Neural Collaborative Filtering,
2017
Singapore Management University
Neural Collaborative Filtering, Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
In recent years, deep neural networks have yielded immense success on speech recognition, computer vision and natural language processing. However, the exploration of deep neural networks on recommender systems has received relatively less scrutiny. In this work, we strive to develop techniques based on neural networks to tackle the key problem in recommendation --- collaborative filtering --- on the basis of implicit feedback.Although some recent work has employed deep learning for recommendation, they primarily used it to model auxiliary information, such as textual descriptions of items and acoustic features of musics. When it comes to model the key factor in …
A Sandbox In Which To Learn And Develop Soar Agents,
2017
Air Force Institute of Technology
A Sandbox In Which To Learn And Develop Soar Agents, Daniel Lugo
Theses and Dissertations
It is common for military personnel to leverage simulations (and simulators) as cost-effective tools to train and become proficient at various tasks (e.g., flying an aircraft and/or performing a mission, among others). These training simulations often need to represent humans within the simulated world in a realistic manner. Realistic implies creating simulated humans that exhibit behaviors that mimic real-world decision making and actions. Typically, to create the decision-making logic, techniques developed from the domain of artificial intelligence are used. Although there are several approaches to developing intelligent agents; we focus on leveraging and open source project called Soar, to define …
Detecting Similar Repositories On Github,
2017
Singapore Management University
Detecting Similar Repositories On Github, Yun Zhang, David Lo, Pavneet Singh Kochhar, Xin Xia, Quanlai Li, Jianling Sun
Research Collection School Of Computing and Information Systems
GitHub contains millions of repositories among which many are similar with one another (i.e., having similar source codes or implementing similar functionalities). Finding similar repositories on GitHub can be helpful for software engineers as it can help them reuse source code, build prototypes, identify alternative implementations, explore related projects, find projects to contribute to, and discover code theft and plagiarism. Previous studies have proposed techniques to detect similar applications by analyzing API usage patterns and software tags. However, these prior studies either only make use of a limited source of information or use information not available for projects on GitHub. …
Mining Data On Traumatic Brain Injury With Reconstructability Analysis,
2017
Portland State University
Mining Data On Traumatic Brain Injury With Reconstructability Analysis, Martin Zwick, Nancy Carney, Rosemary Nettleton
Complex Systems Faculty Publications and Presentations
This paper reports the analysis of data on traumatic brain injury using a probabilistic graphical modeling technique known as reconstructability analysis (RA). The analysis shows the flexibility, power, and comprehensibility of RA modeling, which is well-suited for mining biomedical data. One finding of the analysis is that education is a confounding variable for the Digit Symbol Test in discriminating the severity of concussion; another - and anomalous - finding is that previous head injury predicts improved performance on the Reaction Time test. This analysis was exploratory, so its findings require follow-on confirmatory tests of their generalizability.
