nils-herrmann/clean_scirepeval huggingface dataset:
A new method for DOA and amplitude joint estimation

A new technology for spatially localizing acoustic backscatter called VS-CAATI (Virtual and Sub-array Computed Angle-of-Arrival Transient Imaging) is proposed in this paper. The new technology can jointly estimate DOA and amplitude at the same time. The principles underlying VS-CAATI, which are based on virtual array processing and sub-array technology, are presented in detail in the paper. VS-CAATI is easily implemented and offers dramatic improvements over conventional CAATI. Furthermore, this technique is superior to some other DOA estimation methods.
Silk-fibroin peptide hydrogel for 3D culture of chondrocytes in vitro

A peptide hydrogel for in vitro culture of chondrocytes was prepared and investigated based on the designed and synthesised peptide SGGAGGAGGAGGAGGS. Chondrocytes cultured in the peptide hydrogels were observed for changes of morphology characteristic, and the chondrocyte-seeded peptide hydrogels at the designed time point were obtained and the analysis of DNA content, histological staining and immuno-histochemistry was carried out. Our results suggested that the peptide hydrogel may induce the synthesis of collagen type II and glycosaminoglycans (GAGs) in the chondrocytes. Results of GAG and collagen type II in the chondrocytes-hydrogel composites suggested that significant increases are observed with the increasing culture time, which became more intense compared to those of the control, respectively. Analysis of the extracellular matrix molecules also showed that the peptide hydrogel may maintain the phenotypes of chondrocytes during the culture time of 21 days. These findings suggested that this hydrogel containing designed peptide might be used for a potential 3D-scaffold of tissue engineering cartilage.
A unidirectional bullet conformal monopole antenna designed for impulse radar system

A simple unidirectional bullet conformal monopole antenna designed for impulse radar system is presented in this paper. The antenna is used to radiate first derivative Gaussian impulse with peak-peak width of 200 ps. To adapt to the bullet structure and realize unidirectional radiation pattern, impedance loaded is adopted to achieve UWB impedance match and unidirectional radiation. The impedance band width is 0.67 GHz-2.15 GHz for S11 ≤ -10 dB. The time domain and unidirectional radiation characteristics are studied by simulation and experiment. The simulation and experiment results are presented.
Finite-horizon bounded H ∞ synchronisation and state estimation for discrete-time complex networks: local performance analysis

This study is concerned with the finite-horizon bounded H ∞ synchronisation and state estimation for the discrete-time complex networks with missing measurements based on the local performance analysis. First, a new local description of the bounded H ∞ synchronisation performance index is proposed, which considers only the synchronisation errors among neighbours. In addition, a more general sector-bounded condition is presented, where the parameter matrices are different for different node. Next, by establishing the vector dissipativity-like for the complex network dynamics, the H ∞ synchronisation criterion is derived in term of the locally coupled conditions for each node. These conditions implemented in a cooperative manner can judge whether the complex network reaches synchronisation. Similarly, the existence conditions for the estimator on each node are obtained, and then the estimator parameters are designed via the recursive linear matrix inequalities. Notably, these conditions on each node by cooperation among neighbours can achieve the desirable performance index. The distinctive features of the authors' algorithms are low complexity, scalability, and distributed execution. At last, two numerical examples are utilised to verify the effectiveness and applicability of the proposed algorithms.
An improved wall following method for escaping from local minimum in artificial potential field based path planning

This paper surveys the utilization of the wall following concept for path planning in mobile robotics and proposes an improved wall following method for escaping from local minimum encountered by the artificial potential field (APF) method used in real-time path planning. In the new algorithm, more reliable switching conditions are designed to guarantee the success of escape. Moreover, memory information of key points is incorporated in to enhance the robot's capability of making decision. It can be applied effectively in some more complicated unknown environments in which some previous wall following methods are proved to be inefficient or invalid. Simulation studies have been carried out for analyzing the memory information and verify the validity of the proposed method.
Transductive Inference with Hierarchical Clustering for Video Annotation

In this paper, we present a novel framework for video semantic detection based on transductive inference and hierarchical clustering, which directly focuses on predicting the available samples in a current unlabeled pool, instead of trying to build a classifier workable for any unavailable data. In this framework, a number of hierarchical clustering results are constructed from the entire video dataset containing both labeled and unlabeled examples. We aim to make the clusters as pure as possible, i.e., samples in a same cluster mostly have a same label. To further purify these hierarchical clustering results, an EM based cluster-tuning algorithm is iteratively employed. Based on these clustering results, several hypotheses are generated by probability voting among labeled samples in the obtained clusters. From these hypotheses, one of them is chosen according to the Vapnik combined bound, and it is then applied to predict the labels of unlabeled samples. This selected transductive hypothesis, which is only interested in predicting the available unlabeled samples in test set rather than producing a general classifier like inductive inference learning, exploits the structure and distribution of the unlabeled pool to achieve a minimal test error bound. Thus it can have better generalization ability for video annotation both theoretically and experimentally. This is also shown by our experiment results.
An approach to dynamic traveling salesman problem

