nils-herrmann/clean_scirepeval huggingface dataset:
3D MIMO Outdoor to Indoor Macro/Micro-Cellular Channel Measurements and Modeling

3-dimensional Multiple-Input Multiple-Output (3D MIMO) systems have received great interest recently because of the spatial diversity advantage and capability for full-dimensional beamforming, making them promising candidates for practical realization of massive MIMO. For 3D MIMO system design, it is important to have full characterization of the 3D MIMO propagation channel, i.e., characterize both the elevation and azimuth characteristics of the wireless propagation channel, especially at the base station end. In this paper, we present first results from a measurement campaign for obtaining these characteristics. For those measurements we use a hybrid switched/virtual cylindrical array with 480 antenna elements at the base station (BS), and a switched array with 24 antenna elements at the user equipment (UE). We perform outdoor-to-indoor (O2I) channel measurements in an urban macro-cellular (UMa) and a micro-cellular (UMi) environments. We provide the elevation and azimuth angular spreads at the transmitter and receiver, and study their dependence on the UE height. With the increase in the UE height, the BS elevation spreads decreased from 1.24 deg to 1 deg and 1.15 deg to 0.78 deg respectively for UMa and UMi; the azimuth spreads remained approximately the same (7.5 deg). Based on the measurements done with the UE placed on different floors, we study the feasibility of separating users in the elevation domain. Users were separable in 44% and 54.17% scenarios respectively for the UMa and UMi environments.
A fast and optimal deterministic algorithm for NP-Hard antenna selection problem

Existing fast antenna selection algorithms have either low performance gains or they are efficient only for the selection of particular size sub-matrices. Our motivation to the study of NP-Hard antenna selection problem is two-fold. First, we intend to propose an optimal algorithm that is equally efficient for each possible subset cardinality of the transmit and/or receive antennas. Second, different from any of the antenna selection algorithms proposed so far, our algorithm deterministically increases the strength of the singular values during the selection of each column of the selected matrix. This increase in the singular values is defined by a very tight bound. This bound has previously been used to analyze the efficiency of low rank approximation algorithms. Hence, our antenna selection procedure is as efficient as that of a best algorithm for matrix low rank approximations.
A Method for Recursive Least Squares Filtering Based Upon an Inverse QR Decomposition

A new computationally efficient algorithm for re- cursive least squares filtering is derived, which is based upon an inverse QR decomposition. The method solves directly for the time-recursive least squares filter vector, while avoiding the highly serial backsubstitution step required in previously de- rived direct QR approaches. Furthermore, the method employs orthogonal rotation operations to recursively update the filter, and thus preserves the inherent stability properties of QR ap- proaches to recursive least squares filtering. The results of sim- ulations over extremely long data sets are also presented, which suggest stability of the new time-recursive algorithm. Finally, parallel implementation of the resulting method is briefly dis- cussed, and computational wavefronts are displayed.
A Hidden Knowledge Discovering Approach for Past Tense and Plural Problems to Language Cognition

One purpose of using computational models in cognitive related researches is to use them as a tool to understand human's learning processes, especially focusing on understanding the processes of language development. Although connectionist computational models can simulate the learning process in a black-box way, understanding the inside rational relations is as important as the correlations between input and output. Therefore, this problem can be transferred to a machine learning problem: to discover the hidden knowledge(rules) for a non-classification problem domain. Unfortunately, most available rule extraction techniques are focusing on classification problems, few of them can solve non-classification problems. In this paper, we proposed a hidden knowledge exploration model for the Auto-encoder based computational models which implements the following two functions: (1) simulate the language learning process, (2) reveal the correlations between prior knowledge and the new knowledge through re-building the inherent rules. Experiments prove its efficiency by comparing its fidelity performances with the well performed black-box learning technique(Multi Layer Perceptron Artificial Neural Network).
An Unsupervised Algorithm to Extract Face Texture from Video

Building face models is an essential task in face recognition, tracking and etc. However, most of the current techniques require hand-labelling or special machinery such as cyber-scanner to extract the face model. In the paper, we propose an unsupervised algorithm to learn the face texture from video. The proposed approach models the video sequence as a mixture of dynamic face-layers and background layers, where the dynamic face-layers may undergo 3D motions in the video. The hidden variables and their generating process is represented by probabilistic graphical model. The model is learnt by EM algorithm with variational approximation. The proposed approach offers several advantage over existing algorithms. First, it derive its learning power by a generative model which naturally represents the generating process of videos. Second, it does not require any labelling or face detection algorithm. Third, the application domain of the proposed algorithm is not restricted to extracting face texture and it can be adapted to model other objects as well. The experimental results demonstrate that our model is capable of learning the appearance model of faces with complex 3D motions in the video.
Broadband Imager-Sounder for Terrestrial Remote Observations (BISTRO)

