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2020

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Articles 301 - 330 of 4524

Full-Text Articles in Computer Sciences

Dublin Smart City Data Integration, Analysis And Visualisation, Hammad Ul Ahad Nov 2020

Dublin Smart City Data Integration, Analysis And Visualisation, Hammad Ul Ahad

Doctoral

Data is an important resource for any organisation, to understand the in-depth working and identifying the unseen trends with in the data. When this data is efficiently processed and analysed it helps the authorities to take appropriate decisions based on the derived insights and knowledge, through these decisions the service quality can be improved and enhance the customer experience. A massive growth in the data generation has been observed since two decades. The significant part of this generated data is generated from the dumb and smart sensors. If this raw data is processed in an efficient manner it could uplift …


A Model For Massless Gravitons In Radiation And Matter Dominated Universes, Ioannis Haranas, Eli Cavan, Ioannis Gkigkitzis Nov 2020

A Model For Massless Gravitons In Radiation And Matter Dominated Universes, Ioannis Haranas, Eli Cavan, Ioannis Gkigkitzis

Physics and Computer Science Faculty Publications

A massless model of the graviton is explored by considering the minimum amount of information they can carry. The total entropy of the universe is calculated and compared to estimates from Super Massive Black holes and massive models of the graviton. The running cosmological constant is calculated using the entropy relation previously computed and compared to its experimentally accepted value. Both results are quantified considering radiation and matter dominated universes.


Goamlp: Network Intrusion Detection With Multilayer Perceptron And Grasshopper Optimization Algorithm, Farshid Bagheri Saravi Nov 2020

Goamlp: Network Intrusion Detection With Multilayer Perceptron And Grasshopper Optimization Algorithm, Farshid Bagheri Saravi

Student Scholarship

In this paper, an intrusion detection system is introduced that uses data mining and machine learning concepts to detect network intrusion patterns. In the proposed method, an artificial neural network (ANN) is used as a learning technique in intrusion detection. The metaheuristic algorithm with the swarm-based approach is used to reduce intrusion detection errors. In the proposed method, the Grasshopper Optimization Algorithm (GOA) is used for better and more accurate learning of ANNs to reduce intrusion detection error rate. The role of the GOAMLP algorithm is to minimize the intrusion detection error in the neural network by selecting useful parameters …


Creating Optimal Conditions For Reproducible Data Analysis In R With ‘Fertile’, Audrey M. Bertin, Benjamin Baumer Nov 2020

Creating Optimal Conditions For Reproducible Data Analysis In R With ‘Fertile’, Audrey M. Bertin, Benjamin Baumer

Statistical and Data Sciences: Faculty Publications

The advancement of scientific knowledge increasingly depends on ensuring that data-driven research is reproducible: that two people with the same data obtain the same results. However, while the necessity of reproducibility is clear, there are significant behavioral and technical challenges that impede its widespread implementation and no clear consensus on standards of what constitutes reproducibility in published research. We present fertile, an R package that focuses on a series of common mistakes programmers make while conducting data science projects in R, primarily through the RStudio integrated development environment. fertile operates in two modes: proactively, to prevent reproducibility mistakes from happening …


Computational Cognition And Deep Learning, Andy Malinsky Nov 2020

Computational Cognition And Deep Learning, Andy Malinsky

The Compass

No abstract provided.


Connecting Swosu To The Open Science Grid, Arianna Martin, Jeremy Evert Nov 2020

Connecting Swosu To The Open Science Grid, Arianna Martin, Jeremy Evert

Student Research

No abstract provided.


Development Of A Mobile Ten Frames App For Philippine K-12 Schools, Debbie Marie Versoza, Ma. Louise Antonette N. De Las Peñas, Jumela F. Sarmiento, Mark Anthony C. Tolentino, Mark L. Loyola Nov 2020

Development Of A Mobile Ten Frames App For Philippine K-12 Schools, Debbie Marie Versoza, Ma. Louise Antonette N. De Las Peñas, Jumela F. Sarmiento, Mark Anthony C. Tolentino, Mark L. Loyola

Mathematics Faculty Publications

This paper reports on the Quick Images app, whose design framework is informed by research on ten-structured thinking and gamification principles. Inclusivity was also a major consideration, especially in the context of a developing country. Thus, the app was made freely available and required only moderate system requirements. Pilot studies revealed that the app has the potential to promote children’s ability to see two-digit numbers in relation to tens and ones, which is a major goal of elementary school mathematics. Collaborations with the Philippine Department of Education to ensure the app’s sustained use are also discussed.


