Java vs JavaScript | Edureka

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The document compares Java and JavaScript, highlighting that Java, developed by James Gosling in 1995, is an object-oriented programming language requiring a Java Virtual Machine, while JavaScript, created by Brendan Eich in 1990 as a scripting language, runs on web browsers without the need for setup. Both languages use similar syntax to C/C++ and have extensive support and documentation, but differ in scoping methods and compilation processes. Additionally, Java is compiled and interpreted, while JavaScript is solely interpreted.

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INTRODUCTION TO JAVA
INTRODUCTION TO JAVASCRIPT
PARAMETERS OF COMPARISON
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Java is a programming language invented by James
Gosling and developed by Sun Microsystems. It was
first released in 1995, and several new versions have
been launched since then.

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Brendan Eich at Netscape, Inc. created this
programming language in 1990 and named it
“Livescript” initially. Later on, it was renamed
to JavaScript.

Parameters of
Comparison
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OOPS
Platform
Syntax
Compilation
Learning Curve
Scope
Support

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Java is an object-oriented programming
language. It uses objects to perform
actions based on relations between
objects.
JavaScript is an object-oriented scripting
language. It uses the objects to perform actions
similar in Java.

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Java applications and programs run
in Java Virtual Machine (JVM). Also, you
need to install JDK and JRE.
JavaScript applications run on a web browser.
there is no need for any initial setup.

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The syntax of Java is similar to C/C++
programming language. It uses
classes and objects.
The syntax of JavaScript is similar to C
language but it uses the naming conventions
similar to Java.

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Java programs are compiled and
interpreted as it is a programming
language.
JavaScript is only interpreted as it is a scripting
language or a plain text code.

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Java has various online forums,
documentation and community support. You
can learn this language to build various
applications.
JavaScript also has extensive documentation
and online resources. You can learn
JavaScript to build web applications and
websites.

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Java uses block-based scoping. In
this, the variable goes out of scope
once the control comes out of a block
JavaScript uses function-based scoping as
the variable can be accessed in the function.

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Java is supported by almost all the
operating systems.
JavaScript supported by almost all the web
browsers that come with different operating
systems.

Copyright © 2017, edureka and/or its affiliates. All rights reserved.
www.edureka.co

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Floods in Valencia: Two FME-Powered Stories of Data ResilienceSafe Software

In October 2024, the Spanish region of Valencia faced severe flooding that underscored the critical need for accessible and actionable data. This presentation will explore two innovative use cases where FME facilitated data integration and availability during the crisis. The first case demonstrates how FME was used to process and convert satellite imagery and other geospatial data into formats tailored for rapid analysis by emergency teams. The second case delves into making human mobility data—collected from mobile phone signals—accessible as source-destination matrices, offering key insights into population movements during and after the flooding. These stories highlight how FME's powerful capabilities can bridge the gap between raw data and decision-making, fostering resilience and preparedness in the face of natural disasters. Attendees will gain practical insights into how FME can support crisis management and urban planning in a changing climate.

Can We Use Rust to Develop Extensions for PostgreSQL? (POSETTE: An Event for ...NTT DATA Technology & Innovation

Reducing Conflicts and Increasing Safety Along the Cycling Networks of East-F...Safe Software

In partnership with the Belgian Province of East-Flanders this project aimed to reduce conflicts and increase safety along a cycling route between the cities of Oudenaarde and Ghent. To achieve this goal, the current cycling network data needed some extra key information, including: Speed limits for segments, Access restrictions for different users (pedestrians, cyclists, motor vehicles, etc.), Priority rules at intersections. Using a 360° camera and GPS mounted on a measuring bicycle, we collected images of traffic signs and ground markings along the cycling lanes building up mobile mapping data. Image recognition technologies identified the road signs, creating a dataset with their locations and codes. The data processing entailed three FME workspaces. These included identifying valid intersections with other networks (e.g., roads, railways), creating a topological network between segments and intersections and linking road signs to segments and intersections based on proximity and orientation. Additional features, such as speed zones, inheritance of speed and access to neighbouring segments were also implemented to further enhance the data. The final results were visualized in ArcGIS, enabling analysis for the end users. The project provided them with key insights, including statistics on accessible road segments, speed limits, and intersection priorities. These will make the cycling paths more safe and uniform, by reducing conflicts between users.

