Bearing fault diagnosis with cascaded space projection and a CNN

Fault diagnosis is essential for the normal and safe operation of dynamic systems. To improve the spatial resolution among multiple channels and the discriminability among categories of the original data collected from actual operating equipments and to further achieve high diagnostic accuracy, this paper proposes a method for fault diagnosis by cascaded space projection (CSP) and a convolutional neural network (CNN) model. First, one of every kind of sample is selected from the original data to calculate the PCA transformation matrices. Second, the original data are expanded to 10 dimensions by the W2C projection matrix provided by Google-image searching, which is the main part of CSP. Third, the ten-dimensional matrix is multiplied by the PCA transformation matrix, which corresponds to its fault type, to make the data more representative by reducing unnecessary dimensions. Finally, the processed data are converted into images to input into a CNN, the backbone structure for fault diagnosis. To verify the effectiveness and reliability of the proposed method, the Case Western Reserve University (CWRU) and Xi’an Jiaotong University (XJTU-SY) rolling bearing datasets are used to perform experiments. Comparison with other methods is carried out to show the superiority of the proposed method. The experimental results demonstrate that the method proposed in this paper can effectively achieve 100% accuracy.     

Combining search space partition and abstraction for LTL model checking

The state space explosion problem is still the key obstacle for applying model checking to systems of industrial size. Abstraction-based methods have been particularly successful in this regard. This paper presents an approach based on refinement of search space partition and abstraction which combines these two techniques for reducing the complexity of model checking. The refinement depends on the representation of each portion of search space. Especially, search space can be refined stepwise to get a better reduction. As reported in the case study, the integration of search space partition and abstraction improves the efficiency of verification with respect to the requirement of memory and obtains significant advantage over the use of each of them in isolation.     

A new method of speech transmission over space time block coded co-operative MIMO–OFDM networks using time and space diversity

Reliable and good quality of service for speech transmission over wireless network has been a major challenge for the communication engineers and researchers. In this paper a new technique of speech compression and transmission using different Daubechies wavelets in a space time block coded co-corporative MIMO–OFDM networks using time and space diversity has been proposed. The main focus has been laid on design and development of wavelet based compression of multimedia signals for cooperative MIMO–OFDM system. We tried to find out various major issues regarding the wavelet compression of a speech signal. These issues include choice of a wavelet, decomposition level and thresholding criteria suitable for speech compression and transmission in co-operative MIMO–OFDM systems. A wavelet based speech compression technique using hard and soft thresholding algorithm has been proposed. The work shows that wavelet compression with QPSK modulation is a promising compression technique in a cooperative MIMO–OFDM system which makes use of the elegant theory of wavelets. The performance has been evaluated using mean square error, peak signal to noise ratio, compression ratio, bit error rate, and retained signal energy. It has been found that the transmitted speech signal is retrieved well under noisy conditions at higher order Daubechies wavelets. From the results it is clear that proposed technique aims at a radio access technology that can provide service performance comparable to that of current fixed Line accesses. To evaluate the performance of the proposed method, various performance parameters have been compared with previously implemented techniques and it has been found that the proposed work shows better performance as compared to the already existing techniques.     

Finite difference method for time–space linear and nonlinear fractional diffusion equations

ABSTRACT

In this paper a finite difference method is presented to solve time–space linear and nonlinear fractional diffusion equations. Specifically, the centred difference scheme is used to approximate the Riesz fractional derivative in space. A trapezoidal formula is used to solve a system of Volterra integral equations transformed from spatial discretization. Stability and convergence of the proposed scheme is discussed which shows second-order accuracy both in temporal and spatial directions. Finally, examples are presented to show the accuracy and effectiveness of the schemes.     

Refinement of flexible space–time finite element meshes and discontinuous Galerkin methods

In this paper we present an algorithm to refine space–time finite element meshes as needed for the numerical solution of parabolic initial boundary value problems. The approach is based on a decomposition of the space–time cylinder into finite elements, which also allows a rather general and flexible discretization in time. This also includes adaptive finite element meshes which move in time. For the handling of three-dimensional spatial domains, and therefore of a four-dimensional space–time cylinder, we describe a refinement strategy to decompose pentatopes into smaller ones. For the discretization of the initial boundary value problem we use an interior penalty Galerkin approach in space, and an upwind technique in time. A numerical example for the transient heat equation confirms the order of convergence as expected from the theory. First numerical results for the transient Navier–Stokes equations and for an adaptive mesh moving in time underline the applicability and flexibility of the presented approach.     

