Search Results (406)

Intermittently Connected Wireless Networks (ICWNs) are characterized by dynamic node mobility and the absence of persistent end-to-end paths, making them highly susceptible to security threats. This paper proposes a novel secure routing protocol, called the Evolutionary Game Theoretic model with Reinforcement Learning (EGT-RL), designed to provide adaptive and resilient protection against blackhole attacks in such networks. EGT-RL integrates Q-learning for dynamic threat assessment with evolutionary game theory to model and influence node behavior over time. Simulation results, based on both synthetic and real-world mobility traces, show that EGT-RL significantly outperforms three benchmark protocols in delivery ratio, packet drops, end-to-end latency, and communication overhead. Full article

Previous studies, constrained by the overly rigid stability requirements, often fail to adapt to complex systems and struggle to identify stable outcomes that align with the practical context of multi-agent resource allocation. To address the three-sided matching problem in complex socio-technical and business management systems, this paper proposes a fuzzy stable matching method for three-sided agents under a framework of combinatorial preference relations, integrating network and decision theory. First, we construct a membership function to measure the degree of preference satisfaction between elements of different agents, and then define the concept of fuzzy stability. By incorporating preference satisfaction, we introduce the notion of fuzzy blocking strength and derive the generation conditions for blocking triples and fuzzy stability under the fuzzy stable criterion. Furthermore, we abstract the three-sided matching problem with combined preference relations into a shortest path problem. Second, we prove the equivalence between the shortest path solution and the stable matching outcome. We adopt Dijkstra’s algorithm for problem-solving and derive the time complexity of the algorithm under the pruning strategy. Finally, we apply the proposed model and algorithm to a case study of project assignment in software companies, thereby verifying the feasibility and effectiveness of this three-sided matching method. Compared with existing approaches, the fuzzy stable matching method developed in this study demonstrates distinct advantages in handling preference uncertainty and system complexity. It provides a more universal theoretical tool and computational approach for solving flexible resource allocation problems prevalent in real-world scenarios. Full article

The widespread application of robots in complex and dynamic environments demands that Visual SLAM is both robust and accurate. However, dynamic objects, varying illumination, and environmental complexity fundamentally challenge the static world assumptions underlying traditional SLAM methods. This review provides a comprehensive investigation into the mathematical foundations of V-SLAM and systematically analyzes the key optimization techniques developed for dynamic environments, with particular emphasis on advances since 2020. We begin by rigorously deriving the probabilistic formulation of V-SLAM and its basis in nonlinear optimization, unifying it under a Maximum a Posteriori (MAP) estimation framework. We then propose a taxonomy based on how dynamic elements are handled mathematically, which reflects the historical evolution from robust estimation to semantic modeling and then to deep learning. This framework provides detailed analysis of three main categories: (1) robust estimation theory-based methods for outlier rejection, elaborating on the mathematical models of M-estimators and switch variables; (2) semantic information and factor graph-based methods for explicit dynamic object modeling, deriving the joint optimization formulation for multi-object tracking and SLAM; and (3) deep learning-based end-to-end optimization methods, discussing their mathematical foundations and interpretability challenges. This paper delves into the mathematical principles, performance boundaries, and theoretical controversies underlying these approaches, concluding with a summary of future research directions informed by the latest developments in the field. The review aims to provide both a solid mathematical foundation for understanding current dynamic V-SLAM techniques and inspiration for future algorithmic innovations. By adopting a math-first perspective and organizing the field through its core optimization paradigms, this work offers a clarifying framework for both understanding and advancing dynamic V-SLAM. Full article

