Looking at the effectiveness of an earth science unit designed using the Understanding by Design process

This report shares my efforts in developing a solid unit of instruction that has a clear focus on student outcomes. I have been a teacher for 20 years and have been writing and revising curricula for much of that time. However, most has been developed without the benefit of current research on how students learn and did not focus on what and how students are learning. My journey as a teacher has involved a lot of trial and error. My traditional method of teaching is to look at the benchmarks (now content expectations) to see what needs to be covered. My unit consists of having students read the appropriate sections in the textbook, complete work sheets, watch a video, and take some notes. I try to include at least one hands-on activity, one or more quizzes, and the traditional end-of-unit test consisting mostly of multiple choice questions I find in the textbook. I try to be engaging, make the lessons fun, and hope that at the end of the unit my students get whatever concepts I‘ve presented so that we can move on to the next topic. I want to increase students‘ understanding of science concepts and their ability to connect understanding to the real-world. However, sometimes I feel that my lessons are missing something. For a long time I have wanted to develop a unit of instruction that I know is an effective tool for the teaching and learning of science. In this report, I describe my efforts to reform my curricula using the “Understanding by Design” process. I want to see if this style of curriculum design will help me be a more effective teacher and if it will lead to an increase in student learning. My hypothesis is that this new (for me) approach to teaching will lead to increased understanding of science concepts among students because it is based on purposefully thinking about learning targets based on “big ideas” in science. For my reformed curricula I incorporate lessons from several outstanding programs I‘ve been involved with including EpiCenter (Purdue University), Incorporated Research Institutions for Seismology (IRIS), the Master of Science Program in Applied Science Education at Michigan Technological University, and the Michigan Association for Computer Users in Learning (MACUL). In this report, I present the methodology on how I developed a new unit of instruction based on the Understanding by Design process. I present several lessons and learning plans I‘ve developed for the unit that follow the 5E Learning Cycle as appendices at the end of this report. I also include the results of pilot testing of one of lessons. Although the lesson I pilot-tested was not as successful in increasing student learning outcomes as I had anticipated, the development process I followed was helpful in that it required me to focus on important concepts. Conducting the pilot test was also helpful to me because it led me to identify ways in which I could improve upon the lesson in the future.

Real Walking through Virtual Environments by Redirection Techniques

We present redirection techniques that support exploration of large-scale virtual environments (VEs) by means of real walking. We quantify to what degree users can unknowingly be redirected in order to guide them through VEs in which virtual paths differ from the physical paths. We further introduce the concept of dynamic passive haptics by which any number of virtual objects can be mapped to real physical proxy props having similar haptic properties (i. e., size, shape, and surface structure), such that the user can sense these virtual objects by touching their real world counterparts. Dynamic passive haptics provides the user with the illusion of interacting with a desired virtual object by redirecting her to the corresponding proxy prop. We describe the concepts of generic redirected walking and dynamic passive haptics and present experiments in which we have evaluated these concepts. Furthermore, we discuss implications that have been derived from a user study, and we present approaches that derive physical paths which may vary from the virtual counterparts.

A benchmark of kriging-based infill criteria for noisy optimization

Responses of many real-world problems can only be evaluated perturbed by noise. In order to make an efficient optimization of these problems possible, intelligent optimization strategies successfully coping with noisy evaluations are required. In this article, a comprehensive review of existing kriging-based methods for the optimization of noisy functions is provided. In summary, ten methods for choosing the sequential samples are described using a unified formalism. They are compared on analytical benchmark problems, whereby the usual assumption of homoscedastic Gaussian noise made in the underlying models is meet. Different problem configurations (noise level, maximum number of observations, initial number of observations) and setups (covariance functions, budget, initial sample size) are considered. It is found that the choices of the initial sample size and the covariance function are not critical. The choice of the method, however, can result in significant differences in the performance. In particular, the three most intuitive criteria are found as poor alternatives. Although no criterion is found consistently more efficient than the others, two specialized methods appear more robust on average.

