nils-herrmann/clean_scirepeval huggingface dataset:
A new simulation model for frequency hopping wideband Rayleigh fading channels

A new simulation model based on Ricepsilas sum of sinusoids is proposed for frequency hopping wideband Rayleigh fading channels. It is shown that a frequency hop in the physical channel model corresponds to phase hops in the simulation model, while maintaining all other parameters unchanged. Due to the fact that closed-form expressions are given for all simulation parameters, so the correlation properties of the proposed simulation model can be studied. Both theory and simulation show that very good approximations between the correlation properties of the simulation model and those of the underlying reference model have been observed in the low computational complexity.
Image Segmentation Method based on Lifting Wavelet and Watershed Arithmetic

The overlapping phenomenon often appears in medical cell images. Traditional watershed based image segmentation methods have the drawback of over-segmentation. A method combining lifting wavelets with watersheds is presented to solve this problem. Lifting wavelet transform is firstly used to create multi-resolution images, then the watershed arithmetic based on distance transform is applied to segment the low-resolution image. At last, the inverse lifting wavelet transform is used to get the high-resolution image. Experimental results show that this arithmetic can successfully separate the cell clusters.
Effect of multi-pass hot rolling process on the microstructure of steel 2.25Cr1MoNb

Effect of controlled multi-pass hot rolling process on the microstructure of steel 2.25Cr1MoNb was investigated in this paper. The simulation experiment of thermo-mechanical treatment was carried out on the Gleeble-1500 system. Results show that the grain size and the ferrite volume fraction were improved obviously by multi-pass hot rolling.
Feasibility Study of the Impregnation of a No-Insulation HTS Coil Using Solder

This paper reports the feasibility of the impregnation of no-insulation (NI) high-temperature superconducting (HTS) coils using solder. NI coils are widely studied and used in many situations. To utilize an HTS coil under high mechanical loads such as field coils for rotating machines, the HTS tapes must be stabilized mechanically. Epoxy impregnation is a common method to protect the HTS field from mechanical disturbances caused by the magnetic field and rotational vibration of the rotor to enhance the mechanical stability. However, traditional epoxy resins are electrical insulating materials which might cause the turn-to-turn contact resistance of NI coils to increase. Therefore, we proposed a new kind of impregnation method using the electrically conductive material, solder. Two coils were fabricated and tested for comparison. One is the NI coil without impregnation and the other is the NI coil impregnated with solder. The charge–discharge and sudden-discharge tests were performed in liquid nitrogen at 77 K. The experimental results were studied with equivalent circuit analyses. The results of this paper could provide useful data for the application of solder impregnated NI HTS coils.
The Vehicle Scheduling Model and Algorithm of Hazardous Materials under Social Acceptable Risk Constraint

Vehicle scheduling of Hazardous materials is one of effective means to prevent accidents and reduce the loss of lives and property. On the basis of previous studies, this paper adds the constraint of Social Acceptable Risk, and studies the vehicle scheduling problem of Hazardous materials based on the transportation risks which vary with time. After a mixed integer programming model is proposed, a novel heuristic algorithm is designed. Finally, a numerical example is presented to show its validity and feasibility of this algorithm. Hazardous Materials; Vehicle Scheduling Problem; Transportation Network; Social Acceptable Risk; Heuristic Algorithm.
The comparison with improved mixture kernel SVM and traditional neural network

Support Vector Machines bases on statistical learning theory and replace the minimization experiential risk minimization by structural risk minimization, thus have large advantage over the traditional neural network on small sample set for classification. Related documents and experimental data prove that SVM is the best learning machine among all kinds recently and has large advantage over those of traditional neural networks. In this paper we prove that the performance of an improved SVM with mixed kernel will make the advantage more obviously. Different from some papers choose kernels and parameters randomly, we choose the kernels for SVM theoretically, through observing and computing the kernel matrix. Base on this, we used the selected kernel functions to get a new mixed kernel function. Experiential data proved that this new SVM has a better performance than that of that traditional neural network. This will give us a method to get a new learning machine for pattern identification.
Research on motion simulation for robot based on virtual reality

Aiming at the shortcomings of using traditional solid model for network-based simulation, the 3D visualization of the model and motion simulation for robot is realized by VRML and Java interaction through the External Authoring Interface (EAI) in this paper. In order to observe the three-dimensional robot in motion on a WEB browser, the virtual environment of the robot is established by VRML based on virtual reality technology, and the 3D assembling model of robot is built by UG software and channelled into the virtual environment by VRML format. According to the direct kinematics' problems and inverse kinematics' problems of robot, the motion simulation program for robot is made by VRML and Java language with the movement simulation control function to realize the motion simulation. The method can not only browse motion process of robot, but also is suitable for transmission of network to realize resource-sharing, therefore the research of motion simulation for robot based on internet has important research value and application prospect.
Mechanical Design of a Nb3Sn Superconducting Magnet System for a 45 GHz ECR Ion Source

