491 skills found · Page 1 of 17
LMAX-Exchange / DisruptorHigh Performance Inter-Thread Messaging Library
EmenstaNougat / ESP32 BlueJammerThe ESP32-BlueJammer (Bluetooth jammer, BLE jammer, WiFi jammer, RC jammer) disrupts 2.4GHz communications. Using an ESP32 and nRF24 modules, it generates noise and unnecessary packets, causing interference between the devices communicating, making them unable to work as intended. Ideal for controlled disruption and security testing.
exchange-core / Exchange CoreUltra-fast matching engine written in Java based on LMAX Disruptor, Eclipse Collections, Real Logic Agrona, OpenHFT, LZ4 Java, and Adaptive Radix Trees.
smarty / Go DisruptorA port of the LMAX Disruptor to the Go language.
disruptor-net / Disruptor NetPort of LMAX Disruptor to .NET
liyupi / Yu Picture编程导航的新项目，基于 Vue 3 + Spring Boot + COS + WebSocket 的企业级智能协同云图库平台。项目应用场景广泛，可作为表情包网站、设计素材网站、壁纸网站、个人云盘、企业活动相册等。用户可以在平台公开上传和检索图片素材；管理员可以上传、审核和管理分析图片；个人用户可将图片上传至私有空间进行批量管理、检索、编辑和分析；企业可开通团队空间并邀请成员，共享图片并实时协同编辑图片。技术栈包括 MySQL 分库分表、Redis + Caffeine 多级缓存、COS 对象存储、Sa-Token 权限控制、DDD 领域驱动设计、WebSocket 实时通讯、JUC、Disruptor、AI 绘图大模型、设计模式等。从 0 到 1 的真实企业级项目设计开发，绝对让你收获满满
nicholassm / Disruptor RsLow latency inter-thread communication library in Rust inspired by the LMAX Disruptor.
ProgrammerAnthony / HaafizHaafiz is a gateway in Micro Service which is inspired by many open source gateway :Zuul 1.x , spring cloud gateway，currently Not Released Now， Only For Study ......Haafiz （在英文中是守护者的意思）参考了很多开源网关的思想，基于Netty，Disruptor，etcd等技术做一个开源网关目前，暂未发布，仅供学习
gchq / BoilingFrogsGCHQ's internal Boiling Frogs research paper on software development and organisational change in the face of disruption #boilingfrogs
chanjarster / Artemis Disruptor Miaosha没有redis也能够支撑"小米在印度把亚马逊搞挂了"事件的秒杀解决方案
yireyun / Go QueueHigh-performance lock-free queue (Disruptor 1400/s)
W0rthlessS0ul / NRF24 JammerThe nRF24 jammer is a powerful tool that requires an ESP32 and configurable numbers of NRF24 modules to assemble. It is designed to create interference, disrupting the normal operation of Bluetooth devices 🔊, BLE technology 📱, drones 🚁, Wi-Fi networks 📶 and Zigbee 📡. Additionally, it features a user-friendly web interface 🌐.
fsaintjacques / Disruptor disruptor concurency pattern in c++
Abc-Arbitrage / Disruptor CppPort of LMAX Disruptor to C++
changmingxie / Aggregate FrameworkAggregate Framework是为方便开发人员运用DDD和CQRS思想来构建复杂的、可扩展的Java企业应用系统而提供的Java技术框架。该框架提供了Aggregate、Repository、Domain Event等构建块的实现；使用DomainEvent，借助于内建的Disruptor组件，AggregateFramework可使开发人员方便的实现高性能SEDA架构。此外，该框架支持与Spring集成，提供使用 annotation的方式让开发人员方便地为Domain Event定义一个或多个事件处理, 同时可指定事件处理是同步还是异步触发，并支持分布式事务事件; 使用Spring事务管理器管理事务时，支持Unit Of Work数据访问模式以及内建一级缓存以提高访问性能，另也支持可配置的2级缓存。
huangjian888 / Jeeweb Mybatis SpringbootSpringboot2.0+redis+SpringMVC+Spring+Mybatis+Mybatis Plus的Java web分布式开发系统；NettySocketIo排队系统/排队模块/排队框架,它是一款具有代码生成功能的智能快速开发平台；是以Spring Framework为核心容器，Spring MVC为模型视图控制器，Mybatis为数据访问层， Apache Shiro/Spring security为权限授权层，Ehcahe/Redis/Hazelcast对常用数据进行缓存，Disruptor作为并发框架,Bootstrap作为前端框架的优秀开源
natanielruiz / Disrupting Deepfakes🔥🔥Defending Against Deepfakes Using Adversarial Attacks on Conditional Image Translation Networks
conversant / DisruptorDisruptor BlockingQueue
PentHertz / RF Swift🚀 A powerful multi-platform RF toolbox that deploys specialized radio, hardware, and other security tools in seconds on Linux, Windows, and macOS—supporting x86_64, ARM64 (Raspberry Pi, Apple Silicon), and RISC-V architectures without disrupting your primary OS. 📡✨
duemig / Stanford Project Predicting Stock Prices Using A LSTM NetworkStanford Project: Artificial Intelligence is changing virtually every aspect of our lives. Today’s algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is an exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Models that explain the returns of individual stocks generally use company and stock characteristics, e.g., the market prices of financial instruments and companies’ accounting data. These characteristics can also be used to predict expected stock returns out-of-sample. Most studies use simple linear models to form these predictions [1] or [2]. An increasing body of academic literature documents that more sophisticated tools from the Machine Learning (ML) and Deep Learning (DL) repertoire, which allow for nonlinear predictor interactions, can improve the stock return forecasts [3], [4] or [5]. The main goal of this project is to investigate whether modern DL techniques can be utilized to more efficiently predict the movements of the stock market. Specifically, we train a LSTM neural network with time series price-volume data and compare its out-of-sample return predictability with the performance of a simple logistic regression (our baseline model).
