bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel Knowledge-Compatibility Benchmarker for Semantic Segmentation
Authors: Dewanto Vektor , Aprinaldi  , Ian Zulfikar , Jatmiko Wisnu 
Published: November 2017

Abstract
The quality of a semantic annotation is typically measured with its averaged class-accuracy value, whose computation requires scarce ground-truth annotations. We observe that humans accumulate knowledge through their vision and believe that the quality of a semantic annotation is proportionally related to its compatibility with the vision-based knowledge. We propose a knowledge-compatibility benchmarker, whose backbone is a regression machine. It takes as input a semantic annotation and the vision-based knowledge, then outputs an estimate of the corresponding averaged class-accuracy value. The knowledge encodes three kinds of information, namely: cooccurrence statistics, scene properties and relative positions. We introduce three types of feature vectors for regression. Each specifies the characteristics of a probability vector that captures the compatibility between an annotation and each kind of the knowledge. Experiment results show that the Gradient Boosting regression outperforms the ν -Support Vector regression. It achieves best performance at an R2-score of 0.737 and an MSE of 0.034. This indicates not only that the vision-based knowledge resembles humans’ common sense but also that the feature vector for regression is justifiable.
A Study on Optimization Methods of X-Ray Machine Recognition for Aviation Security System
Authors: Zhang Ning 
Published: November 2017

Abstract
Traditional X-ray machine image recognition methods for airport security system have difficulties in recognition and are prone to result in recognition errors due to the impact of placing angle, density and volume of detected objects. This paper accurately describes the image features of X-ray machine visual image, carries out SVM classification after a visual dictionary is formed and enhances the accuracy of image discrimination by means of robust acceleration. The experimental results indicate that both identification efficiency and accuracy are improved to some extent.
Performance Bound Analysis on Transmit Antennas Selection Systems Considering Erroneous Channel Information
Authors: Zhuang Mingjie 
Published: November 2017

Abstract
We consider multiple-inputs-single-output (MISO) systems equipped with N transmit and single receive antennas, and concentrate on transmit antenna selection (TAS) for flat Rayleigh fading channels. We assume perfect channel state information (CSI) at receiver and imperfect CSIs through an feedback link at transmitter. The metric of TAS are those with the largest instantaneous signal-to- noise ratio (SNR), the best 2 out of N available transmit antennas always are selected. We use Alamouti encoding scheme and derive the probability density function (PDF) of Frobenius norm of column vector of the channel matrix. Using the known PDF we can derive the joint PDF of order statistics channel for the subseti, j. Assuming that the transmitted signals employ Mary phase-shift keying (MPSK) constellation, we consider the impact of imperfect antenna selection subsets on system performance, and explicitly derive a closed-form BER expression of Chernoff upper bounds (CUB). For two special cases with 2 out of N =3 and 4 possible transmit antennas, we analyses asymptotic performance of selected subsets. Numerical and simulating results show that we can achieve full spatial diversity with antenna selection in the presence of imperfect CSI and the largest ordinal number antenna selected as if all the transmit antennas were used; there may be some loss in the diversity order without the best transmit antenna.
Design of an Intelligent Car for Searching Track and Avoiding Obstacles
Authors: Yang Degang , Liu Tingya , Hu Chunyan 
Published: November 2017

Abstract
With the rapid development of informational and intelligent technology, the mobile robot has become an important branch of robot. In this paper, through UP-InnoSTARTM robot kits for the chassis and MultiFLEXTM 2-PXA270 controller for the control core, we design an intelligent car. It uses infrared proximity sensors to detect obstacles and gray-scale sensors to search the track. And the main functions are: autonomously recognizing the trajectory, searching it steadily, making quick judgment and timely responses when meeting obstacles. In addition, a simple laboratory experiments are also proposed to illustrate the practicability of our design.
Development of Wireless Sensor Network using Bluetooth Low Energy (BLE) for Construction Noise Monitoring
Authors: Hughes Josie , Yan Jize , Soga Kenichi 
Published: November 2017

