Open Access. Powered by Scholars. Published by Universities.®

Computer Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

2021

Discipline
Institution
Keyword
Publication
Publication Type
File Type

Articles 121 - 150 of 1378

Full-Text Articles in Computer Engineering

Analysis Of Library Book Borrower Patterns Using Apriori Association Data Mining Techniques, Lucky Zamzami, Ari Agung Prastowo, R Rulinawaty, Robbi Rahim Nov 2021

Analysis Of Library Book Borrower Patterns Using Apriori Association Data Mining Techniques, Lucky Zamzami, Ari Agung Prastowo, R Rulinawaty, Robbi Rahim

Library Philosophy and Practice (e-journal)

The library is one of the most important facilities because it manages collections of written works, printed works, and recorded works and can provide information resources as well as be a driving force for the advancement of an educational institution. Conventional libraries will have piles of book borrowing transaction data recorded in the agenda book, which is only an archive, and the placement of books far apart, which causes members to take longer to find books when borrowing books of different types, is an issue that must be addressed. To overcome these two issues, a recommendation for an intelligent system …

Go to article

Research On Intelligent Gait Recognition Method Based On Plantar Pressure Perception, Xueqin Liu, Liu Ning, Su Zhong, Jingxiao Wang, Chaojie Yuan Nov 2021

Research On Intelligent Gait Recognition Method Based On Plantar Pressure Perception, Xueqin Liu, Liu Ning, Su Zhong, Jingxiao Wang, Chaojie Yuan

Journal of System Simulation

Abstract: In view of the complexity and low accuracy of gait recognition in the past, an intelligent gait recognition method based on plantar pressure perception is proposed. The pressure data of the gait of plantar periodic motion is collected and the obtained gait data is classified by the vector machines,the intelligent gait recognition of plantar pressure perception is realized, and the accuracy of gait feature analysis is improved. Through experiment verification, the overall classification accuracy of the classifier is more than 90%, which verifies the rationality of the feature extraction. By evaluating the real state and the results of …

Go to article

A Natural Computing Method Based On Spatial Division Search Strategy, Xiaoqing Sun, Cheng Hao, Luyao Zhang, Weidong Ji, Wang Xu Nov 2021

A Natural Computing Method Based On Spatial Division Search Strategy, Xiaoqing Sun, Cheng Hao, Luyao Zhang, Weidong Ji, Wang Xu

Journal of System Simulation

Abstract: A natural computing method based on spatial division search strategy is proposed. The strategy can map the high-dimensional space to the three-dimensional Cartesian coordinate system by grouping the dimensional space into a group of three dimensions. The individual after spatial segmentation is numbered into subindividual, to increases the particle number while reducing the dimension, thus the individual is distributed over wider search space to effectively increases the diversity of the population. The algorithm iterates to a certain extent and can synthesize the individual into the original individual through the numbered index. By calculating the fitness value, some poor …

Go to article

Short-Term Wind Power Prediction Method Based On Random Forest, Liu Xing, Wang Yan, Zhicheng Ji Nov 2021

Short-Term Wind Power Prediction Method Based On Random Forest, Liu Xing, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: In order to effectively predict the power and value fluctuation range of the short-term wind, a wind power prediction method based on clustering and kernel principal component analysis combined with random forest algorithm is proposed. The clustering analysis data processing method is used to preprocess the meteorological wind power generation data to improve the data quality, and the kernel principal component analysis method is used to reduce the dimensionality of the eight groups of characteristic data to remove the correlation of the wind power data, the random forest algorithm is used to forecast the wind power, to obtain …

Go to article

Adaptive Center Node Selection Method For Unmanned Cluster, Hua Xiang, Chenglong Shi, Baohua Li, Jietao Zhang, Jiaxian Zuo Nov 2021

Adaptive Center Node Selection Method For Unmanned Cluster, Hua Xiang, Chenglong Shi, Baohua Li, Jietao Zhang, Jiaxian Zuo

Journal of System Simulation

Abstract: In the unmanned cluster task execution, following the change of relative position of unmanned system, network changes in real time leads to the change of node importance of each unmanned system, and the corresponding change of data transmission and communication flow. For the better network management, the central node for controlling data communication needs to be selected. An adaptive selection method for the center node of unmanned cluster is proposed, and the mapping and feature of unmanned cluster network is expressed as graph theory. Laplacian centrality is introduced to evaluate the importance of nodes themselves. Weakening factors are …

