nils-herrmann/clean_scirepeval huggingface dataset:
Document image compression by subband system

With the advance of optical storage devices, a large amount of office documents can be stored in the form of scanned images which allow a more efficient retrieval system and ease of handling. Image compression is applied to increase the storage efficiency. Traditionally, a subband system has suffered from basis related visual artifacts. Since the document image contains mainly sharp characters and drawings on a monochrome background, strong ringing is expected as the image contains strong edges. The ringing effect is further worsened by the lack of a noise masking background. In this paper, a subband filter with nonnegative scaling functions and small mean square spatial width is considered to suppress the ringing effect and provide good spatial localization for sharp edge reconstruction. A quantization scheme is investigated to exploit the characteristics of the document image for more visually pleasing results. Design examples with high spatial localization property and their application in document image coding are presented.
Real-time sign language fingerspelling recognition using convolutional neural networks from depth map

Sign language recognition is important for natural and convenient communication between deaf community and hearing majority. We take the highly efficient initial step of automatic fingerspelling recognition system using convolutional neural networks (CNNs) from depth maps. In this work, we consider relatively larger number of classes compared with the previous literature. We train CNNs for the classification of 31 alphabets and numbers using a subset of collected depth data from multiple subjects. While using different learning configurations, such as hyper-parameter selection with and without validation, we achieve 99.99% accuracy for observed signers and 83.58% to 85.49% accuracy for new signers. The result shows that accuracy improves as we include more data from different subjects during training. The processing time is 3 ms for the prediction of a single image. To the best of our knowledge, the system achieves the highest accuracy and speed. The trained model and dataset is available on our repository1.
Optimal Motion Compensation for Low Bit Rate Wavelet Based Error Frame Coding

Wavelets can be used effectively in spatial scalable video coding while maintaining the classical predictive loop for temporal correlation exploitation. At low bit rates, however, the choice of the best parameters for motion compensation is not straightforward. This paper analyzes the dependence of the optimum parameters on the target bit rate. A fast algorithm towards optimal block based motion compensation in the case of frame error coding through wavelets is also presented
Performance comparison between tracking and fixed photovoltaic system: A case study of Hoa Lac Hi-tech Park, Hanoi

Vietnam has declared its first official support mechanisms for the development of solar power projects by the Decision 11/2017/QD-TTg, officially signed by the Prime Minister of Vietnam in April 2017. The Decision creates a legal framework for solar energy market and promotes solar electricity development in Vietnam. Since 2016, Energy Department of the University of Science and Technology of Hanoi has been implementing a 15 kWp grid-connected photovoltaic (PV) system in Hanoi. The PV array performance is mostly influenced by its tilt angle, orientation, climatic conditions and geographic location. From simulated results, this paper aims to evaluate the performance comparison between a PV automatic tracking system and a PV fixed mounting system on identical PV arrays with the same rated powers in a one-year period, under similar environmental conditions and installed location. Firstly, the architectural design of the entire system is going to be described. Next, the energy outputs of the fixed and tracking system are analyzed by using the PVsyst software as a simulation tool . This work examines the maximum performance of the PV output during the early stage of the system design by adjusting the optimum titled angle of the PV modules monthly, seasonal and yearly for non-tracking PV arrays. Then, the results are compared with the performance of automatic tracking systems. The study confirmed that the automatic single North-South axis tracker, which continuously tracks the sun from East to West, is the most suitable for PV system at Hoa Lac Hi-tech Park in the north of Vietnam, in the tropical zone.
Hardware-in-the-Loop approach to the development and validation of precision induction motor servo drive using xPC Target

The development of a Hardware-in-the-Loop (HiL) simulation platform for precision induction motor (IM) servo drive development, evaluation and testing of various control architectures is described in this paper. The platform uses industrial graded hardware components, i.e. Mitsubishi IGBT inverter, 3-phase induction motor and incremental optical encoder as well as various measurement sensors. Its main computational core is implemented using an xPC Target platform which enables rapid validation, prototyping and deployment of various control algorithms via Matlab & Simulink.
Integer fast Fourier transform (INTFFT)

The concept of integer fast Fourier transform (IntFFT) for approximating the discrete Fourier transform is introduced. Unlike the fixed-point fast Fourier transform (FxpFFT), the new transform has properties that it is an integer-to-integer mapping, power-adaptable and also reversible. A lifting scheme is used to approximate complex multiplications appearing in the FFT lattice structures. Split-radix FFT is used to illustrate the approach for the case of 2/sup N/-point FFT. The transform can be implemented by using only bit shifts and additions but no multiplication. While preserving the reversibility, the IntFFT is shown experimentally to yield the same accuracy as the FxpFFT when their coefficients are quantized to a certain number of bits. Complexity of the IntFFT is shown to be much lower than that of the FxpFFT in terms of the numbers of additions and shifts.
Adaptive In-Loop Prediction Refinement for Video Coding

