nils-herrmann/clean_scirepeval huggingface dataset:
All-Optical Gated Wavelength Converter-Eraser Using a Single SOA-MZI

We propose and experimentally demonstrate an original scheme for simultaneous all-optical wavelength conversion and data erasing under an optical gate signal, suitable for on-off keying (OOK) signals. This function is obtained in a semiconductor optical amplifier Mach-Zehnder interferometer (SOA-MZI) exploiting nonlinear interaction between a continuous data stream and an optical gate signal at a different wavelength. In correspondence of the gate signal, a burst of data from the optical stream is converted at the optical gate wavelength and, at the same time, cancelled at the input stream wavelength. Fast switching time enabling selective wavelength shifting on a data stream at 10 Gb/s without any bit loss is demonstrated. Error-free operation with 0.2-dB power penalty for the wavelength-preserved output data and 1.8 dB for the shifted data is reported.
A class of directional filter banks [image processing applications]

In this paper, we introduced a class of directional filter banks (DFB) having the previously proposed uniform DFB (uDFB) as a special case. The new DFBs implement a multiresolution and multidirection decomposition of images, while remaining perfect reconstruction (PR) and maximally decimated. We also discussed the permissible property of the filter banks in cases of being implemented by a tree structure and by direct implementation. The result shows that only one DFB in the class, which we call the quincunx uDFB, has the permissibility when being implemented directly by an eight-channel filter bank. Finally, an efficient tree structure for implementation of the quincunx uDFB is proposed.
External short circuit fault diagnosis based on supervised statistical learning

This paper proposes a fault diagnosis method for external short circuit detection based on the supervised statistical learning. The maximum likelihood estimator is used to capture the statistical properties of the fault and non-fault datasets, and the Gaussian classifier is applied to distinguish the two states. Validation experiments demonstrate the good performance of the proposed method in dynamic conditions. Compared to the prevailing fault detection methods, this method does not require extensive modeling work, determines the fault completely based on the data in existing fault occurrence, and can be adopted easily with the trend of big data and connected vehicles.
Linear-phase perfect reconstruction filter bank: lattice structure, design, and application in image coding

A lattice structure for an M-channel linear-phase perfect reconstruction filter bank (LPPRFB) based on the singular value decomposition (SVD) is introduced. The lattice can be proven to use a minimal number of delay elements and to completely span a large class of LPPRFBs: all analysis and synthesis filters have the same FIR length, sharing the same center of symmetry. The lattice also structurally enforces both linear-phase and perfect reconstruction properties, is capable of providing fast and efficient implementation, and avoids the costly matrix inversion problem in the optimization process. From a block transform perspective, the new lattice can be viewed as representing a family of generalized lapped biorthogonal transform (GLBT) with an arbitrary number of channels M and arbitrarily large overlap. The relaxation of the orthogonal constraint allows the GLBT to have significantly different analysis and synthesis basis functions, which can then be tailored appropriately to fit a particular application. Several design examples are presented along with a high-performance GLBT-based progressive image coder to demonstrate the potential of the new transforms.
Robust mixed generalized H/sub 2//H/sub /spl infin// filtering of 2-D nonlinear fractional transformation systems

This study considers robust filtering problems for uncertain two dimensional (2-D) discrete systems in nonlinear fractional transformation (NFT) representations. Like one-dimensional (1-D) systems, the NFT in this paper serves to complement the linear fractional transformation (LFT). Linear matrix inequality (LMI) formulations are given to analyze as well as synthesize robust filters. Numerical examples show the advantage of the NFT over the LFT in terms of not only computational savings but also substantial performance gains and verify the efficiency of the proposed techniques.
Robust watermarking with improved modified spread spectrum

This paper presents a robust approach for spread spectrum (SS) based watermarking process. Unlike the traditional SS or other improvements, this method can work properly in case of absence of watermark and achieve good performance. If the channel has no noise, the error probability of the new design is zero, which is not existed in almost SS-based watermarking systems. Based on analysis by theory, the optimal threshold is calculated. Moreover, the simulations are implemented to verify to the theory.
Wireless phone threat assessment for aircraft communication and navigation radios

Emissions in aircraft communication and navigation bands are measured for the latest generation of wireless phones. The two wireless technologies considered, GSM/GPRS and CDMA2000, are the latest available to general consumers in the U.S. A base-station simulator is used to control the phones. The measurements are conducted using reverberation chambers, and the results are compared against FCC and aircraft installed equipment emission limits. The results are also compared against baseline emissions from laptop computers and personal digital assistant devices that are currently allowed to operate on aircraft.
Learning the Kernel Matrix for Superresolution

