Real Problems Research Articles

A Multi-Strategy Improved Northern Goshawk Optimization Algorithm for Optimizing Engineering Problems.

Northern Goshawk Optimization (NGO) is an efficient optimization algorithm, but it has the drawbacks of easily falling into local optima and slow convergence. Aiming at these drawbacks, an improved NGO algorithm named the Multi-Strategy Improved Northern Goshawk Optimization (MSINGO) algorithm was proposed by adding the cubic mapping strategy, a novel weighted stochastic difference mutation strategy, and weighted sine and cosine optimization strategy to the original NGO. To verify the performance of MSINGO, a set of comparative experiments were performed with five highly cited and six recently proposed metaheuristic algorithms on the CEC2017 test functions. Comparative experimental results show that in the vast majority of cases, MSINGO's exploitation ability, exploration ability, local optimal avoidance ability, and scalability are superior to those of competitive algorithms. Finally, six real world engineering problems demonstrated the merits and potential of MSINGO.

An enhanced Moth-Flame optimizer with quality enhancement and directional crossover: optimizing classic engineering problems

As a popular meta-heuristic algorithm, the Moth-Flame Optimization (MFO) algorithm has garnered significant interest owing to its high flexibility and straightforward implementation. However, when addressing engineering constraint problems with specific parameters, MFO also exhibits limitations such as fast convergence and a tendency to converge to local optima. In order to address these challenges, this paper introduces an enhanced version of the MFO, EQDXMFO. EQDXMFO integrates a Quality Enhancement (EQ) strategy and a Directional Crossover (DX) mechanism, fortifying the algorithm’s search dynamics. Specifically, the DX mechanism is designed to augment the population’s diversity, enhancing the algorithm’s exploratory potential. Concurrently, the EQ strategy is employed to elevate the solution quality, which in turn refines the convergence precision of the algorithm. To verify the effectiveness of EQDXMFO, experiments are carried out on the test set of the IEEE CEC2017. A total of 5 classical algorithms, five excellent MFO variants, and seven state-of-the-art algorithms are selected for comparison, which confirm the significant advantages of EQDXMFO. Next, EQDXMFO is applied to five complex engineering constraint problems, demonstrating that EQDXMFO can optimize realistic problems. The comprehensive analysis shows that EQDXMFO has strong optimization capabilities and provides methods for research on other complex real-world problems.

Variance Matrix Priors for Dirichlet Process Mixture Models With Gaussian Kernels

SummaryBayesian mixture modelling is widely used for density estimation and clustering. The Dirichlet process mixture model (DPMM) is the most popular Bayesian non‐parametric mixture modelling approach. In this manuscript, we study the choice of prior for the variance or precision matrix when Gaussian kernels are adopted. Typically, in the relevant literature, the assessment of mixture models is done by considering observations in a space of only a handful of dimensions. Instead, we are concerned with more realistic problems of higher dimensionality, in a space of up to 20 dimensions. We observe that the choice of prior is increasingly important as the dimensionality of the problem increases. After identifying certain undesirable properties of standard priors in problems of higher dimensionality, we review and implement possible alternative priors. The most promising priors are identified, as well as other factors that affect the convergence of MCMC samplers. Our results show that the choice of prior is critical for deriving reliable posterior inferences. This manuscript offers a thorough overview and comparative investigation into possible priors, with detailed guidelines for their implementation. Although our work focuses on the use of the DPMM in clustering, it is also applicable to density estimation.

Methods of Multi-Criteria Optimization of Technological Processes in a Fuzzy Environment Based on the Simplex Method and the Theory of Fuzzy Sets

Many modern technological objects in practice are characterized by the uncertainty of the initial information necessary for their management. Recently, one of the pressing scientific and practical problems is the development of new optimization methods for controlling the operating modes of such objects in a fuzzy environment. In this regard, the objective of this study is to develop methods of multi-criteria optimization in a fuzzy environment by modifying the simplex method and various optimality principles based on fuzzy mathematics methods. The methodology of the proposed study is based on a hybrid approach, which consists of the integrated use and modification of simplex methods and optimization methods with various optimality principles for working in a fuzzy environment. The main results are as follows: a simplex method of multi-criteria optimization of immeasurable criteria (here, we are talking about the impossibility of physical measurements of criteria, the values of which are estimated by decision maker); a theorem on the convergence of the solution sequence obtained using the proposed method to the minimum value of the criteria; a heuristic method based on a modification for fuzziness and a combination of the maximin and Pareto optimality principles, which allows effectively solving multi-criteria optimization problems in a fuzzy environment. The heuristic method proposed will be used to solve a real production problem—optimization of the technological process of benzene production.

