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Robust Re-Weighted Multi-View Feature Selection
Get PDFIn practical application, many objects are described by multi-view features because multiple views can provide a more informative representation than the single view. When dealing with the multi-view data, the high dimensionality is often an obstacle as it can bring the expensive time consumption and an increased chance of over-fitting. So how to identify the relevant views and features is an important issue. The matrix-based multi-view feature selection that can integrate multiple views to select relevant feature subset has aroused widely concern in recent years. The existing supervised multi-view feature selection methods usually concatenate all views into the long vectors to design the models. However, this concatenation has no physical meaning and indicates that different views play the similar roles for a specific task. In this paper, we propose a robust re-weighted multi-view feature selection method by constructing the penalty term based on the low-dimensional subspaces of each view through the least-absolute criterion. The proposed model can fully consider the complementary property of multiple views and the specificity of each view. It can not only induce robustness to mitigate the impacts of outliers, but also learn the corresponding weights adaptively for different views without any presetting parameter. In the process of optimization, the proposed model can be splitted to several small scale sub-problems. An iterative algorithm based on the iteratively re-weighted least squares is proposed to efficiently solve these sub-problems. Furthermore, the convergence of the iterative algorithm is theoretical analyzed. Extensive comparable experiments with several state-of-the-art feature selection methods verify the effectiveness of the proposed method
Dynamic Analysis of a Horizontal Oscillatory Cutting Brush
Get PDFStreet sweeping is an important public service, as it has an impact on aesthetics and public health. Typically, sweeping vehicles have a gutter brush that sweeps the debris that lies in the road gutter. As most of the debris is located in the gutter, the effective operation of the gutter brush is important. The aim of this work is to study the performance of a type of gutter brush, the cutting brush, through a 3D dynamic (transient), large deflection finite element model developed by the authors. In this brush model, the brush mounting board is modelled as fixed, and, consequently, inertia forces are applied to the bristle, which is modelled as a beam element. In order to simulate the interaction with the road surface, this is rotated, translated, and raised. Bristle-road contact is modelled through a flexible-to-rigid contact pair. Particularly, the concept of a cutting brush rotating at variable speed is explored through the finite element analysis of a constrained horizontal cutting brush. This analysis helps to understand the behaviour of oscillatory cutting brushes for different frequencies of brush oscillation. It is concluded that, for a horizontal cutting brush, oscillations have an impact on bristle dynamics, and its performance may be improved by varying the brush rotational speed at certain frequencies
An Efficient Greedy Traffic Aware Routing Scheme for Internet of Vehicles
Get PDFA new paradigm of VANET has emerged in recent years: Internet of Vehicles (IoV). These networks are formed on the roads and streets between travellers who have relationships, interactions and common social interests. Users of these networks exchange information of common interest, for example, traffic jams and dangers on the way. They can also exchange files such as multimedia files. IoV is considered as part of the Internet of Things (IoT) where objects are vehicles, which can create a multitude of services dedicated to the intelligent transportation system. The interest is to permit to all connected vehicles to communicate with each other and/or with a central server, through other vehicles. Vehicle to Vehicle (V2V) communication is the main component, because the services encompassed in the IoV are based on the vehicles in question, such as transmitter, relay and receiver. This work is focusing on designing and developing a Quality of Service (QoS) routing scheme dedicated to IoV networks. Especially, we aim to improve the Greedy Traffic Aware Routing (GyTAR) protocol to support QoS in IoV networks. To evaluate the proposed approach in terms of QoS in the context of IoV networks, the performance metrics such as average end-to-end delay and packet delivery ratio are taken into consideration to analyse the network situation
Research on Sensor Network Coverage Enhancement Based on Non-Cooperative Games
Get PDFCoverage is an important issue for resources rational allocation, cognitive tasks completion in sensor networks. The mobility, communicability and learning ability of smart sensors have received much attention in the past decade. Based on the deep study of game theory, a mobile sensor non-cooperative game model is established for the sensor network deployment and a local information-based topology control (LITC) algorithm for coverage enhancement is proposed. We both consider revenue of the monitoring events and neighboring sensors to avoid nodes aggregation when formulating the utility function. We then prove that the non-cooperative game is an exact potential game in which Nash Equilibrium exists. The proposed algorithm focuses on the local information of the neighboring sensors and decides sensors’ next action based on the actions of the other sensors, which maximizes its own utility function. We finally evaluate the performance of the proposed method through simulations. Simulation results demonstrate that the proposed algorithm can enlarge the coverage of the entire monitoring area while achieving effective coverage of the events
A Fair Blind Signature Scheme to Revoke Malicious Vehicles in VANETs
