Unified Interface Research Articles

A Conceptual Consent Request Framework for Mobile Devices

The General Data Protection Regulation (GDPR) identifies consent as one of the legal bases for personal data processing and requires that it should be freely given, specific, informed, unambiguous, understandable, and easily revocable. Unfortunately, current technical mechanisms for obtaining consent often do not comply with these requirements. The conceptual consent request framework for mobile devices that is presented in this paper, addresses this issue by following the GDPR requirements on consent and offering a unified user interface for mobile apps. The proposed conceptual framework is evaluated via the development of a City Explorer app with four consent request approaches (custom, functionality-based, app-based, and usage-based) integrated into it. The evaluation shows that the functionality-based consent, which was integrated into the City Explorer app, achieved the best evaluation results and the highest average system usability scale (SUS) score. The functionality-based consent also scored the highest number of SUS points among the four consent templates when evaluated separately from the app. Additionally, we discuss the framework’s reusability and its integration into other mobile apps of different contexts.

The HMC Information Portal for Enhanced Metadata Collaboration in the Helmholtz FAIR Data Space

The Helmholtz Metadata Collaboration (HMC) platform was launched in late 2019 to turn FAIR (Findable, Accessible, Interoperable, Reusable) research data into reality within the Helmholtz Association and beyond. The Information Portal was initiated to enable the structured cartography of metadata and FAIR landscape of Helmholtz, providing information for multi-level decision-making and creating a curated knowledge base for research data managers, scientists and other stakeholders.
 Developed through a top-down approach, 18 categories, and associated metadata schemas were defined and aligned by an HMC taskforce. Data curation followed, with resources collected from different domains based on the aligned metadata schema. The Information Portal is a web application for capturing FAIR data practices across all Helmholtz domains, offering a unified user interface for collecting and exploring results.
 Built using state-of-the-art technologies, including Python and Docker, the Information Portal leverages GitLab as a database. It offers a public / central read-only version for stakeholders and a personal instance for curation - synchronized to a GitLab repository. Git-based systems offer advantages, such as raw data accessibility, flexible data curation, easy synchronization, and customizable repositories.
 The single-page web application is user-friendly and developed in multiple iterations for an intuitive and flexible interface. The Information Portal is crucial for creating a sustainable, distributed, semantically enriched Helmholtz data space, promoting seamless data sharing and reuse.

A Unified Multimodal Interface for the RELAX High-Payload Collaborative Robot.

This manuscript introduces a mobile cobot equipped with a custom-designed high payload arm called RELAX combined with a novel unified multimodal interface that facilitates Human-Robot Collaboration (HRC) tasks requiring high-level interaction forces on a real-world scale. The proposed multimodal framework is capable of combining physical interaction, Ultra Wide-Band (UWB) radio sensing, a Graphical User Interface (GUI), verbal control, and gesture interfaces, combining the benefits of all these different modalities and allowing humans to accurately and efficiently command the RELAX mobile cobot and collaborate with it. The effectiveness of the multimodal interface is evaluated in scenarios where the operator guides RELAX to reach designated locations in the environment while avoiding obstacles and performing high-payload transportation tasks, again in a collaborative fashion. The results demonstrate that a human co-worker can productively complete complex missions and command the RELAX mobile cobot using the proposed multimodal interaction framework.

The Unified Payment Interface and the growth of digital payments in India: An analysis

This paper analyses the massive growth in digital payments in India since 2010. In addition to discussing the various factors that have contributed to this, most notably the introduction of the Unified Payment Interface (UPI), the paper also highlights some of the challenges facing the UPI, and how these might be addressed. By way of comparison, the paper also analyses a similarly successful system, namely Brazil’s PIX. As many developing nations are now investigating UPI-like solutions and hoping for similar results, this paper sets out to improve understanding about digital payment infrastructure and the factors that have driven the successful growth of digital payments and the UPI in India in order to support such nations to determine the appropriate strategy going forward.

