Framework For Development Of Systems Research Articles

Visualizing the Philippines’ SDG 11.3.1 Status and Progress Using Open-Source Geospatial Software and Earth Observation Datasets

Abstract. This paper presents the development and implementation of a web GIS-based application designed to visualize the status and progress of Sustainable Development Goals (SDGs). Focusing specifically on SDG 11.3.1, which pertains to sustainable urbanization, we propose a prototype (accessible at https://ccgeoinformatics.github.io/sdg1131ph/) that leverages open-source geospatial software and earth observation (EO) datasets. By following the "where-when-what-how" framework of SDG visualization system development, we address the need for effective visualization methods while showcasing the potential of accessible datasets and technology in supporting sustainable development monitoring efforts across different administrative levels. We demonstrate the feasibility of the system in aiding policymakers and stakeholders in their decision-making processes toward achieving the SDGs by 2030. Additionally, our work exemplified how open-source software and EO datasets can address the challenges associated with SDG reporting, particularly in areas where both data and visualization tools are scarce or inaccessible. This paper also contributes to the ongoing discourse on SDG visualization and underscores the importance of localized analysis and visualization in understanding and addressing the challenges of sustainable urbanization using the example of the Philippines.

Harnessing Oxygenic Photosynthetic Microorganisms for Sustainable Wastewater Treatment Systems: A Comprehensive Review

Aquaculture systems globally face significant environmental challenges, particularly concerning wastewater management. This review explores the innovative application of oxygenic photosynthetic microorganisms (OPhMs), specifically microalgae and cyanobacteria, as a sustainable solution for wastewater treatment within these systems. OPhMs offer a dual role in wastewater treatment by removing harmful pollutants such as nitrogen, phosphorus, and heavy metals, while simultaneously improving water quality through oxygenation. We evaluate the integration of OPhMs into existing aquaculture operations, considering key factors such as system design, operational conditions, and economic viability. Additionally, we discuss the potential of algal biomass as a secondary resource for producing biofuels, animal feed, and other bio-products, contributing to the circular economy model. Our findings highlight the ability of OPhM systems to significantly reduce the ecological footprint of aquaculture while recovering valuable resources. However, challenges such as process stability, especially under low-temperature conditions, and the efficiency of biomass harvesting, require further research. This study provides a comprehensive framework for future development and optimization of OPhM-based wastewater treatment systems to improve the sustainability of aquaculture operations.

Optimizing Wireless Power Transfer Systems: A Simulation-Based Approach Using CST Studio Suite

In the rapidly evolving field of wireless power transfer (WPT), achieving systems that combine efficiency with reliability is crucial. This paper presents a simulation-based approach using CST Studio Suite to optimize WPT systems for wireless battery chargers in electric bikes. The study fixes the size of both the transmitter and receiver coils, the spacing between turns, and the number of coil turns, with a set distance of 20mm between the transmitter and receiver coils. CST Studio Suite is employed to determine the parameters of resonance capacitors and the optimal switching frequency to enhance WPT efficiency. This powerful simulation tool allows researchers and engineers to design resonance compensation circuits more effectively, optimizing power transfer efficiency. The simulation conducted with CST Studio Suite confirms its effectiveness in designing a WPT system, achieving an impressive peak efficiency of 99.61% at the resonant frequency. The paper demonstrates CST Studio Suite's capability to accurately predict WPT system performance by developing detailed electromagnetic models and fine-tuning simulation parameters to reflect real operating conditions. Iterative simulations resulted in optimized practices, validated by select results that highlight the method's effectiveness and showcase an optimal balance between system complexity and efficiency. These findings provide a strategic framework for future WPT system development, offering practical guidance for researchers and industry professionals aiming to advance WPT technology.

Ethical Considerations in Artificial Intelligence A Framework for Responsible Information Systems Development

This research aims to develop a framework that explains ethical considerations in the responsible development of Information Systems (IS) related to artificial intelligence (AI). The research method used involved a thorough literature review to identify relevant ethical principles in the context of AI and IS. Apart from that, an in-depth analysis of various existing models and frameworks was also carried out to understand ethical considerations in technology development. The result of this research is a framework consisting of a series of ethical principles that must be considered at every stage of IS development that uses AI technology. This framework considers not only the technical aspects of system development, but also relevant social, legal and cultural aspects. Through the application of this framework, IS developers can ensure that the resulting products are not only of high technical quality, but also pay attention to their impact on individuals, society and the environment. The conclusions of this research emphasize the importance of including ethical considerations as an integral part of the IS development process that uses AI to achieve the goals of socially responsible technology development.

