153 research outputs found

    Event-based clustering for reducing labeling costs of event-related microposts

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    Automatically identifying the event type of event-related information in the sheer amount of social media data makes machine learning inevitable. However, this is highly dependent on (1) the number of correctly labeled instances and (2) labeling costs. Active learning has been proposed to reduce the number of instances to label. Albeit the thematic dimension is already used, other metadata such as spatial and temporal information that is helpful for achieving a more fine-grained clustering is currently not taken into account. In this paper, we present a novel event-based clustering strategy that makes use of temporal, spatial, and thematic metadata to determine instances to label. An evaluation on incident-related tweets shows that our selection strategy for active learning outperforms current state-of-the-art approaches even with few labeled instances

    Cost-effective online trending topic detection and popularity prediction in microblogging

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    Identifying topic trends on microblogging services such as Twitter and estimating those topics’ future popularity have great academic and business value, especially when the operations can be done in real time. For any third party, however, capturing and processing such huge volumes of real-time data in microblogs are almost infeasible tasks, as there always exist API (Application Program Interface) request limits, monitoring and computing budgets, as well as timeliness requirements. To deal with these challenges, we propose a cost-effective system framework with algorithms that can automatically select a subset of representative users in microblogging networks in offline, under given cost constraints. Then the proposed system can online monitor and utilize only these selected users’ real-time microposts to detect the overall trending topics and predict their future popularity among the whole microblogging network. Therefore, our proposed system framework is practical for real-time usage as it avoids the high cost in capturing and processing full real-time data, while not compromising detection and prediction performance under given cost constraints. Experiments with real microblogs dataset show that by tracking only 500 users out of 0.6 million users and processing no more than 30,000 microposts daily, about 92% trending topics could be detected and predicted by the proposed system and, on average, more than 10 hours earlier than they appear in official trends lists

    Expanding the applications of poly(dimethylsiloxane) in biomicrofluidics

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    This work aims to create novel applications for poly(dimethylsiloxane) (PDMS) in the field of biomicrofluidics through oxidative stress detection, doping of the polymer for intentional leaching into microdevices, and the development of low-cost implements for fabricating PDMS microfluidic devices. PDMS has become the polymer of choice for research in microfluidics due to its optical clarity, ease of fabrication, flexibility in design, good mechanical properties, and the ability to chemically modify the surface. Biomicrofluidics enables the rapid throughput and analysis of small biological samples requiring less time investment and reagent use than traditional macroscale laboratory techniques. Polymer devices are inexpensive, easily fabricated using rapid prototyping techniques, and lend themselves well to surface chemistry modifications. A new chemical surface modification has been developed that allows the selective capture of carbonylated proteins on a PDMS microchannel. PDMS can be doped with small molecules prior to curing of the prepolymer mixture, and these small molecules can subsequently leach into cell culture media or a microfluidic flow. By quantifying the leaching amount over time, this research lays the groundwork for tunable doped microfluidic devices that can deliver a steady low concentration dose of certain molecules into a cell culture or microdevice without human interference or risk of contamination. PDMS soft lithography traditionally relies on cleanroom techniques such as photolithography for creation of mold masters for PDMS devices. Such methods require significant investment into specialized equipment and environments to develop molds that may not be suitable for the desired applications. This research employs computational fluid dynamics (CFD) and rapid prototyping techniques in the development of novel microfluidic designs. CFD provides verification of the flow rate and pressure drop in a microfluidic channel, ensuring that the resulting flow speeds allow the captured proteins or attached cells in culture to remain attached to the microchannel. A 3D printer and an Arduino microcontroller were used to create a spin table for coating silicon wafers in photoresist, and a UV LED light source was designed for exposing the photoresist. This approach reduces the equipment cost involved in creating microfluidic molds and allows the creation of a variety of new microfluidic devices

    Fabrication of clog-free microfluidic cell isolation and solid-state light-emitting devices for biomedical applications

