Category: Technology

Hackathon Diaries #4 FaceFinder: Face Recognition Application

Hackathon Diaries #4 FaceFinder: Face Recognition Application

April 4, 2023

Hey there tech enthusiasts. Welcome to the fourth edition of Hackathon Diaries, where we present to you the latest and greatest innovations created by the brilliant minds at INT. Hackathon 2023. Hold on to your hats because this time we’re taking things up a notch with our cutting-edge solution, FaceFinder. It’s all about securing today for a safer tomorrow, and we’re thrilled to share all the exciting details with you. FaceFinder Picture this: You arrive at your workplace, but instead of fumbling around with keys or access cards, you just stand in front of the gate and let FaceFinder work its magic.  It is an application to open gates securely and automatically through facial recognition technology. It facilitates users to upload/register images of their faces, which can be used to recognise them. The stored image in the database will be used to verify any new entry request. It grants access to matching, otherwise,  the gate won’t open and physical intervention will be needed. The Techie  V Sweta Working Flowchart But let’s get into the nitty-gritty of how it all works. Our brilliant tech-savvy superstar has designed an innovative flowchart that seamlessly integrates various tools to make FaceFinder a robust and reliable solution.  Tech Stack We’re talking about:  ASP.NET Core at the backend Azure Cognitive Service Computer Vision and Face API for detecting and recognising people Azure Storage account to store all your pretty faces And of course, Entity Framework Core is there to make sure everything is stored in our trusty SQL server Now, let’s talk benefits Enhanced Security: Using facial recognition technology to open gates can enhance the security of the premises by ensuring access to only authorised individuals Convenience: With this application, users can open gates without having to manually unlock them Efficiency: Automatic gate opening saves time and effort for individuals who frequently access the premises Enhanced User Experience: The intuitive UI/UX of the application makes it hassle-free for users accessing the gateway Cost Savings: Reduces the need for security personnel, thereby cutting costs associated with staffing and training. It also eliminates the requirement for physical access controls such as keys or access cards, which can be expensive to produce and maintain. Potential Challenges Of The Prototype and The Future Opportunities But we’re not going to shy away from potential challenges. FaceFinder has a few limitations, like being unable to recognise identical twins, finding it difficult to identify individuals with facial injuries, and struggling to identify those wearing a cap or scarf.  Hey, we’re not giving up on these. We’re already working on ways to improve FaceFinder, such as implementing IoT devices, maintaining a block list to restrict specific individuals, initiating breaching alerts, enhancing scalability, reducing response time, and exploring more use cases. So, there you have it. FaceFinder is the future of secure and convenient gate access, and we’re excited to take this technology to new heights. Stay tuned for more exciting developments from Hackathon Diaries.

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Data analytics plays a crucial role in clinical trial design and analysis by providing valuable insights into the effectiveness of new treatments and therapies.

