Moving‐picture response time (MPRT) of LCDs for the oblique viewing direction

Abstract— The dynamic performance of displays is an important characteristic for multimedia applications. Motion‐picture response time (MPRT) has been used as an indicator of the dynamic performance of LCDs. This paper describes a comprehensive method of MPRT evaluation for the oblique viewing direction. By using a tilted camera configuration, the angular dependency of MPRT is investigated for the condition that the horizontally scrolling patterns are observed from the vertical direction. For each gray‐to‐gray transition, distinct changes in MPRT and the luminance profile of blur are observed.     

Modeling the Influences of Cyclic Top-Down and Bottom-Up Processes for Reinforcement Learning in Eye Movements

Understanding and reproducing complex human oculomotor behaviors using computational models is a challenging task. In this paper, two studies are presented, which focus on the development and evaluation of a computational model to show the influences of cyclic top-down and bottom-up processes on eye movements. To explain these processes, reinforcement learning was used to control eye movements. The first study showed that, in a picture-viewing task, different policies obtained from different picture-viewing conditions produced different types of eye movement patterns. In another visual search task, the second study illustrated that feedback information from each saccadic eye movement could be used to update the model's eye movement policy, generating different patterns in the following saccade. These two studies demonstrate the value of an integrated reinforcement learning model in explaining both top-down and bottom-up processes of eye movements within one computational model.     

Multibody dynamics analysis of the driveshaft coupling of the ball and tripod types of constant velocity joints

The paper proposes a multibody dynamic simulation to numerically evaluate the generated axial force (GAF) and plunging resistant force (PRF) practically related to the shudder and idling vibration of an automobile. A numerical analysis of the drive shaft coupling of a ball joint (BJ) and two plunging type joints, a tripod joint (TJ), and a very low axial force tripod joint (VTJ), are conducted using the commercial program DAFUL. User-defined subroutines of a friction model illustrating the contacted parts of the outboard and inboard joint are subsequently developed to overcome the numerical instability and improve the solution performance. The Coulomb friction effect is applied to describe the contact models of the lubricated parts in the rolling and sliding mechanisms. The numerical results, in accordance with the joint articulation angle variation, are validated with experimentation. The offset between spider and housing is demonstrated to be the critical role in producing the third order component of the axial force that potentially causes the noise and vibration in the vehicle. The VTJ shows an excellent behavior for the shudder when compared with the TJ. In addition, a flexible nonlinear contact analysis coupled with multibody dynamics is also performed to show the dynamic strength characteristics of the rollers, housing, and spider.     

Layered Diffusion-based Coverage Control in Wireless Sensor Networks

Coverage is an important performance metric for many applications, such as surveillance in wireless sensor networks. Coverage control is used to select as few active nodes as possible from all deployed sensor nodes, such that sufficient coverage of the monitored area can be guaranteed while reducing the energy consumption of each individual sensor node to prolong the network lifetime. This paper classifies three types of coverage control protocols based on the available information about nodes’ distances or locations, and reviews several representative protocols for each type. We also propose a new distributed and localized coverage control protocol, called Layered Diffusion-based Coverage Control (LDCC). The LDCC protocol does not require information about the node location coordinates when selecting active nodes. Instead, it exploits hop count information, which is easily obtained in a WSN, to select active sensor nodes. Furthermore, the LDCC protocol is very simple and does not require any sophisticated computation such as distance or covered area computation. Our simulation results show that the LDCC protocol achieves a high coverage ratio while incurring very low message overhead compared with other existing protocols. Furthermore, simulation results suggest that in a large-scale sensor network with medium to large localization errors, LDCC performs even better than location-based coverage control protocols.     

Pitchfork bifurcation and flip-flop operation with a coupled nonlinear system

A ring cavity system consisting of two hybrid Michelson interferometers coupled together with feedback is constructed. This system shows spatial bifurcation and can be utilized as an all-optical flip-flop device. We demonstrate experimentally a flip-flop operation by use of only a positive pulse in this system.     

