nils-herrmann/clean_scirepeval huggingface dataset:
Path Similarity Based Directory Ontology Matching

In a directory ontology, only concepts and hypernym/hyponym relationships between them are defined. Directory ontologies are widely used in many real-world applications such as product catalogues and Web directories. The widely used heterogeneous directories also bring a big challenge for integration of them. Previously, little attentions have been paid attention to the problem in the research community. In this paper, we propose a path similarity based approach for directory ontology matching. We define the concept's local label and the concept's path label. Next, we propose a path similarity method, which combines the local label and path label information. Then, a top-down similarity flooding is utilized to improve the matching result. Our experimental results on the music genre ontologies show that the proposed method can achieve a precision of 78% and a recall of 66%, significantly outperforming the baseline method.
The data clustering method applied in land grading based on Fuzzy-Hypergraph model

Based on the shortage of the classifying methods in the farmland, fuzzy theory, Hypergraph model, and GIS were integrated to develop a Fuzzy Hypergraph space data clustering Model. The feasibility of applying this Model to classify the farmland in the Fogang city in Guangdong Province was investigated and verified. The results show that classifying the farmland by using Fuzzy Hypergraph space data clustering Model is stable and reliable.
Finite element simulation of thermal properties of 40Si-Al alloys for electronics packaging

Due to lighter, stiffer and offer superior heat-sinking than traditional packaging materials, Si-Al alloys have been proved as novel materials used for packaging microwave hybrid circuitry. In the current paper, finite element geometric models based on the real microstructural images of 40Si-Al are generated. Furthermore, based on Fourier's law for heat conduction and thermal expansion equation, thermal properties including the thermal conductivity and the coefficient of thermal expansion (CTE) of 40Si-Al are quantified by finite element method (FEM). By means of statistical method in conjunction with FEM results, the thermal conductivity and CTE at room temperature are calculated, respectively. The numerical simulation result agrees with the corresponding experimental result, which shows that the methodology developed in this paper is efficient in calculating thermal properties of Si-Al alloys.
Design of a New Fasten-Able Linear Motor for Smart Distributed Robot System

Distributed robot often contains two systems. One is for moving,, another one is for fastening. In this paper, we focus on a new linear motor, in addition to motion function, it can provide suction force,, does not require continuous energy supply for suction. A basic circuit for the new linear motor was designed, tested, which can freely control the length of dead-time. Design guide for initial design are also summed up.
Indium-zinc-oxide electric-double-layer thin-film transistors for artificial synapse applications

Phosphorous-doped nanogranular SiO2 gated laterally coupled indium-zinc-oxide electric-double-layer synaptic transistors are self-assembled on glass substrate. A strong electric-double-layer effect is observed. Synaptic functions, such as excitatory postsynaptic currents (EPSC) and paired-pulse facilitation (PPF) are mimicked on the proposed IZO synaptic transistor. The time scales of the PPF behaviors are similar to that observed in biological synapse. The proposed synaptic transistors are meaningful for neuron bionics.
Dual-mode substrate integrated waveguide (SIW) bandpass filters with an improved upper stopband performance

Dual-mode substrate integrated waveguide (SIW) filters with improved upper stopband attenuation is presented. The filter is comprised of TE102 and TE201 modes waveguide resonator. The proposed filters are implemented using substrate integrated waveguide (SIW) technology featuring compact size, low cost, and high power-capacity. A simple solution for improving the upper stopband performance while maintaining compact size realization is provided. The stopband improvement is achieved by using defected ground structure (DGS) which is etched on the ground plane of the SIW cavity. Compared to previous-reported SIW filters with improved stopband achieved by lowpass cleanup filters, the proposed approach provides a relatively compact realization while reducing the complexity of the overall structure. Simulation examples of single- and double-cavity dual-mode SIW filters are realized using EM simulations for demonstrating the underlying principle.
An Improved LDA Multi-document Summarization Model Based on TensorFlow

Latent Dirichlet Allocation (LDA), has been recently used to automatically generate text corpora topics, and applied to sentences extraction based multi-document summarization algorithms. In this paper, we propose a novel approach to automatic generation of aspect-oriented summaries from multiple documents. Our approach is to combine the traditional summary generation algorithm and the the abstract generation algorithm based on deep learning.We employ the improved traditional summary generation algorithm to convert multiple documents into a single document, and then using the resulting single document with the deep learning method to extract the final summary. At first, we apply improved LDA model to cluster sentences in all documents. Second, We employ the extended LexRank algorithm to sort the sentences in each cluster. Third, we use extended Hedge Trimmer algorithm for sentence compression. Fourth, We apply Integer Linear Programming for sentence selection, and in this step ,we get the single document. Finally, We employ the textum on TensorFlow to get the final abstract. The experiments showed that the proposed algorithm achieved better performance compared the other state-of-the-art algorithms on DUC2005 and TAC2010 corpus.
Improved performance of fiber optic hydrogen sensor based on high reflective Bragg grating and WO3-Pd2Pt-Pt composite films

