Problem-solving Techniques Research Articles

Integrating AI and ML Education in Small Liberal Arts Institutions: Curriculum and Pedagogical Considerations

The proliferation of artificial intelligence (AI) and machine learning (ML) in modern institutions has necessitated integrating these technologies into academic curricula. This transition challenges small liberal arts institutions, which offer unique educational opportunities but face distinct hurdles in adapting their programs to meet the growing demand for AI and ML expertise. This article highlights the importance of providing computer science graduates from these institutions with a solid foundation in AI and ML systems. The recommended curriculum includes problem-solving techniques, algorithm design, data preprocessing, model training, and ethical considerations in AI and ML. The pedagogy emphasizes practical assignments, projects, and collaborative learning to foster critical thinking and creative problem-solving skills. Moreover, integrating AI and ML concepts across disciplines enables students to explore these technologies' broader implications and ethical dimensions.Small liberal arts institutions can leverage their unique educational environments to promote interdisciplinary collaborations and provide students with a well-rounded understanding of AI and ML applications. In conclusion, adapting small liberal arts institutions to incorporate AI and ML education is vital for preparing computer science graduates to meet the evolving demands of the modern workforce. By embracing these advancements and tailoring their programs accordingly, these institutions can equip their students with the necessary skills and knowledge to thrive in an AI-driven world.

Prevalence and Predictive Factors of Compassion Fatigue among Healthcare Workers in Saudi Arabia: Implications for Well-Being and Support.

Compassion fatigue (CF) poses significant challenges to healthcare workers' (HCWs) well-being. This study aimed to estimate the prevalence of CF and identify its predictive factors among HCWs in all regions of Saudi Arabia (SA). As such, all HCWs from different disciplines in different centers were allowed to participate, resulting in 678 participants. The study tool, distributed between October 2022 and January 2023, consisted of a questionnaire created by the authors based on the Professional Quality of Life Scale (ProQOL). The ProQOL measures the positive (compassion satisfaction [CS]) and negative (CF) effects of helping those who have suffered, noting that burnout (BO) and secondary traumatic stress (STS) are the two subscales that constitute CF. Our findings revealed that 63.9% of HCWs experienced average STS, while 57.2% reported average BO levels. HCWs in the southern and northern regions exhibited higher STS (p-value = 0.003 and 0.010, respectively). Physicians displayed higher BO levels (p-value = 0.024). Higher levels of CS were found among older HCWs (p-value = 0.001) and lower levels among those with more years of experience (p-value = 0.004). Support at work and job, life, and financial income satisfaction were significantly and positively correlated with CS and negatively correlated with BO and STS. These findings highlight the need for tailored awareness campaigns targeting HCWs, particularly physicians, to promote well-being, enhance coping skills, and foster problem-solving techniques. Keywords: burnout; compassion fatigue; compassion satisfaction; healthcare workers; professional quality of life; Saudi Arabia; secondary traumatic stress; medical trainees' well-being.

Gamified Cyber-Crime Monitoring and Control Framework in a Computer Network Environment

Recent advancements in cybercrime are continually emerging, with the estimated damages to the global economy reaching the billion dollar mark. In the past, people acting alone or in small groups were the main perpetrators of cybercrime. Complex cybercriminal networks are now bringing people from all over the world together in real time to commit crimes on a never-before-seen scale. Game theory gives a formal vocabulary for the description and study of interacting situations in which a number of "entities," known as players, take actions that have an effect on one another. The field of cyber security could benefit from problem-solving techniques based on games theory to protect assets. In this article, we suggest a conceptual framework for a system for monitoring and controlling cybercrime.

Machine Learning based Data Analysis for Wordle Game

As wordle game is becoming more and more popular all over the world, the study of the intrinsic patterns and problem-solving techniques of the game has become a popular topic. In this paper, we obtained daily result files of wordle over a period of time, which included data such as words of the day, the number of people who reported their scores on the day, and the number of players who entered the difficult mode, and further analyzed the data. In order to predict the results reported on a future day, this paper first eliminates the abnormal data in the dataset, and then builds the LSTM model and ARIMA model. On the test set, the MAPE (mean absolute error) of the LSTM model is 5.643, and the LSTM is significantly better than the ARIMA model. Secondly, in order to predict the distribution of word results for a given future date, the 12 features of the network training data were first subjected to PCA dimensionality reduction, and the results showed that the percentages were consistent with time by performing the Shapiro-Wilk normalization test on the correlation percentages. Based on this observation, we built a BP-LSTM parallel model to extract word attributes and extract percentage features over time. The model has a MAPE of 6.09, which outperforms a BP neural network that can only extract word attributes.