A framework for the practical development of condition monitoring systems with application to the roller compactor

Implementing a condition-based maintenance strategy requires an effective condition monitoring (CM) system that can be complicated to develop and even harder to maintain. In this paper, we review the main complexities of developing condition monitoring systems and introduce a four-stage framework that can address some of these difficulties. The framework achieves this by first using process knowledge to create a representation of the process condition. This representation can be broken down into simpler modules, allowing existing monitoring systems to be mapped to their corresponding module. Data-driven models such as machine learning models could then be used to train the modules that do not have existing CM systems. Even though data-driven models tend to not perform well with limited data, which is commonly the case in the early stages of pharmaceutical process development, application of this framework to a pharmaceutical roller compaction unit shows that the machine learning models trained on the simpler modules can make accurate predictions with novel fault detection capabilities. This is attributed to the incorporation of process knowledge to distill the process signals to the most important ones vis-à-vis the faults under consideration. Furthermore, the framework allows the holistic integration of these modular CM systems, which further extend their individual capabilities by maintaining process visibility during sensor maintenance.

Vitamin B12 in Photocatalysis - An Underexplored Frontier in Cooperative Catalysis.

Vitamin B12 (VB12) is a flexible and sustainable catalyst both in nature and the reaction flask, facilitating varied organic transformations of high value to both enzymatic processes and synthetic chemists. Key to this value is the breadth of reactivity it possesses, capable of both ionic, 2 electron chemistry, and radical, 1 electron chemistry. In particular, the ability to generate carbon-centered radical intermediates via photolysis of organocobalt intermediates formed from alkyl electrophiles opens the door to powerful new radical transformations challenging to achieve using classical photoredox or ligand-to-metal charge transfer (LMCT) catalysis. While this unique photocatalytic reactivity of VB12 has been increasingly leveraged in monocatalytic schemes, recent reports have demonstrated VB12 is able to function as the photocatalytic component in cooperative schemes, driving diverse reactivity including remote elimination of alkyl halides, regioselective epoxide arylation, and regioselective epoxide reduction. This concept briefly overviews the enabling photochemical properties of VB12 and recent applications in cooperative catalysis, providing a framework for the continued development of new cooperative catalyst systems using this powerful photoactive complex.

Perancangan Sistem Informasi Peminjaman Berkas Rekam Medis di RSUD Al-Ihsan

This study aimed to evaluate current systems and processes as well as design and build a medical record lending information system using Visual Studio 2012 at Al-Ihsan Regional Hospital in Bandung. The research method used is qualitative research with data collection through observation, interviews, internet browsing and information system design within a system development framework built using the waterfall method using the Microsoft Visual Studio 2012 tool. In this study, several problems were found in the medical record borrowing process, among others, inefficiencies in the document borrowing system, the use of using Excel-based manuals, as well as obstacles in obtaining documents. It is suggested that a system designed to record loans be used to speed up the process and manage duplicate data more effectively.

Strategic Framework for Development of Typology-based Fertilizer Policy and Regulatory Systems in Sub-Saharan Africa

Strategic Framework for Development of Typology-based Fertilizer Policy and Regulatory Systems in Sub-Saharan Africa

Pembuatan Aplikasi Persediaan Barang Berbasis Web Pada PT. Bayan Resources Tbk

This research aims to design and implement a web-based Goods Inventory Information System at PT Bayan Resources Tbk. The company faces challenges in inventory management, such as stock uncertainty, variations in order cycle time, and operational efficiency levels that need to be improved. Waterfall method is used as a framework for system development, with stages of requirement analysis, design, implementation, testing, and maintenance. The system is designed to improve operational efficiency through integration of inventory data, order management, and item tracking. The result is a web-based application with features such as a secure login page, informative dashboard, master data management, efficient input of incoming and outgoing goods, and careful user control. With the implementation of dark mode, the system gives users the flexibility to customize the display according to their preferences. Users can easily access, track, and analyze inventory data, supporting faster and more accurate decision-making for the company.

