Task In Process Research Articles

Conceptual framework of coaches’ decision-making in conventional sports

IntroductionA coach’s managerial and pedagogical tasks in the sports training process constitute the substantive core of their work, while decision-making serves as the fundamental method underpinning these tasks. Some decisions made by coaches result from deliberate, analytical thinking, which involves extensive information gathering, analysis, and discussion. Others, however, are made quickly and spontaneously, triggered by unforeseen situations during training or competition that demand immediate action. Consequently, the purpose of this study is to develop a conceptual framework for understanding coaches’ decision-making behavior in conventional sports. This framework aims to establish appropriate relationships between the various decisions coaches make during the training process and theoretical concepts related to decision-making, both in general and within the coaching context.MethodsTo design the research, we used the methodology of a conceptual paper and a “model paper” approach, which seeks to build a theoretical framework that predicts relationships between distinct research concepts and scientific disciplines, aiming to integrate them into a cohesive model of coaches’ decision-making behavior.ResultsThe proposed conceptual framework encompasses a comprehensive range of situations that may arise during the sports training process and potential ways to address them. This framework identifies different types of decisions and characteristics associated with coaches’ decision-making behavior. It incorporates various sport-specific and general theories of decision-making and cognitive functioning to offer a deeper understanding of how coaches process and execute decisions in diverse contexts.DiscussionThe developed conceptual framework outlines three primary types of decisions—strategic, tactical, and operational—each playing a distinct role in the broader sports training process. These decisions are based on different cognitive processes, which manifest in varied decision-making behaviors and are reinforced by specific leadership styles. The practical value of this framework lies in its potential application for selecting appropriate experts to address the diverse decision-making scenarios encountered in sports training. This ensures the alignment of decision-making styles with the requirements of specific training situations, thereby enhancing the effectiveness and outcomes of the coaching process.

Dual-Language Sentiment Analysis: A Comprehensive Evaluating SVM, Logistic Regression, XGBoost, and Decision Tree Using TF-IDF On Arabic and English Dataset

Sentiment analysis (SA) is a growing area of study that straddles a number of disciplines, including machine learning, data mining, and natural language processing. It is focused on the automatic extraction of viewpoints presented in a certain text. Many studies have been conducted in the area of sentiment analysis because to its broad uses, particularly on texts in English, whereas other languages like Arabic have gotten less attention. The Arabic language presents several difficulties, such as its rich morphology and the difficulty of tracing words back to their original roots. Arabic comments have been analyzed and categorized into good and negative attitudes using a framework. With the aim of evaluating any tweet, opinion, purpose, or reputation, such as a university, company, mobile, and others, the research analyzes the comments made by users of the social networking site Twitter. It does this by using classification technology and machine learning, which are among the fundamental tasks of the data mining process used in the larger process, which is to explore knowledge . This search helps the user to access the evaluation of other users through their tweets and comments on the social networking site for an opinion immediately and automatically, and then the process of uploading and evaluating the opinions using appropriate algorithms for this purpose as(Decision Tree classifier DTC , XGboost, Logistic Regression LR, Support Vector Machine SVM )with Term Frequency-Inverse Document Frequency TF_IDF

AN IMPROVED MATHEMATICAL MODEL OF THE METHOD OF FULLY PREPARING THE DETERMINATION OF FIRING UNITS FOR HITTING THE INFORMATION AND CALCULATION COMPONENT OF THE AUTOMATED FIRE CONTROL SYSTEM OF COMBAT VEHICLES OF REACTIVE ARTILLERY

