Digital Commons Network^™

A Classifier-Driven Deep Learning Clustering Approach To Enhance Data Collection In Manets, Ali Abdullah Ali, Mohammed Khaleel Hussein, Mohammed Ahmed Subhi

Mesopotamian Journal of CyberSecurity

The conventional clustering and routing approaches used in mobile ad hoc networks (MANETs) may fail to work effectively in a dynamic network environment where nodes are highly mobile and the traffic load may also vary significantly. These limitations result in negative effects such as high packet drop rates, delays in data transmission, and low delivery rates, which make these methods unfit for modern high-density networks. To overcome these issues, this paper proposes a new deep learning-based classifier for adaptive clustering in MANETs. Through the use of machine learning algorithms, the proposed method is able to adapt to node clustering through …

An Optimized Model For Network Intrusion Detection In The Network Operating System Environment, Abbas A. Abdulhameed, Sundos A. Hameed Alazawi, Ghassan Muslim Hassan

Mesopotamian Journal of CyberSecurity

With the heavy reliance on computers and information technology to send and receive data across networks of various types, there has been concern about securing that data from intrusions and cyber-attacks. The expansion of network usage has led to an increase in hacker attacks, which has led to prioritizing cybersecurity precautions in detecting potential threats. Intrusion detection techniques are a critical security measure to protect networks in both personal and corporate environments that are managed by network operating systems. For this, the paper relies on designing a network intrusion detection model. Since deep neural networks (DNNs) are classic deep learning …

A Systematic Literature Review On Cyber Attack Detection In Software-Define Networking (Sdn), Dalia Shihab Ahmed, Abbas Abdulazeez Abdulhameed, Methaq T. Gaata

Mesopotamian Journal of CyberSecurity

The increasing complexity and sophistication of cyberattacks pose significant challenges to traditional network security tools. Software-defined networking (SDN) has emerged as a promising solution because of its centralized management and adaptability. However, cyber-attack detection in SDN settings remains a vital issue. The current literature lacks comprehensive assessment of SDN cyber-attack detection methods including preparation techniques, benefits and types of attacks analysed in datasets. This gap hinders the understanding of the strengths and weaknesses of various detection approaches. This systematic literature review aims to examine SDN cyberattack detection, identify strengths, weaknesses, and gaps in existing techniques, and suggest future research directions …

Ai-Powered Cyber Threats: A Systematic Review, Mafaz Alanezi, Ruah Mouad Alyas Al-Azzawi

Mesopotamian Journal of CyberSecurity

The joining of artificial intelligence (AI) across different areas has fundamentally improved productivity and development. Nevertheless, this progression has increased cybersecurity threats, especially those determined by AI itself. These AI-powered threats exploit the advancements intended to obtain computerized frameworks, in this manner subverting their honesty. This systematic review focuses on the intricacies of AI-driven cyber threats, which use complex AI abilities to lead to intricate and tricky cyberattacks. Our review integrates existing examinations to determine the extension, location procedures, effects, and relief systems connected with AI-initiated threats. We feature the powerful exchange between AI improvement and cybersecurity, underlining the requirement …

Dental Segmentation Via Enhanced Yolov8 And Image Processing Techniques, Dhiaa Mohammed Abed, Shuzlina Abdul-Rahman, Sofianita Mutalib

Mesopotamian Journal of CyberSecurity

By blending computer-aided medical systems with cutting-edge privacy technologies, healthcare providers can deliver more personalized, effective care while maintaining the highest data security standards and patient trust. The challenge of dental segmentation in computer vision, a task focused on accurately outlining dental structures in images, traditional methods, particularly convolution neural networks (CNNs), didn't reach high accuracy in this area due to suboptimal performance and computational inefficiency. The goal of image segmentation is to group pixels on the basis of their visual properties, such as color, texture, intensity, or spatial proximity, to identify and delineate the boundaries of distinct objects or …

Shifting Baselines: Visualizing Climate Change In America’S National Parks, Lee Lines

Faculty Publications

No abstract provided.

