Real Problems Research Articles

On the Generalisation Performance of Geometric Semantic Genetic Programming for Boolean Functions: Learning Block Mutations

In this paper we present the first rigorous theoretical analysis of the generalisation performance of a Geometric Semantic Genetic Programming (GSGP) system. More specifically, we consider a hill-climber using the GSGP Fixed Block Mutation (FBM) operator for the domain of Boolean functions. We prove that the algorithm cannot evolve Boolean conjunctions of arbitrary size that are correct on unseen inputs chosen uniformly at random from the complete truth table i.e., it generalises poorly. Two algorithms based on the Varying Block Mutation (VBM) operator are proposed and analysed to address the issue. We rigorously prove that under the uniform distribution the first one can efficiently evolve any Boolean function of constant size with respect to the number of available variables, while the second one can efficiently evolve general conjunctions or disjunctions of any size without requiring prior knowledge of the target function class. An experimental analysis confirms the theoretical insights for realistic problem sizes and indicates the superiority of the proposed operators also for small parity functions not explicitly covered by the theory.

Research on a Three-Way Decision-Making Approach, Based on Non-Additive Measurement and Prospect Theory, and Its Application in Aviation Equipment Risk Analysis.

Due to the information non-independence of attributes, combined with a complex and changeable environment, the analysis of risks faces great difficulties. In view of this problem, this paper proposes a new three-way decision-making (3WD) method, combined with prospect theory and a non-additive measure, to cope with multi-source and incomplete risk information systems. Prospect theory improves the loss function of the original 3WD model, and the combination of non-additive measurement and probability measurement provides a new perspective to understand the meaning of decision-making, which could measure the relative degree by considering expert knowledge and objective data. The theoretical basis and framework of this model are illustrated, and this model is applied to a real in-service aviation equipment structures risk evaluation problem involving multiple incomplete risk information sources. When the simulation analysis is carried out, the results show that the availability of this method is verified. This method can also evaluate and rank key risk factors in equipment structures, which provides a reliable basis for decisions in aviation safety management.

Learning fast while changing slow in spiking neural networks

Reinforcement learning (RL) faces substantial challenges when applied to real-life problems, primarily stemming from the scarcity of available data due to limited interactions with the environment. This limitation is exacerbated by the fact that RL often demands a considerable volume of data for effective learning. The complexity escalates further when implementing RL in recurrent spiking networks, where inherent noise introduced by spikes adds a layer of difficulty. Life-long learning machines must inherently resolve the plasticity-stability paradox. Striking a balance between acquiring new knowledge and maintaining stability is crucial for artificial agents. To address this challenge, we draw inspiration from machine learning technology and introduce a biologically plausible implementation of proximal policy optimization, referred to as lf-cs (learning fast changing slow). Our approach results in two notable advancements: firstly, the capacity to assimilate new information into a new policy without requiring alterations to the current policy; and secondly, the capability to replay experiences without experiencing policy divergence. Furthermore, when contrasted with other experience replay techniques, our method demonstrates the added advantage of being computationally efficient in an online setting. We demonstrate that the proposed methodology enhances the efficiency of learning, showcasing its potential impact on neuromorphic and real-world applications.