Integration of WSNs into enterprise systems based on semantic physical business entities

Internet of Things based systems are anticipated to gain widespread use in industrial applications. Standardization efforts, like 6L0WPAN and the Constrained Application Protocol (CoAP) have made the integration of wireless sensor nodes possible using Internet technology and web-like access to data (RESTful service access). While there are still some open issues, the interoperability problem in the lower layers can now be considered solved from an enterprise software vendors' point of view. One possible next step towards integration of real-world objects into enterprise systems and solving the corresponding interoperability problems at higher levels is to use semantic web technologies. We introduce an abstraction of real-world objects, called Semantic Physical Business Entities (SPBE), using Linked Data principles. We show that this abstraction nicely fits into enterprise systems, as SPBEs allow a business object centric view on real-world objects, instead of a pure device centric view. The interdependencies between how currently services in an enterprise system are used and how this can be done in a semantic real-world aware enterprise system are outlined, arguing for the need of semantic services and semantic knowledge repositories. We introduce a lightweight query language, which we use to perform a quantitative analysis of our approach to demonstrate its feasibility.

A reliable, traffic-adaptive and energy-efficient link layer for wireless sensor networks

The paper presents a link layer stack for wireless sensor networks, which consists of the Burst-aware Energy-efficient Adaptive Medium access control (BEAM) and the Hop-to-Hop Reliability (H2HR) protocol. BEAM can operate with short beacons to announce data transmissions or include data within the beacons. Duty cycles can be adapted by a traffic prediction mechanism indicating pending packets destined for a node and by estimating its wake-up times. H2HR takes advantage of information provided by BEAM such as neighbour information and transmission information to perform per-hop congestion control. We justify the design decisions by measurements in a real-world wireless sensor network testbed and compare the performance with other link layer protocols.

Traffic-Adaptive and Link-Quality-Aware Communication in Wireless Sensor Networks

This paper is a summary of the main contribu- tions of the PhD thesis published in [1]. The main research contributions of the thesis are driven by the research question how to design simple, yet efficient and robust run-time adaptive resource allocation schemes within the commu- nication stack of Wireless Sensor Network (WSN) nodes. The thesis addresses several problem domains with con- tributions on different layers of the WSN communication stack. The main contributions can be summarized as follows: First, a a novel run-time adaptive MAC protocol is intro- duced, which stepwise allocates the power-hungry radio interface in an on-demand manner when the encountered traffic load requires it. Second, the thesis outlines a metho- dology for robust, reliable and accurate software-based energy-estimation, which is calculated at network run- time on the sensor node itself. Third, the thesis evaluates several Forward Error Correction (FEC) strategies to adap- tively allocate the correctional power of Error Correcting Codes (ECCs) to cope with timely and spatially variable bit error rates. Fourth, in the context of TCP-based communi- cations in WSNs, the thesis evaluates distributed caching and local retransmission strategies to overcome the perfor- mance degrading effects of packet corruption and trans- mission failures when transmitting data over multiple hops. The performance of all developed protocols are eval- uated on a self-developed real-world WSN testbed and achieve superior performance over selected existing ap- proaches, especially where traffic load and channel condi- tions are suspect to rapid variations over time.