Secure Unlinkability Schemes For Privacy Preserving Data Publishing In Weighted Social Networks, Chong Kah Meng Nov 2020

Secure Unlinkability Schemes For Privacy Preserving Data Publishing In Weighted Social Networks, Chong Kah Meng

Student Works (2020-2029)

Preserving privacy of users has been one of the important research issues in social networks. Social networks contain sensitive personal information that are often released for business and research purposes. The privacy of a user can be breached if the data are not released in an anonymized form. In this thesis, we address edge weight disclosure, link disclosure and identity disclosure problems in publishing weighted network data. To counter these privacy risks while preserving high utility of the published data, we define two key privacy properties, namely edge weight unlinkability and node unlinkability. We design two novel anonymization schemes namely …


Covid-19 And Mental Health/Substance Use Disorders On Reddit: A Longitudinal Study, Amanuel Alambo, Swati Padhee, Tanvi Banerjee, Krishnaprasad Thirunarayan Nov 2020

Covid-19 And Mental Health/Substance Use Disorders On Reddit: A Longitudinal Study, Amanuel Alambo, Swati Padhee, Tanvi Banerjee, Krishnaprasad Thirunarayan

Computer Science and Engineering Faculty Publications

COVID-19 pandemic has adversely and disproportionately impacted people suffering from mental health issues and substance use problems. This has been exacerbated by social isolation during the pandemic and the social stigma associated with mental health and substance use disorders, making people reluctant to share their struggles and seek help. Due to the anonymity and privacy they provide, social media emerged as a convenient medium for people to share their experiences about their day to day struggles. Reddit is a well-recognized social media platform that provides focused and structured forums called subreddits, that users subscribe to and discuss their experiences with …


Moving Target Network Steganography, Tapan Soni Nov 2020

Moving Target Network Steganography, Tapan Soni

Theses and Dissertations

A branch of information hiding that has gained traction in recent years is network steganography. Network steganography uses network protocols are carriers to hide and transmit data. Storage channel network steganography manipulates values in protocol header and data fields and stores covert data inside them. The timing channel modulates the timing of events in the protocol to transfer covert information. Many current storage channel network steganography methods have low bandwidths and they hide covert data directly into the protocol which allows discoverers of the channel to read the confidential information. A new type of storage channel network steganography method is …


Energy-Based Neural Modelling For Large-Scale Multiple Domain Dialogue State Tracking, Anh Duong Trinh, Robert J. Ross, John D. Kelleher Nov 2020

Energy-Based Neural Modelling For Large-Scale Multiple Domain Dialogue State Tracking, Anh Duong Trinh, Robert J. Ross, John D. Kelleher

Conference papers

Scaling up dialogue state tracking to multiple domains is challenging due to the growth in the number of variables being tracked. Furthermore, dialog state tracking models do not yet explicitly make use of relationships between dialogue variables, such as slots across domains. We propose using energy-based structure prediction methods for large-scale dialogue state tracking task in two multiple domain dialogue datasets. Our results indicate that: (i) modelling variable dependencies yields better results; and (ii) the structured prediction output aligns with the dialogue slot-value constraint principles. This leads to promising directions to improve state-of-the-art models by incorporating variable dependencies into their …


Implementation Of Smartphone Navigation Features By Combined Forces In Determining The Hazards Of Terrorism In Poso, Mahturai Rian Fitra Mrf, Arthur Josias Simon Runturambi Ajsr Nov 2020

Implementation Of Smartphone Navigation Features By Combined Forces In Determining The Hazards Of Terrorism In Poso, Mahturai Rian Fitra Mrf, Arthur Josias Simon Runturambi Ajsr

