Systems Methodology Research Articles

Solar PV technologies selection for the design of photovoltaic installations in Mexico based on the analysis of meteorological satellite data from the region

Mexico’s expansive territory spans diverse climatic conditions, which directly influences the selection of commercial photovoltaic technologies. This study utilizes solar irradiance, temperature, and cloud index data (derived from satellite sources) to generate a suitability map for commercial solar panel technologies through the Analytical Hierarchy Process-Geographical Information Systems methodology. The map illustrates that chalcopyrites and cadmium telluride emerge as the most suitable technologies in 47.12% of the national territory. Following closely behind is amorphous silicon, covering 30.45%, while monocrystalline and polycrystalline silicon account for 22.43%. The primary objective of this paper is to guide the proper selection of solar panel technology types that align optimally with Mexico’s climatic conditions. This strategic approach aims to strengthen the planning and viability of photovoltaic solar energy projects nationwide.

Navigating Generative AI: The Teacher Librarian's Role in Cultivating Ethical and Critical Practices

ABSTRACT The recent evolution of Generative Artificial Intelligence (GAI) has already made a tangible impact within the realm of education. Positioned at the forefront of information and digital literacies, teacher librarians (TLs) can be leaders in exploring the potential for AI platforms to transform learning and teaching. This research is based on an exploratory methodology, to investigate how TLs might teach with and about GAI by applying the CATWOE analysis technique [Checkland, P., & Poulter, J. (2006). Learning for action: A short definitive account of soft systems methodology, and its use for practitioners, teachers and students. Wiley.] within the context of three specific GAI platforms. Findings highlight the multifaceted role that TLs can assume, extending beyond the pedagogical integration of GAI to encompass a broader educational mandate: to scaffold students’ capabilities as critical and ethical users of these tools in the creation and use of information.

Design a model to improve sustainable supply chain performance with an emphasis on identifying effective financial components through the soft systems method

Today, in the world of competition, it is necessary for organizations to formulate structured management plans to operate in these conditions. One of the most important issues that can be investigated in depth can make organizations successful in the field of competition, the issue of supply chain management. A new point of view is a financial point of view. Therefore, in the current research, the aim is to provide a solution to improve the performance of the sustainable supply chain by identifying the financial components affecting it. In this way, using the soft systems methodology, approach, the problem of unstructured sustainable supply chain management from the financial point of view is expressed, and then by analyzing it, the image of different players of the drawing system and their root definition is raised. In the following, a conceptual model of activities is presented using the root definition and then the model is compared with the real world. Finally, the desired changes to improve and develop the actual system are identified and programs implemented to improve the performance and increase the profitability of the supply chain management system. Finally, the financial, monetary, sustainability and risk dimensions were identified as the four main factors affecting the sustainable supply chain. The results of this study will be effective for designing improvement patterns in sustainable supply chain management.

Real-Time Simulation of Open Quantum Spin Chains with the Inchworm Method.

We study the real-time simulation of open quantum systems, where the system is modeled by a spin chain with each spin associated with its own harmonic bath. Our method couples the inchworm method for the spin-boson model and the modular path integral methodology for spin systems. In particular, the introduction of the inchworm method can significantly suppress the numerical sign problem. Both methods are tweaked to make them work seamlessly with each other. We represent our approach in the language of diagrammatic methods and analyze the asymptotic behavior of the computational cost. Extensive numerical experiments are performed to validate our method.

Towards a Unified Architecture Methodology for Product Service Systems

AbstractThere is ongoing digital transformation in many industrial contexts including non‐digital hardware‐intensive domains such as heavy construction equipment machinery. This transformation is augmented by the latest technologies, increasing sustainability regulations, as well as integrated customer needs. This paradigm shift is causing transformation of current product‐centric business models towards complex business models enabled by so‐called Product Service Systems (PSS) offering advanced “capabilities” and “services”. However, the development of PSSs requires a holistic approach to unify underlying solution domains such as mechatronic systems, embedded software control as well as information systems. In this paper, we describe a holistic “unified” architecture description methodology towards aligning the underlying domain‐specific design and development contexts. The framework, developed in construction domain, consists of two main parts: a minimalistic reference model as the “common language” for cross‐functional stakeholder communication; a modeling methodology based on existing standard modeling frameworks. We illustrate the methodology using examples from the construction equipment domain.

