Two-layered Scheme Research Articles

Communication-Constrained Routing and Traffic Control: A Framework for Infrastructure-Assisted Autonomous Vehicles

With the increasing demand for advanced autonomous driving, the available communication resources may become constrained over different geographic areas. In addition, due to dynamic channel variations and imperfect cell deployments, guaranteeing the required communication resources for data hungry and delay-sensitive applications in autonomous vehicles (AVs), along their entire trips, becomes challenging. To address these issues, the paper investigates the feasibility of a hybrid system-optimum and user-equilibrium AV traffic framework subject to communication constraints, as well as its performance gain. Within such a framework, the paper introduces the problems of communication-constrained routing (CCR) and traffic control (CCTC) in the context of infrastructure-assisted autonomous driving and presents respective solutions. For CCR, an efficient two-layered routing scheme is proposed which can provide optimal trip duration. Simulation results show that the routing scheme achieves a good balance between longer duration of communication coverage and acceptable source-to-destination travel time. For CCTC, it is shown that there exists an optimal AV speed on each road segment, as well as an optimal inter-AV distance and an optimal number of AVs in each cell, to maximize the road-network AV throughput within a single cell. Moreover, spectrum allocation is used to achieve Pareto-optimal road-network throughput across cells, and a new key performance index (KPI) is defined to evaluate the traffic control capability of cellular systems. Simulation results validate the improvement of AV throughput via the proposed CCTC solution.

A Two-Layered Incentive Scheme for Cooperation in Sliced 5G D2D Networks

In the fifth generation (5G) networks, isolated logical slices are formed by the same infrastructure, and spectrum resource. In the coverage regions of the sharing access points (APs), device to device (D2D) communication can occur among different slices, i.e., one mobile terminal (MT) acts as a D2D relay for another MT serving by a different slice. Since the slices, and the MTs are selfish who will not help others voluntarily, this paper proposes a two-layered incentive scheme to stimulate cooperation. To achieve this, two resource allocating problems of the proposed incentive scheme are formulated which introducing the slices,' and the MTs' cooperative activities, thus more resources will be allocated to the cooperative slices, and MTs as reward. Since the slices,' and the MTs' instantaneous resource allocations can not be obtained by the two optimal problems, the incentive scheduling algorithms of the slices, and the MTs are designed. Finally, we define the isolation indexes to evaluate slice isolation when carrying out cooperation. By simulating, it is proved that the proposed incentive scheme can stimulate cooperation efficiently, since the throughputs of the cooperative slices, and MTs are both improved. And the proposed incentive scheme is helpful for the slices, and the MTs to meet the statistical service quality requirements, and brings the bad effect to the instantaneous service quality requirements.

A Hierarchical Buffer Management Approach to Rate Adaptation for 360-Degree Video Streaming

For the 360-degree virtual reality (VR) videos, to achieve the same user-perceived playout quality with traditional video, the overall video bitrate has to be much higher, which significantly increases the bandwidth requirement. To overcome this issue, most of rate adaptation schemes are proposed based on the users' Field of View (FoV), since users only view part of the entire videos when watching 360-degree videos. However, the FoV prediction is only valid in short terms which incurs low robustness against network dynamics and results in frozen screen events. Since the playback buffer can effectively avoid re-buffering by storing videos in advance, we propose a two-layered hierarchical buffer-based rate adaptation scheme for 360-degree VR videos in this paper. The tiles will be updated to enhance the video quality in the short buffer layer based on FoV prediction, meanwhile the long buffer layer takes charge of downloading new chunks to guarantee the buffer occupancy. To better improve the quality of experience (QoE), we jointly consider the users' FoV, channel conditions and buffer status. Our method achieves a good trade-off between video quality and buffer occupancy. Besides, the maximum buffer level selection is optimized to further improve the performance. The simulation results show that our proposed scheme and algorithms outperform other methods by about 5%-30% of QoE improvement.

Trusting privacy in the cloud

Cloud computing technologies can increase innovation and economic growth considerably. Because of privacy concerns, however, many users underutilize cloud technologies. This paper designs an institution attenuating the problem: a two-layered certification scheme built around a private, nonprofit organization called cloud association. This association is governed by representatives of both users and cloud service providers and sources auditing and certification of providers out to independent for-profit certifiers. It is shown how this institution incentivizes providers to produce high data security, and users with strong privacy preferences to trust them and pay a premium for their services.

Novel classification for global gene signature model for predicting severity of systemic sclerosis.

