nils-herrmann/clean_scirepeval huggingface dataset:
A New Random Switching Technique for the Single Phase Switched Reluctance Motor Drives

This paper proposes a new random switching strategy using DSP TMS320F2812 in order to reduce the harmonics spectra of a single phase switched reluctance machine. The proposed method combines random turn-on, turn-off angle technique and random pulse width modulation technique. A harmonic spread factor (HSF) is used to evaluate the random modulation technique. The experimental results show that the harmonic intensity of output voltage for the proposed method is better than that for conventional methods.
A Wideband InP DHBT True Logarithmic Amplifier

A wideband logarithmic amplifier is demonstrated in this paper using InP-InGaAs double heterojunction bipolar transistor technology. The amplifier uses cascaded gain stages including the limiting and unity amplifiers to achieve a piecewise approximation to the ideal logarithmic response. The performance of 43-dB dynamic range, 22-GHz bandwidth, and <plusmn2-dB log error is achieved. The integrated circuit consumes 650 mW and has a chip dimension of 1times0.8 mm2
A Hybrid Solid State Induction Modulator for klystrons

A solid state induction modulator was designed and operated for the Next Linear Collider accelerator project at SLAC ( to drive 8 X-band klystron. With the redirection of the NLC physics program, the remaining hardware from the DFM (Design for Manufacturability) modulator was combined with existing pulse transformers to fabricate two hybrid solid state induction modulators, one to drive two XK5 klystrons at 420 kV 400 A 1.5 mus and a second modulator to drive a single 5045 klystron to 360 kV 430 A 3.5 mus. These modulators use induction cells to drive a conventional pulse transformer. Both modulator are smaller and operate at a lower operating voltage than a equivalent modulator using thyratron and PFN. The modulator have been fabricated, tested, and are in operation. The design, implementation, and results will be describe in the paper.
Bistatic passive mapping of the field distribution of single element transducer in agar phantom

High intensity focused ultrasound (HIFU) can provide a means of noninvasive ablation or hyperthermia of tissues such as tumors. Real-time monitoring of the progression of the field distribution of the HIFU transducer during treatment is important for localizing the intersection of the beam with the tissue. By continuously visualizing the HIFU field in a tissue, better positioning of the HIFU beam for therapy can be obtained during treatment. To visualize the HIFU field in a tissue, a passive listening technique was employed using beamforming approaches and a linear array system co-aligned with the HIFU source. The passive array made use of the weakly scattered signal from the medium to reconstruct the field pattern of the HIFU field in the medium.
A principled approach to biological motor control for generating humanoid robot reaching movements

This paper presents an application of neurobiological motor principles to the control of humanoid robot reaching movements. The model is mainly based on the hypotheses that the energy of motoneurons signals is continuously minimized along the motion and that dynamic and static efforts are processed separately. This paradigm is used to control the robot HRP2 by considering a dynamic model of the arm including, for each degree of freedom, two second order low-pass filters modeling the neuromuscular system defined by a pair of antagonist muscles. The optimal control problem is solved as a nonlinear programming problem by using a direct transcription method coupled with the optimization software Ipopt. This approach allows to generate realistic movements with anthropomorphic features such as quasi-rectilinear trajectories and bell-shaped velocity.
Balancing Content and Style with Two-Stream FCNs for Style Transfer

Style transfer is to render given image contents in given styles, and it has an important role in both computer vision fundamental research and industrial applications. Following the success ofdeep learning based approaches, this problem has been re-launched very recently, but still remains a difficult task because of trade-of between preserving contents and faithful rendering of styles. In this paper, we propose an end-to-end two-stream Fully Convolutional Networks (FCNs) aiming at balancing the contributions of the content and the style in rendered images. Our proposed network consists ofthe encoder and decoder parts. The encoder part utilizes a FCN for content and a FCN for style where the two FCNs are independently trained to preserve the semantic content and to learn the faithful style representation in each. The semantic content feature and the style representationfeature are then concatenated adaptively and fed into the decoder to generate style-transferred (stylized) images. In order to train our proposed network, we employ a loss network, the pre-trained VGG-I6, to compute content loss and style loss, both of which are efficiently used for the feature concatenation. Our intensive experiments show that our proposed model generates more balanced stylized images in content and style than state-of-theart methods. Moreover, our proposed network achieves efficiency in speed.
All-optical packet header processing scheme based on pulse position modulation in packet-switched networks

In this paper, we investigate all-optical ultrafast pulse-position- modulation (PPM) based header processing scheme for all-optical packet-switched network with up to 32 nodes by means of software simulation. A new routing table and packet header address format based on PPM is proposed, which offers reduced routing table size and the header-processing time. In addition, we show that packet forwarding in multiple transmitting modes is also possible. Simulation results presented demonstrate the working principal of the proposed concept.
An automated design methodology for FPGA-based Multi-Gbps LDPC decoders

