Systems Development Research Articles

Functional characterization of BbEaf6, a homolog of Eaf6 in Beauveria bassiana: Implications for fungal virulence and stress response

ABSTRACT The Eaf6 protein, a conserved component of the NuA4 and NuA3 complexes in yeast and MOZ/MORF complexes in humans, plays crucial roles in transcriptional activation, gene regulation, and cell cycle control. Despite its significance in other organisms, the functional role of Eaf6 in entomopathogenic fungi (EPF) remained unexplored. Here, we investigate the function of BbEaf6, the Eaf6 homolog in the entomopathogenic fungus Beauveria bassiana. We demonstrate that BbEaf6 is predominantly localized in nuclei, similar to its counterpart in other fungi. Deletion of BbEaf6 resulted in delayed conidiation, reduced conidial yield, and altered conidial properties. Transcriptomic analysis revealed dysregulation of genes involved in asexual development and cell cycle progression in the ΔBbEaf6 mutant. Furthermore, the ΔBbEaf6 mutant exhibited decreased tolerance to various stresses, including ionic stress, cell wall perturbation, and DNA damage stress. Notably, the ΔBbEaf6 mutant displayed attenuated virulence in insect bioassays, accompanied by dysregulation of genes associated with cuticle penetration and haemocoel infection. Overall, our study elucidates the multifaceted role of BbEaf6 in stress response, development, and virulence in B. bassiana, providing valuable insights into the molecular mechanisms governing fungal pathogenesis and potential targets for pest management strategies.

Green building progress assessment: analysis of registered and certified buildings for LEED rating system

Green buildings are of great importance to overcome climate change effects and the depletion of natural resources. This paper aims to provide a review of the progress in green building constructions that have used the LEED (Leadership in Energy and Environmental Design) rating system for the last two decades. To do this the researchers have analyzed the data of around 61000 LEED-registered buildings (from the U.S. Green Building Council (USGBC) website) Using Google data analysis module studying different factors affecting green building growth and trying to spot any possible correlation between LEED and each factor. The review will provide the researchers and the construction industry with the necessary information about the analysis of green building development. The results showed the trends in the green building progress and provided insight analysis for the reasons behind this progress which can help rating system developers, green building designers, and governmental decision-makers, to promote green building worldwide.

A Review on FPGA-based Architectures for Noise Removal of Digital Images using High-Level Design

Image corruption during the acquisition and transmission operations may be caused by a variety of disturbances. Scientists are still having trouble getting rid of the noise in the original picture. picture denoising is a technique used to improve a picture's visual quality and extract small details from a damaged image. Improving an image to make it crisper than it was originally is the aim of image restoration. The field of image processing is vast. This paper presents the results of some significant work in the subject of image denoising. It looks into image denoising using some of the most recent methods, such as SEPD (Simple Edge Preserved De-noising) and RSEPD (Reduced Simple Edge Preserved De- noising).Image corruption during the acquisition and transmission operations may be caused by a variety of disturbances. Scientists are still having trouble getting rid of the noise in the original picture. picture denoising is a technique used to improve a picture's visual quality and extract small details from a damaged image. Improving an image to make it crisper than it was originally is the aim of image restoration. The field of image processing is vast. This paper presents the results of some significant work in the subject of image denoising. It looks into image denoising using some of the most recent methods, such as SEPD (Simple Edge Preserved De-noising) and RSEPD (Reduced Simple Edge Preserved De- noising). Keywords— Power consumption analysis, Digital logic circuits, Ultra-low power, Subthreshold operation, Static CMOS gates

Predicting hospital length of stay using machine learning on a large open health dataset

