Open Access. Powered by Scholars. Published by Universities.®
Databases and Information Systems Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
-
- Control co-design (2)
- Formal syntax (2)
- Journal Publications (2)
- Mathematica notebook (2)
- Multihop communication networks (2)
-
- Multihop control networks (2)
- Networking co-design (2)
- Radiocommunication (2)
- Switched systems (2)
- Telecommunication network routing (2)
- Telecommunication network topology (2)
- Wireless HART specification (2)
- Adaptive resonance theory (1)
- Air indices (1)
- Autonomous Learning 2012 (1)
- Classifier (1)
- Data mining (1)
- Data restructuring (1)
- Database (1)
- Exploration-exploitation dilemma (1)
- Extreme learning machines (ELM) (1)
- GO database (1)
- Hierarchical planning (1)
- INNS-WC 2012 (1)
- K-armed bandit (1)
- Machine intelligence (1)
- Natural intelligence (1)
- PFAM database (1)
- Plan learning (1)
- Preference discovery (1)
- Publication
- Publication Type
Articles 1 - 12 of 12
Full-Text Articles in Databases and Information Systems
Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin
Cognitive Architectures And Autonomy: Commentary And Response, Włodzisław Duch, Ah-Hwee Tan, Stan Franklin
Research Collection School Of Computing and Information Systems
This paper provides a very useful and promising analysis and comparison of current architectures of autonomous intelligent systems acting in real time and specific contexts, with all their constraints. The chosen issue of Cognitive Architectures and Autonomy is really a challenge for AI current projects and future research. I appreciate and endorse not only that challenge but many specific choices and claims; in particular: (i) that “autonomy” is a key concept for general intelligent systems; (ii) that “a core issue in cognitive architecture is the integration of cognitive processes ....”; (iii) the analysis of features and capabilities missing in current …
A Probabilistic Graphical Model For Topic And Preference Discovery On Social Media, Lu Liu, Feida Zhu, Lei Zhang, Shiqiang Yang
A Probabilistic Graphical Model For Topic And Preference Discovery On Social Media, Lu Liu, Feida Zhu, Lei Zhang, Shiqiang Yang
Research Collection School Of Computing and Information Systems
Many web applications today thrive on offering services for large-scale multimedia data, e.g., Flickr for photos and YouTube for videos. However, these data, while rich in content, are usually sparse in textual descriptive information. For example, a video clip is often associated with only a few tags. Moreover, the textual descriptions are often overly specific to the video content. Such characteristics make it very challenging to discover topics at a satisfactory granularity on this kind of data. In this paper, we propose a generative probabilistic model named Preference-Topic Model (PTM) to introduce the dimension of user preferences to enhance the …
Data Mining Of Protein Databases, Christopher Assi
Data Mining Of Protein Databases, Christopher Assi
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Data mining of protein databases poses special challenges because many protein databases are non-relational whereas most data mining and machine learning algorithms assume the input data to be a relational database. Protein databases are non-relational mainly because they often contain set data types. We developed new data mining algorithms that can restructure non-relational protein databases so that they become relational and amenable for various data mining and machine learning tools. We applied the new restructuring algorithms to a pancreatic protein database. After the restructuring, we also applied two classification methods, such as decision tree and SVM classifiers and compared their …
Feature-Based Opinion Mining And Ranking, Magdalini Eirinaki, S. Pisal, J. Singh
Feature-Based Opinion Mining And Ranking, Magdalini Eirinaki, S. Pisal, J. Singh
Magdalini Eirinaki
The proliferation of blogs and social networks presents a new set of challenges and opportunities in the way information is searched and retrieved. Even though facts still play a very important role when information is sought on a topic, opinions have become increasingly important as well. Opinions expressed in blogs and social networks are playing an important role influencing everything from the products people buy to the presidential candidate they support. Thus, there is a need for a new type of search engine which will not only retrieve facts, but will also enable the retrieval of opinions. Such a search …
Ifalcon: A Neural Architecture For Hierarchical Planning, Budhitama Subagdja, Ah-Hwee Tan
Ifalcon: A Neural Architecture For Hierarchical Planning, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Hierarchical planning is an approach of planning by composing and executing hierarchically arranged predefined plans on the fly to solve some problems. This approach commonly relies on a domain expert providing all semantic and structural knowledge. One challenge is how the system deals with incomplete ill-defined knowledge while the solution can be achieved on the fly. Most symbolic-based hierarchical planners have been devised to allow the knowledge to be described expressively. However, in some cases, it is still difficult to produce the appropriate knowledge due to the complexity of the problem domain especially if the missing knowledge must be acquired …
Spatial Queries In Wireless Broadcast Environments [Keynote Speech], Kyriakos Mouratidis
Spatial Queries In Wireless Broadcast Environments [Keynote Speech], Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
Wireless data broadcasting is a promising technique for information dissemination that exploits the computational capabilities of mobile devices, in order to enhance the scalability of the system. Under this environment, the data are continuously broadcast by the server, interleaved with some indexing information for query processing. Clients may tune in the broadcast channel and process their queries locally without contacting the server. In this paper we focus on spatial queries in particular. First, we review existing methods on this topic. Next, taking shortest path computation as an example, we showcase technical challenges arising in this processing model and describe techniques …
