bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study on Feature Selection and Identification Method of Tool Wear States Based on Svm
Authors: Li Weilin , Fu Pan , Cao Weiqing 
Published: February 2018

Abstract
This paper presents an on-line tool wear condition monitoring system for milling. The proposed system was developed taking the cost and performance in practice into account, in addition to a high success rate. The cutting vibration signal is obtained during the cutting process, and then extracting features using time-domain statistical and wavelet packet decomposition algorithms. It would result in two major disadvantages if creating a tool wear states identification model based on all extracted features, i.e. high computational cost and inefficient complexity of the model, which leads to overfitting. It is crucial to extract a smaller feature set by an effective feature selection algorithm. In this paper, an approach based on one-versus-one multi-class Support Vector Machine Recursive Feature Elimination (SVM-RFE) is proposed to solve the feature selection problem in tool wear condition monitoring. Moreover, in order to analyze a performance degradation process on the machine tool, Least Squares Support Vector Machines (LS-SVM) is introduced. In order to estimate the effectiveness of feature selection algorithm, the comparative analysis among Fisher Score (FS) Information Gain (IG) and SVM-RFE is exploited to real milling datasets. The identification result proves that: The selected feature set based on SVM-RFE is more effective to recognize tool wear state; LS-SVM wear identification method is superior to BP neural network, and it has higher identification accuracy; the proposed feature selection and identification method for tool wear states is efficient and feasible.
Observer Based Dynamic Surface Control of A Hypersonic Flight Vehicle
Authors: Butt W. A. 
Published: February 2018

Abstract
This paper describes the design and analysis of a proportional integral air speed controller and a nonlinear adaptive dynamic surface altitude controller for the longitudinal dynamics of a generic hypersonic flight vehicle. The uncertain nonlinear functions in the pure feedback flight vehicle model are approximated by using radial basis function neural networks. For the controller design, the complete states are assumed to be available for measurement, then a sliding mode observer is incorporated to estimate the states which are difficult to measure in practice. A detailed stability analysis of the designed altitude controller shows that all the signals of the closed loop system are uniformly ultimately bounded. The robustness and performance of the designed controllers, with and without the observer are verified through numerical simulations of the flight vehicle model for trimmed cruise conditions of 110,000 ft and Mach 15.
Signal Sensing By The Architecture Of Embedded I/O Pad Circuits
Authors: Chen Shen-Li , Cheng Yang-Shiung 
Published: February 2018

Abstract
In this study, the detecting structures in an embedded CUP wafer, which are called sensors, are investigated through a contactless sensing analysis. These novel sensing structures, which were designed using the ADS 2009 platform and the design rules for the TSMC 0.18-μm CMOS process, were placed under bonding pads. However, signals would still pass through these I/O sensing structures (i.e., ESD devices or circuits) and become coupled up to the pads of the top-layer metal as square, sinusoidal, or ESD pulse waveforms are injected. Through the resulting sensing relationship, we could then judge whether or not the bottom circuit is a good candidate for EMI consideration. Eventually, it was found that during an ESD occurred situation, a strong signal coupling can be sensed by the ESD protection circuits, especially by gate-coupled ESD protection circuitry.
Left-Handedness Detection
Authors: Leong W.Y , Andrew Ng C.R 
Published: February 2018

abstract
In this paper, a new left-handedness sensing and detection module, has been developed to classify the handedness of a person. Handedness of the person can be determined from the EEG data captured and further confirmed using a simple game as testing module. EEG signals were obtained from three locations namely A1, O1 and O2. The signals were then classified into four different frequency bands: Alpha, Beta, Delta and Theta before they were used to determine the Mean EEG Coherence. Generally the left handed person has higher Mean EEG Coherence which means that there are more connections between the left and right hemisphere of cerebrums through the corpus callosum. Based on research, personal non-right handedness has been associated with both increased corpus callosum size and increased functional interaction between cerebral hemispheres. To relate the former to the later, it is suggested that the increased size of corpus callosum, which somehow passes information between the two sides of the brain, allows greater inter-hemispheric communication. Handedness is determined based on this criterion. At the end of the research, the module developed enables the determination of handedness personnel.
Features Of Sleep Apnea Recognition And Analysis
Authors: Yie Leong Wai , Ming Joel Than Chia 
Published: February 2018

