246 skills found · Page 1 of 9
robcowart / ElastiflowNetwork flow analytics (Netflow, sFlow and IPFIX) with the Elastic Stack
activecm / Rita LegacyReal Intelligence Threat Analytics (RITA) is a framework for detecting command and control communication through network traffic analysis.
benedekrozemberczki / LittleballoffurLittle Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)
JayRHa / EndpointAnalyticsRemediationScriptsCollection of ready-to-use Intune Endpoint Analytics Proactive Remediation scripts for detection and remediation of common Windows endpoint issues including security, performance, networking, and application management.
activecm / RitaReal Intelligence Threat Analytics (RITA) is a framework for detecting command and control communication through network traffic analysis.
austin-taylor / FlareAn analytical framework for network traffic and behavioral analytics
ayrshare / Social Media ApiSocial Media API: Automate Posting and Analytics to Social Networks like Instagram, TikTok, X/Twitter, Facebook, LinkedIn, Reddit, YouTube, and Telegram
microsoft / CtsTrafficctsTraffic is a highly scalable client/server networking tool giving detailed performance and reliability analytics
FaceONNX / FaceONNXFace recognition and analytics library based on deep neural networks and ONNX runtime
DynamiteAI / Dynamite NsmDynamiteNSM is a free Network Security Monitor developed by Dynamite Analytics to enable network visibility and advanced cyber threat detection
keithmcnulty / Ona BookHandbook of Graphs and Networks in People Analytics
USSoccerFederation / Ussf Ssac 23 Soccer GnnU.S. Soccer Federation 2023 MIT Sloan Sports Analytics Conference Graph Neural Network soccer research repository
flipkart-incubator / Okhttp StatsOkHttp Analytical library to get stats like average network speed. Also get global callbacks for network errors and successes. Can be used for logging errors to Fabric or Firebase analytical tools
TalwalkarLab / PaleoAn analytical performance modeling tool for deep neural networks.
Aryia-Behroziuan / NeuronsAn ANN is a model based on a collection of connected units or nodes called "artificial neurons", which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit information, a "signal", from one artificial neuron to another. An artificial neuron that receives a signal can process it and then signal additional artificial neurons connected to it. In common ANN implementations, the signal at a connection between artificial neurons is a real number, and the output of each artificial neuron is computed by some non-linear function of the sum of its inputs. The connections between artificial neurons are called "edges". Artificial neurons and edges typically have a weight that adjusts as learning proceeds. The weight increases or decreases the strength of the signal at a connection. Artificial neurons may have a threshold such that the signal is only sent if the aggregate signal crosses that threshold. Typically, artificial neurons are aggregated into layers. Different layers may perform different kinds of transformations on their inputs. Signals travel from the first layer (the input layer) to the last layer (the output layer), possibly after traversing the layers multiple times. The original goal of the ANN approach was to solve problems in the same way that a human brain would. However, over time, attention moved to performing specific tasks, leading to deviations from biology. Artificial neural networks have been used on a variety of tasks, including computer vision, speech recognition, machine translation, social network filtering, playing board and video games and medical diagnosis. Deep learning consists of multiple hidden layers in an artificial neural network. This approach tries to model the way the human brain processes light and sound into vision and hearing. Some successful applications of deep learning are computer vision and speech recognition.[68] Decision trees Main article: Decision tree learning Decision tree learning uses a decision tree as a predictive model to go from observations about an item (represented in the branches) to conclusions about the item's target value (represented in the leaves). It is one of the predictive modeling approaches used in statistics, data mining, and machine learning. Tree models where the target variable can take a discrete set of values are called classification trees; in these tree structures, leaves represent class labels and branches represent conjunctions of features that lead to those class labels. Decision trees where the target variable can take continuous values (typically real numbers) are called regression trees. In decision analysis, a decision tree can be used to visually and explicitly represent decisions and decision making. In data mining, a decision tree describes data, but the resulting classification tree can be an input for decision making. Support vector machines Main article: Support vector machines Support vector machines (SVMs), also known as support vector networks, are a set of related supervised learning methods used for classification and regression. Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm builds a model that predicts whether a new example falls into one category or the other.[69] An SVM training algorithm is a non-probabilistic, binary, linear classifier, although methods such as Platt scaling exist to use SVM in a probabilistic classification setting. In addition to performing linear classification, SVMs can efficiently perform a non-linear classification using what is called the kernel trick, implicitly mapping their inputs into high-dimensional feature spaces. Illustration of linear regression on a data set. Regression analysis Main article: Regression analysis Regression analysis encompasses a large variety of statistical methods to estimate the relationship between input variables and their associated features. Its most common form is linear regression, where a single line is drawn to best fit the given data according to a mathematical criterion such as ordinary least squares. The latter is often extended by regularization (mathematics) methods to mitigate overfitting and bias, as in ridge regression. When dealing with non-linear problems, go-to models include polynomial regression (for example, used for trendline fitting in Microsoft Excel[70]), logistic regression (often used in statistical classification) or even kernel regression, which introduces non-linearity by taking advantage of the kernel trick to implicitly map input variables to higher-dimensional space. Bayesian networks Main article: Bayesian network A simple Bayesian network. Rain influences whether the sprinkler is activated, and both rain and the sprinkler influence whether the grass is wet. A Bayesian network, belief network, or directed acyclic graphical model is a probabilistic graphical model that represents a set of random variables and their conditional independence with a directed acyclic graph (DAG). For example, a Bayesian network could represent the probabilistic relationships between diseases and symptoms. Given symptoms, the network can be used to compute the probabilities of the presence of various diseases. Efficient algorithms exist that perform inference and learning. Bayesian networks that model sequences of variables, like speech signals or protein sequences, are called dynamic Bayesian networks. Generalizations of Bayesian networks that can represent and solve decision problems under uncertainty are called influence diagrams. Genetic algorithms Main article: Genetic algorithm A genetic algorithm (GA) is a search algorithm and heuristic technique that mimics the process of natural selection, using methods such as mutation and crossover to generate new genotypes in the hope of finding good solutions to a given problem. In machine learning, genetic algorithms were used in the 1980s and 1990s.