Contribution: This work in progress innovative practice paper describes an approach to implement Peter Liljedahl's classroom practices in a college first-year engineering course. Background: This course meets twice each week in a studio-style classroom. Liljedahl defines a thinking classroom as “a space that is inhabited by thinking individuals as well as individuals thinking collectively, learning together and constructing knowledge and understanding through activity and discussion” [1]. Thinking classrooms and in-class activities are also supported by Vygotsky's [2] Zone of Proximal Development theory and Bruner's [3] scaffolding methods. Original applications of Liljedahl's research are in secondary school mathematics courses, including the uses of visibly random groups and vertical non-permanent surfaces. Visibly random groups are temporary groups of students where the students can clearly see the random group assignment process [4]. This paper proposes a new style of in-class activities in this first-year engineering course and explains a research design procedure to test if this style improves students' achievement of learning objectives. Intended outcomes: My proposed in-class activity format involves groups of four engineering students working together to solve a problem while standing up and writing on a vertical surface with a nonpermanent writing tool. Additionally, this modified format in each class session seeks to provide students with incentive to complete in-class activities and feedback while completing them. Incentive can come from the “gamification” of in-class activities [5], leaderboards, team-oriented events, or adding more relevant background context. Feedback can be provided to students through implementing Learning Management System quizzes or MATLAB P-code in coding activities. Application design: This approach aims to improve student learning by providing students with a new, consistent format for in-class activities that is exciting, engaging, and team-oriented. Students in a control group or an experimental group will take pre- and post- tests before and after experiencing the traditional or modified in-class activities. Expected findings: I anticipate class sections that participate in the alternative in-class activity format will have significantly higher mastery levels than the traditional sections. The existing in-class activities are already aligned with course learning objectives, but encouraging students to complete them thoroughly with their group may help each student gain a better understanding of the content.

A robust control design is proposed for the lane-keeping and obstacle avoidance of semiautonomous ground vehicles. A robust Model Predictive Controller (MPC) is used in order to enforce safety constraints with minimal control intervention. An uncertain driver model is used to obtain sets of predicted vehicle trajectories in closed-loop with the predicted driver's behavior. The robust MPC computes the smallest corrective steering action needed to keep the driver safe for all predicted trajectories in the set. Simulations of a driver approaching multiple obstacles, with uncertainty obtained from measured data, show the effect of the proposed framework.

This paper presents the design of a novel active safety system preventing unintended roadway departures. The proposed framework unifies threat assessment, stability, and control of passenger vehicles into a single combined optimization problem. A nonlinear model predictive control (MPC) problem is formulated, where nonlinear vehicle dynamics, in closed-loop with a driver model, is used to optimize the steering and braking actions needed to keep the driver safe. A model of the driver's nominal behavior is estimated based on his observed behavior. The driver commands the vehicle, whereas the safety system corrects the driver's steering and braking actions in case there is a risk that the vehicle will unintentionally depart from the road. The resulting predictive controller is always active, and mode switching is not necessary. We show simulation results detailing the behavior of the proposed controller and experimental results obtained by implementing the proposed framework on embedded hardware in a passenger vehicle. The results demonstrate the capability of the proposed controller to detect and avoid roadway departures while avoiding unnecessary interventions.

Significant technological advances were made toward utilizing the Hale telescope for receiving the faint laser communication signals transmitted from an optical transceiver on a spacecraft orbiting Mars. The so-called Palomar receive terminal design, which would have supported nominal downlink data rates of 1-30 Mbps, is described. Testing to validate technologies for near-Sun (3deg from edge of solar disc) daytime operations is also discussed. Finally, a laboratory end-to-end link utilizing a 64-ary pulse-position modulated photon-counting receiver and decoder that achieved predicted near-capacity (within 1.4 dB) performance is described.

We consider the problem of power controlled minimum frame length scheduling for TDMA wireless networks. Given a set of one-hop transmission requests, our objective is to schedule them in a minimum number of time slots, so that each slot schedule is free of self-interferences and meets desired SINR constraints. Additionally, the transmit power vector corresponding to each slot schedule should be minimal. We consider two different versions of the problem, a per-slot version and a per-frame version, and develop mixed integer linear programming models which can be used for solving the problems optimally. In addition, we propose a heuristic algorithm for the per-slot version.

