Physical Sciences and Mathematics Commons^™

Development Of A Web-Based Information System For Student Leave Permission At Dar Al-Raudhah Islamic Boarding School: Iso Quality Standards Analysis, Bonita Destiana, Priyanto Priyanto, Rahmatul Irfan, Muhammad Gus Khamim, Muhammad Yusuf Ridlo, Muhammad Iqbal

Elinvo (Electronics, Informatics, and Vocational Education)

Dar Al-Raudhah Entrepreneur, Islamic Boarding School, has adopted digital technology by upgrading hardware and software also investing in reliable internet infrastructure. However, this school still faces issues with students’ leave permission process due to reliance on manual bookkeeping and Excel, which leads to potential errors. Based on those problems, this research aims to create a web-based student leave permission system called SIPERSAN. The SIPERSAN system was developed with a Waterfall development model, which includes requirements analysis, design, implementation, testing, and deployment. The database is managed with MySQL, and the system is developed using PHP with the Laravel framework. Based on …

The Impact Of Data Recovery Criteria, Data Backup Schedule And Data Backup Prosses On The Efficiency Of Data Recovery Management In Data Centers, Maen T. Alrashdan, Mutaz Abdel Wahed, Emran Aljarrah, Mohammad Tubishat, Malek Alzaqebah, Nader Aljawarneh

All Works

A large-scale cloud data center must have a low failure incidence rate and great service dependability and availability. However, due to several issues, such as hardware and software malfunctions that regularly cause task and job failure, large-scale cloud data centers still have high failure rates. These mistakes can have a substantial impact on cloud service dependability and need a large resource allocation to recover from failures. Therefore, it is important to have an efficient management of data recovery to protect organizations data from loss. This paper aims to study some factors that may improve the management of data recovery by …

Enhancing Fuel Injection System Reliability Through Weibull Family Functions Analysis, Ali Nouri Qarahasanlou, Abbas Barabadi, Meisam Saleki, Ali Rahimazar, Parisa Rezakhania, Masoume Gholamia

Journal of Sustainable Mining

The efficient operation of heavy machinery is crucial to the success of mining and civil construction operations. To guarantee this performance, equipment performance is assessed using the Reliability Index, which analyzes failures to study the ability of a system to carry out its intended functions under predetermined conditions. On the other hand, the failure rate and operational environmental condition (such as management decisions, maintenance performance, etc., that are defined as “risk factors”) over the life cycle of industrial systems pose a significant challenge to reliability analysis. This paper proposes an approach to address these challenges by extending Weibull family functions …

Sequential Optimization For Stressor-Informed Test Planning Through Integration Of Experimental And Simulated Data, Jacob Brecheisen

Data Science Undergraduate Honors Theses

This technical report details an innovative approach in reliability engineering aimed at maximizing system durability through a synergistic use of physical experimentation and computer-based modeling. Our methodology explores the efficient design and analysis of computer experiments and physical tests to facilitate accelerated reliability growth, while leveraging a sequential integration of data from these two distinct sources: costly physical experiments, characterized by random errors, and inexpensive computer simulations, marked by inherent systematic errors. The key innovation lies in the adoption of a closed-loop design and analysis method. This method begins by identifying a viable subset of important environmental stressors—such as temperature, …

Beyond A Joke: Dead Code Elimination Can Delete Live Code, Haoxin Tu, Lingxiao Jiang, Debin Gao, He Jiang

Research Collection School Of Computing and Information Systems

Dead Code Elimination (DCE) is a fundamental compiler optimization technique that removes dead code (e.g., unreachable or reachable but whose results are unused) in the program to produce smaller or faster executables. However, since compiler optimizations are typically aggressively performed and there are complex relationships/interplay among a vast number of compiler optimizations (including DCE), it is not known whether DCE is indeed correctly performed and will only delete dead code in practice. In this study, we open a new research problem to investigate: can DCE happen to erroneously delete live code? To tackle this problem, we design a new approach …

Segac: Sample Efficient Generalized Actor Critic For The Stochastic On-Time Arrival Problem, Honglian Guo, Zhi He, Wenda Sheng, Zhiguang Cao, Yingjie Zhou, Weinan Gao

Research Collection School Of Computing and Information Systems

This paper studies the problem in transportation networks and introduces a novel reinforcement learning-based algorithm, namely. Different from almost all canonical sota solutions, which are usually computationally expensive and lack generalizability to unforeseen destination nodes, segac offers the following appealing characteristics. segac updates the ego vehicle’s navigation policy in a sample efficient manner, reduces the variance of both value network and policy network during training, and is automatically adaptive to new destinations. Furthermore, the pre-trained segac policy network enables its real-time decision-making ability within seconds, outperforming state-of-the-art sota algorithms in simulations across various transportation networks. We also successfully deploy segac …

