nils-herrmann/clean_scirepeval huggingface dataset:
Effect of carboxyl methyl cellulose on the adhesion properties of sodium silicate wood adhesive

Carboxyl methyl cellulose (CMC) was used to improve the bonding capacity of sodium silicate (Na2SiO3) wood adhesive in this study. Compared with Na2SiO3 wood adhesive without CMC, the bonding strength of Na2SiO3 wood adhesive with 7.5% CMC increased by 56.3% in dry state, while its water resistance did not improve. The improved performance of CMC/Na2SiO3 wood adhesive was supported by its strengthened molecular structure, enhanced thermal stability, beneficial changes in flexibility of Na2SiO3 wood adhesive from the analysis results using Fourier transform infrared spectroscopy, thermogravimetric analyzer, and scanning electron microscopy. The improvement effect of CMC on the structure and properties of the adhesive indicates that CMC can be used to prepare environmentally friendly Na2SiO3 wood adhesive with high performance.
A robust estimator for direction finding with hierarchical prior

An estimator that can maintain acceptable performance for the hard conditions on which the maximum-likelihood estimator fails, i.e. when the signal-to-noise ratio falls below a certain threshold, is derived by introducing the prior information into the estimation. The prior information may be the approximate signal powers and the noise power. Because the available prior information is always vague, a robust way to incorporate it is developed. Simulation results showing the significant performance improvement are given.<<ETX>>
Fractal, entropic and chaotic approaches to complex physiological time series analysis: A critical appraisal

A wide variety of methods based on fractal, entropic or chaotic approaches have been applied to the analysis of complex physiological time series. In this paper, we show that fractal and entropy measures are poor indicators of nonlinearity for gait data and heart rate variability data. In contrast, the noise titration method based on Volterra autoregressive modeling represents the most reliable currently available method for testing nonlinear determinism and chaotic dynamics in the presence of measurement noise and dynamic noise.
Energy-saving technology of medium density fiberboard enterprise

High production energy consumption of medium density fiberboard restricted enterprise economic benefits seriously. In this paper, medium density fiberboard production characteristics was analyzed, energy-saving technology of medium density fiberboard enterprise was disscused. The analysis showed that establishing “energy plant” to reach power cascade utilization by using integrated combustion technology in the medium density fiberboard production, and making frequency conversion energy-saving transformation of high energy-consumption equipment by using frequency converter can effectively decrease the energy consumption and improve the competitiveness of enterprise in market.
State-feedback stabilisation for stochastic non-holonomic systems with time-varying delays

This study investigates the problem of state-feedback stabilisation for a class of stochastic non-holonomic systems in chained form with time-varying delays. By using input-state-scaling technique and backstepping recursive approach, and choosing an appropriate Lyapunov–Krasoviskii functional, a state-feedback controller is constructed. Based on switching strategy to eliminate the phenomenon of uncontrollability, the proposed controller could ensure that the closed-loop system is globally asymptotically regulated at origin in probability. A simulation example is provided to illustrate the effectiveness of the proposed method.
Fair Access to External Memory for Chip-multiprocessor

A memory arbitration scheme is required for chip-multiprocessor accessing external (off-chip) memory. A round-robin arbitration is an efficient and low-cost candidate for chip-multiprocessor. However, the adoption of simple round robin scheme raises a potential problem of uneven sharing of external memory bandwidth. One way to manage an unbalanced resource allocation resulting from the use of arbiters is to use priority arbitrations combined with a look-up table, but this is not economical since large lookup tables require a large silicon area. We propose an admission control scheme operating at the edge of on-chip interconnection. The fair-sharing service is guaranteed using a token mechanism to schedule packets onto fabric. This work shows that a fair service problem can be solved by controlling traffic of on-chip interconnect, since it avoid saturation in critical paths and to maintain equilibrium in the allocation of resource.
Minimum Spanning Forest With Embedded Edge Inconsistency Measurement Model for Guided Depth Map Enhancement

