nils-herrmann/clean_scirepeval huggingface dataset:
Communication-Based Train Control (CBTC) Systems With Cooperative Relaying: Design and Performance Analysis

A communication-based train control (CBTC) system is an automated train control system using bidirectional train-ground communications to ensure the safe operation of rail vehicles. CBTC systems have stringent requirements for communication availability and latency. Most existing CBTC train-ground communication systems work in the infrastructure mode without train-train communications. Due to unreliable wireless communications and frequent handoffs, existing CBTC systems can severely affect train control performance, train operation efficiency, and the utility of the railway. In this paper, we use recent advances in cooperative relaying to enable train-train communications and, consequently, enhance the train control performance of CBTC systems. Trains act not only as end communication points but as relays for other trains as well. Unlike existing works on cooperative relaying, in this paper, linear quadratic cost for the train control performance in CBTC systems is considered as the performance measure. We jointly consider cooperative relaying and handoff decision issues in CBTC systems. Moreover, to mitigate the impacts of handoff latency on the train control performance, we propose an optimal guidance trajectory calculation scheme in the train control procedure that takes full consideration of the tracking error caused by handoff latency. Simulation results show that the train control performance can be substantially improved in our proposed CBTC system with cooperative relaying.
Design of a novel passive endoscopic robot for sinus surgery

In order to overcome the disadvantages of traditional Functional Endoscopic Sinus Surgery (FESS), a novel passive endoscopic robot for sinus surgery is designed in this paper. This paper mainly focuses on the design of the prototype of a novel passive endoscopic robot and the lock methods of the passive joints. The design of the robot is divided into two parts-the position arm and the end-effector with an endoscope. A parallelogram based passive position arm is proposed and detailed analyzed then, and a three spherical joints based end-effector is proposed and detailed analyzed. Hereafter, different lock methods for joints are discussed and evaluated for both passive position arm and end-effector. For passive position arm, a gear-like lock mechanism is proposed and detailed analyzed, and a bladder-spring based lock mechanism is proposed for the end-effector. The mechanical model of bladder-spring based lock mechanism is derived to guide the detailed design of the prototype of the robot.
Ensemble of support vector machines for heartbeat classification

This paper proposes a novel and simple method that uses the randomness of random matrix and SVM ensemble learning to discriminate eight types of heartbeats. We use random matrices to generate 15 groups of random features. Then we construct one SVM classifier on each group of random features along with a RR interval. The type of heartbeat is determined using majority voting strategy to combine 15 SVM classifiers. 3062 heartbeats obtained from the MIH-BIH electrocardiogram (ECG) database are used for experiments. The results show that our proposed method has an accuracy of 98.65% and is an effective method for heartbeat classification.
Numerical Study of the Thermal Stability of YBa2Cu3O7- δ Tapes Suffering Lightning Current

In this paper, we presented a numerical model that took into account both the thermal and the electromagnetic aspects to study the thermal stability of YBa2Cu3O7−δ  (YBCO) tapes suffering lightning current (LC). The electromagnetic and thermal equations have been implemented in finite-element method software in order to obtain a novel homogenization model. The validity of this model was verified by experiment. Based on the model, the distributions of the current and temperature in different layers were presented. The influence of the dimension and material type of different layers on the thermal stability was investigated in detail. The calculated results showed that increasing the width of a YBCO tape and the thicknesses of the encapsulation layer could decrease the maximum temperature. Moreover, the encapsulation layer made of copper is a more desired choice than that made of stainless steel to improve the thermal stability.
Self-Switching Classification Framework for Titled Documents

Ambiguous words refer to words that have different meanings such as apple, window, etc. In text classification they are usually removed by feature reduction methods like information gain. Sometimes there are too many ambiguous words in the corpus that we cannot simply throw them away, especially when classifying documents from the Web. In this paper we look for a method to classify titled documents with the help of ambiguous words. Titled documents are a kind of documents that have a simple structure containing a title and an excerpt. News, messages, and paper abstracts with titles are such examples. Instead of introducing another feature reduction method, we describe a framework to make the best of ambiguous words in the titled documents. The framework improves the performance of traditional bag-of-words classifier with the help of a bag-of-word-pairs classifier. We implement the framework using one of the most popular classifiers, multinomial naive Bayes (MNB), as a case in point. The experiments with three real life datasets show that in our framework the MNB model performs much better than traditional MNB classifier and the naive weighting algorithm, which simply puts more weight on the title words.
A new sliding-mode control algorithm with simulation