Pias: Privacy-Preserving Incentive Announcement System Based On Blockchain For Internet Of Vehicles, Yonghua Zhan, Yang Yang, Hongju Cheng, Xiangyang Luo, Zhuangshuang Guan, Robert H. Deng

Research Collection School Of Computing and Information Systems

More vehicles are connecting to the Internet of Things (IoT), transforming Vehicle Ad hoc Networks (VANETs) into the Internet of Vehicles (IoV), providing a more environmentally friendly and safer driving experience. Vehicular announcement networks show promise in vehicular communication applications. However, two major issues arise when establishing such a system. Firstly, user privacy cannot be guaranteed when messages are forwarded anonymously, thus the reliability of these messages is in question. Secondly, users often lack interest in responding to announcements. To address these problems, we introduce a Blockchain-based incentive announcement system called PIAS. This system enables anonymous message commitment in a …

A Psychometric Analysis Of Natural Language Inference Using Transformer Language Models, Antonio Laverghetta Jr.

USF Tampa Graduate Theses and Dissertations

Large language models (LLMs) are poised to transform both academia and industry. But the excitement around these generative AIs has also been met with concern for the true extent of their capabilities. This dissertation helps to address these questions by examining the capabilities of LLMs using the tools of psychometrics. We focus on analyzing the capabilities of LLMs on the task of natural language inference (NLI), a foundational benchmark often used to evaluate new models. We demonstrate that LLMs can reliably predict the psychometric properties of NLI items were those items administered to humans. Through a series of experiments, we …

Vlc-Assisted Safety Message Dissemination In Roadside Infrastructure-Less Iov Systems: Modeling And Analysis, Yuncong Xie, Dongyang Xu, Tiantian Zhang, Keping Yu, Amir Hussain, Mohsen Guizani

Machine Learning Faculty Publications

Internet-of-vehicles (IoV) is an emerging paradigm with significant potential to improve traffic efficiency and driving safety. Here, we focus on the design of a novel visible light communication (VLC)-assisted scheme to enable driving safety-related IoV services that require ultra-reliable and low-latency communications (URLLC). Specifically, the vehicle-to-vehicle (V2V) communication mode is adopted to satisfy the ultra-low latency requirement of URLLC in roadside infrastructure-less IoV systems. In the outdoor V2V-VLC scenarios, the quality of the received optical signal is degraded by path loss, atmospheric turbulence and additive noise. In addition, the short-packet feature of URLLC introduces inevitable data decoding errors and imperfect …

Decentralized Multimedia Data Sharing In Iov: A Learning-Based Equilibrium Of Supply And Demand, Jiani Fan, Minrui Xu, Jiale Guo, Lwin Khin Shar, Jiawen Kang, Dusit Niyato, Kwok-Yan Lam

Research Collection School Of Computing and Information Systems

The Internet of Vehicles (IoV) has great potential to transform transportation systems by enhancing road safety, reducing traffic congestion, and improving user experience through onboard infotainment applications. Decentralized data sharing can improve security, privacy, reliability, and facilitate infotainment data sharing in IoVs. However, decentralized data sharing may not achieve the expected efficiency if there are IoV users who only want to consume the shared data but are not willing to contribute their own data to the community, resulting in incomplete information observed by other vehicles and infrastructure, which can introduce additional transmission latency. Therefore, in this paper, by modeling the …

A New Method To Determine The Posterior Distribution Of Coefficient Alpha, John Mart V. Delosreyes

Psychology Theses & Dissertations

There is a focus within the behavioral/social sciences on non-physical, psychological constructs (i.e., constructs). These constructs are indirectly measured using measurement instruments that consist of questions that capture the manifestations of these constructs. The indirect nature of measuring constructs results in a need of ensuring that measurement instruments are reliable. The most popular statistic used to estimate reliability is coefficient alpha as it is easy to compute and has properties that make it desirable to use. Coefficient alpha’s popularity has resulted in a wide breadth of research into its qualities. Notably, research about coefficient alpha’s distribution has led to developments …

