bluuebunny/crossref_metadata_2025 huggingface dataset:
EVOLUTION OF THE CONCEPT OF HUMAN RESOURCE MANAGEMENT
Authors:   Odessa National Maritime University, Yurganov Mykyta
Published: September 2024

The article is devoted to a complex analysis of the concept of "human resources management". The etymology of the term "human resource" and the attitude towards employees at each stage of the country's economic development were studied. In this period of time, the term "human resource" refers to the set of physical, psychological and mental potentials of a person, his mental characteristics, which, together with the accumulated knowledge, skills, information and experience, are used by an individual in the process of creating material, spiritual and intellectual products. Under the influence of external and internal factors in relation to a certain company, the management's attitude towards employees also changed, and accordingly, the requirements for each applicant for a certain position, which directly affects the choice of a human resources management strategy. Due to this, the evolution of the term "human resource" and its interpretation also took place as labor force, labor and personnel resources. In the sources at the moment you can find synonyms of this term, which are considered in the work. It was determined that in the post-industrial period of the development of society, the key asset in the economy is the employee. At the same time, special attention is paid to his intellectual development, especially emotional intelligence. The article noted that when selecting executors for any project, along with taking into account "hard skills", that is, specific knowledge and experience that are necessary for the performance of certain duties of each specialist and make up the skills of a specific profession, it is necessary to take into account , giving certain advantages to "soft skills". The work provides a list of basic soft skills that a specialist (especially a manager) should possess. They are classified by groups such as communication skills, critical thinking, leadership qualities, work capacity, creative skills. However, depending on the position, their recruitment may change. The author connects the perspectives of researching the problems of "human resource management" within the enterprise with the aim of increasing its efficiency with the research of the historical aspect of the emergence of this term.
ACCOUNTING AND ANALYTICAL SUPPORT FOR INVESTMENT IN INNOVATION: NATIONAL AND INTERNATIONAL STANDARDS
Authors:   National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Skorobogatova Natalia
Published: September 2024

The article presents an examination of the issue of the methodical accounting of investments in innovative activities of the enterprise. A review of the domestic and international regulatory framework and scientific literature reveals an absence of a clear mechanism for accounting for enterprises' investments in innovative activities. The article identifies the differences between invention and innovations from the perspective of accounting, taking into account their development and implementation stages. A methodical approach to the accounting and control of investments in innovation is put forth, based on the definition of the essential feature of the anticipated outcomes from the implementation of such investments. The proposed approach allows for the creation of an effective system of accounting and analytical support for investments in enterprise innovations, in accordance with the requirements of national accounting regulations (standards) and international accounting and reporting standards.
METHODOLOGY FOR EVALUATING CONSTRUCTION PROJECT MANAGEMENT IN THE CONTEXT OF SUSTAINABLE DEVELOPMENT
Authors:   Sumy National Agrarian University, Pihul Oleh , Glukh Vadym ,   Sumy National Agrarian University
Published: September 2024

The article is dedicated to developing a methodology for evaluating construction project management within the context of sustainable development. The aim of the article is to develop a methodology for assessing construction project management in the context of sustainable development. General scientific methods of cognition were used in the course of the research. The study's results show that the proposed methodology for evaluating construction project management in the context of sustainable development integrates key project management stages, including planning, execution, checking, and action. Each of these stages is interconnected with the phases of the product life cycle, which include raw material supply, production, use, maintenance, recycling, and disposal. At each stage, specialized indicators are used for a detailed analysis of the project's environmental impact. For instance, indicators such as CO2 emissions, resource use, waste management, energy efficiency, and other environmental parameters are assessed, allowing for a comprehensive evaluation of the project's alignment with sustainable development principles. The application of the Analytical Hierarchy Process (AHP) and its modifications, such as the Analytic Network Process (ANP), enhances decision-making through a structured analysis of the interdependencies among evaluation criteria. The use of weighting coefficients in the evaluation process allows for the calculation of an integrated indicator for each project level as well as for the entire life cycle. This approach enables not only the assessment of the current state of the project but also the monitoring of the long-term development dynamics of the construction project at various stages of its implementation. The proposed methodology allows construction companies to manage their projects more effectively by minimizing environmental impact and improving ecological efficiency in accordance with sustainable development principles. The practical significance of the research lies in creating a tool for comprehensive evaluation of construction project management, which will contribute to the enhanced effectiveness of project implementation in line with sustainable development principles.
РОЗВИТОК ЦИФРОВОЇ ТРАНСФОРМАЦІЇ ЕКОНОМІКИ РЕГІОНІВ УКРАЇНИ: ВИКЛИКИ ТА ПЕРСПЕКТИВИ
Authors: Пріхно І.М. , Марченко О.Ю.
Published: September 2024

