5153 research outputs found
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Banana Peel Decomposition in Microgravity: A UB-Student Spaceflight Experimental Project Mission 12
No full textIn this experiment, the decomposition speed of a banana peel in microgravity versus the decomposition speed of a banana peel on earth will be determined. The banana peel may decompose slowly while it is exposed to microgravity but if it does, then compost can be, better supply of nutrients to the plant, stabilization of soil pH and possibly suppressing soil-borne plant pathogens. created as a result of decomposed organic matter. If a banana peel can decompose in the ISS, the astronauts can use the compost to grow better plants than before. The many benefits of compost are (but not limited to) better soil structure for holding roots, improved water holding capacity
Does Big Government Cause Poverty?
No full textPhilip Maymin's poster examining the wage gap between free market and large government economies
Reciprocal Mentoring: An Innovative Clinical Exercise
No full textReciprocal mentoring is a relationship concept that harnesses the power of mentoring into a mutually beneficial relationship in which participants take turn learning from each other. Nursing students enrolled in a gerontology course participated in a reciprocal mentoring assignment instead of a traditional clinical placement. This was a pilot study using a qualitative design. 15 students were paired with 15 older adults to learn about the process of aging from each other. Three themes emerged after data analysis namely, competency in assessment skills, increased knowledge of aging and more positive outlook of aging
Design and Simulation of a BioMEMS Leukocyte Counter with Concurrent Processing
No full textCell counting (such as white blood cells, red blood cells) is a popular technique being used in blood testing for disease diagnosis. It can give important indication about the health condition of a patient, and give hints for doctors to effectively diagnose disease. In this poster, a BioMEMS (Bio-Microelectromechanical Systems) cell counter with concurrent processing is proposed. It has presorting stage to separate out red blood cells, white blood cells and/or other cells of interest from the microfluidic flow of blood sample. The cells are then passed to branching stage to divide it into multiple braches. Each branch allows cells to pass through the microchannel in series. The cell counting is achieved by electrical impedance sensing. By introducing concurrent counting based on branching, it leads to faster throughput and improved efficiency. The proposed BioMEMS cell counter is designed and simulated in COMSOL. Simulation results verified the correct counting function of the cell counter device
Classroom Engagement: Encouraging Attention vs Punishing Distraction
No full textGiven the rise in ownership and use of personal communication devices-Smartphones-by undergraduate students while attending classes, this study examines undergraduate students’ attitudes and perceptions regarding their rights to use such devices and their knowledge regarding the negative effect such usage has on their ability to synthesize new subject material. Given prior research into the negative aspects of digital devices in the classroom, this study examines the effect, if any, of using positive reinforcement versus restrictive bans to encourage believed appropriate learning behavior
Prospect Theory & Gain Aversion: How People Make Decisions
No full textTanuj Gupta and Philip Z. Maymin's poster on how people make decisions through the lense of prospect theory and gain aversion
Evolutionary Modular Robotics: Survey and Analysis
No full textThis paper surveys various applications of artificial evolution in the field of modular robots. Evolutionary robotics aims to design autonomous adaptive robots automatically that can evolve to accomplish a specific task while adapting to environmental changes. A number of studies have demonstrated the feasibility of evolutionary algorithms for generating robotic control and morphology. However, a huge challenge faced was how to manufacture these robots. Therefore, modular robots were employed to simplify robotic evolution and their implementation in real hardware. Consequently, more research work has emerged on using evolutionary computation to design modular robots rather than using traditional hand design approaches in order to avoid cognition bias. These techniques have the potential of developing adaptive robots that can achieve tasks not fully understood by human designers. Furthermore, evolutionary algorithms were studied to generate global modular robotic behaviors including; self-assembly, self-reconfiguration, self-repair, and self-reproduction. These characteristics allow modular robots to explore unstructured and hazardous environments. In order to accomplish the aforementioned evolutionary modular robotic promises, this paper reviews current research on evolutionary robotics and modular robots. The motivation behind this work is to identify the most promising methods that can lead to developing autonomous adaptive robotic systems that require the minimum task related knowledge on the designer side.https://doi.org/10.1007/s10846-018-0902-
Cruelty - Free Design
No full textA vegan designer does not incorporate any products, materials, or fabrics that contain, harm, torture, or exploit any conscious living being. Vegan design acknowledges that all living creatures have emotions, feelings, experience pain, and should not be used for the sake of luxury
Machine Learning Approaches for Flow-Based Intrusion Detection Systems
No full textIn cybersecurity, machine/deep learning approaches can predict and detect threats before they result in major security incidents. The design and performance of an effective machine learning (ML) based Intrusion Detection System (IDS) depends upon the selected attributes and the classifier. This project considers multi-class classification for the Aegean Wi-Fi Intrusion Dataset (AWID) where classes represent 17 types of the IEEE 802.11 MAC Layer attacks. The proposed work extracts four attribute sets of 32, 10, 7 and 5 attributes, respectfully. The classifiers achieved high accuracy with minimum false positive rates, and the presented work outperforms previous related work in terms of number of classes, attributes and accuracy. The proposed work achieved maximum accuracy of 99.64% for Random Forest with supply test and 99.99% using the 10-fold cross validation approach for Random Forest and J48
