Digital Commons Network^™

One Hand Doesn't Clap: The Moderation Of Individual Factors On The Relationship Between Leader Narcissism And Followers' Outcomes, Wafa Mohammed Al Wahedi

Dissertations

Drawing on leadership and social exchange theories, the purpose of this study is to examine the adverse impact of the toxic triangle; namely, Leader Narcissism (LN), Perceived Unethical Climate (PUC) and Followers' Submissiveness (FS) on followers' outcomes, particularly Psychological Capital (PsyCap) and Constructive Deviance (CD) through the mediation of Leader-Member Exchange (LMX). The study introduces Moral Identity (MI) as a moderator. The conceptual framework was put to the test with data collected from both leaders and their followers in UAE-based organizations. Hierarchical linear model analysis was run on leaders and followers' dyadic data for testing whether moral identity moderated the …

Keynote Address: "Attacking And Defending The Administrative State", Jack M. Beermann

Faculty Scholarship

At the beginning of this semester I told my students at Boston University that this is the most interesting time to take administrative law since I started teaching it nearly forty years ago. Doctrines that seemed settled just a few years ago have been questioned and significant change seems to be on the horizon. Don't get me wrong, we've been here before. In the 1970s and 1980s there were a few Supreme Court decisions on separation of powers¹ that indicated the possibility of big changes, but ultimately it fizzled out into the administrative law revolution that wasn't.

Things feel …

Decision Tree And Rule Based Classification For Predicting Online Purchase Behavior In Malaysia, Maslina Abdul Aziz, Nurul Ain Mustakim, Shuzlina Abdul Rahman

Malaysian Journal of Computing (MJoC)

In Malaysia, fast growth in e-commerce speeds a business need to understand and predict consumer online behavior in order to be more competitive. While the whole world is embracing big data analytics, many businesses in Malaysia, particularly those in the ecommerce sector, find it hard to harness these technologies to their benefit. The absence of specific predictive models and the complexity of socio-cultural diversity further complicate the efforts toward understanding consumer preferences. Therefore, this research tries to fill in some of the gaps by applying decision tree and rule-based algorithms to classify online purchasing behavior amongst Malaysian consumers. The study …

Prediction Of Diabetic Retinopathy Among Diabetic Neuropathy In T2dm Patients Using Data Mining Algorithm, Nur Balqis Oon, Zuraida Khairudin, Hezlin Aryani Abd Rahman, Norbaizura Kamarudin, Nur Syamimi Haji Abu Bakar, Nor Azimah Abd Aziz

Malaysian Journal of Computing (MJoC)

Diabetic retinopathy (DR) and diabetic neuropathy (DN) are the most common complications among diabetes mellitus (DM) patients. Despite the widespread awareness, the implications of these serious diabetes complications remain poorly understood. Hence, this study aims to determine the association between DR and DN, predict DR and identify the significant risk factors associated with DR among DN patients based on the best predictive model obtained. Three models are employed in this study; Logistic Regression (LR) (Forward, Backward, Enter and Optimize), Decision Tree (Information Gain, Gini Index and Gain Ratio) and Artificial Neural Network with a splitting of 70-30. This study involved …

Analyzing The Impact Of Feature Selection Using Information Gain For Airlines Customer Satisfaction, Farah Aqilah Bohani, Farah Syazwani Mohamed Rashid, Yuzi Mahmud, Sitti Rachmawati Yahya

Malaysian Journal of Computing (MJoC)

Feature selection has become a focus of research in many fields that deal with machine learning and data mining because it makes classifiers cost-effective, faster, and more accurate. In this paper, the impact of feature selection using filter methods such as Information Gain is shown. The impact of feature selection has been analyzed based on the accuracy of two classifiers: J48 and Naïve Bayes. The Airline Customer Satisfaction datasets have been used for comparing with and without applying Information Gain. As a result, J48 achieved 0.33% and 0.29% improvements in accuracy after applying Information Gain for 10-fold and 20-fold cross-validation, …

Design And Fabrication Of Iot Smart Farm, Hazim Sharudin, Ab Aziz Mohd Yusof, Haszeme Abu Kasim, Noor Hafiz Noordin, Aiman Muqhriz Usuloudin

Malaysian Journal of Computing (MJoC)

This project will help farmers stay connected with their farm from anywhere. It can help to observe the temperature, humidity, and potential of hydrogen (pH) in the land. Most farmers will have difficulty keeping watch on the farm when traveling far away for work. The constant hot weather in Malaysia supports this. So, this project aims to design and fabricate an automatic plant watering system that helps farmers keep the farm in check at any place and time. The project will use a few sensors such as a temperature, pH, and soil humidity sensor to get the information needed and …

