An Integrated Air Data / GPS Navigation System for Helicopters

In this study, the integration of two navigation systems Air Data System (ADS) and Global Positioning System (GPS) was aimed. ADS is a widely used navigation system which measures static and total air pressure and the air temperature. ADS has high sampling frequency and poor accuracy, on the other hand, another navigation system GPS has high accuracy compared to ADS but lower sampling frequency.Kalman Filter is used to integrate and minimize the errors of the two navigation systems. By this integration a navigation system with high sampling frequency and high accuracy is aimed. Another object is to calculate the wind speed with high accuracy.

Progress and future prospects of decadal prediction and data assimilation:A review

年代际预测,也称为“近期气候预测”,旨在预测未来1-10年内的气候变化,是气候预测和气候变化研究领域的一个新关注点.它位于季节至年际预测和长期气候变化预测之间,结合了初值问题和外部强迫问题的两个方面.年代际预测的核心技术在于用于模式初始化的同化方法的准确性和效率,其目标是为模式提供准确的初始条件,其中包含观测到的气候系统内部变率,年代际预测的初始化通常涉及在耦合框架内同化海洋观测,其中观测到的信号通过耦合过程传递到其他分量,如大气和海冰.然而,最近的研究越来越关注在海洋-大气耦合模式中探索耦合数据同化(CDA),有人认为CDA有潜力显著提高年代际预测技巧.本文综合评述了该领域的三个方面的研究现状:初始化方法,年代际气候预测的可预测性和预测技巧,以及年代际预测的未来发展和挑战.

Outlier Detection of Air Quality for Two Indian Urban Cities Using Functional Data Analysis

Human living would be impossible without air quality. Consistent advancements in practically every aspect of contemporary human life have harmed air quality. Everyday industrial, transportation, and home activities turn up dangerous contaminants in our surroundings. This study investigated two years’ worth of air quality and outlier detection data from two Indian cities. Studies on air pollution have used numerous types of methodologies, with various gases being seen as a vector whose components include gas concentration values for each observation per-formed. We use curves to represent the monthly average of daily gas emissions in our technique. The approach, which is based on functional depth, was used to find outliers in the city of Delhi and Kolkata’s gas emissions, and the outcomes were compared to those from the traditional method. In the evaluation and comparison of these models’ performances, the functional approach model studied well.

Enhancing Patients Outcomes and Infection Control through Smart Indoor Air Quality Monitoring Systems

Air pollution poses a critical threat to public health and environmental sustainability globally, and Nigeria is no exception. Despite significant economic growth and urban development, Nigeria faces substantial air quality challenges, particularly in urban centers. While outdoor air pollution has received considerable attention, the issue of indoor air quality remains underexplored yet equally critical. This study aims to develop a reliable, cost-effective, and user-friendly solution for continuous monitoring and reporting of indoor air quality, accessible from anywhere via a web interface. Addressing the urgent need for effective indoor air quality monitoring in urban hospitals, the research focuses on designing and implementing a smart indoor air quality monitoring system using Arduino technology. Employing an Arduino Uno, ESP8266 Wi-Fi module, and MQ135 gas sensor, the system collects real-time air quality data, transmits it to the ThingSpeak cloud platform, and visualizes it through a user-friendly web interface. This project offers a cost-effective, portable, and reliable solution for monitoring indoor air quality, aiming to mitigate health risks and promote a healthier living environment.

Powermitter:Data Exfiltration from Air-Gapped Computer through Switching Power Supply

Air-gapped computers are isolated both logically and physically from all kinds of existing common communication channel, such as USB ports, wireless and wired networks. Although the feasibility of infiltrating an air-gapped computer has been proved in recent years, data exfiltration from such systems is still considered to be a challenging task. In this paper we present Powermitter, a novel approach that can exfiltrate data through an air-gapped computer via its power adapter. Our method utilizes the switched-mode power supply, which exists in all of the laptops, desktop computers and servers nowadays. We demonstrate that a malware can indirectly control the electromagnetic emission frequency of the power supply by leveraging the CPU utilization. Furthermore, we show that the emitted signals can be received and demodulated by a dedicated device. We present the proof of concept design of the power covert channel and implement a prototype of Powermitter consisting of a transmitter and a receiver. The transmitter leaks out data by using a variant binary frequency shift keying modulation, and the emitted signal can be captured and decoded by software based virtual oscilloscope through such covert channel. We tested Powermitter on three different computers. The experiment re-sults show the feasibility of this power covert channel. We show that our method can also be used to leak data from different types of embedded systems which use switching power supply.

