nils-herrmann/clean_scirepeval huggingface dataset:
An Approach of Digital Rights Management for E-Museum with Enforce Context Constraints in RBAC Environments

In this paper, a personal digital rights management system based upon the role based access control with the dynamic context constrains is proposed. The constrained table is constructed with the context constrains. The context constrains includes time, location information, the user devices, O.S., service group, connection rate. This dynamic RBAC constraint will check by one or more context constraints to assign the right permissions. With our approach we aim to preserve the advantages of RBAC and offer an additional means for the definition and enforcement of fine-grained context-dependent access control policies. The user downloads the digital content into the personal devices such as PDA or mobile phone. The user fingerprint has embedded into the digital contents to achieve the information security objectives of non-repudiation, integrity and security. Some of legal users may leak their rights to unauthorized member to use the digital content. This system authority can use the traitor tracing to revoke the usage license of the traitor and to catch traitors that leaks secrets. Hence, the misuse users will be degraded the permissions in the future. With this new approach, the management of access rights becomes much flexible and efficient on the e-museum applications.
Multimodal partial estimates fusion

Fusing partial estimates is a critical and common problem in many computer vision tasks such as part-based detection and tracking. It generally becomes complicated and intractable when there are a large number of multimodal partial estimates, and thus it is desirable to find an effective and scalable fusion method to integrate these partial estimates. This paper presents a novel and effective approach to fusing multimodal partial estimates in a principled way. In this new approach, fusion is related to a computational geometry problem of finding the minimum-volume orthotope, and an effective and scalable branch and bound search algorithm is designed to obtain the global optimal solution. Experiments on tracking articulated objects and occluded objects show the effectiveness of the proposed approach.
A new anisotropic diffusion model for image denoising

In this paper, we propose a new algorithm for image denoising. Our method is an anisotropic diffusion model, and it is based on variation and partial differential equations. The new model not only overcomes the shortcoming of TV model, which does not fully comply with the morphologic principles of image processing, but also overcomes the shortcoming of ALM model, which depends on gradient information alone to determine the speed and direction of diffusion. Numerical results show that our model can maintain the main features of the image. The denoising effect of our model is better than some traditional models. The main feature of our new model is making the processed image retain edge feature and corner information of the image.
A Dynamic Video Streaming Scheme Based on SP/SI Frames of H.264/AVC

Video streaming is very important in both wired and wireless communications. Switching among streams of different bit-rates and/or views is always necessary in related applications. The techniques of SP/SI frames in H.264/AVC have been developed to facilitate bit-stream switching without causing drift errors. However, the frames that are allowed for switching have to be determined in advance so real-time switching may not be achieved effectively. In this research, a dynamic video switching mechanism is proposed. An inter-predicted frame will be separated into a residual frame and a motion-compensated frame. The latter will be encoded based on the methodology of SP/SI-frames. In addition to the advantage of dynamic switching, the quality of video frames is maintained more consistently and the volume of data that have to be sent during switching is reduced. The experimental results show the feasibility of the proposed scheme.
Low emittance lattices for the Duke FEL Storage Ring

In this paper we present two options for a new lattice of the 1 GeV Duke FEL Storage Ring reducing horizontal beam emittance from existing 18 nm*rad to 1.4 nm*rad and 0.9 nm*rad respectively. One of proposed lattices reuses existing magnetic elements, another is based on completely new design. The use of combined function magnets with dipole, quadrupole and sextupole components allows us to keep the ring compact and fit it into existing footprint. 2D and 3D field simulations for such a magnet showed good quality of magnetic field. Preliminary results for dynamic aperture simulations are also presented. We also discuss the choice of lattice cell and tune advances and the concept of local compensation of nonlinear aberrations.
Improving the efficiency of white OLEDs based on a gradient refractive index substrate

For use in lighting applications, white organic light-emitting devices (WOLEDs) must operate at higher biases to ensure an ample flux. However, stressed operation voltages often result in poor performance and limited device lifetime. This could be addressed by modifying the inherent optical properties of OLEDs. This study proposes a gradient refractive index (GRIN) substrate to adjust the ratio of the light-waveguided modes as well as the radiation mode. An embedded nanocomposite film consisting of titanium dioxide (TiO2) nanoparticles (NPs) was inserted between ITO and glass to create an internal light-extraction structure (IES). The high refractive index of TiO2 is essential for increasing the refractive index of the photoresist film and thus diminishing the total internal reflection between the interfaces. In addition, the silicon dioxide NPs mixed polydimethylsiloxane was used to form an external light-extraction structure (EES). The refractive indices of the IES and EES were adjusted to form a GRIN substrate. Compared with a control device, this sophisticated substrate produced a 1.6 fold efficiency improvement.
Generative Hierarchical Learning of Sparse FRAME Models

