nils-herrmann/clean_scirepeval huggingface dataset:
Hemodynamic characteristics for improvement of EEG-BCI performance

Although brain computer interfaces (BCI) based on electroencephalographic (EEG) signals have been studied increasingly over decades, their performance is still limited in two main aspects. First, the shorter the EEG epochs, the more difficult the detection of a BCI command. Second, BCI commands are often misclassified while the subject is not performing any tasks by not focusing on a command (offset condition) because the EEG characteristics of the offset condition are not unique. In order to circumvent these limitations, the hemodynamic fluctuations in the brain during stimulation with steady-state visual evoked potentials (SSVEP) were measured using near infrared spectroscopy (NIRS) simultaneously with EEG. The offset condition is distinguished from the onset condition (focusing on a command) with extracted NIRS features through the design of low-pass filter. BCI command estimates were based on EEG SSVEP response. Simultaneous evaluation of EEG and NIRS was shown to improve the SSVEP classification, notably including the offset condition as an independent class, using a novel offset condition estimation approach. For 13 subjects, wrong classification for 9 classes with inclusion of offset condition were decreased. This proposed bimodal approach including the offset condition detection may render current BCI systems more reliable.
Heterogeneous QoS Video Broadcasting with Optimal Joint Layered Video and Digital Fountain Coding

Heterogeneous QoS video broadcast over wireless network is a challenging problem, where the demand for better video quality needs to be reconciled with different display size, channel condition and QoS requirements. In this paper, we present a framework for broadcasting scalable video to heterogeneous mobile users with diverse display devices and different channel conditions, which includes joint spatial-temporal layered video and Fountain coding optimization. First, we develop an elastic rate video adaptation method so as to serve mobile users with heterogeneous QoS requirements, which includes a hybrid temporal-spatial quality metric. Joint Fountain coding protection is introduced so as to provide adaptive and reliable video streams. Second, we use dynamic programming approach to obtain optimal video layer structure, so as to achieve maximum broadcasting utility. The objective is to achieve maximum overall receiving quality of the heterogeneous QoS users. Experimental results demonstrate the effectiveness of the solution.
Motion estimation based on iterative color matching and structure matching

Motion estimation in detail is required by many vision applications. Conventional method such as optical flow method is often used to calculate the motion between two image frames. Color based constraint such as the assumption of brightness constancy underlies most optical flow estimation methods. However, it is impossible to calculate precise optical flows from only color value, since changing view point and inconstant illumination make the colors of some regions of objects entirely different between consecutive frames. The structure based constraint of object is very necessary for tracking as well. In our proposed method, both the color matching and structure matching are formulated by linear assignment problem and motions are obtained by solving them alternately.
A length matching routing method for disordered pins in PCB design

In this paper, for the disordered pins in printed circuit board (PCB) design, a heuristics algorithm is proposed to obtain a length matching routing. We initially check the longest common subsequence of pin pairs to assign layers for pins. Then, adopt single commodity flow to generate base routes. R-flip and C-flip are finally carried out to adjust the wire length. The experiments show that our algorithm generates the optimal routes with better wire balance within reasonable CPU times.
Embedded binary tree for dynamic point cloud geometry compression with graph signal resampling and prediction

This paper proposes a temporal prediction scheme for the compression of point cloud sequences with dynamic 3D geometry information. Since the point cloud sequences are non-uniformly sampled signals on a graph, it is difficult to apply traditional prediction schemes in video coding such as motion compensation. Instead, we propose a binary tree with embedded octree coding scheme that allows for motion compensation and residual coding at the level of binary tree leaf node. Graph signal processing based reference block re-sampling is employed to eliminate the need to signal the reference points, and a bipartite graph pruning algorithm is used for residual prediction. Simulation results demonstrate the effectiveness of the proposed scheme in a rate distortion sense.
Experimental and Numerical Study of a DC Induction Heater Prototype With an Adjustable Air Gap Structure

To improve the poor efficiency of conventional ac induction heaters, which is usually below 50%, a high-temperature superconducting (HTS) dc induction heater has been proposed as a candidate solution. In previous researches, the air gap structure is fixed, which leads to a less controllable magnetic field distribution along the axial direction of billets, hence a less controllable temperature distribution along the same direction. However, an adjustable temperature distribution along the axial direction of billets is required in the aluminum extrusion industry. In order to solve this problem, a novel adjustable air gap structure is proposed and fabricated in our laboratory-scale prototype of the HTS dc induction heater. To validate the method, heating experiments for uniform and gradient temperature distribution were performed with different air gap structures. In addition, a novel adjustment method, i.e., unilateral adjustment, for air gap structure was proposal and tested, which simplified the adjustment method. A finite-element method model of the heater was built to analyze the temperature distribution and the theoretical availability of adjustable air gap structure.
Nested Web Service Interface Control Flow Automata

