基于ANDROID的LTE冰水情自动监测客户端设计

在冰水情信息监测工作中,数据实时远程传送和现场远程实时监控、告警是能否准确实现预测、报警的关键因素.随着通信技术的发展,LTE(第四代移动通信技术)系统已大规模商用,在基于LTE网络架构的冰水情灾害自动监测设备中,利用大带宽高传输速率的优势,视频、图像数据的实时传送成为现实.在应用中,远程智能手机客户端的开发成为一个重要问题.基于Android(安卓手机操作系统)系统的LTE冰水情自动监测客户端具备较强的稳定性、可靠性、可移植性,能够在很好的在满足用户移动性的同时,实现远程监控、告警功能.能够为LTE冰水情灾害自动监测设备远程用户端提供一个有效的解决方案.     

Motion correction of a statistically uncertain system under communication constraints

The problem of motion correction of a controlled system is considered. It is required to minimize a terminal functional under statistical uncertainty of the disturbance and incomplete information about the state of the system. Reachable sets of filtering and prediction equations are used; these sets are uniquely determined for a given time moment by the realizations of the observed signal and the chosen control. A modification of the correction problem under communication constraints is considered, in which the bounded capacity of the digital data transmission channel is taken into account. It is assumed that the object is equipped with a computing facility that can remember the measured information, process it with a high level of accuracy, transmit it, and receive encoded signals via communication channels. Signals in the form of words of bounded length consisting of integers come to the control and information processing center (CIPC) at discrete time moments. For simplicity, the communication channel is assumed to be noise- and delay-free. The encoding device in the communication channel is used for transmitting information about the measured parameters of the object to the CIPC and the control action from the CIPC to the object. At the CIPC, the information about the parameters is decoded and used for calculating the correction moments and optimal control. Relations between the reconstruction accuracy of the measured parameters and the optimal value of the functional are obtained as well as between the length of the transmitted word and the transmission frequency. Several results are exemplified.     

Topology design for on-demand dual-path routing in wireless networks

One way to achieve reliability with low-latency is through multi-path routing and transport protocols that build redundant delivery channels (or data paths) to reduce end-to-end packet losses and retransmissions. However, the applicability and effectiveness of such protocols are limited by the topological constraints of the underlying communication infrastructure. Multiple data delivery paths can only be constructed over networks that are capable of supporting multiple paths. In mission-critical wireless networks, the underlying network topology is directly affected by the terrain, location and environmental interferences, however the settings of the wireless radios at each node can be properly configured to compensate for these effects for multi-path support. In this work we investigate optimization models for topology designs that enable end-to-end dual-path support on a distributed wireless sensor network. We consider the case of a fixed sensor network with isotropic antennas, where the control variable for topology management is the transmission power on network nodes. For optimization modeling, the network metrics of relevance are coverage, robustness and power utilization. The optimization models proposed in this work eliminate some of the typical assumptions made in the pertinent network design literature that are too strong in this application context.     

Synchronized states in a ring of four mutually coupled oscillators and experimental application to secure communications

Data encryption has become increasingly important for many applications including phone, internet and satellite communications. Considering the desirable properties of ergodicity and high sensitivity to initial conditions and control parameters, chaotic signals are suitable for encryption systems. Chaotic encryption systems generally have high speed with low cost, which makes them better candidates than many traditional ciphers for multimedia data encryption. In this paper, analytical and numerical methods as well as experimental implementation are used to prove partial and complete synchronized states in a ring of four autonomous oscillators in their chaotic states. Application to secure communication is discussed.     

Approximate reasoning and finite state machines to the detection of actions in video sequences

In this paper a novel approach for recognizing actions in video sequences is presented, where the information obtained from the segmentation and tracking algorithms is used as input data. First of all, the fuzzification of input data is done and this process allows to successfully manage the uncertainty inherent to the information obtained from low-level and medium-level vision tasks, to unify the information obtained from different vision algorithms into a homogeneous representation and to aggregate the characteristics of the analyzed scenario and the objects in motion. Another contribution is the novelty of representing actions by means of an automaton and the generation of input symbols for the finite automaton depending on the comparison process between objects and actions, i.e., the main reasoning process is based on the operation of automata with capability to manage fuzzy representations of all video data. The experiments on several real traffic video sequences demonstrate encouraging results, especially when no training algorithms to obtain predefined actions to be identified are required.     

