Autonomous Control of a Scale Model of a Trailer-Truck using an Obstacle-Avoidance Path-Planning Hierarchy

A scale model of a tractor-trailer truck was developed as a testbed for control algorithms. The truck operates in autonomous or semi-autonomous modes. An on-board Pentium computer with a PC104 bus performs the computations and data collection. Various sensors and a wireless transceiver are on-board the truck. Our research focus has been in the autonomous control of vehicles using intelligent systems. For this document we have employed a multi-resolutional hierarchy to plan a path for the tractor-trailer truck. The hierarchy starts with a simple path then warps it around obstacles. The modular construction of the hierarchy allows more intelligent agents to perform some of tasks. The current system has some limitations as to the placement of obstacles, however, it is an extremely fast algorithm and is able to handle some motion of the obstacles

Accelerated BS/MS Program in Electrical and Computer Engineering

The Electrical and Computer Engineering Department at Missouri University of Science and Technology implemented an Accelerated BS/MS Program in 2019. This program is designed to encourage and facilitate undergraduate majors in electrical and computer engineering to pursue a masters program. It is similar to engineering programs at other institutions that are identified with titles such as accelerated masters, combined BS/MS, and 4+1 options. It reduces the time needed for undergraduates to earn a graduate degree and exposes these students to research work. It provides a route for faculty to obtain quality graduate students and it builds enrollment for the department. This paper discusses the structure and the implementation of the first program of this type at Missouri University of Science and Technology. The experience of the initial electrical and computer engineering students in the Accelerated BS/MS program is described. While the number of students who participated is not large, the program provides a valuable option to the curriculum

A Radar Sensing Algorithm by Gabor Theory

In this paper, an alternative Target Density Function( TDF) is proposed for narrowband radar model. This is achieved by estimating a new target density function by Gabor theory. It is shown how Gabor transform can be used to obtaining wideband target density function by transmitting a waveform which is a kernel for this transform. The windowing characteristics of this theory is plausible to reaching an accurate result. The presented wideband target density function is developed in a various manner different from the conventional methods

An Approach to Active Sensor Imaging

In this paper, an alternative Target Density Function (TDF) is proposed to image the radar targets in a dense target environment. It is obtained by considering a novel range and scanning angle plane different from the conventional methods. An alternative method is briefly proposed for smoothing the target density function by taking advantage of Walsh functions. Although the imaging is obtained via the phased array radars, the problem associated with beamforming in linear phased array radar system is bypassed in this new algorithm

An Alternative Target Density Function for Radar Imaging

In this paper, an alternative Target Density Function (TDF) is proposed to image the radar targets in a dense target environment. It is produced by wavelet theory considering a new range and angle plane different from the conventional methods. It is shown that Wavelet theory can be used as approach to imaging by active sensors by transmitting a waveform which is a kernel for this transform such as a window function. Although the imaging is obtained via the phased array radars, the problem associated with beamforming in linear phased array radar system is bypassed in this new algorithm

Self-Healing Control with Multifunctional Gate Drive Circuits for Power Converters

Many commercial and military transport systems have fault diagnostic functions implemented to help protect the device when a severe fault occurs. However, most present systems do not contain prognostics capability which would allow operators to observe an unhealthy system component in its pre- fault condition. In industry applications, scheduled downtime can result in considerable cost avoidance. The next technology step is self-healing system components which observe not only potential problems, but can also take steps to continue operation under abnormal conditions - whether due to long-term normal wear-and-tear or sudden combat damage. In this paper, current and voltage information using the double-layer gate drive concept is fed to intelligent networks to identify the type of fault and its location. These intelligent networks are based on unsupervised and supervised learning networks (self-organizing maps and learning vector quantization networks respectively). The proposed concept allows the reconfiguration of the electric machinery system for continued normal operation of the machine. This paper presents an intelligent health monitoring and self-healing control strategy for a multi-phase multilevel motor drive under various types of faults

Using Coupled Eulerian and Lagrangian Grids to Model Explosive Interactions with Buildings

