nils-herrmann/clean_scirepeval huggingface dataset:
Design of a Ka-band gyro-TWT for radar applications

The design of a Ka-band gyrotron traveling wave tube (TWT) amplifier capable of operating over a wide range of peak powers and bandwidths is presented. The amplifier operates in the TE/sub 11/ mode at the fundamental cyclotron harmonic. Instantaneous bandwidths in the range of 2.5 to 3.9 GHz (at 1 dB below saturation) with corresponding peak powers between 92.2 and 57.9 kW can be achieved by simply adjusting the mod-anode voltage of the electron gun. The corresponding gains range from 57.1 to 36.0 dB. The design performance is obtained with a high quality, 6 A, 70 kV electron beam generated with a double-anode magnetron injection gun. This wide range performance capability in the design is achieved via the use of the distributed loss approach in the interacting circuit, which also guarantees zero-drive stability. A diffractive loading scheme is employed in the lossy section of the circuit to ensure high average power operation of the amplifier.
A Short Study on the Validity of Miller's Theorem Applied to Transistor Amplifier High-Frequency Performance

The use of Miller's theorem in the determination of the high-frequency cutoff frequency of transistor amplifiers was recently challenged by a paper published in this transactions. Unfortunately, that paper provided no simulation or experimental results to bring credence to the challenge or to validate the alternate method of determination proposed. This paper provides SPICE simulation results that validate the common usage of Miller's theorem, limit the alternate method provided in that recent paper to a very small class of amplifiers, and reinforce the need to consider transistor amplifiers as two-pole systems.
Assessing cost/benefits of research and development investments

A methodology is presented for assessing the economic and noneconomic cost/benefits of investments in research and development. It is argued that the most difficult aspect of cost/benefit analysis is not calculation, but representation of stakeholders, products, benefits, and costs. A stakeholder-based methodology is described that focuses on these representation issues. Use of this methodology is illustrated with a case study of a long-term government research and development (R&D) program.
Emotional expressions in audiovisual human computer interaction

Visual and auditory modalities are two of the most commonly used media in interactions between humans. The authors describe a system to continuously monitor the user's voice and facial motions for recognizing emotional expressions. Such an ability is crucial for intelligent computers that take on a social role such as an actor or a companion. We outline methods to extract audio and visual features useful for classifying emotions. Audio and visual information must be handled appropriately in single-modal and bimodal situations. We report audio-only and video-only emotion recognition on the same subjects, in person-dependent and person-independent fashions, and outline methods to handle bimodal recognition.
Active power filtering under non-ideal voltage conditions using the conservative power theory

This paper reviews the capabilities of the conservative power theory (CPT) for active power filtering (APF) and power factor correction, specifically under distorted and asymmetric voltage regime. Both through simulation and experimental verification it is demonstrated how the CPT can selectively neutralize current non-idealities, under harsh voltage conditions. Thus, the experimental results confirm that the CPT framework provides means of achieving Fryze currents, with unity power factor, transporting real power at the minimum line current RMS value.
Automatic tracking of intraoperative brain surface displacements in brain tumor surgery

In brain tumor surgery, soft-tissue deformation, known as brain shift, introduces inaccuracies in the application of the preoperative surgical plan and impedes the advancement of image-guided surgical (IGS) systems. Considerable progress in using patient-specific biomechanical models to update the preoperative images intraoperatively has been made. These model-update methods rely on accurate intraoperative 3D brain surface displacements. In this work, we investigate and develop a fully automatic method to compute these 3D displacements for lengthy (~15 minutes) stereo-pair video sequences acquired during neurosurgery. The first part of the method finds homologous points temporally in the video and the second part computes the nonrigid transformation between these homologous points. Our results, based on parts of 2 clinical cases, show that this speedy and promising method can robustly provide 3D brain surface measurements for use with model-based updating frameworks.
Application of direct and large-eddy simulation methods to late wakes of submerged bodies

Late wakes of submerged bodies are simulated in support of the ONR mechanics and energy conversion turbulence program. Direct numerical simulations (DNS) is used to examine the dynamics, energetics, and structure of wakes evolving to late times. Particular emphasis is placed on quantifying the structural differences between wakes of towed and self-propelled bodies and on quantifying the influences of environmental shear and stratification. The DNS results clearly show that wakes of towed bodies lead to larger-scale coherent structures at late times. Stratification tends to confine the wake in the vertical direction and provides a mechanism for the radiation of internal waves. Shear is found to interrupt the upscale cascade of vorticity. In addition to DNS, large-eddy simulation (LES) is considered as a means of accessing higher Reynolds numbers and of enabling broader parameter studies. As a first step in this direction, the LES approach is validated by repeating prior DNS on much coarser meshes. A parameter-free dynamic subgrid-scale model is used for this purpose and good results for low-order statistics are obtained on a mesh that is a factor of 4 coarser in each direction as compared with the DNS. When the effect of the increased time step is taken into account, this represents a factor of 4/sup 4/ = 256 reduction in computational expense. Thus LES can greatly reduce the computer time needed for wake studies and can allow significant increases in Reynolds number.
A fast, on-line collision avoidance method for a kinematically redundant manipulator based on reflex control

