Open Access. Powered by Scholars. Published by Universities.®
Databases and Information Systems Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Social and Behavioral Sciences (76)
- Communication (65)
- Communication Technology and New Media (50)
- Life Sciences (50)
- OS and Networks (50)
-
- Bioinformatics (46)
- Science and Technology Studies (45)
- Numerical Analysis and Scientific Computing (31)
- Business (17)
- Social Media (13)
- Artificial Intelligence and Robotics (12)
- Software Engineering (12)
- Management Information Systems (11)
- Engineering (10)
- Other Computer Sciences (10)
- Theory and Algorithms (10)
- Graphics and Human Computer Interfaces (9)
- Information Security (9)
- Computer Engineering (8)
- Business Administration, Management, and Operations (7)
- Library and Information Science (6)
- Medicine and Health Sciences (5)
- Geographic Information Sciences (4)
- Geography (4)
- Management Sciences and Quantitative Methods (4)
- Operations and Supply Chain Management (4)
- Systems Architecture (4)
- Institution
-
- Singapore Management University (113)
- Wright State University (45)
- University of Nebraska at Omaha (9)
- University of Dayton (6)
- Western Kentucky University (6)
-
- Technological University Dublin (5)
- Cleveland State University (4)
- Old Dominion University (4)
- LSU New Orleans (3)
- University of Nebraska - Lincoln (3)
- Western University (3)
- California Polytechnic State University, San Luis Obispo (2)
- California State University, San Bernardino (2)
- Edith Cowan University (2)
- New Jersey Institute of Technology (2)
- Prairie View A&M University (2)
- University of Arkansas Little Rock (2)
- University of Texas at El Paso (2)
- Bridgewater College (1)
- Chapman University (1)
- Coastal Carolina University (1)
- Columbus State University (1)
- Dakota State University (1)
- Duke Law (1)
- Embry-Riddle Aeronautical University (1)
- Kennesaw State University (1)
- Louisiana Tech University (1)
- Portland State University (1)
- University of Arkansas, Fayetteville (1)
- University of Connecticut (1)
- Keyword
-
- Twitter (9)
- Data mining (5)
- Semantic Sensor Web (5)
- Clustering (4)
- Collaboration (4)
-
- Online learning (4)
- Agent (3)
- Classification (3)
- Coordination (3)
- Forgetting (3)
- GIS (3)
- Memory (3)
- Metadata (3)
- Northern Ohio Data and Information Service (NODIS) (3)
- Semantic Perception (3)
- Social Media (3)
- Social media (3)
- Social network (3)
- Social network analysis (3)
- ART (2)
- Adaptive Resonance Theory (2)
- Air indices (2)
- Analytical models (2)
- Anomaly Detection (2)
- Application software Development (2)
- Biomedicine (2)
- China (2)
- Crisis Computing (2)
- Crisis Informatics (2)
- Database management (2)
- Publication
-
- Research Collection School Of Computing and Information Systems (110)
- Kno.e.sis Publications (37)
- Computer Science and Engineering Faculty Publications (8)
- Information Systems and Quantitative Analysis Faculty Proceedings & Presentations (8)
- Computer Science Faculty Publications (5)
-
- Masters Theses & Specialist Projects (5)
- Conference papers (4)
- MIS/OM/DS Faculty Publications (4)
- All Maxine Goodman Levin School of Urban Affairs Publications (3)
- Electrical and Computer Engineering Publications (3)
- LSU New Orleans Theses and Dissertations (3)
- Theses and Dissertations (3)
- Applications and Applied Mathematics: An International Journal (AAM) (2)
- Master's Theses (2)
- Research outputs 2012 (2)
- Theses Digitization Project (2)
- Books/Book Chapters (1)
- Business Faculty Articles and Research (1)
- Business Faculty Publications (1)
- COURI Symposium Abstracts, Summer 2012 (1)
- DLPS Faculty Publications (1)
- Dissertations (1)
- Dissertations and Theses (1)
- Dissertations and Theses Collection (Open Access) (1)
- Doctoral Dissertations (1)
