nils-herrmann/clean_scirepeval huggingface dataset:
An Adaptive Multigrid method for modeling photon transport through biological tissues in bioluminescence tomography

In this paper, we develop an Adaptive Multigrid method (AMGM) to model photon transport through biological tissues in bioluminescence tomography. In our method, the smoothing operation on fine levels and residual correction on coarse levels in V-Cycle offer fast convergence rate for this forward problem. Using a heterogeneous phantom, the methodology is validated by Monte Carlo simulations, and the computation speed is much higher than conventional smoothing iteration methods on a single grid. In actual biomedical imaging applications, especially when there are many sources in small animal body, AMGM is potential to accurately simulate the forward problem at very low computation cost.
On the security of ID-based multi-receiver threshold signcryption scheme

Identity-based Public Key is an important public key systems. It removes certificate management and certificate update of traditional PKC. Threshold cryptography is an important method to solve key leakage. Recently, Qin etal. proposed an ID-based multi-receiver threshold signcryption scheme and Claimed that their scheme was secure. However, in this paper, we analyze the security of Qin etal's. multi-receiver threshold signcryption scheme, and show that the signcryption scheme are insecure though the schemes was proven to be secure under the random oracle model in , the schem doesn't satisfy confidentiality and unforgeability of signcryption. Finally, we give the corresponding attack, and to overcome the above flaws, we also discuss the corresponding improved method.
Study on the Application of Surface Modeling Algorithm

Surface modeling algorithms were designed using models including TC-Bézier, B spline curve with shape parameter, trigonometric B spline curve with shape parameter and hyperbolic polynomial B spline curve. The SMS (Surface Modeling System) was developed, OpenGL as the graph library, in Microsoft Visual C++ 6.0 programming environment. Founded the uniform platform of surface modeling, and realized and verified the proposed algorithms. The experiment result showed that the algorithms were feasible and the SMS was practicable.
Lightweight and Adaptive Service API Performance Monitoring in Highly Dynamic Cloud Environment

Cloud platforms and services usually provide an APIlayer as decoupled, language agnostic interface for both front-endclient integration and back-end data and/or function access. Theavailability and performance of the APIs have significant impact onthe quality of end user or client experiences due to its nature ofinteraction endpoints. However, the extreme dynamics, complexityand scale of the current cloud platforms challenge the applicabilityof the existing performance monitoring and anomaly detection approachesfrom timeliness, accuracy, and scalability perspectives. Thispaper presents a novel approach to API performance monitoring,which recognizes performance problems by response time deviationfrom a baseline response time / throughput model that are createdand continuously updated through online learning. In the postdetectionphase, an MIC (Maximal Information Criteria) basedcorrelation algorithm is used to group alerts into a higher leveland more informative hyper-alerts for end user notification. Weprototyped our solution for a large-scale commercial cloud platform,evaluated it using three months’ API performance metrics data,and compared with a couple of existing representative algorithmsand tools. The results show our approach is able to detect APIperformance anomalies with a high F1-score. Compared to existingGranger based approach, our approach has achieved nearly onetime increase in F1-score. Moreover, the alert reduction ratio of ourapproach outperforms several state-of-the-art approaches.
A similarity index algorithm for link prediction

Link prediction in networks is that using the existing known network structure or node infor­mation to predict the possibility between the two nodes which haven't connected to each other. It's important to learn about the evolution mechanism of network and the interaction relationship of nodes. The link possibility between nodes is closely related to the similarity. The method which is based on the node attributes and local information has the simple and direct calculation and better effect of prediction. So it is more suitable for the large-scale network applications. But it only considers the degree of final nodes or neighbor nodes and the number of neighbor nodes. Does not take into account that each neighbor nodes has the different effect for the different final nodes. The paper through experiments to analysis and compare different similarity contribution of neighbor nodes and end points. And further verified the weak-link effect in networks. Also we proposed a new common neighbor measurement algorithm, through distinguish the influence of each common neighbor for the different end nodes so that the prediction accuracy has been further improved.
Cooperative localization with communication delays for MAUVs

In this paper, we consider the problem of Cooperative Localization(CL) with communication delays for Multiple Autonomous Underwater Vehicles(MAUVs). Localization is a crucial cycle for long range navigation of MAUVs. In the Leader-follower cooperative structure, one master AUV is equipped with high precision navigation system, and several slaver AUVs are equipped with low precision navigation system. To sharing information, inter-vehicle communication is becoming an important requirement for Cooperative Localization. However, due to the terrible underwater environment, acoustic communication is still a difficult challenge for AUVs until now. Taking into account the communication delays, a Delayed Extended Kalman Filter (DEKF) for Cooperative Localization is designed, where the delayed messages were converted to current after some useful transformations. At the end of this paper, simulation results are provided to prove the superiority and practicality of the proposed DEKF algorithm.
Chinese Firms' Internationalization and Performance on the Basis of Learning Capability