Efficient Core Utilization In A Hybrid Parallel Delaunay Meshing Algorithm On Distributed-Memory Cluster,
2017
Old Dominion University
Efficient Core Utilization In A Hybrid Parallel Delaunay Meshing Algorithm On Distributed-Memory Cluster, Daming Feng, Andrey N. Chernikov, Nikos P. Chrisochoides
Computer Science Faculty Publications
Most of the current supercomputer architectures consist of clusters of nodes that are used by many clients (users). A user wants his/her job submitted in the job queue to be scheduled promptly. However, the resource sharing and job scheduling policies that are used in the scheduling system to manage the jobs are usually beyond the control of users. Therefore, in order to reduce the waiting time of their jobs, it is becoming more and more crucial for the users to consider how to implement the algorithms that are suitable to the system scheduling policies and are able to effectively and …
Ansi/Niso Z39.99-2017 Resourcesync Framework Specification,
2017
Old Dominion University
Ansi/Niso Z39.99-2017 Resourcesync Framework Specification, Kevin Ruthen, Jill Emery, Mark Doyle, Mark Needleman, Sue Baughman, Evan Owens, Oliver Pesch, Mike Dicus, Nassib Nassar, Tim Auger, Amy Kirchhoff, Sally Mccallum, Diana Magnoni, Paul Swanson, Gregory Grazevich, Nara Newcomer, Gregory Grazevich, Juha Hakala, Barbara Rapp, Beverly Geckle, Carol Brent, Gary Van Overborg, Rick Burke, Kristin Antelman, Scott Bernier, Pascal Calarco, John Dove, Lucy Harrison, Peter Murray, Christine Stohn, Julie Zhu, Todd Carpenter, Bernhard Haslhofer, Richard Jones, Martin Klein, Graham Klyne, Carl Lagoze, Stuart Lewis, Peter Murray, Michael Nelson, Shlomo Sanders, Robert Sanderson, Herbert Van De Sompel, Paul Walk, Simeon Warner, Zhiwu Xie, Jeff Young
Computer Science Faculty Publications
This ResourceSync specification describes a synchronization framework for the web consisting of various capabilities that allow third-party systems to remain synchronized with a server’s evolving resources. The capabilities may be combined in a modular manner to meet local or community requirements. This specification also describes how a server should advertise the synchronization capabilities it supports and how third-party systems may discover this information. The specification repurposes the document formats defined by the Sitemap protocol and introduces extensions for them.
Spatial Data Mining Analytical Environment For Large Scale Geospatial Data,
2016
LSU New Orleans
Spatial Data Mining Analytical Environment For Large Scale Geospatial Data, Zhao Yang
LSU New Orleans Theses and Dissertations
Nowadays, many applications are continuously generating large-scale geospatial data. Vehicle GPS tracking data, aerial surveillance drones, LiDAR (Light Detection and Ranging), world-wide spatial networks, and high resolution optical or Synthetic Aperture Radar imagery data all generate a huge amount of geospatial data. However, as data collection increases our ability to process this large-scale geospatial data in a flexible fashion is still limited. We propose a framework for processing and analyzing large-scale geospatial and environmental data using a “Big Data” infrastructure. Existing Big Data solutions do not include a specific mechanism to analyze large-scale geospatial data. In this work, we extend …
Android Drone: Remote Quadcopter Control With A Phone,
2016
California Polytechnic State University, San Luis Obispo
Android Drone: Remote Quadcopter Control With A Phone, Aubrey John Russell
Computer Engineering
The purpose of the “Android Drone” project was to create a quadcopter that can be controlled by user input sent over the phone’s Wi-Fi connection or 4G internet connection. Furthermore, the purpose was also to be able to receive live video feedback over the internet connection, thus making the drone an inexpensive option compared to other, equivalent drones that might cost thousands of dollars. Not only that, but the Android phone also has a host of other useful features that could be utilized by the drone: this includes GPS, pathing, picture taking, data storage, networking and TCP/IP, a Java software …
A System For Detecting Malicious Insider Data Theft In Iaas Cloud Environments,
2016
Dakota State University
A System For Detecting Malicious Insider Data Theft In Iaas Cloud Environments, Jason Nikolai, Yong Wang
Research & Publications
The Cloud Security Alliance lists data theft and insider attacks as critical threats to cloud security. Our work puts forth an approach using a train, monitor, detect pattern which leverages a stateful rule based k-nearest neighbors anomaly detection technique and system state data to detect inside attacker data theft on Infrastructure as a Service (IaaS) nodes. We posit, instantiate, and demonstrate our approach using the Eucalyptus cloud computing infrastructure where we observe a 100 percent detection rate for abnormal login events and data copies to outside systems.
