Automation Support Research Articles

A model-driven, metrics-based approach to assessing support for quality aspects in MLOps system architectures

In machine learning (ML) and machine learning operations (MLOps), automation serves as a fundamental pillar, streamlining the deployment of ML models and representing an architectural quality aspect. Support for automation is especially relevant when dealing with ML deployments characterised by the continuous delivery of ML models. Taking automation in MLOps systems as an example, we present novel metrics that offer reliable insights into support for this vital quality attribute, validated by ordinal regression analysis. Our method introduces novel, technology-agnostic metrics aligned with typical Architectural Design Decisions (ADDs) for automation in MLOps. Through systematic processes, we demonstrate the feasibility of our approach in evaluating automation-related ADDs and decision options. Our approach can itself be automated within continuous integration/continuous delivery pipelines. It can also be modified and extended to evaluate any relevant architectural quality aspects, thereby assisting in enhancing compliance with non-functional requirements and streamlining development, quality assurance and release cycles.

SQL2FPGA: Automated Acceleration of SQL Query Processing on Modern CPU-FPGA Platforms

Today’s big data query engines are constantly under pressure to keep up with the rapidly increasing demand for faster processing of more complex workloads. In the past few years, FPGA-based database acceleration efforts have demonstrated promising performance improvement with good energy efficiency. However, few studies target the programming and design automation support to leverage the FPGA accelerator benefits in query processing. Most of them rely on the SQL query plan generated by CPU query engines and manually map the query plan onto the FPGA accelerators, which is tedious and error-prone. Moreover, such CPU-oriented query plans do not consider the utilization of FPGA accelerators and could lose more optimization opportunities. In this article, we present SQL2FPGA, an FPGA accelerator-aware compiler to automatically map SQL queries onto the heterogeneous CPU-FPGA platforms. Our SQL2FPGA front-end takes an optimized logical plan of an SQL query from a database query engine and transforms it into a unified operator-level intermediate representation. To generate an optimized FPGA-aware physical plan, SQL2FPGA implements a set of compiler optimization passes to (1) improve operator acceleration coverage by the FPGA, (2) eliminate redundant computation during physical execution, and (3) minimize data transfer overhead between operators on the CPU and FPGA. Furthermore, it also leverages machine learning techniques to predict and identify the optimal platform, either CPU or FPGA, for the physical execution of individual query operations. Finally, SQL2FPGA generates the associated query acceleration code for heterogeneous CPU-FPGA system deployment. Compared to the widely used Apache Spark SQL framework running on the CPU, SQL2FPGA—using two AMD/Xilinx HBM-based Alveo U280 FPGA boards and Ver.2020 AMD/Xilinx FPGA overlay designs—achieves an average performance speedup of 10.1x and 13.9x across all 22 TPC-H benchmark queries in a scale factor of 1 GB (SF1) and 30 GB (SF30), respectively. While evaluated on AMD/Xilinx Alveo U50 FPGA boards, SQL2FPGA using Ver. 2022 AMD/Xilinx FPGA overlay designs also achieve an average speedup of 9.6x at SF1 scale factor.

PASTA: Programming and Automation Support for Scalable Task-Parallel HLS Programs on Modern Multi-Die FPGAs

In recent years, the adoption of FPGAs in datacenters has increased, with a growing number of users choosing High-Level Synthesis (HLS) as their preferred programming method. While HLS simplifies FPGA programming, one notable challenge arises when scaling up designs for modern datacenter FPGAs that comprise multiple dies. The extra delays introduced due to die crossings and routing congestion can significantly degrade the frequency of large designs on these FPGA boards. Due to the gap between HLS design and physical design, it is challenging for HLS programmers to analyze and identify the root causes, and fix their HLS design to achieve better timing closure. Recent efforts have aimed to address these issues by employing coarse-grained floorplanning and pipelining strategies on task-parallel HLS designs where multiple tasks run concurrently and communicate through FIFO stream channels. However, many applications are not streaming friendly and many existing accelerator designs heavily rely on buffer channel based communication between tasks. In this work, we take a step further to support a task-parallel programming model where tasks can communicate via both FIFO stream channels and buffer channels. To achieve this goal, we design and implement the PASTA framework, which takes a large task-parallel HLS design as input and automatically generates a high-frequency FPGA accelerator via HLS and physical design co-optimization. Our framework introduces a latency-insensitive buffer channel design, which supports memory partitioning and ping-pong buffering while remaining compatible with vendor HLS tools. On the frontend, we provide an easy-to-use programming model for utilizing the proposed buffer channel; while on the backend, we implement efficient placement and pipelining strategies for the proposed buffer channel. To validate the effectiveness of our framework, we test it on four widely used Rodinia HLS benchmarks and two real-world accelerator designs and show an average frequency improvement of 25%, with peak improvements of up to 89% on AMD/Xilinx Alveo U280 boards compared to Vitis HLS baselines.