Internationalization is an important strategic choice of the firms facing economic globalization challenge. Strategic management theories consider that firm internationalization is a behavior of growing strategy and market diversification. Researches about firms' internationalization and performance are focused on the academics and practice. This paper studies on the relationship among learning capability, internationalization and performance using samples from Chinese listed companies data. After empirical analysis, it is concluded that learning capability has the positive moderating effect on the relationship between firms' internationalization and performance.
Improved extraordinary transmission of light through a single nano-slit by exciting the hybrid state of Tamm and surface plasmon polaritions

A novel method is proposed to effectively enhance the extraordinary optical transmission through a nano-slit. The hybrid state of Tamm plasmon polaritons (TPPs) and the surface plasmon polaritons (SPPs) can be excited. The excitation efficiency of SPPs can be improved significantly. A high transmittance through the single nano-slit is achieved.
Notice of RetractionVibration test and analysis of plane gate in inverted siphon

Vibration has strong effects on working condition of hydraulic gate. Vibration measuring point layout and testing system design of a water-control project are discussed in this paper. By vibration testing and analysis, the relationship between the gate vibration and operation condition is obtained. The research results can provide valuable experience and references to operation in the future. It shows that the vibration of gate is transient, wide-range and excited. Structural resonance is very easy to be induced. The pier is in safety. Based on the adequate data, the mechanism of flow-induced vibration can be studied further.
Design and analysis of a two-DOF coupling motion robotic joint

In this paper, a robotic joint with a two-DOF coupling motion is proposed for higher payload ability, power density and speed. With these advantages the joint is ideal for use in robots, especially multi-DOF manipulators. The entire robot manipulator composed of these joints is not involved in this paper. It will be reported in detail in a future publication. Here we just focus on the robotic joint. This robotic joint which is configured as a series-parallel hybrid structure can be called as angular swivel joint. And the joint can move on a spherical surface whose apex angle is 100° by the coupling motions of two independent motor-reducer drive systems. Details of the mechanism design, kinematics analysis and differential kinematics will be depicted. In addition, all motions of the joint can be divided into two modes: mode 1 is that the two motor-reducer systems work in the same speed and with the opposite direction (SSOD); and mode 2 is that the two motor-reducer drive systems work in the same speed and with the same direction (SSSD). Moreover, a unique control strategy based on these two basic motion modes are presented. Finally, simulations and experiments are implemented to verify the feasibility and performance of the joint.
Supply chain coordination with loss-averse agents under a returns policy

Supply chain coordination with both a loss-averse retailer and loss-averse supplier under a returns policy is studied. The objective of each supply chain agent is to maximize the expected utility. A returns policy is applied for channel coordination and mitigating loss aversion. The necessary and sufficient conditions for the optimal returns price are identified. In particular, it is shown that a returns policy can't always coordinate the supply chain and its coordination depends on how the difference between the loss aversions of the supplier (as a supply chain coordinator) and the retailer is. Numerical studies are conducted and managerial insights are developed.
Broadband transition between air-filled waveguide and substrate integrated waveguide

A Ka-band broadband transition between an air-filled waveguide and a substrate integrated waveguide (SIW) is proposed. The transition is realised by using a radial probe inserted into the height-tapered metal waveguide. Results show that an insertion loss less than 2.5 dB and a return loss better than 14 dB in the frequency band 28.3-39.5 GHz are obtained for a back-to-back structure
A novel X-band half mode substrate integrated waveguide (HMSIW) bandpass filter

This paper presents the design of a novel X-band half mode substrate integrated waveguide (HMSIW) bandpass filter by quarter wavelength resonators. The quarter wavelength resonators are coupled alternately by impedance and admittance inverters. Keeping the advantages of the substrate integrated waveguide (SIW), the proposed HMSIW filter is nearly half reduction in size. Simulated result shows the HMSIW filter has good performance of low insertion loss, compact size and high Q-factor.
A Planar Integrated Left-Handed Microstrip Line Formed by Linearly Placed Spiral Elements

A planar integrated left-handed microstrip line formed by linearly placed spiral elements is presented in this paper. This structure is simple to fabricate and is scalable to higher frequencies, which is ideal for microwave and millimeter-wave hybrid integrated circuit (HMIC) and monolithic integrated circuit (MMIC) applications. Left-handed propagations over this kind of transmission line are validated by both full-wave simulations and experimental measurements.
Natural Interaction in Freehand Pointing: Designing the mapping of interaction space.