Go to article

Intelligent Evaluation Of Rescuing Persons From Water In Navigation Simulator, Haichao Wang, Yin Yong Nov 2021

Intelligent Evaluation Of Rescuing Persons From Water In Navigation Simulator, Haichao Wang, Yin Yong

Journal of System Simulation

Abstract: Aiming at the arbitrariness and inconsistent standards in the subjective assessment of the personnel overboard rescue training evaluation in the navigation simulator, the maneuvering process of Williamson turn rescue overboard personnel is analyzed. The evaluation index system is obtained by using the expert investigation method. The sample data of the personnel overboard rescue operation is obtained by the navigation simulator. Combining the expert investigation method, the subjective score of each sample is obtained. By using the BP neural network to train and test the samples, the intelligent evaluation model of personnel overboard rescue is obtained, and the intelligent evaluation …

Go to article

Access Control Mechanism Of Uav Cluster Based On Blockchain Smart Contract, Ting Duan, Weiping Wang, Yifan Zhu, Wang Tao, Meigen Huang Nov 2021

Access Control Mechanism Of Uav Cluster Based On Blockchain Smart Contract, Ting Duan, Weiping Wang, Yifan Zhu, Wang Tao, Meigen Huang

Journal of System Simulation

Abstract: A Unmanned Aerial Vehicle (UAV) cluster access control mechanism based on Ethereum blockchain smart contract is proposed to solve the problems of the strategic stability and low security of UAV cluster access control mechanism. The role-based access control mechanism model is improved, and the formal definition of the access control model for UAV cluster is given. The access control architecture of UAV cluster based on blockchain technology is proposed, and the corresponding basic framework and execution process is proposed, which can effectively reduce the cost of UAV cluster operation management resources, solve the problem of incomplete state …

Go to article

Modeling And Simulation Of Radiation Measurement System Based On Monte Carlo Method, Jinghai Cheng, Hongzhi Wang, Luoyuan Xu, Xia Tian Nov 2021

Modeling And Simulation Of Radiation Measurement System Based On Monte Carlo Method, Jinghai Cheng, Hongzhi Wang, Luoyuan Xu, Xia Tian

Journal of System Simulation

Abstract: A method is applied to build a virtual simulation radiometric measurement system. The mathematical and physical models of gamma ray interaction with matter, radiation sources, measurement electronics system and protective materials are constructed by using Monte Carlo method. Through numerical calculation and scene simulation of the radiation measurement system, virtual simulation acquisition and energy spectrum processing of radiation measurement data are realized. It, the system, can simulate single channel measurement and computer multi-channel measurement experiments. It can realize energy measurement, activity measurement and energy spectrum measurement of mixed, unknown or custom radiation sources in different size crystals. It can …

Go to article

System Performance Evaluation Method Based On Multi-Source Prior Data, Haozhe Liu, Li Wei, Ma Ping, Yang Ming Nov 2021

System Performance Evaluation Method Based On Multi-Source Prior Data, Haozhe Liu, Li Wei, Ma Ping, Yang Ming

Journal of System Simulation

Abstract: When using the Bayes method to evaluate the performance of the system with multi-source prior data, the multi-source prior data is fused, the posterior distribution is calculated by synthesizing the fused prior distribution and test data. The parameters of posterior distribution are estimated to obtain the performance evaluation results. A weighted fusion method of multi-source prior data based on Kullback-Leibler divergence is proposed, which can effectively integrate the multi-source prior data. The commonly used Markov Chain Monte Carlo method is used to estimate the parameters of Bayes posterior distribution. The influence of different proposal distributions on the sampling results …

Go to article

Normalization Of Simulation System Credibility Index Based On Vague Set, Yuhang Ren, Li Wei, Ma Ping, Yang Ming Nov 2021

Normalization Of Simulation System Credibility Index Based On Vague Set, Yuhang Ren, Li Wei, Ma Ping, Yang Ming

Journal of System Simulation

Abstract: Focus on various types of simulation system credibility indexes and the difficulty to convert the index results to credibility, a normalization method of credibility indexes based on Vague sets is proposed, which includes qualitative and quantitative conversion methods; Aiming at the problem of credibility Vague value index synthesis, the weighted arithmetic mean operator and the weighted geometric mean operator based on Vague set are given, and the applications are explained; According to the similarity principle of Vague sets, a method of transforming the credibility Vague value to the credibility single value is proposed, which improves the …

