Computer science

Bluetooth is another short range wireless technology that is primarily used to transfer audio. Bluetooth can be integrated into speakers, or headphones. Bluetooth technology can also be used in such computing devices as keyboard or mouse. YouTube video

 NFC is an acronym for nearfield communication. NFC communication is short-range, typically it is about 4 cm. NFC is typically used for contactless payments or payments which are done with mobile phones. YouTube video

Lightning connector is Apple's proprietary connection type. It had been used in iPhones and iPads. Apple transitions using USB-C connector for its devices. YouTube video

Micro USB connector is an older type of connection that could be found on mobile phones, or portable devices such as tablets. USB-C had been replaced micro USB connection. If you are working with older technology, than such a connection could be found there. Micro USB is not reversable and fragile, so don't force it.  YouTube video

1. The Perfection Trap In the clinical, idealized world of introductory computer science, every problem has an elegant, exact answer. But as we transition from the classroom to the chaotic architecture of reality, we collide with the "NP-hard" problems—computational giants like the Traveling Salesperson or the Steiner Tree. These are not merely "difficult"; they are effectively unsolvable in their worst-case scenarios within any reasonable human timeframe. If we demand perfection, we find ourselves paralyzed by exponential time. Approximation algorithms offer an escape from this perfection trap. They represent a fundamental shift in our goals: we stop hunting for the elusive optimal solution (OPT) and instead design algorithms (ALG) that produce results with a mathematical guarantee of quality. These are not "heuristics"—the digital equivalent of a finger in the wind—but rigorous compromises. By accepting a fixed approximation factor (α), we trade the impo...

Algorithms are the invisible architects of the modern world. They dictate how your morning meetings are scheduled, how web traffic is balanced across a global cluster of servers, and even how a self-driving car distinguishes a pedestrian from a shadow. Yet, when we face complex problems, our human intuition is often a blunt tool. In the realm of advanced algorithmic design, the optimal solution is often the one our gut tells us to ignore. In the study of advanced algorithms—the kind explored in the rigorous CS787 curriculum—efficiency isn't just about speed; it is about the elegant, often surprising logic that governs complex systems. Here are five takeaways that challenge our standard definitions of "efficiency." 1. Why "Earliest Finish" Beats "Earliest Start" When faced with the "Interval Scheduling" problem—maximizing the number of non-overlapping jobs on a single machine—most people reach for the most "obvious" strategies. We th...