Distant pointing using freehand is usually applied in interaction environments where the visual interface is out of a user's arm reach . One example is a user sitting on a couch who is controlling a smart television (TV) across the room. This kind of method is becoming more popular because of the rapid development of large-screen intelligent terminals in recent years. The visual freehand pointing technique is one kind of interaction method using gestures to control the computer.
Short Term Traffic Flow Prediction Based on Online Learning SVR

A number of different forecasting methods have been proposed for traffic flow forecasting including historic method, real-time method, time series analysis, and artificial neural networks (ANN), but accuracy and time efficiency in prediction are a couple of contradictions to be hard to resolve for real-time traffic information prediction. In order to improve time efficiency of prediction, a new short-term traffic flow prediction model and method based on accurate online support vector regression (AOSVR) is proposed in this paper, which can update the prediction function in real time via incremental learning way. A comparison of the performance of AOSVR with ANN, real time, and historic approach is carried out. Experiments results demonstrate that the AOSVR predictor can reduce significantly both relative mean errors and root mean squared errors of predicted travel times. Therefore, AOSVR based traffic flow prediction is applicable and performs well for traffic data analysis.
The hybrid extended Born approximation and CG-FFT method for electromagnetic induction problems

The authors propose the hybridization of the extended Born approximation (EBA) with the conjugate-gradient fast Fourier transform (CG-FFT) method to improve the efficiency of numerical solution of electromagnetic induction problems. This combination improves the solution efficiency in two ways. First, using the FFT in the extended Born approximation decreases the computational cost of the conventional EBA method from O(N/sup 2/) to O(N log/sub 2/ N) arithmetic operations, where N is the number of unknowns in the problem. This approach, referred to as the FFT-EBA method, applies to problems with a fairly large contrast. Secondly, using the EBA as a partial preconditioner for the CG-FFT method increases the convergence speed of the conventional CG-FFT method. This second approach, referred to as the EBA-CGFFT method, is in principle applicable to all problems with a homogeneous background, but is particularly efficient for problems with a higher contrast. Numerical experiments suggest that the combination of these two methods is more accurate and more efficient for electromagnetic induction problems.
Accurate multi-bias equivalent circuit model for graphene resonant channel transistors

This paper presents a compact small signal equivalent circuit model of graphene resonant channel transistors (G-RCTs) suitable for different bias conditions. The model combines a bias dependent model for a GFET with a continuum mechanics model for 2-D graphene membrane. The model has been validated by graphene resonators fabricated by mechanical exfoliation techniques and transfer techniques. The characterization of G-RCT at very wide gate bias range with Vgs from -20 to 20V is predicted for the first time by using equivalent circuit model, which proves the validation of the proposed model. With the proposed compact model, the RCTs can be useful for developing high sensitivity sensor, or in the perspective of high quality RF filters by using graphene nano-electromechanical systems (NEMS).
Fast Modeling of Analytics Workloads for Big Data Services

Building models to predict analytics workloads' execution is a foundational capability that enables key scenarios for big data services, like SLA-driven service provisioning and elastic auto scaling. Given the various infrastructure and workload characteristics, it's more preferable to build the models in a "black-box" fashion, for example, by leveraging machine learning techniques. However, this approach has assumptions on the volume and quality of workloads' existing records to learn from, which require sophisticate benchmark or long time monitoring. In this paper, we present a method to accelerate the modeling process of an analytics workload for its quick time-to-value in the context of big data services. Specifically, clustering and transfer learning techniques are leveraged for this acceleration by shifting the data collection from the online service phase to the offline preparation phase. This paper focuses on the conceived service model and fast modeling techniques. Their feasibility is demonstrated by experiments.
The use of environmental variables to predict cholera hazard

Vibrio cholerae(V. cholerae) is a component of coastal and estuarine microbial ecosystems, with the copepod species of zooplankton that comprise the aquatic fauna of rivers, bays, estuaries and the open ocean serving as host for the bacterium. There is a remarkably strong association between cholera and some regional environmental factors such as the sea and climate. In this paper, the sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) of the nearest coastal environment derived from satellite remote sensing data are employed to predict the cholera hazard in coastal regions of eastern China, and the association between monthly cholera cases and in the study and the lag effects of the three oceanic environmental factors to the local cholera magnitude are analyzed.
The Growth Behaviors of IMC Layers in Solid-liquid Interfacial Reactions of Sn1.5Cu/Cu in High Magnetic Field

