nils-herrmann/clean_scirepeval huggingface dataset:
Application of Kano model to discuss tourist satisfaction on Hinoki village in Taiwan for ICASI 2016

This study adopts Kano Model to explore the relevance of the historical building, Hinoki Village, its quality and tourists' satisfaction. In order to improve the tourism and enhance its service quality, the study focuses on three aspects of Hinoki Village: space facilities, landscape and information. The data is processed by various statistical methods in the hope of improving the tourism of Hinoki Village.
Design of anti-lock braking system for electric vehicles via short-circuit braking

The slip ratio control problem in anti-lock braking system (ABS) is highly nonlinear and complicated. In this paper, a sliding mode controller is developed to generate appropriate torque for the driving motor of two-wheel electric vehicles that ensures optimality of the slip ratio for efficient vehicle brake. The design is based on a novel short-circuit braking mechanism to emulate the mechanical ABS for the traditional gas-powered vehicles.
Efficiency Improvement of GaN-Based LEDs With $ \hbox{SiO}_{2}$ Microrod Array and Textured Sidewalls

High-performance nitride-based light-emitting diodes (LEDs) grown with SiO2 microrod array have been demonstrated. The light output power of LEDs with SiO2 microrod array was 9.03% higher than conventional LEDs at the injection current of 20 mA. The improvement contributed to the enhancement of the light extraction efficiency, and epitaxial GaN film quality improved by direct heteroepitaxial lateral overgrowth with SiO2 microrod array. The light output power could be further enhanced by about 18.36% as compared with the conventional LEDs when adopting the textured sidewall surface which use buffered oxide etch to remove SiO2 microrod arrays and use NaOH to etch the sidewall again into an inverted pyramid shape. After the texturing process, the LEDs show higher electroluminescence intensity and broader far-field pattern. Furthermore, the LEDs with SiO2 microrod array and additional wet-etching process will not affect the electrical property.
Ultra High Power Light-Emitting Diodes with Electroplating Technology

Heat dissipation and thermal management of devices package are now a critical problem for applications of high power light emitting diodes (LEDs). In this paper, a novel package method with copper electroplating on the red, green, and blue LED chips were performed. With the copper plating layer, the endurable injection current of these LED chips can be increased easily from typical value of 350 mA to more than 1680 mA in room temperature; especially the input power of the GaN-based single chip blue LED can be increased up to 12W. The relative luminous intensity at 350 mA of the novel red, green, and blue LEDs (RGB LEDs) have 53%, 69%, and 23% enhancement respectively compared with those of the conventional packaged LEDs. When the injection current of these LED chips were increased to 850 mA , the relative luminous intensity of the novel RGB LEDs chips have 431% and 83%, and 18% enhancement respectively compared with those of the conventional packaged ones.
Immune Memory Network-Based Fault Diagnosis

In this paper, based on artificial immune network, a novel approach to immune memory network-based fault diagnosis methodology for on-line fault diagnosis system is presented. The diagnosis scheme consists of the memory cell network and the antibody network. They are employed to work together for network establishment, immune identification and antibody learning. Meanwhile, the key parameters of the approach are analyzed with experiments. In order to test the proposed network, the vibration signal of rolling bearing is selected as raw inputs due to its simplicity and efficiency. The results of the experiment confirm the performance of the fault pattern recognition and the strategy of `on-line' learning
Adaptive Object Tracking by Learning Hybrid Template Online

This paper presents an adaptive tracking algorithm by learning hybrid object templates online in video. The templates consist of multiple types of features, each of which describes one specific appearance structure, such as flatness, texture, or edge/corner. Our proposed solution consists of three aspects. First, in order to make the features of different types comparable with each other, a unified statistical measure is defined to select the most informative features to construct the hybrid template. Second, we propose a simple yet powerful generative model for representing objects. This model is characterized by its simplicity since it could be efficiently learnt from the currently observed frames. Last, we present an iterative procedure to learn the object template from the currently observed frames, and to locate every feature of the object template within the observed frames. The former step is referred to as feature pursuit, and the latter step is referred to as feature alignment, both of which are performed over a batch of observations. We fuse the results of feature alignment to locate objects within frames. The proposed solution to object tracking is in essence robust against various challenges, including background clutters, low-resolution, scale changes, and severe occlusions. Extensive experiments are conducted over several publicly available databases and the results with comparisons show that our tracking algorithm clearly outperforms the state-of-the-art methods.
Synthesis of Genetic Clock with Combinational Biologic Circuits

