nils-herrmann/clean_scirepeval huggingface dataset:
Improved non-intrusive polynomial chaos for reliability analysis under hybrid uncertainty

With the increasing of systems' scale and complexity, reliability analysis faces more challenges which mainly include hybrid uncertainty, implicit limit state function and numerous uncertain input variables. Non-intrusive polynomial chaos (NIPC) is a promising technology for uncertainty quantification with high efficiency and accuracy. However, as polynomial chaos is defined in probability space, NIPC is not applicable to reliability analysis under hybrid uncertainty with multiple input variables. To address this issue, an improved NIPC approach is proposed that Klir log-scale transformation is employed to unify fuzzy variables and random variables. And a combinatorial optimization algorithm is developed to efficiently select the optimal collocation points for NIPC with multiple uncertain inputs. Comparative study on the airborne retractable system shows that the proposed approach can achieve higher accuracy than response surface method with identical computational cost.
A direct measurement scheme of amalgamated aging effects with novel on-chip sensor

Aggressive technology scaling has led to a significant reduction of device reliability. As a consequence Integrated Circuits (ICs) reliability became a major issue and Dynamic Reliability Management (DRM) schemes have been proposed to assure ICs' lifetime reliability. Though, up to date, various aging sensors have been proposed, few of them can provide real quantitative aging measurements. In view of this, we propose a direct measuring scheme by using the drain current as aging indicator. We designed a novel on-chip aging sensor able to detect the amalgamated aging effects of ICs caused by joint failure mechanisms. This is achieved by detecting the peak power supply current (Ipp) degradation from the device and/or circuit, which is a signature of the total drain current. Unlike the existing aging sensors which indirectly estimate the aging status of a device, the proposed sensor allows for direct aging assessment for single device and/or circuit blocks. Simulation results using the TSMC 65nm technology indicate that the proposed sensor can operate at 1GHz. Accelerated test simulation in Cadence for a set of ISCAS85 benchmark circuits indicates that the drain current exhibits a similar aging rate as the threshold voltage for the entire circuit lifetime, but with a better sensitivity towards the End-of-Life (EOL), which demonstrates the validity and practical relevance of the proposed aging monitoring framework.
Design a Learnable Self-feedback Ratio-Memory Cellular Nonlinear Network (SRMCNN) for Associative Memory Applications

The self-feedback ratio-memory cellular nonlinear network (SRMCNN) structure with learning capability for associative memory applications is designed and analyzed. The architecture was realized the modified Hebbian learning algorithm in the SRMCNN is proposed. It can learn the exemplar patterns and correctly output the recognized patterns in the associative memory. The weights of B template are generated from the product of the desired output pixel value and the nearest five input neighbouring elements as associative memory for all input exemplar patterns. The learned weights are processed in the ratio with the summation of absolute coefficients on the B template to enhance the feature of pattern. As the results shown that it was learned and recognized 8 incompletely exemplar patterns and output correctly pattern. The structure of the SRMCNN with B template and the modified Hebbian learning algorithm for associative memory are implemented in the 9times9 VLSI circuits for the TSMC 0.25 mum 1P5M CMOS technology. The capability of SRMCNN for the more variant exemplar patterns learning and recognition is greatly improved in the auto-associative memory applications
Edge-preserving image coding based on local modeling of images

A coding scheme which encodes each contiguous block of an image based on its local structure is developed. Three different types of models are constructed to characterize the image patterns occurring most frequently in a small block. The average bit rate is reduced by making use of the special constraint among the pixels in an oriented model, where the intensity variation is along only one direction. Judging from the image quality around edges, the reconstructed images with a bit rate less than 0.68 bit/pixel are perceptually superior to those obtained by the block and truncation coding at a bit rate of 1.64 bits/pixel. The complexity of this algorithm increases linearly with the size of the block and the number of orientations considered, which is much lower than that of the standard vector quantization techniques.<<ETX>>
Flaw detection and measurement for mobile display

With advanced small-pixel and high-resolution mobile displays, the display are obtaining smaller pixel size and higher resolution on thin-film-transistor (TFT) array process. This study proposed the flaw detection and measurement in small pixel design mobile displays based on oxide-semiconductor-based TFT liquid crystal displays. The measurement is with respect to electrical-physic characterisation metrics and observer studies. Studies resulted in small-sized pixel TFT array between the flaw detection performance and maker preference approaches. Detection performance factors provided information on the differences among small pixel design for advanced mobile display technologies. The results of the detection performance and preference study showed that the application for advanced mobile display panels. It also shown that critical pixel defect played an important role than previously seen in non-small pixel TFT array panels for managing process yield. The method of voltage imaging for detection, developed in this study provides an initial insight into the high resolution of small-sized pixel designs for advanced mobile displays with precision and diagnostic images in portable devices.
Multiple description image coding using signal decomposition and reconstruction based on lapped orthogonal transforms