Go to article

Trajectory Tracking Control Of Planetary Entry Phase Based On Neural Network And Fractional Sliding Mode, Cunli Fan, Dai Juan, Haitao Liu, Su Zhong, Zhu Cui, Wenting Xu Nov 2021

Trajectory Tracking Control Of Planetary Entry Phase Based On Neural Network And Fractional Sliding Mode, Cunli Fan, Dai Juan, Haitao Liu, Su Zhong, Zhu Cui, Wenting Xu

Journal of System Simulation

Abstract: A fractional order sliding mode control method based on Radial Basis Function (RBF) neural network is proposed to solve the landing accuracy being affected by the interference during the landing process of planetary probe. Based on sliding mode control, a trajectory tracking control method for the entry phase of the probe is designed. Fractional calculus is introduced to alleviate the chattering caused by sliding mode control. RBF neural network is used to estimate and compensate the atmospheric density uncertainty. The method is applied to Mars landing scene simulation. The simulation results show that the proposed control method can accurately …

Go to article

An Electromechanical-Electromagnetic Transient Stability Simulation System For Ac/Dc Hybrid Power System, Weijie Dong, Huang Min, Guoqing He, Bao Wei, Yilong Wang, Liu Quan Nov 2021

An Electromechanical-Electromagnetic Transient Stability Simulation System For Ac/Dc Hybrid Power System, Weijie Dong, Huang Min, Guoqing He, Bao Wei, Yilong Wang, Liu Quan

Journal of System Simulation

Abstract: In order to improve the hybrid simulation speed of AC/DC power grid, it is necessary to improve the simulation method of sub grid parallel. An electromechanical transient stability simulation system is presented for AC/DC hybrid power grid. The AC/DC sub network module is used to divide the large AC/DC power grid into small AC/DC sub networks, so that each sub network can be simulated in parallel. The numerical calculation method is improved for the efficiency and accuracy of simulation calculation. Taking IEEE 10-39 bus as an example, the effectiveness of the method is verified in PSCAD (Power Systems Computer …

Go to article

Supplier Selection Based On Supplier Portrait And Markov Monte Carlo Method, Bingli Sun, Song Xiao, Guanghong Gong Nov 2021

Supplier Selection Based On Supplier Portrait And Markov Monte Carlo Method, Bingli Sun, Song Xiao, Guanghong Gong

Journal of System Simulation

Abstract: The supplier selection problem is a complex multi-objective decision-making problem and the key is how to establish the supplier's portrait. For the supplier selection of aerospace equipment, enterprise qualification management, business risks, and product quality are comprehensively considered. Based on Bayesian theory, the multi-parameter joint distribution derivation of portrait sample data is realized. Combined with the mathematical model derived, a Markov Monte Carlo simulation method is proposed. And combined with Gibbs sampler, the supplier ranking and selection are achieved when data is difficult to obtain or missing, which provides a new idea for supplier selection in the aerospace …

Go to article

Virtual Reality As Pedagogical Tool To Enhance Experiential Learning: A Systematic Literature Review, Muhammad Mujtaba Asad, Aisha Naz Ansari, Prathamesh Churi, Mohammad Mehdi Tahanzadeh Nov 2021

Virtual Reality As Pedagogical Tool To Enhance Experiential Learning: A Systematic Literature Review, Muhammad Mujtaba Asad, Aisha Naz Ansari, Prathamesh Churi, Mohammad Mehdi Tahanzadeh

Institute for Educational Development, Karachi

Since half of the century, technology has dominated the modern era. The rapid advancement of technology has reached generating artificial intelligence and artificial realities. So, virtual reality is an emerging technology and is applicable in education as well. Virtual reality is a computer-generated simulation, where people can interact within an artificial environment. Moreover, in an educational setting, such an environment provides students with a chance to get experiential learning. This paper has a systematic literature review on emerging technologies, such as virtual reality as a pedagogical tool for enhancing students’ experiential learning. This review aims to explore and understand the …

Go to article

Robust Feature Space Separation For Deep Convolutional Neural Network Training, Ali Sekmen, Mustafa Parlaktuna, Ayad Abdul-Malek, Erdem Erdemir, Ahmet Bugra Koku Nov 2021