- Doctoral Dissertations and Master's Theses (1)
- Engineering Management & Systems Engineering Theses & Dissertations (1)
- Erforschung biologischer Ressourcen der Mongolei / Exploration into the Biological Resources of Mongolia, ISSN 0440-1298 (1)
- Faculty Scholarship (1)
- Graduate Theses and Dissertations (1)
- Publication Type
- File Type
Articles 91 - 120 of 233
Full-Text Articles in Databases and Information Systems
Exact Soft Confidence-Weighted Learning, Jialei Wang, Steven C. H. Hoi
Exact Soft Confidence-Weighted Learning, Jialei Wang, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
In this paper, we propose a new Soft Confidence-Weighted (SCW) online learning scheme, which enables the conventional confidence-weighted learning method to handle non-separable cases. Unlike the previous confidence-weighted learning algorithms, the proposed soft confidence-weighted learning method enjoys all the four salient properties: (i) large margin training, (ii) confidence weighting, (iii) capability to handle non-separable data, and (iv) adaptive margin. Our experimental results show that the proposed SCW algorithms significantly outperform the original CW algorithm. When comparing with a variety of state-of-the art algorithms (including AROW, NAROW and NHERD), we found that SCW generally achieves better or at least comparable predictive …
Online Kernel Selection: Algorithms And Evaluations, Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Yi, Steven C. H. Hoi
Online Kernel Selection: Algorithms And Evaluations, Tianbao Yang, Mehrdad Mahdavi, Rong Jin, Jinfeng Yi, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Kernel methods have been successfully applied to many machine learning problems. Nevertheless, since the performance of kernel methods depends heavily on the type of kernels being used, identifying good kernels among a set of given kernels is important to the success of kernel methods. A straightforward approach to address this problem is cross-validation by training a separate classifier for each kernel and choosing the best kernel classifier out of them. Another approach is Multiple Kernel Learning (MKL), which aims to learn a single kernel classifier from an optimal combination of multiple kernels. However, both approaches suffer from a high computational …
Mydeal: The Context-Aware Urban Shopping Assistant, Kartik Muralidharan, Swapna Gottipati, Jing Jiang, Narayan Ramasubbu, Rajesh Krishna Balan
Mydeal: The Context-Aware Urban Shopping Assistant, Kartik Muralidharan, Swapna Gottipati, Jing Jiang, Narayan Ramasubbu, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
A common problem in large Urban cities, of the sort seen in Asia, is the huge number of retail options available in the city. In particular, it is not uncommon to find multiple malls, each with hundreds of stores inside, just a short distance from each other in almost every part of these cities. These factors make it incredibly hard for consumers to identify stores of interest to them in any particular mall.In response, a number of shopping assistance applications have been created for mobile phones.However, these applications mostly just allow users to know which stores are where or to …
Finding Bursty Topics From Microblogs, Qiming Diao, Jing Jiang, Feida Zhu, Ee Peng Lim
Finding Bursty Topics From Microblogs, Qiming Diao, Jing Jiang, Feida Zhu, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Microblogs such as Twitter reflect the general public’s reactions to major events. Bursty topics from microblogs reveal what events have attracted the most online attention. Although bursty event detection from text streams has been studied before, previous work may not be suitable for microblogs because compared with other text streams such as news articles and scientific publications, microblog posts are particularly diverse and noisy. To find topics that have bursty patterns on microblogs, we propose a topic model that simultaneousy captures two observations: (1) posts published around the same time are more likely to have the same topic, and (2) …
