nils-herrmann/clean_scirepeval huggingface dataset:
Correlation properties of time-hopping sequences for impulse radio

Time-hopping (TH) techniques have received increasing attention, as ultra wide band (UWB) impulse radio (IR) is proposed. The correlation properties of TH sequences have an important effect on the performance of IR communication system. This paper analyses the correlation properties of TH sequences. The definition of the correlation function of TH sequences is given. The upper and lower limits of correlation value of time-hopping sequences are obtained. Finally, the way to improve the correlation property of TH sequences is obtained. By this means, the maximum correlation value of TH sequences is decreased to half of original value.
Low complexity variable-size block-matching motion estimation for adaptive motion compensation block size in H.264

An efficient merge-based algorithm for variable-size block matching ME (motion estimation) to reduce the computation of block-size decision process in H.264 video encoder is proposed. Fixed-size 4 /spl times/ 4 small blocks are used for the integer-pixel accuracy full search ME and several candidate MVs are reserved for each 4 /spl times/ 4 blocks to determined if the neighboring blocks could be merge into other predefined block types or not. Simulation result shows the computational load of our method is significantly reduced than H.264 JM 7.3.
A lock-free algorithm for union-find with deletion

The classical union-find algorithm is the basis for many graph algorithms and for dealing with equality. The easiest way to implement concurrent objects is by means of classical software solutions, but this leads to blocking when the process that holds exclusive access to the object is delayed or stops functioning. Thus we require our solutions to the data structure problem have the lock-free property. In this paper, we present an efficient lock-free algorithm for union-find with deletion, which promises more robust performance and reliability than conventional lock-based implementations.
Rank learning on training set selection and image quality assessment

Machine learning (ML) techniques are widely used in recent no-reference visual quality assessment (NR-VQA) metrics by training on subjective image quality databases. In these metrics, the optimization function is constructed based on L2 norm of the distance between subjective image quality and predicted image quality. There are two problems in these L2 norm based methods: (1) human's opinion on subjective image quality rating is not reliable at fine-scale level. A small difference between subjective image qualities represented by mean opinion scores (MOSs) of two images may not truly reflect the real quality difference between these two images, but acts as noise. The optimization process should avoid such noise. (2) Generally, human's opinion on pairwise comparison (PC) for image quality is more reliable and believable than MOS. The importance of PC is ignored during the optimization process of existing ML-based studies, which are designed based on the numerical rating system. In this paper, we introduce image quality ranking concept to establish a new optimization objective instead of L2 norm optimization, and then a novel NR-VQA is constructed based on ranking learning. The proposed metric firstly suggests a reasonable training set for ML, which is ignored by existing ML-based NR-VQA. The ranking theory is adopted to build optimization function, which reflects the properties of PC over the numerical ranting system used by traditional NR-VQA. By ignoring the small difference between MOSs from two images during the optimization process, the proposed ranking-based NR-VQA can also well address the first problem from the existing related metrics. Experimental results show that the proposed ranking-based NR-VQA can obtain better performance over the state-of-the-art NR-VQA approaches.
Incoherent optical modulation of graphene based on inline fiber Mach-Zehnder interferometer

We investigated the incoherent optical modulation of graphene based on an inline fiber Mach-Zehnder interferometer fabricated by splicing D-shaped fiber and single mode fibers. Single layer graphene was covering on the D-shaped fiber face. With a backward pump-probe setup, we found that the incoherent optical modulation was independent of the wavelength difference between pump and probe laser, supporting theoretical analysis that the incoherent optical modulation is mainly contributed by the carrier-phonon process of graphene. Further, both the decrease of the pump wavelength and the increase of pump power would deepen the modulation in an exponential trend.
Impact-factor-guided X-filling for peak power reduction during test

Peak power during testing system-on-chip (SoC) circuits is a challenging issue for both reliability and yield. Because test vectors always try to activate as many faults as possible in the capture cycles, peak power during test usually happens in these cycles. X-filling is one effective way to reduce transitions happened in capture cycles to reduce peak power during test. However, its efficiency is limited and needs well exploration. This paper proposes an X impact-factor-metric to estimate the impact of filling one X bit on other X bits in test cube. This metric is utilized to efficiently guide the X-filling to reduce the capture power. We call it impact-factor-Guided (IFG) X-filling. Experimental results on larger ISCAS'89 benchmark circuits show that the average and maximum capture power can be reduced through our IFG X-filling by 65% and 31% on average, respectively.
Research on Acoustic Emission Signal of Three-dimensional Braided Composite Material

