Time-varying Objects Research Articles

Governance with multiple objectives: Evidence from top executive turnover in China

We examine the relationship between Chief Executive Officer (CEO) turnover and the performance of listed Chinese firms and obtain two results. First, we find a negative relationship between the level of pre-turnover profitability and CEO turnover when firms are incurring financial losses, but no such relationship when they are making profits. Second, there is an improvement in post-turnover profitability in loss-making firms, but no such improvement in profit-making firms. These results indicate the existence of a time-varying objective function, whereby shareholders have a greater incentive to discipline their CEOs on the basis of financial performance when their firms are incurring financial losses rather than profits.

Improved k–t BLAST and k–t SENSE using FOCUSS

The dynamic MR imaging of time-varying objects, such as beating hearts or brain hemodynamics, requires a significant reduction of the data acquisition time without sacrificing spatial resolution. The classical approaches for this goal include parallel imaging, temporal filtering and their combinations. Recently, model-based reconstruction methods called k–t BLAST and k–t SENSE have been proposed which largely overcome the drawbacks of the conventional dynamic imaging methods without a priori knowledge of the spectral support. Another recent approach called k–t SPARSE also does not require exact knowledge of the spectral support. However, unlike k–t BLAST/SENSE, k–t SPARSE employs the so-called compressed sensing (CS) theory rather than using training. The main contribution of this paper is a new theory and algorithm that unifies the abovementioned approaches while overcoming their drawbacks. Specifically, we show that the celebrated k–t BLAST/SENSE are the special cases of our algorithm, which is asymptotically optimal from the CS theory perspective. Experimental results show that the new algorithm can successfully reconstruct a high resolution cardiac sequence and functional MRI data even from severely limited k–t samples, without incurring aliasing artifacts often observed in conventional methods.

TheGALEXUltraviolet Variability Catalog

We present version 1.0 of the NASA Galaxy Evolution Explorer (GALEX) ultraviolet variability (GUVV) catalog, which contains information on 84 time-variable and transient sources gained with simultaneous near-ultraviolet (NUV) and far-ultraviolet (FUV) photometric observations. These time-variable sources were serendipitously revealed in the various 12 diameter star fields currently being surveyed by the GALEX satellite in two ultraviolet bands (NUV 1750–2750 Å, FUV 1350–1750 Å) with limiting AB magnitudes of 23–25. The largest amplitude variable objects currently detected by GALEX are M dwarf flare stars, which can brighten by 5–10 mag in both the NUV and FUV bands during short-duration (<500 s) outbursts. Other types of large-amplitude ultraviolet variable objects include ab-type RR Lyrae stars, which can vary periodically by 2–5 mag in the GALEX FUV band. This first GUVV catalog lists galactic positions and possible source identifications in order to provide the astronomical community with a list of time-variable objects that can now be repeatedly observed at other wavelengths. We expect the total number of time-variable source detections to increase as the GALEX mission progresses, such that later version numbers of the GUVV catalog will contain substantially more variable sources.

A MATHEMATICAL THEORY FOR LEARNING, AND ITS APPLICATION TO TIME-VARYING COMPUTED TOMOGRAPHY

The brain has evolved to enable organisms to survive in a complicated and dynamic world. Its operation is based upon a priori models of the environment which are adapted, during learning, in response to new and changing stimuli. The same qualities that make biological learning mechanisms ideal for organisms make their underlying mathematical algorithms ideal for certain technological applications, especially those concerned with understanding the physical processes giving rise to complicated data sets. In this paper, we offer a mathematical model for the underlying mechanisms of biological learning, and we show how this mathematical approach to learning can yield a solution to the problem of imaging time-varying objects from X-ray computed tomographic (CT) data. This problem relates to several practical aspects of CT imaging including the correction of motion artifacts caused by patient movement or breathing.

Balance set and Pareto solutions in linear space with application to ongoing optimal resource allocation, investment planning, production, and control problems with multiple objectives

The notion of balance set is extended onto infinite-dimensional linear spaces. For multiobjective problems of ongoing optima, resource allocation, continuing investment planning with risk forecasting, optimal production models with time-varying objectives, the notion of finite causality is introduced leading to separable programs and sequential (not necessarily convergent) balance and Pareto sets. Selector sequences (or functions for continuous models) are proposed to determine particular Pareto solutions obtained from infinite sequences of the balance set equations. The method is extended onto multicriteria, global optimal control problems, and the use of Schauder bases is made for obtaining monotonic approximations to the sets of balance points and Pareto solutions. An algorithm is tien proposed for computing those approximations and illustrated by a practical example of the bicriteria min-time, min-fuel vertical soft landing problem to facilitate software design.