Adaptive Cgf For Pilots Training In Air Combat Simulation, Teck-Hou Teng, Ah-Hwee Tan, Wee-Sze Ong, Kien-Lip Lee
Adaptive Cgf For Pilots Training In Air Combat Simulation, Teck-Hou Teng, Ah-Hwee Tan, Wee-Sze Ong, Kien-Lip Lee
Research Collection School Of Computing and Information Systems
Training of combat fighter pilots is often conducted using either human opponents or non-adaptive computer-generated force (CGF) inserted with the doctrine for conducting air combat mission. The novelty and challenges of such non-adaptive doctrine-driven CGF is often lost quickly. Incorporating more complex knowledge manually is known to be tedious and time-consuming. Therefore, a study of using adaptive CGF to learn from the real-time interactions with human pilots to extend the existing doctrine is conducted in this work. The goal of this study is to show how an adaptive CGF can be more effective than a non-adaptive doctrine-driven CGF for simulator-based …
On-Line Portfolio Selection With Moving Average Reversion, Bin Li, Steven C. H. Hoi
On-Line Portfolio Selection With Moving Average Reversion, Bin Li, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
On-line portfolio selection has attracted increasing interests in machine learning and AI communities recently. Empirical evidences show that stock's high and low prices are temporary and stock price relatives are likely to follow the mean reversion phenomenon. While the existing mean reversion strategies are shown to achieve good empirical performance on many real datasets, they often make the single-period mean reversion assumption, which is not always satisfied in some real datasets, leading to poor performance when the assumption does not hold. To overcome the limitation, this article proposes a multiple-period mean reversion, or so-called Moving Average Reversion (MAR), and a …
Fast Bounded Online Gradient Descent Algorithms For Scalable Kernel-Based Online Learning, Peilin Zhao, Jialei Wang, Pengcheng Wu, Rong Jin, Steven C. H. Hoi
Fast Bounded Online Gradient Descent Algorithms For Scalable Kernel-Based Online Learning, Peilin Zhao, Jialei Wang, Pengcheng Wu, Rong Jin, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Kernel-based online learning has often shown state-of-the-art performance for many online learning tasks. It, however, suffers from a major shortcoming, that is, the unbounded number of support vectors, making it non-scalable and unsuitable for applications with large-scale datasets. In this work, we study the problem of bounded kernel-based online learning that aims to constrain the number of support vectors by a predefined budget. Although several algorithms have been proposed in literature, they are neither computationally efficient due to their intensive budget maintenance strategy nor effective due to the use of simple Perceptron algorithm. To overcome these limitations, we propose a …
Topic Discovery From Tweet Replies, Bingtian Dai, Ee Peng Lim, Philips Kokoh Prasetyo
Topic Discovery From Tweet Replies, Bingtian Dai, Ee Peng Lim, Philips Kokoh Prasetyo
Research Collection School Of Computing and Information Systems
Twitter is a popular online social information network service which allows people to read and post messages up to 140 characters, known as “tweets”. In this paper, we focus on the tweets between pairs of individuals, i.e., the tweet replies, and propose a generative model to discover topics among groups of twitter users. Our model has then been evaluated with a tweet dataset to show its effectiveness.
