nils-herrmann/clean_scirepeval huggingface dataset:
A multi-vehicle testbed for multi-modal, decentralized sensing of the environment

This video presents experiments conducted on our multi-vehicle environmental testbed. The first experiment is the prioritized multi-sensing behavior, which uses a magnetic and light source for the robots to take sensor measurements. During the experiment robots create a Voronoi partitioning based on their current positions, then optimize the probability of detection map (POD) to determine a point in their own Voronoi partition that has the highest probability of obtaining good sensor readings from a magnetic or light source. When a point by each robot is identified, the robots navigate to that goal point while avoiding collisions with obstacles in the environment as well as with other robots. As the robots navigate to the goal point sensor measurements are taken. When each robot has reached its destination, sensor measurement information as well as position information is exchanged. This is then repeated for 30 iterations and the resulting magnetic and light intensity maps are shown. The second experiment conducted is the adaptive decentralized nonholonomic sensor network algorithm. Initially the robot at the right corner is exposed to the greatest concentration of light. Light measurements are taken using four precision light sensors mounted on the aluminum plate. Every robot is moving to their estimated center of mass of its respective Voronoi cell. As they are using a difference equation approximation of the adaptive law we notice back and forth motion. This is due to the centers of mass variation at every calculation time. In another top view, we see the actual distribution of the robots and their Voronoi partitions related to the light concentration. This is approximately a centroidal Voronoi tesselation based on the estimate distribution function which is illustrated as well. The light distribution is changed by switching the light source concentration. At this point the robots change their estimate parameter vectors in order to excite the adaptation law by increasing the difference between what they are measuring and what they are estimating. The robots then start moving towards the new light concentration. Finally, a top view of the robots with respect to the light distribution and the estimated density function are shown. This experiment verifies the behavior of the adaptive decentralized nonholonomic sensor network controller.
Direct Fourier reconstruction in computer tomography

Direct Fourier transform (FT) reconstruction of images in computerized tomography (CT) is not widely used because of the difficulty of precisely interpolating from polar to Cartesian samples. In this paper, an exact interpolation scheme is proposed which, in practice, can be approached with arbitrary accuracy using well-conditioned algorithms. Several features of the direct FT method are discussed. A method that allows angular band limiting of the data before processing -to avoid angular aliasing artifacts in the reconstructed image-is discussed and experimentally verified. The experimental results demonstrate the feasibility of direct FT reconstruction of CT data.
Maximum-likelihood parameter estimation of the harmonic, evanescent, and purely indeterministic components of discrete homogeneous random fields

This paper presents a maximum-likelihood solution to the general problem of fitting a parametric model to observations from a single realization of a two-dimensional (2-D) homogeneous random field with mixed spectral distribution. On the basis of a 2-D Wold-like decomposition, the field is represented as a sum of mutually orthogonal components of three types: purely indeterministic, harmonic, and evanescent. The suggested algorithm involves a two-stage procedure. In the first stage, we obtain a suboptimal initial estimate for the parameters of the spectral support of the evanescent and harmonic components. In the second stage, we refine these initial estimates by iterative maximization of the conditional likelihood of the observed data, which is expressed as a function of only the parameters of the spectral supports of the evanescent and harmonic components. The solution for the unknown spectral supports of the harmonic and evanescent components reduces the problem of solving for the other unknown parameters of the field to a linear least squares. The Cramer-Rao lower bound on the accuracy of jointly estimating the parameters of the different components is derived, and it is shown that the bounds on the purely indeterministic and deterministic components are decoupled. Numerical evaluation of the bounds provides some insight into the effects of various parameters on the achievable estimation accuracy. The performance of the maximum-likelihood algorithm is illustrated by Monte Carlo simulations and is compared with the Cramer-Rao bound.
The design and evaluation of an asynchronous microprocessor

AMULET1 is a fully asynchronous implementation of the ARM microprocessor which was designed at Manchester University between 1991 and 1993. First silicon arrived in April 1994 and was found to be functional, demonstrating that asynchronous design of complex circuits is feasible with present day CAD tools. This paper presents the motivation for the work, some of the design choices which were made, the problems which were encountered during the development of the design and the characteristics of the device itself. The future potential for asynchronous circuits is also discussed.<<ETX>>
Wavelet domain binary partition trees for image segmentation

When performing segmentation using tree based representations it is evident that contiguous objects are often dispersed widely across the tree making controlled selection difficult. This paper demonstrates robust segmentation by the generation of binary partition trees entirely within the wavelet domain. By using spatial frequency in conjunction with colour, a threshold free tree is produced which compels objects to reside inside single branches of the tree by constraining their merging development. Experimental results show the superior performance of the proposed algorithm compared to the existing colour based BPT algorithms.
Decision-directed segmentation for the restoration of images degraded by a class of space-variant blurs