Journal of Terrorism Studies

The presence of armed terrorist groups in Poso can threaten security conditions in the country because their activities are considered quite dangerous for the surrounding community. This terrorist group did not hesitate to kill civilians who tried to deny its existence. Therefore, various joint military operations have been launched to crush this armed terrorist group, such as Camar Maleo and Tinombala. However, until now this terrorist group is difficult to destroy, due to the condition of the operating area in the form of dense tropical rainforest and steep slopes. This makes it difficult for troops to carry out chases and …


Autonomous Vehicles And The Ethical Tension Between Occupant And Non-Occupant Safety, Jason Borenstein, Joseph Herkert, Keith Miller Nov 2020

Autonomous Vehicles And The Ethical Tension Between Occupant And Non-Occupant Safety, Jason Borenstein, Joseph Herkert, Keith Miller

The Journal of Sociotechnical Critique

Given that the creation and deployment of autonomous vehicles is likely to continue, it is important to explore the ethical responsibilities of designers, manufacturers, operators, and regulators of the technology. We specifically focus on the ethical responsibilities surrounding autonomous vehicles that these stakeholders have to protect the safety of non-occupants, meaning individuals who are around the vehicles while they are operating. The term “non-occupants” includes, but is not limited to, pedestrians and cyclists. We are particularly interested in how to assign moral responsibility for the safety of non-occupants when autonomous vehicles are deployed in a complex, land-based transportation system.


Machine Learning Augmentation Micro-Sensors For Smart Device Applications, Mohammad H. Hasan Nov 2020

Machine Learning Augmentation Micro-Sensors For Smart Device Applications, Mohammad H. Hasan

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Novel smart technologies such as wearable devices and unconventional robotics have been enabled by advancements in semiconductor technologies, which have miniaturized the sizes of transistors and sensors. These technologies promise great improvements to public health. However, current computational paradigms are ill-suited for use in novel smart technologies as they fail to meet their strict power and size requirements. In this dissertation, we present two bio-inspired colocalized sensing-and-computing schemes performed at the sensor level: continuous-time recurrent neural networks (CTRNNs) and reservoir computers (RCs). These schemes arise from the nonlinear dynamics of micro-electro-mechanical systems (MEMS), which facilitates computing, and the inherent ability …


New Methods For Deep Learning Based Real-Valued Inter-Residue Distance Prediction, Jacob Barger Nov 2020

New Methods For Deep Learning Based Real-Valued Inter-Residue Distance Prediction, Jacob Barger

Theses

Background: Much of the recent success in protein structure prediction has been a result of accurate protein contact prediction--a binary classification problem. Dozens of methods, built from various types of machine learning and deep learning algorithms, have been published over the last two decades for predicting contacts. Recently, many groups, including Google DeepMind, have demonstrated that reformulating the problem as a multi-class classification problem is a more promising direction to pursue. As an alternative approach, we recently proposed real-valued distance predictions, formulating the problem as a regression problem. The nuances of protein 3D structures make this formulation appropriate, allowing predictions …


Under Impact Of Non-Motor Vehicle Violation An Analysis On Vehicle Operation Efficiency, Sun Di, Zhou Jin, Sijia Liu, Xiaoming Zhang, Xueying Gao Nov 2020

Under Impact Of Non-Motor Vehicle Violation An Analysis On Vehicle Operation Efficiency, Sun Di, Zhou Jin, Sijia Liu, Xiaoming Zhang, Xueying Gao

Journal of System Simulation

Abstract: In order to study the impact of non-motor vehicle violations on motor vehicle traffic efficiency at signalized intersections, the non-motor vehicle traffic behaviors are analyzed. An actual intersection is selected as study object, the main violation behaviors of on selected intersection are analyzed by using the linear regression model. For traffic light violation behavior of non-motor vehicles, the violation rate is modeled by using logistic model, and the results are analyzed. At the signal controlled intersection, non-motor vehicle violations affect the normal motor vehicles, and time is delayed. The delay time of motor vehicle under non-motor vehicle …


Time-Varying Parameter System Modeling Method Based On Zonotope-Ellipsoid Double Filtering, Ziyun Wang, Peiyu Wang, Yacong Zhan Nov 2020

