Digital Commons Network^™

Bitcoin Bubbles And A Monetary Measure Of Fundamental Value, Paul Hallwood

Pennsylvania Economic Review

Several papers estimate the time series properties of bitcoin prices. However, to know that bubbles occur, an estimate of fundamental value is needed. Few estimates of bitcoin’s fundamental price exist, and these are either statistical in nature or based on questionable economic theory. This paper calculates the non-bubble dollar price of bitcoin using a modification to the quantity theory of money, and it is estimated to be about $54.00. At the November 2021 peak market price of bitcoin, the bubble component was more than 99%. Even at end-August 2023 after bitcoin prices had more than halved, the bubble component was …

Detecting Arabic Misinformation Using An Attention Mechanism-Based Model, Bashar M. Nema, Mohammed Haqqi Al-Tai

Iraqi Journal for Computer Science and Mathematics

The proliferation of fake news or misinformation, commonly referred to as fake news, has a significant effect on a global scale, as it is aimed at influencing public opinion as well as crowd decision-making. It istherefore crucial to verifythe truthfulness of news before it is released to the public. Today, most studies on early detection of Arabic misinformation rely on machine learning methods and transformer-based models. Therefore, in the current study, we used deep learning techniques to propose a model for detecting Arabic misinformation by leveraging the contextual features of news article content. The proposed model was built based on …

Piecing Together Performance: Collaborative, Participatory Research-Through-Design For Better Diversity In Games, Daniel L. Gardner, Louanne Boyd, Reginald T. Gardner

Engineering Faculty Articles and Research

Digital games are a multi-billion-dollar industry whose production and consumption extend globally. Representation in games is an increasingly important topic. As those who create and consume the medium grow ever more diverse, it is essential that player or user-experience research, usability, and any consideration of how people interface with their technology is exercised through inclusive and intersectional lenses. Previous research has identified how character configuration interfaces preface white-male defaults [39, 40, 67]. This study relies on 1-on-1 play-interviews where diverse participants attempt to create “themselves” in a series of games and on group design activities to explore how participants may …

Methods For Achieving A Target Joint Preload, Daniel P. Hess

USF Patents

A method for achieving a target joint preload includes identifying a thread pitch of a first fastener element used to secure two components together. The first fastener element is passed through the two components and a second fastener element is threaded onto the first fastener element. A tightening torque is applied to the second fastener element, which is measured as the trial tightening torque. A loosening torque is applied to the second fastener element, which is measured as the trial removal torque. A required tightening torque that is required to be applied to the second fastener element to achieve the …

Attochemistry Regulation Of Charge Migration, Aderonke Folorunso

LSU Doctoral Dissertations

Charge migration (CM) is a coherent attosecond process that involves the movement of localized holes across a molecule. This phenomenon is potentially useful to understand the fundamental principles of photochemistry, such as light harvesting. The first part of this dissertation discusses the molecular modes of attosecond charge migration. In this work, we used first-principles calculations to investigate the modes of charge migration (CM) in halogenated hydrocarbon chains at attosecond timescales. We have simulated the creation of a localized hole on the halogen atom using constrained density functional theory (DFT) and then tracked its subsequent dynamics with time-dependent DFT (TDDFT). Our …

Offline Handwritten Signature Identification Based On Hybrid Features And Proposed Deep Model, Zainab Hashim, Hanaa Mohsin, Ahmed Alkhayyat

Iraqi Journal for Computer Science and Mathematics

Handwritten signature identification is the process of determining an individual’strue identity by analyzing their signature. This is an important task in various applications such as financial transactions, legal documentverification, and biometric systems. However, verifying handwritten signatures is challenging even in the age of digital transactions and remote document authentication. The inherent variety in people’s signatures, which may occurdue to factors such as mood, exhaustion, or even the writing tool used, contributes to the problem. Furthermore, the proliferation of sophisticated forgery methods, such as freehand mimicking and sophisticated picture manipulation, necessitates the development of reliable and precise tools for identifying authentic …

Inpatient Costs Of Treating Patients With Covid-19, Kandice A Kapinos, Richard M Peters, Robert E Murphy, Samuel F Hohmann, Ankita Podichetty, Raymond S Greenberg

Faculty, Staff and Student Publications

IMPORTANCE: With more than 6.2 million hospitalizations due to COVID-19 in the US, recognition of the average hospital costs to provide inpatient care during the pandemic is necessary to understanding the national medical resource use and improving public health readiness and related policies.

