Digital Commons Network^™

The Impact Of Student Motivation, Preparation, And Learned Helplessness On Undergraduate Students’ Communication With Advisors, Heather Carmack

Journal of the Association for Communication Administration

The purpose of this exploratory study was to examine communication factors that influence students’ academic advising appointments, including predictors of scheduling future advising appointments. Undergraduate students’ motivation and feelings of learned helplessness were related to their advising meeting preparation and their communication involvement during advising meetings. Students who reported high levels of motivation and low levels of learned helplessness were more likely to prepare for advising meetings and be communicative during meetings. Students with immediate advisors were more likely to communicate with their advisors during meetings. Advising meeting preparation, motivation, and learned helplessness were significant factors in future advising appointments.

Learning To Think Like A Leader, Mark Hickson Iii

Journal of the Association for Communication Administration

This is the second in a three-part series that the author has been working on. The first part was included in an earlier issue of this journal.

An Empirical Analysis Of The Impact Of Covid-19 On Trade: Evidence From A Small Island African Economy, Z Khan Jaffur, V Tandrayen-Ragoobur, B Seetanah

Journal of African Trade

This study investigates the potential impacts of the COVID-19 pandemic and related containment measures on the trade system of Mauritius for the period January 2010 to June 2021. As the pandemic spread across the globe due to high interconnectedness across countries, authorities has also established stringent health containment measures in the form of restrictions on people and businesses to slow the propagation of the virus. Being a small island economy highly dependent on international trade, Mauritius also faced the brunt of the pandemic which disrupted its economic activities and trade flows with its main trading partners. COVID-19 incidence and lockdown …

Stochastic Tumor-Immune Interaction Model With External Treatments And Time Delays: An Optimal Control Problem, H. J. Alsakaji, F. A. Rihan, K. Udhayakumar, F. El Ktaibi

All Works

Herein, we discuss an optimal control problem (OC-P) of a stochastic delay differential model to describe the dynamics of tumor-immune interactions under stochastic white noises and external treatments. The required criteria for the existence of an ergodic stationary distribution and possible extinction of tumors are obtained through Lyapunov functional theory. A stochastic optimality system is developed to reduce tumor cells using some control variables. The study found that combining white noises and time delays greatly affected the dynamics of the tumor-immune interaction model. Based on numerical results, it can be shown which variables are optimal for controlling tumor growth and …

Overhead Based Cluster Scheduling Of Mixed Criticality Systems On Multicore Platform, Amjad Ali, Asad Masood Khattak, Shahid Iqbal, Omar Alfandi, Bashir Hayat, Muhammad Hameed Siddiqi, Adil Khan

All Works

The cluster-based technique is gaining focus for scheduling tasks of mixed-criticality (MC) real-time multicore systems. In this technique, the cores of the MC system are distributed in groups known as clusters. When all cores are distributed in clusters, the tasks are partitioned into clusters, which are scheduled on the cores within each cluster using a global approach. In this study, a cluster-based technique is adopted for scheduling tasks of real-time mixed-criticality systems (MCS). The Decreasing Criticality Decreasing Utilization with the worst-fit (DCDU-WF) technique is used for partitioning of tasks to clusters, whereas a novel mixed-criticality cluster-based boundary fair (MC-Bfair) scheduling …

Lstda: Link Stability And Transmission Delay Aware Routing Mechanism For Flying Ad-Hoc Network (Fanet), Farman Ali, Khalid Zaman, Babar Shah, Tariq Hussain, Habib Ullah, Altaf Hussain, Daehan Kwak

All Works

The paper presents a new protocol called Link Stability and Transmission Delay Aware (LSTDA) for Flying Ad-hoc Network (FANET) with a focus on network corridors (NC). FANET consists of Unmanned Aerial Vehicles (UAVs) that face challenges in avoiding transmission loss and delay while ensuring stable communication. The proposed protocol introduces a novel link stability with network corridors priority node selection to check and ensure fair communication in the entire network. The protocol uses a Red-Black (R-B) tree to achieve maximum channel utilization and an advanced relay approach. The paper evaluates LSTDA in terms of End-to-End Delay (E2ED), Packet Delivery Ratio …