Most researches in evolutionary computation focus on the optimization of static and no-change problems. Many real world optimization problems however are actually dynamic, and optimization methods capable of continuously adapting the solution to a changing environment are needed. In this paper, we introduce an approach to solving the dynamic TSP. A dynamic TSP is harder than a general TSP, which is a NP-hard problem, because the city number and the cost matrix of a dynamic TSP are time varying. We propose an algorithm to solve the dynamic TSP problem, which is the hybrid of EN and inver-over algorithm. From the results of the experiment, we conclude this algorithm is effective.
cDNA, genomic sequence cloning and sequence analysis of ribosomal protein L18A gene( RPL18A ) from the Giant Panda (Ailuropoda melanoleuca)

RPL18A is a component of the 60S large ribosomal subunit encoded by RPL18A gene, which plays an important role in ribosome. To explore the structure characteristic of ribosomal protein L18 (RPL18A) gene of the Giant Panda (Ailuropoda melanoleuca) and the differences with other species reported,we have designed primers which based on the already-known information of RPL18A gene. Then, the cDNA and the genomic sequence of RPL18A were cloned successfully from the Giant Panda using RT-PCR technology respectively, followed by sequencing and analyzing. The result indicated that the cDNA fragment of the RPL18A cloned from Giant Panda is 571 bp in size, containing an open reading frame of 531bp, and deduced protein was composed of 176 amino acids with an estimated molecular weight of 20.76 kD and PI of 11.42. The length of the genomic sequence is 1999bp, which was found to possess four exons and three introns. Alignment analysis indicated that the nucleotide sequence and the deduced amino acid sequence are highly conserved to other four mammals studied, including Homo sapiens, Mus musculus, Rattus norvegicus and Bos taurus. The homologies for nucleotide sequences of Giant Panda RPL18A with that of these species are 91.53%, 92.66%, 89.27% and 89.83%, respectively, while the homologies for amino acid sequences are 98.86%, 98.86%, 98.30% and 98.30%, respectively. Topology prediction showed there are 4 different patterns of functional sites in the RPL18A protein of the Giant Panda. The cDNA and the genomic sequence of RPL18A were cloned successfully from the Giant Panda in this research, which provided scientific material to enrich and improve the mammals RPL18A gene database.
A Wireless Video Framework Based on RCPC and FEC

A framework of video transmissions over 3G wireless channels based on RCPC and FEC is proposed, which can cope with the bit error and packet loss occurred in transmission. The bit error model and packet loss model are used to estimate the bit error rate and packet loss rate, with which the RCPC code and FEC code is adjusted, and the datum are divided into the same length packet to be transmitted. The datum are unpacked, FEC coded and Viterbi decoded at the receiving terminal, then transmitted to video decoder to rebuild video signal, while some statistical informations including data packet loss rate, bit error rate, etc, are recorded in a network monitoring module at the receiving terminal, which are fed back to the sending terminal to control coding rate. The experiments show that the transmission framework can improve the received video quality in 3G wireless channels.
Extraction of image semantic features with spatial-range mean shift clustering algorithm

In recent years, the Bag-of-visual Words image representation has led to many significant results in visual object recognition and categorization. However, experiments show that the unsupervised clustering of primitive visual features tends to result in the limited discriminative ability of the visual codebook, since it does not take the spatial relationship between visual primitives into consideration. This paper aims at generating descriptive higher-order semantic features, which are extracted from visual word sets clustered by spatial-range mean shift and are a better representation for images. This method first uses mean shift algorithm to cluster visual words for an image from the spatial and color space, then uses FP-growth algorithm to mine the meaningful spatially concurrent groups of visual words in all images and regards the high frequency visual word combinations which can represent parts of objects as semantic features. The experiments on Caltech 101 dataset demonstrate that the proposed higher-order semantic features can achieve good results.
Facile synthesis of Pt/TiO2 nanotube arrays: A reusable platform for direct methanol fuel cell

Uniform Pt nanoparticles (diameter ∼5 nm) are decorated on the TiO2 nanotube arrays (TiNT) by a two-step photo irradiation method. The resulting hybrid nanotube arrays show an excellent catalytic activity for methanol electrooxidation. The anodic current density of methanol electrooxidation reaches 21 mA/cm2 with 1 mg Pt loading (previous methods typically reach ∼10 mA/cm2). The photocatalytic properties of TiO2 make the Pt/TiNT arrays reusable after a short UV treatment, and the electrooxidation current density of Pt/TiNT after UV-cleaning can almost fully be re-established.
Ohmic Contact to n-Type Ge With Compositional W Nitride

