Association for Scientic Computing Electronics and Engineering (ASCEE): Open Journal Systems
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Exploring the roles of special schools' principals in teacher quality improvement: A case study of special schools
Get PDFConcern about the role of school principals in improving the quality of special schools remains one of the challenges in realizing better quality education in Indonesia. However, some obstacles to the role of the principal in improving the quality of special schools still exist. Principals of special schools are still faced with obstacles to improving school quality, such as the quality of teachers. Therefore, this qualitative study aims to explore the role of the principal of the Southwest Aceh public special school in improving teacher quality. In particular, it discusses the main challenges faced by the Southwest Aceh public special school principals and the roles and strategies they use to improve teacher quality. This qualitative research is to investigate the role of the head of the Southwest Aceh public special school in Indonesia, asking the main research question, what is the role of the principal in improving teacher quality? This research was conducted using a case study design. Data was collected through in-depth interviews with school principals, observation, and secondary data, including official documents and existing literature on the role of school principals. Data analysis was used using data analysis techniques according to Miles and Huberman: data collection, data presentation, data reduction, and conclusions. The interconnected theoretical framework built through the role of the principal and the theory of quality improvement is the most suitable because it helps to understand the experience, working conditions, and challenges of exploring the role of the principal in improving school quality critically. The research findings reveal the role of the school principal in improving the quality of teachers; that is, the principal conducts guidance, coaching, and supervision, grants study permits for schools to a higher level, and conducts training to increase teacher competence. Besides that, the principal explores new ideas from teachers according to the times in the world of education and creates harmonious relationships, openness, adjustments to the curriculum, division of teaching tasks or additional assignments, and differential learning, and provides rewards and punishments to teachers who break the rules. In giving the workload of main tasks and additional assignments to teachers, the average is high, and the school program is not related to each other
Intelligent Controller Based on Artificial Neural Network and INC Based MPPT for Grid Integrated Solar PV System
Get PDFSolar photovoltaic (PV) systems have become an integral part of today's advanced energy infrastructure due to its low kinetic energy, its abundance availability, and its freedom from human interference. Solar PV systems have the potential to greatly reduce our reliance on fossil fuels, but their intermittent nature means they cannot provide a constant source of electricity. The system's security should be well thought out, and it should be able to withstand a lot of abuse. The current energy system faces a significant difficulty in ensuring continuous supply. In this study, a three-phase, two-stage photovoltaic system that is managed by artificial neural networks (ANN). A DC-DC boost converter with maximum power point tracking (MPPT) based on the incremental conductance (INC) method is incorporated in the first stage. In the next step, an ANN-based controller optimizes the performance of a three-phase switching PWM inverter that is connected to the grid by controlling currents along the d-q axis. Comprehensive simulations were carried out using MATLAB or Simulink to evaluate the system's performance under various illumination and temperature conditions. Results show that the suggested approach outperforms the baseline in a number of areas. Better dynamic reactions, accurate tracking of reference currents within permissible bounds, and quick settling periods after startup are all displayed by it. These findings show that our method has the potential to greatly improve the efficiency and dependability of solar PV systems. The results of this study have implications for renewable energy in general and present a viable path toward enhancing the resilience and sustainability of energy infrastructure
Magnetometer-Only Kalman Filter Based Algorithms for High Accuracy Spacecraft Attitude Estimation (A Comparative Analysis)
