nils-herrmann/clean_scirepeval huggingface dataset:
Towards unbiased end-to-end network diagnosis

Internet fault diagnosis is extremely important for end-users, overlay network service providers (like Akamai [), and even Internet service providers (ISPs). However, because link-level properties cannot be uniquely determined from end-to-end measurements, the accuracy of existing statistical diagnosis approaches is subject to uncertainty from statistical assumptions about the network. In this paper, we propose a novel least-biased end-to-end network diagnosis (in short, LEND) system for inferring link-level properties like loss rate. We define a minimal identifiable link sequence (MILS) as a link sequence of minimal length whose properties can be uniquely identified from end-to-end measurements. We also design efficient algorithms to find all the MILSs and infer their loss rates for diagnosis. Our LEND system works for any network topology and for both directed and undirected properties and incrementally adapts to network topology and property changes. It gives highly accurate estimates of the loss rates of MILSs, as indicated by both extensive simulations and Internet experiments. Furthermore, we demonstrate that such diagnosis can be achieved with fine granularity and in near real-time even for reasonably large overlay networks. Finally, LEND can supplement existing statistical inference approaches and provide smooth tradeoff between diagnosis accuracy and granularity.
Strategy of combining random subspace and diversified active learning in CBIR

Generally speaking, several aspects related to relevance feedback based CBIR include what means should be adopted for approximate semantic description of image content, what strategies be applied to sample labeling in feedback and what relevance model would be built for online discrimination. Using random sampling strategy, we construct a set of random subspaces for learning multiple intrinsic descriptions of image content, with each of which stable component classifier can be trained. To enhance the generalization capability of relevance model, the diversified active learning is carried out by collecting more informative samples, i.e. those samples spreading around decision boundary dispersedly. The final favorable performance also contributes to the application of ensemble scheme on individual component classifier.
Application research of Raman thermometer on quality evaluating of fiber coil

Fiber coil is a kind of key optical component used in fiber optic gyroscope, and its stability and anti-jamming capability directly influence the performance of the whole fiber optic gyroscope. The quadrupolar winding of fiber coil can restrain thermally induced nonreciprocity obviously at ideal conditions; however, various nonideal factors severely limit the advantage of the quadrupolar winding. A novel method for analyzing the quality of the fiber coil using Raman temperature measurement technology is proposed. The nonreciprocity of fiber coil can be judged by analyzing Raman scattering of fiber coil under conditions of varying temperature, and then the quality of winding a coil can be judged. The corresponding experiments have been done to verify the effect this new method. The results show that this non-destructive method has a guiding role to the fiber coil winding method and technology, and also provide a way for evaluating the quality of the fiber coil.
Multiple PiPs detection in unbounded video stream

Picture-in-picture detection aims to detect the video clips that are embedded as a sub-window into a background video with similar semantic meaning, which plays an important role in various multimedia applications such as video copy detection and semantic relationship mining. While some PiP detection algorithms have been given in existing work, less effort has been made on the detection of multiple PiP clips in unbounded video streams. In this paper, we propose a successive-group prior of both PiP and non-PiP clips based on the statistics of single PiP detection accuracy. Using this prior, a new algorithm, which involves a series of geometrical and temporal constraints for handling both the spatial and temporal localizations, is proposed for detecting multiple PiP clips. The extensive experimental results show that the proposed algorithm can efficiently localize the spatial positions and precisely detect the starting and ending time stamps of multiple PiP clips.
Notice of RetractionExperimental Investigation of Solar Panel Cooling by a Novel Micro Heat Pipe Array

A novel micro heat pipe array was used in solar panel cooling. Both of air-cooling and water-cooling conditions under nature convection condition were investigated in this paper. Compared with the ordinary solar panel, the maximum difference of the photoelectric conversion efficiency is 2.6%, the temperature reduces maximally by 4.7°C, the output power increases maximally by 8.4% for the solar panel with heat pipe using air-cooling, when the daily radiation value is 26.3 MJ. Compared with the solar panel with heat pipe using air-cooling, the maximum difference of the photoelectric conversion efficiency is 3%, the temperature reduces maximally by 8°C, the output power increases maximally by 13.9% for the solar panel with heat pipe using water-cooling, when the daily radiation value is 21.9 MJ.
A profust-reliability-based health monitoring technique of spacecraft

