Search Results (22)

The advancement of digital technologies has fostered distinctive behaviour patterns and cultural phenomena in online environments. As digital natives, Chinese Generation Z has gradually developed digital hoarding behaviour under the dual influence of technological convenience and emerging social pressures. Such behaviour functions as a coping mechanism for managing both real-world competitive anxieties and emotional uncertainties. Drawing on in-depth interviews with 35 Generation Z participants, this study employs fuzzy-set qualitative comparative analysis (fsQCA) to systematically examine the influence mechanisms of six antecedent conditions—media dependency, perceived usefulness, perceived ease of use, uncertainty avoidance, emotional attachment, and deletion barriers—on attitudes toward digital hoarding behaviour. The findings reveal two core configurational paths leading to high acceptance of digital hoarding: the first represents strategic knowledge accumulation pursued under the pressures of involution, where digital hoarding becomes a means of seeking competitive advantage; the second reflects a retreat into the digital sphere, where hoarding practices provide emotional security amid experiences of offline relational alienation. This study thus contributes a theoretical lens that moves beyond technological rationality toward social adaptation, explicating the intertwined emotional, psychological, and social drivers of digital hoarding. It also provides empirical insights for the design of supportive digital infrastructures and health education initiatives aimed at enhancing youth digital well-being. Full article

In this paper, we aim to investigate a type of lattice-valued fuzzy metric within the framework of L-topology. Firstly, we present a comprehensive construction theorem for this type of metric, utilizing the concept of L-quasi metric. Secondly, we provide an equivalent characterization through the use of C-nbd clusters, which are formed from all $B_r$: one of four types of basic spheres defined herein. Thirdly, recognizing that these four types of basic spheres serve as essential tools for characterizing various metrics, we meticulously examine the relationships among them and outline a series of topological properties associated with these metrics, which include their opening and closing characteristics, symmetrical property, and more. Finally, in addressing the corresponding symmetry problem between two types of basic spheres, namely $B_r\left(a\right)$ and $Q_r\left(a\right)$, we introduce a novel fuzzy p-metric and demonstrate tht the L-real line $\mathbf{R}\left(L\right)$ satisfies this fuzzy p-metric. Full article

In this study, a hybrid heading control framework for unmanned surface vehicles (USVs) is proposed, combining variable domain fuzzy Proportional–Integral–Derivative (VUF-PID) with an improved algorithmic Beetle Antennae Search–Particle Swarm Optimization–Simulated Annealing (BAS-PSO-SA) optimization to address the multi-objective control challenge. Key innovations include a self-tuning VUF mechanism that improves disturbance rejection by 42%, a weighted adaptive optimization strategy that reduces parameter tuning iterations by 37%, and an asymmetric learning factor that balances global exploration and local refinement. Benchmarks using Rastrigin, Griewank, and Sphere functions show superior convergence and 68% stability improvement. Ocean heading simulations of a 7.02 m unmanned surface vehicle (USV) using the Nomoto model show a 91.7% reduction in stabilization time, a 0.9% reduction in overshoot, and a 30% reduction in optimization iterations. The experimental validation under wind and wave disturbances shows that the heading deviation is less than 0.0392°, meeting the IMO MSC.1/Circ.1580 standard, and an 89.5% improvement in energy efficiency. Although the processing time is 12.7% longer compared to the GRO approach, this framework lays a solid foundation for ship autonomy systems, and future enhancements will focus on MPC-based time delay compensation and Field-Programmable Gate Array (FPGA) acceleration. Full article

Our research is dedicated to developing sustainable business models (SBMs). In this study, we review numerous empirical articles, reviews, and papers on SBMs, including 17,412 SCIE articles and 17,237 SSCI papers, published between 2009 and 2023. Our research provides guidance on how to achieve and maintain sustainability. We identify the most effective practices for conceptualizing an SBM. Our citations of over 130 articles highlight the importance of integrating corporate actions and consequences across the environmental, societal, and economic spheres, while also considering stakeholder engagement and long-term perspectives. We also emphasize the need to move beyond the traditional dichotomous treatment of SBMs and reflect more contemporary practices. To provide a more practical explanation, we use fuzzy set qualitative comparative analysis to predict the future evolution of SBMs from a corporate responsibility perspective, drawing on the lessons of the China phenomenon. This approach clarifies how the theoretical and practical elements obtained from the literature correspond with the new SBMs. Full article

