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- Faculty of Engineering and Information Sciences - Papers: Part A (56)
- Faculty of Engineering and Information Sciences - Papers: Part B (16)
- Journal of Digital Forensics, Security and Law (3)
- Dissertations, Theses, and Capstone Projects (2)
- Professor Farzad Safaei (2)
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- Ah Chung Tsoi (1)
- Anthony A Espinoza Mr (1)
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- Information Systems Undergraduate Honors Theses (1)
- International Journal of Geospatial and Environmental Research (1)
- March 13, 2013: Regional Sea Level Rise Assessment, Adaptation and Flood Mitigation Projects (1)
- Nagesh Shukla (1)
- Professor Katina Michael (1)
- The Journal of Sociotechnical Critique (1)
- University of Vermont Transportation Research Center (1)
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Articles 31 - 60 of 93
Full-Text Articles in Social and Behavioral Sciences
A Bottom-Up Data Collection Methodology For Characterising The Residential Building Stock In Australia, Clayton Mcdowell, Georgios Kokogiannakis, Paul Cooper, Michael P. Tibbs
A Bottom-Up Data Collection Methodology For Characterising The Residential Building Stock In Australia, Clayton Mcdowell, Georgios Kokogiannakis, Paul Cooper, Michael P. Tibbs
Faculty of Engineering and Information Sciences - Papers: Part B
In Australia the majority of the current residential building stock has been constructed with little regard to energy consumption or thermal comfort. With only 1-2 % of Australia's building stock being replaced each year retrofitting solutions are necessary if residential energy consumption is to be reduced. Australia's records of the characteristics of its current building stock are minimal and outdated and thus these need to be renewed to enable the evaluation of retrofit upgrade strategies. Thus this paper presents a methodology and results of a bottom-up data collection tool that captured building and occupant characteristics from 200 elderly low income …
Tour-Based Travel Mode Choice Estimation Based On Data Mining And Fuzzy Techniques, Nagesh Shukla, Jun Ma, Rohan Wickramasuriya, Nam N. Huynh, Pascal Perez
Tour-Based Travel Mode Choice Estimation Based On Data Mining And Fuzzy Techniques, Nagesh Shukla, Jun Ma, Rohan Wickramasuriya, Nam N. Huynh, Pascal Perez
Nagesh Shukla
No abstract provided.
A Comparative Analysis Of Multichannel Data Acquisition Systems For Quality Assurance In External Beam Radiation Therapy, Iolanda Fuduli, Claudiu Porumb, Anthony Espinoza, Abdullah Aldosari, Martin Carolan, Michael Lf Lerch, Peter E. Metcalfe, Anatoly Rosenfeld, Marco Petasecca
A Comparative Analysis Of Multichannel Data Acquisition Systems For Quality Assurance In External Beam Radiation Therapy, Iolanda Fuduli, Claudiu Porumb, Anthony Espinoza, Abdullah Aldosari, Martin Carolan, Michael Lf Lerch, Peter E. Metcalfe, Anatoly Rosenfeld, Marco Petasecca
Anthony A Espinoza Mr
The paper presents a comparative study performed by the Centre of Medical Radiation Physics (CMRP) on three multichannel Data Acquisition Systems (DAQ) based on different analogue front-ends to suit a wide range of radiotherapy applications. The three front-ends are: a charge-to-frequency converter developed by INFN Torino, an electrometer and a charge-to-digital converter (both commercial devices from Texas Instruments). For the first two (named DAQ A and B), the CMRP has designed the read-out systems whilst the third one (DAQ C) comes with its own evaluation board. For the purpose of the characterization DAQ A and DAQ B have been equipped …
The "Bring Your Own Device" Conundrum For Organizations And Investigators: An Examination Of The Policy And Legal Concerns In Light Of Investigatory Challenges, Carla J. Utter, Alan Rea
The "Bring Your Own Device" Conundrum For Organizations And Investigators: An Examination Of The Policy And Legal Concerns In Light Of Investigatory Challenges, Carla J. Utter, Alan Rea
Journal of Digital Forensics, Security and Law
