nils-herrmann/clean_scirepeval huggingface dataset:
An electrical method to measure SOI film thicknesses

Others have identified three normal operating regions for silicon-on-insulator (SOI) MOSFET's. In two of these regions the threshold voltage depends on the silicon film thickness and the buried insulator thickness. Based on the threshold equations, a method has been developed to nondestructively measure the two film thicknesses. The method uses a feedback amplifier to hold the drain biases nearly constant while the body and/or the buried gate voltages are varied. Calculated threshold voltages from the top-gate voltages are used to calculate the film thicknesses. The method is illustrated on devices built in oxygen implanted substrates. Measurements compare well with SEM image measurements.
Bayesian separation of audio-visual speech sources

In this paper, we investigate the use of audio and visual rather than only audio features for the task of speech separation in acoustically noisy environments. The success of existing independent component analysis (ICA) systems for the separation of a large variety of signals, including speech, is often limited by the ability of this technique to handle noise. In this paper, we introduce a Bayesian model for the mixing process that describes both the bimodality and the time dependency of speech sources. Our experimental results show that the online demixing process presented here outperforms both the ICA and the audio-only Bayesian model at all levels of noise.
Effects of non-periodic variations in periodic RF structures

The theory of perfectly periodic RF structures has been extensively developed, motivated largely by the many applications, some of which are millimeter wave radiation sources, amplifiers, and slow-wave circuits. Of course, the realization of a periodic structure is never perfect, due to fabrication tolerances and variations in material properties from cell to cell. Such differences among cells may also be intentionally introduced in order to tailor the structure properties for a specific application. In the perfectly periodic case, the geometry and composition of a single cell determines the dispersive and other electromagnetic properties of the structure; these properties are also affected by the properties of the terminations, for structures of finite length.
Correlation Properties of Large Scale Fading Based on Indoor Measurements

Statistical channel models are attractive for their simplicity but sometimes lack in precision. In order to improve modelling accuracy, statistical model parameters, which are dependent on the environment, are extended to include spatial and temporal correlation. In outdoor scenarios these parameters are assumed constant over "large" areas of several wavelengths hence the name large scale parameters. This paper studies the large scale fading (LSF) and the applicability of bringing this previously used outdoor variable to the indoor case. The impacts of the model of the LSF on the outdoor system-performance have been studied and several relevant models have been proposed for outdoor cases. We present the intra-site autocorrelation as well as the inter-site cross correlation of the LSF for an indoor channel. The results are based on two separate measurement campaigns conducted at KTH, Stockholm and TUI, Ilmenau, using a single mobile station (MS) and multiple base stations (BSs) to investigate such models. We observe that the areas under which the LSF could be assumed constant are, in indoor scenarios, so small that it can be assumed independent from one local area to another. Furthermore, we find results that point towards the existence of inter-site correlation in some specific scenarios.
Audio segment retrieval using a short duration example query

We propose a general approach to audio segment retrieval using a synthesized HMM. The approach allows a user to query audio data by an example audio segment of a short duration and find similar segments. The basic idea of our approach is to first train a theme HMM using the given example and a general background HMM using all the audio data, and then combine these individual HMMs to form a synthesized "background-theme-background" HMM. This synthesized HMM can then be applied to any audio stream as a parser to detect the most likely theme segment. We overcome the problem of a short duration being used to train a theme HMM, by using the MAP rule with the background model as a prior model. Evaluation of the proposed retrieval scheme, using short duration example audio clips of narration as queries, gives quite promising results.
Action detection in complex scenes with spatial and temporal ambiguities

In this paper, we investigate the detection of semantic human actions in complex scenes. Unlike conventional action recognition in well-controlled environments, action detection in complex scenes suffers from cluttered backgrounds, heavy crowds, occluded bodies, and spatial-temporal boundary ambiguities caused by imperfect human detection and tracking. Conventional algorithms are likely to fail with such spatial-temporal ambiguities. In this work, the candidate regions of an action are treated as a bag of instances. Then a novel multiple-instance learning framework, named SMILE-SVM (Simulated annealing Multiple Instance LEarning Support Vector Machines), is presented for learning human action detector based on imprecise action locations. SMILE-SVM is extensively evaluated with satisfactory performances on two tasks: 1) human action detection on a public video action database with cluttered backgrounds, and 2) a real world problem of detecting whether the customers in a shopping mall show an intention to purchase the merchandise on shelf (even if they didn't buy it eventually). In addition, the complementary nature of motion and appearance features in action detection are also validated, demonstrating a boosted performance in our experiments.
Classifying motion picture soundtrack for video indexing

