Presemt architecture
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PRESEMT is a machine translation system that uses pattern recognition and statistical techniques. It develops a novel phrase aligner using clustering, employs pattern recognition for syntax, and uses biologically-inspired techniques for disambiguation. PRESEMT also extensively uses automation for parameter optimization, adapts to user preferences, and leverages parallel computing for faster translation speeds using large web corpora.
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The .NET framework is a technology from Microsoft that other Microsoft technologies will depend on in the future. It provides a common language runtime, class libraries, and compiler support for multiple programming languages. The common language runtime manages memory, threads, and provides a language-independent environment. The framework class library includes a large collection of reusable classes and interfaces organized in a hierarchical structure. The .NET framework simplifies development, provides consistent programming models across languages, direct support for security, and easy application deployment and maintenance.
SANTOSH KUMAR M -FD
Santosh Kumar is a software QA engineer with 2 years of experience in automated testing. He is proficient in Perl, Selenium, Java and has experience developing test automation scripts for GUI and functional testing. He has worked on several projects at Netapp related to transitioning data from 7-mode to clustered storage. His roles included developing centralized libraries for automation, assisting with automation script development, executing manual tests and managing test suites. He is looking for new opportunities in QA automation in Bangalore, Hyderabad or Chennai.
Metta Innovations - Introdução ao Deep Learning aplicado a vídeo analytics
Deep learning is a machine learning technique using artificial neural networks with many hidden layers. It is well-suited for complex tasks like computer vision, speech recognition, and natural language processing. Deep learning models can automatically extract features from data rather than relying on manual feature engineering. Open source deep learning libraries like CNTK, Caffe, TensorFlow, Theano, and Torch allow researchers to experiment with deep learning. CNTK in particular defines neural networks as computational graphs that can be composed into complex models and trained using gradient descent.
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LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...
This LF Energy webinar took place June 20, 2024. It featured:
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In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms.
This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups.
Three primary specifications will be discussed:
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Essentials of Automations: Exploring Attributes & Automation Parameters
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
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Introducing BoxLang : A new JVM language for productivity and modularity!
Just like life, our code must adapt to the ever changing world we live in. From one day coding for the web, to the next for our tablets or APIs or for running serverless applications. Multi-runtime development is the future of coding, the future is to be dynamic. Let us introduce you to BoxLang.
Dynamic. Modular. Productive.
BoxLang redefines development with its dynamic nature, empowering developers to craft expressive and functional code effortlessly. Its modular architecture prioritizes flexibility, allowing for seamless integration into existing ecosystems.
Interoperability at its Core
With 100% interoperability with Java, BoxLang seamlessly bridges the gap between traditional and modern development paradigms, unlocking new possibilities for innovation and collaboration.
Multi-Runtime
From the tiny 2m operating system binary to running on our pure Java web server, CommandBox, Jakarta EE, AWS Lambda, Microsoft Functions, Web Assembly, Android and more. BoxLang has been designed to enhance and adapt according to it's runnable runtime.
The Fusion of Modernity and Tradition
Experience the fusion of modern features inspired by CFML, Node, Ruby, Kotlin, Java, and Clojure, combined with the familiarity of Java bytecode compilation, making BoxLang a language of choice for forward-thinking developers.
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Astute Business Solutions | Oracle Cloud Partner |
Your goto partner for Oracle Cloud, PeopleSoft, E-Business Suite, and Ellucian Banner. We are a firm specialized in managed services and consulting.
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Read More - https://bit.ly/3VKly70
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Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
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In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
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Mutation Testing for Task-Oriented Chatbots
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
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Presemt architecture
- 1. Pattern REcognition-based Statistically Enhanced MT PRESEMT Architecture