[71][72] Conversely, machine learning techniques have been used to improve the performance of genetic and evolutionary algorithms.[73] Training models Usually, machine learning models require a lot of data in order for them to perform well. Usually, when training a machine learning model, one needs to collect a large, representative sample of data from a training set. Data from the training set can be as varied as a corpus of text, a collection of images, and data collected from individual users of a service. Overfitting is something to watch out for when training a machine learning model. Federated learning Main article: Federated learning Federated learning is an adapted form of distributed artificial intelligence to training machine learning models that decentralizes the training process, allowing for users' privacy to be maintained by not needing to send their data to a centralized server. This also increases efficiency by decentralizing the training process to many devices. For example, Gboard uses federated machine learning to train search query prediction models on users' mobile phones without having to send individual searches back to Google.[74] Applications There are many applications for machine learning, including: Agriculture Anatomy Adaptive websites Affective computing Banking Bioinformatics Brain–machine interfaces Cheminformatics Citizen science Computer networks Computer vision Credit-card fraud detection Data quality DNA sequence classification Economics Financial market analysis[75] General game playing Handwriting recognition Information retrieval Insurance Internet fraud detection Linguistics Machine learning control Machine perception Machine translation Marketing Medical diagnosis Natural language processing Natural language understanding Online advertising Optimization Recommender systems Robot locomotion Search engines Sentiment analysis Sequence mining Software engineering Speech recognition Structural health monitoring Syntactic pattern recognition Telecommunication Theorem proving Time series forecasting User behavior analytics In 2006, the media-services provider Netflix held the first "Netflix Prize" competition to find a program to better predict user preferences and improve the accuracy of its existing Cinematch movie recommendation algorithm by at least 10%. A joint team made up of researchers from AT&T Labs-Research in collaboration with the teams Big Chaos and Pragmatic Theory built an ensemble model to win the Grand Prize in 2009 for $1 million.[76] Shortly after the prize was awarded, Netflix realized that viewers' ratings were not the best indicators of their viewing patterns ("everything is a recommendation") and they changed their recommendation engine accordingly.[77] In 2010 The Wall Street Journal wrote about the firm Rebellion Research and their use of machine learning to predict the financial crisis.[78] In 2012, co-founder of Sun Microsystems, Vinod Khosla, predicted that 80% of medical doctors' jobs would be lost in the next two decades to automated machine learning medical diagnostic software.[79] In 2014, it was reported that a machine learning algorithm had been applied in the field of art history to study fine art paintings and that it may have revealed previously unrecognized influences among artists.[80] In 2019 Springer Nature published the first research book created using machine learning.[81] Limitations Although machine learning has been transformative in some fields, machine-learning programs often fail to deliver expected results.[82][83][84] Reasons for this are numerous: lack of (suitable) data, lack of access to the data, data bias, privacy problems, badly chosen tasks and algorithms, wrong tools and people, lack of resources, and evaluation problems.[85] In 2018, a self-driving car from Uber failed to detect a pedestrian, who was killed after a collision.[86] Attempts to use machine learning in healthcare with the IBM Watson system failed to deliver even after years of time and billions of dollars invested.[87][88] Bias Main article: Algorithmic bias Machine learning approaches in particular can suffer from different data biases. A machine learning system trained on current customers only may not be able to predict the needs of new customer groups that are not represented in the training data. When trained on man-made data, machine learning is likely to pick up the same constitutional and unconscious biases already present in society.[89] Language models learned from data have been shown to contain human-like biases.[90][91] Machine learning systems used for criminal risk assessment have been found to be biased against black people.[92][93] In 2015, Google photos would often tag black people as gorillas,[94] and in 2018 this still was not well resolved, but Google reportedly was still using the workaround to remove all gorillas from the training data, and thus was not able to recognize real gorillas at all.[95] Similar issues with recognizing non-white people have been found in many other systems.[96] In 2016, Microsoft tested a chatbot that learned from Twitter, and it quickly picked up racist and sexist language.[97] Because of such challenges, the effective use of machine learning may take longer to be adopted in other domains.[98] Concern for fairness in machine learning, that is, reducing bias in machine learning and propelling its use for human good is increasingly expressed by artificial intelligence scientists, including Fei-Fei Li, who reminds engineers that "There’s nothing artificial about AI...It’s inspired by people, it’s created by people, and—most importantly—it impacts people. It is a powerful tool we are only just beginning to understand, and that is a profound responsibility.”[99] Model assessments Classification of machine learning models can be validated by accuracy estimation techniques like the holdout method, which splits the data in a training and test set (conventionally 2/3 training set and 1/3 test set designation) and evaluates the performance of the training model on the test set. In comparison, the K-fold-cross-validation method randomly partitions the data into K subsets and then K experiments are performed each respectively considering 1 subset for evaluation and the remaining K-1 subsets for training the model. In addition to the holdout and cross-validation methods, bootstrap, which samples n instances with replacement from the dataset, can be used to assess model accuracy.[100] In addition to overall accuracy, investigators frequently report sensitivity and specificity meaning True Positive Rate (TPR) and True Negative Rate (TNR) respectively. Similarly, investigators sometimes report the false positive rate (FPR) as well as the false negative rate (FNR). However, these rates are ratios that fail to reveal their numerators and denominators. The total operating characteristic (TOC) is an effective method to express a model's diagnostic ability. TOC shows the numerators and denominators of the previously mentioned rates, thus TOC provides more information than the commonly used receiver operating characteristic (ROC) and ROC's associated area under the curve (AUC).[101] Ethics Machine learning poses a host of ethical questions. Systems which are trained on datasets collected with biases may exhibit these biases upon use (algorithmic bias), thus digitizing cultural prejudices.