This paper presents a comprehensive evaluation of a new control technique for the sphere motor system, aimed at achieving accurate tracking, robust and dispersion of vibrations. Control methods include the determination of a nonlinear model and the application of feedback linearization, followed by the optimization of the proportional derivative (PD) coefficients through the Adaptive Neuro-Fuzzy Inference System. In addition, the system’s reaction to harsh environments is managed using Long Short-Term Memory. In order to gain a deeper understanding, symmetrical environmental disturbances and trajectories are introduced during the testing phase. The results demonstrate the superior performance of the control strategy, with reduced vibrations, faster recovery and confirmed tracking accuracy. In addition, the control method shows its adaptability and reliability, as evidenced by the significant reduction in CO₂ emissions compared to conventional PD control methods. The use of symmetric trajectories and visualizations further emphasizes the behavior of the system under symmetric conditions, strengthening the effectiveness and applicability of the control strategy in real-world scenarios. Overall, this study presents a promising solution for converting complex systems under different conditions and making them potentially applicable in various industrial contexts. Full article

In the Small Island Developing States (SIDS), public sector infrastructure projects (PSIPs) fail to both meet targeted performance metrics and deliver on the intended benefits to society. In terms of the cost performance metric, cost overruns (COs) beyond the initial contract value are more of a norm than a unique occurrence. Therefore, to ensure economic sustainability for SIDS, and value for money on PSIPs, there is a need to investigate and evaluate the risk impacts on COs. The purpose of this research was to identify and evaluate the perceived cost overrun risk factors that are within the primary project stakeholders’ sphere of control, and to reduce the ongoing ambiguities that exist in the prioritization of these risks. This was achieved by extracting critical risk factors from selected comparative studies in developing countries to formulate a closed-ended questionnaire to be administered to construction professionals in Trinidad and Tobago. Thereafter, the process of fuzzy synthetic evaluation (FSE) was used to develop a risk model based on three tiers of risks: 11 critical risk factors, 3 critical risk groupings (CRGs) and an overall risk level (ORL). The results showed that the two highest-ranked critical risks were project funding problems and variations by client. The leading critical risk grouping was client-related risk (5.370), followed by professional-related risk (4.815) and physical risk (4.870). The ORL was 5.068. Based on the FSE’s linguistic scaling, the CRGs and the ORL are perceived to be high risks in PSIPs. This research adds to the CO body of knowledge in primarily three ways. Firstly, the study extends the comparative assessment previously undertaken in scholarship into the context of SIDS to build on the generalizability of this context-specific phenomenon. Secondly, the FSE evaluation undertaken provides a practical tool to be promoted for use in SIDS’ construction industry among practitioners to focus and prioritize the critical risks in the planning phases and improve on contemporary risk practices in the execution phases of projects. Finally, this quantitative model approach is recommended to supplement the traditional qualitative risk management practices adopted in SIDS, thus contributing towards the overall improved economic sustainability and viability of PSIPs. Full article

With the rapid development of Moon exploration, the concept of establishing Moon-based station for Earth observation (MBSEO) has received more and more attention. Compared with the space-borne Earth observation method, the MBSEO can observe Earth with advantages of higher stability, longer period, wider range, better integrity, and consistency. The MBSEO can not only cover the entire Earth disc, but also has good observation of the target area (TA) whose radius is several times that of the Earth radius (e.g., plasma-sphere/magnetosphere). Basically, site selection is a prerequisite for MBSEO. In this paper, the time coverage of TA (TCTA), e.g., the whole Earth disc or Earth-related plasma-sphere and magnetosphere, and the time coverage of sunlight (TCS) without topography are briefly presented to show their distribution. However, the unevenly distributed craters on the near side make TCTA and TCS badly affected by complicated topography, thereby causing those sites with a high selection possibility of a single factor to not necessarily be suitable for other factors. For example, potential sites at the low-middle latitude on the near side might have better TCTA and flat topography, but its TCS might be terrible for MBSEO. In order to evaluate the above factors comprehensively, a multi-factor fuzzy evaluation (MFE) method based on a multiple-input single-output (MISO) model will be utilized in the period of 18.6 nutation years. By using the proposed evaluation method, the sites near the dividing line, e.g., Amundsen, can still have the absolute possibility of exceeding 0.6, which was selected as MBSEO in low acceptability of sunlight. A similar situation exists in other areas with weaker sunlight constraint, e.g., Malapert A, in the case that the absolute selection possibility of areas becomes closer if more sunlight is tolerable. The results indicate that the areas with low thermal environment for radiation protection and relatively flat topography will have more possibility to be selected, and those potential sites unevenly distributed in craters can still be picked out through our proposed method. Full article