3d Indoor Modeling And Game Theory Based Navigation For Pre And Post Covid-19 Situation, Jaiteg Singh, Noopur Tyagi, Saravjeet Singh, Babar Shah, Farman Ali, Ahmad Ali Alzubi, Abdulrhman Alkhanifer

All Works

The COVID-19 pandemic has greatly affected human behavior, creating a need for individuals to be more cautious about health and safety protocols. People are becoming more aware of their surroundings and the importance of minimizing the risk of exposure to potential sources of infection. This shift in mindset is particularly important in indoor environments, especially hospitals, where there is a greater risk of virus transmission. The implementation of route planning in these areas, aimed at minimizing interaction and exposure, is crucial for positively influencing individual behavior. Accurate maps of buildings help provide location-based services, prepare for emergencies, and manage infrastructural …

Fuzzy Logic-Based Approach For Location Identification And Routing In The Outdoor Environment, Saravjeet Singh, Jaiteg Singh, Sukhjit Singh Sehra, Babar Shah, Farman Ali, Daehan Kwak

All Works

Finding the precise and accurate location of devices on road networks is challenging in remote areas with poor internet connectivity and Global Positioning System coverage. Navigation applications that completely depend on the internet and reference spatial data for location identification and mapping do not perform well in case of frequent internet disconnection. These reference spatial data sources have many associated challenges like large size, errors in data, and restricted access. To address these challenges, this paper provides an approach for localization and routing using self-generated reference data using likelihood estimation. According to the proposed approach, the trajectory information is used …

Design And Delivery Of National Housing In The Uae: An Alternative Approach, Basem Eid Mohamed, Mohamed Elkaftangui, Rana Zureikat, Rund Hiyasat

All Works

The provision of national housing to citizens in the United Arab Emirates (UAE) is considered a crucial topic. Over the past four decades, the process of developing national housing has emerged into multiple housing programs and schemes, all with the same aim of offering affordable and high-quality housing to citizens, in addition to meeting the needs of local families regarding spatial configurations while maintaining cultural values. However, despite all these efforts, the question has always remained: are the offered housing practices suited for family needs, socioeconomic trends, and environmental challenges? This study aims to offer an alternative approach for the …

Green Synthesis Of Lead Oxide Nanoparticles For Photo-Electrocatalytic And Antimicrobial Applications, Zia Ul Haq Khan, Noor Shad Gul, Faisal Mehmood, Sana Sabahat, Nawshad Muhammad, Abdur Rahim, Jibran Iqbal, Syed Khasim, Mohamed Abdel Salam, Taj Malook Khan, Jianbo Wu

All Works

Synthesis of nanoparticles (NPs) for many different uses requires the development of environmentally friendly synthesis protocols. In this article, we present a simple and environmentally friendly method to synthesize lead oxide (PbO) NPs from the plant material of the Mangifera indica. Analytical techniques such as spectroscopy, X-ray diffraction, and microscopy were used to characterize the synthesized PbO NPs, and their photo-electrocatalytic and antifungal properties were also evaluated. H2O2 was used to investigate the efficacy of removing methylene blue dye. At a range of pH values, H2O2 was used to study the role of hydroxyl radicals in the breakdown of methylene …

Dynamic Data Sample Selection And Scheduling In Edge Federated Learning, Mohamed Adel Serhani, Haftay Gebreslasie Abreha, Asadullah Tariq, Mohammad Hayajneh, Yang Xu, Kadhim Hayawi

All Works

Federated Learning (FL) is a state-of-the-art paradigm used in Edge Computing (EC). It enables distributed learning to train on cross-device data, achieving efficient performance, and ensuring data privacy. In the era of Big Data, the Internet of Things (IoT), and data streaming, challenges such as monitoring and management remain unresolved. Edge IoT devices produce and stream huge amounts of sample sources, which can incur significant processing, computation, and storage costs during local updates using all data samples. Many research initiatives have improved the algorithm for FL in homogeneous networks. However, in the typical distributed learning application scenario, data is generated …

Air Quality Improvement Following Covid-19 Lockdown Measures And Projected Benefits For Environmental Health, Yuei An Liou, Trong Hoang Vo, Kim Anh Nguyen, James P. Terry