BackgroundGovernments worldwide are facing growing pressure to increase transparency, as citizens demand greater insight into decision-making processes and public spending. An example is the release of open healthcare data to researchers, as healthcare is one of the top economic sectors. Significant information systems development and computational experimentation are required to extract meaning and value from these datasets. We use a large open health dataset provided by the New York State Statewide Planning and Research Cooperative System (SPARCS) containing 2.3 million de-identified patient records. One of the fields in these records is a patient’s length of stay (LoS) in a hospital, which is crucial in estimating healthcare costs and planning hospital capacity for future needs. Hence it would be very beneficial for hospitals to be able to predict the LoS early. The area of machine learning offers a potential solution, which is the focus of the current paper.MethodsWe investigated multiple machine learning techniques including feature engineering, regression, and classification trees to predict the length of stay (LoS) of all the hospital procedures currently available in the dataset. Whereas many researchers focus on LoS prediction for a specific disease, a unique feature of our model is its ability to simultaneously handle 285 diagnosis codes from the Clinical Classification System (CCS). We focused on the interpretability and explainability of input features and the resulting models. We developed separate models for newborns and non-newborns.ResultsThe study yields promising results, demonstrating the effectiveness of machine learning in predicting LoS. The best R2 scores achieved are noteworthy: 0.82 for newborns using linear regression and 0.43 for non-newborns using catboost regression. Focusing on cardiovascular disease refines the predictive capability, achieving an improved R2 score of 0.62. The models not only demonstrate high performance but also provide understandable insights. For instance, birth-weight is employed for predicting LoS in newborns, while diagnostic-related group classification proves valuable for non-newborns.ConclusionOur study showcases the practical utility of machine learning models in predicting LoS during patient admittance. The emphasis on interpretability ensures that the models can be easily comprehended and replicated by other researchers. Healthcare stakeholders, including providers, administrators, and patients, stand to benefit significantly. The findings offer valuable insights for cost estimation and capacity planning, contributing to the overall enhancement of healthcare management and delivery.

Usability of PPGIS tools exemplified by geodiscussion – a tool for public participation in shaping public space

Abstract The article explores the usability of the geodiscussion administrative panel, an online tool aiding Public Participation Geographic Information Systems. This tool was specifically designed and developed for distribution in a Software as a service model, offering geodiscussion users the flexibility to leverage the tool without the need for substantial investments in expensive infrastructure or complex deployments. The research primarily centers on the geodiscussion administrative panel, a key component empowering organizers of public consultations in spatial planning to efficiently create and manage consultation processes. In contrast to previous studies that focused on the usability for consultation participants, this research uniquely targets individuals responsible for organizing and overseeing the consultation processes. A diverse array of usability research methods were employed, ranging from the creation of personas and conducting direct interviews based on test scenarios to non-invasive methods for recording user activities. The study involved 682 participants who had prior experience with public consultations across various public administration units and representatives from consulting firms. Given that the usability studies were an integral part of the geodiscussion administrative panel’s development process, the research team has the opportunity to influence the further implementation of the applied functionalities. This implies that insights gained from the research can actively shape and enhance the tool’s features as it progresses in its development cycle.

Financial Development, Monetary Policy, and the Monetary Transmission Mechanism—An Asymmetric ARDL Analysis

This paper’s objective is to examine the asymmetric cointegration and asymmetric effects of financial development and monetary policy on monetary transmission mechanisms in the Nigerian context using annual data spanning the period from 1986 to 2023. This study pushes the frontiers of knowledge by providing information on the nonlinear impacts of monetary policy and financial sector innovations on monetary transmission mechanisms in Nigeria to help policymakers tailor their strategies to local conditions, enhancing the effectiveness of monetary interventions in the economy. To achieve this, this paper adopted nonlinear ARDL models to understand how changes in the direction of monetary policy and developments in the financial system induce changes in the transmission of monetary policy. The findings document the existence of asymmetries in both the short and long run, revealing that the impacts of financial development and monetary policy on the different monetary policy channels are not uniform. These asymmetries indicate that the responses of various economic variables to monetary policy actions differ depending on the level of financial development. These findings underscore the complexity of the monetary transmission mechanism and the necessity for a nuanced understanding of how financial development and monetary policy interact in different contexts. Consequently, this finding is symptomatic of some characteristics of those financial markets on their way toward advanced developments. As the financial system matures, monetary policy may have a greater impact on the cost of short-term funding for banks without having any discernible effect on the rates at which businesses and households access funding. Therefore, this paper recommends focusing on the policies that will foster the financial system across the banking sector, capital market, bond market, and overall financial sector to improve the efficiency of the monetary transmission process.