A novel method was proposed to improve hydrogen sensitive performance of fiber Bragg grating (FBG) hydrogen sensor. The hydrogen performance of the sensor can be greatly improved by using WO3-Pd2Pt-Pt composite films as sensing element. The high reflective Bragg gratings was written in single mode fiber. The end-face of single mode fiber was deposited with WO3-Pd2Pt-Pt composite films as sensing element. The peak intensity of high reflective FBG is employed for reference, while that of baseline intensity of reflected light source is used as hydrogen characterization. The experimental results prove the resolution of the hydrogen sensing system can reach to 5 ppm, and the proposed sensor displays good repeatability during the hydrogen response.
Learning Style-directed Dynamics of Human Motion for Automatic Motion Synthesis

This paper presents a new model, the HMM/Mix-SDTG, which describes Markov processes under control of a global vector variable called style variable. We present an EM learning algorithm to learn an HMM/Mix-SDTG from one or more 3D motion capture sequences labelled by their style values. Because each dimension of the style variable has explicit physical meaning, with the presented synthesis algorithm, we are able to generate arbitrarily new motion with style exactly as demand by specifying a style value. The output densities of HMM/Mix-SDTG is represented by mixtures of stylized decomposable triangulated graphs (Mix-SDTG), which, in addition to parameterizing the Markov process with the style variable, also achieve more numerical robustness and preventing common artifacts of 3D motion synthesis.
Audio-visual speaker identification with multi-view distance metric learning

Both audio and visual information can be useful for speaker identification in videos. This paper proposes an audio-visual speaker identification approach that benefits from a multi-view distance metric learning method. Our metric learning scheme not only builds distance measures based on the label information of training data but also the consistency of different views. In this way, better metrics can be learned in comparison with metric learning for each view individually. We conduct experiments on VidTIMIT dataset and empirical results have demonstrated the effectiveness of our approach over a set of existing methods. In addition, we also implement our method on a multi-view digit recognition task and encouraging results are also obtained.
Kinetic Analysis of Aminoethylisothiourea on Diphenolase of Mushroom Tyrosinase

This study demonstrates that Aminoethylisothiourea (AET), a potent inhibitor of inducible nitric oxide synthase (NOS), is an irreversible competitive inhibitor of the diphenolase activity of mushroom tyrosinase when L -DOPA was assayed spectrophotometrically in vitro. The inhibition of diphenolase activity of tyrosinase by AET showed positive kinetic cooperativity which arose from the protection of both substrate and o-quinone against inhibition by AET.
A Time Synchronization Protocol in WSN Applied in RAMR

Clock synchronization represents a crucial element in the operation of wireless sensor networks (WSN). This paper analyzes many time synchronization protocols in WSN. According to the sources affecting time synchronization and the characteristics of remote automatic wattmeter reading (RAWR), this paper gives an improved algorithm of DMTS, called FU-DMTS and simulates it. Besides transmitting less messages, this algorithm is higher precise than DMTS, and it can meet the requirements of RAWR.
Notice of RetractionA Novel Processing Process for Preparing Solid Dispersions of Acyclovir

In the present study, a novel processing process was successfully developed for preparing solid dispersions (SD) of acyclovir (ACY). During the process, the drug and the hydrophilic polymer polyvinylpyrrolidone were co-dissolved to form aqueous solutions at an evaluated temperature, then the solutions were frozen using liquid nitrogen, following by vacuum freeze drying to prepare the SD. The solubility measurements of ACY under different conditions and the polarization microscope observations gave the warrants for the novel process. The improvement of wettability of the drug in the SD membrane and most of the ACY presented in the amorphous physical status, which were demonstrated by contact angle measurement and X-ray diffraction, obviously facilitated the dissolution process of ACY in the SD membrane. In vitro dissolution tests showed that 84.3% of ACY was released out in first 5 minutes, only 20.6% and 4.29% of ACY could be free into the dissolution media for compressed tablets and pure ACY particles at the same time period. This novel process is useful for preparing SD to improve the dissolution properties of a type of poorly water-soluble drug and free of organic solvents.
Real time control system of Active Reflector of FAST

Active Reflector is one of the most important part of FAST (The Five-Hundred-Meter Aperture Spherical Radio Telescope),and its performance is related with performance of whole telescope. So a real time control system is needed for Active Reflector System. In this paper, a design based on EPICS (Experimental Physics and Industrial Control System) is introduced including IOC design interfacing with thousands of nodes through Ethernet/RS485/CAN and control client using EPICS QT framework and 3D modeling technology—OpenGL for ARS Visualization. From view of command, status, alarm, log of ARS, a layer pattern with data flow is applied into architecture of control system. It is provided that command interface, status interface, alarm interface and log interface with Central Control System. The system is accomplished and tested as a prototype in Miyun Model of FAST which has 30-meter aperture.
Application of SVM optimized by genetic algorithm in forecasting and management of water consumption used in agriculture

