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Full-Text Articles in Computer Engineering

Cloud-Edge Collaborative Service Architecture For Lvc Training System, Peng Yong, Miao Zhang, Yue Hu Sep 2023

Cloud-Edge Collaborative Service Architecture For Lvc Training System, Peng Yong, Miao Zhang, Yue Hu

Journal of System Simulation

Abstract: LVC training, an important means of military training, has received great attention from military and M&S experts. As the virtual and physical elements become more abundant and deeply integrated, LVC training systems become increasingly complex. Aiming at physical-virtual connection, information interaction, simulation computation, run-time control, etc., this paper designs a cloud-edge collaborative service architecture for LVC training systems (CESA-LVC) by reference to cyber-physical systems and cloud-edge computing architectures. CESA-LVC standardizes the structures of LVC training systems from several aspects of intelligent real-time interconnection, joint simulation computation, training auxiliary service, training cognitive decision, and dynamic configuration optimization. It provides a …


Learning Relation Prototype From Unlabeled Texts For Long-Tail Relation Extraction, Yixin Cao, Jun Kuang, Ming Gao, Aoying Zhou, Yonggang Wen, Tat-Seng Chua Feb 2023

Learning Relation Prototype From Unlabeled Texts For Long-Tail Relation Extraction, Yixin Cao, Jun Kuang, Ming Gao, Aoying Zhou, Yonggang Wen, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Relation Extraction (RE) is a vital step to complete Knowledge Graph (KG) by extracting entity relations from texts. However, it usually suffers from the long-tail issue. The training data mainly concentrates on a few types of relations, leading to the lack of sufficient annotations for the remaining types of relations. In this paper, we propose a general approach to learn relation prototypes from unlabeled texts, to facilitate the long-tail relation extraction by transferring knowledge from the relation types with sufficient training data. We learn relation prototypes as an implicit factor between entities, which reflects the meanings of relations as well …


Setransformer: A Transformer-Based Code Semantic Parser For Code Comment Generation, Zheng Li, Yonghao Wu, Bin Peng, Xiang Chen, Zeyu Sun, Yong Liu, Paul Doyle Jan 2023

Setransformer: A Transformer-Based Code Semantic Parser For Code Comment Generation, Zheng Li, Yonghao Wu, Bin Peng, Xiang Chen, Zeyu Sun, Yong Liu, Paul Doyle

Conference Papers

Automated code comment generation technologies can help developers understand code intent, which can significantly reduce the cost of software maintenance and revision. The latest studies in this field mainly depend on deep neural networks, such as convolutional neural networks and recurrent neural network. However, these methods may not generate high-quality and readable code comments due to the long-term dependence problem, which means that the code blocks used to summarize information are far from each other. Owing to the long-term dependence problem, these methods forget the previous input data’s feature information during the training process. In this article, to solve the …


Mitigating Popularity Bias In Recommendation With Unbalanced Interactions: A Gradient Perspective, Weijieying Ren, Lei Wang, Kunpeng Liu, Ruocheng Guo, Ee-Peng Lim, Yanjie Fu Dec 2022

Mitigating Popularity Bias In Recommendation With Unbalanced Interactions: A Gradient Perspective, Weijieying Ren, Lei Wang, Kunpeng Liu, Ruocheng Guo, Ee-Peng Lim, Yanjie Fu

Research Collection School Of Computing and Information Systems

Recommender systems learn from historical user-item interactions to identify preferred items for target users. These observed interactions are usually unbalanced following a long-tailed distribution. Such long-tailed data lead to popularity bias to recommend popular but not personalized items to users. We present a gradient perspective to understand two negative impacts of popularity bias in recommendation model optimization: (i) the gradient direction of popular item embeddings is closer to that of positive interactions, and (ii) the magnitude of positive gradient for popular items are much greater than that of unpopular items. To address these issues, we propose a simple yet efficient …


Feed Forward Neural Networks With Asymmetric Training, Archit Srivastava Aug 2022

Feed Forward Neural Networks With Asymmetric Training, Archit Srivastava

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Our work presents a new perspective on training feed-forward neural networks(FFNN). We introduce and formally define the notion of symmetry and asymmetry in the context of training of FFNN. We provide a mathematical definition to generalize the idea of sparsification and demonstrate how sparsification can induce asymmetric training in FFNN.

In FFNN, training consists of two phases, forward pass and backward pass. We define symmetric training in FFNN as follows-- If a neural network uses the same parameters for both forward pass and backward pass, then the training is said to be symmetric.