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High Availability On-Premises FME Flow.pdfSafe Software

FME Flow is a highly robust tool for transforming data both automatically and by user-initiated workflows. At the Finnish telecommunications company Elisa, FME Flow serves processes and internal stakeholders that require 24/7 availability from underlying systems, while imposing limitations on the use of cloud based systems. In response to these business requirements, Elisa has implemented a high-availability on-premises setup of FME Flow, where all components of the system have been duplicated or clustered. The goal of the presentation is to provide insights into the architecture behind the high-availability functionality. The presentation will show in basic technical terms how the different parts of the system work together. Basic level understanding of IT technologies is required to understand the technical portion of the presentation, namely understanding the purpose of the following components: load balancer, FME Flow host nodes, FME Flow worker nodes, network file storage drives, databases, and external authentication services. The presentation will also outline our lessons learned from the high-availability project, both benefits and challenges to consider.

No-Code Workflows for CAD & 3D Data: Scaling AI-Driven InfrastructureSafe Software

When projects depend on fast, reliable spatial data, every minute counts. AI Clearing needed a faster way to handle complex spatial data from drone surveys, CAD designs and 3D project models across construction sites. With FME Form, they built no-code workflows to clean, convert, integrate, and validate dozens of data formats – cutting analysis time from 5 hours to just 30 minutes. Join us, our partner Globema, and customer AI Clearing to see how they: -Automate processing of 2D, 3D, drone, spatial, and non-spatial data -Analyze construction progress 10x faster and with fewer errors -Handle diverse formats like DWG, KML, SHP, and PDF with ease -Scale their workflows for international projects in solar, roads, and pipelines If you work with complex data, join us to learn how to optimize your own processes and transform your results with FME.

Mastering AI Workflows with FME - Peak of Data & AI 2025Safe Software

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National Fuels Treatments Initiative: Building a Seamless Map of Hazardous Fu...Safe Software

The National Fuels Treatments Initiative (NFT) is transforming wildfire mitigation by creating a standardized map of nationwide fuels treatment locations across all land ownerships in the United States. While existing state and federal systems capture this data in diverse formats, NFT bridges these gaps, delivering the first truly integrated national view. This dataset will be used to measure the implementation of the National Cohesive Wildland Strategy and demonstrate the positive impact of collective investments in hazardous fuels reduction nationwide. In Phase 1, we developed an ETL pipeline template in FME Form, leveraging a schema-agnostic workflow with dynamic feature handling intended for fast roll-out and light maintenance. This was key as the initiative scaled from a few to over fifty contributors nationwide. By directly pulling from agency data stores, oftentimes ArcGIS Feature Services, NFT preserves existing structures, minimizing preparation needs. External mapping tables ensure consistent attribute and domain alignment, while robust change detection processes keep data current and actionable. Now in Phase 2, we’re migrating pipelines to FME Flow to take advantage of advanced scheduling, monitoring dashboards, and automated notifications to streamline operations. Join us to explore how this initiative exemplifies the power of technology, blending FME, ArcGIS Online, and AWS to solve a national business problem with a scalable, automated solution.

The State of Web3 Industry- Industry ReportLiveplex

Web3 is poised for mainstream integration by 2030, with decentralized applications potentially reaching billions of users through improved scalability, user-friendly wallets, and regulatory clarity. Many forecasts project trillions of dollars in tokenized assets by 2030 , integration of AI, IoT, and Web3 (e.g. autonomous agents and decentralized physical infrastructure), and the possible emergence of global interoperability standards. Key challenges going forward include ensuring security at scale, preserving decentralization principles under regulatory oversight, and demonstrating tangible consumer value to sustain adoption beyond speculative cycles.