An Overview of Current Challenges and Emerging Technologies to Facilitate Increased Energy Efficiency, Safety, and Sustainability of Railway Transport

This article presents a review of cutting-edge technologies poised to shape the future of railway transportation systems, focusing on enhancing their intelligence, safety, and environmental sustainability. It illustrates key aspects of the energy-transport-information/communication system nexus as a framework for future railway systems development. Initially, we provide a review of the existing challenges within the realm of railway transportation. Subsequently, we delve into the realm of emerging propulsion technologies, which are pivotal for ensuring the sustainability of transportation. These include innovative solutions such as alternative fuel-based systems, hydrogen fuel cells, and energy storage technologies geared towards harnessing kinetic energy and facilitating power transfer. In the following section, we turn our attention to emerging information and telecommunication systems, including Long-Term Evolution (LTE) and fifth generation New Radio (5G NR) networks tailored for railway applications. Additionally, we delve into the integral role played by the Industrial Internet of Things (Industrial IoT) in this evolving landscape. Concluding our analysis, we examine the integration of information and communication technologies and remote sensor networks within the context of Industry 4.0. This leveraging of information pertaining to transportation infrastructure promises to bolster energy efficiency, safety, and resilience in the transportation ecosystem. Furthermore, we examine the significance of the smart grid in the realm of railway transport, along with the indispensable resources required to bring forth the vision of energy-smart railways.

Conceptualization, Realization, and Validation of Distributed Cyber-Physical Systems for Sensing and Automation

Abstract This paper investigates the feasibility of the pragmatic implementation of distributed algorithms in real-world cyber-physical systems (CPSs). We detail how distributed (and parallel) computing systems can be realized using existing system-design software for CPS development. A series of experiments is devised and used to verify the information-exchange capacity of the computing nodes and the synchronous and real-time operational effectiveness of the overall distributed computing system development framework. Finally, an actual distributed computing system is realized and validated by executing a fundamental distributed consensus protocol.

An ontology-based framework for semantic geographic information systems development and understanding

Geographic information systems (GIS) are a widely used approach for geodata manipulation, analysis, and geoinformation visualization. Although the issue of semantic heterogeneity for GIS applications has been widely addressed, the development of flexible semantic GIS systems can still be improved, and GIS interfaces can be further unified to enhance system understanding among users of various GIS systems. This study proposes an ontology-based semantic GIS conceptual framework that can seamlessly combine ontology models, GIS elements and user actions for semantic GIS application development. In addition, a GIS components ontology that encompasses the five fundamental components of GIS is proposed to integrate GIS elements that can perceive GIS operations and processes semantically and to support customized GIS system designs. Moreover, a semantic WebGIS implementation framework is designed on the basis of the proposed conceptual framework to facilitate semantic WebGIS development. The implementation uses two common application scenarios regarding urban change analysis and user interaction. The former performs semantic retrieval for urban change analysis with system understanding, whereas the latter conducts online thematic mapping with semantic interpretation. The study contributes in terms of innovation in the design of a unified GIS components ontology and successful implementation of a semantic GIS system using the ontology-driven approach, thereby providing a convincing demonstration of the latter and showing the potential for semantic GIS application paradigms.

Single-Wire Control and Fault Detection for Automotive Exterior Lighting Systems.

The design of exterior lighting is crucial for automotive manufacturers to ensure the visibility and safety of the driver. This article proposes a new strategy to control and diagnose one or more exterior lighting functions in electric vehicles by maximising the electrical faults that are detected and their transfer over a single-wire. The outcome is a decreased system cost and an additional method for vehicle lighting infrastructure control and diagnosis. Virtual simulation tools are used to explore the correlation between master-slave architecture and the effectiveness of the single-wire approach to comply with safety and regulatory demands. Safety-related and non-safety-related needs are explored to properly assess lighting functions, internal logic, and fault-case scenarios. Furthermore, assessing the viability of minimizing wire harness utilization while retaining the diagnostic capabilities for the controlled lighting sources, thereby simultaneously reducing the vehicle's overall weight. This approach aims to concurrently decrease the overall weight of the vehicle. This work has three main contributions: (1) the development of efficient and reliable lighting systems in electric vehicles, a critical factor for achieving optimal performance, ensuring customer satisfaction, meeting regulatory compliance, and enhancing cost-effectiveness in automotive lighting systems. (2) Framework for future development and implementation of lighting systems in electric vehicles. (3) Simulation of the hardware architecture associated with the system strategy to achieve the desired system strategy for effectively applying the single-wire approach.

