nils-herrmann/clean_scirepeval huggingface dataset:
Monocular Video Foreground/Background Segmentation by Tracking Spatial-Color Gaussian Mixture Models

This paper presents a new approach to segmenting monocular videos captured by static or hand-held cameras filming large moving non-rigid foreground objects. The foreground and background objects are modeled using spatialcolor Gaussian mixture models (SCGMM), and segmented using the graph cut algorithm, which minimizes a Markov random field energy function containing the SCGMM models. In view of the existence of a modeling gap between the available SCGMMs and segmentation task of a new frame, one major contribution of our paper is the introduction of a novel foreground/background SCGMM joint tracking algorithm to bridge this space, which greatly improves the segmentation performance in case of complex or rapid motion. Specifically, we propose to combine the two SCGMMs into a generative model of the whole image, and maximize the joint data likelihood using a constrained Expectation- Maximization (EM) algorithm. The effectiveness of the proposed algorithm is demonstrated on a variety of sequences.
A Steering Vector Estimation Algorithm in Uncalibrated Arrays

The projection rotation scaling algorithm has perfect performance for estimating the steering vectors of uncalibrated isotropic sensors. But orders of the estimated steering vectors have randomicity in the algorithm. This paper presents a new steering vector initialization and signal subspace forming method. The method not only improves performance of the projection rotation scaling algorithm especially in low SNR conditions, but also can eliminate the randomicity of the orders. Numerical stimulations are provided to prove the effectiveness.
A new wideband source number estimation algorithm based on line property

The research of wideband source number estimation is still key issue in space spectrum estimation. The veracity of the direction finding algorithms is directly influenced by the false alarm and miss probability. However, the performances of them are degraded under the low SNR, colored noise fields and these algorithms have higher computational complexity. To overcome these drawbacks, a new wideband source number estimation algorithm based on line property is proposed. The simulation results with low SNR, colored noise fields demonstrate the correctness and effectiveness.
Color tracking by transductive learning

One of the difficulties of color tracking is that color changes in different lighting conditions, and static color models would be inadequate to capture the nonstationary color distribution over time. Although some work has been done on adaptive color models, this problem still needs further investigation. Different from many other approaches, we formulate the nonstationary color tracking problem as a transductive learning problem, in which the generalization of a trained color classifier is only defined on the pixels in a specific image, rather than the whole color space. This formulation offers a way to design and transduce color classifiers through non-stationary color distribution. Instead of assuming a color transition model. We assume that some unlabeled pixels in a new image frame can be "confidently" labeled by a "weak classifier" according to a preset confidence level. The proposed Discriminant-EM (D-EM) algorithm offers an effective way to transduce color classifiers as well as automatically select a good color space. Experiments show that D-EM successfully handles some problems in color tracking. As a component our natural gesture interface, this algorithm gives tight bounding boxes of the hand or face regions in video sequences.
A TOC combining ACO sequencing method for the semiconductor manufacturing fabrication

Based on the analysis on the scheduling characteristics of the semiconductor manufacturing fabrication lines, we propose a TOC(Theory-of-Constraints) combining ACO(Ant Colony Optimization) sequencing method. The method firstly determines the bottlenecks of a semiconductor manufacturing fabrication line, and then applies an ACO algorithm to obtain the optimized jobs processing priority sequence of the bottlenecks, which is the constraint to deduce the jobs processing priority sequence of other non-bottleneck areas. A simplified semiconductor wafer fabrication line model(Mini-fab) is used to verify and validate the proposed method. The simulation results show that the proposed method is superior to the common scheduling rules (such as FIFO, EDD and CR), with the ability to obtain an optimized scheduling solution in a reasonable time.
Investigation on Strain-Sensing Suspended Single-Walled Carbon Nanotube Arrays

An electromechanical system is constructed to explore the electrical properties of well-aligned horizontal suspended single-walled carbon nanotube (SWCNT) arrays under the influence of tensile stretching. The suspended SWCNT array sensing structure consists of a well-grown SWCNT array suspended between two separated metal electrodes on top of a silicon (Si) wafer with 500-nm-thick thermal oxide layer. Sensor properties are explored in linear region, including sensitivity (gauge factor ~248), linearity (better than 99%), and hysteresis. Results show that the suspended SWCNT array devices have potential application as strain gauges due to their high sensitivity.
A new robust adaptive beamforming method against array imperfections and uncertainties