Context. As part of the automation of the fire control system of rocket artillery combat vehicles, in relation to the preparation of data for firing and fire control, the information and computing process of this system has been improved, namely, the mathematical model of the method of fully preparing the determination of installations for firing projectiles used in rocket salvo fire systems has been improved. In the system of differential equations of the mathematical model of the information and computing process of the component of the automated fire control system of combat vehicles of jet artillery, weighting functions for air temperature, wind influence for the active and passive sections of the projectile flight trajectory and the section of the opening of combat elements have been introduced, which allows determining the weighting coefficients for them for each projectile type. Objective. To improve the information and calculation component of the automated fire control system of combat vehicles of reactive artillery, by improving the mathematical model of the method of full preparation of the determination of installations for firing on damage. Having proposed a system of differential equations that will take into account the weighting functions of air temperature, wind influence for active and passive sections of the projectile flight path and the section of the opening of combat elements, and will also give the opportunity to determine weighting coefficients for each type of projectile based on them, which in turn will lead to an increase the accuracy of determining firing settings. Method. The proposed analytical method allows: to calculate the weighting coefficients for each type of rocket, characterizing the process of the approach of the rocket flight to the tabular trajectory and to set the initial conditions necessary for solving the differential equations of the mathematical model of the information-computing process of the component of the automated fire control system of combat vehicles of rocket artillery; to increase the accuracy of determining firing positions when performing firing tasks, which makes it possible to quickly respond to a change in the combat situation by means of changes in the softwaremathematical process of the automated fire control system; effectively and efficiently ensure the development or clarification of textual and graphic administrative and combat documents based on the results obtained using differential equations of the mathematical model of the information-computational process of the component of the automated fire control system. Results. The improved information and calculation component of the automated fire control system of combat vehicles of jet artillery was tested during the conduct of hostilities. The system of differential equations of the mathematical model of the information-computing process of the component of the automated fire control system of combat vehicles of reactive artillery ensures a timely response to a change in the situation in the information-computational process of the component of the automated fire control system of combat vehicles of reactive artillery during firing and fire control. Provides an opportunity to efficiently and quickly ensure the development or clarification of textual and graphic administrative and combat documents based on the information received during the execution of fire missions. Conclusions. The calculations based on the proposed system of differential equations confirm the improvement of the information-calculation component of the automated fire control system of jet artillery combat vehicles and allow timely response to changes in tasks in the information-calculation process during firing and fire control, as well as effectively and quickly ensure the formation of formalized messages and documents based on the information received during the execution of a fire mission by units of reactive artillery. Prospects for further research are the creation of agreed mathematical methods, models, algorithms and programs for the implementation of the goals and tasks of firing and fire control when compiling Firing Tables for prospective or received combat vehicles of reactive artillery from partners.

Value vectors in the education system of students at a modern Russian higher educational institution

The article states that the most important task of the current educational process in higher educational institutions is not only the training of a professional, but also the moral education of modern Russian youth. The author believes that the value vectors in the system of educating young specialists should be the formation of cultural identity, humanistic consciousness, and moral goal-setting among the younger generation of Russia. It is noted that cinema and music play a significant role in this process, which have acquired special significance as a tool for the mass familiarization of young people with national cultural codes in the conditions of information and technological development of post-industrial society. The author proposes different types of activities through mass art forms that contribute to the formation of national and cultural identity.

Slovak database of speech affected by neurodegenerative diseases

A new Slovak speech database EWA-DB was created for research purposes aimed at early detection of neurodegenerative diseases from speech. It contains 1649 speakers performing various speech and language tasks, such as sustained vowel phonation, diadochokinesis, naming and picture description. The sample of speakers consists of individuals with Alzheimer’s disease, mild cognitive impairment, Parkinson’s disease, and healthy controls. In this article we describe the EWA-DB development process, the language and speech task selection, patient and healthy control recruitment, as well as the testing and recording protocol. The structure and content of the database and file formats are described in detail. We assume that the presented database could be suitable for the development of automatic systems predicting the diagnoses of Alzheimer’s disease, mild cognitive impairment, and Parkinson’s disease from language and speech features.

Task design and rater effects in task‐based language assessment

AbstractTask‐based language assessment represents a major component of task‐based language teaching syllabi. Current perspectives emphasise the importance of tasks in the assessment process, suggesting that adherence to influential models of language production during task design yields predictable test outcomes. The current study contends that the significance of the rater has been overlooked, resulting in adverse consequences when employing current task‐based frameworks. The article reviews literature on the rating process, with a focus on interactions between rater characteristics, rating scales, and rater effects. Drawing on the findings of the review, the author proposes a revised model of task‐based language assessment that curbs the impact of task design on test scores. The revised model underscores the need to regard raters as active agents in the assessment process to enhance validity and fairness and makes recommendations about minimizing rater effects.

Architectural Suggestions for Ontology Management

Abstract This document describes the steps that required for creating and maintaining an ontology; for exploiting an ontology in order to describe data from one or more data sources; and for developing services and applications that provide unified access and insightful analysis on the data. The document provides the state of the art of the various tools and software components that exist and can be used for carrying out various tasks of the overall process. The components are grouped based on their intended use and for each one of them a concise description, as well as other useful details (i.e. if they are open‐source, their license, etc.), are provided. For each step or task, the involved software components are also described in a table presenting their details with respect to various dimensions (e.g. open‐source, license, available online, key advantages, etc.), in order to enable their quick comparison. Moreover, successful examples of semantic data integration are presented, i.e., for cases where a top‐level ontology is used for integrating data for the cultural and biodiversity domain, and services for large‐scale semantic data integration (including hundreds of datasets from several domains). Furthermore, it provides the high‐level architectural suggestions that can be used as a basis for the actual implementation of any ontology‐based system; the described processes and tools can be exploited for the development of the ontology‐based functionality. Finally, it offers the adaptations of the proposed architecture for the EFSA case studies, by providing details about their components and indicative pipelines and tools.

