Revisiting the Internet of Things: New Trends, Opportunities and Grand Challenges

The Internet of Things (IoT) has brought the dream of ubiquitous data access from physical environments into reality. IoT embeds sensors and actuators in physical objects so that they can communicate and exchange data between themselves to improve efficiency along with enabling real-time intelligent services and offering better quality of life to people. The number of deployed IoT devices has rapidly grown in the past five years in a way that makes IoT the most disruptive technology in recent history. In this paper, we reevaluate the position of IoT in our life and provide deep insights on its enabling technologies, applications, rising trends and grand challenges. The paper also highlights the role of artificial intelligence to make IoT the top transformative technology that has been ever developed in human history

Blended MOOCs acceptance and use: A cross-cultural study of the factors affecting lecturers' use of bMOOCs

Massive Open Online Courses (MOOCs) have a significant impact on traditional teaching and learning in Higher Education institutions. Specifically, the use of MOOCs contents as part of F2F courses’ activities in blended learning format, an approach called blended MOOCs (bMOOCs) and are not intended to replace traditional learning methods but rather to enhance them. Most research on bMOOCs has focused on students’ perception and institutional threats whereas there is a lack of published research on academics’ perceptions and attitude of bMOOCs. Thus, the main purpose of the study is to investigate the impact of the characteristics of MOOCs on the use of bMOOCs by lecturers in universities. Furthermore, since culture plays a significant role in how individuals adopt a new technology, the study investigates the impact within two different cultures namely, the Anglophone and the Saudi Arabian. With regards to how MOOCs could be integrated in formal education, it can be realised from the review of literature that there have been few attempts to date to describe in depth the various ways in which MOOCs have been integrated with formal teaching and learning, this means that there are few guides for practitioners and that it is difficult for the research community to compare different examples. Thus, one of the main contributions of this study is to propose a hierarchy classification of how MOOCs are used for blended learning by presenting a systematic literature review leading to an analysis of 20 different case studies, which is then validated by an independent expert review. The resulting classification model differentiates between Supplementary and Integrated bMOOCs, where Integrated can itself be broken down into models that focus on Content, Assessment, or Interaction. The study shows that there are at least eight different models for using MOOCs within formal teaching and learning. To investigate the impact of the characteristics of MOOCs on lecturers’ use of blended MOOCs, the Technology Acceptance Model (TAM) is adopted in this study to understand the individual behavioural intention to use a new technology, in our case blended MOOCs. Hence, this study proposes a new model based on the TAM model that is extended to include six external factors related to the characteristics of MOOCs namely High Quality Resources of a MOOC (QR), Availability of Useful Tools in a MOOC (AUT), Large Number of MOOCs Participants' engagement (LNP), A Completion Certificate from a MOOC (CC), MOOCs Delivery Platform’s Features (PF) and Similarity of MOOCs to Traditional Courses (STC). The aim of this model is to enable better understanding of the most influential characteristic on lecturers’ use of bMOOCs. The study follows a sequential mixed method design that gathers qualitative and quantitative data in an ordered sequence. The first phase, which included interviews with twelve experts from Computer Science and Education disciplines, provided support to the proposed model and inspired improvements. The second phase included a large-scale quantitative study that gathered data from 192 lecturers through an online questionnaire; the model was then assessed using Stepwise Regression Analysis for the two different cultures. Lastly, the results were further explained through a follow-up questionnaire from both cultures. The main finding was that the high-quality materials of MOOCs were found to be a key motivator for using MOOCs in traditional teaching in both cultures followed by the perceived usefulness of MOOCs to enhance lecturers’ performance. One interesting observation in this study was regarding Perceived Ease of Use of bMOOCs (PEOU) which was found to have no significant direct effect on lecturers’ Perceived Usefulness in the Anglophone sample and on the other hand, PEOU had no significant direct effect on the lecturers’ Behaviour intention on the Saudi sample. One of the main differences between the two cultures is that Similarity of MOOCs to Traditional Courses (STC) was found to have a significant positive effect on Perceived Usefulness in the Saudi sample whereas Similarity of MOOCs to Traditional Courses (STC) was found to have a significant negative direct effect on Perceived Ease of Use in the Anglophone sample and the follow-up questionnaire finding revealed further explanations and justifications. The research contributes to the body of knowledge in the fields of technology acceptance research, blended E-learning and cross-cultural research theoretically and practically. It also demonstrates the importance and benefits of MOOCs in traditional teaching and learning from lecturers’ perspective