A decision-directed filtering algorithm has been developed for model-based segmentation and restoration of images degraded by a class of space-variant blurs. It is assumed that the space-variant blur can be represented by a collection of L distinct point-spread functions, where L is a predetermined integer, so that at each pixel one of the functions will be more or less matched to the observed data. A multiple-model Kalman filtering procedure with online model detection based on maximum a posteriori probability decision was used to restore the image. The result of the decision process constitutes a model-based segmentation of the degraded image into regions of spatially invariant blurs. There are several applications of the proposed algorithm. Among these, automatic blur detection, i.e. segmentation of a partially blurred image into regions of blur and no-blur, is demonstrated as an example.<<ETX>>
An intrusion detection scheme for driverless vehicles based gyroscope sensor profiling

Vehicular ad-hoc networks of self-driving vehicles are potentially exposed to both internal and external attacks. The privacy and security of these networks is paramount for effective protection of communication systems from possible attacks. We propose an intelligent intrusion detection system in this paper that is based on Integrated Circuit Metrics (ICMetrics), which has significant defensive capability against unexpected attacks. The proposed security system shows good performance in identifying and blocking malicious vehicles in vehicular ad-hoc networks of driverless vehicles and semi driverless vehicles.
Weighted multi-playback buffer management for scalable video streaming

Video streaming in a best effort network, where bandwidth availability fluctuates over time, is one of the most challenging in the multimedia research field. Bandwidth fluctuation leads to a variation in the delay of the video flow and therefore degradation of the quality of experience (QOE). To tolerate variations in instantaneous bandwidth, the scalable video codec (SVC) an extension of the H.264/AVC was designed. This paper presents the weighted multi-playback buffer management system for scalable video streaming in a congested network. The approach intrinsically provides weighted protection to the more important video layers within a video stream. We compare the performance of our weighted scheme with a multi-playback buffer which gives equal protection to every video layer. The simulation results show that weighted multi-playback buffer management can improve the average Y-PSNR and the continuity of the SVC video stream.
AMULET1: a micropipelined ARM

A fully asynchronous implementation of the ARM microprocessor has been developed in order to investigate the potential of asynchronous logic for low-power applications. The work demonstrates the feasibility of complex asynchronous design and shows that the cost and performance characteristics are similar to clocked designs. AMULET1 is the first attempt at applying asynchronous techniques to a design of this complexity and as such there is much room for improvement. The authors introduce the design approach and organisation of the chip; they then cover the lessons learned from the first design and point towards future strategies for its enhancement and the likely benefits which will accrue from mature asynchronous technology.<<ETX>>
Heterogeneous sensor network for prioritized sensing

In this paper we relax the assumption of network connectivity within the sensor network and introduce mobile communication relays to the network. This addition converts the homogeneous sensor network to a heterogeneous one. Based on the communication geometry of both sensing and communication relay agents we derive communication constraints within the network that guarantee network connectivity. We then define a heterogeneous proximity graph that encodes the communication links that exist within the heterogeneous network. By specifying particular edge weights in the proximity graph, we provide a technique for biasing particular connections within the heterogeneous sensor network. Through a minimal spanning tree approach, we show how to minimize communication links within the network which allows for larger feasible motion sets of the sensing agents that guarantee the network remains connected. We also provide an algorithm that allows for adding communication links to the minimal spanning tree of the heterogeneous proximity graph to create a biconnected graph that is robust to a single node failure. We then combine a prioritized search algorithm and the communication constraints to provide a decentralized prioritized sensing control algorithm for a heterogeneous sensor network that maintains network connectivity.
An experimental comparison of the EM algorithm versus general optimization for combined image identification and restoration

The problem of learning the parameters needed for image restoration from the given noisy and blurred image has been addressed. The asymptotically optimal approach of finding the maximum-likelihood estimate of the parameters and then using this value of the parameter to construct the restoration filter has been taken. One way to do this is to iteratively solve the nonlinear problem of maximizing the a posteriori probability of the image given the blurred observations and also the unknown parameters. The ellipsoidal algorithm and the expectation-maximization (EM) algorithm have been used for this purpose. An experimental comparison of these two methods for parametrically restoring images when the parameters are not known a priori has been made.<<ETX>>
The wobble motor: design, fabrication and testing of an eccentric-motion electrostatic microactuator