We consider the "at least" version of the generalized minimum spanning tree problem (L-GMST). Unlike the MST, the L-GMST is known to be NP-hard. In this paper, we propose an ant colony system based solution approach for the L-GMST. A key feature of our algorithm is its use of ants of different behavioral characteristics, which are adapted over time. Computational results on datasets used in earlier literature indicate that our algorithm provides similar or better results for most of them.

We consider the problem of minimum power bidirectional topology optimization in wireless networks with sectored antennas. We first develop a mixed integer linear programming model for optimal solution of the problem with sectored antennas. Subsequently, we discuss a centralized heuristic algorithm which is based on Kruskal's algorithm for the minimum spanning tree problem. However, unlike Kruskal's algorithm which chooses minimum cost edges from a set of edge weights, our algorithm uses an incremental cost mechanism to select edges. This incremental cost mechanism is motivated by the inherently broadcast nature of the wireless medium. We also discuss a simple branch exchange heuristic which can be used to improve the topology generated by the Kruskal-like algorithm. Simulation results indicate that reasonably good solutions can be obtained using the proposed heuristic algorithms.

In this paper the problem of minimum power multicasting in wireless networks with sectored antennas is considered. For omnidirectional antenna systems, a transmission from node i to node j will also reach all nodes which are closer to i than j. Depending on the network geometry, this strategy can be highly power efficient In ideal sectored antenna systems, however, this phenomenon is sector specific; i.e., only those nodes which are located in the same sector as j will receive the transmission implicitly. Though this might seem an apparent disadvantage, the higher gains associated with directional antennas (as opposed to omni-directional antennas) allow for reduced transmission powers without sacrificing the signal-to-interference ratio at the receiver. In this paper, we first develop a mixed integer linear programming model for optimal solution of the minimum power multicast problem with sectored antennas. Subsequently, we discuss a biologically inspired algorithm for solving the problem to near-optimality at a very reasonable computation time. Experiments on randomly generated 10, 20 and 30-node networks indicate that near-optimal solutions can be obtained using the proposed algorithm.

We consider the problem of maximizing the time-to-first-failure, defined as the time till the first node in the network runs out of battery energy, in energy constrained broadcast wireless networks. We discuss a greedy algorithm and prove that it solves the problem optimally for a broadcast application, in polynomial time, provided the complete power matrix and the battery residual capacities are known.

Broadcasting in wireless networks, unlike wired networks, inherently reaches several nodes with a single transmission. For omni-directional wireless broadcast to a node, all nodes closer will also be reached. This property can be used to compute routing trees which minimize the sum of the transmitter powers. It has been shown that this problem is NP-complete. In this paper, we present the r-shrink procedure, a heuristic for improving the solutions obtained using fast sub-optimal algorithms. Specifically, we focus on the low-complexity BIP algorithm and Prim's minimum spanning tree algorithm and show through extensive simulations that better solutions are obtained almost always, with considerably lower tree power, if the proposed procedure is used to improve the trees generated using these algorithms.

We present an outline of reconfigurable processor technologies and design methods with emphasis on an object-oriented approach and on both full and partial dynamic reconfiguration. A specific, broadly applicable architecture for implementing a software reconfigurable network processor for wireless communication applications is presented; a prototype of which is currently operating in the laboratory. This architecture, with its associated object oriented design methods and partial reconfiguration techniques, enables rapid prototyping and rapid implementation of communications and navigation signal processing functions, provides long-life communications infrastructure and results in dynamic operation within networks with heterogeneous nodes, as well as compatibility with other networks. This work builds upon numerous advances in the commercial industry, as well as military software radio developments, to space-based radios and network processing. The development of such radios and the network processor presented here requires the correct combination of processing methods ("objects") to be defined and appropriate dynamic reconfiguration techniques to be developed as a function of system goals and operating parameters.