This paper proposes the application of learned kernels in support vector regression to superresolution in the discrete cosine transform (DCT) domain. Though previous works involve kernel learning, their problem formulation is examined to reformulate the semi-definite programming problem of finding the optimal kernel matrix. For the particular application to superresolution, downsampling properties derived in the DCT domain are exploited to add structure to the learning algorithm. The advantage of the proposed method over other learning-based superresolution algorithms include specificity with regard to image content, structured consideration of energy compaction, and the added degrees of freedom that regression has over classification-based algorithms
Generalized Block-Lifting Factorization of $M$-Channel Biorthogonal Filter Banks for Lossy-to-Lossless Image Coding

Generalized block-lifting factorization of M-channel (M >; 2) biorthogonal filter banks (BOFBs) for lossy-to-lossless image coding is presented in this paper. Since the proposed block-lifting structure is more general than the conventional lifting factorizations and does NOT require many restrictions such as paraunitary, number of channels, and McMillan degree in each building block unlike the conventional lifting factorizations, its coding gain is higher than that of the previous methods. Several proposed BOFBs are designed and applied to image coding. Comparing the results with conventional lossy-to-lossless image coding structures, including the 5/3- and 9/7-tap discrete wavelet transforms in JPEG 2000 and a 4 × 8 hierarchical lapped biorthogonal transform in JPEG XR, the proposed BOFBs achieve better result in both objective measure and perceptual visual quality for the images with a lot of high-frequency components.
Digital filter bank design quadratic-constrained formulation

Formulate the filter bank design problem as an quadratic-constrained least-squares minimization problem. The solution of the minimization problem converges very quickly since the cost function as well as the constraints are quadratic functions with respect to the unknown parameters. The formulations of the perfect-reconstruction cosine-modulated filter bank, of the near-perfect-reconstruction pseudo-QMF bank, and of the two-channel biorthogonal linear-phase filter bank are derived using the proposed approach. Compared with other design methods, the proposed technique yields PR filter banks with much higher stopband attenuation. The proposed technique can also be extended to design multidimensional filter banks.
Image coding ringing artifact reduction using morphological post-filtering

Ringing is an annoying artifact frequently encountered in low bit-rate transform and subband decomposition based compression of different media such as image, intra frame video and graphics. A mathematical morphology based post-processing algorithm is presented in this paper for image ringing artifact suppression. First, we use binary morphological operators to isolate the regions of an image where the ringing artifact is most prominent to the human visual system (HVS) while preserving genuine edges and other (high-frequency) fine details present in the image. Then, a gray-level morphological nonlinear smoothing filter is applied to the unmasked regions of the image under the filtering mask to eliminate ringing within this constraint region. To gauge the effectiveness of this approach, we propose an HVS compatible objective measure of the ringing artifact. Preliminary simulations indicate that the proposed method is capable of significantly reducing the ringing artifact on both subjective and objective basis.
High Throughput FPGA Implementation for regular Non-Surjective Finite Alphabet Iterative Decoders

This paper deals with the recently introduced class of Non-Surjective Finite Alphabet Iterative Decoders (NS-FAIDs). First, optimization results for an extended class of regular NS-FAIDs are presented. They reveal different possible trade-offs between decoding performance and hardware implementation efficiency. To validate the promises of optimized NS-FAIDs in terms of hardware implementation benefits, we propose two high-throughput hardware architectures, integrating NS-FAIDs decoding kernels. Implementation results show that NS-FAIDs allow significant improvements in terms of both throughput and hardware resources consumption, as compared to a baseline Min-Sum decoder, with even better or only slightly degraded decoding performance.
Grid-connected PV system design option for nearly zero energy building in reference building in Hanoi

Building is responsible for more than 40 percent of energy consumption and one third of greenhouse gas emissions. Europe has stablished the path towards nearly zero-energy buildings (nZEB), soon required in every new construction and large renovation in existing buildings by 2020. Achieving nZEB required the use of photovoltaic modules for generating electricity. In Vietnam, photovoltaic systems are in most cases not used in building today. This research, we aim to implement the platform that will be dedicated to prototyping and tools to support research training in the reference building. In order to achieve nZEB, a 15 kWp of PV array will be installed in the rooftop of this building to compensate the energy needed. The objectives are to benefit from PV source, to improve energy efficiency and to reduce cost of electrical consumption in different scenarios. The Photovoltaic simulation tool is important in predicting the energy production from the solar panels. The first study investigates the use of a simulation tool PVSYST as a method of informing the design decision of building installed photovoltaic system. Input to the simulation software such as meteorological data has been evaluated.
Iterative Rate-Distortion Optimization of H.264 With Constant Bit Rate Constraint

