nils-herrmann/clean_scirepeval huggingface dataset:
A Ontological Collaborative Framework for Bussiness Process Integration

With the development of web services and its extension with Semantic Web augmented-Semantic Web Services (SWS), the modern approaches for business-to-business integration (B2Bi) focus on their business process integration between enterprises. Cross-enterprise collaboration is one of challenges on the B2Bi research nowadays. With the support of Semantic Web technologies, the gap between business and IT communities has been reduced in order to tackle the challenge. Semantic Web-based approaches for BPM have been foreseen as a promising solution with taking advantages of Semantic Web technologies such as ontologies, SWS. Taking into account the challenge of dynamically forming collaborative business processes with attached services into the execution, in this paper, based on our previous work, we propose a semantic framework for forming a dynamic collaboration of business processes within our BizKB systems for across-enterprise collaboration. We focus on a dynamic service discovery based on the consensus methodology.
A new LMI based H∞ observer design method for Lipschitz nonlinear systems

This note deals with H∞ observer design for Lipschitz nonlinear systems. Thanks to a new and judicious use of the Young's relation, new and less conservative LMI conditions are proposed to solve the problem of observer design. Two LMI design methods are provided. First, we propose a new enhanced LMI technique that allows to improve the standard LMI methods for Lipschitz systems. A second method is proposed to improve more the first one. It consists in combining the first method and the well known LPV approach. This technique exploits the advantages of the LPV approach for larger Lipschitz constants and in the second time, it allows to reduce the high number of LMIs of the classical LPV method. An application to a neural mass model is presented to show the effectiveness of the proposed method.
A Workload Prediction Approach Using Models Stacking Based on Recurrent Neural Network and Autoencoder

Workload prediction in computing systems like Cloud and Grid is an essential prerequisite for successful load balancing and achieving service-level agreements. However, since workloads in different systems and architectures have varied characteristics, providing an accurate single prediction model can be very challenging. Therefore, in this paper we have designed and implemented a model of stacking prediction algorithms to predict workload time series in Cloud and Grid systems using Recurrent Neural Network and Autoencoder. We have also performed experiments with several datasets containing different workload types and conducted comparisons with each component algorithm as well as the fixed weighted optimal combination value. Experimental results show that our model achieves lower average NRMSE in 3 datasets than the fixed weighted optimal combination value, and outperforms the component algorithms with improvements in NRMSE from 7.43% to 12.45%.
Design of Balanced QPSK Space-Time Trellis Codes for Several Transmit Antennas

A new class of QPSK space time trellis codes (STTC) for several transmit antennas is proposed in this paper. We call these codes balanced STTC because they use the points of the constellation with the same probability. Comparing to known codes, these codes offer the best performance. Therefore, the systematic search for good codes can be reduced to this class. It is shown that all the best published codes are balanced. The paper presents the design of these balanced STTC and gives a complete list of the best 4-state codes for 2 transmit antennas. Several 16-state balanced codes for 2 and 3 transmit antennas are also given.
A Hybrid Approach for Control Flow Graph Construction from Binary Code

Binary code analysis has attracted much attention. The difficulty lies in constructing a Control Flow Graph (CFG), which is dynamically generated and modified, such as mutations. Typical examples are handling dynamic jump instructions, in which destinations may be directly modified by rewriting loaded instructions on memory. In this paper, we describe a PhD project proposal on a hybrid approach that combines static analysis and dynamic testing to construct CFG from binary code. Our aim is to minimize false targets produced when processing indirect jumps during CFG construction. To evaluate the potential of our approach, we preliminarily compare results between our method and Jakstab, a state-of-the-art tool in this field.
A three-phase cascaded H-bridge quasi switched boost inverter for renewable energy

Recent years, multilevel inverters have become more attractive for researchers due to low total harmonic distortion (THD) in the output voltage and low electromagnetic interference (EMI). This paper proposes a three-phase cascaded H-bridge quasi-switched-boost inverter (CHB-qSBI). The advantages of the proposed inverter are as follows: buck-boost voltage with single stage power conversion, reduced passive components and shoot-through immunity. Furthermore, the dc-link voltage of each module can be controlled by individual shoot-through duty cycle to achieve the same values. Therefore, the proposed inverter solves the imbalance problem of the dc-link voltage in the traditional inverter. The operating principle and control strategy for the proposed inverter are presented. The simulation results are shown to verify the operating principle of the three-phase cascaded H-bridge quasi-switched-boost inverter.
Definition of linearly dependent screws in singularity configurations of parallel mechanisms and experimental based on computing of the system