Lawrence Berkeley National Laboratory in collaboration with the Institute of Modern Physics, Lanzhou, China, has developed a Nb3Sn superconducting magnet system for a fourth-generation electron cyclotron resonance (ECR) ion source operating at the microwave frequency of 45 GHz. This paper presents a mechanical design capable of supporting the magnet up to the required operational level, resulting in peak coil fields in the order of 12 T, without exceeding the stress limits of any of the components—particularly, the brittle Nb3Sn conductor. The coil system, based on the sextupole-in-solenoid configuration, is supported by a shell-based structure that uses an aluminum cylinder pretensioned using Bladder & Key Technology (with water-pressurized bladders) during the magnet assembly. High thermal contraction of the shell attains the target preload level at cryogenic temperatures during operation without overstressing the coils during roomtemperature assembly. We present the optimization progression of the support structure, describe its main components and assembly procedure, and examine the predicted coil stress at each step of the magnet assembly and operation using the three-dimensional finite-element mechanical model.
Vibration Signal Analysis of Rotor System Based on Time-Frequency Attributes

The time-frequency analysis by Hilbert-Huang transform (HHT) plays on a significant role in the analysis of singularities, which hide in the signal, and is an effective method for non-stationary signal. Based on empirical mode decomposition (EMD), the Hilbert-Huang method can obtain a true instantaneous frequency representation of a signal. The analytical background of the HHT is introduced, and its effectiveness is experimentally evaluated using vibration signal. The experiment data of typical vibration faults signal were analyzed by the method, and the result shows that the proposed method can not only reveal the time-frequency features of vibration signal but also extrude components of low energy. Therefore, it is a very effective tool to diagnose the early faults of rotor system. And it provides new means for state detection and fault diagnosis of rotating machine.
Preparation, Sustained-Release and Transdermal Penetration Properties of Drug-Loaded Hollow Fibers

Acyclovir-loaded PAN hollow fibers were prepared with dry-wet spinning processes. The co- blendine method was employed to prepare the spinning liquid. The prepared hollow fibers had a diameter 01 300 mum. The drug content in the hollow fibers is lower than that in the spinning liquid, 20.28% of the drug was lost during the spinning processes. SIn vitro dissolution tests indicated the obvious initial burst effect. Permeability test results illustrated that the permeation of acyclovir is limited by the skin.
Research and Development of Simulation System for Virtual Grinding

Based on virtual reality technology, the paper does some researches and developments for virtual grinding system. A friendly human-computer interaction interface and virtual machining environment are programmed with Visual C++ and OpenGL, and their characters of interaction and immersion are embodied completely. Physical model of virtual grinding wheel and mathematical model of contact between abrasive grain and workpiece are built. Take surface grinding as an example, the simulation system is tested. The results show that the simulation system could make operators have a further understanding to chip formation, and the simulation results could reflect realistic surface topography of workpiece. So the simulation system could be used to forecast surface roughness in actual abrasive machining.
Link scheduling and Data Forwarding in Wireless Sensor Networks of long chains tree topology

Wireless sensor network (WSN) is characterized by the information transmission from multiple sensor nodes observing an environment. WSN based monitoring system with its nodes of low cost can be deployed in strict environment. According to the structure and the layout of the Monitoring objects, the long chain tree-like topology of wireless sensor network is often used. Such monitoring systems include power transmission line, oil transportation, gas transportation and road traffic monitoring. This paper firstly reviews the basic WSN theory and protocols concentrating basically on the MAC layer, try to identify the maximum throughput achievable in multi-hop long chain tree structure WSNs. A second objective of this paper is to propose a multimode hierarchical network based multi-channel assignment algorithm for data collection applications. The proposed algorithm has three components, Multimode Hierarchical Network Establishment (MHN), Channel Assignment (CA), and Data Forwarding (DF). The MHN module partitions the whole network into NL subnetworks, and each subnetwork represents a data dissemination mode. CA module assigns one unique channel to each mode. And then DF forwards each data flow only along its corresponding level. Evaluation results show that the algorithm proposed in this paper can significantly reduce data collection time, improve the network throughput.
A Proximity-Aware Technique for Distributing Replicas in DHT-Based P2P Networks

Replication technique is an effective method for improving the availability of data and enhancing performance, however, it also brings significant costs in storage space and traffic. In this paper, we study how to decrease redundant traffic cost and redundant replicas for replication in structured P2P overlay by topology optimization. We develop a Hierarchical Proximity-Aware P2P overlay with dominating set nodes acting as super peers, and design a replication technique with multiple hash functions for costless query. Our method can efficiently disseminate replicas across the network, increase query hit ratio, and decrease redundant query messages and storage space required. We give theoretical analysis for performance metrics, and by simulation, we verify the superiority of our method.
A low temperature coefficient voltage reference utilizing BiCMOS compensation technique

