標(biāo)題: Titlebook: Learning from Data Streams; Processing Technique Jo?o Gama,Mohamed Medhat Gaber Book 2007 Springer-Verlag Berlin Heidelberg 2007 LEGO Minds [打印本頁(yè)] 作者: deep-sleep 時(shí)間: 2025-3-21 16:12
書(shū)目名稱(chēng)Learning from Data Streams影響因子(影響力)
書(shū)目名稱(chēng)Learning from Data Streams影響因子(影響力)學(xué)科排名
書(shū)目名稱(chēng)Learning from Data Streams網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱(chēng)Learning from Data Streams網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱(chēng)Learning from Data Streams被引頻次
書(shū)目名稱(chēng)Learning from Data Streams被引頻次學(xué)科排名
書(shū)目名稱(chēng)Learning from Data Streams年度引用
書(shū)目名稱(chēng)Learning from Data Streams年度引用學(xué)科排名
書(shū)目名稱(chēng)Learning from Data Streams讀者反饋
書(shū)目名稱(chēng)Learning from Data Streams讀者反饋學(xué)科排名
作者: CANE 時(shí)間: 2025-3-21 21:47 作者: Thyroid-Gland 時(shí)間: 2025-3-22 02:19 作者: 陳舊 時(shí)間: 2025-3-22 06:38 作者: ALE 時(shí)間: 2025-3-22 10:23 作者: 思考 時(shí)間: 2025-3-22 16:55 作者: 變白 時(shí)間: 2025-3-22 20:15 作者: Archipelago 時(shí)間: 2025-3-22 22:15 作者: Charlatan 時(shí)間: 2025-3-23 04:30
learning, and tensor analysis techniques.Presents applicatio.Sensor networks consist of distributed autonomous devices that cooperatively monitor an environment. Sensors are equipped with capacities to store information in memory, process this information and communicate with their neighbors. Proces作者: 常到 時(shí)間: 2025-3-23 09:09
Predictive Learning in Sensor Networksthe learning process and managing the trade-off between the cost of updating a model and the benefits in performance gains. In this chapter we illustrate these ideas in two learning scenarios—centralized and distributed—and present illustrative algorithms for these contexts.作者: 人充滿(mǎn)活力 時(shí)間: 2025-3-23 12:25
Tensor Analysis on Multi-aspect Streamsions of WTA, independent-window tensor analysis (IW) and moving-window tensor analysis (MW), are presented and evaluated extensively on real data sets. Finally, we illustrate one important application, Multi-Aspect Correlation Analysis (MACA), which uses WTA and we demonstrate its effectiveness on an environmental monitoring application.作者: Traumatic-Grief 時(shí)間: 2025-3-23 16:18
Knowledge Discovery from Sensor Data for Security Applicationsof knowledge discovery. This chapter describes a case study in the area of transportation security to describe both the key challenges, as well as the possible solutions, in this high-priority area. A?suite of knowledge discovery tools developed for the purpose is described along with a discussion on future requirements.作者: 排他 時(shí)間: 2025-3-23 21:47
TinyOS Education with LEGO MINDSTORMS NXTed on the same hardware. This chapter argues that this comparability facilitate across-community adoption and awareness of TinyOS. Finally, we present the first TinyOS project on NXT, hosted both at TinyOS 2.x contrib and SourceForge under the . name.作者: agonist 時(shí)間: 2025-3-24 00:25 作者: 檔案 時(shí)間: 2025-3-24 04:06
M. A. Hammad,T. M. Ghanem,W. G. Aref,A. K. Elmagarmid,M. F. Mokbel作者: Minuet 時(shí)間: 2025-3-24 06:40
Knowledge Discovery from Sensor Data For Scientific Applicationshazards have established history of using sensor data, such as data from DOPPLER radars. Recent advances in sensor technology and computational strengths have created a need for new approaches to analyzing data associated with weather, climate, and associated natural hazards. Knowledge discovery off作者: semble 時(shí)間: 2025-3-24 11:07
Book 2007o researchers and graduate students the state of the art in data stream processing in sensor networks. The huge bibliography offers an excellent starting point for further reading and future research. .作者: collateral 時(shí)間: 2025-3-24 17:34 作者: 宣誓書(shū) 時(shí)間: 2025-3-24 19:24 作者: ERUPT 時(shí)間: 2025-3-25 01:23
Jo?o Gama,Mohamed Medhat Gaberations, discrete dislocation dynamics and other micro/mesoscopic computational analyses. The Symposium attracted sixty-six participants from eight countries, and forty- two papers were presented. The presentations comprised a wide variety of fundamental subjects of physics, mechanical models, comput作者: Neuralgia 時(shí)間: 2025-3-25 04:31
Pedro Pereira Rodrigues,Jo?o Gama. Several models have been proposed in the past for describing this process [2]. They are based on the assumption that the emitted dislocations are distributed randomly in the matrix, i.e. that the yield properties of the matrix are homogeneous. The present work aims at giving a new insight into thi作者: 表示問(wèn) 時(shí)間: 2025-3-25 09:33
Jo?o Gama,Rasmus Ulslev Pedersenariation of the displacements was accepted (i.e. three and twelve parameters or degrees of freedom were used to describe a field of each component of displacement vector for the subcell and the cell, respectively). These models can give overestimated values of macroscopic stresses. The question is o作者: Nonporous 時(shí)間: 2025-3-25 14:05
