The technological advancements in the field of agriculture have increased to a great extent in recent years, and many techniques have evolved from other techniques. Some methods are improved or upgraded from the previ...
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Video summarization aims to generate a compact summary of the original video for efficient video browsing. To provide video summaries which are consistent with the human perception and contain important content, super...
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In this article, we address the problem of designing a scalable control architecture for a safe coordinated operation of a multi-agent system with aerial (UAVs) and ground robots (UGVs) in a confined task space. The p...
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As the routine operations are starting to become highly automated, it is crucial to develop autonomous solutions that are infrastructure independent. Achieving this is challenging due to the ever-changing landscape of...
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ISBN:
(数字)9788993215380
ISBN:
(纸本)9798331517939
As the routine operations are starting to become highly automated, it is crucial to develop autonomous solutions that are infrastructure independent. Achieving this is challenging due to the ever-changing landscape of mines, which complicates infrastructure development. In response, this paper introduces a robust framework employing drones to gather data from hard-to-access areas in mines and deliver the data back to the base station for routine monitoring purposes. These tasks include gathering data from operational vehicles (mine trucks, loaders etc.), as well as various sensors (e.g. monitoring rock bolts) and relaying the data to the mine’s base station for monitoring purposes. The proposed framework is based on autonomous navigation using a known point cloud map of the mine, proximity detection via Ultra WideBand (UWB) radios and the data transfer is accomplished through the IEEE 802.15.4 communication standard, operating in the 868 MHz ISM band, with the aim to guarantee long range operation. On the mission level, the drones act as data mules capable of autonomously extracting data from operating vehicles, storing the data onboard and eventually delivering the data to the base station, which is enabled through a Point and Click (PAC) autonomy framework based on global planning, reactive navigation, communication link and behavior management. The efficacy of this framework has been demonstrated through real-world experiments conducted at a test mine in Sweden, validating the overall architecture of the proposed solution.
Reconstructing three-dimensional (3D) scenes with semantic understanding is vital in many robotic applications. Robots need to identify which objects, along with their positions and shapes, to manipulate them precisel...
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ISBN:
(数字)9798350377705
ISBN:
(纸本)9798350377712
Reconstructing three-dimensional (3D) scenes with semantic understanding is vital in many robotic applications. Robots need to identify which objects, along with their positions and shapes, to manipulate them precisely with given tasks. Mobile robots, especially, usually use lightweight networks to segment objects on RGB images and then localize them via depth maps; however, they often encounter out-of-distribution scenarios where masks over-cover the objects. In this paper, we address the problem of panoptic segmentation quality in 3D scene reconstruction by refining segmentation errors using non-parametric statistical methods. To enhance mask precision, we map the predicted masks into a depth frame to estimate their distribution via kernel densities. The outliers in depth perception are then rejected without the need for additional parameters in an adaptive manner to out-of-distribution scenarios, followed by 3D reconstruction using projective signed distance functions (SDFs). We validate our method on a synthetic dataset, which shows improvements in both quantitative and qualitative results for panoptic mapping. Through real-world testing, the results furthermore show our method’s capability to be deployed on a real-robot system. Our source code is available at: https://***/mkhangg/refined_panoptic_mapping.
This mini review provides a thorough examination of recent advances in finite element analysis (FEA) for cancer therapy, with a focus on magnetic nanoparticle (MNP) hyperthermia. The paper begins by discussing the fun...
This mini review provides a thorough examination of recent advances in finite element analysis (FEA) for cancer therapy, with a focus on magnetic nanoparticle (MNP) hyperthermia. The paper begins by discussing the fundamental principles of FEA and their applications in biomedical sciences. It then describes the application of FEA to the in vitro and in vivo modeling of MNP hyperthermia, including the development and validation of computational models that simulate magnetic nanoparticles behavior under alternating magnetic field (AMF), heat generation, its transfer, and cellular/tissue responses. The review further explores the emerging trends and future directions in the application of FEA for MNP hyperthermia, including the integration of experimental data, incorporation of patient-specific parameters, and optimization of treatment protocols. The paper also discusses the key challenges and limitations of current FEA models, shedding light on potential areas for future research and development. By synthesizing the most recent advances in this field, the review aims to provide a valuable resource for researchers, clinicians, and engineers working on the optimization and clinical translation of MNP hyperthermia for effective cancer therapy.
In recent years, object detection approaches using deep convolutional neural networks (CNNs) have derived major advances in normal images. However, such success is hardly achieved with rainy images due to lack of visi...
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In recent years, several industries have increased their demand for processing precision, automatic detection, and visualization interfaces. Therefore, to keep pace with the fourth industrial revolution, machine tool ...
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In recent years, several industries have increased their demand for processing precision, automatic detection, and visualization interfaces. Therefore, to keep pace with the fourth industrial revolution, machine tool operators install a large number of sensors on machine tools to obtain more precise physical quantities during processing and use a variety of sensors to obtain measurements in various situations. However, these additional sensors on machine tools result in complicated wire layouts, which exhibit negative effects on processing. Such problems lead to the birth of wireless data transmission, which is expected to become the new standard in the future. At present, there is more and more interactive integration between relevant embedded system and the machine tool, which allows information communication between each other in the wireless domain. However, generally, the majority of machine tool operators focus on optimizing the sensing conditions during processing, but they disregard the importance of information security. In the current era of the Internet of Things (IoT), information security is regarded as a crucial factor. For the wireless communication between the IoT equipment for each machine in the machining field, the transmitted data are almost exposed within public space directly due to the loss in constraint and protection of physical wiring. Therefore, such a process can easily be intercepted by other devices that capture information on relevant status of the machine or command messages received by the controller, where intentional individual may possibly control the operating mechanism and progress of entire plant. This leads to theft of relevant secrets in manufacturing technology for the subject company, or intentional shutdown, machine damage, and vicious blackmailing attacks. Therefore, introducing the mechanism of safety protection during wireless signal transmission is an inevitable technology to maintain the company interests and also the
In this work, we demonstrated upconversion imagers integrated with shortwave infrared photodetectors paired with an electron blocking layer. The use of electron blocking layer screened charge injection to prevent reco...
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This paper presents the use of natural language processing for the problem of information extraction and sentiment analysis. The dataset is from Twitter that has the information of people mentioning about COVID-19, th...
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