nils-herrmann/clean_scirepeval huggingface dataset:
Robust fault detection dynamic observer design for LTI systems

Dynamic observer provides more freedom to meet the diversified performance specifications for fault detection purpose in contrast with static observer. However, little attention is paid on its design and only a few papers investigated how to design a fault detection dynamic observer. In this work, we propose an innovative dynamic observer design approach for linear time invariant (LTI) systems subjected to unknown disturbance and possible faults with the aid of the generalized KYP lemma developed recently. The dynamic observer is designed such that the disturbances are attenuated to a specified level to meet the H∞ performance in the concerned finite frequency interval while the sensitivity to the possible faults in its frequency domain is maximized in the H- index sense. The existence conditions of such an observer are given in terms of linear matrix inequalities (LMIs). An iterative algorithm is presented to achieve the solution. The effectiveness of the proposed method is illustrated by a numerical example.
A Portable Micropump System Based on Piezoelectric Actuation

Despite significant efforts to develop micropumps, cumbersome driving equipment means that the design of portable micropumps remains a challenge. This study presents a stand-alone micropump system, which includes a peristaltic micropump based on piezoelectric actuation and a driving circuit. This battery-based driving circuit comprises a 12 V battery, an ATmega 8535 microprocessor, a 12 V-to-180 V DC to DC converter using transformerless technology, three differential amplifiers, an IC 7805, a phase controller, an A/D converter, a keyboard and an LCD module. The system can produce step-function signals with voltages of up to 228 V and frequencies ranging from 10 Hz to 100 kHz, as the inputs for the pump. It is portable and programmable with the package size of 22 cm times 12.8 cm times 9 cm. Additionally, this proposed system is used to design the driving signals of the pump which are 3-, 4, and 6- phase actuation sequences. This work performs the circuit testing and fluid pumping, and demonstrates the effects of actuation sequences on pump performance in terms of the dynamic behavior of the diaphragm, flow rates and back pressure of the system. The experimental results show that the pump excited by the 6-phase sequence results in better performance compared with the 3- and 4-phase sequences, and produces a maximum flow rate of 36.8 mul/min and a maximum back pressure of 520 Pa with deionized water at 100 Vpp and 700 Hz.
Development of a Java-based distributed platform for the implementation of computation intelligence techniques

This work reports three phases of development of a Java-based distributed system for the implementation of computational intelligence techniques to solve practical engineering problems. The first design of the Java-based system is called Para Worker. It is a library of application program interface (APIs) to facilitate parallel computation. Next, a new system, termed Para Worker 2 aimed at improving ease of programming and performance. It also adds enhanced features of improved dynamic object reallocation, adaptive consistency protocols, and location transparency. However, neither of these systems addressed the fundamental issues of Java virtual machine (JVM) in distributed environment. The third phase of development of the Java-based system is a new form of distributed JVM in order to execute Java program efficiently. The new system is termed Java distributed platform (JavaDP).
A multi-objective invasive weed optimization for task assignment in prefabricated systems

A novel discrete invasive weed optimization (DIWO) algorithms is proposed to solve the task assignment problems in the prefabricated systems. Three objectives are considered simultaneously, i.e., minimization of the total execution time, the total transportation cost and the total balance of execution time. In the proposed algorithm, a novel reproduction heuristic based on the p-optimality criteria is embedded to decide the number of offspring for each weed during the generation, which can obviously increase the searching quality and diversity of the algorithm. Moreover, five types of neighborhood structures are proposed to realize the dispatching mechanism in the canonical IWO algorithm, which can only applicable for the continuous optimization problems. Furthermore, to decrease the computational complexity, during each generation, the newly-generated weeds are stored and applied the non-dominated sorting algorithm to update the Pareto archive set. Detailed comparisons on the randomly-generated instances show the efficiency and diversity of the proposed DIWO algorithm.
Evaluation of ET data products: Parameterizations, rate limiting process and influential surface properties

Radiometric measurements taken at a distance from evaporating bodies have been used for about 50 years to obtain a measure of water use. The basic physics of determining water use is the principle of energy conservation at the evaporating surface, but energy flux densities need to be parameterized using the variables which can be actually captured by radiometric measurements. Both observations of surface temperature and of soil water content are used for this purpose. Models of energy and water exchange vary from semi-empirical relationships between latent heat flux density and surface temperature to fully three-dimensional models of the soil-foliage-atmosphere system. Several ET satellite data products are available and evaluations against ground measurements have been published. Results suggest a dependence of accuracy on climate, soil and vegetation. The review of documented performance is combined with the sensitivity analysis of widely used ET algorithms, e.g. SEBI, SEBS, SEBAL and ET Monitor.
An ultra-wideband Darlington low noise amplifier design based on SiGe HBT