A computationally efficient method to achieve reflexive collision avoidance is described. The system consists of four parallel, asynchronous control layers: a conventional servo tracking controller, a reactive trapezoidal velocity profiler, a joint-by-joint reflexive collision avoidance layer, and a guiding potential-function layer. The lowest two layers guarantee that the robot will not overshoot any joint-space position setpoint. The higher two layers compute successive set points based on a continuous, online inspection of configuration space. The guiding potential-function layer incorporates task-space-based attraction to a hand goal, while the reflexes permit use of kinematic redundancy for obstacle avoidance. In many cases, no explicit path planning is required to achieve competent, collision-free motion to a task-space goal while moving in a cluttered environment. Experimental results are described for the physical implementation of the system on the first four joints of a kinematically redundant robot.<<ETX>>
Enhanced Field Effect Mobility on 4H-SiC by Oxidation at 1500°C

A novel 1500°C gate oxidation process has been demonstrated on Si face of 4H-SiC. Lateral channel metal-oxide-semiconductor-field-effect-transistors (MOSFETs) fabricated using this process have a maximum field effect mobility of approximately 40 cm\2 V-1 s-1 without post oxidation passivation. This is substantially higher than other reports of MOSFETs with thermally grown oxides (typically grown at the standard silicon temperature range of 1100-1200°C). This result shows the potential of a high temperature oxidation step for reducing the channel resistance (thus the overall conduction loss), in power 4H-SiC MOSFETs.
Characteristics and device design of sub-100 nm strained Si N- and PMOSFETs

Current drive enhancements were demonstrated in the strained-Si PMOSFETs with sub-100 nm physical gate lengths for the first time, as well as in the NMOSFETs with well-controlled threshold voltage V/sub T/ and overlap capacitance C/sub OV/ characteristics for L/sub poly/ and L/sub eff/ below 80 nm and 60 nm. A 110% enhancement in the electron mobility was observed in the strained Si devices with 1.2% tensile strain (28% Ge content in the relaxed SiGe buffer), along with a 45% increase in the peak hole mobility.
Efficient Operation of Traveling-Wave Tube Amplifier with Dynamically Adjusted Collector Bias Voltages

We describe a novel efficiency enhancement technique for traveling-wave tube amplifiers (TWTAs) for applications in digital communication systems. The enhancement is obtained by tracking the time-dependent power envelope of the input waveform and dynamically adjusting the bias voltages of the TWTs multi-stage depressed collector. The instantaneous amplitude of the input waveform is used as a guide to optimize the collector bias voltages to the particular energy distribution of the spent electron beam to achieve maximum energy recovery. The improvement in recovered energy and efficiency has been demonstrated by experiment and through simulation by the large-signal helix TWT code CHRISTINE.
An advanced electromagnetic eigenmode solver for vacuum electronics devices-CTLSS

The Cold-Test and Large-Signal Simulation code (CTLSS), a design tool for vacuum electronics devices, is presented. The prototype tool is a three-dimensional, frequency-domain cold-test code that operates on a rectangular structured grid. It uses a generalisation of the Jacobi-Davidson algorithm that has proven effective in solving for eigenmodes in problems having sharp-edged structures with materials having large dielectric constants and loss tangents as high as 100%. We present the CTLSS algorithm and code features that are useful for vacuum electronics design. Analysis of both closed cavities and periodic slow-wave structures are given. Tests indicate that the CTLSS algorithm can determine mode frequencies to well below 0.1% accuracy for all modes computed. A new formulation has been implemented to compute the complex axial wavenumber, k/sub z/, in a periodic waveguide, as the eigenvalue for a specified real frequency, and test results will be presented. This code is being extended to include an unstructured mesh for the conformal representation of structures using high order elements.
A practical implementation of a 3D game engine

Creating a 3D game engine is not a trivial task as gamers often demand for high quality output with top notch performance in games. In this paper, we show how various real-time rendering algorithms can be applied to implement a practical 3D game engine. We explore the general architecture of a 3D engine and discuss the role of a scene graph in a 3D engine. We look at scene graph from the software engineering perspective. In particular, we show the way to design a scene graph that is object-oriented and portable across different rendering engine. Then, we explain the algorithms that we apply to speed up the performance of our 3D engine. We optimize the 3D engine on the scene graph and object geometry levels. The algorithms that we propose are expected to perform reasonably well for both static and dynamic scenes. Finally, we give a brief preview on the possibility of parallel processing in scene graph to create a 3D engine with multiprocessing capability.
A Template-Matching Based Method to Perform Iris Detection in Real-Time Using Synthetic Templates