Predication of water consumption used in agriculture is significant to set the planning of configuration optimization of water resources. In order to forecast water consumption used in agriculture exactly, support vector machine and genetic algorithm is proposed to forecast water consumption used in agriculture, where genetic algorithm (GA) is used to select the parameters of support vector machine. The experimental results demonstrate that the proposed GA-SVM model provides better prediction capability and is therefore considered as a promising alternative method for forecasting water consumption used in agriculture.
Modeling and Compensation of Asymmetric Hysteresis Nonlinearity for Piezoceramic Actuators With a Modified Prandtl–Ishlinskii Model

This paper presents a modified Prandtl-Ishlinskii (P-I) (MPI) model for the asymmetric hysteresis description and compensation of piezoelectric actuators. Considering the fact that the classical P-I (CPI) model is only efficient for the symmetric hysteresis description, the MPI model is proposed to describe the asymmetric hysteresis nonlinearity of piezoceramic actuators (PCAs). Different from the commonly used approach for the development of asymmetric P-I models by replacing the classical play operator with complex nonlinear operators, the proposed MPI model still utilizes the classical play operator as the elementary operator, while a generalized input function is introduced to replace the linear input function in the CPI model. By this way, the developed MPI model has a relative simple mathematic format with fewer parameters to characterize the asymmetric hysteresis behavior of PCAs. The benefit for the developed MPI model also lies in the fact that an analytic inverse model of the CPI model can be directly applied for the inverse compensation of the asymmetric hysteresis nonlinearity represented by the developed MPI model in real-time applications. To validate the developed MPI model and the inverse hysteresis compensator, simulation, and experimental results on a piezoceramic actuated platform are presented.
High Availability Cluster with Combining NAS and ISCSI

To meet enterprise and grand challenge-scale performance and high availability requirements, a new type of storage cluster - iSCSI-based NAS cluster (iNC) is being designed. There are many advantages in an iNC system: firstly, it provides scalability without the added complexity by a single consolidated centralized storage management view for integrating multi-NAS with multi-user virtualized file system; secondly, it provides the flexibility for application by combining file-based NAS and block-based SANs via iSCSI in the same device; thirdly, it provides high performance and high availability by load-balancing and fault-tolerating mechanism; finally, it eliminates the single failure point and the bottleneck of I/O performance for the metadata server by storage agency. In this paper, we describe an implementation that demonstrates and validates iNC' potential. The I/O throughput for both file and block I/O requests, and the availability of our prototype are higher than that of NAS
A New Architecture for Cognitive Radio Networks Platform

Cognitive radio networks is recognized as the technology to solve the problem of spectrum shortage and promote the efficient use of the spectrum. However, the research of CR networks technologies only stays in the theoretical stage recently. Therefore, developing a CR networks platform becomes an urgent problem to solve. Several CR platforms have being deployed by the research community. However, most platforms provide cognition either in physical layer or network layer. Few platform addresses all layers cognition for wireless network. This paper proposes a new architecture which is aimed at stimulating cognition process in all layers for wireless networks. We firstly review the current main CR platforms. Then, a new CR networks platform is proposed. We clearly describe the components of the new platform and give work flow of the new platform. Finally, we use the platform to simulate and verify two spectrum assignment algorithms, and give performance comparison. Simulation results indicate that the greedy algorithm is better than fair algorithm in spectrum utilization and the greedy algorithm outperforms the greedy algorithm in fairness.
Notice of RetractionThe Optimization of the Bio-Panning Process of the Affinity Ligand of Tyrosinase by Phage Display Technology

The aim of this study was to search an optimal bio-panning process of phage display. In this study, the target protein is tyrosinase. Through changing the screening conditions, we found a successful method to obtain a high recovery ratio when the specificities of the sequences were not affected. Ultimately, the optimum bio-panning conditions are as follows: the incubate time is 40min, the wash time is 6 times and the wash time is 35min. The verifying experiment showed that this bio-panning process can obtain a high recovery ratio of phages, and the result of the ELISA showed that the specificities of the sequences were not affected.
A Dispatching-Rule-Based Task Scheduling Policy for MapReduce with Multi-type Jobs in Heterogeneous Environments