Modeling And Analysis Of Multi-Hop Control Networks, Alur Rajeev, Alessandro D'Innocenzo, Karl H. Johansson, George James Pappas, Gera Weiss
Modeling And Analysis Of Multi-Hop Control Networks, Alur Rajeev, Alessandro D'Innocenzo, Karl H. Johansson, George James Pappas, Gera Weiss
George J. Pappas
We propose a mathematical framework, inspired by the Wireless HART specification, for modeling and analyzing multi-hop communication networks. The framework is designed for systems consisting of multiple control loops closed over a multi-hop communication network. We separate control, topology, routing, and scheduling and propose formal syntax and semantics for the dynamics of the composed system. The main technical contribution of the paper is an explicit translation of multi-hop control networks to switched systems. We describe a Mathematica notebook that automates the translation of multihop control networks to switched systems, and use this tool to show how techniques for analysis of …
Modeling And Analysis Of Multi-Hop Control Networks, Alur Rajeev, Alessandro D'Innocenzo, Karl H. Johansson, George James Pappas, Gera Weiss
Modeling And Analysis Of Multi-Hop Control Networks, Alur Rajeev, Alessandro D'Innocenzo, Karl H. Johansson, George James Pappas, Gera Weiss
George J. Pappas
We propose a mathematical framework, inspired by the Wireless HART specification, for modeling and analyzing multi-hop communication networks. The framework is designed for systems consisting of multiple control loops closed over a multi-hop communication network. We separate control, topology, routing, and scheduling and propose formal syntax and semantics for the dynamics of the composed system. The main technical contribution of the paper is an explicit translation of multi-hop control networks to switched systems. We describe a Mathematica notebook that automates the translation of multihop control networks to switched systems, and use this tool to show how techniques for analysis of …
Extreme Learning Machine Terrain-Based Navigation For Unmanned Aerial Vehicles, Ee May Kan, Meng Hiot Lim, Yew Soon Ong, Ah-Hwee Tan, Swee Ping Yeo
Extreme Learning Machine Terrain-Based Navigation For Unmanned Aerial Vehicles, Ee May Kan, Meng Hiot Lim, Yew Soon Ong, Ah-Hwee Tan, Swee Ping Yeo
Research Collection School Of Computing and Information Systems
Unmanned aerial vehicles (UAVs) rely on global positioning system (GPS) information to ascertain its position for navigation during mission execution. In the absence of GPS information, the capability of a UAV to carry out its intended mission is hindered. In this paper, we learn alternative means for UAVs to derive real-time positional reference information so as to ensure the continuity of the mission. We present extreme learning machine as a mechanism for learning the stored digital elevation information so as to aid UAVs to navigate through terrain without the need for GPS. The proposed algorithm accommodates the need of the …
Identification Of Influential Social Networkers, Magdalini Eirinaki, S. P. Singh Monga, S. Sundaram
Identification Of Influential Social Networkers, Magdalini Eirinaki, S. P. Singh Monga, S. Sundaram
Magdalini Eirinaki
Online social networking is deeply interleaved in today's lifestyle. People come together and build communities to share thoughts, offer suggestions, exchange information, ideas, and opinions. Moreover, social networks often serve as platforms for information dissemination and product placement or promotion through viral marketing. The success rate in this type of marketing could be increased by targeting specific individuals, called 'influential users', having the largest possible reach within an online community. In this paper, we present a method aiming at identifying the influential users within an online social networking application. We introduce ProfileRank, a metric that uses popularity and activity characteristics …
Self‐Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Yuan-Sin Tan
Self‐Regulating Action Exploration In Reinforcement Learning, Teck-Hou Teng, Ah-Hwee Tan, Yuan-Sin Tan
Research Collection School Of Computing and Information Systems
The basic tenet of a learning process is for an agent to learn for only as much and as long as it is necessary. With reinforcement learning, the learning process is divided between exploration and exploitation. Given the complexity of the problem domain and the randomness of the learning process, the exact duration of the reinforcement learning process can never be known with certainty. Using an inaccurate number of training iterations leads either to the non-convergence or the over-training of the learning agent. This work addresses such issues by proposing a technique to self-regulate the exploration rate and training duration …
Preface: Trends In Natural And Machine Intelligence, Jonathan H. Chan, Ah-Hwee Tan
Preface: Trends In Natural And Machine Intelligence, Jonathan H. Chan, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Trends in natural and machine intelligence are increasingly reflecting a convergence in these two well-established fields of study. The Third International Neural Network Society Winter Conference (INNS-WC 2012) was held in Bangkok, Thailand, on October 3-5, 2012. INNS-WC2012, with an aim to bring together scientists, practitioners, and students worldwide, to discuss the past, present, and future challenges and trends in the area of natural and machine intelligence. This event has been a bi-annual conference of the International Neural Network Society (INNS) to provide a forum for international researchers to exchange latest ideas and advances on neural networks and related discipline.