A - 126 Examining Five Point Test Strategy Use on Everyday Problem-Solving Abilities in Mild Cognitive Impairment and Alzheimer’s Disease

Abstract Objective Activities of daily living (ADLs) and executive functional abilities are increasingly impaired in mild cognitive impairment (MCI) and Alzheimer’s disease (ad). Impaired individuals adopt executive strategies to aid in executing executive everyday tasks. The Five Point Test measures indices of executive functioning when completing the task. The study examines the role of strategy use in everyday problem-solving in healthy older adults (HOA), MCI, and ad. Method Participants included HOA adults (n = 58), persons with MCI (n = 63), and individuals with ad (n = 18). Participants completed a background questionnaire, including the Everyday Problems Test (EPT). In the Five Point Test, using straight lines, participants were instructed to draw various designs in three minutes, avoiding errors across three conditions. The use of the Rotational Strategy is measured by participants generating a new design by rotating the previous spatial configuration. The use of an enumerative strategy was measured by participants generating a pattern by consecutively adding or deleting a line from the previous design. Results Linear regressions were conducted to determine the role of strategy use in everyday problem-solving (i.e., rotational and enumerative strategies). It was revealed that the use of the rotational strategy predicted EPT solving in the MCI group. However, problem-solving abilities did not predict EPT solving in HOA and ad. Conclusion Interestingly, the rotational strategy was better executed across all groups, while the ad group exhibited limited strategy use. Results suggest that those with subtle cognitive deficits adopt strategies to better execute problem-solving in real-life problems.

Exploring uncharted wilderness: a new conceptualization of transformative leadership education

In this explorative essay, we ask how to integrate current development in entrepreneurship education with an education for societal transformation towards sustainability, more explicitly phrased as what and how educators should teach to make students develop transformative capabilities and build action competence for leading societal transformation. We conclude that entrepreneurship education has much to offer and that educators and students ought to transgress institutional borders and explore wilderness together to learn how to create transformative leadership education. Current knowledge indicates that a purposeful education for this end should address seven complementary competencies where students learn to take action, collaborate, engage with society, manage own growth, ground themselves, scout the future, and reframe the system. Due to its inherent qualities, entrepreneurship education, built on engagement in real-world transformative problems, can be considered the most potent foundation for such aspirations. However, as current educational institutions are formed by the malfunctioning and unsustainable system they serve, today’s institutions might not be the best forerunners of change in any pedagogical practice. This is why we also conclude that progressive educators need to leave their ivory towers, classrooms, and lecture halls behind and engage in real transformative problems head-on with their students by their sides.

Secondary teachers’ guided reinvention of the definitions of reducible and irreducible elements

Informed by Realistic Mathematics Education, we designed a hypothetical learning trajectory on graduate students’ guided reinvention of reducible and irreducible elements in rings. We created experientially real context problems for use in a teaching experiment, in which secondary in-service and pre-service teachers used algebra tiles as an emergent model of factoring integers and quadratics in Zx. In their mathematical activity, this became the teachers’ model for abstracting the shared structure of (ir)reducible elements in Z and Z[x], which they used to formally define (ir)reducible elements. In this paper, we discuss the progression of the teachers’ reasoning and defining activities that were evident as they reinvented the definitions of reducible and irreducible elements of integral domains.

