Digital Communications and Networking Commons^™

Forecasting Economic Growth And Movements With Wavelet Transform And Arima Model, Omar Alsinglawi, Omar Alsinglawi, Mohammad Aladwan, Mohammad Aladwan, Saddam Alwadi, Saddam Alwadi

Applied Mathematics & Information Sciences

This study uses historical data and modern statistical models to forecast future Gross Domestic Product (GDP) in Jordan. The Wavelet Transformation model (WT) and Autoregressive Integrated Moving Average (ARIMA) model were applied to the time series data and yielded a best-fitting result of (2,1,1) for estimating GDP between 2022-2031. The study concludes that GDP is expected to increase with a positive growth rate of around 3.22%, and recommends government agencies to monitor GDP, strengthen existing policies, and adopt necessary economic reforms to support growth. Additionally, the private sector is encouraged to enhance production tools to achieve economic growth that benefits …

Neutrosophic Adaptive Lsb And Deep Learning Hybrid Framework For Ecg Signal Classification, Abdallah Rezk, Ahmed S. Sakr, H. M. Abdulkader

Applied Mathematics & Information Sciences

This paper proposes a novel hybrid framework for ECG signal classification and privacy preservation. The framework includes two phases: the first phase uses LSTM+CNN with attention gate for ECG classification, while the second phase utilizes adaptive least signal bit with neutrosophic for hiding important data during transmission. The proposed framework converts data into three sets of degrees (true, false, and intermediate) using neutrosophic and passes them to an embedding layer. In the sender part, the framework hides important data in ECG signal as true and false degrees, using the intermediate set as a shared dynamic key between sender and receiver. …

Compatibility Of Clique Clustering Algorithm With Dimensionality Reduction, Ug ̆Ur Madran, Duygu Soyog ̆Lu

Applied Mathematics & Information Sciences

In our previous work, we introduced a clustering algorithm based on clique formation. Cliques, the obtained clusters, are constructed by choosing the most dense complete subgraphs by using similarity values between instances. The clique algorithm successfully reduces the number of instances in a data set without substantially changing the accuracy rate. In this current work, we focused on reducing the number of features. For this purpose, the effect of the clique clustering algorithm on dimensionality reduction has been analyzed. We propose a novel algorithm for support vector machine classification by combining these two techniques and applying different strategies by differentiating …

The Influence Of Supply Chain Management Strategies On Organizational Performance In Hospitality Industry, Omar Jawabreh, Abdullah Mahfoud Baadhem, Basel J. A. Ali, Anas Ahmad Bani Atta, Anis Ali, Fahmi Fadhl Al- Hosaini

Applied Mathematics & Information Sciences

The studys primary goal is to analyze the connection between SCM practices and organizational performance, and it also aims to evaluate the moderating role of management type. Quantitative data collected from Jordans hotel and restaurant workers via questionnaire. Structural equation modeling is used to examine the hypothesized relationships. Organizational Performance is positively impacted by effective information sharing. Information Quality (IQ) positively affects Organizational Performance (OP), and Strategic Supplier Partnerships (SSP) play a crucial role. Customer Relationship Management (CRM) had no discernible effect on OP, according to the study. OP is positively impacted by Postponement (POS) techniques. When implemented, postponement increases …

The Effect Of System Quality And User Quality Of Information Technology On Internal Audit Effectiveness In Jordan, And The Moderating Effect Of Management Support, Ahmad Yahiya Ahmad Bani Ahmad (Ayassrah), Anas Ahmad Mahmoud Bani Atta, Hanan Ali Alawawdeh, Nawaf Abdallah Aljundi, Amer Morshed, Saleh Amin Dahbour

Applied Mathematics & Information Sciences

The goal of this study is to ascertain the moderating role that management support has in internal audit effectiveness in Jordan, as well as the impact of system quality and user quality of information technology. There were 172 responders in all, and they were split across Jordanian auditors. In the data analysis process, the quantitative analysis test— which consists of the validity test, reliability test, test of conventional assumptions, and hypothesis test—is applied. Information technology system and user quality are independent variables in this study. The dependent variable in this study is internal audit effectiveness, and the moderating variable is …

Optimal Control Analysis Of The Dynamics Of Covid-19 With Application To Ethiopian Data, Temesgen Duresa Keno, Fekadu Mosisa Legesse, Ebisa Olana Bajira

