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APPLE TECHNOLOGY CASE ANALYSIS made by UCSG students. Explanation on the difference between disruptive and innovative technologies.
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Even with many years of research efforts, the occupational exposure limits of different risk factors for development of Musculoskeletal disorders (MSDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors of MSDs interact in causing the injury, as the nature and mechanism of these disorders are relatively unknown phenomena. The task of an industrial ergonomist is complicated because the potential risk factors that may contribute to the onset of the MSDs interact in a complex way, and require an analyst to apply elaborate data measurement and collection techniques for a realistic job analysis. This makes it difficult to discriminate well between the jobs that place workers at high or low risk of above disorders. The main objective of this study was to to develop an artificial neural network based diagnostic system which can classify industrial jobs according to the potential risk for physiological stressors due to workplace design. Such a system could be useful in hazard analysis and injury prevention due to manual handling of loads in industrial environments. The results showed that the developed diagnostic system can successfully classify jobs into low and high risk categories of above musculoskeletal disorders based on carrying task characteristics. The Neural network based system developed gave the correct classification of the analysed industrial jobs with low and high risk. So, the system can be used as an expert system which, when properly trained, will classify carrying load by male and female workers into two categories of low risk and high risk work, based on the available characteristics factors.
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This presentations targets students or working professionals. You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many developer tools, platforms & APIs? This comprehensive yet still high-level overview outlines the most impactful tools for where to run your code, store & analyze your data. It will also inspire you as to what's possible. This talk is 50 minutes in length.
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What are drone anti-jamming systems? The drone anti-jamming systems and anti-spoof technology protect against interference, jamming, and spoofing of the UAVs. To protect their security, countries are beginning to research drone anti-jamming systems, also known as drone strike weapons. The anti-jam and anti-spoof technology protects against interference, jamming and spoofing. A drone strike weapon is a drone attack weapon that can attack and destroy enemy drones. So what is so unique about this amazing system?
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Even with many years of research efforts, the occupational exposure limits of different risk factors for development of Musculoskeletal disorders (MSDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors of MSDs interact in causing the injury, as the nature and mechanism of these disorders are relatively unknown phenomena. The task of an industrial ergonomist is complicated because the potential risk factors that may contribute to the onset of the MSDs interact in a complex way, and require an analyst to apply elaborate data measurement and collection techniques for a realistic job analysis. This makes it difficult to discriminate well between the jobs that place workers at high or low risk of above disorders. The main objective of this study was to to develop an artificial neural network based diagnostic system which can classify industrial jobs according to the potential risk for physiological stressors due to workplace design. Such a system could be useful in hazard analysis and injury prevention due to manual handling of loads in industrial environments. The results showed that the developed diagnostic system can successfully classify jobs into low and high risk categories of above musculoskeletal disorders based on carrying task characteristics. The Neural network based system developed gave the correct classification of the analysed industrial jobs with low and high risk. So, the system can be used as an expert system which, when properly trained, will classify carrying load by male and female workers into two categories of low risk and high risk work, based on the available characteristics factors.
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What are drone anti-jamming systems? The drone anti-jamming systems and anti-spoof technology protect against interference, jamming, and spoofing of the UAVs. To protect their security, countries are beginning to research drone anti-jamming systems, also known as drone strike weapons. The anti-jam and anti-spoof technology protects against interference, jamming and spoofing. A drone strike weapon is a drone attack weapon that can attack and destroy enemy drones. So what is so unique about this amazing system?
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Sara Mae O’Brien Scott and Tatiana Baquero Cakici, Senior Consultants at Enterprise Knowledge (EK), presented “AI Fast Track to Search-Focused AI Solutions” at the Information Architecture Conference (IAC24) that took place on April 11, 2024 in Seattle, WA. In their presentation, O’Brien-Scott and Cakici focused on what Enterprise AI is, why it is important, and what it takes to empower organizations to get started on a search-based AI journey and stay on track. The presentation explored the complexities of enterprise search challenges and how IA principles can be leveraged to provide AI solutions through the use of a semantic layer. O’Brien-Scott and Cakici showcased a case study where a taxonomy, an ontology, and a knowledge graph were used to structure content at a healthcare workforce solutions organization, providing personalized content recommendations and increasing content findability. In this session, participants gained insights about the following: Most common types of AI categories and use cases; Recommended steps to design and implement taxonomies and ontologies, ensuring they evolve effectively and support the organization’s search objectives; Taxonomy and ontology design considerations and best practices; Real-world AI applications that illustrated the value of taxonomies, ontologies, and knowledge graphs; and Tools, roles, and skills to design and implement AI-powered search solutions.