Enhancing Access Privacy Of Range Retrievals Over B+Trees, Hwee Hwa Pang, Jilian Zhang, Kyriakos Mouratidis
Enhancing Access Privacy Of Range Retrievals Over B+Trees, Hwee Hwa Pang, Jilian Zhang, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
Users of databases that are hosted on shared servers cannot take for granted that their queries will not be disclosed to unauthorized parties. Even if the database is encrypted, an adversary who is monitoring the I/O activity on the server may still be able to infer some information about a user query. For the particular case of a B+-tree that has its nodes encrypted, we identify properties that enable the ordering among the leaf nodes to be deduced. These properties allow us to construct adversarial algorithms to recover the B+-tree structure from the I/O traces generated by range queries. Combining …
Joint Learning For Coreference Resolution With Markov Logic, Yang Song, Jing Jiang, Xin Zhao, Sujian Li, Houfeng Wang
Joint Learning For Coreference Resolution With Markov Logic, Yang Song, Jing Jiang, Xin Zhao, Sujian Li, Houfeng Wang
Research Collection School Of Computing and Information Systems
Pairwise coreference resolution models must merge pairwise coreference decisions to generate final outputs. Traditional merging methods adopt different strategies such as the best first method and enforcing the transitivity constraint, but most of these methods are used independently of the pairwise learning methods as an isolated inference procedure at the end. We propose a joint learning model which combines pairwise classification and mention clustering with Markov logic. Experimental results show that our joint learning system outperforms independent learning systems. Our system gives a better performance than all the learning-based systems from the CoNLL-2011 shared task on the same dataset. Compared …
Detecting Anomalous Twitter Users By Extreme Group Behaviors, Hanbo Dai, Ee-Peng Lim, Feida Zhu, Hwee Hwa Pang
Detecting Anomalous Twitter Users By Extreme Group Behaviors, Hanbo Dai, Ee-Peng Lim, Feida Zhu, Hwee Hwa Pang
Research Collection School Of Computing and Information Systems
Twitter has enjoyed tremendous popularity in the recent years. To help categorizing and search tweets, Twitter users assign hashtags to their tweets. Given that hashtag assignment is the primary way to semantically categorizing and search tweets, it is highly susceptible to abuse by spammers and other anomalous users [1]. Popular hashtags such as #Obama and #ladygaga could be hijacked by having them added to unrelated tweets with the intent of misleading many other users or promoting specific agenda to the users. The users performing this act are known as the hashtag hijackers. As the hijackers usually abuse common sets of …
Formal Analysis Of Pervasive Computing Systems, Yan Liu, Xian Zhang, Jin Song Dong, Yang Liu, Jun Sun, Jit Biswas, Mounir Mokhtari
Formal Analysis Of Pervasive Computing Systems, Yan Liu, Xian Zhang, Jin Song Dong, Yang Liu, Jun Sun, Jit Biswas, Mounir Mokhtari
Research Collection School Of Computing and Information Systems
Pervasive computing systems are heterogenous and complex as they usually involve human activities, various sensors and actuators as well as middleware for system controlling. Therefore, analyzing such systems is highly nontrivial. In this work, we propose to use formal methods for analyzing pervasive computing systems. Firstly, a formal modeling framework is proposed to cover the main characteristics of pervasive computing systems (e.g., context-awareness, concurrent communications, layered architectures). Secondly, we identify the safety requirements (e.g., free of deadlocks and conflicts etc.) and propose their specifications as safety and liveness properties. Finally, we demonstrate our ideas using a case study of a …
Information-Theoretic Multi-View Domain Adaptation, Pei Yang, Wei Gao, Qi Tan, Kam-Fai Wong
Information-Theoretic Multi-View Domain Adaptation, Pei Yang, Wei Gao, Qi Tan, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
We use multiple views for cross-domain document classification. The main idea is to strengthen the views’ consistency for target data with source training data by identifying the correlations of domain-specific features from different domains. We present an Information-theoretic Multi-view Adaptation Model (IMAM) based on a multi-way clustering scheme, where word and link clusters can draw together seemingly unrelated domain-specific features from both sides and iteratively boost the consistency between document clusterings based on word and link views. Experiments show that IMAM significantly outperforms state-of-the-art baselines.
Iexplore: A Provenance-Based Application For Exploring Biomedical Knowledge, Vinh Nguyen, Olivier Bodenreider, Thomas Rindflesch, Amit P. Sheth
Iexplore: A Provenance-Based Application For Exploring Biomedical Knowledge, Vinh Nguyen, Olivier Bodenreider, Thomas Rindflesch, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
The ∑Iq Methodology: An Information Quality Perspective On Oil Data, Yusuf Yiliyasi
The ∑Iq Methodology: An Information Quality Perspective On Oil Data, Yusuf Yiliyasi
Theses and Dissertations
Information quality (IQ) theories and frameworks have been increasingly studied and applied in various organizations to assess, improve and monitor the quality of their information products. Yet information quality problems remain pervasive in many organizations, industries and government institutions. For example various governmental as well as non-governmental organizations, institutions, and companies collect, compile and distribute information products in order to satisfy the needs of information consumers in the energy industry. What are the qualities of their information products? How do they collect or disseminate their data products? Why do information quality problems exist and how are the problems created? How …
W3c Semantic Sensor Networks: Ontologies, Applications, And Future Directions, Cory Andrew Henson
W3c Semantic Sensor Networks: Ontologies, Applications, And Future Directions, Cory Andrew Henson
Kno.e.sis Publications
Plenary Talk discussing the W3C Semantic Sensor Network, including the ontology, applications, and future directions.
