nils-herrmann/clean_scirepeval huggingface dataset:
Selective Data Pruning-Based Compression Using High-Order Edge-Directed Interpolation

This paper proposes a selective data pruning-based compression scheme to improve the rate-distortion relation of compressed images and video sequences. The original frames are pruned to a smaller size before compression. After decoding, they are interpolated back to their original size by an edge-directed interpolation method. The data pruning phase is optimized to obtain the minimal distortion in the interpolation phase. Furthermore, a novel high-order interpolation is proposed to adapt the interpolation to several edge directions in the current frame. This high-order filtering uses more surrounding pixels in the frame than the fourth-order edge-directed method and it is more robust. The algorithm is also considered for multiframe-based interpolation by using spatio-temporally surrounding pixels coming from the previous frame. Simulation results are shown for both image interpolation and coding applications to validate the effectiveness of the proposed methods.
Seismic data compression using GenLOT: towards "optimality"?

Seismic data compression is desirable in geophysics for both storage and transmission stages. Wavelet coding methods have generated interesting developments, including a real-time field test trial in the North Sea in 1995. Previous work showed that GenLOT with basic optimization also outperforms state-of-the-art biorthogonal wavelet coders for seismic data. In this paper, we focus on the problem of filter bank optimization using various properties of seismic data. It is often desirable to evaluate the compression performance of a transform on a set of data using a priori objective measures, to reduce extensive testings by selecting only good a priori transforms, and to tailor transforms to the statistical properties of the data set. In the scope of this work, we use symmetric AR models up to order 4 to obtain an average model of the horizontal and vertical signals of a seismic stack section. Rosten et al. (1999), have already shown that order 1 or 2 models give good results in filter bank optimization for non-unitary filter banks, using coding gain optimization. Several other criteria may be used for transform optimization. Following the theory in Tran and Nguyen (1999), we use a weighted combination of C/sub o/=k/sub C/C/sub C/+k/sub S/C/sub S/+k/sub d/C/sub D/ of coding gain, stopband attenuation and DC leakage minimization functions.
A hybrid filter bank approach to analog-to-digital conversion

This paper presents a novel approach to high-speed, high-resolution analog-to-digital (A/D) conversion using a hybrid filter bank with an array of slower speed A/D converters (ADCs). The hybrid filter bank is a new class of filter bank that employs continuous-time analysis filters to allocate a frequency band to each ADC in the array and discrete-time synthesis filters to reconstruct the digitized signal. The filter bank improves the speed and resolution of the A/D conversion by reducing the effects of mismatches between the ADCs in the array. This paper presents a filter design algorithm which minimizes mean-squared reconstruction error for the M-channel hybrid filter bank. A near-perfect-reconstruction, two-channel hybrid filter bank which introduces 0.00095 dB average deviation from 0 dB distortion and -108 dB average aliasing is developed.<<ETX>>
Statistical learning based intra prediction in H.264

In this paper, we improve the performance of intra prediction and simplify mode decision procedure at the same time. For these works, we apply a statistical learning method such as Support Vector Machines for Regression (SVR) to improve the performance of current H.264 intra prediction via batch learning. In addition, we only use single Macro Block type and one intra prediction mode with high prediction performance to simplify mode decision procedure. In our knowledge, this work is the first approach to apply a statistical learning method for prediction of video sequences. Therefore, we introduce theoretical backgrounds of SVR, and show the possibility of this challenge for video compression. From the experimental results, statistical learning based intra prediction improves significantly the average Peak Signal-to-Noise Ratio of intra prediction than the performance of current H.264.
A New FPGA Implementation of a Time-to-Digital Converter Supporting Run-Time Estimation of Operating Condition Variation

A Time-to-Digital Converter (TDC) is widely used in applications that need to measure the time interval between events. Previous designs based on a feedback loop and an extended delay line suffers from poor accuracy caused by Process, Voltage, and Temperature (PVT) variations of the feedback path. This paper proposes a novel design of a synthesizable TDC that can estimate the operating event at run-time. The proposed TDC includes a ring oscillator of which oscillation period is measured at run-time to detect any change of operating event. The proposed TDC is implemented by using Xilinx Spartan-6 LX9 FPGA with 50MHz oscillator and it achieves about 19ps resolution. For 3ns time interval, the TDC detects it as 2.989ns on average with the standard deviation of about 148ps at 70°C.
Nanostructured Metal–Insulator–Metal Metamaterials for Refractive Index Biosensing Applications: Design, Fabrication, and Characterization