The role of data analytics in clinical trial design and analysis

March 31, 2023

What is the role of data analysis in clinical trials? Can there be better clinical trial data analysis using R and other technologies? Is there a case for using big data analysis in clinical trials? Experts would certainly say Yes to all these questions. Clinical trials themselves have gone through sweeping changes over the last decade, with several new developments in immunotherapy, stem cell research, genomics, and cancer therapy among numerous segments. At the same time, there has been a transformation in the implementation of clinical trials and the process of identifying and developing necessary drugs.  To cite a few examples of the growing need for clinical trial data analysis, researchers gain quicker insights through the evaluation of databases of real-world patient information and the generation of synthetic control arms, while identifying drug targets alongside. They can also evaluate drug performance post-regulatory approvals in this case. This has lowered the cost and time linked to trials while lowering the overall burden on patients and enabling faster go-to-market timelines for drugs too.  What is driving data analysis in clinical trials?  Clinical trial data analysis is being majorly driven by AI (artificial intelligence) along with ML (machine learning), enabling the capabilities of collection, analysis, and production of insights from massive amounts of real-time data at scale, which is way faster than manual methods. The analysis and processing of medical imaging data for clinical trials, along with tapping data from other sources is enabling innovation of the entire process while being suitable for supporting the discovery procedure in terms of quickening the trials, go-to-market approaches, and launches.  The data volumes have greatly increased over the last few years, with more wearable usage, genomic and genetic understanding of individuals, proteomic and metabolomic profiles, and detailed clinical histories of patients derived from electronic health records. Reports indicate 30% of the data volumes of the world are generated by the global healthcare industry. The CAGR (compound annual growth rate) for healthcare data will touch 36% by the year 2025 as well. The volume of patient data in clinical systems has already grown by a whopping 500% to 2020 from 2016.  Data analysis in clinical trials- What else should you note?  Here are a few factors that are worth noting:  Synthetic control arm development  The role of data analysis in clinical trials is even more evident when one considers the development of synthetic control arms. Clinical drug discovery and trials may be fast-tracked while enhancing success rates and designs of clinical trials. Synthetic control arms may help in overcoming challenges linked to patient stratification and also lower the time required for medical treatment development. It may also enable better recruitment of patients through resolving concerns about getting placebos and enabling better management of diverse and large-sized trials.  Synthetic control arms tap into both historical clinical trials and real-world data for modelling patient control groups and doing away with the requirement for the administration of placebo treatments for patients which may hinder their health. It may negatively impact patient outcomes and enrolment in trials. The approach may work better for rare ailments where populations of patients are tinier and the lifespan is also shorter owing to the disease’s virulent nature. Using such technologies for clinical trials and bringing them closer to end-patients may significantly lower the overall inconveniences of travelling to research spots/sites and also the issue related to consistent tests.  ML and AI for better discovery of drugs ML and AI may enable a quicker analysis of data sets gathered earlier and at a swifter rate for clinicians, ensuring higher reliability and efficiency in turn. The integration of synthetic control arms in mainstream research will offer new possibilities in terms of transforming the development of drugs.  With an increase in the count of data sources including health apps, personal wearables and other devices, electronic medical records, and other patient data, these may well become the safest and quickest mechanisms for tapping real-world data for better research into ailments with sizeable patient populations. Researchers may achieve greater patient populations which are homogenous and get vital insights alongside. Here are some other points worth noting:  The outcomes of clinical trials are major metrics with regard to performance, at least as far as companies and investors are concerned. They are also the beginning of collaborations between patients, groups, and the healthcare sector at large. Hence, there is a clearly defined need for big data analysis in clinical trials as evident through the above-mentioned aspects.  FAQs How can data analytics be used in clinical trial design and analysis? Data analytics can be readily used for clinical trial design and analysis, expanding patient selection criteria, swiftly sifting through various parameters and helping researchers better target matching patients who match the criteria for exclusion and inclusion. Data analysis methods also enable better conclusions from data while also improving clinical trial design due to better visibility of the possible/predicted risk-reward outcomes.  What are the benefits of using data analytics in clinical trial design and analysis? The advantages of using data analytics in clinical trial design and analysis include the integration of data across diverse sources, inclusive of third parties. Researchers get more flexibility in terms of research, finding it easier to analyze clinical information. Predictive analytics and other tools are enabling swifter disease detection and superior monitoring.  What are the challenges of using data analytics in clinical trial design and analysis? There are several challenges in using data analytics for the analysis and design of clinical trials. These include the unavailability of skilled and experienced resources to implement big data analytics technologies, data integration issues, the uncertainty of the management process, storage and quick retrieval aspects, confidentiality and privacy aspects and the absence of suitable data governance processes.  What are the best practices for implementing data analytics in clinical trial design and analysis? There are numerous best practices for the implementation of data analytics for the analysis and design of clinical trials. These include good clinical data management practices, clinical practices, data governance

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World Earth Day – Role of Digital Technologies in Correcting Environmental Impact