Implementation of Internal Organizational Communication in the Motor Vehicle Registration and Identification (Regident) System in the South Sulawesi Police Traffic Directorate

The purpose of this study is to analyze the implementation of organizational communication from the aspect of internal communication in the Motor Vehicle Registration and Identification (Regident) System at the South Sulawesi Regional Police Traffic Directorate. The research uses a quantitative and qualitative approach with an Explanatory Design research design. The results show that internal organizational communication plays a very important role in the context of implementing information technology for the Motor Vehicle Registration and Identification (Regident) System services at the South Sulawesi Regional Police Traffic Directorate. Here are some key points to consider: first, Coordination and Collaboration where internal organizational communication facilitates effective collaboration between various units or departments within the Traffic Directorate. Second is Information Dissemination where effective communication ensures that all staff understand the latest changes or developments in the Regident system, including the implementation of new technology or improvements made. Third is Motivation and Engagement where good communication can increase staff motivation and their engagement in achieving organizational goals, and fourth is Conflict Resolution where open and clear communication helps in addressing conflicts or disagreements among staff or departments that may arise in the management of Regident.

Enabling radical and potentially disruptive innovations through interdisciplinarity: challenges and practices in industrial companies

The motivation behind this paper and the underlying research is to shed light on how companies deal with interdisciplinary innovation activities, especially looking at the development of radical and potentially disruptive innovations. This includes the analysis of methods, processes, and organizational structures applied to support interdisciplinary innovation activities as well as challenges faced. Whereas this thematic field has been widely investigated for academic institutions and, in companies on a team level, there is only a little information on industrial companies’ current state. This understanding is especially important as shortening development cycles, and technological convergence combined with intersectoral innovations might lead to increases in radical and potentially disruptive innovations and thereby create the need for improved methods and structures throughout the innovation process. To gain insights into challenges and current practices of interdisciplinary collaboration in innovation activities, semi-structured exploratory interviews were carried out with representatives from seven industrial companies. Among others, the results of the study revealed that whereas many methodologies are said to support interdisciplinary innovation activities, a wide majority of these methodologies are applied for other reasons which make supporting interdisciplinarity seem like a kind of byproduct.

Development of motion control function library based on PLCopen specification

The motion control library is a standard set of functional blocks integrated in a programmable integration environment, which is of great significance for the rapid development of reconfigurable Programmable Automation Controllers (PAC). However, due to the encapsulation and concealment of function blocks and the incompatibility between software and hardware, the development efficiency of function blocks is low, which is not conducive to the development of autonomous, controllable PAC. Aiming at the above problems, the methods of function block opening and key technology are studied, and a kind of motion control function library architecture and rapid development method based on the PLCopen specification are proposed. A series of motion control function libraries are developed on domestic PLC software. An experimental platform based on domestic hardware and software was designed to verify the typical motion control function library. Experimental results show that this method can effectively shorten the development cycle and that the developed motion control module can meet the actual control needs.

Reinterpreting the Nursing Record for an Electronic Context: Development Principles.

The full potential for electronic health record systems in facilitating a positive transformation in care, with improvements in quality and safety, has yet to be realised. There remains a need to reconceptualise the structure, content and use of the nursing component of electronic health record systems. The aim of this study was to engage and involve a diverse group of stakeholders, including nurses and electronic health record system developers, in exploring together both issues and possible new approaches to documentation that better fit with practice, and that facilitate the optimal use of recorded data. Three focus groups were held in the UK and USA, using a semi-structured interview guide, and a common reflexive approach to analysis. The findings were synthesised into themes that were further developed into a set of development principles that might be used to inform a novel electronic health record system specification to support nursing practice.

