Tail latency is a term used to describe the high-percentile response times seen in a system. This is usually measured at the 95th, 99th, or 99.9th percentile, not the average latency. In distributed systems, cloud computing, and large-scale web services, even a small number of slow requests can make the user experience and system performance much worse. Tail latency often happens because of things like resource contention, network variability, garbage collection pauses, and hardware heterogeneity. A major problem in system design is managing tail latency, because lowering average latency doesn't always make the worst-case performance better. To lessen its effects, people often use techniques like request hedging, replication, load balancing, and adaptive timeouts. In latency-sensitive applications like search engines, financial systems, and real-time services, where service-level objectives (SLOs) are often based on high-percentile latencies, it is especially important to understand and improve tail latency.
Behavior informatics
Behavior informatics (BI) is the informatics of behaviors so as to obtain behavior intelligence and behavior insights. BI is a research method combining science and technology, specifically in the area of engineering. The purpose of BI includes analysis of current behaviors as well as the inference of future possible behaviors. This occurs through pattern recognition. Different from applied behavior analysis from the psychological perspective, BI builds computational theories, systems and tools to qualitatively and quantitatively model, represent, analyze, and manage behaviors of individuals, groups and/or organizations. BI is built on classic study of behavioral science, including behavior modeling, applied behavior analysis, behavior analysis, behavioral economics, and organizational behavior. Typical BI tasks consist of individual and group behavior formation, representation, computational modeling, analysis, learning, simulation, and understanding of behavior impact, utility, non-occurring behaviors, etc. for behavior intervention and management. The Behavior Informatics approach to data utilizes cognitive as well as behavioral data. By combining the data, BI has the potential to effectively illustrate the big picture when it comes to behavioral decisions and patterns. One of the goals of BI is also to be able to study human behavior while eliminating issues like self-report bias. This creates more reliable and valid information for research studies. == Behavior == From an Informatics perspective, a behavior consists of three key elements: actors (behavioral subjects and objects), operations (actions, activities) and interactions (relationships), and their properties. A behavior can be represented as a behavior vector, all behaviors of an actor or an actor group can be represented as behavior sequences and multi-dimensional behavior matrix. The following table explains some of the elements of behavior. Behavior Informatics takes into account behavior when analyzing business patterns and intelligence. The inclusion of behavior in these analyses provides prominent information on social and driving factors of patterns. == Applications == Behavior Informatics is being used in a variety of settings, including but not limited to health care management, telecommunications, marketing, and security. Behavior Informatics provides a manner in which to analyze and organize the many aspects that go into a person's health care needs and decisions. When it comes to business models, behavior informatics may be utilized for a similar role. Organizations implement behavior informatics to enhance business structure and regime, where it helps moderate ideal business decisions and situations.
Asymmetric follow
An asymmetric follow social network is one which allows many people to follow an individual or account without having to follow them back. It is also known as asynchronous follow or sometimes asymmetric friendship. Asymmetric follow is a common pattern on Twitter, where someone may have thousands of followers, but themselves follow few (or no) accounts. In September 2010 Facebook started experimenting with a similar feature, which Facebook calls "Subscribe To."
DBOS
DBOS (Formerly Database-Oriented Operating System, now just DBOS) is an open source durable workflow execution software library written for the Python, TypeScript, Java, and Go programming languages. DBOS arose from a joint open source project from MIT and Stanford, after a discussion between Michael Stonebraker and Matei Zaharia on how to scale and improve scheduling and performance of millions of Apache Spark tasks. Today it is a commercial company that offers an open source system to add durable computing to any software, built on concepts derived from the joint research project. == History == === 2020: Academic R&D Project === DBOS originated in 2020 as a joint open source project between MIT, Stanford, and Carnegie Mellon. The project explored the idea of operating system services built atop a distributed database - a database-oriented operating system meant to simplify and improve the scalability, security and resilience of large-scale distributed applications. The basic concept was to run a multi-node multi-core, transactional, highly-available distributed database, such as VoltDB, as the only application for a microkernel, and then to implement scheduling, messaging, file systems and other operating system services on top of the database. The architectural philosophy is described by this quote from the abstract of their initial preprint: All operating system state should be represented uniformly as database tables, and operations on this state should be made via queries from otherwise stateless tasks. This design makes it easy to scale and evolve the OS without whole-system refactoring, inspect and debug system state, upgrade components without downtime, manage decisions using machine learning, and implement sophisticated security features. A prototype was built with competitive performance to existing systems. ==
International Webmasters Association
The International Webmasters Association (IWA) is a non-profit association for education and certification of web professionals founded in 1996. It provides a Certified Web Professional certification. One of its objectives is to build a World Wide Web that is a true global community. According to the IWA, as of 2025 it has more than 100 official chapters with over 300,000 individual members in 106 countries. In 2001, the IWA merged with the HTML Writers Guild (HWG) and joined the World Wide Web Consortium (W3C). IWA's accomplishments include the publishing of the industry's first guidelines for ethical and professional standards, web certification and education programs, specialized employment resources, and technical assistance to individuals and businesses. IWA members participate to the activities of W3C WCAG Working Group, ATAG Working Group, and the XHTML Working Group. They have also participated in other initiatives such as the Multimodal Interaction Working Group which developed EMMA, the Extensible MultiModal Annotation markup language.
