nils-herrmann/clean_scirepeval huggingface dataset:
Hierarchical Face Clustering using SIFT Image Features

In this paper an algorithm to cluster face images found in video sequences is proposed. A novel method for creating a dissimilarity matrix using SIFT image features is introduced. This dissimilarity matrix is used as an input in a hierarchical average linkage clustering algorithm, which yields the clustering result. Three well known clustering validity measures are provided to asses the quality of the resulting clustering, namely the F measure, the overall entropy (OE) and the Gamma statistic. The final result is found to be quite robust to significant scale, pose and illumination variations, encountered in facial images
Evaluation of tracking reliability metrics based on information theory and normalized correlation

The efficiency of three tracking reliability metrics based on information theory and normalized correlation is examined in this paper. The two information theory tools used for the metrics construction are the mutual information and the Kullback-Leibler distance. The metrics are applicable to any feature-based tracking scheme. In the context of this work, they are applied for comparison purposes on an object tracking scheme using multiple feature point correspondences. Experimental results have shown that the information theory based metrics perform better than the normalized correlation one.
Movement recognition exploiting multi-view information

In this paper a novel view-invariant movement recognition method is presented. A multi-camera setup is used to capture the movement from different observation angles. Identification of the position of each camera with respect to the subject's body is achieved by a procedure based on morphological operations and the proportions of the human body. Binary body masks from frames of all cameras, consistently arranged through the previous procedure, are concatenated to produce the so-called multi-view binary mask. These masks are rescaled and vectorized to create feature vectors in the input space. Fuzzy vector quantization is performed to associate input feature vectors with movement representations and linear discriminant analysis is used to map movements in a low dimensionality discriminant feature space. Experimental results show that the method can achieve very satisfactory recognition rates.
Adaptive subsampling of color images

Conventional coding of digital color images is done in a luminance-chrominance domain, and the chrominance components are subsampled in a fixed ratio with respect to the luminance. We propose an adaptive method of subsampling the chrominance components that improves the quality vs. sample rate trade-off. In applications such as compositing color graphics images, the advantage of using the adaptive method as against the conventional method is demonstrated.<<ETX>>
The construction and evaluation of behavioral models for microwave devices based on time-domain large-signal measurements

We present a new procedure for creating nonlinear behavioral models of microwave devices, based on techniques developed in time-series analysis. We illustrate this procedure by creating a model for a HEMT device. Large-signal time-domain microwave measurements are used to generate the time-series data of the terminal currents and voltages. The dynamical model of the HEMT is defined by fitting multivariate polynomials to the terminal voltages and their higher-order derivatives. The model accurately predicts DC, small-signal, and large-signal behavior.
QoS arbitration for improving the QoE in multimedia transmission

This contribution presents a Quality of Experience (QoE) framework. It evaluates QoE using QoS metrics, network feedback, and dynamic user requirements. and proposes a definition for QoE. A model for experimenting within the QoE framework is presented. It is believed that a better QoE can be achieved when the QoS and its interaction with the network and application layer, is considered as a whole rather than a single entity.
Fast recursive estimation of the parameters of a space-varying autoregressive image model

The identification of two-dimensional (2-D) autoregressive (AR) image models has been previously shown to be an integral part of image estimation. Furthermore, because of the nonhomogeneous nature of images, much better results are obtained with space varying models. To this effect, the development of a fast recursive method is now proposed for estimating the parameters of a two-dimensional AR image model, at each pixel, based on a finite memory. This fast method can be coupled to a space-variant Kalman filter for on-line adaptive estimation or can be used to estimate 2-D spectra for space-variant fields.
2-D direct form, recursive filter design with magnitude and phase specifications

This paper presents an extension of the spectral factorization based optimization method to approximate both magnitude and phase specifications for 2-D, recursive, direct-form, nonsymmetric half-plane filters. Examples are presented of filters approximating ideal linear phase lowpass and fan filters as well as causal (in the nonsymmetric half-plane sense) Wiener filters which have non-linear phase characteristics.
IMS Student Design Competitions

The student design competitions held at the IEEE International Microwave Symposium (IMS) each year have been one of the most successful innovations of the IEEE Microwave Theory and Techniques Society (MTT-S) in the past ten years. In just a few years, this contest has grown from a single competition (the High-Efficiency Power Amplifier Design Competition in 2005) to over ten distinct competitions in 2012, involving the participation of 17 MTT Technical Committees and hundreds of students from all over the globe. The competitions are unique events that challenge the creativity, competitive spirit, and enthusiasm of the students. They offer tough problems that are designed to exercise the creativity of the students. The enthusiasm of the participants is evident and tangible. This is an encouraging sign of the future health of the Society and of the radio frequency (RF) and microwave industry in general.
Radon transformation of time-frequency distributions for analysis of multicomponent signals