Program Analysis For Android Security And Reliability, Sydur Rahaman

Dissertations

The recent, widespread growth and adoption of mobile devices have revolutionized the way users interact with technology. As mobile apps have become increasingly prevalent, concerns regarding their security and reliability have gained significant attention. The ever-expanding mobile app ecosystem presents unique challenges in ensuring the protection of user data and maintaining app robustness. This dissertation expands the field of program analysis with techniques and abstractions tailored explicitly to enhancing Android security and reliability. This research introduces approaches for addressing critical issues related to sensitive information leakage, device and user fingerprinting, mobile medical score calculators, as well as termination-induced data loss. …

Analysis Of Predictive Performance And Reliability Of Classifiers For Quality Assessment Of Medical Evidence Revealed Important Variation By Medical Area, Simon Šuster, Timothy Baldwin, Karin Verspoor

Natural Language Processing Faculty Publications

Objectives: A major obstacle in deployment of models for automated quality assessment is their reliability. To analyze their calibration and selective classification performance. Study Design and Setting: We examine two systems for assessing the quality of medical evidence, EvidenceGRADEr and RobotReviewer, both developed from Cochrane Database of Systematic Reviews (CDSR) to measure strength of bodies of evidence and risk of bias (RoB) of individual studies, respectively. We report their calibration error and Brier scores, present their reliability diagrams, and analyze the risk–coverage trade-off in selective classification. Results: The models are reasonably well calibrated on most quality criteria (expected calibration error …

Toward A Simulation Model Complexity Measure, J. Scott Thompson, Douglas D. Hodson, Michael R. Grimaila, Nicholas Hanlon, Richard Dill

Faculty Publications

Is it possible to develop a meaningful measure for the complexity of a simulation model? Algorithmic information theory provides concepts that have been applied in other areas of research for the practical measurement of object complexity. This article offers an overview of the complexity from a variety of perspectives and provides a body of knowledge with respect to the complexity of simulation models. The key terms model detail, resolution, and scope are defined. An important concept from algorithmic information theory, Kolmogorov complexity, and an application of this concept, normalized compression distance, are used to indicate the possibility of measuring changes …

Detecting C++ Compiler Front-End Bugs Via Grammar Mutation And Differential Testing, Haoxin Tu, He Jiang, Zhide Zhou, Yixuan Tang, Zhilei Ren, Lei Qiao, Lingxiao Jiang

Research Collection School Of Computing and Information Systems

C++ is a widely used programming language and the C++ front-end is a critical part of a C++ compiler. Although many techniques have been proposed to test compilers, few studies are devoted to detecting bugs in C++ compiler. In this study, we take the first step to detect bugs in C++ compiler front-ends. To do so, two main challenges need to be addressed, namely, the acquisition of test programs that are more likely to trigger bugs in compiler front-ends and the bug identification from complicated compiler outputs. In this article, we propose a novel framework named Ccoft to detect bugs …

Environmentally-Aware And Energy-Efficient Multi-Drone Coordination And Networking For Disaster Response, Chengyi Qu, Francesco Betti Sorbelli, Rounak Singh, Prasad Calyam, Sajal K. Das

Computer Science Faculty Research & Creative Works

In a Disaster Response Management (DRM) Scenario, Communication and Coordination Are Limited, and Absence of Related Infrastructure Hinders Situational Awareness. Unmanned Aerial Vehicles (UAVs) or Drones Provide New Capabilities for DRM to Address These Barriers. However, There is a Dearth of Works that Address Multiple Heterogeneous Drones Collaboratively Working Together to Form a Flying Ad-Hoc Network (FANET) with Air-To-Air and Air-To-Ground Links that Are Impacted By: (I) Environmental Obstacles, (Ii) Wind, and (Iii) Limited Battery Capacities. in This Paper, We Present a Novel Environmentally-Aware and Energy-Efficient Multi-Drone Coordination and Networking Scheme that Features a Reinforcement Learning (RL) based Location Prediction …

A Method Of Loose Coupling Entity Modeling Based On Variable Rules, Zheng Yang, Zhimin Xiang, Shiwen Ma

Journal of System Simulation

Abstract: Operational Entity Modeling is a hot research topic in the field of combat simulation. A loose coupling entity modeling method based on variable rules is proposed. The architecture of operational entity model based on variable rules and the internal and external interaction mechanism of the model are presented in terms of entity, mission, action, interaction, event and rule. On this basis, the running framework of operational entity model is designed, and the entity model uniform scheduling mechanism is standardized, which solves the problems of over-tight coupling of operational rules in the operational entity model and low reliability of the …

Parametric And Reliability Estimation Of The Kumaraswamy Generalized Distribution Based On Record Values, Mohd. Arshad, Qazi J. Azhad

Journal of Modern Applied Statistical Methods

A general family of distributions, namely Kumaraswamy generalized family of (Kw-G) distribution, is considered for estimation of the unknown parameters and reliability function based on record data from Kw-G distribution. The maximum likelihood estimators (MLEs) are derived for unknown parameters and reliability function, along with its confidence intervals. A Bayesian study is carried out under symmetric and asymmetric loss functions in order to find the Bayes estimators for unknown parameters and reliability function. Future record values are predicted using Bayesian approach and non Bayesian approach, based on numerical examples and a monte carlo simulation.

