bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel Packet Queuing And Scheduling Algorithm And Its Link Sharing Performance For Home Router
Authors: Yan Jin , Xiaoyuan Chen 
Published: February 2018

Abstract
A home router, or a home gateway, is the node that resides between a public network and a home network for computers to share Internet connections. To insert customized queuing and scheduling codes into the embedded Linux kernel is a way to make the Linux-based home routers support Quality of Service (QoS). It is desirable that the small Linux kernel adopts an efficient queuing and scheduling algorithm to support link sharing, priority and traffic shaping. The algorithm presented in this paper is based on the concept of hierarchical link-sharing and each class in the hierarchy is bound with a token bucket, which can shape the traffic of this class. The analysis and experiment results presented in the paper show that through the novel way of weighted fair token sharing, this proposed algorithm guarantees basic bandwidth service for each class and enables weighted fair sharing of excess bandwidth, with which home computers connected to the network share the Internet service evenly.
A Lexicon-Corpus-based Unsupervised Chinese Word Segmentation Approach
Authors: Pengyu Lu , Jingchuan Pu , Mingming Du , Xiaojuan Lou , Lijun Jin 
Published: February 2018

Abstract
This paper presents a Lexicon-Corpus-based Unsupervised (LCU) Chinese word segmentation approach to improve the Chinese word segmentation result. Specifically, it combines advantages of lexicon-based approach and Corpus-based approach to identify out-of-vocabulary (OOV) words and guarantee segmentation consistency of the actual words in texts as well. In addition, a Forward Maximum Fixed-count Segmentation (FMFS) algorithm is developed to identify phrases in texts at first. Detailed rules and experiment results of LCU are presented, too. Compared with lexicon-based approach or corpus-based approach, LCU approach makes a great improvement in Chinese word segmentation, especially for identifying n-char words. And also, two evaluation indexes are proposed to describe the effectiveness in extracting phrases, one is segmentation rate (S), and the other is segmentation consistency degree (D).
Self-Tuning Fuzzy Speed Controller Of Travelling Wave Ultrasonic Motor
Authors: Shi Jingzhuo , Zhao Juanping , Cao Zhe , Liang Yunpeng , Yuan Lan , Sun Bin 
Published: February 2018

Abstract
Aiming at the nonlinear characteristic of ultrasonic motor, some control strategies have been proposed to control the rotating speed of ultrasonic motor. But most of these strategies are too complex to realize using a low-cost embedded device. In this paper, a simple fuzzy speed controller is designed for ultrasonic motor. Until now, there has no mature and theoretic design method of fuzzy controller. Therefore, experience of expert is often used as the base of design. It makes the design of fuzzy controller become a sophisticated task. In this paper, the design method of fuzzy controller based on fuzzy model is described in detail. Rules of the fuzzy controller are optimized offline using ant colony optimization, and the appropriate parameters of fuzzy controller are also ascertained during the process of optimization. The designed controller is used to control the rotating speed of traveling wave ultrasonic motor with the type of USR60. According to the difference between the actual responses with different speed References, a kind of online tuning method is proposed to modulate the proportional coefficient of fuzzy control. Experiments indicate the validity of the proposed fuzzy controller.
Evaluation Of Different Sensing Approaches Concerning To Nondestructive Estimation Of Leaf Area Index (Lai) For Winter Wheat
Authors: Tavakoli H. , Mohtasebi S.S. , Alimardani R. , Gebbers R. 
Published: February 2018

Abstract
Different approaches of non-destructive estimation of the LAI in winter wheat were compared. Plant height had weak relation with the LAI, while estimated biomass showed high logarithmic relationship (R2=0.839). NDRE and REIP were logarithmically well related to the LAI (R2=0.726 and 0.779 respectively). Saturation effect of NDRE and REIP was less than NDVI. Some RGB-based indices also showed good potential to estimate the LAI. Among the indices, Gm, GMB, RMB, and NRMB were better related to the LAI. The results indicated that digital cameras can be used as an affordable and simple approach for assessment of the LAI of crops.
Moving Target Detection Based On Global Motion Estimation In Dynamic Environment
Authors: Jun-chai GAO , Ming-yong LIU , Fei XU 
Published: February 2018