The potential of genetic clock lies in its role to triggering logic reaction for sequential biological circuits. In general, biochemical reaction of the biological system is extremely slow. However, a square wave generator used as a genetic clock the transient response should be fast enough to catch the reaction change between two logic levels. Therefore, the requirement for instantaneous changes in logic status is not likely to exist in biological systems. This paper presents a method of synthesizing a genetic clock generator based on the combination of a toggle switch with two biological logic gates. A dual repressor is used to connect the two fundamental biologic circuits. Analysis of the characteristic responses of this genetic clock with its relation to the key parameters is provided.
Association Rule Based Context Modeling for Web Service Discovery

Web service is essential in achieving dynamic business process. With the dramatically increased number of Web services advertised in UDDI, Web Portal or Internet, how to locate the best Web service according to a user's requirement is becoming more and more important, which calls for efficient and effective Web service discovery mechanism. Considerable efforts have been attained in solving this problem among them semantic based approaches show encouraging result. However, when several semantically equivalent Web service candidates are returned by matchmaking process, how to discern which one is the most suitable one is a real challenge. This paper presents a framework by which provider's context and user's context has been explored to help understand the real need of a user. This framework uses association rule for context modeling of provider and user from Web service composition perspective. After modeling context, a ranking service is invoked to compare Web service candidates with user's requirement and then the best suitable potential Web service will be selected.
Extending Sample Information for Small Data Set Prediction

This paper proposes a method that focuses on creating new data attributes by using fuzzy operations for solving small dataset learning problems. Using the idea of fuzzy rules, the membership value of antecedents in each rule can be extracted from the data point. Therefore, in this research, those membership values will be deemed as new data features and the data dimensionality will be extended. To test the effectiveness of the proposed method, the data set with new data features and the one with no special treatment will be utilized respectively to build predictive models. Paired t-test is carried out to see how effective the proposed method can improve the learning on the basis of small sample sets.
Using Two Nodes and Neighbors Examining to Improve Positioning Capability in Sensor Networks

Traditional triangulation positioning requires that a node needs three position-known neighbors to be positioned. This requirement limits the positioning capability, or the number of nodes being positioned, particularly for sparse sensor networks. We propose a positioning approach, two nodes and neighbors examining, by which the node with less than three position-known neighbors may still be positioned as long as its surroundings provide enough useful information. Our simulation results show that the number of nodes being positioned may be dramatically improved. We also consider distance measurement errors which may cause triangulation fail. The two nodes and neighbors examining approach may be used to estimate positions. Besides, we discuss how to estimate positions for some special cases and refine the estimations, and then illustrate the simulation results
The angular dependence of AC transport losses for a BSCCO/Ag tapes in DC applied field

In the application of high temperature superconductors, the superconducting tapes are often exposed to magnetic fields with different orientations. Thus AC losses in such cases depend not only on the magnitude of the external magnetic field, but also on its orientation with respect to the tape surface. In this paper, AC transport losses of a BSCCO/Ag tape were measured at 77 K in 48 mT, 80 mT and 120 mT DC magnetic fields, respectively. The angle between the direction of the magnetic field and the wide side of the tape varied from 0 to 90 degrees with a step of 10 degrees. Using the theoretical model we had proposed for the angular dependence of critical current, we developed a theoretical model to describe the angular dependence of AC transport losses by modifying Norris formula. The comparison between the theoretical values and the measured data were presented and discussed.
The Construction Progress of a High-Tc Superconducting Power Substation in China