This paper presents a fuzzy quality certification of wheat. This analysis is based on the fuzzy analysis model of wheat. We developed a Matlab application with the help of which we modeled the perceptions in relation to the main quality physical and chemical characteristics of wheat obtaining a quality index of wheat lots. The algorithm presented in this article allows for obtaining and using the global quality index, generating applicability not only to the commercial sphere as a quality reference and price setting, but also a measure of appreciation of processing opportunities. Indices of fuzzy quality associated with wheat lots using a fuzzy model offer the opportunity to develop local markets through quality certification. Full article

Over the last couple of decades, there have been direct and indirect evidences for massive compact objects than their conventional counterparts. A couple of such examples are super-Chandrasekhar white dwarfs and massive neutron stars. The observations of more than a dozen peculiar over-luminous type Ia supernovae predict their origins from super-Chandrasekhar white dwarf progenitors. On the other hand, recent gravitational wave detection and some pulsar observations provide arguments for massive neutron stars, lying in the famous mass-gap between lowest astrophysical black hole and conventional highest neutron star masses. We show that the idea of a squashed fuzzy sphere, which brings in noncommutative geometry, can self-consistently explain either of the massive objects as if they are actually fuzzy or squashed fuzzy spheres. Noncommutative geometry is a branch of quantum gravity. If the above proposal is correct, it will provide observational evidences for noncommutativity. Full article

The rapid development of the process of informatization of modern society has necessitated cybersecurity in all spheres of human activity, as the implementation of deliberate or unintentional influences on the information sphere by both external and internal sources can damage security and lead to moral, material, financial, reputational and other forms of damage. The purpose of the paper is to create functional cognitive models to assess the level of their protection. The method of building a fuzzy cognitive map of the state of cybersecurity of banks is used. There have been developed cognitive models to determine the level of protection of the computer network, information security system and critical infrastructure (banks). Scenarios have been developed that reflect the response of the system at the complex maximum attenuation of the impact of the most important cyber threats. In conclusion, the practical implementation of the method provides an opportunity to predict the state of cybersecurity of banks, and contributes to the implementation of the necessary mechanisms to prevent, protect and control access at the appropriate levels of network infrastructure. Full article

The quality of output or decision-making depends on high-quality input data, their adequate evaluation, the application of adequate approaches, and accurate calculation. In this paper, an objective criticism of applying the fuzzy SWARA (step-wise weight assessment ratio analysis) method based on the Chang TFN (triangular fuzzy number) scale is performed. Through research, it has been noticed that a large number of studies use this approach and, as an epilogue, there are wrong decisions based on inconsistent values in relation to the initial assessment of decision-makers (DMs). Seven representative studies (logistics, construction industry, financial performance management, and supply chain) with different parameter structures and decision matrix sizes have been singled out. The main hypothesis has been set, which implies that the application of this approach leads to wrong decisions because the weight values of the criteria are incorrect. A comparative analysis with the improved fuzzy SWARA (IMF SWARA) method has been created and a number of negative conclusions has been reached on using the fuzzy SWARA method and the Chang scale: Primarily, that using such an approach is impossible for two or more criteria to have equal value, that allocating TFN (1,1,1) leads to criteria values that are inconsistent with expert evaluation, that the last-ranked criteria in the fuzzy SWARA method have no influential value on the ranking of alternatives, that there is a great gap between the most significant and last-ranked criteria, and that the most significant criterion has a huge impact on the evaluation of alternative solutions and decision making. As a general conclusion, it is given that this approach is not adequate for application in problems of multi-criteria decision making because it produces inadequate management of processes and activities in various spheres. Full article

Real-time systems are widely used in industry, including technological process control systems, industrial automation systems, SCADA systems, testing, and measuring equipment, and robotics. The efficiency of executing an intelligent robot’s mission in many cases depends on the properties of the robot’s sensor and control systems in providing the trajectory planning, recognition of the manipulated objects, adaptation of the desired clamping force of the gripper, obstacle avoidance, and so on. This paper provides an analysis of the approaches and methods for real-time sensor and control information processing with the application of machine learning, as well as successful cases of machine learning application in the synthesis of a robot’s sensor and control systems. Among the robotic systems under investigation are (a) adaptive robots with slip displacement sensors and fuzzy logic implementation for sensor data processing, (b) magnetically controlled mobile robots for moving on inclined and ceiling surfaces with neuro-fuzzy observers and neuro controllers, and (c) robots that are functioning in unknown environments with the prediction of the control system state using statistical learning theory. All obtained results concern the main elements of the two-component robotic system with the mobile robot and adaptive manipulation robot on a fixed base for executing complex missions in non-stationary or uncertain conditions. The design and software implementation stage involves the creation of a structural diagram and description of the selected technologies, training a neural network for recognition and classification of geometric objects, and software implementation of control system components. The Swift programming language is used for the control system design and the CreateML framework is used for creating a neural network. Among the main results are: (a) expanding the capabilities of the intelligent control system by increasing the number of classes for recognition from three (cube, cylinder, and sphere) to five (cube, cylinder, sphere, pyramid, and cone); (b) increasing the validation accuracy (to 100%) for recognition of five different classes using CreateML (YOLOv2 architecture); (c) increasing the training accuracy (to 98.02%) and testing accuracy (to 98.0%) for recognition of five different classes using Torch library (ResNet34 architecture) in less time and number of epochs compared with Create ML (YOLOv2 architecture); (d) increasing the training accuracy (to 99.75%) and testing accuracy (to 99.2%) for recognition of five different classes using Torch library (ResNet34 architecture) and fine-tuning technology; and (e) analyzing the effect of dataset size impact on recognition accuracy with ResNet34 architecture and fine-tuning technology. The results can help to choose efficient (a) design approaches for control robotic devices, (b) machine-learning methods for performing pattern recognition and classification, and (c) computer technologies for designing control systems and simulating robotic devices. Full article