Jimeng Sun,Spiros Papadimitriou,Philip S. Yuent on the microstructural features and the concentration of the included phase. Finally, the case of the thermal shock resistance of porous ceramics is presented as an example of application of the microstructure-property correlations to design new materials with improved properties.作者: 使虛弱 時(shí)間: 2025-3-25 18:02 作者: Robust 時(shí)間: 2025-3-25 23:41
Auroop R. Ganguly,Olufemi A. Omitaomu,Randy M. Walkerls. However, the second approach allows to reuse and to recombine the parameterized, reduced order component models arbitrarily. It therefore introduces more flexibility in the modeling process, enabling for example a toolbox based optimization with parameterized, reduced order models.作者: 雄辯 時(shí)間: 2025-3-26 00:30
Auroop R. Ganguly,Olufemi A. Omitaomu,Yi Fang,Shiraj Khan,Budhendra?L. Bhaduri thicknesses decrease it is observed that the yield strength required to fit the curves increases and scale-dependent materials properties are essential for design. Similarly the assessment of fracture response of very thin coatings requires modeling of the indentation stress field and how it is mod作者: 慷慨不好 時(shí)間: 2025-3-26 08:02 作者: 諷刺 時(shí)間: 2025-3-26 09:16
Sensory Data Monitoringying which data is most relevant to user’s goals, minimising the cost of gathering that data, and clearing the gathered data. This chapter outlines the state-of-the-art in addressing each of these challenges.作者: misshapen 時(shí)間: 2025-3-26 12:52
Clustering Techniques in Sensor Networkstely transformed into a web of sensorial devices, some of them with local processing ability. This scenario represents a new knowledge-extraction environment, possibly not completely observable, that is much less controlled by both the human user and a common centralized control process.作者: aesthetic 時(shí)間: 2025-3-26 18:01 作者: 他一致 時(shí)間: 2025-3-26 22:25
Tensor Analysis on Multi-aspect Streamsture, humidity, etc.) as well as location. Aside from time stamp, type and location are the two additional aspects. How to model such streams? How to simultaneously find patterns within and across the multiple aspects? How to do it incrementally in a streaming fashion? In this paper, all these probl作者: echnic 時(shí)間: 2025-3-27 04:51
Knowledge Discovery from Sensor Data for Security Applicationst recognition is through online knowledge discovery based on dynamic, heterogeneous data available from strategically placed wide-area sensor networks. The knowledge discovery process needs to coordinate adaptive predictive analysis with real-time analysis and decision support systems. The ability t作者: 自作多情 時(shí)間: 2025-3-27 06:58
Knowledge Discovery from Sensor Data For Scientific Applicationsl environments. The ability to generate insights or new knowledge from sensor data is critical for many high-priority scientific applications especially weather, climate, and associated natural hazards. One example is sensor-based early warning systems for geophysical extremes such as tsunamis or ex作者: cancer 時(shí)間: 2025-3-27 13:24 作者: Jogging 時(shí)間: 2025-3-27 13:47
ion takes place when the temperature is lowered, and a reverse transformation occurs when they are subsequently heated [1–6]. Upon heating, steels normally do not show a well defined shape memory effect while NiTi does. One of the major differences between these two materials is the deformation mech作者: Cleave 時(shí)間: 2025-3-27 20:03 作者: 責(zé)怪 時(shí)間: 2025-3-27 23:49 作者: Hiatus 時(shí)間: 2025-3-28 02:50 作者: 河潭 時(shí)間: 2025-3-28 09:26
Jo?o Gama,Rasmus Ulslev Pedersenblem available in the literature [1–3] are based on a number of simplifying assumptions which allow the distribution of local fields of displacements, strains, stresses in a composite to be described in terms of a small number of parameters (degrees of freedom). For example, for the construction of 作者: Incommensurate 時(shí)間: 2025-3-28 10:37
Jimeng Sun,Spiros Papadimitriou,Philip S. Yus. It deals with the aim, to get a better scientific insight into the effects of microstructure on the properties of multiphase materials and to use the results technologically for designing purposes. In this context porous materials are considered to be the limiting case of multiphase materials, wh作者: 賞心悅目 時(shí)間: 2025-3-28 17:55
of several parameterized component models. Two approaches for the?Parametric Model Order Reduction?of such coupled systems are presented and compared in a reduced order shape optimization?example. In the first approach, the coupled, parameterized system is derived by coupling the parameterized, full作者: Digitalis 時(shí)間: 2025-3-28 21:18
Auroop R. Ganguly,Olufemi A. Omitaomu,Randy M. Walkerof several parameterized component models. Two approaches for the?Parametric Model Order Reduction?of such coupled systems are presented and compared in a reduced order shape optimization?example. In the first approach, the coupled, parameterized system is derived by coupling the parameterized, full作者: TIGER 時(shí)間: 2025-3-29 00:30 作者: 車(chē)床 時(shí)間: 2025-3-29 03:58
9樓作者: Malaise 時(shí)間: 2025-3-29 09:15
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9樓作者: AGONY 時(shí)間: 2025-3-29 16:56
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