Institute For Global Health And Development : Issue 9 - September 2024, Institute For Global Health And Development

IGHD Newsletters

• A Call for Action
• Recent Events
• Supporting Women in Science 2024
• Climate Change and Health Symposium
• Breaking Barriers for Gender and Health Equity
• IGHD Summer Internship Program 2024
• The New Faces at IGHD

Antibiotic-Loaded Dendrimer Hydrogels In Periodontal Bone Regeneration: An In Vitro Release Feasibility Study, Nicholas Yesbeck, Da Huang, Caroline Carrico, Parthasarathy Madurantakam, Hu Yang

Chemical and Biochemical Engineering Faculty Research & Creative Works

The prescription of a course of oral antibiotics following bone grafting procedures is a common practice in clinical periodontics to reduce surgical site infections. The goal of this study is to characterize the release profile of antibiotics via local delivery using dendrimer hydrogels (DH) and to analyze the effect of two different particulate bone allografts on the release of the antibiotics in vitro. DH were synthesized from Poly amidoamine (PAMAM) dendrimer G5 and polyethylene glycol diacrylate, and cefazolin was chosen as the antibiotic. The antibiotic-loaded samples were bathed in PBS and incubated at 37 °C; aliquots were taken (1 h, …

A New Air-Assisted Flare Tip Design For Managing Gas Flare Emissions (Cfd Analysis), Ahmed A. Maaroof, Joseph D. Smith, Mohammed H.S. Zangana

Chemical and Biochemical Engineering Faculty Research & Creative Works

Recently, flares have been considered as a major source of air pollution from the petroleum refining industry. The United Nations has instigated an international effort related to the management of flare emissions to reduce the global warming impact related to flaring. Eliminating or removing the need for gas flares is difficult because these devices are generally used as safety devices to allow the combustion of flammable gases in a controlled fashion which supports safe operation. However, reducing flaring is generally possible using well-designed, efficiently operated flare equipment. In general, flare performance can be enhanced following the API-521 methodology and using …

Féminas Speaking Up: Three Papers On Feminine Transgender Identities, Gender Identity Activism, And Language Reform In Lima, Peru, Ernesto Cuba

Dissertations, Theses, and Capstone Projects

In this three-paper dissertation, I explore the linguistic and discursive practices of Féminas, a leading transgender rights activist organization based in Lima, Peru. Building on scholarship on language ideologies (Irvine & Gal, 2000), queer linguistics (Motschenbacher, 2011), and socio-onomastics (Ainiala & Östman, 2017), I analyze the role that language beliefs and language-in-use plays in performing local (trans)gender identities and shaping grassroots politics within this specific community of practice (Eckert & McConnell-Ginet, 1992). Based on an extensive corpus of semi-structured interviews and ethnographic material gathered during my long-term investigation with Féminas, I present three studies exploring distinct –though related– ideologically-driven sociolinguistic …

Winning The War While Losing Their Souls: The Crisis Of Honor And Discipline Within The French Army In Algeria, Thomas A. Schellhammer

Dissertations, Theses, and Capstone Projects

From 1939 to 1962, the French military fought in continuous conflicts. In 1961, in the midst of the Algerian War, these wars would result in military coup attempts and mutiny, as well as the formation of a breakaway terrorist group of army officers known as the Organisation de l’Armée Secrete (OAS), dedicated to the political overthrow and assassination of President of France Charles de Gaulle. While both the insurrectionists and the OAS and its adherents were ultimately unsuccessful, for members of a stable, functioning military to even contemplate such dire political action, these events illustrated a profound breach of military …

Exploiting The Heavy Chain Glycans For The Improvement Of Radioimmunoconjugates, Cindy Rodriguez

Dissertations, Theses, and Capstone Projects

Radiolabeled antibodies have become indispensable tools in nuclear medicine. However, the natural roles of antibodies within the immune system mean that they have several intrinsic limitations as a platform for radiopharmaceuticals. A handful of recent preclinical studies suggest that binding by FcR and particularly FcyRI can affect the pharmacokinetic profiles of 89Zr-labeled radioimmunoconjugates. Fc receptors (FcR) are responsible for many of the interactions between immunoglobulins (IgG) and immune cells. In biomedicine, this interplay is critical to the activity of several types of immunotherapeutics; however, relatively little is known about how FcRs affect the in vivo performance of radiolabeled antibodies. Antibodies …

