Visual recognition efficiency of handheld infrared thermometer interface information under low ambient illuminance

One of the symptoms of plagues, epidemics or pandemics is often a fever, so during such unprecedented times, handheld infrared thermometers are vital devices for monitoring symptomatic individuals. It is therefore very important to enhance reading efficiency when these thermometers are used for lengthy periods of time in a low illuminance environment. The need for the efficient reading of infrared thermometers or a fast reaction time when reading the information is even more relevant now during the COVID-19 pandemic. In this study, a target search experiment of digital characters is carried out through a simulated interface and use scenarios of a handheld thermometer based on three variables: the inclination angle or slant of the seven segment display characters, screen brightness, and ambient illuminance. The experimental results show that the inclination angle or slant of the characters and ambient illuminance have a significant effect on the reaction speed. In general, the slowest reaction time is found when reading characters with a slant of 10° to the left and the reaction time is the fastest with a right slant of 20°. A continued reduction in ambient illuminance does not affect the visual recognition performance but instead further enhances reading efficiency. Increasing the screen brightness increases the reaction time more in relatively low ambient illuminance conditions as opposed to relatively high ambient illuminance, which implies that in higher ambient illuminance conditions, a brighter screen needs to be used to obtain the same reaction speed as that in lower ambient illuminance conditions.     

Parametric study of the electrical to thermal power conversion in an inductively coupledrf plasma torch

An inductively coupled (ic) radio-frequency (rf) stabilized argon plasma was generated in a quartz tube using a 7 MHzrf generator. The electrical and thermal powers were measured and the efficiency of energy conversion was computed. The results indicate that for a constant power input, there is an optimum argon flow rate for which maximum energy conversion efficiency occurs.     

小波域最小嵌入失真函数设计及其在隐写中的应用

为了提高隐写方案的安全性,提出一种基于最小嵌入失真原理和网格码的图像隐写算法。首先在离散小波域结合人眼视觉特性和整数提升小波变换设计了失真测度函数,主要考虑了亮度、频率和纹理掩蔽因子对载体失真的影响。然后结合网格码设计了隐写算法,将嵌入信息对载体的修改最小化并且集中在人眼不敏感区域。实验结果显示,方案具有良好的视觉不可见性,且能抵抗空域、小波域等隐写分析的攻击,安全容量达到0.4 bits/pixel。     

有限遥测速率下卫星遥测数据设计方法研究

针对国内小卫星常用的统一遥测模式,讨论了在遥测速率受限的条件下,分包遥测格式设计应满足的基本条件;定义了分包遥测数据格式设计过程中的包编码损失率,并以此作为包数据格式编码效率的评价函数;分析了分包遥测数据格式设计过程中包长度、包采样周期等参数变化对评价函数的影响,进而给出了分包遥测数据格式设计中的应满足的条件和遵循的原则。     

基于K-距离拓扑的分布式数据存储方法

针对分布式数据存储算法通常需要较长的等待时间、且对海量数据加密时严重浪费计算资源和时间的问题,提出了一种基于K-距离拓扑的分布式数据存储方法.通过寻找K-距离拓扑子图来实现数据的安全放置,优先选择存取速度更快的节点和自身保护能力强的节点实现总体性能的提升.在Internet 2拓扑图与随机拓扑图下的仿真测试结果表明,所提出的方法能在满足安全距离约束的条件下选择到最优的数据存储节点,从而减小数据存取时间.     

车联网基于信任度的RSU识别及资源分配算法

在车联网中,由于部分路侧单元（RSU）的位置比较偏远,无法得到网络管理员的及时维护,可能遭到攻击,变为不可信任的路侧单元,降低了车辆的通信质量和网络能效.为了有效地识别RSU的可靠性,提出了一种基于信任度的路侧单元识别及资源分配算法,将路侧单元识别、传输模式的选择和功率分配联合建模为网络能效的优化问题,并分成3个子优化问题,分别求解.首先,采用基于信任度的RSU识别算法,识别出可信任和不可信任的路侧单元;其次,优化车辆资源块配置和链路选择;最后,通过次梯度算法优化传输功率,最大化网络能效.理论分析和仿真结果表明,所提算法具备较低的复杂度,可以达到较高的路侧单元识别准确度,并有效地提升网络总能效.     

多孔纤维型重整微反应器的等效电阻网络建模

针对应用于重整制氢微反应器的复杂多孔金属纤维载体（PFS）的流速场高效分析难题,建立载体中随机微通道的等效电阻网络分析模型. 基于复杂随机纤维结构的统计网络模型,将纤维载体中三维联通的随机微通道结构及与之相连的进出口腔简化为规则的网络通道结构.借鉴基尔霍夫定律,建立纤维载体的等效电阻网络模型,并确定求解方法. 纤维载体流速场实例分析的结果表明,基于等效电阻网络模型求解的纤维载体流速场与计算流体力学(CFD)方法的结果之间的皮尔森相关系数约为98%,且求解效率约为CFD方法的2.9×10⁴倍. 研究成果为多孔纤维型重整制氢微反应器的设计制造提供了新的支撑方案.     

振荡翼改进运动模型的能量捕获性能分析

为了提高振荡水翼的水动力性能和能量捕获效率,基于传统简谐运动模型提出改进运动模型,通过引入俯仰运动系数k,推导改进后俯仰运动规律的一般形式,利用Fluent软件建立水翼的二维模型,综合分析半主动振荡模型下不同俯仰运动系数、折算频率和俯仰振幅等运动参数对水翼能量捕获性能的影响。结果表明:与传统简谐运动模型相比,改进运动模型能够使水翼升力系数在较长时间段内维持较大数值,提高水翼的升力系数和捕能效率;在相同的折算频率和俯仰振幅下,减小俯仰运动系数会增大俯仰角转动的角速度,进而增大俯仰运动所消耗的能量;不同俯仰振幅下对应不同的最优折算频率,折算频率越低水翼的捕能性能越不稳定,俯仰振幅越大,转动俯仰角所消耗的能量越多。在给定参数条件下,水翼的能量转化效率可超过40%。     

Future energy goals for Maryland: Greenhouse gas reductions

Legislative requirements in Maryland set very robust goals for the implementation of energy efficiency by utilities. Significant energy savings has been achieved in all customer sectors and efficiency gains have been made over time in equipment and building construction. Looking forward, utilities should implement programs to promote energy efficiency with a greater emphasis on GHG reductions. Feasibility studies need to occur, but flexibility is key given changing codes and standards and market transformation.     

Interpretable modeling of metallurgical responses for an industrial coal column flotation circuit by XGBoost and SHAP-A “conscious-lab” development

Surprisingly, no investigation has been explored relationships between operating variables and metallurgical responses of coal column flotation (CF) circuits based on industrial databases for under operation plants. As a novel approach, this study implemented a conscious-lab “CL” for filling this gap. In this approach, for developing the CL dedicated to an industrial CF circuit, SHapley Additive exPlanations (SHAP) and extreme gradient boosting (XGBoost) were powerful unique machine learning systems for the first time considered. These explainable artificial intelligence models could effectively convert the dataset to a basis that improves human capabilities for better understanding, reasoning, and planning the unit. SHAP could provide precise multivariable correlation assessments between the CF dataset by using the Tabas Parvadeh coal plant (Kerman, Iran), and showed the importance of solid percentage and washing water on the metallurgical responses of the coal CF circuit. XGBoost could predict metallurgical responses (R-square > 0.88) based on operating variables that showed quite higher accuracy than typical modeling methods (Random Forest and support vector regression).