nils-herrmann/clean_scirepeval huggingface dataset:
An evaluation method of step-down stress accelerated life test based on Amsaa model

Life evaluation method of complex systems is facing main difficulties including selection of multiple failure modes or competition failure mode, and expensive test equipment and high testing costs currently. To solve this problem, a multiple step down stresses accelerated life test evaluation method is put forward based on the reliability growth model of complex systems. We reduce the comprehensive stress to an equivalent single stress by properly designing the comprehensive stress profile. We further use the similarity between the growth test and step-down stress accelerated life test to evaluate the reliability of the step-down stress accelerated life test using the Amsaa model. The Amsaa model overcomes the difficulties of choosing from multiple the accelerated models of step-down stress. Finally, the simulation results verify the feasibility of the method.
Advances in Studies on Chemical Constituents and Biological Activities of Typhonium giganteum Engl. Tuber Extracts

The dried tuber of Typhonium giganteum Engl. as a Chinese traditional medicine (Baifuzi) was recorded in Chinese Pharmacopoeia, which has the effects of "dispelling wind-phlegm" and apoplexy with gurgling in the throat etc. Recently, it has been shown that Typhonium giganteum Engl. tuber extracts possess a wide range of pharmacological properties, including effects on anti-tyrosinase, anti-inflammation, immunomodulation, apoptosis induction in cancer cells and so on. In this paper, we summarized the chemical constituents, biological activities and metabolism research advancement of Typhonium giganteum Engl. tuber extracts.
A real-time simulation system for satellite based on RTW and VxWorks

A new real-time simulation system is developed based on the Real Time Workshop (RTW) and real-time operation system VxWorks. The whole model of satellite is defined, which is proved by simulation in Simulink. This model is divided into two parts. One part is the attitude and orbit controller, i.e., attitude and orbit control system (AOCS), named AOCS model. The other is the external model of AOCS, named external model. The CAN bus interface blocks are designed for the two parts, respectively. The compiled codes of the two models are downloaded to two target computers with VxWorks for real-time simulation, which are connected by CAN bus. In addition, a method is proposed to verify the availability of the model in VxWorks, although not all blocks in Simulink can be implemented in VxWorks. This proposed method is compared by the simulation results of simulation in the Simulink and VxWorks. A simulation example is developed to test the availability and reliability of the system.
A Study of the Schottky-Barrier Height of Nickel Germanosilicide Contacts Formed on $\hbox{Si}_{1-x}\hbox{Ge}_{x}$ Epilayer on Si Substrates

Formation and electrical properties of nickel silicidized n-type Si and <formula formulatype="inline"><tex Notation="TeX">$ \hbox{Si}_{1-x}\hbox{Ge}_{x}$</tex></formula> epilayers on a Si substrate are comparatively studied. The improvement of thermal stability of germanosilicide can be attributed to the thicker NiSi(Ge) film and the delay of phase transformation with Ge incorporation, as well as the reduction in interface energy with Ge segregation at the interface. The Schottky-barrier heights (SBHs) of the contacts formed by sputtering Ni on the strained <formula formulatype="inline"><tex Notation="TeX">$\hbox{Si}_{1-x}\hbox{Ge}_{x}$</tex></formula> (<formula formulatype="inline"> <tex Notation="TeX">$x = \hbox{0.07}$</tex></formula> and 0.2) epilayers significantly increase after germanosilicidation and with increasing annealing temperature, markedly contrasting to the quick drop of SBH of the silicidized Si contact made by the same process. The raise of SBH of the <formula formulatype="inline"><tex Notation="TeX">$\hbox{Ni/Si}_{1-x}\hbox{Ge}_{x}$ </tex></formula> contact after germanosilicidation and with increasing annealing temperature is dominated by a Fermi-level pinning effect due to Ge segregation at the interface and the generation of dislocations driven by strain relaxation in the <formula formulatype="inline"><tex Notation="TeX">$\hbox{Si}_{1-x}\hbox{Ge}_{x}$</tex></formula> epilayers, rather than the reduction in work function when Ni transforms to NiSiGe during the germanosilicidation process.
A new Bug-type navigation algorithm considering practical implementation issues for mobile robots