This paper examined the parallel mechanisms such as Stewart-Gough platform, for which an algorithm for determining the groups of linearly dependent screws that arise in singular condition. The algorithms to determine the model of mechanism take into account singularities configuration based on screw theory are proposed, the criterion of closeness to singularity is determined, the basic impact modeling results of parallel mechanisms. The research results on issues of singular condition of the parallel mechanism, which uses screw theory and Plücker coordinates. The experimental based on computation and determining the parameters of kinematic, dynamics and simulation for the control parallel mechanisms are considered. Speaking of which resolved the relations velocity, acceleration between the moving platform with the legs in the application; and relationship between external forces acting on the moving platform with forces on the legs of the system.
Comparative study of railgun housings made of modern fiber wound materials, ceramic, or insulated steel plates

The acceleration in electromagnetic railguns of projectiles with a mass of several hundreds of grams up to velocities ranging between 2000 and 3000 m/s requires currents with intensities of several megamperes. In ISL rail launchers, the repulsion forces created by these currents acting on the rails can reach values in the order of 20 MN/m. The housing of the launcher has to withstand these high mechanical stresses to maintain the rails in position and thus to keep the caliber constant. A comparative study of different possibilities of housings is presented. The limits of the actual fiber wound materials are shown and a selection of new insulating materials capable of withstanding the mechanical stresses is given. We also present the concept of a housing made of insulated steel plates allowing a good mechanical stiffness combined with a minimum loss due to eddy currents in steel. In particular, we show that the good mechanical behavior of the steel plate housing makes it possible to reach the same overall efficiency as that obtained with a fiber-wound material housing.
An Efficient Model for Cooperative Caching in Mobile Information Systems

Data availability in mobile information systems is lower than in traditional information systems due to its limitations of wireless communication such as low bandwidth, instability, and easy disconnection. Cooperative data caching is an attractive approach to this problem. This paper proposes an efficient approach for cooperative caching in mobile information systems. We use references to share data among client’s caches. We evaluated and demonstrated the effectiveness of our approach by experiments on simulation datasets.
Congestion-aware and hybrid routing protocol for vehicular ad hoc network

In vehicular ad hoc network (VANET), nodes have to cooperate to forward each other's packets through the networks. Every node, including source and intermediate nodes, has a fair opportunity to transmit a packet. Consequence, the hot spot may incur traffic congestion. The packet loss rate and the transmission delay are increased, but the throughput is decreased. On account of the contention for the shared channel, the throughput of each single node is limited not only by the channel capacity, but also by the transmissions in its neighborhood. Additionally, the network throughput still restrict by the channel capacity. Some other related works using multiple channels simultaneously to transmit packets without interfering each other increases the throughput. But if the traffic load is heavy, these schemes may trigger off more serious packet loss on the contrary because they do not consider the congestion problem especially in VANET environment. In this paper we use cross layer approach to design routing protocol for VANET with aim to restrict the number of packets of every flow passing by congested nodes. Firstly, we estimate congested probability at each node by using MAC overheads, quality of link, and data rate. Subsequently, we use congested probability assessment as route metric. This method enhances link stable and network throughputs. For building routing protocol operation we use hybrid model (inherit good chacters from proactive and reactive routing protocols). It helps restrict route overheads and fast convergence of route discovery process. The simulation results illustrate our prominent proposed routing protocol.
Bit Error Rate Performance of Multiple-Channel OTDM Demultiplexer Employing A Chained Symmetric Mach-Zehnder Switch

This paper presents a high-speed multiple-channel optical time division multiplexed (OTDM) demultiplexer based on a chained symmetric Mach-Zehnder (CSMZ) switch. In CSMZ switch semiconductor optical amplifier (SOA) are shared between two chained arms in contrast to the MZ based multiple-channel demultiplexers where there is an SOA in each arm. The analysis for bit error rate (BER) and the average received power penalty is presented and the results are compared with the simulated data. It is shown that the power penalty incurred is highly dependent on the value of coupling ratio and the channel number.
Bandwidth allocation based on declared UPC parameters in ATM networks

We present a new method of calculating the required bandwidth for ATM connections. We first develop analytical models for bandwidth allocation of constant bit rate (CBR) and variable bit rate (VBR) services based on the declared usage parameter control (UPC) parameters. We then derive the closed form expressions for both service classes, and we also provide a numerical analysis in which there exists a close relationship between the quality of service (QoS) parameters (cell loss and delay parameters) and network resource (link capacity and buffer size). The closed form expressions can be used for a simple but efficient bandwidth allocation scheme for the call admission control (CAC) function.
An effective ant-based algorithm for the degree-constrained minimum spanning tree problem

The minimum spanning tree problem with an added constraint that no node in the spanning tree has the degree more than a specified integer d, is known as the degree-constrained minimum spanning tree problem. Finding the degree-constrained minimum spanning tree of a graph is a well-studied NP-hard problem. This paper presents an effective ant-based algorithm for the degree-constrained minimum spanning tree problem. Experimental results on a benchmark set of problem instances show that the algorithm performs very well against previous algorithms.
A vernier regulator for ILC Marx droop compensation

