nils-herrmann/clean_scirepeval huggingface dataset:
On the imperfection of channel estimation, relay's forwarding policy and destination's knowledge of signal presence

In this paper, we analyze two different decode-and-forward (DF) relay-assisted communication system models, which display different levels of practicality and represent large classes of DF systems in the literature. We spell out delineating aspects of the two models and rigorously show inequality among their symbol error probabilities (SEPs). Both system models assume imperfect channel side information at receivers and maximum ratio combining (MRC) at the destination node.
Synthetic thinned aperture radiometer for Mars exploration

One of NASA's long term goals is determining if subsurface water on Mars exists and, if water is found, whether it could be accessed by future manned space missions. A shorted-annular-ring reduced-surface-wave (SAR-RSW) design is presented under the realistic constraints already mentioned. This design is compared with a circular patch and the performance differences are discussed. Next, results of a STAR design are discussed as well as a brief overview of antenna performance under deformation conditions.
Optimizing the energy efficient VM placement by IEFWA and hybrid IEFWA/BBO algorithms

In this paper, we present a problem-specific, information-based enhanced fireworks algorithm (IEFWA) and a hybrid of the IEFWA and the Biogeography-based optimization (BBO) algorithm. These new algorithms are tested for virtual machine (VM) placement problem with the objective of minimizing the energy consumption in datacenters, which is an integer space optimization problem. The EFWA algorithm is a relatively recent development in swarm intelligence (SI), and is based on explosion amplitude operator that operates in the continuous space. The 'round' function is used to convert the explosion amplitude value to the nearest integer to operate in integer space. In our IEFWA algorithm design, some domain knowledge of VM placement problem was used. During the spark generation in IEFWA, the explosion amplitude is added to the information-based selected components of the fireworks instead of adding the explosion amplitude into instead of all components. The hybrid IEFWA/BBO algorithm probabilistically chooses the explosion amplitude operator of IEFWA algorithm or the migration operator of BBO algorithm with a user determined probability for the exploitation of good candidate solutions. The VM placement problem is NP-hard, and existing results demonstrate that evolutionary algorithms (EAs) can be useful choice for good-quality solution with reasonable computing resources. We experimentally compare the performance of BBO, EFWA, IEFWA, hybrid IEFWA/BBO and the first fit decreasing (FFD) algorithms. Simulation results demonstrate the two key findings of this study. First, IEFWA algorithm consumes less CPU time as compared to the EFWA algorithm. Second, IEFWA and hybrid IEFWA/BBO algorithms outperform EFWA and BBO algorithms in terms of average energy consumed in datacenters.
Acceleration of TM cylinder EFIE with CUDA

In this paper, we have shown that exploitation of the GPU's massively parallel architecture can dramatically increase the speed of MoM calculations. While the code can certainly be improved, matrix fill speed-up factors are already commonly found to be between 150X–260X. The conjugate gradient solver stands to be improved at this writing but still results in performance increases of 1.25X–20X. Continued development of MoM codes with GPU acceleration will undoubtedly bring about a new era of computational electromagnetics.
Design and nonlinear servo control of MEMS mirrors and their performance in a large port-count optical switch

In this paper, we demonstrate full closed-loop control of electrostatically actuated double-gimbaled MEMS mirrors and use them in an optical cross-connect. We show switching times of less than 10 ms and optical power stability of better than 0.2 dB. The mirrors, made from 10-/spl mu/m-thick single-crystal silicon and with a radius of 400-450 /spl mu/m, are able to tilt to 8/spl deg/ corresponding to 80% of touchdown angle. This is achieved using a nonlinear closed-loop control algorithm, which also results in a maximum actuation voltage of 85 V, and a pointing accuracy of less than 150 /spl mu/rad. This paper will describe the MEMS mirror and actuator design, modeling, servo design, and measurement results.
Maximizing energy efficiency over imperfectly known fading channel gains

In this paper, we study the issue of selecting the transmission power (energy per symbol) and power allocation between pilot and data symbols to maximize the energy efficiency (EE). We consider the system that has a slow-fading channel and employs a minimum mean square error (MMSE)-based channel estimation scheme for a pilot symbol-assisted modulation. We derive a closed-form expression for a lower bound on the channel capacity in the presence of channel estimation error, and use this lower bound to derive the energy efficiency. We then discuss optimizing transmission power and also power allocation between pilot and data symbols for maximizing the energy efficiency. At the end we present a very simple method for finding a suboptimal solution for transmission power and also the power allocation between pilot and data symbols that result in a performance very close to the optimal solution.
Regularized discriminant analysis for transformation-invariant object recognition