Time-Varying Parameter System Modeling Method Based On Zonotope-Ellipsoid Double Filtering, Ziyun Wang, Peiyu Wang, Yacong Zhan

Journal of System Simulation

Abstract: The traditional system modeling method using zonotopes as the feasible parameter sets islikely to increase the computational complexity of the algorithm due to the increasing dimensions of the zonotope shape matrix. This paper proposes a time-varying parameter modeling systems method based on zonotope-ellipsoid double filtering technique. Considering the time-varying parameters, a zonotope with the minimum volume is obtained during the iterations of the intersection with the constraint strip. After transforming the shape matrix of the zonotope, the dimensionality reduction is performed, instead of directly finding the row sum of the extended shape matrix, to reduce the algorithm conservativeness originated …


Research On Configurable Simulation Integration Technology For Equipment Software, Yuanyuan Wang, Yuxin Duan, Guangzhao Song Nov 2020

Research On Configurable Simulation Integration Technology For Equipment Software, Yuanyuan Wang, Yuxin Duan, Guangzhao Song

Journal of System Simulation

Abstract: The problems of the traditional distributed digital simulation system are analyzed. The method of constructing the digital simulation system based on the equipment software is studied. The configurable simulation integration middleware is designed. The overall structure of the configurable middleware is designed and the design ideas of each module are briefly summarized. An example of a digital simulation system with networked transformation of equipment shows that the middleware can be effectively and flexibly configured and can provide support for constructing digital simulation system with software, which can be promoted and used in other simulation systems.


Research On Multi-Objective Optimization Method Based On Model, Jianjun Liu, Guangya Si, Yanzheng Wang, Dachuan He Nov 2020

Research On Multi-Objective Optimization Method Based On Model, Jianjun Liu, Guangya Si, Yanzheng Wang, Dachuan He

Journal of System Simulation

Abstract: There is a model-based algorithm for the optimization of multiple objective functions by means of black-box evaluation is proposed. The algorithm iteratively generates candidate solutions from a mixture distribution over the solution space and updates the mixture distribution based on the sampled solutions’ domination count, such that the future search is biased towards the set of Pareto optimal solutions. The proposed algorithm seeks to find a mixture distribution on the solution space so that each component of the mixture distribution is a degenerate distribution centered at a Pareto optimal solution and each estimated Pareto optimal solution is uniformly spread …


Research And Application Of A Lightweight Real-Time Human Posture Detection Model, Hongkun Zhu, Jiawei Yin, Wenyu Feng, Hua Liang, Minrui Fei, Kun Zhang Nov 2020

Research And Application Of A Lightweight Real-Time Human Posture Detection Model, Hongkun Zhu, Jiawei Yin, Wenyu Feng, Hua Liang, Minrui Fei, Kun Zhang

Journal of System Simulation

Abstract: The traditional OpenPose model has good accuracy but slow speed in human posture detection. In order to accelerate the detection speed and reduce the model on condition of the detection precision, based on the traditional OpenPose model, the residual network with second-order term fusion is used to extract the low-level features, the weights of the trained model are pruned by the L1 norm weight, and an improved OpenPose model is proposed. Experiments show that when the detection accuracy is approximately equal to original model, the model size reduces to about 8%, the parameters reduces by nearly 83%, and the …


Construction And Test Method Of A Semi-Physical Simulation System For Laser Driving Guidance Weapon, Zhang Xiang, Mengyan Liu, Zhang Peng, Kewei Zhu, Xiaodong Yan Nov 2020

Construction And Test Method Of A Semi-Physical Simulation System For Laser Driving Guidance Weapon, Zhang Xiang, Mengyan Liu, Zhang Peng, Kewei Zhu, Xiaodong Yan

Journal of System Simulation

Abstract: To achieve the previous semi-physical simulation of the laser beam-guided weapon, the two-dimensional translation system must be used. But the technical index of the two-dimensional translation system is not high enough to meet the requirements of the relative motion simulation speed and acceleration of the projectile. To solve the problem, a new method and test method for the semi-physical simulation system of laser driving guidance weapon is proposed. The “two-axis turret + load bracket” simulation system construction method is adopted to replace the linear motion of the two-dimensional translation system by the rotational angular motion of the …