This paper discusses the application and experimental method of acoustic emission for the three-dimensional (3D) braided composite material under flexural testing. It describes the feature of acoustic emission when applied to three-dimensional braided composite material under flexural testing. In order to know the materials damage position precisely, it is very important to collect the signal of acoustic emission source. The results of flexural experiment show that it is precise on the research of acoustic emission source location by the method of wave form analysis. During the collecting signal of acoustic emission, it is compared between parameter analysis and wave form analysis. According to the attenution degree of signal, it is selected signal of acoustic emission source exactly. It is the method to extract the precise acoustic emission signal by the different algorithm of wavelet analysis.
Radio Map Recovery and Noise Reduction Method for Green WiFi Indoor Positioning System Based on Inexact Augmented Lagrange Multiplier Algorithm

Currently, WiFi indoor positioning system based on IEEE 802.11 is widely attractive for its free infrastructure and high localization performance. However, due to working on-demand strategy in green WiFi scenario, the access points are not always available for mobile when radio map is built in the offline phase. Radio map with unknown received signal strength is not valid for positioning and usually be replaced by the minimum value, which leads to poor positioning performance. In This paper we propose a radio map recovery method based on inexact augmented Lagrange multiplier (IALM) algorithm, which achieves to precisely recover the missing received signal strength in the radio map for those access points unavailable in the offline. By solving the nuclear norm minimization, the IALM algorithm could not only recover the missing received signal strength, but also reduce the noise effectively. We have implemented the proposed method in our lab and evaluated its performances. The experiment results indicate the proposed method could precisely recover the radio map and achieve good positioning performance.
Polarization Reconfigurable Broadband Rectenna With Tunable Matching Network for Microwave Power Transmission

A broadband polarization reconfigurable rectenna is proposed, which can operate in three polarization modes. The receiving antenna of the rectenna is a polarization reconfigurable planar monopole antenna. By installing switches on the feeding network, the antenna can switch to receive electromagnetic (EM) waves with different polarizations, including linear polarization (LP), right-hand and left-hand circular polarizations (RHCP/LHCP). To achieve stable conversion efficiency of the rectenna (nr) in all the modes within a wide frequency band, a tunable matching network is inserted between the rectifying circuit and the antenna. The measured nr changes from 23.8% to 31.9% in the LP mode within 5.1-5.8 GHz and from 22.7% to 24.5% in the CP modes over 5.8-6 GHz. Compared to rectennas with conventional broadband matching network, the proposed rectenna exhibits more stable conversion efficiency.
A dataset and evaluation methodology for visual saliency in video

Recently, visual saliency has drawn great research interest in the field of computer vision and multimedia. Various approaches aiming at calculating visual saliency have been proposed. To evaluate these approaches, several datasets have been presented for visual saliency in images. However, there are few datasets to capture spatiotemporal visual saliency in video. Intuitively, visual saliency in video is strongly affected by temporal context and might vary significantly even in visually similar frames. In this paper, we present an extensive dataset with 7.5-hour videos to capture spatiotemporal visual saliency. The salient regions in frames sequentially sampled from these videos are manually labeled by 23 subjects and then averaged to generate the ground-truth saliency maps. We also present three metrics to evaluate competing approaches. Several typical algorithms were evaluated on the dataset. The experimental results show that this dataset is very suitable for evaluating visual saliency. We also discover some interesting findings that would be addressed in future research. Currently, the dataset is freely available online together with the source code for evaluation.
Global rainfall interception loss derived from multi-source satellite earth observations

Global rainfall interception loss information is essential to understand the dynamics of the water cycle. And it remains large uncertainty in its global variation, since its ground observation are scattered. The development of satellite earth observation provides good opportunity for global rainfall interception loss estimation to reveal its spatiotemporal variation. In current study, an analytical model, Gash model, was revised and applied for global rainfall interception estimation based mainly on satellite based remote sensing products, e.g. precipitation, leaf area index, canopy height. The ratio of interception loss to precipitation showed good agreement with in situ observations, with correlation factor and RMSE of 0.65 and 6.17%. Large spatial variation of rainfall interception loss were found with high value in tropical rainfall forest region and high latitude forest regions. However, the temporal variation was much less.
Optimisation strategies for distributed computing using an adaptive randomised structured network

One way to improve computational efficiency for complex engineering applications is to utilise distributed computing. In such distributed system, accessing objects through location-independent names can improve the systempsilas transparency, scalability and reliability. Names however need to be resolved prior to passing the messages between the objects. This paper reports an Adaptive RandoMised Structured search network termed ARMS, which utilises a distributed ant colony optimisation algorithms (ACO) to improve the efficiency of searching in a distributed environment. The paper further investigates different kinds of optimisation strategies in order to improve search efficiency. Simulation studies have shown ARMS is superior to Chord, a well-known structured network, under various performance measures.
Performance of atmospheric coherent laser receiver and bandwidth for adaptive optics system