The relation between ambulance transports due to heat stroke and air temperature using daily data in Okayama prefecture, Japan

The aim of this study was to investigate the link between ambulance transports due to heat stroke and air temperature by using daily data of ambulance transports in Okayama prefecture, Japan. Daily observations for ambulance transports due to heat stroke from July to September in 2010 in Okayama prefecture, Japan were obtained from Fire and Disaster Management Agency in Japan. Data of meteorological parameters in Okayama prefecture, Japan were also obtained from Japan Meteorological Agency. Effect of meteorological parameters on ambulance transports due to heat stroke was analyzed. A total of 1133 ambulance transports due to heat stroke were observed in from July to September of 2010 in Okayama prefecture, Japan. Ambulance transports due to heat stroke was significantly correlated with air temperature. In addition, number of subjects with ambulance transports due to heat stroke over 34°C in the highest air temperature was 21.2 ± 9.8 per day. Higher air temperature was closely associated with higher ambulance transports due to heat stroke by using daily data in Okayama, prefecture, Japan.

Air-combat behavior data mining based on truncation method

This paper considers the problem of applying data mining techniques to aeronautical field.The truncation method,which is one of the techniques in the aeronautical data mining,can be used to efficiently handle the air-combat behavior data.The technique of air-combat behavior data mining based on the truncation method is proposed to discover the air-combat rules or patterns.The simulation platform of the air-combat behavior data mining that supports two fighters is implemented.The simulation experimental results show that the proposed air-combat behavior data mining technique based on the truncation method is feasible whether in efficiency or in effectiveness.

Missing Data Imputations for Upper Air Temperature at 24 Standard Pressure Levels over Pakistan Collected from Aqua Satellite

This research was an effort to select best imputation method for missing upper air temperature data over 24 standard pressure levels. We have implemented four imputation techniques like inverse distance weighting, Bilinear, Natural and Nearest interpolation for missing data imputations. Performance indicators for these techniques were the root mean square error (RMSE), absolute mean error (AME), correlation coefficient and coefficient of determination ( R2 ) adopted in this research. We randomly make 30% of total samples (total samples was 324) predictable from 70% remaining data. Although four interpolation methods seem good (producing <1 RMSE, AME) for imputations of air temperature data, but bilinear method was the most accurate with least errors for missing data imputations. RMSE for bilinear method remains <0.01 on all pressure levels except 1000 hPa where this value was 0.6. The low value of AME (<0.1) came at all pressure levels through bilinear imputations. Very strong correlation (>0.99) found between actual and predicted air temperature data through this method. The high value of the coefficient of determination (0.99) through bilinear interpolation method, tells us best fit to the surface. We have also found similar results for imputation with natural interpolation method in this research, but after investigating scatter plots over each month, imputations with this method seem to little obtuse in certain months than bilinear method.

COMPARATIVE ANALYSIS OF VARIOUS DATA OF AIR-SEA TEMPERATURE DIFFERENCE AND ITS VARIATION ACROSS SOUTH CHINA SEA IN THE PAST 35 YEARS

Using the International Comprehensive Ocean-Atmosphere Data Set(ICOADS) and ERA-Interim data, spatial distributions of air-sea temperature difference(ASTD) in the South China Sea(SCS) for the past 35 years are compared,and variations of spatial and temporal distributions of ASTD in this region are addressed using empirical orthogonal function decomposition and wavelet analysis methods. The results indicate that both ICOADS and ERA-Interim data can reflect actual distribution characteristics of ASTD in the SCS, but values of ASTD from the ERA-Interim data are smaller than those of the ICOADS data in the same region. In addition, the ASTD characteristics from the ERA-Interim data are not obvious inshore. A seesaw-type, north-south distribution of ASTD is dominant in the SCS; i.e., a positive peak in the south is associated with a negative peak in the north in November, and a negative peak in the south is accompanied by a positive peak in the north during April and May. Interannual ASTD variations in summer or autumn are decreasing. There is a seesaw-type distribution of ASTD between Beibu Bay and most of the SCS in summer, and the center of large values is in the Nansha Islands area in autumn. The ASTD in the SCS has a strong quasi-3a oscillation period in all seasons, and a quasi-11 a period in winter and spring. The ASTD is positively correlated with the Nio3.4 index in summer and autumn but negatively correlated in spring and winter.