Traditional recommendation systems are largely built upon the “rational-agent” assumption, representing user preferences as static numerical vectors while neglecting the pivotal role of emotions in decision-making. However, according to the dual-system theory in cognitive psychology, human decisions are jointly governed by two interacting subsystems: a rational system responsible for deliberate reasoning and an affective system driven by emotion and intuition. Conflicts between these two systems often lead to inconsistencies between users’ preferences and emotional experiences in real-world recommendation scenarios. To address this challenge, we propose an Emotion-Enhanced Dual-Agent Collaborative Framework (EDACF) that explicitly models and leverages cognitive conflicts between users’ emotional experiences and rational preferences. EDACF introduces user and item agents equipped with separate natural language memories for preference, emotion, and conflict representations, enabling cognitive-level reasoning beyond static numerical modeling. The framework features three key innovations: (1) a conflict detection mechanism that identifies users’ cognitive inconsistency states; (2) a dual-memory update strategy that maintains preference stability while capturing emotional dynamics; and (3) an adaptive reasoning mechanism that adjusts decision weights based on detected conflicts. Extensive experiments demonstrate that EDACF outperforms state-of-the-art baselines by 9.9% in NDCG@10 and 13.1% in MRR@10, with improvements exceeding 32% among user groups with high conflict. These results highlight a paradigm shift in recommendation systems from behavior prediction toward cognitive-level understanding of user decision processes. Full article

Systemic cognition combines the humanities and social sciences with systems science to support a unified field, Human Systems Integration (HSI). It draws on complementary, sometimes conflicting, fields of research, including phenomenology, positivism, logic, teleological approaches, humanism, computer science, and engineering. It is time to gain a deeper understanding of our approach to HSI in complex socio-technical systems. Over the past fifty years, we have transformed our lives in unprecedented ways through technology, both in terms of useful and usable hardware and software resources. We have developed means of transport that enable geographical connectivity anywhere and at any time, which is now a standard feature. We have developed information systems that will allow people to communicate with each other in seconds, anywhere on the planet, and at any time. Systemic cognition aims to provide ontological support for discussing this sociotechnical evolution and to develop HSI not only based on a Human-Centered Design (HCD) approach, but also by focusing on society, which is becoming increasingly immersed in a world equipped with artificial resources (particularly with the growing incorporation of artificial intelligence), which separates us from nature. This article proposes an epistemological approach that extends contemporary theories of systemic and socio-cognitive modeling by integrating constructivism and research on HCD-based HSI developed over the last three decades. Aeronautical examples are used to support the concepts being developed. Full article

This study analyses the operational efficiency of urban loading and unloading zones (LUZs) by applying queuing theory without waiting (Erlang B model) and incorporating weighted occupancy time as a fundamental metric. Six scenarios were evaluated in an urban block in Zaragoza, Spain: three using field data obtained through real world observation and three simulated. The system’s performance was compared under conditions of free access with a model that strictly enforces the municipal ordinance for Urban Goods Distribution, restricting access to authorized vehicles and maximum dwell times. The objective of this study is to evaluate the operational performance of different LUZ configurations, assessing how real versus regulation-compliant usage affects system capacity, estimated loss rates, and the spatial temporal productivity of the zones. The M/M/1/1 model in Kendall notation is suitable for representing this type of queuing-free urban environment, and weighted occupancy time proves to be a robust indicator for evaluating the performance of heterogeneous zones. The scenario assessment confirms that the sizing of these zones is correct if their proper use is guaranteed. The study concludes with recommendations and best practices for city governance in formulating urban policies aimed at developing more efficient and sustainable logistics to control land use in the LUZ. Full article