[102] For example, using job hiring data from a firm with racist hiring policies may lead to a machine learning system duplicating the bias by scoring job applicants against similarity to previous successful applicants.[103][104] Responsible collection of data and documentation of algorithmic rules used by a system thus is a critical part of machine learning. Because human languages contain biases, machines trained on language corpora will necessarily also learn these biases.[105][106] Other forms of ethical challenges, not related to personal biases, are more seen in health care. There are concerns among health care professionals that these systems might not be designed in the public's interest but as income-generating machines. This is especially true in the United States where there is a long-standing ethical dilemma of improving health care, but also increasing profits. For example, the algorithms could be designed to provide patients with unnecessary tests or medication in which the algorithm's proprietary owners hold stakes. There is huge potential for machine learning in health care to provide professionals a great tool to diagnose, medicate, and even plan recovery paths for patients, but this will not happen until the personal biases mentioned previously, and these "greed" biases are addressed.[107] Hardware Since the 2010s, advances in both machine learning algorithms and computer hardware have led to more efficient methods for training deep neural networks (a particular narrow subdomain of machine learning) that contain many layers of non-linear hidden units.[108] By 2019, graphic processing units (GPUs), often with AI-specific enhancements, had displaced CPUs as the dominant method of training large-scale commercial cloud AI.[109] OpenAI estimated the hardware compute used in the largest deep learning projects from AlexNet (2012) to AlphaZero (2017), and found a 300,000-fold increase in the amount of compute required, with a doubling-time trendline of 3.4 months.[110][111] Software Software suites containing a variety of machine learning algorithms include the following: Free and open-source so
stellar-expert / Stellar Expert ExplorerStellarExpert Explorer – block explorer and analytics platform for Stellar Network.
Gorilla-Lab-SCUT / AnalyticMeshAn Efficient Implementation of Analytic Mesh Algorithm for 3D Iso-surface Extraction from Neural Networks
matomo-org / Searchengine And Social ListList of Search engines URLs, keywords and Social network URLs definitions used by Matomo Analytics
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9H3V8h1v1zm0-3H3v1h1V6zm0-2H3v1h1V4zm0-2H3v1h1V2zm8-1v12c0 .55-.45 1-1 1H6v2l-1.5-1.5L3 16v-2H1c-.55 0-1-.45-1-1V1c0-.55.45-1 1-1h10c.55 0 1 .45 1 1zm-1 10H1v2h2v-1h3v1h5v-2zm0-10H2v9h9V1z"/></svg> <svg height="16" width="16" class="octicon octicon-project flex-shrink-0 js-jump-to-octicon-project d-none" title="Project" aria-label="Project" viewBox="0 0 15 16" version="1.1" role="img"><path fill-rule="evenodd" d="M10 12h3V2h-3v10zm-4-2h3V2H6v8zm-4 4h3V2H2v12zm-1 1h13V1H1v14zM14 0H1a1 1 0 0 0-1 1v14a1 1 0 0 0 1 1h13a1 1 0 0 0 1-1V1a1 1 0 0 0-1-1z"/></svg> <svg height="16" width="16" class="octicon octicon-search flex-shrink-0 js-jump-to-octicon-search d-none" title="Search" aria-label="Search" viewBox="0 0 16 16" version="1.1" role="img"><path fill-rule="evenodd" d="M15.7 13.3l-3.81-3.83A5.93 5.93 0 0 0 13 6c0-3.31-2.69-6-6-6S1 2.69 1 6s2.69 6 6 6c1.3 0 2.48-.41 3.47-1.11l3.83 3.81c.19.2.45.3.7.3.25 0 .52-.09.7-.3a.996.996 0 0 0 0-1.41v.01zM7 10.7c-2.59 0-4.7-2.11-4.7-4.7 0-2.59 2.11-4.7 4.7-4.7 2.59 0 4.7 2.11 4.7 4.7 0 2.59-2.11 4.7-4.7 4.7z"/></svg> </div> <img class="avatar mr-2 flex-shrink-0 js-jump-to-suggestion-avatar d-none" alt="" aria-label="Team" src="" width="28" height="28"> <div class="jump-to-suggestion-name js-jump-to-suggestion-name flex-auto overflow-hidden text-left no-wrap css-truncate css-truncate-target"> </div> <div class="border rounded-1 flex-shrink-0 bg-gray px-1 text-gray-light ml-1 f6 d-none js-jump-to-badge-search"> <span class="js-jump-to-badge-search-text-default d-none" aria-label="in this repository"> In this repository </span> <span class="js-jump-to-badge-search-text-global d-none" aria-label="in all of GitHub"> All GitHub </span> <span aria-hidden="true" class="d-inline-block ml-1 v-align-middle">↵</span> </div> <div aria-hidden="true" class="border rounded-1 flex-shrink-0 bg-gray px-1 text-gray-light ml-1 f6 d-none d-on-nav-focus js-jump-to-badge-jump"> Jump to <span class="d-inline-block ml-1 v-align-middle">↵</span> </div> </a> </li> </ul> <ul class="d-none js-jump-to-no-results-template-container"> <li class="d-flex flex-justify-center flex-items-center f5 d-none js-jump-to-suggestion p-2"> <span class="text-gray">No suggested jump to results</span> </li> </ul> <ul id="jump-to-results" role="listbox" class="p-0 m-0 js-navigation-container jump-to-suggestions-results-container js-jump-to-suggestions-results-container"> <li class="d-flex flex-justify-start flex-items-center p-0 f5 navigation-item js-navigation-item js-jump-to-scoped-search d-none" role="option"> <a tabindex="-1" class="no-underline d-flex flex-auto flex-items-center jump-to-suggestions-path js-jump-to-suggestion-path js-navigation-open p-2" href=""> <div class="jump-to-octicon js-jump-to-octicon flex-shrink-0 mr-2 text-center d-none"> <svg height="16" width="16" class="octicon octicon-repo flex-shrink-0 js-jump-to-octicon-repo d-none" title="Repository" aria-label="Repository" viewBox="0 0 12 16" version="1.1" role="img"><path fill-rule="evenodd" d="M4 9H3V8h1v1zm0-3H3v1h1V6zm0-2H3v1h1V4zm0-2H3v1h1V2zm8-1v12c0 .55-.45 1-1 1H6v2l-1.5-1.5L3 16v-2H1c-.55 0-1-.45-1-1V1c0-.55.45-1 1-1h10c.55 0 1 .45 1 1zm-1 10H1v2h2v-1h3v1h5v-2zm0-10H2v9h9V1z"/></svg> <svg height="16" width="16" class="octicon octicon-project flex-shrink-0 js-jump-to-octicon-project d-none" title="Project" aria-label="Project" viewBox="0 0 15 16" version="1.1" role="img"><path fill-rule="evenodd" d="M10 12h3V2h-3v10zm-4-2h3V2H6v8zm-4 4h3V2H2v12zm-1 1h13V1H1v14zM14 0H1a1 1 0 0 0-1 1v14a1 1 0 0 0 1 1h13a1 1 0 0 0 1-1V1a1 1 0 0 0-1-1z"/></svg> <svg height="16" width="16" class="octicon octicon-search flex-shrink-0 js-jump-to-octicon-search d-none" title="Search" aria-label="Search" viewBox="0 0 16 16" version="1.1" role="img"><path fill-rule="evenodd" d="M15.7 13.3l-3.81-3.83A5.93 5.93 0 0 0 13 6c0-3.31-2.69-6-6-6S1 2.69 1 6s2.69 6 6 6c1.3 0 2.48-.41 3.47-1.11l3.83 3.81c.19.2.45.3.7.3.25 0 .52-.09.7-.3a.996.996 0 0 0 0-1.41v.01zM7 10.7c-2.59 0-4.7-2.11-4.7-4.7 0-2.59 2.11-4.7 4.7-4.7 2.59 0 4.7 2.11 4.7 4.7 0 2.59-2.11 4.7-4.7 4.7z"/></svg> </div> <img class="avatar mr-2 flex-shrink-0 js-jump-to-suggestion-avatar d-none" alt="" aria-label="Team" src="" width="28" height="28"> <div class="jump-to-suggestion-name js-jump-to-suggestion-name flex-auto overflow-hidden text-left no-wrap css-truncate css-truncate-target"> </div> <div class="border rounded-1 flex-shrink-0 bg-gray px-1 text-gray-light ml-1 f6 d-none js-jump-to-badge-search"> <span class="js-jump-to-badge-search-text-default d-none" aria-label="in this repository"> In this repository </span> <span class="js-jump-to-badge-search-text-global d-none" aria-label="in all of GitHub"> All GitHub </span> <span aria-hidden="true" class="d-inline-block ml-1 v-align-middle">↵</span> </div> <div aria-hidden="true" class="border rounded-1 flex-shrink-0 bg-gray px-1 text-gray-light ml-1 f6 d-none d-on-nav-focus js-jump-to-badge-jump"> Jump to <span class="d-inline-block