Evaluation of social personalized adaptive E-Learning environments : end-user point of view

The use of adaptations, along with the social affordances of collaboration and networking, carries a great potential for improving e-learning experiences. However, the review of the previous work indicates current e-learning systems have only marginally explored the integration of social features and adaptation techniques. The overall aim of this research, therefore, is to address this gap by evaluating a system developed to foster social personalized adaptive e-learning experiences. We have developed our first prototype system, Topolor, based on the concepts of Adaptive Educational Hypermedia and Social E-Learning. We have also conducted an experimental case study for the evaluation of the prototype system from different perspectives. The results show a considerably high satisfaction of the end users. This paper reports the evaluation results from end user point of view, and generalizes our method to a component-based evaluation framework

Scalable Distributed DNN Training using TensorFlow and CUDA-Aware MPI: Characterization, Designs, and Performance Evaluation

TensorFlow has been the most widely adopted Machine/Deep Learning framework. However, little exists in the literature that provides a thorough understanding of the capabilities which TensorFlow offers for the distributed training of large ML/DL models that need computation and communication at scale. Most commonly used distributed training approaches for TF can be categorized as follows: 1) Google Remote Procedure Call (gRPC), 2) gRPC+X: X=(InfiniBand Verbs, Message Passing Interface, and GPUDirect RDMA), and 3) No-gRPC: Baidu Allreduce with MPI, Horovod with MPI, and Horovod with NVIDIA NCCL. In this paper, we provide an in-depth performance characterization and analysis of these distributed training approaches on various GPU clusters including the Piz Daint system (6 on Top500). We perform experiments to gain novel insights along the following vectors: 1) Application-level scalability of DNN training, 2) Effect of Batch Size on scaling efficiency, 3) Impact of the MPI library used for no-gRPC approaches, and 4) Type and size of DNN architectures. Based on these experiments, we present two key insights: 1) Overall, No-gRPC designs achieve better performance compared to gRPC-based approaches for most configurations, and 2) The performance of No-gRPC is heavily influenced by the gradient aggregation using Allreduce. Finally, we propose a truly CUDA-Aware MPI Allreduce design that exploits CUDA kernels and pointer caching to perform large reductions efficiently. Our proposed designs offer 5-17X better performance than NCCL2 for small and medium messages, and reduces latency by 29% for large messages. The proposed optimizations help Horovod-MPI to achieve approximately 90% scaling efficiency for ResNet-50 training on 64 GPUs. Further, Horovod-MPI achieves 1.8X and 3.2X higher throughput than the native gRPC method for ResNet-50 and MobileNet, respectively, on the Piz Daint cluster.Comment: 10 pages, 9 figures, submitted to IEEE IPDPS 2019 for peer-revie

Predicting Success Study Using Students GPA Category

. Maintaining student graduation rates are the main tasks of a University. High rates of student graduation and the quality of graduates is a success indicator of a university, which will have an impact on public confidence as stakeholders of higher education and the National Accreditation Board as a regulator (government). Making predictions of student graduation and determine the factors that hinders will be a valuable input for University. Data mining system facilitates the University to create the segmentation of students' performance and prediction of their graduation. Segmentation of student by their performance can be classified in a quadrant chart is divided into 4 segments based on grade point average and the growth rate of students performance index per semester. Standard methodology in data mining i.e CRISP-DM (Cross Industry Standard Procedure for Data Mining) will be implemented in this research. Making predictions, graduation can be done through the modeling process by utilizing the college database. Some algorithms such as C5, C & R Tree, CHAID, and Logistic Regression tested in order to find the best model. This research utilizes student performance data for several classes. Parameters used in addition to GPA also included the master's students data are expected to build the student profile data. The outcome of the study is the student category based on their study performance and prediction of graduation. Based on this prediction, the university may recommend actions to be taken to improve the student achievement index and graduation rates

Implementing Integrated STEM Forensic and Soil Sciences Lab Activities to Promote Interest in STEM Careers