An Improved Combinatorial Benders Decomposition Algorithm for the Human-Robot Collaborative Assembly Line Balancing Problem

As an emerging technology, human-robot collaboration (HRC) has been implemented to enhance the performance of assembly lines and improve the safety of human workers. By integrating the advantages of human workers and collaborative robots (cobots), HRC enables production systems to process tasks consecutively, concurrently, or collaboratively. However, the introduction of cobots also makes the corresponding human-robot collaborative assembly line balancing problem more complex and difficult to solve. To solve this problem, we first propose an enhanced mixed integer program (EMIP) with various enhancement techniques and tighter bounds, and then, we develop an improved combinatorial Benders decomposition algorithm (Algorithm ICBD) with new local search strategies, Benders cuts, and acceleration procedures. To verify the effectiveness of our proposed model and algorithms, we conduct extensive computational experiments, and the results show that our proposed EMIP model is significantly better than the existing mixed integer program model; the percentages of instances that can obtain feasible and optimal solutions are increased from 82.42% to 100% and from 29.17% to 43.5%, respectively, whereas the average gap is decreased from 19.81% to 5.64%. In addition, our proposed Algorithm ICBD can get 100% of feasible solutions and 65.92% of optimal solutions for all of the test instances, and the average gap is only 1.49%. Moreover, compared with existing Benders decomposition methods for this problem, our approach yields comparatively better solutions in notably shorter average computational time when run in the same computational environment. History: Accepted by Andrea Lodi, Area Editor for Design & Analysis of Algorithms–Discrete. Funding: This research was supported by the National Natural Science Foundation Council of China [Grants 72401214, 92167206, 7221101377, 72471169, and 72231005], the Ministry of Education of China [Grant 24YJC630078], and Computation and Analytics of Complex Management Systems (Tianjin University). This research was also supported by the Tianjin Natural Science Foundation Project [Grant 23JCQNJC01900] and the Tianjin Philosophy and Social Science Planning Project [Grant TJGL21-016]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0279 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0279 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .

Decentralized multi-hop data processing in UAV networks using MARL

Unmanned Aerial Vehicles (UAVs) have become integral to numerous applications, prompting research towards enhancing their capabilities. For time-critical missions, minimizing latency is crucial; however, current studies often rely on sending data to ground station or cloud for processing due to their limited onboard capacities. To leverage the networking capabilities of UAVs, recent research focuses on enabling data processing and offloading within the UAV network for coordinated decision-making. This paper explores a multi-hop data offloading scheme designed to optimize the task processing and resource management of UAVs. The proposed distributed strategy uses multi-agent reinforcement learning, where UAVs, each with varying computational capacities and energy levels, process and offload tasks while managing energy consumption and latency. The agents, represented as actor-critic models, learn and adapt their actions based on current state and environment feedback. The study considers a consensus-based method to update learning weights, promoting cooperative behavior among the agents with minimum interaction. Through multiple training episodes, the agents improve their performance, with the overall system achieving faster convergence with high rewards, demonstrating the viability of decentralized data processing and offloading in UAV networks.

The Internet as an object of study of criminalistics science

Relevance. The Internet acts as an object accumulating a large array of results of user actions in the form of electronic and digital traces, as well as a significant amount of other information that can be used in the investigation of crimes. Given the ongoing growth of attacks in which the global network has become a means of committing them, it is necessary to offer investigative authorities recommendations on using the Internet as a source of necessary information and as a means of solving the tasks of criminal proceedings.The purpose of the research is to determine from which sides and to what extent the Internet manifests itself in those patterns that are the subject of criminalistics science, in order to propose a systematic approach to the use of information resources of the network in solving the tasks of the investigation process. Objectives: to characterize the Internet as a source of electronic digital traces and other criminally significant information; to show that techniques, tools and methods of working with evidence implemented through the Internet are criminalistics; to highlight the features of the Internet as a manifestation of the mechanism of criminal activity and the source of the criminalistic characteristics.Methodology. The methodological basis of the research was the dialectical method of cognition, and a set of general scientific and private scientific research methods (system-structural, formal-logical, predictive, etc.) were also used. Results. Separate theoretical provisions of the methodology of using the Internet in the investigation of crimes have been developed.Conclusion. The Internet, reflecting virtual life, can be represented as one of the sides of the object of criminalistics, acting as a functional side of both criminal and crime detection and investigation activities, and the patterns of the mechanism of various types of crimes that manifest themselves on the network, the emergence and finding of information about the crime and its participants, the possibility of search and obtaining criminally significant information, securing, researching and using it as evidence, as well as the use of the Internet as a means of judicial research and crime prevention, the Internet is an element of the subject of criminalistics science.

