nils-herrmann/clean_scirepeval huggingface dataset:
A high voltage narrow pulse generator in nanometre CMOS process

A high voltage narrow pulse generating circuit (HNPG) in 90nm CMOS process is introduced which can produce a narrow pulse with amplitude of twice the level of the power supply and can be used to turn on a NMOS transistor completely in a short time in the low power supply environment of 90nm CMOS process. The circuit, which is applied for a patent with the application number 201510243084.6 , solves the problem that under the low power level of the nano-metre CMOS process chips, a NMOS transistor can't be turned on completely. The sampling rate of the tracking and holding circuit which employ the HNPG is improved from 700Msps to 1.25Gsps and other performances are also enhanced, with only a little punishment of chip area and power consumption.
A system of robot mobile manipulation based on teleoperation with human motion capture

Mobile manipulation is simple for human, but difficult for robot. A mobile robot named CHR is developed for mobile manipulation by teleoperation based on mobile Internet. The operator's command is transferred to the robot located in the house. In this paper the manipulation is divided into four parts: preparing, approaching, orientation adjusting, operating. In different parts, different control command generating tools are used. Some experiments are provided. In this paper we use the network camera to capture the information of manipulation scene, transmitted through the cloud server, displayed in the master part. Through stereo equipment, body motion was captured and compared with the data from the infrared motion capture system. Then, select the optimal data to match with the robot. In this paper, it has realized that the small mobile robot turned off the lights. Through the remote operator arm to control the movement of robot, right hand respectively to turn off the lights, prove the feasibility of teleoperation.
Design and Research of Double Closed-Loop Control Strategy for Inverted Pendulum System

The Newton-Euler method was used to derive the dynamic equation of the linear inverted pendulum, and obtained the mathematical model of the linear inverted pendulum after linearization. Based on this model, a double closed-loop control scheme was proposed. The inner loop regulated the angle of pendulum by using root locus control, while the outer loop controlled the position of the car by using fuzzy logic control method. With the help of the control scheme, it was easier realize the control of the pendulum angle and cart position synchronously, in addition, reduced difficulty of the controller design. Finally, in the programming environment of Mat lab, the computer simulation and real-time control was finished, and the controlled system had good performance. The results of simulation and real-time control showed the correctness of modelling and the validity of control scheme.
Cryptanalysis of a Certificateless Multi-receiver Signcryption Scheme

Certificateless public key cryptography eliminatescertificate management in traditional public key infrastructure and solves the key escrow problem in identity-based cryptography. Certificateless signcryption is one of the most important primitives in certificateless public key cryptography which achieves confidentiality and authentication simultaneously. Multi-receiver signcryption signcrypts a message to a large number of receivers. Selvi et al. proposed the first efficient and provably secure certificateless multi-receiver signcryption scheme. Recently, they found the scheme is insecure againstthe type I adversary and gave an enhanced one. However, wefind that their enhanced scheme is still insecure against the type I adversary. In this paper, we present an attack on Selvi et al.’s enhanced scheme. Specifically, we show that a type I adversary can first replace a sender’s public key and generate a signcrypted message on behalf of the sender.
An Adaptive On-Line Inspection Method Based on Singular Value Decomposition

Singular value decomposition(SVD) is an effective method of algebraic feature extraction. It has the stability, rotation invariability, brightness invariability and other important features. In this thesis, through autonomous learning in small sample space and extracting the SVD feature, the similarity calculation method of singular value feature is given, the similarity is used to recognition. This method significantly reduce the requirements for the training image, and it can be applied to wider fields. Finally, the method is testified by a experiment of button battery case.
A new flux/current method for SRM rotor position estimation