ml-1 v-align-middle">↵</span> </div> </a> </li> <li class="d-flex flex-justify-start flex-items-center p-0 f5 navigation-item js-navigation-item js-jump-to-global-search d-none" role="option"> <a tabindex="-1" class="no-underline d-flex flex-auto flex-items-center jump-to-suggestions-path js-jump-to-suggestion-path js-navigation-open p-2" href=""> <div class="jump-to-octicon js-jump-to-octicon flex-shrink-0 mr-2 text-center d-none"> <svg height="16" width="16" class="octicon octicon-repo flex-shrink-0 js-jump-to-octicon-repo d-none" title="Repository" aria-label="Repository" viewBox="0 0 12 16" version="1.1" role="img"><path fill-rule="evenodd" d="M4 9H3V8h1v1zm0-3H3v1h1V6zm0-2H3v1h1V4zm0-2H3v1h1V2zm8-1v12c0 .55-.45 1-1 1H6v2l-1.5-1.5L3 16v-2H1c-.55 0-1-.45-1-1V1c0-.55.45-1 1-1h10c.55 0 1 .45 1 1zm-1 10H1v2h2v-1h3v1h5v-2zm0-10H2v9h9V1z"/></svg> <svg height="16" width="16" class="octicon octicon-project flex-shrink-0 js-jump-to-octicon-project d-none" title="Project" aria-label="Project" viewBox="0 0 15 16" version="1.1" role="img"><path fill-rule="evenodd" d="M10 12h3V2h-3v10zm-4-2h3V2H6v8zm-4 4h3V2H2v12zm-1 1h13V1H1v14zM14 0H1a1 1 0 0 0-1 1v14a1 1 0 0 0 1 1h13a1 1 0 0 0 1-1V1a1 1 0 0 0-1-1z"/></svg> <svg height="16" width="16" class="octicon octicon-search flex-shrink-0 js-jump-to-octicon-search d-none" title="Search" aria-label="Search" viewBox="0 0 16 16" version="1.1" role="img"><path fill-rule="evenodd" d="M15.7 13.3l-3.81-3.83A5.93 5.93 0 0 0 13 6c0-3.31-2.69-6-6-6S1 2.69 1 6s2.69 6 6 6c1.3 0 2.48-.41 3.47-1.11l3.83 3.81c.19.2.45.3.7.3.25 0 .52-.09.7-.3a.996.996 0 0 0 0-1.41v.01zM7 10.7c-2.59 0-4.7-2.11-4.7-4.7 0-2.59 2.11-4.7 4.7-4.7 2.59 0 4.7 2.11 4.7 4.7 0 2.59-2.11 4.7-4.7 4.7z"/></svg> </div> <img class="avatar mr-2 flex-shrink-0 js-jump-to-suggestion-avatar d-none" alt="" aria-label="Team" src="" width="28" height="28"> <div class="jump-to-suggestion-name js-jump-to-suggestion-name flex-auto overflow-hidden text-left no-wrap css-truncate css-truncate-target"> </div> <div class="border rounded-1 flex-shrink-0 bg-gray px-1 text-gray-light ml-1 f6 d-none js-jump-to-badge-search"> <span class="js-jump-to-badge-search-text-default d-none" aria-label="in this repository"> In this repository </span> <span class="js-jump-to-badge-search-text-global d-none" aria-label="in all of GitHub"> All GitHub </span> <span aria-hidden="true" class="d-inline-block ml-1 v-align-middle">↵</span> </div> <div aria-hidden="true" class="border rounded-1 flex-shrink-0 bg-gray px-1 text-gray-light ml-1 f6 d-none d-on-nav-focus js-jump-to-badge-jump"> Jump to <span class="d-inline-block ml-1 v-align-middle">↵</span> </div> </a> </li> <li class="d-flex flex-justify-center flex-items-center p-0 f5 js-jump-to-suggestion"> <img src="https://github.githubassets.com/images/spinners/octocat-spinner-128.gif" alt="Octocat Spinner Icon" class="m-2" width="28"> </li> </ul> </div> </label> </form> </div> </div> </div> <ul class="d-lg-flex pl-lg-2 flex-items-center text-bold list-style-none"> <li class="d-lg-none"> <a class="HeaderNavlink px-lg-2 py-2 py-lg-0" data-ga-click="Header, click, Nav menu - item:dashboard:user" aria-label="Dashboard" href="/dashboard"> Dashboard </a> </li> <li> <a class="js-selected-navigation-item HeaderNavlink px-lg-2 py-2 py-lg-0" data-hotkey="g p" data-ga-click="Header, click, Nav menu - item:pulls context:user" aria-label="Pull requests you created" data-selected-links="/pulls /pulls/assigned /pulls/mentioned /pulls" href="/pulls"> Pull requests </a> </li> <li> <a class="js-selected-navigation-item HeaderNavlink px-lg-2 py-2 py-lg-0" data-hotkey="g i" data-ga-click="Header, click, Nav menu - item:issues context:user" aria-label="Issues you created" data-selected-links="/issues /issues/assigned /issues/mentioned /issues" href="/issues"> Issues </a> </li> <li class="position-relative"> <a class="js-selected-navigation-item HeaderNavlink px-lg-2 py-2 py-lg-0" data-ga-click="Header, click, Nav menu - item:marketplace context:user" data-octo-click="marketplace_click" data-octo-dimensions="location:nav_bar" data-selected-links=" /marketplace" href="/marketplace"> Marketplace </a> </li> <li> <a class="js-selected-navigation-item HeaderNavlink px-lg-2 py-2 py-lg-0" data-ga-click="Header, click, Nav menu - item:explore" data-selected-links="/explore /trending /trending/developers /integrations /integrations/feature/code /integrations/feature/collaborate /integrations/feature/ship showcases showcases_search showcases_landing /explore" href="/explore"> Explore </a> </li> </ul> </nav> <div class="d-lg-flex"> <ul class="user-nav d-lg-flex flex-items-center list-style-none" id="user-links"> <li class="dropdown"> <span class="d-none d-lg-block px-2"> <a aria-label="You have no unread notifications" class="notification-indicator tooltipped tooltipped-s my-2 my-lg-0 js-socket-channel js-notification-indicator" data-hotkey="g n" data-ga-click="Header, go to notifications, icon:read" data-channel="notification-changed:47923458" href="/notifications"> <span class="mail-status "></span> <svg class="octicon octicon-bell" viewBox="0 0 14 16" version="1.1" width="14" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M14 12v1H0v-1l.73-.58c.77-.77.81-2.55 1.19-4.42C2.69 3.23 6 2 6 2c0-.55.45-1 1-1s1 .45 1 1c0 0 3.39 1.23 4.16 5 .38 1.88.42 3.66 1.19 4.42l.66.58H14zm-7 4c1.11 0 2-.89 2-2H5c0 1.11.89 2 2 2z"/></svg> </a> </span> </li> <li class="dropdown"> <details class="details-overlay details-reset d-none d-lg-flex px-lg-2 py-2 py-lg-0 flex-items-center"> <summary class="HeaderNavlink" aria-label="Create new…" data-ga-click="Header, create new, icon:add"> <svg class="octicon octicon-plus float-left mr-1 mt-1" viewBox="0 0 12 16" version="1.1" width="12" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M12 9H7v5H5V9H0V7h5V2h2v5h5v2z"/></svg> <span class="dropdown-caret mt-1"></span> </summary> <details-menu class="dropdown-menu dropdown-menu-sw"> <a role="menuitem" class="dropdown-item" href="/new" data-ga-click="Header, create new repository"> New repository </a> <a role="menuitem" class="dropdown-item" href="/new/import" data-ga-click="Header, import a repository"> Import repository </a> <a role="menuitem" class="dropdown-item" href="https://gist.github.com/" data-ga-click="Header, create new gist"> New gist </a> <a role="menuitem" class="dropdown-item" href="/organizations/new" data-ga-click="Header, create new organization"> New organization </a> <div class="dropdown-divider"></div> <div class="dropdown-header"> <span title="Alvin9999/new-pac">This repository</span> </div> <a role="menuitem" class="dropdown-item" href="/Alvin9999/new-pac/issues/new" data-ga-click="Header, create new issue"> New issue </a> </details-menu> </details> </li> <li class="dropdown"> <a class="d-lg-none HeaderNavlink name tooltipped tooltipped-sw px-lg-2 py-2 py-lg-0" href="/p4g5" aria-label="View profile and more" aria-expanded="false" aria-haspopup="false"> <img alt="@p4g5" class="avatar float-left mr-1" src="https://avatars2.githubusercontent.com/u/47923458?s=40&v=4" height="20" width="20"> <span class="text-bold">p4g5</span> </a> <details class="details-overlay details-reset d-none d-lg-flex pl-lg-2 py-2 py-lg-0 flex-items-center"> <summary class="HeaderNavlink name mt-1" aria-label="View profile and more" data-ga-click="Header, show menu, icon:avatar"> <img alt="@p4g5" class="avatar float-left mr-1" src="https://avatars2.githubusercontent.com/u/47923458?s=40&v=4" height="20" width="20"> <span class="dropdown-caret"></span> </summary> <details-menu class="dropdown-menu dropdown-menu-sw"> <div class="header-nav-current-user