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- Faculty of Engineering and Information Sciences - Papers: Part A (8)
- Australian Institute for Innovative Materials - Papers (2)
- Faculty of Engineering and Information Sciences - Papers: Part B (2)
- Research Collection School Of Computing and Information Systems (2)
- Dr. Dolittle Project: A Framework for Classification and Understanding of Animal Vocalizations (1)
Articles 1 - 17 of 17
Full-Text Articles in Engineering
Thermal Features Vis A Vis Strain Features Of Fracturing Process In Jointed Rock Layer Under Concentrated Load, Haiqing Yang, Bolong Liu, Shivakumar Karekal
Thermal Features Vis A Vis Strain Features Of Fracturing Process In Jointed Rock Layer Under Concentrated Load, Haiqing Yang, Bolong Liu, Shivakumar Karekal
Faculty of Engineering and Information Sciences - Papers: Part B
In case of earthquakes and crustal movement, the concentration of impounding load over a large region of crust can cause disturbances to the stratum. In order to quantitatively investigate crack initiation, propagation and coalescence processes of jointed stratum based on thermal variations caused by concentrated mechanical loading, a series of indention tests were performed on granite specimens. In the experiment, fracture process and resulting infrared radiation fields of specimens were respectively recorded by synchronized digital image correlation system and infrared camera. Then, thermal characteristics of mixed shear-tensile and tensile conical crack were analyzed. Experimental results indicate that the highlighted temperature …
Comparative Evaluation Of The Structural And Other Features Governing Photo-Electrochemical Oxygen Evolution By Ca/Mn Oxides, Ankita Gagrani, Mohammed Alsultan, Gerhard F. Swiegers, Takuya Tsuzuki
Comparative Evaluation Of The Structural And Other Features Governing Photo-Electrochemical Oxygen Evolution By Ca/Mn Oxides, Ankita Gagrani, Mohammed Alsultan, Gerhard F. Swiegers, Takuya Tsuzuki
Australian Institute for Innovative Materials - Papers
Mn-Based oxides, particularly CaMn oxides, have recently attracted significant practical interest as a new class of catalyst due to their elemental and structural similarity to the natural oxygen evolving cluster (OEC) in photosynthetic plant cells. However, their performance as oxygen-generating anodes in photoelectrochemical cells has not been studied in detail. In this work, ultra-fine particles of amorphous MnO2, crystalline MnO2 nanorods, Ca2Mn3O8, CaMn2O4 and CaMnO3 were synthesised using a green and scalable mechanochemical method. The particles were comparatively studied as water oxidation photocatalysts in a photo-electrochemical cell at near-neutral pH. The oxides were immobilized on the anode surface using an …
Early Prediction Of Merged Code Changes To Prioritize Reviewing Tasks, Yuanrui Fan, Xin Xia, David Lo, Shanping Li
Early Prediction Of Merged Code Changes To Prioritize Reviewing Tasks, Yuanrui Fan, Xin Xia, David Lo, Shanping Li
Research Collection School Of Computing and Information Systems
Modern Code Review (MCR) has been widely used by open source and proprietary software projects. Inspecting code changes consumes reviewers much time and effort since they need to comprehend patches, and many reviewers are often assigned to review many code changes. Note that a code change might be eventually abandoned, which causes waste of time and effort. Thus, a tool that predicts early on whether a code change will be merged can help developers prioritize changes to inspect, accomplish more things given tight schedule, and not waste reviewing effort on low quality changes. In this paper, motivated by the above …
Androparse - An Android Feature Extraction Framework & Dataset, Robert Schmicker, Frank Breitinger, Ibrahim Baggili
Androparse - An Android Feature Extraction Framework & Dataset, Robert Schmicker, Frank Breitinger, Ibrahim Baggili
Electrical & Computer Engineering and Computer Science Faculty Publications
Android malware has become a major challenge. As a consequence, practitioners and researchers spend a significant time analyzing Android applications (APK). A common procedure (especially for data scientists) is to extract features such as permissions, APIs or strings which can then be analyzed. Current state of the art tools have three major issues: (1) a single tool cannot extract all the significant features used by scientists and practitioners (2) Current tools are not designed to be extensible and (3) Existing parsers do not have runtime efficiency. Therefore, this work presents AndroParse which is an open-source Android parser written in Golang …
