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Fusion of WiFi and Visual Signals for Person Tracking 16

Fusion of WiFi and Visual Signals for Person Tracking

引用

7th Symposium on Information and Communication Technology (SoICT)

作者： Thuy Thi Thanh Pham Thi-Lan Le Trung-Kien Dao Acad People Secur Hanoi Vietnam HUST GRENOBLE INP CNRSUMI 2954 Int Res Inst MICA Hanoi Vietnam

ISBN: (纸本)9781450348157

Person tracking is crucial in any automatic person surveillance systems. In this problem, person localization and re-identification (ReID) are both simultaneously processed to show separated trajectories for each individual. In this paper, we propose to use mixture of WiFi and camera systems for person tracking in indoor surveillance regions covered by WiFi signals and disjointed camera FOVs (Field of View). A fusion method is proposed to combine the position observations achieved from each single system of WiFi or camera. The combination is done based on an optimal assignment between the position observations and predicted states from camera and WiFi systems. The correction step of Kalman filter is then applied for each tracker to give out state estimations of locations. The fusion method allows tracking by identification in non-overlapping cameras, with clear identity information taken from WiFi adapter. The experiments on a multi-model dataset show outperforming tracking results of the proposed fusion method in comparison with vision-based only method.

关键词： Camera WiFi fusion method optimal algorithm Kalman filter person tracking

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Effective Cell Size Scheme in Multi-hop Cellular Networks

Effective Cell Size Scheme in Multi-hop Cellular Networks

引用

IEEE Global Telecommunications Conference (GLOBECOM 09)

作者： Tam, Y. Hung Benkoczi, Robert Hassanein, Hossam S. Akl, Selim G. Queens Univ Sch Comp Kingston ON K7L 3N6 Canada

ISBN: (纸本)9781424441471

In 3G-based multi-hop cellular networks (MCNs), the cell size affects the cell capacity and the network reachability, which in turn affect the total demand of source nodes that can be served or the system throughput. Improper cell size assignment greatly affects the performance of the networks. To address the cell size issue, we recently proposed the optimal Cell Size (OCS) scheme to find optimal cell sizes to maximize the system throughput for a 3G TDD W-CDMA MCN. Although OCS provides an optimal cell size solution, it is computationally expensive. In this paper, we propose a heuristic cell size scheme, called Small Cell Size First (SCSF), which is more efficient and provides good results in terms of throughput compared to the optimal solutions provided by OCS. SCSF outperforms the fixed small cell size (SCS) multi-hop case when the network is sparse and the large cell size single-hop case regardless of the network density.

关键词： multi-hop cellular networks TDD CDMA cellular networks optimal algorithm heuristic cell size throughput

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Decentralized control in the discrete-time systems with interconnected delays

Decentralized control in the discrete-time systems with inte...

引用

7th World Congress on Intelligent Control and Automation

作者： Gao, Xin SW Univ Nationalities China Inst Elect & Informat Engn Chengdu 610041 Sichuan Peoples R China

ISBN: (纸本)9781424421138

This paper addresses the decentralized control problem of a class of discrete-time linear time-invariant (LTI) systems composed of two interconnected subsystems. By means of the well-known projection theorem, a sufficient stability condition of such systems is established, which is less conservative than the existing results. This condition is then extended to the case where the systems involve delays. All the conditions can be verified by a combination of linear matrix inequalities (LMI) toolbox and optimal search algorithm of Matlab. Numerical example is provided to illustrate the effectiveness and advantages of the obtained results.

关键词： Decentralized control interconnected systems delay parameter-dependent Lyapunov function optimal algorithm

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Cooperative Task offloading and Dispatching Optimization for Large-scale Users via UAVs and HAP

Cooperative Task offloading and Dispatching Optimization for...

