Association for Scientic Computing Electronics and Engineering (ASCEE): Open Journal Systems
Not a member yet
785 research outputs found
Sort by
Improving Efficiency and Effectiveness of Wheeled Mobile Robot Pathfinding in Grid Space Using a Genetic Algorithm with Dynamic Crossover and Mutation Rates
Full text linkIncorrect parameter tuning of crossover and mutation rates in Genetic Algorithms (GA) can negatively impact their effectiveness and efficiency in mobile robot pathfinding. This study focuses on improving the performance of wheeled mobile robots in grid-based environments by introducing a Dynamic Crossover and Mutation Rates (DCMR) strategy within the GA framework. The primary contribution of this research is enhancing the efficiency and effectiveness of mobile robot pathfinding, resulting in shorter average path lengths and faster convergence times. Additionally, this method addresses the challenge of selecting appropriate GA parameters while increasing the algorithm's adaptability to different phases of the search process. The DCMR approach involves linearly increasing the crossover rate by 10% (from 0% to 100%) and decreasing the mutation rate by 10% (from 100% to 0%) over every 10 generations during the GA's evolution. Unlike fixed parameter tuning or exponential and sigmoid parameter tuning—both of which require trial and error to determine optimal values—the DCMR method provides a systematic and efficient solution without additional computational cost. Experiments were conducted across eight scenarios featuring varying distances between the start and target points, with two obstacles randomly placed in the robot's environment. The results showed that implementing the DCMR method consistently identified the optimal path, reduced average path lengths by 0.99%, and accelerated algorithm convergence by 48.39% compared to fixed parameter tuning. These findings demonstrate that the DCMR method significantly enhances the performance of GAs for mobile robot pathfinding, offering a reliable and efficient approach for navigating complex environments
Creation of fiber art from fabric waste using weaving, collage, and patchwork techniques
Full text linkIn addition to contributing to economic growth, the textile industry has the potential to produce large amounts of fabric waste, which often ends up in trash cans and pollutes the environment. Responding to these conditions, this study aims to explore the use of fabric waste as the main material in the creation of fiber art, evaluate environmental and economic benefits, and see positive impacts on society. This research uses an art practice-based approach to create fiber art from waste materials using weaving, collage, and patchwork techniques. The method includes collecting and selecting fabric waste based on the type of textile material, applying various artistic techniques, and analyzing the aesthetics and functionality of the artwork made. The results of the study show that textile waste created through a combination of weaving, collage, and patchwork techniques can produce artistic and aesthetic fiber artworks. This fiber artwork contributes to the concept of sustainability in fine art and emphasizes that fabric waste can be converted into creative products to extend the life cycle of materials. Thus, it can open new opportunities in the recycling-based creative industry
Design an Optimal Nonlinear Fractional Order PI Controller for Controlling Congestion in Network Routers
Full text linkActive Queue Management (AQM) is a mechanism adapted for notifying senders with network congestion traffics before any overflow happens in the queue which is led to loss data. AQM technique can be applicable in different network size in different fields like industrial systems, colleges and government. In this paper, a nonlinear Fractional Order proportional Integral (NLFOPI) controller is proposed for controlling the Active Queue Management (AQM) system in a stable and robust behavior. An intelligent optimization algorithm called Pelican Optimization algorithm (POA) has been chosen for attain optimal system desired response based on tuning the proposed controller gains for minimizing the error depending on the use of Integral time absolute Error as a fitness function to maintain the whole tuning process based on Matlab program. The proposed NLFOPI controller is regarded as one of the fractional order controllers that depend on using one fractional variable for the integral term only, due to this the tuning parameter will be three instead of two also the nonlinear term will give an enhanced robustness that reflected clearly on system performance. The evaluation analysis represented by settling time, peak time, rise time and overshoot value appeared in system response are done, based on comparison with different classical controllers (PI-PID-FOPI) to show the performance of the proposed controller in different scenarios and then a robustness analysis is adopted by varying the desired queue number values in different time period and also by disturbance rejection when add disturbances signals with values ± 100 packets to desired number of queue in two different periods (15-35) sec., the results reflect how does the system faces these tests done efficiently. Based on simulation results, the NLFOPI controller is regarded as the best controller based on its faster peak time value (tp=3.8 sec) with stable response and a smooth rise time value (tr=1.8 sec.) also a fast-settling time (ts=3.4 sec.) is achieved with un noticeable overshoot (0.2%) if it is compared to other controllers then its robust response is appeared by achieving a satisfied stability and robustness
Recent Advances in Artificial Intelligence for Dyslexia Detection: A Systematic Review