Investigation of the influence of the number of poles on the external characteristic of a brushless DC machine in the generator mode

The article presents the results of a study on the generator mode of operation of a brushless DC machine (BLDC) when operating under active load. For analysis, two models were created with the number of permanent magnets on the rotor differing by a factor of two. The relevance of the research is due to the wide range of applications of BLDC in various fields. One of the key advantages of BLDC is the absence of a brush-commutator unit, which is replaced by a controller with semiconductor elements. This increases the reliability of BLDC and expands the range of operating modes. The main objective of this study is to determine the impact of the number of permanent magnets on the external characteristic of BLDC in generator mode. To achieve this goal, computer modeling was performed using ANSYS Maxwell software. This software is designed to study and calculate the magnetic field pattern using the finite element method in electromechanical devices, providing accurate results for analysis. For each BLDC model, the degree of saturation of the magnetic system elements was determined, and graphs of voltage, current, and braking torque at the generator shaft over time were obtained. Analysis of the calculation results for BLDC models with 46 and 92 permanent magnets demonstrated an impact on the voltage and current waveforms, leading to some slight distortion of their shape. The obtained calculation results allowed determining the efficiency and constructing the external characteristic for both BLDC models. Higher efficiency was obtained for the BLDC model with 92 permanent magnets on the rotor. The external characteristic for the generator mode of BLDC operation demonstrated a change in voltage when transitioning from idle to nominal current operation within the range of 15% and 21%, indicating the stiffness of the characteristic. The conclusions of the study indicate the potential for improving the efficiency of BLDC through optimization of the magnetic system design and cooling conditions, and can be useful for engineers and developers of electromechanical systems aiming to improve the performance of their products.

Strategies of the countries’ innovative activity in development of intelligent systems

Development of intelligent systems based on artificial intelligence in the area of research and development of technical systems is a new competitive advantage and a growth driver for a country. The authors of the article present the indicators of innovative activity of the countries in development of intelligent systems: the share of the country’s patents in the number of patents for all countries, the number of national strategies in the area of intelligent systems in the country, the geography of implementation of the intelligent systems developed by a country. The authors introduce a term of “index of a country specialization in the sphere of intelligent technology”. Index of specialization is a correlation of factual number of types of patents registered in the country in the sphere of intelligent technology to 10 potentially possible types of patents. These include the patents on advanced manufacturing technologies, robotics, advanced materials, artificial intelligence, big data, the Internet of things, mobility, photonics, security, and digital twins. Using a cluster method, the authors classify 43 countries by the level of innovative activity in the sphere of development of intelligent systems, on the basis of the data provided by the World Intellectual Property Organization and the European Commission in 2023. This allowed developing a classification of 11 strategies of innovative activity in the sphere of development of intelligent systems (based on the scoring assessment). The proposed strategy classification makes it possible to perform benchmarking to study the country’s experience and evaluate the investment risks for the projects in development of intelligent systems.

Estimating the Monkman−Grant relation in the presence of errors in measurement of times to failure and minimum creep rates: with application to some high temperature materials

ABSTRACT The Monkman−Grant relation has the potential to reduce the development cycle for new materials, as it provides a means of lifting based on minimum creep rates that are typically observed early on. This paper outlines problems in estimating the nature of this relation using the least squares technique that stems from errors made in measuring failure times and minimum creep rates. The paper outlines some solutions to this problem that have been proposed within the scientific literature – such as reverse regression and the Deming regression. The evidence from the materials studied in this paper, suggest that the use of least squares results in overly conservative lifetime predictions when using the Monkman-Grant relation. It was found that for 2.25Cr-1Mo steel, the life expected for a minimum creep rate of 3.67E-12s−1 was 57 years when the least squares technique was used, but this increased to 78 years when using the Deming regression.

Community Service on Implementing Learning Media as Support Technology for Neurodivergent Children Community in Surabaya

Neurodivergent children may present with conditions such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), dyslexia, or other learning differences. These children often face challenges in communication, social interaction, and academic performance, necessitating tailored support within educational settings. This community service program partners with ELMO, a community for neurodivergent children. The program's goals are twofold: to develop assistive learning media in the form of eLearning modules, and to facilitate technology transfer to ensure its sustainability. The Asset Based Community Development (ABCD) technique guides the program's methodology. Information gathering utilizes questionnaires and focus group discussions to tailor the program to the specific needs of neurodivergent students. The results have demonstrated a positive impact, satisfying both our partner organization and the parents of neurodivergent children who can now track their children's progress more effectively. The positive impact on learning and parental tracking highlights the potential of such collaborations to improve educational equity for neurodivergent students. Future efforts can focus on expanding the modules and promoting wider adoption to reach more children