In this paper, we apply the primal-dual decomposition and subgradient projection methods to solve the rate-distortion optimization problem with the constant bit rate constraint. The primal decomposition method enables spatial or temporal prediction dependency within a group of picture (GOP) to be processed in the master primal problem. As a result, we can apply the dual decomposition to minimize independently the Lagrangian cost of all the MBs using the reference software model of H.264. Furthermore, the optimal Lagrange multiplier is iteratively derived from the solution of the dual problem. As an example, we derive the optimal bit allocation condition with the consideration of temporal prediction dependency among the pictures. Experimental results show that the proposed method achieves better performance than the reference software model of H.264 with rate control.
A heuristic approach for shadow and light regions fast detection in face images

Face detection and recognition have become more and more popular, especially in the era of hand-held devices. As a result, many algorithms have been developed to process face images. However, many of those also have problems with uneven illumination effects, because images have been captured under various lighting conditions. In this paper, we introduce a heuristic approach for shadow and light regions fast detection in face images. The results will be used as clues for other correction algorithms. Within the available samples of the face region, we use the K-means algorithm to cluster pixels into shadow, light and light-balanced regions. Since the heuristic K-means method may generate misclassified pixels, we use image processing techniques to enhance the clustered results. Experiments conducted on the Caltech face dataset show that our proposed approach can robustly, totally and quickly detect shadow and light regions in face images.
A 167-Processor Computational Platform in 65 nm CMOS

A 167-processor computational platform consists of an array of simple programmable processors capable of per-processor dynamic supply voltage and clock frequency scaling, three algorithm-specific processors, and three 16 KB shared memories; and is implemented in 65 nm CMOS. All processors and shared memories are clocked by local fully independent, dynamically haltable, digitally-programmable oscillators and are interconnected by a configurable circuit-switched network which supports long-distance communication. Programmable processors occupy 0.17&nbsp;mm<sup>2</sup> and operate at a maximum clock frequency of 1.2 GHz at 1.3 V. At 1.2 V, they operate at 1.07 GHz and consume 47.5&nbsp;mW when 100% active, resulting in an energy dissipation of 44 pJ per operation. At 0.675 V, they operate at 66 MHz and consume 608&nbsp;muW when 100% active, resulting in a total energy dissipation of 9.2 pJ per ALU or MAC operation.
Parallel and reliable execution of a WDR algorithm in high speed networks

This paper presents an idea for a parallel version of the WDR (wavelet difference reduction) compression algorithm. An implementation of the idea is applied to the Nguyen-Chen-Walker's WDR codec and related analysis are demonstrated. The parallel WDR codec (PWDR) reaches up to 50 percent speedup compared to the original sequential implementation for some images. A reliable extension of the parallelized program and analyses of its performance have been presented.
A quadratic-constrained least-squares approach to the design of digital filter banks

The author formulates the filter bank design problem as a quadratic-constrained least-square minimization problem. The solution of the minimization problem converges very fast since the cost function and the constraints are quadratic functions with respect to the unknown parameters. The cosine-modulated and the two-channel linear-phase filter banks are designed using the proposed formulation. Compared to other design methods, the proposed technique yields PR (perfect reconstruction) filter banks with much higher stopband attenuation. The filter designed using the new approximation could be used as an initialization filter in a conventional PR filter bank design.<<ETX>>
18F autoradiography using pixelated CMOS technology

Autoradiography is a method that allows to take ex-vivo images of thin sections of tissue labelled with a radioactive tracer. In the present work, we aim to study the feasibility of autoradiography with CMOS ( Mimosa-28 by using 2-Deoxy-2-18F-fluoro-D-glucose (18F-FDG). Autoradiography allows a functional imaging pixelated with a resolution equivalent to optical microscopy. In this paper, we report the characterisation of the Mimosa-28 sensor. The sensor presents a linearity detection of positrons emitted from 18F with an activity from 450Bq to 3kBq. The detection efficiency was 77.660% ± 0.024% for a source in contact with the sensor. The spatial resolution was 153µm ± 7µm. Mimosa-28 CMOS sensor demonstrates the capability to do autoradiography of a tissue section labelled with 18F-FDG.
Using filter banks to enhance images for fluid lens cameras based on color correlation

The novel field of fluid lens cameras introduces unique image processing challenges. Intended for surgical applications, these fluid optics systems have improved miniaturization over glass lenses and do not have moving parts while zooming. However, the liquid medium creates non-uniform color blur, which causes certain color planes to appear sharper than others. We propose an adapted perfect reconstruction filter bank that uses high frequency sub-bands of sharp color planes to improve blurred color planes. The approach is refined by adjusting the decomposition level based on limited channel information. This paper primarily considers the use of a sharp green color plane to improve a blurred blue color plane. More generally, these methods could improve the red color plane as well as any system with high edge correlation between two images.
Efficiently VLSI-realizable prototype filters for modulated filter banks

