As a sensor providing long-range perception and precise measurements, Light Detection and Ranging (LiDAR) can assist the development of smart cities in various aspects, which raises the rising interest in the topic of LiDAR Odometry (LO) research. Despite the popular application of LiDAR Odometry for the localization purpose, existing LiDAR Odometry methods are still limited by the estimation error in the elevation direction due to the low vertical resolution of LiDAR and the increasing storage cost with time. To address these issues, we propose Ground and Memory Optimized LiDAR Odometry (GMLO) for autonomous vehicles by integrating a joint scan-matching optimization between consecutive LiDAR frames. In addition, an efficient and robust ground extraction method, Polar Region Ground Plane Fitting (PR-GPF), is integrated into GMLO. Finally, we propose a novel scan-to-mapping scheme to eliminate accumulated errors with low storage cost and good efficiency in updating historical mapping data. To evaluate the performance of GMLO in various aspects, we have conducted extensive experiments based on the KITTI Odometry and Semantic-KITTI datasets, and the test results show that GMLO is effective with 1.03
Semantic communication (SC) is critical for the efficient and accurate transmission of data in complex environments, especially for unmanned surface vehicles (USVs) operating in marine settings characterized by strong interference and limited bandwidth. Traditional methods of transmitting large volumes of raw data are inefficient and susceptible to errors. Additionally, semantic communication systems, which depend on labeled datasets, have limited capacity to handle unfamiliar objects in dynamic marine environments. The long-tailed data distribution further complicates the recognition and processing of novel data types. To address these issues, this paper presents a novel approach that integrates zero-shot learning (ZSL) with SC, effectively enhancing image transmission and recognition tasks accuracy in various conditions. The proposed method employs semantic encoding and decoding to prioritize meaningful data, thereby enhancing transmission efficiency and accuracy. Additionally, we introduce semantic metrics for training and evaluating system performance, improving the ability to handle unfamiliar data types. Experimental results demonstrate that our algorithm significantly outperforms traditional methods in image transmission.
Current warranty systems for businesses with diverse products or extensive customer bases are bogged down by complexity. Traditional warranty management often faces challenges such as complexity, fraud, cost, customer dissatisfaction, and inefficiency. Businesses need to address these issues to effectively manage warranties, reduce costs, and improve customer satisfaction. For example, by implementing blockchain-based solutions, businesses can streamline warranty processes, reduce fraud, and enhance transparency. This research work presents an innovative, blockchain-powered solution to mitigate the above-stated issues. Each product is assigned an unique and secure warranty in the form of a Non-Fungible Token (NFT). This NFT tracks ownership and expiry directly on the blockchain, guaranteeing its validity and eliminating potential fraud. To ensure a user-friendly experience, account abstraction simplifies interaction with the system and reduces transaction fees. Finally, Gelato Ops automates the secure burning of expired NFTs upon reaching their designated date. This system streamlines warranty management for businesses, enhances trust through automation, and leverages the security and immutability of blockchain technology.
In ultra-high speed visible light communications (VLC) with light emitting diodes (LEDs) as the transmitter, analog pre-equalizers are often adopted to extend the modulation bandwidth. However, pre-equalizer may severely degrade the signal-to-noise-ratio (SNR) in the low frequency if we only focus on its bandwidth extending feature. And therefore, an important issue is that there exists a tradeoff between extending the system bandwidth and improving the SNR. In this paper, we first study the small signal characteristics of LEDs using the ABC parameters by taking into account of its internal quantum efficiency. And then, we propose an asymmetric bridged-T pre-equalizer considering an impedance matching network, based on which we study the bandwidth-SNR tradeoff problem via analytical derivations. We formulate a data rate maximization problem by considering the above tradeoff issue. Interestingly, different from common intuition, simulations results indicate that when the LED driving current and modulation bandwidth both reach maximal values, the achievable rate cannot reach the highest point. Specifically, using an OSRAM green LED, a maximum data rate of 1.15 Gbps can be achieved with a bias current of 378.63 mA and transmitter bandwidth of 163.31 MHz. The simulated data rate is 1.47 times higher than that of the literature using similar LED with 1/2 of the signal power attenuation. In the future, we will based on the optimized LED driving and equalization circuit to design PCB and test its impacts in real deployments.
Topological photonic crystals have emerged as an important branch of physics for their excellent ability to manipulate light. Furthermore, a large-area photonic crystal can provide an additional degree of freedom by inserting a photonic crystal structure without a band gap between topologically distinct photonic crystals. In this article, we propose a hybrid topological heterostructure with the potential to be applied in modern communication. The time-reversal symmetry is broken by applying an external magnetic field while the spatial-inversion symmetry is broken by rotating the dielectric components. Our system exhibits the characteristics of large-area one-way transmission that evenly distributes over the middle domain. The unidirectional excitation properties and inherent robustness are verified in a Z-shaped channel. The proposed heterostructure provides broad application prospects in photonic integrated networks and on-chip integrated communication systems.