У статті визначено критично важливі причини розуміння сутності дефініції «цифрова трансформація» та систематизовано підходи вчених-економістів щодо розуміння сутності цифрової трансформації. Сформульовано власне визначення дефініції «цифрова трансформація», під якою розуміємо процес інтеграції інформаційно-комунікаційних технологій в економічну систему держави з метою якісних змін її характеристик на основі використання інноваційних складових. Досліджено індекс цифрової трансформації в Україні в динаміці. З’ясовано, що індекс цифрової трансформації в Україні демонструє позитивну динаміку, але є ще значний потенціал для зростання. Виявлено чинники, які стримують темпи розвитку цифрової трансформації в Україні. Запропоновано напрями прискорення темпів розвитку цифрової трансформації, реалізація яких сприятиме зростанню економіки, покращенню якості життя та зміцненню державності.
PERAN PEMERINTAH INDONESIA DALAM MENDORONG TRANSISI ENERGI MELALUI SOUTH-SOUTH AND TRIANGULAR COOPERATION
Authors: Wijanarka Tunjung , Dewi Ni Nyoman Clara Listya
Published: September 2024

This article examines the Indonesian government’s role in using the South-South and Triangular Cooperation (SSTC) mechanism to promote clean energy transition and accomplish the Paris Agreement’s Nationally Determined Contribution (NDCs) targets through the Clean, Affordable, and Secure Energy for Southeast Asia (CASE) Project. The SSTC is a multi-sector cooperation framework among states that includes governmental actors, international organizations, and civil society, with the goal of pursuing sustainable development. This research employs Green theory and SSTC norms through a qualitative descriptive analysis and data gathering methods based on a literature review. The study indicates that the CASE Project, through collaborative initiatives involving grassroots movements, can evantually support the Indonesian government in attaining renewable energy transition and national NDC targets.
UNITED NATIONS OFFICE ON DRUGS AND CRIME (UNODC) MELALUI PROGRAM GLO. ACT ASIA DAN TIMUR TENGAH DALAM MENGATASI PERDAGANGAN MANUSIA DAN PENYELUNDUPAN MIGRAN
Authors: Feby Anggrela  , Robi Sugara
Published: September 2024

This study aims to analyze the eradication of human trafficking and migrant smuggling cases by UNODC through the GLO.ACT Asia and Middle East program in Afghanistan, Iraq, Iran, and Pakistan. This study was formulated by looking at the facts of program implementation in each country and then analyzed using the concepts of International Organizations, Trafficking in Persons, and Smuggling of Migrants with qualitative methods through interviews and literature studies. This study found that the GLO.ACT program has attempted to develop strategies and policies, legislative assistance, capacity building, regional and transregional cooperation, and protection and assistance to victims of these cases in the four countries. However, the GLO.ACT program intervention in target countries has different progress and challenges depending on the cooperation of each government and the ability of UNODC and its partners in managing the program
GEOPOLITICS OF MEDITERRANEAN REGION
Authors: Zafar Javed
Published: September 2024

The present paper will discuss the contemporary geopolitical setting of the Mediterranean region. This paper will examine how different powers, including Europe and Asia, are struggling to influence the Mediterranean strategic space. The paper will also discuss how the region is emerging as an alternative to Russian energy for Europe. Turkey is an important stakeholder and player in the Mediterranean region. Turkey has multiple interests, including cultural, economic, and strategic; therefore, the country is serious about its engagements in the region. The paper also focusses on how Turkey has been managing its interests in the region. The paper is based on descriptive and analytical research methods. The historically Mediterranean region always plays an important role in global geopolitics. The region is important for NATO. In the post-Cold War era, new coalitions were made in the region. Ukraine's war makes the region more important. Turkey is restructuring its strategy in the region
KENDALA AMERIKA SERIKAT DALAM MEREGULASI PERUSAHAAN MEDIA SOSIAL META PLATFORMS
Authors: Ivan Borneva
Published: September 2024

This research aims to analyze and understand what the obstacles for the United States are in regulating Meta Platforms (previously Facebook, inc.) which is the parent company of social media such as Facebook and Instagram. However, the various scandals that befell them further reduced US confidence regarding Meta's ability to carry out self-regulation. This research uses qualitative methods by collecting data through literature study and refers to two important elements of effective regulation proposed by Sheetal Radia. It was found that from the two senate sessions held, US senators, who on average became adults in an era without social media, still have a poor understanding of Meta's business model and how social media works. Also, the Federal Trade Commission, which is the main agency in dealing with data and privacy issues in the US, still has various limitations that make them less effective in reining Meta
ASEAN'S PREPAREDNESS AND RESPONSE AGAINST HYBRID THREAT IN CYBERSPACE
Authors: Gultom Yosua Saut Marulitua
Published: September 2024

