Finding your way into an open online learning community

Making educational materials freely available on the web is not only a noble enterprise, but also fits the call of helping people to become lifelong learners; a call which gets louder and louder every day. The world is rapidly changing, requiring us to continuously update our knowledge and skills. A problem with this approach to lifelong learning is that the materials that are made available are often both incomplete and unsuitable for independent learning in an online setting. The OpenER (Open Educational Resources) project at the Open Universiteit Nederland makes more than 20 short courses, originally developed for independent-study, freely available from the website www.opener.ou.nl. For our research we start from an envisioned online learning environment now under development. We use backcasting to select research topics that form steps from the current to the ultimate situation. The two experiments we report on here are an extension to standard forum software and the use of student notes to annotate learning materials: two small steps towards our ultimate open learning environment

Acoustic mechanisms of a species-based discrimination of the chick-a-dee call in sympatric black-capped (Poecile atricapillus) and mountain chickadees (P. gambeli)

Previous perceptual research with black-capped and mountain chickadees has demonstrated that these species treat each other’s namesake chick-a-dee calls as belonging to separate, open-ended categories. Further, the terminal dee portion of the call has been implicated as the most prominent species marker. However, statistical classification using acoustic summary features suggests that all note-types contained within the chick-a-dee call should be sufficient for species classification. The current study seeks to better understand the note-type based mechanisms underlying species-based classification of the chick-a-dee call by black-capped and mountain chickadees. In two, complementary, operant discrimination experiments, both species were trained to discriminate the species of the signaler using either entire chick-a-dee calls, or individual note-types from chick-a-dee calls. In agreement with previous perceptual work we find that the D note had significant stimulus control over species-based discrimination. However, in line with statistical classifications, we find that all note-types carry species information. We discuss reasons why the most easily discriminated note-types are likely candidates to carry species-based cues.Publisher PDFPeer reviewe

Discovering the best: Informational efficiency and liquidity of alternative trading mechanisms in experimental asset markets

This paper reports the results of 18 experimental asset markets with 262 subjects that explore the effects of liquidity and aggregation of information. The main focus lies on the comparison of different trading mechanisms of stock exchanges. Compared to most of financial markets experiments, reality is met by introducing long-living assets and integrating all subjects in a multi-period decision-making process. In accordance with the evidence from the empirical research in real financial markets, our results show that the continuous auction achieves the highest informational efficiency. Dealer markets do the worst; call markets (batch trading) reach an intermediate position. A comparable result is achieved regarding the liquidity of the trading mechanisms. For both success factors of real stock exchanges our results show a strong tendency that continuous trading outperforms the other market structures, at least in the framework of the present measurement and on the chosen abstraction level. This does not exclude for the practice to offer a combination with call markets in certain titles and at certain times, particularly, if the here met assumptions of an open market access and information symmetry between the investors do not apply in full extent. --Market Microstructure,Experimental Asset Markets,Market Efficiency,Informational Efficiency,Liquidity,Call Markets,Continuous Auction

Towards Emulation of Intelligent IoT Networks on EU-US Testbeds

This paper introduces our project on experimental validation of intelligent Internet of Things (IoT) networks. The project is a part of the NGIAtlantic H2020 third open call to perform experiments on EU and US wireless testbeds. The project proposes five different experiments to be performed on EU/US testbeds: (1) automatic configuration/discovery of Software Defined Networking (SDN) in wireless IoT sensor networks, (2) Machine Learning (ML) assisted control and data traffic path discovery experiments, (3) GPU and Hadoop cluster assisted experiments for ML algorithms, (4) Inter-testbed experiments, and (5) Failure recovery intercity experiments. Further, initial experimentation on EU/US testbeds is explored and presented. The results show the feasibility of performing the above experiments on the proposed testbeds

Gradient-orientation-based PCA subspace for novel face recognition

This article has been made available through the Brunel Open Access Publishing Fund.Face recognition is an interesting and a challenging problem that has been widely studied in the field of pattern recognition and computer vision. It has many applications such as biometric authentication, video surveillance, and others. In the past decade, several methods for face recognition were proposed. However, these methods suffer from pose and illumination variations. In order to address these problems, this paper proposes a novel methodology to recognize the face images. Since image gradients are invariant to illumination and pose variations, the proposed approach uses gradient orientation to handle these effects. The Schur decomposition is used for matrix decomposition and then Schurvalues and Schurvectors are extracted for subspace projection. We call this subspace projection of face features as Schurfaces, which is numerically stable and have the ability of handling defective matrices. The Hausdorff distance is used with the nearest neighbor classifier to measure the similarity between different faces. Experiments are conducted with Yale face database and ORL face database. The results show that the proposed approach is highly discriminant and achieves a promising accuracy for face recognition than the state-of-the-art approaches