Epidemiological Profile of Diabetic Ketoacidosis

Diabetic ketoacidosis is a real public health problem in our context with an incidence of 12.67%. Diabetic ketoacidosis is a therapeutic emergency that requires rigorous management, especially in the acute phase, while respecting the therapeutic particularities of each patient and taking care to detect the etiologies. The etiological research of ketoacidotic decompensation has enabled us to determine, as the main triggering factors, therapeutic non-compliance and then infections, predominated by urinary infections and pneumonia. Initial treatment is based on rehydration, insulin therapy and correction of electrolyte and acid-base disorders, of course, with rigorous and essential monitoring combating possible complications, particularly iatrogenic, represented in our context mainly by the hypokalemia, hypoglycemia, cerebral edema and acute renal failure. The analytical statistical study allowed us to conclude that death was essentially linked to complications occurring during the hospital stay, notably septic shock, cerebral involvement, renal failure and the use of mechanical ventilation.

The Efficiency of Block Hybrid Method for Solving Malthusian Growth Model and Prothero-Robinson Oscillatory Differential Equations

The efficiency of block hybrid method for solving Malthusian Growth Model, Prothero-Robinson equation and highly stiff oscillatory differential equations was proposed using a power series polynomial through interpolation and collocation. The new method's basic properties, including order, error constant, consistency, zero-stability, and stability regions, were comprehensively analyzed and satisfied all necessary conditions for analysis. Tested on various real-life problems, the new method demonstrated superior performance compared to existing techniques. The study highlights the innovative approach's enhanced convergence and stability properties, providing a more reliable numerical analysis tool for researchers and practitioners. Practical applications validate the method's effectiveness, showcasing its superior performance across different examples and establishing it as a highly effective solution for Malthusian growth model and oscillatory differential equations.

The Role of the Law in Protecting Individuals from Electronic Blackmail

The main idea centers on describing the role of the law in defending people against the phenomenon of electronic blackmail by defining the term, outlining its types and characteristics, and outlining the role of the law in combating this phenomenon. This is because laws will inevitably be created to address the enormous advancements in technology and human behavior that have coincided with these advancements. The real problem, which is the incapacity to prosecute those who commit these electronic crimes, has emerged because of the tremendous scientific advancement in the field of technology. This has led to the emergence of new patterns and a new class of criminals who have taken advantage of these sciences and modified them to serve their criminal goals. Crime has gone up, as it has in every nation on the planet. Recent years have seen instances of electronic extortion in Egypt, and judges find it challenging to prosecute these contemporary crimes—especially the offense of electronic extortion. The Egyptian lawmaker demanded prompt action to update the legislation against information technology crimes, include provisions for electronic blackmail, and impose harsh punishments on anyone who engage in such behavior. The psychological and social effects to which individuals are exposed to electronic blackmail were also discussed, and we touch on the impact of these effects on the psychological health and social relationships of individuals. In conclusion, the importance of legal safeguards for victims of cyber extortion in Egypt cannot be overstated, given the ever-changing landscape of cybercrime and the inherent challenges it poses to traditional legal systems. It is necessary to review Egypt's current legal framework. Strict protocols must be established for reporting cases of blackmail against members of society to ensure their protection under Egyptian law.

Rapid assessment of human–elephant conflict: a crime science approach

An interdisciplinary approach has the potential not only to help solve conservation-centric problems but also to enrich and improve evidence-based scientific research. Crime science, an offshoot of criminology, provides a comprehensive, solution-oriented approach that transcends disciplinary boundaries and bridges science and practice for developing effective conservation interventions to real-life problems such as Human Elephant Conflict (HEC). This paper focuses on HEC as a conservation concern, but the resultant behaviors toward elephants, people, and their property are criminology’s concern. Using the Action Research paradigm, a rapid assessment of human–elephant conflict (HEC) in India was undertaken to identify contextual solutions. This study utilized problem-oriented field research methods that enabled the gathering of data on elephant habitat-landscape, villagers’ lifestyle (habitat) in the fringe areas, their current approaches in dealing with the conflict, the challenges forest officials face to mitigate HEC, and the assistance provided by district administrators to protect villagers and their corps and HEC-related deaths. The qualitative inquiry, including observation of village-forest fringe areas, focus group discussions with villagers, and interviews with forest officers and rangers, and district administrators/collectors who are handlers, guardians, and managers of the conflict space, provided rich data in identifying situational practical measures and underscored the role of crime science in providing a conceptual framework to gather evidence in addressing HEC in forest areas. The findings of the research suggest that human–animal convergence space is the source (or location) of conflict and criminology-driven situational crime prevention measures, including increasing effort, risks, reducing rewards and provocations, and removing excuses might mitigate the conflict, requiring coordinated efforts by villagers, forest and district administrators, and local law enforcers.