Energy-Efficient Management Of Heterogeneous Wireless Sensor Networks

Various applications for the purposes of event detection, localization, and monitoring can benefit from the use of wireless sensor networks (WSNs). Wireless sensor networks are generally easy to deploy, with flexible topology and can support diversity of tasks thanks to the large variety of sensors that can be attached to the wireless sensor nodes. To guarantee the efficient operation of such a heterogeneous wireless sensor networks during its lifetime an appropriate management is necessary. Typically, there are three management tasks, namely monitoring, (re) configuration, and code updating. On the one hand, status information, such as battery state and node connectivity, of both the wireless sensor network and the sensor nodes has to be monitored. And on the other hand, sensor nodes have to be (re)configured, e.g., setting the sensing interval. Most importantly, new applications have to be deployed as well as bug fixes have to be applied during the network lifetime. All management tasks have to be performed in a reliable, time- and energy-efficient manner. The ability to disseminate data from one sender to multiple receivers in a reliable, time- and energy-efficient manner is critical for the execution of the management tasks, especially for code updating. Using multicast communication in wireless sensor networks is an efficient way to handle such traffic pattern. Due to the nature of code updates a multicast protocol has to support bulky traffic and endto-end reliability. Further, the limited resources of wireless sensor nodes demand an energy-efficient operation of the multicast protocol. Current data dissemination schemes do not fulfil all of the above requirements. In order to close the gap, we designed the Sensor Node Overlay Multicast (SNOMC) protocol such that to support a reliable, time-efficient and energy-efficient dissemination of data from one sender node to multiple receivers. In contrast to other multicast transport protocols, which do not support reliability mechanisms, SNOMC supports end-to-end reliability using a NACK-based reliability mechanism. The mechanism is simple and easy to implement and can significantly reduce the number of transmissions. It is complemented by a data acknowledgement after successful reception of all data fragments by the receiver nodes. In SNOMC three different caching strategies are integrated for an efficient handling of necessary retransmissions, namely, caching on each intermediate node, caching on branching nodes, or caching only on the sender node. Moreover, an option was included to pro-actively request missing fragments. SNOMC was evaluated both in the OMNeT++ simulator and in our in-house real-world testbed and compared to a number of common data dissemination protocols, such as Flooding, MPR, TinyCubus, PSFQ, and both UDP and TCP. The results showed that SNOMC outperforms the selected protocols in terms of transmission time, number of transmitted packets, and energy-consumption. Moreover, we showed that SNOMC performs well with different underlying MAC protocols, which support different levels of reliability and energy-efficiency. Thus, SNOMC can offer a robust, high-performing solution for the efficient distribution of code updates and management information in a wireless sensor network. To address the three management tasks, in this thesis we developed the Management Architecture for Wireless Sensor Networks (MARWIS). MARWIS is specifically designed for the management of heterogeneous wireless sensor networks. A distinguished feature of its design is the use of wireless mesh nodes as backbone, which enables diverse communication platforms and offloading functionality from the sensor nodes to the mesh nodes. This hierarchical architecture allows for efficient operation of the management tasks, due to the organisation of the sensor nodes into small sub-networks each managed by a mesh node. Furthermore, we developed a intuitive -based graphical user interface, which allows non-expert users to easily perform management tasks in the network. In contrast to other management frameworks, such as Mate, MANNA, TinyCubus, or code dissemination protocols, such as Impala, Trickle, and Deluge, MARWIS offers an integrated solution monitoring, configuration and code updating of sensor nodes. Integration of SNOMC into MARWIS further increases performance efficiency of the management tasks. To our knowledge, our approach is the first one, which offers a combination of a management architecture with an efficient overlay multicast transport protocol. This combination of SNOMC and MARWIS supports reliably, time- and energy-efficient operation of a heterogeneous wireless sensor network.

NextServe Framework: Supporting Services Over Content-Centric Networking

The future Internet architecture aims to reformulate the way the content/service is requested to make it location-independent. Information-Centric Networking is a new network paradigm, which tries to achieve this goal by making content objects identified and requested by name instead of address. In this paper, we extend Information-Centric Networking architecture to support services in order to be requested and invoked by names. We present NextServe framework, which is a service framework with a human-readable self-explanatory naming scheme. NextServe is inspired by the object-oriented programming paradigm and is applicable with real-world scenarios.

Testbed Evaluation of Sensor Node Overlay Multicast

The Sensor Node Overlay Multicast (SNOMC) protocol supports reliable, time-efficient and energy-efficient dissemination of data from one sender node to multiple receivers as it is needed for configuration, code update, and management operations in wireless sensor networks. SNOMC supports end-to-end reliability using negative acknowledgements. The mechanism is simple and easy to implement and can significantly reduce the number of transmissions. SNOMC supports three different caching strategies namely caching on each intermediate node, caching on branching nodes, or caching on the sender node only. SNOMC was evaluated in our in-house real-world testbed and compared to a number of common data dissemination protocols. It outperforms the selected protocols in terms of transmission time, number of transmitted packets, and energy-consumption.