Applied Mathematics & Information Sciences

In this paper, we proposed an optimal control of the COVID-19 transmission dynamics. First, we investigated system features such as solution boundedness, positivity, disease-free and endemic equilibrium, and the local and global stability of equilibrium points. Besides, a disease-free equilibrium point is globally asymptotically stable if the basic reproduction number is less than one, and an endemic equilibrium point exists otherwise. Secondly, we have shown the sensitivity analysis of the basic reproduction number. Also the model is then fitted using COVID-19 infected reported in Ethiopia from February 1,2023 to March 2,2023. The values of model parameters are then estimated from …

Nexus Between Intellectual Capital And Financial Performance Sustainability: Evidence From Listed Jordanian Firms, Ali M. Alrabei, Leqaa N. Al-Othman, Thaer A. Abutaber, Mustafa S. Alathamneh, Tareq M. Almomani, Mohammed H. Qeshta

Applied Mathematics & Information Sciences

Purpose: The authors observe the effect of exploring the reality of Intellectual Capital (IC) and its impact on the financial performance of Jordanian industrial firms in Amman Stock Exchange. This empirical research explores the effect of intellectual capital on financial performance using data from 36 Jordanian industrial firms listed in Amman Stock Exchange for the period 2016-2020. The Value-Added Intellectual coefficient (VAIC) was adopted to measure the intellectual capital, while the return on assets (ROA), return on equity (ROE), and earnings per share (EPS) were adopted as measures of the companys financial performance. The effect of IC was tested by …

Assessing The Moderating Effect Of Innovation On The Relationship Between Information Technology And Supply Chain Management: An Empirical Examination, Heba Hatamlah, Mahmoud Allahham, Ibrahim A. Abu-Alsondos, Alaa S. Mushtaha, Ghadeer M. Al-Anati, Mustafa Al-Shaikh

Applied Mathematics & Information Sciences

This study examines how innovation (INN) influences the relationship between supply chain management and information technology in Jordan. 211 employees of Jordanian industrial enterprises who work in the Operations Department provided information for the study, which examines this subject. The findings indicate a close connection between information technology and supply chain management. Innovation also dramatically modifies the interaction between supply chain management and information technology. Management help may be the subject of future research.

The Role Of Business Intelligence Adoption As A Mediator Of Big Data Analytics In The Management Of Outsourced Reverse Supply Chain Operations, Heba Hatamlah, Mahmoud Allahham, Ibrahim A. Abu-Alsondos, Alaa Al-Junaidi, Ghadeer M. Al-Anati, Mustafa Al-Shaikh

Applied Mathematics & Information Sciences

The fluctuating and disorganized state of todays global markets is the result of several factors. COVID-19 is an illustration. Supply chain managers should re-evaluate their competitive strategy and leverage big data analytics in light of the rising volatility in demand and supply, rivalry among supply chain partners, and the requirement to deliver tailored goods and services (BDA). Supply chain firms require sophisticated BDA processes and procedures to provide useful insights from big data to better decision-making and supply chain operations, as many leaders in the sector have acknowledged the necessity for improving with data" (SCO). This research gives theoretical justification …

The Artificial Intelligence As A Decision-Making Instrument For Modeling And Predicting Small Cities’ Attractiveness: Evidence From Morocco, Sohaib Khalid, Driss Effina, Khaoula Rihab Khalid, Mohamed Salem Chaabane

Applied Mathematics & Information Sciences

This study analyzes residential attractiveness in small Moroccan cities using statistical models. Net migration rates are commonly used to assess attractiveness. The study estimated net migration rates for each city and employed a structural econometric model with logistic regression to identify influential variables that affect the net migration rate. These variables were then used in a predictive model with an artificial neural network algorithm. The logistic model revealed insights, highlighting the complexity of residential attractiveness influenced by factors like job supply, accessibility, and housing conditions. The artificial neural network model provided accurate predictions (over 80%), aiding policymakers in decision-making and …

Improving The Performance Of A Series-Parallel System Based On Lindley Distribution, Abdelfattah Mustafa, M. I. Khan, Maher. A. Alraddadi

Applied Mathematics & Information Sciences

In this article, the performance of a series-parallel system is improved. The system components are assumed to follows independently and identically Lindley distributed with three parameters. The system reliability for the given system will be improved by using reduction method, hot, cold and imperfect duplication method. Some reliability measures are derived. Two types of reliability equivalence factors and gamma fractiles are calculated. A numerical example is introduced to explain the theoretical results.