All Works

Many regions worldwide suffer from heavy air pollution caused by particulate matter (PM2.5) and nitrogen dioxide (NO2), resulting in a huge annual disease burden and significant welfare costs. Following the outbreak of the COVID-19 global pandemic, enforced curfews and restrictions on human mobility (so-called periods of ‘lockdown’) have become important measures to control the spread of the virus. This study aims to investigate the improvement in air quality following COVID-19 lockdown measures and the projected benefits for environmental health. China was chosen as a case study. The work projects annual premature deaths and welfare costs by integrating PM2.5 and NO2 …

Design Of Block Copolymer With Tunable Hydrophobic/Hydrophilic/Fluorophilic Interactions, Tatiane De Fatima Dutra

Theses, Dissertations and Culminating Projects

Block copolymers (BCP) with balanced interactions and their resultant bulk-phase self-assembly have become increasingly important in advancing nanotechnology, separation, and energy applications. However, a few reports have addressed the synthesis challenge and bulk-phase self-assembly of such triblock copolymers. This thesis presents a facile route for preparing triblock copolymer via controlled radical and organocatalytic ring-opening polymerization that allows precise control over the incorporation of individual moieties in resultant polymer, responsible for balanced hydrophilic, hydrophobic/lipophilic, and fluorophilic interactions. Synthesized polymer with suggested self-assembled 2D lamellar nanostructure exhibits high-temperature stability. The long-term goal of this work is to selectively use this polymer class …

A Functioning Code May Not Be A Secure Code : A Preliminary Study On The Students' Complacency With Secure Coding, Jeremiah Niiquaye Kotey

Theses, Dissertations and Culminating Projects

Eleanor Roosevelt once said: "Learn from the mistakes of others. You can’t live long enough to make them all yourself". Mistakes are almost inevitable while coding or designing a system. Therefore, patches are created to fix the issues in the code either by a manual review, or through a static analysis tool. Oftentimes, mistakes in programming emanate from lack of skills thus, competence with a particular programming language but negligence also plays a role in other instances. A functioning code that solves a particular problem does not guarantee that the code is secure, hence the code should be structured to …

Facial Expression Recognition Using Lightweight Deep Learning Modeling, Mubashir Ahmad, Saira, Omar Alfandi, Asad Masood Khattak, Syed Furqan Qadri, Iftikhar Ahmed Saeed, Salabat Khan, Bashir Hayat, Arshad Ahmad

All Works

Facial expression is a type of communication and is useful in many areas of computer vision, including intelligent visual surveillance, human-robot interaction and human behavior analysis. A deep learning approach is presented to classify happy, sad, angry, fearful, contemptuous, surprised and disgusted expressions. Accurate detection and classification of human facial expression is a critical task in image processing due to the inconsistencies amid the complexity, including change in illumination, occlusion, noise and the over-fitting problem. A stacked sparse auto-encoder for facial expression recognition (SSAE-FER) is used for unsupervised pre-training and supervised fine-tuning. SSAE-FER automatically extracts features from input images, and …

An Experiment On The Effects Of Using Color To Visualize Requirements Analysis Tasks: Supplemental Material, Yesugen Baatartogtokh, Irene Foster, Alicia M. Grubb

Computer Science: Faculty Publications

Supplemental material for the paper: "An Experiment on the Effects of using Color to Visualize Requirements Analysis Tasks".
This paper is a scientific evaluation of the effectiveness and usability of EVO. We conduct an experiment to measure any effect of using colors to represent evidence pairs.

Social Cognitive Processes Explain Bias In Juror Decisions, Jaime J. Castrellon, Shabnam Hakimi, Jacob M. Parelman, Lun Yin, Jonathan R. Law, Jesse A.G. Skene, David A. Ball, Artemis Malekpour, Donald H. Beskind, Neil Vidmar, John M. Pearson, J. H. Pate Skene, R. Mckell Carter

Faculty Scholarship

Jury decisions are among the most consequential social decisions in which bias plays a notable role. While courts take measures to reduce the influence of non-evidentiary factors, jurors may still incorporate biases into their decisions. One common bias, crime-type bias, is the extent to which the perceived strength of a prosecutor’s case depends on the severity of the crime. Moral judgment, affect and social cognition have been proposed as core processes underlying this and other biases. Behavioral evidence alone has been insufficient to distinguish these explanations. To identify the mechanism underlying crime-type bias, we collected functional magnetic resonance imaging patterns …

Corporate Governance And Risk-Taking: A Statistical Approach, Steven L. Schwarcz

Faculty Scholarship

Because prudent corporate governance often requires managers to take risks based on statistically expected outcomes, corporate failures that have a small but finite chance of occurring cannot always be prevented. This Article makes three related claims about risk-taking in corporate governance.

