Page 72 - Undergraduate Research Opportunities Program Proceedings 2017-18

School of Engineering
Department of Computer Science & Engineering

Can We Build a Cloud from the Crowd? Cloud Computing on Smartphones

Supervisor: HUI Pan / CSE
Student: LI Xiang / COMP Course: UROP1100, Fall

The title of my UROP project is “Can We Build a Cloud from the Crowd? Cloud Computing on Smartphones”. During this
UROP, I have learned a lot about Android programming, computer network and specifically the WIFI P2P communication
network among android phones. After learning about an open source WIFI P2P API Salut, I have created an instant
messaging APP that sends messages between two phones over peer to peer WIFI connection. Also, I have carried out
extensive experiments to calculate the speed of data transfer and detecting hosts using Salut. Finally, an APP is
implemented that applies Salut to synchronize two databases on different devices. My UROP study will continue and our
final objective is to understand and contribute to an open source middleware OPENRP.

Security on Internet of Things (IoT) Devices and Network Protocols

Supervisor: HUI Pan / CSE
Student: SONG Renhe / COMP Course: UROP1100, Summer

New technology advances such as wearables, computer vision can also lead to new shopping experiences and analytics.
However, many current approaches lack of precision (e.g., wireless) or threats customer’s privacy (e.g., face recognition,
smartphone tracking). In this report, we propose an innovative system to track shopper’s gaze and provide better
insights about customers’ behavior in physical stores. EyeShopper is a gaze estimator ubiquitous system which includes
privacy awareness (i.e., face recognition) and works on video surveillance footage. We believe that the fine-grained
information collected by our system can be the key to success for retail stores. We define customer’s gaze as a two-
parameter function based on head pose: yaw, and pitch. In this report we will focus on back head detection algorithms
so the system will be able to not only estimate clients’ gazes but track them. So this gaze estimations can be provided to
retailers as another level of granularity (i.e., what customers look at and for how long) to enhance their store analytics
with augmented features such as most viewed products.

Supervisor: HUI Pan / CSE
Student: VERMA Kshitij / COMP Course: UROP1100, Spring

Currently, most cryptocurrencies are based on the blockchain architecture, which has limitations on the frequency at
which transactions can be added to the network. Additionally, having separate miners maintain correctness of the
ledger imposes transaction fees and consumes a lot of computing power. This stemmed the creation of DAG based
cryptocurrencies, in which the ledger is maintained in the form of a directed acyclic graph of transactions or blocks of
transactions by the users themselves. This architecture allows for faster verification of transactions. This report explores
the working, advantages and disadvantages of various DAG based ledgers. It also explains in depth possible security
flaws in IOTA, a cryptocurrency which maintains a DAG of transactions as a ledger.

A Data-Mining-based System for Trip Planning

Supervisor: HUI Pan / CSE
Student: YANG Hsuan-ru / COMP Course: UROP1100, Fall

The project applies data-mining techniques on over 33, 000 user records, 15,000 question records, and 100,000 answer
records and have discovered frequent patterns in the relationship between users, questions, and answers on the
knowledge sharing platform Quora.com. The length of answer text has a negative impact on the number of votes and

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