(R1239) A New Type Ii Half Logistic-G Family Of Distributions With Properties, Regression Models, System Reliability And Applications, Emrah Altun, Morad Alizadeh, Haitham M. Yousof, Mahdi Rasekhi, G. G. Hamedani

Applications and Applied Mathematics: An International Journal (AAM)

This study proposes a new family of distributions based on the half logistic distribution. With the new family, the baseline distributions gain flexibility through additional shape parameters. The important statistical properties of the proposed family are derived. A new generalization of the Weibull distribution is used to introduce a location-scale regression model for the censored response variable. The utility of the introduced models is demonstrated in survival analysis and estimation of the system reliability. Three data sets are analyzed. According to the empirical results, it is observed that the proposed family gives better results than other existing models.

Trustworthy Medical Segmentation With Uncertainty Estimation, Giuseppina Carannante, Dimah Dera, Nidhal C. Bouaynaya, Rasool Ghulam, Hassan M. Fathallah-Shaykh

Computer Science Faculty Publications and Presentations

Deep Learning (DL) holds great promise in reshaping the healthcare systems given its precision, efficiency, and objectivity. However, the brittleness of DL models to noisy and out-of-distribution inputs is ailing their deployment in the clinic. Most systems produce point estimates without further information about model uncertainty or confidence. This paper introduces a new Bayesian deep learning framework for uncertainty quantification in segmentation neural networks, specifically encoder-decoder architectures. The proposed framework uses the first-order Taylor series approximation to propagate and learn the first two moments (mean and covariance) of the distribution of the model parameters given the training data by maximizing …

Gp3: Gaussian Process Path Planning For Reliable Shortest Path In Transportation Networks, Hongliang Guo, Xuejie Hou, Zhiguang Cao, Jie Zhang

Research Collection School Of Computing and Information Systems

This paper investigates the reliable shortest path (RSP) problem in Gaussian process (GP) regulated transportation networks. Specifically, the RSP problem that we are targeting at is to minimize the (weighted) linear combination of mean and standard deviation of the path's travel time. With the reasonable assumption that the travel times of the underlying transportation network follow a multi-variate Gaussian distribution, we propose a Gaussian process path planning (GP3) algorithm to calculate the a priori optimal path as the RSP solution. With a series of equivalent RSP problem transformations, we are able to reach a polynomial time complexity algorithm with guaranteed …

Characterizations And Reliability Measures Of The Generalized Log Burr Xii Distribution, Fiaz Ahmad Bhatti, Gholamhossein G. Hamedani, Azeem Ali, Sedigheh Mirzaei Salehabadi, Munir Ahmad

Mathematical and Statistical Science Faculty Research and Publications

In this paper, we derive the generalized log Burr XII (GLBXII) distribution [2] from the generalized Burr-Hatke differential equation. We characterize the GLBXII distribution via innovative techniques. We derive various reliability measures (series and parallel). We also authenticate the potentiality of the GLBXII model via economics applications. The applications of characterizations and reliability measures of the GLBXII distribution in different disciplines of science will be profitable for scientists.

Construct Validity And Invariance Assessment Of The Social Impacts Of Occupational Heat Stress Scale (Siohss) Among Ghanaian Mining Workers, Victor F. Nunfam, Ebenezer Afrifa-Yamoah, Kwadwo Adusei-Asante, Eddie J. Van Etten, Kwasi Frimpong, Isaac Adjei-Mensah, Jacques Oosthuizen

Research outputs 2014 to 2021

Heat exposure studies over the last decade have shown little attention in assessing and reporting the psychometric properties of the various scales used to measure impacts of occupational heat stress on workers. A descriptive cross-sectional survey including 320 small- and large-scale mining workers was employed to assess the construct validity of the social impacts of occupational heat stress scale (SIOHSS) in the Western Region of Ghana in 2017. A confirmatory factor analysis (CFA) and invariance analysis were carried out using AMOS version 25 and statistical product and service solutions (SPSS) version 26 to examine the model fit and establish consistency …

Computational Design Of Nonlinear Stress-Strain Of Isotropic Materials, Askhad M.Polatov, Akhmat M. Ikramov, Daniyarbek Razmukhamedov