Low density parity check (LDPC) codes are error-correcting codes that offer huge advantages in terms of coding gain, throughput and power dissipation. Error correction algorithms are often implemented in hardware for fast processing to meet the real-time needs of communication systems. However hardware implementation of LDPC decoders using traditional hardware description language (HDL) based approach is a complex and time consuming task. This paper presents an efficient automated high level approach to designing LDPC decoders using a collection of high level modelling tools. High data rate Multi-Gbps LDPC decoders have been developed and implemented on FPGA using the proposed methodology. These Multi-Gbps LDPC decoders can be utilized in the latest generation of high data rate wireless communication such as WLAN, WiMAX and DVB-S2.
An adaptive streaming method of 360 videos over HTTP/2 protocol

Nowadays, 360-degree video has become an important component of virtual reality (VR) technology. Unfortunately, this state-of-the-art content type requires a huge bandwidth from a server to a client. In order to solve the bandwidth problem in streaming VR videos over HTTP/2, a dynamic adaptation method is crucial. In this paper, we propose a novel adaptive streaming method based on tiled streaming. By using H.265 standard, a video at the server is divided into spatial tiles, each of which is subdivided into multiple temporal segments. In order to support adaptive streaming method from client, each tile is also encoded into different versions. The priority of tiles is defined based on the user's viewport. Then, the priority feature of HTTP/2 is used to request the server to push the tiles of higher priority first. This ensures that the visible tiles will arrive at the client and be decoded first. Besides, in the case of bandwidth fluctuation, we use the stream termination feature to cancel pushing the tiles that would arrive at the client after their playout deadlines.
Application of raytracing technique for predicting average power distribution in indoor environment

In order to estimate the signal parameters for mobile systems, it is necessary to estimate a systempsilas propagation characteristics through a medium. Propagation analysis provides a good initial estimate of the signal characteristics. The ability to accurately predict radio-propagation behavior for wireless personal communication systems, such as cellular mobile radio, is becoming crucial to system design. Since site measurements are costly, propagation models have been developed as suitable, low-cost, and convenient alternative. The empirical and statistical techniques offer computational simplicity but low accuracy, while the deterministic techniques based on the numerical calculation of electromagnetic field (such as finite difference method, moment method, finite element method, etc.) provide high accuracy but very high computational intensity. The ray-tracing technique, which speeds up the computation while maintaining the reasonable accuracy, is an appropriate selection. In this paper, we develop a software program for predicting distribution of average power in indoor wireless communications based on ray-tracing technique. The efficiency of the proposed software program is shown in numerical results and is verified by measurement results.
DASC: Robust Dense Descriptor for Multi-Modal and Multi-Spectral Correspondence Estimation

Establishing dense correspondences between multiple images is a fundamental task in many applications. However, finding a reliable correspondence between multi-modal or multi-spectral images still remains unsolved due to their challenging photometric and geometric variations. In this paper, we propose a novel dense descriptor, called dense adaptive self-correlation (DASC), to estimate dense multi-modal and multi-spectral correspondences. Based on an observation that self-similarity existing within images is robust to imaging modality variations, we define the descriptor with a series of an adaptive self-correlation similarity measure between patches sampled by a randomized receptive field pooling, in which a sampling pattern is obtained using a discriminative learning. The computational redundancy of dense descriptors is dramatically reduced by applying fast edge-aware filtering. Furthermore, in order to address geometric variations including scale and rotation, we propose a geometry-invariant DASC (GI-DASC) descriptor that effectively leverages the DASC through a superpixel-based representation. For a quantitative evaluation of the GI-DASC, we build a novel multi-modal benchmark as varying photometric and geometric conditions. Experimental results demonstrate the outstanding performance of the DASC and GI-DASC in many cases of dense multi-modal and multi-spectral correspondences.
Block Clustering Based on Difference of Convex Functions (DC) Programming and DC Algorithms

We investigate difference of convex functions (DC) programming and the DC algorithm (DCA) to solve the block clustering problem in the continuous framework, which traditionally requires solving a hard combinatorial optimization problem. DC reformulation techniques and exact penalty in DC programming are developed to build an appropriate equivalent DC program of the block clustering problem. They lead to an elegant and explicit DCA scheme for the resulting DC program. Computational experiments show the robustness and efficiency of the proposed algorithm and its superiority over standard algorithms such as two-mode K-means, two-mode fuzzy clustering, and block classification EM.
A Performance Analysis of Deflection Routing and FDLs with Wavelength-Based QoS in OBS Networks

