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COMMITTEE CHAIR<\/strong>: Dr. Harshica Fernando<\/p>\n

TITLE<\/strong>: SYNTHESIS AND CHARACTERIZATION OF MIXED GREEN NANO CATALYSTS FOR AMMONIA SYNTHESIS<\/p>\n

ABSTRACT: <\/strong>Ammonia, (NH3), is a chemical that is most used industrially for uses that sustain millions of people, such as in the agricultural industry in fertilizers or in other potential applications like energy storage and power generation. This chemical is possible to be produced at a grand scale because of the Haber-Bosch Process developed in 1913. While the Haber-Bosch Process is renowned for the ammonia synthesis process and the effects it has had on the world over the past century, it is a significant contributor of around 1-2% CO2 emissions annually and the Iron (Fe) catalyst requires extreme conditions for the reaction to take place. In turn, recent research has pivoted in exploring mild conditioned methods of ammonia synthesis. In addition, the synthesis and characterization of a green mixed metal nano catalyst, Iron Tungsten (FeW), for photocatalytic NH3 synthesis. The nano catalyst was characterized by using Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscope (SEM), Energy Dispersive Spectroscopy (EDS), X-ray Diffraction (XRD), X-Ray photoelectron spectroscopy (XPS), and redox properties evaluated using cyclic voltammetry. The results show the qualities such as size, redox potential and surface chemistry of the nano catalysts that could determine how it plays a role in ammonia synthesis. The quantification of ammonia from the Photocatalytic synthesis was measured using an Ion Selective Electrode. Results show the mixed metal nano catalyst was effective in the ammonia synthesis process.<\/p>\n

Keywords: <\/strong>Nano catalyst, Ammonia Synthesis, Photocatalytic, Dextrose, Mixed Metal, Green Synthesis<\/p>\n

Room Location: <\/strong>New Science Building, Room 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21:05:21","url":"https:\/\/www.pvamu.edu\/graduateschool\/event\/breayshia-traneece-perry-masters-thesis-defense-tuesday-august-4-2026-1100-am-central-time\/","rest_url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/tribe\/events\/v1\/events\/9602","title":"Bre’Ayshia Traneece Perry Master\u2019s Thesis Defense, Tuesday, August 4, 2026 @ 11:00 am Central Time","description":"

COMMITTEE CHAIR<\/strong>: Dr. Gina Chiarella Mansilla<\/p>\n

TITLE<\/strong>: EVALUATION OF FOUR IRON OXIDE-OXYHYDROXIDE SORBENTS FOR ARSENIC REMOVAL IN FERTILIZER AND SOIL AMENDMENT SYSTEMSSYNTHESIS AND CHARACTERIZATION OF MIXED GREEN NANO CATALYSTS FOR AMMONIA SYNTHESIS<\/p>\n

ABSTRACT:\u00a0<\/strong>Arsenic contamination in agricultural fertilizers and soil amendments has become a significant environmental concern due to the persistence, mobility, and toxicity of arsenic species, as well as their potential transfer into soils, groundwater, crops, and ultimately, the food chain. Iron-based materials have been widely recognized as effective adsorbents for arsenic remediation; however, their performance in complex environments derived from fertilizers has not been systematically evaluated. This study investigates the adsorption of arsenate [As(V)] using four iron-based sorbents: natural goethite, goethite nanoparticles, ferrihydrite, and magnetite nanoparticles synthesized via a sol-gel method. Six commercially available fertilizers and soil amendment products were selected to represent a range of agricultural matrices differing in nutrient composition, phosphorus content, and organic matter levels. Initial experiments examined the effect of solution pH on arsenic adsorption, followed by batch adsorption studies designed to evaluate the influence of fertilizer composition, sorbent type, and arsenic concentration under controlled laboratory conditions. Adsorption experiments were conducted using a 100 ppm As(V) stock solution and a series of working concentrations to assess adsorption efficiency and sorbent performance across environmentally relevant conditions. The physicochemical properties of the iron-based materials were characterized before and after arsenic adsorption using Fourier Transform Infrared Spectroscopy (FTIR), Powder X-ray Diffraction (PXRD), Scanning Electron Microscopy (SEM), Thermogravimetric Analysis (TGA), and X-ray Photoelectron Spectroscopy (XPS). Quantitative determination of arsenic removal was performed using Atomic Absorption Spectroscopy (AAS) and Inductively Coupled Plasma (ICP) analysis. The combined use of these techniques provides detailed insight into adsorption mechanisms, surface interactions, and structural changes associated with arsenic uptake in fertilizer-containing systems. The results of this study are expected to advance the understanding of arsenic interactions with iron-based sorbents in agriculturally relevant environments and support the development of effective remediation strategies aimed at reducing arsenic contamination in fertilizers, soils, and agricultural production systems.<\/p>\n