This Article’s first claim is that managers should not automatically be presumed to be at fault for corporate failures that result from risk-taking decisions based on statistical methodologies that reasonably justify the decisions ex ante. Conceptually, the business judgment rule should protect corporate managers for engaging in a reasonable decision-making process, including one that is statistically based. Jurisdictionally, however, …

Is Disclosure And Certification Of The Use Of Generative Ai Really Necessary?, Maura R. Grossman, Paul W. Grimm, Daniel G. Brown

Faculty Scholarship

No abstract provided.

The Possible Futures Of American Democracy, Jedediah Purdy

Faculty Scholarship

No abstract provided.

“A Map Is Not The Territory”: The Theory And Future Of Sensitive Places Doctrine, Joseph Blocher, Jacob D. Charles, Darrell A. H. Miller

Faculty Scholarship

In the wake of the Supreme Court’s decision in New York State Rifle & Pistol Ass’n v. Bruen, courts are now confronted with new questions about where guns can be restricted and what justifications support those regulations. This Essay urges that the development of the doctrine governing location-based prohibitions should focus as much on the why as the where. Instead of simply isolating each location and considering the historical pedigree of gun restrictions in that place, judges should evaluate the reasons behind the sensitive places doctrine itself. We aim to recenter these first order questions to avoid haphazard doctrinal development …

Coming Out While Going Fast: Queer Conviviality In Speedrunning Live Streams, Johanna Brewer

Computer Science: Faculty Publications

Drawing on ethnographic research of LGBTQIA+ live streaming speedrunners, this article demonstrates how by centering queer perspectives, we can catalyze meaningful social changes for all. Though for most people, beating the original Super Mario Bros. in under five minutes would seem unfathomably difficult, LGBTQIA+ speedrunning live streamers regularly accomplish this superhuman feat, while coming out to an audience of thousands at the same time. For queer and trans folks, broadcasting such a transgressive, transformational form of play is defiant demonstration of vulnerability; one that creates a comfortable space for a community to thrive, by cultivating a culture of queer conviviality. …

#Metoo & The Courts: The Impact Of Social Movements On Federal Judicial Decisionmaking, Carol T. Li, Matthew E.K. Hall, Veronica Root Martinez

Faculty Scholarship

In late 2017, the #MeToo movement swept through the United States as individuals from all backgrounds and walks of life revealed their experiences with sexual abuse and sexual harassment. After the #MeToo movement, many scholars, advocates, and policymakers posited that the watershed moment would prompt changes in the ways in which sexual harassment cases were handled. This Article examines the impact the #MeToo movement has had on judicial decisionmaking. Our hypothesis is that the #MeToo movement’s increase in public awareness and political attention to experiences of sexual misconduct should lead to more pro-claimant voting in federal courts at the district …

On The Basis Of Childbirth: How The Federal Clerkship's Lack Of Parental Leave Fosters Gender Inequality, Bailey K. Sanders

Faculty Scholarship

This Essay argues that the lack of paid parental leave for federal law clerks enables pregnancy discrimination, restricts women’s reproductive choice, and perpetuates gender inequality within the legal profession. Protections against pregnancy discrimination are hollow when clerks can be fired—or have clerkship offers rescinded—for requiring maternity leave, and the lack of leave disproportionately impacts female clerks by constraining their ability to pursue career and family simultaneously. The lack of leave also restricts (some) pregnant women’s reproductive choice by forcing them to choose between keeping their position or carrying their pregnancy to term. Such a state of affairs was intolerable in …

Inequitable Distribution Of Plastic Benefits And Burdens On Economies And Public Health, Rachel Karasik, Nancy Lauer, Anne-Elisabeth Baker, Niki E. Lisi, Jason A. Somarelli, William C. Eward, Kathinka Fürst, Meagan M. Dunphy-Daly