Robust Feature Space Separation For Deep Convolutional Neural Network Training, Ali Sekmen, Mustafa Parlaktuna, Ayad Abdul-Malek, Erdem Erdemir, Ahmet Bugra Koku

Computer Science Faculty Research

This paper introduces two deep convolutional neural network training techniques that lead to more robust feature subspace separation in comparison to traditional training. Assume that dataset has M labels. The first method creates M deep convolutional neural networks called {DCNNi}M i=1 . Each of the networks DCNNi is composed of a convolutional neural network ( CNNi ) and a fully connected neural network ( FCNNi ). In training, a set of projection matrices are created and adaptively updated as representations for feature subspaces {S i}M i=1 . A rejection value is computed for each training based on its projections on …

Go to article

Cyber Physical Systems For Non-Contact Infrastructure Monitoring, Roya Nasimi Nov 2021

Cyber Physical Systems For Non-Contact Infrastructure Monitoring, Roya Nasimi

Civil Engineering ETDs

In recent decades, the decay of infrastructure has become a relevant challenge of both developed and under developing countries. Prioritization of maintenance and repairs of transportation infrastructure is a new worldwide priority since it is important to quantify the rate of decay of assets to increase both safety and cost-efficient operations. Infrastructure owners need frequent inspections on their assets to predict and to avoid unsafe conditions prone to cause disasters. Frequent infrastructure inspections call for cost-effective methods. Traditional measurement methods require human access to the infrastructure, are subjective, expensive, and unsafe. Therefore, infrastructure managers are interested in exploring new non-contact …

Go to article

Determinants Of Effective Change Management For Software Deployment Projects, Abebaw Zeleke, Walter Mccollum Nov 2021

Determinants Of Effective Change Management For Software Deployment Projects, Abebaw Zeleke, Walter Mccollum

International Journal of Applied Management and Technology

Software application deployment change management is one of the emerging research themes that is gaining increased focus day by day. Our study examined the factors that affect software application deployment change management in Agile software development settings. Our study provided a systematic review and synthesized the approaches, practices, and challenges reported for adopting and implementing deployment change management. The prime objective of our study was to systematically synthesize the data extracted and formulate evidence-based practical recommendations that are influential in software deployment change management. Six research themes are proposed to evaluate the rationale of the research question. This qualitative study …

Go to article

Asynchronous, Distributed Optical Mutual Exclusion And Applications, Ahmed Bahaael Mansour Nov 2021

Asynchronous, Distributed Optical Mutual Exclusion And Applications, Ahmed Bahaael Mansour

LSU Doctoral Dissertations

Silicon photonics have drawn much recent interest in the setting of intra-chip andmodule communication. In this dissertation, we address a fundamental computationalproblem, mutual exclusion, in the setting of optical interconnects. As a main result, wepropose an optical network and an algorithm for it to distribute a token (shared resource)mutually exclusively among a set ofnprocessing elements. Following a request, the tokenis granted in constant amortized time andO(n) worst case time; this assumes constantpropagation time for light within the chip. Additionally, the distribution of tokens is fair,ensuring that no token request is denied more thann−1 times in succession; this is thebest possible. …

Go to article

Disaster Recovery System And Service Continuity Of Digital Library, Sivankalai S, Virumandi A, Sivasekaran K, Sharmila M Nov 2021

Disaster Recovery System And Service Continuity Of Digital Library, Sivankalai S, Virumandi A, Sivasekaran K, Sharmila M

Library Philosophy and Practice (e-journal)

This paper will discuss catastrophe recovery and likelihood development for digital library structures. The article establishes a foundation for establishing Library continuity and disaster recovery strategies through the use of best practices. Library continuity development and catastrophe recovery are critical modules of the planning stage for a virtual digital library. Few institutions that experience a catastrophic disaster occurrence are powerless to recover always, but libraries can suggestively boost the possibility of long-term recovery of institutional digital resources by drafting a continuity and recovery strategy in preparation. This article is intended for system designers and administrators, as well as high-ranking library …

