nils-herrmann/clean_scirepeval huggingface dataset:
Optimal learning algorithm in bidirectional associative memories

The authors present an optimal learning algorithm in a discrete bidirectional associative memory (BAM). According to the cost function that measures the goodness of BAM, the authors transform the problem of specifying the connection matrix into a global optimization, solved by a gradient descent method. This learning algorithm guarantees to store all trained patterns whenever it is allowable. Experimental results are reported to demonstrate the power of the algorithm.<<ETX>>
Analysis of sports statistics via graph-signal smoothness prior

Since teams in a sporting league compete head-to-head according to a structured schedule, it is natural to interpret statistics emanating from competitions as signals on a graph modeling similarities among competing entities. In this paper, we analyse available sports statistics to predict game outcomes from a graph signal processing (GSP) perspective: GSP tools are used to remove (denoise) unwanted variability to reveal underlying predictable trends, and to interpolate missing data-predicted game outcomes in terms of point differential. First, we construct a graph for the desired graph-signal (point differential for every team pair): for an N-team league, we construct N subgraphs Gj, each containing N - 1 nodes representing teams competing against opponent j. We next assign weight to each intra-subgraph edge based on similarity in observed statistics (e.g., total points scored, assists, etc) of the two connecting nodes (teams). We then connect nodes in different subgraphs representing the same teams, where the weight of an inter-subgraph edge connecting nodes in subgraphs Gk and Gi now reflects the similarity between opponents k and l. Finally, assuming a graph-signal smoothness prior, we compute the desired graph-signal on the constructed graph via an alternating convex programming procedure. Experimental results show that our graph-based scheme achieves better prediction than a competing k-nearest neighbor (kNN) scheme.
A static contact angle algorithm and its application to hydrophobicity measurement in silicone rubber corona aging test

To improve the accuracy of the static contact angle measurement for the corona aged silicone rubber, a static contact angle algorithm based on the least-squares circle fitting is presented, and the least-squares model, the optimization algorithm, the determination of initial values and the convergence criterion are introduced in a systematic way and at the same time the best selections are given by the systematical comparison. With regards to the numerically generated water drop profiles and the water drop images of the corona aged silicone rubber, the accuracy and the computation time of the goniometry, the θ/2 method, the circle fitting algorithm and the ADSA-P (axisymmetric drop shape analysis-profile) algorithm are analyzed and compared. The influence of the water drop volume/contact angle/profile point number on the accuracy of the circle fitting algorithm is analyzed. The results reveal that the contact angle errors increase with the water drop volume/contact angle/noise. The goniometry has the characteristics of relative low accuracy, expensive computation and large workload. The computed result of the circle fitting algorithm is very close to that of the θ/2 method, and both the two methods have relative less computation time. In the meantime, the fitted water drop edges can be obtained by the circle fitting algorithm, which can be taken as an indicator of the computation accuracy, while the θ/2 method cannot give such indicator. The ADSA-P algorithm has high accuracy and high computational complexity, and is very easy to be interfered by the noise. Therefore, it is not suited to the case of small contact angle and volume, and high interference. The circle fitting algorithm has less computation time, and is intrinsically resistant to noise. Therefore, for the case of small contact angle and volume, not the ADSA-P algorithm but the circle fitting algorithm should be selected. Therefore, the circle fitting algorithm is selected to measure the static contact angle of the corona aged silicone rubber. The critical water drop volumes and the critical contact angles of different liquids are given, which can be guaranteed for high accuracy of the static contact angle measurement.
Discussion on problems of single conductor small corona cage's design

Corona cage was an important research method to research corona effect. As design corona cage, the distance form cage wall to conductor, critical distance of AC charge, and corona cage length, and these questions should be resolved. Corona onset voltage, breakdown voltages were important coefficients to research conductor corona characteristics, and this was significant for transmission line design. To a certain diameter conductor, the diameter of corona cage should be small enough to make the conductor corona onset at a low voltage. Simultaneously, the gap between cage wall and conductor should be lager enough, so as to make breakdown voltage 50% higher than corona onset voltage. The critical distance of AC charge was calculated, and the length of corona cage was selected. The cross-section side width of the corona cage was 1.8m × 1.8m., and the measurement length of the cage was 3m, both of the protection length were 0.5m respectively. As in test, conductors were placed in at the center of the cage, and corona loss measurement system was adopted to measure conductors corona loss. Corona loss of conductor LGJ-630/45, LGJ-400/35, LGJ-300/40 were measured, and an excellent test effect was obtained.
Synthesis and characterization of highly ordered TiO2 nanotube arrays