By varying composition of the WNx film electrode, modulation of the Schottky barrier height (SBH) of WNx/n-Ge contacts was demonstrated. The effective SBH decreased from 0.52 eV for W/n-Ge contact to 0.47, 0.42, and 0.39 eV for WNx/n-Ge contacts with various nitrogen x components, which were 0.06, 0.09, and 0.15, respectively. Ohmic contact property was achieved when the nitrogen component in WNx reached x = 0.19. As an explanation, an electrical potential caused by the N-Ge dipoles layer across the WNx/n-Ge contact interface is proposed to alleviate the Fermi-level pinning effect.
Forecasting of corporation cash flow from operating activity: Using grey topological model

Corporation cash flow from operating activity has the characteristics of small sample scale, severe fluctuation and more influencing factors, which could not meet the requirements of normal forecasting model on sample's scale and distribution. In this paper, operating cash flow forecasting model is built using grey topological predicting approach, which could overcome the restriction of normal forecasting model on sample's characteristics. Empirical test showed that grey topological predicting model can forecast the operating cash flow in mid-term with better accuracy.
Distribution network reconfiguration with distributed power based on genetic algorithm

This paper focuses on distributed power(DG) impact on distribution network and distribution network reconfiguration algorithms. First the article describes the impact of DG on distribution networks failure reconfiguration, Then set reconfiguration evaluation model based on Wind turbine as a specific DG, based on the above, adjust the fitness function structure of Improved genetic algorithm. Meanwhile, this selection operator using the tournament selection method combined with elitist selection method approach in order to make the Selection operator of genetic algorithm focus on the fitness value compared and keep high fitness individuals. Finally, test examples show that the algorithm is reasonable and effective.
RCS measurement at terahertz waves for cylinders with different surface roughness

The radar cross-section (RCS) measurements for cylinders with different surface roughness have performed in the terahertz bands. The terahertz radar system has 220 and 440 GHz carrier frequencies. It is a solid-state system whose base band signal is generated by a phasor network analyser. The original recorded data are calibrated by the results of the smooth surface cylinder. These calibrated RCS results are compared with calculated results. The experiments suggested that targets with the rough surface will provide complicated scattering in terahertz. The results of this experiment can prove that the surface roughness of the target has a certain impact on RCS measurement results in the terahertz band.
A Fast Evolutionary Algorithm for Robot Path Planning

Robot path planning is a NP problem, traditional optimization methods are not very effective to it, which are easy to plunge into local minimum. In this paper, we devise an evolutionary algorithm to solve the robot path planning problems based on some new genetic operators.The problems in algorithm design mainly considered are how to select the evolutionary operators, how to avoid the solutions falling into the local optimal and how to enhance the efficiency of the evolution process and so on. The new algorithm has been carried on the operation to the test examples. The experiment results indicated that the new algorithm is efficiency for solving the robot path planning problems and the best path usually can be found.
Research on the sensor calibration of pressure transmitter based on the least square method

The accuracy of capacitance pressure sensor is easily disturbed by work environment. In order to improve the accuracy of pressure sensor, the paper researches on the sensor calibration of pressure transmitter based on the least square method. The measurement circuit is designed to convert the output of sensor from the capacitance value to the cycle value. Working quadric surface is fitted with the value of environmental temperature, the output of pressure sensor and setting pressure by the least square method. The pressure transmitters can accurately measure at different temperatures by the experiment.
Term recognition using Conditional Random fields

A machine learning framework, Conditional Random fields (CRF), is constructed in this study, which exploits syntactic information to recognize biomedical terms. Features used in this CRF framework focus on syntactic information in different levels, including parent nodes, syntactic functions, syntactic paths and term ratios. A series of experiments have been done to study the effects of training sizes, general term recognition and novel term recognition. The experiment results show that features as syntactic paths and term ratios can achieve good precision of term recognition, including both general terms and novel terms. However, the recall of novel term recognition is still unsatisfactory, which calls for more effective features to be used. All in all, as this research studies in depth the uses of some unique syntactic features, it is innovative in respect of constructing machine learning based term recognition system.
A New Sub-Pixel Subdivision Location Algorithm for Star Image