Progression of systemic scleroderma (SSc), a chronic connective tissue disease that causes a fibrotic phenotype, is highly heterogeneous amongst patients and difficult to accurately diagnose. To meet this clinical need, we developed a novel three-layer classification model, which analyses gene expression profiles from SSc skin biopsies to diagnose SSc severity. Two SSc skin biopsy microarray datasets were obtained from Gene Expression Omnibus. The skin scores obtained from the original papers were used to further categorize the data into subgroups of low (<18) and high (≥18) severity. Data was pre-processed for normalization, background correction, centering and scaling. A two-layered cross-validation scheme was employed to objectively evaluate the performance of classification models of unobserved data. Three classification models were used: support vector machine, random forest, and naive Bayes in combination with feature selection methods to improve performance accuracy. For both input datasets, random forest classifier combined with correlation-based feature selection (CFS) method and naive Bayes combined with CFS or support vector machine based recursive feature elimination method yielded the best results. Additionally, we performed a principal component analysis to show that low and high severity groups are readily separable by gene expression signatures. Ultimately, we found that our novel classification prediction model produced global gene signatures that significantly correlated with skin scores. This study represents the first report comparing the performance of various classification prediction models for gene signatures from SSc patients, using current clinical diagnostic factors. In summary, our three-classification model system is a powerful tool for elucidating gene signatures from SSc skin biopsies and can also be used to develop a prognostic gene signature for SSc and other fibrotic disorders.

Decision Support for Enhancement of Manufacturing Sustainability: A Hierarchical Control Approach

From the sustainability science point of view, improvement of manufacturing sustainability involves a series of system (performance) state transitions in a sustainable development (SD) space. The transitions occur based on the system information obtained through stage-wised sustainability assessment and the actions on the system taken based on the derived stage-wised decisions. From the standpoint of control engineering, this is a multiobjective system control problem. In this paper, we introduce a general decision-support framework for deriving strategies to achieve short-to-long-term sustainability goals. In this framework, a two-layered hierarchical control scheme is introduced to implement strategic and tactical control for dynamic sustainability control. A comprehensive case study on biodiesel manufacturing is illustrated to demonstrate methodological efficacy.

From bird’s eye views to molecular communities: two-layered visualization of structure–activity relationships in large compound data sets

The analysis of structure-activity relationships (SARs) becomes rather challenging when large and heterogeneous compound data sets are studied. In such cases, many different compounds and their activities need to be compared, which quickly goes beyond the capacity of subjective assessments. For a comprehensive large-scale exploration of SARs, computational analysis and visualization methods are required. Herein, we introduce a two-layered SAR visualization scheme specifically designed for increasingly large compound data sets. The approach combines a new compound pair-based variant of generative topographic mapping (GTM), a machine learning approach for nonlinear mapping, with chemical space networks (CSNs). The GTM component provides a global view of the activity landscapes of large compound data sets, in which informative local SAR environments are identified, augmented by a numerical SAR scoring scheme. Prioritized local SAR regions are then projected into CSNs that resolve these regions at the level of individual compounds and their relationships. Analysis of CSNs makes it possible to distinguish between regions having different SAR characteristics and select compound subsets that are rich in SAR information.

The Distribution and Strength of Brönsted Acid Sites on the Multi-Aluminum Model of FER Zeolite: A Theoretical Study

One of the fundamental issues in catalysis is to identify the catalytic active site. Due to its prominent pore topology and acidity, ferrierite (FER) zeolite has attracted extensive interest in various catalytic reactions such as isomerization of butenes. However knowledge on the active Brönsted acid site is still absent. In the present study, we perform extensive density functional theory calculations to explore the distribution and strength of the Brönsted acid sites and their potential catalytic activity for the double-bond isomerization of 1-butene to 2-butene. We employ a two-layered ONIOM scheme (our Own N-layered Integrated molecular Orbital + molecular Mechanics) to describe the structure and energetic properties of FER zeolite. We find that the hydrogen bond could improve the stability of Brönsted acid sites effectively, and, as a result, Al4-O6-Si2 and Al4-O-(SiO)2-Al4 are the most stable sites for 1-Al substitution and 2-Al substitution, respectively. We further find that the Brönsted acid strength tends to decrease with the increase of Al contents and increase when the distance between the Al atoms is increased in 2-Al substitution. Finally it is demonstrated that the strength of acid sites determines the catalytic activity for the double bond isomerization of 1-butene to 2-butene.