Agent-based social skills training systems: the ARTES architecture, interaction characteristics, learning theories and future outlooks

ABSTRACT Agent-based training systems can enhance people's social skills. The effective development of these systems needs a comprehensive architecture that outlines their components and relationships. Such an architecture can pinpoint improvement areas and future outlooks. This paper presents ARTES: a general architecture illustrating how components of agent-based social training systems work together. We studied existing systems and architectures for training and tutoring to design ARTES and identify its essential components and interaction characteristics. ARTES comprises two core components: the agent simulation of social situations, and educational elements to provide guided learning. We link ARTES's crucial components to four primary learning theories (behaviourism, cognitivism, social cognitive theory, and constructivism) to illustrate the role of agent simulation and tutoring elements in establishing desired learning outcomes. Furthermore, we map ARTES's components against eight architectures, 43 systems and three tools to indicate the components' relevance, completeness, generalisation, and deployment potential across contexts. In addition to ARTES, the paper also contributes by identifying future improvements and research directions, such as the agent's thinking, tutoring methods, knowledge transfer, and ethical implications. We believe ARTES can help bridge the gap between virtual human simulations and impactful educational learning, offering training system developers desirable features like understandability and adaptability.

SISTEM PENDUKUNG KEPUTUSAN REKOMENDASI PENGEMBANGAN KARIR DAN PROMOSI JABATAN STRUKTURAL MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING (SAW)

One of the authorities possessed by The Employment Agency Education and Training of Tegal District is Career Development and Promotion Activity. There are many obstacles in carrying out this activity, such as the large number of employee data and the data processsing is still manual, resulting a complex decision-making process and takes a lot of time. In addition, the formulation used is still not suitable with the mandate of PP Number 17 of 2020 concerning the merit system approach to ASN management. The merit system is an ASN policy and management based on qualifcations, copetence, and performance. In this study, the authors create a support system (SPK) with The Simple Additive Weighting SAW method which will facilitate and save time in providing ASN nomination and reccomendation in the career development and promotion process.This research method applies the Research and Development (R&D) method. This method choosen because it is compatible with the software development cycle or SDLC waterfall.

Evaluation of the Arthur Project: Evidence-Based Mentoring in a Social Work Framework with a Social Justice Approach

Low-income students from underrepresented communities experience significant educational inequalities, including chronic absenteeism, mental health crises, trauma exposure, and social injustices. These conditions escalate risks of dropping out and justice system involvement. Middle-school youth must navigate intense social and emotional change. To address such challenges, The Arthur Project (TAP) provides intensive, in-school, therapeutic mentoring and family support. The program teaches students essential life skills, such as problem-solving, communication, and academic engagement. Students are empowered to strengthen their resilience, perseverance, self-actualization, and confidence. TAP provides up to 500 h of therapeutic mentoring yearly over three years, delivered individually and in small groups by social work interns. The research question was as follows: Does structured, intensive in-school therapeutic mentoring with social work interns increase the socioemotional, cognitive, noncognitive, and academic skills and engagement of underserved middle-school students? This evaluation for the school year 2022–2023 is based on the program of 200 students and 30 mentors, with quantitative mentee, mentor, teacher, and caregiver surveys and qualitative interview data. The program and evaluation methodology are described, with results and conclusions. Students showed significant improvement in all domains; mentors reported student increases in confidence, perseverance, problem-solving, and communication; and teachers and caregivers reported students’ increased academic engagement. The Arthur Project program can become a national middle-school mentoring model to address widespread student inequalities.