Efficient Online Summarization Of Large-Scale Dynamic Networks,
2016
Chinese Academic of Sciences
Efficient Online Summarization Of Large-Scale Dynamic Networks, Qiang Qu, Siyuan Liu, Feida Zhu, Christian S. Jensen
Research Collection School Of Computing and Information Systems
Information diffusion in social networks is often characterized by huge participating communities and viral cascades of high dynamicity. To observe, summarize, and understand the evolution of dynamic diffusion processes in an informative and insightful way is a challenge of high practical value. However, few existing studies aim to summarize networks for interesting dynamic patterns. Dynamic networks raise new challenges not found in static settings, including time sensitivity, online interestingness evaluation, and summary traceability, which render existing techniques inadequate. We propose dynamic network summarization to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or …
Towards Autonomous Behavior Learning Of Non-Player Characters In Games,
2016
Singapore Management University
Towards Autonomous Behavior Learning Of Non-Player Characters In Games, Shu Feng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Non-Player-Characters (NPCs), as found in computer games, can be modelled as intelligent systems, which serve to improve the interactivity and playability of the games. Although reinforcement learning (RL) has been a promising approach to creating the behavior models of non-player characters (NPC), an initial stage of exploration and low performance is typically required. On the other hand, imitative learning (IL) is an effective approach to pre-building a NPC’s behavior model by observing the opponent’s actions, but learning by imitation limits the agent’s performance to that of its opponents. In view of their complementary strengths, this paper proposes a computational model …
Addsmart: Address Digitization And Smart Mailbox With Rfid Technology,
2016
Columbus State University
Addsmart: Address Digitization And Smart Mailbox With Rfid Technology, Jonathon Ross Tew
Theses and Dissertations
ADDSMART is a research project focused on digitizing addresses of locations and building a smart mailbox by combining wireless sensors, cameras, locks, and RFID readers and tags into a system controlled by an Arduino board. The aim of the project is to explore the idea of address digitization (using RFID tags to store addresses) and incorporate it into a mailbox that can communicate wirelessly with the homeowner to provide mail status updates and home security footage through digital photographs. This paper demonstrates the proposed ideas, describes the design of a smart mailbox, the technology that has been used, and the …
A Feasible No-Root Approach On Android,
2016
Singapore Management University
A Feasible No-Root Approach On Android, Yao Cheng, Yingjiu Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
Root is the administrative privilege on Android, which is however inaccessible on stock Android devices. Due to the desire for privileged functionalities and the reluctance of rooting their devices, Android users seek for no-root approaches, which provide users with part of root privileges without rooting their devices. In this paper, we newly discover a feasible no-root approach based on the ADB loopback. To ensure such no-root approach is not misused proactively, we examine its dark side, including privacy leakage via logs and user input inference. Finally, we discuss the solutions and suggestions from different perspectives.
An Adaptability-Driven Model And Tool For Analysis Of Service Profitability,
2016
Singapore Management University
An Adaptability-Driven Model And Tool For Analysis Of Service Profitability, Eng Lieh Ouh, Jarzabek Stan
Research Collection School Of Computing and Information Systems
Profitability of adopting Software-as-a-Service (SaaS) solutions forexisting applications is currently analyzed mostly in informal way. Informalanalysis is unreliable because of the many conflicting factors that affect costs andbenefits of offering applications on the cloud. We propose a quantitative economicmodel for evaluating profitability of migrating to SaaS that enables potentialservice providers to evaluate costs and benefits of various migration strategiesand choices of target service architectures. In previous work, we presented arudimentary conceptual SaaS economic model enumerating factors that have todo with service profitability, and defining qualitative relations among them. Aquantitative economic model presented in this paper extends the conceptualmodel with equations …
Prosense,
2016
California Polytechnic State University, San Luis Obispo
Prosense, Johnny Favazza Ii, Casey Glasgow, Matt Epperson
Computer Engineering
