This paper describes a study to assess the demand of problems posed in undergraduate electrical engineering courses. This is part of a larger study to examine the gap between the demand of problems and the types of reasoning students use when attempting to solve them. The analysis uses a two-dimensional taxonomy table consisting of rows and columns that define cognitive processes and categories of knowledge, respectively. The cognitive process dimension (i.e., the rows of the table) contains six categories: remember, understand, apply, analyze, evaluate, and create. The knowledge dimension (i.e., the columns of the table) contains four categories: factual, conceptual, procedural, and metacognitive. Preliminary results suggest that the proposed two-dimension analysis can be successfully used to characterize the demand of electrical engineering problems.

Maintaining the health and well‐being of animals is critical to the efficiency and profitability of livestock operations. However, it can be difficult to monitor the health of animals in large group‐housed settings without the assistance of technology. This study presents a system that uses depth images to continuously track individual pigs in a group‐housed environment. It is an alternative to traditional manual observation used by both researchers and producers for the analysis of animal activities and behaviours. The tracking method used by the system exploits the consistent shape and fixed number of the targets in the environment by applying expectation maximisation as a policy for fitting an ellipsoid to each target. Results demonstrate that the system can maintain the correct positions and orientations of 15 group‐housed pigs for an average of 19.7 min between failure events.

We offered professional development to in-service K-12 teachers. Teachers learned programming, and how to teach programming. During the subsequent academic year, they taught programming in their schools. We interviewed the teachers to better understand their experiences. This poster describes case studies of K-12 teachers as they teach programming for the first time. As this study is qualitative, it does not attempt to measure findings. Rather, in exploring individual teachers' experiences, we hope to benefit both future teachers who will need to teach computing as well as those who will be helping those teachers.

The ability to solve problems is a critical skill in all undergraduate engineering curricula. Students' capacity for problem solving is complicated by the fact that higher level reasoning skills, including the capacity for abstraction, are not innate in a person until the mid-twenties or later. The results of an exploratory study that looked at students' episodes of reasoning when solving problems in a sophomore level electrical circuits course are presented. Students' problem solving attempts are analyzed using the representation mapping framework developed by Hahn and Chater that is based on store representations of knowledge and how they are applied. This framework distinguishes between similarity and rules-based cognitive processes, and accounts for memory-bank, rules-based, similarity-based and prototype types of reasoning. Students were asked to think aloud when solving specific problems selected by the course instructor. The interviews were recorded, transcribed, and analyzed in detail to identify the types of reasoning and the degree of abstraction in the students' problem solving attempts. This study demonstrated that representation mapping is useful framework for studying students' problem solving skills in electrical engineering.

“Transfer shock” is a well-known phenomenon during the process of articulation, when students move from short-cycle applied programs to more academic longer-cycle study programs. In the US context this problematic transition has been observed in students transferring from community colleges into the traditional university system. In Ireland's binary higher education structure, one set of institutions, known as Institutes of Technology (IoTs) allow for this transition to take place entirely within individual institutions. This paper is part of an ongoing investigation into one such IoT, where engineering students who achieve high grades at the end of 3-year (so-called Level 7) “ordinary degree” programs frequently transfer into the 3rdyear of 4-year Level 8 “honors degree” programs, with surprisingly successful outcomes. One surprise derives from the fact that the students who enter Level 7 engineering programs are deemed at the outset to be academically less able, particularly in mathematics, than those who go directly into Level 8 programs from secondary school. Relatively little work has been done on this transition to date. In the 3rdand 4thyear of many honors engineering programs within this institution it is not unusual to have 30–50% of the students coming from an ordinary degree background, the majority from within the institution itself — with others transferring from other IoTs in Ireland. Previous research has shown that students from this background initially struggle in the 3rdyear of the honors degree program when compared with students who have proceeded directly through the honors program, before going on to successfully graduate. Can this be attributed to ‘transfer shock’ even though most of these students are continuing in an institution and with faculty that they are already familiar with? In order to examine this phenomenon we interview students from several engineering disciplines at various points in this transition. We explore the perceptions of the students regarding this transition and, based on the information coming from the interviews, we conduct a large scale survey to be administered to articulating students across engineering programs in the institution. The preliminary results of this survey are also presented here.