This paper proposes a new principle of sensorless position estimation for a switched reluctance motor (SRM) drive, based on an improved flux/current method. The estimation algorithm makes full use of the structural symmetry of SRM, and only some specific position flux linkage data are needed, which greatly decrease the need for the high speed and capacity of microcontroller. The proposed method does not require external hardware and hence the reliability of the scheme is expected to be good while not adding to the system cost. Preliminary investigation shows that the proposed sensorless scheme can give position information with high resolution for speeds. The basic principle of this method is analyzed, simulations and real-time implementation of the sensorless scheme using Matlab-simulink are carried out based on a 12/8 SRM, the result of which shows the feasibility of the algorithm. Hardware aspects along with the implementation details of the sensorless scheme are discussed briefly. Experimental investigation is underway and complete set of test results will be provided in the next step work.
2.074- $\mu \text{m}$  Lasing From Ho3+-Doped Fluorotellurite Microstructured Fibers Pumped by a 1120-nm Laser

We demonstrate 2.074-μm lasing from Ho<sup>3+</sup>-doped fluorotellurite microstructured fibers (FTMFs) pumped by a 1120-nm Yb<sup>3+</sup>-doped fiber laser. Ho<sup>3+</sup>-doped FTMFs based on TeO<sub>2</sub>-BaF<sub>2</sub>-Y<sub>2</sub>O<sub>3</sub> glasses are fabricated by using a rod-in-tube method. With increasing the pump power to 253 mW, lasing at 2.074 μm is achieved from a 42-cm-long Ho<sup>3+</sup>-doped FTMF. With further increasing the pump power to 1015 mW, a maximum unsaturated power of 98 mW is obtained, and the corresponding slope efficiency is up to 12.4%. In addition, relatively strong 1.2- and 2.9-μm emissions are also observed from the Ho<sup>3+</sup>-doped FTMF.
ARISTA - image search to annotation on billions of web photos

Though it has cost great research efforts for decades, object recognition is still a challenging problem. Traditional methods based on machine learning or computer vision are still in the stage of tackling hundreds of object categories. In recent years, non-parametric approaches have demonstrated great success, which understand the content of an image by propagating labels of its similar images in a large-scale dataset. However, due to the limited dataset size and imperfect image crawling strategy, previous work can only address a biased small subset of image concepts. Here we introduce the Arista project, which aims to build a practical image annotation engine targeting at popular concepts in the real world. In this project, we are particularly interested in understanding how many image concepts can be addressed by the data-driven annotation approach (coverage) and how good the performance is (precision). This paper reports the first stage of the work. Two billions web images were indexed, and based on simple yet effective near-duplicate detection, the system is capable of automatically generating accurate tags for popular web images having near-duplicates in the database. We found that about 8.1% web images have more than ten near duplicate and the number increases to 28.5% for top images in search results. Further, based on random samples in the latter case, we observed the precision of 57.9% at the point of the highest recall of 28% on ground truth tags.
A Descriptive Bayesian Approach to Modeling and Calibrating Drivers' En Route Diversion Behavior

This paper presents a Bayesian approach for modeling and calibrating drivers' en route route changing decision with behavior data collected from laboratory driving simulators and field Bluetooth detectors. The behavior models are not based on assumptions of perfect rationality. Instead, a novel descriptive approach based on naive Bayes' rules is proposed and demonstrated. The en route diversion model is first estimated with behavior data from a driving simulator. Subsequently, the model is recalibrated for Maryland, based on Bluetooth detector data, and applied to analyze two dynamic message sign scenarios on I-95 and I-895. This calibration method allows researchers and practitioners to transfer the en route diversion model to other regions based on local observations. Future research can integrate this en route diversion model with microscopic traffic simulators, dynamic traffic assignment models, and/or activity-based/agent-based travel demand models for various traffic operations and transportation planning applications.
Design and realization of SMS4 algorithm based on MicroBlaze