This paper considers the use of multiple description coding (MDC) for image transmission in communication systems where long burst errors and sometimes complete channel failures are inevitable. A general framework for MDC is proposed, which uses nonhierarchical signal decomposition at the encoder and image reconstruction at the decoder. A realization of this framework using lapped orthogonal transforms (LOTs) is developed. In the encoder, the bitstream generated by a conventional LOT-based image coder is decomposed so that each description consists of a subsampled set of the coded LOT coefficient blocks. In the decoder, instead of using the inverse LOT directly, a novel image reconstruction technique is employed, which makes use of the constraints between adjacent LOT coefficient blocks and the smoothness property of common image signals. To guarantee a satisfactory reconstruction quality, the transform should introduce a desired amount of correlation among adjacent LOT coefficient blocks. The tradeoff between coding efficiency and reconstruction quality obtainable by using different LOT bases is investigated.
Recurrent Fuzzy Cerebellar Model Articulation Controller and Its Application on Robotic Tracking Control

A kind of recurrent fuzzy cerebellar model articulation controller (RFCMAC) model is presented. The recurrent network is embedded in the RFCMAC by adding feedback connections on the first layer to embed temporal relations in the network. A nonconstant differentiable Gaussian basis function is used to model the hypercube structure and the fuzzy weight. A gradient descent learning algorithm is used to adjust the free parameters. Simulation experiments are made by applying proposed RFCMAC on robotic manipulator tracking control problem to confirm its effectiveness.
Control strategy of flow on single layer of injection well

As the injection well flow control system of highly-intense water contained oil mining project is a complex embraced with time-varying, non-linear, severe interference, the complicate model and other problems, which results in a long adjusting time, and underground power loss. Traditional control application is difficult to achieve satisfactory effect of flow control dealing with the problem above. This paper has proposed and designed a new type of single-layer flow control strategy, which adopted variable universe adaptive fuzzy algorithm in the injection wells flow control, using fuzzy variable universe to automatically adapt to the changes in the parameter in the process to achieve online revision of the contraction-expansion factor. And establish a Matlab / Simulink simulation model of system for the unit step response simulation.
Adaptive stripe based patch matching for depth estimation

A novel stereo matching technique for depth estimation in stereoscopic image pairs is presented. The input image pair is preprocessed in the intensity domain and together with edge maps an adaptive mesh in which individual elements approximate linearly modeled regions are obtained. Then, an iterative stripe based, quadrilateral patch matching technique is employed to estimate the depth map from the image pair in a hierarchical manner. Finally, the resultant map is postprocessed to smooth the depth map at the patch borders. The quality of the test results demonstrates the effectiveness of the technique.
High-Frequency Characterization of Through-Silicon-Vias With Benzocyclobutene Liners

This paper presents design, fabrication, and high-frequency characterization of through-silicon-vias (TSVs) with benzocyclobutene (BCB) as the dielectric liner to exploit its low dielectric constant. Fabrication processes for BCB polymer liner TSVs are developed, and BCB-liner TSVs have been successfully fabricated in both low-resistivity silicon and high-resistivity silicon substrates for comparison. A de-embedding method that enables extraction of S-parameters from cascade TSV chains is developed based on the thru-reflect-line calibration algorithm, and the S-parameters of BCB-liner TSVs have been obtained from the measured transmission properties of cascade TSV chains with frequencies up to 25 GHz. Measurement results show that the BCB liner improves transmission properties of TSVs up to 10 GHz compared with SiO2-liner TSVs, and sub-strate resistivity dominates transmission properties for frequencies higher than 10 GHz.
Design of vehicle stability control of distributed-driven electric vehicle based on optimal torque allocation

This paper presented a hierarchical vehicle-stability-control design based on the longitudinal force distribution optimization for the handling and stability control of the distributed-driven electric vehicle. The 8-DOF vehicle model and the three-layer control system were developed. By selecting the sideslip angle and the yaw rate as the state variables and introducing the virtual control to decouple two control variables, the upper controller adopted the integral 2-DOF vehicle model to calculate the equivalent yaw moment for the vehicle stability. Under the restrictions of the vehicle actuators, the middle controller utilized the linear quadratic optimization (LQR) method to optimize the distribution of the front and rear steering angles and the tire longitudinal forces. The sliding-mode-based slip controller in the lower layer was also designed to reallocate the wheel torques. A simulation test was carried out to verify the effectiveness of the proposed design. Results show that the control system can make the vehicle follow the expectation effectively and enhance the vehicle handling and stability in extreme conditions with high speed as well as its active safety under the actuator failures.
Human action recognition system for elderly and children care using three stream ConvNet