基于计量测试技术的气流组织与机房空调节能运行研究

为量化气流组织对机房空调节能的影响,以某数据中心作为测试对象,基于计量测试技术将抽象的气流组织参数化、指标化,通过测量数据的分析,指出了机房内气流组织存在的问题,并制定了有针对性的气流组织调优和空调节能运行策略。测试数据表明,在机房热环境满足国家标准要求的前提下,机房空调节能率超过28%。

基站空调在640层CT数据机房的使用效果

目的探讨基站空调在640层CT数据机房的使用效果。方法640层CT正常开机时,分别记录并比较基站空调和普通空调开启后数据机房温度由28℃降至24℃所需时间、正常运行必需后勤维护项目及次数、整体价格。结果室外温度为-5~30℃时,两种空调达到设定温度所需时间比较,差异无统计学意义(P>0.05),后勤维护项目次数相同;室外环境温度为31~42℃时,基站空调机房降温时间短于普通空调(P<0.05);普通空调需完成后勤维护项目一2次和项目二1次,基站空调需完成项目一2次;在室外环境温度为-6~-15℃时,普通空调故障停机,基站空调达到设定温度需要(12.4±1.5)min;基站空调整体价格高于普通空调;基站空调的整机性价比、操作使用、降温效率、故障报警和环境影响评分高于普通空调(P<0.05)。结论基站空调虽整体价格偏贵,但制冷速度快、可靠性高、维护简单,更适用于640层CT数据机房。

Processing the rig test data of an air filling twin-tube shock absorber

A separation method is proposed to design and improve shock absorber according to the characteristics of each force. The method is validated by rig test. The force data measured during rig test is the resultant force of damping force, rebound force produced by pressed air, and friction force. Different characters of damping force, air rebound force and friction force can be applied to seperate each force from others. A massive produced air filling shock absorber is adopted for the validation. The statistic test is used to get the displacement-force curves. The data are used as the input of separation calculation. Then the tests are carried out again to obtain the force data without air rebound force. The force without air rebound is compared to the data derived from the former tests with the separation method. The result shows that this method can separate the damping force and the air elastic force.

贫数据中基于模型自训练的空气处理设备故障诊断

针对空气处理设备(AHU)故障贫数据,基于深度置信网络(DBN)模型对4种特征选择算法进行对比研究,结果表明最大相关最小冗余算法的特征子集在诊断准确率及子集元素稳定性上表现最优。提出将DBN嵌入自训练框架的故障诊断模型,发现DBN自训练的诊断准确率较单纯DBN最高可提升19.5%。提出均匀抽样及按比例抽样2种自训练伪标签抽样策略,二者的诊断准确率均随抽样数减小而增大,在不同抽样数中的最大差异为3.42%;在所有贫数据样本中,均匀抽样策略始终优于按比例抽样,诊断准确率最大相差1.39%,表明在故障标签匮乏时,采用均匀抽样策略及较小的抽样数有利于提升DBN自训练的诊断性能。

随机误差传递的高空气象秒级数据快速校验方法

【目的】为保证气象预报结果的准确性。【方法】提出了考虑随机误差传递的高空气象秒级数据快速校验方法。对高空气象秒级数据进行预处理,包括数据中心化处理、特征点提取。数据中心化的处理方式为实施各组数据的加权平均处理,获得新的数据组作为基准数据;特征点提取使用的处理方法为遍历法,需要遍历全部数据点。考虑数据获取过程中的随机误差传递情况,对预处理后的高空气象秒级数据实施空间一致性检查、内部一致性检查。应用集合经验模态分解EEMD(Ensemble Empirical Mode Decomposition)算法与对比源反演CSI(Contrast Source Inversion)算法构建基于CSI-EEMD的高空气象秒级数据快速校验模型,实施数据得到快速校验。【结果】测试结果表明,该方法能够实现4个气象站数据的快速校验,校验结果的均方根误差与平均绝对误差均低于0.1,实现了数据的质量控制。【结论】将该方法应用于气象站数据校验中,可以实现精准度的数据校验,具有一定的实用价值。