Strategy for developing data standards in support of automation of Systematic Reviews

Strategy for developing data standards in support of automation of Systematic Reviews

A method of drawing double arrow symbols with automation support for 2D digital map applications

This paper addresses the challenges of translating pivotal military symbols like double arrows onto 2D digital maps, particularly when automation is essential. It proposes a comprehensive method integrating data structure, user workflow, and algorithms to generate tactically aligned, balanced, and visually appealing double arrows for military 2D digital maps. Experimental validation affirms its efficacy in meeting tactical requisites and aesthetic standards. Additionally, it outlines avenues for future research to further enhance and broaden the applicability of this method. In essence, this study presents a robust solution for the automated generation of double arrows on 2D digital military maps, marking a significant step in advancing automated symbolization for military planning.

INTELLIGENT FIELD AUTOMATION SYSTEM

The economy of India is a developing diverse economy. Nowadays, India grades second worldwide in farm production. Farming and connected areas like forestry and fisheries accounted for 13.7% of the GDP (gross domestic product) in 2013, about 50% of the workforce. The economic contribution of agriculture to Indias GDP is steadily declining with the countrys broad-based economic growth. Agriculture is the broadest economic sector and it has an importantplace in the overall socio-economic fabric of India.The prime concern being played is that deficiency of water, not just any water, but potable water. Agriculture automation [1] is the procedure of using several technical apparatuses to improve and automate agricultural dealings. This toolis essentially proposed to improve the labor-intensive and time-consuming agricultural procedures that farmers all over the world face. Farmers may gain more time and resources to devote in their properties with the support of farm automation and agriculture technology growths.This system is used to provide water to the field according to the need of soil by measuring the soil moisture level and atmospheric humidity level [2]. This systemavoids the wastage of water and electricity. The power consumption and water consumption can be controlled by a single motor, water tanks and some valves. Pump water to various water tanks by using single motor, valves and from multiple wells. The unauthorized persons intervention to the field, current atmospheric temperature level and moisture level of soil and animal attack can be remotely monitored and can be take necessary actions[3].

Legal Protection for Automatic Exchange of Information Taxation in Indonesia: The Importance of Synergy with Cybersecurity Institutions

<span lang="EN-US">Every citizen who is the subject of taxes and already has a Taxpayer Identification Number (NPWP or NIK) must do tax reporting on his income. Such reporting ensures taxpayer property and income data validation while supporting good governance. Data automation support is needed from other agencies such as banks to find out the balance and ownership of deposits and bank securities, land bodies to know land ownership, stock exchanges to know share ownership and other institutions related to property ownership. Integration between these institutions will increase the validity of reporting property and income owned by government officials, ultimately improving integrity towards good governance. In reality, there is no automation of validation of annual notification letter (SPT) charging data on property ownership data in each institution due to the sectoral ego of each institution, and there is no real-time regulation of property validation. Automatic Exchange of Information (AEOI) enables the automated sharing of a set of information that has been previously defined by the tax authorities. AEOI is a plan of the G20 members and is initiated by the OECD. The AEOI system works through the exchange of financial data of foreign nationals living in a country. The exchange of financial data is carried out between the tax authorities in each country. Indonesia is prepared to put this into practice as a G20 member, as evidenced by the previous release of Minister of Finance Regulation Number 39/PMK.03/2017 (PMK 39), covering Procedures for Exchange of Information Based on International Agreements. Types of Documents and/or Additional Information Required to Be Retained by Taxpayers Conducting Transactions with Related Parties and Procedures for Management, Minister of Finance Regulation No. 213/PMK..03/2016 (PMK 213). As a result, in addition to the Automatic Exchange of Information (AEOI) regulation put out by the Organization for Economic Cooperation and Development, there needs to be legal protection (OECD). Furthermore, the author emphasizes the importance of cooperation and synergy with cybersecurity institutions to secure tax exchange data.</span>

