communicating designs orally and in writing how do we let our client know about our solutions
engineering design a project based introduction 4th edition
... made? 10.2.4 How much will it cost? 141 10.3 Notes 141 CHAPTER 11 137 COMMUNICATING DESIGNS ORALLY AND IN WRITING How we let our client know about our solutions? 142 11.1 General guidelines for technical ... mind that we are not presenting a recipe for doing design Instead, we are outlining a framework within which we can articulate and think about what we are doing as we design something Further, ... that we explore in greater detail in later chapters We then list some of the kinds and sources of design knowledge that informs what we as designers, including: how we acquire information; how we...
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fracture mechanics of concrete concepts, models and determination of material properties
... progress in research, the time appears ripe for introducing fracture mechanics into design practice This should not only bring about more uniform safety margins, thus improving safety and economy ... nonlocal strain-softening models, etc.) are described and random particle simulation o f aggregate microstructure is discussed The principles o f implementation of these models in finite element ... humidity and temperature, as well as the effect o f cyclic loading Chapter is devoted t o the effect of reinforcing bars and their bond slip on fracture propagation, and t o fracture of fiber-reinforced...
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Data Streams Models and Algorithms- P1
... stamps Ti, .Tin maintained in is CF2t The sum of the time stamps Ti, Tin maintained in CFlt is The number of data points is maintained in n E7L=1 e; We note that the above definition of micro-cluster ... Ambuj K.Singh Introduction Indexing Streams 2.1 Preliminaries and definitions 2.2 Feature extraction 2.3 Index maintenance 2.4 Discrete Wavelet Transform Querying Streams 3.1 Monitoring an aggregate ... data mining problems on streams Our discussion illustrates the importance of our approach for a variety of mining problems in the data stream domain Introduction In recent years, advances in hardware...
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Data Streams Models and Algorithms- P2
... the buffersize at 1600 points, which means upon receiving 1600 points (including both training and test stream points) we' ll use a small set of the training data points (In this case kfit =80) ... to incorporate user-interaction rn The integration of data stream management systems and data stream mining approaches: The integration among storage, querying, mining and reasoning of the incoming ... purpose, we only maintain the summary statistics for the data points in the clusters as opposed to the individual data points themselves In addition to the first and second order moments we also maintain...
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Data Streams Models and Algorithms- P3
... DATA STREAMS: MODELS AND ALGORITHMS Sliding window: Given the length of the sliding window w and current timepoint t, we are interested in the frequent pattern time in the window W [t - w 1,t] As ... frequent pattern-mining questions over different type of window models Landmark window: In this model, we are interested in, from a starting timepoint i to the current timepoint t, what are the ... [9] Domingos P and Hulten G (2000) Mining High-speed Data Streams In Proceedings of the Association for Computing Machinery Sixth International Conference on Knowledge Discovery and Data Mining...
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Tài liệu Data Streams Models and Algorithms- P4 doc
... the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, 2003 [8] Moses Charikar, Kevin Chen, and Martin Farach-Colton Finding frequent items in data streams In ICALP ... R Jin and G Agrawal An algorithm for in- core frequent itemset mining on streaming data In ICDM, November 2005 [23] Ruoming Jin and Gagan Agrawal An algorithm for in- core frequent itemset mining ... work in [13,14] is focussed on the effects of evolution on data mining models and algorithms While these results show some interesting results in terms of generalizing existing data mining algorithms,...
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Tài liệu Data Streams Models and Algorithms- P5 docx
... processing and mining in data cubes, and management and mining o stream data We briefly review previous f research in these areas and point out the differences from our work In data warehousing and ... on-line response, and both space and time are critical in processing, we examine both time and space consumption In our study, besides presenting the total time and memory taken to compute and ... answering time The remaining of the paper is organized as follows In Section 2, we define the basic concepts and introduce the problem In Section 3, we present an architectural design for on-line...
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Tài liệu Data Streams Models and Algorithms- P6 pdf
... load shedding decisions on the streams being joined Joins between data streams are typically sliding window joins A sliding window join with window size w introduces an implicit join predicate ... join Similarly, in order to efficiently process sliding-windowjoins, we would like to maintain statistics over the sliding windows, for streams participating in the join Besides being useful for ... sliding-window joins are quite popular in most stream applications In order to improve join processing, database systems maintain "join statistics" for the relations participating in the join...
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Tài liệu Data Streams Models and Algorithms- P7 ppt
... Another kind of inequality often used in stream mining is the Hoeffding inequality In this inequality, we bound the sum of k independent bounded random variables For example, for a set of k independent ... to determine sliding window sketches with a fixed window length For each window of length 1, we need to perform k operations for a sketch of size k Since there are O(n - 1) sliding windows, this ... variety of mining and query processing techniques in data stream processing Some key synopsis methods include those of sampling, wavelets, sketches and histograms In this chapter, we will provide...
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Tài liệu Data Streams Models and Algorithms- P8 doc
... "jumping window" semantics [22], we divide the sliding window into a number of sub-windows; when the newest sub-window fills up, it is appended to the sliding window while the oldest sub-window in ... time-based sliding-window join under the CQL semantics is classified as a weak non-monotonic operator by Golab and 0zsu [24] However, for a tuple-based sliding-window join, how to infer deletions in the ... sets with inter-attribute correlations, in which methods such as histograms and wavelets become increasingly ineffective Sampling is however ineffective in counting measures which rely on infrequent...