Analysis of the impact of rail head wear on railway superstructure stability

Continuous welded rail track (CWR) is a superstructure construction of the railway that withstands significant compressive forces from the longitudinal extension of the rails due to temperature changes, ensuring the safe railway operation. The applicable for the Bulgarian railway system methodology for determining the critical compressive force at which the CWR loses stability has been examined. Different types of rails with their respective design parameters, important for the force calculation, have been taken into consideration. The considered design parameters, as moment of inertia and sectional modulus of the rails, change during operation due to the rail head wear. The aim of the article is to examine specific examples of railway tracks on curves, analyzing the impact of the changed operational design parameters of the rail on the stability of the track. The operational and geometric parameters of the railway track have been considered.

A Clinic Appointment System with Authentications for Klinik Sejahtera

The clinic is a health facility for outpatients in indigenous communities. Traditionally, patients need to walk into the clinic or telephone the clinic if they want to make a medical appointment. For this project, Klinik Sejahtera has been chosen as the case study. Klinik Sejahtera is located at Parit Raja, Johor. Klinik Sejahtera was using “first come, first serve” to their patients that came on that day. Usually, the appointment will be taken at the counter during the patient's come to the clinic. The responsible employee at the counter will ask the patient for their identity card and search for the record. They also offer an appointment by contacting the clinic. The problem arises when staff need to record manually and need to remind the patient about the appointment. There are also problems with duplication because of too many physical reports. Therefore, this project proposed a clinic appointment system with authentications which is password-based and Completely Automated Public Turing Test to Tell Computers and Humans Apart (CAPTCHA). The system will be web-based. The web-based will be used by the patients, nurses, and doctor. Object-oriented system development is used for the methodology of the proposed system.

A Soft Systems Methodology Application to Promote the Multidimensional Model of e-Government Project Management in Indonesia’s Construction Services

The Integrated Construction Services Information System (ICSIS) project is one of the Indonesian government's initiatives to meet public demand for better construction business services. Despite being in operation for approximately 6 (six) years, ICSIS performs poorly. Fragmented business processes, noninteroperable systems, and unaccountable data all demonstrate poor performance in this regard. With all the best efforts, ICSIS only reaches 12% of the total target users. This paper discusses a problem-structuring approach to problem analysis and comprehension, as well as the critical factors to consider through stakeholder interaction. From various perspectives, the results of this structuring phase using literature study, comparative analysis and soft systems methodology indicate that multidimensional factors must be considered in order to achieve the expected ICSIS values. This technique assists decision makers in developing a multidimensional model in ICSIS project management with the goal of fostering more dependable and long-term e-government in the construction services.

A novel fault detection and diagnostic Petri net methodology for dynamic systems

Faults can have significant, negative impacts on the operation and performance of simple and complex dynamic systems. Based on the integration of Bayesian network diagnostic features with Petri net formalism, the existing Bayesian-supported Petri net tool has demonstrated the flexibility of using the Petri net approach for diagnosing failure scenario of a dynamic system. However, studies on using the proposed hybrid Petri net approach for condition monitoring and early detection and diagnosis of single and multiple failures in a dynamic system with feedback control loops are yet to be investigated. Thus, this paper presents a methodology to address this research gap using the operation of a water tank level control system as a case study. The method combines the constructed Generalised Stochastic Petri Net (GSPN) model of the system operation with its corresponding fault diagnostic Petri net model, created using the proposed modified Bayesian Stochastic Petri Net (mBSPN) formalism. The GSPN model establishes the causal relationships between the system’s components and/or subsystems. It further identifies deviations in the sensor measurements of the observable process variables characterising the system operation. The information provided by the sensors in the system model are then inputted into the mBSPN model to diagnose the root cause of the observed deviations. The obtained results demonstrated the capability of using the proposed integrated Petri net methodology for system condition monitoring, early fault detection and diagnosis of single and multiple failures in a dynamic system with feedback control loops.