OBJECTIVE: To examine the mean cost to provide inpatient care to treat COVID-19 and how it varied through the pandemic waves and by important sociodemographic patient characteristics.

DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used inpatient-level data from March 1, 2020, to March 31, 2022, extracted from a repository of clinical, administrative, and financial information covering 97% …

Robust 6d Fluorescence Microscopy, Jasmine Cheng

Electrical and Systems Engineering Undergraduate Student Research

Single-Molecule Orientation Localization Microscopy (SMOLM) measures the positions and orientations of single fluorophores precisely, approaching fundamental classical and quantum limits. However, a disadvantage of SMOLM is the time-consuming nature of its acquisition and reconstruction processes. In my thesis, I introduce an innovative framework that simplifies the detection and estimation algorithms used in SMOLM into a computationally efficient high-dimensional deconvolution algorithm. This framework extracts six-dimensional information of continuous biological structures from just a single camera image (i.e., a single shot). While this method is diffraction limited, unlike conventional SMOLM algorithms, it nevertheless offers accurate and precise estimations of the orientations of …

Estimating The Cholesterol Affinity Of Integral Membrane Proteins From Experimental Data, Theodore L. Steck, S. M. Ali Tabei, Yvonne Lange

Faculty Publications

The cholesterol affinities of many integral plasma membrane proteins have been estimated by molecular computation. However, these values lack experimental confirmation. We therefore developed a simple mathematical model to extract sterol affinity constants and stoichiometries from published isotherms for the dependence of the activity of such proteins on the membrane cholesterol concentration. The binding curves for these proteins are sigmoidal, with strongly lagged thresholds attributable to competition for the cholesterol by bilayer phospholipids. The model provided isotherms that matched the experimental data using published values for the sterol association constants and stoichiometries of the phospholipids. Three oligomeric transporters were found …

A Review Of Machine Learning Techniques Utilised In Self-Driving Cars, Zahraa Salah Dhaif, Nidhal K. El Abbadi

Iraqi Journal for Computer Science and Mathematics

Science and technology researchers are currently focused on the creationof self-driving cars. This can havea profound effect on social and economic progress;self-driving vehicles can help reduce auto accidents dramatically and enhance the quality of life of people the world over. Self-driving cars have had a tremendous increase in popularity in the recent past because of artificial intelligence development. However, there is a lot of research work to be done to manufacture fully-automated cars becausea self-driving carshas tto be able to sense its environment and operate without human involvement. A human passenger is not required to take control of the vehicle …

Multi-Strategy Fusion Forenhancinglocalization In Wireless Sensor Networks (Wsns), Mahdi Abed Salman, Muhammed Abaid Mahdi

Iraqi Journal for Computer Science and Mathematics

Localization in wireless sensor networks (WSNs) plays a crucial role in various applications that rely on spatial information. This paper introduces the Multi-Strategy Fusion for Localization model, which integrates optimization techniques (ABO, DSA, EHO, and KNN) and neurocomputing techniques (BP, MTLSTM, BILSTM, and Autoencoder) to enhance localization accuracy in WSNs. The work is divided into three phases: data collection, model building, and implementation. The first and the last are carriedoutin the field,while the second is made in the laboratory. The three phases involve a few general steps.The (1) Data Collection Phase includesfour steps:(a) Deploy three anchors at known locations,forming an …

Early Detection Of Cardiovascular Disease Utilizing Machine Learning Techniques: Evaluating The Predictive Capabilities Of Seven Algorithms, Maad M. Mijwil, Alaa K. Faieq, Mohammad Aljanabi

Iraqi Journal for Computer Science and Mathematics

Heart disease is the leading cause of death indeveloped countries, as it causes many deaths annually. Despite the availability of effective treatments, heartdisease remains a significant challenge to public health, so early detection is essential in enhancing patient outcomesand reducing mortality.Artificial intelligence seeks to help physicians make the right decisions about a patient's health condition. In this regard, the authors decided to utilize machine learning techniques (k-nearest neighbor, decision tree, linear regression, support vector machine, naïve bayes, multilayer perceptron, random forest) to contribute to the classification of the heart disease dataset, where it is determined whether a person is suffering …

The Optimal Scaling Factor Based On Secantmethod For Imagewatermarkingusing The Hybrid Dtcwt-Dct Domain, Mohamed Lebcir, Suryanti Awang, Ali Benziane