Development Of A Complex Public Health Intervention To Reduce Anxiety Of Children Aged 13-15 Years Attending Government Sinhala Medium Schools In Colombo District, Sri Lanka

Background: Anxiety disorders (AD) are the most prevalent psychological problem among adolescents. Both anxiety disorders and anxiety symptoms can lead to adverse outcomes. The aim of the study was to develop an evidence-based intervention package to reduce anxiety among school children aged 13-15 years.Methods: Design: UK Medical Research Council guidance for development of complex interventions were followed. Identification of evidence based was done by literature-search and expert opinions. Most suitable theory was identified based on level of evidence through consensus of Advisory committee (AC) consisting of experts. Subcomponents of the selected theory were mapped with associated factors of the AD. Eleven KII were conducted with school principals, teachers, parents, and students. Framework of the intervention package with suitable deliverables was designed with consensus of the AC by triangulating the findings. This was further fine-tuned with by using Modified-Delphi technique with participation of broader group of experts. These Delphi items were systematically derived from findings of the systematic reviews, expert opinion, and inputs from intervention recipients. The content development was done based on the proposed framework. Modeling process was done by conducting four consultative meetings with stakeholders with the aim of ensuring content and consensual validity followed by a consensus workshop. Feasibility study and pretesting of deliverables were done. Participants: Advisory committee [n=6] and stakeholder group [n=11] in Delphi component & four consultative meetings and a wider stakeholder group [n=23] in 1-day consensus workshop were involved.Results: Four RCTs and 12 RCTs/cRCTs were identified through literature review. Six types of intervention modalities were identified. CBT based intervention modality was shortlisted by AC considering the level of evidence. Five broad solutions, namely psycho education, realistic thinking, problem solving, graded exposure and relaxation techniques under CBT were mapped against the associated factors with consensus of the AC. Activities were developed under these broad solutions and most suitable options of these activities were selected by a stakeholder group using Modified Delphi technique. The intervention package was finalized by conducting a consensual workshop followed by feasibility study and pretesting of deliverables.Conclusions: A CBT-based universal intervention package was developed to reduce anxiety among children with ToT workshop for teachers with a field training, eight weekly 40 minutes sessions for children and one 40-minute session for parents. Teachers’ guide, Student’s workbook and leaflet for parents were deliverables. A process evaluation framework was used to monitor implementation.

A Planning Approach to Repair Domains with Incomplete Action Effects

Automated planning is a problem solving technique for a wide range of scenarios and goals, which typically involves the creation of domain and problem files in formal languages. However, producing complete model descriptions can be challenging and time-consuming, especially for non-experts. Although many tools have been developed to support file editing, mistakes can still be made, such as incomplete or improper specification of the initial state or the set of actions. These errors often result in unsolvable tasks for planners, making it impossible to generate a plan. Explaining the absence of a solution in such cases is essential to support humans in the development of automated planning tasks. In this paper, we introduce a novel approach to repair planning models where the effects of some actions are incomplete, without further information from the user side. We propose a compilation of the unsolvable task to a new extended planning task, in which new actions are permitted to insert possible missing effects. The solution is a plan that achieves the goals of the original problem while also alerting users of the modifications made to do so. Experimental results demonstrate that this approach can effectively repair incomplete planning domains.

Preserving and Sharing Knowledge – Extending the UAF Security Views with Libraries, Patterns and Profiles

AbstractKnowledge and experience are gained during the execution of every project. This knowledge remains in the heads of the engineers, but often is not distributed more widely. In Model‐Based Systems Engineering (MBSE) projects, this knowledge can include problem solving techniques, algorithms, libraries of types, patterns, interfaces, components, etc. One of the ways to preserve this knowledge is by creating libraries of these reusable assets. For example, the newest version of Unified Architecture Framework (UAF) included a library developed by Mitre of 1200 different security controls defined in National Institute of Standards and Technology (NIST) standard 800‐53r5. These controls can be referenced on projects to mitigate many common security risks. Each defined control can be integrated with the corresponding risks, security metrics, mitigating elements, solutions, and so forth. All these elements could then be used to construct Security Patterns showing risks that the security controls can mitigate as well as abstract solutions that can satisfy these controls. Patterns publicly provided as a curated, searchable, solution set library could be leveraged by projects and augmented over time, preserving their Intellectual Property (IP) and knowledge assets. This paper discusses these concepts and methods and demonstrates how they can be applied to improve system security.

