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Articles 1 - 8 of 8
Full-Text Articles in Social and Behavioral Sciences
Automatic Ventricular Nuclear Magnetic Resonance Image Processing With Deep Learning, Binbin Yong, Chen Wang, Jun Shen, Fucun Li, Hang Yin
Automatic Ventricular Nuclear Magnetic Resonance Image Processing With Deep Learning, Binbin Yong, Chen Wang, Jun Shen, Fucun Li, Hang Yin
Faculty of Engineering and Information Sciences - Papers: Part A
Cardiovascular diseases (CVD) seriously threaten the health of human beings, and they have caused widespread concern in recent years. At present, the diagnosis of CVD is mainly conducted by computed tomography (CT), echocardiography and nuclear magnetic resonance (NMR) technologies. NMR imaging technology is widely used in medical applications owing to its characteristics of high resolution and very low radiation. However, manual NMR image segmentation is time-consuming and error-prone, which has led to the research on automatic NMR image segmentation technologies. Researchers tend to explore the ventricular NRM image segmentation to improve the accuracy of CVD diagnosis. In this study, based …
Energy Efficiency Analysis Of Antenna Selection Multi-Input Multi-Output Automatic Repeat Request Systems Over Nakagami-M Fading Channels, Ngoc Phuc Le, Le Chung Tran, Farzad Safaei, Vineeth Satheeskum Varma
Energy Efficiency Analysis Of Antenna Selection Multi-Input Multi-Output Automatic Repeat Request Systems Over Nakagami-M Fading Channels, Ngoc Phuc Le, Le Chung Tran, Farzad Safaei, Vineeth Satheeskum Varma
Faculty of Engineering and Information Sciences - Papers: Part A
In this study, the authors investigate energy efficiency in antenna selection multi-input multi-output automatic repeat request (MIMO ARQ) wireless systems. The authors first derive an approximate expression for the average frame-error rate (FER) in antenna selection MIMO systems over quasi-static Nakagami-m fading channels. The FER approximation is then used to obtain an analytical expression of an energy-efficiency metric that is defined as the total energy required to successfully deliver one information bit. The authors prove that this energy-efficiency metric is a quasi-convex function with respect to the average signal-to-noise ratio value. Based on this analysis, the authors obtain the optimal …
Speech Analysis For Alphabets In Bangla Language: Automatic Speech Recognition, Asm Sayem
Speech Analysis For Alphabets In Bangla Language: Automatic Speech Recognition, Asm Sayem
Faculty of Engineering and Information Sciences - Papers: Part A
This paper presents a technique for recognizing spoken letter in Bengali Language. We first derive feature from spoken letter. Mel-frequency cepstral coefficient (MFCC) has been used to characterize a feature. Dynamic time warping (DTW) employed to calculate the distance of an unknown letter with the stored ones. K-nearest neighbors (KNN) algorithm is used to improve accuracy in noisy environment.
