nils-herrmann/clean_scirepeval huggingface dataset:
Robust object detection scheme using feature selection

Feature selection is an important issue for object detection. In this paper, we propose an effective wrapper-based feature selection scheme using Binary Particle Swarm Optimization (BPSO) and Support Vector Machine (SVM) for object detection. In our algorithm, Scale-Invariant Feature Transform (SIFT) descriptors in a patch around the keypoints are extracted as the initial feature representations. The initial feature set is fed into the feature selection module in which the BPSO searches the feature space, and a SVM classifier serves as an evaluator for the performance of the feature subset selected by the BPSO. We tested the proposed detection scheme on the UIUC car dataset and our results show that feature selection scheme not only improves the detection accuracy but also enhances the detection efficiency.
Optimal design of triplet halfband filter banks via Semidefinite Programming

This paper proposes a computationally efficient method for designing a class of triplet halfband filter banks. We show that the design of perfect reconstruction two-channel Alter banks with arbitrary regularity order can be precisely formulated as a semi-definite programming problem. We also show that the dual problem has a significant smaller number of variables and, hence, can be solved efficiently. The effectiveness of the proposed method is demonstrated by the design examples of filter banks with high filter order and arbitrary regularity order.
The design of arbitrary FIR digital filters using the eigenfilter method

The design of finite impulse response (FIR) digital filters for approximating an arbitrary function (in both magnitude and phase) in the least-square sense is studied. The design method is based on the computation of an eigenvector of an appropriate real, symmetric and positive-definite matrix. The design of the complex-coefficient filter is shown to be an extension of the design of the real-coefficient filter. Several design examples, including the constant-group-delay filters and digital phase all-pass filters, are presented. Comparisons to existing methods are made.
A Fully Scalable Motion Model for Scalable Video Coding

Motion information scalability is an important requirement for a fully scalable video codec, especially for decoding scenarios of low bit rate or small image size. So far, several scalable coding techniques on motion information have been proposed, including progressive motion vector precision coding and motion vector field layered coding. However, it is still vague on the required functionalities of motion scalability and how it collaborates flawlessly with other scalabilities, such as spatial, temporal, and quality, in a scalable video codec. In this paper, we first define the functionalities required for motion scalability. Based on these requirements, a fully scalable motion model is proposed along with tailored encoding techniques to minimize the coding overhead of scalability. Moreover, the associated rate distortion optimized motion estimation algorithm will be provided to achieve better efficiency throughout various decoding scenarios. Simulation results will be presented to verify the superiorities of proposed scalable motion model over nonscalable ones.
Biorthogonal cosine-modulated filter bank

Cosine-modulated filter banks have been studied extensively because of their design ease and efficient implementation. These filter banks either have restricted lengths or assume the paraunitary property for the polyphase matrices. In this paper, the biorthogonal cosine-modulated filter bank with arbitrary length is considered and the perfect reconstruction (PR) conditions are derived. These conditions are the general form of the PR conditions reported in the literature. Examples of PR systems with variable overall delay are designed using the quadratic constrained least squares formulation.
An Online Learning Approach to Occlusion Boundary Detection

We propose a novel online learning-based framework for occlusion boundary detection in video sequences. This approach does not require any prior training and instead “learns” occlusion boundaries by updating a set of weights for the online learning Hedge algorithm at each frame instance. Whereas previous training-based methods perform well only on data similar to the trained examples, the proposed method is well suited for any video sequence. We demonstrate the performance of the proposed detector both for the CMU data set, which includes hand-labeled occlusion boundaries, and for a novel video sequence. In addition to occlusion boundary detection, the proposed algorithm is capable of classifying occlusion boundaries by angle and by whether the occluding object is covering or uncovering the background.
Cooperative communication techniques for cluster size expansion in cluster based Wireless Sensor Network

In the context of energy constrained wireless sensor networks where individual nodes can cooperate together to deploy the cooperative communications, Relay and cooperative Multi-Input Multi-Output (MIMO) techniques can be used to exploit the diversity gain to increase the performance or to reduce the transmission energy consumption. Based on the energy efficiency of cooperative communication, a new scheme of using cooperative MISO and Relay techniques for two way data transmission in cluster based Wireless Sensor Networks (WSN) is proposed in this paper. The energy consumption of the multi-hop, Relay and cooperative MISO transmission have been investigated in this paper. Simulation and energy calculation results show that the proposed cooperative scheme has a much lower energy consumption than the traditional multi-hop transmission scheme and the proposed scheme can be used to increase efficiently the size of WSN cluster.
An Alternative Filter Bank View for Real Orthogonal STBC in Frequency Selective Channel