In order to improve use flexibility of the State's commercial cipher symmetric algorithm SMS4, SOC design method for embedded soft core based on Xilinx Company's MicroBlaze is developed to design key extension and encryption/decryption operation of SMS4 algorithm into IP hardcore by means of hardware and connect SMS4 hardcore to PLB by interface module. Test result shows that encryption algorithm realized by hardware can greatly increase encryption rate of embedded system and encryption and decryption rate can reach 177.8Mbps in the case of system dominant frequency of 50MHz.
Context-based bias removal of statistical models of wavelet coefficients for image denoising

Existing wavelet-based image denoising techniques all assume a probability model of wavelet coefficients that has zero mean, such as zero-mean Laplacian, Gaussian, or generalized Gaussian distributions. While such a zero-mean probability model fits a wavelet subband well, in areas of edges and textures the distribution of wavelet coefficients exhibits a significant bias. We propose a context modeling technique to estimate the expectation of each wavelet coefficient conditioned on the local signal structure. The estimated expectation is then used to shift the probability model of wavelet coefficient back to zero. This bias removal technique can significantly improve the performance of existing wavelet-based image denoisers.
A 24GHz low phase noise feedback CMOS LC-VCO

This paper proposes an effective method to improve phase noise in voltage controlled oscillator (VCO), which is realized with 90nm RF CMOS technology. A current source is used in this design to control the VCO power consumption, while the filtering technique is incorporated to reduce VCO phase noise, and a feedback loop from output to input is also adopted to further improve the phase noise performance. A •100.85 — •104.7dBc/Hz phase noise is achieved at 1MHz offset, and the frequency tuning range(FTR) spans from 24.7GHz to 28.8GHz, with a total power consumption of 5.5mW from 1.2V supply.
An On-line Visual Seam Tracking Sensor System During Laser Beam Welding

This paper deals with a seam tracking system of welding of Tailored Weld Blanks based on active laser-triangulation. The system consists of DSP based vision camera and stripe-type laser diode. The total system is assembled into a compact module which can be attached ahead of welding torch and it has high dynamic performance in guiding the robot arm welder accurately over the seam. its structure, basic principle of this system and the main function are introduced . The images taken by the camera are analyzed using image processing algorithms: setting the range of interest, the median filtering and bi-level thresholding. Furthermore, the middle line of the laser stripe is extracted. Finally, a search method is carried out to examine the mid-point. A prototype sensor system has been developed and experimental results show its effectiveness and good performance.
Barriers and solutions of e-commerce in China: An exploratory study

Due to the considerably big marketplace, enterprises seek to benefit from e-commerce in China. But up to now very few of them have been successful, because some successful business models and strategies in developed countries can not be applied in China. This study examines obstacles on e-commerce development in China and attempts to find out some solutions to overcome these barriers. The relevant data was gathered by a questionnaire and the review of two successful Chinese e-commerce companies, and it revealed that the two most important factors affecting customerspsila participation of the e-commerce are lack of trust due to Internet security and Privacy concerns and lack of customer service. This study also confirms that consumerspsila attitude and intention to participate in e-commerce behaviors can be improved effectively by the transformation about the laws and legislations related to e-commerce in China.
A Novel Workflow-Level Data Placement Strategy for Data-Sharing Scientific Cloud Workflows

Cloud computing can provide a more cost-effective way to deploy scientific workflows than traditional distributed computing environments such as cluster and grid. Due to the large size of scientific datasets, data placement plays an important role in scientific cloud workflow systems for improving system performance and reducing data transfer cost. Traditional task-level data placement strategy only considers shared datasets within individual workflows to reduce data transfer cost. However, it is obvious that task-level strategy is not necessarily good enough for the situation of multiple workflows at the workflow level. In this paper, a novel workflow-level data placement model is constructed, which regards multiple workflows as a whole. Then, a two-stage data placement strategy is proposed which first pre-allocates initial datasets to proper datacenters during workflow build-time stage, and then dynamically distributes newly generated datasets to appropriate datacenters during runtime stage. Both stages use an efficient discrete particle swarm optimization algorithm to place flexible-location datasets. Comprehensive experiments demonstrate that our workflow-level data placement strategy can be more cost-effective than its task-level counterpart for data-sharing scientific cloud workflows.
Bulk synthesis of long silicon nitride nanowires on silicon wafer

