How Behavior of Nontarget Species Affects Perceived Accuracy of Scat Detection Dog Surveys

Detection dogs, specially trained domestic dogs (Canis familiaris), have become a valuable, noninvasive, conservation tool because they remove the dependence of attracting species to a particular location. Further, detection dogs locate samples independent of appearance, composition, or visibility allowing researchers to collect large sets of unbiased samples that can be used in complex ecological queries. One question not fully addressed is why samples from nontarget species are inadvertently collected during detection dog surveys. While a common explanation has been incomplete handler or dog training, our study aimed to explore alternative explanations. Our trials demonstrate that a scat’s genetic profile can be altered by interactions of nontarget species with target scat via urine-marking, coprophagy, and moving scats with their mouths, all pathways to contamination by nontarget species’ DNA. Because detection dogs are trained to locate odor independent of masking, the collection of samples with a mixed olfactory profile (target and nontarget) is possible. These scats will likely have characteristics of target species’ scats and are therefore only discovered faulty once genetic results indicate a nontarget species. While the collection of nontarget scats will not impact research conclusions so long as samples are DNA tested, we suggest ways to minimize their collection and associated costs

Mechanix: An Intelligent Web Interface for Automatic Grading of Sketched Free-Body Diagrams

Sketching free body diagrams is an essential skill that students learn in introductory physics and engineering classes; however, university class sizes are growing and often have hundreds of students in a single class. This situation creates a grading challenge for instructors as there is simply not enough time nor resources to provide adequate feedback on every problem. We have developed a web-based application called Mechanix to provide automated real-time feedback on hand-drawn free body diagrams for students. The system is driven by novel sketch recognition algorithms developed for recognizing and comparing trusses, general shapes, and arrows in diagrams. We have discovered students perform as well as paper homework or other online homework systems which only check the final answer through deployment to five universities with 450 students completing homework on the system over the 2018 and 2019 school years. Mechanix has reduced the amount of manual grading required for instructors in those courses while ensuring students can correctly draw the free body diagram

Impact of a sketch-based tutoring system at multiple universities

Large class sizes in engineering programs often prevent instructors from providing detailed and meaningful feedback to students on their homework problems. While the literature shows that frequent and immediate formative feedback has several benefits in terms of knowledge gain and academic motivation, several instructors struggle to provide any feedback. Motivated by this inability, a sketch-based virtual tutoring system, named Mechanix, has been developed and implemented. Mechanix lets the students to sketch their freebody diagram on a virtual interface and the process involved is very close to using a pencil and paper. The system provides real-time feedback on the accuracy of their Freebody diagrams and the solution to the problem. This paper reports the implementation of Mechanix at two large public universities in the United States - Georgia Institute of Technology and Texas State University. Mechanix is used to solve specific assignments from each school that involve the use of freebody diagrams. Pre- and post- concept inventories are used to measure the improvements in the conceptual understanding of the students. The results show that students who solve their homework using Mechanix outperform their peers who do not in one school, whereas the results are similar across the two groups in the second school. The evaluation of the concept inventories shows that the students who used Mechanix has the same level of improvement in their conceptual knowledge compared to the control group

Sketchtivity, an Intelligent Tutoring Software: Broadening Applications and Impact

