Self-Evaluation Applied Mathematics 2003-2008 University of Twente

This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008

Interim research assessment 2003-2005 - Computer Science

This report primarily serves as a source of information for the 2007 Interim Research Assessment Committee for Computer Science at the three technical universities in the Netherlands. The report also provides information for others interested in our research activities

Keberkesanan program simulasi penapis sambutan dedenyut terhingga (FIR) terhadap kefahaman pelajar kejuruteraan elektrik

Kefahaman merupakan aset bagi setiap pelajar. Ini kerana melalui kefahaman pelajar dapat mengaplikasikan konsep yang dipelajari di dalam dan di luar kelas. Kajian ini dijalankan bertujuan menilai keberkesanan program simulasi penapis sambutan dedenyut terhingga (FIR) terhadap kefahaman pelajar kejuruteraan elektrik FKEE, UTHM dalam mata pelajaran Pemprosesan Isyarat Digital (DSP) bagi topik penapis FIR. Metodologi kajian ini berbentuk kaedah reka bentuk kuasi�eksperimental ujian pra-pasca bagi kumpulan-kumpulan tidak seimbang. Seramai 40 responden kajian telah dipilih dan dibahagi secara rawak kepada dua kllmpulan iaitu kumpulan rawatan yang menggunakan program simulasi penapis FIR dan kumpulan kawalan yang menggunakan kaedah pembelajaran berorientasikan modul pembelajaran DSP UTHM. Setiap responden menduduki dua ujian pencapaian iaitu ujian pra dan ujian pasca yang berbentuk kuiz. Analisis data berbentuk deskriptif dan inferens dilakllkan dengan menggunakan Peri sian Statistical Package for Social Science (SPSS) versi 11.0. Dapatan kajian menunjukkan kedua-dua kumpulan pelajar telah mengalami peningkatan dari segi kefahaman iaitu daripada tahap tidak memuaskan kepada tahap kepujian selepas menggunakan kaedah pembelajaran yang telah ditetapkan bagi kumpulan masing-masing. Walaubagaimanapun, pelajar kumpulan rawatan menunjukkan peningkatan yang lebih tinggi sedikit berbanding pelajar kumpulan kawalan. Namun begitu, dapatan kajian secara ujian statistik menunjukkan tidak terdapat perbezaan yang signifikan dari segi pencapaian markah ujian pasca di antara pelajar kumpulan rawatan dengan pelajar kumpulan kawalan. Sungguhpun begitu, penggunaan program simulasi penapis FIR telah membantu dalam peningkatan kefahaman pelajar mengenai topik penapis FIR

A review of the role of sensors in mobile context-aware recommendation systems

Recommendation systems are specialized in offering suggestions about specific items of different types (e.g., books, movies, restaurants, and hotels) that could be interesting for the user. They have attracted considerable research attention due to their benefits and also their commercial interest. Particularly, in recent years, the concept of context-aware recommendation system has appeared to emphasize the importance of considering the context of the situations in which the user is involved in order to provide more accurate recommendations. The detection of the context requires the use of sensors of different types, which measure different context variables. Despite the relevant role played by sensors in the development of context-aware recommendation systems, sensors and recommendation approaches are two fields usually studied independently. In this paper, we provide a survey on the use of sensors for recommendation systems. Our contribution can be seen from a double perspective. On the one hand, we overview existing techniques used to detect context factors that could be relevant for recommendation. On the other hand, we illustrate the interest of sensors by considering different recommendation use cases and scenarios

