513 research outputs found

    Power Aware Routing for Sensor Databases

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    Wireless sensor networks offer the potential to span and monitor large geographical areas inexpensively. Sensor network databases like TinyDB are the dominant architectures to extract and manage data in such networks. Since sensors have significant power constraints (battery life), and high communication costs, design of energy efficient communication algorithms is of great importance. The data flow in a sensor database is very different from data flow in an ordinary network and poses novel challenges in designing efficient routing algorithms. In this work we explore the problem of energy efficient routing for various different types of database queries and show that in general, this problem is NP-complete. We give a constant factor approximation algorithm for one class of query, and for other queries give heuristic algorithms. We evaluate the efficiency of the proposed algorithms by simulation and demonstrate their near optimal performance for various network sizes

    Quantum Impurity in a Nearly Critical Two Dimensional Antiferromagnet

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    We describe the spin dynamics of an arbitrary localized impurity in an insulating two dimensional antiferromagnet, across the host transition from a paramagnet with a spin gap to a Neel state. The impurity spin susceptibility has a Curie-like divergence at the quantum-critical coupling, but with a universal, effective spin which is neither an integer nor a half-odd-integer. In the Neel state, the transverse impurity susceptibility is a universal number divided by the host spin stiffness (which determines the energy cost to slow twists in the orientation of the Neel order). These, and numerous other results for the thermodynamics, Knight shift, and magnon damping have significant applications to experiments on layered transition metal oxides.Comment: 12 pages, 3 figures; Additional details and results are in cond-mat/991202

    Medians and Beyond: New Aggregation Techniques for Sensor Networks

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    Wireless sensor networks offer the potential to span and monitor large geographical areas inexpensively. Sensors, however, have significant power constraint (battery life), making communication very expensive. Another important issue in the context of sensor-based information systems is that individual sensor readings are inherently unreliable. In order to address these two aspects, sensor database systems like TinyDB and Cougar enable in-network data aggregation to reduce the communication cost and improve reliability. The existing data aggregation techniques, however, are limited to relatively simple types of queries such as SUM, COUNT, AVG, and MIN/MAX. In this paper we propose a data aggregation scheme that significantly extends the class of queries that can be answered using sensor networks. These queries include (approximate) quantiles, such as the median, the most frequent data values, such as the consensus value, a histogram of the data distribution, as well as range queries. In our scheme, each sensor aggregates the data it has received from other sensors into a fixed (user specified) size message. We provide strict theoretical guarantees on the approximation quality of the queries in terms of the message size. We evaluate the performance of our aggregation scheme by simulation and demonstrate its accuracy, scalability and low resource utilization for highly variable input data sets

    Ethnomedicinal Plants Used by the ethnic Communities of Tinsukia District of Assam, India

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    An ethnobotanical study focused on medicinal utility of plants was carried out among the ethnic communities of Tinsukia district of upper Assam with aims to document the traditional knowledge of the medicinal plants used in various ailments. The information was based on normal conversation, interview and discussion with local herbal practitioners, elderly men and women of different tribal communities. In this study, a total of 175 plant species belonging to 76 families were described which have been used in the treatment of around 56 diseases. Herbs, shrubs and trees were the dominant category of the plants. Most frequently medicated claims were stomach ailments, gynaecological problems, lung and respiratory diseases, cuts and wounds, skin diseases, urinary troubles and as well as their use as blood purifier. The most cited family was Euphorbiaceae, the most widely used plant part was the leaf and the most common mode of administration was decoction. All these claims need to be subjected to both phyto- and pharmaco-chemical investigations to discover the potentiality of these plants and plant parts as drugs

    Impurity spin dynamics in 2D antiferromagnets and superconductors

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    We discuss the universal theory of localized impurities in the paramagnetic state of 2D antiferromagnets where the spin gap is assumed to be significantly smaller than a typical exchange energy. We study the impurity spin susceptibility near the host quantum transition from a gapped paramagnet to a Neel state, and we compute the impurity-induced damping of the spin-1 mode of the gapped antiferromagnet. Under suitable conditions our results apply also to d-wave superconductors.Comment: 2 pages, 1 fig. Proceedings of the M2S-HTSC-VI conference, Houston 2000, submitted to Physica C. More details can be found in cond-mat/991202

    Nanoscale Studies of the Ferroelectric and Electromechanical Properties of Hafnia-based Capacitors

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    The work presented in this dissertation aims to provide nanoscopic insights into the electrical and electromechanical behavior of the recently discovered ferroelectric HfO2 or hafnia-based capacitors. Hafnia-based ferroelectrics are highly promising for technological applications due to compatibility with the existing Si technology. To realize the full potential of hafnia, however, requires comprehensive understanding of its properties. In this regard, this dissertation hopes to bridge a gap between an understanding of the nanoscopic and macroscopic properties of hafnia by performing combined high-resolution piezoresponse force microscopy (PFM) and pulse switching studies. More specifically, the dynamics of domain nucleation and wall motion during polarization reversal in hafnia was investigated. Polarization reversal was found to occur mainly via nucleation of new domains, albeit with limited expansion and sluggish domain wall motion, following the nucleation limited switching (NLS) model at low fields. At high fields, close to the thermodynamic activation fields, a convergence of the NLS and the Kolmogorov-Avrami-Ishibashi switching models was observed, signifying a uniform domain-less polarization reversal process. Furthermore, negative d33 was demonstrated for the first time in hafnia after careful calibration of the PFM phase signal, providing confirmation of a theoretically predicted negative d33. However, the sign was found to be strongly sample dependent. Depending on the film thickness, electrode materials, deposition method used, or state of the capacitors (pristine vs field-cycled), hafnia-based capacitors exhibited either a uniformly negative or positive d33 response or a mixture of both positive and negative d33 responses. In addition, a unique imprint behavior was identified in hafnia that was found to strongly depend on the switching pre-history. Our measurements highlight the critical role played by injected charges and mobile charges/defects in the imprint behavior of hafnia-based devices. Finally, application of PFM spectroscopy to ZrO2-based capacitors revealed dramatically different PFM amplitude response compared to hafnia that could be attributed to the divergence of dielectric susceptibility during field-induced antiferroelectric - ferroelectric phase transitions, providing a microscopic confirmation of antiferroelectricity in ZrO2. Adviser: Alexei Gruverma

    Classroom Assessments for Improving Writing Proficiency of English Language Learners: Innovation, Interaction, and Impact

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    Classroom assessments are one of the most essential educational tools which can help teachers understand what their students are learning, by means of a) identifying students’ strengths and weaknesses, b) monitoring their learning and progress, and c) planning and conducting instruction. The current study aims at investigating various strategies of classroom assessments for improving writing proficiency of English language learners (ELLs) while highlighting primarily on three parameters: 1) innovation (new and innovative classroom assessment strategies), 2) interaction (student interactivity and engagement), and 3) impact (impact of the new assessment strategies on ESL writing proficiency in particular and overall learning process and proficiency in general)
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