Evaluation of the use of antibiotics using the anatomical therapeutic chemical/defined daily dose and Gyssens methods in pneumonia patients at a tertiary care general hospital in Medan

Background: The impact of irrational antibiotic usage in pneumonia patients is an increase in resistance, an increase in drug side effects, and a failure of therapy that causes patients' health to deteriorate, lowering their quality of life and raising their treatment costs. The primary objective of this study is to assess the extent to which antibiotics are being used rationally in the inpatient facility of a private tertiary care hospital located in Medan. Methods: The present study employs an observational design with a prospective cross-sectional approach, carried out within the timeframe of September to November 2022. The evaluation of antibiotic utilization was conducted utilizing the anatomical therapeutic chemical (ATC)/defined daily dose (DDD) methodology and the Gyssens methodology. Results: The findings of the study indicate that a significant proportion of individuals diagnosed with pneumonia fell between the age range of 46 to 55 years, comprising 23.4% of the overall patient population. Moreover, the male gender was found to be the most prevalent, accounting for 55.81% of the 278 patients who satisfied the inclusion criteria. The findings from the evaluation of antibiotic utilization, employing the ATC classification system and DDD methodology, yielded a rate of 145.72 DDD per 100 days of care. Ceftriaxone exhibited the highest value, reaching 87.59 DDD/100 days of treatment. The evaluation of the Gyssens approach yielded a total of 254 patients who were administered antibiotics in an appropriate manner (category 0), while 24 patients were found to have received unsuitable antibiotics (categories I-VI). Conclusions: Based on the findings of this study, it can be inferred that the utilization of antibiotics within the hospital under investigation remains inadequate in terms of both quantity and quality.

A qualitative exploration of forensic pathology service staff perceptions of the implementation barriers and facilitators of manual- and electronic injury mortality surveillance system methods in South Africa

BackgroundInjury mortality surveillance systems are critical to monitor changes in a population’s injury outcomes so that relevant injury prevention responses may be adopted. This is particularly the case in South Africa, where the injury burden is nearly twice the global rate. Regular evaluations of surveillance systems are pivotal to strengthening surveillance capacity, performance, and cost effectiveness. The National Injury Mortality Surveillance System (NIMSS) is an injury mortality surveillance system that is currently focused in Mpumalanga and utilises manual and electronic web-based systems for data collection. This study explored Forensic Pathology Service (FPS) staff perceptions of the implementation barriers and facilitators of manual- and electronic injury mortality surveillance system methods.MethodsA qualitative study was employed using purposive sampling. Forty-seven participants, aged 29 to 59 years comprising 31 males and 16 females were recruited across 21 FPS facilities that serve the province. The formative evaluation occurred over the November 2019 to November 2022 period. Twelve focus group discussions were thematically analysed to determine emerging themes and patterns related to the use of the system using the WHO surveillance system guidelines as a framework.ResultsThe key themes concerning the barriers and facilitators were located along WHO attributes of simplicity, acceptability, timeliness, flexibility, data quality and stability. Distinctions between the manual and e-surveillance systems were drawn upon across the attributes highlighting their experience with the system, user preference, and its contextual relevance. With Mpumalanga predominantly rural, internet connectivity was a common issue, with most participants consequently showing a preference for the manual system, even though the electronic system’s automated internal validation process was of benefit. The data quality however remained similar for both methods. With program stability and flexibility, the manual system proved more beneficial as the dataset was reported to be easily transferrable across computer devices.ConclusionObtaining FPS perceptions of their experiences with the system methodologies are pertinent for the enhancement of injury surveillance systems so to improve prospective engagements with the systems. This will facilitate timely and accurate injury mortality information which is vital to inform public policy, and injury control and prevention responses.

A GIS-based FAHP and FEDAS analysis framework for suitable site selection of a hybrid offshore wind and solar power plant

This study presents a Geographic Information System (GIS) based suitable site selection methodology for a hybrid system that includes offshore wind and solar PV. The methodology utilizes open source databases about decision criteria and applies this data using GIS to determine suitable sites for offshore wind and solar PV systems. For the assessment of multi-criteria which affect the potential hybrid energy power plants and the determination of the best suitable areas, Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Evaluation based on Distance Average Solution (FEDAS) are used in the study. Results show that technical criteria has the priority weight of 0.60 while the weight of social criteria is about 0.07. Among sub-criteria, the wind speed has the highest priority weight while distance to port and visibility are the highest criteria of priority weight under economic and social main criteria, respectively. Among the alternatives, Area 2 (A-2) is determined as the best alternative for hybrid offshore power plants in the study area. This proposed methodology can be utilized by decision-makers to determine the best suitable locations for hybrid offshore wind and solar PV systems at any location. This paper suggests a new approach integrating GIS, fuzzy setbased AHP and EDAS as a novelty.