A new Bug-type algorithm is proposed in this paper for the navigation of mobile robots. Unlike the related works which mainly focus on the theoretical analysis while ignoring the implementation issues, the new method presents not only an abstract concept which shortens the path length comparing with some previous works in the premise of guaranteeing convergence by its new switching conditions, but also a lower layer approach to realize its concept by keeping a safe distance to obstacles for collision avoidance. Simulation studies show that the new method generates shorter path than the classical Bug2 algorithm and a recent work termed as Bug2+. Experiment results on a real Pioneer3-AT robot further verify its practicability.
LID-Senones and Their Statistics for Language Identification

Recent research on end-to-end training structures for language identification has raised the possibility that intermediate language-sensitive feature units exist which are analogous to phonetically sensitive senones in automatic speech recognition systems. Termed language identification (LID)-senones, the statistics derived from these feature units have been shown to be beneficial in discriminating between languages, particularly for short utterances. This paper examines the evidence for the existence of LID-senones before designing and evaluating LID systems based on low- and high-level statistics of LID-senones with both generative and discriminative models. For the standard NIST LRE 2009 task on 23 languages, LID-senone-based systems are shown to outperform state-of-the-art deep neural network/i-vector methods both when LID-senones are used directly for classification and when LID-senone statistics are used for i-vector formation.
Development of the 40 V hybrid super-capacitor unit

A newly hybrid super-capacitor for the power source of EM launch system is developed. By the optimization of combined structure, the hybrid super-capacitor unit can be charged and discharged at the working voltage of 40 V. Compared with other super-capacitors, the working voltage gets raising actually. According to the electricity performance test, it shows that the capacitor has the high energy density and the ability of quick charging and discharging. And the analysis of electrical impedance spectroscopy (EIS) shows that it has good characteristics of impedance and frequency. The analysis method of equivalent circuit for the capacitor with impedance characteristic is meaningful for the comprehension of the process and determination of the production processes.
Improved language identification using deep bottleneck network

Effective representation plays an important role in automatic spoken language identification (LID). Recently, several representations that employ a pre-trained deep neural network (DNN) as the front-end feature extractor, have achieved state-of-the-art performance. However the performance is still far from satisfactory for dialect and short-duration utterance identification tasks, due to the deficiency of existing representations. To address this issue, this paper proposes the improved representations to exploit the information extracted from different layers of the DNN structure. This is conceptually motivated by regarding the DNN as a bridge between low-level acoustic input and high-level phonetic output features. Specifically, we employ deep bottleneck network (DBN), a DNN with an internal bottleneck layer acting as a feature extractor. We extract representations from two layers of this single network, i.e. DBN-TopLayer and DBN-MidLayer. Evaluations on the NIST LRE2009 dataset, as well as the more specific dialect recognition task, show that each representation can achieve an incremental performance gain. Furthermore, a simple fusion of the representations is shown to exceed current state-of-the-art performance.
Recursive filtering with randomly occurring false data injection attacks

This paper is concerned with the recursive filter analysis and synthesis problem for a class of nonlinear systems with randomly occurring false data injection attacks. A novel randomly occurring attack model is established by using a Bernoulli binary distributed white sequence with the given probability. The aim of the addressed filtering problem is to design a recursive filter such that, there exists an upper bound for the filtering error covariance in the presence of nonlinearities and randomly occurring false data injection attacks. Moreover, such an upper bound is minimized at each sampling instant. By solving two Riccati-like difference equations, the filter gain is calculated recursively. Furthermore, a sufficient condition is derived to guarantee the stochastic boundedness of the filtering error. Finally, a numerical example is presented to show the effectiveness of the proposed filtering scheme.
Synthesis of Novel Glycyrrhetinic Acid Analogues

