Critical Thinking in Electrical and Computer EngineeringAbstractIn evaluating how the Department of Electrical and Computer Engineering (ECE) will meet therequirements of a recently launched, University-wide, quality enhancement program (QEP), ECEfaculty were questioned about the role of critical thinking in their teaching and in the professionof engineering. There was unanimous agreement that critical thinking is an importantrequirement to be successful within the engineering profession. However, at the present, criticalthinking is not an explicit component in course lectures, syllabi, or objectives, assuming instead,that students understand critical thinking and its role in the practice of engineering. In an effortto help students become better critical thinkers and appreciate the importance of its practicethroughout their education and careers, critical thinking and engineering reasoning will beincorporated in selected courses throughout the ECE curriculum.As part of the School of Engineering’s response to the University wide quality enhancementprogram (QEP) all incoming freshman are given explicit and implicit instruction in criticalthinking in Introduction to Engineering (XXXX XXX), a compulsory course for all freshmanengineering students. In XXXX XXX students are taught explicitly about critical thinking byusing the Paul-Elder model of critical thinking to define and operationalize critical thinking. Theinstruction is followed by explicit critical thinking exercises. Also during the course, several casestudies are presented where students learn about and explore the practice of engineering ingreater detail. Both the instructor’s discussion of case studies and related assignments includeimplicit and explicit critical thinking elements. The critical thinking instruction in XXXX XXXprepares students to embrace more elaborate critical thinking required of them in future,discipline specific, courses and begins associating critical thinking with the practice andprofession of engineering.At the sophomore level, the XXX XXX Network Analysis I and XXX XXX Logic Designcourses have been selected for critical thinking emphasis. Students will be encouraged to use thecritical thinking skills which were developed during XXXX XXX, to analyze requirements andconstraints which would apply in real-world design projects using the material covered in thesetwo courses. At the junior level, similar use of critical thinking will be applied in XXX XXXEmbedded Systems, which looks at the design and application of microcontroller systems. Atthe senior level, critical thinking skills will again be strengthened and assessed in the XXX XXXCapstone Design Course and the XXX XXX Professional Issues and Current Topics Seminar.The latter course emphasizes understanding of professional ethics and current topics in electricaland computer engineering. At the present, the instructors for XXX XXX are developingbenchmark data about critical thinking abilities, against which future students, having the fullexposure to critical thinking instruction, will be compared. A summary of this initial data will bepresented and discussed in the full paper.

This chapter describes the formal modeling and machine-checking of a bump-in-the-wire device that secures field device communications in industrial control networks. Field devices serve as the connection points between computer-based control systems and the physical processes being controlled. Industrial control network traffic is routinely checked for transmission errors, but limited mechanisms are available for combating attacks that exploit industrial control protocols to target critical infrastructure assets. This chapter focuses on a bump-in-the-wire solution that can be retrofitted on field devices to provide security functionality. The TLA+ formal specification language in combination with the isolation guarantees provided by the seL4 microkernel are used to demonstrate that the bump-in-the-wire solution provides important security and liveness properties. The resulting machine-checked system correctly applies hash-based message authentication to verify the authenticity of incoming messages while being resistant to attacks.

The authors combined virtual reality technology and social robotics to develop a tutoring system that resembled a small-group arrangement. This tutoring system featured a virtual teacher instructing sight words, and included a humanoid robot emulating a peer. The authors used a multiple-probe design across word sets to evaluate the effects of the instructional package on the explicit acquisition and vicarious learning of sight words instructed to three children with autism spectrum disorder (ASD) and the robot peer. Results indicated that participants acquired, maintained, and generalized 100% of the words explicitly instructed to them, made fewer errors while learning the words common between them and the robot peer, and vicariously learned 94% of the words solely instructed to the robot.