Modern video compression codecs achieve high compression efficiency by exploiting the temporal and spatial redundancies present in video sequences. Although state of the nit block based intra and inter prediction have been refined to better adapt to the content in the scene, they still exhibit limitations in fully extracting information from the decoded data. We propose the addition of an in-loop prediction refinement stage that is initialized with the conventional intra or inter predicted result and is capable of further reducing the spatial redundancies present in the sequence. By extracting additional information from the decoded neighborhood, the refinement stage is able to bring the prediction closer to the original data, thus improving compression efficiency. In this work, we study one possible method of refinement for the particular case of intra prediction. This uses sparse decomposition of blocks that overlap decoded neighboring blocks and the current predicted block in order to make prediction more coherent with already encoded data.
A single layer high gain Fabry-Perot cavity antenna

A single layer and single feed high gain Fabry-Perot cavity type antenna is presented in this paper. The antenna is designed to operate at around 22 GHz so that it can be used for K-band applications. An open-ended leaky-wave slit dipole fed by a coplanar waveguide is printed on one side of the substrate whereas a frequency selective surface made of a circular hole array is defined on another side of the substrate; thus forms a substrate-integrated Fabry-Perot cavity. The simulation results show that the proposed feeding structure exhibits a wide impedance bandwidth characteristic and effectively excites the resonance of the substrate cavity simultaneously. After optimization, the antenna is capable of having an impedance bandwidth (VSWR≤2) of about 8%, a maximum gain of about 14 dBi, and a 3-dB gain bandwidth of approximately 1.5% at a resonance frequency of 21.7 GHz.
Analysis of Crosstalk in 3D Circularly Polarized LCDs Depending on the Vertical Viewing Location

Crosstalk in circularly polarized (CP) liquid crystal display (LCD) with polarized glasses (passive 3D glasses) is mainly caused by two factors: the polarizing system including wave retarders and the vertical misalignment (VM) of light between the LC module and the patterned retarder. We show that the latter, which is highly dependent on the vertical viewing location, is a much more significant factor of crosstalk in CP LCD than the former. There are three contributions in this paper. Initially, a display model for CP LCD, which accurately characterizes VM, is proposed. A novel display calibration method for the VM characterization that only requires pictures of the screen taken at four viewing locations. In addition, we prove that the VM-based crosstalk cannot be efficiently reduced by either preprocessing the input images or optimizing the polarizing system. Furthermore, we derive the analytic solution for the viewing zone, where the entire screen does not have the VM-based crosstalk.
Interpolated Mth-band filters for image size conversion

Image/video size conversion at variable rates requires that a large set of interpolation filters should be stored in a table. We present the interpolated Mth-band filters as the interpolation filters, which are obtained from the cubic spline interpolation of a prototype M/sub p/th-band eigenfilter. The proposed filter can be calculated in real time, eliminating the need for a large on-chip memory. Scaled images using the proposed filters show superb image quality.
Fast one-pass motion compensated frame interpolation in high-definition video processing

In this paper, a fast one-pass processing method with an efficient architecture is proposed for motion compensated frame interpolation (MCFI) in high-definition (HD) videos. Unlike previous works involving high complexity, complicated time-consuming iterations, and less practicability, the proposed method adopts one-pass and low-complexity concept. The proposed method operates a modified fast full-search algorithm, multi-level successive eliminate algorithm (MSEA), in a raster scan order as in the usual block-based processing order in popular codecs, such as H.264/AVC and VC-1. The proposed method analyzes and classifies temporal information to compensate insufficient spatial information based on preprocessed neighboring blocks. According to the analyzed temporal information, our method explores true motion candidates and refines the accuracy of true motions for sub-blocks. When searching motion candidates, the proposed method introduces an adaptive overlapped block matching algorithm called a multi-directional enlarged matching algorithm (MDEMA), and considers different overlapped types based on directions of current sought motion vector in order to enhance the searching accuracy and visual quality. Experimental results show that the proposed algorithm provides better video quality than conventional methods and shows satisfying performance.
Single Image Super-Resolution via Adaptive High-Dimensional Non-Local Total Variation and Adaptive Geometric Feature

