nils-herrmann/clean_scirepeval huggingface dataset:
Mapping Elements with the Hungarian Algorithm: An Efficient Method for Querying Business Process Models

Efficient query processing over a large amount of business process models is important for managing the business process model repository. The structural similarity between two process models is considered as the main measurement for ranking the process models for a given search model. Current business process query methods are inefficient since too many expensive computations of the graph edit distance are involved for constructing the elements mapping as well as deriving the structural similarity. To address this, using Petri-net as the modelling method, this paper presents the Hungarian algorithm based query method, where we firstly define the context similarity for a pair of place nodes that are from different process models by taking into account both the common paths and common transitions, then transform the elements (e.g., The transitions and the places) mapping to classical assignment problem that can be solved by Hungarian algorithm efficiently. In this way, we can save a lot of time for searching the best combination of elements mapping. Finally, we use the common method of the graph edit distance to measure the structural similarity based on the found best combination of elements mapping.
A novel flat micro heat pipe with fiber wick

A novel flat micro heat pipe with glass fiber wick structure is introduced in this paper. The structure of the wick is presented and also the excellence of the structure is described. For the novel flat micro heat pipe, a mathematical model is founded and the maximum heat transports is calculated which is 2.3 w. Experimental testing is performed for the fabricated micro heat pipe in vacuum. The testing maximum heat transport is about 2 w, and the testing results are also compared with grooved micro heat pipe.
A study on printed form processing and reconstruction

Considering we deal with a lot of forms in our daily life, form-processing system has a great value in office automation. This paper focuses on processing and reconstructing the printed forms. The main problems in form processing are the broken lines and the errors in field extraction. These problems affect the result of the form processing. Some methods are introduced in this paper to improve the result of field extraction. First we use regulated morphology to solve the broken lines. Second a novel method by heuristic algorithm is used to improve the field extraction accuracy. The results indicate that these methods improve the result of form processing. The reconstruction of form image is also discussed in this paper.
Palmprint recognition based on isodata clustering algorithm

This paper analyzes the palmprint textures with a multi-resolution method. Texture feature vectors of palmprint are extracted by wavelet transformation. With the texture feature, isodata clustering method is used to achieve classification of the Feature vectors. Based on the classification, euclidean distance within-class and between-class are calculated to match the feature. Experimental result illustrates that the proposed approach for palmprint recognition is effective.
Trust Calculation Model Based on Social Network and Evidence Theory

To solve the trust issue caused by malicious users in e-commerce, we propose a trust calculation model based on social network. Through analysing the trust features, social network is introduced into this trust model to get information from the most trusted source according to the subjectivity and the compositionality feature of trust to improve the buyers' situation of asymmetric information in electronic trading. In view of the advantage that conflicted evidences can be well combined by evidence theory, we resolve the conflict of information from each recommended third-party. We also introduce other various trust influence factors, such as transaction rating dictionary, transaction background important factor, transaction amount factor and trading time factor, etc. Finally, through simulation experiments, we set different confidence factors depending on different trading environment, and verify that the method to combine social network and evidence theory for obtaining a reasonable recommendation trust value is feasible. It proves that our proposed trust calculation model based on social network has a better anti-attack ability.
Disparity estimation of misaligned images in a scanline optimization framework

Modern, state-of-the-art disparity estimation techniques are able to very accurately estimate the disparity for a wide variety of scene types. However all of these methods assume that the input images are epipolar rectified. When an image pair is not rectified, it must be pre-processed before any estimation can be done. In this paper we propose a disparity estimation scheme that is able to handle non-rectified images without requiring a rectification step. We show how a minor modification to an existing estimation framework can allow for any disparity estimation framework to produce disparity maps for non-rectified images.
A trellis-based approach for robust view synthesis

View synthesis is an essential function for a number of 3D video applications including free-viewpoint navigation and view generation for auto-stereoscopic displays. Depth Image Based Rendering (DIBR) techniques are typically applied for this purpose. However, the quality of the rendered views is very sensitive to the quality of the depth image. In this paper, a novel trellis-based view synthesis framework is proposed to overcome the above limitations in depth images and reduce artifacts in the rendered picture. Our results demonstrate that the proposed approach offers visible improvements in rendering quality compared to existing view synthesis techniques.
A Multi-Agent and PSO Based Simulation for Human Behavior in Emergency Evacuation

