Rad Future
We're running out of time. Fossil fuels are choking the planet and renewable energy isn't cutting it. The solution has been hiding in plain sight all along. Nuclear. When most people hear that word, they go to a very bad place: bombs, Chernobyl, hazmat suits, radioactive fallout... the stuff of nightmares. But what if everything you think you know about nuclear is wrong? In Rad Future, science influencer Isabelle Boemeke shatters the fear and misinformation surrounding this technology and shows how the actual science tells a different story. It turns out that nuclear-generated electricity--nuclear electricity--is our best option for ensuring the future of the planet. Nuclear can power cities, desalinate water, create carbon-free fertilizer, and heat homes, all with the smallest environmental footprint of any energy source. Boemeke exposes how decades of fearmongering, a few dramatic (but preventable) disasters, and relentless bad PR have convinced the world that nuclear is dangerous when it's actually the key to an affordable, sustainable future. We've fumbled the bag on the cleanest, most powerful energy source we have, and it's time to fix that. This isn't your typical science book. Boemeke's signature mix of humor, sass, and deep research makes Rad Future a wild ride through the science, history, and future of nuclear electricity. From Cold War politics to Hollywood-fueled paranoia to cutting-edge reactor designs, she details exactly how nuclear works and why it's our best shot at ending the climate crisis and creating a future of radical abundance. Rad Future is the first truly accessible breakdown of nuclear electricity, and it will leave you feeling stoked about what's possible.
Modeling, Design and Engineering Optimization of Energy Systems
Numerical Methods and Modeling Applied for Composite Structures
Renewable Energy Power Generation and Power Demand Side Management
Effects of Laser Treatment on Surface Characterization and Mechanical Properties of Alloys
Artificial Intelligence in Fault Diagnosis and Signal Processing
Characterization of the Target-Mount Interaction in Radar Cross Section Measurement Calibrations
Topographic Surveying Using the Sokkisha SET2 Electronic Total Station With the NEC MOBILE PRO 780 Computer
Characterization of a Polymer-Based MEMS Pyroelectric Infrared Detector
Advances in Additive Manufacturing and Their Applications (2nd Edition)
Recent Advance and Application of Wearable Inertial Sensors in Motion Analysis
Ethics for Engineers
Ethics for Engineers: Toward Ethical Behavior within Engineering Organizations offers a multilevel perspective on engineering ethics with considerable breadth and depth, making it a valuable resource for students, educators, and professionals alike.This pragmatic book contains case studies of micro-level ethical violations, evaluating their moral implications and discussing moral self-licensing behind making unethical decisions. It also explores macro-level cases that have caused significant reputational and financial damage to major companies. In addition, the authors touch on topics whose overall impact is not yet fully understood, such as environmental ethics issues related to wind turbine blades and space debris management. By presenting examples from different levels and offering reflections from various perspectives, this text prompts readers to critically evaluate the ethical implications of their actions and understand what may drive a work community to behave unethically.Key features: Covers both moral theoretical and behavioral ethics perspectives. Contains day-to-day micro-level cases from the lives of practicing engineers, supplemented with macro-level cases. Provides pragmatic guidance for individual engineers and their organizations to move toward value-based ethics. Features colloquial language to make the book an enjoyable and accessible read. Includes 29 demonstrative vignettes, 87 class exercises, and an insightful interview with an ethics ambassador. This unique text serves as a pedagogically sound learning companion for courses in Engineering Ethics and related topics, striking a balance between research-based findings (with over 40 scholarly references) and real-world experiences (featuring an Appendix by an industry executive).
Advances of Healthy Environment Design in Urban Development
Numerical Methods and Computer Simulations in Energy Analysis, 2nd Edition
Strategic Planning and Control in Complex Project Management
Hybrid Intelligent Modeling Technology and Optimization Strategy for Industrial Energy Consumption Processes
Precision Planting Technology and Equipment in Advanced Crop Cultivation
Advancements in Power Management Systems for Hybrid Electric Vessels
Ethics for Engineers
Ethics for Engineers: Toward Ethical Behavior within Engineering Organizations offers a multilevel perspective on engineering ethics with considerable breadth and depth, making it a valuable resource for students, educators, and professionals alike.This pragmatic book contains case studies of micro-level ethical violations, evaluating their moral implications and discussing moral self-licensing behind making unethical decisions. It also explores macro-level cases that have caused significant reputational and financial damage to major companies. In addition, the authors touch on topics whose overall impact is not yet fully understood, such as environmental ethics issues related to wind turbine blades and space debris management. By presenting examples from different levels and offering reflections from various perspectives, this text prompts readers to critically evaluate the ethical implications of their actions and understand what may drive a work community to behave unethically.Key features: Covers both moral theoretical and behavioral ethics perspectives. Contains day-to-day micro-level cases from the lives of practicing engineers, supplemented with macro-level cases. Provides pragmatic guidance for individual engineers and their organizations to move toward value-based ethics. Features colloquial language to make the book an enjoyable and accessible read. Includes 29 demonstrative vignettes, 87 class exercises, and an insightful interview with an ethics ambassador. This unique text serves as a pedagogically sound learning companion for courses in Engineering Ethics and related topics, striking a balance between research-based findings (with over 40 scholarly references) and real-world experiences (featuring an Appendix by an industry executive).
SkinIntel AI - Your AI Dermatologist for Skin Health
Skin cancer remains one of the most widespread cancers globally, and detecting it early plays a vital role in ensuring effective treatment. However, traditional diagnosis methods depend heavily on the expertise of dermatologists, which can make the process slow and costly. This project introduces an automated approach to skin cancer detection using a combination of deep learning and machine learning techniques, aimed at supporting early and efficient diagnosis. To improve accuracy and reliability, several preprocessing steps were applied, including image augmentation, normalization, and class balancing. The model was further enhanced using transfer learning with pre-trained ImageNet weights, allowing it to perform well even with limited data.
Leveraging Artificial Intelligence and Machine Learning
As cybersecurity threats continue to evolve in sophistication, velocity, and impact, the conventional reactive security approaches cannot keep up with them. In these cases, cyber attackers have employed more sophisticated strategies such as polymorphic malware, fileless attacks, and living-off-the-land techniques that do not depend on traditional detection methods. Anticipating this, predictive risk looking (more notably using artificial intelligence (AI) and machine learning) has emerged as a key technology in today's cybersecurity strategies. Predictive risk finding allows security teams to proactively detect hidden risks, spot anomalies, and anticipate adversary behaviours before it results in a breach or device compromise. AI/ML approaches leverage behavioural analytics, large-scale telemetry data, and real-time learning to uncover overlooked patterns often missed by human analysts or rule-based architectures. In this article, we provide an exclusive overview of today's cutting-edge AI and ML applications in predictive risk looking. We focus on core technologies, device architectures, algorithmic models, and industry specific implementations.