This paper presents a low temperature coefficient BiCMOS voltage reference circuit designed in IBM's 8HP Silicon-Germanium (SiGe) technology platform. A BiCMOS compensation approach by combining the temperature properties of HBTs and CMOS transistors has been employed: the Complementary to Absolute Temperature (CTAT) current is generated by a SiGe HBT, while the Proportional to Absolute Temperature (PTAT) current is generated by MOSFETs operating in the subthreshold region. In addition, by adding a nonlinear component, a higher level of temperature compensation is achieved. Simulation results show that with a power supply of 1.2 V, the circuit generates an output voltage of 0.981 V with a temperature coefficient of 0.6 ppm/°C over the temperature range of -25°C to 125°C.
Utility-driven distributed transmission coordination for video communications over Ad Hoc wireless network

Video is becoming the dominant traffic over the wireless networks. Given the limited wireless resources, supporting multi-user video streaming with good video playback quality- of-service (QoS) is very challenging. The key difficulties involve providing good playback quality while also satisfy- ing the stringent video packet delay bounds. The allocation of wireless resources need to be efficient and coordination of mobile video users should have a distributed fashion. In this paper we present a distributed framework for multi-user video streaming over an ad-hoc 802.11 like networks. The proposed algorithm is based on a utility-driven scheme that adjusts the video users' sending rates according to APP layer video buffer status. Simulation results demonstrate that the proposed scheme is quite efficient on radio resource while have better QoS than content blind 802.11 DCF scheme.
The design and implementation of an excellent text categorization system

Based on the study of text classification techniques, a new text categorization method which uses a weight adjustment measure to improve a vector space model and naive Bayesian classifier is proposed, and an experimental text classification system CWZ is implemented to make comparison within various text classification approaches. Compared with many commercial text classification systems, the behavior of CWZ is much better. We introduce its framework, function, main modules and running environment, give our experimental results, and discuss a few important technical issues involved in the system to get some valuable conclusions. We also describe how to improve the vector space model and naive Bayesian classifier.
A research of Object Constraint Language used in PIM accurate modeling

Model-Driven Architecture (MDA) is a new software development method proposed by the OMG, which can automatically generate final complete application from the abstract model established against the business logic. It is based on UML and other industry-standard framework to support the software design and model visualization, storage and exchange, the core technology is the conversion between platform-independent model (PIM) and platform specific model (PSM). This paper analyzes the deficiencies in the process of MDA modeling, combines with Object Constraint Language (OCL) to complement dynamic semantics in PIM, establishes a precise enough platform-independent model of specific domain.
Saliency-cognizant robust view synthesis in free viewpoint video streaming

In free viewpoint video, texture and depth maps from two camera-captured viewpoints are transmitted, so that at receiver, a novel virtual view chosen by the client can be synthesized via depth-image-based rendering (DIBR). When irrecoverable packet losses occur during transmission-typically affecting less important spatial regions in the video given unequal error protection (UEP) is deployed-appropriate error concealment strategies must be used at decoder to minimize resulting visual degradation in the synthesized view. Towards this goal, we propose a new optimization framework based on visual saliency to combine two different concealment techniques. First, given a pixel in the virtual view is typically constructed as a convex combination of corresponding pixels in the left and right captured views, weighted pixel blending (WPB) readjusts the weights in the linear sum to reflect the expected error in code blocks that contain the corresponding pixels. Second, exemplar-based patch matching (EPM) finds the most similar patches in the known spatial region to complete missing pixels in the unknown region. To choose between candidates constructed using the two techniques when filling a given pixel patch in the synthesized view, we first compute a weighted sum of expected error and visual saliency for each candidate patch. The candidate with the smaller sum (one with small expected error and visual saliency, so that even if errors do occur, they do not stand out visually) is selected for pixel completion. Experimental results show that our scheme can outperform the use of co-located blocks from a previous frame by up to 0.7dB in PSNR and improve subjective visual quality.
Compression of touchless multiview fingerprints

Recently, touchless multiview fingerprinting technology has been proposed as an alternative to overcome the intrinsic problems of traditional contact-based systems. Nevertheless, compression of this kind of signal has not been fully evaluated and standardized. This paper investigates the comparative performance of several encoders for this data, namely WSQ, JPEG2000, H.264/AVC and MMP. Experimental results show that WSQ encoder, which is the current compression standard for contact-based fingerprints, is objectively outperformed by all others. In particular, MMP, which achieved the best results, outperforms WSQ by up to 4 dB.
Context adaptive mode sorting for fast HEVC mode decision