Highly-ordered TiO2 nanotube arrays (TNA) by anodizing Ti foil were carried out using a slightly modified electrochemical process. The parameters such as anodization potentials and duration have been varied in order to fabricate the specific length and diameter of TNA. The morphologies of TNA were characterized by field emission scanning electron microscope (Hitachi S-4100 FE-SEM). The crystalline phase and structure were analyzed using X-ray diffraction (Rigaku, XRD). The processing anodic current density with time was recorded by Keithley 2400. The photocurrents induced by UV-light were characterized by CHI 611. The performance of hydrogen production from photoelectrocatalytic effect of larger diameter TNA is found to be higher than the smaller diameter TNA. Base on the microstructure and calculation, we confirmed that larger diameter TNA do exhibit higher surface area.
Analysis of independent director’s behaviour in China’s listed companies based on evolutionary game model

The behaviours of independent directors and managers of Chinapsilas listed companies is analysed based on evolutionary game theory. The results show that only under the condition that the incentive is greater than the cost of supervision for independent directors, such optimal evolutionary stable strategy as independent directors choose ldquosuperviserdquo, enterprise managers choose ldquonot cheatrdquo may exist. The incentive mechanism is not sound, and independent status can not be guaranteed. It may be the main reasons for independent directorspsila nonfeasance in Chinapsilas listed companies.
Link scientific publications using linked data

Scientific publication management services are changing drastically. On the one hand, researchers demand intelligent search services to discover scientific publications. On the other hand, publishers need to incorporate semantic information to better organize their digital assets and make publications more discoverable. For this purpose, we investigate how to manage scientific publications using Linked Data and introduce FELinker, an entity linking component that links scientific publications with DBPedia. In particular, this paper introduces advantages of linking scientific publications with Linked Data, discusses major challenges, and outlines the proposed method. Experiment shows the proposed method could get promising performance in scientific publication linkage.
Study on fault diagnosis for power transformer based on cloud matter element analysis principle and DGA

Dissolved gas-in-oil analysis (DGA) is an important method to find the hidden or incipient insulation faults of oil-immersed power transformer. Matter element theory was employed to research the fault diagnosis of transformer with qualitative and quantity advantages. However, the method did not consider the uncertain essence of the fault diagnosis of transformer. And in the fact, there were two uncertain characteristic in it, random and fuzzy. Hence a new fault diagnosis method is presented in this paper. The method has two advantages of considering two uncertain characteristic and realizing fault diagnosis qualitatively and quantitatively based on cloud model and matter element theory. By building the cloud matter element models of transformer fault diagnosis and calculating the correlation function of feature matter element models and standard ones, fault modes of transformer are identified effectively. Then, the results of examples research indicate the method is effective.
UHV AC corona loss measurement and analysis under rain

Transmission line corona loss research is one of the critical technologies of 1000kV UHV transmission and transformation engineering. Transmission line corona loss relates with many factors of climate, and rainfall rate effects corona loss distinctly very much. By means of UHV AC single circuit test line corona loss monitoring and UHV corona cage conductor corona loss measurement, this paper researched the effect of rainfall rates to UHV AC single circuit transmission line's corona loss. This paper applied corona loss monitoring system to monitor corona loss of UHV single circuit test line, and obtained corona loss monitoring data in light rain, moderate rain, and heavy rain conditions. Analyze corona loss test results. Corona loss value in light rain, moderate rain, and heavy rain conditions are obtained. The results show that, rain has an obvious influence on corona loss of the line, at the beginning of raining, corona loss increases quickly, after rain, corona loss decreases with drying of the conductor. Decay time is related with surface field strength, wind speed, air humidity, temperature and other factors. When rainfall rate is low, corona loss increases fast with the increase of the rainfall rate. With the increase of the rainfall rate, corona loss grows slowly. When rainfall rate increases to some level, corona loss stop growing.
Initialization Algorithm Based on SNIR Model for Wireless Sensor Networks

A newly deployed sensor network is unstructured and sensor nodes at the beginning are in the "blind" state, which have almost no knowledge about the topology of the network. The most urgent and important thing for deployment of sensor networks is to set up a coarse structure. In this paper, a practical algorithm to initialize the network and select cluster leader nodes is presented. The algorithm is analyzed on SNIR model, which addressed the specific characteristics in the deployment of wireless sensor network, such as nodes do not feature a reliable collision detection mechanism and may wake up asynchronously, and especially co-channel interference effect on transmission during initialization phase. A novel concept of interference-tolerant neighbor nodes is proposed to guarantee efficiency of the algorithm. The simulation result shows even in the restrict applicable model, clustering can be completed successfully
VxWorks porting based on MPC8313E hardware platform

