Educational approach to the wye–delta transformations using simple circuit analysis techniques

Between 2008 and 2010 an introductory circuit analysis course for second year engineering students had its lectures recorded (2008 was audio only, other years were by video) and the recordings were made available to registered students as a supplemental resource. Attendance to lectures was still required. In 2011 an introductory programming course was recorded in a similar way. In each of these offerings the students were anonymously surveyed at the end of the course using an online survey tool with most questions using a five point Likert category scale. The survey looked at the perceived usefulness of the recordings, the approach to watching and the impact on attendance. The responses showed strong support to having video lecture capture and the reported use of the videos was to watch selected material. There was a difference between the courses on the impact on attendance, with the circuit analysis course indicated little impact on attendance, whereas the responses from the other course indicates more missed lectures due to the availability of recordings.

Contribution: This article describes the implementation, assessment, and evaluation of conceptual-based writing exercises in an introductory course on electric circuit analysis. Background: Students’ struggles in gateway courses such as circuit analysis are often traced to inadequate metacognitive skills on the part of the student as well their misconceptions regarding fundamental phenomena related to the course. Writing is known to be a powerful tool for insight into a student’s thought process and to foster metacognitive activity. Research Questions: What effect does the use of short writing exercises have on students’ understanding of fundamental concepts related to the behavior of electric circuits operating at dc? What effect does the use of the conceptually based writing exercises have on students’ ability to justify their responses when answering conceptual questions related to basic electric circuit concepts? Methodology: In the first semester of the study, a single writing exercise was given and in the second semester, a total of five such exercises were administered. In each semester, students were separated into “at-risk” and “not at-risk” groups based on their responses to the first writing exercise. A <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2 \times 2 \times $ </tex-math></inline-formula> (2) mixed analysis of variance (ANOVA) was conducted, with at-risk/not at-risk and semester/semester between-subjects factors and pre-test/post-test on a multiple-choice conceptual-based exam a within-subjects factor. Findings: Results suggest that only the at-risk group may have benefited in terms of deepened conceptual understanding and the ability to justify their responses from the use of multiple conceptual-based writing exercises.

Nowadays, Information and Communication Technologies (ICT) make great strides in computer assisted education. They enable development of new, Self-Directed Learning (SDL) driven, models of teaching and learning, and among them, Flip Teaching (FT) seems to be the most promising one. The flipped classroom is based on e-materials, then, the associated assessments have to be fully based on e-tests, FT-Computer-Assisted Assessment (CAA) program. Design of such program is the main motivation of the described research. Matching of this program to FT characteristics, taking into account both specific structure of the learning content and students behavior is the main objective. After a short introduction to FT, the e-test organization in the flipped classroom is briefly discussed. Then, Electric Circuit Analysis course case study is presented: organization of Moodle-quizzes based assessment program, taking into account common students behavior, their good and bad habits, is shown, conclusions are drawn and some guidelines are given.

Linear circuit analysis is a foundational course for electrical engineers. Instructors of linear circuit analysis courses have traditionally relied on print textbooks for student learning materials. With the rise of student use of computers and the internet, materials like lecture slides and online videos have also been used for learning materials. Increasingly, traditional textbooks (including online formats) are experiencing a decline, while interactive textbooks are growing in popularity. This paper describes auto-graded learning tools, called challenged activities, from various topics in an online linear circuit analysis textbook. Instructors often assign challenge activities as homework. Each challenge activity has 3-5 levels of increasingly difficult problems. Each level randomly generates a question from a large set of questions of similar difficulty. Students must correctly answer a question in a level to progress to the next level. This paper describes the student usage of 4 challenge activities in an online circuit analysis textbook. The average time spent per activity was under 10 minutes and the vast majority of students who started a level ended up completing that level, indicating little attrition. In fact, most levels had 0% of students give up and the highest was only 8%, which is remarkably low based compared to more traditional paper-and-pencil activities based on the teaching experience of the authors.

The reform of any course cannot be accomplished in one move and needs to be improved continuously for a long time. The scheme of blended learning reforms was shown from selecting online learning resources, dividing curriculum content, the problem of Blending learning hours and the implementation of discussion and cooperative learning in this paper. We also discussed some problems faced by Fundamentals of Circuit Analysis course in the Blending learning reform, and shared some of the accumulated experience and relevant suggestions. After 4 years’ blended learning reforms, the class based on Fundamentals of Circuit Analysis has effectively improved the dull state, and enhanced students’ interest in learning, which has also significantly improved the teaching effect. At the same time, this “student-centered” teaching design plays a great role in cultivating students’ innovation ability.