Glycyrrhetinic acid (GA, 3&#946;-hydroxyl-11-oxo-olean-12-ene-29-oic acid, 1) isolated from Glycyrrhiza glabra was found to have several pharmacological activities. A series of novel GA derivatives were designed and synthesized as antitumor agents. Their structures were confirmed using MS and 1H-NMR.
The research of capacity utilization measurement on manufacturing industry in China

Capacity utilization, as the core factor of estimating capacity and excess production capacity, indicates the resource allocation and the economic progress. This paper generalized and summarized existing definitions of capacity and capacity utilization, further analyzed measurements of two capacity utilization based on physical and economic capacity definitions. Furthermore, estimated the capacity utilization under different scale hypothesis, in addition, analyzed the ray capacity utilization under the physical capacity perspective by comparison. Finally, empirically analyzed the capacity utilization of 12 segment manufacturing industries in China. Compared the differences of two measurement methods. Meanwhile, output elasticity of average cost, scale efficiency and excess production capacity are also discussed. Study found that, first, a majority of manufacturing industries are in the state of overcapacity in China, especially coal, oil and nuclear fuel, basic metal manufacturing industry, food, tobacco, where chemical industry is more serious; second, under the view of physical capacity definition, most industries could realize the maximum capacity, achieve a higher capacity utilization. Only a little part industries have a slightly excess production capacity.
Controller design for matrix second-order nonlinear plants based on requirements on tracking performance and disturbance rejection

In this paper, controller design for matrix second-order nonlinear plants based on requirements on tracking performance and disturbance rejection is addressed. The proposed controller is composed of a decoupling controller and a disturbance term observer. When designing the controller, a new tracking performance index is first defined, which reflects the desired modes of tracking errors of the closed-loop system. Based on this index, a decoupling controller with a disturbance term is derived. A disturbance term observer is then designed to estimate the disturbance term. In this research, Stability is proved for the closed loop system and it is shown that the speed and shape of response of the closed loop tracking error can be conveniently regulated with only two parameters; furthermore the closed loop system has strong disturbance rejection property. Good performance of the proposed controller is demonstrated by controlling a three-link nonlinear robot manipulator.
Recovering Hidden Diagonal Structures via Non-Negative Matrix Factorization with Multiple Constraints

Revealing data with intrinsically diagonal block structures is particularly useful for analyzing groups of highly correlated variables. Earlier researches based on non-negative matrix factorization (NMF) have been shown to be effective in representing such data by decomposing the observed data into two factors, where one factor is considered to be the feature and the other the expansion loading from a linear algebra perspective. If the data are sampled from multiple independent subspaces, the loading factor would possess a diagonal structure under an ideal matrix decomposition. However, the standard NMF method and its variants have not been reported to exploit this type of data via direct estimation. To address this issue, a non-negative matrix factorization with multiple constraints model is proposed in this paper. The constraints include an sparsity norm on the feature matrix and a total variational norm on each column of the loading matrix. The proposed model is shown to be capable of efficiently recovering diagonal block structures hidden in observed samples. An efficient numerical algorithm using the alternating direction method of multipliers model is proposed for optimizing the new model. Compared with several benchmark models, the proposed method performs robustly and effectively for simulated and real biological data.
The description of iFlyTek Speech Lab system for NIST2009 Language Recognition Evaluation

In this paper, we present a description of the iFlyTek Speech Lab system for NIST 2009 LRE (Language Recognition Evaluation). The system consists of acoustic systems (i.e. GMM-MMI and GMM-SVM) and phonotactic systems (i.e. PPR 4-gram LM and PPR 3-gram SVM). First, we describe several state-of-the-art techniques applied in our language recognition system, such as FA (Factor Analysis), MMI (Maximum Mutual Information), and generative and discriminative LM (Language Modelling) techniques etc. Then, we will discuss our data preprocessing techniques for handling large amount training and development data, and the mismatch among different languages, genders and channels. Finally, the evaluation results for NIST2009's tasks and detailed analysis are given for 30, 10 and 3 seconds durations.
Research and development of vehicle fault diagnostic protocol ISO15765