MapReduce has emerged as an important and widely used programming model for distributed and parallel computing, due to its ease of use, generality and scalability. This model is proposed to mainly solve large-scale data processing, i.e. data-intensive jobs, and it is optimized for homogenous environment, in which computing nodes are identical and dedicated. Today enterprise IT systems preserve massive, historical management and operational data, which need both data-intensive and computation-intensive analysis while using heterogeneous computing resources. In order to support enterprise data analysis application with the MapReduce model, it is important to improve MapReduce's task scheduling algorithm that can reduce the overall completion time with multi-type jobs and in heterogeneous environments. This paper formulates the scheduling problem as an optimization problem. Based on the job shop scheduling theory and existing approximation algorithms, we propose a new dispatching-rule-based and online scheduling policy LPT-θ. By using LPT-θ, the tasks with larger processing time and within a θ-space would be assigned with higher priorities. Numerical results show that LPT-θ can achieve a 12%~45% performance gain compared with the original scheduling algorithm in MapReduce.
A new deterministic traffic model for core-stateless scheduling

Core-stateless scheduling algorithms have been proposed in the literature to overcome the scalability problem of the stateful approach. Instead of maintaining per-How information or performing per-packet How classification at core routers, packets are scheduled according to the information (time stamps) carried in their headers. They can hence provision quality of service (QoS) and achieve high scalability. In this paper, which came from our observation that it is more convenient to evaluate a packet's delay in a core-stateless network with reference to its time stamp than to the real time, we propose a new traffic model and derive its properties. Based on this model, a novel time-stamp encoding scheme, which is theoretically proven to be able to minimize the end-to-end worst case delay in a core-stateless network, is presented. With our proposed traffic model, performance analysis in core-stateless networks becomes straightforward.
MDMeter A New Test Tool for Meta-data Throughput of Parallel File System

As the existing performance evaluation benchmark software for parallel file system has too many test items, it can’t evaluate the meta-data throughput accurately, and there are great difficulties to evaluate the meta-data throughput performance in practical application environment. To solve these problems, a new meta-data throughput evaluation tool, called as MDMeter, has been designed and accomplished in this paper. A new simulation model for file operation is designed according to the real file operation records which were captured by IOTrace tool. MDMeter can launch a variety of meta-data operations on parallel file system, and can provide a comprehensive test result report to users; it can evaluate the meta-data throughput performance accurately for different application environment. At the last, some tests are performed on Lustre parallel file system by MDMeter and traditional tools, the results show that MDMeter not only can give a simple and integrated performance test result to users, but also can evaluate the meta-data throughput for parallel file system more precisely than the existing test tools.
Research of Key Problem of Receiving and Recovery of Signal Based on Wide Band Receiver

The SNR of TEMPEST leaking signal and bandwidth for receiving of receiver were key factors of affecting information recovery. To improve the quality of information recovery, make mention of the conception of prime bandwidth for receiving and present the definition of prime bandwidth for receiving. Relation between prime bandwidth for receiving and SNR of signal has been researched, as well as relation with characteristic of frequency domain of signal. Make digital baseband signal as an example for deducing prime bandwidth for receiving and discuss the prime bandwidth for receiving aiming at complicated signals.
Seamless mobility in data aware networking

The underlying networks (of the Internet) have been reworked to make way for new technologies, some serious inefficiencies and security problems have arisen. As a result, over the past years, fundamentally new network designs have taken shape and are being tested. In ITU Recommendation Y.3001 , four objectives are identified in line with the requirements for Future Network; one of them is data awareness. In ITU Recommandation Y.3033 , the `Mobility' is addressed as one of the key problem spaces of data aware networking (DAN). This paper proposes Named-Node-Networking (3N), a novel architecture for DAN. We design a simulator (nnnSIM)  for evaluating our proposed 3N architecture which is the second major contribution of this paper. The nnnSIM simulator is written in C++ under the ns-3 framework  and has been made available as open-source software for the scientific community. Considering the importance of a unique DAN architecture, we propose a study for standardization work in the ITU as an initiative which can lead to its rapid adaptation.
Spectral approximation to point set similarity metric

In a variety of problems, objects are represented as a collection of feature points {fk} and their spatial positions {pk}. In some cases, feature points doesn't carry enough discriminating information to identify objects so as to raise the question of point set verification, i.e., matching two point sets to identify whether they are match or not. Point set verification problem involves two challenges. The first challenge is to identify a one-to-one mapping between two point sets and the second is to measure the similarity between the two aligned point sets. The first challenge is a well-known one-to-one mapping problem in computer vision with a combinatorial nature and computationally expensive. However, we are able to avoid the computation of one-to-one mapping by directly giving a matching similarity score. The second challenge is attacked with lots of solutions, which shares two disadvantages, i.e., sensitive to both outliners and affine transform. These two challenges are solved simultaneously by our eigenvalue approximation solution. In this work, the point sets are modeled as affinity matrix and the distances between affinity matrices of two point sets are lower bounded by eigenvalue distance. This affinity representation is invariant to scale, translation and rotation and insensitive to outliners and affine transforms. Experiments on both synthetic data and real data shows that this method outperforms both statistics based and geometry based methods.