Moving destination prediction offers an important category of location-based applications and provides essential intelligence to business and governments. In existing studies, a common approach to ...destination prediction is to match the given query trajectory with massive recorded trajectories by similarity calculation. Unfortunately, due to privacy concerns, budget constraints, and many other factors, in most circumstances, we can only obtain a sparse trajectory dataset. In sparse dataset, the available moving trajectories are far from enough to cover all possible query trajectories; thus the predictability of the matching-based approach will decrease remarkably. Toward destination prediction with sparse dataset, instead of searching similar trajectories over the sparse records, we alternatively examine the changes of distances from sampling locations to final destination on query trajectory. The underlying idea is intuitive: It is directly motivated by travel purpose, people always get closer to the final destination during the movement. By borrowing the conception of gradient descent in optimization theory, we propose a novel moving destination prediction approach, namely MGDPre. Building upon the mobility gradient descent, MGDPre only investigates the behavior characteristics of query trajectory itself without matching historical trajectories, and thus is applicable for sparse dataset. We evaluate our approach based on extensive experiments, using GPS trajectories generated by a sample of taxis over a 10-day period in Shenzhen city, China. The results demonstrate that the effectiveness, efficiency, and scalability of our approach outperform state-of-the-art baseline methods.
Purpose
How to make accurate action decisions based on visual information is one of the important research directions of industrial robots. The purpose of this paper is to design a highly optimized ...hand-eye coordination model of the robot to improve the robots’ on-site decision-making ability.
Design/methodology/approach
The combination of inverse reinforcement learning (IRL) algorithm and generative adversarial network can effectively reduce the dependence on expert samples and robots can obtain the decision-making performance that the degree of optimization is not lower than or even higher than that of expert samples.
Findings
The performance of the proposed model is verified in the simulation environment and real scene. By monitoring the reward distribution of the reward function and the trajectory of the robot, the proposed model is compared with other existing methods. The experimental results show that the proposed model has better decision-making performance in the case of less expert data.
Originality/value
A robot hand-eye cooperation model based on improved IRL is proposed and verified. Empirical investigations on real experiments reveal that overall, the proposed approach tends to improve the real efficiency by more than 10% when compared to alternative hand-eye cooperation methods.
In comparison to single-model based trackers, the model-ensembled tracking strategy has shown a substantial adaptivity in handling various tracking challenges. As the performance of the tracker has ...been improved by combining different model outputs linearly, the insufficient consideration of each ensemble member's contribution still limits the tracking performance to be further enhanced. As the performance of the tracker has been improved by combining different model outputs linearly, the insufficient consideration of each ensemble member's contribution still limits the tracking performance to be further enhanced. In this paper, a tracking strategy based on multiple instance models regression (MIMRT) is proposed with a unified ensembling scheme. By formulating the tracking initialization with an instance model, the encoding process for an object's specific detail is performed corresponding to the samples in each frame. The advantage of this operation is to guarantee the model frame-wise discrimination of short-term training, as well as to evaluate the reliability of each instance model by utilizing the long-lifetime samples obtained throughout the whole tracking procedure. To finalize the proposed tracking, all the independent instance models attached to the learned regression coefficients are ensembled with respect to the long-lifetime samples. This also effectively bridges the instance model as a latent variable to investigate a semantic association between the tracking model and the overall samples. A comprehensive experiment has shown that the proposed tracker is able to achieve superior performances compared to the state-of-art tracking approaches on both short-term datasets ( e.g. , OTB2013, OTB100, VOT2016, UAV123) and long-term dataset (UAV20L).
In this study, the electrochemical technique is applied to accelerate chloride-ion migration in cement-based material to estimate its permeability. This article presents a simplified procedure to ...obtain the chloride profile in cement-based materials after the accelerated chloride migration test. The chloride profile can be obtained from the total amount of chloride and the surface chloride content. A good correlation is observed between the charge passed and the total amount of chloride during the non-steady-state condition, and the approximate surface chloride content can be obtained from the chloride content at the first slice (about 5 mm thickness). A simplified procedure using the charge passed and the near surface chloride content is developed to obtain the chloride profile. The chloride penetration depth is determined from the profile and the depth can be used to determine the non-steady-state chloride migration coefficient.
In this paper we present an operational model for XML document security. Given an XML document
X, the operational model defines the process of encrypting data and embedding digital signatures which ...sign the data in
X. The secured XML document
X
s includes encrypted and unencrypted data of
X, and embedded digital signatures. The operational model also defines the processes of decrypting
X
s and verifying the digital signatures embedded in
X
s. It offers a security mechanism which integrates element-wise encryption and temporal-based element-wise digital signatures. Our operational model provides element-wise encryption that is more general than previous forms of XML security, by including element encryption, content encryption, and two types of attribute encryption. Moreover, the model of temporal-based element-wise digital signature is novel. Based on the generalized operational model, we define a new language—called document security language (DSL)—to support it. The syntax of the encrypted document and the corresponding transformation language are presented. For automation reasons, the DSL includes a definition for the “standard DSL algorithm downloading and linking protocol” which fulfills automatic algorithm download and linking requirements in the operational model. This makes the DSL based securing tool configurable. Two different implementations further demonstrate its practicability: one uses the Java programming language to implement the securing tool, whilst the other employs the extension mechanism of XSLT 1.0 to implement the encryption and decryption transforms. The two implementations are available free on the Internet. Experimental results obtained when using our securing tool demonstrate the automation, efficiency, and practicability of the proposal operational model. In addition, we have developed a DSL editor with a friendly graphic user interface to make it easier for users to generate DSL documents.