This paper presents an alternative approach for viewing a real orthogonal space time block code (ROSTBC) in frequency selective channel as a filter bank (FB). A communications system with multiple transmitting antennas and a single receiving antenna is considered. From the FB point of view, this system when employing a rate-1 ROSTBC, can be treated as a maximally decimated FB. Likewise, it becomes a non-maximally decimated FB, when a non-rate 1 ROSTBC is employed. The amount of redundancy can be observed from the number of channels between the analysis and the synthesis polyphase matrices versus the number of input channels. When there is redundancy, the block MIMO channel (describing the overall physical channels between the transmitter and receiver) becomes a tall matrix. Hence an FIR inverse (synthesis matrix) is more likely to exist at the receiver side. On the other hand, for all full rate ROSTBCs, the channel matrix becomes a square matrix. Its Smith form always consists of a nontrivial FIR term, prohibiting the existence of its FIR inverse. Simulations and examples are given to illustrate various concepts developed in this paper.
An adaptive extension of combined 2D and 1D-directional filter banks

In this paper, we propose an extension of combined 2D and 1D-directional filter banks (TODFBs) with adaptive approach in their 1D-directional stages. TODFBs show better performance in image coding and denoising compared to the traditional wavelet transform (WT), however, they still have possibilities to improve their performance in image coding by adopting the adaptive directional WTs for their 1D-directional stages. An efficient method to determine the transform directions is also proposed. In image coding results, our proposed filter banks gain PSNR and visual quality improvements compared with the WTs and the non-adaptive TODFBs.
Crosstalk analysis in LCD stereoscopic displays with active shutter glasses

Improvement in the quality of Liquid Crystal Displays (LCD) triggers a significant surge in the 3DTV market. A large segment of the 3DTV market has adopted active shutter glasses (active 3DTV). In this system, crosstalk is an important factor that affects the viewing quality of active 3DTV. This paper proposes a mathematical model for crosstalk and analyses the temporal, spatial, LCD-based and liquid crystal shutter glasses (LCS)-based features of crosstalk in active 3DTV. Simulations of 120Hz active 3DTV under several scenarios are conducted and the result is compared with the measured crosstalk, verifying our model. Furthermore, the proposed model is used to analyze crosstalk for different parameters in both monitor and glasses and an effective method to reduce crosstalk is presented.
Dynamic behavior and protocol models for incremental changes among a set of collaborative objects

Separation of concerns [P. Tarr et al., (1999)] plays a critical role to the success of software development and evolution. We focus mainly on an approach to separate concerns during analysis stage. More specifically, concerns are collaborations in a given role-based system [T. T. Nguyen et al., (2003), Y. Smaragdakis et al., (1998)], and one or more other collaborations to be added due to an incremental change. First, we investigate changes made to an individual object's behavior by superimposing the refinement on the object's statechart within a proposed formal dynamic behavior model. Such individual extensions of collaborative objects are then put together in a collaborative context for a holistic effect crosscutting many objects due to the introduction of an incremental change. In addition to behavior model based on statecharts, we claim that modeling a collaborative system requires an extra protocol model which is separate but complementary to the behavior model. We believe that complete behavior of any system, either complete or partial, can be fully expressed by these two models. More importantly, incremental changes and their effects can be easily handled in a modular fashion within these models.
Hazy image modeling using color ellipsoids

Several methods exist that try to remove haze from a single image but they lack in the support for why a particular method was chosen. The idea of using color ellipsoids is presented in this paper for the purpose of developing a new framework for analyzing single image dehazing methods. Synthetic and real world images are used to support important properties of the color ellipsoids that give a queue to the amount of haze in an image. As an example of its usefulness, a single dehazing method is analyzed within the color ellipsoid framework.
A general formulation of modulated filter banks

This paper presents a general framework for maximally decimated modulated filter banks. The theory covers the known classes of cosine modulation and relates them to complex-modulated filter banks. The prototype filters have arbitrary lengths, and the overall delay of the filter bank is arbitrary, within fundamental limits. Necessary and sufficient conditions for perfect reconstruction (PR) are derived using the polyphase representation. It is shown that these PR conditions are identical for all types of modulation-modulation based on the discrete cosine transform (DCT), both DCT-III/DCT-IV and DCT-I/DCT-II, and modulation based on the modified discrete Fourier transform (MDFT). A quadratic-constrained design method for prototype filters yielding PR with arbitrary length and system delay is derived, and design examples are presented to illustrate the tradeoff between overall system delay and stopband attenuation (subchannelization).
A lapped transform progressive image coder