Because of the change of family structure and population ageing, elderly and children care is become a very important issue in modern society. When adults are busy working, they have no time to care elderly and children who standalone in the home. This paper proposes an elderly and children care system to solve this important problem. The proposed intelligent surveillance system is based on action recognition technique of image processing. In this paper, a three stream convolution neural network is proposed for recognize human actions such as fall floor and baby craw. If the system detect abnormal activities are occurred, it will raise alarm and notice family members. In the experiment, there are totally 21 categories activities are collected from HMDB-51 dataset, UCF-101 dataset and Internet. The proposed system achieves 93.42% recognition rate of selected actions.
A 15-bit two-step sigma-delta ADC with embedded compression for image sensor array

This paper presents a novel incremental Σ-Δ ADC using two-step conversion and the fully-floating double-sampling integrator to greatly reduce the converting time. With a special procedure to solve the accuracy loss problem, the resolution of ADC is improved by one bit at the same time. What's more, another comparison is added during the conversion to detect redundant pixels in the image so that data compression is achieved in a simple way.
Subjective Quality Evaluation of Decoded Video in the Presence of Packet Losses

This paper investigates the perceptual quality of decoded video bitstreams after packet losses. We focus on low-resolution and low-bit rate video coded by the H.264/AVC encoder, and packet loss patterns likely in 3G wireless networks. We examine the impact of several factors on the perceptual quality, including the error length (the error propagation duration after a loss), the loss severity (measured by the drop in PSNR due to a loss), and loss location (forgiveness effect). We further propose an objective quality measure based on the findings of our study.
Super-consumer based reputation management for web service systems

In this paper, we propose a mechanism of using super consumers to manage reputation. Super consumers are consumers with more capabilities, such as cpu power, storage and bandwidth. Super consumers can serve as reputation managers to build global reputation for a service based on the opinions from all the members in the system. Super consumers can also build community-based reputation for a service, by forming their own communities based on similar interests and judgement criteria. Our experiments show that the system using both global and community-based reputation can perform better than the system using just global reputation.
Robust adaptive dynamical neural control for uncertain chaotic system

Robust adaptive control of chaotic system with uncertainty was investigated in the presence of modeling error. The scheme of adaptation was based on identification estimates via dynamical neural networks. By using proposed nonlinear adaptive controller, the chaotic signal of the unknown system dynamics tends to be driven into a well controlled steady state. Moreover, the mathematical proof of stability properties of the system was guaranteed. Finally, simulation results have demonstrated the effectiveness of the proposed method through application on the Chen's chaotic system.
Synthesis of silver particles decorated anodic aluminium oxide substrates for metal-enhanced fluorescence

Silver nanoparticles for metal-enhanced fluorescence (MEF) have been successfully synthesised by pulsed electrodeposition of silver in the anodic aluminium oxide (AAO) templates. X-ray diffraction and scanning electron microscopy indicate that the as-synthesised samples were composed of face-centred cubic Ag nanoparticles and the average nanoparticle size increased with the increasing electrodeposition time. The UV–visible reflection spectra were measured to investigate the surface plasma resonance absorbance. Taking rhodamine B as the probing molecule, high-quality MEF spectra were observed by excitation with a 480 nm laser line. The enhancement ability could be well controlled by simply adjusting the deposition times. The high enhancement factor suggests that this substrate could be used to fabricate ‘hot spots’ for MEF.
A Selection Model for Optimal Fuzzy Clustering Algorithm and Number of Clusters Based on Competitive Comprehensive Fuzzy Evaluation

Fuzzy c-means (FCM) and its variants suffer from two problems-local minima and cluster validity-which have a direct impact on the formation of final clustering. There are two strategies-optimization and center initialization strategies-that address the problem of local minima. This paper proposes a center initialization approach based on a minimum spanning tree to keep FCM from local minima. With regard to cluster validity, various strategies have been proposed. On the basis of the fuzzy cluster validity index, this paper proposes a selection model that combines multiple pairs of a fuzzy clustering algorithm and cluster validity index to identify the number of clusters and simultaneously selects the optimal fuzzy clustering for a dataset. The promising performance of the proposed center-initialization method and selection model is demonstrated by experiments on real datasets.
Partial directed coherence analysis of intracranial neural spikes in epilepsy patients