April 20, 2022

Environmental impact, natural calamities and global warming are the biggest moot points today among policymakers and corporates worldwide. While Nature’s Fury is not fully in our hands, technology can be a future safeguard in terms of better response systems, mitigation strategies and correcting environmental impact. With World Earth Day around the corner on 22nd April 2022, now is the time for countries and authorities to adopt comprehensive digital technologies for managing environmental impact, and conditions and contribute towards futuristic, sustainable and sound policymaking. Digital Technologies- How They Stack Up? Digital technologies may enable easier decision-making and response systems through their integration into environment-linked data. For instance, with New Delhi suffering from toxic air quality last winter, residents were able to track everything on the GEMS Air (Global Environment Monitoring System Air) site in real-time. GEMS Air is one of the numerous technologies deployed by the UNEP (United Nations Environment Programme) for tracking environmental conditions at local, global and national levels. In the near future, integrated digital data platforms will help countries understand, track, manage and mitigate environmental hazards including growing air pollution and harmful emissions. Multiple public and private sector players are already tapping into digital technologies and data for scaling up environmental action plans. At a time when the world is battling pollution, loss of biodiversity and climate change, digital technologies are enabling transformational measures for safeguarding nature, lowering pollution and boosting overall sustainability. GEMS Air for instance is the biggest air pollution network worldwide, encompassing almost 5,000 cities. More than 50 million people accessed it in 2020 as per reports. It is now playing a crucial role in alerting citizens about risks with real-time updates. How Other Digital Tools Are Contributing To Much-Needed Environmental Action? Big data and other technologies are helping generate timely and effective insights. For instance, farmers now have accurate data on weather and predictive modelling/forecasting applications. They can lower the usage of water, conserve natural resources and prepare for calamities. Applying digital technologies to environmental information is helping in better management and regulations. For instance, migrations of birds are hard to track and cover various regions. This is a major obstacle to conservation efforts in this space. Yet, forecasting models are now helping understand patterns and variances in migration. This knowledge is helping combat migration issues with better policies. Non-governmental change agents are also being mobilized through environmental insights and information, including corporates, communities and organisations. Some tools are already tapping data on emissions of methane already and offering analytics to companies for building future sustainability goals. Simultaneously, digital technologies are playing a role in enhancing overall accountability among all stakeholders, veering policy-making away from distractions towards hardcore and understandable analytics and environmental data. Minimizing environmental impact, identifying potential problems and finding solutions are processes made faster and easier through digital technologies. AI and big data analytics along with IoT, social platforms and mobile applications are contributing towards enhanced sustainability, lower resource usage and greater awareness. At a rudimentary level, these technologies are digitizing workplaces, production units and establishments, making them more environment-friendly and conserving more resources as a result. More corporates are depending on AI and IoT along with analytics for coming up with futuristic and more sustainable practices that lower carbon emissions and minimize wastage. Big data analytics is already at work in certifying products based on their environmental sustainability quotient. Blockchain may be used for greater sustainability in the future, scaling up lifecycles of products, maximizing usage of resources and lowering emissions, thereby greatly contributing to lowering environmental impact. These are only a few of the multifarious use cases of digital technologies and their role in mitigating environmental impact. One aspect is crystal clear- A fusion of environmental understanding, policies and sustainability with digitization is mandatory. It is digital transformation that will enable countries to move towards lower resource wastage, higher conservation and more sustainable ecosystems. On World Earth Day, it is time to embrace the power of technology and use it for environmental good.

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future-of-devsecai

Future of DevSecAI: Should You Discuss It With Your Software Development Partner

August 24, 2021

The concept of DevSecOps is on the rise lately and for all the good reasons! The framework has been a boon for software development partners around the world. With its increased productivity and rate of software deployments, the DevSecOps methodology is the turning point for the success of organizations, allowing them to become vested in code development during the initial stages of the production cycle. With AI/ML taking over the lead with greater adoption and security integrated operations, stats by the Analytical Research Cognizance highlight that the global DevSecOps market will highlight a growth rate of CAGR of 33.7% during 2017-2023. But the question is, what’s the future of Devsec AI? To know better, let’s first understand what Devsec is… Introduction to Devsec DevSecOps (a collective term used for development, security, and operations), is the integration of security that goes on through the multiple phases of the lifecycle of software development. Operations on DevSecOps begin from initial design through deployment, testing, integration, and software delivery. If we look at it, DevSecOps represents an essential evolution in the security approach for development organizations. We term ‘DevSecOps’ as an evolution because it revolutionizes the way operations have changed. Previously, ‘security’ was ‘tacked on’ to the final product, tested by separate quality assurance (QA) and security team at the end of the development cycle. Now that we know what DevSecOps is let’s look at the different pillars of the process! Pillars of DevSecOps People The people or resources of any given organization catalyze the growth of DevSecOps. People help in breaking the traditional barriers of operations. Initiating operations with small teams helps boost confidence that can be taken forward to other teams. Further, collaboration with a like-minded team allows you to share common goals provides accountability, transparency, and ownership. Process Along with quality and speed, consistency is one of the significant elements that organizations should include in the processes. Adopting different practices like implementing threat modelling storyboards, developing a design for customers, and different static code scanning that is packed to eliminate security rework and breaches. Technology Another major pillar of DevSecOps is technology. Cybersecurity software allows keeping pace with different pipeline tools such as testing-as-code, security-as-code, and infrastructure-as-code. This way, DevSecOps allows to boost security and eradicate manual security activities. Governance Organizations structure a designed and scalable framework (at macro and micro level), simplifying collaborations and development. On the micro-level, the governance of tools and processes allows the users to boost efficiency. On the contrary, the macro-level showcases hierarchical structures. How is DevSecOps Essential? When integrated with security, the DevOps approach saves security-related concerns, which may arrive later in the process. In essence, DevSecOps allows the security team to perform security testing and identify the different bugs, besides other vulnerabilities in the process. Cons of using DevSecOps Similar to all the other frameworks and methodologies, DevSecOps also has its limitations, especially when dealing with the whole team or individual members. Let’s check them out: Limited to closed communication    For DevSecOps to work properly, collaboration and communication are the keys to software development and security. The methodology will fail to work as intended. Should be Accepted by Everyone Not all employees are keen on accepting non-traditional working arrangements. Some live by the mantra, “If it ain’t broke, don’t fix it.” It can be difficult to ditch the old ways of doing things and choose new working methods. Employees with this mindset may be hard to convince about the importance of DevSecOps. Additionally, they need time and few success stories to accept the new workflow. May Not be The Management’s Main Priority Not all executives in a software development company consider security as their priority. The reason being that company executives may not consider accepting the changes proposed by a DevSecOps manager or consultant. The Bottomline: Will AI take over completely? If we look at it briefly, DevSecOps is a methodology that integrates security in the preliminary stages of software development, supported by different elements of AI and ML. However, when compared to the manual process of development, DevSecOps is still a distant dream. Lastly, considering that it cannot highlight the exact error in a source code, working with such a methodology can lead to crippling setbacks. Which, in contrast, is not a hurdle with the manual approach.