Keywords:\u00a0<\/strong>Arsenic, Fourier Transform Infrared Spectroscopy, Inductively Coupled Plasma, Powder X-ray Diffraction<\/p>\n

Room Location:\u00a0<\/strong>E.E. O\u2019Banion Science Building, Room 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COMMITTEE CHAIR<\/strong>: Dr. Daniel Doe
\nCOMMITTEE CO-CHAIR<\/strong>: Dr. Anthony Hill<\/p>\n

TITLE<\/strong>: A HYBRID PHYSICS-GUIDED AI FRAMEWORK FOR SOURCE-AWARE ANOMALY DETECTION AND DIAGNOSIS IN THREE-PHASE PHOTOVOLTAIC SYSTEMS<\/p>\n

ABSTRACT:\u00a0<\/strong>As photovoltaic (PV) systems progressively integrate into modern power architecture, reliable monitoring and fault detection methods are essential to ensure efficient and stable operation. Customary monitoring systems constantly rely on simple data visualization or threshold-based alarm, which sometimes fail to detect subtle abnormalities in the system\u2019s behavior. This research proposes a physics informed ground truth framework for anomaly detection in PV power systems. It will exemplify a system designed to integrate statistical analysis with electrical power system constraints. The proposed methodology uses operational data collected from a three-phase photovoltaic system. The specific features utilized are measurements of phase voltages, currents, power, solar irradiance, and cell temperature. This data analysis is performed in Python, where statistical anomaly detection techniques are applied to find unusual operating conditions within the time-series dataset. To make detection more reliable, the statistical results are further confirmed using Physics-based ground-truth equations derived from three-phase power system principles. Beyond detection, the framework includes a source-aware classification stratum that distinguishes whether the anomalies originate from environmental factor, like fluctuations in irradiance, variations in temperature, and electrical faults within the system. Results are attained by analyzing the relationships between environmental inputs and electrical outputs to identify physically consistent patterns associated with each anomaly type. To further evaluate the effectiveness of the proposed system architecture, PSIM simulations are used to model photovoltaic system behavior under both normal and abnormal operating conditions. The simulations tested are scenarios varying in environmental disturbances and electrical faults. Anomalies identified are cross-referenced with simulated system responses to validate the framework\u2019s ability to correctly identify both the presence and source of abnormal behavior. The results show that combining machine learning with the validity of Physics-based equations and source-aware classification can significantly improve the accuracy and clarity of anomaly detection in photovoltaic systems. The proposed structure provides a reliable way for identifying abnormal system conditions. It also offers a scalable foundation for developing more intelligent monitoring of three-phase solar energy systems.<\/p>\n

Keywords:\u00a0<\/strong>Anomaly Detection, machine learning, photovoltaic systems (PV), renewable energy systems, time-series analysis, physics-based validation<\/p>\n

Room Location:\u00a0<\/strong>Electrical Engineering Conference Room 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COMMITTEE CHAIR<\/strong>: Dr. Stella Smith<\/p>\n

TITLE<\/strong>: SHAPING LEADERSHIP SYSTEMS: A MULTIPLE CASE STUDY OF BLACK FEMALE EXECUTIVE-LEVEL HUMAN RESOURCES LEADERS IN TEXAS K-12 EDUCATION<\/p>\n