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    Over the past few decades, research and development on microfluidic devices, also referred to as lab-on-a-chip systems or microfluidic total analysis systems (TAS), have advanced quickly. There aren't many commercial success stories for microfluidic devices, despite the many advantages they offer, including improved analytical performance, decreased sample and reagent usage in the biomedical disciplines. From liquid biopsies, microfluidics has been used to filter out rare tumor cells from blood. Low flow rates and device clogs brought on by a single fluidic path function severely restrict processing. A novel technique was created employing multifunctional hybrid microposts with various features has effectively ensured high effective separation of rare cells from biological fluids. Furthermore, Solid-State perovskite material is synthesized, fabricated in 3D printed layers, and characterized for the need to be incorporated into fluorescence imaging of biological cells. Since effective imaging techniques are required to image the cells in a PDMS-based microfluidic device, the emission of the perovskite material shows positive signs as a fluorescent light source for identification of cells based on their emission of light.Includes bibliographical references

    Efficient document filtering using vector space topic expansion and pattern-mining: the case of event detection in microposts

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    Automatically extracting information from social media is challenging given that social content is often noisy, ambiguous, and inconsistent. However, as many stories break on social channels first before being picked up by mainstream media, developing methods to better handle social content is of utmost importance. In this paper, we propose a robust and effective approach to automatically identify microposts related to a specific topic defined by a small sample of reference documents. Our framework extracts clusters of semantically similar microposts that overlap with the reference documents, by extracting combinations of key features that define those clusters through frequent pattern mining. This allows us to construct compact and interpretable representations of the topic, dramatically decreasing the computational burden compared to classical clustering and k-NN-based machine learning techniques and producing highly-competitive results even with small training sets (less than 1'000 training objects). Our method is efficient and scales gracefully with large sets of incoming microposts. We experimentally validate our approach on a large corpus of over 60M microposts, showing that it significantly outperforms state-of-the-art techniques

    Replication of metal-based high-aspect microscale structures by high temperature micromolding

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    In microsystem technology a large range of materials will be available only after the necessary microfabrication technologies have been developed or adapted. More than a decade ago, the existing microfabrication technologies were restricted to structuring and shaping techniques producing three-dimensional microstructures out of silicon, mostly unfilled plastics or a few pure metals or binary alloys. However, the choice of materials for microcomponents is determined by the function and conditions of use of microsystems. Some microdevices can only work well when made of specific metal components. To meet this need, several microfabrication techniques have been developed, such as second electroforming of molded plastic mold, microcasting, microinjection molding, ultra precision micromilling, micro electrical discharge maching, and their modified techniques, each with a certain range of metal choices. In chapter 1, these techniques are reviewed briefly and compared with each other. More importantly, a new technique for fabricating microscale metal structures - high-temperature compression molding is proposed and the related issues are discussed, including surface engineering of the mold insert, molding behavior comparison between molding different metals and molding with surface modified inserts and unmodified inserts, and molding mechanics. Chapters 2, 3 and 4 focus on the first issue - surface engineering of the mold insert, including characterization of Ti containing hydrocarbon (Ti-C:H) coatings in terms of microstructure, mechanical properties, tribological characteristics and tribochemistry, and conformal coating of Ti-C:H over LiGA fabricated microscale structures. The second issue - molding behavior is discussed in chapters 5, 6 and 7, including preliminary experiments on micromolding of Pd and Zn, instrumented micromolding of Pb and high-temperature instrumented micromolding of Al with LiGA fabricated Ni inserts. Chapter 8 focuses on the third issue - the mechanics of molding. In this chapter, a simple mechanics model of the micromolding process was developed, which relates the stresses on the insert during micromolding primarily to the yield strength of the molded metal and frictional tractions on the sides of the insert. Finally, chapter 9 summarizes this whole dissertation research with main results and achievements highlighted and the future research discussed
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