Understanding people attentional focus can be useful for several applications. One important challenge in this area is to determine the iris position in image/video in order to estimate gaze behavior. To this end, this paper presents a robust and non-intrusive method to locate human iris position in low resolution grayscale images, in real-time. The method requires the previous knowledge of the face location and provides iris position in a region of interest (ROI) estimated based on anthropometric parameters. We achieved good results, varying from 90% to 100% of accuracy on images and video sequences. In addition, we tested our algorithm with noisy images. The lowest levels of accuracy are mainly due to light reflection on spectacles and eyes occlusion by eyelids.
Automated substation event analysis using IED data

The installation of Intelligent Electric Devices (IEDs) in the substations has changed the face of protection engineering. These devices not only record a variety of analog and digital values but also communicate the data to the control centre. Thus, the same engineers who were struggling for data earlier with electromechanical relays now have sufficient data to analyze the events taking place in the system from time to time. The IEDs generate operational data, which helps to analyze what went wrong in the system and non-operational data, which indicates why things went wrong in the system. Thus, with each IED sending data at the control centre, a large volume of data gets accumulated which cannot be analyzed manually. Automated systems are required to assist engineers analyze the data received from IEDs and provide quality information to the various user groups. In this paper, an attempt has been made to reduce large amount of data generated by the new generation relay IEDs using rough set theory. The logic has been developed to analyze the concise data available after using rough set technique and communicate the information so extracted to the operator, protection and maintenance departments. These departments make use of the information in running the system in a more effective and efficient manner.
EcMLST: an online database for multi locus sequence typing of pathogenic Escherichia coli

In order to provide a portable and accurate typing system for the unambiguous characterization of pathogenic Escherichia coli isolates to the scientific community, we have constructed an online database for multilocus sequence typing of pathogenic E. coli (EcMLST) using current Internet and open source technology. The system consists of an XML specification of the E. coli MLST system, and a set of peri modules defining the database tables and generating dynamic Web pages for querying the database. It is implemented on a Sun server running the Apache web server. The underlying tier is the MySQL database system. Currently, the database contains nucleotide sequence data and annotated allelic profile data of 15 house-keeping genes for 600 representative E. coli isolates. Access to the central-held typing and epidemiology data is supported by parametric searching, full-text searching, as well as query interface links to the reference center of Shiga toxin-producing E. coli (STEC, http://www.shigatox.net/stec). EcMLST has been used by public health laboratories and researchers for epidemiology and evolutionary studies. The system can be accessed at http://www.shigatox.net/mlst.
A 2-D fluid electron and 1-D particle ion hybrid model of ion noise in microwave tubes

Since there is always some ambient gas in electron beam devices, background ionization is ubiquitous. For long pulse times, the electrostatic potentials associated with this ionization can reach significant levels and give rise to such observed phenomena as phase noise in microwave tubes. Observations of noise in microwave tubes such as coupled-cavity traveling wave tubes (CC-TWTs) and klystrons have been discussed in the literature. A hybrid model has been developed in which the electron beam is treated as a 2D fluid using the beam envelope equation, and the ions generated by beam ionization are treated as discrete particles in 1D. The effect of secondary electrons is neglected in the present analysis. The ionization rate depends on the ambient gas pressure and species as well as on the electron beam current and energy. Based on this rate, ions are created and distributed on an axial grid on each time step. The ion charge is then mapped onto the grid, and Poisson's equation is then solved in 1D under the assumption that the transverse scale lengths are less than the betatron wavelength of the electron beam. The ion charge distribution is then used to integrate the beam envelope equation that updates the beam equilibrium. The ion motion is then integrated subject to the wall potential, the space-charge potential of the electron beam, and the self-consistent ion potential. This process is iterated over any desired pulse time.
Development of a relative motion facility for simulations of autonomous air to air refuelling

The initial development and results of a comprehensive simulation and testing environment for autonomous air to air refuelling is presented. A thirteen degree of freedom relative motion facility has been installed at the University of Bristol to support the design, testing, and validation of measurement systems and autonomous control algorithms through hardware in the loop simulations. Initially this facility is used to simulate the `hook-up space' in air to air refuelling. A real-time platform handles the control of the manipulators in synchronisation with streamed data generated by simulated kinematics. An air-to-air refuelling simulation provides the kinematic data of a refuelling probe and drogue, with the feedback loop made by the provision of position measurements from proximity and vision-based sensors. The synthetic environment is real-time and consists of nonlinear models for the receiver and tanker, and accounts for the additional dynamics of the probe and drogue. Data packaging and delay compensation on the network between the real-time platform and the robot controller is addressed in this paper.
Do Deep Neural Networks Learn Facial Action Units When Doing Expression Recognition?