STUDENTS' MATHEMATICAL LITERACY IN SOLVING PROBLEMS SYSTEM OF EQUATION OF THREE VARIABLES

The main focus in this study aims to analyze the mathematical literacy skills of students at senior high school in solving problems involving the system of linear equations of three variables. The researcher took a qualitative descriptive method. The research subjects were 34 students from class X8. Problem sheets and interviews were the main data collection methods in this study. Researchers reduced data, presented data, and drew conclusions to handle data using a triangulation approach. The indicators of mathematical literacy skills studied were 1) Communication; 2) Mathematization; 3) Strategies in problem solving; 4) Use of language and symbolic operations; formal and technical; 5) Reasoning and argumentation skills. The findings of this study revealed that only one indicator, the communication indicator, was mastered by students in the low mathematical literacy category. Three indicators, namely communication indicators, problem solving techniques and mathematical communication indicators, can be mastered by students with medium mathematical literacy. Students with high mathematical literacy were able to understand and use each sign correctly. Students at SMA Negeri 1 Slogohimo have an average percentage of low mathematical literacy ability of 21%, medium mathematical literacy ability of 18%, and high mathematical literacy ability of 61%

SOCIAL CRITICAL REVIEW OF ISLAMIC EDUCATION BASED ON LOCAL WISDOM VALUES

AbstractWriting this journal aims to find out that the process of Islamic education cannot be carried out uniformly but must understand the cultural context from the results of the identification of local cultural treasures as social institutions that functionally act as a set of problem-solving techniques that are passed down as culture from one generation to the next. This research method is a research library using descriptive analysis. The results of this study indicate that Islamic education based on local wisdom is one of the strategies for building the Indonesian nation's civility with the values of wise practices. In a conception of Western philosophical values, the terms altruism and hard work are known.

PEGARUH MODEL PEMBELAJARAN CREATIVE PROBLEM SOLVING TERHADAP KETERAMPILAN BERPIKIR KREATIF PADA SISWA KELAS V SD

This study intends to determine the impact of Creative Problem Solving (CPS) on student’s creative thinking as well as the reactions of students to the use of Creative Problem Solving technique. This lack of student participation in the teaching and learning processes is what motivated the researcher to conduct this study. The only teaching strategy that can improve student’s ability for creative though is Creative Problem Solving. One group pre-test and post-test models were employed in the quantitative model for this study. This study was carried out for fifth grades students at SDN Lemahputro 1 Sidoarjo. With fiftheen 15 students served as the sample for this research. The results of the student questionnaires and a paired sample T-test with a sig. 0,05 were employed in this study. The outcame of the hypothesis measurement is 0,00 because 0,00 < 0,05, meaning that H1 was rejected since it could be inferred that the creative problem solving approach had an impact on student’s creative thinking. As 85% of the students responded to the questionnaires, it is reasonable to assume that they were quite comfortable with the creative problem solving method.

Socratic Questioning Sebagai Solusi Masalah Waswas: Pendekatan Hadis Terpilih

Several hadiths reported by the Prophet Muhammad ﷺ contain several questions and answers about a topic. It discusses a lot about all the issues that occur, as well as answers to the issues that are provided. However, questions and answers from hadiths on mental issues have long been employed as one of the therapies used by psychiatrists and clinical psychologists today, known as Socratic inquiry. This technique is significant in the process of mental health therapy, particularly for waswas or obsessive-compulsive disorder (OCD), as well as for other mental disorders such as anxiety disorder. Based on a knowledge of Hadith jurisprudence, the purpose of this research is to compile those hadiths linked to waswas that contain features of Socratic inquiry. A total of four hadiths have been recognised as being associated with misgiving and the use of Socratic inquiry as a problem-solving technique. As a result, three forms of Socratic inquiry have been developed based on four hadiths linked to misgiving, namely Questions of Clarification, Questions About the Question, and Questions that Probe Assumptions. This study is anticipated to emphasise the chosen hadith method as one component of treatment in mental health, specifically the waswas issue.

Development and Validation of STEM-Based Science Digital Worksheet on Object Motion Material for Junior High School Students

In the present day, it is anticipated that students possess the ability to effectively utilize digital technology to process information and address contextual problems. One possible course of action would be to develop a STEM-based Science Digital Worksheet on the Material of Object Motion. The STEM aims to facilitate the application of contextual problem-solving techniques through the utilization of students' literacy and numeracy skills. The scope of this study encompasses the field of research and development, commonly referred to as R&D. The R&D model employed ADDIE. One of the stages defined in this model is the developmental stage, which is intended to assess and evaluate the product through expert validation tests. The validators comprised of educators in the field of Integrated Science at FMIPA Semarang State University, ICT experts at SMA Negeri 1 Kudus, and science teachers at SMP 2 Dawe Kudus. The obtained media validation results from three experts yielded a value of 95%, while material experts obtained 96.67%. As a result, both were classified as highly feasible. It can be concluded that the Science Digital Worksheet is appropriate for use in learning activities