Background: The high prevalence of overweight and obesity in Singapore necessitates scalable primary prevention strategies. This study evaluated the short-term effectiveness of FitterLife, a 12-week, digitally delivered, group-based behavioural weight management programme targeting at-risk adults without diabetes or hypertension in the community. Methods: In a retrospective matched cohort study, we compared 306 FitterLife participants (enrolled from October 2021 to January 2025) with 5087 controls identified from a population health data mart, matched on age, sex, ethnicity, and baseline body mass index (BMI). The primary outcome was achieving ≥5% weight loss or a ≥1 kg/m² BMI reduction at 12 weeks. Programme effectiveness was analysed using propensity score matching (1:1) and inverse probability weighted regression. Mixed-effects models assessed weight/BMI trajectories and modified Poisson regression identified behavioural factors associated with success. Results: After matching, FitterLife participants were more likely to achieve the weight loss target than controls (45.7% vs. 13.7%, coefficient = 0.32, 95% confidence interval [CI]: 0.26–0.38) and were over three times as likely to succeed (Adjusted incidence rate ratio [aIRR] = 3.37, 95% CI: 2.87–3.93). The programme group showed significant reductions in weight (−2.23 kg, 95% CI: −2.57 to −1.90) and BMI (−0.86 kg/m², 95% CI: −0.95 to −0.73) at the end of programme. Higher session attendance and improved behavioural factors were associated with success. Conclusions: FitterLife was effective in achieving clinically significant short-term weight loss in a real-world setting. The findings demonstrate the potential of a scalable, behavioural theory-informed, virtual group model as a viable primary prevention strategy within national chronic disease management efforts. Full article

In developing countries, technology-based startups (TBSs) play a vital role in driving innovation, and they significantly contribute to the generation of jobs and economic development. However, despite their importance, startups have a high failure rate worldwide, and a major contributing factor is a lack of funding. The objective of this study is to compare the existing financing mechanisms in Ethiopia, Uganda, and Kenya and determine the relative position of Ethiopia in the financing landscape. This study was based on resource-based theory and signaling theory. A desk research methodology was employed, and a total of 70 sources were reviewed. The data sources include academic literature, publications from the World Bank, local reports, government policies of the three nations, articles published in reputable journals, and global database indexes. Articles were also selected based on their relevance to the research question and the credibility of the publication. The comparison was carried out based on identifying similarities and differences in economic indicators, the innovation performance of the countries, the innovation eco-system, the types of existing financing mechanisms in each country, and various government policies and initiatives. We also validated our findings by cross-checking information from multiple sources to avoid bias. The results reveal that Ethiopia is lagging behind in most of the parameters set for comparison, while its neighbors, Uganda and Kenya, have a relatively better status in general. Finally, this study has theoretical and practical implications. Full article

The year 2025 marks two significant milestones for aflatoxin research: 65 years since aflatoxin was first identified in 1960, and 50 years of focused research on preharvest aflatoxin contamination since it was first recognized in 1975. Studies in the 1970s revealed that A. flavus could infect crops like maize and produce aflatoxin in the field before harvest and made it possible to investigate the potential genetic resistance in crops to mitigate the issues. Tremendous efforts have been made to learn about the process and regulation of aflatoxin production along with interactions between A. flavus and host plants as influenced by environmental factors. This has allowed for the breeding of more resistant crops and investigations into the underlying genetic and genomic components of resistance mechanisms in crops like maize and peanut. However, despite decades of studies, many questions remain. One established “dogma” is that drought stress, especially when combined with high temperatures, is the single greatest contributing factor to preharvest aflatoxin contamination and is a perennial risk faced throughout the major agricultural production regions of the world. Although there are many reviews summarizing the decades’ long wealth of information about A. flavus, aflatoxin biosynthesis, management and host plant resistance, there are few reports that put the spotlight on why aflatoxin contamination is exacerbated by drought stress, which places plants under severe physiological stress and weakens immune systems. Therefore, here we will focus on three major areas of research in maize: the “living embryo” theory and host resistance mechanisms, the “Key Largo hypothesis” and the causes of drought-exacerbated aflatoxin contamination, and recent advancements in CRISPR-based genome editing for enhancing drought tolerance and increasing plant immune responses. This will highlight key breakthroughs and future prospects for the continuing development of superior crop germplasm and cultivars and for mitigating aflatoxin contamination in food and feed supply chains. Full article