This research examines ASEAN's readiness and response to threats in cyberspace. ASEAN is a region with growing internet users and a thriving economy. Unfortunately, ASEAN's cyber defense is considered low. This research uses the concept of hybrid threats by Hoffman which states that future conflicts/war create hybrid strategies, where conventional and non-conventional means are brought together to see the vulnerability. Using a descriptive study using primary and secondary data in the form of official documents, journal articles, news, and internet sources. This article found that China's rise in the cyber field, as well as the attack activities it has carried out both directly and indirectly, provide a strong threat perception for the ASEAN region.  For this reason, this article concludes that ASEAN must intensify collaboration within the region and with global partners while also establishing a comprehensive cyber defense strategy, including a potential for a cyber army across the region.
Path Dependencies of Urban Sprawl: Learning From the Evolution of a Mid-Size City and Its Transition From a Destination to Commuter Community
Authors: Sperry Jessica
Published: September 2024

Suburban sprawl research in Canada is directed to bigger cities. The evolution of suburban sprawl in the context of smaller Canadian mid-size cities such as Halifax is much less understood. This paper explores the outcomes of suburban sprawl in Lower Sackville, Nova Scotia. By tracing the evolution of the built form, this paper highlights various path dependencies that contribute and reinforce the built form of Lower Sackville today such as policy, physical geography, infrastructure, and changes in urban needs. During a period of post-suburban densification, planners can benefit from understanding the path-dependent systems that underlie the urban fabric of mid-size cities.
Imagery Rescripting of Hypothetical Worst-Case Scenarios: Impact on Worry and Associated Difficulties
Authors: Ovanessian Melina
Published: September 2024

Research suggests that when individuals with chronic worry engage in written exposure (i.e., "confront" their worries by writing them out in vivid, concrete detail), their worrying improves. The literature on imagery rescripting (IR), an intervention aimed at changing negative meanings linked to distressing memories, suggests that IR may augment the efficacy of written exposure for worry. The objective of the present study was to investigate the efficacy of a future-oriented written IR intervention for improving worry, generalized anxiety disorder (GAD) symptoms, and cognitive processes, relative to standard written exposure or neutral writing. Adults high in worry and GAD symptoms (N = 101) were randomly assigned to one of three conditions: (1) standard written exposure (WE), (2) written exposure with rescripting (RWE), or (3) neutral writing (NC) and engaged in four 30-minute writing sessions over the course of 2 weeks. During the 2-week intervention and 3 days postintervention, participants also tracked their day-to-day experiences of affect, worry duration, controllability, and intensity using an online diary. Outcomes were assessed at baseline, postintervention, 1-week and 1-month follow-ups. Participants in all three conditions displayed significant improvements in worry at midtreatment, but not posttreatment or follow-up. Participants in the RWE condition displayed significant improvements in general self-mastery, and perceptions of probability, cost, and coping.
Analysis of Orthotropic Bridge Decks with Supports Normal to Traffic under Canadian Truck Loading
Authors: Fronda Patrick
Published: September 2024

Orthotropic bridge decks spanning parallel to traffic direction take the form of (i) unidirectional open steel ribs, (ii) open steel grid, (iii) fully/partially filled steel grid, (iv) closed steel ribs, and (v) reinforced concrete slab. While the Canadian Highway Bridge Design Code specifies treating the fifth type as slab bridges with respect to the simplified method of analysis, it does not specify a reliable simplified method of analysis for the other deck types. This may lead to possible error due to neglecting the deck's flexural and torsional rigidity effects. Therefore, a parametric study was conducted, using the Orthotropic Plate Theory, on different deck configurations under truck loading conditions, with key parameters including deck span and width, longitudinal-to-transverse flexural rigidities, and torsional rigidities. The data generated from this research was used to develop reliable equations for the longitudinal and transverse moments, and deflection for use by designers and code writers.
What's Free?: The Struggle for Liberation Out of the Tradition of the Oppressed in Hip-Hop Nation
Authors: McConnell Cory
Published: September 2024

The aim of the present project is to work out the potential for contemporary liberation struggles emerging out of a unique constellation of the thought of Walter Benjamin and hip-hop alongside relevant sources from the fields of political theology and hip-hop studies. More specifically, I take up key concepts from Benjamin—including shock-experience, the tradition of the oppressed, citational practices, and translation—to work out how they might help make sense of the political work that the form—sampling and scratching—and content—lyrics—of hip-hop have always performed. With this in mind, the present project is neither a comparative work nor a Benjaminian reading of hip-hop (or vice versa). Rather, it is an attempt to draw out the political insights and a potentially viable political project out of my reading of Benjamin and continued engagement with hip-hop.
Mother-to-Child Transmission of Depressive Symptoms: Maternal Socialization of Infant Positive Affect as a Mediator
Authors: Schmitt Gabrielle
Published: September 2024

Numerous studies highlight the transmission of depressive symptoms from mothers to children; yet less is known about the mechanisms through which this transmission occurs. Using a prospective longitudinal design, the present study examined maternal socialization of positive affect as a mediator of the relationship between mothers' and toddlers' depressive symptoms. A community sample of 128 mother-infant dyads participated in three assessment periods. At 6 and 12 months postpartum, mothers reported on their depressive symptoms and were video recorded during 30 minutes of mother-infant play. The videos were subsequently coded for mothers' supportive and nonsupportive responses to their infants' positive affect. At 18 months, mothers rated their toddlers' depressive problems. A mediation analysis revealed that mothers with higher depressive symptoms were less supportive of their infants' positive affect, which in turn, increased infants' risk for depressive problems in toddlerhood. Findings have implications for future prevention and early intervention efforts.
Streamlining Low Impact Development Implementation in Ontario: Recommendations for Small- and Medium-Sized Municipalities
Authors: Sookoo Karuna
Published: September 2024