We present a novel method for incorporating prior knowledge about invariances in object recognition for discriminant analysis. In contrast to conventional isotropic regularization approaches, our approach shows how to incorporate known transformation invariances in the geometry of the problem to better regularize discriminant analysis. In particular, we show how to incorporate group invariance and tangent vector structure with multiple parameters and derive special covariance terms that are used to regularize discriminant analysis. We apply this method to Fisher discriminant analysis, as well as its kernelized version, and show that this invariant regularization improves recognition performance over conventional regularization techniques.
Joint user selection and quantized power control schemes for uplink cognitive MIMO systems

In this paper, we investigate interference-aware joint secondary user (SU) selection/scheduling and quantized power control (JSUS-QPC) schemes for the uplink communication in the cognitive MIMO system. The main objective of the JSUS-QPC is to maximize the sum-rate capacity of the cognitive MIMO uplink communication system under the constraint that the interference to the primary users (PU) is below a specified level. The computational complexity of finding an optimal JSUS-QPC scheme by exhaustive search grows exponentially with the number of users and power levels. In this paper, we present two low-complexity algorithms for JSUS-QPC in the cognitive MIMO system. We also examine the effect of different system parameters (e.g., interference threshold level, the number of primary users, the number of secondary users, the number of quantized power levels etc.) on the performance of the proposed algorithms. The proposed algorithms have low computational complexity, and their effectiveness is verified through simulation results.
Complexity Analysis of Optimal Stationary Call Admission Policy and Fixed Set Partitioning Policy for OVSF-CDMA Cellular Systems

In this paper, we study a problem of making call admission decisions for dynamically arriving call requests in multi-rate multi-class CDMA cellular systems. We limit our scope to systems that employ orthogonal variable spreading factor (OVSF) codes for providing different channels for different users -e.g., wideband CDMA. We study the optimal stationary randomized call admission control policy and the optimal fixed-set-partition policy. We analyze computational complexities associated with these policies. We discuss both 1) offline computation for optimally designing these policies and 2) online execution of these polices.
Estimation of Distribution algorithm for sensor selection problems

In this paper, we apply Estimation-of-Distribution Algorithms (EDAs) to the problem of selecting a set of k sensors from m sensors for the purpose of parameter estimation. Unlike other evolutionary algorithms, in EDAs a new population of individuals in each iteration is generated without crossover and mutation operators; instead, a new population is generated based on a probability distribution, which is estimated form the best selected individuals of previous iteration. Our results indicate that EDA is a good candidate for solving the sensor selection problems.
Modular low-cost humanoid platform for disaster response

Developing a reliable humanoid robot that operates in uncharted real-world environments is a huge challenge for both hardware and software. Commensurate with the technology hurdles, the amount of time and money required can also be prohibitive barriers. This paper describes Team THOR's approach to overcoming such barriers for the 2013 DARPA Robotics Challenge (DRC) Trials. We focused on forming modular components - in both hardware and software - to allow for efficient and cost effective parallel development. The robotic hardware consists of standardized and general purpose actuators and structural components. These allowed us to successfully build the robot from scratch in a very short development period, modify configurations easily and perform quick field repair. Our modular software framework consists of a hybrid locomotion controller, a hierarchical arm controller and a platform-independent operator interface. These modules helped us to keep up with hardware changes easily and to have multiple control options to suit various situations. We validated our approach at the DRC Trials where we fared very well against robots many times more expensive.
On the throughput gain for rapid dynamic symbol duration adaptation within discrete duration sets

In this paper, we quantitatively analyze the gain in error-constrained bit throughput achieved by the rapid symbol duration adaptation. We focus on the adaptive system that can choose for each symbol a symbol duration only from a discrete set of symbol durations. The results show that the rapid adaptation with a discrete duration set can often achieve a throughput gain similar to that achieved with a continuous set of durations. The results are especially applicable to spreading gain adaptation in CDMA systems.
Complex permittivity and permeability extraction for multilayered samples using S-parameter waveguide measurements

In this paper, a novel technique is presented for accurately extracting the complex constitutive parameters (/spl epsiv//spl circ/, /spl mu//spl circ/) for individual layers of a multilayer sample using S-parameter waveguide measurements. The technique is based on a modified sequential quadratic programming algorithm, which utilizes a large number of initial guess points, thereby alleviating the possibility of local minima trapping. The algorithm was found to be significantly faster and more accurate than traditional global optimization methods such as the genetic algorithm. Computer-generated S-parameter data sets were initially used to establish the achievable accuracy of the algorithm for one-, two-, and three-layer cases. Sensitivity of the S-parameters to changes in the constitutive parameters and layer thicknesses was also investigated. Two-port S-parameter measurements (8.2-10 GHz) were conducted on three material samples in single and multilayer arrangements. The algorithm accurately extracted the complex constitutive parameters for each layer. These values were then compared with values extracted using a modified short-circuit line (SCL) method (single-layer cases only). S-parameters were also generated using the extracted values and compared with the measured data. In all cases, results were found to be in good overall agreement with both the SCL method values and the measured data.
Dual-layer WDM routing for wafer-scale packaging of photonically-interconnected computing systems