In this paper, CAN based vehicle fault diagnostic protocol ISO15765 is introduced, and the architecture of ISO15765 is analyzed. The paper provides the overall design of the ISO15765 protocol stack, the software realizations of each layer of ISO15765 are also introduced. Lower layers provide interfaces to higher layers. The development of internal operation of each layer adopts modular design. The result of the experiment shows that the protocol stack provided by the paper satisfies ISO15765 standard and general fault diagnosis requirements.
Thermal Stability of Nickel Germanide Formed on Tensile-Strained Ge Epilayer on Si Substrate

The thermal stability of a nickel germanide film formed on a tensile-strained Ge epilayer on a silicon substrate with a low-temperature Si0.77Ge0.23 (50-nm)/Ge (50-nm) buffer is investigated. A record temperature of 700°C for the stability of sheet resistance of nickel germanide is reported, which is increased by about 150°C compared to that on bulk Ge and comparable to the temperature for nickel silicide on the Si substrate. The improvement of the thermal stability is demonstrated due to the delay of the agglomeration of the nickel germanide film on Ge-on-Si, which is proposed to be attributed to the increase of the tensile strain in the Ge epilayer during thermal annealing due to the thermal mismatch between Si and Ge.
An automatic language identification method based on subspace analysis

Gaussian mixture models (GMM) have become one of the standard acoustic approaches for language identification. Furthermore, the GMM-SVM is proven to work well by introducing the discriminative method into the GMM-based acoustic systems. In these systems, the intersession variability within language has become an important adverse factor that degrades the system performance. To tackle this problem, we propose a subspace analysis method, termed as Intra-language Difference Subspace Estimatio (IDSE), under the GMM-SVM framework. In IDSE method, the difference vector is modeled with three components: Extra-language difference, Intra-language difference and noise difference. Then the Intra-language and noise difference are effectively estimated and eliminated from the difference vector. The experiments on NIST 07 evaluation tasks show effectiveness of the proposed method.
Area-Efficient On-Chip DC–DC Converter With Multiple-Output for Bio-Medical Applications

Multiple-supply are required to minimize the power consumptions in bio-implant systems. A single-inductor multiple-output (SIMO) switching converter is one of the solutions. But it has inherent problems which block the applications in the embedded biomedical systems. In this paper, a circuit arrangement for providing multiple outputs based on low-dropout (LDO) regulator is proposed. The regulating transistor of LDO is time-shared by N output legs. Two error amplifiers (EAs) are utilized in the topology, irrespective of number of the output legs. The corresponding switching strategy alleviates the difficulties associated with controlling multiple switching functions for conventional time-sharing methods, and thus, permits multiple outputs to be generated easily. A prototype multiple-output LDO (MOLDO) regulator with four output legs was fabricated with a standard 0.35 μm CMOS process. The measurement results verify the good performance of this design such as no cross regulation (CR), small ripples, and less power consumption. Moreover, it does not require inductor and presents low total harmonic distortion, which is very suitable for bio-implant fields.
Multi-part boosting LSTMS for skeleton based human activity analysis

This paper presents the methods we adopt for ICME2017 large scale 3D human activity analysis challenge in depth videos. There are two tasks including the segmented activity recognition and the untrimmed activity detection. We adopt a network structure comprised of two LSTM layers, a fully connected layer and a softmax layer. For the recognition task, we investigate several schemes to handle the inconsistency of subject number of different activities. For the detection task, we trim multi-scale segment parts from untrimmed videos and adopt a proposal network followed by a classification network.
Unified Video Annotation via Multigraph Learning