Systematic AI Support for Decision-Making in the Healthcare Sector: Obstacles and Success Factors

BackgroundCurrently, health care is expert-centric, especially with regard to decision-making. Innovations such as artificial intelligence (AI) or interconnected electronic health records (EHRs) suffer from low adoption rates. In the rare cases of technically successful implementation, they often result in inefficient or error-prone processes. Aim & MethodsThis paper explores the state of the art in AI-based digital decision support systems (DDSSs). To overcome the low adoption rates, we propose a systematic strategy for bringing DDSS research into clinical practice based on a design science approach. DDSSs can transform health care to be more innovative, patient-centric, accurate and efficient. We contribute by providing a framework for the successful development, evaluation and analysis of systems for AI-based decision-making. This framework is then evaluated using focus group interviews. ResultsCentred around our framework, we define a systematic approach for the use of AI in health care. Our systematic AI support approach highlights essential perspectives on DDSSs for systematic development and analysis. The aim is to develop and promote robust and optimal practices for clinical investigation and evaluation of DDSS in order to encourage their adoption rates. The framework contains the following dimensions: disease, data, technology, user groups, validation, decision and maturity. ConclusionDDSSs focusing on only one framework dimension are generally not successful; therefore, we propose to consider each framework dimension during analysis, design, implementation and evaluation so as to raise the number of DDSSs used in clinical practice. Public Interest SummaryThe digital transformation of the healthcare sector creates the potential for the sector to be more accurate, efficient and patient-centric using AI, or so-called digital decision support systems. In this research, we explore why these systems are needed and how they can be successfully implemented in clinical practice. For this, we propose a systematic approach based on our conceptual framework. Against this background, we present our vision for further advancing these technologies. We see our systematic AI support as a primary driver, with the possibility to facilitate the much-needed breakthrough of decision support systems in health care.

Modeling language for the function-oriented development of mechatronic systems with motego

As mechatronic products gain in popularity, methods for mastering the complexity of these systems in development become increasingly relevant, such as model-based systems engineering (MBSE). Main pillars of MBSE are method, language and tool. A method specifies procedures in product development. The application of the method is supported by a language and tool as the language specifies a system of symbols with which development artifacts can be represented in a software environment (i.e. tool). Currently, various MBSE methods exist, such as motego. Motego specifies a framework for the function-oriented seamless development of mechatronic systems from requirements to the physical realization down to mechanical and electrical contacts and the description of these via parameters and models. Central element in MBSE is the system model, which connects all relevant development artefacts. The system model is created with a language in a software environment such as Cameo Systems Modeler. In MBSE, the graphical systems modeling language SysML is widely established. The language elements in SysML are very abstract and numerous. As a result, the language is difficult to apply. However, its reasonable applicability is an essential prerequisite for the introduction of the motego methods in industrial practice. This results in the following research need: A specific modeling language for the motego method is needed that supports its reasonable application. Therefore, in this paper a modeling language is presented whose language elements are specifically adapted to the motego method. With the help of this domain specific language, the user is guided through method-compliant modeling.

A Low-code Development Framework for Cloud-native Edge Systems

Customizing and deploying an edge system are time-consuming and complex tasks because of hardware heterogeneity, third-party software compatibility, diverse performance requirements, and so on. In this article, we present TinyEdge, a holistic framework for the low-code development of edge systems. The key idea of TinyEdge is to use a top-down approach for designing edge systems. Developers select and configure TinyEdge modules to specify their interaction logic without dealing with the specific hardware or software. Taking the configuration as input, TinyEdge automatically generates the deployment package and estimates the performance with sufficient profiling. TinyEdge provides a unified development toolkit to specify module dependencies, functionalities, interactions, and configurations. We implement TinyEdge and evaluate its performance using real-world edge systems. Results show that: (1) TinyEdge achieves rapid customization of edge systems, reducing 44.15% of development time and 67.79% of lines of code on average compared with the state-of-the-art edge computing platforms; (2) TinyEdge builds compact modules and optimizes the latent circular dependency detection and message routing efficiency; (3) TinyEdge performance estimation has low absolute errors in various settings.

