nils-herrmann/clean_scirepeval huggingface dataset:
A hybrid Fuzzy-PI cascade controller for transient stability improvement in DFIG wind generators

Doubly-Fed Induction Generator (DFIG) Wind Turbine (WT) can be affected by power system faults and requires crowbar protection. When the crowbar is triggered, the rotor is short circuited over the crowbar impedance, the DFIG operates as a Squirrel-cage Induction Generator (SCIG) that tends to drain large amount of reactive power from the grid during fault, potentially causing a voltage drop. In this research, therefore, we propose the use of DFIG based Low-voltage-Ride-Through (LVRT) scheme including crowbar, PSS (Power System Stabilizer), RSC (Rotor-side converter) and GSC (Grid-side converter) in order to enhance the transient stability of a grid-connected DFIG. A hybrid cascade Fuzzy-PI based controlling technique is introduced to control the Insulated gate Bipolar Transistor (IGBT) based frequency converter to enhance the transient stability. In the simulations here presented, the proposed control scheme is investigated by comparing the performance of the DFIG system with and without LVRT and damping control scheme.
A reordering model for Vietnamese-English statistical machine translation using dependency information

Reordering is a major challenge in machine translation (MT) between two languages with significant differences in word order. In this paper, we present an approach to learn reordering rules as pre-processing step based on a dependency parser in phrase-based statistical machine translation (SMT) from Vietnamese to English. Dependency parser and transformation rules are used to reorder the source sentence and applied for systems translating Vietnamese to English. We evaluated our approach on Vietnamese-English machine translation tasks, and showed that it outperform the baseline phrase-based SMT system.
10.8 A multi-standard 2G/3G/4G Cellular modem supporting carrier aggregation in 28nm CMOS

Mobile networks today are divided into multiple radio access technologies (RATs) scattered over a variety of frequencies and functionality depending on the network region. The scattered networks require that the digital baseband for mobile user equipment handle multiple RATs, multiple bands, as well as seamlessly transition between these. In 3GPP release 10  the problem with scattered frequency bands has been addressed by the possibility to aggregate spectrum from two separated carriers to create a wider aggregated total bandwidth. Which carriers to combine depends on the spectrum available to the specific operator.
An EMR of Tire-Road Interaction Based-On "Magic Formula" for Modeling of Electric Vehicles

Energetic Macroscopic Representation (EMR) has become more and more powerful tool to model and control the multi-physical systems. In literature, the well-known "magic formula" of Pacejka seems to be not adequately presented in EMR due to the conflict of energy balance. In this paper, the authors propose an EMR of tire-road interaction using Pacejka's model. The advantage of the proposed description is in two aspects: (i) the action - reaction principle of EMR based-on energy balance is preserved; and (ii) we use the "magic formula" of Pacejka's model which is familiar with vehicle motion control engineers. The effectiveness of this representation is confirmed by simulation in MATLAB/SIMULINK environment.
A new scheme to support voice call over wireless multi-channel MAC protocol

This paper presents a new scheme to support voice calls over a wireless multichannel MAC protocol (VMcMAC). We increase the voice capacity of wireless networks by reducing protocol overhead and interference between voice traffic and data traffic. Voice calls are allocated to specific reserved channels in a distributed TDMA fashion. Each voice node visits the voice channel with a fixed frequency and then transmits a voice frame without sending control messages. With this scheme, we exploit multichannel nature of 802.11 standards to significantly reduce the protocol overhead and avoid most of the interference between voice and data traffic. Our simulation results show a significant improvement in the voice capacity of wireless Ad-hoc networks.
Breaking the Gridlock of Spatial Correlations in GPS-Aided IEEE 802.11p-Based Cooperative Positioning