Persuasive Systems Design Features In Promoting Medication Management For Consumers, Khin Than Win, Judy Mullan, Sarah Katherine Howard, Harri Oinas-Kukkonen
Persuasive Systems Design Features In Promoting Medication Management For Consumers, Khin Than Win, Judy Mullan, Sarah Katherine Howard, Harri Oinas-Kukkonen
Faculty of Engineering and Information Sciences - Papers: Part B
Medication safety continues to be a growing concern in the healthcare industry. Providing medication information to consumers and supporting self- management would help to reduce medication errors and to increase medication adherence. This paper reviews the persuasive systems design features used in current medication management applications for consumers. A database search was conducted to identify relevant articles, which were then reviewed using the Persuasive Systems Design model as a framework for analysis. The results highlighted the applicability of these features for the medication management information systems available to consumers. Primary task support and Dialogue support categories were highly cited in …
From Footprint To Evidence: An Exploratory Study Of Mining Social Data For Credit Scoring, Guangming Guo, Feida Zhu, Enhong Chen, Qi Liu, Le Wu, Chu Guan
From Footprint To Evidence: An Exploratory Study Of Mining Social Data For Credit Scoring, Guangming Guo, Feida Zhu, Enhong Chen, Qi Liu, Le Wu, Chu Guan
Research Collection School Of Computing and Information Systems
With the booming popularity of online social networks like Twitter and Weibo, online user footprints are accumulating rapidly on the social web. Simultaneously, the question of how to leverage the large-scale user-generated social media data for personal credit scoring comes into the sight of both researchers and practitioners. It has also become a topic of great importance and growing interest in the P2P lending industry. However, compared with traditional financial data, heterogeneous social data presents both opportunities and challenges for personal credit scoring. In this article, we seek a deep understanding of how to learn users’ credit labels from social …
Features Of A Self-Mixing Laser Diode Operating Near Relaxation Oscillation, Bin Liu, Yanguang Yu, Jiangtao Xi, Yuanlong Fan, Qinghua Guo, Jun Tong, R A. Lewis
Features Of A Self-Mixing Laser Diode Operating Near Relaxation Oscillation, Bin Liu, Yanguang Yu, Jiangtao Xi, Yuanlong Fan, Qinghua Guo, Jun Tong, R A. Lewis
Faculty of Engineering and Information Sciences - Papers: Part A
When a fraction of the light reflected by an external cavity re-enters the laser cavity, both the amplitude and the frequency of the lasing field can be modulated. This phenomenon is called the self-mixing effect (SME). A self-mixing laser diode (SM-LD) is a sensor using the SME. Usually, such LDs operate below the stability boundary where no relaxation oscillation happens. The boundary is determined by the operation condition including the injection current, optical feedback strength and external cavity length. This paper discovers the features of an SM-LD where the LD operates beyond the stability boundary, that is, near the relaxation …
3d Face Recognition Using Anthropometric And Curvelet Features Fusion, Dan Song, Jing Luo, Chunyuan Zi, Huixin Tian
3d Face Recognition Using Anthropometric And Curvelet Features Fusion, Dan Song, Jing Luo, Chunyuan Zi, Huixin Tian
Faculty of Engineering and Information Sciences - Papers: Part A
Curvelet transform can describe the signal by multiple scales, and multiple directions. In order to improve the performance of 3D face recognition algorithm, we proposed an Anthropometric and Curvelet features fusion-based algorithm for 3D face recognition (Anthropometric Curvelet Fusion Face Recognition, ACFFR). First, the eyes, nose, and mouth feature regions are extracted by the Anthropometric characteristics and curvature features of the human face. Second, Curvelet energy features of the facial feature regions at different scales and different directions are extracted by Curvelet transform. At last, Euclidean distance is used as the similarity between template and objectives. To verify the performance, …
Machine Vision Identification Of Airport Runways With Visible And Infrared Videos, Andrew J. Moore, Matthew Schubert, Chester Dolph, Glenn Woodell
Machine Vision Identification Of Airport Runways With Visible And Infrared Videos, Andrew J. Moore, Matthew Schubert, Chester Dolph, Glenn Woodell
Electrical & Computer Engineering Faculty Publications