Analysis of Determination of Sea Toll Routes in Eastern Indonesia (KTI) Using Dynamic Programming

The sea highway program is part of the fourth pillar, namely the pillars of the maritime economy, infrastructure and increasing welfare, one of the seven pillars of Indonesia's Maritime Policy (KKI). The aim of the Sea Highway Program is to grow the maritime economy by turning the sea into a production and marketi ng center between the Indonesian territory and the islands and surrounding areas. This study aims to analyze the decision of maritime highway routes in Eastern Indonesia Region (KTI) in order to provide the best route with a minimum distance. Four shipping highway routes from Surabaya to Eastern Indonesia Region, namely route T-13 (Tanjung Perak-Rote (Ndao)-Sabu (Biu)-Tanjung Perak), T-14 (Tanjung Perak-Lembata (Lewoleba)-Tabilota/Larantuka- Tanjung Perak), T-15 (Cape Perak-Makassar (Soekarno Hatta)-Jailolo-Morotai (Daruba)-Tanjung Perak), and T-18 (Tanjung Perak-Badas-Bima-Merauke (Kelapa Lima)-Tanjung Perak) combined into 1 (one) route from Tanjung Perak to Merauke, resulting in 1 (one) optimal route with the minimum distance obtained from the smallest value at each stage . This study uses quantitative methods and Multistage Graph problem-solving techniques with Dynamic Programming backward or bottom-up methods, and primary data collection through interviews and secondary data such as: documents/journals/books. The selected optimal route is (Tanjung Perak-Makassar-Tabilota/Larantuka-Sabu (Biu)-Merauke (Kelapa Lima)) with a distance from Tanjung Perak to Makassar is 437 Nm. Makassar to Tabilota/Larantuka is 340 Nm. Tabilota/Larantuka to Sabu (Biu) is 163.8 Nm. Sabu (Biu) to Merauke (Kelapa Lima) is 1261.24 Nm. So that the total shipping distance from Tanjung Perak to Merauke is 2202.04 Nm.

A Pair-Task Heuristic for Scheduling Tasks in Heterogeneous Multi-cloud Environment

Heterogeneous multi-cloud environments make use of a collection of diverse performance rich cloud resources, linked with huge-speed, performs varied applications which are of computational nature. Applications in the multi-cloud environment require distinct computational features for processing. Heterogeneous multi-cloud domain well suits to satisfy the computational need of very big diverse nature of collection of tasks. Scheduling tasks to distributed heterogeneous clouds is termed NP-complete which leads to the ultimate establishment of heuristic problem solving technique. Identifying the heuristic which is appropriate and best still exists as a complicated problem. In this paper, to address scheduling collection of ‘n’ tasks in two groups among a set of 'm' clouds, three heuristicsPair-Task Threshold Limit (PTL), PTMax-Min, and PTMin-Max are proposed. Firstly, proposedheuristics calculate tasks threshold valuebased on the tasks attributes to determine the tasks scheduling order and then tasks are sorted in descending order of threshold value. Group 1 comprises ([n/2]) tasks ordered in descending value of threshold. Group 2 comprises remaining tasks ([n/2] − 1) ordered in ascending value of threshold. Secondly, tasks form group 1 are scheduled first based on minimum completion time, and then tasks in group 2 are scheduled. The proposed heuristicsare compared with existing heuristics, namely MCT, MET, Min-Min using benchmark dataset. The proposed approaches PTL, PTMax-Min, and PTMin-Max explicitly shows the better results in terms of reduced makespan, completion time, response time and more resource utilization compared to MCT, MET, and Min-min.

Theoretical Models Explaining the Level of Digital Competence in Students

In the new global scene, digital skills are a key skill for students to seize new learning opportunities, train to meet the demands of the labor market, and compete in the global market, while also communicating effectively in their everyday and academic lives. This article presents research aimed at relating the impact of personal variables on the digital competence of technical problem solving in Spanish students from 12 to 14 years old. A quantitative methodology with a cross-sectional design was employed. A sample of 772 students from 18 Spanish educational institutions was used. For data collection, an assessment test was designed (ECODIES®) based on a validated indicator model to evaluate learners’ digital competence (INCODIES®), taking as a model the European framework for the development of digital competence. Mediation models were used and theoretical reference models were created. The results allowed us to verify the influence of personal, technology use, and attitudinal variables in the improvement of digital skill in technical problem solving. The findings lead to the conclusion that gender, acquisition of digital devices, and regular use do not determine a better level of competence.