We investigate a method for classification of patterns with temporal support. This method combines the ability of a nonlinear-kernel based classifier (in the form of a support vector machine) to discriminate and the ability of a first order Markov chain to model temporal transitions. We apply this to the task of classifying motion picture soundtrack. Experiments with classification of the soundtrack into speech and non-speech audio patterns reveal improvement in classification performance using this proposed method over HMM-based classification as well as SVM-based classification. Using a normalized margin obtained from the SVM and mapping it to a non-negative confidence measure bounded by 1, we attempt to alter the classification of patterns close to the separating boundary, by using the constraints on the transition between the two classes. Sound track classification with semantic classes can help browse and index a video efficiently.
Design and construction of a test bench to characterize efficiency and reliability of high voltage battery energy storage systems

Stationary battery energy storage systems are widely used for uninterruptible power supply systems. Furthermore, they are able to provide grid services. This yields in rising installed power and capacity. One possibility uses high voltage batteries. This results in an improvement of the overall system efficiency. High voltage batteries may be advantageous for future medium voltage DC-grids as well. In all cases, high availability and reliability is indispensable. Investigations on the operating behavior of such systems are needed. For this purpose, a test bench for high voltage storage systems was built to analyze these processes for different battery technologies. A special safety infrastructure for the test bench was developed due to the high voltage and the storable energy of approximately 120 kWh. This paper presents the layout of the test bench for analyzing high voltage batteries with about 4,300 volts including all components, the safety requirements with the resultant safety circuit and the aim of the investigations to be performed with the test bench.
Built-in place substation buildings: an attractive and affordable alternate to packaged units

Light rail traction power substations (TPS's) do not have to be unsightly and hidden in the most remote recesses of the project. The large painted metal boxes surrounded by cyclone fence that have become the familiar norm for many projects are being replaced by built-in-place buildings in Portland, Oregon, where TriMet and the community are concerned with aesthetics and have made the TPS an important and prominent design element. This paper discusses the general design, construction, costs, contract packaging, advantages/disadvantages and features of the TriMet built-in-place substation buildings and compares them with similar packaged units.
Damage thresholds at metal surfaces for short pulse IR lasers

Measurements of damage to metal surfaces induced by intense nanosecond pulses of IR radiation are reported. Single-shot damage thresholds of Cu, stainless steel, molybdenum, and aluminum surfaces have been measured for various angles of incidence and the predicted increase in damage thresholds for grazing incidence optical components have been experimentally verified for the first time at 10 μm. In addition multiple-shot damage tests have been performed and practical lifetime curves for Cu mirrors have been established. The results are compared with existing theoretical models and shown to be in general agreement.
An Encrypted, Content Searchable Scalable Distributed Data Structure

Scalable Distributed Data Structures (SDDS) store data in a file of key-based records distributed over many storage sites. The number of storage sites utilized grows and shrinks with the storage needs of applications, but transparently to them. An application can search records by key or by content in parallel at all storage sites. The need for privacy of the data at the storage sites might require the encryption of the records. However, the scheme needs to preserve the capability to search in parallel. We propose a scheme that achieves this goal. We create a collection of additional SDDS indices. We encrypt these so that we can still perform string searches performed in parallel at the storage sites. We present the scheme and evaluate its strength as well as storage and access performance.
Electron Cyclotron Resonance Gain in the Presence of Collisions

A cyclotron resonance maser source using low-effective-mass conduction electrons in graphene, if successful, would allow for generation of far infrared (FIR) and terahertz (THz) radiation without requiring magnetic fields running into the tens of tesla. In order to investigate this possibility, we consider a situation in which electrons are effectively injected via pumping from the valence band to the conduction band using an IR laser source, subsequently gyrate in a magnetic field applied perpendicular to the plane of the graphene, and give rise to gain for an FIR/THz wave crossing the plane of the graphene. The treatment is classical, and includes on equal footing the electron interaction with the radiation field and the decay in electron energy due to collisional processes. Gain is found even though there is no inversion of the energy distribution function. Gain can occur for electron damping times as short as hundreds of femtoseconds.
Analysis of direct torque controlled BLDC motor with reduced torque ripple

