Engineering design motivations : a qualitative and quantitative analysis of university students

What motivates students to perform and pursue engineering design tasks? This study examines this question by way of three Learning Through Service (LTS) programs: 1) an on-going longitudinal study examining the impacts of service on engineering students, 2) an on-going analysis of an international senior design capstone program, and 3) an on-going evaluation of an international graduate-level research program. The evaluation of these programs incorporates both qualitative and quantitative methods, utilizing surveys, questionnaires, and interviews, which help to provide insight on what motivates students to do engineering design work. The quantitative methods were utilized in analyzing various instruments including: a Readiness assessment inventory, Intercultural Development Inventory, Sustainable Engineering through Service Learning survey, the Impacts of Service on Engineering Students’ survey, Motivational narratives, as well as some analysis for interview text. The results of these instruments help to provide some much needed insight on how prepared students are to participate in engineering programs. Additional qualitative methods include: Word clouds, Motivational narratives, as well as interview analysis. This thesis focused on how these instruments help to determine what motivates engineering students to pursue engineering design tasks. These instruments aim to collect some more in-depth information than the quantitative instruments will allow. Preliminary results suggest that of the 120 interviews analyzed Interest/Enjoyment, Application of knowledge and skills, as well as gaining knowledge are key motivating factors regardless of gender or academic level. Together these findings begin to shed light on what motivates students to perform engineering design tasks, which can be applied for better recruitment and retention in university programs.

Multi-antenna non-line-of-sight identification techniques for target localization in mobile ad-hoc networks

Target localization has a wide range of military and civilian applications in wireless mobile networks. Examples include battle-field surveillance, emergency 911 (E911), traffc alert, habitat monitoring, resource allocation, routing, and disaster mitigation. Basic localization techniques include time-of-arrival (TOA), direction-of-arrival (DOA) and received-signal strength (RSS) estimation. Techniques that are proposed based on TOA and DOA are very sensitive to the availability of Line-of-sight (LOS) which is the direct path between the transmitter and the receiver. If LOS is not available, TOA and DOA estimation errors create a large localization error. In order to reduce NLOS localization error, NLOS identifcation, mitigation, and localization techniques have been proposed. This research investigates NLOS identifcation for multiple antennas radio systems. The techniques proposed in the literature mainly use one antenna element to enable NLOS identifcation. When a single antenna is utilized, limited features of the wireless channel can be exploited to identify NLOS situations. However, in DOA-based wireless localization systems, multiple antenna elements are available. In addition, multiple antenna technology has been adopted in many widely used wireless systems such as wireless LAN 802.11n and WiMAX 802.16e which are good candidates for localization based services. In this work, the potential of spatial channel information for high performance NLOS identifcation is investigated. Considering narrowband multiple antenna wireless systems, two xvNLOS identifcation techniques are proposed. Here, the implementation of spatial correlation of channel coeffcients across antenna elements as a metric for NLOS identifcation is proposed. In order to obtain the spatial correlation, a new multi-input multi-output (MIMO) channel model based on rough surface theory is proposed. This model can be used to compute the spatial correlation between the antenna pair separated by any distance. In addition, a new NLOS identifcation technique that exploits the statistics of phase difference across two antenna elements is proposed. This technique assumes the phases received across two antenna elements are uncorrelated. This assumption is validated based on the well-known circular and elliptic scattering models. Next, it is proved that the channel Rician K-factor is a function of the phase difference variance. Exploiting Rician K-factor, techniques to identify NLOS scenarios are proposed. Considering wideband multiple antenna wireless systems which use MIMO-orthogonal frequency division multiplexing (OFDM) signaling, space-time-frequency channel correlation is exploited to attain NLOS identifcation in time-varying, frequency-selective and spaceselective radio channels. Novel NLOS identi?cation measures based on space, time and frequency channel correlation are proposed and their performances are evaluated. These measures represent a better NLOS identifcation performance compared to those that only use space, time or frequency.