A fuzzy logic assessment framework for collaborative development of product-service systems

The development and value chain management of product-service systems (PSS) requires companies to look for new capabilities, regarding the disparate components of a PSS. However, interfirm collaboration in this context presents several particularities which may be challenging for the stakeholders and can lead to project failure. In this regard, there is still limited literature addressing frameworks and tools to manage the collaborative aspects of PSS from an organisational point of view. This paper presents a methodology to develop a framework to support companies in choosing suitable partners in a PSS development project and to improve collaboration. Thus, an assessment model is built using key performance indicators (KPIs) based on important collaboration performance factors, with the help of a fuzzy logic tool. This model is then tested and validated in two different PSS case studies.

A Framework for Neonatal Prematurity Information System Development Based on a Systematic Review on Current Registries: An Original Research.

Registries are regarded as a just valuable fount of data on determining neonates suffering prematurity or low birth weight (LBW), ameliorating provided care, and developing studies. This study aimed to probe the studies, including premature infants' registries, adapt the needed minimum data set, and provide an offered framework for premature infants' registries. For this descriptive study, electronic databases including PubMed, Scopus, Web of Science, ProQuest, and Embase/Medline were searched. In addition, a review of gray literature was undertaken to identify relevant studies in English on current registries and databases. Screening of titles, abstracts, and full texts was conducted independently based on PRISMA guidelines. The basic registry information, scope, registry type, data source, the purpose of the registry, and important variables were extracted and analyzed. Fifty-six papers were qualified and contained in the process that presented 51 systems and databases linked in prematurity at the popular and government levels in 34 countries from 1963 to 2017. As a central model of the information management system and knowledge management, a prematurity registry framework was offered based on data, information, and knowledge structure. To the best of our knowledge, this is a comprehensive study that has systematically reviewed prematurity-related registries. Since there are international standards to develop new registries, the proposed framework in this article can be beneficial too. This framework is essential not only to facilitate the prematurity registry design but also to help the collection of high-value clinical data necessary for the acquisition of better clinical knowledge.

A Framework for Human-aware Collaborative Robotics Systems Development

In the last decade, the manufacturing domain has been marked by a veritable flood of technological breakthroughs. Collaborative robotics, in particular, has enabled workstations to be shared between humans and their robotic counterparts. The ability of collaborative robots to work side-by-side with humans has opened up new possibilities for task and activity design in manufacturing. However, despite the promising outlook, actual collaboration between humans and cobots in existing applications is very limited, so the potential of the technology is only partially realised. In this paper, a framework is proposed to help practitioners and researchers in implementing human-aware collaborative robotics systems. The framework supported the development of a collaborative screwdriving application in which both the operator and the robot support and perceive each other to optimise process performance and worker well-being.

A BPMN-driven framework for Multi-Robot System development

Programming robotic systems is often a challenging task requiring advanced skills, especially when the goal is to ensure loosely-coupled coordination in heterogeneous Multi-Robot Systems (MRSs). Model-driven approaches for robotic system engineering have shown their benefits in facilitating the development of robots’ behavior, controllers, and system components. However, the state of the art still lacks contributions addressing crucial aspects of the model-driven approach applied to MRSs, such as developing robots’ distributed cooperation through models supporting the communication among robots.In this paper, we present a novel framework for modeling, configuring and enacting the cooperative behaviors of MRSs through collaboration diagrams as provided by the BPMN 2.0 standard. The advantages of our solution lie, indeed, in the use of BPMN, which provides easily understandable and highly expressive diagrams for representing the cooperation among distributed robots, and benefits from a wide list of supporting tools. Starting from the selection of BPMNelements, we define a set of guidelines for driving the developer in modeling an MRS mission using BPMN. The developer configures the resulting collaboration diagram to link elements in the model to the robotic middleware, ROS2 in the toolchain we implemented. Finally, the configured model is enacted by BPMN engines integrated into the ROS2 middleware run by each robot involved in the MRS, thus obtaining a fully distributed cooperation. We assess our framework’s effectiveness through experiments in simulated and real environments.