IDECAMB: an implementation of interacting dark energy cosmology in CAMB

Interacting dark energy (IDE) scenario is a natural and important extension to the standard ΛCDM cosmology. We develop a full numerical routine, called IDECAMB, as a patch to the public Einstein-Boltzmann solver CAMB, to solve the background and perturbation equations of the IDE models. The IDECAMB solver provides a unified interface for the widely studied IDE models by employing a parametrization model with five free functions. By configuring these five functions, one can easily map the coupled quintessence (CQ) and coupled fluid (CF) models into the parametrization. We handle the perturbation evolutions of the CF models with the parametrized post-Friedmann (PPF) approach to avoid the possible large-scale instability. Compared with the previous established PPF approach whose form depends on a specific IDE model, the PPF approach in this work are model-independent, making it easy to use. We constrain a specific CQ model with the IDECAMB package. The fitting results are consistent with those obtained by Planck Collaboration, which confirms the validity of the package.

Role of Fintech in Financial Inclusion in India

Financial Technologies (Fintech) have been playing a crucial role in banking the unbanked population thereby accelerating financial inclusion in India. Aftermath of the 2008 financial crisis, the advent of fintech companies began which has been tremendously impacting on every segment of the Indian economy in general and banking in particular. As such, fintech has emerged as one of the hotspots introducing a variety of technologies to the traditional banking to suit different needs of the masses with a view to reaching out every nook and corner of the country. Meanwhile, a number of initiatives implemented by the government has propelled the process of financial inclusion such as Pradhan Mantri Jan dhan Yojana (PMJDY), Pradhan Mantri Vaya Vandana Yojana (PMVVY), Pradhan Mantri Mudra Yojana (PMMY), etc., which are all being advanced by fintech companies at large. In this way, the present paper sheds a light on the role of fintech in financial and outcomes of the study reveal that fintech has a significant role in spurring financial inclusion through a diverse use of technology such as Unified Payment Interface (UPI).

A Data integration tool for the integrated modeling and analysis for EAST

A large amount of heterogeneous data is generated during the experiments, operations, and simulations of the Experimental Advanced Superconducting Tokamak (EAST). The semantic and formatting inconsistencies of these heterogeneous data barrier the automation of data processes in integrated modeling and analysis. Data integration approaches based on a unified data model are an effective way to address this problem. A data integration tool, SpDB, was developed to unify data access for EAST’s integrated modeling process. SpDB unifies access to heterogeneous data sources under a single entry point in a namespace compatible with Integrated Modeling and Analysis Suite (IMAS). Users can access abstract tree data structures through a unified path without worrying about the format of specific data sources. SpDB enables automating integrated modeling workflows by combining multiple data sources into a single data structure that acts as a unified IO interface to the module.

Unified Payment Interface: A Unique Payment Interface in the Universe- Secondary Data Analysis

The country's payment system has undergone numerous significant changes, thanks to the Unified Payment Interface (UPI), which has eventually spurred economic growth. Life has become easier with UPI's existence. It significantly accelerates India's transition to a cashless economy as it helps to protect the environment by going greener, to improve the quality of life by embracing technology, and to create more jobs that initiate open many FinTech and Startups that lead to economic sustainability. India serves as the poster child for instant payments and an epitome of how a concerted, widespread, national endeavour may unleash enormous economic and social potential. It is an innovative online financial product in India that has reached heights of popularity within a short span (Deshpande, 2021). Our honourable Prime Minister Mr. Narendra Modi shared our country’s experience with UPI at the G20 summit by describing it as a “path-breaking digital payment platform”, which could become a template for digital payments to other nations. In this background, this study attempts to perceive the progress of this platform which enlightens us about its significance and to know about its present status. The study has employed the descriptive method by using secondary data from various scientific articles, relevant reports, records, books, published data, and journals to analyze the pathway of UPI’s progress by glorifying its uniqueness, the rationale of its evolution, and the challenges confronted to positively disrupt the sustainability of this product.

