Search results for: video indexing and retrieval

Authors: Divya SY. Ang, Mark B. Tan, Nicholas EM. Yeo, Siti RB. Sudirman, Khong Yik Chew

Abstract:

Introduction: The importance of the amalgamation of technological and engineering advances with surgical principles of reconstruction cannot be overemphasized. With earlier detection of cancer, consequences of high-speed living and neglect, like traumatic injuries and infection, resulting in increasingly younger patients with bone defects. This may result in malformations and suboptimal function that is more noticeable and palpable in the younger, active demographic. Our team proposes a technique that encapsulates a mesh of multidisciplinary effort, tissue engineering and reconstructive principles. Methods/Materials: Our patient was a young competitive footballer in his early 30s who was diagnosed with submandibular adenoid cystic carcinoma with bony involvement. He was thus counselled for a right hemi mandibulectomy, the floor of mouth resection, right selective neck dissection, tracheostomy, and free fibular flap reconstruction of his mandible and required post-operative radiotherapy. Being young and in his prime sportsman years, he was unable to accept the morbidities associated with using his fibula to reconstruct his mandible despite it being the gold standard reconstructive option. The fibula is an ideal vascularized bone flap because it’s reliable and easily shaped with relatively minimal impact on functional outcomes. The fibula contributes to 30% of weightbearing and is the attachment for the lateral compartment muscles; it is stronger in footballers concerning lateral bending. When harvesting the fibula, the distal 6-8cm and up to 10% of the total length is preserved to maintain the ankle’s stability, thus, minimizing the impact on daily activities. There are studies that have noted gait variability post-operatively. Therefore, returning to a premorbid competitive level may be doubtful. To improve his functional outcomes, the decision was made to try and restore the fibula's form and function. Using the concept of Fused Deposition Modelling (FDM), our team comprising of Plastics, Otolaryngology, Orthopedics and Radiology, worked with Osteopore to design a 3D bioresorbable implant to regenerate the fibula defect (14.5cm). Bone marrow was harvested via reaming the contralateral hip prior to the wide resection. 30mls of his blood was obtained for extracting platelet rich plasma. These were packed into the Osteopore 3D-printed bone scaffold. This was then secured into the fibula defect with titanium plates and screws. The flexor hallucis longus and soleus were anchored along the construct and intraosseous membrane, done in a single setting. Results: He was reviewed closely as an outpatient over 10 months post operatively. He reported no discernable loss or difference in ankle function. He is satisfied and back in training and our team has video and photographs that substantiate his progress. Conclusion: FDM allows regeneration of long bone defects. However, we aimed to also restore his eversion and inversion that is imperative for footballers and hence reattached his previously dissected muscles along the length of the Osteopore implant. We believe that the reattachment of the muscle stabilizes not only the construct but allows optimum muscle tensioning when moving his ankle. This is a simple but effective technique in restoring complete function and form in a young patient whose minute muscle control is imperative to life.

Keywords: fused deposition modelling, functional reconstruction, lower limb bony defects, regenerative surgery, 3D printing, tissue engineering

Procedia PDF Downloads 42

Authors: Nazym Zhumabayeva, Aleksandr Mezin, Alexandra Knysheva

Abstract:

Women's underrepresentation in STEM is critical, worsened by ineffective engagement in educational practices. UNICEF Kazakhstan and GameLab KBTU's collaborative initiatives aim to enhance female STEM participation by fostering an inclusive environment. Learning from LEVEL UP's 2023 program, which featured a hackathon, the 2024 strategy pivots towards non-competitive gamification. Although the data from last year's project showed higher than average student engagement, observations and in-depth interviews with participants showed that the format was stressful for the girls, making them focus on points rather than on other values. This study presents a gamified educational system, DPG Lab, aimed at incentivizing young women's participation in STEM through the development of digital public goods (DPGs). By prioritizing collaborative gamification elements, the project seeks to create an inclusive learning environment that increases engagement and interest in STEM among young women. The DPG Lab aims to find a solution to minimize competition and support collaboration. The project is designed to motivate female participants towards the development of digital solutions through an introduction to the concept of DPGs. It consists of a short online course, a simulation videogame, and a real-time online quest with an offline finale at the KBTU campus. The online course offers short video lectures on open-source development and DPG standards. The game facilitates the practical application of theoretical knowledge, enriching the learning experience. Learners can also participate in a quest that encourages participants to develop DPG ideas in teams by choosing missions throughout the quest path. At the offline quest finale, the participants will meet in person to exchange experiences and accomplishments without engaging in comparative assessments: the quest ensures that each team’s trajectory is distinct by design. This marks a shift from competitive hackathons to a collaborative format, recognizing the unique contributions and achievements of each participant. The pilot batch of students is scheduled to commence in April 2024, with the finale anticipated in June. It is projected that this group will comprise 50 female high-school students from various regions across Kazakhstan. Expected outcomes include increased engagement and interest in STEM fields among young female participants, positive emotional and psychological impact through an emphasis on collaborative learning environments, and improved understanding and skills in DPG development. GameLab KBTU intends to undertake a hypothesis evaluation, employing a methodology similar to that utilized in the preceding LEVEL UP project. This approach will encompass the compilation of quantitative metrics (conversion funnels, test results, and surveys) and qualitative data from in-depth interviews and observational studies. For comparative analysis, a select group of participants from the previous year's project will be recruited to engage in the DPG Lab. By developing and implementing a gamified framework that emphasizes inclusion, engagement, and collaboration, the study seeks to provide practical knowledge about effective gamification strategies for promoting gender diversity in STEM. The expected outcomes of this initiative can contribute to the broader discussion on gamification in education and gender equality in STEM by offering a replicable and scalable model for similar interventions around the world.