Iraqi Journal for Computer Science and Mathematics

This paper proposes an implementation of the secant optimization method on the watermark embedding in DTCWTdomain. An objective function combining PSNR and NC (The Normalized Correlation) values calculated for a set of common attacks is used in the optimization process. The aim is to enhance the trade-off between robustness and imperceptibility against the various image processing attacks via an automatic and careful selectionof the scalingfactor using optimization. The watermark is inserted in the high energy bands ofDCT-transformed sub-vectors, which were generated from the DTCWT coefficient decomposition of the host image. Experimental results performed on a set of 512×512 greyscale images, …

Enhancing The Zebra Optimization Algorithm With Chaotic Sinusoidal Map For Versatile Optimization, D Anand, Osamah Ibrahim Khalaf, G Rajesh Chandra

Iraqi Journal for Computer Science and Mathematics

In this study, the Chaotic Sinusoidal Map (CSM)-enhanced Zebra Optimization Algorithm (CZOA) is introduced. CZOA combines CSM's integration strengths with ZOA's optimization skills. ZOA already exhibits great optimization capabilities, but the addition of CSM increases its potential even more. This addition greatly strengthens ZOA's exploration and exploitation skills and increases its flexibility for various optimization tasks. CZOA outperforms both the original ZOA and contemporary optimisation methods on23 benchmark functions, including high-dimensional (FD), multimodal (MM), and unimodal (UM) challenges. Using the chaos of CSM to investigate regional optimal and determine better convergence and exploration-exploitation equilibrium are shown by CZOA, which also …

A Novel Method For Hill Cipher Encryption And Decryption Using Gaussian Integers Implemented Inbanking Systems, Saba Abdulbaqi Salman, Yasmin Makki Mohialden, Abbas Abdulhameed, Nadia Mahmood Hussien

Iraqi Journal for Computer Science and Mathematics

Cryptographic tools like Hill's encryption algorithm protect digital data. In this work, we present a novel Hill cipher security method that utilizes Gaussian integers from number theory. Using these intriguing mathematical entities to disguise plaintext values dramatically boosts assault resistance and duration.This research includes a three-pass protocol for encryption and decryption without key exchange, ensuring a safe, efficient, and dependable solution. Pandas is used for efficient data processing, and Numpy for computational tasks, notablymatrices.Hill cipher-based encryption and decryption can be utilized in real life. It also demonstrates how to save Pandas DataFrame data to Excel. This strategy assures progress in …

An Automated Prostate-Cancer Prediction System (Apps) Based On Advanced Dfo-Conga2l Model Using Mri Imaging Technique, E Sathesh Abraham Leo, K Nattar Kannan

Iraqi Journal for Computer Science and Mathematics

The prostate cancer is a deadly form of cancer that assassinates a significant number ofmen due of its mediocre identification process. Images from people with cancer include important and intricate details that are difficult for conventional diagnostic methods to extract.This work establishes a novel Automated Prostate-cancer Prediction System (APPS) model for the goal of detecting and classifying prostate cancer utilizing MRI imaging sequences. The supplied medical image is normalized using aCoherence Diffusion Filtering (CDFilter) approach for improved quality and contrast. The appropriate properties are also extracted from the normalized image using the morphological and texture feature extraction approach, which helps …

Physical Activity And Its Association With Academic Performance Among Malaysian Adolescents, Vinura Venugopal

Student Works (2020-2029)

The rates of physical inactivity among adolescents have been increasing yearly. Physical activity can reduce the risk of diseases, help manage weight, improve brain health, and ensure healthy growth and development. Besides these benefits, physical activity has also been linked to better academic achievement in certain studies. This study examines the relationship between physical activity and academic performance (national-based examinations) among adolescents in Malaysia. It was also designed to identify a feasible standardised physical activity programme. Methods: This is a multimethod study. The first phase is a prospective closed cohort study using data from 579 students from the Malaysian Health …

Illinois State University Salaries Fy2024, Illinois State University

Illinois State University Salaries

Includes two sections: administrative professional and civil service salaries, and non-tenure track, tenure track, and faculty associate salaries.