Single image super-resolution (SR) is very important in many computer vision systems. However, as a highly ill-posed problem, its performance mainly relies on the prior knowledge. Among these priors, the non-local total variation (NLTV) prior is very popular and has been thoroughly studied in recent years. Nevertheless, technical challenges remain. Because NLTV only exploits a fixed non-shifted target patch in the patch search process, a lack of similar patches is inevitable in some cases. Thus, the non-local similarity cannot be fully characterized, and the effectiveness of NLTV cannot be ensured. Based on the motivation that more accurate non-local similar patches can be found by using shifted target patches, a novel multishifted similar-patch search (MSPS) strategy is proposed. With this strategy, NLTV is extended as a newly proposed super-high-dimensional NLTV (SHNLTV) prior to fully exploit the underlying non-local similarity. However, as SHNLTV is very high-dimensional, applying it directly to SR is very difficult. To solve this problem, a novel statistics-based dimension reduction strategy is proposed and then applied to SHNLTV. Thus, SHNLTV becomes a more computationally effective prior that we call adaptive high-dimensional non-local total variation (AHNLTV). In AHNLTV, a novel joint weight strategy that fully exploits the potential of the MSPS-based non-local similarity is proposed. To further boost the performance of AHNLTV, the adaptive geometric duality (AGD) prior is also incorporated. Finally, an efficient split Bregman iteration-based algorithm is developed to solve the AHNLTV-AGD-driven minimization problem. Extensive experiments validate the proposed method achieves better results than many state-of-the-art SR methods in terms of both objective and subjective qualities.
A 3D model to characterize EM far-field scattering and its applications in SAR data synthesis

In this research paper, we propose a 3D propagation model that enables to characterize the electromagnetic far-field scattered by a complex scenario at high-frequency bands (i.e. Ka-band). This proposed model is based on the combination between the asymptotic method Uniform Theory of Diffraction (UTD) and a Ray-Tracing (RT) technique. We have conducted some comparisons with the 33-37GHz indoor measurements in the anechoic chamber of School of Electrical Engineering (IU, VNU-HCMC) conducive to validate the model. The validated scenarios are composed of two metallic plates representing walls only and then a 4-in-1 corner reflector bestowed between them. Two identical broadband BBHA9170 antennas are used as transmitter and receiver in order to represent the bistatic configuration. These comparisons have shown that the model gives a good agreement with the experimental results. At the end, we apply the model to synthesize data for evaluating SAR imaging algorithms with the above configurations.
Generalized linear-phase lapped orthogonal transforms

The general factorization of a linear-phase paraunitary filter bank (LPPUFB) is revisited and we introduce a class of lapped orthogonal transforms with extended overlap (GenLOT). In this formulation, the discrete cosine transform (DCT) is the order-1 GenLOT, the lapped orthogonal transform is the order-2 GenLOT, and so on, for any filter length which is an integer multiple of the block size. All GenLOTs are based on the DCT and have fast implementation algorithms. The degrees of freedom in the design of GenLOTs are described and design examples are presented along with some practical applications.<<ETX>>
Portable wireless device threat assessment for aircraft navigation radios

The paper addresses concerns about wireless local area network devices and two-way radios causing electromagnetic interference to aircraft navigation radio systems. Spurious radiated emissions from various IEEE 802.11a, 802.11b, and Bluetooth devices are characterized using reverberation chambers. The results are compared with baseline emissions from standard laptop computers and personal digital assistants (PDAs) that are currently allowed to be used on aircraft. The results indicate that the WLAN devices tested are not more of a threat to aircraft navigation radios than standard laptop computers and PDAs in most aircraft bands. In addition, spurious radiated emission data from seven pairs of two-way radios are provided. These two-way radios emit at much higher levels in the bands considered. A description of the measurement process, device modes of operation and the measurement results are reported.
Design of hybrid filter banks for analog/digital conversion

This paper presents design algorithms for hybrid filter banks (HFBs) for high-speed, high-resolution conversion between analog and digital signals. The HFB is an unconventional class of filter bank that employs both analog and digital filters. When used in conjunction with an array of slower speed converters, the HFB improves the speed and resolution of the conversion compared with the standard time-interleaved array conversion technique. The analog and digital filters in the HFB must be designed so that they adequately isolate the channels and do not introduce reconstruction errors that limit the resolution of the system. To design continuous-time analog filters for HFBs, a discrete-time-to-continuous-time ("Z-to-S") transform is developed to convert a perfect reconstruction (PR) discrete-time filter bank into a near-PR HFB; a computationally efficient algorithm based on the fast Fourier transform (FFT) is developed to design the digital filters for HFBs. A two-channel HFB is designed with sixth-order continuous-time analog filters and length 64 FIR digital filters that yield -86 dB average aliasing error. To design discrete-time analog filters (e.g., switched-capacitors or charge-coupled devices) for HFBs, a lossless factorization of a PR discrete-time filter bank is used so that the reconstruction error is not affected by filter coefficient quantization. A gain normalization technique is developed to maximize the dynamic range in the finite-precision implementation. A four-channel HFB is designed with 9-bit (integer) filter coefficients. With internal precision limited to the equivalent of 15 bits, the maximum aliasing error is -70 dB, and with the equivalent of 20 bits internal precision, maximum aliasing is -100 dB. The 9-bit filter coefficients degrade the stopband attenuation (compared with unquantized coefficients) by less than 3 dB.
Efficient Motion Accuracy Search for Global Motion Vector Coding