In recent years, with the expansion of technology and the desire to downsize costs within the corporate culture, the technology trend has steered towards the integration of personally owned mobile devices (i.e. smartphones) within the corporate and enterprise environment. The movement, known as “Bring Your Own Device” (hereinafter referred to as “BYOD”), seeks to minimize or eliminate the need for two separate and distinct mobile devices for one employee. While taken at face value this trend seems favorable, the corporate policy and legal implications of the implementation of BYOD are further complicated by significant investigatory issues that far outweigh the …
Cyber Black Box/Event Data Recorder: Legal And Ethical Perspectives And Challenges With Digital Forensics, Michael Losavio, Pavel Pastukov, Svetlana Polyakova
Cyber Black Box/Event Data Recorder: Legal And Ethical Perspectives And Challenges With Digital Forensics, Michael Losavio, Pavel Pastukov, Svetlana Polyakova
Journal of Digital Forensics, Security and Law
With ubiquitous computing and the growth of the Internet of Things, there is vast expansion in the deployment and use of event data recording systems in a variety of environments. From the ships’ logs of antiquity through the evolution of personal devices for recording personal and environmental activities, these devices offer rich forensic and evidentiary opportunities that smash against rights of privacy and personality. The technical configurations of these devices provide for greater scope of sensing, interconnection options for local, near, and cloud storage of data, and the possibility of powerful analytics. This creates the unique situation of near-total data …
Arcgis V.10 Landslide Susceptibility Data Mining Add-In Tool Integrating Data Mining And Gis Techniques To Model Landslide Susceptibility, Darshika Palamakumbure, David Stirling, Phillip N. Flentje, Robin N. Chowdhury
Arcgis V.10 Landslide Susceptibility Data Mining Add-In Tool Integrating Data Mining And Gis Techniques To Model Landslide Susceptibility, Darshika Palamakumbure, David Stirling, Phillip N. Flentje, Robin N. Chowdhury
Faculty of Engineering and Information Sciences - Papers: Part A
Landslide susceptibility modeling is an essential early step towards managing landslide risk. A minimum of $4.8 million is lost due to landslide related damages every year in Illawara region of Australia. At present, Data mining and knowledge discovery techniques are becoming popular in building landslide susceptibility models due to their enhanced predictive performances. Until now, the lack of tools to undertake data extraction and making the predictions have limited the applicability of this novel technique in landslide model building. This paper discusses the development of the LSDM (Landslide Susceptibility Data Mining) toolbar which was designed to utilize machine learning techniques …
Vivambc: Estimating Viral Sequence Variation In Complex Populations From Illumina Deep-Sequencing Data Using Model-Based Clustering, Bie M. P Verbist, Lieven Clement, Joke Reumers, Kim Thys, Alexander Vapirev, Willem Talloen, Yves Wetzels, Joris Meys, Jeroen Aerssens, Luc Bijnens, Olivier Thas
Vivambc: Estimating Viral Sequence Variation In Complex Populations From Illumina Deep-Sequencing Data Using Model-Based Clustering, Bie M. P Verbist, Lieven Clement, Joke Reumers, Kim Thys, Alexander Vapirev, Willem Talloen, Yves Wetzels, Joris Meys, Jeroen Aerssens, Luc Bijnens, Olivier Thas
Faculty of Engineering and Information Sciences - Papers: Part A
Background: Deep-sequencing allows for an in-depth characterization of sequence variation in complex populations. However, technology associated errors may impede a powerful assessment of low-frequency mutations. Fortunately, base calls are complemented with quality scores which are derived from a quadruplet of intensities, one channel for each nucleotide type for Illumina sequencing. The highest intensity of the four channels determines the base that is called. Mismatch bases can often be corrected by the second best base, i.e. the base with the second highest intensity in the quadruplet. A virus variant model-based clustering method, ViVaMBC, is presented that explores quality scores and second …
Recent Advances In Security And Privacy In Big Data, Yong Yu, Yi Mu, Giuseppe Ateniese
Recent Advances In Security And Privacy In Big Data, Yong Yu, Yi Mu, Giuseppe Ateniese
Faculty of Engineering and Information Sciences - Papers: Part A
