In this article, we propose an integrated satellite–terrestrial network (ISTN) architecture to support delay-sensitive task offloading for remote Internet of Things (IoT), in which satellite networks serve as a complement to terrestrial networks by providing additional communication resources, backhaul capacities, and seamless coverage. Under this architecture, we investigate how to jointly make offloading link selection and bandwidth allocation decisions for BSs and IoT users. Considering the differentiated decision-making time granularities, we formulate a two-timescale stochastic optimization problem to minimize the overall task offloading delay. To accommodate the two-timescale network dynamics and characterize state–action relations, we establish a hierarchical Markov decision process (H-MDP) framework with two separate agents tackling two-timescale network management decisions, and two evolved MDP-based subproblems are formulated accordingly. To efficiently solve the subproblems, we further develop a hybrid proximal policy optimization (H-PPO)-based algorithm. Specifically, a hybrid actor–critic architecture is designed to deal with the mixed discrete and continuous actions. In addition, an action mask layer and an action shaping function are designed to sample feasible task offloading decisions from the time-variant action set. Extensive simulation results have validated the superiority of the proposed ISTN architecture and the H-PPO-based algorithm, especially, in scenarios with scarce spectrum resources and heavy traffic loads.

The ever-growing aging population has led to an increasing need for removable partial dentures (RPDs) since they are typically the least expensive treatment options for partial edentulism. However, the digital design of RPDs remains challenging for dental technicians due to the variety of partially edentulous scenarios and complex combinations of denture components. To accelerate the design of RPDs, we propose a U-shape network incorporated with Transformer blocks to automatically generate RPD clasps, one of the most frequently used RPD components. Unlike existing dental restoration design algorithms, we introduce the voxel-based truncated signed distance field (TSDF) as an intermediate representation, which reduces the sensitivity of the network to resolution and contributes to more smooth reconstruction. Besides, a selective insertion scheme is proposed for solving the memory issue caused by Transformer blocks and enables the algorithm to work well in scenarios with insufficient data. We further design two weighted loss functions to filter out the noisy signals generated from the zero-gradient areas in TSDF. Ablation and comparison studies demonstrate that our algorithm outperforms state-of-the-art reconstruction methods by a large margin and can serve as an intelligent auxiliary in denture design.

In this paper, we investigate the joint cache placement and content delivery in satellite-terrestrial integrated cloud radio access networks. We consider the scenario where cache-enabled access points (APs), including multiple base stations (BSs) and one low orbit earth satellite, are connected to a central processor via backhaul links and cooperatively serve users via joint beamforming. To minimize the long-term power consumption, we formulate an optimization problem to jointly optimize the cache placement, AP clustering, and multicast beamforming, while satisfying the constraints on the transmission power, quality-of-service, and caching storage. Since the formulated problem has mixed timescales, it is decoupled into two sub-problems. For the short-term delivery sub-problem, we first reformulate it as an equivalent sparse multicast beamforming problem and approximate the non-convex objective function by a concave smooth function, and then solve it with a convex-concave procedure approach. For the long-term cache placement sub-problem, we propose an alternating based method to tackle it iteratively. Simulation results validate the advantages of our proposed method and show the impacts of different cache capacities and file numbers on the long-term power consumption.

In this paper, an uplink power and bandwidth allocation problem for multiple services with multi-homing technology is formulated for cognitive heterogeneous networks. The joint power and bandwidth allocation with multiple services is subject to constraints in system available bandwidth, proportional fairness transmission rate for non-real-time secondary mobile terminals (MTs), minimum required transmission rate for real-time secondary MTs, interference power for primary base station, and total power consumption for each secondary MT. The joint power and bandwidth allocation problem with multiple services based on risk-return model is formulated as a bargaining game framework, first. Then, an optimal power and bandwidth allocation algorithm utilizing a dual decomposition method is proposed to obtain Nash bargaining solution. Finally, a heuristic algorithm is proposed to reduce computational complexity. Simulation results demonstrate the optimal and heuristic algorithms not only improve the spectrum efficiency, but also guarantee the fairness for secondary MTs with non-real-time service.

In this paper, a downlink security-aware resource allocation problem with delay constraint via spectrum sensing is modeled as a mixed integer non-linear problem for non-orthogonal multiple access-based cognitive radio network. The security-aware resource allocation is subject to constraints in required delay for each secondary user, maximum number of accessed secondary users at each subchannel, total interference power threshold introduced to primary users, and total power consumption at secondary BS. The security-aware resource allocation is based on channel state information at the physical layer and queue state information at the link layer. According to the queue buffer occupancy, a probability upper bound of exceeding the maximum packet delay based on M/D/1 queuing model is analyzed in terms of a required minimum secrecy transmission rate. Then, a secondary user scheduling problem and a power allocation problem are solved, separately. Finally, the secondary user scheduling problem is solved via greedy algorithm, and a power allocation algorithm is proposed by successive convex approximation method. The simulation results demonstrate that the performance of proposed algorithms can be improved significantly.

As energy and signal transmission medium, cable harness is widely used in complex mechatronic products, and cable harness information are the basis and premise conditions of the flexible cable harness assembly simulation of complex mechatronic products system. To retrieve cable harness information from the information management system or repository effectively, a push method of cable harness information for complex mechatronic products based on variable precision rough sets (VPRS) was proposed in this paper. By using the cable harness information reduction method, the cable harness information repository is simplified, and rules which can support the precise push also be distilled from the reduct cable harness information repository. On the basis of the above approach, cable harness wiring designers, assembly process planners and assembly process simulation designers can efficiently share cable harness information during all design processes. Finally, a case is employed to validate the proposed method of this paper.