Get PDFKalman Filter (KF) based algorithms are the most frequently employed attitude estimation algorithms. Typically, a fully observable system necessitates the use of two distinct sensor types. Therefore, relying on a single sensor, such as a magnetometer, for spacecraft attitude estimation is deemed to be a challenge. The present investigation centers on utilizing magnetometers as the exclusive sensor. Several KF based estimation algorithms have been designed and evaluated to give the designer of spacecraft Attitude and Orbit Control System (AOCS) the choice of a suitable algorithm for his mission based on quantitative measures. These algorithms are capable of effectively addressing nonlinearity in both process and measurement models. The algorithms under examination encompass the Extended Kalman Filter (EKF), Sequential Extended Kalman Filter (SEKF), Pseudo Linear Kalman Filter (PSELIKA), Unscented Kalman Filter (USKF), and Derivative Free Extended Kalman Filter (DFEKF). The comparison of the distinct algorithms hinges on key performance metrics, such as estimation error for each axis, computation time, and convergence rate. The resulting algorithms provide numerous benefits, such as diverse levels of high estimation accuracy (with estimation errors ranging from 0.014o to 0.14o), varying computational demands (execution time ranges from 0.0536s to 0.0584s), and the capability to converge despite large initial attitude estimation errors (which reached 170o). These properties render the algorithms appropriate for utilization by spacecraft designers in all operational modes, supplying high-precision attitude estimations better than (0.5o) despite high magnetometer noise levels, which reached (200 nT)
Performance Enhancement of a Variable Speed Permanent Magnet Synchronous Generator Used for Renewable Energy Application
Get PDFThe paper aims to develop an improved control system to enhance the dynamics of a permanent magnet synchronous generator (PMSG) operating at varying speeds. The generator dynamics are evaluated based on lowing current, power, and torque ripples to validate the effectiveness of the proposed control system. The adopted controllers include the model predictive power control (MPPC), model predictive torque control (MPTC), and the designed predictive voltage control (PVC). MPPC seeks to regulate the active and reactive power, while MPTC regulates the torque and flux. MPPC and MPTC have several drawbacks, like high ripple, high load commutation, and using a weighting factor in their cost functions. The methodology of designed predictive voltage comes to eliminate these drawbacks by managing the direct voltage by utilizing the deadbeat and finite control set FCS principle, which uses a simple cost function without needing any weighting factor for equilibrium error issues. The results demonstrate several advantages of the proposed PVC technique, including faster dynamic response, simplified control structure, reduced ripples, lower current harmonics, and decreased computational requirements when compared to the MPPC and MPTC methods. Additionally, the study considers the integration of blade pitch angle and maximum power point tracking (MPPT) controls, which limit wind energy utilization when the generator speed exceeds its rated speed and maximize wind energy extraction during wind scarcity. In summary, the proposed PVC enhanced control system exhibits superior performance in terms of dynamic response, control simplicity, current quality, and computational efficiency when compared to alternative methods
Optimization of a bio-based drilling fluid from waste Dacryodes Edulis (local pear) for oil exploration
Get PDFThis study focused on the development and optimization of a bio-based drilling fluid from local pear seed for oil exploration, which can help lessen the environmental impact of oil spills. Local pear seed being a biodegradable material was collected, prepared, its oil extracted, modified and optimized to obtain an eco-friendly and cost-effective drilling fluid. The selected materials used for this study was Local pear oil. The drilling fluid was characterized for proximate parameters and ultimate parameters. The prepared drilling fluid was optimized using response surface methodology (RSM) provided by Design-Expert software 13.0. Central composite design (CCD) was applied to study the variables affecting rheology of drilling fluid. The process factors which include pH (A), viscosity (B), mud density (c), temperature (D), rheology (E) interacted to produce the response (drilling fluid yield) for the studied sample. The optimized drilling fluid yield and the optimum values were obtained through iterations of one hundred (100) solutions and the best yield was selected at iteration number seven (95th solution), at a pH of 1, Viscosity of 119.783cP, mud density of 10.473kg/L, Temperature of 100°C, and Rheology of 76.809s-1, and the optimized drilling fluid yield value was 91.144%. The acidity and the alkalinity of the drilling fluid were measured by the concentration of the 9.5 ion in the fluid. Therefore, the biomaterial studied has demonstrated its optimal effectiveness and potential application as an additive for the development of drilling fluid for oil exploration
Development of a drama gong performance model: an effort to preserve the traditional Balinese drama in the digital era
