Identifying key nodes in a network is crucial for practical applications, especially when it comes to accurately detecting cut vertices, which play a vital role in maintaining network stability. As network complexity ...
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ISBN:
(数字)9798350368369
ISBN:
(纸本)9798350368376
Identifying key nodes in a network is crucial for practical applications, especially when it comes to accurately detecting cut vertices, which play a vital role in maintaining network stability. As network complexity increases, relying on a single method to identify key nodes often fails to provide a comprehensive assessment of node importance in real-world scenarios. To address this, this paper proposes a novel framework for cut vertex identification that evaluates node importance from three perspectives: weighted fusion centrality metrics, the spanning tree algorithm, and topology graph properties. Additionally, existing methods based on centrality metrics often struggle with low accuracy in identifying cut vertices. To overcome this limitation, we have devised a method, termed the MIS-CV algorithm, that enables the accurate identification of network cut vertices by solely evaluating the intersection of node neighborhoods within the maximum independent set. We validated our proposed algorithm through simulation analysis on the Barabasi-Albert scale-free network. The results demonstrate that the MIS-CV key nodes identification algorithm surpasses traditional search tree algorithms in terms of both accuracy and operational efficiency. This proves that the MIS-CV algorithm has higher recognition accuracy without increasing computational complexity.
Human Action Analysis is a procedure in tracking individual gestures, motion and actions which finds applications, including healthcare, surveillance, security and human-computer communication. With the proliferation ...
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ISBN:
(数字)9798331527549
ISBN:
(纸本)9798331527556
Human Action Analysis is a procedure in tracking individual gestures, motion and actions which finds applications, including healthcare, surveillance, security and human-computer communication. With the proliferation of sensors and deep learning techniques, HAR has marked remarkable development in the past few years. This review paper gives a brief survey of the current studies in Activity Analysis, focusing on deep learning-based approaches. The various sensors employed in HAR, including accelerometers, gyroscopes, and vision-based sensors were used in acquiring signals. The main objective is to design an appropriate model for recognizing/classifying human actions effectively to support elderly and differently abled people. The evolution of deep learning architectures used in detection such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory (LSTM) networks can be utilized for action recognition. The characterization of these algorithms is evaluated using various metric indices including precision, accuracy, recall, Fl-score, and mean average precision. The challenges and limitations of existing HAR systems, including data purity, imbalance nature of class, and positioning of sensor were also presented. This review aims to provide a clear picture in Action Recognition, highlighting the Pros and cons of different approaches. By identifying the prospects and obstacles, this review seeks to inspire future research in behaviour analysis, ultimately leading to the development of more accurate, efficient, and robust systems.
In this paper, we propose SurroundSense, a novel event-driven framework that generates contextual information based on the user's surroundings using the Impulse Radio Ultra-Wideband (IR-UWB) Radar integrated into ...
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ISBN:
(数字)9798331508050
ISBN:
(纸本)9798331508067
In this paper, we propose SurroundSense, a novel event-driven framework that generates contextual information based on the user's surroundings using the Impulse Radio Ultra-Wideband (IR-UWB) Radar integrated into smartphones. By leveraging the channel impulse response (CIR) data obtained from the IR-UWB radar, SurroundSense constructs a detailed contextual understanding of the user's environment, allowing for tailored recommendations based on the surrounding conditions. The system processes the CIR data and combines it with acoustic sensing information, specifically noise levels and ambient light information to generate the surrounding information. Further-more, utilizing the IMU sensors enables an expanded field-of-view (FOV), providing a comprehensive $360^o$ environmental awareness. This enhanced surrounding information enhances the accuracy and pertinence of personalized recommendations. Our approach showcases the potential of incorporating IR-UWB technology into personalization algorithms, ultimately improving user experiences and facilitating adaptive, context-aware applications.
Modem surveillance systems often utilize multiple physically distributed sensors of different types to provide complementary and overlapping coverage on targets, In order to generate target tracks and estimates, the s...
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Modem surveillance systems often utilize multiple physically distributed sensors of different types to provide complementary and overlapping coverage on targets, In order to generate target tracks and estimates, the sensor data need to be fused. While a centralized processing approach is theoretically optimal, there are significant advantages in distributing the fusion operations over multiple processing nodes. This paper discusses architectures for distributed fusion, whereby each node processes the data from its own set of sensors and communicates with other nodes to improve on the estimates, The information graph is introduced as a way of modeling information flow is distributed fusion systems and for developing algorithms. fusion for target tracking involves two main operations: estimation and association. Distributed estimation algorithms based on the information graph are presented for arbitrary fusionarchitectures and related to linear and nonlinear distributed estimation results. The distributed data association problem is discussed in terms of track-to-track association likelihoods. Distributed versions of two popular tracking approaches (joint probabilistic data association and multiple hypothesis tracking) are then presented, and examples of applications are given.
In this paper we describe the nature of the problem of surveillance of airport surface movement. We describe the characteristics, performance, and unique problems of various airport sensors available, and the need to ...
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ISBN:
(纸本)0819444812
In this paper we describe the nature of the problem of surveillance of airport surface movement. We describe the characteristics, performance, and unique problems of various airport sensors available, and the need to develop a fusion system to provide an integrated surveillance picture. Parallel sensorfusion developments are described in terms of their applicability to the sensorfusion task in surface surveillance. Paradigms for sensorfusion, including alternative architectures, algorithms, and performance metrics will be described. Finally we describe system implementation and quantitative performance of sensorfusion applied to the surface surveillance problem at demonstrations in Atlanta Hartsfield International Airport (1998, ATL), Dallas Fort Worth International Airport (1999, 2000, DFW), and in-process and planned future developments in sensorfusion.
作者：
Braun, JJMIT
Lincoln Lab Lexington MA 02420 USA
This paper presents an approach to multisensor data fusion based on the use of Support Vector Machines (SVM). The approach is investigated using simulated generic sensor data, representative of data imperfections that...
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ISBN:
(纸本)0819444812
This paper presents an approach to multisensor data fusion based on the use of Support Vector Machines (SVM). The approach is investigated using simulated generic sensor data, representative of data imperfections that may be encountered in multisensorfusionapplications. In particular the issue of data incompleteness is addressed and a method exploiting vicinity of training points is proposed for incompleteness correction. The paper also investigates applicability of vicinal kernels in SVM-based sensor data fusion.
The aim of this gaper is to give a homogeneous and a simple framework in order to present information fusion concepts. The main concept presented here concerns the definition of the information element concept This co...
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ISBN:
(纸本)0819440809
The aim of this gaper is to give a homogeneous and a simple framework in order to present information fusion concepts. The main concept presented here concerns the definition of the information element concept This concept is then illustrated through the general scheme of pattern recognition systems. Different types of information imperfection are then illustrated. Finally, information fusion concepts and fusionarchitectures are illustrated
The report will highlight the final results of an Advanced Technology Demonstration effort for an enhanced all source fusion (EASF) system recently developed at the fusion Technology Branch, Air Force Research Laborat...
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ISBN:
(纸本)0819436771
The report will highlight the final results of an Advanced Technology Demonstration effort for an enhanced all source fusion (EASF) system recently developed at the fusion Technology Branch, Air Force Research Laboratory/IFEA. It will describe an innovative approach of traditional fusion algorithms and heuristic reasoning techniques to significantly improve the detection, identification, location and tracking of mobile red, blue and gray components of the electronic environment.
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