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Many researchers have studied the roles of building envelope materials on UHI, such as roofs, and walls, but few of them have explored the impacts of the emergence of the solar-reflective coatings, films, and panels but well-visible transmittance that is increasingly applied to glazed building facades, especially in hot climates, for outdoor thermal environments. The question then arises: Despite the positive effects of these strong solar-reflective facades on building heating and cooling energy savings, do they have the same positive effects on the adjacent outdoor area, especially in a dense urban context? This research aims to quantify the potential UHI effects of the solar-reflective facades relative to the non-reflective ones in a dense urban context, along with the heating and cooling energy performance analysis. As such, a simulation method in terms of a series of tools including LBNL Radiance, EnergyPlus, and WINDOW software was adopted in this work to analyze the solar radiation interactions between the façade surface and the surrounding urban structures and potential temperature rise under solar-reflective and non-reflective facades. The result shows that the annual cooling energy savings by using the solar-reflective facades are about 33.8% relative to the typical double-pane clear glazed façade because of the substantial reduction of U-factor and solar heat gains; But, this preliminary work also unveils the potential adverse effects of using such materials at the urban scale, leading nearly 2 times greater solar irradiation and UHI effects than the ones by the solar-non-reflective building surfaces in an urban area. Future optimization studies on the trade-off between the building cooling energy savings and UHI effects by the solar-reflective façades need to be conducted. 

This paper describes preliminary findings from NSF-funded research conducted at the New York Hall of Science with an established after school maker education and social entrepreneurship program called Innovation Institute. Using social entrepreneurship (Peredo & McLean, 2006) and hands–on making activities in a maker space environment, participants address community-focused problems they identify on their own in low-income neighborhoods in Queens,, New York. This project studied whether and how specific aspects of this nine-month, after-school computational making (defined by Rode, et al [2015] as combining computational thinking with skills in aesthetics, creativity, constructing, visualizing multiple representations, and understanding materials) program for 13–17-year-olds from recent immigrant populations may influence participants’ perceptions of the relevance, usefulness and accessibility of computer science and engineering as potential academic and career pathways. 

The purpose of this study is to investigate how different facilitator roles (educator, adult caregiver, peer and self-facilitation) influence children’s learning engagement--specifically, the learning practices of seeking and sharing resources (SSR)--in a museum’s makerspace. We address two research questions: 1). In what ways do learners' engagement vary when facilitated by different facilitator roles? 2). In what ways do different types of facilitators influence SSR practices across age ranges? The results show that facilitation from caregivers and self-directed facilitation is associated with significantly more SSR practices. Additionally, we found that the influence of different types of facilitators on learning engagement varies across ages. Self-directed learning is associated with an increase of SSR as children grow, while facilitation from caregivers is associated with a decline of SSR as children age. Based on these findings, we discuss implications for facilitation in museum makerspace. 

Wearable Cognitive Assistance (WCA) applications use computer vision models that require thousands of labeled training images. Capturing and labeling these images requires a substantial amount of work. By using synthetically generated images for training, we avoided this labor-intensive step. The performance of these models was comparable to that of models that were trained on real images. 

We study the problem of house-hunting in ant colonies, where ants reach consensus on a new nest and relocate their colony to that nest, from a distributed computing perspective. We propose a house-hunting algorithm that is biologically inspired by Temnothorax ants. Each ant is modeled as a probabilistic agent with limited power, and there is no central control governing the ants. We show an O( log n) lower bound on the running time of our proposed house-hunting algorithm, where n is the number of ants. Furthermore, we show a matching upper bound of expected O( log n) rounds for environments with only one candidate nest for the ants to move to. Our work provides insights into the house-hunting process, giving a perspective on how environmental factors such as nest quality or a quorum rule can affect the emigration process. 

We study the problem of house-hunting in ant colonies, where ants reach consensus on a new nest and relocate their colony to that nest, from a distributed computing perspective. We propose a house-hunting algorithm that is biologically inspired by Temnothorax ants. Each ant is modelled as a probabilistic agent with limited power, and there is no central control governing the ants. We show a Ω(log n) lower bound on the running time of our proposed house-hunting algorithm, where n is the number of ants. Further, we show a matching upper bound of expected O(log n) rounds for environments with only one candidate nest for the ants to move to. Our work provides insights into the house-hunting process, giving a perspective on how environmental factors such as nest qualities or a quorum rule can affect the emigration process. In particular, we find that a quorum threshold that is high enough causes transports to the inferior nest to cease to happen after O(log n) rounds when there are two nests in the environment. 

We study the problem of house-hunting in ant colonies, where ants reach consensus on a new nest and relocate their colony to that nest, from a distributed computing perspective. We propose a house-hunting algorithm that is biologically inspired by Temnothorax ants. Each ant is modelled as a probabilistic agent with limited power, and there is no central control governing the ants. We show a (log n) lower bound on the running time of our proposed house-hunting algorithm, where n is the number of ants. Further, we show a matching upper bound of expected O(log n) rounds for environments with only one candidate nest for the ants to move to. Our work provides insights into the house-hunting process, giving a perspective on how environmental factors such as nest qualities or a quorum rule can affect the emigration process. In particular, we find that a quorum threshold that is high enough causes transports to the inferior nest to cease to happen after O(log n) rounds when there are two nests in the environment.