Abstract
In this paper the development of a Wireless Sensor Network (WSN) for construction noise identification and sound locating is investigated using the novel application of Bluetooth Low Energy (BLE). Three WSNs using different system-on-chip (SoC) devices and networking protocols have been prototyped using a Raspberry Pi as the gateway in the network. The functionality of the system has been demonstrated with data logging experiments and comparisons has been made between the different WSN systems developed to identify the relative advantages of BLE. Experiments using the WSN for vehicle noise identification and sound location have further demonstrated the potential of the system. This paper demonstrates the versatility of a BLE WSNs and the low power consumption that is achievable with BLE devices for noise detection applications.x
Intelligent Neural Network Control Strategy of Hydraulic System Driven by Servo Motor
Authors: Yu Ma 
Published: November 2017

Abstract
A novel intelligent neural network control scheme which integrates the merits of fuzzy inference, neural network adaptivity and simple PID method is presented in this paper. This control method overcomes the defects existed in the traditional variable frequency induction motor driven hydraulic source, such as slow response, poor control precision, easy to overshoot. Permanent magnet synchronous motor driven constant pump hydraulic system is designed instead of common motor, energy saving, fast response and easy to realize closed loop control. System uses the structure of the combination of neural network control and RBF network online identification. The parameters of the controller are optimized by PSO algorithm offline and error back propagation (BP) algorithm offline, and a RBF network is built to identify the system online. The hydraulic power system’s control simulation experiments are conducted, and the experimental results at the typical working conditions of the hydraulic source show that the controller and its optimization algorithm can effectively improve the system performance, and the system has no steady-state error, good dynamic performance and good robustness, superior to conventional fuzzy controller and PID controller.
Compensation of Capacitive Differential Pressure Sensor using Multi Layer Perceptron Neural Network
Authors: Moallem Payman , Abdollahi Mohammad Ali , Hashemi S. Mehdi 
Published: November 2017

Abstract
Capacitive differential pressure sensor (CPS), which converts an input differential pressure to an output current, is extremely used in different industries. Since the accuracy of CPS is limited due to ambient temperature variations and nonlinear dependency of input and output, compensation is necessary in industries that are sensitive to pressure measurement. This paper proposes a framework for designing of CPS compensation system based on Multi Layer Perceptron (MLP) neural network. Firstly, a test bench for a sample popular CPS is designed and implemented for data acquisition in a real environment. Then, the gathered data are used to train different MLPs as CPS compensation system which inputs are the output current of CPS and temperature value, and the output is compensated current or computed pressure. The experimental results for an ATP3100 smart capacitive pressure transmitter show the trained three layers MLP with Levenberg- Marquardt learning algorithm could effectively compensate the output against variation of temperature as well as nonlinear effects, and reduce the pressure measurement error to about 0.1% FS (Full Scale) , over the temperature range of 5 ~ 60 ° C.
Automatic Recognition of Facial Expression Based on Computer Vision
Authors: Zhu Shaoping 
Published: November 2017

Abstract
Automatic facial expression recognition from video sequence is an essential research area in the field of computer vision. In this paper, a novel method for recognition facial expressions is proposed, which includes two stages of facial expression feature extraction and facial expression recognition. Firstly, in order to exact robust facial expression features, we use Active Appearance Model (AAM) to extract the global texture feature and optical flow technique to characterize facial expression which is determined facial velocity information. Then, these two features are integrated and converted to visual words using “bag-of-words” models, and facial expression is represented by a number of visual words. Secondly, the Latent Dirichlet Allocation (LDA) model are utilized to classify different facial expressions such as “anger”, “disgust”, “fear”, “happiness”, “neutral”, “sadness”, and “surprise”. The experimental results show that our proposed method not only performs stably and robustly and improves the recognition rate efficiently, but also needs the least dimension when achieves the highest recognition rate , which demonstrates that our proposed method is superior to others.
Performance Measurement of Photoelectric Detection and Target Tracking Algorithm
Authors: Yang Haidou , Li Wei 
Published: November 2017