Using a Volterra system model to analyze nonlinear response in video-packet transmission over IP networks

This paper presents a Volterra system-based nonlinear analysis of video-packet transmission over IP networks. With the Volterra system, which is applicable to the modeling of nonlinear dynamic systems from sets of input and output data, we applied a time-series analysis of measured data for network response evaluation. In a test-bed connected to the Internet, we measured two parameters: the time intervals between consecutive packets from a video server at the originating side, and the transmission time of packets between originating and terminating sides. We used these as input and output data for the Volterra system and confirmed that the relative error of this model changed with conditions of network systems, which suggested that the packet transmission process affected the degree of nonlinearity of the system. The proposed method can reproduce the time-series responses observed in video-packet transmission over the Internet, reflecting nonlinear dynamic behaviors such that the obtained results provided us with an effective depiction of network conditions at different times.     

Progressive transmission of subdivision surfaces

Triangle meshes are a standard representation for surface geometry in computer graphics and virtual reality applications. To achieve high realism of the modeled objects, the meshes typically consist of a very large number of faces. For broadcasting virtual environments over low-bandwidth data connections like the Internet it is highly important to develop efficient algorithms which enable the progressive transmission of such large meshes. In this paper we introduce a special representation for storing and transmitting meshes with subdivision connectivity which allows random access to the detail information. We present algorithms for the decomposition and the reconstruction of subdivision surfaces. With this technique, the receiver can reconstruct smooth approximations of the original surface from a rather small amount of data received.     

A Particle Filtering Approach for Tracking an Unknown Number of Objects with Dynamic Relations

In recent years there has been a growing interest on particle filters for solving tracking problems, thanks to their applicability to problems with continuous, non-linear and non-Gaussian state spaces, which makes them more suited than hidden Markov models, Kalman filters and their derivations, in many real world tasks. Applications include video surveillance, sensor fusion, tracking positions and behaviors of moving objects, situation assessment in civil and bellic scenarios, econometric and clinical data series analysis. In many environments it is possible to recognize classes of similar entities, like pedestrians or vehicles in a video surveillance system, or commodities in econometric. In this paper, a relational particle filter for tracking an unknown number of objects is presented which exploits possible interactions between objects to improve the quality of filtering. We will see that taking into account relations between objects will ease the tracking of objects in presence of occlusions and discontinuities in object dynamics. Experimental results on a benchmark data set are presented.     

A new table of permutation codes

Permutation codes (or permutation arrays) have received considerable interest in recent years, partly motivated by a potential application to powerline communication. Powerline communication is the transmission of data over the electricity distribution system. This environment is rather hostile to communication and the requirements are such that permutation codes may be suitable. The problem addressed in this study is the construction of permutation codes with a specified length and minimum Hamming distance, and with as many codewords (permutations) as possible. A number of techniques are used including construction by automorphism group and several variations of clique search based on vertex degrees. Many significant improvements are obtained to the size of the best known codes.     

Learning objects and objectives towards automatic learning construction

This paper presents a method that creates instructionally sound learning experiences by means of learning objects. The method uses a mathematical model, distinguishes two kinds of Learning Objects Properties and proceeds in two major steps: first, the Course Creation is transformed into Set Covering under specific requirements derived from Learning Theories and practice; second, the Alternative Learning Sources are selected by using a similarity measure specially defined for this purpose.     

Some heuristics about the ecosystem of mathematics research data

Like in other sciences, research data play a growing role in mathematics, but in contrast to classical objects like measurements in physics they are much more heterogeneous. They may take the shape of abstract objects like the collection of integer sequences in OEIS, algorithms and their implementations as mathematical software, libraries of test problems or statistical data. From an infrastructure viewpoint, which aims at sustainable and connected data repositories which facilitate researchers to use existing information efficiently, it is essential to define an appropriate framework that allows not just storage but also connection and retrieval of the various types of data. Recently, there have been promising attempts to define standards for mathematical software, but the general task remains a big challenge, which is also addressed within the recently initiated GDML working group of the IMU. This is especially important in the fields of applied mathematics where research is often connected to research data originating from applications. The goal of this talk is a first attempt to analyse the diverse ecosystem of research data based on reference data from zbMATH. This approach has worked quite well for mathematical software, resulting in the formation of the swMATH database. Though reference data involve always a bias, the collected information of about 16 million reference data in zbMATH may be useful to identify the recent needs of researchers in different fields pertaining mathematical research data, and we discuss several aspects of such an analysis. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Analysis of an MMPP/G/1/K queue with queue length dependent arrival rates,and its application to preventive congestion control in telecommunication networks

