Computers

Atrial fibrillation (AF) and ventricular arrhythmia (Arr) are among the most common and fatal cardiac arrhythmias in the world. Electrocardiogram (ECG) data, collected as part of the UK Biobank, represents an opportunity for analysis and classification of these two diseases in the UK. The main objective of our study is to investigate a two-stage model for the classification of individuals with AF and Arr in the UK Biobank dataset. The current literature addresses heart arrhythmia classification very extensively. However, the data used by most researchers lack enough instances of these common diseases. Moreover, by proposing the two-stage model and separation of normal and abnormal cases, we have improved the performance of the classifiers in detection of each specific disease. Our approach consists of two stages of classification. In the first stage, features of the ECG input are classified into two main classes: normal and abnormal. At the second stage, the features of the ECG are further categorised as abnormal and further classified into two diseases of AF and Arr. A diverse set of ECG features such as the QRS duration, PR interval and RR interval, as well as covariates such as sex, BMI, age and other factors, are used in the modelling process. For both stages, we use the XGBoost Classifier algorithm. The healthy population present in the data, has been undersampled to tackle the class imbalance present in the data. This technique has been applied and evaluated using an ECG dataset from the UKBioBank ECG taken at rest repository. The main results of our paper are as follows: The classification performance for the proposed approach has been measured using F1 score, Sensitivity (Recall) and Specificity (Precision). The results of the proposed system are 87.22%, 88.55% and 85.95%, for average F1 Score, average sensitivity and average specificity, respectively. Contribution and significance: The performance level indicates that automatic detection of AF and Arr in participants present in the UK Biobank is more precise and efficient if done in a two-stage manner. Automatic detection and classification of AF and Arr individuals this way would mean early diagnosis and prevention of more serious consequences later in their lives. Full article

Personalisation in e-learning systems has become a major research area in recent times, as online learning is gradually evolving to become a major part of formal education. While there exist several learning management systems with a wide range of capabilities, one thing that remains inefficient is a standard framework for sharing knowledge across different platforms and, also, the inability of such systems to provide personalisation to the learning process by default. A large number of systems that have been implemented to provide personalisation apply few parameters and are course-specific; thus, flexibility, reusability, and scalability are greatly reduced. In this paper, we propose a framework for personalised learning, Weighted Agent System for Personalised E-learning Curriculum (WASPEC) implemented with Moodle, which is independent of the learning management system and provides the possibility of incorporating multiple personalisation parameters. This is accomplished with the combined use of web services, semantic web ontologies, and pedagogical agents, providing dynamic personalisation in the background of the e-learning system. This also provides added advantages of the possibility of sharing knowledge with other systems and reusability. Full article

In colocated multi-user Virtual Reality applications, relative user positions in the virtual environment need to match their relative positions in the physical tracking space. A mismatch between virtual and real relative user positions might lead to harmful events such as physical user collisions. This paper examines three calibration methods that enable colocated Virtual Reality scenarios for SLAM-tracked head-mounted displays without the need for an external tracking system. Two of these methods—fixed-point calibration and marked-based calibration—have been described in previous research; the third method that uses hand tracking capabilities of head-mounted displays is novel. We evaluated the accuracy of these three methods in an experimental procedure with two colocated Oculus Quest devices. The results of the evaluation show that our novel hand tracking-based calibration method provides better accuracy and consistency while at the same time being easy to execute. The paper further discusses the potential of all evaluated calibration methods. Full article