The performance of the general adaptive array beamforming algorithm is known to declined severely in the presence of array imperfections and uncertainties. So the robustness of adaptive array beamforming techniques against uncertainties is one of the important issues. In the situation of array amplitude and phase errors, signal steering errors and other data mismatch, this paper put forward a new method. This new algorithm can enhance the desired signal and suppress the interference signals simultaneity. The new algorithm estimates the power of desired signal by oblique projection property to add some interference signals. Interference signal has the same power. It is different from other methods. So this processing is specially suit to the situation of the difference power between the desired and interference signal. This technique is presented to widen null of array pattern stably. The performance in the present of array amplitude and phase errors and signal steering errors is assured by the uncertain range restriction. Certainly, this optimization with some restriction can be solved by the lagrange method. The iterative weight vector is proved to be convergent. The new algorithm is not complex. Its validity and superiority are proved by simulation results as compared with the general adaptive array beamforming algorithms.
Production of facial expressions using facial feature positioning and deformation

Based on image processing technique, this paper used face images of users as virtual images to automatically produce different facial expression images. The face images in neural state can be transformed into the facial expression images. First, for the face images in neutral state, skin color segmentation and morphological noise processing were conducted to separate the possible face zone from the background. In terms of feature points (FP) and facial animation parameters (FAP) defined in MPEG-4, feature shape control points were marked for features of the facial expressions: color information of brows, eyes, and mouth. The feature control points were marked on the images during production of the facial expressions. Delaunay Triangulation, image registration and image interpolation were performed to move the feature control points to change face images through interactive interface. The image texture was changed by adjusting positions and shapes of feature texture in order to automatically produce new facial expression images.
A cultural particle swarm optimization algorithm

A new culture-based Particle Swarm Optimization (PSO) with mutation, CPSOM, is proposed in this paper to improve the overall optimization performance of the original PSO and combat with the well-known premature problem. In the CPSOM, the Evolutionary Programming (EP) mutation operator is applied to a proportion of the particles in the population space based on the influence function. The mutation operation is directed by the knowledge stored in the belief space, and the mutation proportion can vary linearly with the growth of the swarm generations. Our CPSOM is investigated using ten high-dimension and multi-peak functions. Numerical simulation results demonstrate that it can indeed outperform both the original PSO and EP.
Notice of RetractionAdsorption of Cu²+ from Aqueous Solution by Anaerobic Granular Sludge

Anaerobic granular sludge was used to remove Cu<sup>2+</sup> from aqueous solution. The results showed that anaerobic granular sludge biology absorbent processing including the Cu<sup>2+</sup> wastewater was feasible, the Cu<sup>2+</sup> elimination rate was achieved 97.67%. The best craft operating parameter of the anaerobic granular sludge biology absorbent processes Cu<sup>2+</sup> could be determined as follows: when the initial concentration of the Cu<sup>2+</sup> wastewater was 320mg/L, pH was 6.5, the temperature was 25°C±1, Adsorbent dosing quantitywas 5g, adsorption duration of oscillation was 60min. Ions Cu<sup>2+</sup>, Zn<sup>2+</sup>, Cd<sup>2+</sup> competitive adsorption existed between and mutual inhibition, and all inter-granular sludge adsorption of heavy metal ions had a negative impact.
A Knowledge Management Solution Based on Enterprise Information Portal

Knowledge Management (KM) is a new problem for e- commerce and Enterprise Application Integration (EAI) , and it has become one of the research front and hotspots in management science and engineering. In this paper, the requirements and key problems of e-commerce application oriented enterprise KM are discussed, a Enterprise Information Portal(EIP) based KM solution is presented, the key techniques for implementation are pointed. At last, a case of Midea is studied, in addition, the developing trends and foreground of KM are discussed also.
A Robust UHF Near-Field RFID Reader Antenna

A novel broadband antenna for ultrahigh-frequency (UHF) near-field radio frequency identification (RFID) applications is presented. The antenna is composed of a grounded coplanar waveguide (GCPW), a coplanar stripline (CPS), a lumped balun, multiple resistors, and a finite-sized ground plane. The load impedance is equal to the characteristic impedance of the CPS, hence traveling wave can transmit along the CPS. The proposed antenna structure can produce large currents along the CPS so that a strong and uniform magnetic field distribution is excited in the adjacent region around the antenna. The antenna geometry, design concept, simulated, and measured results are carefully discussed throughout the paper. Measurements show that the antenna operating with a commercial reader demonstrates good performance of tag identification with inductive coupling for near-field RFID applications. In addition, the parametric study is conducted to facilitate the design and optimization processes for engineers.
A Collaboration Proxy for Converging UPnP and Jini Devices Based on OSGi

We design and implement a Collaboration Proxy to integrate devices on the open service platform, OSGi. The proposed architecture is easy to converge various service oriented applications. Further by the API of the Proxy, new applications across the devices of different domains, such as UPnP and Jini, can be created. .The Proxy is a component module of the OSGi Bundle. A prototype that enables Jini clients to access UPnP services and vice versa is implemented to demonstrate the proposed approach.
RF system for the Duke 1 GeV storage ring