The definition of asymmetric training in artificial …


Ship Deck Segmentation In Engineering Document Using Generative Adversarial Networks, Mohammad Shahab Uddin, Raphael Pamie-George, Daron Wilkins, Andres Sousa Poza, Mustafa Canan, Samuel Kovacic, Jiang Li Jan 2021

Ship Deck Segmentation In Engineering Document Using Generative Adversarial Networks, Mohammad Shahab Uddin, Raphael Pamie-George, Daron Wilkins, Andres Sousa Poza, Mustafa Canan, Samuel Kovacic, Jiang Li

Engineering Management & Systems Engineering Faculty Publications

Generative adversarial networks (GANs) have become very popular in recent years. GANs have proved to be successful in different computer vision tasks including image-translation, image super-resolution etc. In this paper, we have used GAN models for ship deck segmentation. We have used 2D scanned raster images of ship decks provided by US Navy Military Sealift Command (MSC) to extract necessary information including ship walls, objects etc. Our segmentation results will be helpful to get vector and 3D image of a ship that can be later used for maintenance of the ship. We applied the trained models to engineering documents provided …


Freelabel: A Publicly Available Annotation Tool Based On Freehand Traces, Philipe A. Dias, Zhou Shen, Amy Tabb, Henry P. Medeiros Mar 2019

Freelabel: A Publicly Available Annotation Tool Based On Freehand Traces, Philipe A. Dias, Zhou Shen, Amy Tabb, Henry P. Medeiros

Electrical and Computer Engineering Faculty Research and Publications

Large-scale annotation of image segmentation datasets is often prohibitively expensive, as it usually requires a huge number of worker hours to obtain high-quality results. Abundant and reliable data has been, however, crucial for the advances on image understanding tasks recently achieved by deep learning models. In this paper, we introduce FreeLabel, an intuitive open-source web interface that allows users to obtain high-quality segmentation masks with just a few freehand scribbles, in a matter of seconds. The efficacy of FreeLabel is quantitatively demonstrated by experimental results on the PASCAL dataset as well as on a dataset from the agricultural domain. Designed …


Big Five Technologies In Aeronautical Engineering Education: Scoping Review, Ruth Martinez-Lopez Jan 2019

Big Five Technologies In Aeronautical Engineering Education: Scoping Review, Ruth Martinez-Lopez

International Journal of Aviation, Aeronautics, and Aerospace

The constant demands that technology creates in aerospace engineering also influence education. The identification of the technologies with practical application in aerospace engineering is of current interest to decision makers in both universities and industry. A social network approach enhances this scoping review of the research literature to identify the main topics using the Big Five technologies in aerospace engineering education. The conceptual structure of the dataset (n=447) was analyzed from different approaches: at macro-level, a comparative of the digital technology identified by cluster analysis with the number of co-words established in 3 and 8 and, a keyword central structure …


Survey Results On Adults And Cybersecurity Education, Frank Breitinger, Joseph Ricci, Ibrahim Baggili Jul 2018

Survey Results On Adults And Cybersecurity Education, Frank Breitinger, Joseph Ricci, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

Cyberattacks and identity theft are common problems nowadays where researchers often say that humans are the weakest link in the security chain. Therefore, this survey focused on analyzing the interest for adults for ‘cyber threat education seminars’, e.g., how to project themselves and their loved ones. Specifically, we asked questions to understand a possible audience, willingness for paying / time commitment, or fields of interest as well as background and previous training experience. The survey was conducted in late 2016 and taken by 233 participants. The results show that many are worried about cyber threats and about their children exploring …


A Usability Study For Electronic Flight Bag (Efb) Flight Planning Applications On Tablet Devices For Ab-Initio Pilots, Jeff Schwartzentruber Apr 2017

A Usability Study For Electronic Flight Bag (Efb) Flight Planning Applications On Tablet Devices For Ab-Initio Pilots, Jeff Schwartzentruber

International Journal of Aviation, Aeronautics, and Aerospace

The proliferation of mobile technology has prompted the use of tablet devices in the cockpit and during ground operations in general aviation. Due to the increase in affordable and reliable hardware (i.e. iPads etc.), the development of pilot-specific software has led to the creation of a commercial-of-the-shelf (COTS), electronic flight bag (EFB) market. EFBs have many advantages, such as reducing the space requirements for flight documents, enabling faster searching and indexing of files, providing useful tools for flight planning, and providing automatic updates. The increase in availability of mobile technology and flight applications has allowed general aviation enthusiast and ab-initio …


Development Of An Android Based Performance Assessment System For Motivational Interviewing Training, Sowmya Pappu Jan 2017

Development Of An Android Based Performance Assessment System For Motivational Interviewing Training, Sowmya Pappu

Browse all Theses and Dissertations

Motivational Interviewing (MI) has been proved to be an effective Screening, Brief Intervention, and Referral to Treatment (SBIRT) technique. It is an evidence-based practice used to identify, reduce, and prevent problematic use, abuse, and dependence on alcohol and illicit drugs. It emphasizes on patient-centered counseling approach that can help resolve their ambivalence through a non-confrontational, goal-oriented style for eliciting behavior change from the patient, almost like patients talk themselves into change. This approach provokes less resistance and stimulates the progress of patients at their own pace towards deciding about planning, making and sustaining positive behavioral change. Thus, training medical professionals …


Measuring The Effectiveness Of Software-Based Training To Improve The Spatial Visualization Skills Of Students In Stem Disciplines In Higher Education Institutions, Peter Cole Jan 2016