Guided depth map enhancement based on Markov random field (MRF) normally assumes edge consistency between the color image and the corresponding depth map. Under this assumption, the low-quality depth edges can be refined according to the guidance from the high-quality color image. However, such consistency is not always true, which leads to texture-copying artifacts and blurring depth edges. In addition, the previous MRF-based models always calculate the guidance affinities in the regularization term via a non-structural scheme, which ignores the local structure on the depth map. In this paper, a novel MRF-based method is proposed. It computes these affinities via the distance between pixels in a space consisting of the minimum spanning trees (forest) to better preserve depth edges. Furthermore, inside each minimum spanning tree, the weights of edges are computed based on the explicit edge inconsistency measurement model, which significantly mitigates texture-copying artifacts. To further tolerate the effects caused by noise and better preserve depth edges, a bandwidth adaption scheme is proposed. Our method is evaluated for depth map super-resolution and depth map completion problems on synthetic and real data sets, including Middlebury, ToF-Mark, and NYU. A comprehensive comparison against 16 state-of-the-art methods is carried out. Both qualitative and quantitative evaluations present the improved performances.
Nonnegative Tensor PCA and Application to Speaker Recognition in Noise Environments

In this paper a new approach called nonnegative tensor principal component analysis (NTPCA) with sparse constraint is proposed for speech feature extraction. We encode speech as a general higher order tensor in order to extract the robust feature from multiple interrelated feature subspace. First, speech signals are represented by cochleagram based on frequency selectivity at basilar membrane and inner hair cells; Then, a low dimension sparse representation based on tensor structure is extracted by NTPCA for robust speaker modeling. Alternating projection algorithm is used to obtain a stable solution and makes sure the useful information of each subspace in the higher order tensor being preserved. Experiment results demonstrate that our method can increase the recognition accuracy specifically in noise environments.
Singlemode hetero-core fiber based refractometer demodulated in a ratiometric system

We propose a fiber refractometer based on a singlemode-small core singlemode (SCSMF)-singlemode (SMF28-SCSMF-SMF28) structure demodulated by a ratiometric measurement system. Both the SMF28 and SCSMF fibers have a step index profile and the conventional SMF28 fiber is used at both ends as the attaching fiber to the small core SMF fiber. By measuring the power variations at the output of the refractometer, the surrounding refractive index (SRI) can be determined. Experiments demonstrate a maximum RI sensitivity of 1.55×10−5 in the SRI range from 1.3340 to 1.4485.
A Cloud-ICT Convergence Service Architecture SDN/NFV powered

The core-network suffers from inflexible and expensive equipment. Service chaining is a common but important problem of network management in Gi-LAN. The requirements of business agility drive the service architecture to services flexibility and scalability. To address these challenges, SDN centralized control and the NFV concept of CT reconstruction with IT virtualization technology are used to enable a reform in the mobile core network and the Gi-LAN service field. In this paper, following the technical trend of 5G, we propose the Cloud-ICT Convergence Service Architecture to construct an open and elastic digital information ecosystem. This architecture is a solution that provides flexibility in managing infrastructure and uses virtualization to dynamically orchestrate service chains on demand. The information ecosystem constructed in this architecture can provide the functional convergence of IT&CT services in addition to the traditional cellular network functions.
Research on the optimal adhesive impregnation conditions of bamboo bundles made for recombined bamboo composite

Some factors was discussed, including solid content of phenol formaldehyde, adhesive impregnation time, moisture content of bamboo bundle and cross section area of bamboo bundle. It was showed that: the optimal process conditions is: solid content of phenol formaldehyde for 25%, adhesive impregnation time for 14min, moisture content of bamboo bundle for 11%, cross section area of bamboo bundle for 10.3mm2.
Study on Technology of Deresination of Pinus massoniana Wood Based on Reducing the Discharge of Wastewater

