nils-herrmann/clean_scirepeval huggingface dataset:
Research and design of a layout structure suitable for active loop used in DC circuit breaker based on artificial current zero technology

Multi-terminal HVDC system has gradually become a focus of DC transmission development because of superior economic efficiency and flexibility. It can effectively solve the breaking problems of DC short circuit current happened in multi-terminal HVDC system by developing a high voltage DC circuit breaker (DCCB) suitable for development needs of DC transmission system in our country, and this does good to improve the safety and stability of the power system operation, as well as the power supply reliability. This paper puts forward a layout structure of active loop suitable for DCCB based on the study of artificial current zero technology, which adopts the modular design, converter capacitor with compound insulating overcoat and the stable structure scheme of fixing frame and diagonal member. The layout structure simplifies the electric connection of converter capacitor and also increases the overall stability of active loop which has verified by the simulation of good seismic performance. The layout structure establishes a basis for engineering design of DCCB based on artificial current zero technology in situation of high voltage and large capacity.
A distributed 2D-to-3D video conversion system

2D-to-3D video conversion is a feasible way to generate 3D programs for the current 3DTV industry. However, for large-scale 3D video production, current systems are no longer adequate in terms of the time and labor required for conversion. In this paper, we introduce a distributed 2D-to-3D video conversion system that includes a 2D-to-3D video conversion module, architecture of the parallel computation on the cloud, and 3D video coding in the system. The system enables cooperation among multiple users in the simultaneous completion of their conversion tasks so that the conversion efficiency is greatly promoted. In the experiments, we evaluate the system based on criteria related to both time consumption and video coding performance.
Depth Template Based 2D-to-3D Video Conversion and Coding System

A Depth Template based 2D-to-3D Video Conversion and Coding system (DTVCC) is proposed by this paper. In DTVCC, triangle meshes are exploited to describe depth template for scenes in 2D video, an interactive system is designed to generate reliable depth template, depth map can be automatically reconstructed based on the depth template and 2D video frame pixels information, and the generated 3D video is compressed just by coding the 2D video plus depth template. Experiment results show that not only high quality 3D video is generated, but also the bit rate of coding the converted 3D video is saved by 12%~38% with our proposed system of DTVCC.
High-Accuracy and Low-Complexity Fixed-Point Inverse Discrete Cosine Transform Based on AAN's Fast Algortihm

In this paper, a high accuracy and low-complexity fixed-point inverse discrete cosine transform (IDCT) based on AAN's fast algorithm is proposed for the approximation of the real IDCT. The proposed transform can be implemented with 16-bit multiplication and 24-bit addition operations. A common factor extraction algorithm is used to obtain a new set of real factors of IDCT whose integer approximations can be implemented with few arithmetic operations. A two-stage scale approach is proposed for constraining the dynamic range to a narrow range in scale part. The experimental results show that the proposed transform has significantly higher accuracy than the thresholds of IEEE1180-1190. The results of the proposed IDCT implemented into the decoder of MPEG-2 also show that the fixed-point IDCT achieves higher performance.
Imprecise computation scheduling on scalable media stream delivery

Scalable media streaming provides a layered representation for transmitting media contents over the Internet with packet loss and variable delay. It is an important problem about how to select and schedule packet delivery of a scalable streaming media server. In this paper, we propose a real-time scheduling algorithm based on imprecise computation model for real-time scalable media streams. The scheduling task of a scalable media stream is partitioned into two sub tasks: the mandatory subtask and the optional subtask. The mandatory subtask is for the substream of base layer and the optional subtask is for the substreams of enhancement layers. The imprecise computer model and scheduling algorithm provide scheduling flexibility by trading off video quality reconstructed in client to meet playback deadline. Thus, the better usage of available bandwidth and the smoother playback are achieved. Simulated results show that, with the proposed approach, the playback quality has an obvious improvement.
Simulation of aircraft cabin pressure control based on Fuzzy-PID

When an aircraft flying at high altitude changes altitude, atmospheric pressure will change. As high-altitude atmospheric is much different from ground atmospheric daily adapted, this change can make physical condition of the crew and passengers abnormal, even be risk for their life. Therefore, Aircraft cabin pressure must vary with altitude and the appropriate pressure rate is necessary in order to ensure the safety of crew and passengers and make them comfortable for the cabin pressure and its changing rate. Contrary to cabin pressure control law of modern large civil aircraft in this paper, pressure control system model is established and a Fuzzy PID algorithm is designed to control the cabin pressure model according to nonlinear characteristics of system model. Lastly, aircraft cabin pressure control system is verified by Matlab simulation software for a complete flight. The results of simulation illustrate that the model and the algorithm have good control effect and can meet the precision requirements of cabin pressure control.
Constructing the relationship between concepts in government ontology based on E-Government Thesauri