Nanofabrication of nanostructured metal-insulator-metal metamaterial (NMIM2) by the electron beam lithography and the liftoff technique is reported in this paper. The NMIM2 consists of periodic arrays of gold (Au) nanotriangles deposited on a gold layer (acting as a mirror) separated by a thin dielectric insulator. Such an NMIM2 stack was fabricated on a silicon wafer. Reflection of the NMIM2 was measured by the Fourier transform infrared spectroscope. The experimental measurement for reflection coefficients are in good agreement with the full-wave finite-different time-domain simulation results. At resonance, we numerically observed a strong field localized inside the gap between the Au nanostructures and the Au mirror, resulting in a strong confinement of incoming light within the insulator spacer and, thus, a pronounced absorption at telecommunication wavelengths. This resonant spectral response is investigated for sensitive label-free refractive index biosensing applications.
Planar, high-gain, substrate-integrated cavity antenna in the terahertz frequency range

In this paper, we propose a planar and highly directive cavity type of antenna in the terahertz frequency range. The antenna consists of a frequency selective surface (FSS) and an open-ended narrow slotline dipole, which are both lithographically patterned on a high-permittivity gallium-arsenide substrate. The FSS in conjunction with the ground plane of the slitline forms a Fabry-Perot resonator and results in significant directivity enhancement. The simulation results show that the substrate volume determines the effective permittivity of the cavity for the resonance operation. The optimized antenna, which has a size of about 3600 μm × 3600 μm × 175 μm, produced a maximum gain of 14.6 dBi, a radiation efficiency of 55%, and side lobe levels of -14.0 dB and -16.4 dB in the two principal planes at a resonance frequency of 317 GHz.
A two dimensional finite difference time domain analysis of quiet zone fields of a low frequency reflector

The authors present an analysis of the reflector of a low-frequency anechoic chamber in two dimensions using the FDTD (finite-difference time-domain) method. A total field formulation is used for determination of the quiet zone fields of the low-frequency reflector. Two source excitations are examined. An analytic function is defined as the excitation source for the first example and an application of the theorem reciprocity yields the excitation source for the second example. The 2-D-FDTD results are compared with results from a 3-D corrected physical optics calculation and agreement is obtained.<<ETX>>
Efficient Inter-View Motion Vector Prediction in Multi-View HEVC

When multi-view video sequences are encoded, the efficient motion vector prediction (MVP) is one of the most important techniques to increase the coding performance. The predictive MV should be highly correlated with the actual MV of the current block to be encoded. In this paper, we explain the inefficiency of the MVP algorithm in the multi-view high efficiency video codec (MV-HEVC) standard. In order to solve the inefficiency problem, we propose an enhanced advanced motion vector prediction algorithm in which the geometry interrelation between two neighboring views is derived based on epipolar geometry, similarity transform, and affine transform, and then predicted motion vectors (PMVs) for efficient MV coding are generated using obtained geometry relation. The experiment results show that the proposed scheme outperforms conventional MV-HEVC with a 1.32%–1.19% coding gain because it provides more efficient PMVs than conventional algorithms.
An improved artificial immune network for solving construction site layout optimization

Nature-inspired algorithms are often used to find optimal solutions for many combinatorial problems. An immune inspired algorithm, opt-aiNet algorithm, is well known for function optimization. In this paper, we develop a combination of local search with opt-aiNet, called lopt-aiNet, to solve construction site layout (CSL) problem. The effectiveness of the proposed algorithm is investigated through experiments on some datasets taken from the state-of-art and a randomly created dataset. Experimental results show that the lopt-aiNet can produce optimal transportation cost with lower run time compared to the site layouts generated by metaheuristics: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and aiNet.
RF loading effects of aircraft seats in an electromagnetic reverberating environment

Loading effects of aircraft seats in an electromagnetic reverberating environment are investigated. The effects are determined by comparing the reverberation chamber's insertion losses with and without the seats. The average per-seat absorption cross-sections are derived for coach and first class seats, and the results are compared for several seat configurations. An example is given for how the seat absorption cross-sections can be used to estimate the loading effects on the RF environment in an aircraft passenger cabin.
FPGA design of high throughput LDPC decoder based on imprecise Offset Min-Sum decoding