Freehand sketching is an essential skill for engineers. Sketching enables designers to represent ideas rapidly and offload working memory. Sketches in the design process also correlate with positive design outcomes. Teaching sketching to engineers, however, presents many challenges in engineering curriculums. Sketching is most often taught in large entry-level courses where individualized feedback, which is vital to learning sketching, is not possible. Sketchtivity is an intelligent tutoring software designed to aid in the practice and feedback on freehand sketching skills. Sketchtivity teaches the basics of two-point perspective sketching providing lessons, feedback, and tips on how to improve. The goal of this project is to implement Sketchtivity at a broader range of universities, to expand on the software functionality, and to understand more about the implications of improving sketching skill. Sketchtivity is currently being implemented in classrooms at three diverse universities across the United States. Our research has shown that the tablet interface does not negatively impact students’ sketching skill development. We are currently conducting further experiments to better understand how students are learning from the feedback the software provides. Beyond measuring current impact, this project seeks to expand the functionality of Sketchtivity to offer lessons on more complex sketching tasks and more poignant feedback to learners. The main research goal is focused on improving sketching skills. The remaining goals turn outward toward the implications for improved sketching skill for engineers. It is essential to understand how to measure sketching skill effectively, and what role sketching skill plays in engineering design. Sketching skill has been measured in many different ways in many different fields and there seems to be no consensus on measurement strategy or validity. As a part of this project, we are conducting a systematic literature review of sketching evaluation. This literature review aims to compile the different methods of measurement to remove some of the ambiguity around evaluating sketching skill in engineering research and education. There has been much research on the role of sketching in engineering design, but the research around sketching skill has been limited. Essential to improving skill in any task is understanding how confidence in the skill is affected. Engineers’ self-efficacy can enable or limit their application of skills. We are also looking at how sketching skill is related to drawing self-efficacy. Sketching has the largest impact in the early stages of design. The final research goal of this project is to investigate the relationship between sketching and creativity in the early stages of design. Through experiments of idea generation and sketching abilities, we hope to better understand to what degree sketching enables creativity in design. To summarize, this project seeks to improve sketching skill through Sketchtivity. We are accomplishing this through expanding reach at multiple universities and expanding the capabilities of the software. It is also essential to understand the implications of improving sketching skill. This is being investigated through improved evaluation of sketching and investigations of sketching’s relationship to drawing self-efficacy and creativity

Performance of chemically modified reduced graphene oxide (CMrGO) in electrodynamic dust shield (EDS) applications

Electrodynamic Dust Shield (EDS) technology is a dust mitigation strategy that is commonly studied for applications such as photovoltaics or thermal radiators where soiling of the surfaces can reduce performance. The goal of the current work was to test the performance of a patterned nanocomposite EDS system produced through spray-coating and melt infiltration of chemically modified reduced graphene oxide (CMrGO) traces with thermoplastic high-density polyethylene (HDPE). The EDS performance was tested for a dusting of lunar regolith simulant under high vacuum conditions (~10-6 Torr) using both 2-phase and 3-phase configurations. Uncapped (bare) devices showed efficient dust removal at moderate voltages (1000 V) for both 2-phase and 3-phase designs, but the performance of the devices degraded after several sequential tests due to erosion of the traces caused by electric discharges. Further tests carried out while illuminating the dust surface with a UV excimer lamp showed that the EDS voltage needed to reach the maximum cleanliness was reduced by almost 50% for the 2-phase devices (500 V minimum for rough and 1000 V for smooth), while the 3-phase devices were unaffected by the application of UV. Capping the CMrGO traces with low-density polyethylene (LDPE) eliminated breakdown of the materials and device degradation, but larger voltages (3000 V) coupled with UV illumination were required to remove the grains from the capped devices.Comment: 22 pages, 7 figure

Spinneret: Aiding Creative Ideation through Non-Obvious Concept Associations

Mind mapping is a popular way to explore a design space in creative thinking exercises, allowing users to form associations between concepts. Yet, most existing digital tools for mind mapping focus on authoring and organization, with little support for addressing the challenges of mind mapping such as stagnation and design fixation. We present Spinneret, a functional approach to aid mind mapping by providing suggestions based on a knowledge graph. Spinneret uses biased random walks to explore the knowledge graph in the neighborhood of an existing concept node in the mind map, and provides "suggestions" for the user to add to the mind map. A comparative study with a baseline mind-mapping tool reveals that participants created more diverse and distinct concepts with Spinneret, and reported that the suggestions inspired them to think of ideas they would otherwise not have explored.Comment: ACM CHI 202

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Design-by-analogy and representation in innovative engineering concept generation

