For retail store owners and multi-location retail operations needing a tool to manage sales, inventory, staff and channels in one place
Vibe Retail is an all-in-one retail point-of-sale and operations platform built for single-store and multi-location retailers seeking to unify inventory, sales, staff and customer data from one mobile-friendly interface. The system lets you track inventory across locations and warehouses, handle item variations (size, color, material), manage purchase orders and supplier deliveries, print custom barcodes, and transfer stock between stores in real time. On the sales side, Vibe supports multiple payment types (cards, cash, checks, gift cards, EBT), layaway workflows, serial number tracking, delivery management, loyalty programs and branded receipts. Retailers can integrate with online platforms (such as Shopify and WooCommerce), sync in-store and online sales, access 40+ real-time reports on sales, inventory and performance, set up promotions and discounts, and print receipts from mobile devices.
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Monitoring, Securing, Optimizing 3rd party scripts
For developers looking for a solution to monitor, script, and optimize 3rd party scripts
c/side is crawling many sites to get ahead of new attacks. c/side is the only fully autonomous detection tool for assessing 3rd party scripts. We do not rely purely on threat feed intel or easy to circumvent detections. We also use historical context and AI to review the payload and behavior of scripts.
Weka4OC: Weka for Overlapping Clustering is a GUI extending WEKA
This is a GUI application for learning non disjoint groups based on Weka machine learning framework. It offers a variety of learning methods, based on k-means, able to produce overlapping clusters. The application also contains an evaluation framework that calculates several external validation measures. The application offers a visualization tool to discover overlapping groups.
Exact Subgraph Matching Algorithm for Dependency Graphs
...We designed a simple exact subgraph matching (ESM) algorithm for dependency graphs using a backtracking approach. The total worst-case algorithm complexity is O(n^2 * k^n) where n is the number of vertices and k is the vertex degree.
We have demonstrated the successful usage of our algorithm in three biomedical relation and event extraction applications: BioNLP 2011 shared tasks on event extraction, Protein-Residue association detection and Protein-Protein interaction identification.
This Java implementation implements our ESM algorithm. ...
An implementation of "k-Way Merging" as described in "Fundamentals of Data Structures" by Horowitz/Sahni. NOTE: This project has been moved to http://code.google.com/p/kway/
K-automaton is a new parsing (syntactic analysis) machine isomorphous to language. Implemented in Java. Can generate Java code from grammars described in EBNF.
Streamline your business with an all-in-one platform for HR, IT, payroll, and spend management.
Effortlessly manage the entire employee lifecycle, from hiring to benefits administration. Automate HR tasks, ensure compliance, and streamline approvals. Simplify IT with device management, software access, and compliance monitoring, all from one dashboard. Enjoy timely payroll, real-time financial visibility, and dynamic spend policies. Rippling empowers your business to save time, reduce costs, and enhance efficiency, allowing you to focus on growth. Experience the power of unified management with Rippling today.
Project Tokaf is an general implementation of top-k algorithm. It provides interfaces for all modules that are needed. It also features user preferences module, for computing new preferences and manipulating existing ones.
KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
brCluster is a class library, written in java, that implements generic clustering algorithms carefully designed to allow its aplication in any kind of data. The algorithms implemented are K-means and Hierarchical Clustering (Simple and Complete Link).