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This paper aims to address research gaps around third party data flows in education by investigating governance practices in higher education with respect to learning management system (LMS) ecosystems. The authors answer the following research questions: how are LMS and plugins/learning tools interoperability (LTI) governed at higher education institutions? Who is responsible for data governance activities around LMS? What is the current state of governance over LMS? What is the current state of governance over LMS plugins, LTI, etc.? What governance issues are unresolved in this domain? How are issues of privacy and governance regarding LMS and plugins/LTIs documented or communicated to the public and/or community members?

This study involved three components: (1) An online questionnaire about LMS, plugin and LTI governance practices from information technology professionals at seven universities in the USA (n = 4) and Canada (n = 3). The responses from these individuals helped us frame and design the interview schedule. (2) A review of public data from 112 universities about LMS plugin and LTI governance. Eighteen of these universities provide additional documentation, which we analyze in further depth. (3) A series of extensive interviews with 25 university data governance officers with responsibilities for LMS, plugin and/or LTI governance, representing 14 different universities.

The results indicate a portrait of fragmented and unobtrusive, unnoticed student information flows to third parties. From coordination problems on individual college campuses to disparate distributions of authority across campuses, as well as from significant data collection via individual LTIs to a shared problem of scope across many LTIs, the authors see that increased and intentional governance is needed to improve the state of student privacy and provide transparency in the complex environment around LMSs. Yet, the authors also see that there are logical paths forward based on successful governance and leveraging existing collaborative networks among data governance professionals in higher education.

Substantial prior work has examined issues of privacy in the education context, although little research has directly examined higher education institutions’ governance practices of LMS, plugin and LTI ecosystems. The tight integration of first and third-party tools in this ecosystem raises concerns that student data may be accessed and shared without sufficient transparency or oversight and in violation of established education privacy norms. However, these technologies and the university governance practices that could check inappropriate data handling remain under-scrutinized. This paper addresses this gap by investigating the governance practices of higher education institutions with respect to LMS ecosystems.

The present study demonstrates how browser plugins have been adopted by libraries in recent times to empower users in participatory academic and research activities. The study aims to present a brief synthesis of the practical use of browser plugins in libraries and their possible future use.

Web-based survey method was applied in the study to search and find browser plugins associated with academic library websites and to explore their area of application.

With the descriptive account of the implementation of plugins in academic libraries, supported by numerous examples, the study presents the pertinence of various approaches as appeared on library websites.

The present investigation is limited to the academic libraries only.

The good practices enumerated in the study will improve the understanding of the young library professionals about the practical usage of plugins and the steps to enhance accessibility to plugins.

To describe the architecture of iPOS (short for iPAQ positioning system), a novel fault‐tolerant and adaptive self‐positioning system with quality‐of‐service (QoS) guarantees for resource‐limited mobile devices.

The iPOS architecture is based on a novel sensor modelling technique in combination with a probabilistic data‐fusion engine, which is capable of efficiently combining the location information obtained from an arbitrary number of heterogeneous location sensors. As a proof of concept, the paper present a prototypical implementation for handheld devices, which was evaluated by means of practical experiments.

A major advantage of the iPOS positioning system is its extensibility and flexibility, which is achieved by means of an open plugin architecture and the support of global positioning coordinates according to the WGS‐84 standard. The iPOS system scales very well with respect to the number of sensor plugins that can be operated in parallel. The main limiting factor for the number of supported active plugins is the amount of available system resources on the MoD. With regard to recognition, the experimental results indicate a good accuracy of the fusion‐based positioning system in comparison to the accuracy of the individual sensing technologies. Thanks to the explicit modelling of reliable sensor events, the iPOS system is capable of providing QoS guarantees to applications with regard to the achieved positioning accuracy.

During the experiments, the author recognized time synchronisation as an important challenge that should be addressed as part of future work.

The system enables resource‐restricted mobile devices and computerised objects to exploit computing resources found in their immediate physical vicinity (locality).

The paper presents a novel lightweight sensor‐fusion architecture for fault‐tolerant and adaptive self‐positioning that performs well on resource‐limited mobile devices. A special feature of the developed data‐fusion architecture is the application of a novel event modelling technique that enables the positioning system to give QoS guarantees under certain conditions.

This study aims to identify the gap between the requirements of the accreditation bodies and the widely used learning management systems (LMSs) in assessing the intended learning outcomes (ILOs). In addition, this study aims to introduce a framework, along with the evaluation of the functionality of the LMS, for measuring the ILO.

A qualitative method was deployed to examine the gap between the requirements of the accreditation standards and the LMS functionalities. The researchers collaborated to design a mechanism, develop a system architecture to measure the ILO in alignment with the accreditation standards and guide the development of the Moodle plugin. The appropriateness and effectiveness of the plugin were evaluated within the scope of assessment mapping and design. Focus group interviews were conducted to collect feedback from the instructors and program leaders regarding its implementation.

The results of this study indicate that there is no standardized mechanism to measure course and program ILO objectively, using the existing LMS. The implementation of the plugin shows the appropriateness and effectiveness of the system in generating ILO achievement reports, which was confirmed by the users.

This study proposed a framework and developed a system architecture for the objective measurement of the ILO through direct assessment. The plugin was tested to generate consistent reports during the measurement of course and program ILO. The plugin has been implemented across Gulf University’s program courses, ensuring appropriate reporting and continuous improvement.

The use of building information modelling (BIM) methodology has been increasing in the architecture, engineering, construction and operation sector, driven to a new paradigm of work with the use of three-dimensional (3D) parametric models. However, building information modelling (BIM) has been mostly used for as-built models of a building, not yet been widely used by designers during project and construction phases for occupational risks prevention and safety planning. This paper aims to show the capacity of developing tools that allow adding functionalities to Revit software to improve safety procedures and reduce the time spent on modelling them during the design phase.