Simulation of SLA-based VM-scaling algorithms for cloud-distributed applications

Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.

Uncalibrated Near-Light Photometric Stereo

In this work we solve the uncalibrated photometric stereo problem with lights placed near the scene. We investigate different image formation models and find the one that best fits our observations. Although the devised model is more complex than its far-light counterpart, we show that under a global linear ambiguity the reconstruction is possible up to a rotation and scaling, which can be easily fixed. We also propose a solution for reconstructing the normal map, the albedo, the light positions and the light intensities of a scene given only a sequence of near-light images. This is done in an alternating minimization framework which first estimates both the normals and the albedo, and then the light positions and intensities. We validate our method on real world experiments and show that a near-light model leads to a significant improvement in the surface reconstruction compared to the classic distant illumination case.

The distinction between real and fictional worlds: Investigating individual differences in fantasy understanding

In this paper, two studies are reported in which children’s ability to distinguish reality from fantasy was investigated. In Experiment 1, children of different ages made pairwise comparisons of 12 pictures of fictional figures and 3 photographs of real people by evaluating on a 6-point scale how easily these figures could meet each other. The results revealed that fantasy/reality distinction develops with age: 7–8-year-old showed a fundamental categorical distinction (comparable to that of adults) whereas 3–4-year-old treated the real world like one of many worlds. In Experiment 2, we took an individual differences approach and tested 116 4–5-year-old who performed the same fantasy task. In addition, they were presented with theory-of-mind tasks and tests measuring non-verbal intelligence and language skills. The results showed that, after statistically controlling for age, non-verbal intelligence, and language skills, theory-of-mind abilities still significantly contributed to the prediction of fantasy understanding.

Recent Advances in Adaptive Sampling and Reconstruction for Monte Carlo Rendering

Monte Carlo integration is firmly established as the basis for most practical realistic image synthesis algorithms because of its flexibility and generality. However, the visual quality of rendered images often suffers from estimator variance, which appears as visually distracting noise. Adaptive sampling and reconstruction algorithms reduce variance by controlling the sampling density and aggregating samples in a reconstruction step, possibly over large image regions. In this paper we survey recent advances in this area. We distinguish between “a priori” methods that analyze the light transport equations and derive sampling rates and reconstruction filters from this analysis, and “a posteriori” methods that apply statistical techniques to sets of samples to drive the adaptive sampling and reconstruction process. They typically estimate the errors of several reconstruction filters, and select the best filter locally to minimize error. We discuss advantages and disadvantages of recent state-of-the-art techniques, and provide visual and quantitative comparisons. Some of these techniques are proving useful in real-world applications, and we aim to provide an overview for practitioners and researchers to assess these approaches. In addition, we discuss directions for potential further improvements.

Three-dimensional mapping of real environments for cognitive robots navigation

Abstract The development of cognitive robots needs a strong “sensorial” support which should allow it to perceive the real world for interacting with it properly. Therefore the development of efficient visual-processing software to be equipped in effective artificial agents is a must. In this project we study and develop a visual-processing software that will work as the “eyes” of a cognitive robot. This software performs a three-dimensional mapping of the robot’s environment, providing it with the essential information required to make proper decisions during its navigation. Due to the complexity of this objective we have adopted the Scrum methodology in order to achieve an agile development process, which has allowed us to correct and improve in a fast way the successive versions of the product. The present project is structured in Sprints, which cover the different stages of the software development based on the requirements imposed by the robot and its real necessities. We have initially explored different commercial devices oriented to the acquisition of the required visual information, adopting the Kinect Sensor camera (Microsoft) as the most suitable option. Later on, we have studied the available software to manage the obtained visual information as well as its integration with the robot’s software, choosing the high-level platform Matlab as the common nexus to join the management of the camera, the management of the robot and the implementation of the behavioral algorithms. During the last stages the software has been developed to include the fundamental functionalities required to process the real environment, such as depth representation, segmentation, and clustering. Finally the software has been optimized to exhibit real-time processing and a suitable performance to fulfill the robot’s requirements during its operation in real situations.