This paper presents the development of a computational model that can be used to study the interactions between structures and detonating explosives contained within them. This model was developed as part of an effort to develop a rubble characterization model for use in AmmoSIM, an agent based urban tactical decision aid (UTDA) software for weapon-target pairing. The rubble pile created following the collapse of a building in a combat situation can significantly impact mission accomplishment, particularly in the area of movement and maneuver. The information provided by AmmoSIM will enable both platoon level and command center staff to make informed decisions concerning urban attack tactics. Computational models were created using a combination of AUTODYN 2D and 3D. The detonation was modeled using a 2D wedge, which is a common method used in AUTODYN. The information obtained from the wedge calculation was then written to a data file and subsequently remapped into a larger 3D Euler air grid. The air grid loaded with blast pressure information was coupled to interact with the Lagrangian building parts. The Riedel, Hiermaier and Thoma (RHT) Concrete Model from the AUTODYN material library was utilized to create the components of the building. Results of the latest models will be given. Additionally, the paper details the development of the model at length including topics such as grid sizing, computational cost comparisons, grid interactions, multi-solver coupling, strain erosion, and material parameters and selections

Rubble Pile Characterization Model

Rubble piles created following the collapse of a building in a combat situation can significantly impact mission accomplishment, particularly in the area of movement and maneuver. Rubble characteristics must be known, for example, in order to predict the ability of a vehicle to override the collateral damage from weapon effects in urban areas. Two types of models are developed: a first-order model and a first-principles-based model. In both models, we assume complete rubblization of the building and develop a rubble profile model using the size and composition of the collapsed structure to predict the rubble volume. In both cases, this profile model includes the size of the footprint area surrounding the original building assuming that the rubble is free to expand horizontally as well as the resulting height of such a rubble pile. Empirical data is now needed to verify the predictive capabilities of these models

Reptile species persistence under climate change and direct human threats in north-western Argentina

Protected areas have been established historically in residual places where the potential for extractive uses is low, implying that places at risk are usually underprotected. Argentina is no exception,with fewprotected areas established in productive regions that are prone to conversion. Here, using reptiles as a study group and considering the most important human threats in north-westernArgentina,we estimated priority conservation areas where we expect species to persist in the face of climate change and land conversion. Protected areas cover no more than 9% of the study region, but represent less than 15% of reptile distributions. There are great opportunities for improving the conservation status in the region by protecting only 8% more of north-western Argentina, with the level of species protection inside the protected area network increasing almost four-fold, reaching 43% of species distributions on average and 59% of the distributions of threatened reptiles. Fortunately, the highest diversity of reptiles in the region does not match the places targeted for agriculture expansion. Our findings suggest that future prioritization schemes should embrace other groups that are especially diverse in the Chaco ecoregion, which overlaps with our study area.FONCYT and SECYTUNC. RL’s research has been constantly funded by CNPq (grants #308532/2014-7, 479959/2013-7, 407094/2013-0 and 563621/2010-9), O Boticário Group Foundation for Nature Protection (grant #PROG_0008_2013) and CNCFlora. This paper is a contribution of the Brazilian Network on Global Climate Change Research funded by CNPq (grant #437167/2016-0) and FINEP (grant #01.13.0353.00). RLP acknowledges the support of the Australian Research Council

Macrophage-Derived Slit3 Controls Cell Migration and Axon Pathfinding in the Peripheral Nerve Bridge

Slit-Robo signaling has been characterized as a repulsive signal for precise axon pathfinding and cell migration during embryonic development. Here, we describe a role for Sox2 in the regulation of Robo1 in Schwann cells and for Slit3-Robo1 signaling in controlling axon guidance within the newly formed nerve bridge following peripheral nerve transection injury. In particular, we show that macrophages form the outermost layer of the nerve bridge and secrete high levels of Slit3, while migratory Schwann cells and fibroblasts inside the nerve bridge express the Robo1 receptor. In line with this pattern of Slit3 and Robo1 expression, we observed multiple axon regeneration and cell migration defects in the nerve bridge of Sox2-, Slit3-, and Robo1-mutant mice. Our findings have revealed important functions for macrophages in the peripheral nervous system, utilizing Slit3-Robo1 signaling to control correct peripheral nerve bridge formation and precise axon targeting to the distal nerve stump following injury