The paper first reviews the present situation of the construction of ontology in China; then introduces the general e-government thesaurus and reviews the relationships between terms. The authors discuss the basic relationships and summarize 15 relationships between the classes in government ontology. Furthermore, in order to construct government ontology based on the general e-government thesaurus, the semantic relationships between terms of the thesaurus need to be adapted. So the authors present the idea of facet reform of the general e-government thesaurus, and analyze the application of facet thesaurus in the construction of government ontology. Finally, a case which takes the class of ldquoproductrdquo as an example is given to demonstrate that. The paper aims to summarize relationships between concepts in the construction of government ontology.
Switch Simulations Based on Workload Pattern Generation and Smoothed Periodic Input

Simulation is crucial to performance evaluation of switches. Currently stochastic simulation is the predominant approach, which has two drawbacks: few workload patterns and long simulation times. In this paper, we propose a novel switch simulation method that is based on two techniques: exhaustive workload pattern generation and smoothed periodic input generation. The exhaustive workload pattern generation can produce a huge number of nonuniform workload patterns, which far exceeds the traditional few ones; conclusions based on such truly extensive simulations are much more convincing. The periodic input or cell arrival pattern outperforms the stochastic counterpart in terms of easy repetition and fast convergence of simulation; in particular, among periodic inputs, the smoothed periodic input is most favorable to switch scheduling, and hence switches performing poor with it probably performs worse under others. Combining these two techniques together can systematically identify lots of stuck states at which some switches show poor performances such as low throughput. Specifically, this method discovers that the throughput of iSLIP, FIRM and DRRM, each with one iteration, may be lower than 60% under certain nonuniform and smoothed periodic traffic pattern.
Simulation Research of Genetic Neural Network based PID Control for Coke Oven Heating

With the background of coke oven heating control system, a genetic algorithm based CMAC (cerebellar model articulation controller) and PID compound control method is presented to control the temperature of coke oven. Genetic algorithm is used to optimize the initial parameter of PID controller, and CMAC neural network is combined with the optimized PID controller. With the simplified model of coke oven, simulations have been done in MATLAB for the new control method. The simulation results prove that it is feasible to apply this method in the process of coke oven temperature control
Discovering sequence association rules with user access transaction grammars

The authors present a new approach to discover the associations between the access sequences, which is the sequence association rule discovery. In this approach, first we mine the Log in the Web server to get the user access transactions, and then according to the regular grammar we define the new user access transaction grammar in order to get the user sequence access transactions from the user access transactions. Subsequently, we employ the association rule discovery algorithm to discover the sequence association rules. To evaluate these kinds of rules, we propose the mutual information. The results of this approach can help the designer of the Web site to understand the user access patterns better and according to the results the designer can adjust the structure of the Web site.
Amplitude-only optimizing method of multi-subaperture multi-beam antenna for SAR applications

An amplitude-only optimizing method is presented to synthesize the multiple beams of an array antenna for multi-mode SAR application, including stripmap mode, DPCA (Displaced Phase Centers Multi-beam in Azimuth) mode, etc. The array antenna is required to work with the whole aperture or several subapertures in azimuth simultaneously. With an iterative solution scheme of improved projection matrix algorithm (PMA), the amplitude excitations are determined and the sidelobe levels of the beams are controlled. Meanwhile, Taylor-based synthesis method and differential evolution algorithm with global and local neighborhoods (DEGL) are also used to synthesize the beams of the array antenna. With a sample application of multi-beam array antenna design, the effectiveness of amplitude-only PMA is validated and its efficiency is better than the later two methods.
Prediction based on backward adaptive recognition of local texture orientation and Poisson statistical model for lossless/near-lossless image compression

This paper is devoted to prediction-based lossless/near-lossless image compression algorithm. Within this framework, there are three modules, including prediction model, statistical model and entropy coding. This paper focuses on the former two, and puts forward two new methods: prediction model based on backward adaptive recognition of local texture orientation (BAROLTO), and Poisson statistical model. As far as we know, BAROLTO is the best predictor in efficiency. The Poisson model is designed to avoid the context dilution to some extent and make use of a large neighborhood; therefore, we can capture more local correlation. Experiments show that our compression system (BP) based on BAROLTO prediction and Poisson model outperforms the products of IBM and HP significantly.
Research and simulation on flow-shop scheduling problem based on improved genetic algorithm

