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Informatics, Volume 8, Issue 2 (June 2021) – 13 articles

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Open AccessFeature PaperArticle
Convolutional Extreme Learning Machines: A Systematic Review
by , , , and
Informatics 2021, 8(2), 33; https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020033 (registering DOI) - 13 May 2021
Abstract
Much work has recently identified the need to combine deep learning with extreme learning in order to strike a performance balance with accuracy, especially in the domain of multimedia applications. When considering this new paradigm—namely, the convolutional extreme learning machine (CELM)—we present a [...] Read more.
Much work has recently identified the need to combine deep learning with extreme learning in order to strike a performance balance with accuracy, especially in the domain of multimedia applications. When considering this new paradigm—namely, the convolutional extreme learning machine (CELM)—we present a systematic review that investigates alternative deep learning architectures that use the extreme learning machine (ELM) for faster training to solve problems that are based on image analysis. We detail each of the architectures that are found in the literature along with their application scenarios, benchmark datasets, main results, and advantages, and then present the open challenges for CELM. We followed a well-structured methodology and established relevant research questions that guided our findings. Based on 81 primary studies, we found that object recognition is the most common problem that is solved by CELM, and CCN with predefined kernels is the most common CELM architecture proposed in the literature. The results from experiments show that CELM models present good precision, convergence, and computational performance, and they are able to decrease the total processing time that is required by the learning process. The results presented in this systematic review are expected to contribute to the research area of CELM, providing a good starting point for dealing with some of the current problems in the analysis of computer vision based on images. Full article
(This article belongs to the Special Issue Feature Paper in Informatics)
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Open AccessArticle
Factors Affecting the Use of Smart Mobile Examination Platforms by Universities’ Postgraduate Students during the COVID-19 Pandemic: An Empirical Study
Informatics 2021, 8(2), 32; https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020032 - 30 Apr 2021
Viewed by 531
Abstract
Recent years have seen an increasingly widespread use of online learning technologies. This has prompted universities to make huge investments in technology to augment their position in the face of extensive competition and to enhance their students’ learning experience and efficiency. Numerous studies [...] Read more.
Recent years have seen an increasingly widespread use of online learning technologies. This has prompted universities to make huge investments in technology to augment their position in the face of extensive competition and to enhance their students’ learning experience and efficiency. Numerous studies have been carried out regarding the use of online and mobile phone learning platforms. However, there are very few studies focusing on how university students will accept and adopt smartphones as a new platform for taking examinations. Many reasons, but most recently and importantly the COVID-19 pandemic, have prompted educational institutions to move toward using both online and mobile learning techniques. This study is a pioneer in examining the intention to use mobile exam platforms and the prerequisites of such intention. The purpose of this study is to expand the Technology Acceptance Model (TAM) by including four additional constructs: namely, content quality, service quality, information quality, and system quality. A self-survey method was prepared and carried out to obtain the necessary basic data. In total, 566 students from universities in the United Arab Emirates took part in this survey. Smart PLS was used to test the study constructs and the structural model. Results showed that all study hypotheses are supported and confirmed the effect of the TAM extension factors within the UAE higher education setting. These outcomes suggest that the policymakers and education developers should consider mobile exam platforms as a new assessment platform and a possible technological solution, especially when considering the distance learning concept. It is good to bear in mind that this study is initial and designed to explore using smartphones as a new platform for student examinations. Furthermore, mixed-method research is needed to check the effectiveness and the suitability of using the examination platforms, especially for postgraduate higher educational levels. Full article
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Open AccessSystematic Review
Should We Be Concerned about How Information Privacy Concerns Are Measured in Online Contexts? A Systematic Review of Survey Scale Development Studies
Informatics 2021, 8(2), 31; https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020031 - 24 Apr 2021
Viewed by 318
Abstract
This systematic review addresses problems identified in existing research on survey measurements of individuals’ information privacy concerns in online contexts. The search in this study focused on articles published between 1996 and 2019 and yielded 970 articles. After excluding duplicates and screening for [...] Read more.