A new method is introduced for stereo matching that operates on minimum spanning trees (MSTs) generated from the images. Disparity maps are represented as a collection of hidden states on MSTs, and each MST is modeled as a hidden Markov tree. An efficient recursive message-passing scheme designed to operate on hidden Markov trees, known as the upward-downward algorithm, is used to compute the maximum a posteriori (MAP) disparity estimate at each pixel. The messages processed by the upward-downward algorithm involve two types of probabilities: the probability of a pixel having a particular disparity given a set of per-pixel matching costs, and the probability of a disparity transition between a pair of connected pixels given their similarity. The distributions of these probabilities are modeled from a collection of images with ground truth disparities. Performance evaluation using the Middlebury stereo benchmark version 3 demonstrates that the proposed method ranks second and third in terms of overall accuracy when evaluated on the training and test image sets, respectively.

High-quality real-time stereo matching has the potential to enable various computer vision applications including semi-automated robotic surgery, teleimmersion, and 3-D video surveillance. A novel real-time stereo matching method is presented that uses a two-pass approximation of adaptive support-weight aggregation, and a low-complexity iterative disparity refinement technique. Through an evaluation of computationally efficient approaches to adaptive support-weight cost aggregation, it is shown that the two-pass method produces an accurate approximation of the support weights while greatly reducing the complexity of aggregation. The refinement technique, constructed using a probabilistic framework, incorporates an additive term into matching cost minimization and facilitates iterative processing to improve the accuracy of the disparity map. This method has been implemented on massively parallel high-performance graphics hardware using the Compute Unified Device Architecture computing engine. Results show that the proposed method is the most accurate among all of the real-time stereo matching methods listed on the Middlebury stereo benchmark.

Conditional upper bounds are given for min-sum decoding of low-density parity-check codes in the error floor region. It is generally thought that absorbing sets, i.e., small collections of variable nodes connected to a relatively small number of unsatisfied check nodes, are the primary source of errors in the error floor region. The conditional upper bounds presented here are based on the assumption that all error floor errors are caused by absorbing sets. In order to bound the probability of error associated with each absorbing set, a directed-edge Tanner graph is used to link absorbing sets to low-weight deviations. These low-weight deviations result when a proportionally large number of nodes within a stopping set belong to an absorbing set contained inside the stopping set. A complete collection of the most problematic absorbing sets, and the minimum deviation weights that result from them, are used to derive a conditional upper bound on the probability of error for min-sum decoding of low-density parity-check codes. Simulation results are given to demonstrate the accuracy of the bound.

A qualitative pilot study designed to ask transfer students about their transfer experiences and develop practices that will increase transfer student success and retention is being conducted. When completed, this qualitative study will include a series of three interviews occurring at three major epochs during a transfer student's first year of study in an undergraduate engineering degree program. The study includes students transferring from community colleges, students transferring from two partner universities in China, and nontraditional students pursuing second careers. The goal of the study is to identify those key factors that lead to a student successfully transferring to undergraduate engineering degree programs.

A dual-network Cyber-physical Networking (CPN) testbed developed at the University of Nebraska-Lincoln is described. The CPN testbed consists of two geographically disparate wireless sensor networks connected by a traditional TCP/IP network and enables peer-to-peer communication between each sensor in the network. The functionality of the testbed is enhanced by a range of software tools that support remote programming and network monitoring, and real-time visualization of sensor data. The resulting architecture supports easy deployment and evaluation of applications for both traditional and interconnected wireless sensor networks. To demonstrate the features of this testbed, a novel ping application was developed and deployed as a proof-of-concept application for peer-to-peer communication in geographically separated wireless sensor networks. Experimental evaluations of the ping application yield insight into the communications overhead that can be expected in future applications of peer-to-peer interconnected sensor networks.

The performance of non-binary joint network-channel decoding (NB-JNCD) is examined in wireless sensor networks with correlated sensors. The operating assumption is that systems containing multiple sensors in close proximity obtain correlated measurements. It is shown that, when the correlation model between sensors is known at the sink, the addition of a correlation-based decoder within the decoding framework greatly improves the error rate performance. Simulation results also indicate that the proposed correlation-based decoder is comparable to source coding across the correlated sensors in terms of error rate, while eliminating the need for costly sensor-to-sensor communication.

Extrinsic tree decoding of low-density parity-check codes operates on modified, finite computation trees created from the Tanner graph of the code. The goal of the extrinsic tree algorithm is to maintain or improve the performance of existing iterative decoders, while providing a decoding algorithm for which upper bounds can be computed. The extrinsic tree algorithm is examined, along with the design of parity-check matrices on which the extrinsic tree decoder performs well.