This paper first proposes two new LDPC decoding algorithms that may be seen as imprecise versions of the Offset Min-Sum (OMS) decoding: the Partially OMS, which performs only partially the offset correction, and the Imprecise Partially OMS, which introduces a further level of impreciseness in the check-node processing unit. We show that they allow significant reduction in the memory (25% with respect to the baseline) and interconnect, and we further propose a cost-efficient check-node unit architecture, yielding a cost reduction of 56% with respect to the baseline. We further implement FPGA-based layered decoder architectures using the proposed algorithms as decoding kernels, for a (3, 6)-regular Quasi-Cyclic LDPC code of length 1296 bits, and evaluate them in terms of cost, throughput and decoding performance. Implementation results on Xilinx Virtex 6 FPGA device show that they can achieve a throughput between 1.95 and 2.41 Gbps for 20 decoding iterations (48% to 83% increase with respect to OMS), while providing decoding performance close to the OMS decoder, despite the impreciseness introduced in the processing units.
Motion-decision based spatiotemporal saliency for video sequences

An adaptive spatiotemporal saliency algorithm for video attention detection using motion vector decision is proposed, motivated by the importance of motion information in video sequences for human visual system. This novel system can detect the saliency regions quickly by using only part of the classic saliency features in each iteration. Motion vectors calculated by block matching and optical flow are used to determine the decision condition. When significant motion contrast occurs (decision condition is satisfied), the saliency area is detected by motion and intensity features. Otherwise, when motion contrast is low, color and orientation features are added to form a more detailed saliency map. Experimental results show that the proposed algorithm can detect salient objects and actions in video sequences robustly and efficiently.
Semiconductor Optical Amplifier-Based Wavelength Conversion of Nyquist-16QAM for Flex-Grid Optical Networks

We experimentally demonstrate semiconductor optical amplifier (SOA)-based wavelength conversion of 3 × 25 GBd Nyquist-16QAM signal for a flex-grid network. The conversion efficiency (CE) and power penalty of each of three channels during single pumped SOA wavelength conversion are studied with respect to three different channel spacings (or frequency grids). The BER performance of all converted channels fall below the FEC threshold of 3.8 × 10-3, even with a 50 GHz grid. The results show the tradeoff between channel spacing, CE, and BER power penalty. Closely packed channels, which clearly increase spectral efficiency, are also shown to decrease conversion power penalty, potentially counter balancing increased crosstalk levels. These results can be used to optimize routing and spectrum allocation strategy when SOA wavelength converter(s) are present in the optical link.
Structures for M-channel perfect-reconstruction FIR QMF banks which yield linear-phase analysis filters

The authors develop structures for FIR (finite impulse response) perfect-reconstruction QMF (quadrature mirror filter) banks, which cover a subclass of systems that yield linear-phase analysis filters for arbitrary M. The parameters of these structures can be optimized to design analysis filters with minimum stopband energy which at the same time have linear phase and satisfy the perfect-reconstruction property. If there are M subbands, then depending on whether the coefficients h/sub k/(n) of each analysis filter are symmetric or antisymmetric, several combinations of filter banks are possible. Some of these permit perfect reconstruction and some do not. For a given M, the authors develop a formula for the number of combinations for a subclass of linear-phase perfect-reconstruction structures. As an example, they elaborate on a perfect-reconstruction linear-phase lattice structure for three channels. The lattice structure is such that, regardless of the parameter values, the QMF bank enjoys the perfect-reconstruction property while at the same time the analysis filters have linear phase. A design example is presented, along with tables of impulse response coefficients.
A directional decomposition: theory, design, and implementation

We propose a new directional decomposition of images. Unlike the conventional original directional filter banks (DFB) with eight directional subbands, our DFB has six directional highpass and two lowpass subbands. The newly constructed DFB is maximally decimated and perfect reconstruction. We also show how to implement the new DFB by cascading three two-channels filter banks and discuss filter design issue related to the structure.
RpR: A Trust Computation Model for Social Internet of Things

Social Internet of Things (SIoT) is an evolutionary idea which combines traditional IoT models with social network paradigms. "Objects" in SIoT formulate social relationships with other "trusted objects" according to the relationships of their owners which deliver trustworthy services on request. From our trust platform concept to identify vital trust metrics, attributes, we propose a Recommendations plus Reputations based Trust Computational Model (RpR) that enables objects in SIoT to build associations in a trustworthy manner. A numerical model is developed to estimate trust of each object based on Recommendation, Reputation parameters. Next, both estimates are merged together, a robust algorithm is proposed. Finally, we demonstrate, validate the usefulness of RpR over prior approaches through simulations, analysis. The aim of our approach is to facilitate accurate modeling of trustworthiness in distributed SIoT environments.
Fabrication of commercially viable anodic aluminum oxide membranes by anodizing commercial aluminum cooking foils