Spatial correlations found in vehicular mobility are jeopardizing the precision level of cooperative positioning for future Cooperative Intelligent Transport System (C-ITS) applications. Bayesian filters traditionally assume independence of the measurement noise terms over space between different vehicles and over time at each vehicle, whereas they are actually correlated due to the local continuity of physical propagation phenomena (e.g., shadowing, multipath, etc.) under highly constrained vehicular mobility. In this paper, we break this gridlock by proposing an innovative data fusion framework capable of mitigating these effects to maintain the positioning precision level under severely correlated environments. We first illustrate the dramatic impact of correlated noise affecting both global positioning system and vehicle-to-vehicle (V2V) received power observations. Then, we propose a new generic data fusion framework based on a particle filter supporting three complementary methods to decorrelate measurement noises in a globally asynchronous context. Compared with conventional cooperative positioning, simulations performed in canonical vehicular scenarios (highway, urban canyon, tunnel) show that our proposed approach could provide up to 60% precision improvement in correlated environments, while matching by less than 15-20% deviation, an optimal cooperative positioning scheme considered under independent measurements.
Classification of rice fields in a complex land-use watershed in Northern Vietnam using RADARSAT-2 data

Due to the strong temporal backscatter signature when the rice grows above the water surface, Synthetic Aperture Radar (SAR) for paddy rice crop mapping is operational in Southern Vietnam (Mekong Delta). In Northern Vietnam, the rice mapping using SAR is a challenge and is rarely performed because of the complex land-use/land-cover. Nevertheless, the information of rice fields is important for hydrological simulation in the studied watershed. The purpose of the research is to adapt the classification methods and algorithms to monitor rice fields over a large and fragmented land-use area as the Câu River watershed, in northern Vietnam. RADARSAT-2 data were collected in dual-pol Standard and quad-pol Fine mode for two rice crop seasons. As result, RADARSAT-2 dual- and quad-pol data have demonstrated their capabilities to identify the cultivated rice fields. However, RADARSAT-2 dual-pol data in Standard mode could not identify all the rice fields identify by the quad-pol data in Fine mode.
A Data Transferring Model for Micro-scale Urban Air Quality Management System

Today, the environmental observing systems are no longer strange to the people, and they are playing an important role in e-sciences, especially in researches about earthquake, climate, air pollution, etc. To be named as Airscope , this micro-scale air quality management system deals with unexpected pollution events in small scope, by using CFD-based air quality modeling [2], USN-based sensor monitoring model, DataTurbine middleware , multi-model interaction platforms and devices. Because of these complicated heterogeneity tools and devices, data transferring inside this project is very important and is a backbone for the whole system. In this paper, we will briefly introduce Airscope project and its elements, our indoor testbed and especially the data flows inside. We also describe about an extended actual system to apply in reality such as a small area in modern urban.
Concatenated image completion via tensor augmentation and completion

This paper proposes a novel framework called concatenated image completion via tensor augmentation and completion (ICTAC), which recovers missing entries of color images with high accuracy. Typical images are second-or third-order tensors (2D/3D) depending if they are grayscale or color, hence tensor completion algorithms are ideal for their recovery. The proposed framework performs image completion by concatenating copies of a single image that has missing entries into a third-order tensor, applying a dimensionality augmentation technique to the tensor, utilizing a tensor completion algorithm for recovering its missing entries, and finally extracting the recovered image from the tensor. The solution relies on two key components that have been recently proposed to take advantage of the tensor train (TT) rank: A tensor augmentation tool called ket augmentation (KA) that represents a low-order tensor by a higher-order tensor, and the algorithm tensor completion by parallel matrix factorization via tensor train (TMac-TT), which has been demonstrated to outperform state-of-the-art tensor completion algorithms. Simulation results for color image recovery show the clear advantage of our framework against current state-of-the-art tensor completion algorithms.
An MMSE-based beamforming algorithm for smart antenna applied to an MC-CDMA system with co-channel interference

