Collaborative Computing: Networking, Applications and Worksharing
18th EAI International Conference, CollaborateCom 2022, Hangzhou, China, October 15-16, 2022, Proceedings, Part II
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767 Result(s)
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**ao** Wei
Artificial Intelligence
Computer Communication Networks
Information Systems Applications (incl. Internet)
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Article
Indexing spatiotemporal trajectory data streams on key-value storage
In a trajectory management system, moving objects are typically equipped with GPS devices to report their locations to a data store. Given the potentially high frequency of location updates by multiple moving ...
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Article
Community anomaly detection in attribute networks based on refining context
With the widespread use of attribute networks, anomalous node detection on attribute networks has received increasing attention. By utilizing communities as reference contexts for local anomaly node detection,...
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Article
An improved indicator-based two-archive algorithm for many-objective optimization problems
The large number of objectives in many-objective optimization problems (MaOPs) has posed significant challenges to the performance of multi-objective evolutionary algorithms (MOEAs) in terms of convergence and...
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Article
TEDA: a trusted execution environment-and-blockchain-based data protection architecture for Internet of Things
With the popularity of the Internet of Things (IoT), massive amounts of data are generated every second. By analyzing this data, attackers can launch kinds of attacks for their own profits, such as data tamper...
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Article
A fast and accurate coupled meshless algorithm for the 2D/3D Gross–Pitaevskii equations on two GPUs
This paper first presents a high-efficient and accurate coupled meshless algorithm for solving the multi-dimensional Gross–Pitaevskii equation (GPE) in unbounded domain, which is implemented on CUDA-program-ba...
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Article
A framework for data anomaly detection based on iterative optimization in IoT systems
With the advent of 5 G, the Internet of Things (IoT) makes many basic applications possible. In IoT applications, sensors are widely deployed to collect various data. Due to the dynamic nature of the wireless ...
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Article
Signed directed attention network
Network embedding has facilitated lots of network analytical tasks by representing nodes as low-dimensional vectors. As an extension of convolutional neural networks from Euclidean data to irregular data, Grap...
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Article
Combining unsupervised and supervised classification for customer value discovery in the telecom industry: a deep learning approach
Customer behaviour analysis in a telecom market is a challenging task in the customer relationship management area. In this paper, we propose a customer behaviour recognition model that combines unsupervised c...
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Article
A Prior-mask-guided Few-shot Learning for Skin Lesion Segmentation
The incidence of skin cancer, which has high mortality, is growing rapidly worldwide. Early detection of skin lesions is crucial for timely diagnosis and treatment to improve the patient survival rate. Compute...
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Article
Trust on wheels: Towards secure and resource efficient IoV networks
The emerging yet promising paradigm of Internet-of-Vehicles (IoV) has received considerable attention in the recent years as an integral and indispensable constituent of the modern intelligent transportation s...
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Article
Network structure optimization for social networks by minimizing the average path length
Network structure plays an important role in the natural and social sciences. Optimization of network structure in achieving specified goals has been a major research focus. In this paper, we focus on structur...
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Chapter and Conference Paper
Calibrating Histopathology Image Classifiers Using Label Smoothing
The classification of histopathology images fundamentally differs from traditional image classification tasks because histopathology images naturally exhibit a range of diagnostic features, resulting in a dive...
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Chapter and Conference Paper
RShield: A Refined Shield for Complex Multi-step Attack Detection Based on Temporal Graph Network
Complex multi-step attacks (i.e., CMA) have caused severe damage to core information infrastructures of many organizations. The graph-based methods are well known as the ability for learning complex interactio...
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Book and Conference Proceedings
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Chapter and Conference Paper
Research on Network Security Situation Assessment Model Based on Double AHP
Network security situation assessment is an important part of the situational awareness research process and the most important thing. Situation assessment refers to the assessment of the current security stat...
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Chapter and Conference Paper
Research on Size System of Disposable PE Gloves Based on Hand Contour Measurement
Disposable PE gloves are in great demand in the catering industry, and although their use accuracy is not high, disposable PE gloves of inconsistent size will still cause great discomfort to consumers. Therefo...
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Chapter and Conference Paper
Detecting Depression, Anxiety and Mental Stress in One Sequential Model with Multi-task Learning
Recent studies employing mobile data to detect psychological disorders have made great progress. Mobile devices record user’s behavior data and physical signals continuously. Such data are able to detect sympt...
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Chapter and Conference Paper
Fast Locomotion of Microrobot Swarms with Ultrasonic Stimuli in Large Scale
In recent years, the acitve motion of micro-nano machines has received wide attention due to its potential applications in biomedicine, biosensing, pollution control and other fields. However, the rapid manipu...
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Chapter and Conference Paper
Reliability Evaluation of Smart DC Microgrid
Nowadays, one of the main contributors of air pollution is thermal power plant. China want to develop renewable energy to solve the problem [1]. In many areas, roof photovoltaic (PV) energy systems, wind energy s...
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Chapter and Conference Paper
Prevention of GAN-Based Privacy Inferring Attacks Towards Federated Learning
With the increasing amount of data, data privacy has drawn great concern in machine learning among the public. Federated Learning, which is a new kind of distributed learning framework, enables data providers ...