A new design approach of the sliding-mode variable structure controller basing on the eigenvector of the specific area is presented for the position tracking servo control system in this paper. In order to accelerate the reaching phase and reduce chattering, the exponential approach law is adopted as the control function. Simulation results show that the new control algorithm exhibits the better control performance than the classical control method. Moreover, its realization is simple and convenient.
Scalable layered multicast with explicit congestion notification

Many layered multicast (LM) congestion control schemes have been proposed to serve different users with heterogeneous bandwidth requirements. Most of the LM algorithms suffer from a large Internet Group Management Protocol (IGMP) leave latency and a sudden rate increase. Layered Increase/Decrease with Dynamic Layering (FLID-DL) was introduced to address these challenges. Nevertheless, FLID-DL can neither provide very good bandwidth fairness with TCP nor work well in the wireless environment with link loss. We propose the Extended FLID-DL (E-FLID-DL), by incorporating explicit congestion notification (ECN) into FLID-DL, to address these issues. E-FLID-DL not only improves bandwidth fairness with TCP, but also provides high throughput in a lossy network environment.
Novel Affinity Membrane Chromatography Technology: Purification of Pepsin Using Immobilized Reactive Dye Ligands

Novel membranes were prepared through covalently coupling of chitosan (CS) to activate nylon membrane after the reaction of the microporous nylon membrane with formaldehyde. Non-specific adsorption on the CS-coated nylon membrane decreased greatly. Yellow 3G-P/Reactive Red 120 were then covalently immobilized onto composite membrane as dye ligands. These Red 120/Yellow 3G-P-CS-membranes were used in the Pepsin adsorption studies. According to the results, it appears that Yellow 3G-P-CS-nylon membranes could be applied for separation and purification of Pepsin without causing any denaturation, much better than Red 120-CS-nylon membrane. Keywords-affinity chromatography; pepsin; adsorption;
A Novel Data Replication and Placement Scheme for Time-Shifted TV Cluster

As a new multimedia streaming service, time-shifted TV introduces new challenges in content distribution. A number of replication algorithms were proposed to alleviate the bandwidth bottleneck, but these algorithms are not suitable for time-shifted TV due to not understanding television user access behavior. In this article, we presented a new popularity model based on analyzing of television access pattern. By using the mode, we proposed a classification-based replication algorithm and a novel replicas placement algorithm, named as least load proportion first placement (LLPFP). The algorithms focus on the time-varying nature of time-shifted TV, and use previous stored information to reduce the cost of redeploying. Simulation reveals that the proposed algorithms are cost-effective on improving the performance of time-shift TV servers in terms of total outgoing bandwidth requirement.
Vicarious calibration of MODIS visible and near infrared bands using gongger test site

On 29 and 31 May 2006, a comprehensive vicarious calibration experiment for the Moderate Resolute Imaging Spectroradiometer(MODIS) visible and near-infrared bands was performed at Gongger test site located in Inner Mongolia, which is a flat and uniform area. The reflectance-based method was used for calibration of MODIS visible and near-infrared bands. In situ measurements of surface and atmospheric conditions were carried out. By computing the surface reflectance of the site, it was concluded that the site was appropriate for calibration because of its stable and uniform characteristics. These data were then inputted to a radiative transfer code, 6S, to compute top-of- atmosphere (TOA) radiances and TOA reflectances, which were compared with the MODIS on-board calibration results. The in situ estimated results were in good agreement with the MODIS on-board calibration results on May 31 with the variations about 2%, while vicarious calibration results on May 29 were slightly inconsistent with those of on-board calibration, whose differences were about 7%.
Anchor graph hashing with semantically consistent graph

Hashing has become a popular technique for fast similarity search in massive databases. However, learning compact binary codes which accelerates similarity search remains a challenge. In order to reduce the computational complexity of mapping semantically similar data to close codes, an anchor graph hashing (AGH) approach is used to build an approximate neighborhood graph using anchor graph, which allows constant time hashing of a new data point by extrapolating graph Laplacian eigenvectors to eigenfunctions. However, the Euclidean distance is mostly used to construct the anchor graph Laplacian in AGH, which may not reflect the semantic similarity of the data points. In this paper, we propose a method to directly optimize the anchor graph Laplacian directly based on the label smoothness and the rank pairwise loss function in the hash function learning process. The learned anchor graph, which represents the semantic similarity better between data points and anchors, is then applied to AGH for effective binary code learning. Extensive simulations are conducted on the publicly available dataset to demonstrate the effectiveness of the proposed approach.
CCN-AMI: Performance evaluation of content-centric networking approach for advanced metering infrastructure in smart grid

