nils-herrmann/clean_scirepeval huggingface dataset:
Variable-accuracy bit-serial multiplication with row bypassing for ultra low power

This paper revisits bit-serial computing and proposes a novel near-threshold serial multiplier with row bypassing and variable precision. A key challenge in the design of Internet-of-Things sensors is to maintain low energy consumption for longer life time. Variable-accuracy computing has attracted significant interest over the decades as a means of balancing energy and accuracy. To illustrate the proposed technique, a design has been developed and synthesised using the ST 65nm CMOS logic process. Results show that at low sampling rates the proposed design significantly outperforms conventional bit-serial and state-of-the-art parallel implementations in terms of both average power and total energy consumption, despite the longer operation time of the bit-serial design. Compared with conventional bit-serial architecture, a few number of extra gates are needed to achieve additional energy savings via the dynamic reduction of bit precision.
Electrolytic deposition of TiC nanoparticles/Ag composite films and their optical properties

TiC nanoparticles/Ag composite films were successfully prepared on an indium tin oxide (ITO) substrate through co-electrodeposition, using the Ag plating solutions with minor addition of TiC nanoparticles, followed by heat treatment in vacuum. The X-ray diffractometer, scanning electron microscope and UV–Vis spectrophotometer were used to characterise phase composition, morphologies and optical properties of as-fabricated films, respectively. Experimental results show that only TiC and Ag phases are identified for the TiC nanoparticles/Ag composite films and TiC nanoparticles are incorporated tightly and uniformly on the surface of the composite films, without obvious clustering. The results of optical property test reveal that the TiC nanoparticles/Ag composite films have similar optical properties as thick silver films perforated with nanohole arrays, which will pave the way towards numerous potential applications of Ag nanohole arrays.
Parallel imaging: A unified theoretical framework for image generation

In order to build computer vision systems with good generalization capability, one usually needs large-scale, diversified labeled image data for learning and evaluating the in-hand computer vision models. Since it is difficult to obtain satisfactory image data from real scenes, in this paper we propose a unified theoretical framework for image generation, called parallel imaging. The core component of parallel imaging is software-defined artificial imaging systems. Artificial imaging systems receive small-scale image data collected from real scenes, and then generate large amounts of artificial image data. In this paper, we survey the realization methods of parallel imaging, including graphics rendering, image style transfer, generative models, and so on. Furthermore, we compare the properties of artificial images and actual images, and discuss the domain adaptation strategies.
Assessing the challenges of environmental signal processing through the sensorscope project

SensorScope is a collaborative project between network, signal processing, and environmental researchers that aims at providing a cheap and out-of-the-box environmental monitoring system based on a wireless sensor network. It has been successfully used in a number of deployments to gather hundreds of megabytes of environmental data. With data gathering techniques well mastered, the efficient processing of the huge amounts of the acquired information to allow for useful exploitation has become an increasingly important issue. In this paper, we present a number of challenging and relevant signal processing tasks that arise from the SensorScope project. We believe the resolution of these problems will benefit from a better understanding of the underlying physical processes. We show an example to demonstrate how physical correlations between different sensing modalities can help reduce the sampling rate.
Distributed spatio-temporal sampling of diffusion fields from sparse instantaneous sources

We study the spatio-temporal sampling of a diffusion field driven by K unknown instantaneous source distributions. Exploiting the spatio-temporal correlation offered by the diffusion model, we show that it is possible to compensate for insufficient spatial sampling densities (i.e. sub-Nyquist sampling) by increasing the temporal sampling rate, as long as their product remains roughly a constant. Combining a distributed sparse sampling scheme and an adaptive feedback mechanism, the proposed sampling algorithm can accurately and efficiently estimate the unknown sources and reconstruct the field. The total number of samples to be transmitted through the network is roughly equal to the number of degrees of freedom of the field, plus some additional costs for in-network averaging.
Research on transient characteristics of a novel longitudinal-torsional ultrasonic motor

This paper introduces a longitudinal-torsional USM. Based on the electrical characteristics of the piezoelectric vibrator, a theoretical model was investigated. It can be used to derive the transient response characteristics of electrical parameters. The finite element analysis was also used to verify the correctness of the parameters change trend. The transient state of the analyzed parameters includes three time interval, the on transient state, steady state and off transient state. The simulation and experiment verified the validity of the theoretical model and performance of the USM. The above mentioned electrical and mechanical parameters rise or fall by degrees in accordance with an exponential form except that the speed of revolution falls linearly approximately. The revolution speed of this USM is about 45 r/min. Experimental results also showed that the response speed of the USM is fast, as the startup time is about 6 ms and the turnoff time is 2 ms.
Latest development of current-fed three phase converter with ROM table-based optimum PWM control scheme and its input line filter design