A new emergency evacuation model based on Multi- Agent framework and Particle Swarm Optimization was presented. This model simulated human's individual behaviors and social behaviors in multi-exit evacuation environment. The Linear Weight Decreasing Particle Swarm Optimization (LWDPSO) was introduced to simulate individual's movement. A hierarchy of behavior rules was described, and a series of individual behaviors and social behaviors during evacuation were defined. A prototype system of emergency evacuation simulation was implemented based on Geographic Information System (GIS) application framework. The result shows that the simulation system well performs some typical evacuation behaviors, the model based on multi- agent and LWDPSO has good efficiency and practicability.
Study on an Improved Numerical Method of Seepage Analysis for Unsaturated Soil Slope

Based on the governing equation of seepage, we investigates the influence of consolidation stress on unsaturated seepage in soil slope, considering the relationships among stress and strain, saturated permeability coefficient and soil porosity, and combining the consolidation stress and Soil-water characteristic curve, put forward a numerical method which couples the unsaturated seepage and stress field in soil. For this method, we writes relative finite element model programs, and compare with the calculating case (ACADS, 2008) to reveal the difference in stress field and seepage field in soil between the situation of coupling and uncoupling. The result shows that the consolidation stress will effect the distribution of seepage field, and method proposed in this paper conforms to reality better.
Knowledge-based intelligent assembly planning system and its related key technologies

Assembly planning is a large scale and highly constrained combinatorial problem, including assembly sequence planning and assembly task planning. In order to reduce the computation complexity, this paper presents a knowledge-based approach to assembly planning. After analyzing the characteristics of connectors, typical knowledge base and standard knowledge base are built for assembly sequence planning. This research shows that the cases stored in typical or standard knowledge base can be applied to a given assembly planning problem. If similar or same structures in base do not give rise to useful plans for the provided structure, the system next generates feasible plans by geometric reasoning with the help of directed-connector knowledge. A novel approach for cooperative assembly task planning is proposed to improve the flexibility and reliability of the automated assembly system. By integrating geometric reasoning with knowledge-based reasoning, the computation complexity is reduced drastically and the assembly plans obtained are more feasible and practical.
On modeling the rendering error in 3D video

We propose an analytical model to estimate the rendering quality in 3D video. The model relates errors in the depth images to the rendering quality, taking into account texture image characteristics, texture image quality, the camera configuration and the rendering process. Specifically, we derive position (disparity) errors from the depth errors, and the probability distribution of the position errors is used to calculate the power spectral density of the rendering errors. Experiment results with video sequences and coding/rendering tools used in MPEG 3DV activities show that the model can accurately estimate the synthesis noise up to a constant offset. Thus, the model can be used to estimate the change in rendering quality for different system designs.
Research on Rapid Reconfiguration Platform of Dynamic Forest Growth Simulation System Based on Service Component

Due to the problem that the forest growth simulation system has relatively fixed system architecture and difficulty in reconstruction, this paper presents a rapid reconfiguration platform of dynamic forest growth simulation system based on service component. The key technologies of the rapid reconfiguration platform such as the flowchart of reconfiguration, the design of service component and knowledge representation methods are described. This platform adopts the basic idea of service-oriented and component-oriented technology, and it is composed of supporting environment layer, simulation resource layer, simulation runtime supporting service layer, simulation integration layer and application layer. In this rapid reconfiguration platform, different simulation systems can be reconfigured rapidly according to the simulation tasks and some simulation systems have been reconfigured successfully.
Graph transformation for keypoint trajectory coding

In contrast to still image analysis, motion information offers a powerful means to analyze video. In particular, motion trajectories determined from keypoints have become very popular in recent years for a variety of video analysis tasks, including search, retrieval and classification. Additionally, cloud-based analysis of media content has been gaining momentum, so efficient communication of salient video information to perform the necessary analysis of video at the cloud server is needed. In this paper, we propose a novel graph transformation to efficiently represent the keypoint trajectories, motivated by the fact that keypoints are distributed irregularly across the images. Compared to conventional DCT-like transformation, it is easier for graph transform to compact the energy and make the coding efficiently. Experimental results on several popular datasets including Stanford MAR, Hopkin155, KITTI, etc. demonstrate a significant rate saving between 26% and 42% with our proposed trajectory coding approaches relative to a DCT based transformation approach, provided that the coding errors are between 2 pixels to 4 pixels.
Fast Resampling of Three-Dimensional Point Clouds via Graphs