Keywords: collaborative learning, competitive learning, digital public goods, educational gamification, emerging regions, STEM, underprivileged groups

Procedia PDF Downloads 19

Authors: Brennan Lodge

Abstract:

Cybersecurity professionals have long been embroiled in a digital arms race, confronting increasingly sophisticated threats with innovative solutions. The field of cybersecurity is in an unending race against malicious adversaries. As threats evolve in complexity, the tools used to defend against them need to advance even faster. Burdened with a vast arsenal of tools and an expansive scope of threat intelligence, analysts frequently navigate a complex web, trying to discern patterns amidst information overload. Herein lies the potential of Retrieval Augmented Generation (RAG). By combining the capabilities of Large Language Models (LLMs) with a generative AI facet, RAG brings to the table an unparalleled ability for real-time cross-referencing, bridging the gap between raw data and actionable insights. Imagine an analyst named Sarah working at a global Fortune 500 company. Every day, Sarah navigates a maze of diverse knowledge bases, real-time threat intelligence, and her company's vast proprietary data, from network specifics to intricate technical blueprints. One day, she's challenged by a potential breach through a personal device due to the company's global "Bring Your Own Device" policy. With the clock ticking, Sarah has mere minutes to trace the malware's origin, all while considering complex regional regulations. As she races against the benchmark of Mean Time To Resolution (MTTR), she wonders: Could "Cozy Bear" with its notorious malware tactic, HAMMERTOSS, be behind this? Balancing policy intricacies, global network considerations, and ever-emerging cyber threats, Sarah's role epitomizes the intense challenges faced by today's cybersecurity analysts. While analysts grapple with this array of intricate, time-sensitive challenges, the necessity for precision and efficiency is key. RAG technology—a cutting-edge advancement in Gen AI—is a promising solution. Designed to assimilate diverse data sources such as cyber advisory notices, phishing email sentiment, secure and insecure code examples, information security policy documentation, and the MITRE ATT&CK framework, RAG equips analysts with real-time querying capabilities through a vector database and a cross referenced concise response from a Gen AI model. Traditional relational databases often necessitate a tedious process of filtering through numerous entries. Now, with the synergy of vector databases and Gen AI models, analysts can rapidly access both contextually or semantically akin data points. This augmented approach equips analysts with a comprehensive understanding of the prevailing cyber threats, elevating the robustness of cybersecurity defenses and upskilling the analyst and team, too. Vector databases underpin the knowledge translation in Gen AI. They bridge the gap between raw data and translation into meaningful insights, ensuring that analysts are equipped with comprehensive and relevant information. This superior capability of the RAG framework, with its impressive depth and precision, finds application across a broad spectrum of cybersecurity challenges. Let's delve into some use cases where its potential becomes particularly evident: Phishing Email Sentiment Analysis: Phishing remains a predominant vector for cybersecurity breaches. Leveraging RAG's capabilities, analysts can not only assess the potential malevolence of an email but can also understand the context behind it. By cross-referencing patterns from varied data sources in real-time, the detection process evolves from a mere content evaluation to a holistic understanding of attacker tactics, behaviors, and evolving profiles. This allows for the identification of nuanced phishing strategies that might otherwise go undetected. Insecure Code Analysis: Software vulnerabilities form a critical entry point for cyber adversaries. With RAG, the process of code evaluation undergoes a transformation. Instead of manual code reviews, the system pulls insights from vector databases and historical code snippets marked as insecure, enabling detection of vulnerabilities based on historical patterns, emerging threat vectors, and even predictive threat modeling. This ensures that even the most obfuscated or embedded vulnerabilities are identified, and corrective measures can be promptly implemented. Vulnerability and Upskill Advisory: In the fast-paced world of cybersecurity, staying updated is paramount. Through RAG's capabilities, analysts are not only made aware of real-time vulnerabilities but are also guided on the necessary skills and tools needed to combat them. By dynamically sourcing data through vulnerability advisories, news on advanced persistent threats, and tactics to defend, RAG ensures that analysts are not only reactive to threats but are also proactively upskilled, thereby bolstering their defense mechanisms. Information Security Policies for Compliance Teams: Compliance remains at the heart of many organizational cybersecurity strategies. However, with ever-shifting regulatory landscapes, staying compliant becomes a moving target. RAG's ability to source real-time data ensures that compliance teams always have access to the latest policy changes, guidelines, and best practices. This not only facilitates adherence to current standards but also anticipates future shifts, assists with audits, and ensures that organizations remain ahead of the compliance curve. Fusing a RAG architecture with platforms like Slack amplifies its practical utility. Slack, known for its real-time communication prowess, seamlessly evolves into more than just a messaging platform in this context. Cybersecurity analysts can pose intricate queries within Slack and, almost instantaneously, receive comprehensive feedback powered by the harmonious interplay of RAG and Gen AI. This integration effectively transforms Slack into an AI-augmented chatbot-like assistant for cybersecurity professionals, always ready to provide informed insights on-demand, making it an indispensable ally in the ever-evolving cyber battlefield. Navigating the vast landscape of cybersecurity, analysts often encounter unfamiliar terminologies and techniques., analysts require tools that not only detect or inform them of threats, like CISA (U.S Cybersecurity Infrastructure Security Agency) Advisories, but also interpret and communicate them effectively. Consider a junior cybersecurity analyst named Alex, who comes across the term "Kerberoasting" while reviewing a network log. Unfamiliar with its intricacies, Alex turns to Slack to pose a query: "chat explain is Kerberoasting, using CISA." Almost instantaneously, Slack, powered by the harmonious interplay of RAG and Gen AI, provides a detailed response, cross-referencing a recent cyber advisory on the technique. It explains how attackers can exploit the Kerberos Ticket Granting Service to decipher service account passwords, potentially compromising a network. In this dynamic realm of cybersecurity, the blend of RAG and Generative AI represents more than just a technological leap. It embodies a paradigm shift, promising a future where human expertise and AI-driven precision join forces. As cyber threats continue their relentless advance, this synergy ensures that defenders are equipped with an arsenal that's not just reactive, but also profoundly insightful. No longer should analysts be submerged in a deluge of data without direction. Instead, they should be empowered, to discern, act, and preempt with unparalleled clarity and confidence. By harmoniously intertwining human discernment with AI capabilities, we should chart a path towards a future where cybersecurity is not just about defense, but about achieving a strategic advantage, paving the way for a safer, informed and a more secure digital horizon.