Signed distance field enhanced fully resolved CFD-DEM for simulation of granular flows involving multiphase fluids and irregularly shaped particles

It is challenging to model granular particles with arbitrary shapes and related complications to fluid–particle interactions for granular flows which are widely encountered in nature and engineering. This paper presents an improved framework of the immersed boundary method (IBM)-based fully resolved computational fluid dynamics (CFD) and discrete element method (DEM), with an emphasis on irregular-shaped particles and the implications to particle–fluid interactions. The improved CFD-DEM framework is featured by two novel enhancements with signed distance field (SDF). First, an SDF-based formulation is employed to enable handling of granular particles with arbitrary shapes in DEM robustly and efficiently. Second, the IBM is modified to be consistent with SDF to fully resolve fluid–particle interactions in the presence of non-spherical particles. Such treatments leverage SDF as a generic interface to furnish a new SDF-CFD-DEM framework for universal modeling of arbitrarily shaped particles interacting with multiphase fluids with desired resolutions. Exemplified particle shape models include super-quadrics, spherical harmonics, polyhedron and level set, and new shape models can be flexibly developed by implementing the unified SDF-based shape interface. The proposed SDF-CFD-DEM is validated and showcased with examples including particle settling, drafting–kissing–tumbling, immersed granular collapse, and mudflow. The results demonstrate the good accuracy and robustness of the SDF-CFD-DEM and its potential for efficient computational modeling of multiphase granular flows involving granular particles with arbitrary shapes.

Papri Chakraborty.

"Science is fun because every day obvious things become more interesting when you get to know the secrets behind them … The greatest scientific advance of the next decade will be the invention of a unified artificial intelligence interface to unravel complex reaction mechanisms." Find out more about Papri Chakraborty in her Introducing … Profile.

MIA is an open-source standalone deep learning application for microscopic image analysis

In recent years, the amount of data generated by imaging techniques has grown rapidly, along with increasing computational power and the development of deep learning algorithms. To address the need for powerful automated image analysis tools for a broad range of applications in the biomedical sciences, the Microscopic Image Analyzer (MIA) was developed. MIA combines a graphical user interface that obviates the need for programming skills with state-of-the-art deep-learning algorithms for segmentation, object detection, and classification. It runs as a standalone, platform-independent application and uses open data formats, which are compatible with commonly used open-source software packages. The software provides a unified interface for easy image labeling, model training, and inference. Furthermore, the software was evaluated in a public competition and performed among the top three for all tested datasets.

Unified Payment Interface—Taking India to the next generation in payments

Unified Payments Interface (UPI) is India’s fastest-growing payment system which makes users mobile as a single platform to send and receive money anytime and anywhere. It is built on top of IMPS, an existing mode used for instant money transfers. UPI is governed by the National Payment Corporation of India (NPCI), which monitors and promotes the UPI payment system. This case study on the payment platform will give detailed information about UPI, its initiatives like UPI123 and “UPI Chalega” and its progress. The case study also expounds on the growth of UPI, the challenges that are prevalent in UPI payments, and the analysis of data published by NPCI on UPI payments.

Harmonic Method for Simulating Unsteady Multispool Interactions

Abstract Modern civil jet engines arrange components on spools with different rotational speeds in order to improve compressor stall margin, overall engine performance, etc. The unsteady interactions among these components can be significant and should be considered at an early design stage if possible. Unsteady Reynolds-averaged Navier–Stokes (URANS) is a common approach to simulate these unsteady effects, but the disparity in time scales in a multispool simulation can lead to expensive URANS simulations. Harmonic methods are effective and efficient approaches to simulate unsteady interactions among turbomachinery components, but their applications to multispool simulations remain a challenge. The objective of this paper is to address this challenge. This paper extends the Favre-averaged non-linear harmonic method to simulate multispool turbomachinery components using a unified bladerow interface which transfers disturbances through bladerows with arbitrary blade counts at any rotational speed. The regularization of non-reflective boundary condition is described for certain circumferential wave number of the zero-frequency mode. The capability of the proposed approach is demonstrated by simulating the transfer of hot streaks through full 3D high- and intermediate-pressure turbines in a three-shaft engine. The temperature distributions from the harmonic method show good agreement with direct unsteady simulation in terms of the mean flow and the instantaneous flow. The radial migration of the hot streaks towards the hub are captured very well by the proposed harmonic method. The required wall-clock time of the harmonic method is roughly 240 times smaller than the whole annulus URANS simulation. This demonstrates that the proposed method can be an efficient design tool to trace hot streaks in multispool turbines at the early design stage.

Does Previous Experience with the Unified Payments Interface (UPI) Affect the Usage of Central Bank Digital Currency (CBDC)?