Recently telecommunication networks have been designed in order to transfer all types of information services such as voice, data and video. Next generation wireless networks has been developed to integrate the existing technologies and to support comprehensive services. As the traffics of diverse services have properties of timecorrelation and burstiness, unpredictable statistical fluctuation of traffic streams may cause congestion. To suggest a congestion control scheme which controls arrival rates according to the queue length, we consider an MMPP/G/1/K queue with queue length dependent arrival rates. The effect of system parameters on performance measures also is explained with the numerical examples.     

New eyes for building models from video

Models of real-world objects and actions for use in graphics, virtual and augmented reality and related fields can only be obtained through the use of visual data and particularly video. This paper examines the question of recovering shape models from video information. Given video of an object or a scene captured by a moving camera, a prerequisite for model building is to recover the three-dimensional (3D) motion of the camera which consists of a rotation and a translation at each instant. It is shown here that a spherical eye (an eye or system of eyes providing panoramic vision) is superior to a camera-type eye (an eye with restricted field of view such as a common video camera) as regards the competence of 3D motion estimation. This result is derived from a geometric/statistical analysis of all the possible computational models that can be used for estimating 3D motion from an image sequence. Regardless of the estimation procedure for a camera-type eye, the parameters of the 3D rigid motion (translation and rotation) contain errors satisfying specific geometric constraints. Thus, translation is always confused with rotation, resulting in inaccurate results. This confusion does not happen for the case of panoramic vision. Insights obtained from this study point to new ways of constructing powerful imaging devices that suit particular tasks in visualization and virtual reality better than conventional cameras, thus leading to a new camera technology. Such new eyes are constructed by putting together multiple existing video cameras in specific ways, thus obtaining eyes from eyes. For a new eye of this kind we describe an implementation for deriving models of scenes from video data, while avoiding the correspondence problem in the video sequence.     

Long Time Motion of NLS Solitary Waves in a Confining Potential

We study the motion of solitary-wave solutions of a family of focusing generalized nonlinear Schr?dinger equations with a confining, slowly varying external potential, V(x). A Lyapunov-Schmidt decomposition of the solution combined with energy estimates allows us to control the motion of the solitary wave over a long, but finite, time interval. We show that the center of mass of the solitary wave follows a trajectory close to that of a Newtonian point particle in the external potential V(x) over a long time interval. Communicated by Rafael D. Benguria Submitted: March 7, 2005 Accepted: January 9, 2006     

An Interactive Icon Index: Images of the Outer Planets

Abstract

We are interested in the exploratory analysis of large collections of complex objects. As an example, we are studying a large collection of digital images that has nearly 30,000 members. We regard each image in the collection as an individual observation. To facilitate our study we construct an index of the images in the collection. The index uses a small copy of each image (an icon or a “thumbnail”) to represent the full-size version. A large number of these thumbnails are laid out in a workstation window. We can interactively arrange and rearrange the thumbnails within the window. For example, we can sort the thumbnails by the values of a function computed from them or by the values of data associated with each of them. By the use of specialized equipment (a single-frame video disk recorder/player), we can instantly access any individual full-size image in the collection as a video image. We regard our software as an early development of statistical exploratory tools for studying collections of images and other complex objects in the same way we routinely study batches of numbers. We expect that the concept of a visual index will extend to other collections of complex objects besides images, for example, time series, functions, and text.     