Get PDFDrama Gong is a traditional Balinese performance art that enjoyed popularity. However, since the 1990s, the advent of television and the internet has led to a decline in the prominence of Drama Gong. Therefore, there is a pressing need to revitalize and innovate this traditional art form. One such effort by Balinese artists involves the creation of a digital adaptation known as 'Drama Keraton Cilinaya.' This qualitative descriptive research aims to explore the development model of Drama Gong in the digital era. The research data were collected through a comprehensive document analysis, which included the examination of seven episodes of 'Drama Keraton Cilinaya,' as well as direct observations and interviews with the creators. The findings revealed that 'Drama Keraton Cilinaya' has undergone significant internal and external innovations. Internally, the artists emphasized the importance of having an open mindset to embrace global changes, packaged stories for enhanced appeal and comprehension, incorporated contemporary dialogue, employed multiple languages, engaged younger talents, enhanced makeup and costume artistry, introduced digital music, and improved stage layouts. External innovations involve collaborations with artists beyond the Drama Gong tradition, utilizing digital technology in production, and distributing the performances through TV media and YouTube channels to broaden their audience reach. It is anticipated that the findings of this research will serve as a valuable digital packaging model, not only for Drama Gong but also for the development of other traditional Balinese performing arts, ensuring their sustainability in the digital era
Vision-based chicken meat freshness recognition system using RGB color moment features and support vector machine
Get PDFChicken meat is a highly sought-after food product among various segments of the general population, known for its high nutritional value and easy accessibility. Presently, meat identification is primarily conducted manually, relying on visual inspection or tactile assessment of the meat's color and texture. However, this approach presents several limitations, particularly when consumers lack the discernment to differentiate the quality of chicken meat freshness. This research aims to identify the freshness level of chicken meat using the Support Vector Machine method, employing the extraction of RGB color moment features to determine the freshness of the meat. The feature extraction process involves calculating the percentage of intensity values for R (Red), G (Green), and B (Blue) in each chicken meat image. Based on the image processing results, the percentage of intensity values, particularly in the R and B parameters, can be used as determining factors. The study involves software testing using fresh and non-fresh chicken meat. The developed system can identify the freshness level of fresh chicken meat with an accuracy rate of 71.6% using the linear kernel SVM and 60.5% using the RBF kernel SVM. This research represents a significant step toward the automation of chicken meat freshness assessment, potentially reducing food waste and enhancing food safety in the food industry. Further research and development could improve the system's accuracy and expand its applications in various food quality control settings.Chicken meat is a highly sought-after food product among various segments of the general population, known for its high nutritional value and easy accessibility. Presently, meat identification is primarily conducted manually, relying on visual inspection or tactile assessment of the meat's color and texture. However, this approach presents several limitations, particularly when consumers lack the discernment to differentiate the quality of chicken meat freshness. This research aims to identify the freshness level of chicken meat using the Support Vector Machine method, employing the extraction of RGB color moment features to determine the freshness of the meat. The feature extraction process involves calculating the percentage of intensity values for R (Red), G (Green), and B (Blue) in each chicken meat image. Based on the image processing results, the percentage of intensity values, particularly in the R and B parameters, can be used as determining factors. The study involves software testing using fresh and non-fresh chicken meat. The developed system can identify the freshness level of fresh chicken meat with an accuracy rate of 71.6% using the linear kernel SVM and 60.5% using the RBF kernel SVM. This research represents a significant step toward the automation of chicken meat freshness assessment, potentially reducing food waste and enhancing food safety in the food industry. Further research and development could improve the system's accuracy and expand its applications in various food quality control settings
New harmony of Javanese keroncong case study: Boogie Rahayu's work on the Kroncwrong album Sono Seni Ensemble
