nils-herrmann/clean_scirepeval huggingface dataset:
Two compact configurations for implementing transmission zeros in microstrip filters

This contribution presents compact structures for the implementation of transmission zeros using the zero shifting property. First, two open-loop resonators operating at different resonances are employed. Then, one of the open-loop resonators is substituted by a (/spl lambda//4) short-circuited transmission line, thus resulting into a more compact structure. Properties of these configurations are discussed, and two manufactured prototypes have been successfully tested. The results show the usefulness and validity of the new structures with high rejection capabilities.
Novel mechanism to taper the illumination of second higher-order mode microstrip leaky-wave antennas

In this contribution, it is proposed a novel mechanism to control the leakage rate of the second higher-order mode of the microstrip line. Using this original technique, one can synthesize a given illumination to reduce the sidelobes level of the MLWA. Leaky-mode results are presented to illustrate the theory, and a cosine tapered MLWA is designed to check the ability to reduce the sidelobes level below -20dB.
Green's functions for 2D periodic structures and applications to the analysis of waveguide components

In this paper different and efficient acceleration techniques for the evaluation of two-dimensional Green's functions with 1D and 2D periodicities are discussed. The proposed summation numerical methods are based on the appropiate extraction of different asymptotic terms in the spectral domain representation of the corresponding Green's functions. The paper provides insight into the different formulation choices, including numerical results that illustrate the advantages and drawbacks when the techniques are applied to a particular problem. This acceleration techniques allows the implementation of efficient integral equation techniques for the analysis of a wide variety of H-plane microwave passive components composed of conducting and dielectric posts and discontinuities.
Light field denoising: exploiting the redundancy of an epipolar sequence representation

Many current light field cameras are based on a single sensor with an overlaid micro lenses array, making them more susceptible to noise. This paper proposes a novel light field denoising solution to reduce the effect of Gaussian noise as this is the most commonly assumed type of noise at the acquisition process. The proposed solution takes a noisy light field image and converts it to a sequence of epipolar images, using as intermediate step a representation based on the ordered sequence of the sub-aperture images. The created epipolar sequence is finally processed by a powerful, generic video denoising engine. The performance of the proposed denoising solution has been assessed using the PSNR and SSIM metrics for a representative set of rendered 2D views. The obtained results for two representative datasets compare favorably against state-of-the-art light field denoising methods, both in terms of objective assessment and visual appearance.
Robust control design of multiple resonant controllers for sinusoidal tracking and harmonic rejection in Uninterruptible Power Supplies

This paper presents a robust control strategy for tracking sinusoidal reference signals with zero steady state error and harmonic compensation in Uninterruptible Power Supplies - UPS. Multiple resonant controllers are derived for DC-AC inverters when supplying energy to (uncertain) nonlinear loads to obtain a nice tradeoff between transient response and disturbance rejection regardless possible load variations. The controller parameters are determined by means of a convex optimization problem subject to a set of linear matrix inequalities (LMIs). Real time experiments demonstrate the potentials of the proposed approach for controlling UPS systems.
Design of an adaptive linearizing control for induction motors

A nonlinear adaptive state feedback linearizing control scheme for induction motors is designed in this paper. The control algorithm relies on the fourth-order nonlinear dynamic model of the motor and a variant of the least squares algorithm is employed for parameter estimation. The multivariable model reference adaptive scheme is used for tracking motor torque and flux references, considering the full state accessible. The closed-loop system stability is proved by Lyapunov like techniques.
Fusion of Calling Sites

The increasing popularity of Graphics Processing Units (GPUs), has brought renewed attention to old problems related to the Single Instruction, Multiple Data execution model. One of these problems is the reconvergence of divergent threads. A divergence happens at a conditional branch when different threads disagree on the path to follow upon reaching this split point. Divergences may impose a heavy burden on the performance of parallel programs. In this paper we propose a compiler level optimization to mitigate this performance loss. This optimization consists in merging function call sites located at different paths that sprout from the same branch. We show that our optimization adds negligible overhead on the compiler. It does not slowdown programs in which it is not applicable, and accelerates substantially those in which it is. As an example, we have been able to speed up the well known SPLASH Fast Fourier Transform benchmark by 11%.
Efficient Analysis tool of Inductive Passive Waveguide Components and Circuits using a Novel Spatial Domain Integral Equation Formulation