Advanced Metering Infrastructure (AMI), as the totality of systems and networks to measure, collect, store, analyze, and use energy usage data, is supposed to the key component that should be preferentially constructed for smart grid. In the meanwhile, content-centric networking (CCN) is perceived as a promising approach where the content itself becomes the core of communication instead of the address or location in the future internet research. Based on its caching advantage, it is widely believed that CCN can effectively reduce the AMI network bandwidth. This paper aims to apply the CCN approach on AMI system, which is called CCN-AMI. To the best of our knowledge, this is the first attempt to distribute contents or requests based on CCN in AMI system. Moreover, a simulation-based performance evaluation is employed to evaluate the effectiveness of the proposed CCN-AMI approach in traffic control for developing AMI system in smart grid.
Transformer fault diagnosis based on euclidean clustering and support vector machines

A new method based on Euclidean clustering and support vector machines is presented and constructed in the paper. According to the Euclidean distances between the transformer's state sorts, build the multi-classification model of support vector machines. The diagnosing experiments of different transformer testing scenarios show this method can avoid the blindness when building the multi-classifier, and can be used on transformer faults diagnosis commendably.
An Investigation on Security of Cognitive Radio Networks

Cognitive Radio Networks (CRNs) emerge as a possible solution for the lack of spectrum, and make different networks merge. However, security becomes the key problem need to be solved. Cognitive radio networks face not only traditional network security intrusion problems, but also unique security risks. In this paper, we investigate security issues in different classes which including spectrum security and security of network merge. Countermeasures are given from three aspects: security mechanism, key management and identity authentication.
Spectral Optimization of Three-Primary LEDs by Considering the Circadian Action Factor

For humans, nonvisual biological effects, which can be parameterized by the circadian action factor (CAF), are important for their health and work performance. In this paper, an approach by adjusting electrical currents of three-primary light-emitting diodes (RGB-LEDs) to tune the CAF and color coordinates to be close to those of the standard light with various correlated color temperature (CCT) (2700 K-6500 K) has been reported. This approach is based on deriving an empirical formula between the optical power and the electrical current. In order to meet the requirement of both high color rendering index (CRI) and better CAF, we theoretically perform further spectral optimization on RGB-LEDs and have found that peak wavelengths of 466, 547, and 615 nm for the blue, green, and red color component, respectively, turn out to be the best peak wavelength combination for obtaining both high CRI and high luminous efficacy of radiation of RGB-LEDs, while the CAF, CCT, and color coordinates of RGB-LEDs approach those of the standard light.
Research on Automatic Fuzzy Ontology Generation from Fuzzy Context

In this paper, we have integrated fuzzy logic in the formal context, developing fuzzy formal concept analysis to support the automatic generation of primitive fuzzy ontology that can deal with uncertain information. The proposed automatic fuzzy ontology generation approach consists of the following steps: first, fuzzy formal concepts are created through fuzzy formal context; then, the decision rules from the generated formal concept are obtained using the implicative relations between two fuzzy concept lattices; and next, Fuzzy clustering is adopted to promote the fuzzy concept hierarchy of fuzzy concept lattice; finally, a primitive fuzzy ontology is constructed according to the concept hierarchy structure. A complete fuzzy ontology can be generated through the expanding of primitive ontology. Since the fuzzy concept lattice should be from specific fuzzy formal context, the proposed automatic generation approach is basis on the concept hierarchy structure which supporting concept learning, thus, for each different application, it is suitable to pursue the own fuzzy domain ontology model automatically.
The application of association rules of data mining in book-lending service

Association rule is an important technology in Data mining. In library lending services, it can be used to analyze and add up the library loan services and information, and can scientifically carry out proposed borrow and recommended books to improve the efficiency of library management. By case analysis, it shows that the apriori algorithm in the association rule can effectively tap the hidden behind the valuable information in the data, and provide decision support for the library services and help libraries to carry out personalized information services.
Modeling and Analysis of Intelligence Assurance System Based on the Complex Networks Theory

Using the theory related to the complex network, the system of electronic countermeasures intelligence assurance is abstracted, the rules and arithmetic of system modeling are settled down. Then, the complex network model of electronic countermeasures intelligence assurance system is built. Finally, simulation of the model and some parameters are carried out. The simulation result indicates that the model of this paper accords with the practicality of electronic countermeasures intelligence assurance system, and it provides a way to research the modeling of other systems.
Hierarchical piece-wise linear projections for efficient intra-prediction coding

