nils-herrmann/clean_scirepeval huggingface dataset:
Experimental research on the friction force of pneumatic cushion cylinder

By the means of test rig for friction force measurement which is set up, the friction force of pneumatic high speed cushion cylinder are investigated experimentally. Under various working condition, the ordering variation of friction force of pneumatic cylinder is obtained by analyzing the detail of test data. The influence of friction force of pneumatic cylinder is compared under various working condition when pneumatic cylinder is working. As the variety feature of friction force of pneumatic cylinder in the stage of cushion, the segmented function of curve fitting of friction force is given in this stage, which provides the theoretical basis for the model of high speed cylinder cushion.
A reference picture selection scheme for video transmission over ad-hoc networks using multiple paths

Enabling video transmission over ad-hoc networks is more challenging than over conventional mobile networks because a connection path in an ad-hoc network is highly error-prone and the path can go down frequently. On the other hand, it is possible to establish multiple paths between a source and a destination, which provides an extra degree of freedom in coding algorithm design. This paper presents a feedback-based reference picture selection scheme for video transmission over ad-hoc networks. Encoded video streams are transmitted over multiple paths and the reference frames for motion compensated prediction are selected according to the feedback information about the paths’ condition. Simulations under the two paths scenario have shown significant improvement over two standard techniques, layered coding and video redundancy coding, which do not use feedback. A novel statistical model for the ad-hoc multi-path environment is also proposed and used in our simulation of transmission loss.
Hybrid constellation mapping for punctured-node LDPC

Punctured-node LDPC can provide close-to-Shannon-limit waterfall performance and low error floor when carefully designed. In this paper, hybrid constellation mapping is proposed to improve performance of coding and modulation with punctured-node LDPC. General bit interleaving is performed over original puncture-node LDPC to obtain hybrid constellation mapping. By applying non-uniform constellation design methodology, the specific constellation is designed, under which the average mutual information (AMI) is approaching the capacity. Compared with punctured-node LDPC with BPSK modulation, hybrid constellation mapping can provide more than 0.2 dB gain in i.i.d Rayleigh channel according to simulation. Moreover, fewer number of iterations is needed in decoding algorithm of hybrid constellation mapping for punctured-node LDPC, which can reduce decoding complexity and power consumption at high SNR.
A Novel No-Reference Video Quality Metric for Evaluating Temporal Jerkiness due to Frame Freezing

In this work, we propose a novel no-reference (NR) video quality metric that evaluates the impact of frame freezing due to either packet loss or late arrival. Our metric uses a trained neural network acting on features that are chosen to capture the impact of frame freezing on the perceived quality. The considered features include the number of freezes, freeze duration statistics, inter-freeze distance statistics, frame difference before and after the freeze, normal frame difference, and the ratio of them. We use the neural network to find the mapping between features and subjective test scores. We optimize the network structure and the feature selection through a cross-validation procedure, using training samples extracted from both VQEG and LIVE video databases. The resulting feature set and network structure yields accurate quality prediction for both the training data containing 54 test videos and a separate testing dataset including 14 videos, with Pearson correlation coefficients greater than 0.9 and 0.8 for the training set and the testing set, respectively. Our proposed metric has low complexity and could be utilized in a system with real-time processing constraint.
Automatic mouse embryo brain ventricle segmentation, gestation stage estimation, and mutant detection from 3D 40-MHz ultrasound data

Volumetric analysis of brain ventricles (BVs) is important to the study of normal and abnormal development of the central nervous system of mouse embryos. High-frequency ultrasound (HFU) is frequently used to image embryos because it is real-time, non-invasive, and provides fine-resolution images. However, manual segmentation of BVs from 3D HFU volumes remains challenging and time consuming. Therefore, automatic segmentation, staging, and mutant detection algorithms are needed for studies with large embryo counts. An accurate and automatic method to segment BVs from high-frequency ultrasound images has been stated in a prior work. This paper presents novel algorithms for deriving the Y-skeleton of a BV region and decomposing the BV region into five components (fourth ventricle, aqueduct, third ventricle and two lateral ventricles). Embryo staging and mutant detection are accomplished by analyzing the volume profile along the BV skeleton and the volumes of the five BV components.
Optimal Design of the High Order FIR Multi-Band-Stop Filters