The growth behaviors of intermetallic compound (IMC) layers in solid-liquid interfacial reactions of Sn1.5Cu/Cu in various intensities of high magnetic field have been investigated. The results show that the growth of IMC layers has been accelerated by high magnetic field through the comparison of growth kinetics of IMC layers among OT to 2.5 T magnetic field. IMC grains in high magnetic field are much bigger than that in OT. By the analyzing of XRD patterns of IMC layers, it can be found that the orientations of IMC have been changed by magnetic field.
LFT uncertain model validation with time- and frequency-domain measurements

In this paper the authors study a model validation problem pertaining to linear fractional uncertainty models. They extend the previous validation approaches, based upon either time or frequency measurements, to one using simultaneously time- and frequency-domain data. They show that this problem can be reduced to two independent convex feasibility tests, each of which corresponds to the time- or frequency-domain data alone, and each can be verified numerically using available algorithms and software programs. The merit of such a mixed time- and frequency-domain approach, therefore, lies in that not only can it accommodate the two distinctively different types of measurement data simultaneously, but also from a computational standpoint it will not suffer from a complexity growth beyond that associated with the existing time-domain tests.
Fluid-Structure Interaction study on a flexible robotic pectoral fin

Interested by the phenomenon that flexible structures of living creatures have better performance than the artificial rigid propeller, a study on Fluid-Structure Interaction (FSI), which solves the coupling between solid structure and fluid, is conducted to investigate the stiffness effect of the pectoral fin. Firstly, a three dimension computational fin model based on the pectoral fin of Koi Carp is adopted and three cases are investigated which are rigid case, flexible case and flexible variable stiffness case, respectively. With this approach, their hydrodynamic force and fluid field are compared, and it is discovered that flexible cases have better hydrodynamic force and special fluid field, and there is a delay-response in the flexible structure. The flexible variable stiffness case exhibits the best performance in our experiment. Moreover, corresponding robotic pectoral fin experiments are carried out and the results Coincide with those of the simulation. The results will be a useful inspiration for the design of flexible underwater propeller and understanding of fish swimming mechanism.
Micromachined WR-1.0 waveguide band-pass filter

A WR-1.0 waveguide band-pass filter is designed and fabricated using the deep reactive ion etching (DRIE) micromachining technique. The metal conductivity is investigated for more accurate designs. Because the influence of the fabrication tolerance on the component performance cannot be negligible while the frequency increases, it is a necessary to adopt the simple structure with less resonant cavities for obtaining the given performance. Therefore, the filter in this letter is designed based on the TE103/TE202 dual-mode rectangular waveguide resonant cavities. The measured center frequency is at about 862 GHz with the bandwidth of 44GHz and the best insertion loss is about 2.9 dB. The effect of the DRIE micromachining process on the performance of the filter is also analyzed.
An Image Fusion Approach Based on Markov Random Fields

Markov random field (MRF) models are powerful tools to model image characteristics accurately and have been successfully applied to a large number of image processing applications. This paper investigates the problem of fusion of remote sensing images, e.g., multispectral image fusion, based on MRF models and incorporates the contextual constraints via MRF models into the fusion model. Fusion algorithms under the maximum a posteriori criterion are developed to search for solutions. Our algorithm is applicable to both multiscale decomposition (MD)-based image fusion and non-MD-based image fusion. Experimental results are provided to demonstrate the improvement of fusion performance by our algorithms.
Mean shift based nonparametric motion characterization

Motion content is a very powerful cue for organizing video data. Efficient and robust identification of the camera motion nature and the dominant object motion is important for the generation of useful motion annotations. Most of existing methods focus on the estimation of a parametric motion model from dense optical flow fields or block-based MPEG motion vector fields (MVF). However, it is hard to achieve a reliable model estimation in large amounts of video data. This is due to the violation of parametric assumption in the presence of large object motion and bad estimation of the optical flow in low-textured regions. In this paper, we employ the mean shift procedure and the histogram to propose a novel nonparametric motion representation. With this motion representation, we transform the motion analysis to the classification problem of camera motion patterns in the presence of dominant object motion and non-dominant object motion. The unique features include three main aspects: 1) instead of computationally expensive and vulnerable parametric regression, we base the motion characterization on the classification of motion patterns, 2) we employ machine learning to capture the knowledge of recognizing camera motion patterns from bad motion fields, and 3) with the mean shift filtering the proposed motion representation elegantly considers the spatial-range cues so as to remove noise and implement discontinuity preserving smoothing of motion fields. Promising results are achieved on 1096 motion vector fields extracted from compressed broadcast soccer video.