Implementation of Ideological and Political Theory Course Based on Problem-Based Learning Combined with Small Private Online Course teaching model to Enhance Learning Achievement and Citizenship of Chinese College Students

Background and Aim: Problem-based learning is a kind of targeted and practical learning for students to solve real problems. In the problem design stage, the design of problem scenarios is the core of problem-based learning. The concept of Small Private Online Course (SPOC) was first proposed by Professor Armando Fox, director of MOOC Lab at the University of California, Berkeley, and is abbreviated for Small Private Online Course. In this study, Problem-Based Learning combined with a Small Private Online teaching model were combined to generate a new teaching model. This teaching model emphasizes the role of the problem in the teaching process. Learning throughout the course is an open and dynamic system that can be adapted and improved based on feedback. The purpose of this study was; 1) To compare students’ learning achievement before and after learning through ideological moral and legal basic courses based on problem-based learning combined with the Small Private Online Course (SPOC) teaching model and 2) To compare citizenship of Chinese college students before and after learning through ideological and political theory course based on problem-based learning and Small Private Online Course (SPOC) teaching model. Materials and methods: In this experimental study, 50 students (one class) from Xi’an University were investigated. This study used test and self-evaluation forms given to students before and after learning through ideological and political theory education based on problem-based learning combined with small private online (SPOC). Data were collected and analyzed by means, standard deviation, and dependent sample t-test. Results: The results of the learning achievement before and after learning based on problem-based learning and small private online (SPOC) on ideological and political theory course, it was found that the mean scores of pretests of students’ learning achievement were 13.31(SD=6.860) and mean scores of posttests were 17.32 (SD=7.197). The post-test score of students' learning achievement was higher than that of the pre-test score at.01 level of significance. Moreover, the results of citizenship of Chinese college students found that the mean scores of pretests of citizen self-evaluation scores were 35.42 (SD=9.338) and the mean scores of posttests were 44.18 (SD=9.736). The posttest scores of citizenships of Chinese college students were higher than that of the pretest scores at.01 level of significance. Conclusion: The developed ideological and political theory course based on problem-based learning combined with small private online (SPOC) has a significant effect on improving the learning achievement and citizenship of Chinese college students.

A Modified Water Cycle Algorithm: An Opposition Based Meta-Heuristic Optimization to Solve Real World Engineering Problems

This paper proposes the Opposition based learning on a latest recent population based Water Cycle Algorithm on different benchmark constraint optimization techniques. Water cycle is a Hydrological based technique which works on better search location of the stream and river that flows to the sea which works on certain control parameters that will be defined initially and obtain the population matrix. With the help of the application of the opposition learning opposite search will be made to receive the better search location to find the better fitness value and avoid the premature convergence and get best convergence rate. This Proposed Opposition based Water Cycle Algorithm is implemented and tested on fifteen benchmark problems mentioning the fitness value as well as the constraints value. The convergence plot using a comparative study between Water Cycle Algorithm and Opposition based Water Cycle Algorithm, the proposed method had proved to obtain the best result and superior for the problems on to which it had implemented. The ANOVA test result is shown for the statistical analysis of the data obtained.