SITUATIONAL-ROLE TASKS IN THE FORMATION OF COMPETENCIES AIMED AT OWNING COMBAT FIGHTING TECHNIQUES IN CADETS OF THE MIA OF RUSSIA

In this paper, the authors of the study consider the issues of including situational role-playing tasks in the educational process of cadets of the Ministry of Internal Affairs of Russia within the framework of the implementation of the discipline “Physical training”. The inclusion of these tasks allows you to simulate quasi-professional actions in training sessions. By quasi-professional actions, we understand a task, a model that is built around a professional object, phenomenon or process, the solution of which is carried out by means of a general education discipline, the main requirement of which is directly related to further professional activity. In particular, quasi-professional actions can describe a professional process, as well as partially characterize a professional object. Using the example of the educational material, situational role-playing tasks are proposed and an algorithm for their implementation is given within the framework of actions to ensure personal safety measures and perform tasks in simulated conditions. The paper presents the key components of these competencies, together with the proposed algorithm, representing the scientific novelty and practical significance of this study.

LAIKO JUOSTOS UŽDUOČIŲ TAIKYMAS MOKANT SUPRASTI ISTORINĮ LAIKĄ PRADINĖS MOKYKLOS TREČIOJE KLASĖJE

School history content in recent years has been shifting away from the "grand" story of history towards historical literacy, based on critical thinking and historical research skills. This encourages the explora-tion of the possibilities of developing these skills from primary school onwards, using a variety of ac-tive learning methods in social education classes. The aim of the study was to determine whether the targeted use of timeline tasks in the educational process can improve the historical time comprehension skills of third grade pupils in Lithuanian primary schools. The focus of the study was the use of timeline tasks in the understanding of historical time. The aim of the study was to explore the changes in the historical time comprehension skills of 3rd grade pupils in a primary school when timeline tasks are purposefully applied in the educational process. An action re-search study was carried out, 16 educational activities were organized in two primary school third grade classes. In one classroom, 8 activities involved the purposeful use of timeline tasks. Students' historical time comprehension skills in the category of timeline application were assessed through quantitative and qualitative content analysis of the questionnaires completed by students. It was found that before the educational activities, some of the pupils in grade 3 had not reached the level of devel-oping understanding of historical time at level A in the category of application of the timeline. A com-parative analysis of the data after the educational activities showed that the pupils in Class X who worked on the timeline tasks during the educational activities achieved higher results than their peers in Class Y who did not work on the timeline tasks during the educational activities. The results of the study suggest that the use of timeline activities in history learning enables students to better orient themselves in historical time and to achieve higher learning outcomes. Keywords: understanding historical time, timeline application, primary education, action research

Navigating the moral maze: a literature review of ethical values in business process management

PurposeBusiness process management (BPM), as a pillar of information systems (IS) research, has become more complex with the advent of new technologies, emphasizing the need for moral and ethical perspectives. To foster moral behavior and responsible action, including ethical values in IT systems and processes can be a solid option. By incorporating a socio-technical perspective, we are able to analyze the various aspects of BPM and organizational processes and the incorporated values. We find an overall acknowledgment of the importance of values and ethics in BPM.Design/methodology/approachThis publication explores ethical values within BPM through a systematic literature review (SLR). The study aims to identify the ethical dimensions inherent in BPM and their practical implications in process management and task execution. The methodological approach adopted is a SLR (Boell and Cecez-Kecmanovic, 2015), adapting the PRISMA guidelines (Page et al., 2021) to identify 82 articles from 21 top IS journals suggested by Lowry et al. (2013).FindingsA descriptive framework is developed to explain the use and application of ethical values within business processes. This framework enables practitioners and researchers to categorize and understand the various ethical considerations involved in BPM. It provides a structured approach highlighting the interrelation between process perspectives and ethical values, demonstrating how different BPM approaches may have varying ethical implications. We compare past and future research in business processes, identifying areas for further investigation and theoretical development. A historical analysis of values and literature also helps contextualize contemporary discussions on ethics in BPM, shedding light on the evolution of ethical considerations within this domain.Originality/valueOur study contributes to a more nuanced understanding of BPM, highlighting the importance of considering ethical values and socio-technical perspectives in designing and implementing business processes. These findings contribute to understanding the values associated with different types of processes and their employment and highlight potential areas for future research. Our study provides ethics-oriented research in IS with novel insights by examining BPM from an ethical value perspective. We contribute to the BPM literature by examining which values are applied in which process types from which perspective. In addition, our research suggestions provide food for thought for both research streams.