Low Impact Development (LID) is a component of stormwater management that has become necessary due to the effects of climate change and urbanization. This research explores policy instruments influencing LID implementation, with a focus on small- and medium-sized municipalities in Ontario. A comprehensive literature review revealed barriers experienced by municipalities. Standards, guidance, incentives, and policies for four municipalities in Ontario were examined. The cities of Philadelphia, Portland, Vancouver, and Burlington, which are considered to be green infrastructure (GI) leaders in North America, were studied for the purpose of gaining insight into factors leading to successful GI/LID implementation. This research concludes with five recommendations that can further enhance the utilization of GI/LID measures in new developments in Ontario.
An Ecotoxicological Approach Assessing the Effects of Weak EMFs on Hyalella Azteca, Lemna Minor, and Daphnia Magna Using Lethal and Sub-Lethal Endpoints
Authors: Stecko Paul
Published: September 2024

The application of EMFs in the environment are widespread yet little research has been completed to assess the ecotoxicological effect on ecologically-relevant organisms. This study aims to assess the ecotoxicological effects of an EMF device used to increase concentrations of dissolved oxygen in water. This was accomplished by using the lethal and sub-lethal endpoints of survival, reproduction, appearance (Lemna minor), and behaviour of Hyalella azteca, and Daphnia magna. All of the endpoints studied showed no statistical evidence that the studied organisms are negatively affected in-lab by these EMFs. A secondary aim of this study was to assess the difficulties and solutions in establishing new mass cultures in laboratories without the same access to various resources. The findings favoured reduced feeding and increased aeration in all vessels, and demonstrated that healthy organisms could be cultured under non-axenic conditions.
"We Are Nothing Alike": Analyzing Misrepresentation of Asian Peoples in Western Media
Authors: Payumo Soukaina
Published: September 2024

This major research paper (MRP) delves into the effects of misrepresentation of Asian communities through Asian characters portrayed in Western media. Subjects such as casting practices, stereotypes imposed on Asian characters, and the outcomes of negative portrayals are analyzed, assessing the ramifications of limiting Asian characters to roles that demean and undermine the diversity of Asian experiences. Positive portrayals of Asian characters are also explored in this paper, investigating the successful reception of films and TV shows that showcase dynamic storylines outside of racist and discriminatory narratives. Six Asian character portrayals in popular Western films and TV shows from the last four decades are examined through this MRP's research study: Long Duk Dong in Sixteen Candles (1984), Papillon Soo Soo and Leanne Hong as Vietnamese Prostitutes in Full Metal Jacket (1987), Rajesh Koothrappali in The Big Bang Theory (2007 - 2019), Mrs. Kim in Gilmore Girls (2000 - 2007), Josh Lin in Love Hard (2021), and Mindy Chen in Emily in Paris (2020 -). Major observations from this research study are thus utilized towards the project portion of this MRP: a rough trailer and a pilot episode script of Jayne and Vicky Get Loud. Jayne and Vicky Get Loud is light-hearted sitcom with an all-Asian main cast, written with a purpose to contribute towards diversifying television in Western media, diminishing outdated and harmful stereotypes, and helping to bring Asian peoples to the spotlight as multidimensional characters with their own complex stories to tell.
Digital Storytelling Practices for Cultivating Empathy in Children for E-Learning Purposes
Authors: Ortega Alcantar Daniel Andres
Published: September 2024

Digital storytelling is the practice of showing stories with different types of media. It can be used for educational purposes for teaching children new concepts and encouraging them to participate in digital conversations. Indeed, children can actively become involved in their own learning process, cognitive development can be fostered, and collaborative teaching practices can be enhanced significantly. Within the learning process, empathy is an essential component that allows children to share their perspectives linked to their personal identity. Empathy fosters emotional intelligence, and through stories, children can promote compassion and solidarity. This Major Research Paper proposes a digital storytelling model where empathy is integrated into the learning process for changing children's learning outcomes. A digital story was created to encourage children to interact with the narrative and understand other perspectives. Digital storytelling may help bolster empathy in children's learning experiences and expand their knowledge through a collaborative path.
A Computational Cardiac Modeling Approach to Study Directional Shock Vectors in Terminating and Modulating Rotors
Authors: Kulangareth Nikhil Valsan
Published: September 2024

