Expository Development of Materials for Live Online Instruction of "STATISTICS FOR RISK MODELING"

Throughout the year, I developed lecture notes, written examples, and lecture videos to aid students’ understanding of the statistical learning component in the future UNC course STOR 518W: “Statistics for Risk Modeling” (SRM). The primary course instructor and designer is my advisor, Dr. Robin Cunningham. This course is designed for the Society of Actuaries actuarial exam of the same name. The primary text for my portion of the course is "An Introduction to Statistical Learning, with Applications in R" (ISLR) by James, Witten, Hastie, and Tibshirani.Bachelor of Scienc

SITE-SPECIFIC GLYCOSYLATION ANALYSIS OF IgG3 AND THE EFFECT OF GLYCOSYLATION ON THE STRUCTURE, PHYSICAL STABILITY AND Fc RECEPTOR INTERACTIONS OF IgG3 Fc

Therapeutic monoclonal antibodies based on the IgG class of antibodies are glycoproteins that contain glycosylation sites within their Fc region. Glycosylation is important for Fc-mediated effector functions such as Antibody Dependent Cellular Cytotoxicity (ADCC) and Complement Dependent Cytotoxicity (CDC). IgG has four subclasses: IgG1, IgG2, IgG3 and IgG4. All IgG subclasses contain a consensus glycosylation site in the CH2 domain at N297, and glycosylation at that site is considered essential for optimal Fc function and stability. IgG3 is the only subclass that has an additional glycosylation site in the CH3 domain at N392. This site has nearly gone unmentioned and was only recently shown to be partially glycosylated in serum IgG3; however, the biological role of N392 glycosylation remains uninvestigated in the literature. The primary focus of this dissertation work is to study the effect of N-glycosylation on Fc receptor interactions, structure and physical stability of IgG3. LC-MS based glycopeptide mapping studies revealed that the N392 site is partially glycosylated in human serum IgG3 and the glycans at the N392 site showed significant differences compared to the N297 site in levels of core fucosylation, bisecting GlcNAc and mannosylation. The presence of glycosylation at the N392 site in the naturally occurring IgG3 establishes its biological relevance and makes a case for its characterization. For structural and biochemical characterization studies, the Fc fragment of IgG3 was expressed in a glycosylation-deficient strain of the yeast Pichia pastoris. Two variants of IgG3 Fc were produced, one with both sites glycosylated and another with only the N297 site glycosylated. These two forms were compared to investigate the effect of N392 glycosylation on the Fc receptor binding activity and physical stability of IgG3 Fc. Our results indicate that presence of the additional N392 glycan does not affect the binding of IgG3 Fc with the FcRIIIA and FcRn receptors but does affect the conformational stability and aggregation propensity of IgG3 Fc. Additionally, crystal structures of both the IgG3 Fc variants were determined with a resolution of 1.8-2.0 Å and were compared with the published structures of Fc fragments from the other IgG subclasses. Structural analysis of key amino acid differences between IgG3 and other IgG subclasses provided insight into IgG3-specific properties, especially related to binding with protein A, protein G, and the FcRn receptor. The importance of N297 glycans for IgG3 Fc- FcRIIIA interaction was also demonstrated from a structural perspective. The location and orientation of the N392 glycans in the IgG3 Fc structure provided a probable explanation for the observed effect of these glycans on Fc receptor binding activity and physical stability of IgG3 Fc

TeD-SPAD: Temporal Distinctiveness for Self-supervised Privacy-preservation for video Anomaly Detection

Video anomaly detection (VAD) without human monitoring is a complex computer vision task that can have a positive impact on society if implemented successfully. While recent advances have made significant progress in solving this task, most existing approaches overlook a critical real-world concern: privacy. With the increasing popularity of artificial intelligence technologies, it becomes crucial to implement proper AI ethics into their development. Privacy leakage in VAD allows models to pick up and amplify unnecessary biases related to people's personal information, which may lead to undesirable decision making. In this paper, we propose TeD-SPAD, a privacy-aware video anomaly detection framework that destroys visual private information in a self-supervised manner. In particular, we propose the use of a temporally-distinct triplet loss to promote temporally discriminative features, which complements current weakly-supervised VAD methods. Using TeD-SPAD, we achieve a positive trade-off between privacy protection and utility anomaly detection performance on three popular weakly supervised VAD datasets: UCF-Crime, XD-Violence, and ShanghaiTech. Our proposed anonymization model reduces private attribute prediction by 32.25% while only reducing frame-level ROC AUC on the UCF-Crime anomaly detection dataset by 3.69%. Project Page: https://joefioresi718.github.io/TeD-SPAD_webpage/Comment: ICCV 202

Egocentric RGB+Depth Action Recognition in Industry-Like Settings

Action recognition from an egocentric viewpoint is a crucial perception task in robotics and enables a wide range of human-robot interactions. While most computer vision approaches prioritize the RGB camera, the Depth modality - which can further amplify the subtleties of actions from an egocentric perspective - remains underexplored. Our work focuses on recognizing actions from egocentric RGB and Depth modalities in an industry-like environment. To study this problem, we consider the recent MECCANO dataset, which provides a wide range of assembling actions. Our framework is based on the 3D Video SWIN Transformer to encode both RGB and Depth modalities effectively. To address the inherent skewness in real-world multimodal action occurrences, we propose a training strategy using an exponentially decaying variant of the focal loss modulating factor. Additionally, to leverage the information in both RGB and Depth modalities, we opt for late fusion to combine the predictions from each modality. We thoroughly evaluate our method on the action recognition task of the MECCANO dataset, and it significantly outperforms the prior work. Notably, our method also secured first place at the multimodal action recognition challenge at ICIAP 2023

