Tam Nguyen

Tam Nguyen
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Tam Nguyen

Pubs By Year

Pub Categories

Computer Science - Networking and Internet Architecture (5)
Computer Science - Computer Vision and Pattern Recognition (3)
Physics - Instrumentation and Detectors (2)
Computer Science - Software Engineering (2)
Instrumentation and Methods for Astrophysics (1)
Computer Science - Artificial Intelligence (1)
Nuclear Experiment (1)
Computer Science - Distributed; Parallel; and Cluster Computing (1)
Computer Science - Information Retrieval (1)
Computer Science - Human-Computer Interaction (1)
Computer Science - Multimedia (1)
Computer Science - Multiagent Systems (1)
Computer Science - Robotics (1)
Computer Science - Computation and Language (1)

Publications Authored By Tam Nguyen

This paper focuses on a passivity-based distributed reference governor (RG) applied to a pre-stabilized mobile robotic network. The novelty of this paper lies in the method used to solve the RG problem, where a passivity-based distributed optimization scheme is proposed. In particular, the gradient descent method minimizes the global objective function while the dual ascent method maximizes the Hamiltonian. Read More

In this paper, we define visual log of a software system as data capturing the interactions between its users and its graphic user interface (GUI), such as screen-shots and screen recordings. We vision that mining such visual log could be useful for bug reproducing and debugging, automated GUI testing, user interface designing, question answering of common usages in software support, etc. Toward that vision, we propose a core framework for mining visual log of software. Read More

This paper focuses on the control of a system composed of an Unmanned Aerial Vehicle (UAV) and an Unmanned Ground Vehicle (UGV) which cooperate to manipulate an object. The two units are subject to actuator saturations and cooperate to move the object to a desired pose, characterized by its position and inclination. The paper proposes a control strategy where the ground vehicle is tasked to deploy the object to a certain position, whereas the aerial vehicle adjusts its inclination. Read More

Commonsense knowledge representation and reasoning is key for tasks such as artificial intelligence and natural language understanding. Since commonsense consists of information that humans take for granted, gathering it is an extremely difficult task. In this paper, we introduce a novel 3D game engine for commonsense knowledge acquisition (GECKA3D) which aims to collect commonsense from game designers through the development of serious games. Read More

With the development of Internet culture, cuteness has become a popular concept. Many people are curious about what factors making a person look cute. However, there is rare research to answer this interesting question. Read More

When developing mobile apps, programmers rely heavily on standard API frameworks and libraries. However, learning and using those APIs is often challenging due to the fast-changing nature of API frameworks for mobile systems, the complexity of API usages, the insufficiency of documentation, and the unavailability of source code examples. In this paper, we propose a novel approach to learn API usages from bytecode of Android mobile apps. Read More

In this paper, we propose using \textit{augmented hypotheses} which consider objectness, foreground and compactness for salient object detection. Our algorithm consists of four basic steps. First, our method generates the objectness map via objectness hypotheses. Read More

User reviews of mobile apps often contain complaints or suggestions which are valuable for app developers to improve user experience and satisfaction. However, due to the large volume and noisy-nature of those reviews, manually analyzing them for useful opinions is inherently challenging. To address this problem, we propose MARK, a keyword-based framework for semi-automated review analysis. Read More

In this paper, we present an adaptive nonparametric solution to the image parsing task, namely annotating each image pixel with its corresponding category label. For a given test image, first, a locality-aware retrieval set is extracted from the training data based on super-pixel matching similarities, which are augmented with feature extraction for better differentiation of local super-pixels. Then, the category of each super-pixel is initialized by the majority vote of the $k$-nearest-neighbor super-pixels in the retrieval set. Read More

The 232U content of various uranium-bearing items was measured using low-background gamma spectrometry. The method is independent of the measurement geometry, sample form and chemical composition. Since 232U is an artificially produced isotope, it carries information about previous irradiation of the material, which is relevant for nuclear forensics, nuclear safeguards and for nuclear reactor operations. Read More

We report on the measurements of the absolute Quantum Efficiency(QE) for Hamamatsu model R11410-10 PMTs specially designed for the use in low background liquid xenon detectors. QE was measured for five PMTs in a spectral range between 154.5 nm to 400 nm at low temperatures down to -110$^0$C. Read More

Network management and security is currently one of the most vibrant research areas, among which, research on detecting and identifying anomalies has attracted a lot of interest. Researchers are still struggling to find an effective and lightweight method for anomaly detection purpose. In this paper, we propose a simple, robust method that detects network anomalous traffic data based on flow monitoring. Read More

Nowadays computing becomes increasingly mobile and pervasive. One of the important steps in pervasive computing is context-awareness. Context-aware pervasive systems rely on information about the context and user preferences to adapt their behavior. Read More

Bandwidth allocation is a fundamental problem in communication networks. With current network moving towards the Future Internet model, the problem is further intensified as network traffic demanding far from exceeds network bandwidth capability. Maintaining a certain user satisfaction degree therefore becomes a challenge research topic. Read More

Context awareness is one of the important fields in ubiquitous computing. Smart Home, a specific instance of ubiquitous computing, provides every family with opportunities to enjoy the power of hi-tech home living. Discovering that relationship among user, activity and context data in home environment is semantic, therefore, we apply ontology to model these relationships and then reason them as the semantic information. Read More

Context awareness is the most important research area in ubiquitous computing. In particular, for smart home, context awareness attempts to bring the best services to the home habitants. However, the implementation in the real environment is not easy and takes a long time from building the scratch. Read More