One of the drawbacks of using global motion estimation in motion-compensated video coding is the overhead associated with the number and accuracy of motion parameters. Although prediction gain increases with increased motion accuracy, higher accuracy is not affordable since this increases motion bit rate as well. Therefore, an efficient global motion vector coding algorithm is necessary for improving the prediction gain. In this paper, we present a new solution for global motion vector coding which finds the best motion accuracy for each frame. Given a fixed motion bit-rate for global motion vectors, the proposed algorithm allocates the bits among differential motion vectors optimally by a best-accuracy search method. Secondly, we propose a novel mean square error modeling approach which reduces the complexity of the optimal search algorithm. The experimental results show that the proposed algorithm give higher peak signal-to-noise ratio (PSNR) compared to the global motion vector coding algorithm proposed in MPEG- 4 standard.
Recognizing logical parts in Vietnamese legal texts using Conditional Random Fields

Analyzing the structure of legal sentences in legal document is an important phase to build a knowledge management system in Legal Engineering. This paper proposes a new approach to recognize logical parts in Vietnamese legal documents based on a statistic machine learning method - Conditional Random Fields. Beside linguistic features such as word features, part of speech features, we use semantic features of logical parts such as trigger features and ontology features to improve the result of the annotation system. Experiments were conducted in a Vietnamese Business Law data set and obtained 78.12% at precision and 68.72% at recall measure. Compare to state-of-the-art systems, it improves the result for recognizing some logical parts.
SDP for multi-criterion QMF bank design

The quadrature mirror filter (QMF) bank, with multi-criterion constraints such as minimal aliasing and/or minimal error coding, is among the most important problems in filter bank design, for solving which linear algebra-based methods are still heuristic and do not always work, especially for large filter length. It is shown in this paper that when filters are of nonlinear phase, this problem can be reduced to convex linear matrix inequality (LMI) optimization, which can be very efficiently solved either by the standard LMI solvers or our previously developed solver. The proposed computationally tractable optimization formulations are confirmed by several simulations.
Embedded image coding using quincunx directional filter bank

An image coding system based on combination of a multiresolution directional decomposition and a morphological dilation algorithm is proposed in this paper. The multiscale filter bank combines the recently introduced non-uniform quincunx directional filter bank at higher scales and the traditional wavelet filter bank at lower scales, to provide a sparse image representation. The coding algorithm then efficiently clusters the significant coefficients using progressive morphological dilation. The remaining scattered significant coefficients are coded with the aid of the Tarp filter. The proposed image coding algorithm achieves better results than the current state-of-the-art wavelet based coders, such as SPIHT and JPEG2000
Massively parallel processor array for mid-/back-end ultrasound signal processing

Ultrasound remains a popular imaging modality due to its mobility and cost-effectiveness. As general purpose computing and DSPs are entering an era of multi-core architectures, the potential for parallel performance gains are significant when used properly. This work explores the possibility of using a massively parallel processor array to meet realtime throughputs for mid-/back-end ultrasound processing. A many-core array of simple DSP cores, shared memories, and an FFT processor is shown to dissipate 87.79 mW for B-mode, 33.20 mW for color flow, and 29.24 mW for spectral doppler, while achieving a frame rate of 37.6 fps for B-mode and 12.5 fps for color flow.
Design strategies to improve self-feeding device - FeedBot for Parkinson patients

The aim of the paper has been to make individuals with disability in arms, who have been fed during meals, completely or partially independent by use of the self-feeding device. In this paper, it describes a self-feeding system designed to increase the independence of a person who is unable to use their arm for self-feeding. It is FeedBot, a highly integrated and compact service robot with manipulator and food index tray. FeedBot is an intelligent device for disabled people in the home health care is self-feeding manipulator especially to Parkinson patients, who have difficulty to feed the foods while eating. In particular,  combines the best of available technology including a 2 DOF light-weight manipulator and an index tray. It operates with a food tray and a manipulator to bring the foods from tray and feed to disabled people as Parkinson patients. The self-feeding system is operated autonomous by itself and sent food's data and relative information to monitoring computer based on Internet. Besides, the tool of management can analyze the data according to the nutritional standards, and controller control movements of manipulator and automation tray based on health situation and needs of patients.
Lattice structures for design of three-channel linear-phase perfect-reconstruction FIR QMF banks

The authors present a perfect-reconstruction FIR (finite impulse response) linear-phase lattice structure for the three-channel QMF (quadrature mirror filter) bank. Both the analysis and the synthesis filters are linear-phase. To speed up the design time, the pairwise mirror-image condition is imposed on the resulting lattice structure. A design example is presented, and the complexity of the analysis bank is discussed.<<ETX>>