Research and Design of a Routing Protocol in Large-Scale Wireless Sensor Networks

无线传感器网络，作为全球未来十大技术之一，集成了传感器技术、嵌入式计算技术、分布式信息处理和自组织网技术，可实时感知、采集、处理、传输网络分布区域内的各种信息数据，在军事国防、生物医疗、环境监测、抢险救灾、防恐反恐、危险区域远程控制等领域具有十分广阔的应用前景。 本文研究分析了无线传感器网络的已有路由协议，并针对大规模的无线传感器网络设计了一种树状路由协议，它根据节点地址信息来形成路由，从而简化了复杂繁冗的路由表查找和维护，节省了不必要的开销，提高了路由效率，实现了快速有效的数据传输。 为支持此路由协议本文提出了一种自适应动态地址分配算——ADAR（AdaptiveDynamicAddre...As one of the ten high technologies in the future, wireless sensor network, which is the integration of micro-sensors, embedded computing, modern network and Ad Hoc technologies, can apperceive, collect, process and transmit various information data within the region. It can be used in military defense, biomedical, environmental monitoring, disaster relief, counter-terrorism, remote control of haz...学位：工学硕士院系专业：信息科学与技术学院通信工程系_通信与信息系统学号：2332007115216

SOLUTIONS OF CONSERVATION LAW SYSTEMS

The work covers the mathematical models of the physical systems described by the differential equations expressing the conservation properties. The aim is to reveal and analyse the basic mathematical structures connected with the problems of approximated method convergence; to prove the theorems about global solvability of the Cauchy problem for the quasi-linear and semi-linear systems having application in the mathematical physics. The convergence of regular approximated methods to the functional solution of conservation laws at condition of the weak approximation and weak method stability has been substantiated. The possible classes of correctness have been described. The convergence of difference method to the functional solution for the Boltzmann type equations has been substantiated. The solvability on a whole has been proved, and the convergence of approximated methods for the general type non-linear conservation lay systems and for concrete models has been substantiated. The results are used in the Moscow State University, in the Physical-Energetical Institute, in the Institute of Nuclear Power Engineering, in the Institute of Hydrodynamics a.o. The application field: gas dynamics, physical kineticsAvailable from VNTIC / VNTIC - Scientific & Technical Information Centre of RussiaSIGLERURussian Federatio

Forming of ducted axisymmetric supersonic air inlets

Relevance of the research. The efficiency of fuel chemical energy conversion into mechanical motion of a supersonic aircraft is determined by energy losses due to aerodynamic drag of the aircraft and total pressure losses in the air inlet of jet engine. Therefore, ceteris paribus the aircraft with lower level of these losses will be more energy efficient. Significant increase in energy efficiency is expected from the use of axisymmetric isentropic ducted air inlets. In the framework of the non-viscous flow, a numerical method is offered for these air inlets with a contoured central body and a cylindrical shell designing. The main aim of the study. Currently there are no designing methods for axisymmetric isentropic ducted air inlets without elements projecting over a cylindrical body of the aircraft. Therefore, the aim of the study is to develop a methodology for designing such inlets. The methods used in the study. Numerical implementation of the characteristics method for isentropic flow is used. The proposed method involves the decision of two problems. In the first problem a flow line around the given focus point of characteristics is plotted which starts at a break point of central body. In the second problem the rest of the contour is calculated using the reversed flow in an annular nozzle with a cylindrical shell. Simultaneously with the decision of the second problem, the position of the shell is determined. The central body can contain angular points at the edges of the contour. If we use an intermediate flow line then the central body will be smooth. The results. The authors developed the methodology for calculating different axisymmetric supersonic air inlet contours, which geometrical characteristics are uniquely described by the original data

Estimating the Parameters of Traffic Flows on the Basis of Processing of Localization Data on the Movement of Vehicles

The article describes the method of estimating the parameters of transport flows using the two-fluid mathematical model of Herman-Prigogine and developed and based on the proposed method of estimating the parameters of the system on the basis of passive processing of navigation data on the movement of vehicles. The efficiency of the proposed algorithms, mathematical models for estimating the parameters of road traffic flow and system as a whole was confirmed during its testing using a set of tracks on the main highways of Commonwealth of Independent States

Genetic Association Study and Machine Learning to Investigate Differences in Platelet Reactivity in Patients with Acute Ischemic Stroke Treated with Aspirin

Aspirin resistance (AR) is a pressing problem in current ischemic stroke care. Although the role of genetic variations is widely considered, the data still remain controversial. Our aim was to investigate the contribution of genetic features to laboratory AR measured through platelet aggregation with arachidonic acid (AA) and adenosine diphosphate (ADP) in ischemic stroke patients. A total of 461 patients were enrolled. Platelet aggregation was measured via light transmission aggregometry. Eighteen single-nucleotide polymorphisms (SNPs) in ITGB3, GPIBA, TBXA2R, ITGA2, PLA2G7, HMOX1, PTGS1, PTGS2, ADRA2A, ABCB1 and PEAR1 genes and the intergenic 9p21.3 region were determined using low-density biochips. We found an association of rs1330344 in the PTGS1 gene with AR and AA-induced platelet aggregation. Rs4311994 in ADRA2A gene also affected AA-induced aggregation, and rs4523 in the TBXA2R gene and rs12041331 in the PEAR1 gene influenced ADP-induced aggregation. Furthermore, the effect of rs1062535 in the ITGA2 gene on NIHSS dynamics during 10 days of treatment was found. The best machine learning (ML) model for AR based on clinical and genetic factors was characterized by AUC = 0.665 and F1-score = 0.628. In conclusion, the association study showed that PTGS1, ADRA2A, TBXA2R and PEAR1 polymorphisms may affect laboratory AR. However, the ML model demonstrated the predominant influence of clinical features