Big data has become an important topic in science, engineering, medicine, healthcare, finance, business and ultimately society itself. Big data refers to the massive amount of digital information stored or transmitted in computer systems. Approximately, 2.5 quintillion bytes of data are created every day. Almost 90% of data in the world today are created in the last two years alone. Security and privacy issues becomes more critical due to large volumes and variety, due to data hosted in large-scale cloud infrastructures, diversity of data sources and formats, streaming nature of data acquisition and high volume inter-cloud migration. In large-scale cloud …
Searchable Atribute-Based Mechanism With Efficiient Data Sharing For Secure Cloud Storage, Kaitai Liang, Willy Susilo
Searchable Atribute-Based Mechanism With Efficiient Data Sharing For Secure Cloud Storage, Kaitai Liang, Willy Susilo
Faculty of Engineering and Information Sciences - Papers: Part A
To date, the growth of electronic personal data leads to a trend that data owners prefer to remotely outsource their data to clouds for the enjoyment of the high-quality retrieval and storage service without worrying the burden of local data management and maintenance. However, secure share and search for the outsourced data is a formidable task, which may easily incur the leakage of sensitive personal information. Efficient data sharing and searching with security is of critical importance. This paper, for the first time, proposes a searchable attribute-based proxy re-encryption system. When compared to existing systems only supporting either searchable attribute-based …
Tour-Based Travel Mode Choice Estimation Based On Data Mining And Fuzzy Techniques, Nagesh Shukla, Jun Ma, Rohan Wickramasuriya, Nam N. Huynh, Pascal Perez
Tour-Based Travel Mode Choice Estimation Based On Data Mining And Fuzzy Techniques, Nagesh Shukla, Jun Ma, Rohan Wickramasuriya, Nam N. Huynh, Pascal Perez
Faculty of Engineering and Information Sciences - Papers: Part A
No abstract provided.
Identity-Based Secure Distributed Data Storage Schemes, Jinguang Han, Willy Susilo, Yi Mu
Identity-Based Secure Distributed Data Storage Schemes, Jinguang Han, Willy Susilo, Yi Mu
Faculty of Engineering and Information Sciences - Papers: Part A
Secure distributed data storage can shift the burden of maintaining a large number of files from the owner to proxy servers. Proxy servers can convert encrypted files for the owner to encrypted files for the receiver without the necessity of knowing the content of the original files. In practice, the original files will be removed by the owner for the sake of space efficiency. Hence, the issues on confidentiality and integrity of the outsourced data must be addressed carefully. In this paper, we propose two identity-based secure distributed data storage (IBSDDS) schemes. Our schemes can capture the following properties: (1) …
Data Scientists As Game Changers In Big Data Environments, Akemi T. Chatfield, Vivian N. Shlemoon, Wilbur Redublado, Faizur Rahman
Data Scientists As Game Changers In Big Data Environments, Akemi T. Chatfield, Vivian N. Shlemoon, Wilbur Redublado, Faizur Rahman
Faculty of Engineering and Information Sciences - Papers: Part A
The potential power of big data to generate insights and create new forms of value in the ways which transform organizations and society has been observed by big data-driven organizations and big data experts. Despite the recent sensational declaration of a data scientist as "the sexiest job of the 21st century", however, there has been the lack of rigorous studies of what a data scientist is, and what job skill requirements this hottest job title may need. In order to address this gap, we systematically examine relevant source material to extract definitions and categorize them with a classification scheme developed …
Roles Of Social Media In Open Data Environments: A Case Study Of The 2014 Indonesian Presidential Election Voting Results, Uuf Brajawidagda, Akemi T. Chatfield
Roles Of Social Media In Open Data Environments: A Case Study Of The 2014 Indonesian Presidential Election Voting Results, Uuf Brajawidagda, Akemi T. Chatfield
Faculty of Engineering and Information Sciences - Papers: Part A