It is expected that superconducting technologies will play an important role in the future smart grid, because the application of superconductor technologies in the power grid can decrease power losses, relieve overload, avoid higher levels of transmission voltage, increase power transmission capacity, and improve power quality and grid stability. In recent years, high temperature (high-Tc) superconducting power technologies have achieved remarkable progress. High temperature superconducting (HTS) power equipment, such as HTS power cables, HTS transformers, high-Tc superconducting fault current limiters (SFCL), and high-Tc superconducting magnetic energy storage devices (SMES) have been demonstrated in the power grids of many countries. With the development of HTS power equipment, the construction of a HTS power substation is ready. In China, a 10.5 kV HTS power substation is under construction in Baiyin city, Gansu province. The substation integrates a HTS power cable, a HTS transformer, a HTS fault current limiter, and a high-Tc SMES. All these HTS power devices, which were previously developed by the Institute of Electrical Engineering (IEE), Chinese Academy of Sciences (CAS), have been demonstrated to operate for a long time in the commercial power grid. In this paper, the design and constructing progress of the HTS substation are introduced in detail.
Research and Implementation of Next Generation Network Intrusion Detection System Based on Protocol Analysis

An intrusion detection system which can work in IPv6 network environment is designed and implemented based on protocol analysis and pattern match technology in this paper. The system not only can fast detect system vulnerabilities and network intrusion events, but also possesses high accuracy and good performance. Furthermore, the system is tested using IDSwakeup. The test shows that the system can detect 90% of the attacking packets and lost hardly any packet when enormous and different types of vicious data packets generated by data packet generator are sent. So the system is efficient and quick-reacting IDS working in IPv6 environment.
Phase Contrast Imaging Methods to Study Waves and Turbulence in High Temperature Tokamak Plasmas

Phase contrast imaging diagnostic (PCI) is an internal reference beam interferometric technique which has been used successfully in high temperature tokamak plasma experiments to image line integrated plasma density fluctuations. The PCI technique utilizes a 18 deep grooved "phase plate" which is inserted into an expanded beam path, and with the aid of a detector array one is able to measure wavelengths and correlation lengths of fluctuations propagating perpendicular to the laser beam. In the Alcator C-Mod and DIII-D tokamak PCI experiments, a CO2 laser beam is used to probe low frequency (f = 1 MHz) instabilities and in addition, in C-Mod high power launched ICRF waves (80 MHz) are also monitored. The fluctuations studied in the past in Alcator C-Mod include the so-called "quasi-coherent mode" (a ballooning mode localized to the edge pedestal), semi-coherent TAE-like modes, including Alfven wave cascades, low frequency turbulence, and high power launched ICRF waves. The ICRF waves are detected by a heterodyne technique using optical modulation of the laser beam. The ICRF wave propagation studies have confirmed mode conversion into kinetic ion cyclotron waves (the shear wave branch) and electrostatic ion Bernstein waves. In DIII-D, PCI has been used to study low frequency turbulence during L to H mode transition, ELMs, and coherent edge modes during the quiescent H-mode. Signatures of zonal flows have also been observed in past experiments. While most of the past studies were limited to wavelengths equal or longer than the ion gyro-radius (ki = 1, f = 1 MHz ), new upgrades to the electronics and optics will allow detection of wavelengths and frequencies in the electron gyro-radius regimes (ke = 1, f = 20 MHz). This new capability will allow us to study the electron temperature gradient modes and the trapped electron mode, both being candidates for determining electron transport in magnetically confined plasmas. While spatial localization of long wavelength modes along the PCI laser beam is usually not possible, in the short wavelength regimes in a sheared magnetic field localization can be achieved by using a rotating masking plate in conjunction with the phase plate
Semantic Object Parsing with Local-Global Long Short-Term Memory

