bluuebunny/crossref_metadata_2025_split huggingface dataset:
Immersive Learning Support System based on Kinect Sensor for Children to Learn About Paleontological Environments
Authors: Nakayama T. , Yoshida R. , Nakadai T. , Ogitsu T. , Mizoguchi H. , Izuishi K. , Kusunoki F. , Muratsu K. , Egusa R. , Inagaki S. 
Published: November 2017

Abstract
This paper proposes a simulation-based environmental learning support system, based on Kinect sensors, which is currently under development. Our system animates paleontological animals and their habitats on a display in synchronization with learners’ actions, immersing learners in a real- life paleontological environment. We evaluated the system by recording real-time measurements of learners’ movements, and controlled the animation based on sensor output. Participants were subsequently interviewed to assess their sense of immersion. The system was found to provide a nearreal experience of a defunct environment and the results confirmed that learners felt a sense of immersion and experienced an enhanced interest.
Fusion Algorithm OF Optical Images and SAR With SVT and Sparse Representation
Authors: Zhouping Yin 
Published: November 2017

Abstract
Due to the different imaging mechanism of optical image and Synthetic Aperture Radar (SAR) image, they have the large different characteristics between the images, so fusing optical image and SAR image with image fusion technology could complement advantages and be able to better interpret the scenes information. A fusion algorithm of Synthetic Aperture Radar and optical image with fast sparse representation on low-frequency images was proposed. For the disadvantage of target information easily missing and the contrast low in fused image, and the fusion method with sparse representation could effectively retain target information of Synthetic Aperture Radar image, so the paper fuses low frequency images of Synthetic Aperture Radar and optical images using sparse representation. Moreover a new sparse coefficient fusion rules is proposed, and sparse decomposition process is improved to reduce the algorithm running time. Experimental results demonstrate the effectiveness of the algorithm.
An Energy Efficient Routing for Vehicular AD HOC Networks using Real-Time Perception of Node Information
Authors: Cui Zhongwei , Zhao Yong , Xu Daoyun , Zuo Yu 
Published: November 2017

Abstract
Integrating recent years’ results and analyzing the VANET (Vehicular ad hoc networks), taking the important role of mobile nodes into account a vehicular opportunity route based on real-time information (VORI) is proposed. VORI uses mobile nodes to collect real time area information, and construct hot area for best inter-area selecting with the information to help delivery message. VORI is consisting of node position query and data transmission. The limited query reduces the number of query copies within the net, and with dynamically selecting hot area message delivery works well.
Opposition-Based Learning Particle SWARM Optimization of Running Gait for Humanoid Robot
Authors: Yang Liang , Xijia Song , Deng Chunjian 
Published: November 2017

Abstract
This paper investigates the problem of running gait optimization for humanoid robot. In order to reduce energy consumption and guarantee the dynamic balance including both horizontal and vertical stability, a novel running gait generation based on opposition-based learning particle swarm optimization (PSO) is proposed which aims at high energy efficiency with better stability. In the proposed scheme of running gait generation, a population initiation policy based on domain knowledge is employed, which helps to guide searching direction guidance at the beginning. A population update mechanism based on opposition learning is proposed for speeding up the convergence and improving the diversity. Simulation results validate the proposed method.
Compressive Sensing by Colpitts Chaotic Oscillator for Image Sensors
Authors: Liu Li , Yang Peng , Zhang Jianguo , Wei Guifen 
Published: November 2017

Abstract
Compressive sensing uses simultaneous sensing and compression to provide an efficient image acquisition technique and it has been demonstrated in optical and electrical image sensors. To guarantee exact recovery from sparse measurements, specific sensing matrix, which satisfies the Restricted Isometry Property (RIP), should be well chosen. Toeplitz-structured chaotic sensing matrix constructed by Logistic map has been proved to satisfy RIP with high probability. In this paper, we propose that chaotic sequence sampled from Colpitts oscillator can also be used to generate Toeplitz- structured chaotic sensing matrix. Simulation results show that the proposed Colpitts chaotic sensing matrix has similar performance to random matrix or other chaotic matrix for exact reconstructing compressible signals and images from fewer measurements.
Identification and Detection of Defect in Metal Casing
Authors: Wu Yinchuan , Guo Baolong 
Published: November 2017