The system health management technology uses observation data, system models, and relative intelligent algorithms to monitor system anomaly, evaluate system degradation, predict residual life, and further determine the corresponding maintenance and operation strategy. Recently, the in-orbit management work of spacecraft in China focuses on fault detection and diagnosis, whereas the spacecraft's health management technology stays in the framework study status. For the spacecraft's health monitoring, the theory and algorithm are important to support practical engineering. Therefore, this paper introduces the profust-reliability-based health monitoring method into the in-orbit management work of spacecraft. This method analyzes telemetry parameters of spacecraft, and calculates the profust reliability of telemetry parameters, component, and system, respectively. Then, the health level of the spacecraft is classified according to the calculated profust reliability value. This method provides a new thought to the in-orbit management work of spacecraft. The simulation result shows that this method can effectively evaluate the health status of spacecraft system.
New progress on integrated environment for intelligent manufacturing automation

A methodology is proposed for advanced automation in manufacturing. Building on top of the current CAD/CAM techniques and expert system methods, integrated intelligent systems can realize decision-making automation based on a knowledge processing technique to meet the challenge of the upcoming knowledge-intensive industry. The parallel hierarchical structure of integrated intelligent software systems is developed, and an architecture of the integrated intelligent unit for controlling and managing large-scale intelligent systems is investigated. In an integrated intelligent system, the different expert systems and numerical computation routines are coordinated by a metasystem. These expert systems and numerical routines are written in different languages or programming tools, and used separately. In this way, it is possible to easily add new programs and reduce the scope of rule search to enhance efficiency.<<ETX>>
The Application of Sensitivity Method in Vehicle Dynamics Analysis

Aimed at the effect of variable coefficients and the constant coefficients to the system, a quarter-car two degree freedom suspension vibration model is described, with the aid of matlab alternating senior programmable language, the algorithm is gained through function file, the simulation model of the road noise and the suspension system is obtained. Moreover, The one order standard sensitivity function is adopted, the actual model of one quarter-car two degree freedom suspension system is designed, and the standard sensitivity response of vehicle body velocity, body displacement and the tire displacement is analyzed, the sensitive degree of the change of the structure dynamic characteristics variation is studied. The results indicate that the method can improve the design efficiency and reduce the cost of the design.
An efficient adaptive failure detection mechanism for cloud platform based on volterra series

Failure detection module is one of important components in fault-tolerant distributed systems, especially cloud platform. However, to achieve fast and accurate detection of failure becomes more and more difficult especially when network and other resources' status keep changing. This study presented an efficient adaptive failure detection mechanism based on volterra series, which can use a small amount of data for predicting. The mechanism uses a volterra filter for time series prediction and a decision tree for decision making. Major contributions are applying volterra filter in cloud failure prediction, and introducing a user factor for different QoS requirements in different modules and levels of IaaS. Detailed implementation is proposed, and an evaluation is performed in Beijing and Guangzhou experiment environment.
Adaptive reversible watermarking using trimmed prediction and pixel-selection-based sorting

Prediction error expansion based on sorting is an important technique in reversible watermarking since it yields large embedding capacity and low distortion. In this paper, an efficient and adaptive reversible watermarking scheme is proposed based on trimmed prediction and pixel selection sorting. The trimmed prediction excludes one singular pixel from the neighboring region. A more efficient sorting method is used to achieve lower distortion. Then, a further sorting that considers context complexity is proposed to ensure better visual quality. The smooth pixels located in rough areas are assigned high priorities for carrying bits by using the prediction error expansion method. With these improvements, our method shows better performances in terms of capacity and distortion.
Comparative Research of a Wound-Field Doubly Salient Generator With Different Rectifiers

The wound-field doubly salient generator (WFDSG) is receiving consideration for the field of industrial and aerospace/aviation, since it has the advantages of high robustness with simple structure and adjustable output voltage. In this paper, upon the analysis of generator structures, the features of three rectifiers that are suitable for WFDSG are analyzed in detail. The comparative research of WFDSG with hybrid half-bridge rectifier (HHBR), full-bridge rectifier (FBR), and half-bridge rectifier is presented by the finite-element method (FEM). Then, the load and no-load characteristics of WFDSG under the three rectifiers mentioned above are researched comparatively. The commutation overlap angles and total commutation output voltage losses of three rectifiers are deduced. The experiments of a 12/8-pole single armature-winding WFDSG (SAW-WFDSG) with an FBR and a 12/8-pole dual-armature-winding WFDSG (DAW-WFDSG) with HHBR prototypes have been performed. The FEM and experiment results shows that the SAW-WFDSG with FBR and the DAW-WFDSG with HHBR both have a good application prospect.
Multiple Description Coding With Randomly and Uniformly Offset Quantizers