The formal definition of NWCFA (nested Web service interface control flow automata) is presented as the model of web service compositions (possibly with recursion). WCFA (Web service interface control flow automata) are used to model individual Web services, which form a composition. WCFA focus on the control flow and service invocation behavior. Then a NWCFA will be constructed to describe the global behavior of the composition. NWCFA use the concept of nested words to deal with recursion. An example is used to illustrate the usage of WCFA and NWCFA. Temporal properties can be verified through an automata-theoretic method.
Research on Ontology Integration Combined with Machine Learning

Recently ontologies are playing very important part in many areas, such as intelligent information retrieve, knowledge management and organization, electronic commerce and so on, however, several drawbacks must be overcome before ontologies become useful and practical tools. As the number of ontologies are made publicly available and accessible on the web increases steadily, a single ontology is no longer enough to support the tasks envisaged by a distributed environment like the semantic web. Multiple ontologies need to be accessed for several applications. A critical issue is ontology integration, which can largely improve the efficiency to enrich such a domain ontology with less time and lower cost for obtaining related knowledge. This paper has deeply studied the principles of ontology integration, then proposes a procedure model for ontology construction and a new framework for ontology integration based on machine learning through analyzing the characteristics and problems in the process of ontology integration.
Research on the collaborative method for vocabulary system constructions

Thesaurus is the basis for document indexing, classification and intelligent information processing. This paper presents the connotation, design method, results of the vocabulary system which is based on collaborative practices, and looks forward to the next step in the Research and Development and application direction. It overcomes the inadequacies of traditional thesaurus such as poor maintenance and long update period. The built science and technology vocabulary system achieves vocabulary management, relation management, new word finding, updates and maintenance and development of API based on web service, forming an integrated system of science and technology vocabulary management and supporting tools.
Transformer Fault Diagnosis Based on Naive Bayesian Classifier and SVR

Because traditional transformer diagnosing approaches are over-rigidity and need almost complete and accurate testing data, a NB (Naive Bayesian) classifier based model to diagnose transformer faults is presented and constructed in the paper. As the diagnosing performance is depressed by incomplete testing data, SVM regression approach is used to estimate the missing data. Thus a new diagnosis model, which integrates SVM regression and NB classifier, is constructed. The diagnosing experiments of different transformer testing scenarios show that the constructed NB diagnosis model has a good performance given complete testing data, and the proposed SVM regression approach can raise the accuracy of transformer diagnosing even if a certainty quantity of data or important data are missed
Macroblock Layer Rate Control in MPEG-2 to AVS-M Transcoder for Mobile Communication

The advanced audio video coding standard-mobile version (AVS-M) is established by AVS Working Group of China for mobile multimedia applications. To meet demands for communication between multimedia source and mobile system, transcoding from MPEG-2 to AVS-M is a key technology. In this paper, we propose a macroblock layer rate control algorithm for MPEG-2 to AVS-M transcoding with the consideration of the influence of new techniques adopted in AVS-M. Analyzing the relation between the mean absolute differences (MADs) of the transcoded and preceded frame, we establish a linear prediction model for MAD prediction when new techniques are used. Utilizing the macroblock layer bit allocation based on MAD, we establish a quadratic R-D model based on frame MAD. The experiment results show that the proposed algorithm based on two models can meet the target bitrate more accurately and achieve a better performance than the reference algorithm in AVS-M encoder.
Study on Simulation System for Turn-Milling Centre Based on VR Technology

A novel 3D simulation system for supporting turn-milling centre design is developed in this paper. In order to solve the shortcomings of using traditional solid model for network-based simulation, the 3D visualization of the model and motion simulation for turn-milling centre is realized by VRML/Java interaction through the external authoring interface (EAI). The virtual environment of the turn-milling centre is established by VRML based on virtual reality technology, and the 3D assembling model is built by UG software and channelled into the virtual environment by VRML format. The optimal method is put forward by three steps optimization data to realize transmission of network. The motion simulation program for turn-milling centre is made by VRML/Java language with the movement simulation control function to realize motion simulation. The system can not only browse motion process of turn-milling centre on a Web browser, but also realize resource-sharing, therefore the research of motion simulation for turn-milling centre based on the Internet has important research value and application prospect.
Fast video shot retrieval by trace geometry matching in principal component space