ABSTRACT:<\/strong> Despite increasing attention to diversity, equity, and inclusion within educational leadership, Black women remain underrepresented in executive-level leadership positions across K-12 educational systems. Existing scholarship has documented barriers related to race, gender, leadership access, organizational culture, and career advancement; however, comparatively limited research has examined the experiences of Black female executive-level Human Resources leaders serving in central administration positions. Given the strategic role executive Human Resources leaders play in shaping workforce systems, leadership development, employee relations, organizational policy, and districtwide decision-making, this population represents an important yet underexamined area of educational leadership scholarship. The purpose of this qualitative multiple-case study is to explore how Black female executive-level Human Resources leaders serving in Texas K-12 educational systems navigate and influence organizational systems while operating at the intersection of race, gender, executive authority, and organizational power. Guided by Black Feminist Thought (Collins, 2000, 2022) and Intersectionality Theory (Crenshaw, 1989) and informed by Culturally Responsive Leadership (Khalifa et al., 2016) as the study’s applied leadership lens, the study seeks to understand how participants construct leadership identities, experience organizational power, and enact equity-centered leadership practices through district-level workforce systems and organizational decision-making. Using a qualitative multiple-case study design guided by Yin (2018), data will be collected through semi-structured interviews with Black female executive-level Human Resources leaders serving in Texas K-12 central administration positions. Data will be analyzed through preparation of the data, transcription verification, familiarization with participant narratives, initial coding, within-case analysis, cross-case analysis, theme development, and interpretation through the integrated theoretical and conceptual frameworks. This study is not intended solely to document inequities experienced by Black women in executive leadership. Rather, it seeks to understand how Black female executive-level Human Resources leaders remain influential while navigating organizational systems that shape leadership opportunity, executive decision-making, and workforce strategy. The findings may contribute to educational leadership, Human Resources leadership, organizational leadership, and equity scholarship by expanding understanding of executive Human Resources leadership as a strategic site of organizational power. In doing so, the study extends existing scholarship beyond questions of representation to examine how Black female executive leaders exercise influence, shape organizational systems, develop leadership capacity, and operationalize equity within Texas K-12 educational organizations.<\/p>\n

Keywords<\/strong>: Black feminist thought, black female executive leaders, culturally responsive leadership, executive human resources leadership, intersectionality, organizational power, qualitative multiple-case study<\/p>\n

\u00a0<\/strong>Zoom Link<\/strong>:<\/p>\n

https:\/\/pvpanther.zoom.us\/j\/85240132797?pwd=z7E2inanXAUFasCsYsSMjqlkwcaoLy.1<\/a><\/p>\n

Meeting ID: 852 4013 2797<\/p>\n

Passcode: 278739<\/p>\n<\/div><\/div><\/div><\/div><\/div>","excerpt":"","slug":"deedra-davis-dissertation-proposal-defense-monday-august-10-2026-100-pm-central-time","image":{"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17.jpg","id":9649,"extension":"jpg","width":2560,"height":1703,"filesize":368052,"sizes":{"medium":{"width":300,"height":200,"mime-type":"image\/jpeg","filesize":14845,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-300x200.jpg"},"large":{"width":1024,"height":681,"mime-type":"image\/jpeg","filesize":89649,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-1024x681.jpg"},"thumbnail":{"width":150,"height":150,"mime-type":"image\/jpeg","filesize":7333,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-150x150.jpg"},"medium_large":{"width":768,"height":511,"mime-type":"image\/jpeg","filesize":57670,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-768x511.jpg"},"1536x1536":{"width":1536,"height":1022,"mime-type":"image\/jpeg","filesize":166639,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-1536x1022.jpg"},"2048x2048":{"width":2048,"height":1362,"mime-type":"image\/jpeg","filesize":263108,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-2048x1362.jpg"},"search-live-thumbnail-32x32":{"width":32,"height":32,"mime-type":"image\/jpeg","filesize":1345,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-32x32.jpg"},"blog-large":{"width":669,"height":272,"mime-type":"image\/jpeg","filesize":30796,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-669x272.jpg"},"blog-medium":{"width":320,"height":202,"mime-type":"image\/jpeg","filesize":15679,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-320x202.jpg"},"recent-posts":{"width":700,"height":441,"mime-type":"image\/jpeg","filesize":49189,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-700x441.jpg"},"recent-works-thumbnail":{"width":66,"height":66,"mime-type":"image\/jpeg","filesize":2716,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-66x66.jpg"},"fusion-200":{"width":200,"height":133,"mime-type":"image\/jpeg","filesize":8327,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-200x133.jpg"},"fusion-400":{"width":400,"height":266,"mime-type":"image\/jpeg","filesize":22319,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-400x266.jpg"},"fusion-600":{"width":600,"height":399,"mime-type":"image\/jpeg","filesize":40511,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-600x399.jpg"},"fusion-800":{"width":800,"height":532,"mime-type":"image\/jpeg","filesize":61640,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-800x532.jpg"},"fusion-1200":{"width":1200,"height":798,"mime-type":"image\/jpeg","filesize":113483,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-1200x798.jpg"},"portfolio-full":{"width":940,"height":400,"mime-type":"image\/jpeg","filesize":53561,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-940x400.jpg"},"portfolio-one":{"width":540,"height":272,"mime-type":"image\/jpeg","filesize":27720,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-540x272.jpg"},"portfolio-two":{"width":460,"height":295,"mime-type":"image\/jpeg","filesize":26871,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-460x295.jpg"},"portfolio-three":{"width":300,"height":214,"mime-type":"image\/jpeg","filesize":15689,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-300x214.jpg"},"portfolio-five":{"width":177,"height":142,"mime-type":"image\/jpeg","filesize":7994,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-177x142.jpg"},"sow-carousel-default":{"width":272,"height":182,"mime-type":"image\/jpeg","filesize":12825,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-17-272x182.jpg"}}},"all_day":false,"start_date":"2026-08-10 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16:37:01","url":"https:\/\/www.pvamu.edu\/graduateschool\/event\/lorie-proctor-dissertation-proposal-defense-tuesday-august-11-2026-100-pm-central-time\/","rest_url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-json\/tribe\/events\/v1\/events\/9652","title":"Lorie Proctor Dissertation Proposal Defense, Tuesday, August 11, 2026 @ 1:00 pm Central Time","description":"