Keywords: cybersecurity, gen AI, retrieval augmented generation, cybersecurity defense strategies

Procedia PDF Downloads 45

Authors: Gertraud Koch, Teresa Stumpf, Alejandra Tijerina García

Abstract:

Discourse analysis research approaches belong to the central research strategies applied throughout the humanities; they focus on the countless forms and ways digital texts and images shape present-day notions of the world. Despite the constantly growing number of relevant digital, multimodal discourse resources, digital humanities (DH) methods are thus far not systematically developed and accessible for discourse analysis approaches. Specifically, the significance of multimodality and meaning plurality modelling are yet to be sufficiently addressed. In order to address this research gap, the D-WISE project aims to develop a prototypical working environment as digital support for the sociology of knowledge approach to discourse analysis and new IT-analysis approaches for the use of context-oriented embedding representations. Playing an essential role throughout our research endeavor is the constant optimization of hermeneutical methodology in the use of (semi)automated processes and their corresponding epistemological reflection. Among the discourse analyses, the sociology of knowledge approach to discourse analysis is characterised by the reconstructive and accompanying research into the formation of knowledge systems in social negotiation processes. The approach analyses how dominant understandings of a phenomenon develop, i.e., the way they are expressed and consolidated by various actors in specific arenas of discourse until a specific understanding of the phenomenon and its socially accepted structure are established. This article presents insights and initial findings from D-WISE, a joint research project running since 2021 between the Institute of Anthropological Studies in Culture and History and the Language Technology Group of the Department of Informatics at the University of Hamburg. As an interdisciplinary team, we develop central innovations with regard to the availability of relevant DH applications by building up a uniform working environment, which supports the procedure of the sociology of knowledge approach to discourse analysis within open corpora and heterogeneous, multimodal data sources for researchers in the humanities. We are hereby expanding the existing range of DH methods by developing contextualized embeddings for improved modelling of the plurality of meaning and the integrated processing of multimodal data. The alignment of this methodological and technical innovation is based on the epistemological working methods according to grounded theory as a hermeneutic methodology. In order to systematically relate, compare, and reflect the approaches of structural-IT and hermeneutic-interpretative analysis, the discourse analysis is carried out both manually and digitally. Using the example of current discourses on digitization in the healthcare sector and the associated issues regarding data protection, we have manually built an initial data corpus of which the relevant actors and discourse positions are analysed in conventional qualitative discourse analysis. At the same time, we are building an extensive digital corpus on the same topic based on the use and further development of entity-centered research tools such as topic crawlers and automated newsreaders. In addition to the text material, this consists of multimodal sources such as images, video sequences, and apps. In a blended reading process, the data material is filtered, annotated, and finally coded with the help of NLP tools such as dependency parsing, named entity recognition, co-reference resolution, entity linking, sentiment analysis, and other project-specific tools that are being adapted and developed. The coding process is carried out (semi-)automated by programs that propose coding paradigms based on the calculated entities and their relationships. Simultaneously, these can be specifically trained by manual coding in a closed reading process and specified according to the content issues. Overall, this approach enables purely qualitative, fully automated, and semi-automated analyses to be compared and reflected upon.