Direct Torque Control (DTC) of brush less DC (BLDC) motor having trapezoidal back emf with a reduced torque ripple is presented in this paper. Unlike conventional six step PWM technique, a quasi square wave current is obtained by selecting the voltage vectors from the pre defined switching table, which results in faster torque response compared to the conventional scheme. In the constant torque region the control of amplitude of the stator flux is found to be difficult due to the sharp dips in the flux trajectory. A pre stored back emf versus position look up table is used to avoid the low frequency oscillations as a result of which, a better torque response is obtained while the amplitude of stator flux linkage is deliberately kept constant by ignoring the flux control in constant torque region. This conventional DTC fails to concentrate on the torque ripple problem due to the variation in switching frequency. The introduction of null vectors causes significant change in the torque response without deteriorating the overall performance of the system. The validity of the scheme is verified from the simulation results.
BodyPrint: Pose Invariant 3D Shape Matching of Human Bodies

3D human body shape matching has large potential on many real world applications, especially with the recent advances in the 3D range sensing technology. We address this problem by proposing a novel holistic human body shape descriptor called BodyPrint. To compute the bodyprint for a given body scan, we fit a deformable human body mesh and project the mesh parameters to a low-dimensional subspace which improves discriminability across different persons. Experiments are carried out on three real-world human body datasets to demonstrate that BodyPrint is robust to pose variation as well as missing information and sensor noise. It improves the matching accuracy significantly compared to conventional 3D shape matching techniques using local features. To facilitate practical applications where the shape database may grow over time, we also extend our learning framework to handle online updates.
A novel open-transistor fault detection method in symmetric cascaded H-bridge multilevel inverter

The increased components requirement to realize multilevel inverters (MLIs) fallout in a higher prospect of fault due to power semiconductor switches. Efficient fault detection and diagnosis (FDD) strategies have to be implemented to guarantee protection as well as the reliable operation of MLIs. This paper presents a novel open-transistor fault detection method in a charge balanced symmetric cascaded H-bridge (CHB) MLI. The method has been formulated based on the simulations and experiments on a charge balanced 5-level CHB-MLI. The proposed method uses the mean value of the bridge voltages as the diagnostic variable. The simulation and experimental results prove that this approach can detect the open-transistor fault and identify the faulty switch pair.
A Product-Focused Approach to Software Certification

The self-regulation of critical products doesn't work - certification by overseeing bodies is necessary. As software invades more areas of everyday life, certification of systems containing software is increasingly important for governments, industry, and consumers alike. Even if an organization isn't worried about safety, it must consider the consequences of using mission-critical software that isn't certified or qualified as fit for purposes. The US Sarbanes-Oxley Act of 2002, for example, imposes stringent requirements on companies' financial IT systems. Many standards bodies and licensing authorities describe attributes of processes by which software should be developed to meet certain standards or certification criteria. However, a good process on its own doesn't necessarily result in high-quality software. Standards and certification processes should be primarily product-focused rather than process-based to raise the certainty in evaluation of software reliability. Evaluations should be based on direct evidence about the product's attributes, not circumstantial evidence about the process.
3D wave-field synthesis for testing of radio devices

For the sake of new radio devices to conform to respective standards, implementing functionality such as cognitive radio, Long Term Evolution beyond 2×2, or Global Navigation Satellite Systems, a demand for extensive testing arises. A promising solution is the validation inside an Over-the-Air testbed that creates a virtual electromagnetic environment using wave-field synthesis. This paper analyzes the polarimetric accuracy of a wave field generated by a hemispheric (3D) antenna arrangement. As most radio devices have a flat shape (e.g. smart phones, tablets, compact cognitive radio antennas) or a metallic backplane along a defined surface, the complexity of the optimization problem can be reduced. Analyzing the wave-field synthesis accuracy, it has to be kept in mind that for most radio devices the signal-to-noise ratio is limited in a range between 0-30 dB, which indirectly defines the upper limits of the required wave-field synthesis accuracy.
CTLSS-an advanced electromagnetic simulation tool for designing high-power microwave sources

Simulation-based-design (SBD) techniques to achieve "first-pass design success" depend on the development of fast, accurate, realistic models that can handle material properties, geometry, and appropriate boundary conditions. This paper describes a new three-dimensional (3-D) electromagnetic and large-signal simulation tool. Cold-Test and Large-Signal Simulator (CTLSS), which has been developed as part of an SBD tool suite for vacuum electron devices. Computational electromagnetic codes are essential for applying the SBD methodology to the design of vacuum electron devices and components. CTLSS offers the unique advantage that its computational electromagnetics model is linked intimately with a large-signal simulation tool for computing the electron-wave interaction in the radiating structure. Currently, this link has been implemented for helix traveling-wave tubes (TWTs) only, using the CHRISTINE code as the large-signal model, but a new, general, large-signal model is under development and is described in this paper. The electromagnetic simulation engine in CTLSS has been designed and implemented as a volumetric frequency-domain model that can handle both resonant eigenvalue problems, using the Jacobi-Davidson algorithm, and nonresonant driven-frequency problems, using the quasi-minimal residual (QMR) technique to invert the non-Hermitian matrices that often occur in real problems. The features and advantages of this code relative to other models and results from the code for several classes of microwave devices are presented.
Enabling Bring-Your-Own-Device using mobile application instrumentation