Lost in space? Cognitive fit and cognitive load in 3D virtual environments

In this paper, we explore how visual representations of information in 3D virtual environments (3DVEs) supports both individual and shared understanding, and consequently contribute to group decision making in tasks with a strong visual component. We integrate insights from cognitive fit theory and cognitive load theory in order to formulate hypotheses about how 3DVEs can contribute to individual understanding, shared understanding, and group decision making. We discuss the results of an experiment in which 192 participants, in 3-person teams, were asked to select an apartment. As proposed by cognitive fit theory, our results indicate that 3DVEs are indeed more effective in supporting individual understanding than 2D information presentations. Next, in line with cognitive load theory, the static presentation of 3D information turns out to be more effective in supporting shared understanding and group decision making than an immersive 3DVE. Our results suggest that although the 3DVE capabilities of realism, immersion and interactivity contribute to individual understanding, these capabilities combined with the interaction and negotiation processes required for reaching a shared understanding (and group decision), increases cognitive load and makes group processes inefficient. The implications of this paper for research and practice are discussed.     

Cloud service: automatic construction and evolution of software process problem-solving resource space

The automatic construction of networked software and its ability to adapt to dynamic environments are important for cloud services that depend upon these capabilities. We provide a cloud service that browses the stacks of problem solution resources produced in the software process (SP for short) by organizing them into a structured Resource Space according to domain topics. Efforts are made to provide the cloud service with the ability of automatic construction of the SP problem-solving Resource Space, including extracting domain topics from document resources with the TDDF algorithm, transforming the topics into several categories to form the logic Resource Space, and deploying the Resource Space in a Peer-to-Peer (P2P for short) network. We also expect to achieve the online service evolution such as adjusting the resource pool and refining the Resource Space Model (RSM for short) by continuously understanding and adapting to its surroundings. Empirical cases are finally presented. Our investigation promotes the adaptability of cloud services to their changing environment.     

Gravitational contributions to pioneer space probe decelerations and the time-delay-doppler “Relativistic Confusion”

Relativistic corrections to the calculations of Pioneer 10 space probe motion (mentioned but not sufficiently detailed by the authors of the observation [1]) are analyzed basing on the assumption that the Solar System gravity is described by the Kerr metric. The geodesic equation for ecliptic-plane motion of the space probe is solved, and all specific gravitational corrections to the probe acceleration are computed up to the 2nd order of the small parameters; values of all general-relativistic corrections are found to be small as compared to the Pioneer anomaly. On the contrary, a study of kinematic effects in the tangent space based on the Quaternion Relativity formalism (the quaternion square root of the Kerr space-time interval) shows that the probe’s signal frequency distorted by relativistic time-scale stretching, when taken for a Doppler portion of the frequency shift, may result in experimental detection of an additional acceleration of the probe. The value of this apparent “correction” (though steadily dropping with distance) is found to be quite close to that of the Pioneer 10 reported acceleration residual.     

A metric space for computer programs and the principle of computational least action

We define a normed metric space for computer programs and derive from it the Principle of Computational Least Action. In our model, programs follow trajectories determined by Newton’s equation of motion in an abstract computational phase space and generate computational action as they evolve. A program’s action norm is the L ₁-norm of its action function, and its distance from other programs is the distance derived from the action norm. The Principle of Computational Least Action states the goal of performance optimization as finding the program with the smallest action norm. We illustrate this principle by analyzing a simple program.

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What makes a space invader? Passenger perceptions of personal space invasion in aircraft travel

Abstract

The invasion of personal space is often a contributory factor to the experience of discomfort in aircraft passengers. This paper presents a questionnaire study which investigated how air travellers are affected by invasions of personal space and how they attempt to adapt to, or counter, these invasions. In support of recent findings on the factors influencing air passenger comfort, the results of this study indicate that the invasion of personal space is not only caused by physical factors (e.g. physical contact with humans or objects), but also other sensory factors such as noise, smells or unwanted eye contact. The findings of this study have implications for the design of shared spaces.