In Optical Burst Switching Network, contention is one of the challenging problems. Contention occurs when more than one burst demand for same output wavelength channel in same time. The deflection routing, fiber delay line (FDL) and wavelength conversion are the methods used to resolve contention in OBS Networks. With deflection routing, contending bursts in send in another route rather than primary route towards it's destination. In this case of wavelength conversion if any contentions occur then one of the burst's wavelength have to be change from its current wavelength to another free wavelength channel. And, FDLs is usual used to provide an extra offset time for deflected burst since deflection route is commonly longer than primary one. This paper is propose a modeling analysis of deflection routing and FDLs with wavelength-based QoS management using Queueing theory to resolving contention problem in OBS Network. Analysis results show that proposed model reduce blocking probability in comparison with models before.
Design of a 70 GHz Power Amplifier using a Digital InP HBT Process

A +15.1 dBm power amplifier (PA) operating at 70 GHz designed in a high speed digital InP HBT process is presented. The extraction of device models for the HBT's used in the PA design is discussed along with an electromagnetic simulation accounting for layout parasitics in the power cells. The design employs single-stage cascode amplifier topology in a finite ground CPW transmission line environment. The amplifier demonstrates the possibilities of utilising high speed digital InP HBT processes in the design of high frequency power amplifiers.
A regularized spectral algorithm for Hidden Markov Models with applications in computer vision

Hidden Markov Models (HMMs) are among the most important and widely used techniques to deal with sequential or temporal data. Their application in computer vision ranges from action/gesture recognition to videosurveillance through shape analysis. Although HMMs are often embedded in complex frameworks, this paper focuses on theoretical aspects of HMM learning. We propose a regularized algorithm for learning HMMs in the spectral framework, whose computations have no local minima. Compared with recently proposed spectral algorithms for HMMs, our method is guaranteed to produce probability values which are always physically meaningful and which, on synthetic mathematical models, give very good approximations to true probability values. Furthermore, we place no restriction on the number of symbols and the number of states. On various pattern recognition data sets, our algorithm consistently outperforms classical HMMs, both in accuracy and computational speed. This and the fact that HMMs are used in vision as building blocks for more powerful classification approaches, such as generative embedding approaches or more complex generative models, strongly support spectral HMMs (SHMMs) as a new basic tool for pattern recognition.
A 10 Mb/s visible light communication system using a low bandwidth polymer light-emitting diode

In this paper we experimentally demonstrate a 10 Mb/s error free visible light communications (VLC) system using polymer light-emitting diodes (PLEDs) for the first time. The PLED under test is a blue emitter with ~600 kHz bandwidth. Having such a low bandwidth means the introduction of an intersymbol interference (ISI) induced penalty at higher transmission speeds and thus the requirement for an equalizer. In this work we improve on previous literature by implementing a decision feedback equalizer, rather than a linear equalizer. Considering 7% and 20% forward error correction codes, transmission speeds up to ~12 Mb/s can be supported.
A smart meeting room scheduling and management system with utilization control and ad-hoc support based on real-time occupancy detection

In most meeting room scheduling or management system, the availability of meeting rooms are mainly based on pre-determined schedules. However, since the meeting duration is not always exact as it is scheduled, there are some situations that a meeting room is underutilized. Therefore, in this paper, we present a smart meeting room scheduling and management system which detect occupancy status of meeting rooms in realtime and integrate this information into the scheduling application to support ad-hoc meetings and increase room utilization. Our system is a simple, ease-of-implementation solution based on PIR sensor fusion devices and Ethernet connectivity. Occupancy data is sent to a central application server by UDP over IP protocols. On this server, a web application is developed and hosted to not only allow people book rooms for their meetings, but also check the utilization of these rooms based on predefined policies. The system also supports ad-hoc meetings by providing real-time availability of meeting rooms to users.
A solid state induction modulator for SLAC NLC

The Next Linear Collider accelerator proposal at SLAC requires a high efficiency, highly reliable, and low cost pulsed-power modulator to drive the 500 KV, 260A X band klystrons. With a pulse width of less than 1.5 microseconds, it is difficult for the present SLAC type modulator with conventional pulse transformer to have a high efficiency due primarily to the inherently slow rise and fall time of the video pulse. The proposed induction modulator utilises a pulse transformer similar to an induction accelerator driven by solid state high voltage IGBTs. The performance of the IGBTs, induction cores and a low voltage model will be discussed as well as the design and construction of a prototype modulator capable of driving up to 8 of the X band klystrons.
Channel estimation algorithms for DS/BPSK-CDMA communications systems