Mobile Spatial Interaction In The Future Internet Of Things, James Carswell, Junjun Yin
Mobile Spatial Interaction In The Future Internet Of Things, James Carswell, Junjun Yin
Conference papers
Research and development of mobile information systems in the Future Internet of Things is about delivering technologies built around management and access to real-time heterogeneous datasets. Analyzing these enormous volumes of disparate data on mobile devices requires context-aware smart applications and services. 3DQ (Three Dimensional Query) is our novel mobile spatial interaction (MSI) prototype for data mining and analysis on today’s location and orientation aware “smartphones” within such 3D sensor web environments. Our application tailors a military style threat dome query calculation using MSI with “hidden query removal” functionality to reduce information overload and heighten situation awareness on these commercial …
Geometric Programming Subject To System Of Fuzzy Relation Inequalities, Elyas Shivanian, Mahdi Keshtkar, Esmaile Khorram
Geometric Programming Subject To System Of Fuzzy Relation Inequalities, Elyas Shivanian, Mahdi Keshtkar, Esmaile Khorram
Applications and Applied Mathematics: An International Journal (AAM)
In this paper, an optimization model with geometric objective function is presented. Geometric programming is widely used; many objective functions in optimization problems can be analyzed by geometric programming. We often encounter these in resource allocation and structure optimization and technology management, etc. On the other hand, fuzzy relation equalities and inequalities are also used in many areas. We here present a geometric programming model with a monomial objective function subject to the fuzzy relation inequality constraints with maxproduct composition. Simplification operations have been given to accelerate the resolution of the problem by removing the components having no effect on …
Numerical Solution Of Interval And Fuzzy System Of Linear Equations, Suparna Das, S. Chakraverty
Numerical Solution Of Interval And Fuzzy System Of Linear Equations, Suparna Das, S. Chakraverty
Applications and Applied Mathematics: An International Journal (AAM)
A system of linear equations, in general is solved in open literature for crisp unknowns, but in actual case the parameters (coefficients) of the system of linear equations contain uncertainty and are less crisp. The uncertainties may be considered in term of interval or fuzzy number. In this paper, a detail of study of linear simultaneous equations with interval and fuzzy parameter (triangular and trapezoidal) has been performed. New methods have been proposed for solving such systems. First, the methods have been tested for known problems viz. a circuit analysis solved in the literature and the results are found to …
Topical Anomaly Detection From Twitter Streams, Pramod Anantharam, Krishnaprasad Thirunarayan, Amit P. Sheth
Topical Anomaly Detection From Twitter Streams, Pramod Anantharam, Krishnaprasad Thirunarayan, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
An Evolutionary Search Paradigm That Learns With Past Experiences, Liang Feng, Yew-Soon Ong, Ivor Tsang, Ah-Hwee Tan
An Evolutionary Search Paradigm That Learns With Past Experiences, Liang Feng, Yew-Soon Ong, Ivor Tsang, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
A major drawback of evolutionary optimization approaches in the literature is the apparent lack of automated knowledge transfers and reuse across problems. Particularly, evolutionary optimization methods generally start a search from scratch or ground zero state, independent of how similar the given new problem of interest is to those optimized previously. In this paper, we present a study on the transfer of knowledge in the form of useful structured knowledge or latent patterns that are captured from previous experiences of problem-solving to enhance future evolutionary search. The essential contributions of our present study include the meme learning and meme selection …
More Of A Receiver Than A Giver: Why Do People Unfollow In Twitter?, Haewoon Kwak, Sue Moon, Wonjae Lee
More Of A Receiver Than A Giver: Why Do People Unfollow In Twitter?, Haewoon Kwak, Sue Moon, Wonjae Lee
Research Collection School Of Computing and Information Systems
We propose a logistic regression model taking into ac- count two analytically different sets of factors–structure and action. The factors include individual, dyadic, and triadic properties between ego and alter whose tie breakup is under consideration. From the fitted model using a large-scale data, we discover 5 structural and 7 actional variables to have significant explanatory power for unfollow. One unique finding from our quantitative analysis is that people appreciate receiving acknowl- edgements from others even in virtually unilateral com- munication relationships and are less likely to unfollow them: people are more of a receiver than a giver.