In this work, which is intended to be a Work in Progress Paper in the Research Category, the results of an extensive study which used three-factor and two-factor linear regression models based on prior grade point average, grades in a pre-requisite physics course, and class size is presented. In both models prior GPA was the most significant factor in predicting student success, followed by the grade in a prerequisite physics course. Even though class size was not a significant factor, removing it from the analysis lowered the R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> values. The study analyzed 39 sections of an introduction to circuit analysis course from fall 2013 to spring 2018 and examined whether previously published novel treatments or class size (or both) were the reason for increased pass rates. It was found that there were no significant entry behavior differences between those students who enrolled in a traditional course vs. the students enrolled in a directed self-placement course. It was found that the sections that used the directed self-placement policy tended to outperform sections that did not use this policy.

In the gossip problem each node of the graph G possesses a unique piece of information - the gossip message. A sequence of one-way or two-way communications between pair of nodes is made to spread the messages so that any node of the graph knows all the gossips. The question is, what is the minimum number of calls between pairs of nodes needed to exchange all gossip messages? The solution to the two-way communication gossip problem is that \(2N-4\) calls (\(N\ge 4\)) suffice if and only if the graph contains a four cycle subgraph. For one-way communication problem the classical results states that in a strongly connected graph \(2N-2\) calls (\(N\ge 4\)) suffice. In this paper we consider the gossip problem in the context of saving the energy consumed by the sensor network nodes. In the process of gossiping the network nodes consume their energy resources. The amount of consumed energy depends on the cost of transmission between pairs of nodes, a selected transmission route and the sizes of the gossip messages. For the fixed size of gossip messages and the fixed cost of transmission of one unit of data between pairs of nodes we search for the optimal transmission route of the gossip messages such that the most overloaded node consumes the minimum amount of energy. We define the network lifetime for the gossiping process as the time until the first node of the network runs out of its energy. By minimizing the energy of the most overloaded node we obtain the solution to the network lifetime gossiping problem. In the paper we solve the problem for the one-dimensional regular sensor network. We propose a load balancing algorithm for solving the problem in networks with evenly distributed sensors in a given area such that an equal energy solution of the problem exists. We also propose a data aggregation scheduling algorithm to calculate the minimum number of calls necessary to spread the gossip messages for a given solution of the network lifetime gossiping problem.

We study the problem of allocating optical bandwidth to sets of communication requests in all-optical networks that utilize Wavelength Division Multiplexing (WDM). WDM technology establishes communication between pairs of network nodes by establishing transmitter- receiver paths and assigning wavelengths to each path so that no two paths going through the same fiber link use the same wavelength. Optical bandwidth is the number of distinct wavelengths. Since state-of-the-art technology allows for a limited number of wavelengths, the engineering problem to be solved is to establish communication between pairs of nodes so that the total number of wavelengths used is minimized; this is known as the wavelength routing problem.In this paper we survey recent advances in bandwidth allocation in tree- shaped WDM all-optical networks. We present hardness results and lower bounds for the general problem and the special case of symmetric communication. We also survey various techniques that have been developed recently, and explain how they can be used to attack the problem. First, we give the main ideas of deterministic greedy algorithms and study their limitations. Then, we show how to use various ways and models of wavelength conversion in order to achieve almost optimal bandwidth utilization. Finally, we show that randomization can help to improve the deterministic upper bounds.KeywordsBipartite GraphGreedy AlgorithmBinary TreeOptical NetworkWavelength Division MultiplexThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

We study the problem of allocating optical bandwidth to sets of communication requests in all–optical networks that utilize Wavelength Division Multiplexing (WDM). WDM technology establishes communication between pairs of network nodes by establishing transmitter–receiver paths and assigning wavelengths to each path so that no two paths going through the same fiber link use the same wavelength. Optical bandwidth is the number of distinct wavelengths. Since state–of–the–art technology allows for a limited number of wavelengths, the engineering problem to be solved is to establish communication between pairs of nodes so that the total number of wavelengths used is minimized; this is known as the wavelength routing problem. In this paper we survey recent advances in bandwidth allocation in tree–shaped WDM all–optical networks. We present hardness results and lower bounds for the general problem and the special case of symmetric communication. We give the main ideas of deterministic greedy algorithms and study their limitations. We demonstrate how we can achieve optimal and nearly–optimal bandwidth utilization in networks with wavelength converters using simple algorithms. We also present recent results about the use of randomization for wavelength routing.