Open data initiatives are critical to open government policies which promote transparency, citizen engagement and collaboration. However, they face challenges in realizing their potential benefits through citizens' active engagement. Despite the sharp rise of social media use by governments or quasi-governmental organizations to engage citizens in transforming public service quality and offers, very little has been written on enabling roles of social media in influencing the outcome of open data initiatives. This research examines the potential enabling roles of social media in motivating and having citizens' engagement easier in open data environments. Specifically, we present social media use in supporting …
Multi-Objective Ant Colony System For Data-Intensive Service Provision, Lijuan Wang, Jun Shen, Junzhou Luo
Multi-Objective Ant Colony System For Data-Intensive Service Provision, Lijuan Wang, Jun Shen, Junzhou Luo
Faculty of Engineering and Information Sciences - Papers: Part A
Data-intensive services have become one of the most challenging applications in cloud computing. The classical service composition problem will face new challenges as the services and correspondent data grow. A typical environment is the large scale scientific project AMS, which we are processing huge amount of data streams. In this paper, we will resolve service composition problem by considering the multi-objective data-intensive features. We propose to apply ant colony optimization algorithms and implemented them with simulated workflows in different scenarios. To evaluate the proposed algorithm, we compared it with a multi-objective genetic algorithm with respect to five performance metrics
A Structure Optimization Algorithm Of Neural Networks For Large-Scale Data Sets, Jie Yang, Jun Ma, Matthew J. Berryman, Pascal Perez
A Structure Optimization Algorithm Of Neural Networks For Large-Scale Data Sets, Jie Yang, Jun Ma, Matthew J. Berryman, Pascal Perez
Faculty of Engineering and Information Sciences - Papers: Part A
Over the past several decades, neural networks have evolved into powerful computation systems, which are able to learn complex nonlinear input-output relationship from data. However, the structure optimization problem of neural network is a big challenge for processing huge-volumed, diversified and uncertain data. This paper focuses on this problem and introduces a network pruning algorithm based on sparse representation, termed SRP. The proposed approach starts with a large network, then selects important hidden neurons from the original structure using a forward selection criterion that minimizes the residual output error. Furthermore, the presented algorithm has no constraints on the network type. …
Multi-Phase Ant Colony System For Multi-Party Data-Intensive Service Provision, Lijuan Wang, Jun Shen
Multi-Phase Ant Colony System For Multi-Party Data-Intensive Service Provision, Lijuan Wang, Jun Shen
Faculty of Engineering and Information Sciences - Papers: Part A
The rapid proliferation of enormous sources of digital data has led to greater dependence on data-intensive services. Each service may actually request or create a large amount of data sets. To compose these services will be more challenging. Issues such as autonomy, scalability, adaptability, and robustness, become difficult to resolve. In order to automate the process of reaching an agreement among service composers, service providers, and data providers, an ant-inspired negotiation mechanism is considered in this paper. We exploit a group of agents automatically negotiating to establish agreeable service contracts. Twostage negotiation procedures are used in our data-intensive service provision …
An Improved Genetic Algorithm For Cost-Effective Data-Intensive Service Composition, Lijuan Wang, Jun Shen, Junzhou Luo, Fang Dong
An Improved Genetic Algorithm For Cost-Effective Data-Intensive Service Composition, Lijuan Wang, Jun Shen, Junzhou Luo, Fang Dong
Faculty of Engineering and Information Sciences - Papers: Part A
The explosion of digital data and the dependence on data-intensive services have been recognized as the most significant characteristics of IT trends in the current decade. Designing workflow of data-intensive services requires data analysis from multiple sources to get required composite services. Composing such services requires effective transfer of large data. Thus many new challenges are posed to control the cost and revenue of the whole composition. This paper addresses the data-intensive service composition and presents an innovative data-intensive service selection algorithm based on a modified genetic algorithm. The performance of this new algorithm is also tested by simulations and …