Go to article

Inverse Kinematics Of The 6dof C12xl, Carl Liu, Lili Ma Nov 2021

Inverse Kinematics Of The 6dof C12xl, Carl Liu, Lili Ma

Publications and Research

Industrial robotic manipulators are widely used in applications such as pick & place, welding, and assembly to perform repeated tasks in replace of human labor. Such tasks typically require fully autonomous mechanical arms that are capable of identifying the parts to operate, path planning, and trajectory generation & tracking. A robotic arm consists of a sequence of rigid links connected by movable components (the joints). Proper control of the arm’s motion requires the knowledge of inverse kinematics, which computes/outputs the joint variables, i.e., angles for revolute joints and displacement for prismatic joints, causing the robotic arm’s end effector (e.g., gripper, …

Go to article

A Survey On Various Image Inpainting Techniques, Nermin Mohamed Fawzy Salem Phd Nov 2021

A Survey On Various Image Inpainting Techniques, Nermin Mohamed Fawzy Salem Phd

Future Engineering Journal

Over the decades' researchers have studied the image inpainting problem intensively due to its high significance and effectiveness in various image processing applications such as people and object security, object removal, face editing applications. Image inpainting is defined as the process of completing or removing a missing region in images. It is considered one of the most challenging topics in the image processing field, although, it requires a deep understanding of the image details in terms of texture and structure. In this paper, a survey of most image inpainting techniques is presented and summarized with comparisons including the merits and …

Go to article

Don't Bite The Bait: Phishing Attack For Internet Banking (E-Banking), Ilker Kara Nov 2021

Don't Bite The Bait: Phishing Attack For Internet Banking (E-Banking), Ilker Kara

Journal of Digital Forensics, Security and Law

Phishing attacks are based on obtaining desired information from users quickly and easily with the help of misdirecting, panicking, curiosity, or excitement. Most of the phishing web sites are designed on internet banking(e-banking) and the attackers can acquire financial information of misled users with the tactics and discourses they develop. Despite the increase of prevention techniques against phishing attacks day by day, an effective solution could not be found for this issue due to the human factor. Because of this reason, real phishing attack studies are essential to study and analyze the attackers’ attack techniques and strategies. This study focused …

Go to article

Learning State-Dependent Sensor Measurement Models To Improve Robot Localization Accuracy, Troi André Williams Nov 2021

Learning State-Dependent Sensor Measurement Models To Improve Robot Localization Accuracy, Troi André Williams

USF Tampa Graduate Theses and Dissertations

This dissertation proposes a novel method called state-dependent sensor measurement models (SDSMMs). Such models dynamically predict the state-dependent bias and uncertainty of sensor measurements, ultimately improving fundamental robot tasks such as localization. In our first investigation, we introduced the state-dependent sensor measurement model framework, described their properties, stated the input and output of these models, and described how to train them. We also explained how to integrate such models with an Extended Kalman Filter and a Particle Filter, two popular robot state estimation algorithms. We validated the proposed framework through a series of localization tasks. The results showed that our …

Go to article

Intelligent Internet Of Things Frameworks For Smart City Safety, Dimitrios Sikeridis Nov 2021

Intelligent Internet Of Things Frameworks For Smart City Safety, Dimitrios Sikeridis

Electrical and Computer Engineering ETDs

The emerging Smart City ecosystem consists of a vast edge network of Internet of Things (IoT) devices that continuously interact with mobile devices carried by its citizens. In this setting, the IoT infrastructure, apart from the main communications facilitator, acts as a crowdsourcing mechanism that collects massive amounts of user data, and can support public safety applications for the Smart City. In this thesis, we design and analyze learning mechanisms that extract intelligence from crowd interactions with the wireless IoT infrastructure, and optimize its energy efficiency while operating as a public safety network. First, we deploy a multi-story facility testbed …

Go to article

Cybert: Cybersecurity Claim Classification By Fine-Tuning The Bert Language Model, Kimia Ameri, Michael Hempel, Hamid Sharif, Juan Lopez Jr., Kalyan Perumalla Nov 2021

Cybert: Cybersecurity Claim Classification By Fine-Tuning The Bert Language Model, Kimia Ameri, Michael Hempel, Hamid Sharif, Juan Lopez Jr., Kalyan Perumalla

Department of Electrical and Computer Engineering: Faculty Publications

We introduce CyBERT, a cybersecurity feature claims classifier based on bidirectional encoder representations from transformers and a key component in our semi-automated cybersecurity vetting for industrial control systems (ICS). To train CyBERT, we created a corpus of labeled sequences from ICS device documentation collected across a wide range of vendors and devices. This corpus provides the foundation for fine-tuning BERT’s language model, including a prediction-guided relabeling process. We propose an approach to obtain optimal hyperparameters, including the learning rate, the number of dense layers, and their configuration, to increase the accuracy of our classifier. Fine-tuning all hyperparameters of the resulting …

