nils-herrmann/clean_scirepeval huggingface dataset:
Capturing articulated human hand motion: a divide-and-conquer approach

The use of the human hand as a natural interface device serves as a motivating force for research in the modeling, analysis and capture of the motion of an articulated hand. Model-based hand motion capture can be formulated as a large nonlinear programming problem, but this approach is plagued by local minima. An alternative way is to use analysis-by-synthesis by searching a huge space, but the results are rough and the computation expensive. In this paper, articulated hand motion is decoupled, a new two-step iterative model-based algorithm is proposed to capture articulated human hand motion, and a proof of convergence of this iterative algorithm is also given. In our proposed work, the decoupled global hand motion and local finger motion are parameterized by the 3D hand pose and the state of the hand respectively. Hand pose determination is formulated as a least-median-of-squares (LMS) problem rather than the nonrobust least-squares (LS) problem, so that 3D hand pose can be reliably calculated even if there are outliers. Local finger motion is formulated as an inverse kinematics problem. A genetic algorithm-based method is proposed to find a sub-optimal solution of the inverse kinematics effectively. Our algorithm and the LS-based algorithm are compared in several experiments. Both algorithms converge when local finger motion between consecutive frames is small. When large finger motion is present, the LS-based method fails, but our algorithm can still estimate the global and local finger motion well.
The Chameleon-Like Vision System

Vision-based surveillance technologies are widely used for security and safety. Successful research of multicamera systems has been conducted in recent years. In this article, we propose a chameleon-like vision system based on two pan-tilt-zoom (PTZ) cameras. Compared with conventional binocular vision systems, the advantages of the proposed system lie in its ability to obtain multiresolution, multiview information and depth information at the same time. Its key components, such as system calibration, system scheduling, camera control, and information fusion, are discussed in this article. We also provide several applications to illustrate the effectiveness of this new system.
False Positive Reduction in Lung GGO Nodule Detection with 3D Volume Shape Descriptor

Lung nodule detection, especially ground glass opacity (GGO) detection, in helical computed tomography (CT) images is a challenging computer-aided detection (CAD) task due to the enormous variances in nodules' volumes, shapes, appearances, and the structures nearby. Most of the detection algorithms employ some efficient candidate generation (CG) algorithms to spot the suspicious volumes with high sensitivity at the cost of low specificity, e.g. tens even hundreds of false positives per volume. This paper proposes a learning based method to reduce the number of false positives given by CG based on a new general 3D volume shape descriptor. The 3D volume shape descriptor is constructed by concatenating spatial histograms of gradient orientations, which is robust to large variabilities in intensity levels, shapes, and appearances. The proposed method achieves promising performance on a difficult mixture lung nodule dataset with average 81% detection rate and 4.3 false positives per volume.
Image representation by active curves

This paper proposes a sparse image representation using deformable templates of simple geometric structures that are commonly observed in images of natural scenes. These deformable templates include active curve templates and active corner templates. An active curve template is a composition of Gabor wavelet elements placed with equal spacing on a straight line segment or a circular arc segment of constant curvature, where each Gabor wavelet element is allowed to locally shift its location and orientation, so that the original line and arc segment of the active curve template can be deformed to fit the observed image. An active corner or angle template is a composition of two active curve templates that share a common end point, and the active curve templates are allowed to vary their overall lengths and curvatures, so that the original corner template can deform to match the observed image. This paper then proposes a hierarchical computational architecture of summax maps that pursues a sparse representation of an image by selecting a small number of active curve and corner templates from a dictionary of all such templates. Experiments show that the proposed method is capable of finding sparse representations of natural images. It is also shown that object templates can be learned by selecting and composing active curve and corner templates.
Research on the Performance Measurement of Knowledge Management Based on Principal Component Analysis

As an important part of knowledge management (KM), the KM performance evaluation tries to find out the key factors restraining the enhancement of the enterprises' performance. In this paper, some primary factors of the performance of enterprises KM are analyzed and an index system of KM performance is established by considering some aspects, such as marketing capability, information management, maturity degree of the learning organizations, and knowledge stocks. A principal component analysis and the arithmetic steps for principal component analysis are presented to evaluate the KM performance. The case analysis shows that the principal component analysis method is efficient and practical for the KM performance evaluation.
Time-Frequency Analysis for Cutting Tools Wear Characteristics

To monitor the tool wear states in drilling, a new method is proposed to obtain the signal characteristics based on the wavelet transformation. The method can reflect the tool wear states by using discrete dyadic wavelet transform. The cutting force signals of cutting process are decomposed; and the values of the decomposed signals in different scales are taken as the feature vectors. The pattern identification is used to monitor the tool wear states in real time. The method can identify the tool wear states correctly by choosing the suitable standard samples. The result shows that the proposed method is suitable for real-time implementation in manufacturing application, and has good identification precision and high efficiency
Independent Gabor Analysis of Multiscale Total Variation-Based Quotient Image