BISTRO a broadband imager-sounder for terrestrial remote observations is designed as an integral instrument for an envisioned future NOAA National Global Operational Environmental Satellite System (NGOESS) architecture. This ultra-spectral imager/sounder provides for greater than 4000 spectral channels covering a band from 0.4 to 16.5 microns. The instantaneous footprint on the ground has 4000 spatial elements ranging from 0.25 to 1 km depending on the channel wavelength. Each S/C in the NGOESS constellation is proposed to carry an identical copy of the instrument supporting complete global coverage. The overall system, using BISTRO as a core observing instrument, is designed to meet or exceed current (e.g. POEs and GOEs) and planned (eg. GOES-R, and NPOESS) EDRs, CDRs, and other anticipated "user" requirements in the optical and infrared areas of the electromagnetic spectrum for sounding and imaging. Anticipated future "science" requirements for short-and or long-term (climate) observations have been explored with the science and operations community and are tentatively provided for in the overall system design.
Determination of camera location from 2D to 3D line and point correspondences

A novel method for the determination of camera location from 2-D to 3-D line or point correspondences is presented. Using this method, the computation of the rotation matrix and the translation vector of the camera are separable. First, the rotation matrix is found by a linear algorithm using eight or more line correspondences, or by a nonlinear algorithm using three of more line correspondences, where the line correspondences are either given or derived from point correspondences. Then, the translation vector can be obtained by solving a set of linear equations based on three or more line correspondences, or two or more point correspondences. Eight 2-D-to-3-D line or point correspondences or six 2-D-to-3-D point correspondences are needed for the linear approach; three 2-D-to-3-D line or point correspondences for the nonlinear approach. Good results can be obtained in the presence of noise if more than the minimum required number of correspondences are used.<<ETX>>
Efficient calculation of impedance matrices for VE device circuit structures

This paper presents an efficient method for the calculation of impedance matrices of slow and standing wave structures used in vacuum electronic devices. These matrices can be imported by large signal parametric codes like TESLA-Z and CHRISTINE-CC for accurate small and large signal analysis of TWTs, klystrons and other VE devices , including effects of all geometric features and material properties included in the calculation of the impedance matrix. The technique employs both lumped (internal) and wave (modal, boundary) ports in the 3D finite element electromagnetic (EM) code ANALYST .
Characterization of nickel Germanide thin films for use as contacts to p-channel Germanium MOSFETs

We have measured the physical properties and resistivity of nickel germanide thin films formed by the rapid thermal annealing of nickel metal on p-type germanium substrates. Rutherford back scattering and high-resolution electron diffraction confirm that the stoichiometry of the resulting nickel germanide film corresponds to NiGe and has an orthorhombic unit cell with dimensions comparable to that of bulk samples. Transmission electron microscopy shows a poly-crystalline film structure with grain size > 0.1 /spl mu/m. The resistivity values for films annealed in the range 350/spl deg/C-500/spl deg/C are comparable to those of metal silicides. Measurements of the specific contact resistance suggest that values approaching 2 /spl times/ 10/sup -7/ /spl Omega/.cm/sup 2/ can be realized using NiGe formed on heavily doped p-type germanium.
Audio-visual event detection using duration dependent input output Markov models

Analysis of audio-visual data and detection of semantic events with spatio-temporal support is a challenging multimedia understanding problem. The difficulty lies in the gap that exists between low level media features and high level semantic concept. We introduce a duration dependent input output Markov model (DDIOMM) to detect events based on multiple modalities. The DDIOMM combines the ability to model non-exponential duration densities with the mapping of input sequences to output sequences. We test the DDIOMM by modelling the audio-visual event explosion. We compare the detection performance of the DDIOMM with the IOMM as well as the HMM. Experiments reveal that modeling of duration improves detection performance.
Automated artifact rejection using ICA and image processing algorithms

This paper discuses about the automatic Electroencephalogram (EEG) artifact removal using Independent Component Analysis (ICA) and Image Processing Algorithms. ICA is used for obtaining the Independent Components (IC's) that are linear in nature from the EEG signal. These IC's also known as topoplots are used for feature extraction and classification. Local binary pattern (LBP) is being utilized to obtain the features. These features are used for training the classifiers and helps in achieving automatic artifact elimination. Classifiers such as Linear Discriminant Analysis (LDA), K-Nearest Neighbour (KNN), and Support Vector Machine (SVM) are used for identifying the artifacts and thereby to remove such signals. The remaining IC components are used for reconstructing the de-noised signal. Of the existing methods mentioned, with respect to artifact elimination methods, LDA gives the best performance in artifact removal and helps in reconstruction of the signal.
Effect of loading pattern on the performance of reconfigured medium size distribution system