Two Gd Atoms Adsorbed On Zigzag Graphene Nanoribbon:A First-Principles Study, Weifeng Xie, Zuo Xu Nov 2020

Two Gd Atoms Adsorbed On Zigzag Graphene Nanoribbon:A First-Principles Study, Weifeng Xie, Zuo Xu

Journal of System Simulation

Abstract: A giant Rashba-type spin splitting is highly critical for the application of spintronics, but one-dimensional magnetic systems are rarely involved. In order to explore the characteristics and strength of Rashba effect in one-dimensional magnetic systems, two Gd atoms adsorbed on Zigzag graphene nanoribbon system is proposed. The characteristics and strength of the Rashba effect in different magnetization directions and the magnetic anisotropy of the system are analyzed through the first-principles calculations. The results show that the antiferromagnetic ground state system has strong Rashba strength and out-of-plane magnetic anisotropy. In addition, the Rashba effect in magnetic system needs to …


Generalized Zero-Inflated Binomial Distribution Model Aimed At Air Quality Data Analysis, Benyue Su, Pengpeng Xu, Sheng Min Nov 2020

Generalized Zero-Inflated Binomial Distribution Model Aimed At Air Quality Data Analysis, Benyue Su, Pengpeng Xu, Sheng Min

Journal of System Simulation

Abstract: For the problem of the quality monitoring and counting of excessive gas emissions in chemical industry parks, a generalized zero-inflated binomial distribution model is constructed. Statistics show that the times of number of excessive gas emissions has a typical zero-inflated feature. The traditional zero-inflated Poisson model and negative binomial regression model and so on will underestimate the probability of zero inflation. A generalized zero-inflated binomial distribution model is constructed by extending the traditional binomial regression model to a more general form. This model satisfies the characteristic that the expectation is less than the variance, and better solves the problems …


Hyper-Heuristic De Algorithm For Solving Zero-Wait Fermentation Process Schedulinge, Shen Peng, Wang Yan, Zhicheng Ji, Jianhua Zhang Nov 2020

Hyper-Heuristic De Algorithm For Solving Zero-Wait Fermentation Process Schedulinge, Shen Peng, Wang Yan, Zhicheng Ji, Jianhua Zhang

Journal of System Simulation

Abstract: A class of zero-wait fermentation process scheduling issues with batch process characteristics are researched. In order to solve the problem of easy deterioration in the process, a super heuristic difference algorithm is proposed, and the maximum makespan is minimized as the optimization goal. The algorithm is divided into two layers. The upper layer is an improved adaptive differential evolution algorithm to select and sort the heuristic operations in lower layer. The lower layer is combined and sorted into a new algorithm to operate on the problem domain, adding simulated annealing algorithm to avoid falling into local optimization. The method …


Modeling And Relevance Analysis Of Urban Epidemic Transmission And Work Resumption Intensity, Gan Mi, Yunyi Tian, Wenchang Zhang, Xihan Zhao Nov 2020

Modeling And Relevance Analysis Of Urban Epidemic Transmission And Work Resumption Intensity, Gan Mi, Yunyi Tian, Wenchang Zhang, Xihan Zhao

Journal of System Simulation

Abstract: On the basis of multi-source big data, the model for analyzing the population migration changes and manpower gaps caused by the COVID-19 epidemic in 34 typical cities across the country is constructed , and the work resumption intensity of other cities is predicited by using the migration base constructed. The SEIR model is used to estimate the basic reproduction number in each city since the simulate results show that it can emulate the transmission trend of this epidemic accurately, and the retrospective matrix analysis of the work resumption intensity is combined with the manpower gap to summarize the anti-epidemic …


Research On Dynamic Flexible Job Shop Scheduling Problem Based On Dynamic Interaction Layer, Zhang Xiang, Wang Yan, Zhicheng Ji Nov 2020

Research On Dynamic Flexible Job Shop Scheduling Problem Based On Dynamic Interaction Layer, Zhang Xiang, Wang Yan, Zhicheng Ji