A Critical Reflection On The Importance Of Education For Sustainable Development, Daniel Kamphambale, Lucia Morales, Cormac H. Macmahon, Jon-Hans Coetzer

Irish Journal of Academic Practice

The United Nations (UN) 2030 Agenda and Sustainable Development highlights the value of the Sustainable Development Goals (SDGs) in enabling societal progress. Contemporary society needs to consider sustainable development in a broader context where equity, diversity, and inclusion are integral to design of educational systems. Education can act as a disruptor that brings change to existing economic growth models misaligned with the needs and demands of modern society. As we transition to economic models that are more attuned to the needs of global society and planet, access to education, natural resources, and human talent is crucial for sustaining development, and …

Development Of A Smart Hybrid Drive System With Advanced Logistics For Railway Applications, Tamer Kamel, Peter Amor, Nursaid Polater, Yizhe Zhang, Zhongbei Tian, Stuart Hillmansen, Pietro Tricoli

School of Engineering, Computing and Mathematics

Fuel Hydrogen cells become nowadays a major candidate to replace the diesel in powering the traction locomotives since they offer low emission of pollutant gases, high efficiency, and flexible modular structure without the need for installation of electrification infrastructure for railway networks. However, they cannot respond appropriately to the fast load transients due to their slow internal electrochemical and thermodynamic responses. Therefore, they shall be integrated with fast dynamics Li-ion battery cells to form a hybrid power source for traction systems. Accordingly, this paper presents a development of a new smart integrated power source of fuel hydrogen and Li-ion battery …

Innovative Cyanine-Based Fluorescent Dye For Targeted Mitochondrial Imaging And Its Utility In Whole-Brain Visualization, Xin Yan, Xinqian Chen, Zhiying Shan, Lanrong Bi

Michigan Tech Publications

Conducting in vivo brain imaging can be a challenging task due to the complexity of brain tissue and the strict requirements for safe and effective imaging agents. However, a new fluorescent dye called Cy5-PEG2 has been developed that selectively accumulates in mitochondria, enabling the visualization of these essential organelles in various cell lines. This dye is versatile and can be used for the real-time monitoring of mitochondrial dynamics in living cells. Moreover, it can cross the blood-brain barrier, making it a promising tool for noninvasive in vivo brain imaging. Based on the assessment of glial cell responses in the hippocampus …

Novel Techniques In Imaging Congenital Heart Disease: Jacc Scientific Statement, Ritu Sachdeva, Aimee K Armstrong, Rima Arnaout, Lars Grosse-Wortmann, B Kelly Han, Luc Mertens, Ryan A Moore, Laura J Olivieri, Anitha Parthiban, Andrew J Powell

Faculty, Staff and Students Publications

Recent years have witnessed exponential growth in cardiac imaging technologies, allowing better visualization of complex cardiac anatomy and improved assessment of physiology. These advances have become increasingly important as more complex surgical and catheter-based procedures are evolving to address the needs of a growing congenital heart disease population. This state-of-the-art review presents advances in echocardiography, cardiac magnetic resonance, cardiac computed tomography, invasive angiography, 3-dimensional modeling, and digital twin technology. The paper also highlights the integration of artificial intelligence with imaging technology. While some techniques are in their infancy and need further refinement, others have found their way into clinical workflow …

Subnational Probabilistic Projections Of Fertility: Rethinking From Latin America, Lucia Andreozzi

Journal of Demography

General trends in fertility, mortality, and migration can be discerned and projected into the future with reasonable results, however, there is considerable uncertainty attached to each specific trend from a particular country or region. Then, subnational projections then represent a special chapter within the demographic projections. After introducing subnational projections and its close relationship with the fertility, this work proposes as the main objective to project fertility rates at the subnational level for Argentina using a probabilistic method; the bayesian hierarchical model (BHM), and then compare the results with the point estimates of deterministic projections published by the national organism …

The Valuation Of Exit Option In A Lignite Mine Using Monte Carlo Simulation, Marcin Pawlak, Tomasz Wiśniewski

Journal of Sustainable Mining

This study aims to demonstrate the application of simulation techniques to the valuation of real options. The nature of the paper is methodological and empirical. The purpose of the valuation of the option to close a lignite mine in Poland is to demonstrate the methodology and advantages of employing Monte Carlo simulation in the valuation of real options. Close to actual numerical data reveals a complex optimization problem in the context of strategy selection by decision-makers. Numerous factors (extraction costs, reclamation costs, the write-off for the reclamation fund, etc.), their interpenetration and multilevel influence on the decision to close the …

Mathematical Model For The Management Of The Wave Processes In Three-Winding Transformers With Consideration Of The Main Magnetic Flux In Mining Industry, M. S. Seheda, O. S. Beshta, P. F. Gogolyuk, Yu. V. Blyznak, R. D. Dychkovskyi, A. Smoliński