Abstract
Based on the propagation rules of electromagnetic waves in metal conductors, this paper analyzes the characteristics of electric field and magnetic field of internal conductors. Then the complex power of electromagnetic wave is calculated. The impedance calculation formula of metal conductor is derived. Moreover, in order to identify and detect defects of metal casing, an alternating current impedance measuring method for the metal casing is proposed by changing the alternating current frequency. Furthermore, a three-dimensional metal casing model is built in COMSOL. Both the electric field and magnetic field are numerically calculated for non-defective and defective casing separately. Meanwhile, the influence of casing defects on the electric field and magnetic field is analyzed. Finally, simulation and measurement results show that: casing defects can be quantitatively detected and effectively located by measuring the alternating impedance of the metal casing.
Modelling of Equipment Failure Rate Accounting for the Uncertainty
Authors: Tian H.X. , Wu W.F. , Wang P. , Li H.Z. 
Published: November 2017

Abstract
A fuzzy model for failure rate with the consideration of the effects of uncertain factors in distribution reliability evaluation is presented. The possibility and credibility distribution analyzed on the basis of sample datum are used for quantifying effects of the uncertainty done to failure rate. Mathematically, the failure rate can be obtained in the interval integration. Moreover, aiming to make the calculating quantity of system reliability evaluation simple and easy, the fuzzy clustering analysis of equipment is adopted. The technique proposed has been implemented in an example distribution system for illustration and the results obtained have been compared with those obtained with average model.
Neutrosophic Concept Lattice based Approach for Computing Human Activities from Contexts
Authors: Mittal Sangeeta , Gopal Krishna , Maskara S.L. 
Published: November 2017

Abstract
Complex human activity recognition suffers from ambiguity of interpretation problem. A novel neutrosophic formal concept analysis method has been proposed to quantify non-determinism leading to ambiguity of interpretation and utilize it in activity recognition. The method works by penalizing performance of non-deterministic activities and rewarding the deterministic ones. Thus, non- deterministic activities are identified during testing due to significantly reduced performance and contexts can be redesigned to improve their description. The proposed method has been implemented on benchmark dataset having both types of activities. Our approach successfully identified nondeterminism in activities description without compromising recognition performance of deterministic activities. It has also been shown that other approaches fail to identify non deterministic activities. Overall accuracy of activity recognition of our approach was comparable to other approaches.
Simulation of Noise Within BOTDA and Cotdr Systems to Study the Impact on Dynamic Sensing
Authors: Funnell Adam , Xu Xiaomin , Yan Jize , Soga Kenichi 
Published: November 2017

Abstract
Real-time structural health monitoring requires dynamic sensing of distributed strain and temperature. Brillouin Optical Time Domain Analysis (BOTDA) and Rayleigh Coherent Optical Time Domain Reflectometry (COTDR) are promising candidates to achieve dynamic sensing. A noise model with specific parametric simulation of independent laser and detector noise sources has been developed. Although ensemble averaging significantly enhances the signal-to-noise ratio (SNR) in both systems, its time-consuming accumulation procedure prevents dynamic sensing. The sequence of averaging in the signal processing workflow varies the SNR for both systems. The system components should be optimized to reduce averaging times and achieve the required system specifications, including dynamic sensing.
Design and Implementation of Intelligent Integrated Measuring and Controlling System for Sugar Cane Crystallization Process
Authors: Meng Yanmei , Zheng Kangyuan , Li Wenxing , Pang Haifeng , Lu Guancheng , Li Guangquan 
Published: November 2017

Abstract
The deficiency in existing sugar cane crystallization automatic control system is difficult to measure some key parameters on line, such as mother liquor supersaturation, mother liquor purity, crystal content and crystal size distribution. Controlling brix with PID can only reflect the massecuite concentration of sugar cane crystallization process, but it is hard to guarantee the crystal quality. During crystallization process, change of mother liquor purity will affect the crystallization rate and supersaturation. The less mother liquor purity in the final stage is, the better absorption of crystals have. Crystal size distribution, including mean area (MA) and coefficient of variation (CV), influences the quantity and quality of crystals. In order to produce sucrose which has uniform size and small coefficient of variation, it’s necessary to study the law of crystal size for sugar cane crystallization. According to the difficulties in measuring some key parameters, an intelligent integrated measuring and controlling system is researched by this paper. The overall structure of this system is designed at first, and also the monitoring system of host computer is developed. Combining with data-driven modeling and hybrid modeling method, the intelligent soft-sensor component for sugar cane crystallization process is implemented. This system realizes automatic monitoring of sugar cane crystallization process, which includes on-line measurement of mother liquor supersaturation, mother liquor purity, crystal content and crystal size distribution (CSD). Experimental results show that this designed intelligent integrated measuring and controlling system for sugar cane crystallization process has not only achieved great on-line prediction for immeasurable parameters, but also has good openness and scalability, which can provide complete parameter detection for the implementation of sugar cane crystallization automatic control system.
Computer Vision-Based Color Image Segmentation with Improved Kernel Clustering
Authors: Wang Yongqing , Wang and Chunxiang 
Published: November 2017