Quantization Of Fractional Constrained Systems With Wkb Approximation, Ola A. Jarabah

Applied Mathematics & Information Sciences

In this paper the constrained systems with two primary first class constraints are studied using fractional Lagrangian, after that we find the fractional Hamiltonian and the corresponding Hamilton Jacobi equation. Using separation of variables technique, we can find the action function S this function helps us to formulate the wave function which describe the behavior of our systems also from the action function S we can find the equations of motion and the corresponding momenta in fractional form. This work is illustrated using one example.

Applications Of The Ara-Residual Power Series Technique To Physical Phenomena, Aliaa Burqan

Applied Mathematics & Information Sciences

In this paper, a new analytical method called the ARA-Residual power series method (ARA- RPSM) is implemented to solve some fractional physical equations. The methodology of the proposed method based on applying the ARA-transform to the given fractional differential equations, followed by the creation of approximate series solutions using Taylor’s expansion. Then the series solution is transformed using the inverse of the ARA-transform to get the solution in the original space. Accuracy, effectiveness, and validity of the suggested method are demonstrated through the discussion of three attractive applications. The solution obtained using ARA-RPSM demonstrates good agreement when compared to the …

Generalization Of Renyi’S Entropy And Its Application In Source Coding, Ashiq Hussain Bhat, Niyamat Ali Siddiqui, Ismail A Mageed, Shawkat Alkhazaleh, Vidyanand Rabi Das, M. A. K Baig

Applied Mathematics & Information Sciences

In this paper, we introduce a new generalization of Renyis entropy β(P) and the most important feature of this generalized entropy Rαβ (P) is that it derives most important entropies that are well known and influence information theory and applied mathematics. Some significant properties of Rαβ (P) has been undertaken in this article. In addition, we introduce a new generalized exponentiated mean codeword length Lβα (P) in this article then determine how Rβα (P) and Lβα (P) are related in terms of source coding theorem.

Toward An Interoperable And Scalable Iot-Driven Smart City Solution Using Blockchain, Nada Abdulaziz A Alasbali

Student Works (2020-2029)

A smart city is primarily an urban region that makes effective use of contemporary technology to manage its resources, assets, and services. Internet of Things (IoT) devices and sensors are installed throughout the smart city in order to facilitate remote monitoring and data collection in relation to a variety of key infrastructures. The data is then utilised to plan the necessary maintenance tasks to ensure that citizens receive high-quality services. Even though IoT devices make it possible to collect data in real-time in a smart city, most sensors and IoT devices do not have a lot of storage space or …

Generalizable Deep-Learning-Based Wireless Indoor Localization, Ali Owfi

All Theses

The growing interest in indoor localization has been driven by its wide range of applications in areas such as smart homes, industrial automation, and healthcare. With the increasing reliance on wireless devices for location-based services, accurate estimation of device positions within indoor environments has become crucial. Deep learning approaches have shown promise in leveraging wireless parameters like Channel State Information (CSI) and Received Signal Strength Indicator (RSSI) to achieve precise localization. However, despite their success in achieving high accuracy, these deep learning models suffer from limited generalizability, making them unsuitable for deployment in new or dynamic environments without retraining. To …

Seek And Classify: End-To-End Joint Multi-Signal Detection And Classification Using Deep Learning, Prashant Subedi

School of Computing: Dissertations, Theses, and Student Research

The rise in the use of wireless communication has led to the problem of spectrum scarcity in licensed bands. The popularity of Internet of Things (IoT) requires innovative solutions that maximize the use of available spectrum to support the increasing number of connected devices. This thesis tackles two significant problems in wireless communication: the need for efficient spectrum sensing techniques and the scarcity of large, diverse raw in-phase (I) and quadrature (Q) datasets.