End-to-End Network Slicing Security Across Standards Organizations

This article makes a holistic analysis of the security aspects specified for 5G network slicing across the main standards and industry organizations, namely 3GPP, ETSI, and GSMA. A network slice is a logical end-to-end network that provides specific network capabilities and characteristics to serve a defined business purpose of communications service providers' (CSPs') customers. That purpose can be motivated by CSP internal reasons including network operation optimization, services classification, resources optimization, cost savings, support of network automation, or other specific customer demands. Network slicing can be defined as a paradigm where network slices are created with appropriate isolation, set of resources, and optimized topology, becoming a key feature and business driver for 5G. The overall security architecture of the 5G network is being constantly enhanced with new security features available as well in network slices as logical networks created within the 5G network. In contrast, the threat surface is increased with network slicing as new factors such as business models, tenants, functions, interfaces, and signaling flows are introduced, especially when the isolation among network slices is not well designed and effectively enforced. By analyzing the underlying security threats on network slicing, the article derives the corresponding security requirements and studies the specified mechanisms to protect the network slices. The article concludes pointing out several gaps in current standards with respect to 5G network slicing security and depicts possible next steps for further investigation.

A core IoT ontology for automation support in edge computing

Service providers provision more and more Internet-of-Things (IoT) services in the cloud for dynamicity and cost-effectiveness purposes. This is made possible thanks to the introduction of edge computing that brings additional computing and resources for analytics close to the data sources and thus enables meeting the low latency requirement. Edge nodes should support (i) the heterogeneity of IoT devices (e.g., sensor, actuator) and (ii) characteristics (e.g., mobility, location awareness). IoT is already integrated to the hybrid cloud/edge environment. However, the ecosystem lacks of automation due to the previously mentioned characteristics. Indeed, edge nodes are often manually selected during deployment time, and most of the regular quality-of-service (QoS) management procedures remain difficult to implement. This paper introduces a comprehensive semantic model called EdgeOnto. It encompasses all concepts related to IoT applied in the context of edge computing. The ultimate goal of EdgeOnto is to automate the several steps that make up the IoT services lifecycle in hybrid cloud/edge environment. On the one hand, semantics enable an automatic discovery of the relevant edge nodes that are suitable to host and execute IoT services considering their requirements. On the other hand, it allows supporting the specific QoS procedures that are related to such setting (e.g., low latency, mobility, jitter). The core ontology was designed with the Protégé open-source tool. A smart strawberry farming use case was implemented and evaluated for illustration purposes. The results validate the accuracy and the precision of the designed semantic matchmaker.

Computer-Aided Formalization of Internal Consistent Product Family Models

The product line approach enables the rapid building of software products by reusing core assets. How to manage the commonality and variability of product family is the core problem of product line engineering. The feature modeling approach is one of the main approaches to solve this problem. However, this approach does not define the internal functions of features. Some researchers use formal descriptions to define the function of features, but they do not consider the connection between feature specification and feature model. These product family modeling approaches result in product family models that suffer from inconsistent descriptions, which are difficult to resolve manually. To this end, this paper proposes a computer-aided approach to construct an internally consistent product family model. The method performs an inconsistency check during the formalization of each feature in the given initial feature model, pushing the evolution of the feature model and feature specification. The creation and evolution of feature models are achieved through a template-based feature modeling approach. The method is implemented by means of templates, each of which contains two parts of knowledge: the elements required for a class of feature model, and a way to convert the given elements into a formal description. An inconsistency check is achieved through a rule-based detection approach. Each rule contains two parts: a class of conditions that the feature model and the feature specification satisfy, and the actions to resolve inconsistencies once the conditions are satisfied. We have developed a tool. The tool guides the user to build an internally consistent product family model that contains the feature model and feature specifications. Experiments have shown that our approach can provide effective automation support for the process of formal product family modeling.