One of most significant obstacles in practical application of inorganic membranes is their very high price, compared to cheap polymeric membranes, In the present paper, an attempt to overcome high price of anodic aluminum oxide (AAO) membranes, due to relatively high price of aluminum raw material and relatively complicate and long processing procedure involved in anodization, was made by using commercial aluminum cooking foils as a raw material and by anodizing them in oxalic acid at two different voltages until through-hole pores formed up to the bottom surface. The results showed that cheap AAO membranes could be fabricated using that method if the surfaces of the aluminum cooking foils were well electro-polished. However, self-ordering of pores was more or less deteriorated due to the presence of relative large amount of impurity elements‥
The new maximum power point tracking algorithm using ANN-based solar PV systems

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 Card DSPACE 1104.
Using Adaboost on contourlet based image deblurring for Fluid Lens Camera Systems

The Fluidic Lens Camera System provides an exciting opportunity for the Image Processing Community. Designed for a surgical environment, this camera has higher magnification and has better portability than traditional laparoscopic cameras. From an image processing prospective, the fluid causes non-uniform blur of different color planes. While the green image is sharp, the red and blue images are blurred. Previous methods have been developed to separate out the edge and shading components of the green image and to use the edge information in green to replace the blurred blue edges. This algorithm succeed in most areas, however in some areas, color bleeding artifacts occurred. We restate this problem as a classification problem. Using the contourlet and wavelet coefficients as features, the proposed algorithm determines in what areas color bleeding will occur and does not apply the sharpening algorithm in these areas. By applying the previous contourlet method in areas where it succeeds, we can produce an overall sharper image with reduced color bleeding artifacts. The ability to correctly classify when the previous algorithm will succeed is crucial to the success of the algorithm. The principal application is medical imaging, however, the fields of satellite pan-sharpening and image denoising can benefit from the results found in this paper.
The Design of On-the-Fly Virtual Channel Allocation for Low Cost High Performance On-Chip Routers

Network-on-Chip (NoC) is an important communication infrastructure for System-on-Chips (SoCs). Designing high performance NoCs with minimized area overhead is becoming a major technical challenge. In this paper, we propose the on-the-fly virtual channel (VC) allocation for low cost high performance on-chip routers. By performing the VC allocation based on the result of switch allocation, the dependency between VC allocation and switch traversal is removed and these stages can be performed in parallel. In this manner, the pipeline of a packet transfer can be shortened in a non-speculative fashion. We have implemented the proposed router on FPGA and evaluated in terms of communication latency, throughput and hardware amount. The experimental results show that, the proposed router with on-the-fly VC allocation reduces the communication latency by 27.3%, and improves throughput by 21.4% as compared to the conventional VC router. In comparison with the look-ahead speculative router, it improves the throughput by 6.2% with 17.6% reduction of area for control logic.
Linear phase paraunitary filter banks with unequal-length filters

This paper presents the theory, design, and efficient implementation of a new class of linear phase paraunitary filter banks (LPPUFB) which find application in transform-based image coding. These new LPPUFB have filters of different lengths: longer filters are kept for low-frequency components to prevent blocking, while shorter filters are reserved for high-frequency components to minimize ringing. The proposed lattice factorization structurally enforces the unequal-length property along with LP and PU properties, and it is robust under the quantization of lattice coefficients. Design and image coding examples are also presented to confirm the validity of the theory.
A High-Definition LIDAR System Based on Two-Mirror Deflection Scanners

This paper addresses the problem of adopting a state-of-art laser marking system with a two-mirror deflection scanner to make a high-definition light detection and ranging (LIDAR) system. To this end, a galvanometer scanner is modeled with parameterization and then the well-known raster scanning strategy is analyzed considering the physical scanning movement and the minimum spanning tree. As a result of this analysis, the relationship between the field of view (FOV) of the captured image and the scanning speed is clearly described. Furthermore, sufficient conditions are derived for an acquired image to fully cover the FOV and also for captured objects to be well aligned for a target frame rate. Finally, a prototype LIDAR system is developed to verify the proposed concepts and to prove that it successfully generates images at various resolutions depending on the target frame rates. Experimental results show that the scanner achieves the frame rates of 17.6, 9.0, and 4.6 frames per second fps for image sizes of <inline-formula> <tex-math notation="LaTeX">$240\times 16$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$240\times 32$ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$240\times 64$ </tex-math></inline-formula> resolutions, respectively.
Identification of a gas furnace process using WSDP model

This paper presents the identification of a gas furnace process using the so called wavelet based State Dependent Parameter (WSDP) models. Here, each of the process' dominant dynamics are characterized by a state dependent parameter in form of wavelet which is able to provide valuable insight, and effective means to measure the system's degree of nonlinearity. To illustrate the advantages of the proposed modeling approach, the identified model is benchmarked with a few welknown reported results, i.e. fuzzy logic, generalised kernel and linear ARX models.