引用

IEEE Wireless Communications and Networking Conference (WCNC)

作者： Cao, Huijuan Yu, Genghua Chen, Zhigang Cent South Univ Sch Comp Sci & Engn Changsha 410075 Peoples R China Univ Victoria Dept Comp Sci Victoria BC V8P 5C2 Canada

ISBN: (纸本)9781665491228

With the development of the 6th generation communication technology, the service traffic of mobile communication is rapidly growing. Many new types of services usually have high requirements for computing resources and low latency constraints. They need to be offloaded to a base station (BS) with computing resources for processing. In some disaster areas, the communication system will go down due to damage to the ground infrastructure. High altitude platforms (HAPs) with extensive coverage and unmanned aerial vehicles (UAVs) with simple deployment can provide various emergency services as aerial BS. UAVs and HAP carry servers and other equipment to serve users. It is a promising technology for communication and computing services. Due to UAVs' limited computing resources and energy, it is a challenge to deploy them effectively and fully use network resources. Therefore, a task-dynamic processing through multi-UAV cooperation (TDPUC) strategy is proposed. A improved Kmeans algorithm is proposed to realize the dynamic deployment, which optimizes the number of UAVs dispatched and reduces the overall energy consumption. In addition, the multi-UAV cooperation for task offloading can realize dynamic task processing under constrained energy and resources. When UAVs cooperate, the multi-agent reinforcement learning (MARL) algorithm is used to optimize resource allocation and learns online. By numerical results, the proposed TDPUC strategy can improve the service capacity of tasks by 11% on average with less energy consumption.

关键词： high altitude platform (HAP) unmanned aerial vehicles (UAVs) cooperation task offloading dynamic dispatching optimal algorithm

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DATA COMPLEXITY FOR IDENTIFYING SUITABLE algorithmS 13

DATA COMPLEXITY FOR IDENTIFYING SUITABLE ALGORITHMS

引用

IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC)

作者： Ramalingam, Prem Anand Fathima, Nikhat Supriya, P. Shetty, Prathish Sanyal, Mainak Yeshaswini, P. Rao, Mukesh Darapaneni, Narayana Paduri, Anwesh Reddy PES Univ Bangalore Karnataka India Great Learning Bangalore Karnataka India

ISBN: (纸本)9798350332865

Suitability of an algorithm to the given job depends on the distribution characteristics of the two classes in a binary-class dataset. A linear modelling algorithm will be more optimal on a linearly separable dataset i.e., the one in which the two classes can be cleanly separated by a linear boundary. Whereas, for a dataset in which the classes are not linearly separable may need a complex kernel-based algorithm to get the job done. A prior idea about the data in terms of the degree of separability of the two classes, is likely to help zoom in on algorithms more suitable than others and in the process reduce model building time, minimize wastage of computational resources. For this, we plan to use a purity metric that helps categorize a dataset into simple, medium, complex (SMC). The value of this metric will be estimated from the underlying distribution characteristics of the data on the various attributes. Simple dataset is the one in which the classes can be linearly separated without any transformations. The purity metric will be high and on the other end of the spectrum, a complex dataset will be the one in which the classes are not linearly separable even after transformations. Such datasets will have low value in purity metric. Further, with the help of boxplots and quantile values, we analyze which model performs better in each category. The paper proposes a set of guidelines to choose an optimal classical Machine Learning algorithm for binary classification.

关键词： linear separability purity computation time optimal algorithm classification

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Using Optimization algorithms to Improve The Classification Of Diseases On Rice Leaf Of EfficientNet-B4 Model 23

Using Optimization Algorithms to Improve The Classification ...

引用

8th International Conference on Intelligent Information Technology (ICIIT)

作者： Quynh, Anh Nguyen Quoc, Khang Nguyen Ngoc, Hoang Tran Quach, Luyl-Da FPT Univ Can Tho Vietnam

ISBN: (纸本)9781450399616

Rice is an important food source, so increasing rice yields is essential to disease management. Much related research has performed classification and disease detection on rice leaf using machine learning models. However, this study aims to synthesize data to evaluate rice leaf diseases through collected data and contribute new data sets. This data set uses optimization algorithms (RMSprop and Adam) combined with the EfficientNet-B4 model with learning rates of 0.01 and 0.001. The research showed that the optimal algorithm combined with the EfficientNet-B4 model gave high results of 93% (F1-Score) and an accuracy of 89%. The research results show the influence of optimal parameters on the models and find the most optimal parameter results.

