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Articles 91 - 101 of 101
Full-Text Articles in OS and Networks
Identification Of Tcp Protocols, Juan Shao
Identification Of Tcp Protocols, Juan Shao
School of Computing: Dissertations, Theses, and Student Research
Recently, many new TCP algorithms, such as BIC, CUBIC, and CTCP, have been deployed in the Internet. Investigating the deployment statistics of these TCP algorithms is meaningful to study the performance and stability of the Internet. Currently, there is a tool named Congestion Avoidance Algorithm Identification (CAAI) for identifying the TCP algorithm of a web server and then for investigating the TCP deployment statistics. However, CAAI using a simple k-NN algorithm can not achieve a high identification accuracy. In this thesis, we comprehensively study the identification accuracy of five popular machine learning models. We find that the random forest model …
Benchmarking Still-To-Video Face Recognition Via Partial And Local Linear Discriminant Analysis On Cox-S2v Dataset, Zhiwu Huang, S. Shan, H. Zhang, S. Lao, A. Kuerban, X. Chen
Benchmarking Still-To-Video Face Recognition Via Partial And Local Linear Discriminant Analysis On Cox-S2v Dataset, Zhiwu Huang, S. Shan, H. Zhang, S. Lao, A. Kuerban, X. Chen
Research Collection School Of Computing and Information Systems
In this paper, we explore the real-world Still-to-Video (S2V) face recognition scenario, where only very few (single, in many cases) still images per person are enrolled into the gallery while it is usually possible to capture one or multiple video clips as probe. Typical application of S2V is mug-shot based watch list screening. Generally, in this scenario, the still image(s) were collected under controlled environment, thus of high quality and resolution, in frontal view, with normal lighting and neutral expression. On the contrary, the testing video frames are of low resolution and low quality, possibly with blur, and captured under …
Motivated Learning For The Development Of Autonomous Agents, Janusz A. Starzyk, James T. Graham, Pawel Raif, Ah-Hwee Tan
Motivated Learning For The Development Of Autonomous Agents, Janusz A. Starzyk, James T. Graham, Pawel Raif, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
A new machine learning approach known as motivated learning (ML) is presented in this work. Motivated learning drives a machine to develop abstract motivations and choose its own goals. ML also provides a self-organizing system that controls a machine’s behavior based on competition between dynamically-changing pain signals. This provides an interplay of externally driven and internally generated control signals. It is demonstrated that ML not only yields a more sophisticated learning mechanism and system of values than reinforcement learning (RL), but is also more efficient in learning complex relations and delivers better performance than RL in dynamically changing environments. In …
Networks - I: Computational Intelligence Based Optimization In Wireless Sensor Network, Rabia Iram, Muhammad Irfan Sheikh, Sohail Jabbar, Abid Ali Minhas
Networks - I: Computational Intelligence Based Optimization In Wireless Sensor Network, Rabia Iram, Muhammad Irfan Sheikh, Sohail Jabbar, Abid Ali Minhas
International Conference on Information and Communication Technologies
There are only two ways to live your life. One is as though nothing is a miracle. The other is as though everything is a miracle and so the technology advancement which proved to be a miracle of the miracles. Wireless Sensor Network (WSN) is one such miracle of the wireless technology which opens up the new dimensions for the researchers to write the technology of the future i.e. ubiquitous computing and intelligence. Nevertheless nature has played its ultimate role as well to give an idea of perfection in optimizing the teething issues in any field and so in WSN. …
A Study Of Three Artificial Neural Networks Models' Ability To Identify Emotions From Facial Images, Timothy Scott Hyde
A Study Of Three Artificial Neural Networks Models' Ability To Identify Emotions From Facial Images, Timothy Scott Hyde
Theses and Dissertations
Facial expressions conveying emotions are vital for human communication. They are also important in the studies of human interaction and behavioral studies. Recognition of emotions, using facial images, may provide a fast and practical approach that is noninvasive. Most previous studies of emotion recognition through facial images were based on the Facial Action Coding System (FACS). The FACS, which was developed by Ekman and Freisen in 1978, was created to identify different facial muscular actions. Previous artificial neural network-based approaches for classification of facial expressions focused on improving one particular neural network model for better accuracy. The purpose of this …
A Neural Network Approach To Border Gateway Protocol Peer Failure Detection And Prediction, Cory B. White
A Neural Network Approach To Border Gateway Protocol Peer Failure Detection And Prediction, Cory B. White
