parameters measured include pH, total dissolved solids, turbidity, and temperature, utilizing an Arduino microcontroller for data processing. Data collected from these stations are transmitted via a Wi-Fi communication module to a web platform, enabling real-time visualization of measurements both spatially and temporally. Utilizing such a device offers several advantages compared to standard methods of assessing rainwater quality. It enables continuous measurements and provides a record of how rainwater quality is affected over time by human and natural activities. [ABSTRACT FROM AUTHOR]

Text-based CAPTCHAs remain the most widely adopted security scheme, which is the first barrier to securing websites. Deep learning methods, especially Convolutional Neural Networks (CNNs), are the mainstream approach for text CAPTCHA recognition and are widely used in CAPTCHA vulnerability assessment and data collection. However, verification code recognizers are mostly deployed on the CPU platform as part of a web crawler and security assessment; they are required to have both low complexity and high recognition accuracy. Due to the specifically designed anti-attack mechanisms like noise, interference, geometric deformation, twisting, rotation, and character adhesion in text CAPTCHAs, some characters are difficult to efficiently identify with high accuracy in these complex CAPTCHA images. This paper proposed a recognition model named Adaptive CAPTCHA with a CNN combined with an RNN (CRNN) module and trainable Adaptive Fusion Filtering Networks (AFFN), which effectively handle the interference and learn the correlation between characters in CAPTCHAs to enhance recognition accuracy. Experimental results on two datasets of different complexities show that, compared with the baseline model Deep CAPTCHA, the number of parameters of our proposed model is reduced by about 70%, and the recognition accuracy is improved by more than 10 percentage points in the two datasets. In addition, the proposed model has a faster training convergence speed. Compared with several of the latest models, the model proposed by the study also has better comprehensive performance. [ABSTRACT FROM AUTHOR]

Electronic banking grants users access to banking services virtually and offers convenience, ease of use, low cost, time saving, fast delivery and online bill payment. These services are mostly provided through websites; hence evaluation of its quality and services are very important. Website quality evaluation entails numerous dimensions and attributes and the processes which are critical as well as complex requires quality, accuracy and objectivity. This paper surveys the criteria and methodologies that have been used over years in e-banking websites quality as well as e-services quality evaluation. The survey covers articles within a five-year period from 2018 - 2022 which mostly focus on e-banking websites quality evaluation. Twenty-three articles which met the inclusion and exclusion criteria set by the authors are used for the study. Results show that the average number of criteria used in most studies are six with security, privacy and ease-of-use taking the lead as the mostly used criteria across different studies. Also, various types of multi-criteria decision-making model were used by different and there is none that is dominant among them. It was observed that fuzzy type of the various types of multi-criteria decision-making models are mostly used in many studies. In general, studies with focus on e-banking websites quality are not yet given much attention in the literature. [ABSTRACT FROM AUTHOR]

The emergence of illegal (gambling, pornography, and attraction) websites seriously threatens the security of society. Due to the concealment of illegal websites, it is difficult to obtain labeled data with high quantity. Meanwhile, most illegal websites usually disguise themselves to avoid detection; for example, some gambling websites may visually resemble gaming websites. However, existing methods ignore the means of camouflage in a single modality. To address the above problems, this paper proposes MEDAL, a multimodality-based effective data augmentation framework for illegal website identification. First, we established an illegal website identification framework based on tri-training that combines information from different modalities (including image, text, and HTML) while making full use of numerous unlabeled data. Then, we designed a multimodal mutual assistance module that is integrated with the tri-training framework to mitigate the introduction of error information resulting from an unbalanced single-modal classifier performance in the tri-training process. Finally, the experimental results on the self-developed dataset demonstrate the effectiveness of the proposed framework, performing well on accuracy, precision, recall, and F1 metrics. [ABSTRACT FROM AUTHOR]

To improve the effect of web page information extraction, this paper proposes an improved information extraction method of mixed text density grids. Under various power constraints of the relay node itself, this paper proposes a design scheme of joint beamforming and artificial noise based on safety and rate maximisation. Furthermore, with the help of semidefinite relaxation techniques and first‐order approximations, it can be approximated as a semidefinite programming problem that is easy to solve. In addition, this paper uses an iterative algorithm based on a continuous convex approximation to process data to improve the accuracy of web page data extraction. The experimental results show that the information extraction method based on improved mixed text density webpages proposed in this paper has a good information extraction effect. [ABSTRACT FROM AUTHOR]