Advancements in project management methodologies: Integrating agile and waterfall approaches for optimal outcomes

Advancements in project management methodologies have revolutionized the way organizations execute complex projects, aiming for optimal outcomes amidst evolving challenges and dynamic environments. This paper explores the integration of Agile and Waterfall approaches as a strategic response to enhance project effectiveness and efficiency. Traditionally, Waterfall methodology has been predominant in industries requiring structured planning and predictable outcomes. Its sequential phases—requirements gathering, design, implementation, testing, and deployment—ensure a methodical progression from initiation to completion. However, its rigidity in accommodating changes during the project lifecycle has been a notable limitation in fast-paced industries where flexibility and rapid adaptation are paramount. In contrast, Agile methodology emerged as a transformative alternative, particularly suited for projects with uncertain or evolving requirements. Agile emphasizes iterative development cycles, continuous stakeholder engagement, and adaptive planning. These principles enable teams to respond swiftly to changes, deliver incremental value, and maintain high levels of transparency and collaboration throughout the project. Recognizing the strengths of both methodologies, practitioners have increasingly advocated for their integration—a hybrid approach that harnesses the structured planning of Waterfall with the adaptive flexibility of Agile. This integration allows organizations to capitalize on Waterfall's clarity in project scope and deliverables while leveraging Agile's responsiveness to customer feedback and evolving market demands. Key challenges in integrating these methodologies include reconciling differences in project planning, managing stakeholder expectations across iterative cycles, and aligning team dynamics to embrace a blended approach. Effective integration strategies often involve clear delineation of phases suitable for Waterfall and Agile, fostering a culture of collaboration and continuous improvement, and utilizing project management tools that support hybrid methodologies. Successful case studies illustrate the benefits of this integrated approach, including accelerated time-to-market, improved product quality, enhanced stakeholder satisfaction, and optimized resource allocation. Moreover, organizations that adopt hybrid methodologies demonstrate resilience in navigating uncertainties and complexities, positioning themselves competitively in dynamic markets. In conclusion, the integration of Agile and Waterfall methodologies represents a paradigm shift in project management, offering a holistic framework that balances structured planning with adaptive execution. As industries continue to evolve, embracing hybrid approaches promises to drive innovation, improve project outcomes, and sustain long-term organizational success. Keywords: Advancement, Project Management, Methodologies, Integrating Agile, Waterfall Approaches.

Optimization and evaluation of modified release solid dosage forms using artificial neural network

This study aims to optimize and evaluate drug release kinetics of Modified-Release (MR) solid dosage form of Quetiapine Fumarate MR tablets by using the Artificial Neural Networks (ANNs). In training the neural network, the drug contents of Quetiapine Fumarate MR tablet such as Sodium Citrate, Eudragit® L100 55, Eudragit® L30 D55, Lactose Monohydrate, Dicalcium Phosphate (DCP), and Glyceryl Behenate were used as variable input data and Drug Substance Quetiapine Fumarate, Triethyl Citrate, and Magnesium Stearate were used as constant input data for the formulation of the tablet. The in-vitro dissolution profiles of Quetiapine Fumarate MR tablets at ten different time points were used as a target data. Several layers together build the neural network by connecting the input data with the output data via weights, these weights show importance of input nodes. The training process optimises the weights of the drug product excipients to achieve the desired drug release through the simulation process in MATLAB software. The percentage drug release of predicted formulation matched with the manufactured formulation using the similarity factor (f2), which evaluates network efficiency. The ANNs have enormous potential for rapidly optimizing pharmaceutical formulations with desirable performance characteristics.

A Novel Computational Paradigm for Reconstructing Solid CAD Features from a Segmented Manifold Triangular Mesh

We introduce a novel computational paradigm for reconstructing solid computer-aided design (CAD) features from the surface of a segmented manifold triangular mesh. This paradigm addresses the challenge of capturing high-level design semantics for manifold triangular meshes and facilitates parametric and variational design capabilities. We categorize four prevalent features, namely extrusion, rotation, sweep, and loft, as generalized swept bodies driven by cross-sectional sketches and feature paths, providing a unified mathematical representation for various feature types. The numerical optimization-based approach conducts geometric processing on the segmented manifold triangular mesh patch, extracting cross-sectional sketch curves and feature paths from its surface, and then reconstructing appropriate features using the Open CASCADE kernel. We employ the personalized three-dimensional (3D) printed model as a case study. Parametric and variant designs of the 3D-printed models are achieved through feature reconstruction of the manifold triangular mesh obtained via 3D scanning.