Abstract
AUV localization is not accurate based on sequence images if moving target is as landmark, so the moving target detection algorithm is studied based on global motion estimation, which detects and eliminates moving target according to the motion inconsistency of the moving target. Generally grid block matching is used in the global motion estimation, it can’t effectively dispose the dynamic background, and the gradient direction invariant moments descriptors method of free circular neighborhood based on feature points is proposed, which is effective for the background rotating and light changing in two adjacent images. For the matching points, the parameters of global motion are estimated robustly combined with normalized linear estimation method and least median squares. Experiments show that the designed algorithm can effectively estimate parameters of global motion, and eliminate the motion target as mismatch.
Augmented Reality Game Therapy For Children With Autism Spectrum Disorder
Authors: Bhatt S.K. , Leon N.I. De , Al-Jumaily Adel 
Published: February 2018

abstract
This paper presents progress on treating children with Autism Spectrum Disorder (ASD) using Augmented Reality based games. The aim of these games is to enhance social interaction and hand-eye coordination in children with ASD thus easing them into becoming more comfortable around unfamiliar people. Colour detection and tracking and motion tracking concepts in augmented reality have been used to develop games for young children with ASD. The idea is that these games will encourage concentration and imagination from children through repetitive movement and visual feedback.
Development Of Neural Network-Based Electronic Nose For Herbs Recognition
Authors: Soh A. Che , Chow K.K. , Yusuf U. K. Mohammad , Ishak A. J. , Hassan M. K. , Khamis S. 
Published: February 2018

abstract
The ability to classify distinctive odor pattern for aromatic plants species provides significant impact in food industry especially for herbs. Each herbs species has a unique physicochemical and a distinctive odors. This project emphasizes on the techniques of artificial intelligence (AI) to distinguish distinctive odor pattern for herbs. Neural Network method has been exploited for the classification and optimization of various odor patterns. Based on AI techniques, Neural Network-based electronic nose system for herbs recognition has been developed. The system consist multi-sensor gas array which detects gas through an increase in electrical conductivity when reducing gases are absorbed on the sensor’s surface. The output from individual sensors are collectively assembled and integrated to produce a distinct digital response pattern. A selected sensor array shows its relationship with the aroma of the herbs through the GC-MS test. By using five samples of herbs, the E-nose system has been tested with five different types of sensor. From the results, E-nose system with five sensors has the highest capability in classifying herbs sample. Accuracy in classifying the correct herbs increases with the number of sensors used. This investigation demonstrates that the neural network-based electronic nose technique promises a successful technique in the ability to classify distinctive odor pattern for aromatic herbs species.
Synthesis, Characterization And Gas Sensing Performance Of Sol-Gel Prepared Nanocrystalline Sno2 Thin Films
Authors: Bari Ramesh H. , Patil Sharad.B. , Bari Anil.R. 
Published: February 2018

abstract
Nanocrystalline SnO2 thin films were successfully prepared using sol-gel dip coating technique. The starting precursor was used as tin chloride dihydrate (SnCl2.2H2O), ethanol and glycerin. As the prepared films were fired at 500oC. These films were characterized using XRD, FE-SEM and TEM to known crystal structure, surface morphology and microstructure property. Elemental composition was studied using energy dispersive spectrophotometer (EDAX). The H2 gas sensing performance of nanocrystalline SnO2 thin films were investigated and presented. It was found that the nanocrystalline SnO2 thin films gives maximum gas response (S= 360) at 75 oC. The sensor shows fast speed of response (TResponse = 2 s) and quick recover (Trecover = 8 s).
Socially Acceptable Smart Wheelchair Navigation From Head Orientation Observation
Authors: Tomari Razali , Kobayashi Yoshnori , Kuno Yoshinori 
Published: February 2018