This paper proposes an adaptive beamforming algorithm, called MC-MMSE, for adaptive antennas applied to an MC-CDMA system. A new method for updating the weight vector based on the MSE criterion is derived. Computer simulations show that the MC-MMSE algorithm is capable of rejecting co-channel interference that affects the MC-CDMA system. Thus, the BER performance of the MC-CDMA system is much higher than that of the MC-CDMA system without using adaptive antenna and that of the DS-CDMA system with adaptive antenna in multipath Rayleigh fading channel.
An Empirical Study on the Impact of Changing Weather Conditions on Repeat-Pass SAR Tomography

Researches carried out in the last years have shown that the use of P-band SAR tomography (TomoSAR) largely improves the retrieval of the above-ground biomass (AGB) in tropical forests, providing a most encouraging element toward the systematic employment of TomoSAR techniques in the frame of the upcoming spaceborne mission BIOMASS. All of these researches were carried out using campaign data acquired in a single day, and under stable (mostly sunny) weather conditions. The impact of temporal decorrelation was considered in the literature by analyzing ground-based Radar data from the TropiSCAT campaign (Paracou, French Guiana), and found not to be a show-stopper for BIOMASS tomography. Yet, the validity of this analysis was limited to sunny days only. Accordingly, a precise assessment of the impact of changing weather conditions on TomoSAR is currently missing. The aim of this paper is to provide a first experimental element to fill this gap. To do this, data from the TropiSCAT archive are reprocessed to mimic BIOMASS repeat-pass tomography. Since BIOMASS tomography will be implemented by taking seven acquisitions with a revisit time of three days, we form tomograms by taking two TropiSCAT antennas every three days (and three antennas on the last day), which means that any single tomogram is actually obtained by mixing seven different days and under different weather conditions. The quality of tomographic imaging is then assessed by evaluating the observed backscattered power fluctuations in the tomogram time series. While imaging quality is observed to degrade by mixing different days, the resulting temporal variations of the backscattered power in the canopy layer are within 1.5-dB rms in cross polarization. For this forest site, this error is translated into an AGB error of about 50–100 t/ha, which is 20% or less of forest AGB.
A Data-Scheduling Mechanism for Multi-Homed Mobile Terminals with Disparate Link Latencies

A mobile terminal equipped with multiple network interfaces can often be found under coverage of multiple access networks. Multihoming enables mobile terminals to communicate simultaneously through multiple interfaces. Connection-oriented transport layer mechanisms ensure reliable, in-order delivery of data, however parallel data transfers in multihoming face problems due to out-of-order reception of data which causes fast-retransmissions and limit the communication throughput. In this paper, we propose a transport layer based mechanism which stripes one flow''s data across multiple disjoint paths efficiently, reducing possible occurrence of out-of-order data. Our mechanism estimates arrival times of data packets to be sent through available paths in an association, and decides which packets are to be sent through each path. We compared our mechanism with a relatively closer approach called Westwood SCTP. We illustrate with the help of simulation results that our mechanism proves to improve multipath communication.
A Dynamic Bayesian Framework for Motion Segmentation

Dynamic textures are sequences of images of moving scenes in time that are common in natural scenes and play an important role in video content analysis. This paper presents a new dynamic Bayesian framework for segmentation of dynamic textures. First, we formulate the problem in the Bayesian framework using mixture model theory. The major advantage of our approach is that it provides a natural way to cluster data based on the components of the mixture that generated it. Second, in order to model the distribution of observed data, only grayscale information is taken into consideration of the existing mixture models. In order to overcome this problem, a new distribution is presented in this paper. The advantage of the proposed distribution is that it has the flexibility to fit different kinds of observed data and is more reliable for changes of noise and contrast levels. Finally, expectation maximization (EM) algorithm is adopted to maximize the lower bound on the data log-likelihood and to optimize the parameters. The proposed model is successfully compared to the state of the arts dynamic texture segmentation approaches. Numerous experiments are presented where our model is tested on various simulated and natural real-world dynamic textures.
A Model for Predicting Transition in Railgun Fiber Brush Armatures