Software engine
A software engine is a core component of a complex software system. The word "engine" is a metaphor of a car's engine. Thus a software engine is a complex subsystem; not unlike how a car engine functions. Software engines work in conjunction with other components of a process or system. They typically have an input and an output, and the productivity is usually linear to running speed. There is no formal guideline for what should be called an engine, but the term has become widespread in the software industry. == Notable examples == === Multi-engine systems === Mainstream web browsers have both a browser engine and a JavaScript engine. Video games are often based on a game engine. Some of these also have specialized physics or graphics engines.
Magnetoquasistatic field
A magnetoquasistatic field is a class of electromagnetic field in which a slowly oscillating magnetic field is dominant. A magnetoquasistatic field is typically generated by low-frequency induction from a magnetic dipole or a current loop. The magnetic near-field of such an emitter behaves differently from the more commonly used far-field electromagnetic radiation. At low frequencies the rate of change of the instantaneous field strength with each cycle is relatively slow, giving rise to the name "magneto-quasistatic". The near field or quasistatic region typically extends no more than a wavelength from the antenna, and within this region the electric and magnetic fields are approximately decoupled. Weakly conducting non-magnetic bodies, including the human body and many mineral rocks, are effectively transparent to magnetoquasistatic fields, allowing for the transmission and reception of signals through such obstacles. Also, long-wavelength (i.e. low-frequency) signals are better able to propagate round corners than shorter-wave signals. Communication therefore need not be line-of-sight. The communication range of such signals depends on both the wavelength and the electromagnetic properties of the intervening medium at the chosen frequency, and is typically limited to a few tens of meters. == Physical principles == The laws of primary interest are Ampère's circuital law (with the displacement current density neglected) and the magnetic flux continuity law. These laws have associated with them continuity conditions at interfaces. In the absence of magnetizable materials, these laws determine the magnetic field intensity H given its source, the current density J. H is not everywhere irrotational. However, it is solenoidal everywhere. == Equipment design == A typical antenna comprises a 50-turn coil around a polyoxymethylene tube with diameter 16.5 cm, driven by a class E oscillator circuit. Such a device is readily portable when powered by batteries. Similarly, a typical receiver consist of an active receiving loop with diameter of one meter, an ultra-low-noise amplifier, and a band-pass filter. In operation the oscillator drives current through the transmitting loop to create an oscillating magnetic field. This field induces a voltage in the receiving loop, which is then amplified. Because the quasistatic region is defined within one wavelength of the electromagnetic source, emitters are limited to a frequency range between about 1 kHz and 1 MHz. Reducing the oscillating frequency increases the wavelength and hence the range of the quasistatic region, but reduces the induced voltage in the receiving loops which worsens the signal-to-noise ratio. In experiments carried out by the Carnegie Institute of Technology, the maximum range reported by was 50 meters. == Applications == === Resonant inductive coupling === In resonant coupling, the source and receiver are tuned to resonate at the same frequency and are given similar impedances. This allows power as well as information to flow from the source to the receiver. Such coupling via the magnetoquasistatic field is called resonant inductive coupling and can be used for wireless energy transfer. Applications include induction cooking, induction charging of batteries and some kinds of RFID tag. === Communications === Conventional electromagnetic communication signals cannot pass through the ground. Most mineral rock is neither electrically conducting nor magnetic, allowing magnetic fields to penetrate. Magnetoquasistatic systems have been successfully used for underground wireless communication, both surface-to-underground and between underground parties. At extremely low frequencies, below about 1 kHz, the wavelength is long enough for long-distance communication, although at a slow data rate. Such systems have been installed in submarines, with the local antenna comprising a wire up to several kilometers in length and trailed behind the vessel when at or near the surface. === Position and orientation tracking === Wireless position tracking is being increasingly used in applications such as navigation, security, and asset tracking. Conventional position tracking devices use high frequencies or microwaves, including global positioning systems (GPS), ultra-wide band (UWB) systems, and radio frequency identification systems (RFID), but these systems can easily be blocked by obstacles in their path. Magnetoquasistatic positioning takes advantage of the fact that the fields are largely undisturbed when in the presence of human beings and physical structures, and can be used for both position and orientation tracking for ranges up to 50 meters. To accurately determine the orientation and position of a dipole/emitter, allowance must be made not only for the field pattern generated by the emitter, but also for the eddy-currents they induce in the earth, which create secondary fields detectable by the receivers. By using complex image theory to correct this field generation from earth, and by using frequencies on the order of a few hundred kilohertz to obtain the required signal-to-noise ratio (SNR), it is possible to analyze the position of the dipole through azimuthal orientation, θ {\displaystyle \theta } , and inclination orientation, ϕ {\displaystyle \phi } . A Disney research team has used this technology to effectively determine the position and orientation of an American football, something not traceable through conventional wave propagation techniques due to human body obstruction. They inserted an oscillator-driven coil, around the diameter of the center of the ball, to generate the magnetoquasistatic field. The signal was able to pass undisturbed through multiple players.