Problems and Prospects of Inclusive Education Development in Chinese Schools

The paper presents a theoretical analysis that reveals the real state, problems and dynamics of inclusive education development in schools of the People’s Republic of China. The existing problems in creating an inclusive educational environment for students with disabilities, low levels of professional competence of teachers, tolerance and social relationships are revealed. Existing models of education focused on inclusion, implemented in the provinces of the PRC, cannot fully cover the entire contingent of children with disabilities who need support in the educational space. There is no understanding and confidence in the possibility of objective support for institutions in resolving issues of organizing accessible education for schoolchildren with limited educational needs as part of the implementation of government orders from the Chinese government. There has been an increase in the enrollment of schoolchildren with disabilities in regular classes in large cities and metropolitan areas, however, schools from remote areas and rural settlements cannot provide an inclusive environment due to the lack of qualified teachers and special technical teaching aids. The existing regulatory framework for inclusive education implemented in the PRC, in our opinion, does not fully cover the algorithm for working with children with various health limitations. The lack of effective state educational standards negatively affects ensuring equal access to education for all Chinese schoolchildren, taking into account the variety of options for educational needs and individual psychophysical capabilities. It is proposed to include universities and colleges with experience in inclusion in the implementation of information and educational projects to expand forms of cooperation and partnership, build the capacity of social investments in the dissemination of individual and group forms of inclusive education, accessible to any student with psychophysical and other forms of health impairment. Keywords: school, inclusive education, disabilities, social justice, adaptation, disability

An improved high-order low dissipation weighted compact nonlinear scheme for compressible flow simulations

Recently, Zhang developed a low-dissipation high-order scheme that employs Fu's targeted essentially non-oscillatory approach. this method incorporates an essentially non-oscillatory-like stencil selection strategy within the framework of the weighted compact nonlinear scheme proposed by Deng. Although this new scheme, termed targeted compact nonlinear scheme (TCNS), can recover ideal weights in smooth regions, it reduces accuracy at the discontinuities by discarding less smooth sub-stencils. Acker et al. showed in a recent study that increasing the weight of less smooth sub-stencils on a relatively coarse grid can further improve the wave resolution. Luo further improved Acker's scheme to fully exploit its potential in spectral characteristics. By following this idea, the less smooth stencil weights were incorporated to overcome problems of classical TCNS and to further improve the scheme's ability to resolve high-frequency waves. Moreover, by introducing an adaptive factor, we further optimized the spectral properties to improve the TCNS. A series of standard cases were used to measure the resolution of the new method for multiscale structures and the ability to suppress nonphysical oscillations at shock waves. The new scheme was applied to three cases involving complex configurations and multiscale flows, demonstrating that its low dissipation characteristics offer advantages in solving real-life problems.

Expected value of generalized trapezoidal bipolar fuzzy number to solve a multi-item marketing planning inventory model with allowable shortages

Decision makers often grapple with the complexity of multi-faceted real-life problems, where uncertainty arises from both positive and negative states of mind. This duality reflects the decision maker’s optimistic and pessimistic perspectives during the decision-making process. To address this, our paper introduces innovative concepts and frameworks for generalized bipolar trapezoidal fuzzy numbers. We propose novel arithmetic operations on these fuzzy numbers, computing the negative α-cut and positive β-cut methods. Furthermore, we uniquely compute the convex combination of expected values from both the positive and negative membership parts. These theoretical advancements are applied to a practical case study: a multi-item marketing planning inventory model with allowable shortages. Our proposed method’s efficacy is highlighted through detailed numerical illustrations, sensitivity analyses and comparative studies complemented by compelling graphical presentations

Utilizing task with scaffolding: growth of students' mathematical understanding from layers of image having to property noticing