abstract
Robotic wheelchairs should move among humans without bringing about uncomfortable situation to them. This paper tackles this issue to propose a method of navigation in indoor environments with presence of humans based on the observation of head information obtained from color and range images. Initially head regions in the color image are tracked and their orientations are estimated using AdaBoost based particle filter trained to classify multiple-pose faces. Then the head orientation data are integrated with the head position data in the range image to determine the wheelchair motion so that it can smoothly move among humans. Experimental results demonstrate the feasibility of the proposed approach
Hybrid Intelligent Method of Identifying Stator Resistance of Motorized Spindle
Authors: Zhang Lixiu , Wu Yuhou , Zhang Ke 
Published: February 2018

abstract
Aiming at the problem that changes of nonlinear dynamic resistance of stator affect the performance of speed sensorless vector control system, a hybrid computing intelligence approach is used in the identification of stator resistance of motorized spindle. The partial least squares (PLS) regression is combined with neural network to solve the problem of few samples and multi-correlation of variables in complicated data modeling. The PLS method is used to extract variable components from sample data and then reduced the dimension of input variables. Moreover, neural network is used to fit the non-linearity between input and output variables. The model based on partial least squares regression and neural network can identify stator resistance under different conditions of the motorized spindle. The results show that the method has high identification precision and is helpful to improve the performance of vector control system.
Extended Kalman Filtering and Pathloss modeling for Shadow Power Parameter Estimation in Mobile Wireless Communications
Authors: Pappas George P. , Zohdy Mohamed A. 
Published: February 2018

abstract
In this paper accurate estimation of parameters, higher order state space prediction methods and Extended Kalman filter (EKF) for modeling shadow power in wireless mobile communications are developed. Path-loss parameter estimation models are compared and evaluated. Shadow power estimation methods in wireless cellular communications are very important for use in power control of mobile device and base station. The methods are validated and compared to existing methods, Kalman Filter (KF) with Gaussian and Non-Gaussian noise environments. These methods provide better parameter estimation and are more accurate in most realistic situations. EKF can estimate the model channel parameters and predict states in state-space.
Vision-Integrated Physiotherapy Service Robot Using Cooperating Two Arms
Authors: Gao Huanbing , Lu Shouyin , Tian Guohui , Tan Jindong 
Published: February 2018

abstract
This paper presents the mechanical architecture, control system, and other modules of a physiotherapy service robot which can treat degenerative disease and chronic disease of middle-aged and aged people by Chinese massage skill. The main body of the robot includes a massage adjustable bed, two 4-DOF(Degree of Freedom) robot arms and two massage hands that can accomplish various massage manipulations. Physiological signal and massage pressure are detecting in real time in massage process to ensure a scientific and safe therapy. Vision system sends the recognized acupoint position to the master system to track the patient’s body, and the acupoint being massaged is displayed in real time by the 3D virtual model. The robot can execute ten massage manipulations, so that the traditional Chinese massage can have a robot instead. The effectiveness for degenerative lumbago in middle-aged and aged is demonstrated by laboratory examination and clinical trial.
Video-Based Vehicle Detection And Classification In Challenging Scenarios
Authors: Chen Yiling , Qin GuoFeng 
Published: February 2018

abstract
In intelligent transportation system, research on vehicle detection and classification has high theory significance and application value. According to the traditional methods of vehicle detection which can’t be well applied in challenging scenario, this paper proposes a novel Bayesian fusion algorithm based on Gaussian mixture model. We extract the features of vehicle from images, including shape features, texture features, and the gradient direction histogram features after dimension reduction. In vehicle classification part, we adopt fuzzy support vector machine, and design a novel vehicle classifier based on nested one-vs-one algorithm. Finally, experimental tests show excellent results of our methods in both vehicle detection and classification.
Prediction And Analysis Of Urban Heat Island Effect In Dangshan By Remote Sensing
Authors: Fang Gang 
Published: February 2018