css-truncate"><a role="menuitem" class="no-underline user-profile-link px-3 pt-2 pb-2 mb-n2 mt-n1 d-block" href="/p4g5" data-ga-click="Header, go to profile, text:Signed in as">Signed in as <strong class="css-truncate-target">p4g5</strong></a></div> <div role="none" class="dropdown-divider"></div> <div class="px-3 f6 user-status-container js-user-status-context pb-1" data-url="/users/status?compact=1&link_mentions=0&truncate=1"> <div class="js-user-status-container user-status-compact" data-team-hovercards-enabled> <details class="js-user-status-details details-reset details-overlay details-overlay-dark"> <summary class="btn-link no-underline js-toggle-user-status-edit toggle-user-status-edit width-full" aria-haspopup="dialog" role="menuitem" data-hydro-click="{"event_type":"user_profile.click","payload":{"profile_user_id":12132898,"target":"EDIT_USER_STATUS","user_id":47923458,"client_id":"1815209117.1550905425","originating_request_id":"818C:75AC:15C5D83:291B1C2:5C7218B8","originating_url":"https://github.com/Alvin9999/new-pac/wiki"}}" data-hydro-click-hmac="ced5050557a7bdc853d992aa928100040ac79be23fc4cb6ea21f7760d65c248f"> <div class="f6 d-inline-block v-align-middle user-status-emoji-only-header pl-0 circle lh-condensed user-status-header " style="max-width: 29px"> <div class="user-status-emoji-container flex-shrink-0 mr-1"> <svg class="octicon octicon-smiley" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M8 0C3.58 0 0 3.58 0 8s3.58 8 8 8 8-3.58 8-8-3.58-8-8-8zm4.81 12.81a6.72 6.72 0 0 1-2.17 1.45c-.83.36-1.72.53-2.64.53-.92 0-1.81-.17-2.64-.53-.81-.34-1.55-.83-2.17-1.45a6.773 6.773 0 0 1-1.45-2.17A6.59 6.59 0 0 1 1.21 8c0-.92.17-1.81.53-2.64.34-.81.83-1.55 1.45-2.17.62-.62 1.36-1.11 2.17-1.45A6.59 6.59 0 0 1 8 1.21c.92 0 1.81.17 2.64.53.81.34 1.55.83 2.17 1.45.62.62 1.11 1.36 1.45 2.17.36.83.53 1.72.53 2.64 0 .92-.17 1.81-.53 2.64-.34.81-.83 1.55-1.45 2.17zM4 6.8v-.59c0-.66.53-1.19 1.2-1.19h.59c.66 0 1.19.53 1.19 1.19v.59c0 .67-.53 1.2-1.19 1.2H5.2C4.53 8 4 7.47 4 6.8zm5 0v-.59c0-.66.53-1.19 1.2-1.19h.59c.66 0 1.19.53 1.19 1.19v.59c0 .67-.53 1.2-1.19 1.2h-.59C9.53 8 9 7.47 9 6.8zm4 3.2c-.72 1.88-2.91 3-5 3s-4.28-1.13-5-3c-.14-.39.23-1 .66-1h8.59c.41 0 .89.61.75 1z"/></svg> </div> </div> <div class="d-inline-block v-align-middle user-status-message-wrapper f6 lh-condensed ws-normal pt-1"> <span class="link-gray">Set your status</span> </div> </summary> <details-dialog class="details-dialog rounded-1 anim-fade-in fast Box Box--overlay" role="dialog" tabindex="-1"> <!-- '"` --><!-- </textarea></xmp> --></option></form><form class="position-relative flex-auto js-user-status-form" action="/users/status?compact=1&link_mentions=0&truncate=1" accept-charset="UTF-8" method="post"><input name="utf8" type="hidden" value="✓" /><input type="hidden" name="_method" value="put" /><input type="hidden" name="authenticity_token" value="UhUocX8QxRCQfi0VVq50V8DOQgt0VtegaH303QE9m8PCCEjaixc+T4i9Uc+Hu37cMb2xXx4TolEIzX4hl4y0uw==" /> <div class="Box-header bg-gray border-bottom p-3"> <button class="Box-btn-octicon js-toggle-user-status-edit btn-octicon float-right" type="reset" aria-label="Close dialog" data-close-dialog> <svg class="octicon octicon-x" viewBox="0 0 12 16" version="1.1" width="12" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M7.48 8l3.75 3.75-1.48 1.48L6 9.48l-3.75 3.75-1.48-1.48L4.52 8 .77 4.25l1.48-1.48L6 6.52l3.75-3.75 1.48 1.48L7.48 8z"/></svg> </button> <h3 class="Box-title f5 text-bold text-gray-dark">Edit status</h3> </div> <input type="hidden" name="emoji" class="js-user-status-emoji-field" value=""> <input type="hidden" name="organization_id" class="js-user-status-org-id-field" value=""> <div class="px-3 py-2 text-gray-dark"> <div class="js-characters-remaining-container js-suggester-container position-relative mt-2"> <div class="input-group d-table form-group my-0 js-user-status-form-group"> <span class="input-group-button d-table-cell v-align-middle" style="width: 1%"> <button type="button" aria-label="Choose an emoji" class="btn-outline btn js-toggle-user-status-emoji-picker bg-white btn-open-emoji-picker"> <span class="js-user-status-original-emoji" hidden></span> <span class="js-user-status-custom-emoji"></span> <span class="js-user-status-no-emoji-icon" > <svg class="octicon octicon-smiley" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M8 0C3.58 0 0 3.58 0 8s3.58 8 8 8 8-3.58 8-8-3.58-8-8-8zm4.81 12.81a6.72 6.72 0 0 1-2.17 1.45c-.83.36-1.72.53-2.64.53-.92 0-1.81-.17-2.64-.53-.81-.34-1.55-.83-2.17-1.45a6.773 6.773 0 0 1-1.45-2.17A6.59 6.59 0 0 1 1.21 8c0-.92.17-1.81.53-2.64.34-.81.83-1.55 1.45-2.17.62-.62 1.36-1.11 2.17-1.45A6.59 6.59 0 0 1 8 1.21c.92 0 1.81.17 2.64.53.81.34 1.55.83 2.17 1.45.62.62 1.11 1.36 1.45 2.17.36.83.53 1.72.53 2.64 0 .92-.17 1.81-.53 2.64-.34.81-.83 1.55-1.45 2.17zM4 6.8v-.59c0-.66.53-1.19 1.2-1.19h.59c.66 0 1.19.53 1.19 1.19v.59c0 .67-.53 1.2-1.19 1.2H5.2C4.53 8 4 7.47 4 6.8zm5 0v-.59c0-.66.53-1.19 1.2-1.19h.59c.66 0 1.19.53 1.19 1.19v.59c0 .67-.53 1.2-1.19 1.2h-.59C9.53 8 9 7.47 9 6.8zm4 3.2c-.72 1.88-2.91 3-5 3s-4.28-1.13-5-3c-.14-.39.23-1 .66-1h8.59c.41 0 .89.61.75 1z"/></svg> </span> </button> </span> <input type="text" autocomplete="off" autofocus data-maxlength="80" class="js-suggester-field d-table-cell width-full form-control js-user-status-message-field js-characters-remaining-field" placeholder="What's happening?" name="message" required value="" aria-label="What is your current status?"> <div class="error">Could not update your status, please try again.</div> </div> <div class="suggester-container"> <div class="suggester js-suggester js-navigation-container" data-url="/autocomplete/user-suggestions" data-no-org-url="/autocomplete/user-suggestions" data-org-url="/suggestions" hidden> </div> </div> <div style="margin-left: 53px" class="my-1 text-small label-characters-remaining js-characters-remaining" data-suffix="remaining" hidden> 80 remaining </div> </div> <include-fragment class="js-user-status-emoji-picker" data-url="/users/status/emoji"></include-fragment> <div class="overflow-auto" style="max-height: 33vh"> <div class="user-status-suggestions js-user-status-suggestions"> <h4 class="f6 text-normal my-3">Suggestions:</h4> <div class="mx-3 mt-2 clearfix"> <div class="float-left col-6"> <button type="button" value=":palm_tree:" class="d-flex flex-items-baseline flex-items-stretch lh-condensed f6 btn-link link-gray no-underline js-predefined-user-status mb-1"> <div class="emoji-status-width mr-2 v-align-middle js-predefined-user-status-emoji"> <g-emoji alias="palm_tree" fallback-src="https://github.githubassets.com/images/icons/emoji/unicode/1f334.png">🌴</g-emoji> </div> <div class="d-flex flex-items-center no-underline js-predefined-user-status-message" style="border-left: 1px solid transparent"> On vacation </div> </button> <button type="button" value=":face_with_thermometer:" class="d-flex flex-items-baseline flex-items-stretch lh-condensed f6 btn-link link-gray no-underline js-predefined-user-status mb-1"> <div class="emoji-status-width mr-2 v-align-middle js-predefined-user-status-emoji"> <g-emoji alias="face_with_thermometer" fallback-src="https://github.githubassets.com/images/icons/emoji/unicode/1f912.png">🤒</g-emoji> </div> <div class="d-flex flex-items-center no-underline js-predefined-user-status-message" style="border-left: 1px solid transparent"> Out sick </div> </button> </div> <div class="float-left col-6"> <button type="button" value=":house:" class="d-flex flex-items-baseline flex-items-stretch lh-condensed f6 btn-link link-gray no-underline js-predefined-user-status mb-1"> <div class="emoji-status-width