Improving Large Language Models For Clinical Named Entity Recognition Via Prompt Engineering, Vipina Kuttichi Keloth, Xu Zuo, Yujia Zhou, Zehan Li, Xiaoqian Jiang, Zhiyong Lu, Kirk Roberts, Hua Xu

Faculty, Staff and Student Publications

IMPORTANCE: The study highlights the potential of large language models, specifically GPT-3.5 and GPT-4, in processing complex clinical data and extracting meaningful information with minimal training data. By developing and refining prompt-based strategies, we can significantly enhance the models' performance, making them viable tools for clinical NER tasks and possibly reducing the reliance on extensive annotated datasets.

OBJECTIVES: This study quantifies the capabilities of GPT-3.5 and GPT-4 for clinical named entity recognition (NER) tasks and proposes task-specific prompts to improve their performance.

MATERIALS AND METHODS: We evaluated these models on 2 clinical NER tasks: (1) to extract medical problems, treatments, …

Generative Large Language Models Are All-Purpose Text Analytics Engines: Text-To-Text Learning Is All Your Need, Kaleb E Smith, Anthony B Costa, Mona G Flores, Jiang Bian, Yonghui Wu

Faculty, Staff and Student Publications

Objective: To solve major clinical natural language processing (NLP) tasks using a unified text-to-text learning architecture based on a generative large language model (LLM) via prompt tuning.

Methods: We formulated 7 key clinical NLP tasks as text-to-text learning and solved them using one unified generative clinical LLM, GatorTronGPT, developed using GPT-3 architecture and trained with up to 20 billion parameters. We adopted soft prompts (ie, trainable vectors) with frozen LLM, where the LLM parameters were not updated (ie, frozen) and only the vectors of soft prompts were updated, known as prompt tuning. We added additional soft prompts as a prefix …

Public Sector Use Of Private Sector Personal Data: Towards Best Practices, Teresa Scassa

Dalhousie Law Journal

Governments increasingly seek to use personal data sourced from the private sector for purposes that range from the generation of statistics to municipal planning. The data collected by companies is often high volume and rich in detail. Location and mobility data—which have many applications—are collected by multiple private sector actors, from cellular service providers to app developers and data brokers. Financial sector organizations amass rich data about the spending and borrowing habits of consumers. Even genetic data is collected by private sector companies. The range of available data is constantly growing as more and more data is harvested, and as …

Observation Of The Galactic Center Pevatron Beyond 100 Tev With Hawc, A. Albert, R. Alfaro, C. Alvarez, A. Andrés, J. C. Arteaga-Velázquez, D. Avila Rojas, H. A. Ayala Solares, R. Babu, E. Belmont-Moreno, A. Bernal, K. S. Caballero-Mora, T. Capistrán, A. Carramiñana, S. Casanova, U. Cotti, J. Cotzomi, S. Coutiño De León, E. De La Fuente, C. De Leon, D. Depaoli, N. Di Lalla, R. Diaz Hernandez, B. L. Dingus, M. A. Duvernois, J. C. Diaz-Velez, K. Engel, T. Ergin, C. Espinoza, K. L. Fan, K. Fang, N. Fraija, S. Fraija, J. A. Garcia-Gonzalez, F. Garfias, H. Goksu, M. M. Gonzalez, J. A. Goodman, S. Groetsch, J. P. Harding, S. Hernandez-Cadena, I. Herzog, J. Hinton, D. Huang, F. Hueyotl-Zahuantitla, T. B. Humensky, P. Huntemeyer, A. Iriarte, S. Kaufmann, D. Kieda, A. Lara, W. H. Lee, J. Lee, H. Leon Vargas, J. T. Linnemann, A. L. Longinotti, G. Luis-Raya, K. Malone, O. Martinez, J. Martinez-Castro, J. A. Matthews, P. Miranda-Romagnoli, J. A. Montes, J. A. Morales-Soto, E. Moreno, M. Mostafa, M. Najafi, L. Nellen, M. Newbold, M. U. Nisa, R. Noriega-Papaqui, L. Olivera-Nieto, N. Omodei, M. Osorio-Archila, Y. Perez Araujo, E. G. Perez-Perez, C. D. Rho, D. Rosa-Gonzalez, E. Ruiz-Velasco, H. Salazar, D. Salazar-Gallegos, A. Sandoval, M. Schneider, G. Schwefer, J. Serna-Franco, A. J. Smith, Y. Son, R. W. Springer, O. Tibolla, K. Tollefson, I. Torres, R. Torres-Escobedo, R. Turner, F. Urena-Mena, E. Valera, Xiaojie Wang, Z. Wang, I. J. Watson, E. Willox, H. Wu, S. Yu, S. Yun-Carcamo, H. Zhou