In order to solve the problem of flow shop scheduling problem which includes disordered material flow and lopsided load of equipment, showing the restraint relationship of workpiece, process and machine with matrix, improving the crossover algorithm and mutation algorithm by introducing linear adaptive algorithm, instancing Car1 (11×5) by applying the improved genetic algorithm. Finally considered the transportation and Simulated Car1 (11×5).
Substructure-finite element method for soil-foundation-structure interaction of CFST arch bridges

In order to study the soil-foundation-structure interaction of concrete filled steel tube(CFST) arch bridges, the theory of substructure is introduced and the substructure-finite element method is adopted. Taking the Nanning Yonghe Bridge for example, three models are developed, which the soil-foundation interaction is introduced in model 1, the interaction is analyzed using Finite Element Method (FEM) in model 2 and using substructure-finite element method in model 3. The vibration characteristics and seismic response of theses models are analyzed. The results show that the natural vibration frequencies of model considered soil-foundation-structure interaction are lower and the displacements and internal forces of seismic response are larger. The natural vibration frequencies and seismic response of the model of soil-foundation-structure interaction simulated using substructure-finite element method are similar to the model using finite element method.
Support vector machines for face recognition with two-layer generated virtual data

This paper presents support vector machines (SVM) for few samples-based face recognition with two-layer artificially generated virtual training data. The few samples cannot express all the conditions of the test data. Thus, we generalize the samples and the feature data to other conditions according to the distribution. First, correspond to the original face images, by locating the eyes center on the face images and facemask template; second is to the feature vectors, we get the feature data by principal component analysis to the face images, then use linear interpolate and extrapolate methods to generate new data. After all the data drawn, SVM is used to train and test. In the ICT-YCNC face database, the proposed system obtains competitive results, and shows the methods are available.
Implicit PID self-tuning controller and its applications

An implicit PID self tuning control algorithm is presented for an intermittently operated chemical reactor in a chemical plant, which is difficult to control with model set up. Getting rid of so many problems in rounding up the parameters of conventional PID algorithm and the length of time to be spent, the algorithm can implement the real time online identification for controlled objects with self tuning function provided for PID controller parameters. Also, the algorithm shows relatively strong robustness via simulation. Therefore, it is available in practice.
Performance Analysis of Dual Frame Motion Compensation

In dual frame video coding, one short-term reference frame (STR) and one long-term reference frame (LTR) are available for motion compensation. The STR is the previous frame of current frame. The LTR remains static for a few frames, and then jump forward. In this paper, for different GOP length and bits allocation of the LTR, the coding performance of dual frame motion compensation is analyzed. The rate-distortion modeling of multi-hypothesis motion compensated prediction is employed to analyze the performance of dual frame motion compensation.
Stabilization of switched linear systems with state multiple time delays

In this paper, the problem of stabilization for consecutive switched system with multiple time-delays is studied. The new multiply time-delays continuous-time switched system stability condition is obtained by designing state feedback controller. The condition is considered by Lyapunov function. The paper not only considered the continuous-time multiple time-delays state feedback system case, but also output feedback system case. At the same time, new criterion of stabilization has been used the same method. At last, the validity and applicability of the proposed approach are successfully demonstrated through simulations.
A parallel context model for level information in CABAC

Context-adaptive binary arithmetic coding (CABAC) is one of the most time-consuming modules in H.264/AVC decoder. A potential way to accelerate CABAC is by parallelization. However, the context modeling process for level information in CABAC is highly serial in nature and can not be parallelized in the coefficient level. In order to improve the throughput of CABAC, in this paper we present a parallel context model for level information. The key feature of the model is to use the total number of the significant coefficients and the scanned position of the current significant coefficient in the quantized transform coefficient block as the context information. Since the context information is independent of the previously decoded significant coefficients, parallel decoding in coefficient level is achieved. In experiments, the proposed context model achieves the similar compression efficiency as the CABAC.
Fast disparity and motion estimation based on correlations for multiview video coding

Recently, multiview video coding has attracted great attention from industries and research institutes. However, the heavy computational complexity limits its practical applications. In this paper, a fast disparity and motion estimation for multiview video coding is presented, based on the correlations between the neighboring cameras and between the motion and the disparity. In the proposed approach, first, a search region estimation is proposed to reduce the disparity estimation complexity according to that the camera set is usually fixed and therefore the disparity between the two neighboring views can be limited to an estimable range. Second, a motion vector derivation is given based on the geometric relationship between the motion and the disparity. In addition, an early termination scheme is provided to further reduce the number of reference frames. The experimental results show that roughly 50% time saving for disparity and motion computing can be reached when compared to the anchor in multiview video coding test model JSVM only with negligible coding efficiency loss.
A greedy clustering algorithm along the time axis for Chinese language recognition