Content-based video retrieval technology holds the key to the efficient management and sharing of video content from different sources, in different scales, across different platforms, and shared over different communication channels. In this work we present a fast retrieval algorithm based on matching the geometry of video sequence traces in the principal component space. Techniques to address scale (spatial and temporal) issues, as well as, noise and other possible distortions, such as frame dropping, are discussed. Experimental results demonstrate the effectiveness of the proposed approach.
Fault Tolerant Algorithm for NVM to Reuse the Error Blocks

Non-Volatile Memory (NVM) has many advantages such as storage density, non-volatility, and lower energy consumption. However, they are constrained by limited write endurance and lack of an efficient mechanism to recovery the error data, which will affect the lifetime of NVM. In this paper, we propose a fault tolerant algorithm for NVM, that inspired by the redundant technology of RAID(Redundant Arrays of Independent Disks) to recovery the error data and reuse the error blocks. Memory architecture models and the algorithms of read, write and recovery are presented. Our experimental results show that more than 50% of error data can be recovered efficiently if the error rate is under 30%, and the recovery rate is nearly more than 80% if the error rate is under 10%, while the time consumption rate of our method is only within 5%.
Symbol Error Probability Analysis of an FFH/MFSK Receiver with Noise-Normalization Combining in a Fading Channel with Partial-Band Jamming

A new analysis method for the error performance analysis of Nakagami-fading channels is proposed. Two forms of the bit error rate (BER) expressions are derived for a noncoherent fast frequency-hopped M-ary orthogonal frequency-shift-keying (FFH/MFSK) spread spectrum (SS) receiver over frequency non-selective slow Nakagami-fading channels. The FFH/MFSK system employs noise-normalization combining in the presence of partial-band interference (PBI) and additive white Gaussian noise (AWGN). The probability density function (pdf) and characteristics function (CF) based approaches are used for analysis of the error performance. Numerical results show the effects of arbitrarily values of fading parameter and diversity level on system performance.
A simulation study of dynamic load balancing for network-based parallel processing

A simulation study of dynamic load balancing for parallel processing on network of workstations (NOW) is presented in this paper. A simulation model is constructed. It includes a representative CPU scheduling policy, and also considers the message exchange, task transfer and migration costs explicitly. A global dynamic load balancing algorithm is simulated. Both task transfer and task migration are considered. The performance of the algorithm under both homogeneous and heterogeneous environments is analyzed. In addition, the interaction of parallel and sequential workloads on an NOW is also examined. Our results show that dynamic load balancing can achieve better performance improvement for heterogeneous systems than for homogeneous systems; it is especially effective in a system where both parallel and sequential tasks concurrently exist; and the use of task migration generally does not further improve performance.
Batch reactor temperature control based on DMC-optimization PID

Batch reactor temperature control is quite complicated because of production requirements and the complex internal mechanism with time-varying parameters and large time delay. A DMC (Dynamic Matrix Control) strategy is employed to optimize and adjust PID controller parameters adaptively according to the working condition, so that the batch reactor temperature can be controlled stably and robustly. The comparison with PFC (Predictive Functional Control)-PID and conventional PID is made by simulation. It is observed that the proposed method for batch reactor temperature control has better dynamic and static characteristics in the presence of external disturbance, time delay and model parameters mismatch.
Research on Virtual NC Technique in Turning and Milling Process

A virtual machining system based on virtual manufacturing technique and NC machining technique for turn-milling center is developed in this paper, which can realize all processes from the establishment of NC procedure to machining simulation. On the platform of visual C++, the virtual machining environment is built by OpenGL technique, and the structure of machining simulation system and its function are proposed. According to turn-milling center characteristic, the mathematical models about turning and milling are respectively built in virtual NC machining process. The geometric simulation and physical simulation are realized on the basis of the models by C++ language. The research demonstrates that the simulations are handled to complete the virtual machining of the product by checking machining ability, rationality of design, prediction manufacture circle, and promptly modifying design. The method offers the theoretical foundation and reference value of practical application for structure design of turn-milling centre.
2D Imaging algorithm of spaceborne SAR based on compressive sensing

To reduce the data transmission load of spaceborne SAR, this paper proposes a 2D imaging scheme based on compressive sensing (CS). First the sparse characteristics of spaceborne SAR echoes are analyzed, and then the echoes' sparse model and the targets' restore matrix are established. The minimum l1 norm algorithm is used to reconstruct the compressed data in distance and azimuth dimensions, and at last the low-load, high-resolution image is got. The simulation results prove the validity of the algorithm.
Improving the tracking performance of atomic force microscope scanner with the modified rate-dependent Prandtl-Ishlinskii model