Journal of Sustainable Mining

The aim of the work is to study the wave processes in three-winding power transformers caused by impulse overvoltage, to create an improved mathematical model for reproducing the process of distribution and transmission of the impulse in the windings of a three-winding power transformer. A mathematical model has been developed for the study of internal overvoltage in the windings of three-winding power transformers, based on the proposed substitute circuit of an infinitesimal element, taking into account the longitudinal and transverse inductive connections between the turns of the winding, the electromagnetic connections between the windings and the flux splitting from the …

The Effect Of Blasting Using Low-Density Emulsion Explosives, Vinko Škrlec, Mario Dobrilović, Barbara Štimac Tumara, Vječislav Bohanek

Journal of Sustainable Mining

Low-density emulsion explosives are essentially blends of an emulsion matrix and a certain amount of gaseous phase inclusions acting as hot spots. With the addition of expanded polystyrene for gaseous sensibilization, the resulting explosive blend was developed to reduce peak values and pressure impulse of gaseous detonation products on surrounding rock. This resulted in a decrease in rock stress and a decrease in cracking zone width outside of the minefield boundary. The use of low-density emulsion explosives correlates with the decrease in the seismic effect of blasting, more precisely, the decrease of induced rock oscillation velocities. The low-density emulsion explosive …

Numerical Simulation On Effect Of Coal Pillar Width On Stability Of Retained Roadway: A Case Study Of Khe Cham Coal Mine, Vietnam, Quang Phuc Le, Tien Dung Le

Journal of Sustainable Mining

When extracting coal seams in Vietnam underground mines, coal pillars are often left unmined for the protection of retained roadways in the longwall mining method. During longwall mining operations, coal pillars are often placed where high-stress concentrations occur in the abutment pressure zone of adjacent panels, especially when extracting seams under hard-to-cave main roof conditions. The instability of coal pillars under the loading of the main roof may cause the roadway to collapse, threatening the safe operation of a coal mine. This paper presents a detailed numerical investigation of the effect of coal pillar width on the stability of retained …

Assessing Compliance To Water Resources And Reconstruction Framework During Post-Conflict Reconstruction Borno State, Muritala Olaniyi Oke Dr

Journal of African Conflicts and Peace Studies

Northeast and northwest of Nigeria have, as a result of activities of Boko Haram, bandit and kidnappers, had their public and private properties destroyed. Governments and other stakeholders, upon some successes of the military, have started post-conflict reconstruction to rebuild the war-torn urban and rural communities with the provision of water taking the center stage. This paper looks at the utilisation of Water Resources and a Reconstruction framework for integrating water projects into reconstruction processes. This paper rests on the argument that water projects during reconstruction should not be handled as “normal” water projects and that a more culturally and …

Mcdonald Generalized Power Weibull Distribution: Properties, And Applications, Shei B. Sayibu, A. Luguterah, A. Luguterah, S. Nasiru

Journal of Statistics Applications & Probability

This research introduces a novel six-parameter model called the McDonald Generalized Power Weibull distribution. The model contains several sub-models that prove highly valuable in modeling real-life scenarios, including the McDonald Weibull, McDonald exponential, McDonald Nadarajah-Haghighi, beta generalized power Weibull distribution, and Kumaraswamy generalized power distributions, among others. The proposed model demonstrates suitability in modeling survival/reliability data, accommodating various hazard failure rates such as increasing, decreasing, unimodal (upside-down bathtub), modified bathtub, and reversed J-shape. Various properties of the new model are investigated, including moments, quantiles, incomplete moments, moment-generating functions, and order statistics. The maximum likelihood estimation method is employed to estimate …

Bell-Touchard-G Family Of Distributions: Applications To Quality Control And Actuarial Data, Muhammad Imran, John T Mendy

Journal of Statistics Applications & Probability

In this article, we developed a new statistical model named as the generalized complementary exponentiated Bell-Touchard model. The exponential model is taken as a special baseline model with a configurable failure rate function. The proposed model is based on several features of zero-truncated Bell numbers and Touchard polynomials that can address the complementary risk matters. The linear representation of the density of the proposed model is provided that can be used to obtain numerous important properties of the special model. The well-known actuarial metrics namely value at risk and expected shortfall are formulated, computed and graphically illustrated for the sub …