Development and Validation of Testing System for Automated Millimeter-Wave Phased Array Multibeam Near-Field Measurement

To ensure millimeter-wave (mmWave) radio system performance, multiple beam-steered radiation patterns of phased arrays are required to be measured in conventional antenna measurement ranges. This is typically done by sequentially measuring the radiation pattern of phased array under test (AUT) with the AUT mechanically rotating in a far-field setup for each steered beam in a beam-lock mode. However, the conventional pattern measurement procedure for mmWave phased arrays with multiple beams is time-consuming and costly due to the repetitive mechanical rotation and the use of far-field anechoic chamber. The problem becomes even more pronounced for mmWave phased arrays with large-scale antenna configuration due to many more beam states and more directive beam patterns. To address this issue, this paper proposes a novel near-field multi-beam measurement system for mmWave phased arrays, which offers unique advantages in terms of short measurement time, support for full automation, no need for mechanical rotation, compact measurement setup and low system cost. For the pattern with its beam steered to any given direction can be reconstructed based on the AUT element patterns retrieved from a few sparse measurement samples. In this work, the principle and effectiveness of the proposed measurement system have been firstly validated by electromagnetic simulations with CST Studio Suite. Besides, a practical system prototype has been built and experimentally validated where the near-field reconstructed multi-beam patterns are shown to match well with the far-field target patterns in terms of beam direction, beam gain, and pattern similarity percentage.

Presentation of the disease diagnosis process based on the verification of the state of fragments of medical biological objects by the decision support subsystem as an automated technological process

This article describes the analysis and synthesis of the diagnostic process and its presentation as a technological process for automating the diagnosis of diseases, which made it possible to increase the detail of diagnostics using technologies consisting in the synthesis of algorithms implemented by the software and information support of the medical information system when implementing methods for verifying the state of fragments of medical biological objects using computed tomographic images for the diagnosis of diseases. The article focuses on the analysis of X-ray images, decision-making based on the analysis of these images, diagnosis based on the decisions made.. Examples of practical implementation of software and information support for automation of verification methods of medical facilities in the form of screen forms for working with fragments of the object under study and the results of the analysis of radiographic images are shown. This makes it possible to increase the efficiency, accuracy of verification of the state of medical biological objects, the reliability of the disease diagnosis process. The scientific novelty, the results of the approbation of the material presented in the article at international, All-Russian conferences, in scientific journals are shown.

Building Social License for Automated Demand-Side Management—Case Study Research in the Swiss Residential Sector

Demand-side management (DSM) is increasingly needed for answering electricity flexibility needs in the upcoming transformation of energy systems. Use of automation leads to better efficiency, but its acceptance is problematic since it is linked with several issues, such as privacy or loss of control. Different approaches investigate what should be done for building community support for automation for the purpose of DSM, but it is only recently that literature has shown interest in the application of social license as a concept merging several issues traditionally treated separately. The social license concept emerged in the mining sector before being adopted for other problematic resources. It serves to identify different levels of community support for a project/company as well as various factors that influence it, such as economic and socio-political legitimacy and interactional trust. This paper investigates, through empirical evidence from eight case studies, what has been done in different contexts to build trust and legitimacy for an automated DSM project. Our findings suggest that patterns exist in respect of benefits, risks and rationale presented, the retention of control, information gathered, and inclusion and that these factors differ according to appliances/devices automated, operators of automation, and end-users targeted.