Prediction Of Topic Volume On Twitter, Yiye Ruan, Hemant Purohit, David Fuhry, Srinivasan Parthasarathy, Amit P. Sheth
Prediction Of Topic Volume On Twitter, Yiye Ruan, Hemant Purohit, David Fuhry, Srinivasan Parthasarathy, Amit P. Sheth
Kno.e.sis Publications
We discuss an approach for predicting microscopic (individual) and macroscopic (collective) user behavioral patterns with respect to specific trending topics on Twitter. Going beyond previous efforts that have analyzed driving factors in whether and when a user will publish topic-relevant tweets, here we seek to predict the strength of content generation which allows more accurate understanding of Twitter users' behavior and more effective utilization of the online social network for diffusing information. Unlike traditional approaches, we consider multiple dimensions into one regression-based prediction framework covering network structure, user interaction, content characteristics and past activity. Experimental results on three large Twitter …
A Web-Based Study Of Self-Treatment Of Opioid Withdrawal Symptoms With Loperamide, Raminta Daniulaityte, Robert G. Carlson, Russel S. Falck, Delroy H. Cameron, Sujan Udayanaga, Lu Chen, Amit P. Sheth
A Web-Based Study Of Self-Treatment Of Opioid Withdrawal Symptoms With Loperamide, Raminta Daniulaityte, Robert G. Carlson, Russel S. Falck, Delroy H. Cameron, Sujan Udayanaga, Lu Chen, Amit P. Sheth
Kno.e.sis Publications
Aims: Many websites provide a medium for individuals to freely share their experiences and knowledge about different drugs. Such user-generated content can be used as a rich data source to study emerging drug use practices and trends. The study aims to examine web-based reports of loperamide use practices among non-medical opioid users. Loperamide, a piperidine derivative, is an opioid agonist approved for the control of diarrhea symptoms. Because of its general inability to cross the blood-brain barrier, it is considered to have no abuse potential and is available without a prescription. Methods: A website that allows free discussion of illicit …
Suffix Trees For Document Retrieval, Ryan Reck
Suffix Trees For Document Retrieval, Ryan Reck
Master's Theses
This thesis presents a look at the suitability of Suffix Trees for full text indexing and retrieval. Typically suffix trees are built on a character level, where the tree records which characters follow each other character. By building suffix trees for documents based on words instead of characters, the resulting tree effectively indexes every word or sequence of words that occur in any of the documents. Ukkonnen's algorithm is adapted to build word-level suffix trees. But the primary focus is on developing Algorithms for searching the suffix tree for exact and approximate, or fuzzy, matches to arbitrary query strings. A …
Semi-Supervised Hierarchical Clustering For Personalized Web Image Organization, Lei Meng, Ah-Hwee Tan
Semi-Supervised Hierarchical Clustering For Personalized Web Image Organization, Lei Meng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Existing efforts on web image organization usually transform the task into surrounding text clustering. However, Current text clustering algorithms do not address the problem of insufficient statistical information for image representation and noisy tags which greatly decreases the clustering performance while increases the computational cost. In this paper, we propose a two-step semi-supervised hierarchical clustering algorithm, Personalized Hierarchical Theme-based Clustering (PHTC), for web image organization. In the first step, the Probabilistic Fusion ART (PF-ART) is proposed for grouping semantically similar images and simultaneously learning the probabilistic distribution of tag occurrence for mining the key tags/topics of clusters. In this way, …
When A Friend In Twitter Is A Friend In Life, Wei Xie, Cheng Li, Feida Zhu, Ee-Peng Lim, Xueqing Gong