This paper describes a new method to select the optimum PWM patterns and a procedure to design a low-pass filter in a large-capacity current-source-fed active PWM converter which is used to suppress higher harmonics flowing into the utility-grid power source. A feasible test is carried out using a 500 kVA active PWM converter designed for unique considerations mentioned above. It is verified that these new considerations are effective to minimize higher harmonic current components flowing into the utility-grid AC line. Furthermore, this experimental work provides highly efficient AC/DC converter characteristics under a unity power factor correction and sinewave line current shaping schemes. Finally, the application for voltage source inverter is described. It is verified that this optimum PWM pattern has an excellent switching performance as compared with conventional PWM modulation.
Sampling Sparse Signals on the Sphere: Algorithms and Applications

We propose a sampling scheme that can perfectly reconstruct a collection of spikes on the sphere from samples of their lowpass-filtered observations. Central to our algorithm is a generalization of the annihilating filter method, a tool widely used in array signal processing and finite-rate-of-innovation (FRI) sampling. The proposed algorithm can reconstruct K spikes from (K+√K)2 spatial samples. For large K, this sampling requirement improves over previously known FRI sampling schemes on the sphere by a factor of four. We showcase the versatility of the proposed algorithm by applying it to three problems: 1) sampling diffusion processes induced by localized sources on the sphere, 2) shot noise removal, and 3) sound source localization (SSL) by a spherical microphone array. In particular, we show how SSL can be reformulated as a spherical sparse sampling problem.
System design considerations for a 5Gb/s source-synchronous link with common-mode clocking

A 5Gb/s source-synchronous signaling system was developed utilizing embedded common-mode clocking technology to minimize clock distribution delays and to reduce the total pin count. The common-mode clocking scheme forwards the clock on the common mode of the differential data channels. In addition to the signal integrity issues present in differential signaling systems, the embedded common-mode clocking scheme presents additional challenges in system design. By means of impedance control for both common mode and differential mode, careful trace length matching, 5W spacing rule etc, we achieved good signal integrity and the link exhibits good margin. Mode conversion is one of the key issues in the common-mode clocking technology, and it is covered in detail. Measurement results show that the clocking scheme can tolerate −13dB mode conversion on both differential pairs at 5Gb/s.
Imaging of Micromotion Targets With Rotating Parts Based on Empirical-Mode Decomposition

For micromotion targets with rotating parts, the inverse synthetic-aperture-radar image of the main body may be shadowed by the micro-Doppler. To solve this problem, this paper proposes an imaging algorithm based on the complex-valued empirical-mode decomposition. First, the radar echoes are decomposed into a series of complex-valued intrinsic-mode functions (IMFs). Then, the IMFs from the rotating parts and those from the main body are separated according to the characteristics of their zero-crossings. Finally, the well-focused imaging of the main body via traditional imaging algorithm and the accurate parameter estimation of the rotating part can be obtained. Both the imaging results for the simulated and measured data are given to verify the validity of the proposed algorithm.
A Distributed Gauss-Newton Method for Power System State Estimation

We propose a fully distributed Gauss-Newton algorithm for state estimation of electric power systems. At each Gauss-Newton iteration, matrix-splitting techniques are utilized to carry out the matrix inversion needed for calculating the Gauss-Newton step in a distributed fashion. In order to reduce the communication burden as well as increase robustness of state estimation, the proposed distributed scheme relies only on local information and a limited amount of information from neighboring areas. The matrix-splitting scheme is designed to calculate the Gauss-Newton step with exponential convergence speed. The effectiveness of the method is demonstrated in various numerical experiments.
A geometrical approach to sampling signals with finite rate of innovation

Many signals of interest can be characterized by a finite number of parameters per unit of time. Instead of spanning a single linear space, these signals often lie on a union of spaces. Under this setting, traditional sampling schemes are either inapplicable or very inefficient. We present a framework for sampling these signals based on an injective projection operator, which "flattens" the signals down to a common low dimensional representation space while still preserving all the information. Standard sampling procedures can then be applied on that space. We show the necessary and sufficient conditions for such operators to exist and provide the minimum sampling rate for the representation space, which indicates the efficiency of this framework. These results provide a new perspective on the sampling of signals with finite rate of innovation and can serve as a guideline for designing new algorithms for a class of problems in signal processing and communications.
Current-fed three phase PWM converter with sinewave line current shaping scheme and its practical input filter design procedure