abstract
Sleep apnea is a growing sleep disorder issue and estimate to affect 7% of the adult population in Malaysia. In this study, the electrical activity of the brain is studied using Electroencephalogram (EEG). The data obtained was then decomposed using three methods; Empirical Mode Decomposition (EMD), Bivariate EMD and finally Ensemble EMD. The Index of Orthogonatility (IO) was obtained which shows EMD performed the most poorly, EEMD the best and Bivariate in between. The performance of EMD greatly improves when the number of samples was greatly decreased and very high peaks and more complex parts of the signal were excluded in the analysis. Segmentation was also conducted and the segmentation error revealed when an Event Related Potential (ERP) has happened which is when apnea occurred.
A Comprehensive Survey Of Vision Based Vehicle Intelligent Front Light System
Authors: LUO Feng , HU Fengjian 
Published: February 2018

abstract
Vehicle intelligent front light system is one of the advanced driver assistance systems. Vision based intelligent front light system is currently the research focus in this field. The purpose of this paper is to present a comprehensive survey of the vehicle front light system development and the latest vision based key technologies and proposals. By analyzing the significant disadvantages of traditional intelligent light systems, some possible improvement proposals and algorithms for lane, vehicle lamp recognition and track are provided. This survey shows that the Matrix-LED system could make the system more flexible and more effective and vision based vehicle intelligent front light system can improve the driving environment for the ego driver and other road users at night.
Study on PLC with Switch Management in Intelligent Manufacturing Network
Authors: Wang Guangfu 
Published: February 2018

abstract
This paper discusses a new solution for switch management in intelligent manufacturing network. It makes PLC (Programmable Logic Controller) communication module have the switch management features and exchange I/O data in manufacturing network. The switch manager has used the chip of the Ethernet switch device 88E6165. The Marvell 88E6165 device embedded in communication devices is a single-chip 6 port gigabit Ethernet switch with five integrated gigabit Ethernet transceivers. It performs the tasks of switch management, a series of services and applications are supported in PLC when it is running in a manufacturing network. It also analyzes the potential network topologies in which our customers may use the communication module and how the communication module’s architecture facilitates these topologies. Actors associated with the switch management service are described further. It proposes a new mechanism to minimize the congestion based on the measure of taking an adaptive decision during transferring multicast messages to handle multicast message growing with industrial Ethernet for manufacturing systems. Proposed approach is to accomplish a device requesting to start and stop the reception of the multicast streams. It joins and leaves message requests through IGMP. Final, an application prototype system contains various devices and the global architecture is proposed to provide transparency between control network and device (IO) network.
An indoor positioning algorithm and its experiment research based on RFID
Authors: Bingbing Yan , Wenbo Ren , Bolin Yin , Yang Li 
Published: February 2018

abstract
A kind of indoor locating algorithm based on RFID has been put forward since the indoor positioning system can not fully meet the requirements of location services. The algorithm takes the propagation characteristic of signal as the breakthrough point and improves the positioning precision of the algorithm by means of regional division, regional judgment strategy, virtual node, and so on. The optimal target position of the access point was put forward and an effective analysis of the regional division and virtual node was done along with the robustness design through the experimental analysis. The result of the indoor positioning experiment shows that this algorithm is of high positioning precision, providing technical support for developing the indoor positioning system based on RFID.
Knowledge-Based Modeling For Predicting Cane Sugar Crystallization State
Authors: Meng Yanmei , Yu Xian , He Haiping , Tang Zhihong , Wang Xiaochun , Chen Jian 
Published: February 2018