This paper presents an efficient software tool for the analysis of inductive waveguide components using a new spatial domain integral equation formulation. For the first time the Kummer and Ewald series acceleration techniques are combined into a single formulation for the efficient evaluation of the spatial domain parallel plate waveguide (PPW) Green's functions. Results are presented for complex microwave filters containing dielectric posts and rounded corners, showing the accuracy and usefulness of the proposed approach
Binary tree decomposition depth coding for 3D video applications

Recent advances in three dimensional display technologies and the growing efforts put in the production of three dimensional videos are intensely demanding for new, more efficient three dimensional content representation formats. One promising format is the so-called multiview plus depth format where multiple views of the observed scene are represented together with a per pixel depth map. Naturally, this format requires to efficiently code not only the video views but also the depth data. In this context, this paper proposes a novel depth map codec encoding the depth data by means of a binary tree triangular decomposition and reconstructing the depth map values by means of a triangle based planar approximation. For depth maps related to typical three dimensional video contents, the proposed depth map codec outperforms both the H.264/AVC standard with all intra coding modes enabled and the JPEG standard. In particular, for the same objective reconstruction quality, the proposed codec allows an average bitrate reduction of 60% and 90% regarding H.264/AVC Intra and JPEG coding, respectively.
Multistage Model for Distribution Expansion Planning with Distributed Generation—Part II: Numerical Results

This paper presents the computer simulation of the multistage model for distribution expansion planning with distributed generation, as described in Part I. The simulations deal with the planning of an electrical power distribution network in three stages, in five different situations: 1. each of the three stages planned independently; 2. multistage planning; 3. multistage planning with distributed generation; 4. multistage planning with distributed generation and constraints on investment; and 5. multistage planning with distributed generation considering three load levels. The influence of additional constraints is analyzed in terms of the computational effort required to find the optimum solution to the problem.
Robust PSC control design for sinusoidal tracking in uninterruptible power supplies

This paper proposes an alternative strategy to track sinusoidal reference signals with zero steady state error for uninterruptible power supplies - UPS. A robust proportional-sinusoidal-cosinusoidal (or in short PSC) controller is derived for sinusoidal voltage regulation subject to load variations. The controller parameters are determined by means of a convex optimization problem subject to a set of linear matrix inequalities (LMIs). Simulations and practical experiments demonstrate the potential of the proposed approach for controlling UPS systems.
A robust Luenberger-like observer for induction machines

A Luenberger-like observer is proposed to the state estimation of induction machines subject to rotor resistance variation and load disturbance. The observer gain is designed in order to minimize these effects on the state estimation performance in an H/spl infin/ sense, where the stability of the error dynamics is guaranteed. The proposed conditions are cast in terms of state-dependent linear matrix inequalities that are solved efficiently using standard software packages. Simulation results demonstrates the performance of the approach.
A simulation framework for flux estimation and vector control of induction machines

This paper presents a simulation environment for the conception and design of high performance controllers used in induction machines developed using Matlab and Simulink. The main idea is to provide designers and researchers with a simulation environment that simplifies the use of complex tools required in the vector control of induction motors. This environment consists of a complete set of individual blocks required for the real time implementation of vector control. Each one of these blocks is carefully designed to reproduce the actual behavior of the overall system. These blocks include the induction motor, flux estimators, parameter estimators, control algorithms, current PWM (CRPWM), antialiasing filter and frequency converter. To reflect the situation encountered in actual implementations, each block has its own integration increment and sample rate. This environment was used to simulate a direct vector control scheme to regulate the rotor speed of an induction motor. The use of this environment allowed the simulator to take the dynamic behavior of each individual block into consideration.
Self-oscillating circuit behavior evaluation through nonlinear dynamic systems analysis

The behavior of self-oscillating circuit used in electronic ballast depends of the limit cycle presence due to its operational principle as a nonlinear control system. In order to elucidate its behavior, it can be represented through block diagrams and modeled in a point of view of control system. It allows determine its behavior more accurately using the equations solution that describes the circuit and to show the presence of limit cycle in this system. The limit cycle can be obtained through the solution of the transition state matrix shown in this paper.
UAV and AUVs coordination for ocean exploration