A design methodology of Darlington low noise figure (LNA) for application at ultra wide bandwidth using a resistive feedback scheme is proposed. The packaged SiGe heterojunction bipolar transistors (HBTs) BFP740 and chip type passive components were used for this direct-coupled LNA. The Darlington amplifier has high gain of 20 dB with variation of 0.5 dB over 3.1-6 GHz, which is twice of single stage LNA. The typical noise figure is 1.8 dB at 3.1 GHz, 2.9 dB at 6 GHz and the circuit keeps unconditional stable for whole 3.1 GHz-6 GHz frequency band. General design procedures are also given in this paper in order to better understand the roles of the various key issues for the LNA.
Road Traffic Flow Prediction with a Time-Oriented ARIMA Model

The prediction of the traffic flow can give the people important traveling information. In this paper, the traffic flow prediction problem is studied. An ARIMA model is proposed for the traffic flow prediction. The ARIMA model is trained according to the different period traffic data. Based on the different period data training, the ARIMA model is refined more accuracy. The experiments show that the ARIMA model trained by the time-oriented data can reach a better result than the non time-oriented data trained model.
Performance improvement in mesh-based optical networks-on-chip

In the optical communication system, crosstalk noise is always the critical factor affecting the optical signal transmission, especially in networks-on-chip (ONoCs). Based on the model at device, router and network level, this paper proposes the Optimized Crux (OC) router which uses the crossing angle of 60° or 120° instead of the conventional 90° to optimize the Crux optical router. The SNR of the Optimized Crux (OC) router is improved by 2.1dB compared with the Crux on the premise that the size of mesh-based ONoCs is 7×7. By comparing analysis, the results show that to achieve the bit error rate (BER) of 10-9 for reliable transmissions, the maximum mesh-based ONoCs size has expanded from 4×4 when using the Crossbar optical router to 8×8 when using the OC router.
Intra-Vehicle Ultra-Wideband Communication Testbed

Modern vehicles are increasingly equipped with more sensors which are connected to control units through cables for transmitting crucial real-time sensing data. To reduce the complexity and cost brought to the automotive design and production by the sensor wiring harness, replacing cables with wireless links has been proposed in . With its fine capability of solving multi-path fading and interference resilience, as well as its freely available spectrum, the ultra-wideband (UWB) technology is considered as a highly promising candidate for such intra-vehicle wireless network. For the purpose of evaluating UWB based sensor network, compared with wired system, from the aspects of performance and reliability in transmitting automotive sensing data, an UWB communication testbed is needed. In this paper we present our first attempt in building an intra-vehicle UWB wireless sensor network to transmit automotive speed data from four wheel speed sensors to the electronic control unit (ECU)1. Assembly of the testbed consists of ABS motor control simulating system, wheel speed sensors, UWB transmitting nodes and the UWB network coordinator interfacing with ECU. The paper also includes the description of the main testbed software modules and the report of initial measurement result. Future measurement plan and further work needed to improve the testbed are discussed in the conclusion section.
An investigation of dual energy transmission measurements in simultaneous transmission emission imaging

In this study we investigate the feasibility of acquiring dual energy transmission projection data using a conventional gamma camera. Transmission projection data are acquired, simultaneously with /sup 99m/Tc emission data, using the two major photopeaks of /sup 153/Gd, at 44 keV and 99 keV. The degree of contamination of the data in the 44 keV window, by scattered 99 keV transmission photons, is investigated using Monte Carlo simulations. A modified scaling method is proposed to convert the two attenuation maps, obtained from transmission data acquired at 44 keV and 99 keV, to one appropriate for /sup 99m/Tc. This attenuation map is compared to one produced by scaling the 99 keV attenuation map, for the attenuation correction of /sup 99m/Tc SPECT images. The use of dual energy transmission imaging is shown to improve the quantitative accuracy of the reconstructed SPECT images compared to a single scale factor method. However, for situations where a dual scaling factor method is possible, this is shown to perform as well as the dual energy method. Dual energy transmission imaging is shown to be more effective at visualizing areas of bone, particularly in regions near the edge of the untruncated field of view.
Pure mode axes of single crystal BaTeMo2O9

The three-dimensional slowness surface method is used to investigate the pure mode axes of single crystal BaTeMo2O9 on the basis of the experimental data. The relationship of the slowness surface and pure mode axes is studied. Under the condition of taking account of the piezoelectric effect, the piezoelectrically stiffened elastic constants are calculated. Pure mode axes of the BaTeMo2O9 crystal are determined and plotted out on the slowness surfaces by software program. The result indicates that Y axis and Z axis are the pure mode axes of single crystal BaTeMo2O9. The validity of the result has been proved by theoretical calculation.
A Benchmark Dataset and Saliency-Guided Stacked Autoencoders for Video-Based Salient Object Detection.