A New Framework For Deploying Virtual Desktop Infrastructure Using Containerization Approach, Nukman Samsuddin, Mohamad Yusof Darus, Muhammad Azizi Mohd Ariffin

Malaysian Journal of Computing (MJoC)

The COVID-19 pandemic accelerated the shift to virtual learning, pushing educational institutions to adopt innovative solutions like Virtual Desktop Infrastructure (VDI). However, traditional VDI faces performance issues due to resource limitations. This research aims to enhance VDI performance and scalability by proposing a new framework based on containerization to address performance degradation issues such as unutilized CPU and memory usage in VDI. Four key performance metrics—CPU performance, memory performance, boot time, and latency—were evaluated. This research employed a qualitative method involving five phases: problem identification, planning, design and development, testing, and result analysis. The results show that the proposed containerization …

Process Simulator For Manual Handling Pesticide Packaging Assembly Line, Siti Norhazlinda Roslan, Bulan Abdullah, Nor Hayati Saad, Razali Hassan, Siti Khadijah Alias

Malaysian Journal of Computing (MJoC)

Reducing production costs without sacrificing product quality is essential for the global market survival. The problem of line balancing, especially assembly line balancing, plays an important role for industry in achieving the highest quality and lowest cost. This project presents the simulation of line balancing the pesticide packaging assembly line in pesticidebased company. This study aims to develop a productive and effective way of assembling the product to meet customer demands. Line balancing is about arranging a production line so that the production flow from one workstation to the next is even. Line balancing also provides a successful tool to …

Osteoarthritis Grading A Synthesized Magnetic Resonance Images Technique, Qiu Ruiyun, Siti Khatijah Nor Abdul Rahim, Nursuriati Jamil, Raseeda Hamzah, Xiaoling Fu

Malaysian Journal of Computing (MJoC)

Osteoarthritis (OA) in the knee is a major cause of decreased activity and physical limitations among older people. Identifying and treating knee osteoarthritis in its early stages can help patients delay the progression of the condition. Currently, early detection of knee osteoarthritis involves the use of X-ray images and assessment using the Kellgren-Lawrence (KL) grading system. Doctors' evaluations can be subjective and may differ among different doctors. Similar to a computer systems analyst, the automatic knee OA grading and diagnosis can be a valuable tool for doctors, enabling them to streamline their workload and provide more efficient care. An innovative …

Drowsy Driver Detection System Via Facial Recognition And Driving Data, Nur Iman Kamila Azharudin, Hafizah Mansor, Shaila Sharmin

Malaysian Journal of Computing (MJoC)

According to the National Highway Traffic Safety Administration, an estimated 17.6% of all fatal crashes in the years 2017–2021 involved a drowsy driver. This study proposes a drowsy driver detection system that uses both facial recognition and vehicular data to detect if a driver is feeling sleepy behind the wheel. We aim to address a lack of works in the literature that combine data measured from the driver (image or biological data) and vehicular data for drowsy driver detection. Our primary data was collected from simulated driving sessions in which a camera was used to record test drivers’ faces while …

Conceptualising State-Centric Mediation: An Analysis Of China's Foreign Investment Complaints Mechanism, Mark Mclaughlin

Research Collection Yong Pung How School Of Law

This article argues that China's foreign investor complaints system constitutes 'state-centric investment mediation'. The Rules on Handling Complaints of Foreign-Invested Enterprises, which entered into force on 1 October 2020, place a state agency in the position of facilitating negotiations between a foreign investor and the agency being complained against. The prospects for this complaints system depend on how the state-as-mediator dynamic is perceived by foreign investors. To this end, it will be argued that settlement agreements reached pursuant to this system may be enforceable under the Singapore Convention on Mediation in certain circumstances. Investors and government entities operating similar systems …

Discovering Significant Topics From Legal Decisions With Selective Inference, Jerrold Tsin Howe Soh

Research Collection Yong Pung How School Of Law

We propose and evaluate an automated pipeline for discovering significant topics from legal decision texts by passing features synthesized with topic models through penalized regressions and post-selection significance tests. The method identifies case topics significantly correlated with outcomes, topic-word distributions which can be manually interpreted to gain insights about significant topics, and case-topic weights which can be used to identify representative cases for each topic. We demonstrate the method on a new dataset of domain name disputes and a canonical dataset of European Court of Human Rights violation cases. Topic models based on latent semantic analysis as well as language …