abstract
This paper proposes a knowledge-based model applied to an experimental scale evaporative cane sugar crystallization process, which combines the methods of offline and online knowledge acquisition. Firstly, a data mining method based on rough set theory is utilized to extract information from the large quantity of relevant data obtained in experiment. This method products an offline predictive knowledge. Thereafter, a method for online knowledge learning and self-improvement is put forward, based on support vector machine with particle swarm optimization, to improve the predictive accuracy and generalization capacity. Furthermore, the intelligent system is tested using a selfregulating intelligent comprehensive monitoring and controlling platform that represents the cane sugar process. Results demonstrate the feasibility of the system for predicting the crystallization state in a real cane sugar process.
Research On The Classification For Faults Of Rolling Bearing Based On Multi-Weights Neural Network
Authors: Qiang Yujian , Chen Ling , Hua Liang , Gu Juping , Ding Lijun , Liu Yuqing 
Published: February 2018

abstract
A methodology based on multi-weights neural network (MWNN) is presented to identify faults of rolling bearing. With considerations of difficulties in analyzing rolling bearing vibration data, we analyzed how to extract time domain feature parameters of faults. Further, the time domain feature parameters extracted from fault signals are utilized to train multi-weights neural network for achieving an optimal coverage of fault feature space. Thus, faults of rolling bearing can be identified. Finally, simulations results based on real sampling data indicate the effectiveness of the methodology proposed in this paper. In addition, simulation results also indicate that MWNN utilized in this paper is more excellent than probabilistic neural network (PNN) and suitable for the classification of small samples.
Augmented Reality Game Based Multi-Usage Rehabilitation Therapist For Stroke Patients
Authors: Leon N.I. De , Bhatt S.K. , Al-Jumaily Adel 
Published: February 2018

abstract
For the surviving stroke patients that are affected physically and mentally, they are required rehabilitation after the stroke. Rehabilitation can be quite expensive on the patient and their families. The augmented reality rehabilitation gaming system aims to decrease the dependency on supervised therapy. This paper presents two augmented reality games. The games focus on rehabilitating stroke patients affected with upper limb disabilities. The games simulate current physical therapy techniques in an interactive augmented environment. The benefits of using a gaming platform are to provide the user with increased motivation, as well as a cost effective rehabilitation solution. The games can be used with or without a hand held roller-ball device, which can change the movement and focus of the exercise.
Robotic Adaptive Impedance Control Based On Visual Guidance
Authors: Erchao Li , Zhanming Li , Junxue He 
Published: February 2018

Abstract
Uncalibrated visual servoing based on SVR-Jacobian estimator is proposed in unknown environment. Multiple support vector regression (SVR) machines are used to estimate the Jacobian matrix of images, and the nonlinear mapping between the image features of the curved line and the robot joint angle is constructed, uncalibrated robot impedance control can be carried out. Image Jacobian matrix expression with Gaussian kernel is put forward, the effectiveness of the presented approach is verified by using a 6 DOF robot with a CCD camera and a force/torque sensor installed in its end effector
An Adaptive Voice Activity Detection Algorithm
Authors: Zhigang Zhang , Junqin Huang 
Published: February 2018

Abstract
Voice Activity Detection (VAD) is a crucial step for speech processing, which detecting accuracy and speed directly affects the effect of subsequent processing. Some voice processing system based phone or in the indoor environment, which need simple and quick method of VAD, for these representative voice signal, this paper proposes a new algorithm which is adaptive and quick based on a major improvement to Dual-Threshold endpoint detection algorithm. First the amplitude normalization is processed to the original voice signal, the characteristic is extracted by means of short-time amplitude, which can simplify operation. Then, large-scale (long frame-length and frame-shift) short-time amplitude is used for rough detection, combining adaptive threshold judgement of consecutive frames, which can find voice areas of start-point and end-point quickly. To these areas, small-scale (short frame-length and frame-shift) short-time amplitude is used for accurate detection, forward scanning is put to start-point area, reverse scanning is put to end-point area, combining adaptive threshold judgement of consecutive frames, start-point and end-point of the effective speech can be accurately located. Experimental results show that the method of this paper can detect endpoints of voice signal more quickly and accurately, which can improve recognition performance dramatically. Large-scale can increase detection speed, small-scale can improve detection accuracy, both can be adjusted to satisfy the different requirements. The method of this paper ensures both detection speed and precision, which has more flexibility and applicability
Discrete S-Transform Based Speech Enhancement
Authors: Hu Guo-hua , Li Rui , Tao Liang 
Published: February 2018