To reduce the cost of storing, processing, and visualizing a large-scale point cloud, we propose a randomized resampling strategy that selects a representative subset of points while preserving application-dependent features. The strategy is based on graphs, which can represent underlying surfaces and lend themselves well to efficient computation. We use a general feature-extraction operator to represent application-dependent features and propose a general reconstruction error to evaluate the quality of resampling; by minimizing the error, we obtain a general form of optimal resampling distribution. The proposed resampling distribution is guaranteed to be shift-, rotation- and scale-invariant in the three-dimensional space. We then specify the feature-extraction operator to be a graph filter and study specific resampling strategies based on all-pass, low-pass, high-pass graph filtering and graph filter banks. We validate the proposed methods on three applications: Large-scale visualization, accurate registration, and robust shape modeling demonstrating the effectiveness and efficiency of the proposed resampling methods.
Analysis on energy cost for wireless sensor networks

As one of data-gathering applications in information technologies, wireless sensor network (WSN) has attracted more and more people's attention. A key challenge is achieving energy consumption distribution of nodes for WSN with any scale in any general regions to the effect that node deployment density can be made to prolong system's lifetime. In this paper, we explore the optimal location of sink to prolong the network lifetime, give the definition of information barycenter and set up a model for WSN with nodes deployed ideally in monitored region. EC curve is proposed to reveal that energy consumption of nodes on different locations takes on curve shift along with its distance to sink. Simulations are carried out to pick up energy consumption of nodes on different positions on the preconditions that all the nodes are deployed in the interested region with uniform distribution or stochastic distribution to validate the availability of the EC curve.
Attribute compression for sparse point clouds using graph transforms

With the recent improvements in 3-D capture technologies for applications such as virtual reality, preserving cultural artifacts, and mobile mapping systems, new methods for compressing 3-D point cloud representations are needed to reduce the amount of bandwidth or storage consumed. For point clouds having attributes such as color associated with each point, several existing methods perform attribute compression by partitioning the point cloud into blocks and reducing redundancies among adjacent points. If, however, many blocks are sparsely populated, few or no points may be adjacent, thus limiting the compression efficiency of the system. In this paper, we present two new methods using block-based prediction and graph transforms to compress point clouds that contain sparsely-populated blocks. One method compacts the data to guarantee one DC coefficient for each graph-transformed block, and the other method uses a K-nearest-neighbor extension to generate more efficient graphs.
Ontology-based knowledge management for forest channel

Forest channel is an important part of land greening. In order to scientifically configure the species of the forest channel, this paper proposed an ontology-based method for forest channel knowledge management. The forest channel knowledge can be described as three parts: green regions, species characteristics, species configure modes. Combined with self-defined rules and knowledge, greening scheme can be reasoned based on customer's requirement. Several typical technologies are used in this system, such as OWL to represent the forest channel ontology and Jena to reason on the rules. This method can help make strategic decisions in forest channel knowledge management.
A retrieval method of ancient Chinese character images based on neighbor clustering

Character image clustering is an assistant way of studying ancient Chinese characters. This paper analyzed the feature of ancient Chinese characters. Aiming at the key problems such as feature extraction and clustering, we designed a simple and effective neighbor clustering method for ancient Chinese character images which extracts adoptive feature of the coarse periphery features, the second coarse periphery features and the edge directional line element feature of ancient characters images. The experimental results show that the character clustering algorithm is effective.
Knowledge-based assembly sequence planning system

This work presents a knowledge-based approach to assembly sequence planning problem. This research shows that the typical or standard CSBAT (connection semantics based assembly tree) can be applied to a given assembly problem. The structure of the KBASP (knowledge-based assembly sequence planning system) is proposed, there are three ways to construct plans for a CSBAT: (1) by retrieving the typical base; (2) by retrieving standard base; and (3) by geometry reasoning. Compared with other system based on the reuse philosophy the approach can generate assembly sequences for each CSBAT directly without the problem of merging plans for different child CSBATs. By integrating geometry-based reasoning with knowledge-based reasoning, the computation complexity is reduced drastically and the assembly sequences obtained are more feasible and practical.
An accurate eye pupil localization approach based on adaptive gradient boosting decision tree

Eye pupil localization is an important part in computer vision applications such as face recognition, gaze estimation and so on. In this paper, we propose an improved method for precise and fast eye pupil localization. Based on gradient boosting decision tree(GBDT) algorithm, a more accurate localization is achieved by increasing the weight of the training samples with larger errors in a moderate rate. Furthermore, a pruning strategy is utilized to avoid overfitting and reduce the localization time without accuracy loss. Experimental results show that the improved method achieves an accuracy of 92.39% at a speed as fast as 1.7ms to locate in the range of eye pupil on BioID database. The proposed method outperforms most state-of-the-art methods in terms of localization accuracy and consumed time.
Robust low rank dynamic mode decomposition for compressed domain crowd and traffic flow analysis