Deresination process, which usually consume a large quantity of water, is widely applied to enhance the addded value of pine wood processing utilization. In order to reduce the consumption of water resource, deresination technology on Pinus massoniana wood was investigated. Results showed that the influence of the degreasing temperature on the of the intermediate deck and the core layer of Pinus massoniana wood and both mean value were highly remarkable, but not remarkable to the leaching quantity of the surface layer; as the temperature increased, the amount of the resin in the surface layer increased first and then decreased, but both quantity of leaching resin of the other layers and their average value displayed increasement, the influence of pressure on the pine wood is not remarkable; when the pressure increases, the quantity of leaching resin increases first and then decrease, and the rate of change scope is quite small. The influence of the degreasing time on the amount of leaching resin of the surface layer wood is not remarkable; it is not the same as quantity of leaching resin of core layer. And along with the extension of degreasing time, the quantity of dissolved resin has basic tendency which increases first and then reduces. The influence of solution volume fraction on amount of leaching resin is not remarkable, and along with the extention of d solution volume fraction, the quantity of leaching resin has basic tendency which increases first and then reduces and increases again. The ideal deresination technology is that the degreasing temperature is 120degC, the degreasing time is 6.5 h, and the solution volume fraction is 3.5%.
Real-time video copy detection based on Hadoop

With the development of multimedia technology and Internet, the amount of videos in the Internet is increasing quickly. Among the large amount of videos in the Internet, a considerable number of them are copies of original videos, which are simply revised versions of the original ones. The purpose of video copy detection technology is to detect copy videos, which has important applications in video tracking, video content retrieval, video copyright protection and other aspects. The current problem is that real-time video copy detection is often difficult to achieve due to the large amount of video data. Hadoop is a distributed computing platform which is designed for deployment in inexpensive hardware and suitable for those applications with a large data set. All of these characteristics could just meet the requirements of real-time video copy detection technology. In this paper, an attempt is done to develop a real-time video copy detection system based on Hadoop platform, and two video copy detection algorithms are implemented on Hadoop platform, which are the method based on brightness sequence and the method based on TIRI-DCT respectively, and their performances are compared. Experiments show that the use of Hadoop platform can significantly improve the efficiency of video copy detection, which has important practical significance for video tracking and real-time video content retrieval application.
Determination of Pyrolytic By-Products of Dendrocalamus barbatus Organism Body by GC/MS

The pyrolytic products of Dendrocalamus barbatus organism body is of important value in healing some diseases. Therefore, the determination of the chemical components from the five-year-old Dendrocalamus barbatus was made by using Py- GC/MS. The results indicated that the main components of the Dendrocalamus barbatus by Py-GC/MS analysis were carbon dioxide (54.34%), 2-butanamine, (s)- (17.4%), oxirane, (ethoxymethyl)- (8.29%), methyl formate (4.14%), 1,6-anhydro- .beta.-d-glucopyranose (3.27%), benzaldehyde, 4-nitro-, o- methylox (1.35%), 1-hepten-4-ol (1.23%), 2,3-butanedione (1.19%), acetic acid (0.72%), ethanone, 1-(3-methoxyphenyl)- (0.68 %), pentanoic acid (0.67%), phenol, diethyl- (0.64%), etc. so the the pyrolysis byproducts of Dendrocalamus barbatus may be used as raw materials of rare biomedicines. Dendrocalamus barbatus; py-gc/ms; biomedical components; pyrolytic by-products
Study on Benzene/ethanol Extractives of Eucalyptus Urophylla Chips for Bioenergy with High Added Value by Py-GC/MS