A widely used machine vision pipeline based on the Speeded-Up Robust Features feature detector was applied to the problem of identifying a runway from a universe of known runways, which was constructed using video records of 19 straight-in glidepath approaches to nine runways. The recordings studied included visible, short-wave infrared, and long-wave infrared videos in clear conditions, rain, and fog. Both daytime and nighttime runway approaches were used. High detection specificity (identification of the runway approached and rejection of the other runways in the universe) was observed in all conditions (greater than 90% Bayesian posterior probability). In the visible band, …
An Application Of Mathematical Morphology Operators As Features Extraction Method For Low Speed Slew Bearing Condition Monitoring, Wahyu Caesarendra, Dwi B. Wibowo, Mochammad Ariyanto, Joga D. Setiawan
An Application Of Mathematical Morphology Operators As Features Extraction Method For Low Speed Slew Bearing Condition Monitoring, Wahyu Caesarendra, Dwi B. Wibowo, Mochammad Ariyanto, Joga D. Setiawan
Faculty of Engineering and Information Sciences - Papers: Part A
This paper presents a new application of mathematical morphology (MM) operators for low speed slew bearing condition monitoring. The MM operators were used as a signal processing step and feature extraction method for bearing vibration signals. Four basic MM operators; erosion, dilation, closing and opening, were studied. This paper also investigates another potential MM operator, namely gradient operator. Two common time domain features in bearing condition monitoring, namely root mean square (RMS) and kurtosis, were extracted from the processed signal. The study shows that the changes in bearing condition can be clearly detected from the extracted features (RMS and kurtosis) …
Effects Of Nanostructure On Clean Energy: Big Solutions Gained From Small Features, Jinyan Xiong, Chao Han, Zhen Li, S X. Dou
Effects Of Nanostructure On Clean Energy: Big Solutions Gained From Small Features, Jinyan Xiong, Chao Han, Zhen Li, S X. Dou
Australian Institute for Innovative Materials - Papers
The increasing energy consumption and environmental concerns have driven the development of cost-effective, high-efficiency clean energy. Advanced functional nanomaterials and relevant nanotechnologies are playing a crucial role and showing promise in resolving some energy issues. In this view, we focus on recent advances of functional nanomaterials in clean energy applications, including solar energy conversion, water splitting, photodegradation, electrochemical energy conversion and storage, and thermoelectric conversion, which have attracted considerable interests in the regime of clean energy.
Mining Mid-Level Features For Action Recognition Based On Effective Skeleton Representation, Pichao Wang, Wanqing Li, Philip O. Ogunbona, Zhimin Gao, Hanling Zhang
Mining Mid-Level Features For Action Recognition Based On Effective Skeleton Representation, Pichao Wang, Wanqing Li, Philip O. Ogunbona, Zhimin Gao, Hanling Zhang
Faculty of Engineering and Information Sciences - Papers: Part A
Recently, mid-level features have shown promising performance in computer vision. Mid-level features learned by incorporating class-level information are potentially more discriminative than traditional low-level local features. In this paper, an effective method is proposed to extract mid-level features from Kinect skeletons for 3D human action recognition. Firstly, the orientations of limbs connected by two skeleton joints are computed and each orientation is encoded into one of the 27 states indicating the spatial relationship of the joints. Secondly, limbs are combined into parts and the limb's states are mapped into part states. Finally, frequent pattern mining is employed to mine the …
Encoding High Dimensional Local Features By Sparse Coding Based Fisher Vectors, Lingqiao Liu, Chunhua Shen, Lei Wang, Anton Van Den Hengel, Chao Wang
Encoding High Dimensional Local Features By Sparse Coding Based Fisher Vectors, Lingqiao Liu, Chunhua Shen, Lei Wang, Anton Van Den Hengel, Chao Wang
Faculty of Engineering and Information Sciences - Papers: Part A
Deriving from the gradient vector of a generative model of local features, Fisher vector coding (FVC) has been identified as an effective coding method for image classification. Most, if not all, FVC implementations employ the Gaussian mixture model (GMM) to characterize the generation process of local features. This choice has shown to be sufficient for traditional low dimensional local features, e.g., SIFT; and typically, good performance can be achieved with only a few hundred Gaussian distributions. However, the same number of Gaussians is insufficient to model the feature space spanned by higher dimensional local features, which have become popular recently. …