Sudden Cardiac Death (SCD) is one among the leading causes of death worldwide. In an analysis, 56 % of the SCD is on account of Out-of-Hospital Cardiac Arrest (OHCA). In the United States, annually, about 356,000 patients experience OHCA, most of them being Ventricular Fibrillation (VF) or pulseless Ventricular Tachycardia (VT). Studies have shown the presence of spatio-temporally organized electrical activities called rotors during VF, and terminating these rotor-like activities can modulate or terminate VF in an in-hospital scenario or research set up. But this approach cannot be implemented in an OHCA scenario. In an OHCA scenario, where the timely intervention is very critical, electrical defibrillation is the main treatment option, and the shock delivered should be optimal, as a lower magnitude shock may not be able to terminate the arrhythmia. Similarly, a higher magnitude of shock than the threshold can lead to myocardial and neurological damages. In this work, the rotor termination approaches are extended into an OHCA scenario, and evaluated whether the effectiveness of the shock in an OHCA can be improved by targeting rotor-like activities or patterns. The hypothesis is that the direction of shock vector orientation has an impact on rotor termination and thereby can improve shock success. To test the hypothesis, a bidomain porcine cardiac model that can simulate rotor activities and defibrillation was developed. The results indicate that, the highest average likelihood of rotor termination is when the defibrillator pads are placed in perpendicular direction with respect to rotor (0.99 +/- 0.03), with an average current density of 7.2A/m2, compared to the parallel direction (0.76 +/- 0.26), and oblique direction (0.08 +/- 0.12). The voltage gradients for the termination were obtained in the acceptable range, and varied as 3.25, 4.71 and 5.37 V/cm for perpendicular, parallel and oblique directions respectively. As a summary, a computational model was used to demonstrate that the rotors are more likely to be terminated by optimizing the orientation of the defibrillation. Further, the results indicate that optimal defibrillator pad orientation combined with sufficient current density magnitude could improve the likelihood of rotor termination, thereby improving defibrillation success in an OHCA scenario.
Joint User Association and UAV Placement in HAP-UAV Integrated Networks
Authors: Goehar Huda
Published: September 2024

In this thesis, a collaboration scheme between a high-altitude platform (HAP) and several unmanned aerial vehicles (UAVs) for wireless communication networks is investigated. The HAP is the centralized entity configuring and managing the network and allocating the bandwidth ratios to users, while the UAVs function as relays to increase coverage and provide better service to ground users. The main objective of this study is to maximize the total downlink throughput of the ground users by optimizing the UAVs' three-dimensional (3D) placements and user associations. An optimization problem is formulated and a separate genetic algorithm-based approach combined with the exhaustive search algorithm is proposed to solve the optimization problem. The K-means algorithm is also utilized to find the initial UAV placement to reduce the convergence time of the proposed genetic algorithm-based allocation that jointly optimizes user association and 3D UAV position. The performance of the proposed algorithm is analyzed in terms of convergence time, complexity, and fairness. Finally, the simulation results show that the proposed HAP-UAV integrated network achieves a higher total throughput through joint user association and UAV placement schemes compared to a scheme with one HAP serving all users.
UAV-Based Multi-Sensor Integration for Precision Navigation and Object Classification
Authors: Elamin Ahmed Gamal Ali Mohamed
Published: September 2024

In this dissertation, a UAV-based multi-sensor data fusion for precision navigation and object classification for seamless indoor-outdoor applications was developed. A UAS equipped with a GNSS/IMU board, a low-cost mechanical LiDAR sensor, and an RGB camera, was used to collect data for the purpose of developing a multi-sensor integration system. Unfortunately, due to a malfunctioning GNSS antenna, there were numerous prolonged GNSS signal outages. To resolve this issue, a GNSS/INS/LiDAR-integrated system was developed. A LiDAR SLAM solution was used to update the INS solution through an EKF. Two case studies were considered: a complete GNSS outage and a GNSS PPP-assisted solution. In comparison with the complete GNSS outage, the results for the second case study were significantly improved. Subsequently, a low-cost UAV-based multi-sensor data fusion model was developed for land cover classification using a DCNN. The collected dataset was used to train and test the developed DCNN. In order to validate the DCNN, a second dataset was collected at a different urban location using a solid-state Lidar UAV-based system. It was shown that the proposed DCNN approach improved the overall accuracy of land cover classification significantly compared to the reference classifiers for both datasets. The feasibility of fusing UAV-based imaging and low-cost LiDAR data was explored to enhance pavement crack segmentation using a DCNN model. A third dataset was collected using the same UAS used in collecting the second dataset. Two types of pavement distress were investigated using the first and third datasets, namely cracks and sealed cracks. The performance metrics decreased for the crack samples in both datasets when the LiDAR data was added. This was essentially due to the quality of the lower-grade LiDAR sensor, which had low spatial resolution. In contrast, for the sealed crack, the addition of LiDAR data improved the matrices for the segmentation accuracy. Finally, an event-based visual-inertial odometry approach was proposed for precise indoor localization. The proposed approach fused events, standard frames, and inertial measurements. The proposed approach resulted in a significant decrease in the RMSE compared to the event-only and the frame-only cases, respectively.
Classification of Images to Detect Distracted Drivers
Authors: Ghaffar Salman
Published: September 2024