A new algorithm for independent Gabor analysis of multiscale total variation-based quotient image is proposed and applied to face recognition with only one sample per subject here. With our preproposed multiscale TV-based quotient image (TVQI) model, the large-scale and small-scale features are firstly fused to produce the most expressive lighting invariant face. Then a bank of Gabor filters is built to extract lighting invariant Gabor face representations with specified scales and orientations. Last, an information maximization algorithm is adopted to extract higher-order statistical relationships among variables of samples for classifier. According to the experiments on the large-scale CAS-PEAL face database, our approach could outperform Gabor-based ICA, Gabor-based KPCA, and TVQI when they face most outliers (lighting, expression, masking, etc.).
Compact miniaturised-element frequency selective surface

A compact miniaturised-element frequency selective surface (FSS) is proposed for size reduction. The proposed structure can be considered as a common square-loop slots FSS overlaid with a periodic array of metallic patches mounted on an ultra-thin dielectric layer. A larger coupling capacitance is brought in each overlap area between the two layers of parallel metallic films. The theoretical analysis and simulation results, together with measured results, demonstrate that a much better compactness characteristic can be realised in the proposed FSS.
Electrical performance analysis of photovoltaic and photocatalytic hybrid system

To make full use of the spectral radiation, a hybrid system comprising a photocatalytic subsystem and a photovoltaic subsystem is proposed for both water purification and electricity output. The photocatalytic subsystem is presented as a convex-lens type structure to concentrate sunlight for photoelectric conversion. The theoretical model of electrical efficiency calculation in the hybrid system is constructed in detail. Result suggests that solar cell GaAs is more suitable for the transmitted spectrum under the reference condition. Compared with the stand-alone PV system, it is found the electrical generation of the hybrid system may be comparable or advantageous when having a higher concentration ratio. In addition, the solar cell temperature is relatively lower than that in the stand-alone PV system.
A Simulation Model for Optimizing Support Resources in Requirement of Warship Mission Reliability

The configuration of support resources is a main factor affecting warship mission reliability. Seeking the balance between support resources and mission reliability to sustain the demands of missions is one of the targets of materiel support studies. This paper proposes a discrete-event simulation model written in ExtendSim and employs an enhanced evolutionary algorithm for optimizing support resources in requirement of warship mission reliability. This would help military planner determine the best configuration of support resources given objective mission reliability and make support decision in operational support concept design for specific military object.
Object Removal By Cross Isophotes Exemplar-based Inpainting

Exemplar-based inpainting algorithm is a new model used for large region removal. It combines the advantages of both inpainting and texture synthesis. The crucial part of this model is data term which is used to preserve linear structure. In this paper, basing on anisotropic diffusion, deeper mathematical analysis of along isophotes exemplar-based inpainting (AIEI) is given, and it is also proved the data term is the strength of isophotes. A novel cross isophotes exemplar-based inpainting (CIEI) model is proposed, which determines the data term cross the isophotes. Data term in CIEI considers the extent of edge, so CIEI has better linear structure preserving property, and it can fill the target region of natural scene more plausibly. Both theoretical analysis and experiments have verified the validity of the new CIEI model proposed in this paper
Research on transport property of carbon nanotube based device

The carrier transport in carbon nanotube is studied using the nonequilibrium Green's function with the self-consistent approximation methods. The model provides the basis for ATK software to simulate the electron transfer characteristics. The I–V characteristic of the carbon nanotube based device was simulated with ATK software. The electrical properties of the device formed by individual nanotube between metal electrodes were characterized at room temperature by measuring current. Those results show that the qualitative features of the simulated I–V characteristics agree with the experimental work, which provide the new theoretical methods for the development of canbron nonotube based device.
Epitaxial growth of high quality InAs/InGaAlAs quantum dash-in-well structure on InP

We report on the growth of InAs quantum-dash in InGaAlAs quantum-well structure on InP substrate using molecular beam epitaxy. The influence of different growth parameters such as InAs layer thickness, quantum barrier growth temperature, and number of stacking layers on the morphology and optical properties of dash structures were studied. The results serve as useful references for improved epitaxial growth control of InAs/InGaAlAs/InP system for optical device applications.
Scalable heterogeneous programming tools