In this study, we examined the influence of users’ experiences with the unified payments interface (UPI) system on the usage behavior of central bank digital currency (CBDC) in India. Our research developed a novel conceptual framework that investigated the relationships between technology, cognitive factors, and behavioral intentions towards CBDC use. The framework integrated UPI usage experience as a moderator within existing models of behavioral intentions and use behaviors. We collected data through a survey conducted in major Indian cities during the pilot launch of CBDC. By utilizing a partial least squares structural equation model (PLS-SEM), we analyzed the proposed model and the relationships between the constructs. Our findings revealed the significant impact of hedonic motivation and performance expectancy on users’ behavioral intentions towards CBDC. Social influence also played a significant role in CBDC usage. Furthermore, we identified that prior UPI usage negatively moderated the relationship between performance expectancy and behavioral intention, as well as the relationship between social influence and use behavior. However, prior UPI usage did not significantly moderate the relationships between perceived risk, hedonic motivation, behavioral intention, and use behavior. These findings contribute to our understanding of the factors influencing CBDC adoption and usage behavior in India.

Development of Active Noise Control System Optimized for Road Noise Reduction

In this paper, a newly developed Active Noise Control (ANC) system is introduced, that effectively reduces road noise, which becomes a major issue with electrified vehicles, and that enhances vehicle interior sound levels matching seamless acceleration by electric drive. Conventionally, reducing road noise using ANC requires numerous sensors and speakers, as well as a processor with high computing power. Therefore, the increase in system cost and the complexity of the system are obstacles to its spread. To overcome these issues, this system is developed based on four concepts. The first is a modular system configuration with unified interface to apply to various vehicle types and grades. The second is the integration and optimal placement of noise source reference sensors to achieve both reduction in number of parts and noise reduction performance. The third is the application of digital communications that combine power superposition, low latency, and high throughput to reduce wiring. The fourth is the development of control technologies that specialize in in-vehicle acoustic characteristics to achieve both computational efficiency and noise reduction performance. The one is a technology to integrate control paths based on the sound field mode characteristics in the vehicle cabin, and another one is the frequency band restrain control technology that matches speaker output characteristics. It is confirmed that this proposed system achieves quietness improvement equivalent to the difference of vehicle segmentation with a minimum system configuration, and that this system has a high superiority in weight efficiency compared to conventional vehicle body measures.

Scalable modular synthetic data generation for advancing aerial autonomy

One major barrier to advancing aerial autonomy has been collecting large-scale aerial datasets for training machine learning models. Due to costly and time-consuming real-world data collection through deploying drones, there has been an increasing shift towards using synthetic data for training models in drone applications. However, to increase widespread generalization and transferring models to real-world, increasing the diversity of simulation environments to train a model over all the varieties and augmenting the training data, has been proved to be essential. Current synthetic aerial data generation tools either lack data augmentation or rely heavily on manual workload or real samples for configuring and generating diverse realistic simulation scenes for data collection. These dependencies limit scalability of the data generation workflow. Accordingly, there is a major challenge in balancing generalizability and scalability in synthetic data generation. To address these gaps, we introduce a scalable Aerial Synthetic Data Augmentation (ASDA) framework tailored to aerial autonomy applications. ASDA extends a central data collection engine with two scriptable pipelines that automatically perform scene and data augmentations to generate diverse aerial datasets for different training tasks. ASDA improves data generation workflow efficiency by providing a unified prompt-based interface over integrated pipelines for flexible control. The procedural generative approach of our data augmentation is performant and adaptable to different simulation environments, training tasks and data collection needs. We demonstrate the effectiveness of our method in automatically generating diverse datasets and show its potential for downstream performance optimization. Our work contributes to generating enhanced benchmark datasets for training models that can generalize better to real-world situations.Video:youtube.com/watch?v=eKpOh-K-NfQ

CCNN: An Artificial Intelligent based Classifier to Credit Card Fraud Detection System with Optimized Cognitive Learning Model