VLSI designs contain very large resistive networks consisting of hundreds of millions (10e11) of resistors. Accurate parasitic extraction and analysis of such large networks is essential in many phases of the VLSI design flow. Existing techniques to analyze large resistive networks using linear solvers, despite recent optimizations, still take prohibitive computation time. In this paper a new technique based on low-distortion embedding to estimate point-to-point effective resistance is presented. Our proposed method employs recently discovered techniques from theoretical computer science to compute an e-approximate resistance embedding matrix from which effective resistances of all node pairs can be estimated as easily as taking the Euclidean norm of column differences. The proposed method runs in almost linear time (linear in the number of resistors), and the accuracy (e) is user specified. The method has been implemented and experimental results on large networks containing upto 10e11 nodes are presented. Compared to existing method using sparse linear solvers, our methods are more than 10 times faster on mesh networks and more importantly given a network of n nodes, allow computation of effective resistance between arbitrary node pairs in O(lg(n)) time (lg denotes logarithm to base 2).

Introduction to Linear Circuit Analysis and Modelling

This research work-in-progress paper investigates faculty perspectives on the switch to online experimentation modalities in the context of our Fundamentals of Circuit Analysis course that includes online laboratory modules. While online (remote and virtual) laboratories have long been considered promising supplemental educational tools, the risks and challenges associated with delivering online labs have limited the willingness of faculty to adopt these methods. However, the development of knowledge, methodologies, and success factors for effective online laboratory instruction is a critical and timely need. With this work, we develop an evidence-based understanding of the transition from hands-on to online experimentation and its associated challenges for faculty. We furthermore generate fundamental knowledge about online experimentation adoption in engineering programs, which includes the full spectrum of faculty participants (early, later, and "never" adopters). Preliminary results show that the most important aspects for faculty in the context with switching to online labs are scheduling flexibility and individualized support, learning outcome differences, a connection between lecture and the lab, and student engagement.

Little is known about geographic properties of large-scale social networks. In this paper, we examine the geospatial attributes of a planetary-scale social network of 240 million people and 1.3 billion edges. We study the interplay among topological, geographical, and algorithmically generated paths connecting pairs of nodes in a social network. Starting in the realm of cyberspace, we find that topologically shortest paths of average length of 6.6 exist between pairs of nodes in the network and that the average degree of separation among nodes is robust to removal of hub nodes. Moving to the realm of locations and distances in geographic space, we find that topologically shortest paths in the social graph grow with increasing geographic distance between path's endpoint nodes. We discover that shortest topological paths are geographically inefficient, but that geography provides an important cue for local algorithmic policies for navigating between source and target nodes. Local algorithmic strategies for navigating the larger network structure in the absence of global navigation procedures have varying success. At the early stages of the navigation, navigating to a hub node helps, while in the middle stage, geography provides the most important clue. While local algorithms for navigating have trouble reaching the target node, they are successful in reaching nodes that are geographically close to the target. Taken together, our results demonstrate a complex interplay between topological and geographical properties of social networks and explain the success of local strategies for navigating such networks.

Mathematical modeling is seen as a key step to understand, predict, and control the temporal dynamics of interacting systems in such diverse areas like physics, biology, medicine, and economics. However, for large and complex systems we usually have only partial knowledge about the network, the coupling functions, and the interactions with the environment governing the dynamic behavior. This incomplete knowledge induces structural model errors which can in turn be the cause of erroneous model predictions or misguided interpretations. Uncovering the location of such structural model errors in large networks can be a daunting task for a modeler. Here, we present a data driven method to search for structural model errors and to confine their position in large and complex dynamic networks. We introduce a coherence measure for pairs of network nodes, which indicates, how difficult it is to distinguish these nodes as sources of an error. By clustering network nodes into coherence groups and inferring the cluster inputs we can decide, which cluster is affected by an error. We demonstrate the utility of our method for the C. elegans neural network, for a signal transduction model for UV-B light induced morphogenesis and for synthetic examples.

Low cost ad hoc networks like Wireless Sensor Networks (WSNs) are best suited to gather sensory information. Sensitivity of these classified information leads to the necessity of implementing security protocols during their exchange. Such implementations use cryptosystems that may suit resourceful Internet of Things (IoT) devices; but overburdens tiny sensors. Moreover most protocols assume that an adversary is well versed with all system information, barring the cryptographic keys. As such the (fixed) operational frequency bands between a given pair of nodes is assumed to be known at all times. Such a strong assumption may not be always necessary in real life deployment zones. In fact tracking an operational frequency between sensors from a range of bands may be difficult in a large network [15]; though not hard. This leads to a hard problem, i.e., to keep track of recursive switch of operational frequencies between a given pair of sensors for consecutive timestamps. We exploit hardness of this problem to achieve confidentiality of message exchange between pairs of nodes. Message to be transmitted is split using secret sharing technique [18]. Each piece is then transmitted via different bands obtained by recursive use of cryptographic hash function on initial preallocated bands. Our approach does not consume extra energy during message transmission or receipt in comparison to existing wireless systems. Storage requirement is minimized to storage of hash functions; no cryptographic key stored. Security achieved is comparable to any existing cryptosystem.