Search results for "e learning"
showing 10 items of 2703 documents
A Network-Based Framework for Mobile Threat Detection
2018
Mobile malware attacks increased three folds in the past few years and continued to expand with the growing number of mobile users. Adversary uses a variety of evasion techniques to avoid detection by traditional systems, which increase the diversity of malicious applications. Thus, there is a need for an intelligent system that copes with this issue. This paper proposes a machine learning (ML) based framework to counter rapid evolution of mobile threats. This model is based on flow-based features, that will work on the network side. This model is designed with adversarial input in mind. The model uses 40 timebased network flow features, extracted from the real-time traffic of malicious and…
A Cooperative Coevolution Framework for Parallel Learning to Rank
2015
We propose CCRank, the first parallel framework for learning to rank based on evolutionary algorithms (EA), aiming to significantly improve learning efficiency while maintaining accuracy. CCRank is based on cooperative coevolution (CC), a divide-and-conquer framework that has demonstrated high promise in function optimization for problems with large search space and complex structures. Moreover, CC naturally allows parallelization of sub-solutions to the decomposed sub-problems, which can substantially boost learning efficiency. With CCRank, we investigate parallel CC in the context of learning to rank. We implement CCRank with three EA-based learning to rank algorithms for demonstration. E…
Shared and personal learning spaces: Challenges for pedagogical design
2012
Abstract The development of new tools for collaboration, such as social software, plays a crucial role in leisure time and work activities. The aim of this article is to summarize the research in the field of computer-supported collaborative learning (CSCL). This is done particularly from the perspective of the blurred line between individual (personal) and group-level (shared) learning that the use of the new tools has forced us to re-think. First, individual and group-level perspectives to learning are discussed to make sense of the major notions of how learning is understood in CSCL research. Second, based on this theoretical grounding, it will be further elaborated what this means to th…
Teaching programming by emphasizing self-direction: How did students react to the active role required of them?
2013
Lecturing is known to be a controversial form of teaching. With massed classrooms, in particular, it tends to constrain the active participation of students. One of the remedies applied to programming education is to use technology that can vitalize interaction in the classroom, while another is to base teaching increasingly on programming activities. In this article, we present the first results of an exploratory study, in which we teach programming without lectures, exams, or grades, by heavily emphasizing programming activity, and, in a pedagogical sense, student self-direction. This article investigates how students reacted to the active role required of them and what issues emerged in …
Issues with a course that emphasizes self-direction
2013
In this paper, we examine a master's level course that emphasizes self-direction on the part of students. The course is run by weekly group assignments and requires independent work such that only one mandatory classroom session is arranged each week. Our specific research interests are how students responded to the setting of this kind and whether they demonstrated self-direction during the course. We surveyed the students' view of the course, their group work experience, and their study habits, and analyzed the resultant survey data for themes. The results suggest that while the pass rate was considerably high and the course was regarded as well-organized by the students, there were sever…
Activity Theory as a Lens to Identify Challenges in Surgical Skills Training at Hospital Work Environment
2015
In this paper the concepts from activity theory (AT) are applied for identifying the challenges and contradictions emerging in surgical residentâs curriculum based training at hospital. AT is utilised as a lens to identify contradictions that cause disturbances, problems, ruptures, breakdowns, and clashes which emerge while surgical skills training is implemented in a new way at hospital. We especially aim at finding solutions for contradictions which emerge while the new and old working culture are confronted and the workers are required to balance themselves between the patient care demands and workplace learning requirements. We are using the conceptual theoretical approach to describe…
Do videowikis on the web support better (constructivist) learning in the basics of information systems science?
2012
This paper describes the combination of a wiki and screen capture videos as a complementary addition to conventional lectures in an information management and information systems development course. Our basis was collaborative problem-based learning with the problems defined by students. The idea was that students were expected to find concepts or issues from four lecture themes which are not well-defined or clarified for them. The students worked in small groups of two or three students or they completed the coursework individually. First, the students selected the theme which was most unclear for them. Second, the students selected the problematic things from this area and created the pre…
Support vector machine integrated with game-theoretic approach and genetic algorithm for the detection and classification of malware
2013
Abstract. —In the modern world, a rapid growth of mali- cious software production has become one of the most signifi- cant threats to the network security. Unfortunately, wides pread signature-based anti-malware strategies can not help to de tect malware unseen previously nor deal with code obfuscation te ch- niques employed by malware designers. In our study, the prob lem of malware detection and classification is solved by applyin g a data-mining-based approach that relies on supervised mach ine- learning. Executable files are presented in the form of byte a nd opcode sequences and n-gram models are employed to extract essential features from these sequences. Feature vectors o btained are…
Evaluating the performance of artificial neural networks for the classification of freshwater benthic macroinvertebrates
2014
Abstract Macroinvertebrates form an important functional component of aquatic ecosystems. Their ability to indicate various types of anthropogenic stressors is widely recognized which has made them an integral component of freshwater biomonitoring. The use of macroinvertebrates in biomonitoring is dependent on manual taxa identification which is currently a time-consuming and cost-intensive process conducted by highly trained taxonomical experts. Automated taxa identification of macroinvertebrates is a relatively recent research development. Previous studies have displayed great potential for solutions to this demanding data mining application. In this research we have a collection of 1350 …
Real-time recognition of personal routes using instance-based learning
2011
Predicting routes is a critical enabler for many new location-based applications and services, such as warning drivers about congestion- or accident-risky areas. Hybrid vehicles can also utilize the route prediction for optimizing their charging and discharging phases. In this paper, a new lightweight route recognition approach using instance-based learning is introduced. In this approach, the current route is compared in real-time against the route instances observed in past, and the most similar route is selected. In order to assess the similarity between the routes, a similarity measure based on the longest common subsequence (LCSS) is employed, and an algorithm for incrementally evaluat…