Circular Domain Features Based Condition Monitoring For Low Speed Slewing Bearing, Wahyu Caesarendra, Prabuono Buyung Kosasih, A Kiet Tieu, Craig A. S Moodie
Circular Domain Features Based Condition Monitoring For Low Speed Slewing Bearing, Wahyu Caesarendra, Prabuono Buyung Kosasih, A Kiet Tieu, Craig A. S Moodie
Faculty of Engineering and Information Sciences - Papers: Part A
This paper presents a novel application of circular domain features calculation based condition monitoring method for low rotational speed slewing bearing. The method employs data reduction process using piecewise aggregate approximation (PAA) to detect frequency alteration in the bearing signal when the fault occurs. From the processed data, circular domain features such as circular mean, circular variance, circular skewness and circular kurtosis are calculated and monitored. It is shown that the slight changes of bearing condition during operation can be identified more clearly in circular domain analysis compared to time domain analysis and other advanced signal processing methods such as …
Helpfulness Of Online Product Reviews As Seen By Consumers: Source And Content Features, Mengxiang Li, Liqiang Huang, Chuan-Hoo Tan, Kwok-Kee Wei
Helpfulness Of Online Product Reviews As Seen By Consumers: Source And Content Features, Mengxiang Li, Liqiang Huang, Chuan-Hoo Tan, Kwok-Kee Wei
Faculty of Engineering and Information Sciences - Papers: Part A
Online product reviews are important determinants of consumers' purchase decision. Although prior research has articulated various benefits of online product reviews, there are few investigations into whether or not they are perceived as helpful by consumers. Product review helpfulness is conceptualized as a second-order formative construct, which is manifested by perceived source credibility, perceived content diagnosticity, and perceived vicarious expression of the product review. In this study, we conduct a laboratory experiment to investigate product review helpfulness as well as its corresponding antecedents from the product review feature perspective (i.e., source- and content-based review features). Findings from the study are …
Novel Features Of Ars Selection In Budding Yeast Lachancea Kluyveri, Ivan Liachko, Emi Tanaka, Katherine A. Cox, Shau Chee C. Chung, Lu Yang, Arael Seher, Lindsay Hallas, Eugene Cha, Gina Kang, Heather Pace, Jasmine Barrow, Maki Inada, Bik Kwoon Tye, Uri Keich
Novel Features Of Ars Selection In Budding Yeast Lachancea Kluyveri, Ivan Liachko, Emi Tanaka, Katherine A. Cox, Shau Chee C. Chung, Lu Yang, Arael Seher, Lindsay Hallas, Eugene Cha, Gina Kang, Heather Pace, Jasmine Barrow, Maki Inada, Bik Kwoon Tye, Uri Keich
Faculty of Engineering and Information Sciences - Papers: Part A
Background: The characterization of DNA replication origins in yeast has shed much light on the mechanisms of initiation of DNA replication. However, very little is known about the evolution of origins or the evolution of mechanisms through which origins are recognized by the initiation machinery. This lack of understanding is largely due to the vast evolutionary distances between model organisms in which origins have been examined.Results: In this study we have isolated and characterized autonomously replicating sequences (ARSs) in Lachancea kluyveri - a pre-whole genome duplication (WGD) budding yeast. Through a combination of experimental work and rigorous computational analysis, we …
Application Of Speech Recognition To African Elephant (Loxodonta Africana) Vocalizations, Patrick J. Clemins, Michael T. Johnson
Application Of Speech Recognition To African Elephant (Loxodonta Africana) Vocalizations, Patrick J. Clemins, Michael T. Johnson
Dr. Dolittle Project: A Framework for Classification and Understanding of Animal Vocalizations
This paper presents a novel application of speech processing research, classification of African elephant vocalizations. Speaker identification and call classification experiments are performed on data collected from captive African elephants in a naturalistic environment. The features used for classification are 12 mel-frequency cepstral coefficients plus log energy computed using a shifted filter bank to emphasize the infrasound range of the frequency spectrum used by African elephants. Initial classification accuracies of 83.8% for call classification and 88.1% for speaker identification were obtained. The long-term goal of this research is to develop a universal analysis framework and robust feature set for animal …