Many enterprises are investigating Bring-Your-Own-Device (BYOD) policies, which allow employees to use their personal devices in the workplace. This has led to mixed-use scenarios, where consumer and enterprise software are installed on the same device. In this paper, we describe the Secured Application Framework for Enterprise (SAFE), a comprehensive system for enabling BYOD that allows enterprise and consumer applications to coexist side-by-side on the device. Rather than partition the device by profiles, SAFE embeds enterprise functions in each enterprise application; this allows for a seamless user experience and minimal intrusiveness on the part of the enterprise. We describe the SAFE toolset that implements the embedding of the SAFE instrumentation layer, and then provide an overview of several enterprise features that can be configured using SAFE. Specifically, we describe modeling for analytics, testing and replay, anomaly detection, and cloud data services, all enterprise features that can transparently be added to mobile applications.
Breaking the Barrier to Transferring Link Information across Networks

Link prediction is one of the most fundamental problems in graph modeling and mining. It has been studied in a wide range of scenarios, from uncovering missing links between different entities in databases, to recommending relations between people in social networks. In this problem, we wish to predict unseen links in a growing target network by exploiting existing structures in source networks. Most of the existing methods often assume that abundant links are available in the target network to build a model for link prediction. However, in many scenarios, the target network may be too sparse to enable robust inference process, which makes link prediction challenging with the paucity of link data. On the other hand, in many cases, other (more densely linked) auxiliary networks can be available that contains similar link structure relevant to that in the target network. The linkage information in the existing networks can be used in conjunction with the node attribute information in both networks in order to make more accurate link recommendations. Thus, this paper proposes the use of learning methods to perform link inference by transferring the link information from the source network to the target network. We also note that the source network may contain the link information irrelevant to the target network. This leads to cross-network bias between the networks, which makes the link model built upon the source network misaligned with the link structure of the target network. Therefore, we re-sample the source network to rectify such cross-network bias by maximizing the cross-network relevance measured by the node attributes, as well as preserving as rich link information as possible to avoid the loss of source link structure caused by the re-sampling algorithm. The link model based on the re-sampled source network can make more accurate link predictions on the target network with aligned link structures across the networks. We present experimental results illustrating the effectiveness of the approach.
Calibration of a gigahertz-bandwidth vector signal generation and analysis system

The calibration procedure for a vector signal generation and analysis system with over 1.6 GHz Bandwidth is described. To achieve the desired bandwidth, two software filters (a prefilter and a postfilter) are used to correct the non-uniform frequency responses in the system. We describe techniques for obtaining the response functions of both the signal generator and the signal analyzer. The measured response functions are used to construct the filters to achieve the flat frequency response. Finally a 1-Gsymbol/s 32-QAM raised-cosine-filtered waveform is generated to demonstrate the application of the system.
Design and development of a medical specialist referral system for the indigent population in Richmond

To help those that are unable to afford medical insurance, free medical clinics have been established throughout the country. In Richmond. Virginia there are fourteen safety-net healthcare clinics that serve the general needs of indigent patients. The current referral procedure relies on the clinic's ability to find an appropriate specialist through favors and acquaintances, which is unorganized and inefficient. To solve this problem we designed a secure, user-friendly electronic referral system for use by all fourteen clinics. This system matches patients to specialists based on several clinic inputs, allows the clinics to record appointments made with specialists, and provides reports that display statistics on the clinics and specialists themselves. We designed the system in three tiers to ensure its integration and acceptance into the Richmond community. The final product sees the convergence of several e-health processes into one system. Lack of health insurance hinders millions of Americans from receiving adequate specialist health care. In addition, shortcomings in the current medical referral system reduce the timely care that patients need. These factors adversely affect the patient's health, family members, livelihood, and community. Our team designed an electronic medical referral system for the indigent population in Richmond, Virginia, which facilitate specialist health care for the uninsured and underinsured. This paper discusses the rationale and impact of this project, the design of the referral system, and the current implementation of it.