This paper proposes a method for generative learning of hierarchical random field models. The resulting model, which we call the hierarchical sparse FRAME (Filters, Random field, And Maximum Entropy) model, is a generalization of the original sparse FRAME model by decomposing it into multiple parts that are allowed to shift their locations, scales and rotations, so that the resulting model becomes a hierarchical deformable template. The model can be trained by an EM-type algorithm that alternates the following two steps: (1) Inference: Given the current model, we match it to each training image by inferring the unknown locations, scales, and rotations of the object and its parts by recursive sum-max maps, and (2) Re-learning: Given the inferred geometric configurations of the objects and their parts, we re-learn the model parameters by maximum likelihood estimation via stochastic gradient algorithm. Experiments show that the proposed method is capable of learning meaningful and interpretable templates that can be used for object detection, classification and clustering.
Monolithic III-V/Si integration

We summarize our work on creating substrate platforms, processes, and devices for the monolithic integration of silicon CMOS circuits with III-V optical and electronic devices. Visible LEDs and InP HBTs have been integrated on silicon materials platforms that lend themselves to process integration within silicon fabrication facilities. We also summarize research on tensile Ge, which could be a high mobility material for III-V MOS, and research on an in-situ MOCVD Al2O3/GaAs process for III-V MOS.
Design and product implementation for an automotive BSD system

This paper proposes a vehicle blind spot detection (BSD) system to reduce the traffic accident when car was changing lanes on the road. The cameras are installed at the bottom of the left and right side view mirrors. The system reaches 99% vehicle detection rate and is applicable during daytime and nighttime without high-cost radar. Furthermore, the system integrates with functions of auto cycle video recording, side view and so on. The system is set with Sunplus®SPHE6700 and achieves real-time detection at 30 frame per second (FPS) with CORTEX®A9 dual-core @1GHz and accomplishes production and sales with TOYOTA® Altis.
Research on the accuracy of Gaussian approximated expressions for energy detection in cognitive radio networks

This paper addresses the problem of the adaptable conditions for Gaussian approximated expressions of energy detection over AWGN and Rayleigh channels. Gaussian approximated expressions of false alarm and detection probabilities have been widely adopted for evaluating the sensing performance of energy detection when the number of samples is large. With deeper study, we find the fact is not such. Extensive analysis and numerical simulations confirm that the approximated expressions can lead to significant errors in the performance of cooperative spectrum sensing over AWGN and Rayleigh channels, especially for a large cooperative network. Also, the approximated expressions are not applicable to the local detection over AWGN and Rayleigh channels, when a lower false alarm probability is required. Moreover, Gaussian approximated expressions overestimate the detection performance in all cases.
Mining compositional features for boosting

The selection of weak classifiers is critical to the success of boosting techniques. Poor weak classifiers do not perform better than random guess, thus cannot help decrease the training error during the boosting process. Therefore, when constructing the weak classifier pool, we prefer the quality rather than the quantity of the weak classifiers. In this paper, we present a data mining-driven approach to discovering compositional features from a given and possibly small feature pool. Compared with individual features (e.g. weak decision stumps) which are of limited discriminative ability, the mined compositional features have guaranteed power in terms of the descriptive and discriminative abilities, as well as bounded training error. To cope with the combinatorial cost of discovering compositional features, we apply data mining methods (frequent itemset mining) to efficiently find qualified compositional features of any possible order. These weak classifiers are further combined through a multi-class AdaBoost method for final multi-class classification. Experiments on a challenging 10-class event recognition problem show that boosting compositional features can lead to faster decrease of training error and significantly higher accuracy compared to conventional boosting decision stumps.
A physics based control system for the Duke storage ring

At the Duke FEL Lab, we have developed a new storage ring control system in terms of the physics quantities of the accelerator. Instead of controlling power supply currents in Amperes, this system controls the effective focusing of magnets. By directly controlling the physics quantities, this control system allows tighter integration of the physics model based high level controls with the EPICS based low-level controls. EPICS events have been extensively used to provide time synchronization during the energy and lattice ramping. This new control system also facilitates the implementation of multiple functions on shared control channels. As a result, the physics based control system simplifies many complex control tasks, improves the beam stability during ramping, and facilitates machine studies. With better understanding of the accelerator, it is possible to fine tune this control system to present users with a virtual accelerator whose operation is independent of the ring energy.
MBE growth of large diameter InP-based lattice-matched and metamorphic HBTs