This systematic review addresses problems identified in existing research on survey measurements of individuals’ information privacy concerns in online contexts. The search in this study focused on articles published between 1996 and 2019 and yielded 970 articles. After excluding duplicates and screening for eligibility, we were left with 13 articles in which the investigators developed a total of 16 survey scales. In addition to reviewing the conceptualizations, contexts, and dimensionalities of the scales, we evaluated the quality of methodological procedures used in the scale development process, drawing upon the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) Risk of Bias checklist. The results confirmed that the breadth of conceptualizations and dimensions of information privacy concerns are constructed with a low emphasis on contextuality. Assessment of the quality of methodological procedures suggested a need for a more thorough evaluation of content validity. We provide several recommendations for tackling these issues and propose new research directions. Full article
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Open AccessArticle
Embracing Industry 4.0: Empirical Insights from Malaysia
Informatics 2021, 8(2), 30; https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020030 - 22 Apr 2021
Viewed by 263
Abstract
Industry 4.0 revolution, with its cutting-edge technologies, is an enabler for businesses, particularly in reducing the cost and improving the productivity. However, a large number of organizations are still too in their infancy to leverage the true potential of Industry 4.0 and its [...] Read more.
Industry 4.0 revolution, with its cutting-edge technologies, is an enabler for businesses, particularly in reducing the cost and improving the productivity. However, a large number of organizations are still too in their infancy to leverage the true potential of Industry 4.0 and its technologies. This paper takes a quantitative approach to reveal key insights from the companies that have implemented Industry 4.0 technologies. For this purpose, 238 technology companies in Malaysia were studied through a survey questionnaire. As technology companies are usually the first in line to adopt new technologies, they can be studied better as leaders in adopting the latest technologies. The findings of this descriptive study surfaced an array of insights in terms of Industry 4.0 readiness, Industry 4.0 technologies, leadership, strategy, and innovation. This research paper contributes by providing 10 key empirical insights on Industry 4.0 that can be utilized by managers to pace up their efforts towards digital transformation, and can help the policymakers in drafting the right policy to drive the digital revolution. Full article
Open AccessArticle
Academic Activities Recommendation System for Sustainable Education in the Age of COVID-19
Informatics 2021, 8(2), 29; https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020029 - 20 Apr 2021
Viewed by 301
Abstract
Currently, universities are going through a critical moment due to the coronavirus disease in 2019. To prevent its spread, countries have declared quarantines and isolation in all sectors of society. This has caused many problems in the learning of students, since, when moving [...] Read more.
Currently, universities are going through a critical moment due to the coronavirus disease in 2019. To prevent its spread, countries have declared quarantines and isolation in all sectors of society. This has caused many problems in the learning of students, since, when moving from a face-to-face educational model to a remote model, several academic factors such as psychological, financial, and methodological have been overlooked. To exactly identify the variables and causes that affect learning, in this work a data analysis model using a Hadoop framework is proposed. By processing the data, it is possible to identify and classify students to determine the problems they present in different learning activities. The results are used by an artificial intelligence system that takes student information and converts it into knowledge, evaluates the academic performance problems they present, and determines what type of activity aligns with the students. The artificial intelligence system processes the information and recommends activities that focus on each student’s abilities and needs. The integration of these systems to universities creates an adaptive educational model that responds to the new challenges of society. Full article
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Open AccessOpinion
Patient Care, Information, Communication and Social Media Influencing Bias—A Discourse
Informatics 2021, 8(2), 28; https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020028 - 18 Apr 2021
Viewed by 303
Abstract
Misinformation and disinformation are prevalent across society today, their rise to prominence developed mainly through the expansion of social media. Communication has always been recognised in health and care settings as the most important element between people who are receiving care and those [...] Read more.