This paper presents the findings from a systematic review of 29 websites and 13 frameworks that provide STEM (Science, Technology, Engineering, Mathematics) educational resources for parents, educators, and children (birth–8 years of age). Our theoretical approach is rooted within a social semiotic perspective that has indicated that multimodality enables children to use different types of expression to communicate a message or share an idea. Using the PRISMA methodology and the narrative document analysis approach, the themes that emerged included how the content and resources available on the websites addressed whether multimodality supported STEM engagement in an inclusive manner. The findings revealed that there were scarce multimodal resources that engaged children with fun, interactive, and meaningful opportunities to be autonomous learners (e.g., children had agency) (n = 11 out of 29), moving between the digital and hands-on physical spaces (n = 8 out of 29), employing gamification for deep learning (n = 4 out of 29), and piquing children's imagination, inquiry, and creativity, and links to everyday STEM scenarios were hardly present (n = 10 out of 29). The implications lie in addressing early STEM engagement by considering children's learning abilities and agency, bearing in mind parents/educators' sociocultural backgrounds, confidence in STEM awareness, and multimodal avenues for communicating STEM learning and inquiry. [ABSTRACT FROM AUTHOR]

Background: This study assesses the quality and readability of Arabic online information about orthodontic pain. With the increasing reliance on the internet for health information, especially among Arabic speakers, it's critical to ensure the accuracy and comprehensiveness of available content. Our methodology involved a systematic search using the Arabic term for (Orthodontic Pain) in Google, Bing, and Yahoo. This search yielded 193,856 results, from which 74 websites were selected based on predefined criteria, excluding duplicates, scientific papers, and non-Arabic content. Materials and methods: For quality assessment, we used the DISCERN instrument, the Journal of the American Medical Association (JAMA) benchmarks, and the Health on the Net (HON) code. Readability was evaluated using the Simplified Measure of Gobbledygook (SMOG), Flesch Reading Ease Score (FRES), and Flesch-Kincaid Grade Level (FKGL) scores. Results: Results indicated that none of the websites received the HONcode seal. The DISCERN assessment showed median total scores of 14.96 (± 5.65), with low overall quality ratings. In JAMA benchmarks, currency was the most achieved aspect, observed in 45 websites (60.81%), but none met all four criteria simultaneously. Readability scores suggested that the content was generally understandable, with a median FKGL score of 6.98 and a median SMOG score of 3.98, indicating middle school-level readability. Conclusion: This study reveals a significant gap in the quality of Arabic online resources on orthodontic pain, highlighting the need for improved standards and reliability. Most websites failed to meet established quality criteria, underscoring the necessity for more accurate and trustworthy health information for Arabic-speaking patients. [ABSTRACT FROM AUTHOR]

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In contemporary society, artificial intelligence (AI) impacts human lives to different extents, including reshaping the public's creative experience. Software and programs enable users to create images from scratch, notwithstanding their actual knowledge or competencies. The visual art system is currently facing an ongoing democratization process, in which the distance separating the creator and the informatic algorithm is gradually fading. Therefore, there is a growing need to analyze AI's implications on the creative process. The paper will analyze the different software and websites providing image-generating services while discussing their impact on society as a whole. [ABSTRACT FROM AUTHOR]

Hospitals use different technological tools to implement corporate communication initiatives and, in this way, improve their relationships with stakeholders (employees, patients, media companies) and build a reputed brand. However, they face different barriers: limited budgets for corporate communication, strict legal frameworks, and stakeholders’ new needs regarding information and emotional support. This paper aims to analyze how the 100 best hospitals in the United States manage smart technologies to promote their brand. To do that, we conducted a literature review about smart hospitals, branding, and corporate communication; and then we defined 34 quantitative indicators to evaluate how the hospitals previously mentioned managed their websites, online newsrooms, about us sections, and artificial intelligence department web sites for reputation purposes. Our results proved that most hospitals respected indicators related to the homepage (8.67/11) but not those referring to online newsrooms (4.44/11) or about us sections (2.66/6). Besides, only 23 hospitals had implemented a department specialized in artificial intelligence that collaborated with external organizations. We concluded that most American hospitals focused their reputation efforts on patients rather than other targets (media companies, employees, suppliers, shareholders); and that these organizations did not integrate enough artificial intelligence projects into their smart branding initiatives. [ABSTRACT FROM AUTHOR]