Risk Assessment of Employing Digital Robots in Process Automation

Using digital technologies is essential to gain a competitive advantage in the global market by adapting to new business models. While digital technologies make business processes efficient, they enable companies to make faster and more accurate decisions by automating daily and routine process tasks. Robotic process automation (RPA) automates routine and repetitive business processes, allowing many jobs performed by humans to be performed faster. This way, advantages such as reduced error rates, reduced costs, increased production speed, and labor productivity are provided. For the successful implementation of RPA, potential risks need to be considered. In this study, failure mode and effect analysis (FMEA) based on decomposed fuzzy sets (DFSs), a new extension of intuitionistic fuzzy sets, has been used to evaluate subjectiveness in expert judgments. Differing from the other extensions of fuzzy set theory, the advantage of DFSs is to simultaneously consider decision-makers’ optimistic and pessimistic answers. Thus, the answer given by the decision-maker to the positive and negative questions on the same subject defines the indeterminacy of the decision-maker, and the method takes this indeterminacy into account in the evaluation. This study assesses and evaluates the potential risks of six digital robots in process automation. Thirteen risks were individually assessed for each automated process. This study found “Sustainability challenge” critical in three processes, “Absence of governance management” in two, and “Security“ in one. Variability in risk importance arose from process vulnerabilities.

Optimization of office process task allocation based on deep reinforcement learning

In office platforms, we often need to face the situation of a large number of parallel heterogeneous process tasks. This not only tests the ability of the task executors themselves, but also puts forward requirements for the performance of the collaborative scheduling system. Using the reinforcement learning method, combined with quantitative analysis such as collaborative coordination and slackness, and based on the Markov Bollinger theory, a multi-agent Bollinger model is proposed to realize the optimization scheduling system with overall process coordination and maximum completion time as the optimization objectives, thereby improving the overall execution efficiency. Taking the real business system process as the test scenario, under the same optimization objective, the reinforcement learning algorithm based on D3QN and DRL and the meta-heuristic algorithm based on ant colony are compared to verify the effectiveness of the proposed method.

Interdisciplinary aspect in the organization of research and project activities of students of a technical university: on the example of the "Graph theory" discipline

The article considers the possibilities of using educational and professional humanitarian-oriented research tasks in the educational process of the university as a means of forming and developing research skills of students of technical specialties. The process of solving educational and professional tasks is considered by the example of constructing an optimal route using graph theory methods.

Ship recycling process in Bangladesh and a survey-based risk assessment with mitigation proposal

Ship recycling industries play a significant role in the economic development of South Asian countries, including Bangladesh. In the wake of entering the Hong Kong Convention (HKC) in June 2025, the industry aims to improve its overall safety standards cost-effectively. However, due to the restrictive nature of the industry, solutions based on field surveys are limited. This study successfully articulates the indigenous industry knowledge of the recycling process in Bangladesh after carefully studying the practices followed by the existing ship recycling yards in the country. Based on field surveys conducted across 18 ship recycling yards in Bangladesh, the risk patterns inherent in the ship recycling industry are studied; for example, highly hazardous tasks in the ship recycling process are found to be (i) explosion hazards during primary cutting operations at the intertidal zone, (ii) falling hazards during inspections at the outer anchorage, (iii) falling and crushing hazards during block cutting and handling heavy objects. Industry experts and scholars consider the perception of the risk pattern regarding the current practices of ship recycling activities to cover a broader perspective of this issue. The correlation of survey outcomes with actual accident cases is comparable. Finally, practical recommendations for minimising risks have been recommended, especially in high-risk workplace areas. The study adds knowledge to the existing literature by giving a clear picture of evidence-based findings for this sector and helps improve the industry's overall safety standard.