The authors of the current investigation developed and evaluated the effects of a tutoring system based on a small-group arrangement to two young adults with autism spectrum disorder on the acquisition, maintenance, and generalization of sight words. The tutoring system was comprised of a virtual teacher to instruct sight words, and a humanoid robot which adopted a peer metaphor, where its function was to act as an emulated peer. With the introduction of the robot peer (RP), the traditional dyadic interaction in tutoring systems was augmented to a novel triadic interaction in order to enrich the social content of the learning environment and to facilitate observational learning (OL). The virtual teacher implemented a constant time delay strategy to instruct three types of sight words: (a) target words exclusive to the participant, (b) target words common between the participant and the RP, and (c) nontarget words exclusive to the RP. In order to examine the efficacy of intervention, a multiple-probe design across three word sets, replicated across two participants, was utilized. Results indicated that both participants acquired, generalized, and maintained target words with 100% accuracy. Furthermore, the participants made fewer errors and required less instruction time to learn the words common between the participants and the RP. Finally, the participants acquired, through OL, the majority of words taught exclusively to the RP.

Industrial control systems monitor, regulate, and control much of our critical infrastructure, including electric power, manufacturing, water and wastewater, oil and gas pipelines, rail transportation, chemical processing plants, and others. Twenty years ago these systems were largely isolated and physical security was the primary security challenge. Today these systems have become vulnerable to electronic intrusion and disruption due to increased use of commodity hardware and software, the move away from isolated industrial systems and enterprise ties to the Internet. This retrospective paper discusses the many cyber vulnerabilities of current industrial control systems, the root causes of these vulnerabilities, and recent advances which will address some of these issues.

In the current study, we examined the effects of an instructional package comprised of an autonomous pedagogical agent, automatic speech recognition, and constant time delay during the instruction of reading sight words aloud to young adults with autism spectrum disorder. We used a concurrent multiple baseline across participants design to evaluate the efficacy of intervention and conducted post-treatment probes to assess maintenance and generalization. Our findings suggest that all three participants acquired and maintained new sight words and demonstrated generalized responding.

This chapter presents a new paradigm that limits and protects information flows to internal and subcontracted factory floor devices to complement perimeter security as essential first steps to secure manufacturing as it embraces Industry 4.0.

While machines (e.g., computers, tablets, cellphones, robots) have begun to co-exist with humans and cooperatively share various tasks; they are still deficient in interpreting and responding to humans as emotional beings. Wearable biosensors that can be used for computerized emotion recognition have great potential for addressing this issue. This paper presents a novel wearable sensor - EmotiGO - for unobtrusive acquisition of a set of physiological signals, i.e., skin conductivity, photoplethysmography, and skin temperature, which can be used as autonomic readouts of emotions. EmotiGO is unobtrusive and sufficiently lightweight to be worn comfortably without interfering with the users' usual activities. EmotiGO's open software and communication protocol provide an easy way for developers to interact with the device and design custom applications. We present the architecture of the device and results from testing that verify its effectiveness against an FDA-approved system for physiological measurement.

The vulnerability of industrial control systems (ICS) to electronic intrusion and malware has recently been well documented in both the technical and popular press. Despite significant attention and much progress over the past 15 years, threats continue to evolve about as fast as preventive solutions. This paper reviews the root causes of ICS cybersecurity vulnerabilities, looks at some common defensive measures and then discusses a new approach to ICS field device cybersecurity, the security preprocessor. This device offers advanced communications security and role-based access control for legacy ICS installations, and utilizes a verified microkernel, with proven security properties.

Coursework that instills patterns of rigorous logical thought has long been a hallmark of the engineering curriculum. However, today’s engineering students are expected to exhibit a wider range of thinking capabilities both to satisfy ABET requirements and to prepare the students to become successful practitioners. This paper presents the initial results from a systematic effort to incorporate broader critical thinking instruction and assessment into electrical and computer engineering education as part of a university-wide quality enhancement program. All incoming freshmen are given explicit and implicit instruction in critical thinking in ENGR 100: Introduction to Engineering and other engineering fundamentals courses, using the Paul-Elder framework of critical thinking to define and operationalize critical thinking. This critical thinking foundation is reinforced later in the disciplinary courses so that students integrate critical thinking with the basic principles and practices of engineering. In the Electrical and Computer Engineering (ECE) program, at the sophomore level, students use critical thinking skills which were developed during their engineering fundamentals courses, to analyze requirements and constraints which would apply in real-world design projects. At the junior level, similar use of critical thinking is applied in an introductory computing methods course; and at the senior level, critical thinking skills are again strengthened and assessed in the capstone design course and in the professional issues and current topics seminar. The latter course emphasizes understanding of professional ethics and current topics in electrical and computer engineering. Initial data from this pilot implementation indicates statistically significant improvement in critical thinking skills in ECE students who have progressed through this sequence, and as a side benefit, it appears that writing skills also improve.