An indirect tire identification method based on a two-layered fuzzy scheme

While the heights and numbers of tires in the assembly line are changing, the traditional methods are difficult to identify the types of the tires, so an indirect tire identification method is proposed to identify the types of the tires, which uses the widths of the tires, the diameters and the shapes of the hubs to classify the tires. First, the tires are identified according to the widths and diameters by using the fuzzy C-means clustering algorithm. Second, the shapes of the hubs are used to distinguish the tires with similar dimensions. Finally, a two-layered fuzzy scheme is designed to identify the tires. Experimental results show that the two-layered fuzzy scheme is more effective than the fuzzy C-means clustering algorithm. And the proposed indirect tire identification method can achieve an accuracy of above 99.9% in the assembly line of tires.

A two-layered cross coupling control scheme for a three-dimensional motion control system

A two-layered modeling and compensation scheme is proposed to reduce the contouring error of a three-dimensional motion control system. In the proposed scheme, the contouring error model of the three-dimensional motion control system is divided into two layers: the top layer and the bottom layer. The proposed multi-layered structure of the contouring error model presents more flexibility in the control system design because the cross coupling controllers in different layers can be designed separately. In this paper, a nonlinear PI controller and a position error compensator are designed in the bottom layer in order to achieve high contouring accuracy in the XY plane, while a unilateral compensator is designed in the top layer to further reduce contouring error in the three dimensional space. Finally, experiments are performed to verify the performance of the proposed two-layered modeling and compensation scheme. Experiment results show that the designed two-layered cross coupling controller can obtain higher contouring accuracy than traditional cross coupling controller both in the XY plane and in the XYZ space.

A low-complexity explicit MPC controller for AFR control

Control of the air–fuel ratio in combustion engines is of imminent importance when aiming at reduction of the fuel consumption and mitigation of emissions. In this paper this is achieved by employing Model Predictive Control (MPC), which keeps the air-fuel ratio close to the stoichiometric value. The real-time implementation of MPC is accelerated by pre-computing the optimal solution and using the explicit MPC approach. The memory footprint of such a controller is subsequently reduced by employing a two-layered compression scheme. Quality of the regulation is demonstrated using real engine data and is compared to traditional control approach based on PID.

Shear Hele-Shaw flows of a weakly compressible liquid

We derive an integro-differential system of equations to describe the shear flows of a weakly compressible multicomponent liquid in a Hele-Shaw cell. The velocities of propagation of nonlinear disturbances in the liquid are determined, and the characteristic form of the system is calculated. The conditions for hyperbolicity of the model are formulated that are necessary for the correct statement of the Cauchy problem. The multilayered one-dimensional motion of the liquid are considered and, within the framework of the two-layered scheme of the flow, interpretation is given of the Saffman-Taylor instability.

Neural-Network-Based Contouring Control for Robotic Manipulators in Operational Space

This brief presents a contouring control scheme for robotic manipulators. The geometric properties of the desired contour are incorporated in the controller design phase, and the resulting controller has been structured as a two-layered hierarchical control scheme that consists of an outer loop and an inner loop. The outer loop is formed by kinematic control system in operational space, which can be designed to assign different dynamics to the tangential, normal, and binormal direction of the desired contour. It is shown that the outer loop can provide a joint velocity reference signal to the inner one. The inner loop is used to implement a velocity servo control system at the robot joint level. Meanwhile, a radial basis function network is adopted to compensate for the nonlinear dynamics of the robotic manipulator, where a robust control strategy is used to suppress the modeling error of neural networks. Experimental results on the Zebra-Zero robotic manipulator have demonstrated the effectiveness of the proposed control scheme in comparison with other control strategies.

A simulated annealing based solution approach for the two-layered location registration and paging areas partitioning problem in cellular mobile networks

This paper presents a mathematical model and simulated annealing based solution approach for finding optimal location updates and paging area configuration for mobile communication networks. We use a two-layered zone-based location registration and paging scheme in which the costs of location updates and paging signaling traffic are reduced by introducing a two-step paging process. The location updates and paging procedures in a two-layered scheme are first described, and an approximation of the measure required for calculating the paging-related signaling volume is provided based on assumptions of cell shapes and mobile stations’ movement patterns. A simulated annealing (SA)-based solution method is devised along with a greedy heuristic, and computational experiments are conducted to illustrate the superiority of the proposed SA-based method over other solution methods.