This paper describes a new method to select the optimum PWM patterns and a procedure to design a low-pass filter in a large-capacity current-source-fed active PWM power converter which is used to suppress higher harmonics flowing into the utility-grid power source. A feasible test is carried out using a 500 kVA active PWM power converter designed for the unique considerations mentioned above. It is verified that these new considerations are effective to minimize higher harmonic current components flowing into the utility-grid AC line. Furthermore, this experimental work provides highly efficient AC/DC power converter characteristics under unity power factor correction and sinewave line current shaping schemes. Finally, this paper indicates that the optimum PWM pattern can be applied to the voltage source converter and has an excellent switching performance as compared with conventional PWM modulation.
Learning optimal parameters for binary sensing image reconstruction algorithms

A novel data-driven reconstruction algorithm for quantum image sensors is proposed. Binary observations are efficiently decoded by modeling the reconstruction structure as a two-layer neural network, where optimal coefficients are obtained via error backpropagation. Such a model encapsulates the structure of state-of-the-art algorithms, yet it presents a considerably faster alternative which adapts to input examples without a priori statistical information. Simulations on natural and synthetic datasets show accurate reconstructions with structural similarities consistent with the state of the art, while requiring approximately 5 times less computational cost.
Optimal order strategy with time-varying demand under permissible delay in payments linked to order quantity

This study presents a deterministic economic order quantity model for a retailer to determine its optimal replenishment number and replenishment schedule in a finite time horizon. The retailer's demand rate is time dependent and the supplier offers a trade credit to the retailer when the retailer's order quantity exceeds a given pre-specified quantity. To maximize the retailer's profit, a mathematical model is developed when the demand rate is a generalized function of the time and the trade credit linked to order quantity is adopted. By analyzing the retailer's profit function, we develop some useful results to characterize the optimal solution and provide an iterative algorithm to find the replenishment schedule and the retailer's order quantities. Numerical examples with different types of demand function are presented to validate the proposed model and the algorithm. Sensitivity analysis of the major parameters including of the quantity at which the delay in payments permitted and the trade credit period are presented.
A New Contourlet Transform with Sharp Frequency Localization

The contourlet transform was proposed as a directional multiresolution image representation that can efficiently capture and represent singularities along smooth object boundaries in natural images. Its efficient filter bank construction as well as low redundancy make it an attractive computational framework for various image processing applications. However, a major drawback of the original contourlet construction is that its basis images are not localized in the frequency domain. In this paper, we analyze the cause of this problem, and propose a new contourlet construction as a solution. Instead of using the Laplacian pyramid, we employ a new multiscale decomposition defined in the frequency domain. The resulting basis images are sharply localized in the frequency domain and exhibit smoothness along their main ridges in the spatial domain. Numerical experiments on image denoising show that the proposed new contourlet transform can significantly outperform the original transform both in terms of PSNR (by several dB 's) and in visual quality, while with similar computational complexity.
Connective prediction using machine learning for implicit discourse relation classification

Implicit discourse relation classification is a challenge task due to missing discourse connective. Some work directly adopted machine learning algorithms and linguistically informed features to address this task. However, one interesting solution is to automatically predict implicit discourse connective. In this paper, we present a novel two-step machine learning-based approach to implicit discourse relation classification. We first use machine learning method to automatically predict the discourse connective that can best express the implicit discourse relation. Then the predicted implicit discourse connective is used to classify the implicit discourse relation. Experiments on Penn Discourse Treebank 2.0 (PDTB) and Biomedical Discourse Relation Bank (BioDRB) show that our method performs better than the baseline system and previous work.
Combining hierarchical segmentation and shape context based recognition

In this paper, we integrate image segmentation and object recognition into one unified process. The process starts from a seed region produced by the initial segmentation. Then it is evolved through alternating shape context based recognition and smaller scale image segmentation, until an object is found. In recognition, the thin plate spline (TPS) transformation is employed to locate the difference between the seed region and the defined model, and guide the subsequent evolution process. Experimental results demonstrate the advantages achieved by the combination of hierarchical segmentation and multi-scale shape contexts based recognition.
The effects of thermal cycling on electromigration behaviors in lead-free solder joints

