Distributed-based massive processing of activity logs for efficient user modeling in a Virtual Campus

This paper reports on a multi-fold approach for the building of user models based on the identification of navigation patterns in a virtual campus, allowing for adapting the campus’ usability to the actual learners’ needs, thus resulting in a great stimulation of the learning experience. However, user modeling in this context implies a constant processing and analysis of user interaction data during long-term learning activities, which produces huge amounts of valuable data stored typically in server log files. Due to the large or very large size of log files generated daily, the massive processing is a foremost step in extracting useful information. To this end, this work studies, first, the viability of processing large log data files of a real Virtual Campus using different distributed infrastructures. More precisely, we study the time performance of massive processing of daily log files implemented following the master-slave paradigm and evaluated using Cluster Computing and PlanetLab platforms. The study reveals the complexity and challenges of massive processing in the big data era, such as the need to carefully tune the log file processing in terms of chunk log data size to be processed at slave nodes as well as the bottleneck in processing in truly geographically distributed infrastructures due to the overhead caused by the communication time among the master and slave nodes. Then, an application of the massive processing approach resulting in log data processed and stored in a well-structured format is presented. We show how to extract knowledge from the log data analysis by using the WEKA framework for data mining purposes showing its usefulness to effectively build user models in terms of identifying interesting navigation patters of on-line learners. The study is motivated and conducted in the context of the actual data logs of the Virtual Campus of the Open University of Catalonia.Peer ReviewedPostprint (author's final draft

DSpace How-To Guide: Tips and tricks for managing common DSpace chores

This short booklet is intended to introduce the commonest non-obvious customization-related tasks for newcomers to DSpace administration. It has been written against the current stable version 1.3.2 of DSpace. We have tried to include instructions for different operating systems as required; most customizations, however, work identically cross-platform. This booklet was created as a handout for the tutorial "Making DSpace Your Own", at the Joint Conference on Digital Libraries (JCDL) 2006 in Chapel Hill, North Carolina.unpublishednot peer reviewe

DSpace How-To Guide: Tips and tricks for managing common DSpace chores

PDF fileThis short booklet is intended to introduce the commonest non-obvious customization related tasks for newcomers to DSpace administration. It has been written against the current stable version 1.3.2 of DSpace. We have tried to include instructions for different operating systems as required; most customizations, however, work identically cross-platform

Performance scalability analysis of JavaScript applications with web workers

Web applications are getting closer to the performance of native applications taking advantage of new standard–based technologies. The recent HTML5 standard includes, among others, the Web Workers API that allows executing JavaScript applications on multiple threads, or workers. However, the internals of the browser’s JavaScript virtual machine does not expose direct relation between workers and running threads in the browser and the utilization of logical cores in the processor. As a result, developers do not know how performance actually scales on different environments and therefore what is the optimal number of workers on parallel JavaScript codes. This paper presents the first performance scalability analysis of parallel web apps with multiple workers. We focus on two case studies representative of different worker execution models. Our analyses show performance scaling on different parallel processor microarchitectures and on three major web browsers in the market. Besides, we study the impact of co–running applications on the web app performance. The results provide insights for future approaches to automatically find out the optimal number of workers that provide the best tradeoff between performance and resource usage to preserve system responsiveness and user experience, especially on environments with unexpected changes on system workload.Peer ReviewedPostprint (author's final draft

Jefferson Groundwater Investigation Green County, Iowa, December 2013

This report details the scientific work completed by Iowa DNR IGWS and delineates the source water capture zones for the City of Jefferson. These areas were created to assist with best management practices to protect the quality of groundwater and reduce the potential for surface contamination that could impact groundwater supplies. The objective of this investigation is to refine source water capture zones, a computermodeled source water area, typically using 2-, 5- and 10-yr. time-of-travel periods, for the City of Jefferson. A source water assessment, completed in 2012 for the City of Jefferson, contained fixed radius circle capture zones due to a lack of aquifer information

Web Engineering: A Quantitative Methodology for Quality Evaluation and Comparison of Web Applications

This research is aimed at defining and discussing a quantitative methodology, the one integral, robust and flexible, for the quality evaluation and comparison of Web sites and applications (WebApps). The approach, from now on called Web-site Quality Evaluation Methodology (Web-site QEM) is intended to perform an engineering contribution proposing for such an end a systematic, disciplined and quantitative strategy customized to the evaluation, comparison, and analysis of the quality of somewhat complex WebApps. We analyze their phases and activities, we describe the produced deliverables, and we present models, methods, procedures, principles and tools to apply in these activities. We outline the approach and its solutions, using along the thesis two case studies for WebApps, and other carried out field studies. In addition, we present a conceptual framework for metric validation and we discuss the theoretical validation of some utilized metrics in the evaluation process. Finally, we describe thoroughly an evaluation process model which Web-site QEM adheres. In this report, just the main methodology’s steps are shown. Besides, some specific models, criteria and procedures to apply in these activities are discussed by quoting case studies already performed (e.g., in the academic domain as well as in museums and e-commerce domain, i.e., international e-bookstores ).Sociedad Argentina de Informática e Investigación Operativ

Jefferson groundwater investigation Greene County, Iowa

https://ir.uiowa.edu/igs_tis/1054/thumbnail.jp

Aquifer Characterization and Drought Assessment Rock River Alluvial Aquifer

This investigation evaluated groundwater resources of the alluvial aquifer located adjacent to the ock River. Recent drought conditions prompted this study and can have a dramatic affect on groundwater resources. The primary objective of this study was to evaluate the aquifer to aid in future water supply development. Existing geologic information combined with geophysical surveys and drilling were compiled to better understand the extent and thicknesses of coarse grained alluvium. Several hydrogeologic parameters were gathered to estimate well potential in the aquifer. The study can be referenced when considering future development or well field expansion.https://ir.uiowa.edu/igs_wrir/1011/thumbnail.jp

Classroom Research and the Digital Learning Media

Udostępnienie publikacji Wydawnictwa Uniwersytetu Łódzkiego finansowane w ramach projektu „Doskonałość naukowa kluczem do doskonałości kształcenia”. Projekt realizowany jest ze środków Europejskiego Funduszu Społecznego w ramach Programu Operacyjnego Wiedza Edukacja Rozwój; nr umowy: POWER.03.05.00-00-Z092/17-00