A new sub-pixel subdivision location algorithm for estimating the position of the star on the focal plane array is proposed. An analytical study of the optics theoretical point spread functions is presented and it is shown that the star intensity distribution is close to the Gaussian point spread function model. Based on the numerical model of the star, a Gaussian curved fitting algorithm for centroiding location of the star image is devised. Since behavior of the new sub-pixel location algorithms is influenced by the size of Gaussian window, an optimal size of calculating window is given out. In order to reduce the negative effects of noise, a weighted scheme for centroiding is considered, and it improves the accuracy of extracting the star position on the focal plane array. The simulation results show that the accuracy of the star position can reach 1/150 pixel, and the optimal size of window for calculating is 5×5, which is under the 10% star magnitude noise. Star trackers determine the attitude of the spacecraft from some reference stars in the celestial sphere. The process of determination attitude can be divided into four steps. Firstly, the star tracker takes the star photo using the photo detectors (CCD or CMOS) in an arbitrary direction. Secondly, the microprocessor operates the image processing in the field of view (FOV) and uses the location algorithm to calculate the stars' centroid coordinates. Thirdly, star coordinates are put into the star pattern recognition algorithm and star constellations are matched in the FOV to a star catalogue covering the entire firmament. Finally, this information is adopted to calculate the attitude matrix and attitude angle and rate are delivered to estimate to the attitude control system. The second part of the process is a most crucial step, because the errors in centroid estimation dictate the overall pointing accuracy of the star tracker. A number of methods are available for estimating the centroid locations. The center of mass (COM) and some modifier algorithms based on the COM are the most commonly used techniques owning to its simplicity and robustness(3). But these algorithms do not consider the star spread numerical model and have relative low accuracy. A new Gaussian Fitting algorithm is proposed in this research. It takes into account the point spread function model and while computationally more intensive is more accuracy than the center of mass. Moreover, we use a weighted scheme to reduce the negative effects of noise, and give out the optimal size of window for calculating under the 10% star magnitude noise.
Femoral Fracture Risk Assessment after Intensity Modulated Radiation Therapy (IMRT) for the Treatment of Soft Tissue Sarcoma Using a Novel Mathematical Model

Intensity modulated radiation therapy (IMRT) is often used for the treatment of soft tissue sarcoma. Due to high radiation doses, many patients have high risk of suffering from a femoral bone fracture sometime following the IMRT treatment. The most common type of radiation treatment-related fracture is a stress fracture. The fracture risk rate may be as high as 24% in sarcoma patients who have undergone periosteal stripping and received chemotherapy. Thus, it is necessary to be able to identify those patients with high risk for IMRT treatment-related bone fracture. In this paper, we will first present IMRT treatment planning techniques. We will then discuss how bone system changes their stiffness and how the fracture risk develops after a certain period of time post radiation treatment. Finally, we will present our latest data on the femoral bone fracture risk factor assessment for patients with soft tissue sarcoma following IMRT treatment. We have developed a novel mathematical model of trabecular bone composed of a disordered cubic network. Based on our preliminary data, we believe that this new mathematical model could shed new light on the relationship between the femoral bone fracture risk factor and the radiation dose delivered by an IMRT plan and provide a valuable prognostic tool for these high-risk patients
PAPDroid: Personalization Awareness Privacy Protection in Android

With more and more Android apps appearing, personalization functions have been the focus of the apps' competition. However, the current implementations of personalization mainly rely on gathering and analyzing users' sensitive information, which may not only break the good ecological environment but also threaten users' privacy security. To address the issue, this paper proposes an architecture, called PAPDroid, which can support applications' personalization functions in Android according to users' personae and uses the concept of profile to prevent sensitive information from being stolen. Furthermore, we provide a privacy protection service for legacy apps which can enforce different protection policies according to the risk level of apps. All of these cooperate to provide personalization awareness privacy protection in Android. Experiments show that our system is feasible and effective.
Body Surface Context: A New Robust Feature for Action Recognition From Depth Videos

Human action recognition in videos is useful for many applications. However, there still exist huge challenges in real applications due to the variations in the appearance, lighting condition and viewing angle, of the subjects. In this consideration, depth data have advantages over red, green, blue (RGB) data because of their spatial information about the distance between object and viewpoint. Unlike existing works, we utilize the 3-D point cloud, which contains points in the 3-D real-world coordinate system to represent the external surface of human body. Specifically, we propose a new robust feature, the body surface context (BSC), by describing the distribution of relative locations of the neighbors for a reference point in the point cloud in a compact and descriptive way. The BSC encodes the cylindrical angular of the difference vector based on the characteristics of human body, which increases the descriptiveness and discriminability of the feature. As the BSC is an approximate object-centered feature, it is robust to transformations including translations and rotations, which are very common in real applications. Furthermore, we propose three schemes to represent human actions based on the new feature, including the skeleton-based scheme, the random-reference-point scheme, and the spatial-temporal scheme. In addition, to evaluate the proposed feature, we construct a human action dataset by a depth camera. Experiments on three datasets demonstrate that the proposed feature outperforms RGB-based features and other existing depth-based features, which validates that the BSC feature is promising in the field of human action recognition.