As an enabling building block to support high bandwidth optical interconnections among supercomputing processing elements, we present the first monolithically integrated chip-to-chip wavelength-division multiplexing (WDM) optical proximity coupler with 4-channel × 200GHz-spacing multiplexer/demultiplexer (MUX/DEMUX) functionality utilizing an echelle grating, micro reflective mirrors, and waveguide mode transformers on single silicon-on-insulator (SOI) substrate. This new photonic integrated circuits can be utilized to provide a data-rate independent optical interface that surpasses the throughput bottleneck of current electrical data paths.
Statistical modeling of the indoor radio propagation channel. II

For pt.I see ibid. (1992). Statistical analyses of indoor radio propagation data are reported. The database includes 12000 impulse response profiles of the channel collected at two office buildings. Statistical properties of the number of multipath components for each profile are described. A Poisson fit to the arrival time data proved to be unsatisfactory. A modified Poisson model showed good fit to the data. Amplitudes were found to be lognormally distributed over both local and global areas, with a log-mean value that decreases almost linearly with increasing the excess-delay. There is a high degree of spatial correlations on path variables which has been quantified for the amplitude sequence.<<ETX>>
Recursive least squares ladder forms for fast parameter tracking

A discussion of some of the most interesting recent developments in the area of real time (or "on-line") algorithm for estimation and parameter tracking using ladder canonical forms for AR and ARMA modeling is presented. Besides their interesting connections to stability and scattering theory, partial correlations and matrix square-roots, they also seem to have well behaved numerical properties. Ladder forms seem to be a "natural" form for Wiener (or whitening) filters due to the fact that the optimal whitening filter is time-varying (even for stationary processes), except for ladder form coefficients, which are constants "switched on" at the appropriate time. This leads to the fact that this parametrization is very well suited for tracking rapidly varying sources. Compared to gradient type techniques, our exact least-squares ladder recursions have only a slightly increased number of operations. This increase is due to the recursively computed likelihood variables which act as optimal gains on the data, enabling the ladder filter to lock rapidly on to a transient. Several ladder form applications will be briefly discussed, such as speech modeling, "zero startup" equalisers, and "noise cancelling and inversion". Computer simulations will be presented at the conference
Closed-loop architecture and protocols for rapid dynamic spreading gain adaptation in CDMA networks

We present a closed-loop architecture and protocols for rapid dynamic spreading gain adaptation and fast feedback between a transmitter and a receiver communicating with each other in CDMA networks. These protocols and architecture do not require the transfer of an explicit control message indicating the change of CDMA spreading gain from transmitter to receiver. Also, with these protocols, the transmitter can change the spreading gain symbol-by-symbol as opposed to frame-by-frame, and feedback information (e.g., the fast-varying channel condition) can be exchanged almost as frequently as the symbol rate; thus, faster adaptation to the time-varying channel conditions of wireless networks and/or the rate variation of traffic is possible than with the existing frame-by-frame approach.
Efficient multiple personal wireless hub assignment in next generation healthcare facilities

Low power wireless sensors, personal wireless hub (PWH) and receivers can reduce the workload of the paramedic staff in a hospital. In this paper, we use multiple PWHs to transfer sensor data to the main central controller, which helps the wireless sensor devices. A well designed multiple PWH assignment and power control scheme can reduce the electromagnetic and in-band interference induced to the other medical devices in the hospital. We propose a framework and low complexity algorithm for interference aware joint power control and multiple PWH assignment (IAJPCPA) in a hospital building with cognitive radio capability. The proposed IAJPCPA is a non-convex mixed integer non-linear optimization problem (NC-MINLP) which is generally NP-hard. We present an efficient PWH assignment and power control scheme for IAJPCPA. We also propose an upper bound on the IAJPCPA that converts the non-convex problem into a convex optimization problem. We examine the effect of different system parameters.
Route-metric-based dynamic routing and wavelength assignment for multifiber WDM networks