“Addressing Evolving AI Model Challenges Through Memory and Storage,” a Prese...Edge AI and Vision Alliance

For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2025/06/addressing-evolving-ai-model-challenges-through-memory-and-storage-a-presentation-from-micron/ Wil Florentino, Senior Segment Marketing Manager at Micron, presents the “Addressing Evolving AI Model Challenges Through Memory and Storage” tutorial at the May 2025 Embedded Vision Summit. In the fast-changing world of artificial intelligence, the industry is deploying more AI compute at the edge. But the growing diversity and data footprint of transformers and models such as large language models and large multimodal models puts a spotlight on memory performance and data storage capacity as key bottlenecks. Enabling the full potential of AI in industries such as manufacturing, automotive, robotics and transportation will require us to find efficient ways to deploy this new generation of complex models. In this presentation, Florentino explores how memory and storage are responding to this need and solving complex issues in the AI market. He examines the storage capacity and memory bandwidth requirements of edge AI use cases ranging from tiny devices with severe cost and power constraints to edge servers, and he explains how new memory technologies such as LPDDR5, LPCAMM2 and multi-port SSDs are helping system developers to meet these challenges.

OpenACC and Open Hackathons Monthly Highlights June 2025OpenACC

The OpenACC organization focuses on enhancing parallel computing skills and advancing interoperability in scientific applications through hackathons and training. The upcoming 2025 Open Accelerated Computing Summit (OACS) aims to explore the convergence of AI and HPC in scientific computing and foster knowledge sharing. This year's OACS welcomes talk submissions from a variety of topics, from Using Standard Language Parallelism to Computer Vision Applications. The document also highlights several open hackathons, a call to apply for NVIDIA Academic Grant Program and resources for optimizing scientific applications using OpenACC directives.

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“From Enterprise to Makers: Driving Vision AI Innovation at the Extreme Edge,...Edge AI and Vision Alliance

For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2025/06/from-enterprise-to-makers-driving-vision-ai-innovation-at-the-extreme-edge-a-presentation-from-sony-semiconductor-solutions/ Amir Servi, Edge Deep Learning Product Manager at Sony Semiconductor Solutions, presents the “From Enterprise to Makers: Driving Vision AI Innovation at the Extreme Edge” tutorial at the May 2025 Embedded Vision Summit. Sony’s unique integrated sensor-processor technology is enabling ultra-efficient intelligence directly at the image source, transforming vision AI for enterprises and developers alike. In this presentation, Servi showcases how the AITRIOS platform simplifies vision AI for enterprises with tools for large-scale deployments and model management. Servi also highlights his company’s collaboration with Ultralytics and Raspberry Pi, which brings YOLO models to the developer community, empowering grassroots innovation. Whether you’re scaling vision AI for industry or experimenting with cutting-edge tools, this presentation will demonstrate how Sony is accelerating high-performance, energy-efficient vision AI for all.

Integration of Utility Data into 3D BIM Models Using a 3D Solids Modeling Wor...Safe Software

Jacobs has developed a 3D utility solids modelling workflow to improve the integration of utility data into 3D Building Information Modeling (BIM) environments. This workflow, a collaborative effort between the New Zealand Geospatial Team and the Australian Data Capture Team, employs FME to convert 2D utility data into detailed 3D representations, supporting enhanced spatial analysis and clash detection. To enable the automation of this process, Jacobs has also developed a survey data standard that standardizes the capture of existing utilities. This standard ensures consistency in data collection, forming the foundation for the subsequent automated validation and modelling steps. The workflow begins with the acquisition of utility survey data, including attributes such as location, depth, diameter, and material of utility assets like pipes and manholes. This data is validated through a custom-built tool that ensures completeness and logical consistency, including checks for proper connectivity between network components. Following validation, the data is processed using an automated modelling tool to generate 3D solids from 2D geometric representations. These solids are then integrated into BIM models to facilitate compatibility with 3D workflows and enable detailed spatial analyses. The workflow contributes to improved spatial understanding by visualizing the relationships between utilities and other infrastructure elements. The automation of validation and modeling processes ensures consistent and accurate outputs, minimizing errors and increasing workflow efficiency. This methodology highlights the application of FME in addressing challenges associated with geospatial data transformation and demonstrates its utility in enhancing data integration within BIM frameworks. By enabling accurate 3D representation of utility networks, the workflow supports improved design collaboration and decision-making in complex infrastructure projects