МЕТОДИЧНА ПІДГОТОВКА МАЙБУТНІХ УЧИТЕЛІВ БІОЛОГІЇ ДО ОРГАНІЗАЦІЇДОСЛІДНИЦЬКОЇ ДІЯЛЬНОСТІ УЧНІВ

The article analyzes the state of methodical training of future teachers for the organization of research activities during biology education. The article analyzes model programs "Biology. 7-9 grades" for institutions of general secondary education. The current state of methodical training of future teachers for the organization of research activities during biology education has been clarified. It has been found that the research approach in the education of education seekers is implemented through the study of all educational disciplines, the formation of research biological skills, takes place during the training of professional disciplines, and is consolidated during the training of selective disciplines and practical training. Acquiring research skills by students is one of the priority tasks of modern biological education. Because STEM education is based on the practical, interdisciplinary application of knowledge and skills to solve practical tasks that students face, not only during education, but also in everyday life. Accordingly, training should aim to teach students disciplines in a pleasant and, above all, practical way, since it is a project-based form of training. Higher education should be aimed at awakening the scientific interest of students and developing their ability to solve problems. The purpose of such training is to teach students to apply an interdisciplinary approach during training, to adapt knowledge and skills to real-life problems, to give them more tools for future professional activities. Mastering research skills by students is one of the priority tasks of modern biological education. STEM education is based on the practical, interdisciplinary application of knowledge and skills to solve practical problems faced by students, not only during their studies but also in everyday life. Accordingly, education should aim to teach students disciplines in an enjoyable and, above all, practical way, as it is a project-based form of learning. Higher education should be aimed at awakening students' scientific interest and developing their ability to solve problems. Implementation of these changes will require significant efforts from all participants in the educational process. However, if these efforts are successful, they will contribute to improving the quality of higher education in Ukraine and ensure that higher education students are prepared for successful professional activities in modern society.

On the issue of rethinking the conceptual foundations of management as a social phenomenon

Social and digital technologies are exposing the impact of governance on society. It acts as a factor that simultaneously solves problems and poses threats to all of humanity as a result of mistakes, personal interests, and unforeseen consequences. With the growing influence of management on social processes, questions arise not only about how management is structured, but also what place it occupies in society. There is a need to rethink the phenomenon of management. Despite the prevalence of the term “management,” its understanding is far from ambiguous. An additional complexity is associated with the absence in foreign scientific literature of a term identical to the Russian word “management”. The article proposes that management is understood as a social phenomenon manifested in the activities of individual and group subjects, which is aimed at interfering in the natural course of events to bring them into line with subjective ideas. In this interpretation, management serves as the basis for the emergence of an artificial component. To understand the place given to management in sociology, the article analyzes the main sociological paradigms based on the typologies of K.Dubar, R.Collins, J.Ritzer. In the usual dualism, objectivism-subjectivism, structure-agent, society-personality, macrosociology-microsociology and the desire to overcome them, management is given a secondary, auxiliary role, and disciplines studying management (sociology of management, sociology of organizations) are given the place of industrial sciences. Each of the sociological paradigms is a response to the challenges of its time. The modern world is characterized by the growth of man-made artificial reality with a simultaneous increase in uncertainty. This actualizes new challenges, the answers to which the author proposes to look for in the problem field of management, expanding it to a general sociological theory. For this purpose, the social space is described as the intersection of the “natural-artificial” and “determined-uncertain” axes. The author sees an important difference between the sociology of management and other disciplines in the study of not only what one should “know in order to foresee, and foresee in order to be able,” but also how this “can” can be realized. The study of management covers the theory and practice of social and, rising to abstract levels, it does not lose pragmatism (it takes into account how knowledge is applied by social individuals in practice to solve real social problems).

Geodesic algorithm: new approach to optimization of temporary fastener arrangement in airframe assembly process

PurposeThe purpose of the current study is development of effective and fast algorithm for optimization the arrangement of temporary fasteners during aircraft assembly.Design/methodology/approachCombinatorial nature, uncertain input data, sensitivity to mechanical properties and geometric tolerances are the specific features of the fastening optimization problem. These characteristics make the problem-solving by standard methods very resource-intensive because the calculation of the objective function requires multiple solution of contact problems. The work provides an extended description of the geodesic algorithm (GA) which is a novel non-iterative optimization approach avoiding multiple objective function calculations.FindingsThe GA makes it possible to optimize the arrangement of temporary fasteners during the different stages of the assembly process. The objective functions for the optimization are number of installed fasteners and quality of contact between joined parts. The mentioned properties of the GA also make it possible to introduce an automatic procedure for optimizing fastener arrangement into everyday practice of aircraft manufacturing.Practical implicationsThe algorithm has been applied to optimization of the assembly process in Airbus company.Originality/valuePerformance of the GA is orders of magnitude greater than standard optimization algorithms while maintaining the quality of results. The use of the assembly process specifics is the main limitation of the GA, because it cannot be automatically applied to optimization problems in other areas. High speed of work and quality of the results make it possible to use it for real optimization problems on assembly line in the production of commercial airliners.