We study the heterogeneous use of two programming paradigms for heterogeneous computing called Cluster-M and HAsC. Both paradigms can efficiently support heterogeneous networks by preserving a level of abstraction which does not include any architecture mapping details. Furthermore, they are both machine independent and hence are scalable. Unlike almost all existing heterogeneous orchestration tools which are MIMD based, HAsC is based on the fundamental concepts of SIMD associative computing. HAsC models a heterogeneous network as a coarse grained associative computer and is designed to optimize the execution of problems with large ratios of computations to instructions. Ease of programming and execution speed, not the utilization of idle resources are the primary goals of HAsC. On the other hand, Cluster-M is a generic technique that can be applied to both coarse grained as well as fine grained networks. Cluster-M provides an environment for porting various tasks onto the machines in a heterogeneous suite such that resource utilization is maximized and the overall execution time is minimized. We illustrate how these two paradigms can be used together to provide an efficient medium for heterogeneous programming. Finally, their scalability is discussed.<<ETX>>
Mining Visual Collocation Patterns via Self-Supervised Subspace Learning

Traditional text data mining techniques are not directly applicable to image data which contain spatial information and are characterized by high-dimensional visual features. It is not a trivial task to discover meaningful visual patterns from images because the content variations and spatial dependence in visual data greatly challenge most existing data mining methods. This paper presents a novel approach to coping with these difficulties for mining visual collocation patterns. Specifically, the novelty of this work lies in the following new contributions: 1) a principled solution to the discovery of visual collocation patterns based on frequent itemset mining and 2) a self-supervised subspace learning method to refine the visual codebook by feeding back discovered patterns via subspace learning. The experimental results show that our method can discover semantically meaningful patterns efficiently and effectively.
Dimensional music emotion recognition by valence-arousal regression

As hot topics in current research, music emotion recognition (MER) have been addressed by different disciplines such as physiology, psychology, musicology, cognitive science, etc. In this paper, music emotions was modeled as continuous variables composed of valence and arousal values (VA values) based on Valence-Arousal model, and MER is formulated as a regression problem. 548 dimensions of music features were extracted and selected. The support vector regression, random forest regression and regression neural networks were adopted to recognize music emotion. Experimental results show that these regression algorithms achieved good regression effect. The optimal R2 statistics of values of VA values are 29.3% and 62.5%, which are achieved respectively by RFR and SVR in Relief feature space.
Average consensus problems of neutral multi-agent systems with time-varying delay and switching topology

This paper introduces a new type of consensus protocol in undirected networks, which leads to a corresponding neutral multi-agent system. Such a protocol not only comprises the usual linear protocol as a particular case, but also allows a less conservative estimate on the upper bound of time delay. By decoupling the neutral multi-agent system in terms of the eigenvalues of the Laplacian matrix, necessary and sufficient conditions for average consensus have been established for the case of fixed topology. For the case of switching topology, a sufficient condition for average consensus is given by using a linear matrix inequality method. Finally, two examples are worked out to explain the effectiveness of the theoretical results.
Common Spatial Pattern Discovery by Efficient Candidate Pruning

Automatically discovering common visual patterns in images is very challenging due to the uncertainties in the visual appearances of such spatial patterns and the enormous computational cost involved in exploring the huge solution space. Instead of performing exhaustive search on all possible candidates of such spatial patterns at various locations and scales, this paper presents a novel and very efficient algorithm for discovering common visual patterns by designing a provably correct and computationally efficient pruning procedure that has a quadratic complexity. This new approach is able to efficiently search a set of images for unknown visual patterns that exhibit large appearance variations because of rotation, scale changes, slight view changes, color variations and partial occlusions.
Understanding the dynamic momentum aperture of the Advanced Light Source

The lifetime of a light source with small emittance like the Advanced Light Source (ALS) is usually limited by the momentum acceptance of the ring. Large momentum acceptances are reached by providing enough RF voltage and by avoiding a degradation of the dynamic momentum aperture. At the ALS the size of the momentum acceptance depends strongly on the transverse dynamics. It is very sensitive to machine conditions such as the tunes and chromaticities since depending on those conditions the Touschek scattered particles explore different resonance regions in the phase space. In this paper we show that by using a single-turn 'pinger' magnet together with turn-by-turn beam position monitors (BPM) one can identify the cause of a reduction in momentum acceptance and take steps to improve the acceptance.
An Improved Coded Repetition Scheme for Safety Messaging in VANETs