Improving Learning Time Management Using Problem Solving Techniques in Group Guidance Activities

The background of this research is based on the phenomenon that occurs that success in learning is influenced by flexible and regular study time management. The purpose of this study was to determine the effectiveness of group guidance problem solving techniques to improve student learning time management. The research used quantitative methods, namely experiments. Research subjects class VIII E students at SMP Negeri 2 Moyudan who have been selected according to the sufficient category. Data collection techniques used scale and observation. Data analysis techniques used the T-test formula. The results showed that based on the results of paired samples t-test, pretest and posttest were obtained. sig.(2-tailed) value of 0.000 then compared to the sig. 5% = 0.05, it can be determined that 0.000 < 0.05 means that Ho is rejected and Ha is accepted. The conclusion is that group guidance services using problem solving techniques is effective to improve student learning time management at SMP Negeri 2 Moyudan.
 

Complementing Solutions for Facility Location Optimization via Video Game Crowdsourcing and Machine Learning Approach

The facility location problem (FLP) is a complex optimization problem that has been widely researched and applied in industry. In this research, we proposed two innovative approaches to complement the limitations of traditional methods, such as heuristics, metaheuristics, and genetic algorithms. The first approach involves utilizing crowdsourcing through video game players to obtain improved solutions, filling the gap in existing research on crowdsourcing for FLP. The second approach leverages machine learning techniques, specifically prediction methods, to provide an efficient exploration of the solution space. Our findings indicate that machine learning techniques can complement existing solutions by providing a more comprehensive approach to solving FLP and filling gaps in the solution space. Furthermore, machine learning predictive models are efficient for decision making and provide quick insights into the system’s behavior. In conclusion, this research contributes to the advancement of problem-solving techniques and has potential implications for solving a wide range of complex, NP-hard problems in various domains.

Using Concept Inventory for Assessing Conceptual Knowledge in the Signals and Systems Course

Abstract: The engineering schools usually target problem-solving skills in students instead of conceptual development, which is an essential skill for transformation from novice to professional engineer as per the program objective. Improving a student's conceptual knowledge can help students understand a problem better and develop a better solution. Conceptual understanding also assists students in identifying gaps in their problem-solving techniques. This paper attempts to administer a Signal and System Concept Inventory (SSCI) to test the conceptual knowledge of core concepts of signals and systems course and then identify the correlation of post-test scores with the student's performance in the end-term exam. The result shows that the students who scored above 80% in concept inventory also performed outstanding in the end-term examination. The result also indicates that most of the students able solve questions on background mathematics and polezero plots but struggled with convolution and Fourier analysis. Keywords: concept inventory, conceptual understanding, assessment, engineering education

Survey of Sustainable Energy Sources for Microgrid Energy Management: A Review

Renewable energy sources are nowadays a viable choice to satisfy the rising energy consumption and promote the advancement of sustainable development. These systems are integrated into microgrids using a variety of technological solutions to ensure customer communication and distributed generation facilities in an optimal way. Energy management in microgrids refers to the information and control system that provides the necessary functionality to guarantee that the generating and distribution systems produce energy at the lowest expenses. This study analyzes the various optimization objectives, constraints, problem-solving techniques, and simulation tools used for connected and freestanding microgrids. It reviews the literature on energy control in microgrids powered by sustainable energy. Energy storage technology is also viewed as an intriguing alternative to managing the intermittent nature of renewable energy because of its advanced techniques, increased energy efficiency, and capacity to perform tasks such as frequency response. The final phase suggests future suggestions, particularly for the model-based prediction of energy storage systems.

Role of Artificial Intelligence in different aspects of Public Health

In the next decade of disease surveillance research, innovative and novel techniques are required to utilise massive quantities of complex and multi-dimensional data, effectively. Public health is one of the most significant domains of public governance and artificial intelligence has emerged as an innovative problem-solving technique in this domain. Artificial intelligence is a requirement for the early identification of diseases and disasters in order to prevent high mortality rates and reduce economic burden by timely providing appropriate healthcare. This detection is made possible in this research by identifying patterns in the database. This review shows that the use and development of AI techniques has increased in the field of public health over the past few years and most of the existing studies show a positive impact of AI in the domain of public health. This study is divided into three portions. The first portion reviews the role and potential usage of artificial intelligence in epidemics, since it is very important to timely investigate them and AI has the potential to cope with them. The second part of the review provides a detailed discussion about serious game usage in public health. Serious games are used for the training and rehabilitation of the gamer. The third part deals with the management of public health emergencies including evacuation, causality response, and information processing.