The RF frequency is 178.5 MHz. An amplifier built by the QEI corporation provides 50 kW power. All the power feeds to a single-cell RF cavity, built by BINP at Novosibirsk, Russia, giving a gap voltage of 720 kV. An ANT circulator is used in the feed line. There are four basic feed-back loops to stabilize the system operation: (1) Cavity frequency tuning loop. (2) Cavity voltage control loop. (3) RF phase stabilization loop. (4) Synchrotron oscillation damping loop. The whole system has been tested and operated since December 1993. It has provided secure and stable operation for the storage ring.
Design of event-based Intrusion Detection System on OpenFlow Network

OpenFlow (OF) Network is a novel network architecture many famous cloud service providers have applied it to build their data center network. The difference between OF Network and traditional network architecture is the decoupling of controller planes and data planes for network management. Intrusion detection is very important in cloud computing to improve system security. Because OF network can improve the response time of an alert by efficiently configuring network flows, we design an event-based Intrusion Detection System (IDS) architecture on OF network.
A fast non-convex regularizer for low rank matrix completion

Several non-convex surrogates for rank functions were proposed recently in the rank minimization for the corrupted image recovery and data analysis. In this paper, we propose a fast non-convex regularizer whose main feature is piecewise linearity with three thresholds. Since most singular values are low or infinitesimal for low-rank matrices, which is beneficial for threshold comparisons, the proximal gradient descent for the proposed regularizer can be fast. We further propose that the randomized singular value decomposition (SVD) algorithm can be adopted to perform the partial SVD. When the matrix is low-rank, the proximal gradient descent with the randomized SVD can effectively recover the low-rank structure and save computational time. Experiments on matrix recovery and image recovery are conducted to validate that the proposed algorithm outperforms state-of-the-art regularizers and other low-rank recovery methods.
Multiple target localization based on probability fusion by spatial association

In detecting multiple targets by means of opportunity transmitters, parameter fusion of multiple sensors is a difficulty, which makes it expensive for the system to detect large numbers of targets simultaneously. This paper proposes a new positioning algorithm in the context of multiple non-cooperative illuminators, multiple sensors, to observe multiple targets. Firstly, each sensor extracts the TDOA of multipath and reconstructs the probability density function (PDF) of real parameters. Secondly, the central processing station fuses the probability from all PDFs according to the spatial association. Finally, the centre localizes the targets by multipeak searching on the fused probability function. This algorithm needs no pretreatment of parameter pairing, since all the TDOA values are matched automatically in the course of fusion. The algorithm has the advantage of inhibiting bad parameters to some extent. Numerical simulations support the characters of the new algorithm.
Connectivity-Based Skeleton Extraction in Wireless Sensor Networks

Many sensor network applications are tightly coupled with the geometric environment where the sensor nodes are deployed. The topological skeleton extraction for the topology has shown great impact on the performance of such services as location, routing, and path planning in wireless sensor networks. Nonetheless, current studies focus on using skeleton extraction for various applications in wireless sensor networks. How to achieve a better skeleton extraction has not been thoroughly investigated. There are studies on skeleton extraction from the computer vision community; their centralized algorithms for continuous space, however, are not immediately applicable for the discrete and distributed wireless sensor networks. In this paper, we present a novel Connectivity-bAsed Skeleton Extraction (CASE) algorithm to compute skeleton graph that is robust to noise, and accurate in preservation of the original topology. In addition, CASE is distributed as no centralized operation is required, and is scalable as both its time complexity and its message complexity are linearly proportional to the network size. The skeleton graph is extracted by partitioning the boundary of the sensor network to identify the skeleton points, then generating the skeleton arcs, connecting these arcs, and finally refining the coarse skeleton graph. We believe that CASE has broad applications and present a skeleton-assisted segmentation algorithm as an example. Our evaluation shows that CASE is able to extract a well-connected skeleton graph in the presence of significant noise and shape variations, and outperforms the state-of-the-art algorithms.
A method of hub auto-recognition on line

The wheel manufacturers are always puzzled by the low efficiency and high error rate of manual testing and classification on the automobile hub production lines, because the workers easily feel confused and tired when having a long time of visual observation. This paper presented a mechanized method applied in the non-contact and auto hub recognition on line, which used the capture of the optical digital image to hub, SIFT(Scale Invariant Feature Transform) features extraction and matching.
A Study on Software Reliability Prediction Based on Transduction Inference

Non-parametric statistical methods are applied to verdict that early failure behavior of the testing process may have less impact on later failure process, so it happens in software failure time prediction that one does not have enough information to estimate the software failure process well but do have enough information to estimate the failure data at given instance. The prediction accuracy of software reliability prediction models based on recurrent neural network, feed-forward neural network, relevance vector machine, support vector machine and some nonhomogeneous Poisson process models is compared. Experimental results show that software failure time prediction models based on transduction inference theory could achieve higher prediction accuracy.
Hand modeling, analysis and recognition