This project aims to gather advanced data sets from MEMS sensors and GPS and deliver it to the user, who can capitalize on the data. The once negligible half-degree difference of your board barreling down a wave can be recorded from a gyro and exploited for the perfect turn. The exact speed dreaded by longboarders where speed wobbles turn into a road rash can be analysed and consequently avoided. Ascertaining the summit of your flight using combined GPS sensors from the ski ramp allows for the correct timing of tricks. When it comes to pursuing excellence in professional sports, amateur …
Exemplar-Driven Top-Down Saliency Detection Via Deep Association,
2016
Singapore Management University
Exemplar-Driven Top-Down Saliency Detection Via Deep Association, Shengfeng He, Rynson W. H. Lau, Qingxiong Yang
Research Collection School Of Computing and Information Systems
Top-down saliency detection is a knowledge-driven search task. While some previous methods aim to learn this "knowledge" from category-specific data, others transfer existing annotations in a large dataset through appearance matching. In contrast, we propose in this paper a locateby-exemplar strategy. This approach is challenging, as we only use a few exemplars (up to 4) and the appearances among the query object and the exemplars can be very different. To address it, we design a two-stage deep model to learn the intra-class association between the exemplars and query objects. The first stage is for learning object-to-object association, and the second …
Packet Filter Approach To Detect Denial Of Service Attacks,
2016
California State University, San Bernardino
Packet Filter Approach To Detect Denial Of Service Attacks, Essa Yahya M Muharish
Electronic Theses, Projects, and Dissertations
Denial of service attacks (DoS) are a common threat to many online services. These attacks aim to overcome the availability of an online service with massive traffic from multiple sources. By spoofing legitimate users, an attacker floods a target system with a high quantity of packets or connections to crash its network resources, bandwidth, equipment, or servers. Packet filtering methods are the most known way to prevent these attacks via identifying and blocking the spoofed attack from reaching its target. In this project, the extent of the DoS attacks problem and attempts to prevent it are explored. The attacks categories …
Learning Natural Language Inference With Lstm,
2016
Singapore Management University
Learning Natural Language Inference With Lstm, Shuohang Wang, Jing Jiang
Research Collection School Of Computing and Information Systems
Natural language inference (NLI) is a fundamentally important task in natural language processing that has many applications. The recently released Stanford Natural Language Inference (SNLI) corpus has made it possible to develop and evaluate learning-centered methods such as deep neural networks for natural language inference (NLI). In this paper, we propose a special long short-term memory (LSTM) architecture for NLI. Our model builds on top of a recently proposed neural attention model for NLI but is based on a significantly different idea. Instead of deriving sentence embeddings for the premise and the hypothesis to be used for classification, our solution …
Poster: Android Whole-System Control Flow Analysis For Accurate Application Behavior Modeling,
2016
Singapore Management University
Poster: Android Whole-System Control Flow Analysis For Accurate Application Behavior Modeling, Huu Hoang Nguyen
Research Collection School Of Computing and Information Systems
Android, the modern operating system for smartphones, together with its millions of apps, has become an important part of human life. There are many challenges to analyzing them. It is important to model the mobile systems in order to analyze the behaviors of apps accurately. These apps are built on top of interactions with Android systems. We aim to automatically build abstract models of the mobile systems and thus automate the analysis of mobile applications and detect potential issues (e.g., leaking private data, causing unexpected crashes, etc.). The expected results will be the accuracy models of actual various versions of …
The Contributions Of Anatol Rapoport To Game Theory,
2016
Western University
The Contributions Of Anatol Rapoport To Game Theory, Erika Simpson
Political Science Publications
Game theory is used to rationally and dispassionately examine the strategic behaviour of nations, especially superpower behaviour. This article explains how basic game theory - at its simplest level - was used by Anatol Rapoport to generate ideas about how to enhance world peace. Rapoport was at the forefront of the game theoreticians who sought to conceptualize strategies that could promote international cooperation. Accordingly, the basic logic of game theory is explained using the game models of ‘Chicken’ and ‘Prisoner’s Dilemma’. These models were used by Rapoport in his books and lectures in simple and complex ways. Then Rapoport’s revolutionary …