We present three dynamic routing and wavelength assignment (RWA) algorithms that are intended for multifiber WDM networks without wavelength converters. For networks with a large number of wavelengths per fiber and/or a large number of fibers per link, our algorithms exhibit particularly good performance, and one of them significantly outperforms other existing algorithms. In response to a connection request, our algorithms first select a physical route among a set of predetermined routes on the basis of some per-route variables. The algorithms then select a wavelength to be used with the selected route. This paper illustrates how we can rethink the criteria for route selection in multifiber networks. We also suggest a method of selecting the set of predetermined routes to balance the traffic load. Our simulation results illustrate that this method exhibits significantly lower blocking probability than the traditional shortest-route-based method. Thus, this paper also illustrates that the choice of predetermined routes can significantly affect the blocking probability of an RWA.
A protocol for rapid symbol duration adaptation and feedback in CDMA networks

We present a closed-loop architecture and protocols for rapid dynamic spreading gain adaptation and fast feedback between a transmitter and a receiver communicating with each other in CDMA networks. This protocol does not require the transfer of an explicit control message indicating the change of CDMA spreading gain from transmitter to receiver. Also, according to this protocol, the transmitter can change the spreading gain symbol-by-symbol as opposed to frame-by-frame, and feedback information (e.g., the fast-varying channel condition) can be exchanged almost as frequently as the symbol rate; thus, faster adaptation to the time-varying channel conditions of wireless networks, and/or the rate variation of traffic, is possible than with the existing frame-by-frame approach.
Gains in Error-Constrained Data Throughput from Extremely Fast Adaptation of Symbol Durations over Multi-Path Fading Channels: Coded and Uncoded Systems

This paper quantitatively analyzes the gain in error-constrained data throughput due to the extremely rapid (symbol-by-symbol) adaptation of symbol durations. The analysis includes systems equipped with maximal ratio combining. For uncoded communication systems, we provide numerical results obtained from the analysis of theoretical throughput gains. For some coded communication systems with commonly used error correction codes, we provide numerical throughput gain results obtained from simulations.
Max-min optimization of transmission powers in the two-way cognitive radio network assisted by orthogonally signaling relays

We study a cognitive radio network in which two sources communicate with each other through multiple relays operating in non-overlapping frequency bands in the radio spectrum. We consider the problem of optimizing the transmission powers of the sources and relays so that the minimum of the two sources' transmission capacities is maximized. Thanks to the non-overlapping nature of the relays' signals, the problem can be represented as a constrained optimization over two variables, but that formulation still results in a non-convex optimization. We show that an optimal solution occurs on the upper boundary of the feasible set. We further show that the objective function is unimodal on the boundary. We suggests a simple method of optimization that utilizes these properties.
A hybrid walk controller for resource-constrained humanoid robots

Zero moment point (ZMP) preview controller is a widely adopted method for bipedal locomotion. However, for robots which are resource constrained or working in dynamic environments, simple reactive walk controllers are still favored as ZMP preview controllers have more control latency and are computationally more demanding. In this work, we present a hybrid walk controller that dynamically switches between a reactive walk controller based on the analytic solution of the linear inverted pendulum model and a ZMP preview controller that uses future foothold positions for more demanding tasks. The boundary conditions of center of mass (COM) state are considered in the optimization process of the ZMP preview controller to ensure a seamless transition between two controllers. We demonstrate the controller in a physically realistic simulations, as well as experimentally on a small humanoid robot platform.
Artificial invariant subspace with potential functions for humanoid robot balancing

Existing trajectory planning based locomotion algorithms lack the analytic tools to fully comprehend energy based movements that would allow for full stability and mobility. Such drawbacks make humanoid robots' locomotion sensitive to external disturbances and compromise robots' agility in unstructured environment. In this work, we specifically focus on the push recovery problem for humanoid robots. We propose an approach to design a nonlinear controller that is robust to external disturbances. It allows the state of the rigid body dynamics to asymptotically converge to the subspace that meet the criteria of balancing, based on the properties of artificial invariant subspace and potential functions. Our algorithm is completely adaptive in real time without requiring trajectory planning in advance. We demonstrate the robustness of the proposed algorithm base on extensive push recovery experiments on the DARWIN-OP robot platform on flat terrains.
Team THOR's adaptive autonomy for disaster response humanoids

This paper describes Team THOR's approach to sliding autonomy in manipulation and full body control of a disaster response robot for the 2015 DARPA Robotics Challenge (DRC) Finals. Under the duress of unpredictable bandwidth constraints, autonomous behaviors become critical for reducing response time and dealing with dynamic disturbances. However, the nature of disaster response presents situations where fine grained and intricate teleoperation remain the only safe method of operation. We present sets of algorithms that gracefully switch among high level autonomous behaviors and low levels of teleoperated control. Manipulation algorithms interact in a hierarchical fashion within a state machine, transitioning between states autonomously or through human intervention. Similarly, the balancing controller scales from low degree of freedom walking to full body motions. To validate our methods, we show results from attempts at the DRC Finals and in our preparation for it.