This paper implements the porting of VxWorks6.6 based on MPC8313E hardware platform which is associated with workbench3.0 and JediView tools for developing and debugging. It analyses the process of the driver of time and serial port based on VxBus driver model of VxWorks. In addition, the authors summarize some experience of system porting and real-time debugging that will be helpful for system porting of other hardware platforms.
High Sensitive Micro-Displacement Sensor Based on M-Z Interferometer by a Bowknot Type Taper

A simple, compact, and high sensitive optical fiber Mach-Zehnder interferometer (MZI) based micro-displacement sensor is presented. The MZI is fabricated by a core offset connecting of two single mode fibers and bowknot-type taper. The shifts of the MZI transmission spectrum correspond to the micro-displacements on the cross section of the core offset. For the micro-displacement ranging from 0 to 13 μm, the proposed sensor shows a high sensitivity of -1.89 dB/μm, which is almost 787 times higher than that of the current similar existing micro-displacement sensor. In addition by using the intensity demodulation method, the proposed sensor can overcome the temperature and displacement cross-sensitivity effects.
An Exploratory Study of API Usage Examples on the Web

Usage examples are helpful for programmers learning to use APIs from third-party frameworks or libraries. There are lots of usage examples scattered in web pages on the Web, such as tutorials, blogs, and forums. A few researches have proposed approaches to leveraging these usage examples to improve programming. However, due to the lack of comprehensive understanding on the current situation of usage examples on the web, the work is still at the very beginning. Many concerns are reserved, for instance, how many usage examples can be found on the Web? how well do such examples support programmers on earth? what factors have impact on these examples' usability? In this paper, we conducted an exploratory study of usage examples on the web, including their distribution, characteristics like content style, correctness, and complexity, as well as their correlations. Through the study, we obtain some insight of how to facilitate utilization of usage examples on the web and what mechanisms could be provided. Possible research directions and problems are proposed at the end.
Simultaneous Localization and Mapping for Mobile Robots Using Sonar Range Finder and Monocular Vision

Localization and map building are two essential tasks for an autonomous mobile robot's indoor navigation without a prior map. This paper describes a mobile robot system designed for simultaneous localization and mapping (SLAM) for an autonomous mobile robot in an indoor environment. Due to variant sensor modeling for sonar range finder and CCD camera, weighted least square fitting and Canny operator are used to extract certain two-dimensional environmental features and vertical edges respectively. Using Kalman filtering (KF) to localization and grid map building simultaneously are also presented. When implemented on a Zixing mobile robot produced by Harbin Institute of Technology (Weihai), the localization technique correctly localized the robot while exploring and mapping.
Subpixel-Based Image Scaling for Grid-like Subpixel Arrangements: A Generalized Continuous-Domain Analysis Model.

Subpixel-based image scaling can improve the apparent resolution of displayed images by controlling individual subpixels rather than whole pixels. However, improved luminance resolution brings chrominance distortion, making it crucial to suppress color error while maintaining sharpness. Moreover, it is challenging to develop a scheme that is applicable for various subpixel arrangements and for arbitrary scaling factors. In this paper, we address the aforementioned issues by proposing a generalized continuous-domain analysis model, which considers the low-pass nature of the human visual system (HVS). Specifically, given a discrete image and a grid-like subpixel arrangement, the signal perceived by the HVS is modeled as a 2D continuous image. Minimizing the difference between the perceived image and the continuous target image leads to the proposed scheme, which we call continuous-domain analysis for subpixel-based scaling (CASS). To eliminate the ringing artifacts caused by the ideal low-pass filtering in CASS, we propose an improved scheme, which we call CASS with Laplacian-of-Gaussian filtering. Experiments show that the proposed methods provide sharp images with negligible color fringing artifacts. Our methods are comparable with the state-of-the-art methods when applied on the RGB stripe arrangement, and outperform existing methods when applied on other subpixel arrangements.
A design of large space automatic cleaning robot with omni-directional wheels

The methods for a large space cleaning task are usually using human-operated cleaning vehicle or brooms, even in the period of mid-night. In addition to hiring a large amount of people (usually senior), the over-work issue during mid-night period is another concern to the cleaning company. Therefore, an omni-directional mechanism/robot suitable for mid-night cleaning period in a large space is proposed; the hardware core is the Arduino microcontroller in association with TETRIX mechanism and sensors. Intelligent obstacle avoidance is fulfilled via sensors while the path planning is throughout the use of fuzzy control.
The Study on Mathematical Model of Urban Land Subsidence Based on Statistical Analysis

