Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Language model (2)
- News videos (2)
- Similarity measure (2)
- Algorithms (1)
- Cell formation (1)
-
- Cellular manufacturing (1)
- Cross-lingual information retrieval (1)
- Factorization (1)
- Genetic algorithms (1)
- Group layout (1)
- Hybrid algorithm (1)
- Image retrieval (1)
- Improvement heuristic algorithm (1)
- Kernel machines (1)
- Linear equations (1)
- Mathematical programming (1)
- Mathematical programming model (1)
- Multimodality (1)
- Multiple modalities (1)
- Near-duplicate keyframe (1)
- Near-duplicate keyframes (1)
- Novelty and redundancy detection (1)
- Problem solving (1)
- QoS routing (1)
- Routing algorithm (1)
- Simulated annealing (1)
- Spanning hyper-tree (1)
- Supervised genetic algorithm (1)
- Supervised search rules (1)
- Support vector machines (1)
Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
Study Of The Minimum Spanning Hyper-Tree Routing Algorithm In Wireless Sensor Networks, Ting Yang, Yugeng Sun, Zhaoxia Wang, Juwei Zhang, Yingqiang Ding
Study Of The Minimum Spanning Hyper-Tree Routing Algorithm In Wireless Sensor Networks, Ting Yang, Yugeng Sun, Zhaoxia Wang, Juwei Zhang, Yingqiang Ding
Research Collection School Of Computing and Information Systems
Designing energy-efficient routing protocols to effectively increase the networks' lifetime and provide the robust network service is one of the important problems in the research of wireless sensor networks. Using the hyper-graph theory, the paper represents large-scale wireless sensor networks into a hyper-graph model, which can effectively decrease the control messages in routing process. Based on this mathematic model, the paper presents the minimum spanning hyper-tree routing algorithm in synchronous wireless sensor networks (MSHT-SN), which builds a minimum energy consumption tree for data collection from multi-nodes to Sink node. The validity of the algorithm is proved by the theatrical analysis. …
Novelty Detection For Cross-Lingual News Stories With Visual Duplicates And Speech Transcripts, Xiao Wu, Alexander G. Hauptmann, Chong-Wah Ngo
Novelty Detection For Cross-Lingual News Stories With Visual Duplicates And Speech Transcripts, Xiao Wu, Alexander G. Hauptmann, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
An overwhelming volume of news videos from different channels and languages is available today, which demands automatic management of this abundant information. To effectively search, retrieve, browse and track cross-lingual news stories, a news story similarity measure plays a critical role in assessing the novelty and redundancy among them. In this paper, we explore the novelty and redundancy detection with visual duplicates and speech transcripts for cross-lingual news stories. News stories are represented by a sequence of keyframes in the visual track and a set of words extracted from speech transcript in the audio track. A major difference to pure …
A Genetic Algorithm For Cellular Manufacturing Design And Layout, Xiaodan Wu, Chao-Hsien Chu, Yunfeng Wang, Weili Yan
A Genetic Algorithm For Cellular Manufacturing Design And Layout, Xiaodan Wu, Chao-Hsien Chu, Yunfeng Wang, Weili Yan
Research Collection School Of Computing and Information Systems
Cellular manufacturing (CM) is an approach that can be used to enhance both flexibility and efficiency in today’s small-to-medium lot production environment. The design of a CM system (CMS) often involves three major decisions: cell formation, group layout, and group schedule. Ideally, these decisions should be addressed simultaneously in order to obtain the best results. However, due to the complexity and NP-complete nature of each decision and the limitations of traditional approaches, most researchers have only addressed these decisions sequentially or independently. In this study, a hierarchical genetic algorithm is developed to simultaneously form manufacturing cells and determine the group …
Near-Duplicate Keyframe Retrieval With Visual Keywords And Semantic Context, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Near-Duplicate Keyframe Retrieval With Visual Keywords And Semantic Context, Xiao Wu, Wan-Lei Zhao, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
Near-duplicate keyframes (NDK) play a unique role in large-scale video search, news topic detection and tracking. In this paper, we propose a novel NDK retrieval approach by exploring both visual and textual cues from the visual vocabulary and semantic context respectively. The vocabulary, which provides entries for visual keywords, is formed by the clustering of local keypoints. The semantic context is inferred from the speech transcript surrounding a keyframe. We experiment the usefulness of visual keywords and semantic context, separately and jointly, using cosine similarity and language models. By linearly fusing both modalities, performance improvement is reported compared with the …