A hysteresis compensation method with the Prandtl-Ishlinskii model is presented to improve the tracking performance of the atomic force microscope (AFM). Due to the asymmetric and rate-dependent hysteresis nonlinearity in this work, a modified rate-dependent Prandtl-Ishlinskii model is then utilized to deal with this effect. Without the inversion calculation, a direct inverse hysteresis compensation method is adopted. Experiments results show that the compensated system is linearized. Afterwards, a proportional-integral (PI) controller is introduced to improve the tracking performance of the scanner of AFM. Comparative experiments with the conventional PI control are presented to verify the effectiveness of the proposed control approach, based on the tracking performance and the imaging capability.
Road Recognition in High Resolution SAR Image Based on Genetic Algorithm

Road recognition from SAR image is a very important problem. In this paper, a new method is proposed which can detect multiple roads in an image. Firstly binary edge image is gained by Canny operator and edge refining. Secondly, edge curves are encoded by reversible chained list, and fitness function is constructed based on SAR image road models, and optimal road boundary curves are linked by improved genetic algorithm. Thirdly, complete road boundaries are detected by curve fitting. At last, mated long road edge curves are found out and road surface are stuffed. The experiment shows that this algorithm can realize roads recognition and eliminate influence of other non-road.
A Fast Neutron Detector Using 10B-Lined Ionization Chamber for Mixed Field Dosimetry

We designed a new fast neutron Bonner multi-cylinder neutron detector using boroned-lined ionization chamber, wrapped in a set of 5 high density polyethylene cylinders. The ionization chamber consists of the cavity chamber twins. The response function of Bonner multi-cylinder neutron detector was simulated by Geant4 code. The sensitivity of detector reaches a level of 8.702×10-15A/(cm-2·s-1) under the experiments based on the 241Am-Be neutron source.
A fault prediction approach for power transformer based on support vector machine

Power transformer is one of the most expensive component of electrical power plants and the failures of such transformer can result in serious power system issues, so fault forecasting for power transformer is very important to insure the whole power system runs normally. In this paper, a novel fault prediction approach for power transformer based on Support Vector Machine (SVM) is presented using data of Dissolved Gas Analysis (DGA). Moreover, by comparing with the traditional method's like the grey prediction algorithm, the prediction precision for power transformer is improved using our scheme and the proposed SVM approach works well especially for the case of limited data set.
Notice of RetractionThe empirical analysis on the relationship between foreign direct investment and quality of employment in Shanghai's service industry

In recent years, foreign direct investment focus from manufacturing to service industry. This article has tested the Cointegration and Granger causality between the growth of FDI and the quality of employment in Shanghai's service industry. And the result shows that there is long-term relationship between them and the growth of FDI in Shanghai's service industry can improve the quality of employment, but higher quality of employment doesn't cause the growth of FDI in Shanghai's service industry. Based on the results, the article gives some suggestions on how to attract and utilize FDI efficiently.
Reachability analysis of Web service interfaces

We use WCFA (Web Service Interface Control Flow Automata) to model web service interfaces. Global behaviors of web service compositions are captured by abstract reachability graph(ARG). A polynomial time algorithm for the construction of ARG is presented. The algorithm uses a reachability analysis to verify both safety and call stack inspection properties. Both kinds of properties are expressed by assertions at control points of ARG. Each control point is equipped with a state formula and a call stack. Verification is done by a SAT solver which checks whether the assertions are logical consequences of the state formulas(or the call stacks).
An Integrated Train–Ground Communication System Using Wireless Network Virtualization: Security and Quality of Service Provisioning

In existing urban rail transit systems, train-ground communication systems for different applications are deployed independently. Investing train-ground communication infrastructures repeatedly not only wastes substantial social resources, it also brings difficulties in maintaining all of the infrastructures. In this paper, with recent advances in wireless network virtualization, we design an integrated train-ground communication system for different urban rail transit applications, including communication-based train control systems, passenger information systems, and closed-circuit television systems. A prevention-based security scheme is used in the integrated train-ground communication system. With the objective to optimize the system quality of service (QoS) and improve the system security performance, we formulate the QoS and security problem as a Q-Learning problem. Extensive simulation results show that the system QoS and security performance can be improved substantially in the proposed integrated train-ground communication system.