Semantic object parsing is a fundamental task for understanding objects in detail in computer vision community, where incorporating multi-level contextual information is critical for achieving such fine-grained pixel-level recognition. Prior methods often leverage the contextual information through post-processing predicted confidence maps. In this work, we propose a novel deep Local-Global Long Short-Term Memory (LG-LSTM) architecture to seamlessly incorporate short-distance and long-distance spatial dependencies into the feature learning over all pixel positions. In each LG-LSTM layer, local guidance from neighboring positions and global guidance from the whole image are imposed on each position to better exploit complex local and global contextual information. Individual LSTMs for distinct spatial dimensions are also utilized to intrinsically capture various spatial layouts of semantic parts in the images, yielding distinct hidden and memory cells of each position for each dimension. In our parsing approach, several LG-LSTM layers are stacked and appended to the intermediate convolutional layers to directly enhance visual features, allowing network parameters to be learned in an end-to-end way. The long chains of sequential computation by stacked LG-LSTM layers also enable each pixel to sense a much larger region for inference benefiting from the memorization of previous dependencies in all positions along all dimensions. Comprehensive evaluations on three public datasets well demonstrate the significant superiority of our LG-LSTM over other state-of-the-art methods.
Antilock braking control system for electric vehicles

In recent years, brushless DC motors (BLDCMs) have replaced brushed DC motors in the design of electric scooters (ESs). This study proposes a new antilock braking system (ABS) based on a slip ratio estimator for ES utilising the braking force generated by the BLDCM when electrical energy is released to the virtual load, yielding an effect analogous to the ABS control in gas-powered vehicles. Compared with mechanical ABS, the proposed design possesses the advantage of rapid torque responses because no mechanical parts needed. Current control design is used to adjust the braking torque, and the sliding-mode control strategy is adopted to regulate the slip ratio to attain the optimal road adhesion during emergency braking. A variety of experiments are conducted for functional and performance verification.
Influences of DBC metal layout on the reliability of IGBT power modules

This paper presents a study of the influences of DBC metal trace layout on the reliability of the high power IGBT module. The research is conducted on a seven-layer IGBT package model using finite element analysis simulation. A parametric study is carried out at different temperatures to simulate the thermal-cycling scenario. It shows in simulation that both total deformation and thermal stress are not balanced even at the symmetrical edges of the module. The stress is related to the metal trace area on the DBC, and larger metal area results in higher thermal stress. Thermal-cycling experiment results verify the analysis to a certain extent. With this knowledge, the paper proposes an improved layout by adding grids to the metal area. The new design can reduce thermal stress and achieve higher reliability of the module.
Quench Behavior of  ${\hbox {Bi}}_{2}{\hbox {Sr}}_{2}{\hbox {Ca}}_{2}{\hbox {Cu}}_{3}{\hbox {O}}_{\rm x}/{\hbox {Ag}}$ Tape With AC and DC Transport Currents and a Comparison With  ${\hbox {YBa}}_{2}{\hbox {Cu}}_{3}{\hbox {O}}_{\rm x}$  Conductors

When operating in power applications, superconducting conductors often carry alternating currents (AC). Thus, understanding the quench behavior under AC conditions is essential for protecting high temperature superconductor-based devices in power applications. In this work, the quench behavior of Bi<sub>2</sub>Sr<sub>2</sub>Ca<sub>2</sub>Cu<sub>3</sub>O<sub>x</sub>/Ag (Bi2223/Ag) tape with AC and DC transport currents is reported. The minimum quench energies and normal zone propagation velocities are measured for different DC and AC transport currents at 45 K. The frequency of the AC transport current is varied from 50 Hz to 400 Hz. AC losses are measured to analyse the background condition of AC quenches. The results are compared with those of a YBa<sub>2</sub>Cu<sub>3</sub>O<sub>x</sub> (YBCO) coated conductor that was studied previously with identical conditions.
Heating stress probing electrical performance of multiple N-channel FinFETs with VT doping energies