The website of a university is considered to be a virtual gateway to provide primary resources to its stakeholders. It can play an indispensable role in disseminating information about a university to a variety of audience at a time. Thus, the quality of an academic website requires special attention to fulfil the users’ need. This paper presents a multi-method approach of quality assessment of the academic websites, in the context of universities of Bangladesh. We developed an automated web-based tool that can evaluate any academic website based on three criteria, which are as follows: content of information, loading time and overall performance. Content of information contains many sub criteria, such as university vision and mission, faculty information, notice board and so on. This tool can also perform comparative analysis among several academic websites and generate a ranked list of these. To the best of our knowledge, this is the very first initiative to develop an automated tool for accessing academic website quality in context of Bangladesh. Beside this, we have conducted a questionnaire-based statistical evaluation among several universities to obtain the respective users’ feedback about their academic websites. Then, a ranked list is generated based on the survey result that is almost similar to the ranked list got from the University ranking systems. This validates the effectiveness of our developed tool in accessing academic website. Full article

There are areas where the competencies obtained through computer coding activities substantially overlap with life skills components. Studies of these common competencies have suggested the possibility of including these contents in a life skills program. Therefore, the purpose of this study was to develop a program through the Entry program that elementary school students could use online to improve their life skills, given the need to increase contactless online classes due to COVID-19. Eight elementary school teachers with 20 years of experience and two curriculum experts participated in the program’s development. For data collection, 360 data points were collected from eight elementary schools located in each Korean province, including urban and rural areas. SPSS 21.0 was used to analyze the data. Upon completing the 8-week program, the difference in life skills between groups was confirmed using variance analysis based on the number of implementation times, and post-hoc testing was conducted. The study’s results confirmed the difference between the groups conducted for two weeks (M = 3.22), four weeks (M = 3.25), and six weeks (M = 3.67), and the group conducted for eight weeks (M = 3.83). In other words, as the number of weeks of participation in the life skills program increased, there was a difference between groups. These findings suggest a life skills program could be included as part of Entry based computer coding activities for elementary school students through a backward curriculum. In conclusion, this study showed the possibility of using contactless online classes with free Entry-based websites to improve the life skills of elementary school students struggling at home due to COVID-19. It also showed that each elementary school teacher could operate the life skills programs as a contactless learning method using a free coding platform and manual. Full article

Most countries have active road safety policies that seek the objective of reducing deaths in traffic accidents. One of the main factors in this regard is the awareness of the safety measures, one of the most important being the correct usage of the seat belt, a device that is known to save thousands of lives every year. The presented work shows a VR-enhanced edutainment application designed to increase awareness on the use of seat belts. For this goal, a motorized rollover system was developed that, synchronized with a VR application (shown in a head-mounted display for each user inside a real car), rolls over this car with up to four passengers inside. This way, users feel the sensations of a real overturn and therefore they realize the consequences and the results of not wearing a seat belt. The system was tested for a month in the context of a road safety exhibition in Dammam, Saudi Arabia, one of the leading countries in car accidents per capita. More than 500 users tested and assessed the usefulness of the system. We measured, before and after the rollover experience, the perception of risk of not using the seat belt. Results show that awareness regarding the use of seat belts increases very significantly after using the presented edutainment tool. Full article

Deep neural networks have achieved almost human-level results in various tasks and have become popular in the broad artificial intelligence domains. Uncertainty estimation is an on-demand task caused by the black-box point estimation behavior of deep learning. The deep ensemble provides increased accuracy and estimated uncertainty; however, linearly increasing the size makes the deep ensemble unfeasible for memory-intensive tasks. To address this problem, we used model pruning and quantization with a deep ensemble and analyzed the effect in the context of uncertainty metrics. We empirically showed that the ensemble members’ disagreement increases with pruning, making models sparser by zeroing irrelevant parameters. Increased disagreement im-plies increased uncertainty, which helps in making more robust predictions. Accordingly, an energy-efficient compressed deep ensemble is appropriate for memory-intensive and uncertainty-aware tasks. Full article

