The traditional RSS-based fingerprint localization algorithm needs RSS values from all access points (AP) at each reference point (RP). In the large-scale indoor environment, the increasing of the number of APs will l...
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The traditional RSS-based fingerprint localization algorithm needs RSS values from all access points (AP) at each reference point (RP). In the large-scale indoor environment, the increasing of the number of APs will lead to establish a large-scale fingerprint database, which occupies a lot of storage space. In this paper, we propose a new reliable localization algorithm, which firstly utilizes quantized RSS to encode the monitoring region which has been divided into grids, so as to specify the grids that the interested target appears roughly. Then, we utilize Multi-Layer Perceptron (MLP) to train the grid regions in which the beacons deployment is non-isomorphic and obtain the accurate localization result. Due to the same deployment of isomorphic regions, it is imperative to train only one model to replace the others, which greatly reduces the computation of neural network. It can be concluded from the experimental results that compared with the traditional MLP-based fingerprint localization algorithm, the proposed algorithm reduces the size of fingerprint database over 80% with guarantee of localization accuracy. Moreover, our algorithm can obtain better localization accuracy compared with the other latest quantization based localization algorithm.
This research addresses the limitations of traditional visual and verbal navigation (VLN) tasks by introducing an innovative RFID-based, brain-inspired route correction scheme. This system integrates visual, voice, RF...
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ISBN:
(纸本)9789819607884;9789819607891
This research addresses the limitations of traditional visual and verbal navigation (VLN) tasks by introducing an innovative RFID-based, brain-inspired route correction scheme. This system integrates visual, voice, RFID, and odometer sensors to tackle real-world navigation challenges such as lighting changes and hardware errors. By combining the brain's grid coding and spatial perception mechanisms with RFID technology, we achieve precise location tracking. Additionally, a PID controller simulates the brain's perception of spatial edges, providing real-time deviation correction for the agent. Moreover, a reinforcement learning-based path planning method, enhanced with domain randomization, ensures continuous navigation. This approach, validated through VLN simulations, significantly improves navigation accuracy and success rates without incurring high learning costs, marking substantial progress in robot navigation technology.
Teaching has become a complex essential tool for students' abilities, due to their different levels of learning and understanding. In the traditional offline teaching methods, dance teachers lack a target for stud...
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Teaching has become a complex essential tool for students' abilities, due to their different levels of learning and understanding. In the traditional offline teaching methods, dance teachers lack a target for students 'classroom teaching. Furthermore, teachers have limited time, so they cannot take full care of each student's learning needs according to their understanding and learning ability, which leads to the polarization of the learning effect. Because of this, this paper proposes an online teaching method based on Artificial Intelligence and edge calculation. In the first phase, standard teaching and student-recorded dance learning videos are conducted through the key frames extraction through a deep convolutional neural network. In the second phase, the extracted key frame images were then extracted for human key points using grid coding, and the fully convolutional neural network was used to predict the human posture. The guidance vector is used to correct the dance movements to achieve the purpose of online learning. The CNN model is distributed into two parts so that the training occurs at the cloud and prediction happens at the edge server. Moreover, the questionnaire was used to obtain the students' learning status, understand their difficulties in dance learning, and record the corresponding dance teaching videos to make up for their weak links. Finally, the edge-cloud computing platform is used to help the training model learn quickly form vast amount of collected data. Our experiments show that the cloud-edge platform helps to support new teaching forms, enhance the platform's overall application performance and intelligence level, and improve the online learning experience. The application of this paper can help dance students to achieve efficient learning.
We disclose the use of the Barker sequences for generating, with phase-only masks, highly selective windows in the optical transfer functions (OTF). The proposed passband procedure is extended to 2-D, by defining a Ba...
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We disclose the use of the Barker sequences for generating, with phase-only masks, highly selective windows in the optical transfer functions (OTF). The proposed passband procedure is extended to 2-D, by defining a Barker matrix as the direct product of Barker sequence. We explore the use of several configurations, and we recognize as a good choice the use of a pair of adjacent, non-overlapping, Barker masks. Our proposal is applied for identifying envelopes in carrier frequency photographs.
grid cells are one of the core building blocks of spatial navigation [1]. Single-cell recordings of grid cells in the rodent entorhinal cortex revealed hexagonal coding of the local environment during spatial navigati...