Intracranial electroencephalograms (EEG) provide a direct observation of neural activity by placing an electrode array on the cortical surface near the suspected epileptic foci. The neural spikes appeared during inter-ictal stages are mainly produced by abnormal neural discharges from epileptic foci. The topological mapping of spikes' potentials is commonly used to identify the epileptogenic zone. However, the propagations among multi-channel spikes are also important to identify the epileptic source activity. In addition, the changes of source activities in a series of consecutive spikes reveal the time-varying neural activations during discharge process, which provide alternative information for interpreting epileptic source activity. This paper proposes a spike classification based on the similarity of phase-space features to select candidate spikes from the intracranial EEGs recorded from an 8×8 electrocorticogram grid. Then, the partial directed coherence (PDC), which can provide the flow of source activity, at each spiking time point is computed. The outflow PDCs of all electrodes are therefore displayed on the grid. Our result showed that the derived source activities in the preceding spikes had high concentrated distributions but decreased in latter spikes. This implied the epileptic discharges were initially induced by a small-area cortex neurons and then spread out.
On the Performance of Space–Time Block-Coded MIMO Video Communications

The problem of efficient video communications over multiple-input-multiple-output (MIMO) wireless systems is of great significance due to the high capacity of the multiple antenna system. The high data rates provided by the MIMO system can be traded off with diversity gain by using different channel-coding schemes. Also, by using different video source-coding methods, high compression gain can be traded off with the error resilience gain. One should jointly consider source coding and channel coding when designing a MIMO wireless video system. However, little is known so far about what combinations of channel-coding and source-coding methods have the best overall performance in a MIMO system. In this paper, by comparing the performances of several different typical combinations through both theoretical and simulation studies, we show that no single combination is the best for the entire range of channel conditions, but rather, different combinations may be best for a subrange
Multiple error diagnosis in large combinational circuits using an efficient parallel vector simulation

This paper presents a parallel vector simulation-based approach to locating multiple errors in large combinational circuits. Two heuristics are proposed to avoid the explosion of the error space. Experimental results on a set of ISCAS'85 and two large benchmarks show that our approach efficiently identifies a small set of correctable nodes that contains the actual error sources. Thus, further error correction can be conducted on the erroneous implementation.
A probabilistic analysis method for functional qualification under Mutation Analysis

Mutation Analysis (MA) is a fault-based simulation technique that is used to measure the quality of testbenches in error (mutant) detection. Although MA effectively reports the living mutants to designers, it suffers from the high simulation cost. This paper presents a probabilistic MA preprocessing technique, Error Propagation Analysis (EPA), to speed up the MA process. EPA can statically estimate the probability of the error propagation with respect to each mutant for guiding the observation-point insertion. The inserted observation-points will reveal a mutant's status earlier during the simulation such that some useless testcases can be discarded later. We use the mutant model from an industrial EDA tool, Certitude, to conduct our experiments on the OpenCores' RT-level designs. The experimental results show that the EPA approach can save about 14% CPU time while obtaining the same mutant status report as the traditional MA approach.
Coded EXcitation with Spectrum Inversion (CEXSI) to improve SNR in sparse array imaging

We have proposed a forward-viewing ring-annular array for intravascular ultrasound imaging. Our proposed beamformer involves a total of 210 transceiver firings per frame. To maintain adequate signal to noise ratio (SNR) in such sparseness, an additional 10 dB SNR improvement is required. Conventional correlation-based coded excitation leads to substantial side-lobes due to small time bandwidth product. A scheme called Coded EXcitation with Spectrum Inversion (CEXSI) is presented. An established optimal binary code whose spectrum has no nulls and possesses the least variation is used for transmission. Decoding is a simple matter of spectrum inversion. Code transmission can be closely coupled to the transducer pass-band. For a 2.6 /spl mu/s code, an array element with a center frequency of 10 MHz and fractional bandwidth of 38%, range side-lobes of about 40 dB have been achieved experimentally with little compromise in range resolution. SNR improvement also has been characterized at 14.5 dB. CEXSI can be extended to improve SNR in general sparse array imaging.
A thickness-shear quartz resonator force sensor with dual-mode temperature compensation

An AT-cut thickness-shear quartz crystal resonator (QXR) has been used as a force sensing and self-temperature-sensing (STS) element to develop a digital output force sensor. The QXR is fixed in a two-line mounting configuration in a cylindrical metal shell by double diaphragms, through which a diametric force proportional to the unknown force is applied to the QXR. The double diaphragms improve the reliability and the mechanical stability of the sensor significantly. In order to increase the measurement range and the sensitivity, the energy trapping-based QXR is cut to a symmetrical, incomplete circular shape to decrease stress concentration. Because operating the QXR in dual-mode excitation allows the separation of force change effects from temperature change effects, force measurement and STS are accomplished simultaneously with the same QXR. The structure and the configuration are optimized with theoretical analysis and FEM. The dual-mode STS and temperature compensation are described in detail, as well as a trimming method to reduce activity dips of AT-cut QXRs.