Image-based salient object detection (SOD) has been extensively studied in past decades. However, video-based SOD is much less explored due to the lack of large-scale video datasets within which salient objects are unambiguously defined and annotated. Toward this end, this paper proposes a video-based SOD dataset that consists of 200 videos. In constructing the dataset, we manually annotate all objects and regions over 7650 uniformly sampled keyframes and collect the eye-tracking data of 23 subjects who free-view all videos. From the user data, we find that salient objects in a video can be defined as objects that consistently pop-out throughout the video, and objects with such attributes can be unambiguously annotated by combining manually annotated object/region masks with eye-tracking data of multiple subjects. To the best of our knowledge, it is currently the largest dataset for video-based salient object detection. Based on this dataset, this paper proposes an unsupervised baseline approach for video-based SOD by using saliency-guided stacked autoencoders. In the proposed approach, multiple spatiotemporal saliency cues are first extracted at the pixel, superpixel, and object levels. With these saliency cues, stacked autoencoders are constructed in an unsupervised manner that automatically infers a saliency score for each pixel by progressively encoding the high-dimensional saliency cues gathered from the pixel and its spatiotemporal neighbors. In experiments, the proposed unsupervised approach is compared with 31 state-of-the-art models on the proposed dataset and outperforms 30 of them, including 19 image-based classic (unsupervised or non-deep learning) models, six image-based deep learning models, and five video-based unsupervised models. Moreover, benchmarking results show that the proposed dataset is very challenging and has the potential to boost the development of video-based SOD.
A Modified Blind MMSE Multi-user Detection Algorithm Based on Subspace Tracking

A modified blind MMSE multi-user detection (MUD) algorithm based on subspace tracking is presented. The modified MMSE just employs signal subspace and avoids performance deterioration induced by eigenvalue estimation error. The proposed method exploits the orthogonal projection approximation subspace tracking (OPAST) algorithm for subspace estimation, since it guarantees the orthogonality of the weight matrix spanned by the signal subspace in every iteration, which must be meet in the modified detector. The numerical simulation results show the substantial performance improvement of our suggested approach over OPAST MUD and PASTd MUD.
Quantization of UWB TR receiver with slightly frequency shifted reference

To eliminate the requirement for a delay unit capable of processing wideband signals in a conventional UWB transmitted reference (TR) receiver, the slightly frequency shifted (SFS) reference UWB signaling scheme has been proposed in the literature. Motivated by the flexibility of the digital systems and the availability of sophisticated digital signal processing circuits, this paper proposes a digital implementation of the SFS TR UWB receiver. Performance of such a digital receiver is derived and evaluated based on the channel measurements from the intra-vehicle environments.
Reliability Evaluation of Distribution System Considering Composite Uncertainty Factors

Uncertainty factors such as unavoidable weather conditions and aging of components with time-varying process are compositely considered in the paper in reliability evaluation of distribution system. A method of distribution system reliability evaluation is introduced by considering uncertainty factors combined with sequential Monte-Carlo simulation method. Reliability and economic indices of load points and system can be calculated. Reliability of IEEE-RBTS-bus5 system is evaluated in the paper, which can illustrate different effects on reliability indices for weather environments and component aging factors. The results of reliability evaluation considering uncertainty factors may be in line with practical situation, which supports references of decision analysis for operating planners.
A density-based quantitative attribute partition algorithm for association rule mining on industrial database

Quantitative attribute partition is an important work of association rule mining, which is widely applied in industrial control at present, and the current partition methods are not suitable for the industrial database, which is generally large, high-dimensional and coupling. The paper proposes a density-based quantitative attribute partition algorithm for industrial database. The proposed algorithm uses an improved density-based clustering algorithm to detect the clusters. The clusters are agglomerated to form the new clusters according to the proximity between clusters and the new clusters are projected into the domains of the quantitative attributes. So the fuzzy sets and the membership functions used for partition are determined. We performed the experiments on a test database and a real industrial database. The experiments results verify the proposed algorithm not only can partition the quantitative attributes of industrial database successfully but also has the higher partition effectiveness.
Analysis of robotic workspace based on Monte Carlo method and the posture matrix

With the development of industrial automation, the application of intelligent robots has been widespread increasingly, but it is difficult to accurately describe robotic workspace. Currently workspace analysis methods include analytic method, graphic and numerical methods, but these common methods have many shortages. This paper presents a method of robotic workspace solution, which combines the theory of Monte Carlo method with posture transformation matrix, Monte Carlo method is used to sample by complying uniform distribution for determining each robot joint motion variables. These joint motion variables that are obtained by sampling are applied for terminal posture transformation matrix to get the posture workspace points, which constitute workspace, and MATLAB platform is applied to draw three-dimensional workspace and plane projection map, with the benefits of intuitive, fast, comprehensive, which provides a new way for the evaluation and design of robotic workspace.
Adaptive IMC Design Using Multiple Models