城市CIS物理关联脆弱性的动态分析方法

本文以城市关键基础设施系统(Critical Infrastructure System, CIS)为研究对象,将关键基础设施之间组成的复杂物理网络划分为个体层面、中观层面和系统层面三种类型,从物理关联势差的角度分析了城市CIS内部物理关联机理。根据城市CIS物理关联特性,引入元胞自动机(Cellular Automata, CA),以一种物理资源为主导建立模型,采用“自底向上”的方法,从微观关键基础设施活动推出宏观城市CIS表现。选取元胞连通性、元胞正常状态变化率和传输效率作为脆弱性评估指标,估算不同时间点城市CIS脆弱性的动态变化,实现物理关联脆弱性的动态分析,并运用加权平均值作为一段时间内城市CIS脆弱值。最后,以S城市为例,对物理关联脆弱性动态分析方法的合理性和有效性进行验证,评估结果为城市CIS保护提供支持。     

Time-dependent moments of the counts on a BMAP

Consider a batch Markovian arrival process (BMAP) as a counting process over an underlying Markov process representing the state of environment. Such a process is useful as a model of correlated inputs, that is, burst traffics made of video and voice, for example. We consider Laplace transformation of the first and second factorial moments of the counts of the BMAP. From this, we get the eigenvalue expression for these moments without assuming distinct eigenvalues of the infinitesimal generator. In this formula, matrix exponential functions are replaced by ordinary exponentials, and the exact time-dependent form of the moments are also obtained. This seems to be profitable for model fitting.     

Secure state estimation for complex networks with multi-channel oriented round robin protocol

This paper focuses on the secure state estimation problem for complex networks (CNs) which are compromised by deception attack and constrained with limited communication resource. Firstly, a multi-channel oriented round robin (RR) protocol is proposed to schedule the data transferred over the communication network consisting of multiple transmission channels. The extended RR protocol can not only avoid the data collision caused by limited communication resource, but also fully utilize the sliced network bandwidth. Then, a state estimation error model is constructed by further considering the influence of deception attack. Following the model, efficient state estimators are designed based on analyzing the sufficient conditions that assuring the stability of the formulated state estimation error system. Finally, numerical results are presented to validate the theoretical outcomes.     

Determining angular frequency from images of rotating objects via a generalized fast Fourier transform

In certain real-world applications, one needs to estimate the angular frequency of a spinning object. We consider the image processing problem of estimating this rate of rotation from a video of the object taken by a camera aligned with the axis of rotation. For many types of spinning objects, this problem can be addressed with existing techniques: simply register two consecutive video frames. We focus, however, on objects whose shape and intensity changes greatly from frame to frame, such as spinning plumes of plasma that emerge from a certain type of spacecraft thruster. To estimate the angular frequency of such objects, we introduce the Geometric Sum Transform (GST), a new rotation-based generalization of the discrete Fourier transform (DFT). Taking the GST of a given video produces a new sequence of images, the most coherent of which corresponds to the object’s true rate of rotation. After formally demonstrating this fact, we provide a fast algorithm for computing the GST which generalizes the decimation-in-frequency approach for performing a Fast Fourier Transform (FFT). We further show that computing a GST is, in fact, mathematically equivalent to computing a system of DFTs, provided one can decompose each video frame in terms of an eigenbasis of a rotation operator. We conclude with numerical experimentation.     

Measuring the efficiency of highway maintenance contracting strategies: A bootstrapped non-parametric meta-frontier approach

Highly deteriorated US road infrastructure, major budgetary restrictions and the significant growth in traffic have led to an emerging need for improving performance of highway maintenance practices. Privatizing some portions of road maintenance operations by state Departments of Transportation (DOTs) under the auspices of performance-based contracts has been one of the innovative initiatives in response to such a need. This paper adapts the non-parametric meta-frontier framework to the two-stage bootstrapping technique to develop an analytical approach for evaluating the relative efficiency of two highway maintenance contracting strategies. The first strategy pertains to the 180 miles of Virginia’s Interstate highways maintained by Virginia DOT using traditional maintenance practices. The second strategy pertains to the 250 miles of Virginia’s Interstate highways maintained via a Public Private Partnership using a performance-based maintenance approach. The meta-frontier approach accounts for the heterogeneity that exists among different types of highway maintenance contracts due to different limitations and regulations. The two-stage bootstrapping technique accounts for the large set of uncontrollable factors that affect the highway deterioration processes. The preliminary findings, based on the historical data for the state of Virginia, suggest that road authorities (counties) that have used traditional contracting for transforming the maintenance expenditures into the improvement of the road conditions seem to be more efficient than road authorities that have used the performance-based contracting. This paper recommends that road authorities use hybrid contracting approaches that include best practices of both traditional and performance-based highway maintenance contracting.