Multistep Iterative Methods for Solving Equations in Banach Space

The novelty of this article lies in the fact that we extend the use of a multistep method for developing a sequence whose limit solves a Banach space-valued equation. We suggest the error estimates, local convergence, and semi-local convergence, a radius of convergence, the uniqueness of the required solution that can be computed under ω-continuity, and conditions on the first derivative, which is on the method. But, earlier studies used high-order derivatives, even though those derivatives do not appear in the body structure of the proposed method. In addition to this, they did not propose computable estimates and semi-local convergence. We checked the applicability of our study to three real-life problems for semi-local convergence and two problems chosen for local convergence. Based on the obtained results, we conclude that our approach improves its applicability and makes it suitable for challenges in applied science.

Developing microbiology literacy in biology education college: future teacher candidates

ABSTRACT Recently, several articles have reflected on the existence of microorganisms in supporting the life and health of living creatures as the beginning of the emergence of microbiology literacy. In the curriculum, understanding the activity of microorganisms has been studied from pre-school, elementary school, and middle school to college. The presence of microorganisms is often associated as a cause of disease. As a result, most students know the negative impact of microorganisms but have not discovered the fundamental role of microorganisms in their lives. Special attention needs to be given as a form of effort to strengthen microbiology literacy. Several studies state that students have an important role in disseminating the concept of sterilization, maintaining a safe distance, and using masks as generally applicable protocols during the pandemic. Therefore, with the aim that microorganisms have an important role, both directly and indirectly and to curb negative perceptions of microorganisms, we propose microbiology competencies among biology education students, who are future teaching candidates. This article identifies the complex challenges of 21st-century microbiology learning and the OECD framework. This approach includes the use of pedagogical interventions with the main objectives: (i) knowledge (to teach fundamental microbiology knowledge, (ii) skills (to increase awareness in recognizing and solving real-life problems), and (iii) attitudes and values (to explain the contribution of microbiology in supporting life).

The modus operandi of the corporate psychopath: Analysis of the literature review

The scarcity of research on corporate psychopaths in Brazil aroused the interest of the present study. The main objective was to analyze and explain the modus operandi adopted by psychopaths in companies, based on the specialized literature. For this, the research, of an exploratory nature, used the bibliographic review as a methodology, consulting books, scientific articles and websites. The results revealed that most authors agree on the characteristics of the corporate psychopath, such as the search for power and control, the manipulation of colleagues, and the exploitation of dysfunctional organizational cultures. However, there are disagreements about the definition, nomenclature, origin and classification of psychopathy. The study concludes that corporate psychopathy is a real problem and that more research is needed to understand and combat it. Identifying and addressing this profile is crucial to protect victims and organizations from the negative impacts of corporate psychopathy.

Metaheuristics for variable-size mixed optimization problems: A unified taxonomy and survey

Many real world optimization problems are formulated as mixed-variable optimization problems (MVOPs) which involve both continuous and discrete variables. MVOPs including dimensional variables are characterized by a variable-size search space. Depending on the values of dimensional variables, the number and type of the variables of the problem can vary dynamically. MVOPs and variable-size MVOPs (VMVOPs) are difficult to solve and raise a number of scientific challenges in the design of metaheuristics. Standard metaheuristics have been first designed to address continuous or discrete optimization problems, and are not able to tackle VMVOPs in an efficient way. The development of metaheuristics for solving such problems has attracted the attention of many researchers and is increasingly popular. However, to our knowledge there is no well established taxonomy or comprehensive survey for handling this important family of optimization problems. This paper presents an unified taxonomy for metaheuristic solutions for solving VMVOPs in an attempt to provide a common terminology and classification mechanisms. It provides a general mathematical formulation and concepts of VMVOPs, and identifies the various solving methodologies than can be applied in metaheuristics. The advantages, the weaknesses and the limitations of the presented methodologies are discussed. The proposed taxonomy also allows to identify some open research issues which needs further in-depth investigations.