A Nickel-catalyzed synthesis method was developed to grow large-scale Si<inf>3</inf>N<inf>4</inf> nanowires on silicon wafer in forming gas of N<inf>2</inf>/H<inf>2</inf>(5%) under 1200°C. These nanowires consisted of uniform diameter ranging from 50 to 100 nm with length up to 500 µm. Vapor-liquid-solid mechanism was proposed to interpret the nanowire growth procedure. It was characterized that the nanowires were mainly composed of single-crystal α-Si<inf>3</inf>N<inf>4</inf>, growing along the [120] direction.
Cambricon-X: An accelerator for sparse neural networks

Neural networks (NNs) have been demonstrated to be useful in a broad range of applications such as image recognition, automatic translation and advertisement recommendation. State-of-the-art NNs are known to be both computationally and memory intensive, due to the ever-increasing deep structure, i.e., multiple layers with massive neurons and connections (i.e., synapses). Sparse neural networks have emerged as an effective solution to reduce the amount of computation and memory required. Though existing NN accelerators are able to efficiently process dense and regular networks, they cannot benefit from the reduction of synaptic weights. In this paper, we propose a novel accelerator, Cambricon-X, to exploit the sparsity and irregularity of NN models for increased efficiency. The proposed accelerator features a PE-based architecture consisting of multiple Processing Elements (PE). An Indexing Module (IM) efficiently selects and transfers needed neurons to connected PEs with reduced bandwidth requirement, while each PE stores irregular and compressed synapses for local computation in an asynchronous fashion. With 16 PEs, our accelerator is able to achieve at most 544 GOP/s in a small form factor (6.38 mm2 and 954 mW at 65 nm). Experimental results over a number of representative sparse networks show that our accelerator achieves, on average, 7.23x speedup and 6.43x energy saving against the state-of-the-art NN accelerator.
An Improved Cooperative Sensing Protocol for Cognitive Radio System

In cognitive radio systems, cooperative spectrum sensing is employed to detect the presence of primary user quickly and accurately. In this paper, we propose a new TDMA cooperation protocol to improve the overall agility and spectrum efficiency compared to the existing protocols. By allowing the cognitive users operating in the same band to cooperate, the detection time is reduced and thus the average number of slots taken for detection is decreased under the new scheme. In particular, it decreases the average detection time per slot. We consider a two-user cognitive radio network and show how the inherent asymmetry in the network can be exploited to increase the agility. Numerical results illustrate that this cooperative relay sensing scheme can improve the detection probability, and the spectrum efficiency of the network.
Capacity of TDD MISO Beamforming Systems with Channel Estimation Error and Delay

This paper examines the capacity of a time division duplex (TDD) multiple input single output (MISO) beamforming system with channel estimation error and delay over the time varying fading channel. In TDD system, the base station estimates the channel state information (CSI) at transmitter based on uplink pilots and then uses it to generate the beamforming vector in the downlink transmission. Because of the constraints of the TDD frame structure and the uplink pilot overhead, there inevitably exists delay and channel estimation error between CSI estimation and its use. In this paper, we first derive the capacity upper bound for TDD MISO beamforming system with channel estimation error and delay. We then obtain the optimal uplink pilot time interval (UPTI), which maximizes the capacity upper bound, given the normalized pilot overhead (the number of pilot symbols per data symbol). The simulation results validate that the optimal UPTI not only maximizes the capacity upper bound but also maximizes the system ergodic capacity. Especially our research is valuable for the uplink sounding reference signal design in LTE- Advanced system.
Avionics R&D platform based on “Engineering Middleware” technology