For atmospheric links, the free space optical communication is challenged by the effects of turbulence. Wave-front aberration and power scintillation of the signal light are the main factors which lead to the degradation of system performance. In this paper, the bit-error-rate performance of atmospheric coherent laser receiver with binary phase shift keying modulation is performed. Beside the turbulence induced wave front phase error and the power scintillation, we investigated the time-delay phase error due to the insufficient of servo bandwidth of adaptive optics system. Our simulation results show that Greenwood frequency can meet the requirement for the servo bandwidth of adaptive optics system when the detected photons per bit are more than 100. However, if there are 70 or less photons per bit detected, the Greenwood frequency is only sufficient for weak scintillation. We should increase the servo bandwidth to almost twice the value of Greenwood frequency at least in order to obtain an acceptable BER performance when the scintillation index is larger than 0.7. In addition, the aperture averaging effects is analyzed and we found that the optimal size of receiving aperture may be around twice of the coherent length r0 when there is no adaptive optics employed in system.
Enhance the AIS data availability by screening and interpolation

The AIS broadcasts the ship's navigation data automatically and autonomously through VHF band. It plays an important role in collision avoidance and maritime situational awareness. However, in inland waterways, it is common that the AIS data-link was obstructed by the river bank and mountains, or sometimes the AIS was encountered with the electromagnetic interference. Consequently, the AIS dynamic data is often lost and mixed with inaccurate, which may lead to misjudgment of the traffic situation. To address this problem, a method was proposed to enhance the availability of AIS data in this paper. Firstly, according to the ships' maneuverability, a set of factors, such as the moving distance, speed, acceleration, and course change rate, were designed to screen the inaccurate AIS data. Then, the piecewise cubic Hermite interpolation and cubic spline interpolation were employed to restore the AIS data. A real AIS trajectory was introduced to validate the accuracy of the two interpolation methods, which proves that the cubic spline interpolation performance is better than piecewise cubic Hermite interpolation. Field experiments in Wuhan reach of Yangtze River show that the method proposed in this paper is highly effective. The accuracy of the location is 3.5m, the speed accuracy is 0.05m/s, and the course accuracy is up to 0.7 degrees, the AIS data can be accurately repaired.
OPTIMOL: automatic Online Picture collecTion via Incremental MOdel Learning

A well-built dataset is a necessary starting point for advanced computer vision research. It plays a crucial role in evaluation and provides a continuous challenge to state-of-the-art algorithms. Dataset collection is, however, a tedious and time-consuming task. This paper presents a novel automatic dataset collecting and model learning approach that uses object recognition techniques in an incremental method. The goal of this work is to use the tremendous resources of the web to learn robust object category models in order to detect and search for objects in real-world cluttered scenes. It mimics the human learning process of iteratively accumulating model knowledge and image examples. We adapt a non-parametric graphical model and propose an incremental learning framework. Our algorithm is capable of automatically collecting much larger object category datasets for 22 randomly selected classes from the Caltech 101 dataset. Furthermore, we offer not only more images in each object category dataset, but also a robust object model and meaningful image annotation. Our experiments show that OPTIMOL is capable of collecting image datasets that are superior to Caltech 101 and LabelMe.
Classification and Screening of Recognition Protein Complexes with Genetic Programming

A protein complex is either transient or obligate. In the organisms, proteins recognize each other with their binding sites and become transient protein complexes. Proteins perform their functions through protein-protein recognition. In this paper, we train a model by genetic programming with physicochemical properties information of the binding sites. The model classifies and screens the proteins of recognition interactions. The model achieves an average classification accuracy of 75%. For screening, given a protein with concave binding site and a database of proteins with convex binding site, from the database we retrieve a small set of proteins in which one of them recognizes with the query protein. In average, 65% of proteins in the database are screened out.  Protein-protein recognition, Genetic programming, Classification and screening
End user mobile task automation using multimodal programming by demonstration

Conversational agents are often used to perform tasks on smartphones, but existing conversational agents are limited in capabilities and lack of customizability. My work explores using the programming-by-demonstration approach to enable end users to program new tasks for conversational agents by demonstrating using the familiar graphical user interfaces of third-party apps. I propose to use a multi-modal (demonstration and verbal instruction) interface to support generalization, editing, error handling as well as creating control structures in creating such smartphone automation.
Face recognition method based on virtual sample

Research the small sample face recognition approach. A small sample statistics face recognition approach based on virtual sample is presented. In this method, prototype faces are used to create virtual sample to extend the sample set, independent component analysis (ICA) algorithm is used to reduce dimensions and extract features, and then Bayesian expectation maximisation algorithm is adopted to learn the parameters of condition probability function of class features. A Bayes classifier is constructed to recognize test samples. Experience result shows the approach can improve face recognize rate of small sample efficiently.
Multiple-access interference in relation to time-hopping correlation properties in multiple-access UWB system