Get PDFThis research aims to unveil one of the compositional works of the Sono Seni Ensemble Surakarta music group, titled 'Boogie Rahayu.' This work offers a distinct paradigm and compositional technique in comparison to the works of typical progressive keroncong orchestra groups. The study endeavors to reveal the composition of 'Boogie Rahayu' through an analysis that integrates source knowledge of karawitan music structures, keroncong playing techniques, attitudes towards sound sources, and an openness to presenting new harmonies. Examining this compositional work contributes to addressing the issue of creativity stagnation in the Javanese style of keroncong. The research adopts a musicological and cultural approach, focusing on the primary objects of the work and the performers. Data collection techniques involve field observations and interviews conducted through both online and offline methods, as well as document and artifact studies using conventional and online methods. During the analysis stage, this study employs an emic approach, considering the composer's thoughts and beliefs, alongside a musicological approach that delves into musical structure, rhythm changes, cadence interpretation, and chord harmony. The results of the research indicate that 'Boogie Rahayu' introduces a new avenue of development capable of transcending artistic and aesthetic boundaries among keroncong music, Javanese style, and Javanese karawita
Method design of interactive digital devices to support the workspace comfort
Get PDFThere are many alterations and adaptations of the workspaces after the Covid-19 pandemic. Nowadays, workspaces are required to have flexibility in facilitating physical and virtual activities, work-from-home (WFH), and work-from-office (WFO) activities. Besides, workspaces must provide comfort based on user preferences and demand to support workers’ health and productivity. In order to answer these problems, the design of interactive digital devices that can be adjusted according to physical needs, activities, and preferences is needed to support the ideal workspace comfort. The research method used in this research is a literature review related to ideal workspace comfort standards and an assessment of the Arduino as an interactive digital device to produce an interactive digital device method design that can detect ideal comfort and be applied to workspaces. The result shows that as an interactive digital device, Arduino can be implemented in a workspace to detect and produce ideal workspace comfort regarding lighting, noise, temperature, and humidity. Arduino also supports flexibility and varied demand in a workspace because of its adjustable artificial intelligence feature. The ideal standard of workspace differs based on the activities and geographical conditions of the country and is related to the varied preferences of its users. Based on its complexity, for further research to be carried out, it is recommended to conduct a case study of ideal workspace interior design with an Arduino device in a specific place to generate more accurate data and suitable workspace design
From bonds to beliefs: Investigating parent, peer attachment, and growth mindset in private vocational high schools
Get PDFThis research focuses on investigating the influence of parent and peer attachment on the growth mindset of students enrolled in Private Vocational High Schools in Purwokerto, Indonesia. Stratified proportional random sampling was employed to select participants for this study. Consent was obtained from 235 students who participated. The gender distribution was skewed toward females (57.9%) compared to males (42.1%), with the majority of participants being 16 years old (46.7%). The Inventory of Parent and Peer Attachment (IPPA) was used to measure parent and peer attachment, while the Growth Mindset Scale was employed to assess participants' growth-oriented attitudes. A linear regression analysis was utilized to examine the predictive relationship between mother, father, and peer attachment and growth mindset scores. The results demonstrated significant gender-based variations across the variables studied. Notably, females exhibited significantly higher Mother Attachment scores, indicating a stronger attachment to their mothers. Nonetheless, no considerable gender disparities emerged in Father Attachment scores. Although the distinction in Peer Attachment scores was close to significance (p = 0.053), females displayed slightly higher attachment to peers. A marked gender discrepancy was identified in Growth Mindset scores, with females displaying a notably more positive perspective toward growth and learning opportunities. Furthermore, predictive modeling revealed that Mother Attachment exerted a significant positive impact on Growth Mindset scores (β = 0.3), implying that a stronger attachment to mothers corresponded to a more favorable growth-oriented mindset. Similarly, Father Attachment positively contributed to Growth Mindset scores (β = 0.25). Additionally, Peer Attachment demonstrated a modest yet positive association (β = 0.13). The calculated R² values indicated that both Mother Attachment and Father Attachment collectively accounted for approximately 18% of the variance in Growth Mindset scores, while Peer Attachment contributed to a smaller extent (1%). Collectively, these findings shed light on the intricate relationships between attachment, age, and mindset. They underscore the roles of different attachments in shaping individuals' growth-oriented perspectives and highlight the nuanced gender differences in attachment and mindset. This study provides valuable insights for educators, parents, and policymakers aiming to promote positive growth mindsets among students