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React-vs-Angular

Reactjs Vs. Angular: Which Development Tool Should Your Software Development Partner Use?

August 10, 2021

Angular and React are easily the two widely used Javascripts for front-end developers. However, when it comes to customers finalizing one with the software development partner, that’s where the trouble begins! The fact that both of these frameworks are equally popular is what makes the task more challenging. With similar JavaScript architectures, finding the difference between React vs. Angular can be a confusing task. Therefore, to help you better understand the primary difference between the two tools, here’s a detailed breakdown. Angular: An Overview AngularJs is a comprehensive MVC (Model-View-Controller) framework, maintained and powered by Google. Compatible with some of the most commonly available code editors, AngularJS is a primary part of the MEAN stack. Centered around developing web applications and dynamic websites, the framework comprises of: Angular or AngularJS (a front-end framework), js (a web application framework) MongoDB (a NoSQL database) Node.js (a server platform) Overview of the framework: Github Stars: 66,000+ Latest update: Angular 10 (August 2020) Official Website. – https://angularjs.org/ ReactJS: An Overview ReactJS is another open-source Javascript library primarily used for developing dynamic UI. Developed by Facebook in 2011, ReactJs is the go-to option for creating reusable HTML elements for front-end development. ReactJs comprises of: JavaScript JSX Redux Components Overview of the open-source library: Github Stars: 156,000+ Latest update: 16.13.1 (March 2020) Official Website – https://reactjs.org/ Now that we have a common idea of the primary differences between the two frameworks, let’s look at the different elements that set them apart. Angular vs. ReactJS: What sets them apart? Framework vs. library The primary difference separating React from Angular is that it’s an open-source library and not a framework. React comprises of ‘View layer’ of a suggested MVC architecture, without any external packages (routing, for example). Thanks to the massive React community, the developer’s community becomes a handy source for exploring various updated and ready-to-use components to streamline the development process. Angular, on the other hand, is a complete framework. It comes with several built-in modules like Angular forms, HTTP module, and router. It provides a complete package to develop any functional app. This functionality of the framework also makes it an excellent option for developing small-scale projects. Component Architecture Component Architecture is the approach of developing an architecture that is based on replaceable components. It simplifies complex build operations and encourages code re-use based on substitutable, independent, and modular components. React Approach to Component Architecture – React’s UI approach is simple; it tends to break down the architecture into components. These components then further come together to create more complex UI solutions. However, the library is heavily reliant on different supporting tools and integrations to get the job done. Given its nature as a full-stack framework, Angular works as a comprehensive solution and provides the developers with several possibilities. Testing the Scalability Before you decide on the specific tool to be used by your software development partner, you must consider the future scalability and success of the application. In our comparison of Angular vs. React, the latter makes the job easier with its core features and extensive modules that help scale any existing application. React, in comparison, is still dominated by different third-party tools. Therefore, `if you had to add new functionalities to your app using the open-source library, things could become challenging. However, thanks to its clean architecture with server-side rendering, it can prove to be a decent tool for development. Features that make Angular different RxJS: RxJS is an asynchronous programming library that uses multiple data exchange channels to decrease resource consumption. Angular CLI: The Angular CLI feature is a potential command-line interface, assisting in creating applications, debugging, testing, and deployment. Dependency injection: The Dependency Injection framework allows developers to decouple components from dependencies and reconfigure components by running them in parallel and alter dependencies. Features that make React different Redux: Redux is a state container that streamlines React’s functions in large applications. The state container also helps in managing and accelerating components in applications with many dynamic elements. Babel: Babel is a transcompiler, allowing developers to convert JSX into JavaScript. React Router: The React Router is a standard URL routing library commonly used with React. The Final Takeaway! Both React and Angular are two different platforms. The base idea behind using Angular is to ensure powerful support and a reliable toolset for a seamless development experience. React, on the contrary, provides developers with a more lightweight and ready-to-work approach to development. Both the solutions were engineered to solve a basic problem in very different ways. Therefore, it’s hard to say that either of them is the best. The final solution is to try both of them and see what suits you best!

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