Several block-transform-based embedded image coders have been proposed recently in literature. The innovation here is to replace the wavelet transform in the EZW or SPIHT progressive image coding framework by popular block transforms such as the DCT or lapped transforms which can offer finer frequency spectrum partitioning and better energy compaction. However, most of the block transform coders above have not been able to compete with the wavelet-based ones on a consistent basis. In this paper, we present a fully progressive coding scheme based on appropriately-designed generalized lapped orthogonal/biorthogonal transforms (GenLOT or GLBT) coupled with several levels of wavelet decomposition of the DC band if needed. The uniform band block transform can be implemented in parallel fashion with fast, robust, and efficient lattice structures. Keying only on the transform stage, we are able to obtain the highest performance embedded coder up to date. This result shows that lapped transforms, when carefully designed, are capable of providing superior reconstructed image quality compared to wavelets, both objectively and subjectively.
Postcompensation of Nonlinear Distortions of 64-QAM Signals in a Semiconductor-Based Wavelength Converter

We experimentally investigate postcompensation of nonlinear distortions induced by a wavelength converter (WC) based on four-wave mixing in a semiconductor optical amplifier. The technique exploits a low-complexity digital filter-based backpropagation (DFBP) method. We perform postcompensation of nonlinear distortions following single stage wavelength conversion of 5 Gbd 64-quadrature amplitude modulation (QAM). We examine the DFBP performance in the presence of a degraded optical signal-to-noise ratio at the WC input, and explore the WC optimal operating conditions. Also, we experimentally demonstrate for the first time in the literature the dual stage wavelength conversion of QAM signals, in particular, 5 Gbd 64-QAM, and show that bit error rate below hard-decision forward error correction threshold is only possible with postcompensation of nonlinear distortions. These results are of importance for the development of wavelength-routed networks requiring successive wavelength conversion stages to enhance routing capabilities.
Nonlinear Modeling of a Magnetic Bearing System using SDP model and Linear Wavelet Parameterization

In this paper, we present the nonlinear modeling of a magnetic bearing system. The approach uses the SDP model to characterize the system's nonlinearities; and an optimized model structure selection algorithm in which linear wavelet functional approximation and PRESS statistics are in use prior to the final parametric estimation. The experimental results reported in this paper demonstrate the approach in identifying a test-stand magnetic bearing system.
Design of Diamond and Circular Filters by Semi-definite Programming

A new design for linear phase diamond-shaped (DS) and circular-shaped (CS) 2D filters is developed. First, the frequency masks are efficiently constrained by 2D second-order trigonometric polynomials. Then semi-definite programming (SDP) of reasonably low dimension is employed to effectively express the filter specifications. Several numerical examples are provided to demonstrate the superior performance of our design in comparison with all other existing designs.
Bidirectional scalable motion for scalable video coding

Motion information scalability is an important requirement for a fully scalable video codec, especially in low bit rate or small resolution decoding scenarios, for which the fully scalable motion model (SMM) has been proposed. SMM can collaborate flawlessly with other scalabilities, such as spatial, temporal and quality, in a scalable video codec and it performs better than nonscalable motion model. To further improve the SMM, this paper further extends the algorithm to support hierarchical B frame structure and bidirectional or multidirectional motion estimation and, moreover, provides the corresponding rate distortion optimized estimation. Several simulation results are presented to verify the improvements of this extension.
Motion vector processing using bidirectional frame difference in motion compensated frame interpolation

In this paper, we address the potential issues in bidirectional motion compensated frame interpolation when the received motion vector field is directly used. Based on this motion vector analysis, we therefore propose using bidirectional motion vector processing method to eliminate the ghost artifacts around the moving objects. The artifacts caused by large motion vector magnitude can be effectively removed by correcting motion vectors bidirectionally. Moreover, since the proposed motion vector selection process chooses the best motion vector from adjacent motion vectors, the computational complexity can be greatly reduced comparing to motion estimation. We also demonstrate how to obtain clearer object edges by allowing displacement adjustment during the bidirectional motion vector processing. Experimental results show that the proposed algorithm outperforms other methods in terms of visual quality.
Optimal temporal interpolation filter for motion-compensated frame rate up conversion

Frame rate up conversion (FRUC) methods that employ motion have been proven to provide better image quality compared to nonmotion-based methods. While motion-based methods improve the quality of interpolation, artifacts are introduced in the presence of incorrect motion vectors. In this paper, we study the design problem of optimal temporal interpolation filter for motion-compensated FRUC (MC-FRUC). The optimal filter is obtained by minimizing the prediction error variance between the original frame and the interpolated frame. In FRUC applications, the original frame that is skipped is not available at the decoder, so models for the power spectral density of the original signal and prediction error are used to formulate the problem. The closed-form solution for the filter is obtained by Lagrange multipliers and statistical motion vector error modeling. The effect of motion vector errors on resulting optimal filters and prediction error is analyzed. The performance of the optimal filter is compared to nonadaptive temporal averaging filters by using two different motion vector reliability measures. The results confirm that to improve the quality of temporal interpolation in MC, the interpolation filter should be designed based on the reliability of motion vectors and the statistics of the MC prediction error.
Research on fuzzy PI control for switched reluctance wind power inverter with SVPWM