Vehicle accidents are a major concern in current transportation systems. The World Health Organization reports that road accidents are the eighth leading cause of death globally. Many of these accidents, over 80%, are caused by distracted driving such as using a mobile phone, talking to passengers, or smoking while behind the wheel. While efforts have been made to address this issue, there is no perfect solution. One potential approach is to use quantitative measures to assess driver activities and create a classification system that can detect distracting actions. In this project, a range of deep learning models are implemented and tested with various different parameter values, that can effectively classify driver distractions and increase driver awareness for improved safety. As a result of this experiment, it has been observed that base Convolutional Neural Network (CNN) model with seven convolutional layers when trained using augmented data performed the best in terms of accuracy. However, ResNet50 outperformed VGG16 based model when comparing transfer learning based models.
Pairing Indigenous and Western Science in the Rehabilitation of Pre-Settler Wetlands
Authors: Everatt Morrigan
Published: September 2024

Wetlands are vital ecosystems; however, changes to them through colonialism has caused a massive degradation. There is a lack of information on applying non-invasive native wetland plants as a solution to rehabilitate wetlands to pre-settler times. Indigenous and Western wetland science was first explored to establish what wetlands could look like to each group. Western wetland scholars value the function of wetlands, such as phosphorus removal. Indigenous Peoples respect wetlands as vital ecosystems as habitats for wildlife, for sustaining food, medicines, and structural resources. Through extensive literature review, wetland plants chosen have Indigenous cultural significance, are non-invasive, native, perennial, emergent, and able to thrive in hydroponic conditions. Carex vulpinoidea, Helenium autumnale, Lobelia cardinalis, Lobelia siphilitica, and Verbena hastata were able to grow under laboratory conditions. Further testing under laboratory conditions is recommended. Most critically, Western wetland research must partner with Indigenous scientists if sustainable rehabilitation of wetlands is to progress.
Examining the Potential of 5G Wireless Technology to Reduce the Digital Divide in Rural Canada
Authors: Shahid Mohammed Adnan
Published: September 2024

Today, a stable and robust broadband connection has become necessary due to the shift of traditional services towards digital and online platforms such as e-Government, e-Education, and e-Health. Canada's urban areas are getting the full advantages of broadband connectivity; however, rural areas are underserved due to low population density, terrain challenges, and less attractive business opportunities for the investor. This thesis explores the potential for 5G wireless networks to reduce the gap in residential broadband availability. It reviews the literature on the importance of broadband as an enabler of socio-economic inclusion, assesses Canada's digital divide and makes the case that continued action is needed to reduce the disparities in access between urban and rural areas. Technical solutions for providing broadband outside urban areas are described, noting that 5G is more capable than any previous wireless generation. The thesis concludes that 5G business case success is strongly dependent on the delivery of mobile wireless and fixed wireless on the same network to share the cost between services and earn more revenue. It also finds that smaller providers have a role in building out small projects that may be below the profit threshold of larger providers. To end the digital divide in Canada, federal and provincial governments and service providers must work together to develop a strong national broadband strategy that maximizes the impact of public investment.
Consumers' Intentions to Use Mobile Food Applications
Authors: Kwan Ralston
Published: September 2024

The use of mobile food applications (MFAs) significantly increased in the past decade. The MFA ecosystem is evolving, and companies need to consider the changing consumer habits to stay competitive. This quantitative study proposes a comprehensive model integrating the Unified Theory of Acceptance and Use of Technology (UTAUT2) and the Theory of Consumption Values (TCV) that examined the factors that affect the behavioural intent to use MFAs. 170 participants were surveyed using the convenience sampling technique administered through the SONA system. The statistical results and discussions showed that social influence was the most significant predictor on consumers' intention to use MFAs. Performance expectancy, hedonic motivation, and habit were also positively associated with the consumers' intention to use MFAs, while effort expectancy, food safety concerns, and affordance values were not. The findings partially supported the proposed model. Limitations of the study and suggestions for future research were discussed.
Using Ensemble Deep Learning and Feature Engineering Approaches to Classify Hospital Readmitted Heart Disease Patients
Authors: Bahrami Parsa
Published: September 2024

Heart disease is one of the leading causes of death worldwide and the costs associated with treating heart disease patients in the US is estimated to surpass $1 trillion by 2035. This is mainly due to the high rate of hospitalization of heart disease patients, as well as their high rate of readmission after being discharged from the hospital. In addition, currently the diagnosis of heart disease is primarily done by medical experts based on their experience and understanding of the disease and after reviewing patients' health history and clinical data, which increases the risk of errors, treatment time, and eventually the total cost of treating heart disease patients. To increase the efficiency of treatment offered by the healthcare professional and reduce the associated costs, it is crucial for an automated prediction model to be developed that can help reduce readmission rates by identifying high-risk patients before they are discharged, and accurately identify at-risk patients who have not yet been diagnosed with heart disease. This study combines deep learning and feature engineering approaches, and proposes a novel stacking ensemble deep learning model to classify hospital readmitted heart disease patients. The proposed model is evaluated by comparing its performance with various general and deep learning models using multiple performance evaluation metrics. The results demonstrate that the proposed model achieves the highest prediction performance among all metrics. Additionally, the study proposes how this model can be realistically deployed in real-world to augment critical healthcare professionals.
Modification of the Si Eutectic Phase in A319 Alloy With Lithium Additions
Authors: Belcastro Adam
Published: September 2024