Despite global progress toward gender parity in education, Ghanaian girls continue to face systemic barriers rooted in entrenched parental gender norms. This paper explores how parental gender norm beliefs and attitudes perpetuate disparities among school-aged, particularly disadvantaging girls in access to and retention in education. Using a desk review methodology, we analyzed peer-reviewed social science and development literature, legal documents, and international reports from organizations such as the United Nations and the World Bank to explore the structural and cultural dynamics affecting girls’ education in Ghana. Anchored in Social Impact Theory, Parental Ethnotheories, and Expectation States Theory, the study provides a multi-theoretical lens to understand how gender norms, cultural expectations, and parental beliefs converge to influence educational outcomes for girls. Analysis of sociocultural norms, economic trade-offs, and safety concerns reveals how parents—often guided by love and pragmatism—prioritize sons’ education while withdrawing daughters for caregiving, early marriages, or income-generating labor. The study highlights three critical dimensions: (1) the economic reasoning behind gendered investments in children’s schooling, (2) sociocultural gender norms limiting girls’ retention in school, and (3) the transformative potential of educated women as community leaders challenging these patterns. Evidence shows that educating girls yields broad benefits, from improved health outcomes to economic growth, yet systemic inequities remain. Findings underscore the need for interventions to move beyond school access to address the familial and cultural ecosystems shaping parental decisions. By disrupting entrenched gender norms, Ghana can advance SDGs 4 and 5 and promote long-term societal change. Full article

This study examines factors driving reliance on mobile phones as a primary information source. Using Information-Seeking Complementarity Theory (ISCT), which posits that frequent use of diverse media channels builds digital habits that reinforce mobile reliance, we analyze World Values Survey (WVS) Time Series 1981–2022 (v4.0), validated with WVS v5.0 and Integrated Values Survey (IVS). A multi-stage pipeline integrates AdaBoost (R 4.3.1), LASSO/BMA (Stata v17), Histogram Gradient Boosting (Python 3.12.7), and mixed-effects logistic regression. Missing data (DK/NA) were excluded or median-imputed. The final model (AUC-ROC > 0.85) identifies five robust predictors: age (negative), and positive associations with digital mail, online social networks, peer interaction, and radio listening—all stable across methods, datasets, and reverse causality checks. Subgroup analysis reveals stronger effects among males, unmarried individuals, urban residents, and higher education/employment groups. Nomograms enable probabilistic forecasting and policy simulation. By identifying technology-agnostic behavioral drivers validated across three decades of global survey data (1981–2022), with mobile reliance measured from 2010 onward, this work provides a transparent, replicable predictive framework with implications for emerging AI and wearable contexts. Full article

Interconnect cables serve as critical components in electronic systems responsible for energy and signal transmission. Their electromagnetic compatibility directly impacts the reliable operation of the system. As internal cable layouts become increasingly complex and compact, crosstalk issues between cables have become more pronounced. In this paper, we investigate the crosstalk characteristics of complex assembled cables, proposing a transmission line coupling calculation method that accounts for the influence of cable insulation layers. We specifically address the challenges of computationally complex coupling analysis and insufficiently in-depth crosstalk characteristic analysis in real-world interconnect cable systems. First, we investigate crosstalk calculation methods for assembled interconnect cables. We analyze and extract typical branch, parallel, and vertical structural features present in assembled cables, establishing an electromagnetic coupling model for complex assembled interconnect cables. Based on multi-conductor transmission line theory and incorporating the weak coupling assumption, the direct coupling from interference sources and their reflected waves to sensitive ports, along with the four types of interference propagation paths corresponding to reflected coupling, are decomposed and identified. Building upon this, a transmission line equation accounting for insulation layer effects is proposed. Finally, the crosstalk values calculated using the proposed method are compared with experimentally measured values and those obtained from CST simulations. The comparison results indicate that under ideal transmission line conditions, the crosstalk values obtained from the three methods show minimal deviation, validating the proposed algorithm. Full article