Tort Theory And The Restatement, In Retrospect, Keith N. Hylton

Faculty Scholarship

This is my third paper on the Restatement (Third) of Torts. In my first paper, The Theory of Tort Doctrine and the Restatement (Third) of Torts, I offered a positive economic theory of the tort doctrine that had been presented in the Restatement (Third) of Torts: General Principles, and also an optimistic vision of how positive theoretical analysis could be integrated with the Restatement project. In my second paper, The Economics of the Restatement and of the Common Law, I set out the utilitarian-economic theory of how the common law litigation process could generate optimal (efficient, wealth-maximizing) rules and compared …

Development Of Coarctation Of The Aorta Software To Combat Hypertension (Coach), Shahd Sawalhi

Master's Theses (2009 -)

Coarctation of the aorta (CoA) is a congenital cardiovascular defect characterized by narrowing of the proximal descending thoracic aorta and is often associated with long-term hypertension (HTN) even after treatment. The current threshold for intervention in CoA patients, defined by a >20 mmHg peak-to-peak blood pressure gradient (BPGpp), does not effectively prevent HTN post-treatment and depends on the approached used for BPGpp measurement. To address this, the objective of this study was to develop the Coarctation of the Aorta App to Combat Hypertension (CoACH), which integrates a new index, the continuous flow pressure gradient (CFPG). The CFPG provides a more …

The Design Of A Quality Improvement Dashboard For Monitoring Spinal Cord And Column Injuries, Zahra Azadmanjir, Mohsen Sadeghi-Naini, Mohammad Dashtkoohi, Maziar Moradi-Lakeh, Jalil Arabkheradmand, James Harrop, Vafa Rahimi-Movaghar

Department of Neurosurgery Faculty Papers

Background: Interactive dashboards are a powerful tool for dynamic visualization and monitoring of patient performance and serve as a useful to for optimal decision-making. The National Spinal Column and Cord Injury Registry of Iran (NSCIR-IR) was designed to efficiently display and broadcast important patient care data. This has been achieved through an electronic dashboard display (graph and visual displays), rather than traditional static paper reports (text). Objectives: The objective of this study was to design and develop an electronic visual dashboard as a display system to monitor the quality of care in the NSCIR-IR collaborating centers. Methods: The indicators chosen …

On Fire And Water: The Intersection Of Wetlands And Burning Strategies In Managing The Anthropogenic Plant Communities Of Yosemite National Park, Douglas Deur, Rochelle Bloom

Anthropology Faculty Publications and Presentations

The existing literature confirms that Native American tribes historically enhanced culturally preferred plant communities through periodic burning in what is today Yosemite National Park; in turn, beginning with nineteenth-century park development, fire suppression contributed to conifer and shrub encroachment on anthropogenic meadows and other culturally significant habitats. However, we contend that traditional burning practices cannot be understood without considering the pronounced cultural role of wetland habitats and species, and the intersection between burning practices and wetland plant communities among tribes of the Sierra Nevada Range. Our ethnographic investigations revealed that a majority of culturally important plants identified by tribal members …

Spring 2024 Shsp Alumni Connections, New York Medical College

School of Health Sciences and Practice

• NYMC Annual Days of Giving Set for March 26 and 27
• CDM Provides Hands-On Training for First Responders
• D.P.T. Class of 2025 Present Community Service Projects
• NYMC NSSLHA Chapter Hosts Fundraiser for Smile Train
• Students Shine at 2023 Multidisciplinary Community Outreach
• NYMC Celebrates Faculty Authorship at 30th Annual Recognition
• NYMC Hosts “Ninety Minutes: The Medical Magazine of the Web”
• Student Spotlight: Dr. P.H. Candidate Advocates for Long Term Care Through the Media
• Alumni Spotlight: SLP Alumna Opens Local Private Practice in Honor of Late Sister
• Alumni Spotlight: D.P.T. Alumnus Finds Solace in Writing After Cardiac Event

A Protective Role For Type I Interferon Signaling Following Infection With Mycobacterium Tuberculosis Carrying The Rifampicin Drug Resistance-Conferring Rpob Mutation H445y, Suhas Bobba, Kuldeep S. Chauhan, Sadia Akter, Shibali Das, Ekansh Mittal, Barun Mathema, Jennifer A. Philips, Shabaana A. Khader