Energy harvesting towards self-powered iot devices

The internet of things (IoT) manages a large infrastructure of web-enabled smart devices, small devices that use embedded systems, such as processors, sensors, and communication hardware to collect, send, and elaborate on data acquired from their environment. Thus, from a practical point of view, such devices are composed of power-efficient storage, scalable, and lightweight nodes needing power and batteries to operate. From the above reason, it appears clear that energy harvesting plays an important role in increasing the efficiency and lifetime of IoT devices. Moreover, from acquiring energy by the surrounding operational environment, energy harvesting is important to make the IoT device network more sustainable from the environmental point of view. Different state-of-the-art energy harvesters based on mechanical, aeroelastic, wind, solar, radiofrequency, and pyroelectric mechanisms are discussed in this review article. To reduce the power consumption of the batteries, a vital role is played by power management integrated circuits (PMICs), which help to enhance the system's life span. Moreover, PMICs from different manufacturers that provide power management to IoT devices have been discussed in this paper. Furthermore, the energy harvesting networks can expose themselves to prominent security issues putting the secrecy of the system to risk. These possible attacks are also discussed in this review article

An Energy-Efficient Skyline Query for Massively Multidimensional Sensing Data

Cyber physical systems (CPS) sense the environment based on wireless sensor networks. The sensing data of such systems present the characteristics of massiveness and multi-dimensionality. As one of the major monitoring methods used in in safe production monitoring and disaster early-warning applications, skyline query algorithms are extensively adopted for multiple-objective decision analysis of these sensing data. With the expansion of network sizes, the amount of sensing data increases sharply. Then, how to improve the query efficiency of skyline query algorithms and reduce the transmission energy consumption become pressing and difficult to accomplish issues. Therefore, this paper proposes a new energy-efficient skyline query method for massively multidimensional sensing data. First, the method uses a node cut strategy to dynamically generate filtering tuples with little computational overhead when collecting query results instead of issuing queries with filters. It can judge the domination relationship among different nodes, remove the detected data sets of dominated nodes that are irrelevant to the query, modify the query path dynamically, and reduce the data comparison and computational overhead. The efficient dynamic filter generated by this strategy uses little non-skyline data transmission in the network, and the transmission distance is very short. Second, our method also employs the tuple-cutting strategy inside the node and generates the local cutting tuples by the sub-tree with the node itself as the root node, which will be used to cut the detected data within the nodes of the sub-tree. Therefore, it can further control the non-skyline data uploading. A large number of experimental results show that our method can quickly return an overview of the monitored area and reduce the communication overhead. Additionally, it can shorten the response time and improve the efficiency of the query

7. GI/ITG KuVS Fachgespräch Drahtlose Sensornetze

In dem vorliegenden Tagungsband sind die Beiträge des Fachgesprächs Drahtlose Sensornetze 2008 zusammengefasst. Ziel dieses Fachgesprächs ist es, Wissenschaftlerinnen und Wissenschaftler aus diesem Gebiet die Möglichkeit zu einem informellen Austausch zu geben – wobei immer auch Teilnehmer aus der Industrieforschung willkommen sind, die auch in diesem Jahr wieder teilnehmen.Das Fachgespräch ist eine betont informelle Veranstaltung der GI/ITG-Fachgruppe „Kommunikation und Verteilte Systeme“ (www.kuvs.de). Es ist ausdrücklich keine weitere Konferenz mit ihrem großen Overhead und der Anforderung, fertige und möglichst „wasserdichte“ Ergebnisse zu präsentieren, sondern es dient auch ganz explizit dazu, mit Neueinsteigern auf der Suche nach ihrem Thema zu diskutieren und herauszufinden, wo die Herausforderungen an die zukünftige Forschung überhaupt liegen.Das Fachgespräch Drahtlose Sensornetze 2008 findet in Berlin statt, in den Räumen der Freien Universität Berlin, aber in Kooperation mit der ScatterWeb GmbH. Auch dies ein Novum, es zeigt, dass das Fachgespräch doch deutlich mehr als nur ein nettes Beisammensein unter einem Motto ist.Für die Organisation des Rahmens und der Abendveranstaltung gebührt Dank den beiden Mitgliedern im Organisationskomitee, Kirsten Terfloth und Georg Wittenburg, aber auch Stefanie Bahe, welche die redaktionelle Betreuung des Tagungsbands übernommen hat, vielen anderen Mitgliedern der AG Technische Informatik der FU Berlin und natürlich auch ihrem Leiter, Prof. Jochen Schiller