In this paper, two multiple description coding schemes are developed, based on prediction-induced randomly offset quantizers and unequal-deadzone-induced near-uniformly offset quantizers, respectively. In both schemes, each description encodes one source subset with a small quantization stepsize, and other subsets are predictively coded with a large quantization stepsize. In the first method, due to predictive coding, the quantization bins that a coefficient belongs to in different descriptions are randomly overlapped. The optimal reconstruction is obtained by finding the intersection of all received bins. In the second method, joint dequantization is also used, but near-uniform offsets are created among different low-rate quantizers by quantizing the predictions and by employing unequal deadzones. By generalizing the recently developed random quantization theory, the closed-form expression of the expected distortion is obtained for the first method, and a lower bound is obtained for the second method. The schemes are then applied to lapped transform-based multiple description image coding. The closed-form expressions enable the optimization of the lapped transform. An iterative algorithm is also developed to facilitate the optimization. Theoretical analyzes and image coding results show that both schemes achieve better performance than other methods in this category.
Efficient Scalable Distributed Video Coding Based on Residual SW-SPIHT

In this paper, a novel scheme for scalable distributed video (SDVC) is introduced, which dealing with quality scalabilities. More specifically, efficient H.264/AVC intra-frame coding is used to obtain a base quality layer, the residual between the base layer and the original video is encoded by distributed video coding (DVC) with SW-SPIHT to generate the enhancement layer. The side information is generated by the residual between the base layer and the frame interpolated by motion estimation. Since the residual coding exploits the similarity between the base layer and enhancement layer, experimental results show this SDVC approach is more efficient than the referenced but with similar encoding computation.
A reversible data hiding based on adaptive prediction technique and histogram shifting

Reversible data hiding recovers the original image from the stego-image without distortion after data extraction. In this paper, we propose a novel reversible data hiding method based on adaptive prediction techniques and histogram shifting. Because most natural images always contain edges, it is not suitable to predict these pixels using existing prediction methods. For more precise prediction, two prediction methods are adaptively used to calculate prediction error according to the characteristic of a pixel. As a result, two prediction error histograms are built. One is for pixels located at edges, and the other is for the rest pixels. Data are embedded in the image by using histogram shifting method. In addition, a new sorting method is applied to histogram shifting, which considers the differences of all pixel pairs in the neighborhood and better reflects the correlation among pixels. Through the sorting method, the prediction errors with small absolute values are arranged in the front and more embeddable pixels are preferentially processed. Therefore, the number of shifting pixels is decreased if the peaks in the histograms are all dealt with or the capacity is satisfied, which is beneficial to distortion reduction. Experimental results demonstrate that the proposed method acquires greater capacity and higher quality compared with other state-of-the-art schemes.
Reversible watermarking based on PMO of triplets

A reversible watermarking algorithm based on piecewise modification operation(PMO) of triplets is proposed in this paper. PMO is designed to embed a bit into any two pixels while remaining the intensity sum of pixels unchanged. Two bits are embedded into a triplet by repeatedly using PMO on every two neighboring pixels. Another advantage of using PMO is that the capacity consumed by the additional information can be largely decreased. As a result, the embedding capacity is considerably increased. A series of experiments is conducted to verify effectiveness and advantages of the proposed approach.
Saliency detection using secondary quantization in DCT domain

Saliency detection as an image preprocessing has been widely used in many applications such as image segmentation. Since most images stored in DCT domain, we propose an effective saliency detection algorithm, which is mainly based on DCT and secondary quantization. Firstly, the DC coefficient and the first five AC coefficients are used to get the color saliency map. Then, through secondary quantization of a JPEG image, we can obtain the difference of the original image and the quantified image, from which we can get the texture saliency map. Next, considering the center bias theory, the center region is easier to catch people's attention. And then the band-pass filter is used to simulate the behavior that the human visual system detects the salient region. Finally, the final saliency map is generated based on these two maps and two priorities. Experimental results on two datasets show that the proposed method can accurately detect the saliency regions and outperformed existing methods.
Fault-Tolerant Performance of a Three-Phase Dual Armature-Winding Doubly Salient Brushless DC Generator