Security-Aware Deadline Constraint Task Scheduling using Hybrid Optimization of Modified Flying Squirrel Genetic Chameleon Swarm Algorithm

Cloud computing enables cost-effective resource sharing in hybrid clouds to tackle the problem of insufficient resources by elastically scaling the service capability based on the users’ needs. However, task scheduling (TS) in cloud environments is challenging due to deadline-based performance and security constraints. To remove the existing drawbacks based on deadline and security constraints, a Security-Aware Deadline Constraint TS (SADCTS) approach is presented using a hybrid optimization algorithm of the Modified Flying Squirrel Genetic Chameleon Swarm Algorithm (MFSGCSA). The proposed MFSGCSA is developed by integrating the genetic operators into CSA and combining it with the modified Flying Squirrel Optimization (FSO) algorithm in which the position update and global search equations are enhanced by adaptive probability factor to reduce the local optimum problem. In this SADCTS approach, the task assignment process is modeled into an NP-hard problem concerning a multi-level security model using user authentication, integrity, and confidentiality. This maximizes tasks’ completion rate and decreases the resource costs to process tasks with different deadline limitations. The optimal schedule sequence is obtained by MFSGCSA, where tasks are scheduled concurrently based on security constraints, demand, and deadlines to improve the prominence of cost, energy, and makespan. Experiments are simulated using the CloudSim toolkit, and the comparative outcomes show that the suggested SADCTS approach reduced the makespan, cost, and energy by 5-20% more than the traditional methods. Thus, SADCTS provides less task violation of 0.0001%, high energy efficiency of 700GHz/W, high resource utilization of 92%, less cost efficiency of 72GHz/$, and less makespan of 480minutes to satisfy the necessary security and deadline requirements for TS in shared resource hybrid clouds.

TAWFN: a deep learning framework for protein function prediction.

Proteins play pivotal roles in biological systems, and precise prediction of their functions is indispensable for practical applications. Despite the surge in protein sequence data facilitated by high-throughput techniques, unraveling the exact functionalities of proteins still demands considerable time and resources. Currently, numerous methods rely on protein sequences for prediction, while methods targeting protein structures are scarce, often employing convolutional neural networks (CNN) or graph convolutional networks (GCNs) individually. To address these challenges, our approach starts from protein structures and proposes a method that combines CNN and GCN into a unified framework called the two-model adaptive weight fusion network (TAWFN) for protein function prediction. First, amino acid contact maps and sequences are extracted from the protein structure. Then, the sequence is used to generate one-hot encoded features and deep semantic features. These features, along with the constructed graph, are fed into the adaptive graph convolutional networks (AGCN) module and the multi-layer convolutional neural network (MCNN) module as needed, resulting in preliminary classification outcomes. Finally, the preliminary classification results are inputted into the adaptive weight computation network, where adaptive weights are calculated to fuse the initial predictions from both networks, yielding the final prediction result. To evaluate the effectiveness of our method, experiments were conducted on the PDBset and AFset datasets. For molecular function, biological process, and cellular component tasks, TAWFN achieved area under the precision-recall curve (AUPR) values of 0.718, 0.385, and 0.488 respectively, with corresponding Fmax scores of 0.762, 0.628, and 0.693, and Smin scores of 0.326, 0.483, and 0.454. The experimental results demonstrate that TAWFN exhibits promising performance, outperforming existing methods. The TAWFN source code can be found at: https://github.com/ss0830/TAWFN.

Arbitrary style transformation algorithm based on multi-scale fusion and compressed attention in art and design

In art and design, style conversion algorithms can fuse the content of one image with the style of another image, thereby generating images with new artistic styles. However, traditional style conversion algorithms suffer from high computational complexity and loss of details during row image conversion. Therefore, this study introduces VGG16 multi-scale fusion feature extraction in any style transition algorithm and introduces a compressed attention mechanism to improve its computational complexity. Then it designs an arbitrary style transformation algorithm on the ground of multi-scale fusion and compressed attention. The results showed that the designed algorithm took 0.014 s and 0.021 s to process tasks on the COCO Stuff dataset and WikiArt dataset, respectively, proving its high computational efficiency. The loss values of the designed algorithm are 0.046 and 0.052, respectively, indicating strong fitting performance and good generalization ability. The IS score and FID score of the design algorithm are 2.36 and 91.67, respectively, proving that the generated images have high diversity and quality. The above results demonstrate the effectiveness and practicality of design algorithms in art and design. It has important theoretical and practical value in promoting the development of style conversion technology, enhancing the creativity and expressiveness of art and design.