This paper presents the results of a performance analysis conducted on an experimental airborne vertical axis wind turbine (VAWT), specifically focusing on the MAGENN Air Rotor System (MARS) project. During its development phase, the company claimed that MARS could generate a power output of 100 kW under wind velocities of 12 m/s. However, no further information or numerical models supporting this claim were found in the literature. Extending our prior conference work, the main objective of our study is to assess the accuracy of the stated rated power output and to develop a comprehensive numerical model to analyze the airflow dynamics around this unique airborne rotor configuration. The innovative design of the solid model, resembling yacht sails, was developed using images in the related web pages and literature, announcing the power coefficient (Cp) as 0.21. In this study, results cover 12 m/s wind and flat terrain wind velocities (3, 5, 6, and 9 m/s) with varying rotational velocities. Through meticulous calculations for the atypical blade design, optimal rotational velocities and an expected Tip Speed Ratio (TSR) of around 1.0 were determined. Introducing the Centroid Speed Ratio (CSR), which is the ratio of the sail blade centroid and the superficial wind velocities for varied wind speeds, the findings indicate an average power generation potential of 90 kW at 1.4 rad/s for 12 m/s and approximately 16 kW at a 300 m altitude for a 6 m/s wind velocity. [ABSTRACT FROM AUTHOR]

Around 2000 years ago, the Roman philosopher Seneca the Younger complained that his peers were wasting their time and money accumulating too many books, admonishing that "the abundance of books is a distraction." Instead, Seneca recommended focusing on fewer but better-quality books and reading them thoroughly and repeatedly. After the invention of the printing press in the 15th century, the plethora of information the machine produced was thought by some to be distracting. Today, information overload and digital over-stimulation lead to digital burnout -- a situation where physical and mental exhaustion is caused by spending too much time in front of screens. Symptoms of this condition are apathy, indifference, or mental exhaustion arising from exposure to too much information. Stress induced by attempts to assimilate excessive amounts of information from the media, particularly social media, the internet, or work makes us ill by interfering with our sleep, sabotaging our concentration and undermining our immune system. David Lewis, a British psychologist, calls this ailment Information Fatigue Syndrome (IFS). This paper looks at Information Fatigue Syndrome (IFS), and particularly at the contribution of grey literature (GL) to IFS. To better understand the amount of grey literature around us, it is enough just to look at the GreyNet website which lists over 150 grey literature types. They include articles, blogs, images, videos, emails, web pages, press releases, lectures, manuals, academic theses, and many others. Today, grey literature occupies a considerable role and is one of the main contributors to our digital burnout. The diversity of GL types, volume generated and shared, frequency of creation and change, currency, veracity, and value will be reviewed. The purpose of the paper is to generate suggestions on how to successfully deal with Information Fatigue Syndrome. Additionally, it will offer suggestions on how to continue using valuable grey literature efficiently, and how to do all of this without causing unnecessary stress or wasting time. [ABSTRACT FROM AUTHOR]

Objectives: The purpose of this research is to summarize the structure of radiomics-based knowledge and to explore potential trends and priorities by using bibliometric analysis. Methods: Select radiomics-related publications from 2012 to October 2022 from the Science Core Collection Web site. Use VOSviewer (version 1.6.18), CiteSpace (version 6.1.3), Tableau (version 2022), Microsoft Excel and Rstudio's free online platforms (http://bibliometric.com) for co-writing, co-citing, and co-occurrence analysis of countries, institutions, authors, references, and keywords in the field. The visual analysis is also carried out on it. Results: The study included 6428 articles. Since 2012, there has been an increase in research papers based on radiomics. Judging by publications, China has made the largest contribution in this area. We identify the most productive institutions and authors as Fudan University and Tianjie. The top three magazines with the most publications are《FRONTIERS IN ONCOLOGY》, 《EUROPEAN RADIOLOGY》, and 《CANCERS》. According to the results of reference and keyword analysis, "deep learning, nomogram, ultrasound, f-18-fdg, machine learning, covid-19, radiogenomics" has been determined as the main research direction in the future. Conclusion: Radiomics is in a phase of vigorous development with broad prospects. Cross-border cooperation between countries and institutions should be strengthened in the future. It can be predicted that the development of deep learning-based models and multimodal fusion models will be the focus of future research. Advances in knowledge: This study explores the current state of research and hot spots in the field of radiomics from multiple perspectives, comprehensively, and objectively reflecting the evolving trends in imaging-related research and providing a reference for future research. [ABSTRACT FROM AUTHOR]