This paper traverses the relations between the amplitude-frequency response of FIR filters with the linear phase and the parallel algorithm of neural network, which its activation matrix is Hd - CTW , presents and proves the convergence theorem of the neural-network parallel algorithm, and gives the optimal design examples of high order FIR multi-band-stop digital filters. The results show that the parallel algorithm is efficient in the field of optimal design on the high order FIR multi-band-stop digital filters with the linear phase
On Complexity Modeling of H.264/AVC Video Decoding and Its Application for Energy Efficient Decoding

This paper proposes a new complexity model for H.264/AVC video decoding. The model is derived by decomposing the entire decoder into several decoding modules (DM), and identifying the fundamental operation unit (termed complexity unit or CU) in each DM. The complexity of each DM is modeled by the product of the average complexity of one CU and the number of CUs required. The model is shown to be highly accurate for software video decoding both on Intel Pentium mobile 1.6-GHz and ARM Cortex A8 600-MHz processors, over a variety of video contents at different spatial and temporal resolutions and bit rates. We further show how to use this model to predict the required clock frequency and hence perform dynamic voltage and frequency scaling (DVFS) for energy efficient video decoding. We evaluate achievable power savings on both the Intel and ARM platforms, by using analytical power models for these two platforms as well as real experiments with the ARM-based TI OMAP35x EVM board. Our study shows that for the Intel platform where the dynamic power dominates, a power saving factor of 3.7 is possible. For the ARM processor where the static leakage power is not negligible, a saving factor of 2.22 is still achievable.
Air-gap/SiO2 liner TSVs with improved electrical performance

This paper reports fabrication and characterization of TSVs that use combined air-gap/SiO2 as the insulators. Fabrication technologies based on reactive ion etching (RIE) of benzocyclobutene (BCB) sacrificial layers have been developed to fabricate uniform and high aspect-ratio air-gaps, and air-gaps with thickness of 2 μm and aspect-ratio of 25:1 have been successfully fabricated. The measured capacitance-voltage (C-V) and current-voltage (I-V) curves at room temperature and high temperatures show that the TSVs with air-gap/SiO2 liners have low capacitance and leakage current. Compared with the TSVs using a sole air-gap insulator, the additional SiO2 liners protects the TSV from being influenced by the residues of sacrificial materials, and the electrical performance and thermal stability are improved.
Multiple description coding using pairwise correlating transforms

The objective of multiple description coding (MDC) is to encode a source into multiple bitstreams supporting multiple quality levels of decoding. In this paper, we only consider the two-description case, where the requirement is that a high-quality reconstruction should be decodable from the two bitstreams together, while lower, but still acceptable, quality reconstructions should be decodable from either of the two individual bitstreams. This paper describes techniques for meeting MDC objectives in the framework of standard transform-based image coding through the design of pairwise correlating transforms. The correlation introduced by the transform helps to reduce the distortion when only a single description is received, but it also increases the bit rate beyond that prescribed by the rate-distortion function of the source. We analyze the relation between the redundancy (i.e., the extra bit rate) and the single description distortion using this transform-based framework. We also describe an image coder that incorporates the pairwise transform and show its redundancy-rate-distortion performance for real images.
Design and implementation of a dual-interface radar data recorder

This paper analyses the design and implementation of a small-scale dual-interface radar data recorder based on DSP+FPGA. It has two types of interfaces: solid-state IDE hard disk and RJ45. The recorder can save sampling data of original radar waveforms in real time for further analysis and validation. It adapts to a variety of application environments and has a high storage speed and reliable operation performance. It can be widely used in radar testing and flight experiments.
Background subtraction based on adaptive non-parametric model

Object detection is an important basis for tracking and recognition in visual surveillance systems via stationary cameras. The traditional background subtraction method is difficult to detect objects accurately in the scenes, because the background is usually cluttered and not completely static. In this paper, we propose a new method for background subtraction based on adaptive non-parametric kernel density estimation. The bandwidth is chosen adaptively based on sample and estimation points, and color combing gradient are measured for pixel features. Computation complexity is also reduced by reasonable and valid assumptions. Experiments on two sequences in outdoors demonstrate that the method can model and subtract the background accurately.
An Empty Bottle Intelligent Inspector Based on Support Vector Machines and Fuzzy Theory

This text studies empty bottle intelligent inspector based machine vision instead of manual inspection. The system structure is illustrated in detail in this paper. The text also presents the method to extract features from images. After extracting feature, the fuzzy support vector machines are used as classifier. A genetic algorithm based on optimization algorithm is simultaneously proposed to confirm the parameters of the fuzzy support vector machines, ensuring that the fuzzy SVMs have good classification ability. The experiments demonstrate that using this method to inspect empty bottles, the accuracy rate may reach above 96%
Relaxing Media Requirements by Using Multi-Island Two-Dimensional Magnetic Recording on Bit-Patterned Media