Abstract
Vegetation index (NDVI) was extracted from bi-temporal multispectral images based on the data obtained from Landsat ETM+on 14th, September, 2000, Landsat ETM+on 9th, September, 2004, Landsat ETM+on 15th, May, 2008 and Landsat-8 on 21st, May 2013 for Dangshan County in Anhui Province. Analysis and data extraction was carried out using the ENVI 5.0 software. Normalized values of thermal radiation brightness temperature and surface brightness temperature were inverted from the bi-temporal thermal infrared band images using the mono-window algorithm. Urban heat island effect in Dangshan County was divided into strong green island zone, green island zone, normal zone, heat island zone and strong heat island zone according based on arithmetic progression. Using regression analysis, quantitative relationship between NDVI and the heat island effect was determined. Results showed an acceleration in urbanization of Dangshan County over the years resulted in a gradual increase in the heat island effect from 2000 to 2013. In addition, area of the heat island and strong heat island increased was observed to increase rapidly, while the area of the green island and strong green island reduced by 46%. Also, using the Markov model, urban heat island effect in Dangshan County was predicted over the next 40 years. This model was feasible in predicting the urban heat island effect with small errors. Finally, it was determine that heat island effect was in negative correlation to the vegetation index (NDVI), and increasing green land appropriately would have a positive effect in alleviating the urban heat island effect
Electromagnetic Force Of High-Speed Solenoid Valve Based On Correlation Analysis
Authors: De Xu , Hong-Zi Fei , Peng Liu , Wei Zhou , Li-Yun Fan 
Published: February 2018

Abstract
High-speed solenoid valve (HSV) is the heart of electronic control fuel system for diesel engines, whose electromagnetic force (EF) determines the dynamic response speed of fuel system. The finite element model of HSV has been established and validated by experiment. Methods of experimental design and correlation analysis have been used for the simulation experiment. The effect laws of six key parameters’ interactions on EF under HSV’s overall operating conditions have been revealed from the results of the simulation. In addition, three key second-order factors’ interaction principles are explained. Results show that under overall operating conditions HSV’s EF is influenced not only by its parameters singly, but also parameters’ interactions
Sefp: A New Routing Approach Using Fuzzy Logic For Clustered Heterogeneous Wireless Sensor Networks
Authors: ALAMI Hassan EL , NAJID Abdellah 
Published: February 2018

Abstract
Wireless sensor networks (WSNs) are composed of set sensor nodes communicating through wireless channels with limited resources. Therefore, several routing protocols and approaches about energy efficient operation of WSNs have been proposed. Clustering algorithm based routing protocols are well used for efficient management of sensing sensor node energy resources. However, many researches were focused on optimization of well-known hierarchical routing approaches of WSNs using fuzzy logic system or heuristic methods. Most of these routing approaches haven’t considered the impact of heterogeneity of sensor nodes, in terms of their energy which is equipped with additional energy resources. In this paper, we propose stable election using three fuzzy parameters approach (SEFP) using fuzzy logic system for heterogeneous WSNs. The main purpose of this routing approach is to improve the network lifetime and particularly the stability period of the network. In the SEFP approach, the sensor node with the maximum chance value becomes a cluster head (CH) based in three fuzzy parameters such as residual energy of each sensor node, closeness to base station (BS), and sum of distances between particular sensor node and other sensor nodes (area distance). The Simulation results of heterogeneous WSNs shows that our approach using fuzzy logic system always preserves more energy as compared to well-known protocols such as LEACH and SEP. additionally, we found that our approach SEFP outperforms LEACH and SEP protocols in prolonging the lifetime and the stability period for heterogeneous WSNs
Universal Intelligent Sensor Interface
Authors: Bhattacharjee D. , Sharma G. , Bera R. 
Published: February 2018