Typical H.265/High Efficiency Video Coding (HEVC) encoder implementations test a variety of prediction modes and select the optimal configuration for each block in terms of Rate-Distortion (RD) cost. A fast HEVC mode decision algorithm is proposed here referred to as Context Adaptive Mode Sorting (CAMS). The frequency of selection of modes and their RD costs are collected while encoding the training frames based on local parameters (the context). This information is then used to sort and restrict the prediction modes to test for each context, while the optimal mode found using CAMS on each CU is validated based on the RD cost distributions found during the training. Experimental results show that the method reduces total encoding time of fast HEVC implementations on average by 29.3%, at modest efficiency losses.
S-EMG Signal Compression in 1D and 2D Approaches.

This work presents algorithms designed for 1D (one-dimensional) and 2D (two-dimensional) surface electromyographic (S-EMG) signal compression. The 1D approach is a wavelet transform-based encoder. An adaptive estimation of the spectral shape is used to carry out dynamic bit allocation for vector quantization of transformed coefficients. Thus, an entropy coding is applied to minimize redundancy in quantized coefficient vector and to pack the data. In the 2D approach algorithm, the isometric or dynamic S-EMG signal is properly segmented and arranged to build a two-dimensional representation. The HEVC video codec is used to encode the signal, using 16 bit-depth precision, all possible Coding/Prediction Unit sizes and all Intra coding modes. The encoders are evaluated with objective metrics, and a real signal data bank is used. Furthermore, performance comparisons are also shown in this work, where the proposed methods have outperformed other efficient encoders reported in the literature.
Fast H.264/AVC to HEVC transcoding based on machine learning

Since the HEVC codec has become an ITU-T and ISO/IEC standard, efficient transcoding from previous standards, such as the H.264/AVC, to HEVC is highly needed. In this paper, we build on our previous work with the goal to develop a faster transcoder from H.264/AVC to HEVC. The transcoder is built around an established two-stage transcoding. In the first stage, called the training stage, full re-encoding is performed while the H.264/AVC and the HEVC information are gathered. This information is then used to build a CU classification model that is used in the second stage (called the transcoding stage). The solution is tested with well-known video sequences and evaluated in terms of rate-distortion and complexity. The proposed method is 3.4 times faster, on average, than the trivial transcoder, and 1.65 times faster than a previous transcoding solution.
Touchless-to-touch fingerprint systems compatibility method

Touchless multiview fingerprinting technology has been proposed as an alternative to overcome intrinsic problems of traditional touchbased systems. However, if one wants to benefit from the advantages presented by touchless scanners, the captured images must be processed in order to become compatible to touchbased systems. This paper proposes a two-step solution to the touchless-to-touch compatibility problem. First, it reproduces the texture of touchbased acquisition; and second, it performs a geometric transformation in order to approximate the nail-to-nail touchbased enrollment process. Two experiments were proposed, one to evaluate the quality of the processed images, another one to estimate the EER (equal error rate) for a set of 200 fingerprints (100 fingers, 2 images per finger). Results show that 90% of the images presented good, very good or excellent scores according to NFIQ. In addition, the observed EER was approximately 4%, demonstrating the viability of the proposed method.
HEVC-based scanned document compression

This paper proposes a hybrid pattern matching/transform-based compression engine for scanned compound documents. The novelty of this approach is demonstrated by using a modified version of the HEVC (High Efficiency Video Coding) Test Model as a compound document compressor, here conveniently referred to as HEDC (High Efficiency Document Coder). The proposed method uses segments of a document to create a video sequence, which is then encoded by HEDC. The idea is to explore interframe prediction as a pattern matching algorithm for coding units pre-classified as text; and intraframe prediction for coding units pre-classified as image. Results show that HEDC outperforms AVC-I, HEVC-I (H.264/AVC and HEVC operating in pure intra mode), H.264/AVC and JPEG2000 by up to 3.3, 2.5, 1.7 and 5 dB, respectively. Furthermore, for most documents the proposed method yields practically the same rate-distortion performance as regular HEVC, but is approximately 5% to 20% faster due to a pre-classification algorithm that prevents it of performing all possible inter/intra prediction tests for each prediction unit.
Parameter estimation for an H.264-based distributed video coder

In this paper we present a statistical model used to select coding parameters for a mixed resolution Wyner-Ziv framework implemented using the H.264/AVC standard. This paper extends the results of a previous work for the H.263+ case to the H.264/AVC coder, since the parameters need to be recalculated for the H.264 case. The proposed correlation estimation mechanism guides the parameter choice process, and also yields the statistical model used for decoding. This mechanism is proposed based on extracting edge information and residual error rate in co-located blocks from the low resolution base layer that is available at both ends.