We introduce and investigate a new multi-island bit representation scheme with bit-patterned media (BPM) to increase the tolerance to the reader noise and the media noise compared with the standard BPM with a single island/bit and to granular media. The key idea is to use multiple islands in two dimensions to represent one bit. The redundancy in such a multi-island representation reduces the impact of the write in errors and decreases the effect of the media noise. We show that these multi-island representations offer improved bit error rate (BER), although only one readback sample per bit is used for equalization and detection. Here, a micromagnetic writing model and a read channel including media noise are used for the simulations, where optimized writer and reader architectures with one, two, and three read elements are investigated. Simulations at a 1 Tb/in2 channel bit density, for the target BER of 10-2 and readback with two readers, indicate that the readback of BPM recording (BPMR) based on 1 Tdot/in2 (1 dot/bit), 2 Tdots/in2 (2 dots/bit), and 4 Tdots/in2 (4 dots/bit) island density can tolerate 1, 3.1, and 3.3 dB more reader noise compared with the granular media. For readback with two readers, at 10-2 target BER, writing with 4 Tdots/in2 and 2 Tdots/in2 island density can tolerate the media noise (modeled by island position jitter and island size fluctuation) levels of 11% and 8.5% compared with the 1 Tdot/in2 with the media noise level of 5%. When the channel bit density is increased to 1.5 Tb/in2, such a multi-island approach can still provide improved reader noise and media noise tolerances compared with the standard BPMR with one bit per island and to granular media at the same density.
Dual Wavelength Silicon-Based-Photodetector for Biomedical Sensing System Applications

The article proposed dual wavelength silicon based photo detector with multi-layer structure, was fabricated and characterized with dual wavelength enhanced operating. We proposed the dual wavelength response of the silicon based bio-photo-detector. It can be enhanced by introducing thin porous silicon layer as the base region of transistor. The device process of manufacture is suitable in design of visible-light sensitive bio-photo-detectors. The experimental results showed that the dual wavelength responses in the developed devices were enhanced as compared to the silicon-based homo-junction photo-detectors in optical parameters, which indicated that the developed bio-photo-detector showed potential for practical silicon based biomedical device and system applications.
Interval type-2 TSK fuzzy neural model for illuminant estimation

This paper presents a type-2 TSK fuzzy neural approach to establish a model for estimation of unknown illuminant, i.e., color temperature, of a digitally captured image based only on the contents of the image. The estimated temperature may be further utilized to perform white balance for the image. The results demonstrate major advancements of the proposed approach over previous and existing methods. The comparative study also suggests that the proposed method is more robust to generic images and varieties of illuminants and scenes than do existing approaches.
An Improved Self-calibration Method for Active Stereo Camera

Camera calibration is an important prerequisite for retrieving 3D information of scene. Considered with peculiar configuration of stereo camera, some reasonable assumptions are introduced to obtain simplified stereo camera model which assumes that principle points locating in the image center, camera axes perpendicular with camera plane, focal length of stereo camera remaining constant during movement. Based on those constrains, a self-calibration method for moving stereo camera is represented in this paper, which determines camera parameters through calculating fundamental matrix corresponding to successive motion sequence. Experimental results on dynamic stereo camera shows that this self-calibration approach has good real-time performance and high resolution when vergence angel and tilt angel is confined to certain range during movement
A motion compensating prior for dynamic MRI reconstruction using combination of compressed sensing and parallel imaging

Many areas in signal processing have benefited from the emergence of compressed sensing and sparse reconstruction methods, one of which is magnetic resonance imaging (MRI). Recent studies showed that MRI acquisition can be highly accelerated with the joint use of compressed sensing and parallel imaging methods. It is also suggested that dynamic MRI can be further improved by making use of temporal correlations. Although methods using motion compensation has been proposed to exploit temporal dependence, most of these require reference frames and/or a sub-portion of k-space to be fully sampled. In this paper we propose a new approach to exploit the motion information during compressed sensing reconstruction without any requirement for reference frames, modeled motion or a specific sampling pattern on the k-space measurements.
Indoor localization for sparse wireless networks with heterogeneous information