Communication Capacity and Quality Enhancement Using a Two-Layered Adaptive Resource Allocation Scheme for Multi-Beam Mobile Satellite Communication Systems

To obtain large capacity, high quality mobile satellite communication systems in the future, we must use a multi-beam that can cope with extremely high levels of frequency reuse. This paper describes a novel resource allocation algorithm for multi-beam satellite communication systems that can dynamically adapt to maximum communication capacity without compromising quality. The algorithm combines two resource allocation schemes that enable it to contend with the ever-changing user distribution and inter-beam interference conditions. The first scheme optimizes the resources amongst beams. To minimize interference, the optimal constraint conditions are clarified when all clusters share and occupy the same bandwidth completely. These constraints are used in the optimization algorithm. The second scheme manages the various required resources and adapts them to the beam gain and interference levels at various user locations within a single beam. We propose a fixed power adaptive modulation scheme to obtain stable communications. This two-layered scheme can satisfactorily allocate multi-beam satellite resources to contend with the increasing communication capacity and still improve the quality.

An analytical delamination model for laminated plates including bridging effects

A penalised interface model, whose strain energy is the penalty functional related to interface adhesion constraint, is introduced in conjunction with a damageable interface whose local constitutive law, in turn, represents bridging stress effects, in order to analyse delamination and bridging phenomena in laminated plates. The laminate is modelled by means of first-order shear deformable layer-wise kinematics and the governing equations are formulated in the form of a non-linear differential system with moving intermediate boundary conditions related to opportune delamination and bridging growth conditions. The problem is solved through an analytical approach. The model leads to an accurate and self-consistent evaluation of the energy release rate and its mode components due to the inclusion of significant contributions arising from coupling between in-plane and transverse shear stresses, and to an asymptotic estimate of interlaminar stresses. The salient features of the proposed model are investigated in the context of an energy balance approach and of a J-integral formulation, thus providing simple results useful to model delamination growth and bridging behaviour when mixed mode loading is involved. The accuracy of the proposed model is substantiated through comparisons with results from continuum analysis obtained by a finite element (FE) procedure. The effectiveness of the proposed model is highlighted by showing the solution of a two-layered plate scheme subjected to pure and mixed mode loading conditions and to fibre bridging stresses. The results point out that the present model, despite its low computational cost in comparison with more complex FE analyses, is an efficient tool to predict delamination and bridging evolution.

A two-layered wavelet-based algorithm for efficient lossless and lossy image compression

In this paper, we propose a wavelet-based image-coding scheme allowing lossless and lossy compression, simultaneously. Our two-layered approach utilizes the best of two worlds: it uses a highly performing wavelet-based or wavelet packet-based coding technique for lossy compression in the low bit range as a first stage. For the second (optional) stage, we extend the concept of reversible integer wavelet transforms to the more flexible class of adaptive reversible integer wavelet packet transforms which are based on the generation of a whole library of bases, from which the best representation for a given residue between the reconstructed lossy compressed image and the original image is chosen using a fast-search algorithm. We present experimental results demonstrating that our compression algorithm yields a rate-distortion performance similar or superior to the best currently published pure lossy still image-coding methods. At the same time, the lossless compression performance of our two-layered scheme is comparable to that of state-of-the-art pure lossless image-coding schemes. Compared to other combined lossy/lossless coding schemes such as the emerging JPEG-2000 still image-coding standard PSNR improvements up to 3 dB are achieved for a set of standard test images.

A new two-layered video compression scheme for multiple applications

The authors describe a new multipurpose two-layered video compression system. The new two-layered video compression system provides the capability of encoding a higher resolution video sequence with a small modification outside the existing compression hardware. The techniques used were subsampling and expansion combined with differential pulse code modulation (DPCM) coding of the detail information lost in the subsampling process. Quadtree coding was used to encode the location of the regions to which the details were added. Simulation results of the two-layered system are included.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Two-layered difference schemes for solving multipoint problems

In a Hilbert space one considers the two-layered difference scheme with the multipoint condition Here B and A (t) are symmetric and positive-definite operators from H into H. Under the assumption of the operator inequalities (τ is the step of the net) τ for some constants ε>O,q>O (3) one establishes estimates for the solution of problem (1), (2) in terms of (). On the basis of these estimates one investigates linear and non-linear schemes with weights. The obtained results are applied to establish the order of convergence of the difference methods for solving periodic boundary-value problems for second-order quasilinear parabolic equations.