Intelligent power grid research, i.e. smart grid, involves many simultaneous users spread over a relatively large geographical area. A tool for advancing research and community education is presented utilizing large-scale visualization centers, e.g. planetariums, in simulating smart grid interactions. This approach immerses the user in virtual smart grid visualization and allows the user, with several other users, to interact in real time. This facilitates community education by demonstrating how the power grid functions with smart technologies. The simulation is sophisticated enough to also be used as a research tool for industry and higher education to test software algorithms, deployment strategies, communications protocols, and even new hardware.

Pedestrian detection is an important problem in the design of driving assistance systems that can reduce accidents and save lives. Although many annotated visible pedestrian datasets are publically available, similar annotated thermal datasets are rare. S uch datasets are essential for training a classifier that can be used for pedestrian detection at night from thermal images. Manual annotation for large datasets is a tedious and time consuming option. In this paper, we propose an automatic alternative for constructing an annotated thermal imaging pedestrian dataset by transferring detections from registered visible images simultaneously captured at day- time where pedestrian detection is well developed in visible images. Histogram of Oriented Gradients (HOG) features are extracted from the constructed dataset and then fed to a discriminatively trained part based classifier that can be used to detect pedestrians at night. The resulting classifier was tested for night driving assistance and succeeded to predict pedestrians even in the situations where visible imaging pedestrian detectors failed because of low light or glare of oncoming traffic.

Recently, several approaches for pedestrian detection have been investigated using discriminatively trained part based models with which Histogram of Oriented Gradients (HOG) showed to be a robust feature. In this paper, we propose a new feature based on HOG to be used with the discriminatively trained part framework for pedestrian detection. Our method is based on computing the image mixed partial derivatives to be used to redefine the gradients of some pixels and to reweigh the vote at all pixels with respect to the original HOG. Our approach was tested on the PASCAL2007 and INRIA person dataset and showed to have an outstanding performance.

This paper presents the results from a recent evaluation of the reliability and cyber-security vulnerability of telemedicine/telehealth systems used today in the United States. As this technology becomes more widely used in an effort to reduce costs and better serve remote and isolated populations, these issues will undoubtedly become more pronounced. This paper presents some background information about telemedicine/telehealth systems and an overview of recognized reliability and cyber-security risks. It then discusses a national survey of equipment and software vendors for telemedicine/telehealth, discusses a risk scoring system that was developed as part of the project, and presents overall results and recommendations for future work in this area.

In this paper, We propose a new approach for solving the Lambertian shape from shading (SFS) problem. The proposed technique employs image information as well as camera calibration parameters. We claim that the incorporation of camera parameters results in a better surface reconstruction. In this work, we slightly modify this more realistic model in order to take into account the attenuation of the illumination due to distance. We propose a new variational formulation that relates an evolving surface model with image information, taking into consideration that the image is taken by a perspective camera with known parameters. A new energy functional is formulated to incorporate brightness, smoothness, and integrability constraints. All of these terms assume a hyper surface that evolves in time to meet their criteria. Gradient descent optimization with Euler-Lagrange is used for optimization. We constructed a database of real surfaces as a ground-truth for the experiments. The proposed approach shows superior performance when compared with other approaches in the literature.

In this paper, we propose a thermal image based measurement technique for the volumetric flow rate of a liquid inside a thin tube. Our technique makes use of the convection heat transfer dependency between the flow rate and the temperature of the flowing liquid along the tube. The proposed method can be applied to diagnose superficial venous disease non-invasively by measuring the volumetric blood flow rate from a FLIR LWIR single thermal image.