Several children struggle with vision difficulties caused by problematic coordination between their left and right eye muscles, i.e., oculomotor dysfunction (OMD). Many OMDs can be improved by training the eyes via physical exercises defined and supervised by vision experts. The aim of this paper is to investigate the feasibility of utilizing Serious Games (SGs) and eye-tracking technologies (ETs) for training the eyes of children having OMD. Via these activities, a trainee can, with her eye gaze, follow objects which are moving, change their directions and speed, or pop up on the screen. The results present mapping the current physical training goals to activities for SGs using input from ETs, and illustrate this correspondence for designing and developing six games. The games’ feasibility evaluation is done via semistructured interviews and evaluating user experiences. Three vision teachers (VTs) were involved in design and development, ensuring achievement of training goals, and five VT students in evaluations. The findings demonstrate the potential of using SGs and ETs to train OMD and point to future needs for improvements. Full article

The financial crisis of the last decade has left many financial institutions with limited personnel and equipment resources. Thus, the IT departments of these institutions are being asked to explore novel approaches to resolve these constraints in a cost-effective and efficient manner. The goal of this paper is to measure the impact of modern enabling technologies, such as virtualization, in the process of replacing legacy infrastructures. This paper proposes an IT services upgrade plan approach for an organization by using modern technologies. For this purpose, research took place in an operating financial institution, which required a significant upgrade of both its service-level and its hardware infrastructure. A virtualization implementation and deployment assessment for the entire infrastructure was conducted and the resulting consolidated data are presented and analysed. The paper concludes with a five-year financial-based evaluation of the proposed approach with respect to the projection of expenditures, the return of investment and profitability. Full article

Narcolepsy with cataplexy is a severe lifelong disorder characterized, among others, by sudden loss of bilateral face muscle tone triggered by emotions (cataplexy). A recent approach for the diagnosis of the disease is based on a completely manual analysis of video recordings of patients undergoing emotional stimulation made on-site by medical specialists, looking for specific facial behavior motor phenomena. We present here the CAT-CAD tool for automatic detection of cataplexy symptoms, with the double aim of (1) supporting neurologists in the diagnosis/monitoring of the disease and (2) facilitating the experience of patients, allowing them to conduct video recordings at home. CAT-CAD includes a front-end medical interface (for the playback/inspection of patient recordings and the retrieval of videos relevant to the one currently played) and a back-end AI-based video analyzer (able to automatically detect the presence of disease symptoms in the patient recording). Analysis of patients’ videos for discovering disease symptoms is based on the detection of facial landmarks, and an alternative implementation of the video analyzer, exploiting deep-learning techniques, is introduced. Performance of both approaches is experimentally evaluated using a benchmark of real patients’ recordings, demonstrating the effectiveness of the proposed solutions. Full article

Gamified applications are regarded as useful for patients in facilitating daily self-care management and the personalization of health monitoring. This paper reports the development of a gamified application by considering a design that had previously been investigated and reported. Numerous game elements were installed in the application, which covered several tasks aimed at managing diabetes mellitus. The development process utilized the Rapid Application Development (RAD) methodology in terms of system requirements, user design, construction, and cutover; this paper refers to the user design and cutover processes. The developed application was tested through system testing and usability testing. The usability testing adopted the Software Usability Scale (SUS) to assess the usability of the application. Twenty participants were involved in the testing. The result showed that the gamified application is easy and practical to use for an individual with or without diabetes. All the provided functions worked as designed and planned, and the participants accepted their usability. Overall, this study offers a promising result that could lead to real-life implementation. Full article

The wide-spread use of wearables and the adoption of the Internet of Things (IoT) paradigm provide an opportunity to use mobile-device sensors for medical applications. Sensors available in the commonly used devices may inspire innovative solutions for physiotherapy striving for accurate and early identification of various pathologies. An essential and reliable performance measure is the ten-meter walk test, which is employed to determine functional mobility, gait, and vestibular function. Sensor-based approaches can identify the various test phases and their segmented duration, among other parameters. The measurement parameter primarily used is related to the tests’ duration, and after identifying patterns, a variety of physical treatments can be recommended. This paper reviews multiple studies focusing on automated measurements of the ten-meter walk test with different sensors. Most of the analyzed studies measure similar parameters as traditional methods, such as velocity, duration, and other involuntary and dangerous patients’ movements after stroke. That provides an opportunity to measure different parameters that can be later fed into machine learning models for analyzing more complex patterns. Full article