A two-part compensation scheme, Vernier Regulation, has been applied to offset the voltage droop (40% without correction) in a Marx-topology klystron modulator developed for the International Linear Collider (ILC). Coarse regulation, ±5%, is achieved by turning on additional Main Marx cells (Delayed Cells) sequentially as the droop reaches the cell voltage (11 kV). Further regulation to ±0.5% is achieved by adding a small Marx in series with the Main Marx. This Vernier Marx is composed of sixteen, 1.2 kV cells that are assembled as a seventeenth cell in the Main Marx. These Vernier Cells are turned on sequentially to generate a series of discrete corrections to the droop in the Main Marx cells with a step size ≤1% of the output voltage. As the required correction reaches 11 kV, all Vernier Cells are turned off synchronously with the turn on of a Delayed Cell. There are up to five Delayed Cells and six Vernier Marx cycles during each ILC Marx output pulse. The Vernier Marx has a local control system that will detect and respond to over-voltage and over-current errors. In this paper, a detailed description of the design, implementation and testing of the Vernier Marx is presented.
A fusion method of geometric and topological features for boundary-based shape matching and retrieval

In this paper, an efficient method for boundary-based shapes matching and retrieval in the presence of occlusion is presented. The geometric and topological information of boundary curves are encoded in the form of longest common sub-curves (LCS) graphs and their similarity is estimated by graph matching. B-spline is used for approximating the original boundary, then inflection points are detected to split such a Bspline to convex/concave segments. The characteristic string is constructed based on these segments' canonical frame. After LCS candidates are found, their graphs, which are constructed using their segments as vertices and the weighted walkthrough (WW) between two segments as edges, are compared to obtain the optimal match. The experimental results and comparisons demonstrate that the proposed method outperforms traditional boundary-based methods in shape matching and it enhances the quality of inexact shape retrieval
An evaluation of quality metrics for 360 videos

360 videos are becoming more and more popular on video streaming platforms. However, a good quality metric for 360 videos is still an open issue. In this work, we investigate both objective and subjective quality metrics for 360 videos. The goals are to understand the perceived quality range provided by existing mobile 360 videos and, especially, to identify appropriate objective quality metrics for 360 video communications. To that end, a subjective test is conducted in this study. Then, the relationship between objective quality and subjective quality is investigated. Especially, ten objective quality measures are computed, considering the coding distortion measurement, cross-format distortion measurement, and end-to-end distortion measurement. It is found that most of the objective quality measures are well correlated with subjective quality. Also, among the evaluated quality measures, PSNR is shown to be the most appropriate for 360 video communications.
Application of multitemporal ERS-2 synthetic aperture radar in delineating rice cropping systems in the Mekong River Delta, Vietnam

The authors report the use of multitemporal ERS-2 satellite synthetic aperture radar (SAR) images in delineating and mapping areas under different rice cropping systems in the Mekong River Delta, Vietnam. Change index maps were generated from seven images acquired between May and December 1996. Using a 3-dB threshold, the pixels in each change index (CI) map were classified into one of three classes: Increasing, decreasing, or constant backscattering. Five of the CI maps were used to generate a composite map with 243 possible change classes. These change classes were grouped into thematic categories of rice cropping systems using two methods: human visual inspection and a semiautomatic hierarchical clustering algorithm. The derived thematic maps were compared with SPOT scenes acquired during the same rice seasons.
Dental intraoral system supporting tooth segmentation

Embedded systems are being further developed and applied in medical devices. In this paper, we present an embedded design for dental intraoral system which supports dental image capturing and image tooth segmentation. This device assists dentists in diagnosis by using dental images, which is captured from dental camera. Moreover, we propose advanced features for the dental intraoral system including touch screen with Vietnamese graphic user interface (GUI), dental image processing, patient records, and dentist's diagnosis note. Especially, the segmentation of teeth is important for examining and extracting teeth features from dental images. A teeth segmentation method based on active contour without edge algorithm has been proposed in this paper. Consequently, our system is portable, economic and ready to be applied at dental clinics. The system can help dentists examine at patient's home and voyages, not only in clinics.
A new approach for frequency analysis of complex fractionated atrial electrograms