Linear Regression With Nested Errors Using Probability-Linked Data, Klairung Samart, Raymond Chambers
Linear Regression With Nested Errors Using Probability-Linked Data, Klairung Samart, Raymond Chambers
Faculty of Engineering and Information Sciences - Papers: Part A
Probabilistic matching of records is widely used to create linked data sets for use in health science, epidemiological, economic, demographic and sociological research. Clearly, this type of matching can lead to linkage errors, which in turn can lead to bias and increased variability when standard statistical estimation techniques are used with the linked data. In this paper we develop unbiased regression parameter estimates to be used when fitting a linear model with nested errors to probabilistically linked data. Since estimation of variance components is typically an important objective when fitting such a model, we also develop appropriate modifications to standard …
Ant-Inspired Multi-Phase And Multi-Party Negotiations In The Data-Intensive Service Provision, Lijuan Wang, Jun Shen, Qingguo Zhou, Ghassan Beydoun
Ant-Inspired Multi-Phase And Multi-Party Negotiations In The Data-Intensive Service Provision, Lijuan Wang, Jun Shen, Qingguo Zhou, Ghassan Beydoun
Faculty of Engineering and Information Sciences - Papers: Part A
The rapid proliferation of enormous sources of digital data and the development of cloud computing have led to greater dependence on data-intensive services. Each service may actually request or create a large amount of data sets. To compose these services will be more challenging. Issues of autonomy, scalability, adaptability, and robustness, become difficult to resolve. In order to automate the process of reaching an agreement in data-intensive service provision, the ant-inspired negotiation mechanism is considered in this paper. There are twostage negotiation procedures in our model, which will provide effective and efficient service selection for service composers. We also present …
An Adaptively Cca-Secure Ciphertext-Policy Attribute-Based Proxy Re-Encryption For Cloud Data Sharing, Kaitai Liang, Man Ho Au, Willy Susilo, Duncan Wong, Guomin Yang, Yong Yu
An Adaptively Cca-Secure Ciphertext-Policy Attribute-Based Proxy Re-Encryption For Cloud Data Sharing, Kaitai Liang, Man Ho Au, Willy Susilo, Duncan Wong, Guomin Yang, Yong Yu
Faculty of Engineering and Information Sciences - Papers: Part A
A Ciphertext-Policy Attribute-Based Proxy Re-Encryption (CP-ABPRE) employs the PRE technology in the attribute-based en- cryption cryptographic setting, in which the proxy is allowed to convert an encryption under an access policy to another encryption under a new access policy. CP-ABPRE is applicable to many real world applications, such as network data sharing. The existing CP-ABPRE systems, how- ever, leave how to achieve adaptive CCA security as an interesting open problem. This paper, for the rst time, proposes a new CP-ABPRE to tackle the problem by integrating the dual system encryption technology with selective proof technique. The new scheme supports any …
A Comparative Analysis Of Multichannel Data Acquisition Systems For Quality Assurance In External Beam Radiation Therapy, Iolanda Fuduli, Claudiu Porumb, Anthony Espinoza, Abdullah Aldosari, Martin Carolan, Michael Lf Lerch, Peter E. Metcalfe, Anatoly Rosenfeld, Marco Petasecca
A Comparative Analysis Of Multichannel Data Acquisition Systems For Quality Assurance In External Beam Radiation Therapy, Iolanda Fuduli, Claudiu Porumb, Anthony Espinoza, Abdullah Aldosari, Martin Carolan, Michael Lf Lerch, Peter E. Metcalfe, Anatoly Rosenfeld, Marco Petasecca
Faculty of Engineering and Information Sciences - Papers: Part A
The paper presents a comparative study performed by the Centre of Medical Radiation Physics (CMRP) on three multichannel Data Acquisition Systems (DAQ) based on different analogue front-ends to suit a wide range of radiotherapy applications. The three front-ends are: a charge-to-frequency converter developed by INFN Torino, an electrometer and a charge-to-digital converter (both commercial devices from Texas Instruments). For the first two (named DAQ A and B), the CMRP has designed the read-out systems whilst the third one (DAQ C) comes with its own evaluation board. For the purpose of the characterization DAQ A and DAQ B have been equipped …