The responsiveness of a web application with minimum latency time and maximum web pages loading speed is determined by its overall performance. When dealing with a large number of users and amount of data, the performance of web applications is significantly affected by ways of data processing, storage and access. This paper identifies the significance of data caching process to speed up access to relational database. The study examines approaches to improve the performance of web applications through the joint use of MySQL relational database management system (DBMS) and Redis NoSQL DBMS. The practical part of the study presents a description of a web application built based on Java and Spring Boot framework. The paper proposes the implementation of the caching strategies that take into account the principles of aspect-oriented programming. Made experiments on performance testing of the developed web application with and without caching are presented. The presented results of the study allowed us to conclude that it is possible to improve the performance of web applications by the optimal use of caching strategies when performing database queries. [ABSTRACT FROM AUTHOR]

The aim of this paper is to evaluate the completeness, accuracy and credibility of the medical information found online about hypertension and to compare the quality of the Romanian and English websites. This observational, cross-sectional study included 25 Romanian and 25 English websites. Pre-established inclusion and exclusion criteria were used for sample selection. Credibility was assessed using 12 criteria based on the eEurope 2002 expert recommendations. Completeness and accuracy of information were evaluated using a quality standard based on information from literature and guidelines. The credibility, completeness and accuracy scores were rated on a scale from 0 to 10. Student t test and Mann-Whitney U were used to compare the two languages subsamples. Spearman and Pearson's tests were applied to test the correlations. The threshold for statistical significance was set at 0.05. The average credibility score was 4.7 for the Romanian websites and 5.6 for English websites (p=0.0686). The average completeness score was 3.7 for the Romanian websites and 5.3 for English websites (p=0.0007). The average accuracy score was 3.88 for the Romanian websites and 3.62 for English websites (p=0.5215). Significant moderate intensity correlation was found between the Google rank and the accuracy of the Romanian websites (r=-0.5438, p=0.0050). The overall quality scores of the Romanian and English websites presenting information about hypertension were modest. This study found a correlation between the Google rank and the accuracy score of the Romanian websites but since this was the only significant correlation, the findings are not sufficient to infer general recommendations. The study suggests that knowing both Romanian and English doesn't offer a significant advantage in accessing high-quality online information about hypertension. The Google rank cannot be used as a quality indicator since there is no consistent correlation between it and the quality scores. [ABSTRACT FROM AUTHOR]

Various applications of artificial intelligence (AI) are currently being developed to enhance and transform the educational experience. However, things like culture, society, and ethics may have an impact on how artificial intelligence is implemented in classrooms all around the world. This study aims to analyze the existing use of AI in education in two Southeast Asian nations, namely Indonesia and Thailand, and to compare those two environments in terms of their potential. Specifically, the research will focus on Indonesia. We gathered papers, publications, and websites from both countries in order to perform an in-depth analysis as part of a comprehensive literature study that we carried out. The ethical and social repercussions of using AI in education, the best practices and suggestions for using AI in education, the possibilities and problems presented by using AI in education, and the preparedness and obstructions presented by using AI in education. Our study demonstrates that there are parallels and variances between the perceptions and experiences of educators and students from the two nations about the use of AI in educational settings, and it also makes recommendations for future research and practice. [ABSTRACT FROM AUTHOR]

This study addresses the gap in knowledge regarding effective design practices for crowdmapping in participatory mapping, considering the diverse agendas, expectations, and needs of stakeholders. Through interviews and analysis of a crowdmapping project, we developed a roadmap and guidelines to inform the design process of a web-based crowdmapping tool. Unlike traditional approaches that focus on end-user evaluation, our paper explores the perspectives of facilitators and developers involved in the participatory process. By understanding their motivations and perceptions, we can plan and design user-friendly tools that meet the requirements of all stakeholders in participatory mapping. [ABSTRACT FROM AUTHOR]

The way by which the news is created and published has been changed by the appearance and the extensive adoption of the Semantic Web (SW) and the concepts of Social Media together with the growth of the Internet. The spread of Fake News (FN) is also prevalent. However, the recognition of FN from the disparate sentences of various website data becomes a challenging task. Hence, an FN detection system is developed in this paper by employing the proposed CKH_GAN model. The process is initiated by gathering data from the scraped dataset, which contains different news and tweets. Then, the acquired data is pre-processed to remove the repeated details, hashtags, and meaningless usernames. Further, the redundant website data are eliminated using the HDFS (Hadoop Distributed File System)-Map Reduce approach. Subsequently, the disparate characteristics, including grammar less and factual less sentences are detected and grouped based on the similarity measures by using the developed FTS-BERT (Fined Tuned Scaling-centered Bidirectional Encoder Representations from the Transformer) algorithm. Further, the informative features are extracted, and the significant features among them are chosen utilizing the proposed CP-EO (Cutting Plane method-centered Equilibrium Optimizer) technique. Eventually, based on the selected features, the FN and real news are categorized using the proposed CKH_GAN (Calculus Krill Herd based Generative Adversarial Networking (CKH_GANs) model for identifying the FN. The experimental outcomes exhibit that the proposed work detected FN with an accuracy of 95.89%, precision of 93.65%, f-score of 94.87%, FPR of 11.23%, and FNR of 10.98%, which are better than the other existing techniques. [ABSTRACT FROM AUTHOR]