With packaging density constantly increasing and the size of solder joints scaling down in microelectronic products, electromigration (EM) becomes serious reliability problem in interconnections which induced by the high current density. Currently, investigations on EM phenomenon mainly focus on microstructure evolution, the change of grain orientation and the dominant diffusion species, etc. Almost all these studies and EM damages are carried out under constant ambient temperature. However, electronic devices usually service in a non-equilibrium state environment in practical. The purpose of this research is investigating the EM behavior under the thermal cycling conditions and trying to understand the relationship between microstructure evolution and resistance change of the solder joints. The one-dimensional Cu/Sn3.0Ag0.5Cu/Cu linear solder joint was employed to study the EM behavior of Sn-3.0Ag-0.5Cu (SAC305) under combined conditions of cycling temperature ranges from -20 to 100 °C and a high current density of 104A/cm2. Resistance change and microstructure evolution were analyzed in this paper. Resistance and microstructure data was collected and observed by paperless recorder and scanning electron microscope (SEM), respectively. The results revealed that high current density can cause voids formation. The propagation of cracks was accelerated by cycling temperature due to the mismatch of coefficient of thermal (CTE) between solder matrix and Cu substrate. Moreover, the coupling effects of high density and cycling temperature can lead to a rapid failure when compare to the monolithic loading condition.
A statistical response-time analysis of complex real-time embedded systems by using timing traces

Real-time embedded systems are becoming ever more complex, and we are reaching the stage where even if static Response-Time Analysis (RTA) was feasible from a cost and technical perspective, the results are overly pessimistic making them less useful to the practitioner. When combined with the fact that most timing analysis tends to be statistical in nature, this suggests there should be a move toward statistical RTA. However, to make such analysis useful, it is imperative that we have evidence that the statistical RTA and the information analyzed is sufficiently accurate. In this paper we present and validate a technique for statistical RTA that can cope with systems that are complex from both a size and tasks' dependencies perspective. This claim is backed up by our evaluation using information from real industrial control systems.
Series-compensated inductor type resonant inverter using pulse density modulation scheme for efficient ozonizer

This paper presents a high-frequency voltage source-fed load-resonant IGBT inverter with a series-compensated resonant inductor for ozonizer power supply, which is characterized by the power control strategy on the basis of pulse density modulation (PDM). The inverter system configuration illustrated through the circuit modeling of the silent discharge-based ozone generating tube and high-voltage transformer. The state-of-the art ozonizer using a high-frequency load resonant inverter is demonstrated and its operating principle of the voltage-fed load-resonant inverter are described for the ozone generating tube. It is noted that the pulse density modulated series resonant high-frequency inverter using IGBTs makes an ozonizer power control scheme simple as well as improves the ozone generating characteristic. Thus, it is effective in improving the ozone producer efficiency. Finally, it is proved that the series load-resonant inverter type ozonizer developed in this paper provides stable silent discharge characteristics over a wide output power range from 10% to 100%.
Electromagnetic induction eddy current-based far infrared rays radiant heater using high frequency ZVS-PWM inverter

This paper presents an innovative prototype of a new conceptual electromagnetic induction type far infrared rays radiant heating appliance using an IGBT voltage-fed quasi-resonant ZVS-PWM high frequency inverter for food cooking and processing, which operates under a constant frequency variable power regulation scheme. This power electronic appliance, with a soft switching IGBT high frequency inverter, has attracted special interest from viewpoints of safety, cleanliness, compactness and rapid temperature response that is more suitable for consumer power electronics applications.
The research about peak voltage suppression technique of direct current (DC) torque motor with large inductance that applies the pulse width modulation (PWM) control method

Aiming at the problem of high peak voltage at two ends of direct current (DC) torque motor with large inductance that during the pulse width modulation (PWM) control process, the original H-bridge PWM control method, the current flow and the main reason of peak voltage have also been analyzed. Based on the analysis, a new H-bridge PWM control method has also been advanced and undertaken the contrast experiment by a self-build experimental platform. According to the results, the new PWM control method can reduce the peak voltage that between the motor ends' significantly.
Information Retrieval in Document Image Databases

With the rising popularity and importance of document images as an information source, information retrieval in document image databases has become a growing and challenging problem. In this paper, we propose an approach with the capability of matching partial word images to address two issues in document image retrieval: word spotting and similarity measurement between documents. First, each word image is represented by a primitive string. Then, an inexact string matching technique is utilized to measure the similarity between the two primitive strings generated from two word images. Based on the similarity, we can estimate how a word image is relevant to the other and, thereby, decide whether one is a portion of the other. To deal with various character fonts, we use a primitive string which is tolerant to serif and font differences to represent a word image. Using this technique of inexact string matching, our method is able to successfully handle the problem of heavily touching characters. Experimental results on a variety of document image databases confirm the feasibility, validity, and efficiency of our proposed approach in document image retrieval.