Different channel estimation algorithms for direct-sequence code-division multiple-access (DS/CDMA) communications systems using binary phase-shift-keying (BPSK) modulation and a RAKE receiver are evaluated under fading multipath conditions. Two strategies are considered: the transmission of a pilot signal in the downlink and the block organization of the data in the uplink. The performance degradation of the system is due mainly to inaccurate estimation of the complex amplitudes rather than the delays; it remains low when using pilot signals with averaging filters or combining preamble information with symbol estimation.
Assessing SAR tomography BIOMASS retrieval method at a mountainous tropical forest

The 7-th ESA Earth Explorer, BIOMASS is a synthetic aperture radar (SAR) which will collect data from employing a multiple baseline orbit during the initial phase of its lifetime. This data can be used for tomographic SAR (TomoSAR) processing resulting in a vertical resolution of about 20 m, sufficient to decompose the backscatter from most tropical forests into two to three layers. A recent study using airborne data from the TropiSAR campaign at the site of Paracou, French Guiana, showed that this information significantly improves the retrieval of forest above-ground biomass (AGB), resulting in an accuracy of about 10% of AGB at a resolution of 1.5-ha. In this paper, we generalize this result, by applying the same algorithm to the Nouragues test site in central French Guiana. This site is characterized by a hilly terrain and an AGB ranging from 150 to 600 t/ha. The relationship between AGB and TomoSAR data at Nouragues was found to be highly similar to the one observed at Paracou. We found that the best correlation between the backscatter signal and AGB is held in the upper canopy layer (i.e. 20-40 m). Cross validation using training plots from Nouragues and validation plots from Paracou, and vice versa, resulted in an accuracy of about 16%-18% of AGB using 1-ha plots. This result suggests that the TomoSAR AGB retrieval method is generalizable to other study sites. In addition we show that, TomoSAR can be used to estimate the canopy height with an error of less than 4 m with forest height ranging from 20 m-40 m.
A 3D model to characterize high-frequency scattering: Applied to synthesize SAR data

In this paper, we propose a 3D propagation model to characterize the scattering far-field by a scenario at high-frequency bands. The proposed scenario is composed of a 1-in-1 corner reflector bestowed between two metallic plates representing walls. Two identical broadband radars are used as transmitter and receiver in bistatic mode. This model is based on a Ray-Tracing (RT) technique combined with the asymptotic method Uniform Theory of Diffraction (UTD). It is practical not only in explicating the propagation mechanisms through the observed area, but also in determining the amplitude and the phase of any point in the scattered far-zone above the ground. In order to validate the model, we have conducted some comparisons with the 33–37GHz indoor measurements in the anechoic chamber. These comparisons have shown that the model can predict precisely the target location. Thus we apply it to synthesize data for evaluating SAR imaging algorithms.
Building earthquake semantic network by mining human activity from Twitter

Since there is 87% of chance of an approximately 8.0 Richter earthquake occurring in the Tokai region of Japan in next 30 years; we are trying to help computers to recommend the most suitable action patterns for the victims if this massive disaster happens. For example, the computer will recommend “what should do to go to a safe place”, “how to come back home”, etc. To realize this goal, it is necessary to have a collective intelligence of action patterns, which relate to the earthquake. Additionally, to help the computers understand the meaning of these action patterns, we should build the collective intelligence based on OWL (Web Ontology Language). However, the manual construction of the collective intelligence will take a large cost. Therefore, in this paper, we firstly design an earthquake semantic network. Secondly, we propose a novel approach, which can automatically collects the action patterns from Twitter for the semantic network.
300 GHz InP DHBT large signal model including current blocking effect and validated by Gilbert multiplier circuits

This paper describes a modeling approach for Vitesse VIP2 300 GHz InP/InGaAs DHBT technology, including the nonlinear effects in base-collector region covering current blocking, velocity modulation and self-heating. Model is verified in terms of single devices and integrated circuits. Good model fitting to measured DC and S-parameters data from single HBTs is achieved, and several circuits based on Gilbert multiplier are designed for the purposes of model validation and high-speed applications. Nonlinear properties of these circuits are measured and compared with the simulation results from different bipolar transistor models. The variable gain amplifier reported in this paper achieves the highest gain-bandwidth product of over 520 GHz under the limitation of measurement capability.
Association-based recommender system using statistical implicative cohesion measure

The strength of the association rule-based approach compared to other approaches in building recommender systems is that it can provide the deep explanations. Besides, evaluating the quality of generated rules to obtain the better recommendations is also necessary. This can be completed by using the statistical implicative cohesion measure - a measure used for finding the rules with strong implicative relationships. The higher the cohesion value of a rule is, the better the quality of that rule is. This paper proposes a new approach based on the association rules and the cohesion measure to discover the tendencies in a data set and recommend the top items to a user. The proposed recommender system is tested on the data sets Groceries and CourseRegistration. Depending on the purpose of users, they can change the thresholds on the measure to observe the tendencies as well as to get the top recommendations.