Model-Based Similarity Measure in TimeCloud

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Anomaly detection (AD) is essential in identifying rare and often critical events in complex systems, finding applications in fields such as network intrusion detection, financial fraud detection, and fault detection in infrastructure and industrial system ...

Deep neural networks (DNN) have become an essential tool to tackle challenging tasks in many fields of computer science. However, their high computational complexity limits their applicability. Specialized DNN accelerators have been developed to accommodat ...

Analytical workloads are evolving as the number of users surges and applications that submit queries in batches become popular. However, traditional analytical databases that optimize-then-execute each query individually struggle to provide timely response ...

Near-term quantum devices can be used to build quantum machine learning models, such as quantum kernel methods and quantum neural networks (QNN), to perform classification tasks. There have been many proposals on how to use variational quantum circuits as ...

Voice activity detection (VAD) is an important pre-processing step for speech technology applications. The task consists of deriving segment boundaries of audio signals which contain voicing information. In recent years, it has been shown that voice source ...

Modern cities dynamically face several challenges including digitalization, sustainability, resilience and economic development. Urban planners and designers must develop urban forms that address these challenges. With the integration of new communication ...

Analytics on modern data analytic and data warehouse systems often need to run large complex queries on increasingly complex database schemas. A lot of progress has been made on executing such complex queries using techniques like scale out query processin ...

Towards the end of the second trimester of gestation, a human fetus is able to register environmental sounds. This in utero auditory experience is characterized by comprising strongly low-pass-filtered versions of sounds from the external world. Here, we p ...

This paper proposes a representational model for image pairs such as consecutive video frames that are related by local pixel displacements, in the hope that the model may shed light on motion perception in primary visual cortex (V1). The model couples the ...

Improving maintenance scheduling of generation units in an electricity market would increase the safety and reliability of the system. This problem can be modeled as a multi-agent bi-level decision-making problem associated with some safety constraints. In ...

Sentiment analysis is the automated coding of emotions expressed in text. Sentiment analysis and other types of analyses focusing on the automatic coding of textual documents are increasingly popular in psychology and computer science. However, the potenti ...

In many applications, a dataset can be considered as a set of observed signals that live on an unknown underlying graph structure. Some of these signals may be seen as white noise that has been filtered on the graph topology by a graph filter. Hence, the k ...

The recent trend of an increasing share of renewable energy sources in modern power systems, as well as the integration of power electronics equipment, is shaping the requirements for stable grid infrastructure. These requirements mainly come from the stab ...

Grading student SQL queries manually is a tedious and error-prone process. Earlier work on testing correctness of student SQL queries, such as the XData system, can be used to test the correctness of a student query. However, in case a student query is fou ...

Optical frequency combs are a series of phase-locked and equidistant laser lines in the spectral domain. In the time domain, they correspond to periodic pulse trains by the Fourier relation. The ability to shape optical combs and pulse trains is pivotal to ...

In the field of UAV object tracking, correlation filter based approaches have received lots of attention due to their computational efficiency. The methods learn filters by the ridge regression and generate response maps to distinguish the specified target ...

We propose a simultaneous noise filtering and phase unwrapping algorithm. Spatial evolution of phase is modeled as an autoregressive Gaussian Markov random field. Accordingly, phase value at a pixel is related to phase values at surrounding pixels in a pro ...

A method of estimating a value (311-313) indicative of a signal component of an input imaging dataset (190) includes determining a normalized Fourier-domain representation of the input imaging dataset (190); and for each one of multiple low-pass filters (3 ...

In this paper, we propose a new variety of strong field confinement, ultra-compact size, easy-to-integrate spoof surface plasmon polariton (SSPP) waveguides based on double-sided parallel-strip lines (DSPSL), which are formed by etching opposite spiral gro ...

Power-Hardware-in-the-Loop (PHIL) setups have gained high importance in validation of the performance of newly developed instruments and devices with low risk and implementation cost. However, the interconnection of a power hardware with a simulated model ...

Model-Based Similarity Measure in TimeCloud

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NNG-Mix: Improving Semi-Supervised Anomaly Detection with Pseudo-Anomaly Generation

Hardware-Software Co-design for Improved Resource Utilization in DNN Accelerators

Efficient Concurrent Analytical Query Processing using Data and Workload-conscious Sharing

Exploring quantum perceptron and quantum neural network structures with a teacher-student scheme

Unsupervised Voice Activity Detection by Modeling Source and System Information using Zero Frequency Filtering

Reviewing the application of machine learning methods to model urban form indicators in planning decision support systems : potential, issues and challenges

Efficient GPU-accelerated Join Optimization for Complex Queries

Prenatal auditory experience and its sequelae

Learning V1 Simple Cells with Vector Representation of Local Content and Matrix Representation of Local Motion

Multi-agent maintenance scheduling of generation unit in electricity market using safe deep reinforcement learning algorithm

Text as signal. A tutorial with case studies focusing on social media (Twitter)

Figlearn: Filter And Graph Learning Using Optimal Transport

Medium Voltage Impedance and Admittance Measurement and System Identification Techniques

Edit Based Grading of SQL Queries

Versatile shaping of optical frequency combs and applications

Learning Temporary Block-Based Bidirectional Incongruity-Aware Correlation Filters for Efficient UAV Object Tracking

Simultaneous unwrapping and low pass filtering of continuous phase maps based on autoregressive phase model and wrapped Kalman filtering

Benchmarking of single imaging datasets

Ultra-compact spoof surface plasmon polariton waveguides and notch filters based on double-sided parallel-strip lines

Stabilization and Performance Improvement of Power-Hardware-in-the-Loop Test Using a Robust Data-Driven Method