Design-by-analogy is an important tool for engineers seeking innovative solutions to design problems. A new method for systematically guiding designers in seeking analogies, the WordTree Design-by-Analogy Method, was created based knowledge gained from a series of experiments and prior literature. The WordTree Method linguistically re-represents the design problem and leads the designer to unexpected, novel analogies and analogous domains. A controlled experiment and the applications of the method to a number of engineering projects prove the method's value. Designers implementing the method identify a greater number of analogies. Application of the method to a set of engineering project resulted in unexpected, novel analogies and solutions. A set of experiments to more deeply understand the individual cognitive and the group social process employed during analogical design guides the development of the WordTree Design-by-Analogy Method. A series of three experiments shows the effects of the problem representation and how the analogy is initially learned on a designers' ability to use the analogy to solve a future design problem. The effect of the problem representation depends on how the analogy is initially learned. Learning analogies in more domain-general representations facilitates later retrieval and use. A fourth experiment explored group brainwriting idea generation techniques including 6-3-5, Gallery, C-Sketch and Brainsketching through a 3 X 2 factorial experiment. The first factor controls how teams represent their ideas to each other, words alone, sketches alone or a combination. The second factor determines how teams exchanged ideas, either all the ideas are displayed on the wall or sets of ideas are rotated between team members. The number, quality, novelty and variety of ideas are measured. The greatest quantity of ideas is produced when teams use a combination of words and sketches to represent their ideas and then rotationally exchange them. This corresponds to a hybrid 6-3-5/C-Sketch method.Mechanical Engineerin

Establishing Functional Concepts Vital for Design by Analogy

DOI: http://dx.doi.org/10.1109/FIE.2015.7344193© 2015 IEEEStudent designers and professionals alike have difficulty accessing appropriate analogies for design problems. Recognizing the advantages of Design-by-Analogy (DbA), the Design-Analogy Performance Parameter System (D-APPS) tool was developed to include a library of analogy entries and a matching algorithm. These components are combined into the Design Repository & Analogy Computation via Unit-Language Analysis (DRACULA) software package that maps functions across domains in order to present analogies to designers as initiated through engineering performance metrics and critical functions. Most tools developed for DbA emphasize the searching by function feature. Since analogies are based on more than function, DRACULA incorporates both performance and function for the user to identify relevant analogous solutions. Prior to exposing engineering students to this tool, we investigated their ability to use analogies when crossing domains. During this process, we identified three function concepts to be vital for students to effectively use analogies across domains: reoccurring functions, critical functions, and mapping functions. The results establish a better understanding of the information that students utilize in order to formulate appropriate and creative analogous design solutions.10.1109/FIE.2015.734419

Training Future Designers: A Study on the Role of Physical Models

Physical Models in Engineering Education: Making Tomorrow’s Designers Creative Innovation and creativity are two essential qualities for tomorrow’s designers. In order to nurture these skills in designers, our engineering curricula need to include more hands-on training. In recent times, many engineering educators have recognized the importance of hands-on training in engineering curriculum. Allowing students to build and test their own physical models and learn from their mistakes can be a very effective way of teaching. Recent studies have shown that physical models play a very important role in design innovation and creativity. Building and testing such models can lead designers to identify the flaws in their designs and thus create more functional ideas. At the same time, physical models have the potential to mitigate design fixation to undesirable features present in an example, where design fixation refers to the blind adherence of designers to the features in examples or their own initial ideas. Design fixation is a major hindrance in design creativity; training engineering students with potential tactics to mitigate fixation needs to be a very important component of engineering education. This paper investigates two hypotheses: (1) providing suitable warnings to novice designers can help the min avoiding design fixation (2) fixation to undesirable example features can be mitigated by building and testing physical models of the designs generated by the designers. These hypotheses are tested using a quasi-experiment conducted during a freshmen class project. Students complete their projects in four different experiment groups. One group receives a fixating example with a number of undesirable features. These undesirable features make the example a flawed one, as said features negatively influence the functionality of the design. The second group receives the same fixating example with warnings about the undesirable features that the example contains. The third group receives an effective example that does not contain said features. The fourth group completes the project without the help of an example (control).Students are instructed to build and test their designs and present the final working design to the instructor. The designs are photographed before each testing and the occurrence of example features in each design is studied. The results show that providing warnings about undesirable features in an example does not help students in the mitigation of design fixation. Meanwhile, as they build and test their ideas, they identify the flaws themselves and gradually mitigate the fixation. Their final designs, after many cycles of testing, contain significantly lower fixating features. This shows that building and testing physical models help students in learning through their mistakes and in improving the functionality of their ideas. In our engineering classrooms,learning through hands-on experiences needs to be encouraged in order to nurture a future generation of engineers who are creative and innovative