Bears in our midst: Familiarity with Level 2 driving automation and attending to surprise on-road events

This study presents an on-road paradigm to measure the effect of Level 2 (L2) system familiarity on attention strategies to salient, but non-hazardous, driving-related events when using the driving automation. A vehicle with an oversized pink teddy bear on the back overtook participants three times while they drove a 2019 Mercedes-Benz C300 equipped with a L2 system for 1 h. This L2 system requires drivers to keep their hands on the wheel while activated. The L2 system was turned on or off, depending on the assigned condition, and participants varied in their familiarity with L2 systems. Cameras recorded participant eye glance behavior. After the drive, participants were asked to recall the bear and the number of times their mind had wandered from the driving task during the drive. Results show that the driving automation support gave only participants familiar with L2 systems an advantage for greater bear recall. Unfamiliar participants were at a relative disadvantage when assisted by the L2 system, with generally poorer bear recall than unfamiliar participants who drove with the system off. Better bear recall corresponded with wider on-road gaze dispersion and more instances of mind wandering. Our findings support the effectiveness of this paradigm to measure driver attention when using a L2 system under real-world conditions and highlight the need to consider the role of driving automation familiarity in future research.

Comparative Analysis between Flutter and React Native

Today’s well know technology is mobile applications and mobile application development depends on demand skills after the invention of smartphones. The current mobile market shares are divided into two powerful technologies giant Android and iPhone. The Native Android mobile applications development Java-Kotlin are used, and on the other hand, for iPhone Apps are used Swift and Objective-C native IOS development. Those applications of Android and iPhone increased the development process and cost the development cost. Recently, cross-platform proved that developers quickly develop Android and iPhone applications with the same code known as a cross-platform mobile application, reducing company and customer effort and cost. In this research paper, the performance is compared between React Native Vs Flutter and efficiency, effectiveness, compatibility, community growth, documentation, Architecture, developer productivity, and Testing Automation Support CI/CD Support.

Understanding the Impact of Time Pressure and Automation Support in a Visual Search Task.

To understand the impact of time pressure and automated decision support systems (DSS) in a simulated medical visual search task. Time pressure usually impairs manual performance in visual search tasks, but DSS support might neutralize this negative effect. Moreover, understanding the impact of time pressure and DSS support seems relevant for many real-world applications of visual search. We used a visual search paradigm where participants had to search for target letters in a simulated medical image. Participants performed the task either manually or with support of a highly reliable DSS. Time pressure was varied within-subjects by either a trialwise time-pressure manipulation (Experiment 1) or a blockwise manipulation (Experiment 2). Performance was assessed based on signal detection measures. To further analyze visual search behavior, a mouse-over approach was used. In both experiments, results showed impaired sensitivity under high compared to low time pressure in the manual condition, but no negative effect of time pressure when working with a highly reliable DSS. Moreover, participants searched less under time pressure and when receiving DSS support, indicating participants followed the automation without thoroughly checking recommendations. However, the human-DSS team's sensitivity was always worse than that of the DSS alone, independent of the strength of time pressure. Negative effects of time pressure can be ameliorated when receiving support by a DSS, but joint overall performance remains below DSS-alone performance. Highly reliable DSS seem capable of ameliorating the negative impact of time pressure in complex detection tasks.

The nature of security: A conceptual framework for integral-comprehensive modeling of IT security and cybersecurity

Cybersecurity is a broadly defined concept comprising security for many different types of elements. Dealing with cybersecurity is a multidimensional problem, and the damage generated by cyberattacks can be very diverse. Reports about cybersecurity show recurrent problems, or increasing on their frequency of appearance, with no clear approach for solving them. Existing models deal with cybersecurity in several different but general ways, and results are not better. Consequently, managing cybersecurity deserves consideration of a new approach. Our approach is based on the nature of security. Security services are modeled around three basic security concepts, namely isolation, interaction, and representation. With these three concepts, a cybersecurity development starts with security objectives for overcoming the cybersecurity challenges, and also has a security representation to achieve integral and comprehensive security results. We propose an architecture-based security conceptual framework having three components, namely a system representation model kind, a security representation model kind, and a security process model kind, to accomplish the security process for a system. The security process is fully guided and supported with security objectives from the beginning to the end. The framework proposes several models, based on data structures for representing the system, the security, and the process itself. The models are scalable to represent systems of any size, from tiny to huge technology infrastructures, and with support for automation of the security process. The scope of the framework is the security of IT systems and cybersecurity, including information, software, virtual resources, hardware, IT devices, money, people, and other related physical objects being represented digitally. The framework was developed while creating a university cloud infrastructure, and consolidated while supporting the security of several national wide software and infrastructure applications for digital signature in Costa Rica. We aim to provide a new and innovative way for doing cybersecurity, by directly targeting the actual security requirements; with a simple, systemic, structured and potentially automated security process, and for achieving integral and comprehensive security solutions.