This paper analyzes the main reasons which cause urban land subsidence, and discusses the mechanisms of the effects caused by building loading and the change of groundwater level. Using the theory of statistical analysis, mathematical model of land subsidence is built, and the effect of the model is also validated by practical data. The analysis results show the fitting effect is good and the model has highly practical value. Urban land subsidence is a common and growing geological phenomena, and a chronic caused by accumulating day by day. It is closely related with urban engineering construction and residents' lives and production activities, and it has characteristics such as generating slowly, large seat of settlement, complex genetic mechanism, no significant influence initially, great difficulty in prevention and treatment, etc. At present, the problem of land subsidence is very serious in America, Japan, Mexico and Italy, and many cities in China are also suffering form it. Therefore, land subsidence has become an important research subject now in the whole world. In China, with the faster development of urbanization, the gradually conspicuous damages of land subsidence seriously disturb the normal development of urban engineering construction and daily life of inhabitants. Land subsidence is one of the most common geologic hazards in our plain region, and the characteristics of it determine its great harm. Besides, land subsidence is a slow process which will be ignored easily. If we don't pay attention to it and don't make renovating and developing shoulder to shoulder, it will very hard for us to make up for the outcome brought about by settlement. To analyze and forecast the status of land subsidence scientifically, accurately and duly is particularly important to the sustainable urban development. For this reason, building an effective mathematical model of land subsidence has become an urgent task. Land subsidence monitoring is pre-requisite during the management of land subsidence, and it is an important mean to protect people's lives and property, reduce economic loss and evaluate urban development. The analysis of monitoring data provide scientific basis for evaluating urban environment geology. Therefore, with the urban development, land subsidence must be monitored in real time to collect first- hand information which will be analyzed scientifically to discover the potential safety hazard of surface. And this is beneficial for government to draw up control measures and ensure the process of urban modernization.
An improvement of the shortest path algorithm based on Dijkstra algorithm

In this paper, based on the Dijkstra algorithm and its past improvements, a new improvement is proposed by considering the case of the nodes, reforming the feature matrix of precursor node, and adding a shortest path tree. The algorithm has its adantages on both reducing the number of repeated operations and reading the shortest path and the path length from the startpoint to all the other nodes by the shortest path tree or by the feature matrix.
Downward spatially-scalable image reconstruction based on compressed sensing

According to the compressed sensing (CS) theory, we can sample a sparse signal at a rate that is (much) lower than the required Nyquist rate, while still enabling a nearly exact reconstruction. Image signals are sparse when represented in a certain domain, and because of this, a large number of CS-based image sampling and reconstruction techniques have been developed recently. In this paper, we focus on the design of the downward spatially-scalable image reconstruction from the CS-sampled data. Traditional methods usually reconstruct an image whose size is the same as the original source image and then achieve the downward scalability through sub-sampling. In our proposed method, we unify these two steps into a single one and promise to deliver a much improved quality.
Semiautomatic Radiofrequency Ablation Planning Based on Constrained Clustering Process for Hepatic Tumors

Radiofrequency ablation (RFA) is currently one of the most effective methods for minimally invasive treatment of hepatic tumors. Planning the probe placements is an essential and challenging step in RFA treatment. To completely destroy the tumor with minimum amount of affected native tissue, a new RFA planning system is proposed in this paper. In the proposed planning system, the minimum number of ablations and a conical insertion region for each ablation session are determined automatically. Based on the geometric character of the tumor, a novel clustering algorithm is developed to allow a better layout of the overlapping ablations. For each case, we force the clustering process under the constraint of a manually defined puncture scope, such that all of the needle trajectories are gathered in a reasonable region. Moreover, the proposed planning system enables the clinician to manually choose a proper insertion path inside the conical insertion region to avoid penetrating large vessels or ribs, which is critical in RFA treatment. The proposed planning system was evaluated on 18 CT scan images and two clinical cases. Results implied that the planning system could provide feasible and accurate RFA treatment plans for hepatic tumors.
Microstructures of carbon nanofilaments growing on graphite nanosheets

This study examines microstructures of a special three-dimensional nanocarbon composed of carbon nanotubes (CNTs) and graphite nanosheets (GNSs). The GNSs were made by exfoliating natural graphite flakes, and CNTs were grown on the GNSs by chemical vapour deposition. Nickel nanoparticles were deposited on the GNSs and employed as the catalyst for CNT growth. The micrographs show that initial deposition of carbon atoms results in structures different from the hollow, multi-walled CNTs. This initial portion forms the root of the CNT and becomes the link between the GNS and the CNT. The root is a form of carbon nanofibres (CNFs) with relatively random graphitic structures. After the CNF, CNT and amorphous carbon are followed. The focus here is how the graphitic structure changes from a disordered CNF to a regularly multi-walled CNT.