Interacting Socially with the Internet of Things (IoT): Effects of Source Attribution and Specialization in Human–IoT Interaction

This study investigates the theoretical mechanisms by which the variations in source attribution (multiple sources vs. single source) and specialization (multifunctionality vs. single functionality) of Internet of Things (IoT) devices influence the quality of human–IoT interaction. Results from a between‐subjects experiment (N = 100) indicate that IoT devices that elicit the sense of multiple agencies and are specialized in a single function induce greater social presence and perceived expertise, which, in turn, lead individuals to show a more positive attitude toward the devices and to ascribe greater quality to the information transmitted by them. The results also reveal that the effect of multiple source attribution is more pronounced for individuals for whom the content of the information has low personal relevance.     

Rendering of HDR images to improve brightness discrimination

The impression of quality of images can be enhanced on a high dynamic range (HDR) displays. Generally, a conventional 8‐bit image can be processed to an HDR image by inverse tone mapping operators. Among the operators, brightness discrimination mapping by applying brightness adaptation model attempted to mimic the human visual system. In this paper, we use a brightness adaptation model to derive a brightness discrimination mapping algorithm for HDR displays. The proposed algorithm maximizes a function, which represents the local and global brightness discrimination range by exploiting characteristics of the human visual system. Enhancement of details is verified by visualizing HDR images from dark to bright regions. Improvement of dynamic range is quantified by measuring increased discrimination ratio.     

Image processing acceleration for intelligent unmanned aerial vehicle on mobile GPU

In this paper, we present an algorithm for providing visually-guided unmanned aerial vehicle (UAV) control using visual information that is processed on a mobile graphic processing unit (GPU). Most real-time machine vision applications for UAVs exploit low-resolution images because the shortage of computational resources comes from size, weight and power issue. This leads to the limitation that the data are insufficient to provide the UAV with intelligent behavior. However, GPUs have emerged as inexpensive parallel processors that are capable of providing high computational power in mobile environments. We present an approach for detecting and tracking lines that use a mobile GPU. Hough transform and clustering techniques were used for robust and fast tracking. We achieved accurate line detection and faster tracking performance using the mobile GPU as compared with an x86 i5 CPU. Moreover, the average results showed that the GPU provided approximately five times speedup as compared to an ARM quad-core Cortex-A15. We conducted a detailed analysis of the performance of proposed tracking and detection algorithm and obtained meaningful results that could be utilized in real flight.     

Sources and leaching of manganese and iron in the Saigon River Basin, Vietnam

High concentrations of manganese and iron in the Saigon River are major problems for the water supply in Ho Chi Minh City (HCMC), Viet Nam. To identify their sources and leaching processes, we surveyed water quality along the Saigon River and ran batch leaching tests using soil and sediment samples. Two important leaching processes were identified: acidic leaching from acid sulfate soil (ASS) in the middle reaches of the river, and Mn dissolution and Fe reduction from sediments in the downstream reaches. Low pH caused the concurrent release of Fe and Mn from the ASS. In contrast, anoxia caused the release of Fe but not Mn from the sediments, whereas low pH facilitated Mn dissolution. Sediments are a more important source of Mn because of their higher Mn contents (10 times) and release rates (14 times) than those from ASS.     

Tensor Clustering for Rendering Many‐Light Animations

Rendering animations of scenes with deformable objects, camera motion, and complex illumination, including indirect lighting and arbitrary shading, is a long‐standing challenge. Prior work has shown that complex lighting can be accurately approximated by a large collection of point lights. In this formulation, rendering of animation sequences becomes the problem of efficiently shading many surface samples from many lights across several frames. This paper presents a tensor formulation of the animated many‐light problem, where each element of the tensor expresses the contribution of one light to one pixel in one frame. We sparsely sample rows and columns of the tensor, and introduce a clustering algorithm to select a small number of representative lights to efficiently approximate the animation. Our algorithm achieves efficiency by reusing representatives across frames, while minimizing temporal flicker. We demonstrate our algorithm in a variety of scenes that include deformable objects, complex illumination and arbitrary shading and show that a surprisingly small number of representative lights is sufficient for high quality rendering. We believe out algorithm will find practical use in applications that require fast previews of complex animation.     

Motion synthesis with decoupled parameterization

In real-time animation systems, motion interpolation techniques are widely used for their controllability and efficiency. The techniques sample the parameter space using example motions, and interpolate them to compute the blend weights corresponding to the given parameters. A main problem of the techniques is that, as the dimension n of the parameter space increases, the number of required example motions increases exponentially, i.e. O(c ⁿ ). To resolve the problem, this paper proposes to use two decoupled parameter spaces for controlling the upper body and the lower body separately. At each frame time, a parameterized motion space produces a source frame, and the target frame is synthesized by splicing the upper body of one source frame with the lower body of the other. In order to have the two source frames correlated with each other, a time-warping scheme has been developed. Furthermore, in order to handle the dynamic properties of the parameter samples of the upper body, we have developed an approximation technique for quickly determining the sample positions in its parameter space. This decoupled parameterization method alleviates the complexity problem, e.g. from O(c ⁶) to O(c ³), while providing the users with the capability of convenient control over the character.     

