Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 77 for “"sliding-window"”.
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Hardware Realization and Implementation Issues for the Sliding-window Packet Switch
… centralized control and memory bottlenecks. The Sliding Window Packet Switch (SW) algorithm is a shared memory switch that employs decentralized control and multiple memory modules to facilitate the scalability of hardware. The SW algorithm is independent of the type of packet or cell. This …
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Unsupervised segmentation of heart sounds
… to segmentation: peak energy detection and sliding window autocorrelation. Emphasis is placed on synchronous detection of the heartbeats, so that subsequent subsystems can superimpose the heartbeats.An experimental database of heart sounds was compiled to assess the performance of the …
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Unsupervised machine learning and k-Means clustering as a way of discovering anomalous events In continuous seismic time series
… identifying anomalies in seismic time series. Sliding window approach was used for generating specific subsequences from the overall waveform. Dynamic Time Warping (DTW) was used as the method for comparing seismic subsequences. DTW barycenter averaging (DBA) was used as the method for …
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Geometric Multimedia Time Series
… community, we turn time series into shapes via sliding window embeddings, which we refer to as ``time-ordered point clouds'' (TOPCs). This framework has traditionally been used on a single 1D observation function for deterministic systems, but we generalize the sliding window technique so that …
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A Bayesian model for dynamic functional connectivity estimation in the human brain with structural priors
… temporal dynamics. Finally, it outperformed sliding window baselines and anatomically un-informed baselines on estimating instantaneous covariances according to out-of-sample log likelihood on two task datasets.
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Data Compression Strategies for RDAT/DDS Media in Hostile Environments
… algorithm to compress the correlated data and a sliding window algorithm to compress the text and switches between the two algorithms as the data type varies. The sliding window compressor T.ZR is adopted when the same principles are applied to the robust compression of English text alone. TJ7R …
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Demarcation of coding and non-coding regions of DNA using linear transforms
… were also applied on entire sequences in a sliding window fashion. Finally, the two transforms were applied on a large number of sequences from a variety of organisms. A Neyman Pearson based detector was used to obtain receiver operating curves, i.e., probability of detection versus …
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Compiler techniques for scalable performance of stream programs on multicore architectures
… nodes that operate on overlapping sliding windows of their input, translating serializing state into minimal and parametrized inter-core communication. Finally, for nodes that cannot be data-parallelized due to state, we are the first to automatically apply software-pipelining …
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Sensor Networks: Studies on the Variance of Estimation, Improving Event/Anomaly Detection, and Sensor Reduction Techniques Using Probabilistic Models
… joint probability, causal relationship, sliding window, and geospatial intelligence (GEOINT) method.
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Analysis of modal evolution caused by a weakly range-dependent seabed in shallow water and its application to inversion for geoacoustic properties
… asymptotic Hankel transform with a short sliding window is utilized. The local peak positions in the output spectra differ from the local eigenvalues due to both the range variation of the local modes and the interference of adjacent modes. The departure due to the former factor is …
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Temporal Dynamics at the Neurobehavioral Interface: In Search of a Common Currency
… INT by measuring the median frequency (MF) via sliding window analyses in both electroencephalography (EEG) activity and subjects’ continuous behavioral assessment of their perceived engagement in different music pieces. The main findings demonstrate significant differences in dynamic MF of both …
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Analysis of single event transients in arbitrary waveforms using statistical window analysis
Window functions are commonly used in data processing to detect transient events or for time-averaging of frequency spectra. A generalized window function is demonstrated using the Ionizing Radiation Effects Spectroscopy (IRES) technique to enhance the measurement of transient anomalies within …
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Non-Invasive Motion Detection and Classification in NICU Patients using Ballistographic Signals from a Pressure Sensitive Mat
… by the COP is tracked over time using a sliding window with data from seven patients. Window-boundary-suppression led to improved motion detection with precision = 0.84 and recall = 0.71 with a window of 10 seconds. For (b), seven features were derived from the COP, and feature selection …
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A Reservoir of Adaptive Algorithms for Online Learning from Evolving Data Streams
… positive, and false negative rates. FHDDM is a sliding window-based algorithm and applies Hoeffding’s inequality (Hoeffding, 1963) to detect concept drift. FHDDM slides its window over the prediction results, which are either 1 (for a correct prediction) or 0 (for a wrong prediction). Meanwhile, …
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Modeling for part-based visual object detection based on local features
… relying on a holistic object model and the sliding window principle. A major concern with holistic object detection is the insufficient tolerance to deformation, partial occlusion, and rotation. Part-based object detection can potentially overcome these limitations. However, the creation of …
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Visual detection and recognition using local features
… where the objects are first localized with a sliding window detector before being identified. We make multiple contributions along this path. All of the contributions pertain to the central theme of local image features. We demonstrate improved object detection performance with our proposed …
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Energy-Aware Inter-Data Center Virtual Machine Migration over Elastic Optical Networks
… DC. Proposing and utilizing the modified sliding-window lower confidence bound (MSW-LCB), we estimate the lowest power consumption among DCs and the lowest migration cost at each round to find a proper destination DC and path, respectively. Additionally, we adopt optical grooming …
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Machine Learning Interference Modelling for Cloud-native Applications
… changing runtime conditions through the use of a sliding window method. Our technique outperforms baseline and competing techniques by 1.45%-92.04%. These contributions can be beneficial to software architects and software operators when designing, deploying, and operating cloud-native …
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Predicting Hard Drive Failures in Computer Clusters
… pattern of messages may be. This approach uses a sliding window (sub-sequence) of messages to predict the likelihood of failure. Then, a frequency representation of the message sub-sequences observed are used as input to the SVM. The SVM associates the messages to a class of failed or non-failed …
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The neural correlates of social and non-social decision-making in resolving complex, dynamic uncertainty
… was examined via inter-subject correlation and sliding window approaches, revealing temporally dynamic, content-sensitive neural alignment in social-cognitive networks. The second study extended this design behaviorally, examining the structure and variability of hypothesis generation across …
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