The increasing demand for paper in Asia is being met by the use of Eucalyptus urophylla to a large extent. However, some pulp mills may be forcedly closed because the Eucalyptus urophylla chips contain extractives severely enough to pollute the water. In this paper, the chemical components in the benzene/ethanol extractives of Eucalyptus urophylla chips were isolated and identified by Py-GC/MS to produce bioenergy with high added value. 114 compounds in the extractives were identified. The mainly abundant constituents were .beta.- sitosterol (10.00%), acetic acid (7.34%), phenol, 2 ,6-dimethoxy- (4.95%), 6H-dibenzo[b,d]pyran-6-one, 7, 9-dihydroxy-3-methoxy- 1-methyl- (4.09%), phenol, 2-methyl- (3.71%), sesquirosefuran (3.36%), carbon dioxide (2.56%), acetone (2.49%), ethanone, 1- (3-methoxyphenyl)- (2.31%), stigmasterol (2.19%), etc. The most components from benzene /ethanol extractives of fresh Eucalyptus urophylla wood are not only abundant and healthy to human, but also can be used as fine bioenergy.
Comparison of algorithms for transient stability simulations on shared and distributed memory multiprocessors

Parallel processing has been applied for time domain simulations of power system transient behavior in order to implement real-time dynamic security assessment. In this paper, two different algorithms have been implemented and compared: the Shifted-Picard (SP) and the Very DisHonest Newton (VDHN). The former has been proved to be effective when parallelism-in-time is adopted whereas the latter is an effective solver when parallelism-in-space is exploited. Furthermore, two different parallel computing architectures have been considered: namely, the Sequent Symmetry computer with 26 processors which is a data shared memory machine and the nCUBE characterized by 128 CPUs which is a typical message passing parallel machine. A realistic network with 662 buses has been used to assess the performance of the different implementations. The comparison of the results allows the reader to understand both the limitations of the algorithmic approaches and the constraints imposed by the two parallel architectures. An optimal grain of the parallelism associated to the problem can be identified through the reported experience.
White Light Trapping Using Supercontinuum Generation Spectra in a Lead-Silicate Fibre Taper

We experimentally investigate white light optical trapping by generating a supercontinuum in a lead silicate fibre pumped by femtosecond pulses from a Ti:Sapphire laser near the zero-dispersion wavelength of 1030 nm, before confining the light using a microfibre half taper with a final tip diameter of 75 nm. Due to the high intensity gradient at the output, robust optical trapping is possible, as demonstrated for individual yeast cells using an average pumping power of 100 mW.
GII Representation-Based Cross-View Gait Recognition by Discriminative Projection With List-Wise Constraints.

Remote person identification by gait is one of the most important topics in the field of computer vision and pattern recognition. However, gait recognition suffers severely from the appearance variance caused by the view change. It is very common that gait recognition has a high performance when the view is fixed but the performance will have a sharp decrease when the view variance becomes significant. Existing approaches have tried all kinds of strategies like tensor analysis or view transform models to slow down the trend of performance decrease but still have potential for further improvement. In this paper, a discriminative projection with list-wise constraints (DPLC) is proposed to deal with view variance in cross-view gait recognition, which has been further refined by introducing a rectification term to automatically capture the principal discriminative information. The DPLC with rectification (DPLCR) embeds list-wise relative similarity measurement among intraclass and inner-class individuals, which can learn a more discriminative and robust projection. Based on the original DPLCR, we have introduced the kernel trick to exploit nonlinear cross-view correlations and extended DPLCR to deal with the problem of multiview gait recognition. Moreover, a simple yet efficient gait representation, namely gait individuality image (GII), based on gait energy image is proposed, which could better capture the discriminative information for cross view gait recognition. Experiments have been conducted in the CASIA-B database and the experimental results demonstrate the outstanding performance of both the DPLCR framework and the new GII representation. It is shown that the DPLCR-based cross-view gait recognition has outperformed the-state-of-the-art approaches in almost all cases under large view variance. The combination of the GII representation and the DPLCR has further enhanced the performance to be a new benchmark for cross-view gait recognition.
An adaptive segment-based view synthesis optimization method for 3D-HEVC