As a core factor in advancing urban agglomeration development and new urbanization, the structural resilience of multi-modal transportation networks in metropolitan areas directly determines their disturbance resistance during emergencies and their sustainable development. To address the prevalent “core–peripheral” connectivity imbalance in medium-sized metropolitan areas, this study takes the Jinan Metropolitan Area as an empirical case to systematically explore its multi-modal transportation network’s structural resilience. A three-dimensional evaluation framework of “absorbing capacity–buffering capacity–recovery capacity” was built based on complex network theory. Network efficiency was used to measure absorbing capacity, the average number of independent paths was used to characterize buffering capacity, and structural entropy was used to determine recovery capacity. The entropy weight method was used to calculate integrated multi-dimensional resilience values, and a sequential node failure simulation was used to analyze network invulnerability. The main findings are as follows: (1) The Jinan Metropolitan Area’s multi-modal transportation network has “small-world characteristics” but low density, with trunk line coverage gaps. (2) Sub-networks differ significantly. The railway sub-network performs best, the highway sub-network is the weakest, and the composite network achieves resilience balance through multi-modal collaboration. (3) Node failure analysis reveals that “core hubs are resilience pillars, while secondary highway nodes are weaknesses.” The proposed “three-dimensional evaluation framework” provides a methodological reference for resilience quantification in similar metropolitan areas, and the “trunk line densification + peripheral connection” strategy supports the implementation of metropolitan planning policies to promote modern metropolitan transportation systems with efficient commuting and robust disturbance resistance. Full article

The Laurentian Great Lakes basin, the largest surface freshwater ecosystem in the world, is heavily impacted by anthropogenic stressors including wetland degradation and loss. Ecological restoration has been identified as a tool to conserve and manage Great Lakes wetlands where studies undergo planning, action, and evaluation stages. A review of 57 studies (1967–2023) on Great Lakes coastal and inland wetlands was conducted to determine when and where ecological restoration is occurring, what approaches are being taken, and how effective they are. Restoration occurred most in coastal wetlands located in the United States of America and Lake Erie. The most implemented monitoring designs were control-impact and before-after-control-impact designs. A common ecological objective of restoration was altering species composition for invasive species management. Studies targeting changes in biological communities integrated ecological theory well within the three stages of restoration. Variable restoration effectiveness was detected, where a mix of ecological objectives were targeted and monitored through many study designs. Future restoration efforts would benefit from greater financial and monitoring investments (especially during the planning stage), continued integration of ecological theory, development of lake-specific benchmarks to assess restoration success, and a collaborative approach that includes practitioner knowledge and Traditional Ecological Knowledge. Full article

Mathematical modeling competency is essential for engineering students, yet significant cognitive obstacles impede their ability to apply theoretical concepts like derivatives to real-world optimization problems. This study investigates the cognitive processes and obstacles encountered by Industrial Engineering and Management students when solving applied derivative problems, utilizing the Mathematical Modeling Cycle (MMC) and Duval’s theory of semiotic registers as analytical frameworks. A qualitative case study design was employed, analyzing students’ written exam responses to an applied optimization task involving tour organization with variable pricing structures. Three representative cases were examined in detail, revealing distinct patterns of cognitive engagement. Results identified specific cognitive obstacles including misunderstanding of variables and domains, weak connections between mathematical and economic contexts, difficulties in graphical representation of constraints, and deficits in validation and critical thinking. While students demonstrated procedural fluency in symbolic manipulation and mathematical work, they struggled to coordinate between different semiotic registers (verbal, algebraic, graphical, and contextual) and failed to complete the full modeling cycle, particularly in the crucial validation stages. These findings suggest that cognitive obstacles stem from representational gaps rather than general learning difficulties, indicating the need for targeted pedagogical interventions that explicitly address transitions between semiotic registers and emphasize the iterative nature of mathematical modeling in engineering contexts. Full article