Providing Metrics And Automatic Enhancement For Hierarchical Taxonomies, Ghassan Beydoun, Francisco Garcia-Sanchez, Cristin M. Vincent-Torres, Antonio A. Lopez-Lorca, Rodrigo Martinez-Bejar
Providing Metrics And Automatic Enhancement For Hierarchical Taxonomies, Ghassan Beydoun, Francisco Garcia-Sanchez, Cristin M. Vincent-Torres, Antonio A. Lopez-Lorca, Rodrigo Martinez-Bejar
Faculty of Engineering and Information Sciences - Papers: Part A
Taxonomies enable organising information in a human-machine understandable form, but constructing them for reuse and maintainability remains difficult. The paper presents a formal underpinning to provide quality metrics for a taxonomy under development. It proposes a methodology for semi-automatic building of maintainable taxonomies and outlines key features of the knowledge engineering context where the metrics and methodology are most suitable. The strength of the approach presented is that it is applied during the actual construction of the taxonomy. Users provide terms to describe different domain elements, as well as their attributes, and methodology uses metrics to assess the quality of …
Tuning Performance Of E-Business Applications Through Automatic Transformation Of Persistent Database Structures, Janusz R. Getta
Tuning Performance Of E-Business Applications Through Automatic Transformation Of Persistent Database Structures, Janusz R. Getta
Faculty of Engineering and Information Sciences - Papers: Part A
Performance of e-business applications strongly depends on internal implementations of persistent database structures and on effective algorithms processing these structures. Commercial database systems, which are the basis of e-business applications typically implement logical database structures with one-size-fits-all persistent storage structure. This work investigates a new class of database systems where a conceptual and logical view of a database can be implemented in many different ways depending on the performance requirements of database applications. We consider the improvements to performance of e-business applications through automatic changes of the persistent database structures in the ways indicated by the performance statistics obtained from …
Automatic Bdi Plan Recognition From Process Execution Logs And Effect Logs, Hongyun Xu, Bastin Tony Roy Savarimuthu, Aditya Ghose, Evan Morrison, Qiying Cao, Youqun Shi
Automatic Bdi Plan Recognition From Process Execution Logs And Effect Logs, Hongyun Xu, Bastin Tony Roy Savarimuthu, Aditya Ghose, Evan Morrison, Qiying Cao, Youqun Shi
Faculty of Engineering and Information Sciences - Papers: Part A
Agent applications are often viewed as unduly expensive to develop and maintain in commercial contexts. Organizations often settle for less sophisticated and more traditional software in place of agent technology because of (often misplaced) fears about the development and maintenance costs of agent technology, and the often mistaken perception that traditional software offers better returns on investment. This paper aims to redress this by developing a plan recognition framework for agent program learning, where behavior logs of legacy applications (or even manually executed processes) are mined to extract a 'draft' version of agent code that could eventually replace these applications …
Stereoscopic Visualization And Editing Of Automatic Abdominal Aortic Aneurysms (Aaa) Measurements For Stent Graft Planning, Luping Zhou, Yaping Wang, Lin-Chia Goh, Ralf A. Kockro, Luis Serra
Stereoscopic Visualization And Editing Of Automatic Abdominal Aortic Aneurysms (Aaa) Measurements For Stent Graft Planning, Luping Zhou, Yaping Wang, Lin-Chia Goh, Ralf A. Kockro, Luis Serra
Faculty of Engineering and Information Sciences - Papers: Part A
For stent graft selection in the treatment of abdominal aortic aneurysms (AAA) anatomic considerations are important. They determine GO/NO-GO of the treatment and help customize the stent. Current systems for AAA stent insertion planning based on pre-operative CT and MR of the patient do not provide an intuitive interface to view the resulting measurements against the pre-operative CT/MR. Subsequent modifications of the measurements are frequent when automatic algorithms are inaccurate. However, 3D editing is difficult to achieve because of the limitations of monoscopic displays and 2D interface. In this paper, we present a system for automatic AAA measurement and interactive …
An Image Database Semantically Structured Based On Automatic Image Annotation For Content-Based Image Retrieval, Xuejian Xiong, Kap Luk Chan, Lei Wang
An Image Database Semantically Structured Based On Automatic Image Annotation For Content-Based Image Retrieval, Xuejian Xiong, Kap Luk Chan, Lei Wang
Faculty of Engineering and Information Sciences - Papers: Part A
In this paper, we presented a semantically structured image database for content-based image retrieval. A class descriptor is proposed to represent each class using a multiprototype model, which can be obtained by using a learning scheme, such as the Unsupervised Optimal Fuzzy Clustering algorithm, on a group of sample images manually selected from the class. Based on the proposed Image-Class Matching Distance, a similarity measure at the semantic level between an image and classes, images can be annotated by tokens of classes. Hence, composite features of images, including low-level descriptors, class descriptors, and image annotation, are stored into a structured …