Globally, the pandemic of COVID-19 has penetrated all spheres of human endeavors, and noteworthy is the tremendous increase in the volume of healthcare wastes generated in Nigeria. There has been an increase in medical waste materials produced as a result of the extensive use of both disposable personal protective equipment (PPE), such as face shields and nose and face masks, and highly infectious waste materials, such as contaminated syringes, needles, and soiled bandages from diagnosed positive cases. Despite the huge volume in waste generation, a standardized evaluation framework is currently lacking in the management of medical wastes in Nigeria. This study has developed a novel assessment framework for managing medical wastes, which is curated from the technical guidelines of the World Health Organization (WHO). The applicability of the framework was examined on seven designated public and private-owned hospitals in Ota. The fuzzy analytical hierarchy process (FAHP) and analytical hierarchy process (AHP) approaches of multi-criteria decision analysis were utilized in modelling an evaluation framework for the objective of medical waste management. Carefully designed interview questionnaires, observations, and site visits were carried out to obtain data from healthcare professionals in Ota. Results show that waste segregation was practiced more decisively in private hospitals than public hospitals. Waste segregation is established as a key determinant in implementing an effective waste management system in any healthcare facility. The success of waste segregation in healthcare institutions is highly dependent on good hospital management, organizational policies, efficient budget planning for waste management, and the operational running cost. Disposal methods investigated were mostly open burning and incessant dumping for most public health care centers. Deficient waste management practices were observed in waste disposal, waste transportation, storage, and organizational policies. While the awareness and capacity building on occupational safety practices and environmental public health is widely known by health workers and waste handlers, compliance and enforcement are critical challenges. The validation of results using fuzzy TOPSIS and a sensitivity analysis shows a high degree of the consistency, stability, and robustness of the model. Findings from the present study can aid decision making, as this will benefit policy makers and key stakeholders in developing more comprehensive and effective medical waste management guidelines in Nigeria. In addition, future decision-making studies could augment the results from the current research by assessing the impact of the pandemic preparedness and response on medical waste management. Full article

In this paper, we demonstrate, in the context of Loop Quantum Gravity, the Quantum Holographic Principle, according to which the area of the boundary surface enclosing a region of space encodes a qubit per Planck unit. To this aim, we introduce fermion fields in the bulk, whose boundary surface is the two-dimensional sphere. The doubling of the fermionic degrees of freedom and the use of the Bogolyubov transformations lead to pairs of the spin network’s edges piercing the boundary surface with double punctures, giving rise to pixels of area encoding a qubit. The proof is also valid in the case of a fuzzy sphere. Full article

The global COVID-19 pandemic has led to the self-isolation of people and the transformation of many economic and social processes into an electronic version thus contributing to the digitalization of all spheres. Being part of this environment, enterprises generate information resources to develop their desired image, which may vary according to the factors characterizing the information environment. Information capital is a comprehensive characteristic of an enterprise and determines its effectiveness and sustainability. The purpose of this study is to develop a toolkit that allows one to assess the information capital of an enterprise, reflecting its perception within the digital information environment. It is necessary to develop the methodology for the formation of such tools. As a result, a fuzzy-plural approach has been developed to evaluate the index of external information capital. This model allows us to assess the external information capital and to simulate its changes caused by various kinds of information events. The study of key elements, for example, the stability and tonality indices, index of target perception made it possible to systematize chaotic changes in the external environment and describe them using the Chen–Lee attractor model. The results of this study can be useful for researchers in the field of digital information analysis, in particular for the comparative analysis of enterprises and the assessment of their information capital. Full article