A longitudinal investigation of gifted students’ creative project production and management for real-life problem solving

A longitudinal investigation of gifted students’ creative project production and management for real-life problem solving

Action learning in public administration education: learning (evidence) from an action research case study

PurposeThis study aims to explore the effectiveness of action learning (AL) in PA education through the action research (AR). Public administration (PA) requires training paths for its officials aimed at developing managerial skills. Training designers must construct pathways that identify goals and results to be obtained. Most importantly, they should adopt techniques that engage all stakeholders and measure training performance. This study uses the action research (AR) method to explore the effectiveness of action learning (AL) in PA education. It shows how a training project for officials of the PA can be designed and managed in a participatory and engaging manner.Design/methodology/approachThe AR approach is particularly suited to long-term training interventions in PA because it offers a means of taking shared responsibility. AR aids in building a bridge between academia and practice and solving real problems with stakeholders, students and end-clients through cyclical interactions of construction, intervention and evaluation. It focuses on AL as an innovative educational tool that links knowledge and action and theory and practice.FindingsThe involvement of different stakeholders, such as teachers, students, administrators and politicians, in the design, management and evaluation process facilitates the identification of educational objectives and monitoring of outcomes in a changing public organizational context. AL is effective because it involves students as individuals and as a team, often as an organization, while trying to solve real problems.Originality/valueAL through the AR approach has not been widely used in education, especially in PA, where teaching legal and administrative content combines traditional teaching methods. The case study shows the innovative potential of AL in a traditional context such as the PA.

Estimating Hardening Soil-Brick model parameters for sands based on CPTU tests and laboratory experimental evidence

The Hardening Soil-Brick model for soils is designed to carry out complex numerical analyses of soil-structure interaction problems taking into account strong stiffness variation in the range of small strains. However, to calibrate its parameters advanced triaxial and oedometric tests are required. In case of uncemented sands laboratory testing is usually difficult. Therefore, to facilitate calibration procedures, a CPTU based method, enhanced by an experimental evidence derived from advanced triaxial drained and oedometric tests, has been proposed and verified. It is shown in the paper that using exclusively the CPTU test results one can calibrate most important model parameters for sands with accuracy that is sufficient for solving real life problems. The major goal of this paper is to identify correlations between all reference stiffness moduli, then verify them, and finally link with the CPTU based identification procedures. It is shown in the paper that such correlations exist and they exhibit very high coefficients of determination. Moreover, as the seismic version of the CPTU test is not often available in the practice, an enhanced procedure for identification of very small strain shear stiffness modulus has been proposed and then verified, using set of the SCPTU tests conducted in Gdańsk sands (Poland).

CMGWO: Grey wolf optimizer for fusion cell-like P systems

The grey wolf optimizer is a widely used parametric optimization algorithm. It is affected by the structure and rank of grey wolves and is prone to falling into the local optimum. In this study, we propose a grey wolf optimizer for fusion cell-like P systems. Cell-like P systems can parallelize computation and communicate from cell membrane to cell membrane, which can help the grey wolf optimizer jump out of the local optimum. Design new convergence factors and use different convergence factors in other cell membranes to balance the overall exploration and utilization capabilities of the algorithm. At the same time, dynamic weights are introduced to accelerate the convergence speed of the algorithm. Experiments are performed on 24 test functions to verify their global optimization performance. Meanwhile, a support vector machine model optimized by the grey wolf optimizer for fusion cell-like P systems has been developed and tested on six benchmark datasets. Finally, the optimizing ability of grey wolf optimizer for fusion cell-like P systems on constrained optimization problems is verified on three real engineering design problems. Compared with other algorithms, grey wolf optimizer for fusion cell-like P systems obtains higher accuracy and faster convergence speed on the test function, and at the same time, it can find a better parameter set stably for the optimization of support vector machine parameters, in addition to being more competitive on constrained engineering design problems. The results show that grey wolf optimizer for fusion cell-like P systems improves the searching ability of the population, has a better ability to jump out of the local optimum, has a faster convergence speed, and has better stability.