Get PDFWith the rapid development of IoT (Internet of Things), VANETs (Vehicular Ad-Hoc Networks) have become an attractive ad-hoc network that brings convenience into people’s lives. Vehicles can be informed of the position, direction, speed and other real-time information of nearby vehicles to avoid traffic jams and accidents. However, VANET environments could be dangerous in the absence of security protection. Because of the openness and self-organization of VANETs, there are plenty of malicious pathways. To guarantee vehicle security, the research aims to provide an effective VANET security mechanism that can track malicious vehicles as necessary. Therefore, this work focuses on malicious vehicles and proposes an anonymous authentication scheme in VANETs based on the fair blind signature to protect vehicle security
WiBPA: An Efficient Data Integrity Auditing Scheme Without Bilinear Pairings
Get PDFThe security of cloud data has always been a concern. Cloud server provider may maliciously tamper or delete user’s data for their own benefit, so data integrity audit is of great significance to verify whether data is modified or not. Based on the general three-party audit architecture, a dynamic auditing scheme without bilinear pairings is proposed in this paper. It utilizes exponential operation instead of bilinear mapping to verify the validity of evidence. By establishing the mapping relation between logic index and tag index of data block with index transformation table, our scheme can easily support dynamic data operation. By hiding random numbers in the integrity evidence, our scheme can protect users’ privacy information. Detailed security analysis shows that our scheme is secure against attacks such as forgery, replaying and substitution. Further experiments demonstrate that our scheme has lower computational overhead
Failure Prediction, Lead Time Estimation and Health Degree Assessment for Hard Disk Drives Using Voting Based Decision Trees
Get PDFHard Disk drives (HDDs) are an essential component of cloud computing and big data, responsible for storing humongous volumes of collected data. However, HDD failures pose a huge challenge to big data servers and cloud service providers. Every year, about 10% disk drives used in servers crash at least twice, lead to data loss, recovery cost and lower reliability. Recently, the researchers have used SMART parameters to develop various prediction techniques, however, these methods need to be improved for reliability and real-world usage due to the following factors: they lack the ability to consider the gradual change/deterioration of HDDs; they have failed to handle data unbalancing and biases problem; they don’t have adequate mechanisms for health status prediction of HDDs. This paper introduces a novel voting-based decision tree classifier to cater failure prediction, a balance splitting algorithm for the data unbalancing problem, an advanced procedure for lead time estimation and R-CNN based approach for health status estimation. Our system works robustly by considering a gradual change in SMART parameters. The system is rigorously tested on 3 datasets and it delivered benchmarks results as compared to the state of the art
Tibetan Multi-Dialect Speech and Dialect Identity Recognition
Get PDFTibetan language has very limited resource for conventional automatic speech recognition so far. It lacks of enough data, sub-word unit, lexicons and word inventories for some dialects. And speech content recognition and dialect classification have been treated as two independent tasks and modeled respectively in most prior works. But the two tasks are highly correlated. In this paper, we present a multi-task WaveNet model to perform simultaneous Tibetan multi-dialect speech recognition and dialect identification. It avoids processing the pronunciation dictionary and word segmentation for new dialects, while, in the meantime, allows training speech recognition and dialect identification in a single model. The experimental results show our method can simultaneously recognize speech content for different Tibetan dialects and identify the dialect with high accuracy using a unified model. The dialect information used in output for training can improve multi-dialect speech recognition accuracy, and the low-resource dialects got higher speech content recognition rate and dialect classification accuracy by multi-dialect and multi-task recognition model than task-specific models
Strategic Estimation of Kinetic Parameters in VGO Cracking
Get PDFFluid catalytic cracking (FCC) unit plays most important role in the economy of a modern refinery that it is use for value addition to the refinery products. Because of the importance of FCC unit in refining, considerable effort has been done by scientists till now on the modelling of this unit for better understanding and improved productivity. To model a FCC unit we have to know the unknown kinetic parameters of the governing equations.
The basic aim of this paper is to prove that MATLABTM can be used as a tool to find unknown kinetic parameters of governing equations for VGO cracking. We have developed a strategic method to find the unknown kinetic parameters using MATLAB and compare the simulation results with the results obtained from methods available in literature and it was found to be the best agreement
Multi-field Coupling of Particulate Systems
No full textA computational framework is established for effective modelling of fluid-thermal-particle interactions. The numerical procedures comprise the Discrete Element Method for simulating particle dynamics; the Lattice Boltzmann Method for modelling the mass and velocity field of the fluid flow; and the Discrete Thermal Element Method and the Thermal Lattice Boltzmann Method for solving the temperature field. The coupling of the three fields is realised through hydrodynamic interaction force terms. Selected numerical examples are provided to illustrate the applicability of the proposed approach