In smart distribution systems operation the network configuration management includes power quality, voltage regulation, loadability limit, energy efficiency, reliability and availability, and operation under faulted conditions as the major influencing factors to achieve desired performance. The network reconfiguration is an integral operational feature in configuration management. Using different methods the various configurations has been suggested in past. Generally, in most of the studies load is assumed fixed, contrary to the practice. The performances of the distribution systems changes with nature of load supplied and variation in loading patterns. This paper considers the effect of loading pattern on smart distribution system performance. A comparative study of power supplied, voltage profile, power loss reduction and loadability limit for performance evaluation has been performed on an IEEE 33 bus distribution system.
A novel switching scheme for Three phase PWM AC Chopper fed induction motor

AC Voltage Controllers are finding important application in speed control of induction motors, light dimmers, heat controllers and soft starters. AC Chopper is an arrangement of bi-directional switches to control the output voltage by varying the duty-cycle of operation of the switches involved. In this paper, a new switching scheme for three phase ac chopper is discussed which requires only three variables for converting the fixed input ac voltage to a controlled ac voltage. The added advantage is that this scheme takes into account the safe operation of the ac chopper by preventing short-circuit conditions. At the same time it provides a path to the motor current when the terminal voltage falls to zero. Implementation of the proposed scheme leads to much simpler control circuitry than discussed in the literature. A Three phase 3HP induction motor-fed from three phase ac chopper is used for the work. The simulation results confirm the improvement in power factor, leading to power savings.
Duration dependent input output markov models for audio-visual event detection

Detecting semantic events from audio-visual data with Spatiotemporal support is a challenging multimedia Understanding problem. The difficulty lies in the gap that exists between low level media features and high level semantic concept. We present a duration dependent input output Markov model (DDIOMM) to detect events based on multiple modalities. The DDIOMM combines the ability to model nonexponential duration densities with the mapping of input sequences to output sequences. In spirit it resembles the IOHMMs  as well as inhomogeneousHMMs . We use the DDIOMM to model the audio-visual event explosion. We compare the detection performance of the DDIOMM with the IOMM as well as the HMM. Experiments reveal that modeling of duration improves detection performance.
40 GHz fully integrated and differential monolithic VCO with wide tuning range in AlInAs/InGaAs HBT

A fully integrated and differential AlInAs/InGaAs HBT voltage controlled oscillator (VCO) with wide tuning range was demonstrated for 40 GHz wireless and optical communication applications. To our knowledge, this 40 GHz IC is the highest frequency fundamental mode fully integrated and differential VCO with wide tuning range ever reported. This VCO delivers a typical differential output power of +5 dBm at a center frequency of 39 GHz with a tuning range of up to 3.5 GHz. Co-planar waveguide (CPW) circuit designs has been employed for the development of the InP HBT MMIC VCOs to reduce chip cost and make them flip chip compatible. The measured phase noise shows -95 dBc/Hz at 1 MHz offset and -75 dBc/Hz at 100 KHz offset. The VCO was realized in a high yield optical lithography triple mesa HBT process. Circuit performance was relatively insensitive to process variation indicating a highly robust circuit design and process.
Effect of Attenuation in Synchronous and Non-Synchronous Beam-Wave Interactions

The gain of a traveling wave tube, in which the beam velocity is closely matched to the phase velocity of a slow circuit wave, decreases as the circuit loss increases. However, sufficiently far from synchronism an increase in circuit loss will cause an increase in gain - a phenomenon well known as the resistive wall instability. Between these extremes there are parameter regimes in which the gain is relatively insensitive to loss. A careful analytical study of a beam interacting with the slow wave fields propagating on a sheath helix, itself supported by a lossy dielectric sleeve, illustrates these effects. The central goal of this study is to determine whether the approximate treatment of circuit attenuation in the CHRISTINE ID large signal helix TWT simulation code is sufficiently accurate for the largest values of attenuation encountered in TWTs (in and near severs), for all operating voltages. Our approach has been to develop an exact small signal theory and associated code for the analysis of a beam interacting with a slow wave supported by a sheath helix. In this paper we will describe the approximate model for attenuation used in CHRISTINE as well as the exact ID small signal model. Numerical results from both models and comparisons using a C-band helix TWT will be presented.
Efficient Calculation of Impedance Matrices for Vacuum Electronic Device Circuit Structures