Despite being the appearance-based classifier of choice in recent years, relatively few works have examined how much convolutional neural networks (CNNs) can improve performance on accepted expression recognition benchmarks and, more importantly, examine what it is they actually learn. In this work, not only do we show that CNNs can achieve strong performance, but we also introduce an approach to decipher which portions of the face influence the CNN's predictions. First, we train a zero-bias CNN on facial expression data and achieve, to our knowledge, state-of-the-art performance on two expression recognition benchmarks: the extended Cohn-Kanade (CK+) dataset and the Toronto Face Dataset (TFD). We then qualitatively analyze the network by visualizing the spatial patterns that maximally excite different neurons in the convolutional layers and show how they resemble Facial Action Units (FAUs). Finally, we use the FAU labels provided in the CK+ dataset to verify that the FAUs observed in our filter visualizations indeed align with the subject's facial movements.
Adaptive local learning in sampling based motion planning for protein folding

Simulating protein folding motions is an important problem in computational biology. Motion planning algorithms such as Probabilistic Roadmap Methods (PRMs) have been successful in modeling the protein folding landscape. PRMs and variants contain several phases (i.e., sampling, connection, and path extraction). Global machine learning has been applied to the connection phase but is inefficient in situations with varying topology, such as those typical of folding landscapes.  We present a local learning algorithm that considers the past performance near the current connection attempt as a basis for learning. It is sensitive not only to different types of landscapes but also to differing regions in the landscape itself, removing the need to explicitly partition the landscape. We perform experiments on 23 proteins of varying secondary structure makeup with 52-114 residues. Our method models the landscape with better quality and comparable time to the best performing individual method and to global learning.
A low-cost acoustic microsensor based system in package for air quality monitoring

In this paper we report on the development of a novel hybrid System in Package (SiP) microsensor utilizing high frequency acoustic wave devices for the real time monitoring of airborne fine particulates. The hybrid particle sensing system consists of a zinc oxide (ZnO) based solidly mounted resonator (SMR) device interfaced to a CMOS application-specific integrated circuit (ASIC) chip. Air is drawn into a virtual impactor where PM2.5 particles are separated and then deposited onto the SMR surface. The mass loading due to the fine particles is measured as a shift in the resonant frequency of the SMR working at 894 MHz. Experimental results performed in both laboratory conditions and real outdoor environment showed that the hybrid system is capable of detecting fine particles with a sensitivity of 7.5 kHz per μg/m3. This system is used as a basis towards a fully integrated portable smart particle sensor based on CMOS-SMR devices for the continuous, real-time and low-cost monitoring of airborne particulate matter.
An analog neural net performing multidimensional maximum entropy spectral estimation

A general algorithm is presented for computationally efficient multidimensional maximum entropy (ME) spectral estimation. The estimator is equivalent to an analog neural net that is governed by an energy function that measures the degree of constraint satisfaction, i.e., correlation-matching property. The multidimensional ME (MDME) spectral-estimation problem is defined. ME spectral estimation is formulated as an initial-value problem. The MDME spectral estimators, or algorithms, for solving the initial-value problem are developed. The neural net algorithm is derived, and simulated experiments with 1D or 2D signals are conducted. In each, the assumed true spectrum is given and autocorrelations at a number of horizontally and vertically equally spaced lags are calculated from the Fourier transform of the true spectrum. The overall results indicate very good performance in estimating ME spectra, even in cases where there are few autocorrelation measurements.<<ETX>>
Controllability and Reduced State Space Models for Feedback Control of the Resistive Wall Kink Mode

Controllability conditions are derived for the resistive wall kink mode using analytic single circuit theory. Using feedback coils that couple more strongly to the plasma than the wall allows controllability up to the ideal wall limit of performance. Conversely, it is found that the controllability of the unstable resistive wall mode is lost at some value of instability growth rate between the no-wall and ideal wall limits when feedback coils are placed outside the passive stabilizing wall. The controllability criterion of the mode can be written in terms of the sign of a dimensionless coupling number that characterizes the magnitude of system inductances. Similar coupling numbers can be defined and used to characterize mode observability conditions as well as the interaction of sensor and feedback coils with the passive wall and plasma. A method is developed based upon contraction of a finite element inductance and resistance matrix model of the system conducting structures that allows quantitative calculation of these coupling numbers for a given system eigenmode. The construction of simple reduced order ordinary differential equation models based upon these coupling numbers accurately calculates mode eigenvalues and serves as a useful starting point for developing few mode approximations of the full eigenmode spectrum for use in advanced controller algorithm development