Go to article

Reliability Models For Smartphone Applications, Sonia Meskini, Ali Bou Nassif, Luiz Fernando Capretz Nov 2021

Reliability Models For Smartphone Applications, Sonia Meskini, Ali Bou Nassif, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

Smartphones have become the most used electronic devices. They carry out most of the functionalities of desktops, offering various useful applications that suit the user’s needs. Therefore, instead of the operator, the user has been the main controller of the device and its applications, therefore its reliability has become an emergent requirement. As a first step, based on collected smartphone applications failure data, we investigated and evaluated the efficacy of Software Reliability Growth Models (SRGMs) when applied to these smartphone data in order to check whether they achieve the same accuracy as in the desktop/laptop area. None of the selected …

Go to article

Protection Of Patient Privacy On Mobile Device Machine Learning, Matthew Nguyen Nov 2021

Protection Of Patient Privacy On Mobile Device Machine Learning, Matthew Nguyen

Cybersecurity Undergraduate Research Showcase

An existing StudentLife Study mobile dataset was evaluated and organized to be applied to different machine learning methods. Different variables like user activity, exercise, sleep, study space, social, and stress levels are optimized to train a model that could predict user stress level. The different machine learning methods would test if both patient data privacy and training efficiency can be ensured.

Go to article

Concolic Execution Of Nmap Scripts For Honeyfarm Generation, Zhe Li, Bo Chen, Wu-Chang Feng, Fei Xie Nov 2021

Concolic Execution Of Nmap Scripts For Honeyfarm Generation, Zhe Li, Bo Chen, Wu-Chang Feng, Fei Xie

Computer Science Faculty Publications and Presentations

Attackers rely upon a vast array of tools for automating attacksagainst vulnerable servers and services. It is often the case thatwhen vulnerabilities are disclosed, scripts for detecting and exploit-ing them in tools such asNmapandMetasploitare released soonafter, leading to the immediate identification and compromise ofvulnerable systems. Honeypots, honeynets, tarpits, and other decep-tive techniques can be used to slow attackers down, however, such approaches have difficulty keeping up with the sheer number of vulnerabilities being discovered and attacking scripts that are being released. To address this issue, this paper describes an approach for applying concolic execution on attacking scripts in Nmap in …

Go to article

Traffic Collision Avoidance System: False Injection Viability, John Hannah, Robert F. Mills, Richard Dill, Douglas D. Hodson Nov 2021

Traffic Collision Avoidance System: False Injection Viability, John Hannah, Robert F. Mills, Richard Dill, Douglas D. Hodson

Faculty Publications

Safety is a simple concept but an abstract task, specifically with aircraft. One critical safety system, the Traffic Collision Avoidance System II (TCAS), protects against mid-air collisions by predicting the course of other aircraft, determining the possibility of collision, and issuing a resolution advisory for avoidance. Previous research to identify vulnerabilities associated with TCAS’s communication processes discovered that a false injection attack presents the most comprehensive risk to veritable trust in TCAS, allowing for a mid-air collision. This research explores the viability of successfully executing a false injection attack against a target aircraft, triggering a resolution advisory. Monetary constraints precluded …

Go to article

Formulating Automated Responses To Cognitive Distortions For Cbt Interactions, Ignacio De Toledo, Giancarlo Salton, Robert J. Ross Nov 2021

Formulating Automated Responses To Cognitive Distortions For Cbt Interactions, Ignacio De Toledo, Giancarlo Salton, Robert J. Ross

Conference papers

One of the key ideas of Cognitive Behavioural Therapy (CBT) is the ability to convert negative or distorted thoughts into more realistic alternatives. Although modern machine learning techniques can be successfully applied to a variety of Natural Language Processing tasks, including Cognitive Behavioural Therapy, the lack of a publicly available dataset makes supervised training difficult for tasks such as reforming distorted thoughts. In this research, we constructed a small CBT dataset via crowd-sourcing, and leveraged state of the art pre-trained architectures to transform cognitive distortions, producing text that is relevant and more positive than the original negative thoughts. In particular, …

Go to article

First Prev Next Last