Atrial fibrillation (AFib) is the most common cardiac arrhythmia. Areas in atrial tissue with complex fractionated atrial electrograms (CFAEs) are among others responsible for the maintenance of AFib. Those areas are ideal target sites for ablation to eliminate AFib and restore sinus rhythm. As CFAEs are associated with high fibrillatory frequency, automated identification of CFAEs with spectral analysis helps developing objective strategies for AFib ablation. While the application of current techniques is restricted, this paper introduces a new approach to determine characteristic frequencies during AFib. By using Teager's energy operator we calculate the signal envelope and study its spectrum after Fast Fourier Transformation. Harmonic analysis of distinctive peaks in the power spectrum is carried out to assess characteristic frequencies of a CFAE. While the currently available methods only find one dominant frequency in the spectrum of the signal, our method is capable to find multiple characteristic frequencies, if present. Since it is believed that during AFib the atrium is activated by one or multiple wavelets, our method opens new opportunities for investigation of multiple wavelets propagation.
Current ratios: a self-scaling technique for production I/sub DDQ/ testing

The use of a single pass/fail threshold for I/sub DDQ/ testing is unworkable as chip background currents increase to the point where they exceed many defect currents. This paper describes a method of using "current signatures" which uses only simple comparisons on the tester, and which automatically scales with process variations which give a wide range of background currents. Dynamic thresholds are used, based on the ratio of maximum to minimum current. Using a single I/sub DDQ/ measurement for each die, upper and lower comparator values are set, against which I/sub DDQ/ for each vector in the suite is compared. Production data is presented to verify the validity of the method.
Adaptive grey predictor-based controller for force control of EHA system

This study aims to develop an effective control approach for force control of a typical EHA system. This control scheme is considered as an advanced combination of a feedforward neural network — based PID (FNNPID) controller and a fuzzy grey predictor (FGP), shortened as feedforward neural network fuzzy grey predictor (FNNFGP). Here, the FNNPID controller is used to drive the system to desired targets. Meanwhile, the FGP predictor with self-tuning ability of the predictor step size takes part in, first, estimating the system output in the near future to optimize the controller parameters in advance and, second, creating a compensating control signal accordingly to the system perturbations and, consequently, improving the control performance. Real-time experiments have been carried out to investigate the effectiveness of the proposed control approach.
An experimental acoustic SFBC-OFDM for underwater communication

Recently underwater wireless communication has been receiving a lot of attention as it is essential to facilitate new industries and applications such as deep sea mining, ocean monitoring, submarine communication, and so on. Latest studies have showed Space-Frequency Block Code (SFBC) OFDM which was studied thoroughly in radio wireless communication is a promising candidate for underwater acoustic communication. However, currently experimental results of acoustic SFBC-OFDM in underwater environment is quite rare. In this paper, we propose a transceiver architecture of acoustic SFBC-OFDM, and show experimental results taken in Shizuoka, Japan. Additionally, we propose a method for compensating sampling rate error due to imperfection of equipment. Overall, our system consists of 2 transmitters and 4 receivers, utilizing an ultrasonic signal from 20(kHz) to 28(kHz), 160 sub-carriers, QPSK, 16QAM, 64QAM modulation, sampling speed of 96(kHz). Experimental results confirmed that our proposal system achieves 7.5 (Kbit/sec) data throughput, over more than 30(m) in vertical direction, under harsh channel conditions.
Analysis of CCME: Coevolutionary Dynamics, Automatic Problem Decomposition, and Regularization

In most real-world problems, we either know little about the problems or the problems are too complex to have a clear vision on how to decompose them by hand. Thus, it is usually desirable to have a method to automatically decompose a complex problem into a set of subproblems and assign one or more specialists to each subproblem. The cooperative coevolutionary mixture of experts (CCME) model was designed to automatically decompose problems by combining the global optimization power of cooperative coevolution with the divide-and-conquer ability of mixture of experts. This paper analyzes how CCME decomposes complex classification problems through a principal-component-analysis-based visualization tool. The visualization shows that CCME decomposes the problem by driving different experts toward different regions of the input space. The paper also investigates the effect of regularization, using learning by forgetting (LF), on CCME. LF significantly reduces the structural complexity of CCME while maintaining the classification accuracy.
A Trajectory-based Parallel Model Combination with a unified static and dynamic parameter compensation for noisy speech recognition

Parallel Model Combination (PMC) is widely used as a technique to compensate Gaussian parameters of a clean speech model for noisy speech recognition. The basic principle of PMC uses a log normal approximation to transform statistics of the data distribution between the cepstral domain and the linear spectral domain. Typically, further approximations are needed to compensate the dynamic parameters separately. In this paper, Trajectory PMC (TPMC) is proposed to compensate both the static and dynamic parameters. TPMC uses the explicit relationships between the static and dynamic features to transform the static and dynamic parameters into a sequence (trajectory) of static parameters, so that the log normal approximation can be applied. Experimental results on WSJCAM0 database corrupted with additive babble noise reveals that the proposed TPMC method gives promising improvements over PMC and VTS.