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Tài liệu Data Streams Models and Algorithms- P9 doc
... i.e., dividing the data sequence into sliding windows, and the query sequence into disjoint windows The overall framework is based on answering pattern queries using a single-resolution index built ... ,and &, i.e., one for each resolution, can be computed However, this requires maintaining all the stream values within a time window equal to the size of the largest sliding window, i.e., in our ... Crete, Greece [18] Ding, L and Rundensteiner, E A (2004) Evaluating window joins over punctuated streams In Proceedings o the 2004 International Conference on f Information and Knowledge Management,...
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Tài liệu Data Streams Models and Algorithms- P10 docx
... of our approach In Section we elaborate on the efficiency and accuracy of SPIRIT Finally, in Section we conclude Related work Much of the work on stream mining has focused on finding interesting ... of our method In this sense, an exponential forgetting factor is more appealing than a sliding window, as the latter has explicit buffering requirements Putting SPIRIT to work We show how we ... discovering hidden variables improve on discovering correlations, by first doing dimensionality reduction with random projections, and then periodically computing the SVD However, the method incurs...
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Tài liệu Data Streams Models and Algorithms- P11 doc
... stream mining in resource constrained domains Third, we summarize research efforts on building systems support for facilitating distributed stream mining Finally, we conclude with emerging research ... Parthasarathy, and M J Zaki Mining frequent itemsets in evolving databases In Proceedings o the SIAMInternational Conference on Data Mining, 2002 f [45] Wei Yu, Dong Xuan, and Wei Zhao Middleware-based ... Conference on Data Mining (SDM), 2005 [13] M Ester, H Kriegel, J Sander, M Wirnmer, and X Xu Incremental clustering for mining in a data warehousing environment In Proceedings o the International Conference...
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Tài liệu Data Streams Models and Algorithms- P12 ppt
... into four sites) We denote by Bol(k), the Bayesian network obtained at step k using our online learning approach and by Bb,(k), the Bayesian network obtained using a regular batch mode learning, ... efficiently handle joins queries over multiple sensors and joins of sensor data with external tables A non-blocking form of join processing is sliding time window join where a time window over the timestamps ... International Conference in Data Mining (SDM), Bethesda, Maryland, 2006 [26] R Wolff and A Schuster Association rule mining in peer-to-peer systems In Proceedings o ICDM'03, Melbourne, Florida, 2003...
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Tài liệu Data Streams Models and Algorithms- P13 docx
... p-stable distributions, 190 Sliding Window Joins, 11 Sliding Window Joins and Loadshedding, 144 Sliding Window Model, 149 Sliding Window Model for Frequent Pattern Mining, 63 Spatial Velocity Profiles, ... MODELS AND ALGORITHMS Hoeffding Inequality, 46, 174 Hoeffding Trees, 46 HPSTREAM 22 Iceberg Cubing for Stream Data, 112 Index Maintenance in Data Streams, 244 Indexing Data Streams, 238 Join Estimation ... Querying Data Streams, 238 Random Projection and Sketches, 184 Relational Join View, 11 Relative Error Histogram Construction, 198 Reservoir Sampling, 174 Reservoir Sampling with sliding window,...
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08 TAYLOR MODELS AND OTHER VALIDATED FUNCTIONAL INCLUDING METHOD MAKINO & m BERZ
... coding integers (ni,1 , ni,2 ) and remainder bound interval I with a oating point real number c is performed in the following manner The tallying variable t and the sweeping variable s are initialized ... resulting in 20 scanning points for each x and y, and 40 scanning points for z, for a total of 20 ì 20 ì 40 = 16, 000 grid points We set the domain for the function evaluation around each scanning ... K Makino, M Berz the errors due to oating point arithmetic are accumulated in a oating point tallying variable t which in the end is used to increase the remainder bound interval I by an interval...
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Tài liệu 44 Speech Production Models and Their Digital Implementations ppt
... Thus, the input and output volume velocities are seen to be linear combinations of a and b Eliminating the parameters a and b from these relationships shows that the input pressure and volume ... Two independent solutions of Eq (44.12) are well known to be cosh(σ x) and sinh(σ x), and a bit of algebra shows that the chain matrix for this case is K= cosh(σ L)ψ (1/β) sinh(σ L) β sinh(σ ... speech is about 0.1 l/s It may peak as high as l/s during rapid inhales in singing Periodic excitation originates mainly at the vibrating vocal folds, turbulent excitation originates primarily downstream...
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Tài liệu SLEEP-RELATED BREATHING DISORDERS EXPERIMENTAL MODELS AND THERAPEUTIC POTENTIAL docx
... mechanical, including photocopying, microfilming, and recording, or by any information storage and retrieval system, without permission in writing from the publisher Current printing (last digit): 10 PRINTED ... Overview: Research on Sleep and Breathing in Rodents Sleep Recordings in Rats Sleep Recordings in Mice Application of Plethysmography to Research in Sleep and Breathing in Rodents References Neurochemical ... in Bulldogs and Control Dogs Age-Related Changes in SDB and Upper Airway Muscle Function in the English Bulldog Neural Mechanisms Underlying OSDB in the Bulldog Conclusions References Sleep in...
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