基于卷积神经网络的随机因子重采样图像检测

图像重采样检测是图像取证领域的重要任务,其目的是检测图像是否经过重采样操作。现有的基于深度学习的重采样检测方法大多只针对特定的重采样因子进行研究,而较少考虑重采样因子完全随机的情况。本文根据重采样操作中所涉及的插值技术原理设计了一组高效互补的图像预处理结构以避免图像内容的干扰,并通过可变形卷积层和高效通道注意力机制(efficient channel attention, ECA)分别提取和筛选重采样特征,从而有效提高了卷积神经网络整合提取不同重采样因子的重采样特征的能力。实验结果表明,无论对于未压缩的重采样图像还是JPEG压缩后处理的重采样图像,本文方法都可以有效检测,且预测准确率相比现有方法均有较大提升。     

双重JPEG压缩图像篡改区域检测与定位

对JPEG(joint photographic experts group)图像实施篡改往往会产生双重JPEG(double JPEG,DJPE) 压缩痕迹,分析该痕迹有助于揭示图像压缩历史并实现篡改区域定位。现有算法在图像尺寸较小和质量因子(quality factor,QF) 较低的时候性能不佳,对两个QF的组合情况存在限制。本文提出了一种端到端的混合QF双重JPEG压缩图像取证网络,命名为DJPEGNet。首先,使用预处理层从图像头文件中提取表征压缩历史信息的量化表 (quantization table,Qtable) 特征,将图像从空域转换至DCT(discrete cosine transform)域构造统计直方图特征。然后,将两个特征输入到由深度可分离卷积和残差结构堆叠而成的主体结构,输出二分类结果。最后,使用滑动窗口算法自动定位篡改区域并绘制概率分布图。实验结果表明,在使用不同Qtable集生成的小尺寸数据集上,DJPEGNet所有指标均优于现有最先进的算法,其中ACC提高了1.78%,TPR提升了2.00%,TNR提升了1.60%。     

Metal Ions versus Protons: Tracking of Charge-Carrier Insertion into a Cathode Oxide in Aqueous Rechargeable Batteries

Protons in aqueous electrolytes can perform as an additional type of charge carrier for insertion/extraction in addition to the primary carrier cations in aqueous rechargeable batteries. Despite many diverse claims regarding the effect of protons, mutually conflicting experimental results and their interpretations without direct evidence have been reported over the last decade. Systematic examinations and analyses are thus imperative to clarify the conditions of proton insertion in aqueous rechargeable batteries. Utilizing V₂O₅ as a model cathode and beaker-type cells with a sufficient amount of ZnSO₄ aqueous electrolytes in this work, it is demonstrated that protons are inserted into the cathode prior to Zn-ions in low-pH conditions (pH ≤ 3.0). In stark contrast, the influence of protons on the discharge voltage and capacity is insignificant, when either the pH becomes higher (pH ≥ 4.0) or the electrolyte volume is considerably low in coin-type cells. Similar behavior of pH-dependent proton insertion is also verified in Na–, Mg–, and Al-ion electrolytes. Providing a resolution to the controversy regarding proton insertion, the present study emphasizes that the influence of protons substantially varies depending on the pH and relative volume of electrolytes in aqueous batteries.     

Skin-like Omnidirectional Stretchable Platform with Negative Poisson's Ratio for Wearable Strain–Pressure Simultaneous Sensor

Conventional elastomeric polymers used as substrates for wearable platforms have large positive Poisson's ratios (≈0.5) that cause a deformation mismatch with human skin that is multidirectionally elongated under bending of joints. This causes practical problems in elastomer-based wearable devices, such as delamination and detachment, leading to poorly reliable functionality. To overcome this issue, auxetic-structured mechanical reinforcement with glass fibers is applied to the elastomeric film, resulting in a negative Poisson's ratio (NPR), which is a skin-like stretchable substrate (SLSS). Several parameters for determining the materials and geometrical dimensions of the auxetic-structured reinforcing fillers are considered to maximize the NPR. Based on numerical simulation and digital image correlation analysis, the deformation tendencies and strain distribution of the SLSS are investigated and compared with those of the pristine elastomeric substrate. Owing to the strain-localization characteristics, an independent strain-pressure sensing system is fabricated using SLSS with a Ag-based elastomeric ink and a carbon nanotube-based force-sensitive resistor. Finally, it is demonstrated that the SLSS-based sensor platform can be applied as a wearable device to monitor the physical burden on the wrist in real time.     

基于IGA-BP神经网络的锂电池健康状态估算

针对锂离子电池健康状态(SOH)估算精度低、传统遗传算法(GA)易陷入局部最优、收敛速度慢的问题,为提高锂电池健康状态的估算精度,提出了交叉概率和变异概率自适应的调整策略对传统GA进行改进,在改进遗传算法(IGA)的作用下,使优良个体仍保持较好的进化能力,算法初期搜索范围、后期局部搜索能力以及收敛速度也得到加强。提取间接健康因子,再用改进的遗传算法对BP神经网络的初始参数寻优得到IGA-BP神经网络模型,基于NASA锂电池数据集分别用GA-BP与IGA-BP神经网络算法对SOH进行估算。结果表明:IGA-BP神经网络算法估算精度更高,且具备快速收敛的优势,平均绝对百分比误差和均方根误差分别下降了0.422%和0.412,拟合程度提高了8.1%。