Abstract
S-transform (ST) is an effective time-frequency representation method with the advantages of short-time Fourier transform and wavelet transform. This paper utilizes the advantages of the power spectral subtraction method and the speech enhancement method to presents a novel speech enhancement algorithm based on discrete ST. Firstly, the speech in time domain is transformed by ST to joint time-frequency domain for spectral subtraction so that the clear speech spectrum can be obtained and then the inverse ST is performed to acquire the enhanced speech in time domain. Simulation experiment is done to verify the validity of the method. The experiment results show that the proposed method can effectively enhance the de-noising ability and improve the signal-to-noise ratio
A Mac And One-Way Function Based Filtering Scheme
Authors: Jing-Guo ZHAO , Qing-Yun LUO , Zhi-Xiong Liu 
Published: February 2018

Abstract
In optical sensor networks, the adversary can inject false reports and old packets, both of which can cause false alarms and drain out the limited energy of the network. Existing security mechanisms can detect and filter out only false reports but not the old packets during forwarding. Furthermore, they cannot resist cooperative attacks. A MAC and one-way function based Filtering Scheme (MOFS) was presented. Each node distributes its key and initial hash value to some other nodes after deployment. A data report must carry the MACs and fresh hash values from t detecting nodes. The forwarding nodes check the logicality of the relative position of the detecting nodes carried in the report, the correctness of the MACs and hash values, and the freshness of these hash values. Analysis and simulation results show that MOFS can not only filter false reports and old packets simultaneously, but also performs well on compromise toleration
On Mass Sensing Using Micro/Nano Resonators - Approaches, Challenges And Directions
Authors: Choubey Bhaskar , McEwan Alistair 
Published: February 2018

Abstract
Micro/Nano electromechanical systems based Mass sensors are being increasingly used for detecting very low masses, with significant applications in bio-sensing as well as environmental sensing. A number of different shapes, excitation mechanisms as well as materials have been suggested for these sensors. In addition, with reducing dimensions due to improvement in fabrication, these sensors have the potential to measure bacterial level masses. This paper reviews some of the research directions in this field. Various sensing and actuation strategies for these resonators are discussed. In addition, three important challenges, which have the potential of providing new directions of research are also explored. These include quality factor, increasing nonlinearity and coupling. Coupling of sensors can provide a unique opportunity to build several resonant sensors on the same chip and reduce the number of contacts required as well as the potential bandwidth
A New Three-Dimension Spatial Location Algorithm Of Wireless Sensor Network
Authors: Hua Xiang , Jinjin Zhang , Lei Bin 
Published: February 2018

abstract
Aiming at three-dimensional space localization problem in wireless sensor network, a method of three-dimensional centroid algorithm with spherical perception radius (3DCSPR) is proposed. The algorithm uses Gaussian probability density function to estimate the sensor node radius, and uses tetrahedron method and three-dimensional center to locate unknown node with estimated. Firstly, RSSI value between beacon nodes and destination node is selected by RSSI distribution density function, that confidence interval of nodes perception radius is estimated. Secondly, satisfied tetrahedron is got by the intersections sphere coverage of beacon nodes in three-dimensional. Finally, destination node localization is calculated with weighted centroid in three-dimensional. Simulation results show that the proposed method can significantly reduce positioning errors in three-dimensional network environment in reality and can be widely applied to many fields
Quadrotors Unmanned Aerial Vehicles: A Review
Authors: Ghazbi S. Norouzi , Aghli Y. , Alimohammadi M. , Akbari A. A. 
Published: February 2018