The Radon transform of a time-frequency distribution produces local areas of signal concentration that facilitate interpretation of multicomponent signals. The Radon transform can be efficiently implemented with dechirping in the time domains; however, only half of the possible projections through the time-frequency plane can be realized because of aliasing. It is shown that the frequency dual to dechirping exists, so that all of the time-frequency plane projections can be calculated efficiently. Some Radon transforms of Wigner distributions are demonstrated.<<ETX>>
Calibration of industrial robots by magnifying errors on a distant plane

This paper describes a robot calibration approach called the virtual closed kinematic chain (ViCKi) method. Traditionally, calibration requires the measurement of the position and orientation of the end effector, and measurement resolution limits the accuracy of the robot model. In ViCKi, we attach a laser to the end effector to create a virtual 7th link. The laser spot produced on a distant plane, the end of this virtual link, magnifies small changes at the end effector, resulting in a high resolution error measurement of the end effector. The accuracy of the robot after using the proposed calibration procedure is measured by aiming at an arbitrary fixed point and measuring the mean and standard deviation of the radius of spread of the projected points. The mean and standard deviation of the radius of spread were improved from 5.64 mm and 1.89 mm to 1.05 mm and 0.587 mm respectively. It is also shown in simulation that the method can be automated by a feedback system that can be implemented in real-time.
Multiple Description Coding and Practical Network Coding for Video Multicast

Multiple description codes have been shown to facilitate heterogeneous multicast using routing with replication. We develop the combination of practical network coding and multiple description coding (introduced by Chou ), but here for video multicast in lossless networks where users get video according to their available resources. We also show that network coding enables the server to provide quality of service that is centrally controlled. The lack of the need to maintain multiple trees (as in routing) helps in ease of construction of the multicast delivery system. The simulation results show that using practical network coding provides significant control over the rate allocation for the resources.
A behavioral modeling approach to nonlinear model-order reduction for RF/microwave ICs and systems

This paper considers an approach to nonlinear model-order reduction for RF/microwave integrated circuits (ICs) from the perspective of "black-box" behavioral modeling. We present a systematic methodology for creating behavioral models using techniques developed from concepts in system identification, nonlinear dynamics, computational geometry, and information theory. Highly complex subsystems can be represented by relatively straightforward input-output relationships involving the observed and identified dynamical variables. Model order is thus significantly reduced compared with the device-level representation. We illustrate the technique by creating a cascadeable transportable model of a wide-band microwave IC amplifier that accurately predicts the dc, large-signal, harmonic and intermodulation distortion, and small-signal (S-parameter) behavior.
Design and implementation of two-dimensional fully recursive digital filters

The two-dimensional (2-D) fully recursive filter was recently introduced by the authors as a more general 2-D recursive filter. In this paper, we present a design algorithm and an implementation method for this class of filters. The design algorithm incorporates a novel stability test. We discuss the boundary condition problem which occurs in the implementation of fully recursive filters. We propose a direct fully recursive implementation method which has been verified in software. Several design examples and comparisons are provided.
Fabrication of micro-structures using non-planar lithography (NPL)

The authors present specific nonplanar lithographic (NPL) techniques for use in fabricating both monolithic micromachines and microcomponents for use in larger systems. The emphasis is on the use of numerically controlled E-beam-based lithography, with the resist exposed over nonplanar surfaces. Previously, nonplanar, optical-mask-based approaches have been used to fabricate devices such as wobble motor rotors, but with less success than the NPL techniques due to depth-of-field problems. The specific focus is on etching cylindrically shaped metal structures which are either (1) homogeneous or (2) layered by successive deposition, masking, and etching. Structures on the order of 80 to 500 microns in diameter have been constructed of either solid metals or sputtered thin metallic layers on quartz shafts. A number of either deep or shallow patterns have been fabricated on and through the structures, with promising results. Examples include helices, longitudinal lines, holes, notches, flexures, barbs, alphanumeric characters, and electrostatic field emitting patterns for use in wobble motors. Efforts are now proceeding toward generating complete systems, including transducers and actuators for industrial and medical applications.<<ETX>>
Some experimental results in adaptive prediction DPCM coding of images