The curvature scale-space (CSS) technique is suitable for extracting curvature features from objects with noisy boundaries. To detect corner points in a multiscale framework, Rattarangsi and Chin investigated the scale-space behavior of planar-curve corners. Unfortunately, their investigation was based on an incorrect assumption, viz., that planar curves have no shrinkage under evolution. In the present paper, this mistake is corrected. First, it is demonstrated that a planar curve may shrink nonuniformly as it evolves across increasing scales. Then, by taking into account the shrinkage effect of evolved curves, the CSS trajectory maps of various corner models are investigated and their properties are summarized. The scale-space trajectory of a corner may either persist, vanish, merge with a neighboring trajectory, or split into several trajectories. The scale-space trajectories of adjacent corners may attract each other when the corners have the same concavity, or repel each other when the corners have opposite concavities. Finally, we present a standard curvature measure for computing the CSS maps of digital curves, with which it is shown that planar-curve corners have consistent scale-space behavior in the digital case as in the continuous case.

According to the characteristics and difficulties of the aircraft tooling collaborative design as well as the state-of-the-art of some aircraft manufacturing enterprises, the necessity of realizing semantic collaboration of the aircraft tooling design is analyzed. By studying semantic collaboration and semantic information transferring in aircraft tooling design, a semantic collaboration implementation framework of aircraft tooling design is constructed. Based on this framework, the multi-agent-based semantic collaboration technology of aircraft tooling design is put forward. By mean of combining multi-agent technology with CAD, PDM and knowledge management technologies, this technology solves the issues in distributed semantic collaboration and semantic information transmission of aircraft tooling design. And the implementation process is introduced through a pilot system. This system has been partially tested in an aviation enterprise. By comparison, this system has the advantages of opening, real-time, intelligence and etc. Finally, further work is prospected.

Geodesic computation is very important in various mesh processing techniques such as re-meshing, parameterizing, segmenting, navigating and editing. In this paper we propose a new approach to compute the geodesic paths on triangular meshes. Considering the geodesic path is a local shortest and straightest path between two points on the surface, we first get an initial approximation of the geodesic path using direction tracking method proposed in this paper, and then the approximate path is corrected using an iterative process to get an accurate approximation with bounded error.

Considering the characteristic and difficulty of airplane tooling design that the correlation is complicated and cooperation is difficult, the collaborative design framework for airplane tooling is constructed, and the key technologies, including the technology of collaboration between tooling design and airplane product design, the collaborative design technology of airplane tooling application model, the correlative design technology of airplane tooling structure, and the correlative design technology of airplane tooling semantic information are brought forward in this paper and the collaborative design for airplane tooling in different levels is realized. The software system based on those technologies is applied to an aviation manufacture enterprise and has many advantages such as little dependence on the network, controllable and correlative update.

The Curvature Scale Space (CSS) technique is considered to be a modern tool in image processing and computer vision. Direct Curvature Scale Space (DCSS) is defined as the CSS that results from convolving the curvature of a planar curve with a Gaussian kernel directly. In this paper we present a theoretical analysis of DCSS in detecting corners on planar curves. The scale space behavior of isolated single and double corner models is investigated and a number of model properties are specified which enable us to transform a DCSS image into a tree organization and, so that corners can be detected in a multiscale sense. To overcome the sensitivity of DCSS to noise, a hybrid strategy to apply CSS and DCSS is suggested.

Concurrent engineering, collaborative design and network manufacturing have higher demands for parts library to share information in and among enterprises. Based on the study of the diverse parts library application status, a parts library application level model (PL-AIM) is put forward, which consists of geometry layer, system layer, neutral layer and network layer. The contents of different layers of the PL-ALM are expatriated. In order to upgrade parts libraries on different layers gradually, a solution is provided aiming at single geometry information, multi-view information, heterogeneous information and distributed information respectively. According to the PL-ALM, evaluation software is developed, which standardizes and advances the application level of parts library of enterprises

Web-based parts library is important to collaborative design, concurrent engineering and supply chain management system. As common resources, Web-based parts library should be integrated into different application systems of not only parts suppliers but also enterprises. Other than research of product design, the research of Web-based parts library pays more attention to previewing parts shape, acquiring features and attributes. The following progresses are achieved in this paper. A data description norm of parts in network is put forward, based on which parts information is described in XML. Accordingly, information integration of parts library not only accords with PLIB standard but also is realized on data dictionary. A hoops-based visualization method of part feature model is presented which realizes quick browse of parts geometric model and share of design intention by extracted feature tree. Parameterized design technology driven by remote data is brought forward. Geometric information and attributes are encapsulated with master parameters and local geometric models are driven by remote geometric parameters. The above achievements are used in China National 863 High-Tech Project. Besides, the achievements have been embodied in the international standard raised by China National Institute of Standardization and provided the technical foundation to propose the international standards with Chinese independent intellectual property right.

The curvature scale space (CSS) technique is one of the key techniques of the MPEG-7 international standard in computer vision and image processing. It was selected as a contour shape descriptor for MPEG-7 after substantial and comprehensive testing. However, to compute a CSS image in general needs to wait a long time. This is very disadvantageous when the CSS technique is applied to an object recognition system to perform real-time recognition. In order to solve this bottleneck problem, a hybrid method for fast computing the CSS image is proposed. In the method, firstly the curve is evolved in low scale space, and after image noise is suppressed then the curvature is evolved directly. Numerical experiments show that the hybrid method can perform equally well as the existing method. It is suitable for recognizing a noisy curve of arbitrary shape at any scale or orientation. On the other hand, the hybrid method only requires 1/3 /spl sim/ 1/5 CPU time of the existing one. As a result, the CSS technique is improved significantly for real-time recognition.