Misinformation and disinformation are prevalent across society today, their rise to prominence developed mainly through the expansion of social media. Communication has always been recognised in health and care settings as the most important element between people who are receiving care and those delivering, managing, and evaluating care. This paper, through a discourse approach, will explore communication through the perception of information formed following personal selection of influencers and try to determine how such affects patient care. Full article
(This article belongs to the Special Issue Nursing Informatics: Consumer-Centred Digital Health)
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Open AccessArticle
Benchmarking Machine Learning Models to Assist in the Prognosis of Tuberculosis
Informatics 2021, 8(2), 27; https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020027 - 15 Apr 2021
Viewed by 537
Abstract
Tuberculosis (TB) is an airborne infectious disease caused by organisms in the Mycobacterium tuberculosis (Mtb) complex. In many low and middle-income countries, TB remains a major cause of morbidity and mortality. Once a patient has been diagnosed with TB, it is critical that [...] Read more.
Tuberculosis (TB) is an airborne infectious disease caused by organisms in the Mycobacterium tuberculosis (Mtb) complex. In many low and middle-income countries, TB remains a major cause of morbidity and mortality. Once a patient has been diagnosed with TB, it is critical that healthcare workers make the most appropriate treatment decision given the individual conditions of the patient and the likely course of the disease based on medical experience. Depending on the prognosis, delayed or inappropriate treatment can result in unsatisfactory results including the exacerbation of clinical symptoms, poor quality of life, and increased risk of death. This work benchmarks machine learning models to aid TB prognosis using a Brazilian health database of confirmed cases and deaths related to TB in the State of Amazonas. The goal is to predict the probability of death by TB thus aiding the prognosis of TB and associated treatment decision making process. In its original form, the data set comprised 36,228 records and 130 fields but suffered from missing, incomplete, or incorrect data. Following data cleaning and preprocessing, a revised data set was generated comprising 24,015 records and 38 fields, including 22,876 reported cured TB patients and 1139 deaths by TB. To explore how the data imbalance impacts model performance, two controlled experiments were designed using (1) imbalanced and (2) balanced data sets. The best result is achieved by the Gradient Boosting (GB) model using the balanced data set to predict TB-mortality, and the ensemble model composed by the Random Forest (RF), GB and Multi-Layer Perceptron (MLP) models is the best model to predict the cure class. Full article
(This article belongs to the Special Issue Machine Learning in Healthcare)
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Open AccessArticle
Information Technology Governance for Higher Education Institutions: A Multi-Country Study
Informatics 2021, 8(2), 26; https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020026 - 13 Apr 2021
Viewed by 280
Abstract
Information Technology governance (ITG) calls for the definition and implementation of formal practices at the highest level in the organization, involving structures, processes and relational practices for the creation of business value from IT investments. However, determining the right ITG practices remains a [...] Read more.
Information Technology governance (ITG) calls for the definition and implementation of formal practices at the highest level in the organization, involving structures, processes and relational practices for the creation of business value from IT investments. However, determining the right ITG practices remains a complex endeavor. Previous studies identify IT governance practices used in the health and financial sectors. As universities have many unique characteristics, it is highly unlikely that the ITG experiences of the financial and health industry can be directly applied to universities. This study, using Design Science Research (DSR), develops a baseline with advised practices for the university sector. The analysis of thirty-four case studies from the literature review provides a set of practices as a starting point for the development of the baseline model proposal through multiple case studies involving interviews with IT directors, in ten universities in five countries: eight new practices emerge in this study. The model proposed was evaluated by experts. The result is a baseline model with adequate practices for IT governance in universities as well as a set of guidelines for its implementation. Findings revealed that is possible to extend the ITG practices’ baseline when looking at specific contexts. Full article
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Open AccessReview
Technological Aspects for Pleasant Learning: A Review of the Literature
Informatics 2021, 8(2), 25; https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020025 - 08 Apr 2021
Viewed by 375
Abstract
The teaching–learning process, at each educational level, is often an open problem for educators and researchers related to the stated topic. Researchers combine emerging technologies to formulate learning tools in order to understand the abstract contents of the subjects; however, the problem still [...] Read more.
