Selective Combining for Hybrid Cooperative Networks

In this study, we consider the selective combining in hybrid cooperative networks (SCHCNs scheme) with one source node, one destination node and $N$ relay nodes. In the SCHCN scheme, each relay first adaptively chooses between amplify-and-forward protocol and decode-and-forward protocol on a per frame basis by examining the error-detecting code result, and $N_c$ ($1\leq N_c \leq N$) relays will be selected to forward their received signals to the destination. We first develop a signal-to-noise ratio (SNR) threshold-based frame error rate (FER) approximation model. Then, the theoretical FER expressions for the SCHCN scheme are derived by utilizing the proposed SNR threshold-based FER approximation model. The analytical FER expressions are validated through simulation results.Comment: 27 pages, 8 figures, IET Communications, 201

SQLdepth: Generalizable Self-Supervised Fine-Structured Monocular Depth Estimation

Recently, self-supervised monocular depth estimation has gained popularity with numerous applications in autonomous driving and robotics. However, existing solutions primarily seek to estimate depth from immediate visual features, and struggle to recover fine-grained scene details with limited generalization. In this paper, we introduce SQLdepth, a novel approach that can effectively learn fine-grained scene structures from motion. In SQLdepth, we propose a novel Self Query Layer (SQL) to build a self-cost volume and infer depth from it, rather than inferring depth from feature maps. The self-cost volume implicitly captures the intrinsic geometry of the scene within a single frame. Each individual slice of the volume signifies the relative distances between points and objects within a latent space. Ultimately, this volume is compressed to the depth map via a novel decoding approach. Experimental results on KITTI and Cityscapes show that our method attains remarkable state-of-the-art performance (AbsRel = $0.082$ on KITTI, $0.052$ on KITTI with improved ground-truth and $0.106$ on Cityscapes), achieves $9.9\%$, $5.5\%$ and $4.5\%$ error reduction from the previous best. In addition, our approach showcases reduced training complexity, computational efficiency, improved generalization, and the ability to recover fine-grained scene details. Moreover, the self-supervised pre-trained and metric fine-tuned SQLdepth can surpass existing supervised methods by significant margins (AbsRel = $0.043$, $14\%$ error reduction). self-matching-oriented relative distance querying in SQL improves the robustness and zero-shot generalization capability of SQLdepth. Code and the pre-trained weights will be publicly available. Code is available at \href{https://github.com/hisfog/SQLdepth-Impl}{https://github.com/hisfog/SQLdepth-Impl}.Comment: 14 pages, 9 figure

Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstruction

Implicit neural representation has opened up new avenues for dynamic scene reconstruction and rendering. Nonetheless, state-of-the-art methods of dynamic neural rendering rely heavily on these implicit representations, which frequently struggle with accurately capturing the intricate details of objects in the scene. Furthermore, implicit methods struggle to achieve real-time rendering in general dynamic scenes, limiting their use in a wide range of tasks. To address the issues, we propose a deformable 3D Gaussians Splatting method that reconstructs scenes using explicit 3D Gaussians and learns Gaussians in canonical space with a deformation field to model monocular dynamic scenes. We also introduced a smoothing training mechanism with no extra overhead to mitigate the impact of inaccurate poses in real datasets on the smoothness of time interpolation tasks. Through differential gaussian rasterization, the deformable 3D Gaussians not only achieve higher rendering quality but also real-time rendering speed. Experiments show that our method outperforms existing methods significantly in terms of both rendering quality and speed, making it well-suited for tasks such as novel-view synthesis, time synthesis, and real-time rendering

weathering fur simulation

ACM SIGGRAPH; ACM SIGCHIThe paper presents a novel approach for simulating the weathering fur. Dusty effects on fur is generated by volumetric γ-ton tracing method and the geometry deformation is modeled through a dynamic PBS. The proposed approach can efficiently simulate the weathering effects of fur. Copyright © 2009 by the Association for Computing Machinery, Inc

time-varying simulation for image-based carpets

China Soc Image & Graph, Xian Univ Technol, NW Univ, Shaanxi Prov Key Lab Speech & Image Informat Proc, Natl Nat Sci Fdn China, TOYOU FEIJI Elect Co, CPS, IEEE Comp SocThe paper presents a novel approach for simulating realistic time-varied carpets. By the approach, a 3D carpet is constructed first by image-based techniques from a single photo input, through a texel structure, established to generate realistic carpet with its pattern guided by the captured image. Secondly, a time-varying simulation model is proposed to capture various aspects of the time-dependent appearance of carpets such as dust accumulation, color fading and fiber change. Additionally, a time-varying map is provided to control the specific weathering degrees at different voxels in time through a hierarchal model. Experimental results show that the realistic time-varying simulation is successfully achieved with the proposed techniques

Evolutionary channel state information feedback control for interference alignment

Interference alignment (IA) has been well recognized as a promising technique to obtain a large multiplexing gain in multiple input multiple output (MIMO) interference channels. However, most of the existing IA schemes require global channel state information (CSI) at the transmitter to design precoding vectors, which causes a large amount of feedback bits. To reduce the feedback overhead, in this paper, we model the evolution and dynamic behavior of the CSI feedback rate control problem using the evolutionary game theory over orthogonal feedback channels with a total bandwidth constraint. The game utility is defined as the performance gain by CSI feedback minus the price as a linear function of the CSI feedback rate, subject to an overall bandwidth constraint. Then, an algorithm for the implementation of the evolution process is also presented. The proposed game-theoretic framework for modeling the interactions among the feedback of multiple users can be used to efficiently control the CSI feedback amount while achieving fairness among all the mobile receivers. ? 2011 IEEE.EI

Improved depressive symptoms in patients with refractory Gilles de la Tourette syndrome after deep brain stimulation of posteroventral globus pallidus interna

Abstract Objective Deep brain stimulation (DBS) has been used on drug‐resistant Gilles de la Tourette syndrome (GTS) for more than two decades until now, but the stimulating targets are still under exploration until now. In this study, the authors reported the efficacy of the bilateral posteroventral globus pallidus interna (GPi) DBS on tic severity and neuropsychiatry symptoms of seven individuals with GTS. Method Seven patients with drug‐resistant GTS were enrolled in this study. The severity of these patients was evaluated with Yale Global Tics Severity Scale (YGTSS), Yale Brown Obsessive Compulsive Scale (YBOCS), Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Rating Scale (HAMA), and Global Assessment of Functioning Scale (GAF). Bilateral posteroventral GPi were selected as the permanent stimulating targets. Follow‐up period was at least 5 years after surgery in the enrolled patients. Results After surgery, one patient reported no improvement during the follow‐up period, and a device removal surgery was performed. The other six patients reported minor to significant improvement. The overall YGTSS, YBOCS, HAMA HAMD, and GAF scores of these patients were changed positively after surgery, but only the improvement of the motor tic and HAMD scores had a statistical difference. No surgical complication was reported. Conclusions Bilateral posteroventral GPi DBS could relieve the motor tics and depressive symptoms of the enrolled patients significantly, but the vocal tics and other psychiatric symptoms presented a progression without statistical difference during the follow‐up period. The results of this study suggested that bilateral posteroventral GPi are effective targets for the motor tics in GTS patients, especially with prominent depressive symptoms

gpu accelerated fast fem deformation simulation

In this paper we present a general FEM (Finite Element Method) solution that enables fast dynamic deformation simulation on the newly available GPU (Graphics Processing Unit) hardware with compute unified device architecture (CUDA) from NVIDIA. CUDA-enab