In this paper, we develop a dynamic mode decomposition algorithm that is robust to both inlier and outlier noise in the data. One application of our algorithm is the identification of multiple crowd or traffic flows from compressed video streams. Our method uses motion vectors that are readily available in the compressed bitstream, and do not require computationally expensive optical flow. These motion vectors are known to be very noisy, however, our algorithm is able to extract the underlying dynamical systems that define the flows. We formulate a rank regularized dynamic mode decomposition problem with total least squares constraints to estimate the Koopman modes of the motion dynamics. The estimated Koopman modes are then used to analyze the stability of the system and extract steady state and transient flows. We demonstrate the improved performance of our approach compared to state of the art schemes and illustrate it applicability in identifying transient and steady-state flows in real video sequences.
A Novel Approach to Network Security Situation Awareness Based on Multi-Perspective Analysis

Describing the security situation and its trend is the research hotspot of network security. As a new research field, Network security situation awareness (NSSA) includes three phases: situation perception, situation evaluation and situation prediction. This paper proposes a novel approach to NSSA model. The situation evaluation model adopts a multi-perspective analysis. It uses the description of security attacks, vulnerabilities and security services to evaluate current network security situation. The situation prediction model adopts time series analysis. It uses past and current situation map to forecast future network security situation. Simulation results show that the model is suitable and efficient.
Depth map processing with iterative joint multilateral filtering

Depth maps estimated using stereo matching between frames from different video views typically exhibit false contours and noisy artifacts around object boundaries. In this paper, iterative joint multilateral filtering is proposed to deal with these artifacts. The proposed filter consists of multiple filter kernels. Knowing that the estimated depth maps are erroneous, besides the kernels which measure the proximity of depth samples and the similarity between depth sample values, we further develop kernels which measure similarity between the corresponding video pixel values. To increase reliability, these novel kernels operate on the color (RGB) domain instead of only on the luminance domain. Furthermore, the filter shapes are designed to adapt brightness variations. Finally, to tackle large misalignment between boundaries in depth maps and in the corresponding video frames, iterative approach is utilized. Our results demonstrate that the proposed method can significantly improve the boundaries in depth maps and can reduce false contours. With the processed depth maps, it is observed that the quality of object boundaries in synthesized views can be improved.
Direct torque control for dual-three phase induction machine with one stator phase opened

A direct torque control (DTC) strategy for dual-three phase induction machine with one stator winding open-circuited is discussed in this paper. An optimums election scheme of space voltage vector is proposed based on fuzzy control and direct torque control. The largest space voltage vectors are selected to control the machine. To verify the presented method, fuzzy direct torque control of dual-three phase induction machine is simulated. The simulation results show that the machine in fault state is still effectively controlled, and good dynamic performances are obtained with the proposed method.
Research on the Mechanics Characteristics of Ship Vibration Reduction and Impact Resistance Isolator Based on MR

In this paper, a new-style isolator system in ship is presented, which is composed of wire rope and MR damper in parallel. By taking advantages of the high damping and damping variability of MR damper, it is possible to make the mechanics characteristics of isolator controllable and then solve the problem of vibration reduction in low frequency and impact resistance in high frequency of ship equipment. In the researches on the impact resistance and vibration reduction performances, numerical experiment and physical experiment are carried out respectively, results indicate that the new isolator has a good active controllable effect on the vibration and impact, especially for controlling resonance and low- frequency vibration of system.
Denoise Investigation on Prestack Reverse time Migration Based on GPU/CPU Collaborative Parallel Accelerating Computation

Based on two-way wave equation, prestack reverse time migration (RTM) overcomes dip limitation, and can image complicated geological body with high precision. However, since the massy storage, large amount of computation, low frequency noise, the industrialization process of this approach develops slowly. High order finite difference algorithm is used to calculate reverse time migration in the paper. By GPU/CPU collaborative parallel accelerating computation, the computation efficiency of RTM has been greatly improved. The random boundary condition is adopted to obtain wavefield information. The paper discusses the theory and specific steps of Laplacian denoise approach. The tests on Marmousi and Sigsbee model illustrate that, by Laplacian operator denoise approach, prestack reverse time migration can image complicated geological body effectively and precisely. This approach has a wide application prospect.