mr-2 v-align-middle js-predefined-user-status-emoji"> <g-emoji alias="house" fallback-src="https://github.githubassets.com/images/icons/emoji/unicode/1f3e0.png">🏠</g-emoji> </div> <div class="d-flex flex-items-center no-underline js-predefined-user-status-message" style="border-left: 1px solid transparent"> Working from home </div> </button> <button type="button" value=":dart:" class="d-flex flex-items-baseline flex-items-stretch lh-condensed f6 btn-link link-gray no-underline js-predefined-user-status mb-1"> <div class="emoji-status-width mr-2 v-align-middle js-predefined-user-status-emoji"> <g-emoji alias="dart" fallback-src="https://github.githubassets.com/images/icons/emoji/unicode/1f3af.png">🎯</g-emoji> </div> <div class="d-flex flex-items-center no-underline js-predefined-user-status-message" style="border-left: 1px solid transparent"> Focusing </div> </button> </div> </div> </div> <div class="user-status-limited-availability-container"> <div class="form-checkbox my-0"> <input type="checkbox" name="limited_availability" value="1" class="js-user-status-limited-availability-checkbox" data-default-message="I may be slow to respond." aria-describedby="limited-availability-help-text-truncate-true" id="limited-availability-truncate-true"> <label class="d-block f5 text-gray-dark mb-1" for="limited-availability-truncate-true"> Busy </label> <p class="note" id="limited-availability-help-text-truncate-true"> When others mention you, assign you, or request your review, GitHub will let them know that you have limited availability. </p> </div> </div> </div> <include-fragment class="js-user-status-org-picker" data-url="/users/status/organizations"></include-fragment> </div> <div class="d-flex flex-items-center flex-justify-between p-3 border-top"> <button type="submit" disabled class="width-full btn btn-primary mr-2 js-user-status-submit"> Set status </button> <button type="button" disabled class="width-full js-clear-user-status-button btn ml-2 "> Clear status </button> </div> </form> </details-dialog> </details> </div> </div> <div role="none" class="dropdown-divider"></div> <a role="menuitem" class="dropdown-item" href="/p4g5" data-ga-click="Header, go to profile, text:your profile">Your profile</a> <a role="menuitem" class="dropdown-item" href="/p4g5?tab=repositories" data-ga-click="Header, go to repositories, text:your repositories">Your repositories</a> <a role="menuitem" class="dropdown-item" href="/p4g5?tab=projects" data-ga-click="Header, go to projects, text:your projects">Your projects</a> <a role="menuitem" class="dropdown-item" href="/p4g5?tab=stars" data-ga-click="Header, go to starred repos, text:your stars">Your stars</a> <a role="menuitem" class="dropdown-item" href="https://gist.github.com/" data-ga-click="Header, your gists, text:your gists">Your gists</a> <div role="none" class="dropdown-divider"></div> <a role="menuitem" class="dropdown-item" href="https://help.github.com" data-ga-click="Header, go to help, text:help">Help</a> <a role="menuitem" class="dropdown-item" href="/settings/profile" data-ga-click="Header, go to settings, icon:settings">Settings</a> <!-- '"` --><!-- </textarea></xmp> --></option></form><form class="logout-form" action="/logout" accept-charset="UTF-8" method="post"><input name="utf8" type="hidden" value="✓" /><input type="hidden" name="authenticity_token" value="Y8HcCFJNTD+hYd7Kv9FtT+Xxj7WUTAFihH0C9cLChd+JHtM9aCiGPnCGrrkcg/KpMKG0LJm8JbL5T2kPHqYNjQ==" /> <button type="submit" class="dropdown-item dropdown-signout" data-ga-click="Header, sign out, icon:logout" role="menuitem"> Sign out </button> </form> </details-menu> </details> </li> </ul> <!-- '"` --><!-- </textarea></xmp> --></option></form><form class="d-lg-none" action="/logout" accept-charset="UTF-8" method="post"><input name="utf8" type="hidden" value="✓" /><input type="hidden" name="authenticity_token" value="oluBBaw9qfMJXUP8GdR5bZc9/Gw7dMAE2fQ5JlOw2OBIhI4wllhj8ti6M4+6huaLQm3H9TaE5NSkxlLcj9RQsg==" /> <button type="submit" class="btn-link HeaderNavlink d-block width-full text-left py-2 text-bold" data-ga-click="Header, sign out, icon:logout" style="padding-left: 2px;"> <svg class="octicon octicon-sign-out v-align-middle" style="margin-right: 2px;" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M12 9V7H8V5h4V3l4 3-4 3zm-2 3H6V3L2 1h8v3h1V1c0-.55-.45-1-1-1H1C.45 0 0 .45 0 1v11.38c0 .39.22.73.55.91L6 16.01V13h4c.55 0 1-.45 1-1V8h-1v4z"/></svg> Sign out </button> </form> <!-- '"` --><!-- </textarea></xmp> --></option></form><form class="sr-only right-0" action="/logout" accept-charset="UTF-8" method="post"><input name="utf8" type="hidden" value="✓" /><input type="hidden" name="authenticity_token" value="b0Bgz4mqScE7zq0QVm08tZv5z1OzCVx+ozCI3NlInJaFn2/6s8+DwOop3WP1P6NTTqn0yr75eK7eAuMmBSwUxA==" /> <button type="submit" class="dropdown-item dropdown-signout" data-ga-click="Header, sign out, icon:logout"> Sign out </button> </form> </div> </div> </div> </header> </div> <div id="start-of-content" class="show-on-focus"></div> <div id="js-flash-container"> </div> <div role="main" class="application-main " data-commit-hovercards-enabled> <div itemscope itemtype="http://schema.org/SoftwareSourceCode" class=""> <div > <div class="pagehead repohead instapaper_ignore readability-menu experiment-repo-nav pt-0 pt-lg-3 "> <div class="repohead-details-container clearfix container-lg p-responsive d-none d-lg-block"> <ul class="pagehead-actions"> <li> <!-- '"` --><!-- </textarea></xmp> --></option></form><form data-remote="true" class="js-social-form js-social-container" action="/notifications/subscribe" accept-charset="UTF-8" method="post"><input name="utf8" type="hidden" value="✓" /><input type="hidden" name="authenticity_token" value="KK6/k23EkvBozTQwWgEA5FH8ZX5XVrBLzcGpR4JinAhq7/tIjemrK8lhd0do997jcIFVbSagHOTaRJTrAyLvEQ==" /> <input type="hidden" name="repository_id" id="repository_id" value="54544023" class="form-control" /> <details class="details-reset details-overlay select-menu float-left"> <summary class="btn btn-sm btn-with-count select-menu-button" data-ga-click="Repository, click Watch settings, action:wiki#index"> <span data-menu-button> <svg class="octicon octicon-eye v-align-text-bottom" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M8.06 2C3 2 0 8 0 8s3 6 8.06 6C13 14 16 8 16 8s-3-6-7.94-6zM8 12c-2.2 0-4-1.78-4-4 0-2.2 1.8-4 4-4 2.22 0 4 1.8 4 4 0 2.22-1.78 4-4 4zm2-4c0 1.11-.89 2-2 2-1.11 0-2-.89-2-2 0-1.11.89-2 2-2 1.11 0 2 .89 2 2z"/></svg> Watch </span> </summary> <details-menu class="select-menu-modal position-absolute mt-5" style="z-index: 99;"> <div class="select-menu-header"> <span class="select-menu-title">Notifications</span> </div> <div class="select-menu-list"> <button type="submit" name="do" value="included" class="select-menu-item width-full" aria-checked="true" role="menuitemradio"> <svg class="octicon octicon-check select-menu-item-icon" viewBox="0 0 12 16" version="1.1" width="12" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M12 5l-8 8-4-4 1.5-1.5L4 10l6.5-6.5L12 5z"/></svg> <div class="select-menu-item-text"> <span class="select-menu-item-heading">Not watching</span> <span class="description">Be notified only when participating or @mentioned.