Abstract
This paper deals with the design of the universal intelligent sensor interface. Incorporating UISI makes the system highly flexible because it gives the freedom of either attaching or detchaing various types of sensor. The front end of the UISI can be configured as per the connected sensor with the help of the TEDS information and the firmware. There are two 10pin connector provided for analog and digital sensors. There are various types of analog sensors. The digital sensor also uses various interfaces such as I2C, SPI and RS232. The detail about the type of sensor and interface it uses is stored in TEDS
Effects Of Low Frequency Weak Magnetic Field On The Cardiovascular System Through The Brain Cortex
Authors: Ren Yumiao , Zhang Jianbao 
Published: February 2018

Abstract
In order to study the effect of low frequency weak magnetic field on the cardiovascular system through the central nervous system, this paper design the experiment that is using a rotating magnetic field acts on the cerebral cortex, the different frequency when different parts of the brain, collecting and analysis ECG and blood pressure signal, and discussing the effect of low frequency rotating magnetic field on cardiovascular system through the brain cortex. It proved that a rotating magnetic field can affect blood pressure through cerebral cortex, has different effects on blood pressure by using different frequencies, the effects on blood pressure is not the same because a different position focused on by magnetic field. The results show the frequency and location stimulated with rotating magnetic field may have certain therapeutic effect for controlling hypertension.
Face Detection In Profile Views Using Fast Discrete Curvelet Transform (Fdct) And Support Vector Machine (Svm)
Authors: Muhammad Bashir , Abu-Bakar Syed Abd Rahman 
Published: February 2018

Abstract
Human face detection is an indispensable component in face processing applications, including automatic face recognition, security surveillance, facial expression recognition, and the like. This paper presents a profile face detection algorithm based on curvelet features, as curvelet transform offers good directional representation and can capture edge information in human face from different angles. First, a simple skin color segmentation scheme based on HSV (Hue - Saturation - Value) and YCgCr (luminance - green chrominance - red chrominance) color models is used to extract skin blocks. The segmentation scheme utilizes only the S and CgCr components, and is therefore luminance independent. Features extracted from three frequency bands from curvelet decomposition are used to detect face in each block. A support vector machine (SVM) classifier is trained for the classification task. In the performance test, the results showed that the proposed algorithm can detect profile faces in color images with good detection rate and low misdetection rate
Adaptive Intelligent Inverse Control Of Nonlinear Systems With Regard To Sensor Noise And Parameter Uncertainty (Magnetic Ball Levitation System Case Study)
Authors: Asad Yaghoub Pour , Shamsi Afshar , Ivani Hoda , Tavoosi Jafar 
Published: February 2018

Abstract
Type-2 Fuzzy Neural Networks have tremendous capability in identification and control of nonlinear, time-varying and uncertain systems. In this paper the procedure of designing inverse adaptive type-2 fuzzy neural controller for online control of nonlinear dynamical systems will be presented. At first the structure of a novel class of Interval Type-2 Nonlinear Takagi-Sugeno-Keng Fuzzy Neural Networks (IT2-NTSK-FNN) will be presented. There is a class of nonlinear function of inputs in the consequent part of fuzzy rules. This IT2-NTSK-FNN comprises seven layers and the fuzzification is done in two first layers including type-2 fuzzy neurons with uncertainties in the mean of Gaussian membership functions. Third layer is rule layer and model reduction occurs in fourth layer via adaptive nodes. Fifth, sixth and seventh layers are consequent layer, centroid rules’ calculation layer and output layer respectively. For training the network backpropagation (steepest descend) method with adaptive training rate is used. Finally, three methods including online adaptive inverse controller based on IT2-NTSK-FNN, IT2-TSK-FNN (linear consequent part) and Adaptive Neuro-Fuzzy Inference System (ANFIS) are employed to control of a magnetic ball levitation system. External disturbances and uncertainty in parameters are considered in the model of magnetic ball levitation system. Simulation results show the efficacy of the proposed method