Lightweight aluminum alloys play a significant role in improving the range and effectiveness of electric vehicles in the automotive industry. Lithium (Li) as an additive element in small quantities has the ability to reduce the weight and improve the mechanical properties of aluminum alloys. In this research, an addition of 0.2 wt.% Li reduced the Si eutectic reaction temperature significantly (‚âà15 °C). Further additions did not provide a significant improvement in this reaction temperature. At this Li concentration (0.2 wt.% Li), the Si eutectic phase was modified to fine grains of spherical morphology. Further additions did not change the morphology of the eutectic phase. XRD analysis determined that the observed blocky phase in the microstructure was AlLiSi, and the size of the particles increased with the Li additions. The porosity in the samples of Li containing alloys was non-uniform and this prevented the development of trends in the density and micro-hardness.
Multifunctional Blue-Green Infrastructure and Low Impact Development for Climate Change Adaptation
Authors: Almaaitah Tamer
Published: September 2024

Blue-Green Infrastructure (BGI) and Low Impact Development (LID) have been identified as promising approaches to help cities mitigate urbanization and adapt to climate change. Among BGI/LID systems, green roofs and permeable pavements are popular ground-based and rooftop applications. As the understanding of the performance of these two established applications has increased, efforts have been made to develop other technologies to maximize the multiple benefits of adapting to climate change. Through a series of three studies conducted by field monitoring, this dissertation investigates the hydrologic and thermal performance of blue and blue-green roofs, including farmed roofs as rooftop systems and permeable interlocking concrete pavers (PICP) and a dome concrete forming system (DCFS) as ground-based systems. The results revealed that the blue-green roof achieved the highest stormwater retention (63%) with the highly organic substrate, whereas the lowest retention was observed on blue roofs with larger orifices (32%). Blue-green roofs significantly improved detention and peak delay compared to green roofs. On the farmed blue-green roof, mean values for retention ranged from 85—88%, peak attenuation ranged from 82—85%, and peak delay ranged from 7.7 to 8 hours. Blue-green and green roofs with highly organic substrates had the highest near-surface air cooling (2.9 °C) compared to the green roof with FLL substrate (1.6 °C). On the rooftop farm and compared to a control roof, the mean air temperature difference above okra, tobacco and beet was 2.5 °C, whereas, above squash, potato and milkweed, it was 1.4 °C. Compared to conventional concrete pavement, the PICP and DCFS achieved an average runoff volume reduction of 33% and 85% and an average peak flow reduction of 43% and 89%, respectively. Surface and near-surface air temperatures were the highest on the DCFS due to the insulating effect of its void-based structure, with a warming effect of 2.3 °C on the surface and 0.7 °C on near-surface air. Altogether, the selection and design of these novel technologies would require a consideration of their trade-offs and a holistic approach considering environmental, social and economic aspects. Future research is therefore needed to determine the optimal design of each technology.
Network Anomaly Detection Scheme Using Graph Neural Network
Authors: Kisanger Patrice
Published: September 2024

Traditional intrusion detection systems (IDSs) and intrusion prevention systems (IPSs) focus on detecting, preventing, and blocking known attacks and obvious threats. Contrary to these systems, the Activity and Event Network (AEN) model is a newly proposed framework capable of identifying long-term threats and novel attack patterns such as custom crafted, multi-stage attack vectors, that the above-mentioned tools cannot detect as its design relies on a large random time varying graph model. In this thesis, the structural foundations of AEN graph are used as a basis to design a graph neural network (GNN)-based network anomaly detection scheme. This work is the first ever application of AEN to build a GNN model for anomaly detection purpose. The proposed model is evaluated using five different labelled datasets, namely, the DDoS, Tor-nonTor, Portmap, UDPLag, and SYN datasets, yielding preliminary promising results in terms of precision, recall, F1 score, and accuracy, chosen as performance metrics.
Optimization of C-Band Erbium Doped Distributed Feedback Fiber Laser
Authors: Bykov Igor
Published: September 2024