Full text linkThe prevalence of dyslexia, a common neurodevelopmental learning disorder, poses ongoing challenges for early detection and intervention. With the advancement of artificial intelligence (AI) technologies in the fields of healthcare and education, AI has emerged as a promising tool for supporting dyslexia screening and diagnosis. This systematic review aimed to identify recent developments in AI applications for dyslexia detection, focusing on the methods used, types of algorithms, datasets, and their performance outcomes. A comprehensive literature search was conducted in 2025 across databases including ScienceDirect, IEEE Xplore, and PubMed using a combination of relevant MeSH terms. The article selection process followed the PRISMA guidelines, resulting in the inclusion of 31 eligible studies. Data were extracted on AI approaches, algorithm types, dataset characteristics, and key performance metrics. The results revealed that machine learning (ML) was the most widely applied method (58.06%), followed by multi-method (22.58%), deep learning (16.13%), and large language models (3.23%). Among the ML algorithms, Random Forest and Decision Tree were the most commonly used due to their robustness and performance on structured datasets. In the deep learning category, CNN were the most frequently used models, especially for image-based and sequential input data. The datasets varied widely, including digital cognitive tasks, EEG, MRI, handwriting, and eye-tracking data, with several studies employing multimodal combinations. Ensemble and hybrid models demonstrated superior performance, with some achieving accuracy rates exceeding 98%. This review highlights that AI, particularly ML and multimodal ensemble methods, holds strong potential for improving the accuracy, scalability, and accessibility of dyslexia detection. Future research should prioritize large-scale, multimodal datasets, interpretable models, and adaptive learning systems to enhance real-world implementation
Transformation of Lampung tapis cloth into modern fashion products through technical and material innovation: cultural and economic impacts
No full textThe transformation of Lampung tapis cloth into a modern fashion product through innovations in manufacturing techniques and materials used has had a significant impact on cultural and economic aspects. The purpose of this study is to analyze the transformation of tapis cloth with a focus on innovations in techniques and materials used and their impact on cultural and economic aspects. The research method used is descriptive qualitative. The data sources used are informants, places and events, and documents. This study collected data through observation, interviews, and document analysis. The data obtained were analyzed using an interactive model. The results of the study indicate that the transformation of Lampung tapis cloth through innovations in techniques and materials was carried out to adapt to the development of the times and dynamic consumer tastes, so that tapis cloth remains relevant and in demand by the wider community. The transformation of tapis cloth has an impact on the cultural aspect, namely supporting efforts to preserve regional culture, strengthening regional identity, and promoting Lampung culture to the national and international levels. In the economic aspect, the transformation of tapis cloth is able to increase people's income and absorb labor, thus providing a positive contribution to the local economy and improving people's welfare
Android-based augmented reality for writing learning for university students: A case study of Indonesian students’ writing literacy problems
Full text linkThis study explores the development and effectiveness of Android-based Augmented Reality (AR) learning media to enhance university students' writing skills in Indonesian language courses. The background stems from challenges observed in writing classes, where reliance on static PowerPoint presentations and lack of interactive media contributed to low student engagement and limited writing outcomes. Utilizing the ADDIE model, this developmental research involved stages of analysis, design, development, implementation, and evaluation. Media content was designed using Macromedia Flash integrated into Android-based AR, focusing on accessibility, interactivity, and the Technological Pedagogical Content Knowledge (TPACK) framework. Validation from material and media experts indicated high feasibility (scores of 3.87 and 3.77, respectively), while student response yielded an Aiken's V index of 0.95–1, categorized as excellent. An experimental test involving control and treatment groups demonstrated significant improvement in writing skills (p-value 0.05). The results suggest that Android-based AR media effectively supports meaningful and engaging writing instruction, addresses students’ literacy gaps, and aligns with 21st-century learning needs. This study contributes to educational technology and writing pedagogy by offering an innovative solution to writing literacy challenges in higher education
Trapezoidal Scheme for the Numerical Solution of Fractional Initial Value Problems
Full text linkThe purpose of this study is to recall the main concepts and definitions in relation to the fractional calculus. In light of this overview, we will propose a novel fractional version of the so-called Trapezoid method named by the fractional Trapezoid method. Such a method will then be used to numerically solve the analog version of the initial value problems called fractional initial value problem FIVPs. As consequences of the proposed numerical approach, several numerical examples will be illustrated to verify the efficiency of the proposed numerical approach