This paper presents an adaptive segment-based view synthesis optimization (VSO) for depth map coding in 3D-HEVC. The original method skips lines of pixels where there is no change in depth data, and exhaustively renders pixels from all the rest of lines to get distortions from synthesized views. It brings unnecessary coding operations and ignores smaller regions which can also be skipped in VSO. The proposed method is designed to skip proper segments of pixels for the non-skipped lines based on both of the texture smoothness and depth data unchangeableness. Experimental results show that the proposed method can achieve low coding complexity without significant performance loss for the synthesized views.
cdma2000 1x Rev. E Forward Link Voice Capacity

The forward link capacity of a cdma2000 lx system is power limited. Therefore, average data rate (ADR), link efficiency, and receiver signal-to-noise ratio (SNR) are the key factors for capacity improvement. In this paper, we introduce the new features of the forward fundamental channel (F-FCH) with radio configuration (RC) 11 for 1x Revision E that is being standardized at the Third Generation Partnership Project 2 (3GPP2) and advanced receivers for mobile stations (MS), targeted at these key factors. Simulations show that the new RC together with interference cancellation and a new voice codec more than doubles the forward link capacity of existing 1x systems, and more than triples the capacity with dual receive antennas. The capacity gain is achieved without any increase in voice latency or any degradation in voice quality.
Finite time tracking control for rigid robotic manipulators with friction and external disturbances

The finite time tracking problem is considered for robotic manipulators with unknown dynamic friction, bounded disturbances and unmodeled dynamics. A global relay switching control scheme with finite time convergence is proposed. For general finite time variable structure controller, the control signals may escape to infinity in finite time when the initial states of the system are in some specified area, causing the singularity phenomena of the closed-loop system. The design scheme for finite time tracking control uses a two-phase switching control method so that the boundedness of the control signal is guaranteed and the singularity phenomena is avoided.
Molecular dynamics simulation on the out-of plane thermal conductivity of monocrystal germanium thin-film

We establish a heat conduction model to investigate the thermal conductivities of monocrystal germanium thin-film based on the anisotropic non-equilibrium molecular dynamics (NEMD) arithmetic and corresponding Tersoff potential energy function. The simulation results indicate that the thermal conductivity of monocrystal germanium thin-film is remarkably lower than corresponding bulk experimental data and increase with increasing the film thickness. Furthermore, the thermal conductivity of that relates to film thickness linearly in the simulative range. For a given film thickness, it vary much small with increasing the temperature, and its size effect is significant comparing with the bulk germanium crystal. This work shows that molecular dynamics, applied under the correct conditions, is a viable tool for calculating the thermal conductivity of monocrystal germanium thin-films. More generally, it demonstrates the potential of molecular dynamics for ascertaining microscale thermophysical properties in complex structures.
Tensor optimal scoring for alzheimer's disease detection

In recent years, the universal application of magnetic resonance imaging has given a new diagnostic approach for lots of diseases, including Alzheimer's disease (AD). In this paper, we propose a new classification framework for AD detection. To avoid the curse of dimensionality problem, a new dimension reduction algorithm in tensor space called tensor optimal scoring (TOS) was proposed to extract efficient features from MRI data of AD. Alternating least square optimization was employed to estimate the projection vector and optimal scores. We validated the effectiveness of our proposed method on OASIS dataset. The experimental results showed that our method outperformed the traditional methods especially for higher order MRI data.
Generating Algorithm of Approximate Decision Rules and its Applications

In the real world applications, those basic decision rules inducted using rough set theory can’t match a new object, so it can’t always make an accurate decision for the object. In order to improve the matching ability of decision rules to a new object, an algorithm which generates approximate decision rules more efficiently is proposed in this article and applied to the field of filtering spam based on rough set theory. The results in experimental test showed that those approximate decision rules obtained by the algorithm can enhance the matching ability to a new mail. So the algorithm proposed in this paper is believed to be more effective and feasible.