The basic characteristics and advantages of microelectromechanical systems, machines constructed of small moving subelements which have characteristic dimensions in the range of about 0.5 to 500 mu m, are reviewed; design problems are considered; and particular attention is given to the wobble motor (WM) developed by S.C. Jacobsen et al. (1989) using electrodischarge machining (EDM). Fifteen EDM WMs have been constructed and utilized for experimental purposes. WM explorations have demonstrated that micro systems can be quite easily constructed by means other than etching silicon. Experiments aimed at generating simple preliminary data have been conducted, and results compare reasonably to analytical studies. Results reported include stall torque measurements, speed measurements, torque-speed measurements, and wear measurements.<<ETX>>
Functional connectivity analysis for thalassemia disease based on a graphical lasso model

Thalassemia is a congenital disorder of hemoglobin synthesis which can lead to thromboembolic events and stroke in the brain. In this work we propose to use a functional connectivity model to discriminate between control and diseased subjects. Our connectivity measure is based on functional magnetic resonance imaging, and hence common variations of the blood oxygenation level in spatially distant areas. Analyzing this connectivity could highlight abnormal neuronal activation and provide us with a descriptor (bio-marker) of the disease. To estimate the connectivity, we propose a robust learning scheme based on the graphical lasso model, whose hyperparameter is validated within a cross-validation scheme. To analyze model fit, we transfer the mean connectivity from the control group to the thalassemic patient group. Our null hypothesis is that the model learned on control subjects is perfectly adequate (in the maximum likelihood sense) to describe the patients. The results of the permutation test suggest that the some patients with thalassemia do not have the same connectivity structure as the control.
MODFET versus MESFET: the capacitance argument

In this paper a detailed charge control analysis is presented for a MESFET and a MODFET to show how the various capacitances associated with the region under the gate contact influence device performance. Where necessary, an exact description of electron confinement is included in the solution scheme by solving the effective mass Schrodinger equation for a single band and within a self-consistent framework. In the case of the MESFET, the analysis shows that the filling of donor impurity states, which are coincident in real space with the conducting channel, gives rise to a large parasitic capacitance which severely degrades both the intrinsic transconductance and cutoff frequency performance. In the case of the MODFET, the separation of the donor impurity level in real space from the conducting channel, and in energy from the Fermi-level, results in a low parasitic capacitance over the whole operating region of the device. Thus it is shown that the MODFET appears to be more suited to millimeter-wave applications, regardless of any electron transport effects.
Two-dimensional recursive filter design--A spectral factorization approach

This paper concerns development of an efficient method for the design of two-dimensional (2-D) recursive digital filters. The specific design problem addressed is that of obtaining half-plane recursive filters which satisfy prescribed frequency response characteristics. A novel design procedure is presented which incorporates a spectral factorization algorithm into a constrained, nonlinear optimization approach. A computational implementation of the design algorithm is described and its design capabilities demonstrated with several examples.
Edge-adaptive Kalman filtering for image restoration with ringing suppression

The authors extend the two-dimensional (2-D) linear space-invariant (LSI) reduced update Kalman filter (RUKF) to edge-adaptive space-invariant restoration of noisy and blurred images using a decision-directed approach. The edge-adaptive RUKF was motivated by the need to suppress the ringing artifacts caused by LSI processing. The authors show that ringing artifacts can be suppressed to a great extent by using multiple image models that provide a better match to local edge orientation. The maximum a posteriori probability decision procedure developed for model selection at each pixel can be used with other 2-D Kalman filtering algorithms as well.
An Ontology for the Quality of Experience framework

Agents need a formal representation of knowledge. This is modelled in an ontology. We present a survey of ontologies in the area of QoS management. From the survey we identified that improvements can be done in the Ontology of the Quality of Experience framework. We believe that with the extension full QoS Management capabilities can be then supported in the context of Quality of Experience. We focus in the appropriate QoS mechanism selection, network monitoring and QoS adaptation. With the additional concepts and actions the QoE ontology meets three key requirements for a QoS ontology: (i) decide which QoS mechanisms is better to fits the user needs; (ii) perform QoS monitoring and detection of SLA violations; and (iii) carry out QoS adaptation. Two experimental scenarios are currently being conducted. In scenario 1 the original ontology is used whilst for scenario 2 the extended version is employed. An initial comparative analysis is performed.
Occam: an asynchronous hardware description language?