The teaching–learning process, at each educational level, is often an open problem for educators and researchers related to the stated topic. Researchers combine emerging technologies to formulate learning tools in order to understand the abstract contents of the subjects; however, the problem still persists. A technological learning tool would be effective when projected into an educational model that looks at motivation, usability, engagement, and technological acceptability. Some of these aspects could be attributed through the use of augmented reality and games. The aim of this work is to analyze, in the literature, the trends of learning models based on computer technologies for an effective and enjoyable learning activity. The analysis of the literature in that context—emphasizing acceptability, categories, entertainment, educational models—shows that it is still not well explored. Full article
(This article belongs to the Section Human-Computer Interaction)
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Open AccessArticle
Acceptance of Google Meet during the Spread of Coronavirus by Arab University Students
Informatics 2021, 8(2), 24; https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020024 - 30 Mar 2021
Viewed by 737
Abstract
The COVID-19 pandemic not only affected our health and medical systems but also has created large disruption of education systems at school and universities levels. According to the United Nation’s report, COVID-19 has influenced more than 1.6 billion learners from all over the [...] Read more.
The COVID-19 pandemic not only affected our health and medical systems but also has created large disruption of education systems at school and universities levels. According to the United Nation’s report, COVID-19 has influenced more than 1.6 billion learners from all over the world (190 countries or more). To tackle this problem, universities and colleges have implemented various technologically based platforms to replace the physical classrooms during the spread of Coronavirus. The effectiveness of these technologies and their educational impact on the educational sector has been the concern of researchers during the spread of the pandemic. Consequently, the current study is an attempt to explore the effect of Google Meet acceptance among Arab students during the pandemic in Oman, UAE, and Jordan. The perceived fear factor is integrated into a hybrid model that combines crucial factors in TAM (Technology acceptance Model) and VAM (Value-based Adoption Model). The integration embraces perceived fear factor with other important factors in TAM perceived ease of use (PEOU) and perceived usefulness (PU) on the one hand and technically influential factor of VAM, which are perceived technicality (PTE) and perceived enjoyment (PE) on the other hand. The data, collected from 475 participants (49% males and 51% females students), were analyzed using the partial least squares-structural equation modelling (PLS-SEM). The results have shown that TAM hypotheses of usefulness and easy to use have been supported. Similarly, the results have supported the hypotheses related to VAM factors of being technically useful and enjoying, which helps in reducing the atmosphere of fear that is created due to the spread of Coronavirus. Full article
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Open AccessArticle
Feasibility Study on the Role of Personality, Emotion, and Engagement in Socially Assistive Robotics: A Cognitive Assessment Scenario
Informatics 2021, 8(2), 23; https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020023 - 26 Mar 2021
Viewed by 476
Abstract
This study aims to investigate the role of several aspects that may influence human–robot interaction in assistive scenarios. Among all, we focused on semi-permanent qualities (i.e., personality and cognitive state) and temporal traits (i.e., emotion and engagement) of the user profile. To this [...] Read more.
This study aims to investigate the role of several aspects that may influence human–robot interaction in assistive scenarios. Among all, we focused on semi-permanent qualities (i.e., personality and cognitive state) and temporal traits (i.e., emotion and engagement) of the user profile. To this end, we organized an experimental session with 11 elderly users who performed a cognitive assessment with the non-humanoid ASTRO robot. ASTRO robot administered the Mini Mental State Examination test in Wizard of Oz setup. Temporal and long-term qualities of each user profile were assessed by self-report questionnaires and by behavioral features extrapolated by the recorded videos. Results highlighted that the quality of the interaction did not depend on the cognitive state of the participants. On the contrary, the cognitive assessment with the robot significantly reduced the anxiety of the users, by enhancing the trust in the robotic entity. It suggests that the personality and the affect traits of the interacting user have a fundamental influence on the quality of the interaction, also in the socially assistive context. Full article
(This article belongs to the Special Issue Feature Paper in Informatics)
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Open AccessArticle
Two-Way Contact Network Modeling for Identifying the Route of COVID-19 Community Transmission
Informatics 2021, 8(2), 22; https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020022 - 25 Mar 2021
Viewed by 509
Abstract
In this study, we address the problem originated from the fact that “The Corona 19 Epidemiological Research Support System,” developed by the Korea Centers for Disease Control and Prevention, is limited to analyzing the Global Positioning System (GPS) information of the confirmed COVID-19 [...] Read more.
