With the unprecedented development of smart mobile devices (SMDs), e.g., Internet-of-Things and smartphones, various computation-intensive applications are explosively increasing in ultradense networks (UDNs). Mobile-edge computing (MEC) has emerged as a key technology to alleviate computation workloads SMDs decrease service latency for applications. benefits network function virtualization, MEC can be integrated with cloud radio access (C-RAN) UDNs communication cooperation. However,...

Heterogeneous graphs with different types of nodes and edges are ubiquitous have immense value in many applications. Existing works on modeling heterogeneous usually follow the idea splitting a graph into multiple homogeneous subgraphs. This is ineffective exploiting hidden rich semantic associations between for large-scale multi-relational graphs. In this paper, we propose Relation Structure-Aware Graph Neural Network (RSHN), unified model that integrates its coarsened line to embed both...

Technological evolutions in unmanned aerial vehicle (UAV) industry have granted UAVs more computing and storage resources, leading to the vision of UAVs-assisted edge computing, which missions can be offloaded from a cellular network UAV cloudlet. In this paper, we propose computation offloading paradigm, where group fly around, while providing value-added services. The complex are decomposed as some typical task-flows with inter-dependencies. By taking into consideration inter-dependencies...

Drug-drug interaction (DDI) prediction identifies interactions of drug combinations in which the adverse side effects caused by physicochemical incompatibility have attracted much attention. Previous studies usually model information from single or dual views whole molecules but ignore detailed among atoms, leads to incomplete and noisy limits accuracy DDI prediction. In this work, we propose a novel dual-view representation learning network for ('DSN-DDI'), employs local global modules...

Unmanned aerial vehicle (UAV)-assisted communication is envisioned as a potential solution to the data traffic explosion in massive machine-type communications (mMTC) scenario. In this article, we investigate UAV-assisted cellular networks, where UAV acts flying relay offload part of from overloaded cell another. We utilize practical spatial distribution and convincing air-to-ground channel model. The quality service (QoS) defined utility function which designed based on packet loss ratio...

Empirical models that relate multiple quality features to a set of design variables play vital role in many industrial process optimization methods. Many the current modeling methods employ single-response normal model analyze processes without taking into consideration high correlations and non-normality among response variables. Also, problem variable selection has also not yet been fully investigated within this framework. Failure account for these issues may result misleading prediction...

GaN with aligned nanopores was fabricated using a lateral anodic etching process in HNO3 solution. This laterally porous structure can be modified from triangular pores to quasi-circular increasing the voltage, indicating transformation anisotropic gradually toward isotropic etching. Furthermore, we have established correlation between current and pore trajectories based on situ chronoamperometry find that is initially driven by avalanche effect, then enter steady state as balance oxidation...

Computation-intensive mobile applications are explosively increasing and cause computation overload for smart devices (SMDs). With the assistance of edge computing cloud computing, SMDs can rent resources offload computation-intensive to clouds remote clouds, which reduces application completion delay energy consumption SMDs. In this paper, we consider with task call graphs investigate offloading resource scheduling problem in hybrid edge-cloud networks. Due interdependency tasks,...

Research and applications of unmanned aerial vehicles (UAVs) are becoming increasingly prosperous in these years due to the maturity aircraft technology regulations. A large amount UAVs be deployed cities undertake tasks such as environment monitoring security surveillance. For those computation-intensive tasks, on-board execution can lead inefficiency unsustainability limited battery life computing resources UAVs. To this end, paper adopts cooperative mobile edge that energy consumption...

The implementationof computation offloading is a challenging issue in the remote areas where traditional edge infrastructures are sparsely deployed. In this study, authors propose unmanned aerial vehicle (UAV)-enabled computing framework, group of UAVs fly around to provide near-users service. They study migration problem for complex missions, which can be decomposed as some typical task-flows considering inter-dependency tasks. Each time task appears, it should allocated proper UAV...

Graph Neural Networks (GNNs) have achieved state-of-the-art performance in many graph data analysis tasks. However, they still suffer from two limitations for representation learning. First, exploit non-smoothing node features which may result suboptimal embedding and degenerated classification. Second, only neighbor information but ignore global topological knowledge. Aiming to overcome these simultaneously, this paper, we propose a novel, flexible, end-to-end framework, Smoothing Splines...

Learning the embeddings for urban regions from human mobility data can reveal functionality of regions, and then enables correlated but distinct tasks such as crime prediction. Human contains rich abundant information, which yields to comprehensive region cross domain tasks. In this paper, we propose multi-graph fusion networks (MGFN) enable prediction First, integrate graphs with spatio-temporal similarity patterns through a graph module. Then, in pattern joint learning module, design...

To address the common issues of wrinkling, tearing, and uneven wall thickness in actual sheet metal stamping process outer ring needle roller bearings, this study analyzes critical technical indicators such as forming limits, distribution, principal strains detail. Three-dimensional models concave convex dies were constructed. The effects different parameters, including speed, edge pressure, thickness, friction coefficient, on quality parts investigated by varying these parameters....

When a fire takes place in tunnel, the surface of asphalt pavement will burn and release large amount smoke, which is toxic to human health. Thus, order prevent combustion under fire, it necessary propose some methods retard its physical chemical reaction high temperature. In this study, ten different combinations retardants control case where no retardant was applied were prepared for evaluation. The thermogravimetric (TG)–mass spectrometry (MS) tests used evaluate their effect on...

While numerous approaches have been developed to embed graphs into either Euclidean or hyperbolic spaces, they do not fully utilize the information available in graphs, lack flexibility model intrinsic complex graph geometry. To strength of both and geometries, we develop a novel Geometry Interaction Learning (GIL) method for well-suited efficient alternative learning abundant geometric properties graph. GIL captures more informative internal structural features with low dimensions while...

Space-air-ground integrated network (SAGIN) is emerging as a prominent framework supporting the ever-growing Internet of Things (IoT) applications in areas without infrastructures. In this paper, we investigate problem IoT task offloading under SAGIN scenario where multiple devices cooperatively use computing resources. We formulate minimizing processing delay all tasks, taking into account dynamics tasks generated by each device, mobility unmanned aerial vehicle (UAV), and difference power...

Abstract Drug-drug interaction (DDI) prediction provides a drug combination strategy for systemically effective treatment. Previous studies usually model information constrained on single view such as the itself, leading to incomplete and noisy information, which limits accuracy of DDI prediction. In this work, we propose novel multi-view substructure network (“MSN-DDI”), learns chemical substructures from both representations (“intra-view”) pair (“inter-view”) simultaneously utilizes update...

Taking a cylindrical roller bearing as research object, the contact stress between and outer ring raceway with taper error is studied by means of ANSYS in order to obtain allowable value upper bound error. The results show that given load corresponds suitable increasing error, stresses increase observably distribution presents more complex asymmetry nonuniformity.

Abstract Failure Mode and Effect Analysis (FMEA) is acknowledged as a beneficial instrument for identifying mitigating system failures. However, the traditional FMEA method has its limitations. For instance, crisp numbers fail to adequately represent intricate information cognitive nuances of experts. Additionally, conventional approach overlooks significance weights assigned experts risk factors (RFs). Furthermore, simplistic ranking failure modes in does not accurately reflect priorities....