The paper investigates the influence of different types of loads on the deformation of building structures, particularly beams, using second-order differential equations that allow modeling deformation processes. For this purpose, we considered two beam deflection equations under concentrated and distributed loads. Several experiments were conducted under different geometrical conditions (variable parameters of the beam cross-section, length, and loads). The solutions were studied using graph-analytical methods: constructing a graph of solutions reflecting the system's behaviour, a hodograph allowing tracking of additional nuances of the studied process, and amplitude and phase-frequency characteristics. The influence of conditions on the nature of system behavior is determined. The study's results can be used to optimise design solutions in construction.

This paper focuses on quantitative research with constructs such as customer characteristics, organizational influence, and project management methodologies, and how the constructs affect their relationship with the dependent variable of agile project management effectiveness. Additionally, partial least squares structural equation modeling or PLS-SEM is employed for this study as the tool to analyze data. Furthermore, 156 data samples were gathered for this study which mainly aims for APM practitioners in Indonesia. The findings of this study indicate that customer characteristics do not support APM effectiveness and the moderating variable of PM methodology between the relationship of customer characteristics and APM effectiveness is not supported. However, the results of this study can conclude that customer characteristics positively affect organizational influence. While organizational influence does positively support APM effectiveness. To improve research on APM effectiveness in Indonesia, this study contributes to laying the preliminary work for future research.

In this paper, we are presenting a numerical investigation of Duffing’s nonlinear system. The Duffing’s system is described by a nonlinear second-order differential equation, which shares he same structure like the damped and driven oscillator systems. The numerical integration of the system is done using Python scientific libraries such as NumPy and SciPy. The proposed technique is utilized to construct the bifurcation diagram and the Poincaré section and to analyze the behavior of the system by changing one parameter. This proposed method is characterized by versatility and the extrapolation of these numerical techniques and algorithms in the study of other nonlinear dynamical systems.

The relevance of introducing additive technologies of 3D printing in construction is to decrease the technological cycle of construction, and minimize expenditure and material costs, while reducing the duration of the development planning process and execution, eliminating inaccuracies and defects, as well as optimizing and automate the process. The technological aspect of 3D printing lies in the optimal selection of parameters based on the created 3D model using effective software. The purpose of the study is to determine the quality indicators of bricks obtained by 3D printing from special concrete. The approach to investigating this matter is rooted in ascertaining the compressive strength of concrete through non-invasive testing techniques, gauging the density of concrete using measurement methods, and validating the efficacy of integrating 3D printing technologies in construction by the method of comparative analysis. The effectiveness of introducing additive technologies of 3D printing was proven drawing upon quality indicators of concrete obtained on a 3D printer which meets all the requirements necessary for its implementation in the construction field. The selected characteristics of concrete compressive strength are fundamental to the basics of selecting a brand of concrete to be utilized in construction. The selected software demonstrated the capacity to generate flawless 3D designs. The result of the study shows a significant reduction in the number of workers involved in the construction process by 38–45%, depending on the chosen method of using 3D printing; a decrease of construction time by 33–42% when printing individual elements, blocks used in production, and by 61–72% when using a printer directly on the construction site; reduction of raw materials costs by 14–28%; as well as reduction of construction downtime by 25%. The results obtained indicate the need to develop and enhance progressive additive technologies for 3D printing in construction.

The present paper examines the mechanical characteristics at the boundary of the distribution of rubber matrix and metal and fabric fibrous materials as a distinct area in the crack braking mechanism, and their impact on the durability of pneumatic tires in the event of damage accumulation during operation. Experimental studies were conducted on the delamination of the components of the tire material composition in samples obtained from diverse locations of the car tire. The strength of the rubber matrix fibers of the metal cord was determined, which makes it possible to assess the overall strength of the tire material as a composition of reinforcing elements and the matrix during the accumulation of damage created artificially during operation. The method of experimental research is reasonably stable. The nature and behavior of the sample rupture during the tests were evaluated.