A classification of how MOOCs are used for blended learning

There are many different examples of where MOOCs have been integrated into teaching and learning in a higher education context. These approaches are typically called blended MOOCs (bMOOCs) and are not intended to replace traditional learning methods but rather to enhance them. Despite increasing interest in bMOOCs there have been few attempts to date to describe with breadth the different ways in which they have been integrated with formal teaching and learning, this means that there are few guides for practitioners, and that it is difficult for the research community to compare different examples. This paper proposes a hierarchy classification of how blended MOOCs are used by presenting a systematic literature review leading to an analysis of 20 different case studies, which is then validated by an independent expert review. The resulting classification model differentiates between Supplementary and Integrated bMOOCs, where Integrated can itself be broken down into models that focus on Content, Assessment, or Interaction. Our work shows that there are at least eight different models for using bMOOCs within formal teaching and learning, although most of the existing research focuses on the Flipped Classroom model (a sub-type of the Content model). Our work therefore reveals gaps in the current understanding of bMOOCs, and will also help to contextualize and scope future research and analysis

A Comparative Study on Traffic Modeling Techniques for Predicting and Simulating Traffic Behavior

The significant advancements in intelligent transportation systems (ITS) have contributed to the increased development in traffic modeling. These advancements include prediction and simulation models that are used to simulate and predict traffic behaviors on highway roads and urban networks. These models are capable of precise modeling of the current traffic status and accurate predictions of the future status based on varying traffic conditions. However, selecting the appropriate traffic model for a specific environmental setting is challenging and expensive due to the different requirements that need to be considered, such as accuracy, performance, and efficiency. In this research, we present a comprehensive literature review of the research related to traffic prediction and simulation models. We start by highlighting the challenges in the long-term and short-term prediction of traffic modeling. Then, we review the most common nonparametric prediction models. Lastly, we look into the existing literature on traffic simulation tools and traffic simulation algorithms. We summarize the available traffic models, define the required parameters, and discuss the limitations of each model. We hope that this survey serves as a useful resource for traffic management engineers, researchers, and practitioners in this domain

<i>Stenotrophomonas maltophilia</i> Epidemiology, Resistance Characteristics, and Clinical Outcomes: Understanding of the Recent Three Years’ Trends

Background. Stenotrophomonas maltophilia is an emerging pathogen classified as a public health concern, that infects critically ill patients and has expressed resistance against antimicrobial therapy. The aim of this study was to examine the epidemiological pattern, resistance characteristics and clinical outcomes of S. maltophilia infections in hospitalized patients. Methods. The study included 393 S. maltophilia isolates from different clinical specimens as well as the clinical data of 209 Intensive Care Unit (ICU) patients. The patients’ data were obtained from medical and laboratory files. Descriptive statistics and a univariate analysis were used to report and compare the demographics, clinical data, and outcomes. Results. The S. maltophilia was mostly isolated from the respiratory specimens of ICU patients. The adult patients were more likely to develop serious infections and worse outcomes than were pediatric patients. The most common co-infecting pathogens were SARS-CoV2 and Pseudomonas aeruginosa. The death rate was 44.5% and increased to 47.1% in the case of a respiratory infection. Septic shock was the most significant predictor of mortality. Older age and mechanical ventilation were independent and significant risk factors that worsened the outcomes in patients with respiratory infections. Conclusions. The identification of S. maltophilia as a threat highlights the importance of surveillance studies in this region

Appropriateness of acid-suppressing agents for stress ulcer prophylaxis in non-intensive care unit setting in Saudi Arabia