In this paper we present results from our work on adaptive prediction dpcm for grey level images using the doubly stochastic Gaussian image model. This model consists of a lower level level 2-D Markov chain which takes on L different values and correspondingly L different sets of predictor parameters for an upper level conditionally Gaussian field. A simple gradient based algorithm which uses fuzzy decision theory is used to identify the lower level chain from observations on the upper level field, i.e. the actual image. The upper level field is encoded by 2-D DPCM using spatially varying predictors as determined by the lower level chain. For our simulations L was chosen to be 5, with 4 models representing edges at 0, 45, 90, and 135 degrees and the fifth model representing the non-edge regions. Both fixed and adaptive (Jayant type) quantizers were used. Greater compression is achieved by subsampling in the non-edge regions of the image and then interpolating at the decoder.
New and efficient interframe extensions of EZBC and JPEG 2000

Nowadays, the development of video coders is resulting in significantly increased performance. Among all coder categories, fine grain scalable video coders have the chance to show great advantage by freely extracting code-streams with different bitrates, resolutions, and frame rates from one source-coded bit file to satisfy the various requirements of subscribers in a multicast network. Based on the widely known ENH-MC-EZBC coder with motion-compensated temporal filtering (MCTF) and multi-mode motion-compensation, we enhance and revise its motion model to incorporate advanced mechanisms such as motion-vector prediction competition, block merging, and affine motion-compensation. Experimental results reveal that up to 17% of bit savings can be achieved. Moreover, we consider JPEG 2000 as a backend coder option for the MCTF-generated temporal subbands to directly enable multi-stage code-stream extraction for hierarchical network distribution. Experimental results on common test clips are presented and compared against the current Internet standard AVC/H.264 (JM16.1 test model).
Class-E power amplifier design at 2.5 GHz using a packaged transistor

A Class-E power amplifier has been designed to operate at 2.5 GHz using a commercial, packaged GaAs pHEMT. The design approach used a novel analysis of the package impedances. The objective was to present optimal harmonic loads to the transistor, using lumped-component matching on commercial PCB material. Using an MRFG35010 plastic packaged transistor, a drain efficiency of 72% with about 3 W output power was achieved at 2.55 GHz.
Comments on "A Model for Radar Images and Its Application to Adaptive Digital Filtering of Multiplicative Noise"

In a recent paper  a model for radar images was derived and a method for mean-square error (MSE) filtering of noisy radar images was presented. The purpose of this correspondence is to point out that the filter in  is not optimum in the MSE sense and to show that the ultimate filter scheme is based on a very restricted model for radar images.
Overlay multi-hop FEC scheme for video streaming over peer-to-peer networks

Overlay networks offer promising capabilities for video streaming, due to their support for application-layer processing at the overlay forwarding nodes. In this paper we propose a novel overlay multi-hop FEC (OM-FEC) scheme that provides FEC encoding/decoding capabilities at intermediate nodes in an overlay path. Based on the current network conditions, the end-to-end overlay path is partitioned into segments, and appropriate FEC codes are applied over those segments. We evaluate our work in a real-world scenario and illustrate that the proposed OM-FEC can outperform a pure end-to-end strategy by 10-15 dB in terms of video PSNR.
Image identification and restoration in the subband domain

When faced with a large-sized point spread function, the expectation-maximization (EM) algorithm is very sensitive to local minima. To deal with this problem, it is proposed that EM image identification and restoration be done in the subband domain. After the image is first divided into subbands, then the EM algorithm is applied to each subband separately. In each subband the point spread function can be modeled by a reduced number of parameters and the image model can be better represented also. An adaptive subband EM method for quantization of the upper frequency subbands is introduced.<<ETX>>
Frequency Scanning Using Software Defined Radio for Localised Range Estimation

Range estimation for localisation in wireless sensor networks is an ill posed problem due to multipath. The advancements in software defined radio have made possible the novel ranging technique outlined in this paper. By using frequency scanning, node localisation is achieved in wireless sensor networks (WSN). The technique examines the periodicities in the frequency scan and concludes that when a frequency scan is performed, the periodicity of the received signal strength is proportional to the distance. By comparing the periodic value to a linear periodic function, the distance between sensor node and anchor node can be estimated. Simulation results demonstrate the proposed ranging technique is capable of giving accurate localised range estimations.
An approach to minimize robotics system development and integration time

This paper presents the design, implementation, and use of a cycle time reduction system (CTRS) for remote cleanup and remediation of hazardous waste sites. The goal is to reduce the amount of time between a site-defined need to a site-delivered implementation of the robotic hardware that solves the problem. The CTRS uses simulation, followed by direct conversion to actual hardware, to meet the requirements of the application, and populates the solution with models of robots, grippers, and other components. The user can easily change robots, grippers, vision systems, control algorithms, sensors, or any other component in the current solution to attempt to find a more effective solution. The CTRS simulates the overall performance of the system. The interfaces between simulated components are the same as the physical interfaces between real components, thereby performing a simulated system integration of both the mechanical and data linkages. In this way, the CTRS will enable expedient transformation of the simulation to actual hardware operation. Once the solution is selected, the simulation is used to train an operator, while the procurement and integration of the real hardware components takes place. Upon integrating the hardware, the system is delivered to the site with a trained operator ready to operate the system.
MTT-Society Fellows of 2013: 25 Members of MTT-S Elected to Fellow of the IEEE in 2013