Abstract
Quadrotors are Vertical Take-Off and Landing aerial vehicles with many potential applications ranging from mapping to supporting rescue operations. This paper aims to provide an overview on various works carried out on the quadrotor, from the perspective of control and dynamic modelling. Also in this paper, based on the information summarized from 160 researches available, different control targets and flight missions are analysed and classified, and according to it, a general flight mission map is introduced. In addition, history of advances in development of quadrotors and set-ups proposed when performing experimental researches on quadrotors is presented
An Electrical Model Optimization For Single Cell Flow Impedance Spectroscopy
Authors: Claudel J. , Nadi M. , Elmazria O. , Kourtiche D. 
Published: February 2018

Abstract
This paper presents an optimization of a single cell electrical model, based on Maxwell’s mixture Theory, applied to flow cytometry coupled to impedance spectroscopy. It is based on the discretization of the measurement area into a square reference volume, centered between microelectrodes, and fixed impedance areas. The first one represents the sensing area, the one impacted by cell presence during measurement, and the second one, all other areas that contribute to global measured impedance. By removing these last impedances, it is possible to compare and model the electrical response of different electrodes geometries. Simulations, performed for 6 different electrodes geometries using Finite Element Method (FEM), were performed to check our assumptions. Results attest the validity of our model for cells with sizes comprised between 30 and 70% of the channel weigh. Finally, measurements performed with our microfluidic sensor show the same impedance variation distribution during the passage of calibrated beads with an error lower than 5%
Trust Aware Data Aggregation And Intrusion Detection System For Wireless Sensor Networks
Authors: Vamsi P. Raghu , Kant Krishna 
Published: February 2018

Abstract
Data Aggregation (DA) is one of the most frequently used techniques in Wireless Sensor Networks (WSNs) to improve the network lifetime. It involves gathering, consolidating, and routing the sensory data collected by sensor nodes. However, research studies have demonstrated that the dependability of the DA process affects severely when malicious nodes are present in the network. Many security solutions using cryptography and Intrusion Detection System (IDS) have been proposed in the literature for smooth conduction of the aggregation process. However, these solutions require more energy and processing capacity, which are the main constraints for sensor nodes. To this end, the current study presents Trust-Aware Data Aggregation and Intrusion Detection System (TDAGIDS) for clustered WSNs. This TDAGIDS has two modules viz., trust management and intrusion detection. Each node runs a Trust Management System (TMS) that computes the trust value of neighbor nodes by observing their activities. On the other hand, the Base Station (BS) is equipped with IDS that collects the trust values of network nodes and runs a statistical test to identify malicious nodes. In this way, TMS at the node level and IDS at BS level work in collaboration to detect and isolate the malicious nodes from the DA process. The simulation results show the effectiveness of the TDAGIDS over baseline T-LEACH (Trusted Low Energy Adaptive Clustering Hierarchy) protocol and recently proposed TDAGIOT (Trust based Data Aggregation for Internet of Things) method
Consensus Of Continuous-Time Multi-Agent Systems Under Noisy Measurement
Authors: Qingbi He , Zhaojun Tang 
Published: February 2018

Abstract
In this paper, we consider the consensus problem of first-order continuous-time multi-agent systems with fixed topology and time-varying topology in the presence of measurement noises. It is assumed that each agent can only obtain the information from its neighbors, and the information is corrupted by white noises. For the case of fixed topology, it is shown that consensus can be reached asymptotically in mean square provided the interaction topology has a spanning tree. For the case of time-varying topology, with the assumption that each interaction topology is balanced and strongly connected, consensus can be reached asymptotically in mean square as well. The convergence analysis is given by studying the reduced-order system with the help of stochastic Lyapunov analysis. Simulation results are presented to illustrate the theoretical results