Next Generation of Product Search and Discovery

Online shopping has become an important part of people’s daily life with the rapid development of e-commerce. In some domains such as books, electronics, and CD/DVDs, online shopping has surpassed or even replaced the traditional shopping method. Compared with traditional retailing, e-commerce is information intensive. One of the key factors to succeed in e-business is how to facilitate the consumers’ approaches to discover a product. Conventionally a product search engine based on a keyword search or category browser is provided to help users find the product information they need. The general goal of a product search system is to enable users to quickly locate information of interest and to minimize users’ efforts in search and navigation. In this process human factors play a significant role. Finding product information could be a tricky task and may require an intelligent use of search engines, and a non-trivial navigation of multilayer categories. Searching for useful product information can be frustrating for many users, especially those inexperienced users. This dissertation focuses on developing a new visual product search system that effectively extracts the properties of unstructured products, and presents the possible items of attraction to users so that the users can quickly locate the ones they would be most likely interested in. We designed and developed a feature extraction algorithm that retains product color and local pattern features, and the experimental evaluation on the benchmark dataset demonstrated that it is robust against common geometric and photometric visual distortions. Besides, instead of ignoring product text information, we investigated and developed a ranking model learned via a unified probabilistic hypergraph that is capable of capturing correlations among product visual content and textual content. Moreover, we proposed and designed a fuzzy hierarchical co-clustering algorithm for the collaborative filtering product recommendation. Via this method, users can be automatically grouped into different interest communities based on their behaviors. Then, a customized recommendation can be performed according to these implicitly detected relations. In summary, the developed search system performs much better in a visual unstructured product search when compared with state-of-art approaches. With the comprehensive ranking scheme and the collaborative filtering recommendation module, the user’s overhead in locating the information of value is reduced, and the user’s experience of seeking for useful product information is optimized

A Natural Image Pointillism with Controlled Ellipse Dots

This paper presents an image-based artistic rendering algorithm for the automatic Pointillism style. At first, ellipse dot locations are randomly generated based on a source image; then dot orientations are precalculated with help of a direction map; a saliency map of the source image decides long and short radius of the ellipse dot. At last, the rendering runs layer-by-layer from large size dots to small size dots so as to reserve the detailed parts of the image. Although only ellipse dot shape is adopted, the final Pointillism style performs well because of variable characteristics of the dot

Machine Learning for Unmanned Aerial System (UAS) Networking

Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex missions simultaneously. However, the limitations of the conventional approaches are still a big challenge to make a trade-off between the massive management and efficient networking on a large scale. With 5G NR and machine learning, in this dissertation, my contributions can be summarized as the following: I proposed a novel Optimized Ad-hoc On-demand Distance Vector (OAODV) routing protocol to improve the throughput of Intra UAS networking. The novel routing protocol can reduce the system overhead and be efficient. To improve the security, I proposed a blockchain scheme to mitigate the malicious basestations for cellular connected UAS networking and a proof-of-traffic (PoT) to improve the efficiency of blockchain for UAS networking on a large scale. Inspired by the biological cell paradigm, I proposed the cell wall routing protocols for heterogeneous UAS networking. With 5G NR, the inter connections between UAS networking can strengthen the throughput and elasticity of UAS networking. With machine learning, the routing schedulings for intra- and inter- UAS networking can enhance the throughput of UAS networking on a large scale. The inter UAS networking can achieve the max-min throughput globally edge coloring. I leveraged the upper and lower bound to accelerate the optimization of edge coloring. This dissertation paves a way regarding UAS networking in the integration of CPS and machine learning. The UAS networking can achieve outstanding performance in a decentralized architecture. Concurrently, this dissertation gives insights into UAS networking on a large scale. These are fundamental to integrating UAS and National Aerial System (NAS), critical to aviation in the operated and unmanned fields. The dissertation provides novel approaches for the promotion of UAS networking on a large scale. The proposed approaches extend the state-of-the-art of UAS networking in a decentralized architecture. All the alterations can contribute to the establishment of UAS networking with CPS

A critical analysis of technology’s impact on teacher’s views of literacy learning and teaching: A continuum of understandings

The purpose of this study was to investigate three middle school English teachers’ understandings of literacy and technology. In particular, how do they view literacy and technology learning and teaching, and how do they use (or not use) technology to enact their views of literacy in their classrooms. This narrative inquiry qualitative study consisted of three open-ended interviews, written literacy narratives, and multiple classroom observations with each participant as well as the collection of various teacher documents, such as lesson plans, presentation notes, rubrics, and student handouts. Narrative methods were used in the data analysis. Findings were organized across a continuum of literacy understandings from traditional understandings to new conceptions of literacy. Discussion and implications point to the need for an expanded definition of literacy with teachers that addresses the complexity of multiliteracies. There is also a need for extending pedagogical repertoires of teachers to recognize TPACK as a beginning to multiliteracies

A critical analysis of technology’s impact on teacher’s views of literacy learning and teaching: A continuum of understandings