Literacy skills are critical for future success, yet over 60% of high school seniors lack proficient reading skills according to standardized tests. The focus on high stakes, standardized test performance may lead educators to “teach-to-the-test” rather than supporting transferable comprehension strategies that students need. StairStepper can fill this gap by blending necessary test prep and reading comprehension strategy practice in a fun, game-based environment. StairStepper is an adaptive literacy skill training game within Interactive Strategy Training for Active Reading and Thinking (iSTART) intelligent tutoring system. StairStepper is unique in that it models text passages and multiple-choice questions of high-stakes assessments, iteratively supporting skill acquisition through self-explanation prompts and scaffolded, adaptive feedback based on performance and self-explanations. This paper describes an experimental study employing a delayed-treatment control design to evaluate users’ perceptions of the StairStepper game and its influence on reading comprehension scores. Results indicate that participants enjoyed the visual aspects of the game environment, wanted to perform well, and considered the game feedback helpful. Reading comprehension scores of students in the treatment condition did not increase. However, the comprehension scores of the control group decreased. Collectively, these results indicate that the StairStepper game may fill the intended gap in instruction by providing enjoyable practice of essential reading comprehension skills and test preparation, potentially increasing students’ practice persistence while decreasing teacher workload. Full article

A programming contest generally involves the host presenting a set of logical and mathematical problems to the contestants. The contestants are required to write computer programs that are capable of solving these problems. An online judge system is used to automate the judging procedure of the programs that are submitted by the users. Online judges are systems designed for the reliable evaluation of the source codes submitted by the users. Traditional online judging platforms are not ideally suitable for programming labs, as they do not support partial scoring and efficient detection of plagiarized codes. When considering this fact, in this paper, we present an online judging framework that is capable of automatic scoring of codes by detecting plagiarized contents and the level of accuracy of codes efficiently. Our system performs the detection of plagiarism by detecting fingerprints of programs and using the fingerprints to compare them instead of using the whole file. We used winnowing to select fingerprints among k-gram hash values of a source code, which was generated by the Rabin–Karp Algorithm. The proposed system is compared with the existing online judging platforms to show the superiority in terms of time efficiency, correctness, and feature availability. In addition, we evaluated our system by using large data sets and comparing the run time with MOSS, which is the widely used plagiarism detection technique. Full article

Flying Adhoc Network (FANET) is a particular type of Mobile Adhoc Network (MANET) that consists of flying drones or unmanned aerial vehicles (UAVs). MANETs are especially useful in rural and remote areas, where the lack of public networks necessitates data delivery through mobile nodes. Additionally, FANETs provide better coverage where there is a lack of roads. Generally, the goal of FANETs is to provide multimedia data to applications such as search and rescue operations, forest fire detection, surveillance and patrol, environmental monitoring, and traffic and urban monitoring. The above applications’ performance and efficiency depend on the quality and timely delivery of these essential data from an area of interest to control centers. This paper presents a Priority-based Routing Framework for Flying Adhoc Networks (PRoFFAN) for the expedited delivery of essential multimedia data to control centers. PRoFFAN reduces the FANET application’s response time by prioritizing the sending and forwarding of critical image data from the UAV to the control center. Our motivation application is crowd management; we believe that having important image features as early as possible will save lives and enhance the crowd’s safety and flow. We integrated PRoFFAN over the RPL routing layer of Contiki-NG’s IPv6 network stack. We used simulations in Cooja to demonstrate the benefit of PRoFFAN over conventional ZigBee. Full article