Geographic information systems (GIS) has been used in archaeology for four decades, and colloquially appears to have become a main tool in the geospatial aspects of archaeological practice. In this paper, we examine temporal trends in the use and/or mention of GIS in archaeological publications (books and journal articles), conference presentations, and websites. We gathered data through keyword searches and with formal sampling surveys and conducted both quantitative and qualitative analyses to characterize the changing nature and intensity of GIS use in archaeology over time, and then contextualize these trends with a narrative history of archaeological GIS. We show how archaeological GIS-use has grown from a few early adopters of the 1980s, through a slow initial integration phase in the 1990s, to a set of two major expansions in the 2000s and 2010s. While we find that applied use of GIS has grown to the point where it can be considered ubiquitous—if not completely universal—in the discipline, we also discovered that the major focus in archaeological GIS advancement is methodological rather than theoretical. We identify five roadblocks that we believe have hampered the development of a theory-rich archaeological GIS: (1) deficiencies in the archaeological GIS education model, (2) over-reliance on commercial software, (3) technical/technological barriers, (4) gaps in acceptance of GIS, and (5) the perception of GIS as "just a tool." We offer initial suggestions for ways forward to mitigate the effects of these roadblocks and build a more robust, theoretically sophisticated relationship with GIS in archaeology. [ABSTRACT FROM AUTHOR]

COVID‐19 brought public health challenges to the public transport system throughout the world. As a result, a range of response measures were implemented to ensure the safety of passengers while maintaining a functioning system. This paper explores the responses of public transport agencies in New Zealand's metropolitan cities (Auckland, Christchurch and Wellington) to the COVID‐19 pandemic by examining their physical and communication measures. We analysed public transport agencies' websites to understand the response measures implemented, including the accessibility of COVID‐19‐related information, and the communication of information via websites and social media platforms. The results show that 13 service responses were implemented across the three public transport agencies, with Auckland implementing the most measures. Seven infrastructural responses were implemented, with Christchurch implementing all seven. Wellington was found to be the public transport agency that used social media the most during the pandemic. The website accessibility findings suggest that the more accessible a public transport agency's website was, the less information was present. The research concludes that all three public transport agencies in New Zealand performed reasonably well and were able to maintain a safe and responsive public transport system. [ABSTRACT FROM AUTHOR]

There are numerous conceptions of violence today, such as physical, psychological, emotional, structural, and epistemic. The question of which social phenomena are to be described as violence is itself a matter of furious dispute. In social theory, there is a widespread tendency to distinguish between 'modern' and 'postmodern' conceptions of violence. In this scheme, modern violence is primarily physical, while postmodern violence takes places across a broad spectrum of forms. The paper questions this binary. The co-occurrence and conflict between these forms of violence leads to a third form, which I call refigured violence. The refiguration of violence can be observed in three developments, which are mediatisation, polycontexturalisation, and translocalisation. I provide one illustration of these considerations with the example of so-called shock sites on the internet. In so doing, I emphasise that the sociology of knowledge can provide a valuable perspective for making sense of contemporary discourses about violence in all their complexity. [ABSTRACT FROM AUTHOR]

Search engines match user queries with webpages. Search efficiency, increases when data-driven network effects attract more users and generate economies of scale and scope in data aggregation. Network effects enhance user welfare but also trigger antitrust concerns because they may "tip" the market towards a single dominant search engine – Google Search. The EU Digital Markets Act imposes an obligation on very large gatekeepers search engines to share their user data with smaller search engines to facilitate market entry and competition. The available empirical literature on search engine efficiency shows that asymmetric data sharing, from larger to smaller search engines, may increase competition but reduce user welfare because it fragments the user data pool that is crucial for efficiency, in particular for rare queries. Tension between competition and user welfare can be overcome by symmetric and mutual data sharing between all search engines, irrespective of market share. [ABSTRACT FROM AUTHOR]