When A Friend In Twitter Is A Friend In Life, Wei Xie, Cheng Li, Feida Zhu, Ee-Peng Lim, Xueqing Gong
Research Collection School Of Computing and Information Systems
Twitter is a fast-growing online social network service (SNS) where users can "follow" any other user to receive his or her mini-blogs which are called "tweets". In this paper, we study the problem of identifying a user's off-line real-life social community, which we call the user'sTwitter off-line community, purely from examining Twitter network structure. Based on observations from our user-verified Twitter data and results from previous works, we propose three principles about Twitter off-line communities. Incorporating these principles, we develop a novel algorithm to iteratively discover the Twitter off-line community based on a new way of measuring user closeness. According …
Self-Organizing Neural Networks For Learning Air Combat Maneuvers, Teck-Hou Teng, Ah-Hwee Tan
Self-Organizing Neural Networks For Learning Air Combat Maneuvers, Teck-Hou Teng, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
This paper reports on an agent-oriented approach for the modeling of adaptive doctrine-equipped computer generated force (CGF) using a commercial-grade simulation platform known as CAE STRIVECGF. A self- organizing neural network is used for the adaptive CGF to learn and generalize knowledge in an online manner during the simulation. The challenge of defining the state space and action space and the lack of domain knowledge to initialize the adaptive CGF are addressed using the doctrine used to drive the non-adaptive CGF. The doctrine contains a set of specialized knowledge for conducting 1-v-1 dogfights. The hierarchical structure and symbol representation of …
A Novel Unbalanced Tree Structure For Low-Cost Authentication Of Streaming Content On Mobile And Sensor Devices, Thivya Kandappu, Vijay Sivaraman, Roksana Boreli
A Novel Unbalanced Tree Structure For Low-Cost Authentication Of Streaming Content On Mobile And Sensor Devices, Thivya Kandappu, Vijay Sivaraman, Roksana Boreli
Research Collection School Of Computing and Information Systems
We consider stored content being streamed to a resource-poor device (such as a sensor node or a mobile phone), and address the issue of authenticating such content in realtime at the receiver. Per-packet digital signatures incur high computational cost, while per-block signatures impose high delays. A Merkle hash tree combines the benefits of the two by having a single signature per-block (at the root of the tree), while allowing immediate per-packet verification by following a hash-path logarithmic in the number of packets. In this paper we explore how the structure of the Merkle tree can be adapted to improve playback …
Memory Formation, Consolidation, And Forgetting In Learning Agents, Budhitama Subagdja, Wenwen Wang, Ah-Hwee Tan, Yuan-Sin Tan, Loo-Nin Teow
Memory Formation, Consolidation, And Forgetting In Learning Agents, Budhitama Subagdja, Wenwen Wang, Ah-Hwee Tan, Yuan-Sin Tan, Loo-Nin Teow
Research Collection School Of Computing and Information Systems
Memory enables past experiences to be remembered and acquired as useful knowledge to support decision making, especially when perception and computational resources are limited. This paper presents a neuropsychological-inspired dual memory model for agents, consisting of an episodic memory that records the agent’s experience in real time and a semantic memory that captures factual knowledge through a parallel consolidation process. In addition, the model incorporates a natural forgetting mechanism that prevents memory overloading by removing transient memory traces. Our experimental study based on a real-time first-person-shooter video game has indicated that the memory consolidation and forgetting processes are not only …