The influence of crustal magnetism on the solar wind interaction with Mars: recent observations

Mars is a unique obstacle to the solar wind flow. It lacks a significant global magnetic field but does possess an extensive exosphere/ionosphere which interacts with the incident solar wind in a manner similar to Venus and comets. However, in contrast to Venus and comets, there are very strong, localized regions of magnetization in the crust of Mars. These crustal magnetic fields contribute to the Martian obstacle locally. As Mars rotates under the Sun, the combination creates an asymmetric and time-varying object. The wealth of data from the Mars Global Surveyor mission has enabled great insights into this interaction. We highlight recent results from the Magnetometer/Electron Reflectometer instrument that illuminate aspects of the amount of influence the crustal magnetic fields have on the solar wind interaction with Mars. They include observations of the plasma flow boundaries like the bow shock, the magnetic pileup boundary, and the photoelectron boundary. In addition, we review their influence on features such as magnetic flux ropes, ionospheric scale heights, and magnetic field morphology.

Nonstationary Robust Vibration Control Considering Scaled Structured and Unstructured Uncertainties (Application to Vibration Control of Wire Changing Its Length)

This paper presents a synthesis method of nonstationary robust controller considering uncertainties of time-varying object such as variation of parameter and spillover due to ignored high order modes of object. The variation of parameter is experessed by a scaled structured uncertainty in the time domain. Meanwhile, the influence of spillover is given as a unstructured uncertainty in the frequency domain. In this research, a nonstationary robust vibration controller considering both uncertainties is designed by solving a time-varying Riccati equation derived from a differential game type criterion function. The proposed control method is applied to the transverse vibration control of wire changing its length. Through numerical calculations, the reduction performance of the proposed controller is verified and the advantage with respect to the robustness for the uncertainties is demonstrated.

Shape and motion measurement of time-varying three-dimensional objects based on spatiotemporal fringe-pattern analysis

A method and tools recently applied in animation are presented, and the associated problems connected with combining the real and the virtual world are described. Approaches include creating computer graphics libraries of realistic 3-D objects and describing their animation in 3-D space. The presented method simplifies the process of virtual-object generation and provides the shape and movement of the monitored object. Optical structured-light methods supported by photo- grammetry are proposed for gathering the information about a shape, deformations of shape, and shifts of 3-D objects. The authors apply the spatiotemporal approach, in which the spatial analysis of fringe pattern delivers information about the shape of the object, while the temporal analysis of the intensity variation l(t) at a given pixel provides information about shape variations and out-of-plane displacement. The function I(t) is analyzed by the Fourier-transform method. Rigid-body motion of the object is determined by a photogrammetry-based marker tracking method. The methodology of measurement is presented, together with experimental results.

Vibration Control for Rope-Sway of Elevator of High-Rise Building. Application of Nonstationary Optimal Control to Time-Varying Flexible System.

This study presents a synthesis method of a nonstationary optimal controller for reducing vibration of a time-varying object such as rope of elevator and crane. Moreover, from the viewpoint of wave propagation, we also propose a method of reducing vibration with controller to remove reflected waves. We deal with a rope of elavator of high-rise building as time-varying flexible system and construct the simultaneous model. For this system, controllers to reduce the vibration is designed by using weightings which depend on the velocity and displacement of rope of elevator, in addition, the reflected waves at both ends of its main-rope. The performance of reducing the vibration due to the rope-sway on a high-rise building is examined through numerical calculation. These controllers are compared with the stationary optimal controller for the case that the structure is subjected to artificial wind wave and Chi-Chi earthquake, and their usefulness are shown.

State space models in process tomography — approximation of state noise covariance

In this paper we consider process tomography in the case of time-varying objects. Especially, we concentrate on the case in which the indirect observations from the system are obtained via electrical impedance tomographic (EIT) measurements and in which the time-evolution of the target can be described by a stochastic convection-diffusion model. We use the state estimation approach to obtain the tomographic reconstructions. The state estimation problem is solved with the fixed-lag Kalman smoother algorithm that is a feasible approach for continuous observation with an insignificant delay in the reconstructions. In particular we focus on the covariance structures associated with state space model. The covariance structures determine the temporal and spatial regularization properties of the algorithm. It is shown that the adoption of nontrivial covariance structures in the evolution model yields good estimates for the time-varying object in such a situation in which stationary reconstructions are completely useless.

Dynamic Vehicle Dispatching at the Intermodal Transfer Station

Transfer time is one of the most important service quality indicators for evaluating intermodal transit systems. In the advent of advanced public transportation systems, vehicle arrival times and transfer demand can be obtained in real time. Thus, the decision of dispatching vehicles at transfer stations can be optimized to reduce the transfer cost. A time-varying total-cost function, including connection delay and missed-connection costs incurred by transfer passengers and vehicle holding cost, is formulated as a function of holding times for vehicles that are ready to be dispatched at transfer stations. A procedure is developed to dynamically optimize the dispatching time for each ready vehicle by minimizing the time-varying objective function. A transit network consisting of four routes connecting at a transfer terminal is designed in this study to demonstrate the application of the dispatching model. The proposed method can be used to advance transit vehicle dispatching strategies and reduce the transfer time.

Iterative method for tomographic reconstruction of time-varying objects

The <i>Journal of Electronic Imaging</i> (JEI), copublished bimonthly with the Society for Imaging Science and Technology, publishes peer-reviewed papers that cover research and applications in all areas of electronic imaging science and technology.