Credit Risk Prediction Based on Psychometric Data

In today’s financial landscape, traditional banking institutions rely extensively on customers’ historical financial data to evaluate their eligibility for loan approvals. While these decision support systems offer predictive accuracy for established customers, they overlook a crucial demographic: individuals without a financial history. To address this gap, our study presents a methodology for a decision support system that is intended to assist in determining credit risk. Rather than solely focusing on past financial records, our methodology assesses customer credibility by generating credit risk scores derived from psychometric test results. Utilizing machine learning algorithms, we model customer credibility through multidimensional metrics such as character traits and attitudes toward money management. Preliminary results from our prototype testing indicate that this innovative approach holds promise for accurate risk assessment.

The Role of the Warehousing Module in the Building of a Modern Enterprise Resource Planning System

This article presents a developed and functioning Enterprise Resource Planning (ERP) for the warehouse logistics management, designed for the needs of small and medium-sized companies in Bulgaria. The current ERP system aims to satisfy the needs of a specific transport company – to track and manage the main activities. The main thesis of the present development is the leading role of software innovations in the use of data, their summation and distribution among the company's employees in real time. The design methodology of the developed system includes a study and thorough analysis of customer needs and requirements in order to fully cover the processes in the client company. At the same time, the system is flexible enough to adapt easily to future changes in the customer environment. The article presents the main characteristics of the implemented system, such as ease of use, speed, and intuitive design. As a result of its implementation, the management decision-making processes of both the middle and senior management teams of the company have been significantly supported and facilitated. The developed system has a market implementation in Bulgaria, and is in the process of searching for sales representatives, partners and customers in other countries.

Detection of Listeria Species by Conventional Culture-Dependent and Alternative Rapid Detection Methods in Retail Ready-to-Eat Foods in Turkey.

Foodborne pathogens, like Listeria monocytogenes, continue to inflict substantial financial losses on the food industry. Various methods for detecting Listeria in food have been developed and numerous studies have been conducted to compare the different methods. But, in recent years, new Listeria species have been identified, and currently the genus comprises 26 species. Therefore, it would be a more accurate approach to re-evaluate existing detection methods by considering new species. The present investigation involved the analysis of 42 ready-to-eat (RTE) foods, encompassing a variety of food categories, such as mezes, salads, dairy products, and meat products, with the aim of ascertaining the presence of Listeria. Among the traditional culture-dependent reference methods, the ISO 11290 method was preferred. The process of strain identification was conducted with the API Identification System. Furthermore, to ascertain the existence of L. monocytogenes and Listeria spp., the samples underwent additional analysis employing the VIDAS Immunoassay System, ELISA, and RT-PCR methodologies. Thus, four alternative approaches were employed in this study to compare not only the different methods used to determine Listeria while taking into account the newly identified Listeria species, but also to assess the compliance of retail RTE food items with microbiological criteria pertaining to the genus Listeria. Based on the conducted analyses, L. monocytogenes was conclusively determined to be present in one sample. The presence of Listeria spp. was detected in 30.9% of the samples, specifically in Turkish cig kofte, sliced salami, and salads.

OTP-Q encryption and Diffie-Hellman mutual authentication for e-healthcare data based on lightweight S-WBSN framework.

Protection of wireless technology-enabled e-healthcare data transfer over constrained devices of body sensor networks using lightweight security mechanisms is the demand of health sector nowadays. A new secure wireless body sensor network architecture (S-WBSN) with reduced CPU cycles and computational cost is proposed. S-WBSN uses OTP-Q (One-Time Pad-Quasi) and Diffie-Hellman key exchange algorithms for encryption and mutual authentication, respectively. To ensure mutual authentication among <WBSN, Local Processing Center (LPC)> and <WBSN, Data Server> components, the Diffie-Hellman key exchange algorithm is used. Using the S-WBSN architecture, security requirements such as mutual authentication, and privacy preservation thwarting security attacks are perfectly met comparing other security-based research works on healthcare data monitoring. The one-time pad-based quasi-group algorithm is a stream block cipher that operates on the data observed from the sensors of the WBSN. Before transmitting encrypted data, authentication is to be established. The proposed system methodology proves to be efficient and consumes fewer CPU cycles. The encryption and decryption processing times are comparatively less than the state-of-the-art approaches.