Enhanced Privacy Of A Remote Data Integrity-Checking Protocol For Secure Cloud Storage, Yong Yu, Man Ho Au, Yi Mu, S Tang, J Ren, Willy Susilo, Liju Dong
Enhanced Privacy Of A Remote Data Integrity-Checking Protocol For Secure Cloud Storage, Yong Yu, Man Ho Au, Yi Mu, S Tang, J Ren, Willy Susilo, Liju Dong
Faculty of Engineering and Information Sciences - Papers: Part A
Remote data integrity checking (RDIC) enables a server to prove to an auditor the integrity of a stored file. It is a useful technology for remote storage such as cloud storage. The auditor could be a party other than the data owner; hence, an RDIC proof is based usually on publicly available information. To capture the need of data privacy against an untrusted auditor, Hao et al. formally defined "privacy against third party verifiers" as one of the security requirements and proposed a protocol satisfying this definition. However, we observe that all existing protocols with public verifiability supporting data update, …
Attribute-Based Data Transfer With Filtering Scheme In Cloud Computing, Jinguang Han, Willy Susilo, Yi Mu, Jun Yan
Attribute-Based Data Transfer With Filtering Scheme In Cloud Computing, Jinguang Han, Willy Susilo, Yi Mu, Jun Yan
Faculty of Engineering and Information Sciences - Papers: Part A
Data transfer is a transmission of data over a point-to-point or point-to-multipoint communication channel. To protect the confidentiality of the transferred data, public-key cryptography has been introduced in data transfer schemes (DTSs). Data transfer is a transmission of data over a point-to-point or point-to-multipoint communication channel. To protect the confidentiality of the transferred data, public-key cryptography has been introduced in data transfer schemes (DTSs). Unfortunately, there exist some drawbacks in the current DTSs. First, the sender must know who the real receivers are. This is undesirable in a system where the number of the users is very large, such as …
A Review Of Data Quality Assessment Methods For Public Health Information Systems, Hong Chen, David Hailey, Ning Wang, Ping Yu
A Review Of Data Quality Assessment Methods For Public Health Information Systems, Hong Chen, David Hailey, Ning Wang, Ping Yu
Faculty of Engineering and Information Sciences - Papers: Part A
High quality data and effective data quality assessment are required for accurately evaluating the impact of public health interventions and measuring public health outcomes. Data, data use, and data collection process, as the three dimensions of data quality, all need to be assessed for overall data quality assessment. We reviewed current data quality assessment methods. The relevant study was identified in major databases and well-known institutional websites. We found the dimension of data was most frequently assessed. Completeness, accuracy, and timeliness were the three most-used attributes among a total of 49 attributes of data quality. The major quantitative assessment methods …
Impacts Of Pheromone Modification Strategies In Ant Colony For Data-Intensive Service Provision, Lijuan Wang, Jun Shen, Junzhou Luo
Impacts Of Pheromone Modification Strategies In Ant Colony For Data-Intensive Service Provision, Lijuan Wang, Jun Shen, Junzhou Luo
Faculty of Engineering and Information Sciences - Papers: Part A
In the provision of dynamic data-intensive services, the cost and response time of data sets as well as the states of services may change over time. An ant colony system for this problem is studied in this paper. Specifically, we consider changing the QoS attributes of services and replacing a certain number of services with new ones at different frequencies. In order to adapt the ant colony system to handle the dynamic scenarios, several pheromone modification strategies in reaction to changes of the optimization scenarios are investigated. The aim of the strategies is to find a balance between preserving enough …
New Insight To Preserve Online Survey Accuracy And Privacy In Big Data Era, Joseph K. Liu, Man Ho Au, Xinyi Huang, Willy Susilo, Jianying Zhou, Yong Yu
New Insight To Preserve Online Survey Accuracy And Privacy In Big Data Era, Joseph K. Liu, Man Ho Au, Xinyi Huang, Willy Susilo, Jianying Zhou, Yong Yu
Faculty of Engineering and Information Sciences - Papers: Part A