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The Raspberry Pi 5 was announced on October 2023. This new version of the popular embedded device comes with a new iteration of Broadcom’s VideoCore GPU platform, and was released with a fully open source driver stack, developed by Igalia. The presentation will discuss some of the major changes required to support this new Video Core iteration, the challenges we faced in the process and the solutions we provided in order to deliver conformant OpenGL ES and Vulkan drivers. The talk will also cover the next steps for the open source Raspberry Pi 5 graphics stack. (c) Embedded Open Source Summit 2024 April 16-18, 2024 Seattle, Washington (US) https://events.linuxfoundation.org/embedded-open-source-summit/ https://eoss24.sched.com/event/1aBEx
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Microsoft's Threat Matrix for Kubernetes helps organizations understand the attack surface a Kubernetes deployment introduces to their environments. This ensures that adequate detections and mitigations are in place. By covering over 40 different attacker techniques, defenders can learn about Kubernetes-specific mitigations and controls to deploy to their environments. In this session, we will explore the MS-TA9013 Host Path Mount technique, which is commonly used by attackers to perform privilege escalation in a Kubernetes cluster. Attendees will learn how attackers and defenders can: * Escape the container's host volume mount to gain persistence on an underlying node * Move laterally from the underlying node into the customer's cloud environment * Analyze Kubernetes audit logs to detect pods deployed with a hostPath mount * Deploy an admission controller that prevents new pods from using a hostPath mount
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Heather Hedden, Senior Consultant at Enterprise Knowledge, presented “The Role of Taxonomy and Ontology in Semantic Layers” at a webinar hosted by Progress Semaphore on April 16, 2024. Taxonomies at their core enable effective tagging and retrieval of content, and combined with ontologies they extend to the management and understanding of related data. There are even greater benefits of taxonomies and ontologies to enhance your enterprise information architecture when applying them to a semantic layer. A survey by DBP-Institute found that enterprises using a semantic layer see their business outcomes improve by four times, while reducing their data and analytics costs. Extending taxonomies to a semantic layer can be a game-changing solution, allowing you to connect information silos, alleviate knowledge gaps, and derive new insights. Hedden, who specializes in taxonomy design and implementation, presented how the value of taxonomies shouldn’t reside in silos but be integrated with ontologies into a semantic layer. Learn about: - The essence and purpose of taxonomies and ontologies in information and knowledge management; - Advantages of semantic layers leveraging organizational taxonomies; and - Components and approaches to creating a semantic layer, including the integration of taxonomies and ontologies
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My presentation at the Lehigh Carbon Community College (LCCC) NSA GenCyber Cyber Security Day event that is intended to foster an interest in the cyber security field amongst college students.
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The presentation explores the development and application of artificial intelligence (AI) from its inception to its current status in the modern world. The term "artificial intelligence" was first coined by John McCarthy in 1956 to describe efforts to develop computer programs capable of performing tasks that typically require human intelligence. This concept was first introduced at a conference held at Dartmouth College, where programs demonstrated capabilities such as playing chess, proving theorems, and interpreting texts. In the early stages, Alan Turing contributed to the field by defining intelligence as the ability of a being to respond to certain questions intelligently, proposing what is now known as the Turing Test to evaluate the presence of intelligent behavior in machines. As the decades progressed, AI evolved significantly. The 1980s focused on machine learning, teaching computers to learn from data, leading to the development of models that could improve their performance based on their experiences. The 1990s and 2000s saw further advances in algorithms and computational power, which allowed for more sophisticated data analysis techniques, including data mining. By the 2010s, the proliferation of big data and the refinement of deep learning techniques enabled AI to become mainstream. Notable milestones included the success of Google's AlphaGo and advancements in autonomous vehicles by companies like Tesla and Waymo. A major theme of the presentation is the application of generative AI, which has been used for tasks such as natural language text generation, translation, and question answering. Generative AI uses large datasets to train models that can then produce new, coherent pieces of text or other media. The presentation also discusses the ethical implications and the need for regulation in AI, highlighting issues such as privacy, bias, and the potential for misuse. These concerns have prompted calls for comprehensive regulations to ensure the safe and equitable use of AI technologies. Artificial intelligence has also played a significant role in healthcare, particularly highlighted during the COVID-19 pandemic, where it was used in drug discovery, vaccine development, and analyzing the spread of the virus. The capabilities of AI in healthcare are vast, ranging from medical diagnostics to personalized medicine, demonstrating the technology's potential to revolutionize fields beyond just technical or consumer applications. In conclusion, AI continues to be a rapidly evolving field with significant implications for various aspects of society. The development from theoretical concepts to real-world applications illustrates both the potential benefits and the challenges that come with integrating advanced technologies into everyday life. The ongoing discussion about AI ethics and regulation underscores the importance of managing these technologies responsibly to maximize their their benefits while minimizing potential harms.
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Digital Global Overview Report 2024 Slides presentation for Event presented in 2024 after compilation of data around last year.
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Factors to Consider When Choosing Accounts Payable Services Providers.pptx
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Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
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Khalfan
1.
Steve Jobs Khalfan AlMuhairi H00255135
2.
SteveJobs Apple’s Company Owner
3.
Steve Jobs &
Apple Int. • Hero in technology & innovation • Excellent businessman • great Marketing Man • Biggest software company
4.
Established1976 Steve jobs, Steve
Wozniak and Ronald Wayne
5.
FirstComputerinthecompany 1976
6.
Macintosh 1984
7.
Macbook-Pro 2006
8.
Macbook-air 2010
9.
Windows Tablet &
I-Pad Windows Tablet I-Pad
10.
IOS I-Phone, I-Pod and
I-pad
11.
Saved the Trees
12.
Saving The Environment
13.
Social Networks
14.
15.
16.
References • http://www.businessnewsdaily.com/1538-steve-jobs-changed- work.html • http://www.apple.com/environment/renewable-energy/
Editor's Notes
Tablet 2001, I-Pad 2010 .. Why is the i-pad more known?