Sign language is the language used by the deaf. Chinese Sign Language (CSL) is primarily composed of a gesture language complemented by a finger-spelling language, containing 30 finger-spelling alphabets and about 5,500 basic sign words. This paper focuses on CSL recognition. Using the characteristics of the sign words in the CSL gesture language, an algorithm called GLATA (Greedy cLustering Algorithm along the Time Axis) is proposed to segment the sign words, a training algorithm based on GLATA is proposed to train the template corresponding to each word, and a recognition algorithm based on GLATA is used to recognize 227 words randomly selected from CSL with an accuracy of 96%. In addition, a sign segmentation technique based on the overall movement speed of the hand is proposed to delete "movement epenthesis" in continuous signing. From the experimental results, it is shown that GLATA is an effective algorithm for CSL recognition.
Event Tactic Analysis Based on Broadcast Sports Video

Most existing approaches on sports video analysis have concentrated on semantic event detection. Sports professionals, however, are more interested in tactic analysis to help improve their performance. In this paper, we propose a novel approach to extract tactic information from the attack events in broadcast soccer video and present the events in a tactic mode to the coaches and sports professionals. We extract the attack events with far-view shots using the analysis and alignment of web-casting text and broadcast video. For a detected event, two tactic representations, aggregate trajectory and play region sequence, are constructed based on multi-object trajectories and field locations in the event shots. Based on the multi-object trajectories tracked in the shot, a weighted graph is constructed via the analysis of temporal-spatial interaction among the players and the ball. Using the Viterbi algorithm, the aggregate trajectory is computed based on the weighted graph. The play region sequence is obtained using the identification of the active field locations in the event based on line detection and competition network. The interactive relationship of aggregate trajectory with the information of play region and the hypothesis testing for trajectory temporal-spatial distribution are employed to discover the tactic patterns in a hierarchical coarse-to-fine framework. Extensive experiments on FIFA World Cup 2006 show that the proposed approach is highly effective.
A HVS-guided approach for real-time image interpolation

In this paper, we propose a novel interpolation algorithm for adapting the human visual system (HVS) and applying in real-time image upscaling. The defined statistical features are first computed in a local window of the low-resolution (LR) counterpart. Then the most correlated neighbours of a missing pixel in high-resolution (HR) image are adaptively selected based on local structural analysis for the prominent edges and fine textures. Finally, the unknown pixel values are estimated through a designed directional clustering model (DCM) which incorporates HVS information into the weighted coefficients. The extensive experimental results show that the proposed image interpolation method can accurately reconstruct the structures of HR image in term of arbitrary magnification factors and effectively suppress the jaggy/ringing artifacts with low computation complexity.
Accurate moving object segmentation by a hierarchical region labeling approach

This paper proposes a new algorithm to segment moving objects from color sequences accurately. The segmentation procedure is treated as a Markovian labeling process and is formulated by a hierarchical Markov random field (MRF) model. Initially, the original frame is partitioned into homogeneous regions with different granularity by the rapid watershed algorithm. Then, the foreground is detected as outliers of the estimated background motion in the initial motion classification stage. After that, the motion vector is estimated for each foreground region and is validated by an elaborate occlusion detection scheme. The initial object mask is segmented by the MRF model on the larger-scale spatial partition and is refined by the other MRF model in the small-scale partition. The hierarchical MRF models provide the fine object boundary. The proposed method is evaluated on several real-world image sequences and the experimental results shows remarkable performance.
A Service Selection Method of Non-critical Task in Parallel Structure

Aiming at the neglected selection for non-critical task in parallel structure, this paper provides a method of services selection based on grey relational analysis. It regards the execution time of critical task as the upper limit for the execution time of non-critical task, uses the execution time of non-critical task as the reference series, and takes other QoS criteria as compared series. And the grey relational grades represent the relational degree between the QoS criteria and the execution time; the grey relational grades are reduced to the QoS criteria’s weights, then evaluating the weighted sum of criteria in order to choose the optimized candidate Web QoS service of parallel structure. Though the selection sacrifices the execution time of non-critical task, it has no influence on the execution time of parallel structure, and improves other QoS criteria simultaneously. The instance analysis shows that the method is a composite service QoS optimization technique which does not affect the execution time of composite services and obtains the better service quality at the cost of sacrificing the execution time of non-critical task.