Hierarchical Cascaded Takagi-Sugeno Model Predictive Control for Performance Enhancement of Doubly-fed Induction Generator-Based Wind Turbine Systems
Full text linkThis paper proposes a cascaded Takagi-Sugeno Model Predictive Controller (TS-MPC) for a Doubly-fed Induction Generator (DFIG) based Wind Power Conversion System (WPCS) to maximize power extraction, maintain zero stator reactive power, and enhance power quality. For this purpose, the Takagi-Sugeno Fuzzy Logic Control (TS-FLC) is arranged in a sequential configuration with the Finite Control-Set Model Predictive Control (FCS-MPC) strategy to enhance the overall performance of the wind power system. The introduced control technique, which is applied to govern the Rotor Side Converter (RSC) of the DFIG, consists of two cascaded control loops for achieving Maximum Power Point Tracking (MPPT). The innermost control loop is implemented to regulate the d-q axis rotor currents using FCS-MPC strategy. Meanwhile the outermost control loop is employed to regulate the DFIG’s rotational speed pursuant to the Tip Speed Ratio MPPT (TSR-MPPT) control framework using the TS-FLC, thus improving the predictive accuracy and control effectiveness. To validate the performance of the devised control scheme, a numerical simulation of a 1.5MW DFIG based WPCS was conducted using MATLAB/Simulink software. The simulation results demonstrate that the proposed cascaded TS-MPC not only outperforms the cascaded PI-MPC in terms of superior adaptability to nonlinearities and varying wind conditions—thanks to the inherent flexibility of TS-FLC—but also in various performance metrics, including response time, steady-state error, and total harmonic distortion (THD).Furthermore, while FCS-MPC approaches are often criticized for computational complexity, the TS-FLC structure enhances real-time feasibility by reducing computational overhead compared to conventional FLC methods. These findings reinforce the practical viability of TS-MPC for large-scale wind energy applications and indicate the effectiveness of the proposed control scheme
Global trends and challenges in bilingual teacher education: A systematic review across sociocultural context
Full text linkAs global interconnectedness increases, the demand for high-quality bilingual education and by extension, well-prepared bilingual educators, has grown significantly. This systematic review investigates global trends and challenges in bilingual teacher education across diverse sociocultural contexts. A total of 68 peer-reviewed studies published between 2005 and 2022 were analyzed using Saldaña’s coding method, with data sourced from six major databases and selected through PRISMA guidelines. Thematic analysis revealed six core areas: global research trends in teacher preparation, evolving teacher competencies, identity formation and intercultural competence, pedagogical models, language policy, and implementation challenges. Findings show that successful bilingual teacher preparation programs are supported by culturally responsive pedagogy, robust policy alignment, and sustained professional development. However, disparities persist due to inadequate training infrastructure, restrictive policies, and lack of localized resources especially in underrepresented regions. The review underscores the need for teacher education models that are context-sensitive, equity-driven, and globally informed. It calls for expanded research in the Global South, integrative policy frameworks, and institutional commitment to build a resilient, inclusive bilingual teaching workforce
The meaning of digital era public communication by Indonesia’s local governments using Luhmann’s system theory: a case study of Central Java provincial government 2018-2022
No full textThis study explores the meaning of public communication by Indonesia’s local governments in response to digital environment. The research aims to examine how local government public communication systems adapt through their meaning of the digital landscape. Grounded in Niklas Luhmann's social system theory, which posits meaning as a stimulus for systems to respond to environmental changes, this study views meaning as the energy that enables a system to autonomously select its needs and methods (autopoiesis) for adaptation. Autopoiesis responds to meaning through three processes: communication (social dimension), evolution (temporal dimension), and differentiation (functional dimension). The meaning stimuli in this study will be explained in terms of their potential for enabling the system to perform autopoiesis. The research employs a case study of the meaning of digital-era public communication by the Central Java Provincial Government (Pemprov Jawa Tengah). Operationally, the meaning is examined by observing how Pemprov Jawa Tengah gives meaning to the digital era and depicts its public communication landscape throughout 2018-2019. Data is collected through interviews and documentation of statements made by Pemprov Jawa Tengah in online media. The results indicate that the social dimension of giving meaning to public communication by local governments in the digital era influences the system's considerations through interactions with the political system, e-government system, information technology system, and media system. In the temporal dimension, the developed meaning will impact public communication systems in three phases: dissemination phase 1 (2018-2019), responsive phase (2020-2021), and dissemination phase 2 (2022). These three phases in the evolutionary dimension elucidate the meaning conducted by local governments, dominated by considerations of the public communication function for quickly responding to public service complaints, strengthening performance reputation, and enhancing the popularity of local government’s leaders