The purpose of this study is to chart the evolution of research papers over 24 years, as well as the trajectory of Indonesia's urban agricultural research trends and the links between scientific concepts. Data for this study were collected between 2008 and 2022 using the quantitative approach known as bibliometric analysis. The Scopus database and the word "urban farming" were used to gather data. Publish or Perish was used to collect data as metadata. The data was bibliometrically analyzed using the Vosviewer program. The findings of this research reveal that the number of urban farming-related articles indexed by Scopus has fluctuated over the previous 10 years. The Scopus database has 169 publications about Indonesia. The expansion of keyword-based urban agriculture research establishes a connection between agribusiness and social entrepreneurship as scientific notions.

WSEAS Transactions on Systems publishes original research papers relating to systems theory. We aim to bring important work to a wide international audience and therefore only publish papers of exceptional scientific value that advance our understanding of this particular area. The research presented must transcend the limits of case studies, while both experimental and theoretical studies are accepted. It is a multi-disciplinary journal and therefore its content mirrors the diverse interests and approaches of scholars involved with systems theory, dynamical systems, fuzzy systems, neural networks and related areas. We also welcome scholarly contributions from officials with government agencies, international agencies, and non-governmental organizations.

In this article, a novel optimization model that was specifically designed as a dynamic-chance-constrained fuzzy uncertain programming framework is introduced. This model serves the purpose of optimizing the efficiency of facultative ponds utilized in domestic wastewater treatment. The primary focus of this study was maximizing the amount of the wastewater treated in the facility subject to quality requirements via the assessment of wastewater quality through the measurement of Biological Oxygen Demand (BOD). The model's development was grounded in a real-world scenario, where decision-makers encountered uncertainties in various parameters, such as the rate of BOD degradation and the incoming wastewater load, both characterized by fuzzy membership functions. In light of this uncertainty, the decision-maker aimed to maximize the wastewater treatment capacity while maintaining a suitable safety margin for both objective and constraint functions, employing policies founded on probability and chance. A case study was carried out at the Bantul domestic wastewater treatment plant, situated in Yogyakarta, Indonesia. The study successfully identified optimal decisions regarding wastewater flow rates and processing times. As a result, it can be concluded that the proposed model effectively resolved the problem at hand, making it a valuable tool for decision-makers in similar contexts.

In the present internet world, accessing cloud resources for a low cost, according to their needs, is available to all users. Sharing resources is becoming increasingly necessary as people complete their activities in the cloud. It becomes essential for distributed workloads to be optimized to perform efficient workload scheduling and progressing resource utilization in a cloud environment. Scheduling cloud resources considerably benefits from the invention of machine learning and metaheuristic models to address this scenario. Though many existing algorithms are developed in cloud-based task scheduling using unsupervised clustering methods, the problem of unknown task requirements or resource availability in adverse conditions is still challenging. In this study, an uncertainty-based unsupervised technique is constructed to group incoming tasks according to the required resources, and it is scheduled to the most suitable resources more prominently. This paper introduced a Robust Neutrosophic C-Means Clustering boosted with the fish school search algorithm (RNCM-FSSA) for clustering the incoming tasks and the resources based on their requirement and availability. With the degree of indeterminacy, neutrosophic C-means discriminating the deterministic and indeterministic schemes and scheduling them to the optimal resources more effectively. Using the fitness value computed by FFSA, the potential cluster centroids are utilized for clustering, thus avoiding the early convergence in the grouping process. The simulation results explore that the robustness of the proposed RCNM-SSA achieves better resource utilization, the degree of imbalance is minimal, and computation complexity is also considerably decreased compared with other unsupervised models.

As a compound fault of bearing is characterized by complexity, disproportion, and interaction, its fault diagnostic accuracy tends to decline sharply. To solve this problem, the present study proposes a transient fault-signal extraction scheme for bearing compound fault intelligent diagnosis. First, the single fault vibration and compound fault vibration signals are transformed into the time-frequency domain by wavelet transform. Then, according to the normal condition signal, the transient fault signal of the single signal and compound signal is extracted through the positive k sigma principle. Next, the single fault signal symptom parameters are calculated to build the fault diagnostic model. Thereafter, the symptom parameters of the extracted compound fault transient signal are brought into the diagnostic model to obtain the model output result. Finally, according to the developed fault diagnosis discrimination criterion, the method can diagnose the compound fault successfully. The effectiveness of the proposed method is validated by bearing fault vibration signals under various conditions. The results show that the diagnostic method has superior performance in intelligently diagnosing the bearing compound fault.