InAlAs/InGaAs/InP heterojunction bipolar transistor (HBT) structures were grown lattice-matched on InP substrates and metamorphically on GaAs substrates by molecular beam epitaxy. Generic structures with a thin base of 500 /spl Aring/ and doped at 4/spl times/10/sup 19/ cm/sup -3/ were chosen to support the frequency response required for advanced wireless and fiber-optic telecommunication products. Beryllium- and carbon-doped large-area devices were found to exhibit similar DC characteristics. No significant difference in current gain or linearity was observed for metamorphic devices compared to their lattice-matched counterparts.
Distributed data association and filtering for multiple target tracking

This paper presents a novel distributed framework for multi-target tracking with an efficient data association computation. A decentralized representation of trackerspsila motion and association variables is adopted. Considering the interleaved nature of data association and tracker filtering, the multi-target tracking is formulated as a missing data problem, and the solution is found by the proposed variational EM algorithm. We analytically show that 1) the posteriori distributions of trackerspsila motions (the real interests in terms of tracking applications) can be effectively computed in the E-step of the EM iterations, and 2) the solution of trackerspsila association variables can be pursued under a derived graph-based discrete optimization formulation, thus efficiently estimated in the M-step by the recently emerging graph optimization algorithms. The proposed approach is very general such that sophisticated data association priori and likelihood function can be easily incorporated. This general framework is tested with both simulation data and real world surveillance video. The reported qualitative and quantitative studies verify the effectiveness and low computational cost of the algorithm.
ID modeling at the ALS

At the Advanced Light Source there are several projects being proposed that will require high field insertion devices. It is important that these devices do not significantly impact the performance of the machine. In particular they should not degrade the beam lifetime or injection efficiency. It is known that high field devices with large field roll off can impact the beam lifetime. It is therefore important to model the effect of the insertion devices including both transverse and longitudinal field roll off. In this paper we present the result of tracking studies using an explicit symplectic integrator with both transverse and longitudinal field roll off. The simulations show where sufficiently large field roll off will impact the beam lifetime.
Direction and polarization estimation using quaternion and polarization rotation matrix

Estimation of directions-of-arrival (DOAs) and polarization parameters of incident signals needs a high-dimensional searching process with long-vector methods, which results in tremendous computational load. To overcome this disadvantage, this paper proposes a novel algorithm using quaternion and polarization rotation matrix on the basis of a uniform circular array (UCA) which is composed of cocenterd orthogonal loop and dipole (COLD) pairs. First, a quaternion mode is set and polarization parameters are separated from the array manifold. Then, DOA parameters are acquired using a two-dimensional searching process. Meanwhile, based on long-vector mode, a polarization rotation matrix is constructed, and closed-form estimation of polarization parameters is obtained. The presented algorithm has a large reduction in computational effort and an obvious improvement in precision for DOA estimation under low signal-to-noise (SNR) ratio. The effectiveness is confirmed through computer simulation.
A Fragile Watermarking Scheme for Tamper-Proof of Web Pages

With the development of the Internet, getting informationthrough browsing web pages has become a popularway. How to protect the integrity of a web page is anurgent problem. As an effective method, a novel fragilewatermarking scheme for tamper-proof of web pages isproposed in this paper for solving the problem. In ourscheme, the watermarks that are related to the content ofthe original web page are generated based on the SHA-1algorithm, and then they are embedded into the embeddinglocations controlled by two secret keys. In the detectionprocedure, whether a web page has been tampered or notcan be judged effectively only by comparing the generatedwatermarks with the extracted watermarks. The experimentshows that the proposed scheme has stronger abilities tolocate the locations of modifications and to identify the typesof modifications.
Direct position determination based on unitary space-time subspace data fusion

Direct position determination (DPD) is a single-step method which directly localizes transmitters from sensor outputs without computing intermediate parameters. Compared with conventional two-step localization methods, DPD achieves higher accuracy especially under low signal to noise ratio (SNR) conditions. This paper proposes an improved subspace data fusion (SDF)-based DPD algorithm with a moving array. Different from the existing SDF-based DPD which uses only the arrival angle information, the proposed algorithm exploits the location information embedded in both arrival angles and Doppler shifts. It relies on a unitary space-time SDF, where multiple stationary transmitters are directly localized by fusing all the unitary (real-valued) space-time subspaces at all positions of the moving array. Therefore, our algorithm realizes the localization by real-valued computations. The simulation results show the superior localization performance of the proposed DPD compared to the existing SDF-based DPD and two-step localization algorithms.
Learning Actionlet Ensemble for 3D Human Action Recognition