Higher threshold-voltage (V<sub>T</sub>) doping energy provides the deeper influence to channel controllability. For drive current (I<sub>DS</sub>) consideration, the higher one demonstrates the larger I<sub>DS</sub> value, but the higher drop ratio at 125°C comparing the measurement results at channel width/channel length (W/L)=0.11/0.5(μm/μm). However, this phenomenon at W/L=0.11/2(μm/μm) is not distinct at room temperature and the drop ratio at higher doping energy process is converse at higher temperature stress.
Spatio-temporal patches for night background modeling by subspace learning

In this paper, a novel background model on spatio-temporal patches is introduced for video surveillance, especially for night outdoor scene, where extreme lighting conditions often cause troubles. The spatio-temporal patch, called brick, is presented to simultaneously capture spatio-temporal information in surveillance video. The set of bricks of a given background patch, under all possible lighting conditions, lies in a low-dimensional subspace, which can be learned by online subspace learning. The proposed method can efficiently model the background and detect the appearance and motion variance caused by foreground. Experimental results on real data show that the proposed method is insensitive to dramatic lighting changes and achieves superior performance to two classical methods.
Fabrication technology and properties of rare earth giant magnetostrictive films based on MSAW application

Rare earth giant magnetostrictive thin films (RGMFs) belong to a new type of electro (magnetic) - mechanical conversion functional materials. Such materials have broad application prospects in magnetic surface acoustic wave (MSAW) devices. In this paper, RGMFs samples are fabricated by ion beam sputtering deposition (IBSD). In order to improve the magnetic sensitivity, films after forming are heat-treated at different temperatures in vacuum condition. RGMFs magnetic hysteresis loops and static magnetostriction characteristics are measured by DWS type ultra precision displacement meter and Alternating Gradient Magnetometer respectively. For the purpose of developing better functional thin films aimed at MSAW devices, preparation technology and effect on static-dynamic magnetostriction characteristics of RGMFs samples by vacuum annealing treatment are primary studied. The results indicate that static-dynamic magnetostrictive characteristics of RGMFs are closely related to factors such as preparation technology, sputtering position, and vacuum sensitivity enhancing technology, etc.
Functional changes in arteries induced by pulsed high-intensity focused ultrasound

Continuous high-intensity focused ultrasound (HIFU) at various intensities has been shown to induce functional changes in arteries. The objective of the current study was to investigate the functional changes in arteries when pulsed HIFU is used at various acoustic power levels. Sonication was applied at an ultrasound frequency of 1 MHz with a burst length of 50 ms and a repetition frequency of 1 Hz. The duration of the whole sonication was 6 s. The femoral arteries and abdominal aortas of Sprague-Dawley rats were surgically exposed and sonicated with pulsed HIFU; the pulsed-HIFU beam was aimed using color images of the blood flow. The peak systolic velocity (PSV) of the blood flow, as measured by Doppler velocimetry, increased in the arteries to which pulsed HIFU had been applied at acoustic powers of 15, 30, and 45 W. The increase in PSV was correlated with the acoustic power of the pulsed HIFU. The temperatures recorded by the thermocouples placed above and below the aorta surfaces did not change significantly during the sonication. Furthermore, no histological changes were found and the vessel wall showed no obvious temperature rise. Therefore, our results indicate that the functional changes induced by pulsed-HIFU exposure are mainly due to mechanical effects.
Intelligent recommendation methodology and system for patent search

Patents are critical intangible assets for enabling an enterprise's creation and technology. Patent knowledge management is a time consuming task that often dominates the valuable time of R&D staff. This research develops an intelligent recommendation methodology and system for efficient and effective patent search. The system provides an algorithm which is an automatic search engine with management modules. The system clusters users' patent search behavior and infers new patent recommendations. The proposed methodology evaluates the filtered information of the searched patents. Afterward, the system clusters the users and finds each user's neighbors based on the collaborative filtering mechanism. By clustering neighbors' behaviors, the proposed system recommends new users to more appropriate patents to study. When enterprises are planning R&D policies or searching patents for possible prior arts, the intelligent recommendation system helps identify and recommend comprehensive and related patents while saving time and costs.