Safety messaging plays an important role in Vehicle-to Vehicle (V2V) communications. By broadcasting packets via an 802.11 based technology, each vehicle informs the neighbors with its real-time status. Since this kind of information is life-critical, it should be received by all the adjacent vehicles with very high probability. In the previous work, we proposed a coded cooperative repetition approach for reliably broadcasting safety message in VANETs. It improves message's reception rate by repeating the received messages and share the scarce wireless bandwidth by coding two repetitions together. However, this method also introduces overheads. Almost 40% of all received coded repetitions are useless due to suboptimal coding decisions. In this paper, we improve this coded repetition method by providing it with more accurate information to guide the coding process. This enhancement incorporates three main techniques: reception rate estimation, neighbor state collection and opportunistic coding. Our experiments show a significant performance improvement. The overhead is reduced from over 40% to around 10% and the reception rate is increased by 15%.
Measurements Study on the I/O Performance of Virtualized Cloud System

By splitting up an underutilized physical host into several virtualized domains, Virtualization can make the optimal use of resources and reduce the energy consumption. By delving into the types of I/O applications, adjusting amount of resource, and combining different applications in one or more domains, several insights are observed in this paper: using a few exclusive physical CPU driver domain can improve the efficiency of forwarding, which makes over 17% performance improvement for I/O applications; in addition, the domain providing mixed services can achieve 70% performance gain, when compared with others that provide single service; last but not least, avoiding running too many network-provider domains simultaneously can relieve the inter-domain interference. These observations not only help to bring performance improvement to cloud consumers but also service stability to cloud providers.
1.0 THz fmax InP DHBTs in a refractory emitter and self-aligned base process for reduced base access resistance

We report 220 nm InP double heterojunction bipolar transistors (DHBTs) demonstrating f<inf>τ</inf> = 480 GHz and f<inf>max</inf> = 1.0 THz. Improvements in the emitter and base processes have made it possible to achieve a 1.0 THz f<inf>max</inf> even at 220 nm wide emitter-base junction with a 1.1 µm wide base-collector mesa. A vertical emitter metal etch profile, wet-etched thin InP emitter semiconductor with less than 10 nm undercut and self-aligned base contact deposition reduces the emitter semiconductor-base metal gap (W<inf>gap</inf>) to ∼ 10 nm, thereby significantly reducing the gap resistance term (R<inf>gap</inf>) in the total base access resistance (R<inf>bb</inf>), enabling a high f<inf>max</inf> device. Reduction in the total collector base capacitance (C<inf>cb</inf>) through undercut in the base mesa below base post further improved f<inf>max</inf>. These devices employ a Mo/W/TiW refractory emitter metal contact which allows biasing the transistors at high emitter current densities (J<inf>e</inf>) without problems of electromigration or contact diffusion under electrical stress .
Molecular Characterization Analysis of Newly Identified Duck Enteritis Virus UL55 Gene

The focus of this paper is on the newly identified UL55 gene of DEV in our laboratory.Available bioinformatic tools were used to describe its molecular characteristics. A identified nucleotide sequence about 561bp of DEV UL55 ,consisting a complete ORF, was deduced to encode a protein with 186 amino acids.The 20.7981 kDa protein whose singnal peptide and transmembrane region are both absent. Codon usage analysis shows the gene could be well expressed in Escherichia BL21.The putative protein is hydrophilic on the whole,its antigen epitope centralizes at the Extended strand (Ee) and Random coil (Cc) regions as well as the corresponding hydrophilic regions.It was predicted to be a nucleoprotein, which is probably invovled in viron entry,assembly,egress,maturation and release as its homologous.However, UL55 protein just plays an accessory role. Phylogenetic tree based on amino acids and its reference herpesvirus reaveals that there is a close relationship between DEV and Mardivirus genus.However, DEV is clustered within a monophyletic clade among others , suggests it is an intermediate taxonomic entity and should be placed in a single genus within the herpetoviridae subfamily.Despite its preliminary characterization, this study can clearly direct our research to elucidate its biological function and physiological features of this newly identified UL55 gene.
Coding Schemes for Noiseless and Noisy Asynchronous CDMA Systems

Novel coding schemes for noiseless and noisy asynchronous code division multiple access (A-CDMA) systems are presented in this paper. The schemes use Wu-Chang spreading code, block interleaver, and synchronizable channel codes to support A-CDMA communications with random delays. For the noiseless case, each active user generates one of M messages, M = ⌊(2T-D -1)/(D + 1)⌋ , and a (T-D)-stage MLSR encoder encodes the message into a codeword of length T. Given a maximum random delay of D chips, the receiver can decode messages of all active users without ambiguity. For the noisy case, extended Bose-Caldwell cyclic codes are used to encode messages. The extended cyclic codes provide error correction and delay recovery effectively. By using a BCH code of length n as the cyclic code, the extended code can correct up to τ ≤ ⌊n/4⌋ errors and recover a maximum random delay of n -1 chips.