18 research outputs found
Impacts of Block-based Programming on Young Learners' Programming Skills and Attitudes in the Context of Smart Environments
No full textInexperienced and young learners typically have difficulties with respect to programming experiences and activities. These difficulties are mainly because of their lack of syntactic knowledge, conceptual knowledge, and strategic knowledge. Considering the complexity of introductory programming for the learners, visual programming has become more and more popular. In particular, block-based programming has emerged as an area of active research.
Block-based programming environments have become the standard medium of instruction in the design of introductory programming courses for young learners. As a result, they are employed by researchers and educators to enable learners to learn programming and author computer programs. In addition to these programming environments, an interesting and motivating context is needed to encourage young learners to start with programming activities. Scientific works emphasize that tangible interactive objects benefit learning, especially for young learners. Moreover, countless block-based programming environments have been employed together with these objects in order to improve the learners' emotional engagement, attitudes, and their computer programming performance. Nevertheless, we have a lack of investigation on the impacts of new and powerful technologies (which provide possibilities to tightly connect computer science to reality and introduce the future) on young learners' programming skills and attitudes. This research is aimed at a better understanding of how the use of block-based programming together with state-of-the-art smart technologies can leverage young learners' interest in programming, and support the acquisition of programming skills
Recurrent strokes as the sole manifestation of antineutrophil cytoplasmic antibody associated vasculitis in a patientwith panuveitis: a case report
No full textAbstract Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitides (AAV) are a heterogeneous group of rare, autoimmune conditions characterized by widespread, multisystemic inflammation of small to medium-sized blood vessels. We present a case report of a 46-year-old male with a history of prior ischemic strokes and recurrent bilateral non-granulomatous panuveitis associated with a strongly positive cytoplasmic anti-neutrophil cytoplasmic antibody (c-ANCA) titer. Initial treatment with steroids, methotrexate, and rituximab were ineffective, but the condition responded moderately to cyclophosphamide. This case underscores the importance of considering AAV in patients with unexplained ocular inflammation and highlights the role of c-ANCA testing in diagnosing and managing such cases, even in the absence of classic systemic symptoms
High strain rate torsional response of maraging steel parts produced by laser powder bed fusion techniques: Deformation behavior and constitutive model
No full textThe deformation performance of maraging steel samples fabricated using the laser powder bed fusion technique was evaluated using the split Hopkinson torsion bar (SHTB) test. Thin-walled tubular maraging steel samples were deformed under dynamic torsional loading at strain rates of 260 s−1 to 720 s−1 using twist angles varying from 3 to 12°. Microstructural and textural investigations were carried out on deformed samples using the electron backscatter diffraction technique and scanning electron microscopy. Results showed that maraging steel samples fractured when deformed using an angle of twist of 12° and strain rate of 650 s−1. As a result of deformation localization at high strain rates, adiabatic shear bands are developed in some thin-walled tubular torsion specimens deformed using the 12-degree angle of twist, leading to fracture. Textural studies showed that texture weakening occurred with an increment in strain rate ascribable to grain fragmentation. In this study, two models (empirically and semi-empirically) were employed for describing maraging steel performance during high strain-rate torsional loading. Simulation results based on Kobayashi-Odd and Nemat-Nasser models agreed well with the experimental data.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Team Kevin Ross
Emergency Room Visits in Patients with Left Ventricular Dysfunction Receiving Hemodialysis : A Case Control Study
No full textIntroduction: Chronic kidney disease (CKD) prevalence in Saudi Arabia has been rising over the past few years. The risk of developing left ventricular dysfunction is high in patients with CKD on hemodialysis. Our aim is to study the frequency of emergency room visits and the length of ER stay in patients with LVD on hemodialysis.Methods: All patients who were on hemodialysis between the period of January 2011 and November 2016 were included in our study. Patients’ demographic, medical, and laboratory data were extracted for all patients. Patients were classified into three groups according to their ejection fraction (EF<40%, EF= 40-49%, and EF≥50%). Descriptive statistics were done for all variables. Logistic regression was used to assess the outcome while adjusting for confounder.Results: Analysis included 333 patients. Two hundred and fifty-seven patients had an EF ³50% and 36 patients with EF 40-49% and 40 patients with EF <40 %. Age was significantly higher in patients with EF<50% compared to patients with EF ³50% (P=0.002). Comorbidities were more prevalent in patients with EF<40% and EF 40-49%. The number of ER visits and length of stay were significantly different between the three groups (P=0.005, P=0.023) ICU admissions show a statistically significant difference between the three groups (P=0.013).Conclusion: Patients with low EF on hemodialysis have a higher rate of ER visits and length of stay in ER when compared to patients with EF≥50
Additional file 2 of Population-level investigation of the knowledge of ocular chemical injuries and proper immediate action
No full textAdditional file 2: Table S2. Educational level of the respondents. Most of the respondents had a bachelor’s degree (575, 64.8%)
Additional file 4 of Population-level investigation of the knowledge of ocular chemical injuries and proper immediate action
No full textAdditional file 4: Table S4. Type of jobs among respondents. About 286 (32.2%) respondents had an office job, and 160 (18.0%) worked in the medical field
Additional file 1 of Population-level investigation of the knowledge of ocular chemical injuries and proper immediate action
No full textAdditional file 1: Table S1. Sex characteristics of the respondents. Most of our study participants were female (624, 70.3%)
Additional file 3 of Population-level investigation of the knowledge of ocular chemical injuries and proper immediate action
No full textAdditional file 3: Table S3. Jobs of the respondents. About 234 (26.4%) respondents were students, and 249 (28.0%) worked in the government sector, while 215 (24.2%) were homemakers or unemployed
RoADS: A road pavement monitoring system for anomaly detection using smart phones
Get PDFAbstract. Monitoring the road pavement is a challenging task. Author-ities spend time and finances to monitor the state and quality of the road pavement. This paper investigate road surface monitoring with smart-phones equipped with GPS and inertial sensors: accelerometer and gy-roscope. In this study we describe the conducted experiments with data from the time domain, frequency domain and wavelet transformation, and a method to reduce the effects of speed, slopes and drifts from sen-sor signals. A new audiovisual data labelling technique is proposed. Our system named RoADS, implements wavelet decomposition analysis for signal processing of inertial sensor signals and Support Vector Machine (SVM) for anomaly detection and classification. Using these methods we are able to build a real time multi class road anomaly detector. We obtained a consistent accuracy of ≈90 % on detecting severe anomalies regardless of vehicle type and road location. Local road authorities and communities can benefit from this system to evaluate the state of their road network pavement in real time.
