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Sentiment analysis, or opinion mining, is the process of extracting sentiment from documents or sentences, where the expressed sentiment is typically categorized as positive, negative, or neutral. Many different techniques have been proposed. In this paper, we report the reimplementation of nine algorithms and their evaluation across four corpora to assess the sentiment at the sentence level. We e
Abstract in UndeterminedPower efficiency has become the most important consideration for many modern computing devices. In this paper, we examine power efficiency of a range of graphics algorithms on different GPUs. To measure power consumption, we have built a power measuring device that samples currents at a high frequency. Comparing power efficiency of different graphics algorithms is done by m
A common assumption in motion blur rendering is that the triangle vertices move in straight lines. In this paper, we focus on scenarios where this assumption is no longer valid, such as motion due to fast rotation and other non-linear characteristics. To that end, we present a higher-order representation of vertex motion based on Bézier curves, which allows for more complex motion paths, and we de
In low-temperature combustion concepts such as partially premixed combustion, the ignition delay should be large enough in order to ensure sufficient fuel and air mixing before the start of combustion. It is also necessary that the combustion timing is sufficiently well phased for high thermal efficiency. Since the ignition delay and combustion timing are intimately coupled, the decoupling of the
Realistic network simulations are necessary to assess the performance of any communication system. In this paper, we describe an implementation of a channel model for vehicle-to-vehicle (V2V) communication in the OMNeT++/Plexe simulation environment. The model is based on previous extensive measurements in a V2V multilink highway scenario and cover line-of-sight (LOS) as well as obstructed LOS (OL
The premise of massive multiple-input multiple-output (MIMO) is based around coherent transmission and detection. Majority of the vast literature on massive MIMO presents performance evaluations over simplified statistical propagation models. All such models are drop-based and do not ensure continuity of channel parameters. In this paper, we quantify the impact of spatially consistent (SC) models
With the potential to provide a clean break from massive multiple-input multiple-output, large intelligent surfaces (LISs) have recently received a thrust of research interest. Various proposals have been made in the literature to define the exact functionality of LISs, ranging from fully active to largely passive solutions. Nevertheless, almost all studies in the literature investigate the fundam
The traditional way to capture rate and amplitude dependence of filled rubbers is by a branched model containing elastic, viscous, and frictional branches, leading to a decoupling of the rate and amplitude dependence. In order to capture the experimentally observed phenomena with a steeper increasing dynamic modulus with frequency, for small amplitudes, a model by Besseling (1958) is revisited. In
Massive multiple-input multiple-output (MIMO) promises significantly higher performance relative to conventional multiuser systems. However, the promised gains of massive MIMO systems rely heavily on the accuracy of the absolute front-end calibration, as well as quality of channel estimates at the base station (BS). In this paper, we analyze user equipment-aided calibration mechanism to estimate t
We propose that CDCL SAT solver heuristics such as restarts and clause database management can be analysed by studying the resolution proofs produced by the solvers, and by trimming these proofs to extract the clauses actually used to reach the final conclusion. We find that for non-adaptive Luby restarts higher frequency makes both untrimmed and trimmed proofs smaller, while adaptive restarts bas
We study planning problems where the transition function is described by a learned binarized neural network (BNN). Theoretically, we show that feasible planning with a learned BNN model is NP-complete, and present two new constraint programming models of this task as a mathematical optimization problem. Experimentally, we run solvers for constraint programming, weighted partial maximum satisfiabil
An algorithm is said to be certifying if it outputs, together with a solution to the problem it solves, a proof that this solution is correct. We explain how state of the art maximum clique, maximum weighted clique, maximal clique enumeration and maximum common (connected) induced subgraph algorithms can be turned into certifying solvers by using pseudo-Boolean models and cutting planes proofs, an
Braided convolutional codes (BCCs) are a class of spatially coupled turbo-like codes that can be described by a (2), (3)-regular compact graph. In this paper, we introduce a family of (d v , d c )-regular GLDPC codes with convolutional code constraints (CC-GLDPC codes), which form an extension of classical BCCs to arbitrary regular graphs. In order to characterize the performance in the waterfall
Propagation models constitute a fundamental building block of wireless communications research. Before we build and operate real systems, we must understand the science of radio propagation, and develop channel models that both reflect the important propagation processes and allow a fair comparison of different systems. In the past five decades, wireless systems have gone through five generations,
Ray-Triangle intersection is a fundamental computation in most ray tracing algorithms. The prohibitive cost of the ray-triangle test algorithms, however, limits the utilization of these algorithms in settings with low power budgets, such as mobile systems. In this work, we analyze the precision requirements for ray-triangle intersection and observe that for most of the rays a low-precision is suff
Radio based positioning or tracking solutions typically require wideband signals or phase coherent antennas. In this paper, we present a target tracking method based on received non-coherent signal strength differences (RSSDs) between antennas for outdoor Internet-of-things (IoT) scenarios. We introduce an RSSD model based on classical path-loss models. With known antenna patterns and antenna arra
This paper presents the development of a non-dimensional model of a continuous cross-flow atomic layer deposition (ALD) reactor with temporally separated precursor pulsing and a structured model-based methodology for scaling up the substrate dimensions. The model incorporates an ALD gas–surface reaction kinetic mechanism for the deposition of thin ZnO films from Zn(C2H5)2 and H2O precursors that w