Deep learning in compression is indeed a high-dimensional regression problem that try to exploit large amount of training data with a good trade-off of the Degree-of-Freedom (DoF) in prediction model. In particular for the High Efficiency Video Coding intra prediction problem, how to best predict pixels from surrounding context is the key efficiency challenge. In this work, we developed an alternative hierarchical piece-wise linear projection based on Canonical Correlation Analysis (CCA) method that allows for much larger DoF in the modeling in intra-prediction. Besides, we try to predict the transform coefficients in transform domain instead of the pixel values in spatial domain to reduce the DoF and obtain more general CCA model. Simulation results yield interesting coding gains, and the proposed framework has a lot of flexibility in designing the prediction architecture and rate-distortion trade-offs.
A Semantic Web Service-Oriented Model for E-Commerce

E-commerce on the Internet provides a high level of flexibility and openness, but it still has many drawbacks due to the heterogeneity of the exchanged information. Web Services have added a new level of functionality on top of current Web, enabling the use and combination of distributed functional components within and across company boundaries, but they offer only syntactical description that are hardly amenable to automation. Developments in the field of semantic Web services (SWS) show the opportunity of adding higher semantic levels to the existing frameworks, to improve their usage and ease scalability. In this paper, we outline a semantic Web e-commerce in which data sources and services are made available through SWS, described by ontologies, allowing interoperability as well as reasoning to create a comprehensive response adapted to user goals. We present a semantic Web service oriented model for e-commerce, aiming to integrate the development of semantic Web services using the WSMO into ISR-III framework, it can also be applied to e-government.
Numerical simulation of the effect of the vertical shaft to the propagation laws of the compression wave in high-speed railway tunnels

The control equations use the Navier - Stokes of three-dimensional viscous, compressible, isentropic, unsteady flows, and the spatial discretization uses the cell-center finite volume method to do the numerical simulation of the propagation laws of the compression wave when the high-speed train pass through the tunnel with the vertical shaft, and the simulation results are consistent with the on-site test data perfectly. Detailed analysis of the effect of the vertical shaft shape, the cross-sectional area, the connecting forms of the shaft and tunnel to the propagation laws of the compression wave in the tunnel. Simulation results show that the processes of the propagation laws of the compression wave in the tunnel are complicated because of the vertical shaft. It should be comprehensively considered because the vertical shaft can cause secondary micro-pressure wave, although it makes the peak of the micro-pressure wave lower at the exit of the tunnel.
Joint Source-Channel Coding and Optimization for Layered Video Broadcasting to Heterogeneous Devices

Heterogeneous quality-of-service (QoS) video broadcast over wireless network is a challenging problem, where the demand for better video quality needs to be reconciled with different display size, variable channel condition requirements. In this paper, we present a framework for broadcasting scalable video to heterogeneous QoS mobile users with diverse display devices and different channel conditions. The framework includes joint video source-channel coding and optimization. First, we model the problem of broadcasting a layered video to heterogeneous devices as an aggregate utility achieving problem. Second, based on scalable video coding, we introduce the temporal-spatial content distortion metric to build adaptive layer structure, so as to serve mobile users with heterogeneous QoS requirements. Third, joint Fountain coding protection is introduced so as to provide flexible and reliable video stream. Finally, we use dynamic programming approach to obtain optimal layer broadcasting policy, so as to achieve maximum broadcasting utility. The objective is to achieve maximum overall receiving quality of the heterogeneous QoS receivers. Experimental results demonstrate the effectiveness of the solution.
A Study on Critical Current and AC Loss Characteristics of Novel 2G HTS Narrow Wires

In high-temperature superconducting (HTS) applications, the external magnetic field affects the performance of the critical current and the ac loss. In this study, to improve the performance, narrowing and twisting processes are first suggested for the second-generation (2G) HTS wires: the original wire with 4-12-mm width is incised into several narrow wires with the same width under 2 mm, and narrow wires are twisted around each other as tight as possible. Using the narrow wires, we prepared various types of novel wire samples with stacking and twisting structures. The main results show that the feasibility of the narrow wires with stack and twist structures is confirmed from both critical current and ac loss points of view.
Performance analysis of MPSK demodulation with different phase noise spectral shape

In this paper we study the MPSK demodulation performance with phase noise which is characterized by its power spectrum density. According to the conditional symbol error rates of MPSK, demodulation penalty with different phase noise spectral shape are derived. MPSK is a kind of constant envelope modulation, the signal envelope of which is not as sensitive as its phase. According to the model of single frequency phase noise, we connect the phase noise represented by its power spectral shape and the bit error rates of coherent demodulation. Evaluation of performance degradation due to the phase noise is analyzed over a Gauss channel. Then, the numerical analysis shows the effects of different phase noise spectral shape and different symbol rate for BPSK, QPSK and 8PSK signals.