关键词： EfficientNet-B4 transfer learning rice diseases rice leaf optimal algorithm

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Search for a Moving Element 17

Search for a Moving Element

引用

17th International Workshop on Algebraic and Combinatorial Coding Theory (ACCT)

作者： Lebedev, Alexey Russian Acad Sci Kharkevich Inst Informat Transmiss Problems Moscow Russia

ISBN: (纸本)9781665402873

We consider the moving element search problem with the minimum total cardinality of tests. As a search space, we consider the set of integer points of a segment of length n. We prove that the total test cardinality of an asymptotically optimal adaptive strategy is n + 2 root n. Also we give an optimal strategy for non-adaptive case with the minimal number of tests.

关键词： combinatorial search test optimal algorithm

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BMI approach to decentralized and cooperative control of large-scale system

引用

26th Chinese Control Conference

作者： Cao Li Nian Xiaohong Tang Wenyan Cent S Univ Sch Informat Sci & Engn Changsha 410075 Hunan Peoples R China

ISBN: (纸本)9787811240559

Based on the bilinear matrix inequality (BMI) technique, the problems of designing decentralized controllers and cooperative controllers of linear large-scale systems are considered. Necessary and sufficient conditions of the optimal decentralized and cooperative stabilization of the linear large-scale systems are obtained. The problems of designing decentralized and cooperative controllers are formulated into the non-convex optimization problems with BMI constraints. To solve these problems, the alternate optimized algorithms are proposed. Finally, example is given to illustrate the main results. It shows that a large-scale system can be stabilized via cooperative controllers or decentralized controllers and needs not presumer each subsystem be stable.

关键词： decentralized control cooperative control large-scale system optimal algorithm BMI

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Efficient State Estimation with Energy Harvesting and Fairness Control Using Stochastic Optimization

Efficient State Estimation with Energy Harvesting and Fairne...

引用

54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Vijayandran, Luxmiram Brandt-Pearce, Maite Kansanen, Kimmo Ekman, Torbjorn Norwegian Univ Sci & Technol Dept Elect & Telecommun Trondheim Norway Univ Virginia Dept Elect & Comp Engn Charlottesville VA 22903 USA

ISBN: (纸本)9781424492688

Wireless sensor networks (WSN) intended for critical applications often rely on energy harvesting batteries, yet also require backup batteries to ensure uninterrupted operation. An optimal algorithm for resource allocation in such WSN used for state estimation is presented. The resulting state estimate approaches a minimum accuracy constraint with efficient use of the harvesting capability to minimize the use of the backup power. Power usage is fairly distributed among the sensors to prolong system lifetime. The algorithm is based on a stochastic Lyapunov optimization used with a standard Kalman filter estimator. The framework can achieve arbitrarily close to optimal power efficiency over time without requiring knowledge of either the channel or harvesting statistics. Asymptotically optimal efficiency is obtained at the expense of an increase in latency for the system to converge to the desired estimation accuracy.

关键词： Accuracy Batteries Optimization Resource management State estimation Wireless sensor networks asymptotically optimal efficiency backup batteries backup power energy harvesting energy harvesting batteries fairness control harvesting capability minimum accuracy constraint optimal algorithm optimal power efficiency optimisation power usage resource allocation standard Kalman filter estimator state estimation state estimation stochastic Lyapunov optimization stochastic optimization stochastic processes system lifetime uninterrupted operation wireless sensor networks wireless sensor networks

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Research on the Continuous Speech Feature Extraction Method for Different Noise

Research on the Continuous Speech Feature Extraction Method ...

引用

International Conference on Advances in Materials Science and Information Technologies in Industry (AMSITI)

作者： Liu Wei Sun Yiming Liu Yanxiu Changchun Univ Sci & Technol Dept Comp Sci & Technol Changchun 130022 Peoples R China

ISBN: (纸本)9783038350125

We propose a noise-robust continuous speech recognition (CSR) method for modeling and recognition. In recognition, we divide the continuous speech vectors to segments using proposed algorithm, then use DRA based on the segments for recognition. The proposed method efficiency is studied for noisy environment. DRA decreases the difference between the model and recognition continuous speech vectors. The new algorithm focuses on adjust the vectors by using different maxima in different segments. Segment-based DRA algorithm can make noisy speech feature vectors closer to the model. The average recognition rate has been improved at different noise and SNR conditions.

关键词： Noise Robust Continuous Speech Recognition optimal algorithm

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