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Enabling BIM / GIS integrations with Other Systems with FMESafe Software

Jacobs has successfully utilized FME to tackle the complexities of integrating diverse data sources in a confidential $1 billion campus improvement project. The project aimed to create a comprehensive digital twin by merging Building Information Modeling (BIM) data, Construction Operations Building Information Exchange (COBie) data, and various other data sources into a unified Geographic Information System (GIS) platform. The challenge lay in the disparate nature of these data sources, which were siloed and incompatible with each other, hindering efficient data management and decision-making processes. To address this, Jacobs leveraged FME to automate the extraction, transformation, and loading (ETL) of data between ArcGIS Indoors and IBM Maximo. This process ensured accurate transfer of maintainable asset and work order data, creating a comprehensive 2D and 3D representation of the campus for Facility Management. FME's server capabilities enabled real-time updates and synchronization between ArcGIS Indoors and Maximo, facilitating automatic updates of asset information and work orders. Additionally, Survey123 forms allowed field personnel to capture and submit data directly from their mobile devices, triggering FME workflows via webhooks for real-time data updates. This seamless integration has significantly enhanced data management, improved decision-making processes, and ensured data consistency across the project lifecycle.

Creating Inclusive Digital Learning with AI: A Smarter, Fairer FutureImpelsys Inc.

Have you ever struggled to read a tiny label on a medicine box or tried to navigate a confusing website? Now imagine if every learning experience felt that way—every single day. For millions of people living with disabilities, poorly designed content isn’t just frustrating. It’s a barrier to growth. Inclusive learning is about fixing that. And today, AI is helping us build digital learning that’s smarter, kinder, and accessible to everyone. Accessible learning increases engagement, retention, performance, and inclusivity for everyone. Inclusive design is simply better design.

Supporting the NextGen 911 Digital Transformation with FMESafe Software

Next Generation 911 involves the transformation of our 911 system from an old analog one to the new digital internet based architecture. The evolution of NG911 opens up a host of new opportunities to improve the system. This includes everything from device based location, to real time text. This can improve location accuracy dramatically as well as provide live updates from the citizen in need along with real time sensor updates. There is also the opportunity to provide multi-media attachments and medical records if the end user approves. This digital transformation and enhancements all require the support of new NENA and CRTC standards, along with integration across a variety of data streams. This presentation will focus on how FME has supported NG911 transformations to date, and how we are positioning FME to support the enhanced capabilities to come. This session will be of interest to emergency services, municipalities and anyone who may be interested to know more about how emergency services are being improved to provide more accurate, localized information in order to improve the speed and relevance of emergency response and ultimately save more lives and provide better outcomes for those in need.

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FME for Distribution & Transmission Integrity Management Program (DIMP & TIMP)Safe Software

Peoples Gas in Chicago, IL has changed to a new Distribution & Transmission Integrity Management Program (DIMP & TIMP) software provider in recent years. In order to successfully deploy the new software we have created a series of ETL processes using FME Form to transform our gas facility data to meet the required DIMP & TIMP data specifications. This presentation will provide an overview of how we used FME to transform data from ESRI’s Utility Network and several other internal and external sources to meet the strict data specifications for the DIMP and TIMP software solutions.