2020-Current year OA Pubs

Interleukin-1 (IL-1) signaling is essential for controlling virulent Mycobacterium tuberculosis (Mtb) infection since antagonism of this pathway leads to exacerbated pathology and increased susceptibility. In contrast, the triggering of type I interferon (IFN) signaling is associated with the progression of tuberculosis (TB) disease and linked with negative regulation of IL-1 signaling. However, mice lacking IL-1 signaling can control Mtb infection if infected with an Mtb strain carrying the rifampin-resistance conferring mutation H445Y in its RNA polymerase β subunit (rpoB-H445Y Mtb). The mechanisms that govern protection in the absence of IL-1 signaling during rpoB-H445Y Mtb infection are unknown. In this study, …

“Art For The Millions:” The Evolution Of Informal Learning From The Charleston Museum To The New Deal, Kristen Walker

Theses

The advent of the first museum in the United States in 1773, The Charleston Museum, sparked a shift in the way education is perceived and how it can be conducted. However, only recently has the intentional implementation of programs and exhibitions been created in a digestible way for the public. This thesis discusses how informal learning has evolved since the establishment of the Charleston Museum and the legacy of the Federal Art Project regarding informal learning and art education. Key research methods include the examination of primary and secondary resources, including oral histories held by the Smithsonian Archives of American …

There’S Always Room For Improvement: Implementing Indoor Navigation Using ‘Mappedin’ In The Rochester Museum And Science Center To Enhance The Visitor Experience, Izzy Moyer

Theses

Since March 2020, museums have dramatically increased their use of technology in museums to make their environments more engaging to their visitors. For indoor navigation, for instance, museums have used still images, PDFs, and QR codes as well as analog measures (such as directional signage and paper maps) to help their visitors navigate their institution. While these are helpful for understanding one’s general location, other digital wayfinding measures can foster information sharing as well as the opportunity to decrease “spatial anxiety.” This thesis describes the creation of a map for portable, indoor navigation using “Mappedin,” a cost-effective platform that is …

Exploring Situational Factors For Female International Students And Their Satisfaction In Higher Education Using Cb-Sem, Dian Fu Chang, Angel Chang, Cheng Yi Kang

Faculty Research, Scholarly, and Creative Activity

While the topic of attracting and maintaining inbound international students has received much scholarly attention in higher education, attracting female international students has rarely been discussed. This study addresses the issue of attracting degree-seeking female international students. Based on the notion of situational factors and total quality management (TQM), we assumed both institutional design and students’ satisfaction are core concepts for attracting and retaining female international students that will make a difference in higher education. A total of 215 survey responses were analyzed, and a covariance-based structural equation modeling (CB-SEM) approach was developed. The results confirm female international students’ perception …

Anonymous Traffic Detection Based On Feature Engineering And Reinforcement Learning, Dazhou Liu, Younghee Park

Faculty Research, Scholarly, and Creative Activity

Anonymous networks, which aim primarily to protect user identities, have gained prominence as tools for enhancing network security and anonymity. Nonetheless, these networks have become a platform for adversarial affairs and sources of suspicious attack traffic. To defend against unpredictable adversaries on the Internet, detecting anonymous network traffic has emerged as a necessity. Many supervised approaches to identify anonymous traffic have harnessed machine learning strategies. However, many require access to engineered datasets and complex architectures to extract the desired information. Due to the resistance of anonymous network traffic to traffic analysis and the scarcity of publicly available datasets, those approaches …

Origin Of The Correlation Between Stellar Kinematics And Globular Cluster System Richness In Ultradiffuse Galaxies, Joel Pfeffer, Steven R. Janssens, Maria Luisa Buzzo, Jonah S. Gannon, Nate Bastian, Kenji Bekki, Jean P. Brodie, Warrick J. Couch, Robert A. Crain, Duncan A. Forbes, J. M.Diederik Kruijssen, Aaron J. Romanowsky

Faculty Research, Scholarly, and Creative Activity

Observational surveys have found that the dynamical masses of ultradiffuse galaxies (UDGs) correlate with the richness of their globular cluster (GC) system. This could be explained if GC-rich galaxies formed in more massive dark matter haloes. We use simulations of galaxies and their GC systems from the E-MOSAICS project to test whether the simulations reproduce such a trend. We find that GC-rich simulated galaxies in galaxy groups have enclosed masses that are consistent with the dynamical masses of observed GC-rich UDGs. However, simulated GC-poor galaxies in galaxy groups have higher enclosed masses than those observed. We argue that GC-poor UDGs …