In this paper, an adaptive IMC controller using just-in-time learning (JITL) technique for nonlinear process control is proposed. Based on a set of linear models obtained on-line by the JITL, not only the parameters of IMC controller are updated, but also IMC filter parameter is adjusted on-line by an updating algorithm derived based on the Lyapunov method to guarantee the convergence of JITL's predicted tracking error. Simulation results are presented to demonstrate the advantage of the proposed adaptive IMC design over its conventional counterparts.
A bandwidth allocation strategy for train-to-ground communication networks

This paper formulates the bandwidth allocation problem in train-to-ground wireless communication networks in operational process of trains. It is shown that the Nash Bargaining game provides an Asymmetric Nash Bargaining Solution which is fair to bandwidth allocation problems in different services. We proposed a bandwidth allocation model for train-to-ground communication system. It can effectively reflect allocation strategies for services with different bargaining power. We define a dynamic adaptive function of bargaining power in order to match utility functions under diverse bandwidths. Easily to implement as it is, an algorithm for bandwidth allocation is derived and then simulated. The simulation show that the proposed scheme has high rate of resource utilization, and is suitable for train-to-ground communication systems.
An algorithm to adjust a rigid CT-SPECT fusion so as to maximize tumor counts from CT VoI in I-131 therapies

The accuracy of the estimate of tumor I-131 activity in therapy patients using CT-SPECT fusion is difficult to establish. In our work, we have had the impression that a tumor volume of interest (VoI) from CT sometimes does not perfectly overlay the true position of the tumor in the SPECT image set. However, the magnitude of the difference between the activity estimate from the procedure and that from a perfect overlay is uncertain. Although we have not estimated that magnitude, we have investigated how much the activity estimate increases if we apply a last variation on the fusion to change the location of the tumor VoI so as to increase tumor counts. The results show that the algorithm can be effective in registering tumors in CT and SPECT locally as proved by visual checks of the optimized location of the tumor VoI in SPECT. For 14 tumors in seven patients the increases in tumor counts average 6.65%. The maximum increase is 26.7%.
A low power SiGe HBT LNA utilizing serial inductance for wideband matching

A UWB LNA (low noise amplifier) based on 0.35 ¿m SiGe BiCMOS technology is presented in this paper. This LNA adopts a resistance feedback topology to optimize the gain and noise figure. The serial inductance at the base is used to matching input impedance and decreasing group delay variation. The simulation results indicate that the gain of LNA reaches 12.5 dB with the variation of 1.9 dB and the power consuming is 6.3 mW in full band from 3.1 GHz to 10.6 GHz. This SiGe UWB LNA exhibits less than 5 ps group delay variation and less than 3.85 dB NF over the entire band.
Direction finding based on cat swarm optimization for bistatic MIMO radar

In the paper, the maximum-likelihood (ML) algorithm is employed to resolve the difficulty of direction finding for bistatic multiple-input multiple-output (MIMO) radar. In order to obtain the global optimal solution of ML algorithm, the cat swarm optimization (CSO) is used to solve the ML equation, which has the advantages of low computational complexity and fast convergence speed. Thus, a novel direction finding approach called CSO-ML is proposed, and it is effective to find coherent and independent signal sources for bistatic MIMO radar. Monte-Carlo simulations show that the proposed CSO-ML can obtain higher accuracy and success rate of estimation compared with previous classical direction finding approaches of bistatic MIMO radar.
Finite Element Analysis of Complex Antennas and Arrays

Various technical issues are addressed in the frequency- and time-domain finite element analysis of complex antennas and arrays that may consist of fine structures and composite materials. The paper starts with the finite element formulation of a generic antenna problem. Formulation for the modeling of general electrically and magnetically dispersive, lossy, and anisotropic materials in the time-domain finite element analysis is presented for the first time. This is followed by discussion of three typical techniques for truncation of the finite element computational domain via the use of absorbing boundary conditions, perfectly matched layers, and boundary integral equations. It then describes the modeling of antenna feeds using a current probe (including an improved model), a voltage gap, and a waveguide port boundary condition. After that, numerical approaches to modeling infinite phased arrays, large finite arrays, and antenna-platform interaction are presented, including two novel domain decomposition algorithms in both the frequency and time domains. Numerical examples are given to demonstrate the capability and application of the finite element analysis of a variety of complex antennas and arrays.
Image processing for artist identification

A survey of the literature reveals that image processing tools aimed at supplementing the art historian's toolbox are currently in the earliest stages of development. To jump-start the development of such methods, the Van Gogh and Kroller-Muller museums in The Netherlands agreed to make a data set of 101 high-resolution gray-scale scans of paintings within their collections available to groups of image processing researchers from several different universities. This article describes the approaches to brushwork analysis and artist identification developed by three research groups, within the framework of this data set.