Stochastic Comparison Algorithm for Discrete Optimization with Estimation of Time-Varying Objective Functions

In this paper, the optimization of time-varying objective functions, known only through estimates, is considered. Recent research defined algorithms for static optimization problems. Based on one of these algorithms, we derive an optimization scheme for the time-varying case. In stochastic optimization problems, convergence of an algorithm to the optimum prevents the algorithm from being efficiently adaptive to changes of the objective function if it is time-varying. So, convergence cannot be required in a time-varying scenario. Rather, we require convergence to the optimum with high probability together with a satisfactory dynamical behavior. Analytical and simulative results illustrate the performance of the proposed algorithm compared with other optimization techniques.

Model-free control of nonlinear stochastic systems with discrete-time measurements

Consider the problem of developing a controller for general (nonlinear and stochastic) systems where the equations governing the system are unknown. Using discrete-time measurement, this paper presents an approach for estimating a controller without building or assuming a model for the system. Such an approach has potential advantages in accommodating complex systems with possibly time-varying dynamics. The controller is constructed through use of a function approximator, such as a neural network or polynomial. This paper considers the use of the simultaneous perturbation stochastic approximation algorithm which requires only system measurements. A convergence result for stochastic approximation algorithms with time-varying objective functions and feedback is established. It is shown that this algorithm can greatly enhance the efficiency over more standard stochastic approximation algorithms based on finite-difference gradient approximations.

Organic dye-doped polymer films for optical phase-conjugate processing

Erythrosin B-doped polyvinyl alcohol (EB/PVA) film, a methyl-orange-doped polyvinyl alcohol (MO/PVA) film and a (EB+MO)/PVA film serve as not only phase conjugators but also hologram-recording media. A phase-conjugate (PC) wave is generated even when a probe wave is linear-polarized orthogonal to the pump polarization direction. Using these dye-doped films, we demonstrate optical PC processing for detecting the phase and amplitude difference between two objects and a moving or time-varying object in a backward degenerate four-wave mixing arrangement.

A pattern-based object calculus

Several object-oriented database management systems have been implemented without an accompanying theoretical foundation for constraint, query specification, and processing. The pattern-based object calculus presented in this article provides such a theoretical foundation for describing and processing object-oriented databases. We view an object-oriented database as a network of interrelated classes (i.e., the intension) and a collection of time-varying object association patterns (i.e., the extension). The object calculus is based on first-order logic. It provides the formalism for interpreting precisely and uniformly the semantics of queries and integrity constraints in object-oriented databases. The power of the object calculus is shown in four aspects. First, associations among objects are expressed explicitly in an object-oriented database. Second, the nonassociation operator is included in the object calculus. Third, set-oriented operations can be performed on both homogeneous and heterogeneous object association patterns. Fourth, our approach does not assume a specific form of database schema. A proposed formalism is also applied to the design of high-level object-oriented query and constraint languages.

特集 センサフュージョン 動きの予測を伴う能動的認識のアルゴリズム

In understanding circumstances, we human beings direct our attention to appropriate information sources and collect necessary information according to our purpose. The author formalized such an attentional perception process as a sequential experimental design based on an information criterion and described its concrete algorithm. In the present article, the author develops the algorithm with an idea of prediction so as to estimate a time-variant object's state efficiently. The algorithm is to predict the object's state using the internal state transition model and to observe the object with the most informative sensor when the ambiguity of the prediction exceeds a specified limit. The author applies the algorithm to a problem of estimating the position of a moving target with observing it by a camera at times, and investigates its behavior through numerical experiments. The result shows that the system turns the camera's visual field to proper directions at proper times and estimates the target's position with specified accuracy by fewer observations.

Spatial and temporal analysis of solid-state imaging systems

Temporal and spatial properties of the image that is stored in the digital memory of a frame grabber through a solid-state image sensor, which employs the X-Y addressing method for scanning the image, are analyzed in the space-time domain by using the mathematical expression that we have obtained. This expression includes not only the static effects of the finite picture-cell size of the sensor and the image sampling in both the sensor and the grabber but also the dynamic effects of the temporal response of photoelectric conversion in the sensor, a one-dimensional electrical filter of the camera controller, and the asynchronous sampling with regard to time in both the sensor and the grabber. Results of the experiment and the numerical simulations based on the mathematical expression are presented for a time-varying one-dimensional object with good agreement.

Collision avoidance for nonrigid objects

The path existence problem and the collision detection problem for time-varying objects in a geometric scene are discussed. For a large class of spherical nonrigid objects, exact solutions of the path existence problem are developed based on decomposition techniques and graph traversal. For the collision detection problem of a single moving circle in the plane, efficient data structures are presented for linear/circular and polynomial paths.

Operational River Water Quality Management

The developments in water pollution control legislation and their interpretation are discussed in the context of the current need to establish flexible operational control hierarchies reflecting conflicting uses of surface waters and overall basin economy. Fussy logic is proposed as a technique to aid the reconciliation of within-plant and within-receiving water operational targets with the consistent interpretation of statutory requirements. An example simulation of the control of a waste-water treatment plant to meet time-varying river water quality objectives is presented in support of the argument.