Design considerations for a larger inmarsat standard ship earth station

A new standard of INMARSAT ship earth station for multi-channel operation could find particular application on large passenger ships and off-shore oil/gas platforms. This paper provides estimates of platform and ship motions and discusses general design requirements, notably of the antenna system. The discussion includes consideration of possible modulation and multiple access techniques. Single channel per carrier (SCPC) operation is advocated which permits easy integration with the present service to single channel INMARSAT Standard-A ship earth stations. Major parameter/relative cost trade-off curves needed in an overall ship earth station design optimization are presented.     

Flow injection spectrofluorimetric determination of carvedilol mediated by micelles

We propose a novel evanescent wave scattering imaging method using an objective-type total internal reflection system to image and track single gold nanoparticles (GNPs) in solution. In this imaging system, only a millimeter-scale hole is employed to efficiently separate GNPs scattering light from the background reflected beam. The detailed experimental realization of the imaging system was discussed, and the effect of the hole size on imaging was investigated. We observed that the hole diameters from 2.5 to 4 mm are suitable to perform the scattering imaging by adjusting the incidence angle. The technology was successfully applied to track single gold nanoparticles in solution and on live cell membrane via the anti-epidermal growth factor receptor antibody. Compared to total internal fluorescence microscopy, the resonance light scattering detection has no photobleaching or blinking inherent to fluorescent dyes and quantum dots. Compared to conventional dark-field microscopy, the evanescent wave illumination can be conveniently applied to study membrane dynamics in living cells. Additionally, the objective-based configuration provides a free space above the coverslip, and allows imaging and concomitant manipulation of live cells in culture by microinjection, patch-clamping, AFM and other techniques.     

A new IMM algorithm using fixed coefficients filters (fastIMM)

In this paper we present an new approach based on two filters αβ$\alpha \beta$ and αβγ$\alpha \beta \gamma$ using Interacting Multiples Models (IMM) design instead of a Kalman filter second and third order for the tracking a single maneuver target. The comparison between the proposed filter and the IMM improves the computing time amount about 60% while having a high accuracy.     

Efficient detection of refugees and migrants in Turkey using convolutional neural network

At the start of the Syrian Civil War in 2011, NGOs played a big part in giving refugees access to aid and distributing that aid so that people could go to school, get a job, or get medical care. Within the last few years, when tensions rose between Syrian refugees and the Turkish community, many non-governmental organizations switched their attention to fostering community among refugees in Turkey. Over the past two decades, family displacement has become a big problem in various countries due to a rise in the frequency with which natural catastrophes, military conflicts, and terrorist strikes occur. It poses severe difficulties for governing bodies and the organizations that oversee them. This research aims to identify and track refugees in surveillance zones by utilizing artificial intelligence. Refugees are vulnerable to acts of nature and human aggression, which makes their random relocation or encampments challenging to manage. To overcome these challenges, a convolutional neural network deep learning model has been proposed to identify and track refugees in surveillance zones. The proposed solution is integrated with Internet of Things (IoT) technology by equipping the system with IoT sensors to capture real-time data on the location and movements of refugees. This combination of AI and IoT has the potential to improve the efficiency and effectiveness of refugee management efforts. The suggested solution uses a convolutional neural network deep learning model, which can quickly identify a refugee’s face. To assist the government in locating a specific refugee, the system simultaneously connects with the refugees and requests that they regularly update their location. The system alerts security to identify the missing immigrant since the refugee does not update their whereabouts. Without human intervention, the deep learning algorithm makes it simple to recognize immigrants and keep an eye on them.     

Reversible Live-Cell Labeling with Retro-engineered HaloTags Enables Long-Term High- and Super-Resolution Imaging

Self-labeling enzymes (SLE) such as the HaloTag have emerged as powerful tools in high and super-resolution fluorescence microscopy. Newly developed fluorogenic SLE substrates enable imaging in the presence of excess dye. To exploit this feature for reversible labeling, we engineered two variants of HaloTag7 with restored dehalogenase activity. Kinetic studies in vitro showed different turnover kinetics for reHaloTagS (≈0.006 s⁻¹) and reHaloTagF (≈0.055 s⁻¹). Imaging by confocal and stimulated emission depletion microscopy yielded 3-5-time enhanced photostability of reHaloTag labeling. Prominently, single molecule imaging with reHaloTags enabled controlled and stable labeling density over extended time periods. By combination with structured illumination, simultaneous visualization of single molecule diffusion and organellar dynamics was achieved. These applications highlight the potential of reHaloTag labeling for pushing the limits of advanced fluorescence microscopy techniques.     

靶场发射初始段雷达精密跟踪技术

航天战略地靶发射初始段测量除了产生必要的跟踪监视信息以外，更重要的任务是获取安控信息源，文章从靶场的雷达环境出发，说明常规跟踪雷达不能实现对复杂背景下的载体（星箭，导弹等）跟踪，经分析研究，提出了ＭＴＴ（Ｍｏｖｉｎｇ－Ｔａｒｇｅｔ－Ｔｒａｃｋｉｎｇ）技术的概念，实验室计算机仿真和工程样机在靶场跟踪的数据分析，说明ＭＴＴ雷达是实现初始段精密跟踪测量的一种有效手段。     

An adaptive critic neural network for motion control of a wheeled mobile robot

In this paper, we propose a new application of the adaptive critic methodology for the feedback control of wheeled mobile robots, based on a critic signal provided by a neural network (NN). The adaptive critic architecture uses a high-level supervisory NN adaptive critic element (ACE), to generate the reinforcement signal to optimise the associative search element (ASE), which is applied to approximate the non-linear functions of the mobile robot. The proposed tracking controller is derived from Lyapunov stability theory and can guarantee tracking performance and stability. A series of computer simulations have been used to emulate the performance of the proposed solution for a wheeled mobile robot.     

PEPT study of particle motion for different riser exit geometries

Laboratory and industrial risers are equipped with exits of many different layouts, and numerous publications discuss the influence of riser exit geometry on local and overall solids hydrodynamics in the riser. The present paper reviews literature findings--mostly based upon indirect experimental techniques and often somewhat contradictory, Direct measurement of particle velocity and particle occupancy near and in the riser exit provide a better indication of the effect of riser exit geometry. Positron Emission Particle Tracking （PEPT） was used in this work for the first time to investigate the exit region of the riser, An abrupt or sharp exit causes particles to be knocked out of the gas flow, so forming a recirculation or reflux region in the upper part of the riser. This is much less pronounced with a curved or gradual exit.     

压缩域直扩测控通信信号伪码跟踪方法研究

压缩感知理论已经在测控(TTC)通信相关领域有初步应用尝试,能够有效降低采样率和数据率,但同时其重构算法复杂度偏高、计算资源消耗过大,这与系统的实时性要求之间存在矛盾。论文基于直扩测控(DS TTC)通信信号稀疏性,对传统伪码跟踪环进行改进,提出一种基于随机解调压缩采样的压缩域伪码跟踪环。该环路不再需要进行信号重构处理,能够直接从直扩测控通信信号的压缩采样值中提取伪码(PN)延时相位信息。该文首先深入分析所提出环路模型及其鉴别特性,其次通过研究交叉噪声特性,对跟踪精度进行理论分析。分析和仿真结果表明,所提出环路能够在压缩域实现伪码延时相位跟踪。该环路可以应用在基于压缩感知的直扩、混扩信号处理等相关领域,具有一定工程应用价值。