</span> <span class="hidden-select-button-text" data-menu-button-contents> <svg class="octicon octicon-eye v-align-text-bottom" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M8.06 2C3 2 0 8 0 8s3 6 8.06 6C13 14 16 8 16 8s-3-6-7.94-6zM8 12c-2.2 0-4-1.78-4-4 0-2.2 1.8-4 4-4 2.22 0 4 1.8 4 4 0 2.22-1.78 4-4 4zm2-4c0 1.11-.89 2-2 2-1.11 0-2-.89-2-2 0-1.11.89-2 2-2 1.11 0 2 .89 2 2z"/></svg> Watch </span> </div> </button> <button type="submit" name="do" value="release_only" class="select-menu-item width-full" aria-checked="false" role="menuitemradio"> <svg class="octicon octicon-check select-menu-item-icon" viewBox="0 0 12 16" version="1.1" width="12" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M12 5l-8 8-4-4 1.5-1.5L4 10l6.5-6.5L12 5z"/></svg> <div class="select-menu-item-text"> <span class="select-menu-item-heading">Releases only</span> <span class="description">Be notified of new releases, and when participating or @mentioned.</span> <span class="hidden-select-button-text" data-menu-button-contents> <svg class="octicon octicon-eye v-align-text-bottom" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M8.06 2C3 2 0 8 0 8s3 6 8.06 6C13 14 16 8 16 8s-3-6-7.94-6zM8 12c-2.2 0-4-1.78-4-4 0-2.2 1.8-4 4-4 2.22 0 4 1.8 4 4 0 2.22-1.78 4-4 4zm2-4c0 1.11-.89 2-2 2-1.11 0-2-.89-2-2 0-1.11.89-2 2-2 1.11 0 2 .89 2 2z"/></svg> Unwatch releases </span> </div> </button> <button type="submit" name="do" value="subscribed" class="select-menu-item width-full" aria-checked="false" role="menuitemradio"> <svg class="octicon octicon-check select-menu-item-icon" viewBox="0 0 12 16" version="1.1" width="12" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M12 5l-8 8-4-4 1.5-1.5L4 10l6.5-6.5L12 5z"/></svg> <div class="select-menu-item-text"> <span class="select-menu-item-heading">Watching</span> <span class="description">Be notified of all conversations.</span> <span class="hidden-select-button-text" data-menu-button-contents> <svg class="octicon octicon-eye v-align-text-bottom" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M8.06 2C3 2 0 8 0 8s3 6 8.06 6C13 14 16 8 16 8s-3-6-7.94-6zM8 12c-2.2 0-4-1.78-4-4 0-2.2 1.8-4 4-4 2.22 0 4 1.8 4 4 0 2.22-1.78 4-4 4zm2-4c0 1.11-.89 2-2 2-1.11 0-2-.89-2-2 0-1.11.89-2 2-2 1.11 0 2 .89 2 2z"/></svg> Unwatch </span> </div> </button> <button type="submit" name="do" value="ignore" class="select-menu-item width-full" aria-checked="false" role="menuitemradio"> <svg class="octicon octicon-check select-menu-item-icon" viewBox="0 0 12 16" version="1.1" width="12" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M12 5l-8 8-4-4 1.5-1.5L4 10l6.5-6.5L12 5z"/></svg> <div class="select-menu-item-text"> <span class="select-menu-item-heading">Ignoring</span> <span class="description">Never be notified.</span> <span class="hidden-select-button-text" data-menu-button-contents> <svg class="octicon octicon-mute v-align-text-bottom" viewBox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M8 2.81v10.38c0 .67-.81 1-1.28.53L3 10H1c-.55 0-1-.45-1-1V7c0-.55.45-1 1-1h2l3.72-3.72C7.19 1.81 8 2.14 8 2.81zm7.53 3.22l-1.06-1.06-1.97 1.97-1.97-1.97-1.06 1.06L11.44 8 9.47 9.97l1.06 1.06 1.97-1.97 1.97 1.97 1.06-1.06L13.56 8l1.97-1.97z"/></svg> Stop ignoring </span> </div> </button> </div> </details-menu> </details> <a class="social-count js-social-count" href="/Alvin9999/new-pac/watchers" aria-label="885 users are watching this repository"> 885 </a> </form> </li> <li> <div class="js-toggler-container js-social-container starring-container "> <!-- '"` --><!-- </textarea></xmp> --></option></form><form class="starred js-social-form" action="/Alvin9999/new-pac/unstar" accept-charset="UTF-8" method="post"><input name="utf8" type="hidden" value="✓" /><input type="hidden" name="authenticity_token" value="GTo3eO2YhEo8L7lENMkL+RSLnBTchg9YTdhcTMAWPQx/JBU/tuW7iAaYUuM24agiYdiJviImlX0ddi4rMZdncg==" /> <input type="hidden" name="context" value="repository"></input> <button type="submit" class="btn btn-sm btn-with-count js-toggler-target" aria-label="Unstar this repository" title="Unstar Alvin9999/new-pac" data-ga-click="Repository, click unstar button, action:wiki#index; text:Unstar"> <svg class="octicon octicon-star v-align-text-bottom" viewBox="0 0 14 16" version="1.1" width="14" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M14 6l-4.9-.64L7 1 4.9 5.36 0 6l3.6 3.26L2.67 14 7 11.67 11.33 14l-.93-4.74L14 6z"/></svg> Unstar </button> <a class="social-count js-social-count" href="/Alvin9999/new-pac/stargazers" aria-label="10597 users starred this repository"> 10,597 </a> </form> <!-- '"` --><!-- </textarea></xmp> --></option></form><form class="unstarred js-social-form" action="/Alvin9999/new-pac/star" accept-charset="UTF-8" method="post"><input name="utf8" type="hidden" value="✓" /><input type="hidden" name="authenticity_token" value="BQPzq91IsEBS9r+jwR/XVm38bv38iO0gZAS8UpQ9frXP14g4U9YoouFFk/ychCBLkSmg2JW6KZBv6jzyY5Ys2A==" /> <input type="hidden" name="context" value="repository"></input> <button type="submit" class="btn btn-sm btn-with-count js-toggler-target" aria-label="Star this repository" title="Star Alvin9999/new-pac" data-ga-click="Repository, click star button, action:wiki#index; text:Star"> <svg class="octicon octicon-star v-align-text-bottom" viewBox="0 0 14 16" version="1.1" width="14" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M14 6l-4.9-.64L7 1 4.9 5.36 0 6l3.6 3.26L2.67 14 7 11.67 11.33 14l-.93-4.74L14 6z"/></svg> Star </button> <a class="social-count js-social-count" href="/Alvin9999/new-pac/stargazers" aria-label="10597 users starred this repository"> 10,597 </a> </form> </div> </li> <li> <!-- '"` --><!-- </textarea></xmp> --></option></form><form class="btn-with-count" action="/Alvin9999/new-pac/fork" accept-charset="UTF-8" method="post"><input name="utf8" type="hidden" 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class="container-lg new-discussion-timeline experiment-repo-nav p-responsive"> <div class="repository-content "> <div id="wiki-wrapper" class="page"> <div class="d-flex flex-column flex-md-row gh-header"> <h1 class="flex-auto min-width-0 mb-2 mb-md-0 mr-0 mr-md-2 gh-header-title instapaper_title">Home</h1> <div class="mt-0 mt-lg-1 flex-shrink-0 gh-header-actions"> <a href="#wiki-pages-box" class="d-md-none ">Jump to bottom</a> </div> </div> <div class="mt-2 mt-md-1 pb-3 gh-header-meta"> 自由上网 edited this page <relative-time datetime="2019-02-19T14:44:48Z">Feb 19, 2019</relative-time> · <a href="/Alvin9999/new-pac/wiki/Home/_history" class="muted-link"> 1061 revisions </a> </div> <div id="wiki-content" class="d-flex flex-column flex-md-row"> <div id="wiki-body" class="mt-4 flex-auto min-width-0 gollum-markdown-content instapaper_body"> <div class="markdown-body"> <h3> <a id="user-content-自由上网方法" class="anchor" href="#%E8%87%AA%E7%94%B1%E4%B8%8A%E7%BD%91%E6%96%B9%E6%B3%95" aria-hidden="true"><svg class="octicon octicon-link" viewbox="0 0 16 16" version="1.1" width="16" height="16" aria-hidden="true"><path fill-rule="evenodd" d="M4 9h1v1H4c-1.5 0-3-1.69-3-3.5S2.55 3 4 3h4c1.45 0 3 1.69 3 3.5 0 1.41-.91 2.72-2 3.25V8.59c.58-.45 1-1.27 1-2.09C10 5.22 8.98 4 8 4H4c-.98 0-2 1.22-2 2.5S3 9 4 9zm9-3h-1v1h1c1 0 2 1.22 2 2.5S13.98 12 13 12H9c-.98 0-2-1.22-2-2.5 0-.83.42-1.64 1-2.09V6.25c-1.09.53-2 1.84-2 3.25C6 11.31 7.55 13 9 13h4c1.45 0 3-1.69 3-3.5S14.5 6 13 6z"></path></svg></a><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong><strong>自由上网方法</strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong></strong> </h3> <pre><code> 一键翻墙浏览器 </code></pre> <p>永久免费。不用安装，无需设置，解压后使用。稳定、流畅、高速，长期更新。</p> <p><img src="https://raw.githubusercontent.com/Alvin9999/pac2/master/%E5%9B%BE%E6%A0%87.PNG" alt=""></p> <p><strong>介绍</strong>：GoProxy ipv6版、GoAgent ipv6版、v2ray版、SSR版、赛风版、WuJie版、FreeGate版、SkyZip版，适合windows操作系统，比如：Xp、win7、win8、win10系统。浏览器自带翻译插件和YouTube视频下载脚本，方便且实用。压缩包文件的格式是7z，如果解压出错，用7解压软件来解压（<a href="https://sparanoid.com/lab/7z/" rel="nofollow">7z解压软件下载地址</a>）。</p> <p><strong>注意</strong>：软件都是采用加密方式的，但为了更稳定、更安全的翻墙，建议卸载国产杀毒软件，至少翻墙时不要用它们！因为很多国产杀毒软件，比如360安全卫生、360杀毒软件、腾讯管家、金山卫士等不仅仅会起干扰作用，造成软件无法正常使用或速度变慢，它们与防火墙还有千丝万缕的关系!