Learning-based video annotation is a promising approach to facilitating video retrieval and it can avoid the intensive labor costs of pure manual annotation. But it frequently encounters several difficulties, such as insufficiency of training data and the curse of dimensionality. In this paper, we propose a method named optimized multigraph-based semi-supervised learning (OMG-SSL), which aims to simultaneously tackle these difficulties in a unified scheme. We show that various crucial factors in video annotation, including multiple modalities, multiple distance functions, and temporal consistency, all correspond to different relationships among video units, and hence they can be represented by different graphs. Therefore, these factors can be simultaneously dealt with by learning with multiple graphs, namely, the proposed OMG-SSL approach. Different from the existing graph-based semi-supervised learning methods that only utilize one graph, OMG-SSL integrates multiple graphs into a regularization framework in order to sufficiently explore their complementation. We show that this scheme is equivalent to first fusing multiple graphs and then conducting semi-supervised learning on the fused graph. Through an optimization approach, it is able to assign suitable weights to the graphs. Furthermore, we show that the proposed method can be implemented through a computationally efficient iterative process. Extensive experiments on the TREC video retrieval evaluation (TRECVID) benchmark have demonstrated the effectiveness and efficiency of our proposed approach.
Extended RRT-based path planning for flying robots in complex 3D environments with narrow passages

Sampling-based methods such as Rapidly Exploring Random Trees (RRT) and Probabilistic Road Maps (PRM) have been recognized as effective tools to solve the path planning problem for both ground mobile robots and flying robots in high-dimensional configuration space. However, the efficiency of the RRT planner will be decreased in complex environments with narrow passages. This paper presents a multiple RRTs-based path planning framework to improve the above mentioned problem. The key ingredient of the framework is a hybrid sampling strategy which takes advantage of the Randomized Star Builder (RSB) and uniform sampling. The RSB method can efficiently recognize narrow passage regions while avoiding unnecessary samples in the corners and dead ends, and generates milestones for growing multiple local trees from narrow passages. Moreover, uniform sampling is used to generate global RRT trees in order to capture global connectivity. Simulation results of 3D flying robots demonstrate the effectiveness of the proposed method. Comparisons between the proposed method and other RRT-based planners are also presented.
Attitude model identification of small satellites with missing data

This paper applies the wavelet reconstruction technique to the identification of attitude model of small satellites when there exists missing phenomenon in the input or/and output experiment data. Two kinds of missing data existing in the satellite attitude control systems, namely, the multirate case and the random missing type are both considered. By employing the wavelet analysis, two corresponding identification algorithms are respectively proposed under the condition of these two kinds of missing measurements. Finally, the simulations and comparisons are given to verify the effectiveness of proposed methods.
Research on application of simulation technology in container ship stowage problem of port logistics

As the international logistics industry develops fast, container loading has become a core part of maritime transport, with its efficiency and safety focused by logistics industry. The enlargement of ships makes the container loading problem much more complex than ever. Traditional ways to study these problems now have been difficult to offer effective solutions, while simulation technology not only can fully reflect the essence of modern system theory, but also puts emphasis on both integrity of one whole problem and the connection of each sub problem. By simulating the operation of container terminal, we can have a deep look into the designed links in container logistics system, to check the operational effectiveness, analyze the bottlenecks in system, forecast the results, show the image of system, and implement the optimization of system. Overall, simulation technology provides guarantee for the optimization, security and automation level of high-degree container loading and thus improve the competitiveness of the port, placing a profound impact on future development and the scale expansion of port logistics in China. This paper studies on how to design the simulation of container ship stowage problem.
Synchronization in coupled fractional order Chen-system and its application in secure communication

A new projective synchronization in coupled fractional order chaotic Chen systems is studied. First, an approximation integer order system for the fractional order Chen system is constructed. Then, since the scaling factor of PS (projective synchronization) is predicted hardly, a control algorithm is thus proposed to improve on the projective synchronization in the new integer order systems. This control scheme can be used in some secure communication systems. Illustrations are also given to show the rightness of the theoretical analysis and the effectiveness of the method proposed.