Journal of System Simulation

Abstract: In order to quickly response to the unforeseen circumstances in flexible job shop, a dynamic flexible job shop scheduling model is constructed, which takes the overall production time and the completion time of emergency orders as the optimization objectives. For the model, a dynamic interaction layer (DIL) model, which has a better performance on DFJSP, is proposed to replace the scroll window. Particle swarm genetic hybrid algorithm (PSGA) is designed to combine the particle swarm optimization algorithm with the genetic algorithm to enhance the ability of local search. Aiming at the unexpected urgent orders in flexible job shop, …


Bert Efficacy On Scientific And Medical Datasets: A Systematic Literature Review, Clayton Cohn Nov 2020

Bert Efficacy On Scientific And Medical Datasets: A Systematic Literature Review, Clayton Cohn

College of Computing and Digital Media Dissertations

Bidirectional Encoder Representations from Transformers (BERT) [Devlin et al., 2018] has been shown to be effective at modeling a multitude of datasets across a wide variety of Natural Language Processing (NLP) tasks; however, little research has been done regarding BERT’s effectiveness at modeling domain-specific datasets. Specifically, scientific and medical datasets present a particularly difficult challenge in NLP, as these types of corpora are often rife with technical jargon that is largely absent from the canonical corpora that BERT and other transfer learning models were originally trained on. This thesis is a Systematic Literature Review (SLR) of twenty-seven studies that were …


Echo Simulation And Verification Of High Resolution Range Profile, Xiaolin Li, Cheng Yu, Haifei Zang, Shuge Wang, Liu Li, Qingqing Yuan Nov 2020

Echo Simulation And Verification Of High Resolution Range Profile, Xiaolin Li, Cheng Yu, Haifei Zang, Shuge Wang, Liu Li, Qingqing Yuan

Journal of System Simulation

Abstract: In order to realize the echo simulation and verification of high-resolution range profile in laboratory environment, the multi-scattering point model and wideband LFM echo signal model are given, and the time-domain convolution and high-precision delay realization methods in echo simulation process are described. According to the different signal bandwidth forms of the tested equipments, a wideband echo simulator is used to realize the corresponding high-resolution range image echo. By comparing with the digital simulation results of the target characteristic modeling software, the fidelity of the high-resolution range echo simulation is verified. Simulation verification is carried out with an aircraft …


Multi-Agent Simulation Model For Covid-19 Virus Prevention And Control, Lihu Pan, Shipeng Qin, Xiaowen Li, Feiping Lu, Fenyu Yang Nov 2020

Multi-Agent Simulation Model For Covid-19 Virus Prevention And Control, Lihu Pan, Shipeng Qin, Xiaowen Li, Feiping Lu, Fenyu Yang

Journal of System Simulation

Abstract: The prevention and control of the novel coronavirus (COVID-19) is the priority work to maintain the public health security of the world nowadays. The COVID-19 prevention and control model using multi-agent modeling and simulation technology is proposed. The model can simulate the different dynamic development trend of the epidemic under different prevention and control measures. Taking Taiyuan as an example, according to the researched COVID-19 transmission rules, the prevention and control simulation of COVID-19 has been achieved under the designing rule of the interactive infection process and status transition process between various resident agents. Multi-scenario simulation experiments are realized …


Design And Implementation Of Cloth Virtual Simulation System For Group Performance, Xiaotian Sun, Boxiang Xiao, Zhengdong Liu Nov 2020

Design And Implementation Of Cloth Virtual Simulation System For Group Performance, Xiaotian Sun, Boxiang Xiao, Zhengdong Liu

Journal of System Simulation

Abstract: Clothing plays an important role in group performance activities and affects directly the overall performance effect. In order to achieve the goal of virtual design and virtual exercise of group performance costume, a virtual simulation system is designed and implemented. The human body model is established by CLO3D, and then individual clothing model is constructed. After the human body and clothing model are imported into Unity, the clothing material is adjusted and the texture map is added. The group model is generated by copying individual clothing models of human body and clothing in Unity. The interactive interface of virtual …