其实win10自带的defender就有杀毒的功能，如果还需要安全软件，可以用国外的杀毒软件<a href="http://files.avast.com/iavs9x/avast_free_antivirus_setup_offline.exe" rel="nofollow">avast</a>，防火墙<a href="https://github.com/henrypp/simplewall/releases/download/v.2.3.4/simplewall-2.3.4-setup.exe">simplewall</a>，还有清理软件<a href="http://downloads.wisecleaner.com/soft/WiseCare365.exe" rel="nofollow">wisecare365</a>。它们都是免费的，而且不会干扰电脑运行。</p> <p><strong>选择指南</strong>：有GoProxy ipv6版、GoAgent ipv6版、v2ray版、SSR版、赛风版、WuJie版、FreeGate版、SkyZip版,可以按照顺序依次尝试。由于国内网络环境不同、地区不同，封锁强度会不同，所以使用效果会有差别，有的地区几乎所有的软件都能使用，有的只能用几款，因此具体哪款软件适合你的网络环境，需要你自己来尝试。内存低于2G的电脑建议用<a href="https://github.com/Alvin9999/new-pac/wiki/%E7%81%AB%E7%8B%90%E7%BF%BB%E5%A2%99%E6%B5%8F%E8%A7%88%E5%99%A8">火狐翻墙浏览器</a>。还有<a href="https://github.com/Alvin9999/new-pac/wiki/%E7%9B%B4%E7%BF%BB%E9%80%9A%E9%81%93">直翻通道</a>可供选择，电脑、手机、平板都能使用。如果想自己搭建翻墙服务器，可以学习<a href="https://github.com/Alvin9999/new-pac/wiki/%E8%87%AA%E5%BB%BAss%E6%9C%8D%E5%8A%A1%E5%99%A8%E6%95%99%E7%A8%8B">自建ss/ssr服务器教程</a>或<a href="https://github.com/Alvin9999/new-pac/wiki/%E8%87%AA%E5%BB%BAv2ray%E6%9C%8D%E5%8A%A1%E5%99%A8%E6%95%99%E7%A8%8B">自建v2ray服务器教程</a>。</p> <p><strong>2018年6月6日</strong>：发布<a href="https://gitlab.com/Alvin9999/free/wikis/home" rel="nofollow">备用项目地址</a> 。</p> <p><strong>2019年1月18日公告</strong>：ipv6版国内大多数地区已失效，如果你无法使用ipv6版，请更换其它类型的软件。</p> <p><strong>推荐YouTube视频频道</strong>：<a href="https://www.youtube.com/channel/UCa6ERCDt3GzkvLye32ar89w/videos" rel="nofollow">历史上的今天</a> <a href="https://www.youtube.com/channel/UCtAIPjABiQD3qjlEl1T5VpA/featured" rel="nofollow">文昭談古論今</a></p> <hr> <p><a href="https://github.com/Alvin9999/new-pac/wiki/%E9%AB%98%E5%86%85%E6%A0%B8%E7%89%88">谷歌浏览器69高内核版</a> （2019年2月16日更新无界版本至19.02,更新自由门版本至7.66）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/ipv6%E5%BC%80%E5%90%AF%E6%96%B9%E6%B3%95">ipv6开启方法</a> （2018年6月22日更新方法）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/GoAgent-ipv6%E7%89%88">谷歌浏览器低内核GoAgent ipv6版</a> （2018年12月20日云端更新GoAgent ipv6）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/v2ray%E7%89%88">谷歌浏览器低内核v2ray版</a> （2018年12月27日云端更新v2ray配置信息）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/SSR%E7%89%88">谷歌浏览器低内核SSR版</a> （2018年9月23日更新版本）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/%E8%B5%9B%E9%A3%8E%E7%89%88">谷歌浏览器低内核赛风版</a> （2018年9月23日更新版本）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/FreeGate%E5%92%8CWuJie%E7%89%88">谷歌浏览器低内核FreeGate和WuJie版</a>（2019年2月16日更新无界版本至19.02,更新自由门版本至7.66）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/SkyZip%E7%89%88">谷歌浏览器低内核SkyZip版</a>（2018年9月23日更新版本）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/GoProxy-ipv6%E7%89%88">谷歌浏览器低内核GoProxy ipv6版</a> （2018年9月23日更新版本）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/%E7%81%AB%E7%8B%90%E7%BF%BB%E5%A2%99%E6%B5%8F%E8%A7%88%E5%99%A8">火狐翻墙浏览器</a>（2019年2月16日更新无界版本至19.02,更新自由门版本至7.66）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/%E7%9B%B4%E7%BF%BB%E9%80%9A%E9%81%93">直翻通道</a> （2018年1月31日更新）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/%E8%B0%B7%E6%AD%8C%E9%95%9C%E5%83%8F">谷歌镜像</a> （2018年10月28日更新）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/%E8%87%AA%E5%BB%BAss%E6%9C%8D%E5%8A%A1%E5%99%A8%E6%95%99%E7%A8%8B">自建SS/SSR服务器教程</a> （2018年11月21日增加SS/SSR部署备用脚本）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/%E8%87%AA%E5%BB%BAv2ray%E6%9C%8D%E5%8A%A1%E5%99%A8%E6%95%99%E7%A8%8B">自建v2ray服务器教程</a> （2019年2月11日更新一键部署v2ray脚本）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/%E5%AE%89%E5%8D%93%E6%89%8B%E6%9C%BA%E7%89%88">安卓手机版</a>（2018年6月24日更新聚缘阁安卓版）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/%E8%8B%B9%E6%9E%9C%E6%89%8B%E6%9C%BA%E7%BF%BB%E5%A2%99%E8%BD%AF%E4%BB%B6">苹果手机翻墙方法</a>（2018年2月24日更新）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/%E8%8B%B9%E6%9E%9C%E7%94%B5%E8%84%91MAC%E7%BF%BB%E5%A2%99%E8%BD%AF%E4%BB%B6">MAC翻墙方法</a>（2017年12月25日删除无效方法）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/%E5%B9%B3%E6%9D%BF%E7%94%B5%E8%84%91%E7%BF%BB%E5%A2%99%E8%BD%AF%E4%BB%B6">平板电脑翻墙方法</a>（2018年2月4日更新）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/Linux%E7%B3%BB%E7%BB%9F%E7%BF%BB%E5%A2%99%E6%96%B9%E6%B3%95">Linux系统翻墙方法</a> （2018年5月30日增加Linux SSR 使用方法二）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/YouTube%E4%B8%8B%E8%BD%BD1080%E6%95%99%E7%A8%8B">YouTube下载1080教程</a> （2018年11月25日发布）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/%E5%AE%9E%E7%94%A8%E7%BD%91%E7%BB%9C%E5%B0%8F%E7%9F%A5%E8%AF%86">实用网络小知识</a> （2018年4月26日更新）</p> <p><a href="https://github.com/Alvin9999/new-pac/wiki/%E6%95%B0%E5%AD%97%E5%AE%89%E5%85%A8%E6%89%8B%E5%86%8C">数字安全手册</a> （推荐两本关于网络安全的书籍）</p> <hr> <p>真心希望大家都能够突破网络封锁、获得真相，祝愿每位善良的人都能拥有一个美好的未来。</p> <p>2019年神韵晚会超清预告片<a href="http://108.61.224.82:8000/f/ddd18239a6/" rel="nofollow">在线观看或下载</a></p> <p><img src="https://raw.githubusercontent.com/Alvin9999/pac2/master/shenyun003.jpg" alt=""></p> <p><img src="https://raw.githubusercontent.com/Alvin9999/pac2/master/1.JPG" alt=""></p> <p><img src="https://raw.githubusercontent.com/Alvin9999/pac2/master/2.JPG" alt=""></p> <hr> <p>有问题可以发帖<a href="https://github.com/Alvin9999/new-pac/issues">反馈交流</a>，或者发邮件到海外邮箱<a href="mailto:kebi2014@gmail.com">kebi2014@gmail.com</a>进行反馈，反馈邮件标题最好注明什么软件及截图。</p> </div> </div> <div id="wiki-rightbar" class="mt-4 ml-md-6 flex-shrink-0 width-full wiki-rightbar"> <div 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href="/Alvin9999/new-pac/wiki/%E5%AE%9E%E7%94%A8%E7%BD%91%E7%BB%9C%E5%B0%8F%E7%9F%A5%E8%AF%86">实用网络小知识</a></strong> </li> <li class="Box-row"> <strong><a class="d-block" href="/Alvin9999/new-pac/wiki/%E5%B9%B3%E6%9D%BF%E7%94%B5%E8%84%91%E7%BF%BB%E5%A2%99%E8%BD%AF%E4%BB%B6">平板电脑翻墙软件</a></strong> </li> <li class="Box-row wiki-more-pages"> <strong><a class="d-block" href="/Alvin9999/new-pac/wiki/%E6%95%B0%E5%AD%97%E5%AE%89%E5%85%A8%E6%89%8B%E5%86%8C">数字安全手册</a></strong> </li> <li class="Box-row wiki-more-pages"> <strong><a class="d-block" href="/Alvin9999/new-pac/wiki/%E7%81%AB%E7%8B%90%E7%BF%BB%E5%A2%99%E6%B5%8F%E8%A7%88%E5%99%A8">火狐翻墙浏览器</a></strong> </li> <li class="Box-row wiki-more-pages"> <strong><a class="d-block" href="/Alvin9999/new-pac/wiki/%E7%9B%B4%E7%BF%BB%E9%80%9A%E9%81%93">直翻通道</a></strong> </li> <li class="Box-row wiki-more-pages"> <strong><a class="d-block" href="/Alvin9999/new-pac/wiki/%E8%87%AA%E5%BB%BAgoogle-appid%E6%95%99%E7%A8%8B">自建google appid教程</a></strong> </li> <li class="Box-row wiki-more-pages"> <strong><a class="d-block" href="/Alvin9999/new-pac/wiki/%E8%87%AA%E5%BB%BAss%E6%9C%8D%E5%8A%A1%E5%99%A8%E6%95%99%E7%A8%8B">自建ss服务器教程</a></strong> </li> <li class="Box-row wiki-more-pages"> <strong><a class="d-block" href="/Alvin9999/new-pac/wiki/%E8%87%AA%E5%BB%BAv2ray%E6%9C%8D%E5%8A%A1%E5%99%A8%E6%95%99%E7%A8%8B">自建v2ray服务器教程</a></strong> </li> <li class="Box-row wiki-more-pages"> <strong><a class="d-block" href="/Alvin9999/new-pac/wiki/%E8%8B%B9%E6%9E%9C%E6%89%8B%E6%9C%BA%E7%BF%BB%E5%A2%99%E8%BD%AF%E4%BB%B6">苹果手机翻墙软件</a></strong> </li> <li class="Box-row wiki-more-pages"> <strong><a class="d-block" href="/Alvin9999/new-pac/wiki/%E8%8B%B9%E6%9E%9C%E7%94%B5%E8%84%91MAC%E7%BF%BB%E5%A2%99%E8%BD%AF%E4%BB%B6">苹果电脑MAC翻墙软件</a></strong> </li> <li class="Box-row wiki-more-pages"> <strong><a class="d-block" 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Orbifold / KnwlerKnwler is a lightweight, single-file Python tool that extracts structured knowledge graphs from documents using AI. Feed it a PDF or text file and receive a richly connected network of entities, relationships, and topics — complete with an interactive HTML report and exports ready for your favorite graph analytics platform.