Comprehensive Evaluation Model and Methodology for Offshore Wind Farm Collection and Transmission Systems

With the gradual development of offshore wind farms toward large-scale and long-distance trends, economically efficient methods for correcting and transmitting offshore wind energy have garnered increasing attention. The rational and effective evaluation of offshore wind power collection and transmission methods has become an urgent issue. To address this, a comprehensive evaluation model for collection and transmission systems, considering factors such as network losses, lifecycle costs, and reliability, was established. This proposed model was applied to multiple sets of typical collection and transmission scenarios, utilizing an improved TOPSIS comprehensive evaluation method based on dynamic combination weighting to achieve the comprehensive optimization of collection and transmission schemes. Case studies have validated the feasibility of the comprehensive evaluation model. The results indicate that with an increase in offshore distance, the AC/DC collection and transmission system is superior to the all-AC collection and transmission system, and the all-DC collection system exhibits potential cost advantages.

A dynamic Bayesian network model for resilience assessment in blockchain-based internet of medical things with time variation

Blockchain technology and the Internet of Medical Things (IoMT) have garnered increased attention recently due to their growing application in effectively managing data security, storage, and transmission concerns within healthcare organizations. However, integrating various advancements, such as coordination, adaptivity, and automated responses, within the framework of blockchain-based IoMT has amplified its susceptibility to a range of attacks and vulnerabilities. Assessing and enhancing the resilience of blockchain-based IoMT is of utmost importance, particularly in anticipation of potential disruptions, to ensure its continuous and sustainable functionality. The stochastic nature of risks adds complexity to evaluating the resilience of blockchain-based IoMT, given that resilience in this domain may fluctuate over time. This study employs a dynamic Bayesian network (DBN) method to address the evolving characteristics of pertinent variables, capturing their temporal dependencies and demonstrating how the resilience capabilities of blockchain-based IoMT may evolve across different time intervals. Additionally, an information theory approach is adopted to mitigate uncertainty regarding the resilience performance of blockchain-based IoMT and its crucial subcomponents. This research showcases the effectiveness and adaptability of the DBN methodology in healthcare systems, offering insights for shaping appropriate and essential strategies for decision-makers to establish a highly resilient framework for blockchain-based IoMT.

Automated workflow for incorporation and evaluation of data uncertainty in ecological networks with autoLIMR

Ecosystems are often modelled as food webs or ecological networks, which map energy flows between species or functional groups. While there are multiple sources of uncertainty in ecological network models, a fundamental difficulty is quantifying the uncertainty of flow magnitudes, even if derived from field data, limiting the degree to which the model captures the inherent uncertainty of the empirical system. Popular techniques of incorporating data uncertainties of flow magnitudes in ecological network models are calculating multiple plausible representations of the food web within data constraints using linear inverse modelling and Markov Chain Monte Carlo (LIM-MCMC) methods. Hurdles in this process include coding input files for data-intense networks and evaluating the quality of the multiple plausible representations. To address these, we present the R package autoLIMR: an open-source automated workflow using LIM-MCMC to incorporate and evaluate data uncertainty in ecological network models. The main objectives are to improve the accessibility of LIM-MCMC, reduce errors, and provide a consistent framework to enhance model output reporting and reproducibility. We display autoLIMR on a small food web time series example and provide guidelines to facilitate the uptake of this robust methodology in the broader ecological systems sciences.

Building A Model in Collaborative Approach: IDSurvey's Role as a Corporate Decarbonization Consultant

Carbon trading and carbon markets are critical mechanisms in global efforts to address the impacts of climate change by reducing greenhouse gas emissions. These initiatives incentivize businesses and countries to limit carbon dioxide (CO2) and other greenhouse gas emissions. This study analyzes the role of IDSurvey as a company that provides decarbonization technical assistance or decarbonization consultants. Using Soft Systems Methodology (SSM), this study examines IDSurvey's collaborative innovation in building the company's capacity to reduce greenhouse gas emissions towards the Net Zero Emissions (NZE) 2060 target. The research illustrates the innovation cycle in the public sector, highlighting idea generation, selection, implementation, and dissemination as critical stages in driving collaborative solutions for mitigation towards NZE. The results show that IDSurvey has a strategic role and position as a consulting company to help corporations benefit from carbon pricing by going through essential stages until the realization of emission reductions and the potential added value that can be obtained from carbon trading through the Carbon Exchange. Carbon pricing is a practice of the "polluters-pay-principle," so anyone who emits carbon emissions must pay compensation for the pollution released, especially for industries or businesses. This article highlights the importance of a systemic and collaborative approach to decarbonization, which places IDSurvey in a critical and global context.