To reach this objective, a structural 3D model of a building is used to validate the developed tools. A plugin prototype based on legal regulations was developed, allowing qualitative safety assessment through the application of job hazard analysis (JHA), SafeObject and checklists. These tools allow the automated detection of falls from height situations and the automated placement of the correspondent safety systems.

Revit application programming interface allowed the conception and addition of several functionalities that can be used in BIM methodology, and more specifically in the prevention of occupational risks in construction, contributing this paper to the application of a new approach to the prevention through design.

This paper is innovative and important because the developed plugins allowed: automated detection of potential falls from heights in the design stage; automated introduction of safety objects from a BIM Safety Objects Library; and the intercommunication between a BIM model and a safety database, bringing JHA integration directly on the project. The prototype of this work was validated for fall from height hazards but can be extended to other potentials hazards since the initial design stage.

The purpose of this paper is to make easily accessible models to test and compare the optimization algorithms we develop.

For this, the paper proposes an optimization framework based on software component, web service, and plugin to exploit these models in different environments.

The paper illustrates the discussion with optimizations in Matlab™ and R (www.r-project.org) of a transformer described and exploitable from the internet.

The originality is to make easy implementation of simulation model and optimization algorithm coupling using software component, web service, and plugin.

The Greenstone digital library software is an open‐source system for the construction and presentation of information collections. Collections built with Greenstone offer effective full‐text searching and metadata‐based browsing facilities that are attractive and easy to use. Moreover, they are easily maintainable and can be augmented and rebuilt entirely automatically. The system is extensible: software “plugins” accommodate different document and metadata types. Greenstone incorporates an interface that makes it easy for people to create their own library collections. Collections may be built and served locally from the user’s own Web server, or (given appropriate permissions) remotely on a shared digital library host. End users can easily build new collections styled after existing ones from material on the Web or from their local files (or both), and collections can be updated and new ones brought online at any time.

This paper aims to discuss the public knowledge project (PKP) preservation network (PN), which provides free preservation services for eligible journals by collecting article content and preserving it in a network of (at the time of writing) eight “preservation nodes” using the LOCKSS system. The PKP PN was launched in June 2016.

This paper addresses the development and implementation of a free, distributed digital PN for open journal systems (OJS) content. It discusses challenges in developing the network, in particular relating to preserving content from a set of partners who have no formal business relationship with PKP. The paper examines data regarding journals that have opted in to the network to date and considers interface usability and other barriers facing those that have not joined.

Within 18 months of launch, more than 600 journals had opted to be preserved in the PKP PN. Many more journals are eligible to join the network; the paper explores potential strategies to increase participation and identifies and proposes methods to overcome technical and communication barriers.

This paper describes a highly collaborative, open-source preservation initiative which forms a unique part of the e-journal preservation landscape and preserves a particularly vulnerable portion of the scholarly record.

Phishing attacks have evolved in recent years due to high-tech-enabled economic growth worldwide. The rise in all types of fraud loss in 2019 has been attributed to the increase in deception scams and impersonation, as well as to sophisticated online attacks such as phishing. The global impact of phishing attacks will continue to intensify, and thus, a more efficient phishing detection method is required to protect online user activities. To address this need, this study focussed on the design and development of a deep learning-based phishing detection solution that leveraged the universal resource locator and website content such as images, text and frames.

Deep learning techniques are efficient for natural language and image classification. In this study, the convolutional neural network (CNN) and the long short-term memory (LSTM) algorithm were used to build a hybrid classification model named the intelligent phishing detection system (IPDS). To build the proposed model, the CNN and LSTM classifier were trained by using 1m universal resource locators and over 10,000 images. Then, the sensitivity of the proposed model was determined by considering various factors such as the type of feature, number of misclassifications and split issues.

An extensive experimental analysis was conducted to evaluate and compare the effectiveness of the IPDS in detecting phishing web pages and phishing attacks when applied to large data sets. The results showed that the model achieved an accuracy rate of 93.28% and an average detection time of 25 s.

The hybrid approach using deep learning algorithm of both the CNN and LSTM methods was used in this research work. On the one hand, the combination of both CNN and LSTM was used to resolve the problem of a large data set and higher classifier prediction performance. Hence, combining the two methods leads to a better result with less training time for LSTM and CNN architecture, while using the image, frame and text features as a hybrid for our model detection. The hybrid features and IPDS classifier for phishing detection were the novelty of this study to the best of the authors' knowledge.

This study aims to explore browsing extension plugins for searching open scholarly literature and gain an understanding of the various available extensions, their functionalities and their benefits.

Instant retrieval of scholarly literature on the internet is challenging for any researcher due to incredibly accessible free and paid content, including various forms of resources, despite the availability of federated and discovery tools. This paper aimed to explore “Access Broker Browser extensions” available for quick retrieval of open scholarly literature. This paper explicitly explains browser extensions – Google Scholar Button, Open Access Button, Open Access Helper, Core, GetFTR and EndNote Click. Furthermore, the paper elaborated on the extension’s features, functionalities and usability in finding scholarly literature. This study found that the Google Scholar Button and GetFTR extensions seems more user-friendly, effective and easy to use on all internet browsers.

This paper identifies that the “Google Scholar Button” and “GetFTR” browser extensions are more effective than any other extensions and very user-friendly to use.

This study recommends that libraries should create awareness and provide training on access broker browser extensions for discovering scholarly open literature for learning.