Practitioner Summary: This paper presents a questionnaire study which investigated personal space in an aircraft environment. The results highlight the factors which affect the perception of personal space invasion in aircraft and can therefore inform the design of aircraft cabin environments to enhance the passenger experience.     

Java内存不足PermGen space错误探究

Java程序运行时可能会遇到java.lang.OutOfMemoryError:PermGen space错误;JavaEE服务器(如tomcat、jboss等)在加载war包或ear包时也可能会出现这种错误,这些都是由于永久保存区域内存不足导致的。本文分析了Java程序的运行机制和JVM的内存结构,解释了什么是permanent generation space,分析了PermGen space错误的常见原因,并给出避免这一错误的解决办法。     

Sense and sidedness in the graphics pipeline via a passage through a separable space

Computer graphics is ostensibly based on projective geometry. The graphics pipeline—the sequence of functions applied to 3D geometric primitives to determine a 2D image—is described in the graphics literature as taking the primitives from Euclidean to projective space, and then back to Euclidean space. This is a weak foundation for computer graphics. An instructor is at a loss: one day entering the classroom and invoking the established and venerable theory of projective geometry while asserting that projective spaces are not separable, and then entering the classroom the following week to tell the students that the standard graphics pipeline performs clipping not in Euclidean, but in projective space—precisely the operation (deciding sidedness, which depends on separability) that was deemed nonsensical. But there is no need to present Blinn and Newell’s algorithm (Comput. Graph. 12, 245–251, 1978; Commun. ACM 17, 32–42, 1974)—the crucial clipping step in the graphics pipeline and, perhaps, the most original knowledge a student learns in a fourth-year computer graphics class—as a clever trick that just works. Jorge Stolfi described in 1991 oriented projective geometry. By declaring the two vectors and distinct, Blinn and Newell were already unknowingly working in oriented projective space. This paper presents the graphics pipeline on this stronger foundation.

The space of EDF deadlines: the exact region and a convex approximation

It is well known that the performance of computer controlled systems is heavily affected by delays and jitter occurring in the control loops, which are mainly caused by the interference introduced by other concurrent activities. A common approach adopted to reduce delay and jitter in periodic task systems is to decrease relative deadlines as much as possible, but without jeopardizing the schedulability of the task set. In this paper, we formally characterize the region of admissible deadlines so that the system designer can appropriately select the desired values to maximize a given performance index defined over the task set. Finally we also provide a sufficient region of feasible deadlines which is proved to be convex.

Trajectory control of a two DOF rigid–flexible space robot by a virtual space vehicle

Model based control schemes use inverse dynamics of the robot arm to produce the main torque component necessary for trajectory tracking. For a model-based controller one is required to know the model parameters accurately. This is a very difficult job especially if the manipulator is flexible. This paper presents a control scheme for trajectory control of the tip of a two arm rigid–flexible space robot, with the help of a virtual space vehicle. The flexible link is modeled as an Euler–Bernoulli beam. The developed controller uses the inertial parameters of the base of the space robot only. Bond graph modeling is used to model the dynamics of the system and to devise the control strategy. The efficacy of the controller is shown through simulated and animation results.     

How much is built? Quantifying and interpreting patterns of built space from different data sources

Land-use/cover change (LUCC) has emerged as a crucial component of applied research in remote sensing. This work compares two methodologies, based on two data sources, for assessing amounts of land transformed from open to built space in three regions in Israel. We use a decision-tree methodology to define open and built space from remotely sensed (RS) Landsat data and a geographic information systems (GIS) platform for analysing 1:50 000 scale survey maps. The methodologies are developed independently, used to quantify and characterize the spatial pattern of built space, and then analysed for their strengths and weaknesses. We then develop a method for combining the built area maps derived from each methodology, capitalizing on the strengths of each. The RS methodology had higher omission errors for built space in areas with high vegetation levels and low-density exurban development, but high commission errors in the arid region. The GIS analysis generally had fewer errors, although systematically missed built surfaces that were not specifically buildings or roads, as well as structures intentionally omitted from the maps. We recommend using maps for baseline estimates whenever possible and then complementing the estimates with clusters of built areas identified with the RS methodology. The results of this comparative study are relevant to both researchers and practitioners who need to understand the strengths and weaknesses of mapping techniques they are using.     