Analyzing hand gestures is a comprehensive task involving motion modeling, motion analysis, pattern recognition, machine learning and even psycholinguistic studies. A comprehensive review of various techniques in hand modeling, analysis, and recognition is needed. Due to the multidisciplinary nature of this research topic, we cannot include all the works in the literature. Rather than function as a thorough review paper, this article serves as a tutorial to this research topic. We study 3-D hand models, various articulated motion analysis methods, and gesture recognition techniques employed in current research. We conclude with some thoughts about future research directions. We also include some of our own research results, some of which are shown as examples.
DS/CDMA with predetection diversity over a frequency selective multipath Rayleigh-fading channel

This paper investigates the bit error rate performance of a direct sequence code division multiple access (DS/CDMA) system with predetection diversity over a frequency selective multipath Rayleigh-fading channel. Differential phase-shift-keying (DPSK) modulation and noncoherent demodulation are considered. It is shown that predetection diversify is relatively more efficient in improving the BER performance of the system when the channel conditions are worse. If is also shown that a large number of resolvable paths are beneficial when they are all combined to combat the multipath fading.
Application of Family Eugenics Based Evolution Algorithms to Electric Power System Fault Section Estimation

In this paper, a new family eugenics based evolution (FEBE) theory is proposed to estimate the faulty section in power system. To apply the method to solve this estimation problem, orthogonal design technique is introduced into the course of offspring's breeding inside a family, so as to enhance the behavior amelioration of divides against prematurity and quicken the convergence of low convergence speed at last period. The proposed method is versatile and can deal with uncertainties in fault section estimation, such as the cases with failure operations of relays and circuit breakers, or multiple faults at the same time. Test results for a sample power system have shown that the FEBE approach developed for fault-section estimation is feasible and efficient
The first GeSn FinFET on a novel GeSnOI substrate achieving lowest S of 79 mV/decade and record high Gm, int of 807 μS/μm for GeSn P-FETs

The world's first GeSn p-FinFETs formed on a novel GeSn-on-insulator (GeSnOI) substrate is reported, with channel lengths L<inf>ch</inf> down to 50 nm and fin width W<inf>Fin</inf> down to 20 nm. In comparison with other reported GeSn p-FETs, record low S of 79 mV/decade, record high G<inf>m, int</inf>, of 807 μS/um (VDs of −0.5 V), and the highest G<inf>m, int</inf>/S<inf>sat</inf>, were achieved. The highest high-field hole mobility of 208 cm2/Vs (at inversion carrier density of 8×10<sup>−2</sup> cm<sup>−2</sup>) for GeSn p-FETs with CVD grown GeSn channel was also obtained.
A New Robust Watermarking Algorithm Based on DWT

Robustness is difficult to resolve in digital watermarking research, and contradicts its stealthiness. So the key of designing robust digital watermarking is selecting watermark embedding positions. Around these problems, we study the robust digital watermarking algorithm based on DWT. By wavelet transform, image smoothing based on PDE, and morphology operators (dilation and erosion), we obtain the relative low-frequency regions with small changing which can not be detected easily by human eyes, and then get the embedding positions. The watermark embedded in these positions has a proper consideration on both robustness and invisibility of the watermark. Experiments show that this algorithm is robust to JPEG2000 compression, also to JPEG compression, sharpening, salt and pepper noise, gama correction, a number of regular geometric attacks and other image processing operations.
Understanding customers using Facebook Pages: Data mining users feedback using text analysis

Unlike large companies, start-up companies usually do not have the available resources to afford traditional mass marketing campaigns such as TV commercials or magazine advertisements. However, social networking services (e.g, Facebook, Twitter, Weibo, etc.) provide a more economically more viable opportunity for these new companies to directly communicate with their potential customers. Social networks are significant marketing communication tools for established, and in particular, start-up companies. Some FB Pages contain hundreds of responses and receive good opinions from the readers whereas some Pages do not. By interpreting these Pages, it is possible to generate the key factors that attract customers and for the young entrepreneurs to react to new postings. Text mining the Pages helps to better understand and manage their Pages and build a closer relationship with the target audience. This research proposes an analytical process to interpret the dialogue between young entrepreneurs and their audience of Facebook Pages. First, collect consumer feedback from social networks, like FB. The interpretation of the dialogues into meaningful statistics, especially when attempting to model, cluster, and analyze the critical elements of posted Internet content, requires new text analysis techniques and methodologies. CKIP (Chinese Knowledge and Information Processing) is applied to extract the key phrases from the Chinese language dialogues. Then clustering is used to generate the critical points that customers care about and then to explore key factors that attracts customers and resolves their needs. Therefore, entrepreneurs better understand how to post an interesting topic to strengthen their marketing communications and increase their market share.