The fault-tolerant generator is widely adopted in high-reliability applications. This paper comprehensively investigates the fault-tolerant performance of a five-phase 20/16-pole single armature-winding doubly salient brushless dc generator (SAW-DSBLDCG) and a three-phase 12/8-pole dual armature-winding DSBLDCG (DAW-DSBLDCG). The two generators are connected to half wave rectifiers. The configurations, the principles, and the characteristics of fault-tolerance for two generators are analyzed. Comparisons in terms of the no-load and load characteristics of three-phase DAW-DSBLDCG with normal and open-circuit faults, the output voltages, powers, and magnetic flux density distributions of the two generators are conducted using finite element method, and the armature reaction characteristics under fault conditions are analyzed. The results show that the three-phase DAW-DSBLDCG has higher power density than the five-phase SAW-DSBLDCG under normal and fault conditions. A prototype three-phase 12/8-pole DAW-DSBLDCG is developed, and the simulation and experimental results show that the three-phase DAW-DSBLDCG with hybrid half-wave rectifier structure has high fault-tolerance ability.
Synthesis of ZnS urchin-like nanostructures for electrochemical determination of uric acid

In this work, Zinc sulphide (ZnS) urchin-like nanocrystals were synthesized via a simple hydrothermal method. By controlling the ratio of the reaction solvent ethylenediamine (EN) and water, we can get different nanostructures. The morphology and crystal properties of synthesized materials were characterized with FESEM and XRD. Optical properties were characterized by UV-visible spectrometer and fluorescence spectrometer. Due to large surface-area-to-volume ratio, ZnS urchin-like nanostructures were chosen to spin-coated on ITO glass and then immobilized with uricase enzyme to form a working electrode to determine the concentration of uric acid in aqueous solution by an enzyme-based electrochemical method. The results showed a high sensitivity of 9.55861e−6A·cm−2-mM−1. The detecting linear range is from 0.01 mM to 1mM with detecting limit of 1.16μM and correlation coefficient of R2=0.99967.
An Integrative Codebook for Natural Scene Categorization

Natural scene categorization (NSC) is an important and challenging task. Several state-of-the-art NSC systems use a codebook of visual terms to characterize images with the statistic of visual word counts. However, some kind of codebook generally tends to be more favorable for characterizing a special scene category, which takes either flat property or salient one. To obtain the good tradeoff performance between the block-based codebook and salience- based one, an integrative codebook for image representation is proposed in this paper. Moreover, we exploit a modified Latent Dirichlet Allocation (LDA) model for learning the code words and themes of natural scene categories. The categorization accuracy of the model based on our integrative codebook achieves about 73.67% on a large set of 15 categories of complex scenes.
Policy Conflict Detection in Composite Web Services with RBAC

In the Web services environment, RBAC (role-based access control) model is widely accepted as an efficient approach to manage the access control. By defining the authorization relationship between subject roles and object roles in the RBAC, authorization policies are utilized to simplify the authorization management on different Web services. But the scalability and complexity of composite Web services may cause authorization policy conflict. A new authorization policy added to the system may conflict with existing ones and result in authorization chaos and authorization leaking. And when implemented in the composite Web services, policy conflict detection would be of high cost with manually checking. That makes automatic policy conflict detection important to ensure the security of authorizations in the composited Web services. This paper analyzes the features of the authorization policy in the CWS-RBAC (RBAC for composite Web services) and presents methods of detecting policy conflict including subject role propagation conflict, object role composition conflict and context conflict. The experiment designed is to validate the efficiency of each conflict detection method.
Single depth image super-resolution with multiple residual dictionary learning and refinement

Learning-based image super-resolution methods often use large datasets to learn texture features. When these methods are applied to depth images, emphasis should be given on learning the geometrical structures at object boundaries, since depth images do not have much texture information. In this paper, we develop a scheme to learn multiple residual dictionaries from only one external image. After depth image super-resolution, some artifacts may appear. An adaptive depth map refinement method is then proposed to remove these artifacts along the depth edges, based on the shape-adaptive weighted median filtering method. Experimental results demonstrate the advantage of the proposed method over many other methods.
Parity-invariability-based reversible watermarking

A reversible integer transform, defined on an image pixel pair, is proposed. The transform can carry 1-bit watermark while retaining the parity of the sum of the pairs. Also, the transform makes one transformed pixel not related to the watermark bit which can be reused to construct a new pair with its next pixel. So the embedding rate can approach 1 bit per pixel for a single embedding process. Meanwhile, the decision on whether this new pair can be used for reversible embedding or not is greatly simplified. In addition, the application of the transform is able to largely increase the compression ratio of the location map, and finally increase the payload. A series of experiments has been conducted to verify the effectiveness of the proposed approach.
Study on network topology discovery in IP networks

Nowadays, network is becoming more and more complicated. Topology discovery becomes a hot research point as it is of high importance to network management. Current topology discovery methods have been investigated in this paper, which can be classified as common-protocol-based method, router-protocol-based method and SNMP-protocol-based method, all of which are specifically discussed in the following sections. The advantages, disadvantages and using scope of every method are analyzed and finally a comparison is made.