The Experts below are selected from a list of 228 Experts worldwide ranked by ideXlab platform
Zhen Zhang - One of the best experts on this subject based on the ideXlab platform.
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CIDR - Toward large Scale Integration: Building a MetaQuerier over databases on the Web
2005Co-Authors: Kevin Chen-chuan Chang, Bin He, Zhen ZhangAbstract:The Web has been rapidly “deepened” by myriad searchable databases online, where data are hidden behind query interfaces. Toward large Scale Integration over this “deep Web,” we have been building the MetaQuerier system– for both exploring (to find) and integrating (to query) databases on the Web. As an interim report, first, this paper proposes our goal of the MetaQuerier for Web-Scale Integration– With its dynamic and ad-hoc nature, such large Scale Integration mandates both dynamic source discovery and on-thefly query translation. Second, we present the system architecture and underlying technology of key subsystems in our ongoing implementation. Third, we discuss “lessons” learned to date, focusing on our efforts in system Integration, for putting individual subsystems to function together. On one hand, we observe that, across subsystems, the system Integration of an Integration system is itself non-trivial– which presents both challenges and opportunities beyond subsystems in isolation. On the other hand, we also observe that, across subsystems, there emerge unified insights of “holistic Integration”– which leverage large Scale itself as a unique opportunity for information Integration.
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toward large Scale Integration building a metaquerier over databases on the web
Conference on Innovative Data Systems Research, 2005Co-Authors: Kevin Chen-chuan Chang, Bin He, Zhen ZhangAbstract:The Web has been rapidly “deepened” by myriad searchable databases online, where data are hidden behind query interfaces. Toward large Scale Integration over this “deep Web,” we have been building the MetaQuerier system– for both exploring (to find) and integrating (to query) databases on the Web. As an interim report, first, this paper proposes our goal of the MetaQuerier for Web-Scale Integration– With its dynamic and ad-hoc nature, such large Scale Integration mandates both dynamic source discovery and on-thefly query translation. Second, we present the system architecture and underlying technology of key subsystems in our ongoing implementation. Third, we discuss “lessons” learned to date, focusing on our efforts in system Integration, for putting individual subsystems to function together. On one hand, we observe that, across subsystems, the system Integration of an Integration system is itself non-trivial– which presents both challenges and opportunities beyond subsystems in isolation. On the other hand, we also observe that, across subsystems, there emerge unified insights of “holistic Integration”– which leverage large Scale itself as a unique opportunity for information Integration.
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Mining semantics for large Scale Integration on the web: evidences, insights, and challenges
Sigkdd Explorations, 2004Co-Authors: Kevin Chen-chuan Chang, Bin He, Zhen ZhangAbstract:The Web has been rapidly "deepened" -- with myriad searchable databases online, where data are hidden behind query interfaces. Toward large Scale Integration over this "deep Web," we are facing a new challenge- With its dynamic and ad-hoc nature, such large Scale Integration mandates dynamic semantics discovery. That is, we must on-the-fly cope with "semantics" of dynamically discovered sources without pre-configured source-specific knowledge. To tackle this challenge, our initial works hinge on the insight that the large Scale is itself also a unique opportunity: We observe that the desired "semantics" often connects to surface presentation characteristics, through some hidden regularities over many sources. Such regularities can be essentially leveraged in enabling semantics discovery. In particular, we report our evidences in three initial tasks for integrating the deep Web: interface extraction, schema matching, and query translation. Generalizing these specific evidences, we thus propose our "unified insight" of "mining" semantics for large Scale Integration by exploiting hidden regularities across holistic sources. Further, to fulfill the promise of such holistic mining, we discuss challenges toward its realization for dynamic semantics discovery. As our initial works as well as several related efforts have witnessed, we believe our unified insight, holistic mining for semantics discovery, is a promising methodology toward enabling large Scale Integration.
Jacques Martinerie - One of the best experts on this subject based on the ideXlab platform.
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The brainweb: Phase synchronization and large-Scale Integration
Nature Reviews Neuroscience, 2001Co-Authors: Francisco Varela, Eugenio Rodriguez, Jean-philippe Lachaux, Jacques MartinerieAbstract:The emergence of a unified cognitive moment relies on the coordination of scattered mosaics of functionally specialized brain regions. Here we review the mechanisms of large-Scale Integration that counterbalance the distributed anatomical and functional organization of brain activity to enable the emergence of coherent behaviour and cognition. Although the mechanisms involved in large-Scale Integration are still largely unknown, we argue that the most plausible candidate is the formation of dynamic links mediated by synchrony over multiple frequency bands.
Kevin Chen-chuan Chang - One of the best experts on this subject based on the ideXlab platform.
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CIDR - Toward large Scale Integration: Building a MetaQuerier over databases on the Web
2005Co-Authors: Kevin Chen-chuan Chang, Bin He, Zhen ZhangAbstract:The Web has been rapidly “deepened” by myriad searchable databases online, where data are hidden behind query interfaces. Toward large Scale Integration over this “deep Web,” we have been building the MetaQuerier system– for both exploring (to find) and integrating (to query) databases on the Web. As an interim report, first, this paper proposes our goal of the MetaQuerier for Web-Scale Integration– With its dynamic and ad-hoc nature, such large Scale Integration mandates both dynamic source discovery and on-thefly query translation. Second, we present the system architecture and underlying technology of key subsystems in our ongoing implementation. Third, we discuss “lessons” learned to date, focusing on our efforts in system Integration, for putting individual subsystems to function together. On one hand, we observe that, across subsystems, the system Integration of an Integration system is itself non-trivial– which presents both challenges and opportunities beyond subsystems in isolation. On the other hand, we also observe that, across subsystems, there emerge unified insights of “holistic Integration”– which leverage large Scale itself as a unique opportunity for information Integration.