Faculty Scholarship

Plastic heterogeneously affects social systems – notably human health and local and global economies. Here we discuss illustrative examples of the benefits and burdens of each stage of the plastic lifecycle (e.g., macroplastic production, consumption, recycling). We find the benefits to communities and stakeholders are principally economic, whereas burdens fall largely on human health. Furthermore, the economic benefits of plastic are rarely applied to alleviate or mitigate the health burdens it creates, amplifying the disconnect between who benefits and who is burdened. In some instances, social enterprises in low-wealth areas collect and recycle waste, creating a market for upcycled goods. …

Finance Against Law: The Case Of China, Shitong Qiao

Faculty Scholarship

Can there be a highly developed financial market without legal protection for investors and creditors? The influential law and finance literature is built on the assumption that legal protection is essential to the development of an impersonal financial market. This Article investigates how two financial markets of trillions of dollars have developed extralegally in the past two decades despite the risk of regulatory enforcement and contract defaults. Specifically, I examine (1) how Chinese internet companies from Sina to Alibaba have designed contracts to circumvent the Chinese government’s ban on foreign capital in its internet industry and (2) how Chinese entities …

Artificial Intelligence In Corneal Topography: A Short Article In Enhancing Eye Care, Guma Ali, Marwa M. Eid, Omar G. Ahmed, Mostafa Abotaleb, Anas M. Zein Alaabdin, Bosco Apparatus Buruga

Mesopotamian Journal of Artificial Intelligence in Healthcare

The eye is a critical part of the human being, as it provides complete vision and the ability to receive and process visual details, and any deficiency in it may affect vision and loss of sight. Corneal topography is one of the essential diagnostic tools in the field of ophthalmology, as it can provide important information about the cornea and the problems that appear in it. Artificial intelligence strategies contribute to the development of the healthcare domain through a group of approaches that have a significant and vital impact on improving the field of ophthalmology. The primary purpose of this …

Artificial Intelligence's Significance In Diseases With Malignant Tumours, Ruchi Doshi, Kamal Kant Hiran, Murat Gök, El-Sayed M. El-Kenawy, Amr Badr, Mostafa Abotaleb

Mesopotamian Journal of Artificial Intelligence in Healthcare

In the field of medicine, artificial intelligence has become a useful tool, particularly in the diagnosis and treatment of disorders with malignant tumours. Deep learning and machine learning algorithms, for example, have significant promise for increasing the precision and effectiveness of tumour diagnosis and treatment. The importance of AI in diseases with malignant tumours is examined in this work, with particular attention paid to its function in medication discovery, therapy prediction, and medical imaging analysis. It also emphasizes the difficulties and restrictions related to the application of AI, such as problems with poor data quality, as well as the requirement …

Employing Artificial Intelligence Methods In Drug Development: A New Era In Medicine, Omega John Unogwu, Mabel Ike, Opkanachi Omatule Joktan

Mesopotamian Journal of Artificial Intelligence in Healthcare

Artificial intelligence (AI) plays a vital role in the development of pharmaceuticals. The whole drug development process, from target identification and lead optimization to clinical trials and post-marketing monitoring, has the potential to be revolutionized by AI. Data analysis is a crucial area where AI thrives. To find trends, correlations, and prospective targets for therapeutic intervention, AI systems can analyse enormous volumes of data, including electronic health records, molecular databases, academic literature, and clinical trial data. This saves time and resources by enabling researchers to decide which compounds or pathways to investigate. Lead optimization is another area where AI is …

Diabetes At A Glance: Assessing Ai Strategies For Early Diabetes Detection And Intervention, Ban Salman Shukur, Noorayisahbe Mohd Yaacob, Mohamed Doheir

Mesopotamian Journal of Artificial Intelligence in Healthcare

For the early identification of diabetes, a chronic illness that affects millions of people globally, artificial intelligence (AI) shows enormous promise. AI algorithms can recognize diabetes signs and give patients and healthcare providers early warnings by examining a variety of data sources, such as medical records, patient histories, and lifestyle factors. AI's capacity to evaluate sizable and intricate datasets is one of its main advantages in the diagnosis of diabetes. AI is capable of taking into account a broad range of variables that could lead to diabetes, such as age, BMI, food preferences, physical activity, and genetic predisposition. Artificial intelligence …