We present a computationally efficient method for the calculation of impedance matrices of a large class of standing- and traveling-wave structures used in klystrons, traveling-wave tubes, and other vacuum electronic (VE) devices. By treating the gaps as “lumped ports,” this method avoids the time and disk spaces consuming steps employed in <xref ref-type="bibr" rid="ref1">[1]</xref>, which required postprocessing the electromagnetic fields from a finite-element (FE) simulation. By applying analytical transformations to the impedance matrix, we show that it may be cast in a form suitable for the large-signal 1-D and 2-D beam-wave interaction codes CHRISTINE-CC <xref ref-type="bibr" rid="ref4">[4]</xref>, <xref ref-type="bibr" rid="ref5">[5]</xref> and TESLA-Z <xref ref-type="bibr" rid="ref1">[1]</xref>. These transformations are formulated in a way to avoid numerical errors near structure resonance frequencies (singularity points). We also derive and apply formulas by which the impedance matrix of a structure may be constructed from the impedance matrices of its component parts, without additional FE simulations; by inverting the algebraic operations, we show that the impedance matrix of a structure from which a selected subsection has been removed may also be computed. Application of these formulas greatly facilitates the accurate calculation of the impedance matrices of large complex circuits that are difficult or impossible to model whole in a single FE simulation.
A Structural Equation Model of Feasibility Evaluation and Project Success for Public–Private Partnerships in Hong Kong

A successful public-private partnership (PPP) scheme can be described as one that can lead to the delivery of high-quality end products and/or services, which can satisfy the needs of the community, achieve the intended targets/goals of the government, as well as provide a favorable financial return for the private sector involved with the project. This study aims to establish an evaluation framework for the initial feasibility evaluation of a PPP project that would satisfy all the stakeholders. The factors for evaluating the feasibility of PPP projects can be classified into five broad categories: technical; financial and economic; social; political and legal; and others. Through the structural equation modeling approach, data attained from a questionnaire survey conducted in Hong Kong was analyzed and a model was developed to examine the relationships between different evaluation factors and the overall satisfaction of stakeholders. The results indicate that technical and social aspects are critical to the feasibility of PPP projects, and therefore, are the determining factors for success. This paper should assist relevant stakeholders to improve their understanding on the relative importance of the evaluation factors, and help to establish a comprehensive framework for decision makers to evaluate the feasibility of PPP projects. The predictors for PPP project success were also determined to enrich the knowledge base and help formulate management strategies to better implement the PPP project delivery approach.
A summary of the 2012 JHU CLSP workshop on zero resource speech technologies and models of early language acquisition

We summarize the accomplishments of a multi-disciplinary workshop exploring the computational and scientific issues surrounding zero resource (unsupervised) speech technologies and related models of early language acquisition. Centered around the tasks of phonetic and lexical discovery, we consider unified evaluation metrics, present two new approaches for improving speaker independence in the absence of supervision, and evaluate the application of Bayesian word segmentation algorithms to automatic subword unit tokenizations. Finally, we present two strategies for integrating zero resource techniques into supervised settings, demonstrating the potential of unsupervised methods to improve mainstream technologies.
An Image Acquisition Subsystem For Tactile Vision Substitution

The desired properties of an image acquisition subsystem for Tactile Vision Substitution (TVS) are defined, and the developed subsystem is presented. An effective and practical subsystem has properties such as real-time response and accurate imaging in any realistic situation. The hardware that acquires the visual information is a small autofocusing video camera interfaced to computer electronics. The processing software includes three options for image presentation which will enable future studies for improving object recognition and portable operation. The developed subsystem achieved the desired results and is effective for TVS.
Design, development, and commissioning of a supervisory control and data acquisition (SCADA) laboratory for research and training

This paper reports a state-of-the-art Supervisory Control and Data Acquisition (SCADA) Laboratory facility for power systems at Jamia Millia Islamia, New Delhi, India. It has been designed to function as a research and training center for utilities, faculty members, and students. This paper covers the design, commissioning, and functioning of the SCADA/EMS laboratory facility, based on distributed-processing technology. The SCADA laboratory will provide hands on experience to students and practicing engineers and will give them an insight into the contemporary SCADA systems. This lab is the first of its kind to be functional in India.
Comparison of flux switching and surface mounted permanent magnet generators for aerospace applications

For embedded power generation within civil gas turbine engines, generators are anticipated to endure high rotor speeds coupled with large rotor diameters. With variable frequency permanent magnet generators finding increased roles due to the perceived higher torque density, the issue of rotor integrity becomes a critical issue. Although banding has been previously used in surface mounted PM (SPM) machines, they inevitably increase the airgap and hence reduce the torque capability of the machine. The flux-switching PM (FSPM) machine has been an intense topic of research for many years. By combining its armature and field sources in the stator, its rotor is a passive single piece, salient steel lamination, making it inherently suitable for high speed applications. This paper compares both machines when optimised for high speed applications by designing the rotors of both machines for mechanical integrity and comparing the electromagnetic performance.