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toward large Scale Integration building a metaquerier over databases on the web
Conference on Innovative Data Systems Research, 2005Co-Authors: Kevin Chen-chuan Chang, Bin He, Zhen ZhangAbstract:The Web has been rapidly “deepened” by myriad searchable databases online, where data are hidden behind query interfaces. Toward large Scale Integration over this “deep Web,” we have been building the MetaQuerier system– for both exploring (to find) and integrating (to query) databases on the Web. As an interim report, first, this paper proposes our goal of the MetaQuerier for Web-Scale Integration– With its dynamic and ad-hoc nature, such large Scale Integration mandates both dynamic source discovery and on-thefly query translation. Second, we present the system architecture and underlying technology of key subsystems in our ongoing implementation. Third, we discuss “lessons” learned to date, focusing on our efforts in system Integration, for putting individual subsystems to function together. On one hand, we observe that, across subsystems, the system Integration of an Integration system is itself non-trivial– which presents both challenges and opportunities beyond subsystems in isolation. On the other hand, we also observe that, across subsystems, there emerge unified insights of “holistic Integration”– which leverage large Scale itself as a unique opportunity for information Integration.
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Mining semantics for large Scale Integration on the web: evidences, insights, and challenges
Sigkdd Explorations, 2004Co-Authors: Kevin Chen-chuan Chang, Bin He, Zhen ZhangAbstract:The Web has been rapidly "deepened" -- with myriad searchable databases online, where data are hidden behind query interfaces. Toward large Scale Integration over this "deep Web," we are facing a new challenge- With its dynamic and ad-hoc nature, such large Scale Integration mandates dynamic semantics discovery. That is, we must on-the-fly cope with "semantics" of dynamically discovered sources without pre-configured source-specific knowledge. To tackle this challenge, our initial works hinge on the insight that the large Scale is itself also a unique opportunity: We observe that the desired "semantics" often connects to surface presentation characteristics, through some hidden regularities over many sources. Such regularities can be essentially leveraged in enabling semantics discovery. In particular, we report our evidences in three initial tasks for integrating the deep Web: interface extraction, schema matching, and query translation. Generalizing these specific evidences, we thus propose our "unified insight" of "mining" semantics for large Scale Integration by exploiting hidden regularities across holistic sources. Further, to fulfill the promise of such holistic mining, we discuss challenges toward its realization for dynamic semantics discovery. As our initial works as well as several related efforts have witnessed, we believe our unified insight, holistic mining for semantics discovery, is a promising methodology toward enabling large Scale Integration.
Ismail Emre Araci - One of the best experts on this subject based on the ideXlab platform.
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recent developments in microfluidic large Scale Integration
Current Opinion in Biotechnology, 2014Co-Authors: Ismail Emre Araci, Philip BriskAbstract:In 2002, Thorsen et al. integrated thousands of micromechanical valves on a single microfluidic chip and demonstrated that the control of the fluidic networks can be simplified through multiplexors [ 1 ]. This enabled realization of highly parallel and automated fluidic processes with substantial sample economy advantage. Moreover, the fabrication of these devices by multilayer soft lithography was easy and reliable hence contributed to the power of the technology; microfluidic large Scale Integration (mLSI). Since then, mLSI has found use in wide variety of applications in biology and chemistry. In the meantime, efforts to improve the technology have been ongoing. These efforts mostly focus on; novel materials, components, micromechanical valve actuation methods, and chip architectures for mLSI. In this review, these technological advances are discussed and, recent examples of the mLSI applications are summarized.
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microfluidic very large Scale Integration mvlsi with integrated micromechanical valves
Lab on a Chip, 2012Co-Authors: Ismail Emre Araci, Stephen R QuakeAbstract:Microfluidic chips with a high density of control elements are required to improve device performance parameters, such as throughput, sensitivity and dynamic range. In order to realize robust and accessible high-density microfluidic chips, we have fabricated a monolithic PDMS valve architecture with three layers, replacing the commonly used two-layer design. The design is realized through multi-layer soft lithography techniques, making it low cost and easy to fabricate. By carefully determining the process conditions of PDMS, we have demonstrated that 8 × 8 and 6 × 6 μm2 valve sizes can be operated at around 180 and 280 kPa differential pressure, respectively. We have shown that these valves can be fabricated at densities approaching 1 million valves per cm2, substantially exceeding the current state of the art of microfluidic large-Scale Integration (mLSI) (thousands of valves per cm2). Because the density increase is greater than two orders of magnitude, we describe this technology as microfluidic very large Scale Integration (mVLSI), analogous to its electronic counterpart. We have captured and tracked fluorescent beads, and changed the electrical resistance of a fluidic channel by using these miniaturized valves in two different experiments, demonstrating that the valves are leakproof. We have also demonstrated that these valves can be addressed through multiplexing.
Shmuel S Oren - One of the best experts on this subject based on the ideXlab platform.
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large Scale Integration of deferrable demand and renewable energy sources
IEEE Transactions on Power Systems, 2014Co-Authors: Anthony Papavasiliou, Shmuel S OrenAbstract:We present a stochastic unit commitment model for assessing the impacts of the large-Scale Integration of renewable energy sources and deferrable demand in power systems in terms of reserve requirements. We analyze three demand response paradigms for assessing the benefits of demand flexibility: the centralized co-optimization of generation and demand by the system operator, demand bids and the coupling of renewable resources with deferrable loads. We motivate coupling as an alternative for overcoming the drawbacks of the two alternative demand response options and we present a dynamic programming algorithm for coordinating deferrable demand with renewable supply. We present simulation results for a model of the Western Electricity Coordinating Council.