Distributed Feedback fiber lasers (DFB FL) are robust narrow linewidth laser sources with its signal generated in optical fiber and can be delivered across a substantial distance through the fiber. Moreover, DFB fiber lasers are relatively small and thus much easier to implement in many transducers. These advantages make DFB excellent for high accuracy sensing of pressure, temperature, and other physical parameters, as the narrow linewidth of DFB fiber lasers allows for high precision measurements. DFB fiber lasers are widely used in many important applications such as high precision meteorology, gravitational wave detection, and coherent LIDAR. These characteristics and applications have made DFB fiber lasers an important topic for research and development. The goal of this research is to improve the performance of DFB fiber lasers. The parameters in focus are the slope efficiency, linewidth, noise spectrum, and the stability of the emission wavelength to temperature variation. A passive athermal compensation package was also designed to stabilize the lasing wavelength with fluctuating temperatures, as well as to reduce the relative intensity noise (RIN). Implementation of these improvements will be discussed in this thesis to make linewidth narrower, RIN noise lower, and lasing wavelength insensitive to thermal fluctuations in normal operation. The measurement techniques for the laser linewidth and RIN etc. will be presented. Many DFB lasers were fabricated and tested. Among them, an Erbium doped fiber laser was made which operates at 1550 nm, with an approximate 1 kHz linewidth at -3 dB. This narrow linewidth was achieved with the use of an asymmetrical double super-Gaussian apodization mask to write the œÄ-phase shifted grating for the DFB. The asymmetrical double super-Gaussian mask also lets almost all the power to be emitted from only one end of the fiber cavity. The passive thermal compensation package decreased the Shot-noise floor of the RIN spectrum down to -150 dB/Hz from -140 dB/Hz. The slope efficiency of the laser almost doubled in comparison with the DFBs apodized with a single Gaussian profile. The thermal compensation packaging improved the emitting wavelength stability under varying temperatures by a factor of 14 from 9.8 pm/°C down to 0.69 pm/°C. The improvements proposed in this thesis can be applied to the DFB fiber lasers made with other gain fibers such as with Yb-doped and Tm-doped fibers.
Redesigning Google Glass With LiDAR, Location-Based AR, and Google Talkback to Act as a Live Assistant for Blind and Partially Sighted People
Authors: Takaffoli Macy
Published: September 2024

In this project, a device inspired by Google Glass is redesigned using modern technology to conceptualize how such a device could better serve the purpose of assisting individuals who are blind or partially sighted when navigating indoor and outdoor areas. Features such as a location-based Augmented Reality (AR) inspired by the ECHOES mobile app, a live voice translator, and distance detection for the obstacles (Using LiDAR technology) are compiled, to assist them in navigating the TMU indoor and outdoor campus with the goal of making the campus more accessible for individuals who are blind or partially sighted. Furthermore, this research consists of theoretical and practical parts using HCI (Human-Computer Interaction) and design principles that are engaged in both the research area and the design stage.
Social Media Information Privacy - Risks vs. Perceived Benefits: An Analysis of Motivations to Join LinkedIn
Authors: Paul Ricia
Published: September 2024

SNSs rely on users' willingness to self-disclose (Gruzd & García 2018). Many professionals shy away from Facebook/Instagram/Snapchat/TikTok citing concerns about privacy as well as the risk of possible backlash from liking or sharing the wrong post or opinion (Vitak & Kim 2014). Many fear the loss of income, a career setback, or being ostracized. However, the average professional has a public Linkedin Account that details private information e.g. education, and employment history - from which one can discern their income, location, etc. Utilizing thematic and discourse analysis, this study sought to uncover how the risks and perceived benefits of self-disclosure on social media are measured by young professionals, that predicate the motivation to join a professional SNS - Linkedin? The findings indicate that evolving talent acquisition trends fuelled by the COVID-19 pandemic, widespread social media adoption by employers and talent recruiters as well as high unemployment rates among other factors influence young professionals to join Linkedin.
Understanding the Invite-Only Strategy in Context of Social Media: An Analysis of Clubhouse
Authors: Sharma Akanksha
Published: September 2024

Clubhouse, a social networking application that combines the features of a teleconference call, radio show, podcast, and video chat, has amassed over 10 million users. Clubhouse, which launched in March 2020 during the COVID-19 pandemic, gave its users a platform to interact with strangers. "Silicon Valley's hottest start-up," and marketed itself as an "exclusive" application that appealed to people from all walks of life. This research examined how the application used exclusivity to attract customers and whether the start-up’s marketing strategy was successful.
Modeling and Investigating the Impact of Fermentation on the Anaerobic Digestion of Waste Sludges
Authors: Dadgarian Amirsaeed
Published: September 2024

In this research, the impact of fermentation on waste activated sludge (WAS), primary sludge (PS), and integrated WAS+PS were studied by BioWin® simulation software. The effect of SRT digester and fermentation were studied for SRT of 10, 20, and 30 days. The impact of fermentation and SRT was found proportional to the biodegradability of the raw sludges. Fermentation improved volatile suspension solids reduction (VSR), biodegradability, and methane production as SRT increased for all cases (i.e., WAS, PS, and PS+WAS). The simulation results of WAS indicated that the VSR increased up to 18% compared to the base model. In PS fermentation, VSR capability was as high as 25%, 43%, and 52% for SRT of 10, 20, and 30 days, respectively. The maximum effect of fermentation was observed for PS+WAS with SRT of 30 days in comparison to the base model scenario by implementing the integrated PS and WAS.