Abstract
Color image segmentation has been widely applied to diverse fields in the past decades for containing more information than gray ones, whose essence is a process of clustering according to the color of pixels. However, traditional clustering methods do not scale well with the number of data, which limits the ability of handling massive data effectively. We developed an improved kernel clustering algorithm for computing the different clusters of given color images in kernel-induced space for image segmentation. Compared to other popular algorithms, it has the competitive performances both on training time and accuracy. The experiments performed on both synthetic and real-world data sets demonstrate the validity of the proposed algorithm.
Research on Power Characteristic of the Electric Forklift EPS System
Authors: He Yan , Xiao Benxian 
Published: November 2017

Abstract
This paper has given the structure, operating principle, and force analysis of electric power steering (EPS) system aimed at a type of forklift. Combing with forklift operating characteristic, three variable power characteristics curve based on steering wheel torque, real-time speed, and load is designed, so is the three dimensional diagram of forklift power gradient by using fuzzy rule. The dynamic model of EPS system and two-degree-of-freedom linear model of forklift dynamics are established. This paper presents a simulation on the basis of three variable power characteristics and dynamic model. The results show that forklift EPS system can provide appropriate power according to the changes of speed and load. It also can meet the demands of coordination between steering portability and road sense.
Sensitivity Analysis of Hierarchical Hybrid Fuzzy - Neural Network
Authors: Haihua Xing , Xianchuan Yu , Dan Hu , Sha Dai 
Published: November 2017

Abstract
To identify the important attributes of complex system, which is high-dimensional and contain both discrete and continuous variables, this paper proposes a sensitivity analysis method of hierarchical hybrid fuzzy - neural network. We derive the sensitivity indexes of discrete and continuous variables through the differential method. To verify the effectiveness of our method, this study employed a man-made example and a remote sensing image classification example to test the performance of our method. The results show that our method can really identify the important variables of complex system and discover the relations between input and output variables; therefore, they can be applied to simplify the model and improve the classification accuracy of model.
A Method To Design Pid Controllers Using Frit-Pso
Authors: Azuma Takehito 
Published: November 2017

Abstract
This paper proposes the Fictitious Reference Iterative Tuning-Particle Swarm Optimization (FRIT-PSO) method to design PID controllers for feedback control systems. The proposed method is an offline PID parameter tuning method. Moreover it is not necessary to derive any mathematical models of objected control systems. The proposed method is demonstrated by comparing with the FRIT method in numerical examples and an experiment
Standard Arpu Calculation Improvement Using Artificial Intelligent Techniques
Authors: Merat Soorena , Almuhtadi Wahab 
Published: November 2017

abstract
Recognizing how developing browsing behaviour could result in greater return for service providers through more efficient data usage without compromising Quality of Service (QoS), this paper proposes a new innovative model to describe the distribution and occurrence of behavioural errors in data usage models. We suggest: a) that the statistics of behavioural errors can be described in terms of locomotive inefficiencies, which increases error probability depending on the time elapsed since the last occurrence of an error; b) that the distribution of inter-error intervals can be approximated by power law and the relative number of errors. Comparing immersive similarities of data usage and foraging behaviours according to the Levy-Flight hypothesis, the length of the usage can be feasibly increased with less errors and eventually increase average revenue per user (ARPU). The validity of the concept is demonstrated with the aid of experimental data obtained from test software called Learn-2-Fly which sought to make browsing behaviours more efficient through user responses to stimuli created by an artificially intelligent engine. Although there were limitations on the scope of this test, a noticeable change in the user browse duration occurred over the duration of testing periods, with test subjects spending more time browsing and reacting to intended visual stimuli. The study establishes the opportunity to provide a higher quality of service to the end-user, whilst also offering a dynamic opportunity to increase revenue streams. Further consequences, refinements, and future works of the model are described in the body of the paper
The Implementation Of High Efficiency Wireless Sensor In Acoustic Object Tracking
Authors: Zhen ChengFang , LIU Wenyi , WEI Hanming 
Published: November 2017