A Multi-Scale Tikhonov Regularization Scheme For Implicit Surface Modeling, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu
A Multi-Scale Tikhonov Regularization Scheme For Implicit Surface Modeling, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu
Research Collection School Of Computing and Information Systems
Kernel machines have recently been considered as a promising solution for implicit surface modelling. A key challenge of machine learning solutions is how to fit implicit shape models from large-scale sets of point cloud samples efficiently. In this paper, we propose a fast solution for approximating implicit surfaces based on a multi-scale Tikhonov regularization scheme. The optimization of our scheme is formulated into a sparse linear equation system, which can be efficiently solved by factorization methods. Different from traditional approaches, our scheme does not employ auxiliary off-surface points, which not only saves the computational cost but also avoids the problem …
Enhancing The Performance Of Semi-Supervised Classification Algorithms With Bridging, Jason Yuk Hin Chan, Josiah Poon, Irena Koprinska
Enhancing The Performance Of Semi-Supervised Classification Algorithms With Bridging, Jason Yuk Hin Chan, Josiah Poon, Irena Koprinska
Research Collection School Of Computing and Information Systems
Traditional supervised classification algorithms require a large number of labelled examples to perform accurately. Semi-supervised classification algorithms attempt to overcome this major limitation by also using unlabelled examples. Unlabelled examples have also been used to improve nearest neighbour text classification in a method called bridging. In this paper, we propose the use of bridging in a semi-supervised setting. We introduce a new bridging algorithm that can be used as a base classifier in any supervised approach such as co-training or selflearning. We empirically show that classification performance increases by improving the semi-supervised algorithm’s ability to correctly assign labels to previouslyunlabelled …
Quality Of Service Routing Strategy Using Supervised Genetic Algorithm, Zhaoxia Wang, Yugeng Sun, Zhiyong Wang, Huayu Shen
Quality Of Service Routing Strategy Using Supervised Genetic Algorithm, Zhaoxia Wang, Yugeng Sun, Zhiyong Wang, Huayu Shen
Research Collection School Of Computing and Information Systems
A supervised genetic algorithm (SGA) is proposed to solve the quality of service (QoS) routing problems in computer networks. The supervised rules of intelligent concept are introduced into genetic algorithms (GAs) to solve the constraint optimization problem. One of the main characteristics of SGA is its searching space can be limited in feasible regions rather than infeasible regions. The superiority of SGA to other GAs lies in that some supervised search rules in which the information comes from the problems are incorporated into SGA. The simulation results show that SGA improves the ability of searching an optimum solution and accelerates …
Solving The Teacher Assignment-Course Scheduling Problem By A Hybrid Algorithm, Aldy Gunawan, Kien Ming Ng, Kim Leng Poh
Solving The Teacher Assignment-Course Scheduling Problem By A Hybrid Algorithm, Aldy Gunawan, Kien Ming Ng, Kim Leng Poh
Research Collection School Of Computing and Information Systems
This paper presents a hybrid algorithm for solving atimetabling problem, which is commonly encountered in manyuniversities. The problem combines both teacher assignment andcourse scheduling problems simultaneously, and is presented as amathematical programming model. However, this problem becomesintractable and it is unlikely that a proven optimal solution can beobtained by an integer programming approach, especially for largeproblem instances. A hybrid algorithm that combines an integerprogramming approach, a greedy heuristic and a modified simulatedannealing algorithm collaboratively is proposed to solve the problem.Several randomly generated data sets of sizes comparable to that ofan institution in Indonesia are solved using the proposed algorithm.Computational results …
An Improvement Heuristic For The Timetabling Problem, Aldy Gunawan, Kien Ming Ng, Kim Leng Poh
An Improvement Heuristic For The Timetabling Problem, Aldy Gunawan, Kien Ming Ng, Kim Leng Poh
Research Collection School Of Computing and Information Systems
This paper formulates a timetabling problem, which is often encountered in a university, as a mathematical programming model. The proposed model combines both teacher assignment and course scheduling problems simultaneously, which causes the entire model to become more complex. We propose an improvement heuristic algorithm to solve such a model. The proposed algorithm has been tested with several randomly generated datasets of sizes that are comparable to those occurring in a university in Indonesia. The computational results show that the improvement heuristic is not only able to obtain good solutions, but is also able to do so within reasonable computational …