Comparative analysis of model‐based and traditional systems engineering approaches for simulating a robotic space system architecture through automatic knowledge processing

AbstractModel‐based Systems Engineering (MBSE) case studies in the literature assert that there are benefits to MBSE when applied to modeling and simulating space systems. This research evaluates the benefits of an MBSE modeling and simulation approach over a traditional, non‐MBSE approach through modeling and simulation of an orbiting sample Capture and Orient Module (COM) architecture for potential Mars Sample Return (MSR). The COM architecture was modeled, simulated, and evaluated against nominal load power and output data rate requirements to compare the two approaches. A new modeling and simulation‐centric V‐model was synthesized from existing V‐model and modeling and simulation process models to map out the modeling and simulation activities within the context of the system development lifecycle and used as a tool to compare the non‐MBSE and MBSE approaches. A three‐phase modeling and simulation process consisting of an analysis and modeling phase, computer programming and implementation phase, and experimentation phase was used to model and simulate the COM. The total number of manual and automatic knowledge processed was calculated for both approaches and used to quantify the benefits of the MBSE approach relative to the non‐MBSE approach. In the non‐MBSE approach, all knowledge elements were manually processed during the modeling and simulation process. In the MBSE approach, 49% of total knowledge processing was automated. The MBSE approach showed user experience benefits with modeling and simulating the COM robotic space system through providing a higher level of support for automation, reducing the burden of systems engineering tasks, and reducing effort.

Robotic process automation support in telemedicine: Glaucoma screening usage case

Glaucoma is a worldwide leading cause of irreversible blindness. Early detection is crucial for successful treatment and prevention of vision loss. Recently, tele-ophthalmology has gained more acceptance for remote consulting, and eye screening. The tele-ocular screening can be enhanced further with emerging technologies in robotic process automation (RPA) that offers the ability to automate repetitive human tasks of the ocular screening process. This work aims to assess time effectiveness of the RPA-supported glaucoma screening. Mobile-based glaucoma screening combining RPA and machine learning (ML) is developed for assessing its usability and the time effectiveness of the RPA-supported glaucoma screening. The usability evaluation of the developed application is conducted with 68 participants including both patients and medical staff. Handling times that users spent with or without RPA support are recorded along with the satisfactory questionnaire surveys. The results show that the screening system with integration of RPA reduces the average handling time per user by 75%. The overall satisfaction score of the application is 8.10 out of 10. The machine learning module helps in notifying clinicians when the preliminary diagnosis results in severe conditions, allowing timely treatment. Integration of RPA and ML can assist clinicians and reduce the workload of medical staff significantly. Our study shows that the RPA and ML-based framework improves customer experiences and cost-time efficiency. It promotes feasibility in large-scale population glaucoma screening and data collection.

Design and Evaluation Study of Visual Analytics Decision Support Tools in Air Traffic Control

AbstractOperators in air traffic control facing time‐ and safety‐critical situations call for efficient, reliable and robust real‐time processing and interpretation of complex data. Automation support tools aid controllers in these processes to prevent separation losses between aircraft. Issues of current support tools include limited ‘what‐if’ and ‘what‐else’ probe functionalities in relation to vertical solutions. This work presents the design and evaluation of two visual analytics interfaces that promote contextual awareness and support ‘what‐if’ and ‘what‐else’ probes in the spatio‐temporal domain aiming to improve information integration and support controllers in prioritising conflict resolution. Both interfaces visualize vertical solution spaces against a time‐altitude graph. The main contributions of this paper are: (a) the presentation of two interfaces for supporting conflict solving; (b) the novel representation of how vertical information and aircraft rate of climb and descent affect conflicts and (c) an evaluation and comparison of the interfaces with a traditional air traffic control support system. The evaluation study was performed with domain experts to compare the effects of visualization concepts on operator engagement in processing solutions suggested by the tools. Results show that the visualizations support operators' ability to understand and resolve conflicts. Based on the results, general design guidelines for time‐critical domains are proposed.