The IEEE grade of Fellow is conferred by the IEEE Board of Directors upon a person with an outstanding record of accomplishments in any of the IEEE fields of interest. The total number selected in any one year cannot exceed one-tenth of 1% of the total voting membership.  Fellow is the highest grade of membership and is recognized by the technical community as a prestigious honor and an important career achievement. There were 298 individuals elevated to IEEE Fellow for 2013. Of these 298, ten Fellows were evaluated by the MTT-Society (MTT-S) as their primary affiliation in IEEE. Their citations and biographies appear here, with some selected highlight achievements, along with portrait photographs so that you can congratulate them on their election to Fellow in person when you meet them at conferences or other meetings. There are a further 15 members of the MTT-S who were elevated to the class of Fellow in 2013, but were evaluated by other Societies. Their names and citations appear after.
Frame-rate up-conversion using transmitted motion and segmentation fields for very low bit-rate video coding

We present a motion-compensated interpolation scheme that allows recovery of skipped frames at the receiver. The interpolation is performed based on an object-based interpretation of the video. The main advantage of the scheme is that the decoded motion and segmentation information is used without refinement. This is attributable to the fact that the object-based representation is true to the "real" motion. We present simulation results in a very low bit-rate coding environment, where multiple frames need to be skipped. The interpolated frames show good reconstruction quality, whereas standard block-based methods lead to unacceptable artifacts.
Broad-band poly-harmonic distortion (PHD) behavioral models from fast automated simulations and large-signal vectorial network measurements

We present an optimal experiment design methodology and a superior and fully automated model generation procedure for identifying a class of broad-band multiharmonic behavioral models in the frequency domain. The approach reduces the number of nonlinear measurements needed, minimizes the time to generate the data from simulations, reduces the time to extract the model functions from data, and when used for simulation-based models, takes maximum advantage of specialized simulation algorithms. The models have been subject to extensive validation in applications to real microwave integrated circuits. The derived model is valid for both small and large amplitude drive signals, correctly predicts even and odd harmonics through cascaded chains of functional blocks, simulates accurately load-pull behavior away from 50 /spl Omega/, and predicts adjacent channel power ratio and constellation diagrams in remarkably close agreement to the circuit model from which the behavioral model was derived. The model and excitation design templates for generating them from simulations are implemented in Agilent Technologies' Advanced Design System.
An empirical study based on a fuzzy logic system to assess the QoS/QoE correlation for layered video streaming

A model that can predict an end user satisfaction or QoE (Quality of Experience) directly from the network QoS (Quality of Service) is still illusive in the field of image processing and is completely absent in multi-layered video. This motivates the derivation of a meaningful QoS to QoE mapping function to allow one to be predicted in the absence of the other. This paper presents an affine fuzzy logic based system that can map the QoS to QoE and can be extended to layered video streaming. The proposed methodology employs a learning system which optimizes the coded layered video for best QoE. Four QoS parameters are chosen as the inputs of the designed model, while the output is the Peak Signal-to-Noise Ratio (PSNR). The designed membership functions and the fuzzy rules extracted from the input and the output enable the proposed model to identify and learn the video QoE.
Next generation marine data networks in an IoT environment

Packet data networks at sea offer the potential for increased safety, connectivity and meteorological data acquisition. Existing solutions including satellite communication are expensive and prohibitive to most small vessels. In this paper, an Internet of Things (IoT) application is proposed as a marine data acquisition and cartography system over Ship Ad-hoc Networks (SANET). Ships are proposed to communicate over Very High Frequency (VHF) which is already available on the majority of ships and are equipped with several sensors such as sea depth, temperature, wind speed and direction, etc. On shore, 5G base station nodes represent sinks for the collected data and are equipped with Mobile Edge Computing (MEC) capabilities for data aggregation and processing. The sensory data is ultimately aggregated at a central cloud on the internet to produce public up to date cartography systems. We discuss the deployment limitations and benefits of the proposed system and investigate it's performance using four different MANET routing protocols which are Ad hoc On-Demand Distance Vector (AODV), Ad hoc On-Demand Multipath Distance Vector (AOMDV), Destination-Sequenced Distance Vector (DSDV) and Dynamic Source Routing (DSR) protocols. Simulation results illustrate the efficiency of the proposed system with packet delivery rates of up to 60 percent at shore base stations.