Physics Faculty Research & Creative Works

We report an observation of ultrahigh-energy (UHE) gamma rays from the Galactic center (GC) region, using 7 yr of data collected by the High-Altitude Water Cherenkov (HAWC) Observatory. The HAWC data are best described as a point-like source (HAWC J1746-2856) with a power-law spectrum ( d N / d E = ϕ E / 26 TeV γ ), where γ = −2.88 ± 0.15stat − 0.1sys and ϕ = 1.5 x 10⁻¹⁵ (TeV cm² s)⁻¹ ± 0.3 stat − 0.13 sys + 0.08 sys extending from 6 to 114 TeV. We find no evidence of a spectral …

Advancements In Legged Walking Robots: Review, Zaineb Wared Matteb, Sadeq Hussein, Nabil Hassan Hadi

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The purpose of this review is to contribute to the body ofknowledge surrounding legged walking robots, specifically those utilizingfour legs. It aims to inform researchers, engineers, and enthusiasts about theadvancements, potential applications, and future prospects of these robots,ultimately driving further research and development in this exciting field.The review covered the most recent research articles in the field of designingand manufacturing robots, as well as how to choose the mechanism ofactuator between hydraulic or electric systems and their impact on theweight increase and energy consumption, or potential noise generationduring the operation like Bigdog robot. The payload was also assessed, witha comparison …

Machine Learning Techniques For Monitoring Water Quality In Water Resources, Hussam Hashim Hussein, Salam Muhsin, Wissam Shaya Abbas

Iraqi Journal of Computers, Communications, Control and Systems Engineering

More than 66% of the Earth's total surface area is covered by water. Cleanwater is one of the basic needs of everyday life. Consistent pollution of water bodies canhave far-reaching effects on the lives of living organisms. The World Health Organizationhas reported that the provision of safe drinking water for human consumption is achallenge that has reached alarming levels. This is because nearly 70% of the total waterwithdrawals worldwide are used in agriculture. To determine the water's suitability forhuman consumption, Tests are typically conducted by examining the properties of water interms of physical, biological, and chemical conditions. There are various …

Machine Learning To Enhance Security Systems, Saja A. Talib

Iraqi Journal of Computers, Communications, Control and Systems Engineering

This research explores the integration of machine learning intosecurity systems, addressing the growing challenges posed by cyber threats. Ittraces the historical context of cybersecurity measures and the development ofmachine learning in intrusion detection, anomaly detection, and behavioralanalysis. By examining traditional security approaches and their limitations,the study highlights the transformative potential of machine learning. Casestudies provide concrete examples of successful applications, demonstratinghow machine learning reduces cyber threats. Ethical considerations,implementation challenges, biases, and regulatory aspects are discussed,highlighting the complexities of integrating machine learning into securityframeworks. Furthermore, the research explores emerging technologies incybersecurity and offers insights into the future of machine learning in …

Survey Of Uav Security Authentication And Cryptography Protocols, Manar H. Abed, Shatha H, Soukaena H. Hashiem

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Unmanned aerial vehicles, or UAVs, are gaining significant attention becauseof the strategic and financial information and value inVolved in aerial applications, as wellas the sensitive data collected through embedded sensors. UAVs are rapidly developing invarious fields and find widespread utility in military applications for effective targettracking, battlefield surveillance, radiation monitoring, and sports. UAVs are useful andadvantageous, but they can also be attacked by a variety of techniques, including jamming,fuzzing, false data injection, and zero attacks. Researchers were looking on robust securitymechanisms to protect UAVs from attackers in order to combat such security risks.However, there is a large number of vulnerabilities …