Solutions of nonlinear delay and advanced partial difference equations in the space lN×N1

A functional analytic method is used to prove a general theorem which establishes the existence and the uniqueness of a solution of a class of nonlinear delay and advanced partial difference equations in the Banach space l_N×N¹. The proof of the theorem has a constructive character, which enables us to obtain a bound of the solution and a region, depending on the initial conditions and the parameters of the equation under consideration, where this solution holds. Some known nonlinear partial difference equations, which appear in applications, are studied as particular cases of the theorem.     

Equivalence of classicality and separability based on P phase–space representation of symmetric multiqubit states

Classical and quantum world views differ in peculiar ways. Understanding decisive quantum features—for which no classical explanation exist—and their interrelations is of foundational interest. Moreover, recognizing non-classical features carries practical significance in information processing tasks as it offers insights as to why quantum protocols work better than their classical counterparts. We focus here on two celebrated notions of non-classicality viz., negativity of P phase–space representation and entanglement in symmetric multiqubit systems. We prove that they imply each other.     

On the space–time of optimal, approximate and streaming algorithms for synopsis construction problems

Synopses construction algorithms have been found to be of interest in query optimization, approximate query answering and mining, and over the last few years several good synopsis construction algorithms have been proposed. These algorithms have mostly focused on the running time of the synopsis construction vis-a-vis the synopsis quality. However the space complexity of synopsis construction algorithms has not been investigated as thoroughly. Many of the optimum synopsis construction algorithms are expensive in space. For some of these algorithms the space required to construct the synopsis is significantly larger than the space required to store the input. These algorithms rely on the fact that they require a smaller “working space” and most of the data can be resident on disc. The large space complexity of synopsis construction algorithms is a handicap in several scenarios. In the case of streaming algorithms, space is a fundamental constraint. In case of offline optimal or approximate algorithms, a better space complexity often makes these algorithms much more attractive by allowing them to run in main memory and not use disc, or alternately allows us to scale to significantly larger problems without running out of space. In this paper, we propose a simple and general technique that reduces space complexity of synopsis construction algorithms. As a consequence we show that the notion of “working space” proposed in these contexts is redundant. This technique can be easily applied to many existing algorithms for synopsis construction problems. We demonstrate the performance benefits of our proposal through experiments on real-life and synthetic data. We believe that our algorithm also generalizes to a broader range of dynamic programs beyond synopsis construction. Sudipto Guha’s research supported in part by an Alfred P. Sloan Research Fellowship and by NSF Awards CCF-0430376, CCF-0644119.A preliminary version of the paper appeared as “Space efficiency in synopsis construction algorithms”, VLDB Conference 2005, Trondheim, [19].     

Strong 2015–2016 El Niño and implication to global ecosystems from space data

During 2015, sea surface temperature (SST) in the central tropical Pacific (TP) was warmer than normal, what indicated about the potential for the development of El Niño Southern Oscillation (ENSO). By December 2015, El Niño intensified when SST anomaly in the Niño-3.4 tropical Pacific area reached +2.9 °C, which indicated about the strongest event of the past 36 years. El Niño normally impacts weather, ecosystems, and socioeconomics (agriculture, fisheries, energy, human health, water resource etc.) on all continents. However, the current El Niño is much stronger than the recent strong 1997–1998 event. Therefore, this paper investigates how the strength of El Niño impacts world ecosystems and which areas are affected. The vegetation health (VH) method and 36-year of its data have been used as the criteria of the impact. Specifically, the paper investigates VH-ENSO teleconnection, focusing on estimation of vegetation response to El Niño intensity and transition of the impact from boreal winter to spring and summer. Two types of ecosystem response were identified. In boreal winter, ecosystems of northern South America, southern Africa, eastern Australia, and Southeast Asia experienced strong vegetation stress, which will negatively affect agriculture, energy, and water resources. In Argentina, southeastern USA and the Horn of Africa ecosystem response is opposite. One of the worst disasters associated with ENSO is drought. The advantages of this study are in derivation of vegetation response to moisture, thermal, and combined conditions including an early detection of drought-related stress. For the first time, ENSO impact was evaluated based on all events with |SSTa|> 0.5 ºC and >2.0 ºC. The current strong El Niño has already triggered drought in Brazil, southern Africa, southeastern Asia, and eastern Australia during December–February. Such conditions will be transitioned from boreal winter to spring but not to summer 2016, except for two regions: northern Brazil and southeastern Asia.