基于GPS-惯性数据的激光大气数据系统标定方法

激光大气数据系统由于系统测量精度较高以及测量区域范围较大,目前尚无有效的高精度标定手段。针对这一问题,提出一种直线折返测速法,可以消除大气中风速的影响,将消除风速影响后的空速数据与GPS-惯性组合导航系统测量的地速数据进行对比分析,以评价激光大气数据系统真空速测量性能。分析了所提方法的各类测量误差以及理论极限精度。飞行实验结果表明,所提方法测量精度优于0.5 m/s,接近理论误差极限,可以用来标定激光大气数据系统,为激光大气数据系统标定技术的发展和应用提供参考。

A Study of Detection of Outliers for Working and Non-Working Days Air Quality in Kolkata, India: A Case Study

A variety of factors affect air quality, making it a difficult issue. The level of clean air in a certain area is referred to as air quality. It is challenging for conventional approaches to correctly discover aberrant values or outliers due to the significant fluctuation of this sort of data, which is influenced by Climate change and the environment. With accelerating industrial expansion and rising population density in Kolkata City, air pollution is continuously rising. This study involves two phases, in the first phase imputation of missing values and second detection of outliers using Statistical Process Control (SPC), and Functional Data Analysis (FDA), studies to achieve the efficacy of the outlier identification methodology proposed with working days and Nonworking days of the variables NO2, SO2, and O3, which were used for a year in a row in Kolkata, India. The results show how the functional data approach outshines traditional outlier detection methods. The outcomes show that functional data analysis vibrates more than the other two approaches after imputation, and the suggested outlier detector is absolutely appropriate for the precise detection of outliers in highly variable data.

数据中心冷却系统研究及应用进展

为加速实现数据中心节能降耗的目标,在合理、高效、最大化地利用自然冷源的同时,更不能忽视机械制冷系统本身能效的提升。加强自然冷却与机械制冷的协同,降低数据中心PUE,充分发挥安全稳定、高效运行的数据中心冷却系统自身能效至关重要。本文通过对气流组织、供/回水温度和冷却系统部件及形式3个方面的研究梳理,总结分析数据中心冷却系统节能提效有关技术研究与应用进展,从而为绿色、高效数据中心冷却系统的研发提供参考和借鉴。

基于空间梯度信息的质量控制方法在红外高光谱AIRS资料同化中的应用研究

本文利用中尺度非静力WRF(Weather Research Forecast,Version 3.4)模式,针对1013号"鲇鱼"台风个例,通过对红外高光谱AIRS(Atmospheric Infrared Sounder)资料经过基于空间梯度信息的质量控制之后同化进入模式,来评估新的质量控制方法对同化效果的影响以及对台风数值模拟的改善情况。研究结果发现,如果仅仅基于WRFDA(WRF Data Assimilation system,Version 3.4)模式自带的质量控制系统,将会有部分梯度距平值明显较大超过阈值的资料被同化进入模式,而这些可能受到"污染"且误差较大的资料同化进入模式必将会导致同化结果有较大误差,影响分析结果的质量。而对AIRS资料经过基于空间梯度信息质量控制之后再同化进入模式,确实可将梯度距平值大于阈值的"坏点"剔除掉,从而使初始场的描述更加准确,台风路径的模拟精度在一定程度上得到提高。综上可知,基于空间梯度信息的质量控制方法整体上对改善同化效果有较好的正效应,对台风的数值模拟也起到一定的促进作用。

大气红外探测器(AIRS)温、湿度反演产品的有效性检验及在数值模式中的应用研究

利用中国540个地面气象观测站点资料,对1和7月大气红外探测器(AIRS)的反演中国区域地面气温精度做了详细评估,分析了产生误差的原因。同时把AIRS的反演温、湿度廓线产品与T213数值预报产品进行比较,分析了它们之间的差异。为进一步考察AIRS温、湿度产品的有效性,我们把经过订正的AIRS地面气温以及温、湿度廓线产品分析同化到中尺度模式MM5中,用于华北降雪天气过程的对比模拟试验,分析AIRS反演产品对降雪量、水汽场、垂直速度场、散度场以及云物理过程等的影响。