Abstract
To solve the unstable problem of target tracking detection system, this paper proposes an improved mean-shift algorithm for object tracking, establishes object tracking processing model;provides the processing algorithm of object tracking. According to the principal of object tracking, papersets up sky background brightness calculation model in photoelectric tracking optical detection area and detection capability calculation model of space object, analyzes the effect of background illumination on the signal to noise ratio(SNR) of photoelectric tracking system, gives the change curve of detection capability based on the exposure time of CCD camera, SNR threshold of photoelectric detection system and dark current of photoelectric detection system. Through calculation and test , paperprovidesthe comparison results of the improved mean-shift and traditional mean-shift, verifies the correctness of the proposed algorithm and calculation models for photoelectric detection capability in target tracking detection system, the results show the improved mean-shiftobject tracking algorithm and detection capability calculation model are correct.
Fabrication of High Frequency Surface Acoustic Wave (SAW) Devices for Real Time Detection of Highly Toxic Chemical Vapors
Authors: Mittal Upendra , Islam Tarikul , Nimal A T , Sharma M U 
Published: November 2017

Abstract
In this paper, a low cost fabrication of sub micron features size SAW device with conventional lithography and their application for toxic chemical vapor detection has been presented. The SAW devices with different interdigital transducer (IDT) electrodes line widths were designed and fabricated. The fabricated SAW devices features had an accuracy of ± 0.1 μm. Frequency response of the SAW devices was measured with vector network analyzer for design parameter confirmation. The fabricated devices have been configured in multisensory oscillator configuration and tested with chemical ware fare agents simulants at very low concentration (ppb).
Study of Three-Dimensional on-line path Planning for UAV based on Pythagorean Hodograph Curve
Authors: Yi Zhang , Xiu-xia Yang , Wei-wei Zhou , He-wei Zhao 
Published: November 2017

Abstract
For the demand of the UAV autonomous path planning in dynamic thread environment, the three-dimensional path planning algorithm on-line of UAV based on Pythagorean Hodograph (PH) curve is put forward. According to the UAV’s current flight state such as location and speed, and the interrupt point or the target’s state, a flyable path with continuous curvature is planed out online. The roles of the key parameters are analyzed and the range of the values are given. On this basis, the distribution estimation algorithm is used to optimize the selection of path parameters, which avoid the blindness iterative process and consider the kinematics constraints such as the curvature, torsion and climbing angle. The multiple UAVs’ three dimensional path planning in dynamic environment are tested. Simulation results prove the validity and practicability of the algorithm.
Prototyping using a Pattern Technique and a Context-Based Bayesian Network in Multimodal Systems
Authors: Zaguia Atef , Tadj Chakib , Ramdane-Cherif Amar 
Published: November 2017

Abstract
Today, technology allows us to produce extensive multimodal systems which are totally under human control. These systems are equipped with multimodal interfaces, which enable more natural and more efficient interaction between man and machine. End users can take advantage of natural modalities (e.g. audio, eye gaze, speech, gestures, etc.) to communicate or exchange information with applications. In this work, we assume that a number of these modalities are available to the user. In this paper, we present a prototype of a multimodal architecture, and show how modality selection and fission algorithms are implemented in such a system. We use a pattern technique to divide a complex command into elementary subtasks and select suitable modalities for each of them. We integrate a context-based method using a Bayesian network to resolve ambiguous or uncertain situations.
Fragrance Measurement of Scented Rice using Electronic Nose
Authors: Jana Arun , Bhattacharyya Nabarun , Bandyopadhyay Rajib , Tudu Bipan , Mukherjee Subhankar , Ghosh Devdulal , Roy Jayanta Kumar 
Published: November 2017