Epidemiology and Management of Anal Suppuration at the Donka National Hospital, Chu De Conakry, Guinea

Introduction: Anal suppurations (fistula and abscess) correspond to two progressive phases of the same disease, characterised by an infection of cryptic origin in the anal canal. The objectives of this study were to determine the hospital frequency, to describe the clinical aspects and to determine the therapeutic modalities of anal suppurations in the department. Methodology: This was a one-year dynamic descriptive study of patients admitted to and operated on for anal suppuration in the Department of Visceral Surgery, Donka National Hospital, Conakry University Hospital. Results: Out of a total of 351 patients operated on, we recorded 21 cases of anal suppuration, i.e. 5.98%. Anal suppuration accounted for 45.65% of all proctological disorders. The average age was 43.09 years. There was a clear male predominance (95.23%) with a sex ratio of 20:1. The clinical picture was dominated by anal discharge and evidence of skin orifices. Retroviral serology, haemogram, HBsAg and blood glucose were performed in all patients. All patients were treated surgically. Post-operative management was straightforward in 95.23% of cases, with complications occurring in 4.76%. Conclusion: Anal suppuration remains by far the most frequent proctological disease in our practice. They constitute a real public health problem because they are underestimated in the African population due to socio-cultural factors. Diagnosis is essentially clinical and treatment is surgical.

Validation of the Chinese version of the 'caring ability of family caregivers of patients with cancer scale (CAFCPCS)' in family caregivers of elderly patients with cancer: A study protocol.

This study aims to translate the English version of the 'caring ability of family caregivers of patients with cancer scale (CAFCPCS)' into Chinese and validate its psychometric properties in the family caregivers of elderly patients with cancer. A methodological study. Based on the Brislin translation model, the original scale will be translated and back-translated, the Delphi expert consultation method will be adopted for cross-cultural adaptation, and the pilot will be carried out in 20-30 family caregivers of elderly patients with cancer. Then, a dual-centre prospective study will be conducted by recruiting 371-542 family caregivers of elderly patients with cancer to validate the psychometric properties of the Chinese version of CAFCPCS. The scale's content validity will be evaluated using the Delphi expert inquiry method, and the face validity will be evaluated using a pre-experiment. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) will be used to assess structural validity, while internal consistency reliability and split-half reliability will be used to assess reliability. Public involvement is of great significance for this study. Participants will be used in a pre-test to give feedback on whether the contents of the clinical pilot version of CAFCPCS after expert consultation can reflect real problems and whether the sentences can be well understood. Based on their opinions, the research group will further refine the scale.

Chaotic RIME optimization algorithm with adaptive mutualism for feature selection problems

The RIME optimization algorithm is a newly developed physics-based optimization algorithm used for solving optimization problems. The RIME algorithm proved high-performing in various fields and domains, providing a high-performance solution. Nevertheless, like many swarm-based optimization algorithms, RIME suffers from many limitations, including the exploration-exploitation balance not being well balanced. In addition, the likelihood of falling into local optimal solutions is high, and the convergence speed still needs some work. Hence, there is room for enhancement in the search mechanism so that various search agents can discover new solutions. The authors suggest an adaptive chaotic version of the RIME algorithm named ACRIME, which incorporates four main improvements, including an intelligent population initialization using chaotic maps, a novel adaptive modified Symbiotic Organism Search (SOS) mutualism phase, a novel mixed mutation strategy, and the utilization of restart strategy. The main goal of these improvements is to improve the variety of the population, achieve a better balance between exploration and exploitation, and improve RIME's local and global search abilities. The study assesses the effectiveness of ACRIME by using the standard benchmark functions of the CEC2005 and CEC2019 benchmarks. The proposed ACRIME is also applied as a feature selection to fourteen various datasets to test its applicability to real-world problems. Besides, the ACRIME algorithm is applied to the COVID-19 classification real problem to test its applicability and performance further. The suggested algorithm is compared to other sophisticated classical and advanced metaheuristics, and its performance is assessed using statistical tests such as Wilcoxon rank-sum and Friedman rank tests. The study demonstrates that ACRIME exhibits a high level of competitiveness and often outperforms competing algorithms. It discovers the optimal subset of features, enhancing the accuracy of classification and minimizing the number of features employed. This study primarily focuses on enhancing the equilibrium between exploration and exploitation, extending the scope of local search.