The PEGASUS railgun at the French-German Research Institute of Saint-Louis is capable of launching 0.3-kg projectiles with muzzle velocities greater than 2500 m/s without mechanical failure of the sabot which is made of fiber-reinforced plastics. Unfortunately, for these high velocities, the metallic fiber brush armature shows contact transition. One of the main long-term objectives is to improve the railgun performance by delaying this armature transition, leading to an increase of the overall railgun efficiency and a reduction of the rail erosion. In order to obtain a better understanding of the transition mechanisms, several series of PEGASUS shots were examined with projectile masses ranging from 250 g up to 2 kg. As a result, a model was developed in order to predict the transition. It determines the mass loss of the brush armature due to electrical heating, mechanical shearing, and viscous heating. It can be shown for the low-weight high-velocity projectiles that friction heating becomes a predominant transition mechanism. For the 13-stage PEGASUS railgun, the transition model was implemented in a lumped parameter simulation code which takes into account the time-dependent armature voltage drop and the armature mass loss. The comparison of the computed transition time with measured values shows a very good agreement.
A polarization-reconfigurable filtering antenna system: a visual approach to investigating the bandwidth of transmission lines with non-z0 impedance [education column]

The Education Column publishes project reports from f nalists in the AP-S Student Design Challenge. In this issue, we present the report from the 2013 team from the School of Electrical and Electronics Engineering at Nanyang Technological University, Singapore: Theng Huat Gan, Zaifeng Yang, Eng Leong Tan, Jun Xian Lim, Minh Quan Huynh, and Moody Mayank. The challenge was to develop a system with reconf gurable antenna elements that could adapt to different propagation conditions to achieve the best link performance.
A high-performance AlGaAs/InGaAs/GaAs pseudomorphic MODFET-based monolithic optoelectronic receiver

A monolithically integrated optoelectronic receiver based on the pseudomorphic InGaAs on GaAs material system has been fabricated and tested for the first time. Quarter-micrometer modulation-doped field-effect transistors (MODFETs) with f/sub t/'s of 66 GHz are used in the two-stage transimpedance amplifier design. The circuit utilizes all active components including a metal-semiconductor-metal (MSM) photodetector and a common-gate FET active feedback resistor.<<ETX>>
Compact metamaterial CPW-fed WLAN antenna

A novel compact metamaterial antenna for wireless area local network (WLAN) applications is proposed in this paper. The antenna is fed by a co-planar waveguide (CPW). Size reduction of the antenna is achieved thanks to the use of a modified conventional composite right/left handed (CRLH) model without vias. As a result, the antenna demonstrates a good size reduction in comparison with the conventional patch antenna resonating at 2.4 GHz. In order to investigate the merits of proposed model, both antennas are simulated and fabricated. Experimental results show a good agreement between the simulated and measured parameters.
A robust algorithm for detection and classification of traffic signs in video data

The accurate identification and recognition of the traffic signs is a challenging problem as the developed systems have to address a large number of imaging problems such as motion artifacts, various weather conditions, shadows and partial occlusion, issues that are often encountered in video traffic sequences that are captured from a moving vehicle. These factors substantially degrade the performance of the existing traffic sign recognition (TSR) systems and in this paper we detail the implementation of a new strategy that entails three distinct computational stages. The first component addresses the robust identification of the candidate traffic signs in each frame of the video sequence. The second component discards the traffic sign candidates that do not comply with stringent shape constraints, and the last component implements the classification of the traffic signs using Support Vector Machines (SVMs). The main novel elements of our TSR algorithm are given by the approach that has been developed for traffic sign classification and by the experimental evaluation that was employed to identify the optimal image attributes that are able to maximize the traffic sign classification performance. The TSR algorithm has been validated using video sequences that include the most important categories of signs that are used to regulate the traffic on the Irish and UK roads, and it achieved 87.6% sign detection, 99.2% traffic sign classification accuracy and 86.7% overall traffic sign recognition.
Assessing a requirements evolution approach: Empirical studies in the Air Traffic Management domain