Master's Theses
The size and speed of computer networks continue to expand at a rapid pace, as do the corresponding errors, failures, and faults inherent within such extensive networks. This thesis introduces a novel approach to interface Border Gateway Protocol (BGP) computer networks with neural networks to learn the precursor connectivity patterns that emerge prior to a node failure. Details of the design and construction of a framework that utilizes neural networks to learn and monitor BGP connection states as a means of detecting and predicting BGP peer node failure are presented. Moreover, this framework is used to monitor a BGP network …
Automatic Speaker Identification Using Reusable And Retrainable Binary-Pair Partitioned Neural Networks, Ashutosh Mishra
Automatic Speaker Identification Using Reusable And Retrainable Binary-Pair Partitioned Neural Networks, Ashutosh Mishra
Electrical & Computer Engineering Theses & Dissertations
This thesis presents an extension of the work previously done on speaker identification using Binary Pair Partitioned (BPP) neural networks. In the previous work, a separate network was used for each pair of speakers in the speaker population. Although the basic BPP approach did perform well and had a simple underlying algorithm, it had the obvious disadvantage of requiring an extremely large number of networks for speaker identification with large speaker populations. It also requires training of networks proportional to the square of the number of speakers under consideration, leading to a very large number of networks to be trained …
A Genetic Algorithm Solution To The Shortest Path Problem In Ospf And Mpls, Wee Jing Tee Wee Jing
A Genetic Algorithm Solution To The Shortest Path Problem In Ospf And Mpls, Wee Jing Tee Wee Jing
Student Works (2000-2009)
This project studies and explores the potential of using genetic algorithm to solve the shortest path problem in Open Shortest Path First (OSPF) and Multiprotocol Label Switching (MPLS). The most critical task for developing a genetic algorithm to the shortest path problem is to how to encode a path in a network. In this project, two genetic algorithm solutions arc developed for the above two problem domains, i.e. Previous-node-based Encoding to solve the shortest path problem in OSPF and Priority-based Encoding to solve the shortest path problem in MPLS. For each of the shortest path problem domains, the proposed solution …
Dynamic Bandwidth Allocation Using Neural-Fuzzy In Atm Network, Yan Sing Chua
Dynamic Bandwidth Allocation Using Neural-Fuzzy In Atm Network, Yan Sing Chua
Student Works (2000-2009)
Dynamic bandwidth allocation is becoming one of the crucial issues in the design and research in the computer network. This is due to the continuous increasing demand of intensive applications that require more bandwidth while retaining higher quality. Dynamic bandwidth allocation utilises the current network state information to optimise the bandwidth distribution. The state information can be gathered through prediction using past data and measurement on current state. Agility and flexibility of dynamic bandwidth allocation using Neural-Fuzzy has the advantage that it can adapt to the state changes of the network. ATM network carries heterogeneous traffic and this causes the …
Intelligent Agent For E-Commerce Using Genetic Algorithm, Sun Sun Kok
Intelligent Agent For E-Commerce Using Genetic Algorithm, Sun Sun Kok
Student Works (2000-2009)
This project report outlines the introduction, literature study and methodology, system analysis and design, system implementation, system testing and summary of the whole project. The major objective of this system is to develop an intelligent agent that can gather. analyze and categorize information from the Web on the printers that complying the parameters specified /identified by the web users, and to provide recommendations for online purchases for all types of printers. The recommended web sites are restricted to web pages that provide online purchase facilities and deliveries in Malaysia. The system is able to update the information from the database …
An Adaptive Fuzzy Logic Controller For Intelligent Networking And Control, Irshad Nainar
An Adaptive Fuzzy Logic Controller For Intelligent Networking And Control, Irshad Nainar
Theses: Doctorates and Masters
In this thesis, we present a fuzzy logic control scheme to regulate the flow of traffic approaching a set of intersections. An adaptive Fuzzy Logic Traffic Controller (FLTC) is used to adjust the green phase split of the north-south and east-west approaches of a set of traffic signals based on the actual traffic approaching the intersection. Each intersection is coordinated with its neighbouring intersections by adjusting the offset of the local intersection. The offset is adjusted by a local fuzzy logic controller loacted at each intersection. A new fuzzy control scheme, using a supervisory Fuzzy Logic Controller, is also proposed …