Abstract
This article describes about an instrument and method for aroma based quality detection of Basmati and other aromatic rice varieties. It comprises few modules such as odour delivery module, sniffing module, water bath module and computing module. Odour handling module helps to deliver odour to the sensor array; a sniffing unit comprising a sensor array module that includes a eight number of metal oxide semiconductor sensors assembled on a printed circuit board, said printed circuit board fitted into a sensor chamber; a water bath module for preparing rice sample, said water bath module including a heater attachment to facilitate cooking; a computing module to quantify the aroma data acquired by sensors; data acquisition module etc. Principal Component Analysis (PCA) implemented for clustering the data sets acquired from sensor array. Also data generated from sensor array was fed to Probabilistic Neural Network (PNN), Back-propagation Multilayer Perceptron (BPMLP) and Linear Discriminant Analysis (LDA) for identification of different rice varieties. Finally, for aroma quantifying, pure-quadratic response surface methodology model used with mean square error (MSE) 0.0028.
Seladg: Secure Energy Efficient Location Aware Data Gathering Approach for Wireless Sensor Networks
Authors: Juliana M. Roseline , Srinivasan S. 
Published: November 2017

Abstract
Recent trends in wireless sensor networks leads to the development of new protocols for data gathering. In this paper, a secure energy efficient location aware data gathering approach is introduced to secure data gathering. An Elliptic Curve Diffie Hellman Key Exchange (ECDHKE) algorithm is utilized for key generation and key exchange between the sensor nodes to maintain security and prevent the data from malicious nodes. The performance of the proposed scheme is validated in terms of packet drop, throughput, energy consumption, residual energy and network lifetime. The proposed scheme achieves better performance than the existing EEHA and SMART schemes.
Dynamic Performance Influences on HOPF Bifurcation Characteristics for Vehicles
Authors: Zhu Haiyan , Wu Pingbo , Zeng Jing , Mai Guoyao 
Published: November 2017

Abstract
This study compares the performance influences for four kinds of tread contour features commonly used in High-Speed trains. The Hopf bifurcation characteristic influencing the dynamic performance for VEHICLE 1 and VEHICLE 2 were analyzed using mathematical matrices models. SIMPACK software was used to create two dynamic models for VEHICLE 1 and VEHICLE 2 for high speed trains equipped with four kinds of treads matched with Chinese 60 rail. Dynamic performance indices for these models were studied during operation in straight track conditions with imposed high interference German track irregularity spectra with the premise of dynamic performance normalized indices processing. The study shows that: VEHICLE 1 exhibits a subcritical bifurcation characteristic under different wheel-rail matching conditions. VEHICLE 2 dynamic performance index values do not increase as speed increases, but wear index gradually increased with increased speed. Vehicles with different structural parameters, wheel-rail matching greatly influences bifurcation stability, comfort and wheel-rail wear. This method indicates an important reference value for wheel-rail matching in high-speed trains and structural parameters of stability and safety for these vehicle systems.
The Use of Artificial Neural Networks in the estimation of the Perception of Sound By the Human Auditory System
Authors: Riordan D. , Doody P. , Walsh J. 
Published: November 2017

Abstract
The human auditory system perceives sound in a much different manner than how sound is measured by modern audio sensing systems. The most commonly referenced aspects of auditory perception are loudness and pitch, which are related to the objective measures of audio signal frequency and sound pressure level. Here we describe an efficient and accurate method for the conversion of the sensed factors of frequency and sound pressure level to perceived loudness and pitch. This method is achieved through the modeling of the physical auditory system and the biological neural network of the primary auditory cortex using artificial neural networks. The behavior of artificial neural networks both during and after the training process has also been found to mimic that of biological neural networks and this method will be shown to have certain advantages over previous methods in the modeling of auditory perception. This work will describe the nature of artificial neural networks and investigate their suitability over other modeling methods for the task of perception modeling, taking into account development and implementation complexity. It will be shown that while known points on the perception scales of loudness and pitch can be used to objectively test the suitability of artificial neural networks, it is in the estimation of the perception of sound from the unknown (or unseen) data points that this method excels.
Research on Lateral Stability of four Hubmotor-in-Wheels Drive Electric Vehicle
Authors: Jin Biao , Sun Chuanyang , Zhang Xin 
Published: November 2017

