Selecting appropriate models of ATM traffic sources is an important issue, since it is closely related to the successful design and efficient performance of the ATM networks to be built in the future. For the three ba...
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Selecting appropriate models of ATM traffic sources is an important issue, since it is closely related to the successful design and efficient performance of the ATM networks to be built in the future. For the three basic categories of sources (voice, data and video), numerous source models have been proposed in the literature. In this paper, we summarize the main features of each of these categories, and present a survey of related models. We argue that it is preferable to select a set of standard source models rather than a single such model. We define a set of criteria to be used in the selection, and choose appropriate source models accordingly.
This paper presents a unified treatment of methods for distribution-free analysis of repairable fault-tolerant systems. Material from diverse sources is presented for the first time in an integrated, easily accessible...
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This paper presents a unified treatment of methods for distribution-free analysis of repairable fault-tolerant systems. Material from diverse sources is presented for the first time in an integrated, easily accessible unit. In addition, new results are derived which enable more detailed analysis than had carlier been possible. New, streamlined proofs based only on elementary techniques are developed, facilitating extensions of the theory to a wider range of applications.
EEG and ECG signals are electrographic measures of brain and heart activity respectively and can indicate neurological states and mental task states. In this paper, we present an enhanced approach of a set of novel te...
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ISBN:
(数字)9798331527495
ISBN:
(纸本)9798331527501
EEG and ECG signals are electrographic measures of brain and heart activity respectively and can indicate neurological states and mental task states. In this paper, we present an enhanced approach of a set of novel temporal features such as energy, Shannon energy, entropy, and temporal energy with state-of-the-art machine learning classifiers to distinguish relaxing from task oriented cognitive states. We besides explore deep learning methods including Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, for their capacity to recognise complex characteristics within EEG and ECG patterns. We used a publicly available dataset from *** consisting of 36 (male and female) subjects with 21 channels (20 EEG plus 1 ECG). We found that no measure besides Random Forest outperformed all other traditional methods, with 99.34% accuracy. However, deep learning models continued to improve classification, specifically by extending into fusion of multi-modal signals and extraction of temporal features, suggesting the promise of real time cognitive state monitoring. Our results provide a direction for utilizing machine learning and deep learning jointly to improve mental state classification and task performance.
Active metasurfaces promise spatiotemporal control over optical wavefronts, but achieving high-speed modulation with pixel-level control has remained an unmet challenge. While local phase control can be achieved with ...
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Dear editor,Data analysis science is currently a hot topic in industry and academia due to ubiquitous and rapidly growing data [1, 2]. Data analysis technology has been applied in a variety of fields and has provided ...
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Dear editor,Data analysis science is currently a hot topic in industry and academia due to ubiquitous and rapidly growing data [1, 2]. Data analysis technology has been applied in a variety of fields and has provided efficient and profitable data-driven decisions. For instance, since the beginning of the20th century, large-scale opinion polls have been
Opens in BICMOS structures are analyzed here. It is shown that some opens cannot be detected by stuck-fault or other functional tests, since some transistors in BiCMOS gates do not affect the logical function of the g...
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Opens in BICMOS structures are analyzed here. It is shown that some opens cannot be detected by stuck-fault or other functional tests, since some transistors in BiCMOS gates do not affect the logical function of the gate. A switch-level model for CMOS circuits is extended to include bipolar devices. With this switch-level model, opens that cannot be detected by stuck-faults or other functional tests are easily identified. It is also shown that, in BICMOS circuits, an open defect in one transistor can accelerate the wearout of another nondefective transistor.
3D point cloud semantic segmentation technology has been widely used. However, in real-world scenarios, the environment is evolving. Thus, offline-trained segmentation models may lead to catastrophic forgetting of pre...
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We have been investigating an approach to parallel database processing based on treating Entity-Relationship (E-R) schema graphs as dataflow graphs. A prerequisite is to find appropriate embeddings of the schema graph...
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We have been investigating an approach to parallel database processing based on treating Entity-Relationship (E-R) schema graphs as dataflow graphs. A prerequisite is to find appropriate embeddings of the schema graphs into a processor graph, in this case a hypercube. This paper studies a class of adjacency preserving embeddings that map a node in the schema graph into a subcube ( relaxed squashed or RS embeddings) or into adjacent subcubes (relaxed extended squashed or RES embeddings) of a hypercube. The mapping algorithm is motivated by the technique used for state assignment in asynchronous sequential machines. In general, the dimension of the cube required for squashed embedding of a graph is called the weak cubical dimension or WCD of the graph. The RES embedding provides an RES-WCD of O (⌈log 2 n ⌉) for a completely connected graph, K n , and RS embedding provides an RS-WCD of O (⌈log 2 n ⌉ + ⌈log 2 m ⌉) for a completely connected bigraph, K m , n . Typical E-R graphs are incompletely connected bigraphs. An algorithm for embedding incomplete bigraphs is presented.
Depleting fossil energy sources and conventional polluting power generation pose a threat to sustainable *** generation from ubiquitous and spontaneous phase transitions between liquid and gaseous water has been consi...
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Depleting fossil energy sources and conventional polluting power generation pose a threat to sustainable *** generation from ubiquitous and spontaneous phase transitions between liquid and gaseous water has been considered a promising strategy for mitigating the energy *** materials with unique flexibility,processability,multifunctionality,and practicability have been widely applied for fibrous materials-based hydroelectricity generation(FHG).In this review,the power generation mechanisms,design principles,and electricity enhancement factors of FHG are first ***,the fabrication strategies and characteristics of varied constructions including 1D fiber,1D yarn,2D fabric,2D membrane,3D fibrous framework,and 3D fibrous gel are ***,the advanced functions of FHG during water harvesting,proton dissociation,ion separation,and charge accumulation processes are analyzed in ***,the potential applications including power supply,energy storage,electrical sensor,and information expression are also ***,some existing challenges are considered and prospects for future development are sincerely proposed.
Mild cognitive impairment (MCI) is an early stage of non-age-related cognitive decline with an increased risk of progressing to dementia. Early detection of MCI is essential for implementing preventative strategies th...
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