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grid cells are one of the core building blocks of spatial navigation [1]. Single-cell recordings of grid cells in the rodent entorhinal cortex revealed hexagonal coding of the local environment during spatial navigation [1]. grid-like activity has also been identified in human single-cell recordings during virtual navigation [2]. Human fMRI studies further provide evidence that grid-like signals are also accessible on a macroscopic level [3-7]. Studies in both non-human primates [8] and humans [9, 10] suggest that grid-like coding in the entorhinal cortex generalizes beyond spatial navigation during locomotion, providing evidence for grid-like mapping of visual space during visual exploration-akin to the grid cell positional code in rodents during spatial navigation. However, electrophysiological correlates of the grid code in humans remain unknown. Here, we provide evidence for grid-like, hexadirectional coding of visual space by human high-frequency activity, based on two independent datasets: non-invasive magnetoencephalography (MEG) in healthy subjects and entorhinal intracranial electroencephalography (EEG) recordings in an epileptic patient. Both datasets consistently show a hexadirectional modulation of broadband high-frequency activity (60-120 Hz). Our findings provide first evidence for a grid-like MEG signal, indicating that the human entorhinal cortex codes visual space in a grid-like manner [8-10], and support the view that grid coding generalizes beyond environmental mapping during locomotion [4-6, 11]. Due to their millisecond accuracy, MEG recordings allow linking of grid-like activity to epochs during relevant behavior, thereby opening up the possibility for new MEG-based investigations of grid coding at high temporal resolution.
The global spatial grid is an important spatial data model for Digital Earth. Discrete Global grid provides a means of rasterizing the earth surface, and then has been considered as the basic data model for digital gl...
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ISBN:
(纸本)9781629935201
The global spatial grid is an important spatial data model for Digital Earth. Discrete Global grid provides a means of rasterizing the earth surface, and then has been considered as the basic data model for digital globes. But Discrete Global grid is only confined to the surface, because it can not reach to the earth inside and outside. The Sphere Shell Space 3D grid (SSSG) proposed here provides a new spatial reference framework for the whole earth 3D space for Digital Earth. The basic conceptions and requirements of SSSG have been discussed in details. It is designed to represent spatial objects distributed from underground, land, sea, air to space within a uniform framework, and also to uniformly organize various kinds of spatial information in each earth sphere shells.
Discrete Global grid has been widely used as the basic data model of digital earth. But it is only confined to the earth surface, and it can not reach to the earth inside or outside. The extended-Octree (e-Octree) sph...
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ISBN:
(纸本)9781629935201
Discrete Global grid has been widely used as the basic data model of digital earth. But it is only confined to the earth surface, and it can not reach to the earth inside or outside. The extended-Octree (e-Octree) spheroid subdivision and coding model proposed here provides a new kind of global 3D grid. This e-Octree model is based on the extension of octree structure, and there are three kinds of extended mechanisms including regular octree, degraded octree and adaptive octree. The process of partition and coding is discussed in details. The prototype system of e-Octree model is implemented, in which e-Octree model has been used to visualize global terrain and space object orbits. These typical applications experiments show that the e-Octree model could not only be used in global change research and earth system science, but also be used for dynamic simulation and spatial index.
Map projections had brought a lot of problems to regional and global spatial data organization and representation, such as distortion, geometric fissure and space metric error Fortunately, Discrete Global grid (DGG) g...
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ISBN:
(纸本)9781424433940
Map projections had brought a lot of problems to regional and global spatial data organization and representation, such as distortion, geometric fissure and space metric error Fortunately, Discrete Global grid (DGG) gave a feasible solution, but it was only confined to the Earth surface, not reached to the Earth inside and outside, which was also very Important to human activity In this paper, a global three-dimensional (3D) grid, called as Spheoid Degenerated Octree grid (SDOG), was presented, and two kinds of coding methods for SDOG, called as SDZ and MDZ, were proposed The properties of SDOG were discussed and the performance of SDZ and MDZ was compared with QuaPA experimentally It revealed that SDOG is a 3D grid with properties of global continuity, multi-hierarchy, similar shape and approximate size, and can serve well for global spatial data organizing and representing, SDZ and MDZ are high performance coding methods, and MDZ is a nicer choice for SDOG coding
In this correspondence, algorithms are introduced to infer surface orientation and structure of visible object surfaces using grid coding. We adopt the active lighting technique to spatially ``encode"" the s...
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In this correspondence, algorithms are introduced to infer surface orientation and structure of visible object surfaces using grid coding. We adopt the active lighting technique to spatially ``encode"" the scene for analysis. The observed objects, which can have surfaces of arbitrary shape, are assumed to rest on a plane (base plane) in a scene which is ``encoded"" with light cast through a grid plane. Two orthogonal grid patterns are used, where each pattern is obtained with a set of equally spaced stripes marked on a glass pane. The scene is observed through a camera and the object surface orientation is determined using the projected patterns on the object surface. If the surfaces under consideration obey certain smoothness constraints, a dense orientation map can be obtained through proper interpolation. The surface structure can then be recovered given this dense orientation map. Both planar and curved surfaces can be handled in a uniform manner. The algorithms we propose yield reasonably accurate results and are relatively tolerant to noise, especially when compared to shape-from-shading techniques. In contrast to other grid coding techniques reported which match the grid junctions for depth reconstruction under the stereopsis principle, our techniques use the direction of the projected stripes to infer local surface orientation and do not require any correspondence relationship between either the grid lines or the grid junctions to be specified. The algorithm has the ability to register images and can therefore be embedded in a system which integrates knowledge from multiple views.
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