An online survey system provides a convenient way for people to conduct surveys. It removes the necessity of human resources to hold paper surveys or telephone interviews and hence reduces the cost significantly. Nevertheless, accuracy and privacy remain as the major obstacles that need additional attention. To conduct an accurate survey, privacy maybe lost, and vice versa. In this paper, we provide new insight to preserve these two seeming contradictory issues in online survey systems especially suitable in big data era. We propose a secure system, which is shown to be efficient and practical by simulation data. Our analysis further …
Learning Diagnostic Diagrams In Transport-Based Data-Collection Systems, Vu Tran, Peter W. Eklund, Christopher David Cook
Learning Diagnostic Diagrams In Transport-Based Data-Collection Systems, Vu Tran, Peter W. Eklund, Christopher David Cook
Faculty of Engineering and Information Sciences - Papers: Part A
Insights about service improvement in a transit network can be gained by studying transit service reliability. In this paper, a general procedure for constructing a transit service reliability diagnostic (Tsrd) diagram based on a Bayesian network is proposed to automatically build a behavioural model from Automatic Vehicle Location (AVL) and Automatic Passenger Counters (APC) data. Our purpose is to discover the variability of transit service attributes and their effects on traveller behaviour. A Tsrd diagram describes and helps to analyse factors affecting public transport by combining domain knowledge with statistical data.
Data Driven Encoding Of Structures And Link Predictions In Large Xml Document Collections, M Hagenbuchner, A C. Tsoi, M Kc, Shujia Zhang
Data Driven Encoding Of Structures And Link Predictions In Large Xml Document Collections, M Hagenbuchner, A C. Tsoi, M Kc, Shujia Zhang
Ah Chung Tsoi
In recent years there have been some significant research towards the ability of processing related data, particularly the relatedness among atomic elements in a structure with those in another structure. A number of approaches have been developed with various degrees of success. This chapter provides an overview of machine learning approaches for the encoding of related atomic elements in one structure with those in other structures. The chapter briefly reviews a number of unsupervised approaches for such data structures which can be used for solving generic classification, regression, and clustering problems. We will apply this approach to a particularly interesting …
Very High Data Rate Mb-Ofdm Uwb Systems With Transmit Diversity Techniques, Ngoc Phuc Le, Le Chung Tran, Farzad Safaei
Very High Data Rate Mb-Ofdm Uwb Systems With Transmit Diversity Techniques, Ngoc Phuc Le, Le Chung Tran, Farzad Safaei
Professor Farzad Safaei
In this paper, the application of space time block codes in a very high data rate multiband-OFDM ultra-wideband (VHDR MB-OFDM UWB) system, where the Modified Dual Carrier Modulation (MDCM) scheme and Low Density Parity Check codes are deployed, is investigated. First, we present a new table-based mapping approach and derive soft-demapping expressions for the MDCM scheme. We then propose a space-time-frequency coded VHDR MB-OFDM UWB system by incorporating space time block codes into the conventional VHDR MB-OFDM UWB system. Numerical simulations of the system supporting a data rate of 1Gbps over the IEEE 802.15.3a channel models are implemented. The simulation …
Double Space-Time Transmit Diversity For Very High Data Rate Mb-Ofdm Uwb Systems, Ngoc P. Le, Le C. Tran, Farzad Safaei
Double Space-Time Transmit Diversity For Very High Data Rate Mb-Ofdm Uwb Systems, Ngoc P. Le, Le C. Tran, Farzad Safaei
Professor Farzad Safaei
In this paper, we investigate a multiband-orthogonal frequency division multiplexing ultra-wideband (MB-OFDM UWB) system with very high data rates (VHDR) of several gigabits per second (Gbps). We propose a DSTTD-based VHDR MB-OFDM UWB system by incorporating a double space-time transmit diversity (DSTTD) scheme into the conventional MB-OFDM UWB system. At the receiver, an efficient soft-demapper that takes into consideration the noise enhancement due to a zero-forcing equalization is developed. Numerical simulations of the proposed system at a very high data rate of 2.Gbps over the IEEE 802.15.3a channel models are implemented. The simulation results show that this system could achieve …