Wireless indoor localization is crucial in ubiquitous computing environments. Although accurate and efficient indoor localization can be provided in dense wireless networks, most existing algorithms fail to locate a mobile user in sparse deployment networks. In order to address this issue, this paper presents a new fingerprinting localization algorithm based on cost function where received signal strengths from heterogeneous wireless networks are applied. To further improve the positioning accuracy, a spatial context constraint area for fingerprint matching is constructed based on the continuity and smoothness of pedestrian movement trajectories. Experimental results show that the proposed algorithm using heterogeneous information can significantly improve the accuracy of indoor pedestrian localization in sparse wireless networks.
Logic Restructuring Using Node Addition and Removal

This paper presents a logic restructuring technique named node addition and removal (NAR). It works by adding a node into a circuit to replace an existing node and then removing the replaced node. Previous node-merging techniques focus on replacing one node with an existing node in a circuit, but fail to replace a node that has no substitute node. To enhance the node-merging techniques on logic restructuring and optimization, we propose an NAR approach in this paper. We first present two sufficient conditions that state the requirements of added nodes for safely replacing a target node. Then, an NAR approach is proposed to quickly detect the added nodes by performing logic implications based on these conditions. We apply the NAR approach to circuit minimization together with two techniques: redundancy removal and mandatory assignment reuse. We also apply it to satisfiability (SAT)-based bounded sequential equivalence checking (BSEC) to reduce the computation complexity of SAT solving. The experimental results show that our approach can enhance our prior automatic test pattern generation-based node-merging approach. Additionally, our approach has a competitive capability of circuit minimization with 44 times speedup compared to a SAT-based node-merging approach. For BSEC, our approach can work together with other optimization technique to save a total of approximately 39-h verification time for all the benchmarks.
Perceptual Quality Assessment of Video Considering Both Frame Rate and Quantization Artifacts

In this paper, we explore the impact of frame rate and quantization on perceptual quality of a video. We propose to use the product of a spatial quality factor that assesses the quality of decoded frames without considering the frame rate effect and a temporal correction factor, which reduces the quality assigned by the first factor according to the actual frame rate. We find that the temporal correction factor follows closely an inverted falling exponential function, whereas the quantization effect on the coded frames can be captured accurately by a sigmoid function of the peak signal-to-noise ratio. The proposed model is analytically simple, with each function requiring only a single content-dependent parameter. The proposed overall metric has been validated using both our subjective test scores as well as those reported by others. For all seven data sets examined, our model yields high Pearson correlation (higher than 0.9) with measured mean opinion score (MOS). We further investigate how to predict parameters of our proposed model using content features derived from the original videos. Using predicted parameters from content features, our model still fits with measured MOS with high correlation.
An estimation of distribution algorithm for the multi-objective flexible job-shop scheduling problem

In this paper, an effective estimation of distribution algorithm (EDA) is proposed to solve the multi-objective flexible job-shop scheduling problem (MFJSP) to minimize the maximum completion time, the total workload of machines and the workload of the critical machine simultaneously. Within the framework of EDA, the new individuals are generated by sampling a probability model, which is built and updated with the superior sub-population by a proposed mechanism. Moreover, the EDA utilizes multiple strategies in a combination way to generate the initial solutions, and used a local search strategy based on critical path to enhance the exploitation ability. Based on the Taguchi method of design-of-experiment, the influence of parameter setting is investigated and suitable parameters are suggested. Finally, numerical simulation based on some well-known benchmarks and comparisons with some existing algorithms are carried out. The results demonstrate the effectiveness of the proposed EDA to solve the MFJSP.
In&Out: Restructuring for threshold logic network optimization

Threshold logic attracts a lot of attention recently due to nanotechnology advances on its physical implementation. Hence, many previous works have focused on the synthesis of threshold logic networks from the Boolean functions. In this paper, we propose a tool, In&Out, which optimizes a threshold logic network from the physical implementation perspective. In&Out consists of two techniques: Add-in and Remove-out. The Add-in is to transform a threshold logic network into an implementation friendly network while the Remove-out is to remove redundant gates from the network. We conducted the experiments on a set of IWLS 2005 benchmarks. The experimental results show that the proposed tool can reduce the implementation cost of threshold networks up to 10% for the benchmarks.
A ring-based architecture for a multi-tier transactional system

Many asynchronous distributed transactional systems use a coordinator, either an application server or an elected database server, to handle the progress of a transaction. When the coordinator fails or the network becomes partitioned, the transaction may block. In this paper we propose a ring-based transactional architecture for distributed database systems. The transaction can progress even if the network is partitioned or the coordinator dies, and the protocol will ensure uniform agreement on success or failure of the transaction. This architecture delivers multiple tokens which piggyback a vector clock with each database server’s state, and each database server uses the information in the token to make a decision of when to go to the next state.