Abstract
Energy control in Wireless Sensor Network is one of the most crucial technologies. Based on the acoustic object localization background, we designed a new structure of the sensor node to realize the energy efficiency in the power supply and artificial sleeping scheduling in this paper. The power control model is independent with data processing and control model and can separately realize the power supply for different part of the node. The node can transfer status according the different circumstance to minimize the energy consumption. Furthermore, a new synchronous sleeping/wake schedule mechanism in the medium access control layer is proposed. Sensor nodes can use the forwarding and listening status to schedule their better energy status on demanded. The experiment has been evaluated and analyzed in a test-bed. The result confirms the structure and the proposed mechanism are energy efficiency and gain better trade-off between the accuracy and efficiency
Cantilever Beam Based Piezoelectric Energy Harvester
Authors: Fenglin Yao , Wengjun Meng , Jie Zhao , Hang Yin 
Published: November 2017

Abstract
With the application of wireless sensor networks become widespread, supply energy for these wireless sensors proves to be a significant issue. Moreover, for the ambient vibration lies everywhere, the vibration can supply energy for the wireless sensor via energy harvester. The piezoelectric energy harvester becomes the research focus for the simple structure and higher energy conversion efficiency. Due to the transcendental equation in distributed parameter model, the numerical method is become powerful complement for theoretical and experimental method. This paper uses ANSYS to analyze the single piezoelectric cantilever in static analysis, model analysis, harmonic response analysis and mechanical-electrical coupling analysis. It analyzes the natural frequency and voltage effect from four aspects which are length to thickness ratio, length to width ratio, the substrate thickness to piezoelectric thickness ratio and seismic mass. Test and measurement for piezoelectric energy harvester is conduct on the testing platform. Macro cantilever beam piezoelectric energy harvester are tested and measured
Real-Time Forecasting Method of Urban Air Quality Based on Observation Sites and Thiessen Polygons
Authors: Liu Xuefeng , Ye Fenxiao , Liu Yuling , Xie Xiange , Fan Jingjing 
Published: November 2017

Abstract
This paper proposes a real-time urban air quality forecasting method based on monitoring sites and Thiessen polygon. Firstly, the concentration of pollutants affecting air quality is obtained through the real-time observations of the monitoring sites deployed in wireless sensor network, according to which the air quality index (AQI) can be calculated and air quality levels and categories can be graded. Then, Thiessen polygons are constructed based on the monitoring sites and the air quality conditions from the only site within any polygon will be the representative to that of any other points within this polygon. Finally, the monitoring sites and Thiessen polygons rendered with standard air quality colors will be visualized on a geographical map for the realization of real-time forecasting method taking Thiessen polygons as forecasting units. Taking Shanghai city as an example, a real-time and visualized air quality prediction platform has been constructed in downtown Shanghai city, the real-time visualization of urban air quality forecasting and early warnings under the constraints of Thiessen polygon have been realized
Exploring a lay Gestalt of schizophrenia? A Danish background population’s explanations on why and how first-episode schizophrenia patients’ narratives were intuitively sensed as contextually inappropriate
Authors: Petersen Charlotte 
Published: November 2017

Abstract

Background
Recent continental-phenomenological psychiatry emphasizes pragmatics or social and contextual inappropriateness as a core disorder of schizophrenia, which is potentially relevant to early identification and treatment.

Objective
However, there are hardly any studies that examine the background population’s sensitivity to inappropriateness in schizophrenia, even if “common” people, from a pragmatic perspective, are likely to be highly sensitive to cultural-conventional norms, including (in)appropriateness.

Method
One empirical evaluation of contextual (in)appropriateness in 10 narratives from first-episode schizophrenia patients and healthy controls, respectively, found that when a phenomenologically informed Danish population (n=157 high-school students; mean age, 18.5) was “blinded” to the control–patient status – that is, “anonymous” narratives of the wordless picture story Frog, Where Are You? – they consequently evaluated patient narratives as more inappropriate than appropriate and control narratives as more appropriate than inappropriate (significant with 0.007). Aiming to explore a potential pattern recognition, distinguishing patient from control narratives, the present study systematizes and discusses salient explanations from lay “experts” who almost consequently (80% to 100%) evaluated patient narratives as inappropriate and control narratives as appropriate (n=63 of 157).

Results
Explanations of inappropriateness concerned affective aspects (about how the patient felt or how the evaluators felt reading the narrative), formal aspects (about pauses, fluency, and brevity), and aspects about sense making (from lack of understanding to nonsense and strangeness).The background population may be sensitive to affective and formal inappropriateness, but only lay experts emphasize the lack of sense in the patients’ narratives.

Conclusion
Further studies might benefit from investigating whether early referrals from family, friends, or schoolteachers of their own accord thematize such inappropriateness aspects, and whether questionnaires targeting inappropriateness could be developed and used in the early identification of young people at risk.