•3D LBM simulation on interactions of multiple droplets for film formation.•Role of droplet spacing and advancing contact angle in affecting the outcome of coalescing process.•Effects of receding ...contact angle on the retracting behaviors of the contact line.•The best value of receding contact angel for uniform film.
3D numerical simulations are performed by depositing multiple droplets simultaneously to analyze the coalescence dynamics during a film formation process on a nonideal surface. This study aims to investigate the effects of droplet spacing(p), advancing contact angle(θA) and receding contact angle(θR) on the morphologies of coalesced films. A pseudopotential based multi-relaxation-time lattice Boltzmann model is employed for computations. With θR fixed at 0°, three different morphologies of film edges are observed with p or θA increases. It is found that the spread width of the connecting ridge undergoes severe changes as p and θA varies. Simulations indicate that θR is a key parameter to affect the retracting behaviors of the contact line, resulting in different outcomes of the coalescence process. When θR is prescribed slightly larger than the minimum value of instantaneous contact angle during the deformation process, the uniformity of film can be largely improved.
In this paper, we develop an optimization model for planning the positions of readers in the RFID network based on a novel multi-swarm particle swarm optimizer called PS
2O. The main idea of PS
2O is ...to extend the single population PSO to the interacting multi-swarms model by constructing hierarchical interaction topology and enhanced dynamical update equations. This algorithm, which is conceptually simple and easy to implement, has considerable potential for solving complex optimization problems. With five mathematical benchmark functions, PS
2O is proved to have significantly better performance than five successful variants of PSO. PS
2O is then used for solving the real-world RFID network planning problem. Simulation results show that the proposed algorithm proves to be superior for planning RFID networks than canonical PSO, multi-swarm cooperative PSO (MCPSO), and two evolutionary algorithms, namely genetic algorithm with elitism (EGA) and self-adaptive evolution strategies (SA-ES), in terms of optimization accuracy and computation robustness.
With the remarkable proliferation of smart mobile devices, mobile crowdsensing has emerged as a compelling paradigm to collect and share sensor data from surrounding environment. In many application ...scenarios, due to unavailable wireless network or expensive data transfer cost, it is desirable to offload crowdsensing data traffic on opportunistic device-to-device (D2D) networks. However, coupling between mobile crowdsensing and D2D networks, it raises new technical challenges caused by intermittent routing and indeterminate settings. Considering the operations of data sensing, relaying, aggregating, and uploading simultaneously, in this article, we study collaborative mobile crowdsensing in opportunistic D2D networks. Toward the concerns of sensing data quality, network performance and incentive budget, Minimum-Delay-Maximum-Coverage (MDMC) problem and Minimum-Overhead-Maximum-Coverage (MOMC) problem are formalized to optimally search a complete set of crowdsensing task execution schemes over user, temporal, and spatial three dimensions. By exploiting mobility traces of users, we propose an unified graph-based problem representation framework and transform MDMC and MOMC problems to a connection routing searching problem on weighted directed graphs. Greedy-based recursive optimization approaches are proposed to address the two problems with a divide-and-conquer mode. Empirical evaluation on both real-world and synthetic datasets validates the effectiveness and efficiency of our proposed approaches.
The dynamics of inkjet deposition in square microcavities are investigated utilizing a three-dimensional multi-relaxation-time pseudopotential lattice Boltzmann (LB) model with large density ratios. ...A geometric scheme is considered within the pseudopotential LBM framework to obtain the desired contact angles. The effects of wettability, density ratios, droplet viscosity and impact velocity are explored to reveal the droplet–microcavity interactions. With the contact angles of microcavity increasing, the physical outcomes including the crown-like shape with a small round dot, circular hollow core, uniform film and convex film are identified and analyzed. At a lower density ratio
ρ
r
= 11.6, the surrounding denser gas resists the droplet recoiling flow resulting in an increasing hollow core. The appropriate higher droplet viscosity and decreasing impact velocity are preferred which could eliminate the hollow core in the recoiling phase and accelerate the inkjet deposition process straightforward. The revelation of droplet-microcavity dynamics is beneficial for optimizing inkjet deposition process and fabricating uniform OLEDs panels.
•We provide a unique classification-based 3D change detection dataset from a complex street environment. There are no other open 3D point cloud datasets released for our purpose.•We evaluate ...different algorithms on the dataset and help finding solutions for 3D point cloud change detection tasks.•The results show that the proposed siamese graph convolutional networks (SiamGCN) are good at extracting representative geometric features and can hereby outperform compared algorithms on the 3D change detection dataset.
Display omitted
The rapid development of 3D acquisition devices enables us to collect billions of points in a few hours. However, the analysis of the output data is a challenging task, especially in the field of 3D point cloud change detection. In this Shape Retrieval Challenge (SHREC) track, we provide a street-scene dataset for 3D point cloud change detection. The dataset consists of 866 3D object pairs in year 2016 and 2020 from 78 large-scale street scene 3D point clouds. Our goal is to detect the changes from multi-temporal point clouds in a complex street environment.
We compare three methods on this benchmark, with one handcrafted (PoChaDeHH) and the other two learning-based (HGI-CD and SiamGCN). The results show that the handcrafted algorithm has balanced performance over all classes, while learning-based methods achieve overwhelming performance but suffer from the class-imbalanced problem and may fail on minority classes. The randomized oversampling metric applied in SiamGCN can alleviate this problem. Also, different siamese network architecture in HGI-CD and SiamGCN contribute to the designing of a network for the 3D change detection task.
PDF