Recently, there has been a resurgence of interest in asynchronous hardware due to the potential of asynchronous logic for higher performance, power efficiency and immunity from clock-related timing problems. This activity has revealed the current lack of suitable languages and notations for the description of asynchronous hardware systems anti has fueled an intense research effort in this area. Communicating sequential processes (CSP) in particular have attracted the interest of many researchers as a potential means for the modelling of asynchronous designs. Contributing to this effort, this paper examines whether Occam, a CSP-based language, may provide a solution to this endeavour.
A video rate architecture for a fully recursive two-dimensional filter

The improvements in VLSI technology over the past few years have made high-speed digital filtering commonplace. This paper presents a video rate architecture for a two-dimensional (2-D) filter which can be implemented using wafer scale integration. The filter is made up of 1-D row operators. These row operators in turn are realized as a block-processed system composed of three basic cells: multipliers, adders, and registers. The row operators are combined recursively to form a 2-D fully recursive filter. A practical application of image enhancement with this filter is presented.
Adaptive restoration of textured images with mixed spectra

We consider the adaptive restoration of inhomogeneous textured images, where the individual regions are modeled using a Wold-like decomposition. A generalized Wiener filter is developed to accommodate mixed spectra, and unsupervised restoration is achieved by using the expectation-maximization (EM) algorithm to estimate the degradation parameters. This algorithm yields superior results when compared with supervised Wiener filtering using autoregressive (AR) image models.
Bias-dependent linear, scalable millimeter-wave FET model

This paper describes a measurement-based, bias-dependent, linear equivalent circuit FET/HEMT model that is accurate to at least 100 GHz and scalable up to 12 parallel gate fingers and from 100-1000 /spl mu/m total gate width. The equivalent circuit element values are determined at each bias point in V/sub gs/-V/sub ds/ space.
Extending static models by using time series to identify the dynamical behavior

We use a simple, static model of an amplifier and augment the model by adding a nonlinear dynamical part in which the dynamics are identified using principles of time series analysis. The static part of the model is a polynomial nonlinearity in the input voltage, and is implemented using a built-in system amplifier model in ADS. The dynamic nonlinear part of the model is implemented using an artificial neural network. This new model is fast to simulate and extends the simple, single frequency system amplifier model to cover a wide bandwidth, maintaining good large-signal predictions.
Reconstruction error in transform/subband coding

We use the linear gain-plus-additive noise model for the class of PDF-optimized scalar quantizers to develop a frequency domain analysis of transform/subband coding systems. We derive a novel and explicit expression for the PSD of the reconstruction error, and show that this PSD has signal, alias and noise components. We employ this expression to compare different block transforms and subband filters with the rate-distortion optimal source coder, for a 1-D Gauss-Markov source. This paper quantifies, via the 'out-of-band' noise energy in the reconstruction error, the performance gap between DCT-based coders and coders that use subband/wavelet filters.
New techniques for non-linear behavioral modeling of microwave/RF ICs from simulation and nonlinear microwave measurements

This paper compares and contrasts recent nonlinear behavioral modeling techniques designed for microwave and RFIC application which arise in radio and communication systems, and in the design of broad-band nonlinear components used for microwave instrumentation. These techniques include dynamic neural networks and nonlinear time series models in the time-domain, nonlinear describing functions in the frequency domain, and envelope-based methods in mixed time and frequency domains. Approaches to generating these models from both simulation and nonlinear microwave measurements are reviewed.
An analysis of the effective position of the two-dimensional electron gas in the channel of MODFET epitaxial layer structures

The charge control behavior of a range of heterostructure material systems typical of MODFETs has been investigated using a numerical model, and the "effective position of the two-dimensional electron gas (2-DEG) in the channel", /spl Delta/d, has been analyzed. We have shown that the parameter /spl Delta/d is well-defined for double-heterojunction structures, though with values very different from the often quoted figure of 80 /spl Aring/ , and that for AlGaAs/GaAs single heterojunctions, /spl Delta/d is strongly gate voltage dependent with values always larger than 80 /spl Aring/.
2-D digital filter stability in the presence of second kind nonessential singularities

We present two new conditions for the stability of 2-D digital filters in the presence of nonessential singularities of the second kind. The first is a necessary condition expressed in terms of tangents to the algebraic curve at a zero of the denominator polynomial on the distinguished boundary of the unit polydisk. This necessary condition is shown to be preserved under parameter quantization in some cases. The second condition we present is sufficient for stability, and is considerably weaker than that imposed by Goodman.
Entropy-constrained SBPVQ for image coding

An entropy-constrained algorithm for a type of finite-state vector quantizer called sliding-block predictive vector quantization (SBPVQ) is presented. This coding algorithm searches small codebooks to achieve high performance at low coding rates. Results from training the coder on a set of monochrome images and then testing it on an image outside the training set are presented. Also, three parallel entropy-constrained SBPVQ coders are used to code 24-b/pixel color images. A total rate of less than 0.5 b/pixel is achieved with good performance by using this vector predictor variant.<<ETX>>