This paper presents the modeling of the networks supporting today’s telemetry. The incorporation of networking features has significantly enhanced the capability and performance of modern telemetry systems. The development of Integrated Network-Enhanced Telemetry protocols and the use of networked telemetry applications has introduced a host of potential cybersecurity risks inherent in modern networking. This paper will investigate how telemetry applications are uniquely structured with wide-, local-, and micro-area networks that represent modern telemetry solutions. The development of these models and the traffic on these networks will enable analysis into the unique threats and vulnerabilities of telemetry networks. The core of this paper is the notion that telemetry networks are unique, and modeling these networks is key to the current work. The core premise of this paper is also that telemetry networks look and function like Supervisory Command and Data Acquisition (SCADA) networks. By digging deeply into both of these structures, we have shown here that SCADA architectures can be adapted to telemetry networks. This approach opens the door to a wealth of analysis, strategies, and solutions for telemetry networks that are well developed in the SCADA realm. Full article

We characterize the LoRa channel in terms of multi-path fading, loss burstiness, and assess the benefits of Forward Error Correction as well as the influence of frame length. We make these observations by synthesizing extensive experimental measurements realized with The Things Network in a medium size city. We then propose to optimize the LoRaWAN Adaptive Data Rate algorithm based on this refined LoRa channel characterization and taking into account the LoRaWAN inherent macro-diversity from multi-gateway reception. Firstly, we propose ${\mathit{ADR}}_{\mathrm{opt}}$, which adjusts Spreading Factor and frame repetition number to maintain the communication below a target Packet Error Rate ceiling with optimized Time-On-Air. Secondly, we propose ${\mathit{ADR}}_{\mathrm{IFECC}}$, an extension of ${\mathit{ADR}}_{\mathrm{opt}}$ in case an Inter-Frame Erasure Correction Code is available. The resulting protocol provides very high reliability even over low quality channels, with comparable Time on Air and similar downlink usage as the currently deployed mechanism. Simulations corroborate the analysis, both over a synthetic random wireless link and over replayed real-world packet transmission traces. Full article

In recent years, research in tracking and assessing wound severity using computerized image processing has increased. With the emergence of mobile devices, powerful functionalities and processing capabilities have provided multiple non-invasive wound evaluation opportunities in both clinical and non-clinical settings. With current imaging technologies, objective and reliable techniques provide qualitative information that can be further processed to provide quantitative information on the size, structure, and color characteristics of wounds. These efficient image analysis algorithms help determine the injury features and the progress of healing in a short time. This paper presents a systematic investigation of articles that specifically address the measurement of wounds’ sizes with image processing techniques, promoting the connection between computer science and health. Of the 208 studies identified by searching electronic databases, 20 were included in the review. From the perspective of image processing color models, the most dominant model was the hue, saturation, and value (HSV) color space. We proposed that a method for measuring the wound area must implement different stages, including conversion to grayscale for further implementation of the threshold and a segmentation method to measure the wound area as the number of pixels for further conversion to metric units. Regarding devices, mobile technology is shown to have reached the level of reliable accuracy. Full article

The COVID-19 pandemic has forced faculties including dental schools into a ‘new normal’, where the adoption of remote or distance learning is required to minimise the risk of infection. Synchronous learning historically was favoured due to the perceived advantage of ‘real time’ interactions between instructors and learners; these interactions are not always possible in asynchronous settings. However, serious games can overcome this limitation of asynchronous learning. This integrative review explores the literature on serious games in dental education, to construct a conceptual framework of their strengths in this pandemic. Following consideration of inclusion and exclusion criteria, 15 articles on 11 serious games designed for dental education were included in this review. Our investigation points to an increase in the use of serious games since 2018. The findings of the review support the use of serious games in dental education during the recent crisis. Key strengths include positive educational outcomes, enhanced engagement and motivation, interactive asynchronous distance learning, a safe learning environment, and the advantage of stealth assessment. Consequently, the ‘new normal’ in education appears to support a very promising future for serious games, particularly in dental education. A conceptual framework is proposed to inform further research across all education settings and timeframes. Full article