We implemented forensic and soil science integrated STEM lab activities with 11 middle school youth at a 4-H day camp at Purdue University. STEM perceived knowledge increased overall for participants. However, the pre- and post-assessments did not show a statistically significant difference. More students also indicated STEM career interest after participating. Because this study was exploratory and had a small sample size, more research on these integrated STEM lab activities should be conducted with larger samples

Continuous quality assessment; development of a simple computer based model for audit

Objective: Accurate assessment of quality of care is a fundamental first step in the process of quality improvement. The vast amount of data generated in a hospital mandates some form of computerization for management of information. We describe a locally developed simple computer based program to access relevant information from a hospital patient management network. The objective was to reduce the amount of manual work involved for busy clinicians attempting to audit quality of care.Methods: A single surgical procedure, Laparoscopic Cholecystectomy was chosen. Quality indicators were identified by literature review as conversion rate from laparoscopic to open cholecystectomy and length of hospital stay (LOS). A simple query was developed to extract the required information from hospital database. Commercially available spreadsheet software (Microsoft Excel) was used to calculate the rates. Outliers were defined as LOS more than 1 standard deviation from the mean. The second part of the study involved a manual review of case notes to validate the program and determine the causes for deviation from the mean.Results: The program was able to access and process data as planned. In a one-year period from March 1997 to February 1998, two hundred and thirty one laparoscopic cholecystectomies were attempted. Twenty-three were converted to open procedures given a conversion rate of 9.96%. On manual review of case notes no false positives or false negatives were found. The reasons for conversion were similar to those described in the literature. The mean length of stay for laparoscopic cholecystectomy was 3.39 days and 7.17 days for converted cases. The commonest reason for delay in discharge was noted to be non-availability of elective operating time.CONCLUSION: We have successfully developed and used a simple computer based program to access information stored in hospital patient management systems. Quality of care indicators identified from literature were used as standards. Outliers with respect to these were reviewed in detail to identify causes for deviation. The program was validated by manual review

AEGRP: an enhanced geographical routing protocol for vanet

Vehicular ad hoc network (VANET), is a derivative type of mobile ad hoc networks with its unique characteristics and an essential part of intelligent transportation system (ITS). In VANET, the vehicles can disseminate information to certain or all vehicles within a region for different applications. Applications can be categorized as safety, convenience and comfort of the driver and passengers such as traffic conditions, accident detection, roadway safety, mobile sensing, and infotainment. These promising applications require intelligent and efficient routing protocols, which are capable of adapting rapidly changing topologies, high mobility in the network. Geographic routing protocols have become a popular routing type because of its simplicity and low overhead features, but recent research has recognized these protocols are not considering many particular constraints of the vehicular environment. However, existing routing protocols offered limited performance due to frequent disconnectivity, high signal interference in the presence of obstacles and lead to network delay and overhead issues. The main objective of this paper is to design an enhanced geographical routing protocol that addresses the network delay problems and provide necessary improvements over conventional geographic routing in light of constraints of these environments

Mode of coronary revascularization and short term clinical outcomes in patients with chronic kidney disease

Abstract BACKGROUND AND OBJECTIVE: Percutaneous coronary intervention (PCI) and coronary artery bypass graft (CABG) surgery are two alternative methods for coronary revascularization, but it remains controversial as which one is associated with lower risks of worse clinical outcomes for chronic kidney disease (CKD) patients. We determined the mode of coronary revascularization (PCI vs. CABG) which is associated with lower risk of mortality and morbidity in CKD patients. METHODS: In this cross sectional study, 159 patients with CKD were enrolled from single center of coronary revascularization at Aga Khan University Hospital Karachi between January 2012 and August 2013. All patients with CKD underwent PCI or CABG. The primary outcome was in-hospital composite of death, myocardial infarction (MI), or stroke. We evaluated which mode of coronary revascularization was associated with reduced risks of clinical outcomes. RESULTS: Out of 159 patients with CKD, 85 (53.5%) received PCI and 74 (46.5%) received CABG. The primary finding of this study is that more patients with moderate to severe CKD underwent PCI and more patients with mild to moderate CKD underwent CABG. In both these categories, no difference was observed in clinical outcomes. There are few factors like age, ST- elevation myocardial infarction (STEMI), non-ST elevation myocardial infarction (NSTEMI) and number of coronary artery disease predicted PCI as treatment strategy in patients with moderate to severe CKD. CONCLUSION: Patients with moderate to severe CKD have similar rates of short term clinical outcomes whether they underwent PCI or CABG. Therefore, PCI can be acceptable and less invasive treatment option alternative to CABG, particularly in patients with moderate to severe CKD