Ensemble Modeling for Multimodal Visual Action Recognition

In this work, we propose an ensemble modeling approach for multimodal action recognition. We independently train individual modality models using a variant of focal loss tailored to handle the long-tailed distribution of the MECCANO [21] dataset. Based on the underlying principle of focal loss, which captures the relationship between tail (scarce) classes and their prediction difficulties, we propose an exponentially decaying variant of focal loss for our current task. It initially emphasizes learning from the hard misclassified examples and gradually adapts to the entire range of examples in the dataset. This annealing process encourages the model to strike a balance between focusing on the sparse set of hard samples, while still leveraging the information provided by the easier ones. Additionally, we opt for the late fusion strategy to combine the resultant probability distributions from RGB and Depth modalities for final action prediction. Experimental evaluations on the MECCANO dataset demonstrate the effectiveness of our approach.Comment: 22nd International Conference on Image Analysis and Processing Workshops - Multimodal Action Recognition on the MECCANO Dataset, 202

TimeBalance: Temporally-Invariant and Temporally-Distinctive Video Representations for Semi-Supervised Action Recognition

Semi-Supervised Learning can be more beneficial for the video domain compared to images because of its higher annotation cost and dimensionality. Besides, any video understanding task requires reasoning over both spatial and temporal dimensions. In order to learn both the static and motion related features for the semi-supervised action recognition task, existing methods rely on hard input inductive biases like using two-modalities (RGB and Optical-flow) or two-stream of different playback rates. Instead of utilizing unlabeled videos through diverse input streams, we rely on self-supervised video representations, particularly, we utilize temporally-invariant and temporally-distinctive representations. We observe that these representations complement each other depending on the nature of the action. Based on this observation, we propose a student-teacher semi-supervised learning framework, TimeBalance, where we distill the knowledge from a temporally-invariant and a temporally-distinctive teacher. Depending on the nature of the unlabeled video, we dynamically combine the knowledge of these two teachers based on a novel temporal similarity-based reweighting scheme. Our method achieves state-of-the-art performance on three action recognition benchmarks: UCF101, HMDB51, and Kinetics400. Code: https://github.com/DAVEISHAN/TimeBalanceComment: CVPR-202

Exploring and Developing Measurements for the Dimension of Contract Governance in Malaysia’s Public-Private Partnership Initiatives

Since 1983, Malaysia has been implementing public-private partnership (PPP) initiatives to acquire public infrastructure and services. These partnerships have been successful in improving public services and reducing public expenditure. Many researches have been conducted on the factors influencing the performance of PPP, including contract governance. However, due to the long duration and contractual obligations of PPP initiatives, there is still a lack of understanding about the influence of contract governance on the performance of these partnerships, highlighting a scarcity of study on contract governance in PPP contexts. Based on mono-method quantitative design, this study aims to develop a survey instrument to measure contract governance in PPP initiatives through Exploratory Factor Analysis (EFA). A pilot study has been conducted with 115 respondents and the data been analyzed using the Principal Component with the Rotation extraction technique. The results showed that all five components of contract governance in the study had a Cronbach's alpha greater than 0.70, indicating a high level of consistency and reliability. The results of this research provide significant knowledge on the measurement of contract governance on PPP project performance to the body of literature on partnership performance and contract governance, therefore assisting concessionaires and policymakers. Managers overseeing PPP projects should possess the ability to improve the performance of their projects by comprehending the impact of contract. governance on project performance.

Functional outcome of arthroscopic labral repair in adults for traumatic shoulder instability: a prospective study

Background: Anterior shoulder instability is often treated either by open procedure or arthroscopic method. present study to assess the functional outcome of the patients with recurrent dislocation of shoulder with Bankart lesion, treated with arthroscopic stabilization to evaluate shoulder function with labral tear and after repair of labral tear, to study epidemiology of labral tear and to study epidemiology of associated lesions. Methods: Prospective study in the 25 consented patients admitted in the orthopaedics department in new civil hospital Surat with different shoulder injury after IEC approval. Statistical analyses done in MS excel. Results: Mean age at time of first dislocation was 30 year and most (50%) were of 20-30 years. Most patients were males (92%). 84% of the cases, the dominant side is involved, right shoulder. Number of episodes of recurrent dislocation prior to surgery averaged 5 times. most common mechanism was Accidental fall (48%) followed by sports (32%), RTA (20%). Association of Hill-Sachs lesions was 80% with labral-tear secured with extra suture anchor. Preoperative parameters; number of dislocations, chronicity, reduction method do not have any significance on outcome. Rowe-score improved from 40.2% Preoperatively to 89.8% postoperatively at 12 weeks. 80% of patients is having excellent outcome. Conclusions: Arthroscopic Bankart’s repair is gold standard for labral tear due to recurrent shoulder dislocation which led to short surgery time, less intraoperative and postoperative complications, increased shoulder function among patients. Associated Hill Sach’s lesion should be repaired for better functional outcome