Keywords: entanglement of structural IT and hermeneutic-interpretative analysis, multimodality, plurality of meaning, sociology of knowledge approach to discourse analysis

Procedia PDF Downloads 201

Authors: Daniela Salih Khidir, Mohamed G. Al Kuwari, Mercia V. Walt, Izzeldin J. Ibrahim

Abstract:

Background: University-based physical activity interventions aim to establish durable social patterns during the transition to adulthood. This study is a comprehensive evaluation of a 3-year intervention-based program to increase the culture of physical activity (PA) routine in Qatar campuses community, using a holistic approach. Methodology: General assessment methods: formative evaluation-SIH Campuses logic model design, stakeholders’ identification; process evaluation-members’ step counts analyze and qualitative Appreciative Inquiry session (4-D model); daily steps categorized as: ≤5,000, inactive; 5,000-7,499 low active; ≥7,500, physically active; outcome evaluation - records 3 years interventions. Holistic PA interventions methods: walking interventions - pedometers distributions and walking competitions for students and staff; educational interventions - in campuses implementation of bilingual educational materials, lectures, video related to PA in prevention of non-communicable diseases (NCD); articles published online; monthly emails and sms notifications for pedometer use; mass media campaign - radio advertising, yearly pre/post press releases; community stakeholders interventions-biyearly planning/reporting/achievements rewarding/ qualitative meetings; continuous follow-up communication, biweekly steps reports. Findings: Results formative evaluation - SIH in Campuses logic model identified the need of PA awareness and education within universities, resources, activities, health benefits, program continuity. Results process evaluation: walking interventions: Phase 1: 5 universities recruited, 2352 members, 3 months competition; Phase 2: 6 new universities recruited, 1328 members in addition, 4 months competition; Phase 3: 4 new universities recruited in addition, 1210 members, 6 months competition. Results phase 1 and 2: 1,299 members eligible for analyzes: 800 females (62%), 499 males (38%); 86% non-Qataris, 14% Qatari nationals, daily step count 5,681 steps, age groups 18–24 (n=841; 68%) students, 25–64; (n=458; 35.3%) staff; 38% - low active, 37% physically active and 25% inactive. The AI main themes engaging stakeholders: awareness/education - 5 points (100%); competition, multi levels of involvement in SIH, community-based program/motivation - 4 points each (80%). The AI points represent themes’ repetition within stakeholders’ discussions. Results education interventions: 2 videos implementation, 35 000 educational materials, 3 online articles, 11 walking benefits lectures, 40 emails and sms notifications. Results community stakeholders’ interventions: 6 stakeholders meetings, 3 rewarding gatherings, 1 focus meeting, 40 individual reports, 18 overall reports. Results mass media campaign: 1 radio campaign, 7 press releases, 52 campuses newsletters. Results outcome evaluation: overall 2013-2016, the study used: 1 logic model, 3 PA holistic interventions, partnerships 15 universities, registered 4890 students and staff (aged 18-64 years), engaged 30 campuses stakeholders and 14 internal stakeholders; Total registered population: 61.5% female (2999), 38.5% male (1891), 20.2% (988) Qatari nationals, 79.8% (3902) non-Qataris, 55.5% (2710) students aged 18 – 25 years, 44.5% (2180) staff aged 26 - 64 years. Overall campaign 1,558 members eligible for analyzes: daily step count 7,923; 37% - low active, 43% physically active and 20% inactive. Conclusion: The study outcomes confirm program effectiveness and engagement of young campuses community, specifically female, in PA. The authors recommend implementations of 'holistic PA intervention program approach in Qatar' aiming to impact the community at national level for PA guidelines achievement in support of NCD prevention.

Keywords: campuses, evaluation, Qatar, step-count

Procedia PDF Downloads 277