This research presents a novel electromagnetic-based sensor for inline measurement of unmilled rice paddy moisture content in the rice mill factory. The proposed sensor has been designed based on the modified planar d...
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Trajectory representation learning (TRL) is an intermediate step in handling trajectory data to realize various downstream machine-learning tasks. While most previous TRL research focuses on modeling structured moveme...
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The continually evolving image segmentation methods in computer vision can further broaden the cognitive abilities of the robot. As humans, we won't judge if the object is moving by accuracy speed estimation but t...
The continually evolving image segmentation methods in computer vision can further broaden the cognitive abilities of the robot. As humans, we won't judge if the object is moving by accuracy speed estimation but through semantic information based on visual input. With the existing video segmentation method, the robot can pay more attention to the foreground objects, which are more important for path planning and navigation in most cases. The proposed methods try to deploy the first-person view segmentation method with an RGBD sensor and get the location information and locally egocentric map. The error of the segmentation methods will cause unexpected objects in the egocentric map, and the self-occlusion will influence the location and distance estimation. To further improve the methods, a spatial anticipate unit is embedded into the framework. We improve 5.6% the localization accuracy(RMSE), 12.9% the distance estimation(MAE) with the trained object, and 28.9% the recall for the trained object. The methods also show the margin on the untrained object dataset for similar objects.
The ability of a robot to perceive and understand its environment is crucial for its actions and behavior. Humans are adept at using semantic information for object localization and path planning, a skill that robots ...
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ISBN:
(数字)9798350384574
ISBN:
(纸本)9798350384581
The ability of a robot to perceive and understand its environment is crucial for its actions and behavior. Humans are adept at using semantic information for object localization and path planning, a skill that robots need to emulate for intelligent adaptation in dynamic settings. Training of the spatial anticipation ability, which can enhance spatial perception through semantic understanding, necessitates the availability of appropriate data. Although extensive research has been conducted on datasets for outdoor environments, especially in the context of autonomous driving, there is still a notable lack of datasets specifically designed for indoor environments, with a focus on dynamic object localization. This paper introduces HabitatDyn 2.0, a dataset specifically designed for enhancing object localization capabilities with semantic information from a robot’s perspective. Besides RGB videos, semantic annotations, and depth information, HabitatDyn 2.0 also features top-down view labels for dynamic objects, which is required for training the spatial anticipation ability based on semantic information. Additionally, an algorithm that leverages spatial anticipation for dynamic object localization is presented, trained, and evaluated on the dataset.
Cloud computing reflects effective delivery of computing services such as software, storage purposes, analytics, intelligence and many others. Besides that, it also offers faster innovation and at the same time flexib...
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Spike detection plays a central role in neural data processing and brain-machine interfaces (BMIs). A challenge for future-generation implantable BMIs is to build a spike detector that features both low hardware cost ...
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Globally, biomass usage as a supply of non-depletable resources materials used in the production of energy at their rawest state is an issue. Pyrolysis is a method of thermally treating biomass that as a consequence i...
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Herein,a two-node beam element enriched based on the Lagrange and Hermite interpolation function is proposed to solve the governing equation of a functionally graded porous(FGP)curved nanobeam on an elastic foundation...
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Herein,a two-node beam element enriched based on the Lagrange and Hermite interpolation function is proposed to solve the governing equation of a functionally graded porous(FGP)curved nanobeam on an elastic foundation in a hygro–thermo–magnetic *** material properties of curved nanobeams change continuously along the thickness via a power-law distribution,and the porosity distributions are described by an uneven porosity *** effects of magnetic fields,temperature,and moisture on the curved nanobeam are assumed to result in axial loads and not affect the mechanical properties of the *** equilibrium equations of the curved nanobeam are derived using Hamilton’s principle based on various beam theories,including the classical theory,first-order shear deformation theory,and higher-order shear deformation theory,and the nonlocal elasticity *** accuracy of the proposed method is verified by comparing the results obtained with those of previous reliable ***,the effects of different parameters on the free vibration behavior of the FGP curved nanobeams are investigated comprehensively.
Classical tasks of a librarian, such as screening and categorizing new documents based on their content, are increasingly replaced by search engines or through the use of cataloging software. A first overview of a cor...
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ISBN:
(纸本)9781450397629
Classical tasks of a librarian, such as screening and categorizing new documents based on their content, are increasingly replaced by search engines or through the use of cataloging software. A first overview of a corpus topical orientation can be achieved by combining graph-based search engines and clustering methods. Existing classical clustering methods, however, often require an a priori specification of the desired number of clusters to be output and do not consider term relationships in graphs, which is deficient from a practical point of view. Therefore, fully unsupervised graph-based clustering approaches at the term level offer new possibilities that mitigate these shortcomings. Within this work, a set of novel graph-based clustering algorithms have been developed. The hierarchical clustering algorithm (HCA) forms term hierarchies by iteratively isolating nodes of a given co-occurrence graph based on the evaluation of the edge weight between the nodes. Based on the co-occurrence graph inherent relationships of terms, a new graph is built agglomerative forming individual term clusters of related terms. The feasibility of the outlined methods for text analysis is shown.
The Mars Helicopter Scout left a milestone in the history of the mankind by successfully completing the first flight on Mars. This achievement opens up to the possibility of having many unmanned aerial vehicles (UAVs)...
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ISBN:
(数字)9781665437608
ISBN:
(纸本)9781665437608
The Mars Helicopter Scout left a milestone in the history of the mankind by successfully completing the first flight on Mars. This achievement opens up to the possibility of having many unmanned aerial vehicles (UAVs) acquiring data from the Martian surface along with firmly anchored machines on ground, such as moving rovers or static landers. Moreover, it is no surprise that space agencies are also paving the way for the first human landing on the Red planet. In this context, it becomes needed to support future missions by providing connectivity to the whole Martian surface in order to allow in-situ wide band data exchange between nodes-user equipments (UEs)-composing the overall network. However, it seems tough to move common mobile terrestrial infrastructures on Mars and install them on-ground or implement them on limited-resource machines, as well as to guarantee everywhere and anytime on-demand connectivity. Thus, this paper will investigate the alternative solution of developing an autonomous Martian space ecosystem, through which globally inter-connect the UEs. UAVs and, eventually, high altitude pseudo satellites (HAPS), will act as radio unit (RU) and, partially, as distributed unit (DU) of a cloud radio access network (CRAN), while small satellites platforms, such as CubeSats (CS), placed in orbit will embark the majority of the computational load by performing the remaining DU and centralized unit (CU) functions. The proposed 3D network configuration, which looks towards a 'Beyond 5G' infrastructure, or even 6G, will start by supposing very low Mars orbit (VLMO) in which CubeSats will be deployed. The design will then proceed through the installation process of CRAN on drones and CubeSats, while respecting strict latency and bandwidth requirements imposed by the Common Public Radio Interface standard (CPRI) at the fronthaul (FH) to allow low PHY-layer splitting options. A link-budget evaluation will then be proposed for the drone-to-Cubesat link. End-to-E
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