Switched reluctance generator (SRG) is a new type generator with excellent performances such as high efficient, sturdy and durable. There are broad prospects for wind power of switched reluctance generator. Considering the nonlinear characteristics of SRG wind power system, the advanced control algorithm such as intelligent control algorithm should be used to overcome the limitation of normal PI algorithm. In this paper, a fuzzy-PI controller for SRG wind power system with three-phase SVPWM inverter is researched, and simulation model of SRG wind power with three-phase SVPWM inverter with fuzzy-PI control algorithm is set up based on MATLAB SIMULINK/POWER SYSTEM. The simulation results given in this paper verify the fuzzy-PI control algorithm combines the advantages of the fuzzy control and PI control. Compared with normal PI controller, the fuzzy-PI control algorithm possesses a better dynamic response and the accuracy of the steady-state and robustness for nonlinear SRG wind power system with three-phase SVPWM inverter.
Software defined networking-based vehicular Adhoc Network with Fog Computing

Vehicular Adhoc Networks (VANETs) have been attracted a lot of research recent years. Although VANETs are deployed in reality offering several services, the current architecture has been facing many difficulties in deployment and management because of poor connectivity, less scalability, less flexibility and less intelligence. We propose a new VANET architecture called FSDN which combines two emergent computing and network paradigm Software Defined Networking (SDN) and Fog Computing as a prospective solution. SDN-based architecture provides flexibility, scalability, programmability and global knowledge while Fog Computing offers delay-sensitive and location-awareness services which could be satisfy the demands of future VANETs scenarios. We figure out all the SDN-based VANET components as well as their functionality in the system. We also consider the system basic operations in which Fog Computing are leveraged to support surveillance services by taking into account resource manager and Fog orchestration models. The proposed architecture could resolve the main challenges in VANETs by augmenting Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Vehicle-to-Base Station communications and SDN centralized control while optimizing resources utility and reducing latency by integrating Fog Computing. Two use-cases for non-safety service (data streaming) and safety service (Lane-change assistance) are also presented to illustrate the benefits of our proposed architecture.
Efficient phase correlation motion estimation using approximate normalization

Motion estimation methods based on phase correlation have been in use for almost three decades. Its ability to measure large motions with subpixel accuracy has made it very appealing in many applications. Significant computational steps involved are FFT, normalized cross-power spectrum and IFFT. While efficient hardware and software solutions exist for FFT and IFFT, normalized cross-power spectrum computation has so far evaded efficient solutions. In this paper, we propose a novel method for computing cross-power spectrum based on approximate normalization of complex scalar, which is very efficient and hardware friendly as compared to existing methods. Proposed algorithm along with its generalization to normalization of complex vectors, results in significant reduction in precision requirements on FFT and IFFT as well. It is related to block floating point representation of numbers but overhead due to exponents have been avoided. Simulation results show that proposed algorithm holds potential for making phase correlation an accessible tool for low power devices as well as applications dealing with very large images.
Lattice structures parameterization of linear phase paraunitary matrices with pairwise mirror-image symmetry in the frequency domain with an odd number of rows

Much attention has been placed on the design of digital filter banks with pairwise mirror-image symmetry in the frequency domain because such filter bank structure requires fewer multipliers and less time to design than most other structures. Furthermore, the designed subband filters have better attenuation in most cases. In this paper, the polyphase matrix of linear phase paraunitary filter banks with an odd number of channels and pairwise mirror-image symmetry frequency responses are completely characterized and parameterized by a lattice structure. The parameterization is shown to be complete and minimal. Design examples are presented.
LCD Motion Blur Reduction: A Signal Processing Approach

Liquid crystal displays (LCDs) have shown great promise in the consumer market for their use as both computer and television displays. Despite their many advantages, the inherent sample-and-hold nature of LCD image formation results in a phenomenon known as motion blur. In this work, we develop a method for motion blur reduction using the Richardson-Lucy deconvolution algorithm in concert with motion vector information from the scene. We further refine our approach by introducing a perceptual significance metric that allows us to weight the amount of processing performed on different regions in the image. In addition, we analyze the role of motion vector errors in the quality of our resulting image. Perceptual tests indicate that our algorithm reduces the amount of perceivable motion blur in LCDs.
Novel Architecture for a Photonics-Assisted Radar Transceiver Based on a Single Mode-Locking Laser

A novel solution for the optical generation of radio-frequency signals for coherent radars is proposed, which exploits the same mode-locking laser of the photonic-assisted radar receiver. The scheme, which is based on the concept of shifting the frequency of a laser mode, exploits a commercial optical in-phase/quadrature modulator to allow using a single mode-locking laser for both the radar transmitter and receiver, making the solution attractive for immediate and practical implementation in photonics-assisted transceivers.