The purpose of this study was to investigate three middle school English teachers’ understandings of literacy and technology. In particular, how do they view literacy and technology learning and teaching, and how do they use (or not use) technology to enact their views of literacy in their classrooms. This narrative inquiry qualitative study consisted of three open-ended interviews, written literacy narratives, and multiple classroom observations with each participant as well as the collection of various teacher documents, such as lesson plans, presentation notes, rubrics, and student handouts. Narrative methods were used in the data analysis. Findings were organized across a continuum of literacy understandings from traditional understandings to new conceptions of literacy. Discussion and implications point to the need for an expanded definition of literacy with teachers that addresses the complexity of multiliteracies. There is also a need for extending pedagogical repertoires of teachers to recognize TPACK as a beginning to multiliteracies

Interactive Cinema

The Piper is a first-person interactive cinema experience based on the legend of the Pied Piper. Set in medieval Germany, the player assumes the role of a child being lured away from the village of Hamelin under the vengeful spell of the Piper’s music. Our team consisted of two programmers, two artists, and a music/audio producer. This report discusses the design goals of The Piper, the methods by which it was developed, technical and aesthetic challenges that the project faced, and the team’s reflections on the development process and final product

Human spatial navigation in the digital era: Effects of landmark depiction on mobile maps on navigators’ spatial learning and brain activity during assisted navigation

Navigation was an essential survival skill for our ancestors and is still a fundamental activity in our everyday lives. To stay oriented and assist navigation, our ancestors had a long history of developing and employing physical maps that communicated an enormous amount of spatial and visual information about their surroundings. Today, in the digital era, we are increasingly turning to mobile navigation devices to ease daily navigation tasks, surrendering our spatial and navigational skills to the hand-held device. On the flip side, the conveniences of such devices lead us to pay less attention to our surroundings, make fewer spatial decisions, and remember less about the surroundings we have traversed. As navigational skills and spatial memory are related to adult neurogenesis, healthy aging, education, and survival, scientists and researchers from multidisciplinary fields have made calls to develop a new account of mobile navigation assistance to preserve human navigational abilities and spatial memory. Landmarks have been advocated for special attention in developing cognitively supportive navigation systems, as landmarks are widely accepted as key features to support spatial navigation and spatial learning of an environment. Turn-by-turn direction instructions without reference to surrounding landmarks, such as those provided by most existing navigation systems, can be one of the reasons for navigators’ spatial memory deterioration during assisted navigation. Despite the benefit of landmarks in navigation and spatial learning, long-standing literature on cognitive psychology has pointed out that individuals have only a limited cognitive capacity to process presented information for a task. When the learning items exceed learners’ capacity, the performance may reach a plateau or even drop. This leads to an unexamined yet important research question on how to visualize landmarks on a mobile map to optimize navigators’ cognitive resource exertion and thus optimize their spatial learning. To investigate this question, I leveraged neuropsychological and hypothesis-driven approaches and investigated whether and how different numbers of landmarks depicted on a mobile map affected navigators’ spatial learning, cognitive load, and visuospatial encoding. Specifically, I set out a navigation experiment in three virtual urban environments, in which participants were asked to follow a given route to a specific destination with the aid of a mobile map. Three different numbers of landmarks—3, 5, and 7—along the given route were selected based on cognitive capacity literature and presented to 48 participants during map-assisted navigation. Their brain activity was recorded both during the phase of map consultation and during that of active locomotion. After navigation in each virtual city, their spatial knowledge of the traversed routes was assessed. The statistical results revealed that spatial learning improved when a medium number of landmarks (i.e., five) was depicted on a mobile map compared to the lowest evaluated number (i.e., three) of landmarks, and there was no further improvement when the highest number (i.e., seven) of landmarks were provided on the mobile map. The neural correlates that were interpreted to reflect cognitive load during map consultation increased when participants were processing seven landmarks depicted on a mobile map compared to the other two landmark conditions; by contrast, the neural correlates that indicated visuospatial encoding increased with a higher number of presented landmarks. In line with the cognitive load changes during map consultation, cognitive load during active locomotion also increased when participants were in the seven-landmark condition, compared to the other two landmark conditions. This thesis provides an exemplary paradigm to investigate navigators’ behavior and cognitive processing during map-assisted navigation and to utilize neuropsychological approaches to solve cartographic design problems. The findings contribute to a better understanding of the effects of landmark depiction (3, 5, and 7 landmarks) on navigators’ spatial learning outcomes and their cognitive processing (cognitive load and visuospatial encoding) during map-assisted navigation. Of these insights, I conclude with two main takeaways for audiences including navigation researchers and navigation system designers. First, the thesis suggests a boundary effect of the proposed benefits of landmarks in spatial learning: providing landmarks on maps benefits users’ spatial learning only to a certain extent when the number of landmarks does not increase cognitive load. Medium number (i.e., 5) of landmarks seems to be the best option in the current experiment, as five landmarks facilitate spatial learning without taxing additional cognitive resources. The second takeaway is that the increased cognitive load during map use might also spill over into the locomotion phase through the environment; thus, the locomotion phase in the environment should also be carefully considered while designing a mobile map to support navigation and environmental learning

PARbot: Personal Assistive Robot

The aging population of the United States is creating a growing need to provide assistive care for elderly and people with disabilities. As the Baby Boomer generation enters retirement, the ratio of caregivers to those that require assistance is projected to decrease. There are currently no commercially available modular assistive robots that can fill this need. Our project aims to provide an alternative to current assisted living options through the development, construction, and testing of a Personal Assistive Robot (PARbot) that allows individuals with general or age related disabilities to maintain some aspects of their independence, such as the ability to shop