End-to-End No-wait Scheduling for Time-Triggered Streams in Mixed Wired-Wireless Networks

Proprietary communication technologies for time-critical communication in industrial environments are being gradually replaced by Time-sensitive Networking (TSN)-enabled Ethernet. Furthermore, attempts have been made to bring TSN features into wireless networks so that the flexibility of wireless networks can be utilized, and the end-to-end timings for Time-Triggered (TT) streams can be guaranteed. Given a mixed wired-wireless network, the scheduling problem should be solved for a set of TT stream requests. In this paper, we formulate the no-wait scheduling problem for mixed wired-wireless networks as a Mixed Integer Linear Programming (MILP) model with the objective of minimizing the flowspan. We also propose a relaxation of the original MILP in the form of a 2-stage MILP formulation. Next, a scalable approach based on the greedy heuristic is proposed to solve the problem for realistic-size networks. Evaluation results show that the greedy heuristic is suitable for realistic problem sizes where the MILP-based approach is found to be practically infeasible. Furthermore, the impact of wireless requests on the performance of the greedy heuristic is reported.

KESAN PENDEKATAN ISU SOSIOSAINTIFIK DAN PEMIKIRAN REKA BENTUK DALAM STEM TERHADAP PEMIKIRAN KREATIF KEUSAHAWANAN MURID SEKOLAH MENENGAH

The Socioscientific Issues Approach (SIA) engages students to study and connect science, daily life and society in the community. While Design Thinking (DT) encourages students to understand the needs of the local community regarding real-life problems, and then apply the knowledge to generate ideas for solutions. The integration of PIS and PRB in STEM teaching and learning is rarely documented in the literature. Thus, this research aimed to examine the effects of integrating SIA an DT approaches in STEM education on entrepreneurial creative thinking among rural secondary school students. A comprehensive instructional module was meticulously designed to facilitate teachers in implementing the SIA-DT framework, aimed at augmenting entrepreneurial creative thinking skills among Form Four students. A quasi-experimental quantitative study was conducted on 267 Form Four students enrolled in rural secondary schools in Tawau, Sabah. These students were randomly assigned to three groups: i) Socioscientific Issue and Design Thinking Integration (SSA-DT, n=89), ii) Design Thinking Approach (DT, n=90), and iii) Traditional Approach (TRD, n=88). The Entrepreneurial Creative Thinking Test (ECTT) instrument was developed and applied to measure pre- and post-intervention levels of entrepreneurial creative thinking. Rigorous statistical analyses employing MANCOVA, ANCOVA, and Effect Size techniques were conducted. MANCOVA results revealed statistically significant effects across all instructional groups, indicating the effects of the interventions in fostering entrepreneurial creative thinking. Furthermore, ANCOVA analysis results indicated that the SSA-DT method significantly fosters entrepreneurial creative thinking, investigation constructs, new ideas, design, creation, and commercialization compared to the DT and TRD methods. These findings support the view that the SSA-DT module has a positive impact on cultivating entrepreneurial creative thinking among students.

NUMERACY LITERACY OF STUDENTS USING I-SPRING 11 LEARNING MEDIA

The low level of numeracy literacy in Indonesia is due to the material tested on TIMSS and PISA, which consists of questions in real-life context problems. Students are not accustomed to solving real problems and cannot analyze information in various forms. The lack of engaging learning materials contributes to students' boredom and makes it difficult for them to tackle numeracy and literacy challenges. This study investigates how well students can read and compute after using the iSpring 11 learning resources. Twenty students from class VII at State Junior High School 46 Palembang were the research subjects. The research method used is design research with a development study, which at the prototype stage uses the Tessmer model. The focus of discussion in this research is the results of the field test stage, where data collection techniques include tests and interviews. Data analysis techniques include test data analysis and interview analysis. This research demonstrates that students' numeracy literacy skills are excellent, with an average score of 88 after learning using the iSpring 11 learning media.