The role of pseudocodewords in causing non-codeword outputs in linear programming decoding, graph cover decoding, and iterative message-passing decoding is investigated. The three main types of pseudocodewords in the literature-linear programming pseudocodewords, graph cover pseudocodewords, and computation tree pseudocodewords-are reviewed and connections between them are explored. Some discrepancies in the literature on minimal and irreducible pseudocodewords are highlighted and clarified, and the minimal degree cover necessary to realize a pseudocodeword is found. Additionally, some conditions for the existence of connected realizations of graph cover pseudocodewords are given. This allows for further analysis of when graph cover pseudocodewords induce computation tree pseudocodewords. Finally, an example is offered that shows that existing theories on the distinction between graph cover pseudocodewords and computation tree pseudocodewords are incomplete.

The discovery of turbo codes and the subsequent rediscovery of low-density parity-check (LDPC) codes represent major milestones in the field of channel coding. Recent advances in the design and theory of turbo codes and their relationship to LDPC codes are discussed. Several new interleaver designs for turbo codes are presented which illustrate the important role that the interleaver plays in these codes. The relationship between turbo codes and LDPC codes is explored via an explicit formulation of the parity-check matrix of a turbo code, and simulation results are given for sum product decoding of a turbo code.

A multiple access/multiple user system called collision frequency shift-keying (CFSK) is investigated. Maximum-likelihood sequence detection (MLSD) provides optimal multiuser detection for the CFSK system but is too complex for practical applications so iterative detection is investigated as a suboptimal approach. The MAP-consensus decoder is given as an example of iterative detection and studied for both the synchronous and asynchronous system. A channel interleaver is introduced so that the performance of the MAP-consensus decoder is asymptotically optimal. The metric of the CFSK system has nonpolynomial complexity so suboptimal metrics with linear complexity are considered. Simulation results show that iterative detection with reduced complexity metrics achieve good performance for moderate spreading factors.

There are several cases where the maximum free distance (MFD) time-invariant convolutional code of a given rate and total encoder memory does not meet the Heller bound or where the encoder that does meet the Heller bound is catastrophic. In order to find codes that meet the Heller bound, it is sometimes necessary to use time-varying convolutional codes. Some periodic time-varying convolutional codes with free distance greater than the best known time-invariant code of the same rate and total encoder memory are presented. These codes also achieve the Heller bound for the given code parameters. In addition, the use of time-varying encoders in order to achieve "spectral thinning" is explored.

The use of the residual redundancy present at the output of a source encoder for the purpose of error correction and detection is explored. Joint source/channel coding schemes of this type utilize redundancy due to the mismatch between the source and the model used to design the source encoder. This idea is extended to include the use of a precoder at the transmitter to create additional redundancy for error correction. A list Viterbi decoder is used at the receiver to perform joint source/channel decoding. The efficacy of this approach is investigated through computer simulation and comparisons to alternative joint source/channel coding schemes.

The performance of turbo codes is addressed by examining the code's distance spectrum. The "error floor" that occurs at moderate signal-to-noise ratios is shown to be a consequence of the relatively low free distance of the code. It is also shown that the "error floor" can be lowered by increasing the size of the interleaver without changing the free distance of the code. Alternatively, the free distance of the code may be increased by using primitive feedback polynomials. The excellent performance of turbo codes at low signal-to-noise ratios is explained in terms of the distance spectrum. The interleaver in the turbo encoder is shown to reduce the number of low-weight codewords through a process called "spectral thinning." This thinned distance spectrum results in the free distance asymptote being the dominant performance parameter for low and moderate signal-to-noise ratios.

The sensitivity of the compressed image representation to bit errors requires application of a channel code before transmission over noisy channels. To prevent the uncontrolled degradation caused by a channel error, an error controlling channel code is applied to the compressed representation before transmission. Many image communication systems have constraints on bandwidth, power and time which prohibit transmission of uncompressed raw image data. Compressed image formats, however, are extremely sensitive to bit errors which can seriously degrade the quality of the image at the receiver. A new list-based iterative trellis decoder is proposed which accepts feedback from a post-processor which can detect channel errors in the reconstructed image. Experimental results are shown which indicate the new decoder provides significant improvement over the standard Viterbi decoder.

A general parity-check equation is presented that defines rotationally invariant trellis codes of rate k/(k+1) for two-dimensional signal sets. This parity-check equation is used to find rate k/(k+1) codes for 4PSK, 8PSK, 16PSK, and QAM signal sets by systematic code searches. The MPSK codes exhibit smaller free Euclidean distances than nonrotationally invariant linear codes with the same number of states. However, since the nonlinear codes have a smaller number of nearest neighbors, their performance at moderate signal to noise ratios is close to that of the best linear codes. The rotationally invariant QAM codes with 8, 32, 64, and 256 states achieve the same free Euclidean distance as the best linear codes. Transparency of user information under phase rotations is accomplished either by conventional differential encoding and decoding, or by integrating this function directly into the code trellis.>