COMMITTEE CHAIR<\/strong>: Dr. Stella Smith<\/p>\n

TITLE<\/strong>: BEYOND A CROWN: EXPLORING LEADERSHIP IDENTITY THROUGH A COLLEGIATE SCHOLARSHIP PAGEANT AT A HISTORICALLY BLACK COLLEGE AND UNIVERSITY<\/p>\n

ABSTRACT:<\/strong> Historically Black Colleges and Universities (HBCUs) have played a central role in developing student leaders, especially Black women. This qualitative study explores how participation in a collegiate scholarship pageant at an HBCU shapes the leadership identity for Black women, guided by Komives et al. (2005) Leadership Identity Development model. While pageants are often seen as surface-level or entertainment-focused, this research reframes them as intentional, culturally grounded spaces that foster leadership, self-awareness, agency, and confidence through experiential learning. The study draws on Cultural Responsiveness (Gay, 2010; Ladson-Billings, 1995) and Black Feminist Thought (Collins, 2000) to examine how gender performance and cultural identity inform leadership development. Specifically, it investigates: (1) How do former titleholders of HBCU collegiate pageants describe the ways their pageant experiences shaped and continue to shape their leadership identity? ; (2) How do former titleholders interpret and reflect on their leadership roles within the cultural and gendered context of an HBCU? ; and (3) How do former titleholders identify and describe the aspects of the collegiate pageant experience that most shaped their leadership practice and voice as Black women?<\/p>\n

Data will be collected through in-depth, semi-structured interviews. The goal is to center the voices of Black women who engaged in this women-centered program and to highlight how their experiences, rooted in cultural affirmation and intersectional identities shape their sense of leadership. This study challenges conventional leadership narratives and expands the understanding of how culturally affirming programs contribute to leadership development in higher education. It also adds to the limited research on Black women\u2019s leadership pathways, particularly within the context of HBCUs.<\/p>\n

Keywords<\/strong>: Leadership Identity Development, Cultural Responsiveness, Black Feminist Thought, Historically Black Colleges and Universities (HBCUs), Collegiate Scholarship Pageants, Black Women<\/p>\n

Zoom Link<\/strong>:<\/p>\n

https:\/\/pvpanther.zoom.us\/j\/81600603777?pwd=dZUrBgO6I98t676V8EDhThltuJoUmD.1<\/a><\/p>\n