Requirements evolution is still a challenging problem in engineering practices. This paper presents a family of empirical studies about the applicability and usefulness of an approach for modeling evolving requirements. The empirical studies involved different categories of users (researchers, master students and domain experts) who have applied the approach to a real industrial evolutionary scenario drawn from the Air Traffic Management (ATM) domain. The results from the studies demonstrated the usefulness of the approach for requirements evolution in complex industrial settings such as the ones in the ATM domain. Furthermore, the validation provided us useful insights about the problem of requirements evolution faced in different industrial contexts.
An IDPSO algorithm-based application mapping method for Network-on-Chips

Application mapping is one of the most challenging issues in designing Network-on-Chips, playing an important role in maximizing the performance of NoC based systems. This paper presents a novel method to map applications onto a targeted NoC architecture using Improved Discrete Particle Swarm Optimization (IDPSO) algorithm. The NOXIM platform has been used to evaluate the efficiency of the proposed method in terms of latency, throughput, and power energy. The obtained results show that the proposed method can help the designers to get better performance for NoC based systems. This information is very useful for designers to decide how they should do in the next steps of designing a real-time system.
Assessment of the P- and L-band SAR tomography for the characterization of tropical forests

The objective of this paper is to provide a better understanding of tomographic capabilities in characterization of dense forested areas at P-and L-band. The analysis is carried out on airborne data acquired by ONERA over the site of Paracou, French Guyana, during the ESA campaign TropiSAR. The results shown support the idea that ground- and -volume interactions play a negligible role at L-band, whereas they are significant at P-band. For a dense forest of 30 m and more, there is very weak ground contribution at L-band. The L-band tomographic profile is quite disturbed as compared to the P-band profile in dense tropical forest areas. In this condition, the use of tomographic imaging at L-band in tropical forests appears limited. However, when the forest top height is roughly below 20 m (e.g., in forest regrowth), the tomographic results are expected to be the same as in boreal forests. Whereas P-band tomography allow us to retrieve the whole forest vertical structure, better characterizing of the ground and/or volume scatterings and providing an unique solution in high biomasss ranging from 150-600 t/ha.
A Versatile Control Plane for EPON-based FTTX Access Networks

The Ethernet PON (EPON), standardized by the IEEE Ethernet First Mile Alliance, is viewed by many as an attractive solution to deliver very high-speed broadband access. While downstream traffic is broadcasted to all customers, the access of upstream traffic to the fiber has to be arbitrated in order to avoid collisions. This is achieved by designing both a Dynamic Bandwidth Assignment (DBA) that shares bandwidth opportunities between customers, and a scheduling policy, which is used by customers to take advantage of the allocated bandwidth opportunities. The DBA and the settings of the scheduling policy are part of the control plane of the PON, and thus characterize which types of services can be supported by the operator. EPON are widely deployed in some geographical areas, but usually offer a simple Best Effort access network. This paper proposes a versatile control plane for EPONs that can be configured to support either a classless Best Effort network, or several relative Classes of Services, or a mix of committed bandwidth and Best Effort services. This control plane includes a framework for enforcing Service Level Agreements, and fairly sharing available resources. The paper also addresses the issue of Connection. Acceptance Control for EPONs and explains its relationship with the DBA. The proposed framework is easily configured (all the control being centralized at the OLT or in the backbone) while allowing the support of large varieties of services.
A Comparison of Graph Embedding Methods for Vertex Nomination

Given an attributed graph representation of data, vertex nomination works to find the group of vertices which are of interest, e.g., those vertices whose attributes are different from others', or the connection among those vertices are more frequent. In this paper we present an algorithm to estimate the power of nominating these interesting vertices. This algorithm is based on Wilcoxon rank sum test. It requires to embed graph vertices into a low dimensional space. Two graph embedding methods, adjacency spectral embedding and multidimensional scaling composed with canonical correlation analysis are employed. We investigate a case where two graphs are available for modeling the same objects in different spaces, and show the effects of data fusion on vertex nomination power.