Measuring The Effectiveness Of Software-Based Training To Improve The Spatial Visualization Skills Of Students In Stem Disciplines In Higher Education Institutions, Peter Cole

Dissertations

This research investigates how software can be used to teach spatial skills leading to greater success in Science, Technology, Engineering, and Mathematical (STEM) fields. Existing research indicates that spatial skills can be taught and that good spatial skills are common to people who succeed in STEM fields. In this work, a software-only testing system with a direct targeted, training intervention module was implemented to measure and teach spatial skills using mental rotations, which are believed to be one of the most significant indicators of success in STEM fields. Spatial skills were tested using a standardized and validated test that measures …


Learning To Rank Algorithms And Their Application In Machine Translation, Tian Xia Jan 2015

Learning To Rank Algorithms And Their Application In Machine Translation, Tian Xia

Browse all Theses and Dissertations

In this thesis, we discuss two issues in the learning to rank area, choosing effective objective loss function, constructing effective regresstion trees in the gradient boosting framework, as well as a third issus, applying learning to rank models into statistcal machine translation. First, list-wise based learning to rank methods either directly optimize performance measures or optimize surrogate functions of performance measures that have smaller gaps between optimized losses and performance measures, thus it is generally believed that they should be able to lead to better performance than point-and pair-wise based learning to rank methods. However, in real-world applications, state-of-the-art practical …


E-Learning And Knowledge Management: The Development Of An E-Learning System For Organisational Training, Alan Muhire Jan 2012

E-Learning And Knowledge Management: The Development Of An E-Learning System For Organisational Training, Alan Muhire

Dissertations

Information technology has major role in most successful companies and organisations around the world, most companies are using IT to reduce operation cost, while improving customer service by providing service twenty four hours, seven days a week and improving communication that helps keep pace with competitors. In most companies and organisation training is a process carried out on a regular basis; the quality of training offered to employee will be reflected on how knowledgeable the staff will become resulting in the organisation becoming more successful. As organisations and companies are currently interested in improving knowledge management, employees are equally working …


Efficient Corona Training Protocols For Sensor Networks, Alan A. Bertossi, Stephan Olariu, Cristina M. Pinotti Jan 2008

Efficient Corona Training Protocols For Sensor Networks, Alan A. Bertossi, Stephan Olariu, Cristina M. Pinotti

Computer Science Faculty Publications

Phenomenal advances in nano-technology and packaging have made it possible to develop miniaturized low-power devices that integrate sensing, special-purpose computing, and wireless communications capabilities. It is expected that these small devices, referred to as sensors, will be mass-produced and deployed, making their production cost negligible. Due to their small form factor and modest non-renewable energy budget, individual sensors are not expected to be GPS-enabled. Moreover, in most applications, exact geographic location is not necessary, and all that the individual sensors need is a coarse-grain location awareness. The task of acquiring such a coarse-grain location awareness is referred to as training. …


H-Infinity Estimation For Fuzzy Membership Function Optimization, Daniel J. Simon Nov 2005

H-Infinity Estimation For Fuzzy Membership Function Optimization, Daniel J. Simon

Electrical and Computer Engineering Faculty Publications

Given a fuzzy logic system, how can we determine the membership functions that will result in the best performance? If we constrain the membership functions to a specific shape (e.g., triangles or trapezoids) then each membership function can be parameterized by a few variables and the membership optimization problem can be reduced to a parameter optimization problem. The parameter optimization problem can then be formulated as a nonlinear filtering problem. In this paper we solve the nonlinear filtering problem using H state estimation theory. However, the membership functions that result from this approach are not (in general) sum normal. …


Usability Over Time, Valerie Mendoza, David G. Novick Sep 2005

Usability Over Time, Valerie Mendoza, David G. Novick

Departmental Papers (CS)

Testing of usability could perhaps be more accurately described as testing of learnability. We know more about the problems of novice users than we know of the problems of experienced users. To understand how these problems differ, and to understand how usability problems change as users change from novice to experienced, we conducted a longitudinal study of usability among middle-school teachers creating Web sites. The study looked at the use both the use of documentation and the underlying software, tracking the causes and extent of user frustration over eight weeks. We validated a categorization scheme for frustration episodes. We found …


Training Radial Basis Neural Networks With The Extended Kalman Filter, Daniel J. Simon Oct 2002

Training Radial Basis Neural Networks With The Extended Kalman Filter, Daniel J. Simon

Electrical and Computer Engineering Faculty Publications

Radial basis function (RBF) neural networks provide attractive possibilities for solving signal processing and pattern classification problems. Several algorithms have been proposed for choosing the RBF prototypes and training the network. The selection of the RBF prototypes and the network weights can be viewed as a system identification problem. As such, this paper proposes the use of the extended Kalman filter for the learning procedure. After the user chooses how many prototypes to include in the network, the Kalman filter simultaneously solves for the prototype vectors and the weight matrix. A decoupled extended Kalman filter is then proposed in order …