Design and Implementation of a Ubiquitous Robotic Space

This paper describes a concerted effort to design and implement a robotic service framework. The proposed framework is comprised of three conceptual spaces: physical, semantic, and virtual spaces, collectively referred to as a ubiquitous robotic space. We implemented a prototype robotic security application in an office environment, which confirmed that the proposed framework is an efficient tool for developing a robotic service employing IT infrastructure, particularly for integrating heterogeneous technologies and robotic platforms.     

Effect of interlayer on structure and performance of anode-supported SOFC single cells

To lower the operating temperatures in solid oxide fuel cell (SOFC) operations, anode-supported SOFC single cells with a single dip-coated interlayer were fabricated and the effect of the interlayer on the electrolyte structure and the electrical performance was investigated. For the preparation of SOFC single cells, yttria-stabilized zirconia (YSZ) electrolyte, NiO-YSZ anode, and 50% YSZ-50% strontium-doped lanthanum manganite (LSM) cathode were used. In order to characterize the cells, scanning electron microscopy (SEM) and atomic force microscopy (AFM) were utilized and the gas (air) permeability measurements were conducted for gas tightness estimation. When the interlayer was inserted onto NiO-YSZ anode, the surface roughness of anode was diminished by about 40% and dense crack-free electrolytes were obtained. The electrical performance was enhanced remarkably and the maximum power density was 0.57W/cm(2) at 800 degrees C and 0.44W/cm(2) at 700 degrees C. On the other hand, the effect of interlayer on the gas tightness was negligible. The characterization study revealed that the enhancement in the electrical performance was mainly attributed to the increase of ion transmission area of anode/electrolyte interface and the increase of ionic conductivity of dense crack-free electrolyte layer.     

Room-Temperature-Processable Highly Reliable Resistive Switching Memory with Reconfigurability for Neuromorphic Computing and Ultrasonic Tissue Classification

Reversible metal-filamentary mechanism has been widely investigated to design an analog resistive switching memory (RSM) for neuromorphic hardware-implementation. However, uncontrollable filament-formation, inducing its reliability issues, has been a fundamental challenge. Here, an analog RSM with 3D ion transport channels that can provide unprecedentedly high reliability and robustness is demonstrated. This architecture is realized by a laser-assisted photo-thermochemical process, compatible with the back-end-of-line process and even applicable to a flexible format. These superior characteristics also lead to the proposal of a practical adaptive learning rule for hardware neural networks that can significantly simplify the voltage pulse application methodology even with high computing accuracy. A neural network, which can perform the biological tissue classification task using the ultrasound signals, is designed, and the simulation results confirm that this practical adaptive learning rule is efficient enough to classify these weak and complicated signals with high accuracy (97%). Furthermore, the proposed RSM can work as a diffusive-memristor at the opposite voltage polarity, exhibiting extremely stable threshold switching characteristics. In this mode, several crucial operations in biological nervous systems, such as Ca²⁺ dynamics and nonlinear integrate-and-fire functions of neurons, are successfully emulated. This reconfigurability is also exceedingly beneficial for decreasing the complexity of systems—requiring both drift- and diffusive-memristors.     

Toward Stable Cycling of a Cost-Effective Cation-Disordered Rocksalt Cathode via Fluorination

The recently developed Li-excess cation-disordered rock salts (DRXs) exhibit an excellent chemical diversity for the development of alternative Co/Ni-free high-energy cathodes. Herein, the synthesis of a highly fluorinated DRX cathode, Li_1.2Mn_0.6Ti_0.2O_1.8F_0.2, based on cost-effective and earth-abundant transition metals, via a solid-state reaction, is reported. The fluorinated DRX cathode using ammonium fluoride precursor exhibits more uniform particle size and delivers a specific discharge capacity of 233 mAh g⁻¹ and specific energy of 754 Wh kg⁻¹, with 206 mAh g⁻¹ retained after 200 cycles. The combined synchrotron X-ray absorption spectroscopy and resonant inelastic X-ray scattering spectroscopy analysis reveals that the remarkable cycling performance is attributed to the high fluorination and thus enhanced Mn content, enabling the utilization of more Mn redox than the oxide analog. This study demonstrates a great promise to develop next-generation cost-effective DRX cathodes with enhanced capacity retention for high-energy Li-ion batteries.