This paper presents methods for the efficient realization of prototype filters for modulated filter banks. The implementation is based on the lattice structure of the polyphase filters. The lattice coefficients, representing rotations, are approximated by a small number of simple /spl mu/-rotations each of which can be realized by some shift and add operations instead of a multiplication. Since the lattice structure is robust against coefficient quantization we do not loose the perfect reconstruction (PR) property of the filter bank when doing this approximation. The frequency responses of the original and approximated prototype filters are compared in terms of complexity and stopband attenuation.
Partial spectrum reconstruction using digital filter banks

The problem of reconstructing a part of the spectrum is reduced to designing the filter bank to satisfy a set of conditions. For the case considered here, these conditions cannot be satisfied simultaneously, so perfect reconstruction is not possible. The necessary and sufficient conditions on the filters so that the resulting filter bank cancels most alias components are found. Such filter banks are called partial alias cancellation filter banks. The product of the polyphase transfer matrices of these filter banks must be a block pseudocirculant matrix. An algorithm design procedure is discussed, and examples are given to demonstrate the theory.
A study of pipe-cleaning and inspection robot

Pipe cleaning and inspection robot is one of the new concepts of professional service robots. Sewer pipes are typically of non-man-entry classification (less than 0.8 m diameter). In this paper, a pipe-cleaning and inspection robot specifically designed for this function is proposed. This paper presents a new approach for design and development of cleaning robots in an unknown pipe workspace. To do so, we propose a new cutting method for cleaning work as well as an underwater inspection method. In this study, we discuss a communication which makes the cleaning robot navigate the sewer pipe. Finally, we also evaluate the performance of our proposed inspection and cleaning processes via experiments and real tests. Also, we verify the effectiveness of the proposed methods through computer simulations.
Interaction analysis of annotated specification and program codes in Extended Static Checking

Software cost can be reduced if more software defects are detected earlier in the development phase. Motivated by the Extended Static Checking (ESC) technique, many programming errors have been discovered by ESC tools. In a typical ESC procedure, the source code of a program written in a high-level programming language, e.g. Java  or C#, Spec# , is translated into some logical imperative-style language, resp. Guarded Commands  or BoogiePL . At the same time, associated annotated specifications which state constraints of the program are also translated into the same logical language. This two-fold translation phase induces code-interleaving phenomenon of annotated specification and program. The subsequent phases in ESC relies on the interleaving codes while there is a possibility that logical imperative codes translated from annotated specification may change behavior of the original program. This paper proposes a formal analysis approach of possible interaction between specification and program codes. It does not only show the range of specification categories which are safe in this ESC procedure, but also presents cases for potential ESC unsoundness.
Adaptive PID tracking control based radial basic function networks for a 2-DOF parallel manipulator

In this paper, an adaptive proportional integral derivative (PID) based on radial basic function neural networks (APID-RBFNs) is proposed for tracking control of a 2 degree of freedom (DOF) parallel manipulator. For developing the controller, a dynamic model of this parallel manipulator is developed based on a matrix form equations. APID-RBFNs is designed to overcome external disturbances and complex noises acting on the parallel manipulator system by using adaptive PID sliding surface with RBFNs. By using the Lyapunov method, the stability of the overall system with full state constraints is proved. The simulation results in universal software Matlab/Simulink show that the proposed control strategy has better dynamic performance and robustness than conventional PID tracking control.
Alias-Free Subband Adaptive Filtering With Critical Sampling

To overcome the limitations of a conventional fullband adaptive filtering, various subband adaptive filtering (SAF) structures have been proposed. Properly designed, an SAF will converge faster at a lower computational cost than a fullband structure. However, its design should consider the following two facts: the interband aliasing introduced by the downsampling process degrades its performance, and the filter bank in the SAF introduces additional computational overhead and system delay. In this paper, to fully exploit the benefits of using an SAF, an almost alias-free SAF structure with critical sampling is proposed. The interband alising is removed from the subband signal by isolating the aliasing using a bandwidth-increased analysis filter. Computer simulations show that the proposed structure converges faster than both an equivalent fullband structure at lower computational complexity and recently proposed SAF structures for a colored input.
The new MPPT algorithm using ANN-based PV

In grid connected photovoltaic (PV) systems, maximum power point tracking (MPPT) algorithm plays an important role in optimizing the solar energy efficiency. In this paper, the new artificial neural network (ANN) based MPPT method has been proposed for searching maximum power point (MPP) fast and exactly. For the first time, the combined method is proposed, which is established on the ANN-based PV model method and incremental conductance (IncCond) method. The advantage of ANN-based PV model method is the fast MPP approximation base on the ability of ANN according the parameters of PV array that used. The advantage of IncCond method is the ability to search the exactly MPP based on the feedback voltage and current but don't care the characteristic on PV array‥ The effectiveness of proposed algorithm is validated by simulation using Matlab/ Simulink and experimental results using kit field programmable gate array (FPGA) Virtex II pro of Xilinx.