The Effect of Using a Combination of Sorbitol and Glycerol Plasticizers on the Characterization of Edible Film from Porang (Amorphophallus oncophyllus) Starch

Edible films present an eco-friendly alternative for food packaging compared to traditional plastic materials. This study investigates the effects of glycerol and sorbitol plasticizers on the properties of edible films. The research involves crafting these films using porang (Amorphophallus Oncophyllus) starch. Glycerol plasticizers were incorporated at a concentration of 100%, while sorbitol was utilized at varying levels (0%, 25%, 50%, 75%, 100%) to evaluate their impact on film characteristics. The films were produced using the melt intercalation method at a gelatinization temperature of 80°C and a firing temperature of 70°C. Notably, the most favorable physical test outcomes were observed with adding 100% sorbitol, including thickness, density, water absorption, and degradability improvements. Meanwhile, adding 25% sorbitol yielded the highest tensile strength and elongation values

Recommendation based trust model with an effective defence scheme for MANETs

YesThe reliability of delivering packets through multi-hop intermediate nodes is a significant issue in the mobile ad hoc networks (MANETs). The distributed mobile nodes establish connections to form the MANET, which may include selfish and misbehaving nodes. Recommendation based trust management has been proposed in the literature as a mechanism to filter out the misbehaving nodes while searching for a packet delivery route. However, building a trust model that relies on the recommendations from other nodes in the network is vulnerable to the possible dishonest behaviour, such as bad-mouthing, ballot-stuffing, and collusion, of the recommending nodes. . This paper investigates the problems of attacks posed by misbehaving nodes while propagating recommendations in the existing trust models. We propose a recommendation based trust model with a defence scheme that utilises clustering technique to dynamically filter attacks related to dishonest recommendations within certain time based on number of interactions, compatibility of information and node closeness. The model is empirically tested in several mobile and disconnected topologies in which nodes experience changes in their neighbourhoods and consequently face frequent route changes. The empirical analysis demonstrates robustness and accuracy of the trust model in a dynamic MANET environment

Ferromagnetism in Li doped ZnO nanoparticles: The role of interstitial Li

ZnO nanoparticles doped with Li (Zn1−yLiyO, y ≤ 0.1) have been investigated with emphasis on the correlation between their magnetic, electronic, and structural properties. In particular, defects such as interstitial Li and Zn atoms, substitutional Li atoms, and oxygen vacancies have been identified by X-ray photoelectron spectroscopy(XPS) and their respective roles in stabilization of the magnetic moment are discussed. X-ray diffraction(XRD) and XPS give clear evidence of Li presence at both substitutional and interstitial sites. XPS studies further show that the amount of substitutional Li defects (Lizn) and interstitial Li defects (Lii) vary non-monotonically with the Li concentration, with the Lii defects being noticeably high for the y = 0.02, 0.08, and 0.10 concentrations, in agreement with the XRD results. Magnetization studies show room temperature ferromagnetism in these nanoparticles with the moment being largest for the particles with high concentration of interstitial lithium and vice versa. Both interstitialZn(Zni) defects and Zn-O bonds were determined from the Zn LMM Auger peaks; however, the variation of these with Li concentrations was not large. Oxygen vacancies (Vo) concentrations are estimated to be relatively constant over the entire Li concentration range. We relate the Lii and Zni defects to the formation and stabilization of Znvacancies and thus stabilizing the p-type ferromagnetism predicted for cation (zinc)vacancy in the ZnO type oxides