Chemical Technology, Control and Management

The article deals with the problems of numerical modeling of nonlinear physical processes of the stress-strain state of structural elements. An elastoplastic medium of a homogeneous solid material is investigated. The results of computational experiments on the study of the process of physically nonlinear deformation of isotropic elements of three-dimensional structures with a system of one- and double-periodic spherical cavities under uniaxial compression are presented. The influence and mutual influence of stress concentrators in the form of spherical cavities, vertically located two cavities and a horizontally located system of two cavities on the deformation of the structure are investigated. Numerical …

Estimating The Reliability Of A Component Between Two Stresses From Gompertz-Frechet Model, Sarah Adnan Jabr, Nada Sabah Karam

Al-Qadisiyah Journal of Pure Science

In this paper, the reliability of the stress-strength model is derived for probability P(

Ft-Cnn: Algorithm-Based Fault Tolerance For Convolutional Neural Networks, Kai Zhao, Sheng Di, Sihuan Li, Xin Liang, For Full List Of Authors, See Publisher's Website.

Computer Science Faculty Research & Creative Works

Convolutional neural networks (CNNs) are becoming more and more important for solving challenging and critical problems in many fields. CNN inference applications have been deployed in safety-critical systems, which may suffer from soft errors caused by high-energy particles, high temperature, or abnormal voltage. Of critical importance is ensuring the stability of the CNN inference process against soft errors. Traditional fault tolerance methods are not suitable for CNN inference because error-correcting code is unable to protect computational components, instruction duplication techniques incur high overhead, and existing algorithm-based fault tolerance (ABFT) techniques cannot protect all convolution implementations. In this paper, we focus …

Deep Unsupervised Anomaly Detection, Tangqing Li, Zheng Wang, Siying Liu, Wen-Yan Lin

Research Collection School Of Computing and Information Systems

This paper proposes a novel method to detect anomalies in large datasets under a fully unsupervised setting. The key idea behind our algorithm is to learn the representation underlying normal data. To this end, we leverage the latest clustering technique suitable for handling high dimensional data. This hypothesis provides a reliable starting point for normal data selection. We train an autoencoder from the normal data subset, and iterate between hypothesizing normal candidate subset based on clustering and representation learning. The reconstruction error from the learned autoencoder serves as a scoring function to assess the normality of the data. Experimental results …

A New Method For Optimal Expansion Planning In Electrical Energy Distributionnetworks With Distributed Generation Resources Considering Uncertainties, Amir Masoud Mohaghegh, S Yaser Derakhshandeh, Abbas Kargar

Turkish Journal of Electrical Engineering and Computer Sciences

The present study aims to introduce a robust model for distribution network expansion planning considering system uncertainties. The proposed method determines optimal size and placement of distributed generation resources, as well as installation and reinforcement of feeders and substations. This model is designed to minimize cost and to determine the best time for the installation of equipment in the expansion planning. In the proposed expansion planning, the fuzzy logic theory is employed to model uncertainties of loads and energy price. Also, since the proposed model is a nonlinear and nonconvex optimization problem, a tri-stage algorithm is developed to solve it. …

The Odd Inverse Rayleigh Family Of Distributions: Simulation & Application To Real Data, Saeed E. Hemeda, Muhammad A. Ul Haq

Applications and Applied Mathematics: An International Journal (AAM)

A new family of inverse probability distributions named inverse Rayleigh family is introduced to generate many continuous distributions. The shapes of probability density and hazard rate functions are investigated. Some Statistical measures of the new generator including moments, quantile and generating functions, entropy measures and order statistics are derived. The Estimation of the model parameters is performed by the maximum likelihood estimation method. Furthermore, a simulation study is used to estimate the parameters of one of the members of the new family. The data application shows that the new family models can be useful to provide better fits than other …

Evaluation Of Reliability Indicators Of Mobile Communication System Bases, Dilmurod Davronbekov, Utkir Karimovich Matyokubov, Malika Ilkhamovna Abdullayeva

Bulletin of TUIT: Management and Communication Technologies

In this study, the reliability of mobile system base stations (BTS) is assessed by analyzing data obtained on faults in about 200 BTS over a six-month period. Five BTSs with the highest number of failures and duration of failure were selected in these BTSs. Based on the data obtained, reliability parameters were calculated and compared.

The study used Weibull’s dismissal process distribution method. The breakdown times of each BTS were sorted. In all five BTS, it was found that β(where the value of β is the approximate value obtained from the values of the smallest squares of the Weibull graph), …