Abstract
This paper focuses on the problem of lateral stability of four hub-motor-in-wheels drive electric vehicle, 7 DOF (degrees of freedom) vehicle simulation model which is verified by field test is established based on Matlab/Simulink software. On basis of simulated model, BP neural network PID torque distribution controller of lateral stability is proposed. The sideslip angle at mass center and yaw rate are selected as the control variables, and the BP neural network PID torque distribution controller is designed. The simulation result shows that proposed strategy can control the electric vehicle’s sideslip angle at mass center and yaw rate, avoid the under steer and over steer of the vehicle and improve the vehicle lateral stability.
Optimal Cluster Head Number Based On Entroy For Data Aggregation In Wireless Sensor Networks
Authors: Yang Mingxin 
Published: November 2017

abstract
In-network data aggregation plays an important role on energy consumption from the point of reducing the amount of communication in cluster-based wireless sensor networks. The selection of cluster heads is usually based on two criteria which are the number of cluster heads network needed and the times of every node serving as the cluster head. Too much or too little cluster head number will shorten the network lifetime for the energy premature depletion of some sensor nodes, so it has a great significance to select the optimal cluster heads number for wireless sensor networks. Based on the information rate-distortion function and network energy model, we propose an algorithm OCHN which calculates the optimal cluster head number for the minimal energy consumption, and further gets the optimal cluster head ratio in the process of data aggregation. Simulation results demonstrate that our proposed algorithm is energy efficient, and the comprehensive performances of network lifetime and data transmission are good for data aggregation in wireless sensor network
Fast Rcs Modeling For Dynamic Target Tracking
Authors: Hua Xiang , Yuan Wuwei , Lei Bin 
Published: November 2017

Abstract
Radar scattering cross section (RCS) is an important parameter characteristic of exterior trajectory tracking system especially in moving state. The paper researches calculation method of RCS based on integral method from Maxwell equation, makes hybrid algorithm combined moment method and physical optics, by establishing the target modeling, uses FEKO to simulate the target RCS and complete fast modeling method research under static conditions. And then it discusses the accuracy of exterior trajectory radar tracking system in experiment, analyzes relationship between RCS with external trajectory and flight attitude, according to the static RCS characteristics with the same type of target in different station arrangement, inducts statistical rules fit the dynamic RCS statistical characteristics in space movement, analyzes its fluctuation rule, and build motion functions of relative angle between target gesture and radar incident direction, then gets RCS compute method during dynamic flight. We design the dynamic RCS simulation experiment under multiple arrangements, multiple targets and multiple angles, and explain simulation results
Amn-Pso Method For Jamming Unmanned Aerial Vehicle Network
Authors: Yu ZHANG , Feng LIU , Jie HAN 
Published: November 2017

Abstract
UAVs are attracting more and more attentions for their versatilities and low costs. This paper focuses on their security and considers launching jamming attacks on them. We firstly formulate the UAVs jamming problem. Secondly the PSO (Particle Swarm Optimization) algorithm is introduced and new metrics like AJRL (Area for jamming a receiving link) and NJRL (Number of AJRLs) are defined. Then we provide a new jamming method AMN-PSO (Achieving Maximal NJRL based on PSO) for UAVs jamming attack. AMN-PSO includes the Tabu search concept to improve its performance. For evaluating the performance, AMN-PSO method together with other methods are simulated comprehensively. The simulation result shows that AMN-PSO performs better than other methods