The ability to detect and classify modulation of the signals efficiently can enable a cognitive radio to monitor the spectrum activity in real time and utilize unused …

Context-Aware Event Forecasting Via Graph Disentanglement, Yunshan Ma, Chenchen Ye, Zijian Wu, Xiang Wang, Yixin Cao, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Event forecasting has been a demanding and challenging task throughout the entire human history. It plays a pivotal role in crisis alarming and disaster prevention in various aspects of the whole society. The task of event forecasting aims to model the relational and temporal patterns based on historical events and makes forecasting to what will happen in the future. Most existing studies on event forecasting formulate it as a problem of link prediction on temporal event graphs. However, such pure structured formulation suffers from two main limitations: 1) most events fall into general and high-level types in the event ontology, …

Numerical Design And Optimization Of Near-Infrared Band- Pass Filter, Hafiza Syeeda Faiza, Ghazi Aman Nowsherwan, Basem A. Abu Izneid, Muhammad Azhar, Saira Riaz, Syed Sajjad Hussain, Saira Ikram, Mohsin Khan, Shahzad Naseem, Mohammad Kanan, Ibrahim M. Mansour

Applied Mathematics & Information Sciences

Band-pass filters functioning in the near-infrared (IR) range are desired for laser technology, multi-photon fluorescence, and IR imaging applications. In this study, we have designed four band-pass filters in the near Infrared spectrum (900-1200 nm) by vertically stacking different high and low-index materials. The band-pass filters are modelled by Essential Macleod software with different thicknesses. The layer’s thicknesses were optimized in such a way to provide the negligible reflectance and maximum transmission on the front side. All the simulated band-pass filters exhibit high transmittance, but TiO2/Al2O3 and Ta2O5/Al2O3 outperforms other modelled structure in terms of performance due to the better …

Characterization And Estimation Of Musculoskeletal Pain Using Machine Learning, Boluwatife Faremi

Master's Theses

Traditional scales utilized for recording pain are known to be highly subjective and biased due to inaccuracies in recollecting actual pain intensities. As a result, machine learning (ML) models that are trained using these scores as ground truth are reported to have low performance for objective pain classification because of the huge disparity between what was felt in moments of pain and the scores recorded afterward.

In the present study, two devices were designed for gathering real-time, continuous in-session subjective pain scores and the recording of the autonomic nervous system (ANS) altered endodermal (EDA) activity. 24 participants were recruited to …

Blockchain Security: Double-Spending Attack And Prevention, William Henry Scott Iii

Electronic Theses and Dissertations

This thesis shows that distributed consensus systems based on proof of work are vulnerable to hashrate-based double-spending attacks due to abuse of majority rule. Through building a private fork of Litecoin and executing a double-spending attack this thesis examines the mechanics and principles behind the attack. This thesis also conducts a survey of preventative measures used to deter double-spending attacks, concluding that a decentralized peer-to-peer network using proof of work is best protected by the addition of an observer system whether internal or external.

What Senior U.S. Leaders Say We Should Know About Cyber, Dr. Joseph H. Schafer

Military Cyber Affairs

On April 6, 2023, the Atlantic Council’s Cyber Statecraft Initiative hosted a panel discussion on the new National Cybersecurity Strategy. The panel featured four senior officials from the Office of the National Cyber Director (ONCD), the Department of State (DoS), the Department of Justice (DoJ), and the Department of Homeland Security (DHS). The author attended and asked each official to identify the most important elements that policymakers and strategists must understand about cyber. This article highlights historical and recent struggles to express cyber policy, the responses from these officials, and the author’s ongoing research to improve national security cyber policy.

Effects Of Factors On The Market Price Of The Shares Using Design Of Experiment, Amir Ahmad Dar, Mohammad Shahfaraz Khan, Imran Azad, Tanveer Ahmad Tarray, N. Anuradha, Qaiser Farroq Dar

Applied Mathematics & Information Sciences

When the cost of capital, dividends and the price of the share at the beginning is known, Modigliani and Miller’s model can be used to estimate the price of the share at the end of the period. A design of experiment (Taguchi’s orthogonal array) is used in order to investigate the impact of three parameters on the price of the share at the end of the period. The main aim of this research article is to find which parameter is more significant on the price of the share at the end of the period. Taguchi’s methodology of design of the …

Critical Infrastructure Workforce Development Pods For Teaching Cybersecurity Using Netlab+, Gideon Sutterfield

Computer Science and Computer Engineering Undergraduate Honors Theses

As digital automation for Industrial Control Systems has grown, so has its vulnerability to cyberattacks. The world of industry has responded effectively to this, but the world of academia is still lagging as its emphasis is still almost entirely on information technology. Considering this, we created a workforce development pod that serves as a hands-on learning module for teaching students key cybersecurity ideas surrounding operational technology using the NETLAB+ platform. A pod serves as the virtual environment where the learning exercise takes place. This project’s implementation involved the creation of a segmented network within the pod where a student starts …