In this paper, we develop a coordination mechanism for multiple Autonomous underwater vehicles (AUVs) and a single Unmanned aerial vehicle (UAV) cooperatively performing a ocean exploration mission. The UAV and the AUVs have limited sensor and communication constraints. The AUVs are deployed in the ocean and surface when their mission leg is completed. The UAV flies over the AUV, acquires the information procured by the AUV and generates a new mission plan to the AUV. The UAV has to meet all the AUVs and reach the base station within a prescribed sortie time. However, the AUVs may not complete the assigned task and may surface anywhere along the current mission leg. Hence, the UAV has to take the uncertainty of AUV surfacing into account while it generates the next mission plan to the AUV otherwise it may not satisfy the sortie time constraint. We develop a robust mechanism of determining the route for the UAV and path generation for the AUV such that the UAV always reaches the base station within the sortie time limit. Theoretical results are presented to show the robustness of the algorithms. Simulations are carried out to show how the mission is accomplished.
Multiple-Loop H-Infinity Control Design for Uninterruptible Power Supplies

This paper presents an innovative tuning strategy for the design of multiple-loop lag-lead compensators for uninterruptible power supplies (UPSs) based on the H-infinity robust control theory. Taking into account an average model of a UPS, the parameters of a double-loop controller are synthesized such that the upper bound on the two-norm of the input-to-output operator is minimized while guaranteeing local stability of the closed-loop system for all admissible load variations. The stabilization conditions are cast in terms of linear matrix inequalities that are solved via standard software packages. To improve regulation dynamics, a newer technique to compute the root-mean-square value of the output voltage is also proposed. Practical results considering a commercial UPS system demonstrate the effectiveness of the proposed approach as a tool for tuning multiloop controllers
Automatic and adaptive network-aware macroblock intra refresh for error-resilient H.264/AVC video coding

In this paper, an automatic and adaptive network-aware macroblock Intra coding refresh method is proposed. It adaptively selects the amount of gracefully forced Intra macroblocks and the amount of cyclic Intra refresh (CIR) macroblocks based on the actual network error conditions, in terms of packet loss rate, an the target encoding bit rate. With the proposed method, the error robustness of H.264/AVC bitstreams can be significantly increased by efficiently taking into account the actual rate-distortion impact of Intra coding macroblock mode decisions, while simultaneously guaranteeing that errors do not propagate endlessly by selecting an adequate amount of CIR macroblocks per frame according to the network packet loss rate and the encoding target bit rate.
Estimation of parameters of induction machines based on instantaneous impedance

This paper proposes a method for parameter estimation of three-phase induction machines based on the concept of instantaneous impedance and using only stator voltages and currents acquired during a no-load startup transient. Basically, the method estimates the parameters using an optimization algorithm which aims to reduce the error between estimated and measured instantaneous impedance. The algorithm assumes that the stator resistance is known and that part of the parameters are estimated from the steady state condition. Stator flux, electromagnetic torque, and rotor speed, required to determine the parameters, are also estimated from measurements. Practical experiments involving two machines of different power (5.5 and 30 kW) were used to validate the proposed algorithm. These experiments showed that the mechanical and electrical parameters can be estimated with acceptable errors in the case of the 5.5-kW machine. In contrast, in the case of the 30-kW machine, the estimation of the rotor parameters is influenced by factors not considered in the model, especially the skin effect. In this case, the use of an algorithm based on deceleration tests combined with the method based on the instantaneous impedance improved the results. Finally, the estimated parameters are compared with those declared by the manufacturer and the agreement between them is discussed.
Hamilton-Jacobi-Bellman Equation and Feedback Synthesis for Impulsive Control

There is an increasing number of applications whose trajectories are better modeled by discontinuous or impulsive trajectories. Thus, we explore optimality conditions for impulsive control system expressed in terms of an Hamilton-Jacobi-Bellman equation. We use a measure driven differential inclusion to model the impulsive behavior since it provides a formal framework in which the control space is complete. Additionally, we use the impulsive Euler solution and invariance results to derive feedback optimal control synthesis.
Second order necessary conditions of optimality for impulsive control systems

Second order conditions of optimality are presented for an impulsive control problem. The general approach defined in order to derive informative optimality conditions allows the consideration of abnormal problems without additional assumptions. After a detailed description of the considered impulsive optimal control problem, the first and second order necessary conditions of optimality are stated. Finally, an outline of the proof, which is based in the extremal principle, is presented with some conclusions.
Optimization model for expansion planning of distribution systems

This paper presents an optimization model for the problem of expansion planning of distribution electrical energy system: more specifically, for defining the route of feeders. The distribution system is represented by a graph in which the nodes represent demands and sources of energy; the branches represent the possible paths for supply. The model can be used to consider the insertion, removal and/or substitution of power lines of different gauge, with the objective of minimizing network installation and maintenance costs, subject to the limits to capacity of power lines and energy substations, and the maximum and minimum voltage limits specified by the problem. The validity and efficiency of the proposed model are demonstrated by means of two examples of medium-voltage distribution systems.
Divergence Analysis and Optimizations