In this study, we address the problem originated from the fact that “The Corona 19 Epidemiological Research Support System,” developed by the Korea Centers for Disease Control and Prevention, is limited to analyzing the Global Positioning System (GPS) information of the confirmed COVID-19 cases alone. Consequently, we study a method that the authority predicts the transmission route of COVID-19 between visitors in the community from a spatiotemporal perspective. This method models a contact network around the first confirmed case, allowing the health authorities to conduct tests on visitors after an outbreak of COVID-19 in the community. After securing the GPS data of community visitors, it traces back to the past from the time the first confirmed case occurred and creates contact clusters at each time step. This is different from other researches that focus on identifying the movement paths of confirmed patients by forward tracing. The proposed method creates the contact network by assigning weights to each contact cluster based on the degree of proximity between contacts. Identifying the source of infection in the contact network can make us predict the transmission route between the first confirmed case and the source of infection and classify the contacts on the transmission route. In this experiment, we used 64,073 simulated data for 100 people and extracted the transmission route and a top 10 list for centrality analysis. The contacts on the route path can be quickly designated as a priority for COVID-19 testing. In addition, it is possible for the authority to extract the subjects with high influence from the centrality theory and use them for additional COVID-19 epidemic investigation that requires urgency. This model is expected to be used in the epidemic investigation requiring the quick selection of close contacts. Full article
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Open AccessArticle
Voltage-Based Hybrid Algorithm Using Parameter Variations and Stockwell Transform for Islanding Detection in Utility Grids
Informatics 2021, 8(2), 21; https://0-doi-org.brum.beds.ac.uk/10.3390/informatics8020021 - 25 Mar 2021
Viewed by 399
Abstract
This paper has introduced an algorithm for the identification of islanding events in the remotely located distribution grid with renewable energy (RE) sources using the voltage signals. Voltage signal is processed using Stockwell transform (ST) to compute the median-based islanding recognition factor (MIRF). [...] Read more.
This paper has introduced an algorithm for the identification of islanding events in the remotely located distribution grid with renewable energy (RE) sources using the voltage signals. Voltage signal is processed using Stockwell transform (ST) to compute the median-based islanding recognition factor (MIRF). The rate of change in the root mean square (RMS) voltage is computed by differentiating the RMS voltage with respect to time to compute the voltage rate of change in islanding recognition factor (VRCIRF). The proposed voltage-based islanding recognition factor (IRFV) is computed by multiplying the MIRF and VRCIRF element to element. The islanding event is discriminated from the faulty and operational events using the simple decision rules using the peak magnitude of IRFV by comparing peak magnitude of IRFV with pre-set threshold values. The proposed islanding detection method (IDM) effectively identified the islanding events in the presence of solar energy, wind energy and simultaneous presence of both wind and solar energy at a fast rate in a time period of less than 0.05 cycles compared to the voltage change rate (ROCOV) and frequency change rate (ROCOF) IDM that detects the islanding event in a time period of 0.25 to 0.5 cycles. This IDM provides a minimum non-detection zone (NDZ). This IDM efficiently discriminated the islanding events from the faulty and switching events. The proposed study is performed on an IEEE-13 bus test system interfaced with renewable energy (RE) generators in a MATLAB/Simulink environment. The performance of the proposed IDM is better compared to methods based on the use of ROCOV, ROCOF and discrete wavelet transform (DWT). Full article
(This article belongs to the Special Issue Digitalisation, Green Deal and Sustainability)
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