Integrated sensing and communication (ISAC) is a promising solution to mitigate the increasing congestion of the wireless spectrum. In this paper, we investigate the short packet communication regime within an ISAC sy...
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Purpose: Accurate depth estimation in surgical videos is a pivotal component of numerous image-guided surgery procedures. However, creating ground truth depth maps for surgical videos is often infeasible due to challe...
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Purpose: Accurate depth estimation in surgical videos is a pivotal component of numerous image-guided surgery procedures. However, creating ground truth depth maps for surgical videos is often infeasible due to challenges such as inconsistent illumination and sensor noise. As a result, self-supervised depth and ego-motion estimation frameworks are gaining traction, eliminating the need for manually annotated depth maps. Despite the progress, current self-supervised methods still rely on known camera intrinsic parameters, which are frequently unavailable or unrecorded in surgical environments. We address this gap by introducing a self-supervised system capable of jointly predicting depth maps, camera poses, and intrinsic parameters, providing a comprehensive solution for depth estimation under such constraints. Approach: We developed a self-supervised depth and ego-motion estimation framework, incorporating a cost volume based auxiliary supervision module. This module provides additional supervision for predicting camera intrinsic parameters, allowing for robust estimation even without predefined intrinsics. The system was rigorously evaluated on a public dataset to assess its effectiveness in simultaneously predicting depth, camera pose, and intrinsic parameters. Results: The experimental results demonstrated that the proposed method significantly improved the accuracy of ego-motion and depth prediction, even when compared with methods incorporating known camera intrinsics. In addition, by integrating our cost volume based supervision, the accuracy of camera parameter estimation, including intrinsic parameters, was further enhanced. Conclusions: We present a self-supervised system for depth, ego-motion, and intrinsic parameter estimation, effectively overcoming the limitations imposed by unknown or missing camera intrinsics. The experimental results confirm that the proposed method outperforms the baseline techniques, offering a robust solution for depth estimation
This article presents a novel method for point target detection in remote sensing imagery, focusing on the development of an innovative approach to enhance detection accuracy and reduce false positives. The core contr...
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This study investigates the transition control problem for a double inverted pendulum system, which has one stable and three unstable equilibrium points. We propose a method for implementing transition control using a...
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This paper presents a data-driven variable reduction approach to accelerate the computation of large-scale transmission-constrained unit commitment(TCUC).Lagrangian relaxation(LR)and mixed-integer linear programming(M...
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This paper presents a data-driven variable reduction approach to accelerate the computation of large-scale transmission-constrained unit commitment(TCUC).Lagrangian relaxation(LR)and mixed-integer linear programming(MILP)are popular approaches to solving ***,with many binary unit commitment variables,LR suffers from slow convergence and MILP presents heavy computation *** proposed data-driven variable reduction approach consists of offline and online calculations to accelerate computational performance of the MILP-based large-scale TCUC problems.A database including multiple nodal net load intervals and the corresponding TCUC solutions is first built offline via the data-driven and all-scenario-feasible(ASF)approaches,which is then leveraged to efficiently solve new TCUC instances ***/off statuses of considerable units can be fixed in the online calculation according to the database,which would reduce the computation burden while guaranteeing good solution quality for new TCUC instances.A feasibility proposition is proposed to promptly check the feasibility of the new TCUC instances with fixed binary variables,which can be used to dynamically tune parameters of binary variable fixing strategies and guarantee the existence of feasible UC solutions even when system structure *** tests illustrate the efficiency of the proposed approach.
This paper presents the development of improved synergetic current control for the injected current of an inverter in the grid-connected microgrid and the distributed generation system(DGS). This paper introduces new ...
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This paper presents the development of improved synergetic current control for the injected current of an inverter in the grid-connected microgrid and the distributed generation system(DGS). This paper introduces new formulas of the macro-variable functions for integral synergetic control(SC)and integral fast terminal SC, which both have an integral term to guarantee zero steady-state error. The proposed integral SC and integral fast terminal SC achieve a seamless performance such as the fast convergence, minimal overshoot, zero steady-state error, and chattering-free operation. To demonstrate the meritorious performance of the proposed scheme for injected current control, it is compared with the performance of a proportional-integral(PI) controller and advanced exponential sliding mode control(SMC). Finally, the practicality of the proposed scheme is justified by experimental results obtained through rapid control prototyping(RCP) using the dSPACESCALEXIO platform.
In recent years, reinforcement learning (RL)-based controller design methods have emerged as a powerful alternatives to traditional methods, providing a novel paradigm that overcomes limitations associated with the ne...
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Privacy-preserving k-nearest neighbor (PPkNN) classification for multiple clouds enables categorizing queried data into a class in keeping with data privacy, where the database and key servers jointly perform cryptogr...
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In this paper, a new block diagonal chaotic model (BDC) is investigated due to higher necessity of advanced secure data transmission method in wireless medium and considerable limitation on computational storage space...
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Modern automobiles are equipped with connectivity features to enhance the user's *** is one such communication technology that is used to pair a personal device with an automotive infotainment *** pairing,the user...
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Modern automobiles are equipped with connectivity features to enhance the user's *** is one such communication technology that is used to pair a personal device with an automotive infotainment *** pairing,the user could access the personal information on the phone through the automotive head unit with minimum distraction while ***,such connectivity introduces a possibility for privacy ***,performing an in-depth analysis of the system with privacy constraints is extremely important to prevent unauthorized access to personal *** this work,we perform a systematic analysis of the Bluetooth network of an automotive infotainment unit to exploit security and privacy-related *** model the identifed threat with respect to privacy constraints of the system,emphasize the severity of attacks through a standardized rating metric and then provide potential countermeasures to prevent the *** perform System Theoretic Process Analysis for Privacy as a part of the systematic analysis and use the Common Vulnerability Scoring System to derive attack *** identifed vulnerabilities are due to design flaws and assumptions on Bluetooth protocol implementation on automotive infotainment *** then elicit the vulnerability by performing a privacy attack on the Automotive system in an actual *** use Android Open-Source Project to report our findings and propose defense strategies.
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