Human action recognition is an important yet challenging task. Human actions usually involve human-object interactions, highly articulated motions, high intra-class variations, and complicated temporal structures. The recently developed commodity depth sensors open up new possibilities of dealing with this problem by providing 3D depth data of the scene. This information not only facilitates a rather powerful human motion capturing technique, but also makes it possible to efficiently model human-object interactions and intra-class variations. In this paper, we propose to characterize the human actions with a novel actionlet ensemble model, which represents the interaction of a subset of human joints. The proposed model is robust to noise, invariant to translational and temporal misalignment, and capable of characterizing both the human motion and the human-object interactions. We evaluate the proposed approach on three challenging action recognition datasets captured by Kinect devices, a multiview action recognition dataset captured with Kinect device, and a dataset captured by a motion capture system. The experimental evaluations show that the proposed approach achieves superior performance to the state-of-the-art algorithms.
Large-area RFID reader antenna for smart shelf at UHF

The design concept, geometry, simulated and measured results of a large-area RFID reader antenna for the smart shelf at UHF are presented. The antenna is implemented by cascading two layers of microstrip lines and being terminated with a matched load. The proposed antenna can produce a uniform magnetic field even though the size of the antenna is large. It has a low far-field gain and adaptability of its dimension as per requirement. These properties make the antenna suitable for smart shelf RFID readers.
Improving power supply performance for the Duke storage ring

As part of the recent Duke storage ring hardware upgrade (2001-2002), a power supply improvement program was put in place to bring all major DC supplies to their specifications. In carrying out this program, power supplies have been modified, tuned, and thoroughly tested. In its actual operation configuration, each power supply was subject to extensive testing to determine its DC stability, reproducibility and linearity, AC ripple and noise, and ramping performance. As a result, all major DC supplies have been improved to meet most important performance specifications for 1 GeV operation.
The research of the engineering education practice teaching system with CDIO

The defect of the engineering education structure has already become a major bottleneck to restrict the development of industry, but CDIO concept is in line with the reform requirements for our country engineering education practice ability. This article will further explore the reform with the engineering education practice teaching based on CDIO. According to the concept of CDIO and engineering specialty practice teaching training target, this article puts forward to the" rely on one core standard, focus on two aspects of quality culture, pay attention to three levels of skills, enhance four levels of practice abilities, improve five links of practice teaching" as the main contents of the engineering practice teaching system.
Dual Circularly Polarized Equilateral Triangular Patch Array

This paper presents a novel sequentially rotated patch array antenna with dual circular polarizations (CP). The present design has the advantages of compact size, simple feed networks, low cross polarization, and high isolation. The radiating elements are dual linearly polarized (LP) equilateral triangular patches with hybrid feeds. The vertical polarization (VP) of the patch antenna is obtained by using an aperture-coupled feed and the horizontal polarization (TIP) is obtained by using a proximity feed. These two feeds are orthogonally positioned and are printed on different PCB layers, which leads to the high isolation between these two ports and facilitates the design of the feed networks. The array antenna consists of six such dual-LP triangular patches sequentially rotated by 60° and fed by separated feed networks. Since LP antenna elements are used, the design of the feed network is much simplified. Through sequentially varying the feeding phase by ±60°, dual circular polarizations are obtained. The operation principle of the array antenna is also analytically explained in this paper. To verify the design concept, one dual LP equilateral triangular patch and one dual CP equilateral triangular patch array resonating at 10.5 GTIz are designed, fabricated, and tested. There is a good agreement between the simulation and measurement results, both of which show that the array antenna exhibits high port isolation and good circular polarizations with low cross polarization at different planes. The proposed design technique can be applied to the design of dual CP array antennas operating at other frequency bands.
Exponential Stabilization for Suspension System of Vehicle Application

In this paper, an active suspension system for the exponential decay control of the three-degree-of-freedom (3DOF) twin-shaft vehicle is proposed. A new exponential stabilization criterion of the second-order vector differential equations is derived and the particle swarm optimization (PSO) method is employed for searching the optimal controller parameters. The proposed method guarantees all of states of the vehicle in an optimally exponentially decaying manner. The simulation results show that the vibration characteristics of the vehicle by the proposed active suspension achieve high performance in the control of the vehicle body vibration and provide higher driving safety than the passive and linear quadratic (LQ) active suspensions.