Meeting ID: 816 0060 3777<\/p>\n

Passcode: 837197<\/p>\n<\/div><\/div><\/div><\/div><\/div>","excerpt":"","slug":"lorie-proctor-dissertation-proposal-defense-tuesday-august-11-2026-100-pm-central-time","image":{"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18.jpg","id":9653,"extension":"jpg","width":2560,"height":1703,"filesize":368052,"sizes":{"medium":{"width":300,"height":200,"mime-type":"image\/jpeg","filesize":14845,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-300x200.jpg"},"large":{"width":1024,"height":681,"mime-type":"image\/jpeg","filesize":89649,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-1024x681.jpg"},"thumbnail":{"width":150,"height":150,"mime-type":"image\/jpeg","filesize":7333,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-150x150.jpg"},"medium_large":{"width":768,"height":511,"mime-type":"image\/jpeg","filesize":57670,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-768x511.jpg"},"1536x1536":{"width":1536,"height":1022,"mime-type":"image\/jpeg","filesize":166639,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-1536x1022.jpg"},"2048x2048":{"width":2048,"height":1362,"mime-type":"image\/jpeg","filesize":263108,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-2048x1362.jpg"},"search-live-thumbnail-32x32":{"width":32,"height":32,"mime-type":"image\/jpeg","filesize":1345,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-32x32.jpg"},"blog-large":{"width":669,"height":272,"mime-type":"image\/jpeg","filesize":30796,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-669x272.jpg"},"blog-medium":{"width":320,"height":202,"mime-type":"image\/jpeg","filesize":15679,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-320x202.jpg"},"recent-posts":{"width":700,"height":441,"mime-type":"image\/jpeg","filesize":49189,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-700x441.jpg"},"recent-works-thumbnail":{"width":66,"height":66,"mime-type":"image\/jpeg","filesize":2716,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-66x66.jpg"},"fusion-200":{"width":200,"height":133,"mime-type":"image\/jpeg","filesize":8327,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-200x133.jpg"},"fusion-400":{"width":400,"height":266,"mime-type":"image\/jpeg","filesize":22319,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-400x266.jpg"},"fusion-600":{"width":600,"height":399,"mime-type":"image\/jpeg","filesize":40511,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-600x399.jpg"},"fusion-800":{"width":800,"height":532,"mime-type":"image\/jpeg","filesize":61640,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-800x532.jpg"},"fusion-1200":{"width":1200,"height":798,"mime-type":"image\/jpeg","filesize":113483,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-1200x798.jpg"},"portfolio-full":{"width":940,"height":400,"mime-type":"image\/jpeg","filesize":53561,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-940x400.jpg"},"portfolio-one":{"width":540,"height":272,"mime-type":"image\/jpeg","filesize":27720,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-540x272.jpg"},"portfolio-two":{"width":460,"height":295,"mime-type":"image\/jpeg","filesize":26871,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-460x295.jpg"},"portfolio-three":{"width":300,"height":214,"mime-type":"image\/jpeg","filesize":15689,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-300x214.jpg"},"portfolio-five":{"width":177,"height":142,"mime-type":"image\/jpeg","filesize":7994,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-177x142.jpg"},"sow-carousel-default":{"width":272,"height":182,"mime-type":"image\/jpeg","filesize":12825,"url":"https:\/\/www.pvamu.edu\/graduateschool\/wp-content\/uploads\/sites\/41\/doctorat-PV-18-272x182.jpg"}}},"all_day":false,"start_date":"2026-08-11 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COMMITTEE CHAIR<\/strong>: Dr. Justin Foreman<\/p>\n

TITLE<\/strong>: MULTI-LEVEL, MULTI-PROTOCOL AUTONOMOUS INTRUSION DETECTION FRAMEWORK FOR INDUSTRIAL OPERATIONAL-TECHNOLOGY NETWORKS<\/p>\n

ABSTRACT: <\/strong>Modern industrial facilities such as power grids, water treatment plants, and manufacturing lines increasingly connect their operational-technology (OT) systems to enterprise IT networks. This convergence improves efficiency but widens the attack surface, because industrial protocols such as MQTT, Modbus TCP, and DNP3 were designed for reliability and interoperability long before cybersecurity became a central design concern. These protocols now carry traffic across multiple levels of the Purdue reference model, yet most existing intrusion detection research addresses only a single protocol, stops at producing an alert, gives little attention to where a detector should sit in the network, and offers operators limited insight into why an alert was raised. This dissertation proposes and evaluates a multi-level, multi-protocol autonomous intrusion detection framework for these converged environments. The framework places a dedicated passive detection agent at the correct Purdue level for each protocol: MQTT at the integration level (Level 3.5), Modbus TCP at the supervisory-control level (Levels 1\u20132), and DNP3 at the field-device level (Level 1). Each agent follows the same four-step process. It passively observes traffic, extracts protocol-specific features, classifies the traffic with a machine-learning model, and produces an English explanation for the operator through a rule-based content-awareness layer. This explanation approach is deterministic and fully auditable, which suits safety-critical OT settings; large-language-model-based explanation is reserved as future work.The methodology combined benchmark evaluation, feature extraction directly from raw packet captures, supervised learning, imbalance-treatment comparison, deliberate leakage prevention, and behavior-only ablation testing, validated end-to-end in the ICS-SimLab containerized testbed. Across all three protocols, Random Forest proved the most defensible classifier. SMOTE consistently outperformed naive upsampling on MQTT but produced classifier-dependent results on Modbus TCP. Per-packet timing features dominated detection across every protocol, though ablations showed that full-feature performance relied partly on network-identity features, an honest limit on cross-site transfer. The study finds that a passive, explainable, availability-preserving autonomous framework is feasible across multiple industrial protocols, while future work must validate cross-agent coordination, cross-site transfer, robustness against evasive attacks, and production deployment.<\/p>\n

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