Nowadays digital transactions play a vital role in money transaction processes. Last 5 years statistical report portrays the growth of internet money transaction especially credit card and unified payments interface. Mean time increasing numerous banking threats and digital transaction fraud rates also growing significantly. Data engineering techniques provide ultra supports to detect credit card forgery problems in online and offline mode transactions. This credit card fraud detection (CCFD) and prevention-based data processing issues raising because of two major reasons first, classification rate of legitimate and forgery uses is frequently changing, and next one is fraud detection dataset values are vastly asymmetric. Through this research work investigating performance of various existing classifier with our proposed cognitive convolutional neural network (CCNN) classifier. Existing classifiers like Logistic Regression (LR), K-nearest neighbor (KNN), Decision Tree (DT) and Support Vector Machine (SVM). These models are facing various challenges of low performance rate and high complexity because of low hit rate and accuracy. Through this research work we introduce cognitive learning-based CCNN classifier methodology with artificial intelligence for achieve maximum accuracy rate and minimal complexity issues. For experimental data analysis uses dataset of credit card transactions attained from specific region cardholders containing 284500 transactions and its various features. Also, this dataset contains unstructured and non-dimensional data are converted into structured data with the help of over sample and under sample method. Performance analysis shows proposed CCNN classifier model provide significant improvement on accuracy, specificity, sensitivity and hit rate. The results are shown in comparison. After cross-validation, the accuracy of the CCNN classification algorithm model for transaction fraudulent detection archived 99% which using the over-sampling model.

A BIM-based framework for automatic numerical modelling and geotechnical analysis of a large-scale deep excavation for transportation infrastructures

Abstract Employing emerging information and communication technologies such as building information modelling (BIM) to streamline engineering design and analysis has been mainstream over the past several years. Although BIM models are well established for aboveground infrastructures, underground BIM is still in its infancy. On one hand, valuable subsurface ground models are missing in current BIM applications as site-specific geotechnical data are often sparse and limited. On the other hand, BIM has been mainly used as a visualization tool for concise representation of design and construction data, and it has not been integrated and utilized to assess geotechnical risks associated with underground infrastructures. This paper proposes a BIM-based approach for automatic numerical modelling and geotechnical analysis. Structural information (e.g. geometries) of different project BIMs are grouped, exported, and saved, which provides a unified interface for automatic information extraction using computer codes (e.g. Python). Subsequently, subsurface ground models generated from sparse data are integrated with extracted basic geometric properties for automatic geotechnical model setup and finite element analysis. The performance of the proposed framework is illustrated using a real deep excavation project. It is revealed that BIM, as a data repository, enables timely and accurate information exchange between structural and geotechnical models in an automatic manner, which emphasizes the need of a BIM-based approach for assessing and managing geotechnical risks associated with deep excavations for underground transportation infrastructures, especially in the urban context.

Consumer’s Perception towards Online Banking Services

In order to determine whether consumers would continue to use the Unified Payment Interface (UPI) for electronic payments, this study looks at the impact of consumer resistance-related issues. The findings suggest that privacy concerns and usage barriers are the two crucial factors to be addressed to break down consumer resistance towards continuing usage of UPI. It also covers consumer behavior, and the entire study is primarily oriented toward existing UPI customers. The basics, such as the workings of UPI and customer concerns, are explained in detail. Multiple Regression Analysis revealed that various factors significantly influence the adoption of cashless payment modes by online consumers and limit consumers' ability to pay for their purchases online.

Engineering and Advancement of Digitization through Unified Payment Interface

Unified Payment Interface introduced in 2016 is an instant real-time payment system developed by National Payments Corporation of India facilitating inter-bank transactions. The interface is regulated by the Reserve Bank of India and works by instantly transferring funds between two bank accounts on a mobile platform. Unlike wallets, the payer and the payee can use two different payment service providers. Unified Payment Interface has brought revolution in payment system in India, making instant real-time payment system possible. This study is focused on looking at engineering side of Unified Payment Interface and its impact around advancement of digitization. Here we see behind Unified Payment Interface engineering infrastructure and how it works. This study also elaborates on surgencies of digitization through Unified Payment Interface mode in India. Study was carried out by taking survey, using Right to Information Act, and understanding computing side of Unified Payment Interface. In survey 214 individuals were asked 20 questions irrespective of age, location, sex, income background, education and religion in India. Findings were listed with both positives and negative aspects highlighted.