Objective: To investigate the appropriateness of acid-suppressive therapy (AST) for stress ulcer prophylaxis (SUP) in noncritically ill hospitalized patients. Materials and Methods: A prospective, observational study with 384 subjects was conducted between October and December 2017 in the emergency and internal medicine departments. The Herzig clinical risk scoring system and the guidelines of the American Society of Health-System Pharmacists guidelines were used to assess risk factors and determine risk scores for gastrointestinal (GI) bleeding. Results: The mean age of subjects was 51.9±19.4 years, and 220 (57.3%) of them were males. Among the absolute risk factors, coagulopathy was observed in 2 (0.5%) patients, mechanical ventilation in 15 (3.9%), and a history of GI bleeding in 1 (0.3%). Of 384 patients with SUP, 370 (96.4%) had a clinical risk score ≤ 9 and 14 (3.6%) had a risk score between 10 and 12 for nosocomial GI bleeding. A statistically significant relationship was found between the risk factor indication and demographics. Conclusion: SUP is frequently administered to noncritically ill hospitalized patients lacking risk factors for GI bleeding. Proton pump inhibitors are the overwhelming first choice of AST among prescribers. Practitioners should follow international guidelines when prescribing ASTs outside the critical-care setting

The Potential Effect of the IDH1 Mutation and MGMT Gene Promoter Methylation on the Control of Glioblastoma-Associated Epilepsy in Patients Receiving Anti-Epileptic Agents and Chemotherapies

Objectives:(a) The objective of the study was to assess the control of seizure in glioblastoma patients receiving anti-epileptic drugs and chemotherapies after total resection and its association with O-methylguanine-DNA methyltransferase (MGMT) promoter methylation and the isocitrate dehydrogenase 1 (IDH1) mutation; (b) to determine which anti-epileptic drug exerts the best effective control on glioblastoma-associated epilepsy; and (c) to identify the relationship between seizure control and anti-epileptic drugs with recurrence interval.Methods:This was a retrospective cohort study of patients with postoperative glioblastoma-associated epilepsy. The correlation between IDH1 mutation and MGMT methylation with anti-epileptic drugs, chemotherapy type, seizure control, and recurrence interval was analyzed.Results:The study included 53 patients with glioblastoma-associated epilepsy. IDH1 mutation was present in 20 patients, and MGMT methylation was present in 13 patients. 37 cases received chemoradiotherapy while 16 cases received only radiotherapy. Levetiracetam was the most prescribed anti-epileptic drug (n=36, 60%), and 36 and 16 patients had controlled and uncontrolled seizures, respectively. IDH1 mutation and unmethylated MGMT were significantly present in cases with controlled epilepsy (p<0.05). Levetiracetam showed significantly better seizure control in cases with IDH1 mutation and unmethylated MGMT promotor (p<0.05).Conclusion:(a) Glioblastoma-associated epilepsy can be better controlled in patients with the IDH1 mutation and unmethylated MGMT, (b) levetiracetam was the first-line anti-epileptic drug for controlling seizure, (c) lack of seizure control in glioblastoma patients may not be related to tumor recurrence despite 1-year treatment, and (d) better understanding of the risk factors associated with glioma-associated epilepsy are needed to improve patient quality of life

Klebsiella pneumoniae bacteraemia epidemiology: resistance profiles and clinical outcome of King Fahad Medical City isolates, Riyadh, Saudi Arabia

Abstract Background and objectives Klebsiella pneumoniae (K. pneumoniae) is the second leading cause of community-acquired and hospital-acquired gram-negative bloodstream infection (BSI). This study aimed to assess the epidemiological and microbial-resistance characteristics and clinical factors associated with K. pneumoniae BSI in Saudi Arabia. Materials and Methods Data of 152 K. pneumoniae isolates diagnosed between January 2019 and January 2020 at King Fahad Medical City, Riyadh, Saudi Arabia were evaluated retrospectively. Clinical records of the patients were collected and analysed statistically. Results In total, 152 cases of K. pneumoniae BSI were identified. Adult patients (66.4%) were at a higher risk of developing the infection than paediatric patients (33.6%). The rate of infection was slightly higher in women than in men. Neurological disorders were the predominant underlying conditions for the acquisition of K. pneumoniae BSI, at all ages. Most of the deceased patients were adults with multi-organ dysfunction. Klebsiella pneumoniae showed disturbing resistance to amoxicillin-clavulanate and cefuroxime (72.4%), ceftazidime (67.8), cephalothin (76.3%), and to Carbapenems (36.1%). Conclusions The impact of K. pneumoniae BSI was seen not only at the patient level, but also at the community level, and was related to multi-drug resistant infection. These findings provide a better understanding of microbial resistance and its association with patient clinical outcomes