Introduction. Learning mathematics accompanied by understanding is an essential component of factual and procedural knowledge skills practical for students in solving real-life problems. Errors in solving systems of linear equations in two variables (SPLDV) among students can be caused by various factors, including students' lack of understanding of this concept, so this problem must be studied in depth by utilizing task with scaffolding. The research aimed to explore the potential of a task to foster mathematical understanding of students from the image-having layer to the property noticing layer in the learning context of a system of linear equations in two variables (SPLDV). Study participants and methods. The study involved three students in grade 8 at a junior high school in Indonesia. They were selected based on their mathematical ability (low, moderate, and high) based on their accumulated score reports in grade 7 and information from the teacher who taught them. This study employed a qualitative research approach, data collection was carried out by giving task to students, observing, and interviews them while doing the task, and data analysis began with transcription and organizing the results of interviews and student task, followed by identification and classification of difficulties faced by students. The results. The study showed that student with low mathematical ability has difficulty recognizing patterns or relationships between coefficients and variables in equations. Even with the help of scaffolding, the student still did not succeed in strengthening her understanding to complete the task given, so her understanding only shifted slightly from the image having layer and could not move completely to the property noticing layer. Next, a student with moderate mathematical ability had a sufficient understanding of the concept of variables and coefficients. However, she still needed additional help to complete task, especially in determining the value of variable. She was observed to be already at the property noticing layer of understanding because she had been able to identify the property of two linear equations in two variables that is equivalence and complete the task given. Lastly, the student with high mathematical ability could understand the relevant mathematical concepts well. She could complete the task assigned well despite folding back and scaffolding. Thus, this student's understanding reached the property noticing layer. Conclusions. The research showed differences in the growth of mathematical understanding from the image having layer to the property noticing layer among junior high school students with low, medium, and high mathematical ability. The student with lower math skills was only slightly shifted from the image having layer and could not be transferred completely to the property noticing layer. The student with moderate mathematical ability had reached the layer of understanding properties because she was able to identify equivalent properties of two linear equations in two variables and complete the given task. Lastly, the student with high mathematical skills has reached the layer of property noticing.

Modeling two-phase flows with complicated interface evolution using parallel physics-informed neural networks

The physics-informed neural networks (PINNs) have shown great potential in solving a variety of high-dimensional partial differential equations (PDEs), but the complexity of a realistic problem still restricts the practical application of the PINNs for solving most complicated PDEs. In this paper, we propose a parallel framework for PINNs that is capable of modeling two-phase flows with complicated interface evolution. The proposed framework divides the problem into several simplified subproblems and solves them through training several PINNs on corresponding subdomains simultaneously. To enhance the accuracy of the parallel training framework in two-phase flow, the overlapping domain decomposition method is adopted. The optimal subnetwork sizes and partitioned method are systematically discussed, and a series of cases including a bubble rising, droplet splashing, and the Rayleigh–Taylor instability are applied for quantitative validation. The maximum relative error of quantitative values in these cases is 0.1319. Our results show that the proposed framework not only can accelerate the training procedure of PINNs, but also can capture the spatiotemporal evolution of the interface between various phases. This framework overcomes the difficulties of training PINNs to solve a forward problem in two-phase flow, and it is expected to model more realistic dynamic systems in nature.

Some Aspects of Teaching Improper Integrals in an Electronic Environment

The development of computer technology and communication systems provides new opportunities for learning in an electronic environment. Remote education in virtual electronic classrooms has been widely used in recent decades, especially during the pandemic. Teaching in an electronic environment makes it possible to conduct lectures with thousands of participants. This article is devoted to a new look at teaching improper integrals at the undergraduate and postgraduate levels. A new partition of unity method is applied in a deep recursive e-learning process. A thorough list of subproblems of a real model problem is demonstrated. Additionally, other appropriate improper integrals are considered.

Effectiveness of public health measures in reducing the incidence and lethality of cancer: A systematic review and meta-analysis

Cancer constitutes a real public health problem, and its burden is expected to increase national health systems. The future burden is likely to be much greater due to the increasing prevalence of factors that increase risk, such as smoking, alcoholism, unhealthy diet, physical inactivity, sedentary lifestyle, etc. The objective of this work is to evaluate, through a systematic review, the impact of public health measures on the incidence and lethality of cancers. 51 studies met the inclusion criteria in this review. High adherence to established public health cancer control guidelines for nutrition and physical activity was consistently and significantly associated with reductions of 10% to 61% in overall cancer incidence colorectal cancer in men and women (27%-52%), the incidence of breast cancer (19-60%) and prostate cancer (5 -10%), Significant reductions in the incidence and lung cancer mortality after tobacco control measures. The human papilloma vaccine has shown excellent safety and close to 100% effectiveness in preventing persistent infections and precancerous lesions of the cervix due to types 16 and 18. Through this study, we were able to know the influence of public health measures on the incidence and lethality of cancers.