Smart Temperature Monitoring System For Machining Process Using Internet Of Things, Ahmed Thamer Hassan, Luma A. H., Amjad Barazan Abdulghafou

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Outer surface integrity must be maintained throughout the machining processduring the production of metal parts, which need the ability to monitor temperatures in realtime. Changes in temperature during the machining process lead to changes in thebehavior of the product after work is completed.To achieve quality and productivitycriteria, the metal parts manufacturing process requires a continuous and precisetemperature measuring and monitoring system by using IOT. An intelligent temperaturemeasurement can be used during machining processes on conventional, non-conventional,and computer numerical control (CNC) machines.This paper presents a performance analysis of a temperature measuring system formachining process applications via Arduino IDE. In this proposal, …

Comparative Analysis Of Two Robust Strategies For An Angular Velocity Control System, Aws Mahmood Abdullah, Hasan H., Arif A. Al-Qassar, Shibly A. Al-Samarraie

Iraqi Journal of Computers, Communications, Control and Systems Engineering

In this paper, a novel flow control strategy which is the inletthrottled pump was used to design an angular velocity control system forrotary actuator. Inlet throttled systems have good performance in addition totheir high efficiency compared to traditional valve controlled systems. Theflow in the proposed system is adjusted by a valve that is positioned at thepump inlet with the purpose of reducing the energy loses across the valve.This regulated flow is used then to control the actuator angular velocity. Thesystem was modeled and the open loop stability and performance werestudied. In order to improve the system performance, Robust-Proportional-Integral-Derivative (RPID) and …

Mixed H2/H-Infinity Controller Design For Triple Inverted Pendulum System, Yamama A. Shafeek, Hazem I.

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The steady increase in reliance on robotic systems in industrialapplications arises the need to ensure their reliability despite the presence ofexternal disturbances in the environment they work in and their parametersvariations due to several factors like: change of temperature, wear and teareffect, and payload variation. Traditional controllers usually fail to maintainthe system's stability and performance in the presence of uncertainty, whilerobust controllers aim to guarantee stability and desired performance across arange of possible uncertainties in the system through incorporating theseuncertainties into their design process. This paper investigates the robustness of three controllers namely, H2 controller, H-infinity controller, and mixed H2/H-infinity …

Spot, Zone And Overcoat Painting Of Steel Bridges, Christopher Goff, Sudhir Palle

Kentucky Transportation Center Research Report

Over the past 25 – 30 years, the Kentucky Transportation Cabinet (KYTC) has replaced lead-based coatings on many bridges, often with zinc-based systems. But many of these coating systems are now degrading and reaching the ends of their service lives. Historically, KYTC has relied entirely on remove-and-replace painting, however, given the programmatic costs associated with remove-and-replace painting and constraints imposed by limited funding, the agency needs to explore more economical options, such as spot, zone, and overcoat painting. This report discusses use cases for spot, zone, and overcoat painting and lays out guidelines staff can use to determine what method …

Addressing The Effect Of Intra-Seasonal Variations In Developing Rainfall Thresholds For Landslides: An Antecedent Rainfall-Based Approach, Vishnu Chakrapani Lekha, Thomas Oommen, Snehamoy Chatterjee, Kochappi Sathyan Sajinkumar

Michigan Tech Publications

We developed a rainfall threshold model with the objective of limiting the effects of uncertainties typically associated with them, such as a lack of robust landslide database, the selection of the contributing rain gauge, seasonal variations in rainfall patterns, and the effect of extreme rainfall conditions. With the aid of gauge-corrected satellite precipitation data and a landslide database compiled from various sources, separate rainfall thresholds were developed for two waves of the monsoon season in the Western Ghats, India. The daily vs. antecedent rainfall distributions for different scenarios of antecedent rainfall were analyzed for landslide occurrence. The different scenarios considered …

