Most of the signal processing that we will study in this course involves local operations on a signal, namely transforming the signal by applying linear combinations of values in the neighborhood of each sample point. You are familiar with such operations from Calculus, namely, taking derivatives and you are also familiar with this from optics namely blurring a signal. We will be looking at sampled signals only. Let's start with a few basic examples. Local difference Suppose we have a 1D image and we take the local difference of intensities, DI(x) = 1 2 (I(x + 1) − I(x − 1)) which give a discrete approximation to a partial derivative. (We compute this for each x in the image.) What is the effect of such a transformation? One key idea is that such a derivative would be useful for marking positions where the intensity changes. Such a change is called an edge. It is important to detect edges in images because they often mark locations at which object properties change. These can include changes in illumination along a surface due to a shadow boundary, or a material (pigment) change, or a change in depth as when one object ends and another begins. The computational problem of finding intensity edges in images is called edge detection. We could look for positions at which DI(x) has a large negative or positive value. Large positive values indicate an edge that goes from low to high intensity, and large negative values indicate an edge that goes from high to low intensity. Example Suppose the image consists of a single (slightly sloped) edge:

http://ieeexplore.ieee.org/iel5/5/31307/01456462.pdf

Linear systems

Bilateral teleoperation: An historical survey

Summary) The abstract should follow the structure of the article (relevance, degree of exploration of the problem, the goal, the main results, conclusion) and characterize the theoretical and practical significance of the study results. The abstract should not contain wording echoing the title, cumbersome grammatical structures and abbreviations. The text should be written in scientific style. The volume of abstracts (summaries) depends on the content of the article, but should not be less than 250 words. All abbreviations must be disclosed in the summary (in spite of the fact that they will be disclosed in the main text of the article), references to the numbers of publications from reference list should not be made. The sentences of the abstract should constitute an integral text, which can be made by use of the words “consequently”, “for example”, “as a result”. Avoid the use of unnecessary introductory phrases (eg, “the author of the article considers...”, “The article presents...” and so on.)

/pdf/ministry-of-education-and-science-of-the-russian-federation-7m2jn0xnm1.pdf

Ministry of Education and Science of the Russian Federation

One of the most important design problems for multi-UAV (Unmanned Air Vehicle) systems is the communication which is crucial for cooperation and collaboration between the UAVs. If all UAVs are directly connected to an infrastructure, such as a ground base or a satellite, the communication between UAVs can be realized through the in-frastructure. However, this infrastructure based communication architecture restricts the capabilities of the multi-UAV systems. Ad-hoc networking between UAVs can solve the problems arising from a fully infrastructure based UAV networks. In this paper, Flying Ad-Hoc Networks (FANETs) are surveyed which is an ad hoc network connecting the UAVs. The differences between FANETs, MANETs (Mobile Ad-hoc Networks) and VANETs (Vehicle Ad-Hoc Networks) are clarified first, and then the main FANET design challenges are introduced. Along with the existing FANET protocols, open research issues are also discussed.

Flying Ad-Hoc Networks (FANETs)

Aircraft wings are a compromise that allows the aircraft to fly at a range of flight conditions, but the performance at each condition is sub-optimal. The ability of a wing surface to change its geometry during flight has interested researchers and designers over the years as this reduces the design compromises required. Morphing is the short form for metamorphose; however, there is neither an exact definition nor an agreement between the researchers about the type or the extent of the geometrical changes necessary to qualify an aircraft for the title ‘shape morphing.’ Geometrical parameters that can be affected by morphing solutions can be categorized into: planform alteration (span, sweep, and chord), out-of-plane transformation (twist, dihedral/gull, and span-wise bending), and airfoil adjustment (camber and thickness). Changing the wing shape or geometry is not new. Historically, morphing solutions always led to penalties in terms of cost, complexity, or weight, although in certain circumstances, thes...

A Review of Morphing Aircraft

Mineral dust is among the top contributors to global aerosol loads. Ability of non-photosynthetic vegetation (NPV) to suppress dust emission has been widely acknowledged but a realistic representation of NPV has not been tested with regional-to-global scale models. In this study, we implemented a satellite-based total vegetation dataset, which included NPV, into a regional atmospheric chemistry model and conducted simulations for the year 2016 over the conterminous United States. To test the response of dust simulations to the NPV coverage, we conducted a control simulation incorporating only the photosynthetic vegetation (PV). Simulated dust emissions decrease by 10-70% over most of the southwestern U.S. from spring to autumn due to NPV. Reductions in dust concentrations are the largest in spring, which attenuate the overpredictions of fine soil concentrations, but accentuate the underpredictions in summer. Overall, the mean errors and correlations of annual simulations are slightly improved with NPV. NPV modulates dust emissions mainly by sheltering the surface and increasing the threshold velocity through drag partitioning. Moreover, we investigated the effect of vegetation height and addressed its uncertainties through a series of sensitivity tests. We observed that a 50% variation in predefined vegetation heights results in small changes in soil concentrations over majority of southwestern U.S., but causes up to 30% changes at local hotspots. This study highlights the significance of including NPV into the dust model and points out the importance of validation of total vegetation datasets as well as more realistic representation of vegetation heights and seasonality. 

Effects of Non‐Photosynthetic Vegetation on Dust Emissions

A fundamental problem in the design of adaptive control systems for vibration isolation is discussed. This application is often characterized by lightly damped dynamics in the adaptive loop. It is shown that these dynamics can adversely affect the stability and performance of the adaptive algorithm. The result is typically an oscillation in parameter estimates, which is not predicted by general analysis approaches, such as averaging theory. Compensation for these dynamics is suggested, based on a control design viewpoint, and simulation evidence for its efficacy is provided.

http://ieeexplore.ieee.org/iel5/4791998/4791999/04792727.pdf

The Parameter Oscillation Problem in Adaptive Vibration Isolation

Force feedback can be used to improve force tracking of haptic interfaces. Single degree-of-freedom (DOF) force sensors work well for force tracking in 1 DOF motion, but multiple single-DOF force sensors combine in unintuitive ways. We present force analysis of a parallel 5 DOF haptic interface and discuss the rami fi cations of using 1 DOF sensors versus multi-DOF sensors.

Sensor Modeling in Parallel Force Feedback Haptic Interfaces

A heliogyro is a solar sail concept that divides the solar sail membrane into a number of long, slender blades of film extended from a central hub, maintained in a flat state through spin-induced tension. The heliogyro can redirect and scale the solar radiation pressure (SRP) force and can achieve attitude control by twisting the blades, similar to a helicopter rotor. Different pitch profiles exist, including pitching the blades in a collective, cyclic or combined collective and cyclic manner. While the forward mapping, i.e., computing the SRP force and moment generated by the heliogyro for a given pitch profile, is straightforward, the inverse of the problem is much more complex. However, this inverse problem (finding the blades’ pitch that results in a desired SRP force and/or moment) is crucial for heliogyro mission design and operations. This paper therefore solves the inverse problem numerically: first, only for a desired SRP force or SRP moment and subsequently for the fully coupled inverse problem. The developed methods are subsequently applied to track a reference trajectory that corrects for injection errors into a solar sail Sun-Earth sub-L1 halo orbit. I. Introduction

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Dale Lawrence

Papers

Effects of Non‐Photosynthetic Vegetation on Dust Emissions

The Parameter Oscillation Problem in Adaptive Vibration Isolation

Sensor Modeling in Parallel Force Feedback Haptic Interfaces

Solving the heliogyro’s inverse problem

Spinning smallsat detumbling and sun acquisition system