A biomimetic orthogonal flow sensor based on an asymmetric optical fiber sensory structure for marine sensing.

With increasing attention on the world's oceans, a significant amount of research has been focused on the sensing of marine-related parameters in recent years. In this paper, a bioinspired flow sensor with corrosion resistance, anti-interference capability, a portable design structure, easy integration, and directional sensing ability is presented to realize flow speed sensing in open water. The sensor is realized by a flexible artificial cupula that seals one side of an optical fiber acting as an artificial kinocilium.

Fractal-Based Hybrid Cryptosystem: Enhancing Image Encryption with RSA, Homomorphic Encryption, and Chaotic Maps.

Protecting digital data, especially digital images, from unauthorized access and malicious activities is crucial in today's digital era. This paper introduces a novel approach to enhance image encryption by combining the strengths of the RSA algorithm, homomorphic encryption, and chaotic maps, specifically the sine and logistic map, alongside the self-similar properties of the fractal Sierpinski triangle. The proposed fractal-based hybrid cryptosystem leverages Paillier encryption for maintaining security and privacy, while the chaotic maps introduce randomness, periodicity, and robustness.

An Intelligent System to Sense Textual Cues for Location Assistance in Autonomous Vehicles.

The current technological world is growing rapidly and each aspect of life is being transformed toward automation for human comfort and reliability. With autonomous vehicle technology, the communication gap between the driver and the traditional vehicle is being reduced through multiple technologies and methods. In this regard, state-of-the-art methods have proposed several approaches for advanced driver assistance systems (ADAS) to meet the requirement of a level-5 autonomous vehicle.

Graph-Collaborated Auto-Encoder Hashing for Multiview Binary Clustering.

Unsupervised hashing methods have attracted widespread attention with the explosive growth of large-scale data, which can greatly reduce storage and computation by learning compact binary codes. Existing unsupervised hashing methods attempt to exploit the valuable information from samples, which fails to take the local geometric structure of unlabeled samples into consideration. Moreover, hashing based on auto-encoders aims to minimize the reconstruction loss between the input data and binary codes, which ignores the potential consistency and complementarity of multiple sources data.

Deep-Learning-Assisted Underwater 3D Tactile Tensegrity.

The growth of underwater robotic applications in ocean exploration and research has created an urgent need for effective tactile sensing. Here, we propose an underwater 3-dimensional tactile tensegrity (U3DTT) based on soft self-powered triboelectric nanogenerators and deep-learning-assisted data analytics. This device can measure and distinguish the magnitude, location, and orientation of perturbations in real time from both flow field and interaction with obstacles and provide collision protection for underwater vehicles operation.

Underwater wireless communication via TENG-generated Maxwell's displacement current.

Underwater communication is a critical and challenging issue, on account of the complex underwater environment. This study introduces an underwater wireless communication approach via Maxwell's displacement current generated by a triboelectric nanogenerator. Underwater electric field can be generated through a wire connected to a triboelectric nanogenerator, while current signal can be inducted in an underwater receiver certain distance away.

Driver's Head Pose and Gaze Zone Estimation Based on Multi-Zone Templates Registration and Multi-Frame Point Cloud Fusion.

Head pose and eye gaze are vital clues for analysing a driver's visual attention. Previous approaches achieve promising results from point clouds in constrained conditions. However, these approaches face challenges in the complex naturalistic driving scene.

Dual-Cameras-Based Driver's Eye Gaze Tracking System with Non-Linear Gaze Point Refinement.

The human eye gaze plays a vital role in monitoring people's attention, and various efforts have been made to improve in-vehicle driver gaze tracking systems. Most of them build the specific gaze estimation model by pre-annotated data training in an offline way. These systems usually tend to have poor generalization performance during the online gaze prediction, which is caused by the estimation bias between the training domain and the deployment domain, making the predicted gaze points shift from their correct location.

Continuous Driver's Gaze Zone Estimation Using RGB-D Camera.

The driver gaze zone is an indicator of a driver's attention and plays an important role in the driver's activity monitoring. Due to the bad initialization of point-cloud transformation, gaze zone systems using RGB-D cameras and ICP (Iterative Closet Points) algorithm do not work well under long-time head motion. In this work, a solution for a continuous driver gaze zone estimation system in real-world driving situations is proposed, combining multi-zone ICP-based head pose tracking and appearance-based gaze estimation.

A Pilot Study of Perceptual-Motor Training for Peripheral Prisms.

Purpose: Peripheral prisms (p-prisms) shift peripheral portions of the visual field of one eye, providing visual field expansion for patients with hemianopia. However, patients rarely show adaption to the shift, incorrectly localizing objects viewed within the p-prisms. A pilot evaluation of a novel computerized perceptual-motor training program aiming to promote p-prism adaption was conducted.

Automatic Calibration Method for Driver's Head Orientation in Natural Driving Environment.

Gaze tracking is crucial for studying driver's attention, detecting fatigue, and improving driver assistance systems, but it is difficult in natural driving environments due to nonuniform and highly variable illumination and large head movements. Traditional calibrations that require subjects to follow calibrators are very cumbersome to be implemented in daily driving situations. A new automatic calibration method, based on a single camera for determining the head orientation and which utilizes the side mirrors, the rear-view mirror, the instrument board, and different zones in the windshield as calibration points, is presented in this paper.

Telescope aiming point tracking method for bioptic driving surveillance.

A bioptic telescope is a visual aid used by people with impaired vision when driving in many U.S. states, though bioptic driving remains controversial.

Physiogenomic resources for rat models of heart, lung and blood disorders.

Cardiovascular disorders are influenced by genetic and environmental factors. The TIGR rodent expression web-based resource (TREX) contains over 2,200 microarray hybridizations, involving over 800 animals from 18 different rat strains. These strains comprise genetically diverse parental animals and a panel of chromosomal substitution strains derived by introgressing individual chromosomes from normotensive Brown Norway (BN/NHsdMcwi) rats into the background of Dahl salt sensitive (SS/JrHsdMcwi) rats.