Design And Analysis Of Self-Tanked Stepwise Charging Circuit For Four-Phase Adiabatic Logic, William Morell, Jin Woo Choi

Michigan Tech Publications

Adiabatic logic has been proposed as a method for drastically reducing power consumption in specialized low-power circuits. They often require specialized clock drivers that also function as the main power supply, in contrast to standard CMOS logic, and these power clocks are often a point of difficulty in the design process. A novel, stepwise charging driver circuit for four-phase adiabatic logic is proposed and validated through a simulation study. The proposed circuit consists of two identical driver circuits each driving two opposite adiabatic logic phases. Its performance relative to ideal step-charging and a standard CMOS across mismatched phase loads is …

Strain And Substrate-Induced Electronic Properties Of Novel Mixed Anion-Based 2d Schx2 (X = I/Br) Semiconductors, Ashima Rawat, Ravindra Pandey

Michigan Tech Publications

Exploration of compounds featuring multiple anions beyond the single-oxide ion, such as oxyhalides and oxyhydrides, offers an avenue for developing materials with the prospect of novel functionality. In this paper, we present the results for a mixed anion layered material, ScHX2 (X: Br, I) based on density functional theory. The result predicted the ScHX2 (X: Br, I) monolayers to be stable and semiconducting. Notably, the electronic and mechanical properties of the ScHX2 monolayers are comparable to well-established 2D materials like graphene and MoS2, rendering them highly suitable for electronic devices. Additionally, these monolayers exhibit an ability to adjust their band …

Water Hyacinths Retain River Plastics, Louise J. Schreyers, Tim H.M. Van Emmerik, Thanh Khiet L. Bui, Lauren Biermann, Remko Uijlenhoet, Hong Quan Nguyen, Nicholas Wallerstein, Martine Van Der Ploeg

School of Biological and Marine Sciences

Rivers represent one of the main conduits for the delivery of plastics to the sea, while also functioning as reservoirs for plastic retention. In tropical regions, rivers are exposed to both high levels of plastic pollution and invasion of water hyacinths. This aquatic plant forms dense patches at the river surface that drift due to winds and currents. Recent work suggests that water hyacinths play a crucial role in influencing plastic transport, by efficiently trapping the majority of surface plastic within their patches. However, a comprehensive understanding of the interaction between water hyacinths and plastics is still lacking. We hypothesize …

Preferred Music Listening For People Living With Dementia: Two Home-Based Case Studies Discussing Compilation Process, Autobiographical And Biophysical Responses, Paul Fernie, Alexander Street, Jörg Fachner, Leonardo Muller, Ming Hung Hsu, Patrizia Di Campli San Vito, Stephen Brewster, Sube Banerjee, Nicolas Farina, Hari Shaji, Paulo Itaborai, Alexis Kirke, Eduardo Reck Miranda

School of Art, Design and Architecture

Neuropsychiatric symptoms (NPS) in dementia can be reduced through music listening. Little has been reported on home-based listening, compilation processes, or individual responses that include biophysiological data. We aim to provide new insights from two home-based case studies focused on specific music selections. Participants were part of a larger study, co-designing an automated radio, diary reminder and personal playlist system for NPS management. Playlists were compiled that would have the best possible chance of achieving this, based on participants’ autobiographical, narrative, heart rate (HR) and videoed responses. Participant's responses to their music aligned with the genre they chose – dancing …

Performance Evaluation And Integration Of Distortion Mitigation Methods For Fisheye Video Object Detection, John Benedict Du, Gian Paolo Mayuga, Maria Leonora Guico

Electronics, Computer, and Communications Engineering Faculty Publications

The distortion observed in fisheye cameras has proven to be a persistent challenge for numerous state-of-the-art object detection algorithms, instigating the development of various techniques aimed at mitigating this issue. This study aims to evaluate various methods for mitigating distortion in fisheye camera footage and their impact on video object detection accuracy and speed. Using Python, OpenCV, and third-party libraries, the researchers modified and optimized said methods for video input and created a framework for running and testing different distortion correction methods and object detection algorithm configurations. Through experimentation with different datasets, the study found that undistorting the image using …