The growing interest in GPU programming has brought renewed attention to the Single Instruction Multiple Data (SIMD) execution model. SIMD machines give application developers a tremendous computational power, however, the model also brings restrictions. In particular, processing elements (PEs) execute in lock-step, and may lose performance due to divergences caused by conditional branches. In face of divergences, some PEs execute, while others wait, this alternation ending when they reach a synchronization point. In this paper we introduce divergence analysis, a static analysis that determines which program variables will have the same values for every PE. This analysis is useful in three different ways: it improves the translation of SIMD code to non-SIMD CPUs, it helps developers to manually improve their SIMD applications, and it also guides the compiler in the optimization of SIMD programs. We demonstrate this last point by introducing branch fusion, a new compiler optimization that identifies, via a gene sequencing algorithm, chains of similarities between divergent program paths, and weaves these paths together as much as possible. Our implementation has been accepted in the Ocelot open-source CUDA compiler, and is publicly available. We have tested it on many industrial-strength GPU benchmarks, including Rodinia and the Nvidia's SDK. Our divergence analysis has a 34% false-positive rate, compared to the results of a dynamic profiler. Our automatic optimization adds a 3% speed-up onto parallel quick sort, a heavily optimized benchmark. Our manual optimizations extend this number to over 10%.
Multiple AUVS for coastal oceanography

This paper presents the recent developments of the project Multiple Autonomous Underwater Vehicles for Coastal Oceanography, of the University of Porto. The project envisages the development of a highly operational and low-cost system for scientific and environmental data collection in the Portuguese coastal waters. The project activities suggested the development of a generalized vehicle (GV) control architecture for multiple vehicles. Reconfigurability, reliability and operational effectiveness, are at the basis of this control architecture, which encompasses human intervention besides the cooperation among AUVs and other system devices. A simulation environment was developed in SHIFT, to support the design and testing of the GV control architecture. SHIFT is a new specification language for describing dynamic networks of hybrid automata, which constitute the most adequate formalism for this problem domain.
Distributed Monoview and Multiview Video Coding

Growing percentage of the world population now uses image and video coding technologies on a regular basis. These technologies are behind the success and quick deployment of services and products such as digital pictures, digital television, DVDs, and Internet video communications. Today's digital video coding paradigm represented by the ITU-T and MPEG standards mainly relies on a hybrid of block- based transform and interframe predictive coding approaches. In this coding framework, the encoder architecture has the task to exploit both the temporal and spatial redundancies present in the video sequence, which is a rather complex exercise. As a consequence, all standard video encoders have a much higher computational complexity than the decoder (typically five to ten times more complex), mainly due to the temporal correlation exploitation tools, notably the motion estimation process. This type of architecture is well-suited for applications where the video is encoded once and decoded many times, i.e., one-to-many topologies, such as broadcasting or video-on-demand, where the cost of the decoder is more critical than the cost of the encoder.
A New Method for PID Tuning Including Plants Without Ultimate Frequency

The classical relay feedback method for tuning proportional-integral-derivative (PID) controllers cannot be applied to plants whose Nyquist diagrams do not cross the negative real axis; these are customarily tuned based on the reaction curve experiment. In this brief, we propose a tuning method based on a modified relay feedback experiment. In this experiment, a transfer function of constant phase in an arbitrarily large range of frequencies is inserted in the loop. The proposed methodology thus unifies the Ziegler-Nichols-like tuning methods, by allowing PID tuning based on relay feedback for a class of plants without ultimate frequency.
Divergence Analysis with Affine Constraints

The rising popularity of graphics processing units is bringing renewed interest in code optimization techniques for SIMD processors. Many of these optimizations rely on divergence analyses, which classify variables as uniform, if they have the same value on every thread, or divergent, if they might not. This paper introduces a new kind of divergence analysis, that is able to represent variables as affine functions of thread identifiers. We have implemented this analysis in Ocelot, an open source compiler, and use it to analyze a suite of 177 CUDA kernels from well-known benchmarks. We can mark about one fourth of all program variables as affine functions of thread identifiers. In addition to the novel divergence analysis, we also introduce the notion of a divergence aware register allocator. This allocator uses information from our analysis to either rematerialize affine variables, or to move uniform variables to shared memory. As a testimony of its effectiveness, our divergence aware allocator produces GPU code that is 29.70% faster than the code produced by Ocelot's register allocator. Divergence analysis with affine constraints is publicly available in the Ocelot compiler since June/2012.