Iot Health Devices: Exploring Security Risks In The Connected Landscape, Abasi-Amefon Obot Affia, Hilary Finch, Woosub Jung, Issah Abubakari Samori, Lucas Potter, Xavier-Lewis Palmer

School of Cybersecurity Faculty Publications

The concept of the Internet of Things (IoT) spans decades, and the same can be said for its inclusion in healthcare. The IoT is an attractive target in medicine; it offers considerable potential in expanding care. However, the application of the IoT in healthcare is fraught with an array of challenges, and also, through it, numerous vulnerabilities that translate to wider attack surfaces and deeper degrees of damage possible to both consumers and their confidence within health systems, as a result of patient-specific data being available to access. Further, when IoT health devices (IoTHDs) are developed, a diverse range of …

Vanet Applications Under Loss Scenarios & Evolving Wireless Technology, Adil Alsuhaim

All Dissertations

In this work we study the impact of wireless network impairment on the performance of VANET applications such as Cooperative Adaptive Cruise Control (CACC), and other VANET applications that periodically broadcast messages. We also study the future of VANET application in light of the evolution of radio access technologies (RAT) that are used to exchange messages. Previous work in the literature proposed fallback strategies that utilizes on-board sensors to recover in case of wireless network impairment, those methods assume a fixed time headway value, and do not achieve string stability. In this work, we study the string stability of a …

Leveraging Artificial Intelligence And Machine Learning For Enhanced Cybersecurity: A Proposal To Defeat Malware, Emmanuel Boateng

Cybersecurity Undergraduate Research Showcase

Cybersecurity is very crucial in the digital age in order to safeguard the availability, confidentiality, and integrity of data and systems. Mitigation techniques used in the industry include Multi-factor Authentication (MFA), Incident Response Planning (IRP), Security Information and Event Management (SIEM), and Signature-based and Heuristic Detection.

MFA is employed as an additional layer of protection in several sectors to help prevent unauthorized access to sensitive data. IRP is a plan in place to address cybersecurity problems efficiently and expeditiously. SIEM offers real-time analysis and alerts the system of threats and vulnerabilities. Heuristic-based detection relies on detecting anomalies when it comes …

Nftdisk: Visual Detection Of Wash Trading In Nft Markets, Xiaolin Wen, Yong Wang, Xuanwu Yue, Feida Zhu, Min Zhu

Research Collection School Of Computing and Information Systems

With the growing popularity of Non-Fungible Tokens (NFT), a new type of digital assets, various fraudulent activities have appeared in NFT markets. Among them, wash trading has become one of the most common frauds in NFT markets, which attempts to mislead investors by creating fake trading volumes. Due to the sophisticated patterns of wash trading, only a subset of them can be detected by automatic algorithms, and manual inspection is usually required. We propose NFTDisk, a novel visualization for investors to identify wash trading activities in NFT markets, where two linked visualization modules are presented: a radial visualization module with …

Self-Learning Algorithms For Intrusion Detection And Prevention Systems (Idps), Juan E. Nunez, Roger W. Tchegui Donfack, Rohit Rohit, Hayley Horn

SMU Data Science Review

Today, there is an increased risk to data privacy and information security due to cyberattacks that compromise data reliability and accessibility. New machine learning models are needed to detect and prevent these cyberattacks. One application of these models is cybersecurity threat detection and prevention systems that can create a baseline of a network's traffic patterns to detect anomalies without needing pre-labeled data; thus, enabling the identification of abnormal network events as threats. This research explored algorithms that can help automate anomaly detection on an enterprise network using Canadian Institute for Cybersecurity data. This study demonstrates that Neural Networks with Bayesian …

The Rise And Risks Of Internet Of Things, Diamond E. Hicks

Cybersecurity Undergraduate Research Showcase

Internet of Things (IoT) has become a necessary part of our everyday lives. IoT is the network in which many different devices communicate, connect, and share data. Though how IoT got to where it is today, the issues it faced, and how it affects our lives today is not common knowledge. Despite the fact that IoT has advanced our technology to what it is today, people do not completely understand what it does.