To accommodate the challenge of avionics system development as the system increasing the complexity, applying new technology, etc., and optimizing the configuration of the R&D process, data, tools, and knowledge rationally, this paper presents the “Engineering Middleware” technology which is very similar as the computer operation system, to realize the management of underlying resources and the top level application customization. The avionics system development platform base on the “Engineering Middleware” technology was performed, which can satisfy the entire R&D lifecycle process from requirements to modeling, simulation and analysis, to system integration and verification. Such platform not only can manage and optimize the resources, but also can rapidly customize application system such as early proposal iteration and associative design and verification to realize the advanced R&D process. The avionics system development platform customized by “Engineering Middleware” with fast, flexible, low cost, feature-rich characteristics can be as the important reference for developing enterprise level avionics system R&D platform.
Design of 2-channel linear phase filter bank: a lifting approach

The structural property is desirable both in design and implementation of a filter bank. It is well known that the lifting structure can obtain the structurally PR property. In this work, it is further shown that by carefully choosing the polynomials for lifting, the linear phase property can be imposed to the structure. The design structure is derived after the factorization of an arbitrary 2-channel filter bank of this type. A lifting-like structure is proposed to tackle the singularity during the lattice factorization of the 2-channel linear phase filter bank. Some examples are also presented.
Design of Mobile Phone Security System Based on Detection of Abnormal Behavior

Mobile phone virus is rapidly developing with the quick development of 3G radio network. The research on mobile phone virus detection is a hotspot in mobile security field. In this paper we analyze the spread methods of various viruses, propose and design a mobile phone virus detection system based on abnormal behavior. The malware's behavior characteristics are represented in a malware database. We set up a behavior analysis model to implement the behavior pattern matching which is more completeness and efficiency. Our evaluation shows that behavioral detection can successfully detect unknown mobile phone virus.
An Intelligent Strategy to Gain Profit for Bitcoin Mining Pools

Bitcoin is a digital cryptocurrency operating on a peer to peer network, which is currently integrated across a number of businesses and exchange markets. New bitcoins is created by participants who contribute computational resources to maintain a public blockchain as miners. Miners collaborate in a mining pool to reduce their variance and earn steadier rewards in Bitcoin. Each mining pool desires to make a profit in the competition against others. To this end, an intelligent mining strategy to enable a mining pool to attain higher probability to get rewards disproportional to its computational power is proposed in this paper. We deploy some forwarding nodes according to the distribution of Bitcoin nodes. This strategy can reduce time delay for messages propagation and increase the probability for new block to be appended on the longest blockchain. It is also easy to deploy in existing network with low expenditure.
A unified power compensation system for the large-scale grid-tied renewable energy generation system

This paper proposed a unified power compensation (UPC) system by using a cascaded inverter plus DC/DC boost converters as the interfacing circuit between the high voltage level power grid and the battery storage systems in order to both compensate the real power fluctuation produced from the renewable energy generation systems and provide the reactive power compensation capability without shortening the battery life cycle when needed. The proposed system can manage the state-of-charges (SOCs) of batteries to be equal to avoid the overcharge or overdischarge of single battery stack. Meanwhile, the dc-link voltages of all H-bridge modules assumed in the cascaded inverter can be easily controlled to be equal also under the condition of producing/absorbing real or reactive power. The multifold operation will assist the renewable energy generation systems to be the grid friendly power sources.
Closed-loop optimal fuzzy reasoning and its application in model helicopters

Fuzzy reasoning is treated as a closed-loop and optimal process, which is different from the dominant view of treating fuzzy reasoning as generalization of classical logical inference, that is, an open-loop and non-optimal process. Further, the fuzzy rule base and the fuzzy reasoning method can constitute a closed-loop control system with a reasoning goals/constraint designed by users. A kind of closed-loop optimal fuzzy reasoning is used in fuzzy adaptive controllers, which are designed for vertical flight of model helicopters. Simulation results show that closed-loop optimal fuzzy reasoning can be used for control of complex systems. And closed-loop optimal fuzzy reasoning provides a framework for various control principles to be applied in fuzzy reasoning or logical inference.