Leveraging Sentiment Analysis For Tokyo Airbnb Hosts And Decision Makers, Shaikha Aldahmani

Theses

This study focused on the growing challenges that Tokyo Airbnb hosts and policymakers face in the holiday homes and home stays market. The study aimed to empower hosts with insights to optimize offerings and assist policymakers in informed decision-making for enhancing neighborhood experiences, with a focus on data-driven business strategies grounded in sentiment analysis. The project employed a robust methodology that leverages sentiment analysis techniques to gain insights from guest comments of Tokyo Airbnb listings spanning from September 2011 to June 2023. The CART algorithm and the Affin sentiment lexicon were used for data cleaning, consolidation, and sentiment analysis. The …

Optimizing Supply Chain Dynamics Using Machine Learning, Mohammad Zubin Siddiqui

Theses

Supply chains face many challenges in today’s business environment. This paper examines how advanced analytics can be used to improve supply chain efficiency and resilience with a particular focus on demand forecasting and late delivery analysis. The thesis focuses on two areas, which are forecasting demand and analyzing late deliveries. With the help of data-driven models for forecasting demand and pinpointing reasons behind delayed shipments, establishments can take appropriate measures that will reduce risks and enhance operational efficiency. A complete analytic framework is suggested that integrates sophisticated analytics into supply chain management so that organizations can optimize all their operations …

Robust Machine Learning Under Vulnerable Cyberinfrastructure And Varying Data Quality, Sergei Chuprov

Theses

In our study, we investigate Machine Learning (ML) application robustness in ML Integrated with Network (MLIN) systems. We consider MLIN as an integration of three major components and interrelations between them: data sources, network facilities, and ML application. In contrast to the conventional approaches that focus on each separate component, we concentrate on their interrelationships, and consider them from the system integration perspective. We formulate our primary goal as to develop methods and tools aimed at assuring ML application performance towards Data Quality (DQ) variation in MLIN through improving ML application robustness. We examine the prior work on ML robustness …

Learning From Disagreement In Human-Annotated Datasets, Tharindu Cyril Weerasooriya

Theses

Artificial intelligence (AI) systems frequently need to learn from human decision makers, which aids in scaling systems for mass use. We see this in automated financial decisions, manufacturing processes, self- driving cars, and content moderation on social networks. These systems are built on human values and trained to mimic human decision-making through human annotation. However, different groups of human annotators, including domain experts, annotate content differently, leading to disagreements. Some practitioners treat dissenting opinions as “label noise”. A common approach to dealing with disagreement is to consider a majority vote, which effectively conceals the disagreements from the trained model. Although …

Predictive Analytics Of Road Traffic Incidents, A Machine Learning Approach, Maryam Essa Jaji

Theses

Traffic accidents rank among the world's most serious concerns due to the high number of deaths, injuries, and fatalities as well as the enormous financial losses they cause every year. Road travel is a necessary component of modern civilization, but because of the rise in traffic accidents, it costs the world economy billions of dollars and over a million deaths annually. Road accidents can be caused by a variety of elements. It can be possible to take action to lessen the severity and extent of the effects if these elements are better recognized and predicted. The goal of this project …

Accommodating Spatio-Temporal Dependency In Airline Demand Modeling, Sudipta Dey Tirtha, Tanmoy Bhowmik, Naveen Eluru

Civil and Environmental Engineering Faculty Publications and Presentations

The objective of the current study is to examine monthly air passenger departures at the airport level considering spatial interactions between airports. In this study, we develop a novel spatial grouped generalized ordered probit (SGGOP) model system of monthly air passenger departures at the airport level. Specifically, we estimate two variants of spatial models including spatial lag model and spatial error model. In the presence of repeated demand measures for the airports, we also consider temporal variations of spatial correlation effects among proximally located airports by employing space and time-based weight matrix. The proposed model is estimated using monthly air …

Low Power Logic Locking Using Design Space Modeling To Achieve System-Wide Security, Long Lam

Theses

Rising design complexity and smaller technology nodes are escalating fabrication costs, prompting design houses to outsource to untrusted external facilities, which raises trust and privacy concerns. These concerns stem from the risk of security breaches like IP piracy, reverse engineering, and hardware trojans. The critical need to protect design intellectual property prompted the development of logic locking, a combinational hardware security technique that corrupts the functionality of a design without the correct secret key. However, the effectiveness of logic locking varies substantially based on how and where it is implemented within a system, including the specific technique families selected, the …