Based on the analysis of the properties of time-hopping (TH) sequences, this paper investigates the multiple-access interference (MAI) in multiple-access ultra-wideband (UWB) wireless communication system. By the transformation of signal model, the hopping format is described in terms of binary TH sequences. The relation between MAI and TH correlation function are formulated. The bit error rate (BER) performance in the presence of MAI is evaluated by both theoretical analysis and computer simulations.
Actively Mode-Locked Fiber Optical Parametric Oscillator

We demonstrate active mode locking of a fiber optical parametric oscillator (FOPO). By inserting an amplitude modulator (AM) into a continuous-wave pumped FOPO loop, intracavity loss is varied periodically. When the modulation frequency of AM coincides with the harmonics of longitudinal modes spacing of the loop cavity, stable 10-GHz pulse train can be obtained. By adjusting the intracavity filter, the wavelength of the pulse train can be tuned over 21 nm.
Proper Reparametrization of Rational Ruled Surface

In this paper, we present a proper reparametrization algorithm for rational ruled surfaces. That is, for an improper rational parametrization of a ruled surface, we construct a proper rational parametrization for the same surface. The algorithm consists of three steps. We first reparametrize the improper rational parametrization caused by improper supports. Then the improper rational parametrization is transformed to a new one which is proper in one of the parameters. Finally, the problem is reduced to the proper reparametrization of planar rational algebraic curves.
Developmental pathway and protein changes of somatic embryogenesis in E. sativa mill

Somatic embryos were induced from cotyledon explants cultured on MS medium supplemented with 1.0 mg·L−1 2,4-D. Morphological and protein changes were performed aiming at the developmental process of somatic embryogenesis of E. sativa. The observation revealed that the embryos pass through the characteristic globular, heart, torpedo, and cotyledon stages. The developmental process of the somatic embryo is similar to that of the zygotic embryo. The results showed there was a decrease in the protein content between the 0 and 14 d of culture on medium with 1.0 mg·L−1 2, 4-D. The protein content of somatic embryos grown on N6 hormone-free medium was distinctly higher than that on the medium supplemented with 1.0 mg·L−1 2,4-D. SDS-PAGE of protein patterns showed specific protein bands with changed staining density. The content of 18 KD proteins was decreased after culture on medium with 1.0 mg·L−1 2, 4-D. On N6 hormone-free medium, protein bands of 65 KD, 68 KD and 70 KD were observed.
Mechanism and analysis of structural color in two typical butterfly scales

In this paper, the microstructures of two kinds of butterfly scales, Morpho type and Urania type, are obtained using scanning electron microscope (SEM) and transmission electron microscope (TEM). Three structure models of the first type are constructed and their corresponding reflectivity spectra are simulated using finite-difference time-domain (FDTD) method. The reflectivity spectrum of 3-D model and 2-D tower model are closer in agreement with the measurement result than the multi-layer model with equal branch and stem. For the second type scale, the structural colors mainly come from the sculpted multi-layer structure, and the 2-D planar multi-layer model can well explain the mechanism of structural colors.
PandaSearch: A fine-grained academic search engine for research documents

In the world of academia, research documents enable the sharing and dissemination of scientific discoveries. During these “big data” times, academic search engines are widely used to find the relevant research documents. Considering the domain of computer science, a researcher often inputs a query with a specific goal to find an algorithm or a theorem. However, to this date, the return result of most search engines is just as a list of related papers. Users have to browse the results, download the interesting papers and look for the desired information, which is obviously laborious and inefficient. In this paper, we present a novel academic search system, called PandaSearch, that returns the results with a fine-grained interface, where the results are well organized by different categories, such as definitions, theorems, lemmas, algorithms and figures. The key technical challenges in our system include the automatic identification and extraction of different parts in a research document, the discovery of the main topic phrases for a definition or a theorem, and the recommendation of related definitions or figures to elegantly satisfy the search intention of users. Based on this, we have built a user friendly search interface for users to conveniently explore the documents, and find the relevant information.
Secure Image Delivery Scheme Using Poisson Editing

We propose a secure image delivery scheme which can protect privacy of the secret region in sending image. In the scheme, the bits of the chosen secret region are first reversibly embedded into non-protection region. The secret region is then concealed or substituted with other meaningful content by our modified Poisson editing method, in which twice Laplacian operator is used to achieve better seamless effect. The protected image after editing can be delivered in channels securely. The attacker can’t obtain the real content of the image without the keys. Experiments are carried out to show effectiveness and security of the scheme.