bluuebunny/crossref_metadata_2025_split huggingface dataset:
Self regulated learning for social cognitive perspective in mathematics lessons
Authors: Zakiah N E , Fajriadi D 
Published: September 2020

Abstract
The research results describe of self-regulated learning for a social cognitive perspective in mathematics lessons. Students adapt to the social environment based on skills, knowledge, and skills previously owned. Every student in the social system adopts information and knowledge. Students learn through the social process of observing, imitating, and modeling the behavior of others. Students need to actively demonstrate independent learning orientation to find challenges and learning opportunities to acquire new skills and knowledge. About 116 new students from one of the state vocational high schools in West Java province of Indonesia participated in the self-regulated learning questionnaire from five aspects: organizations, elaboration, self-evaluation, learning strategies for examinations, and metacognition. We present responses to each self-regulated learning students about academic time management, summarized study materials in a personal way, evaluated their own learning and performance, were strategic in preparing for exams and reflected metacognitively during the study. From social cognitive theory, self-regulated learning is influenced by the students’ personal factors (cognitive, attitudes, and self-evaluation), behavior, and environment (social support). This research contributes to the understanding of students’ self-regulated learning and gives teachers insight into designing learning innovations.
Management of authentic assessment in mathematics lessons to develop 4C skills
Authors: Zakiah N E , Fajriadi D 
Published: September 2020

Abstract
Essential skills for 21st-century called 4c, namely critical thinking, creativity, collaboration, and communication. This ability is following the demands of the curriculum and can be developed in mathematics learning. Concerning assessment, all student views in a series of learning activities can be assessed objectively, as is, and not only based on the final results using an authentic assessment. Thus, this study aims to describe the management of authentic assessment in mathematics lessons to develop 4c skills. This study uses qualitative research with a case study method. The research subjects were mathematics teachers and grade X students at one of the state vocational high schools in West Java province. The data in this study came from observations, interviews, and documentation. Data analysis of aspects of the teacher’s role, support systems, social systems, instructional impacts, and assessment management. The results of this study indicate that: (1) The formulation of assessment instruments is carried out by formulating assessment objectives, making assessment grids, making instruments assessment following assessment guidelines, and analyzing the quality of the instruments; (2) Assessment of attitude aspects using observation and journals techniques. Knowledge assessment uses oral tests, written tests, and assignments according to the competencies being assessed. Skill assessments are conducted through practices or other techniques by competencies assessed using an assessment scale accompanied by a rubric; (3) Utilizing the results of the assessment to monitor and evaluate the process, learning progress, and improvement of students’ learning outcomes.
Students’ creativity level on solving mathematics problem
Authors: Thohari C A F , Budiyono  , Pratiwi H 
Published: September 2020

Abstract
There have been many attempts in order to build and train students’ creativity. However, there have been many obstacles faced regarding to how to encourage the students’ to be creative in the class. One of those obstacles faced is how to assess student’s creativity in solving mathematical problems; because there is a distinctive aspect for normal assessment and creativity assessment. Assessing creativity requires more specific limitations to creativity. By knowing the way to assess creativity, it will help teachers to understand to what extent students’ creativity can be used as a reflection in the effort to build creativity. This study aims to determine students’ creativity level on solving mathematics problem. The information of to what extend students’ creativity level. Moreover, this could be used as a consideration on planning learning strategy in order to increase student creativity on solving mathematics problem. This study employed qualitative research method. The subjects of this research are two 7th grade students of SMPN 1 Ngraho Bojonegoro. Data were collected through three steps namely writing test, interview, and observation. The conclusion of this study indicates that students’ creativity level on solving mathematics problem could be classified based on Siswono’s level of creativity. These levels are categorized into level 4 (very creative), level 3 (creative), level 2 (quite creative), level 1 (less creative), and level 0 (not creative). The first subject has the category of level 1 creativity (less creative). The second subject has the category of level 3 creativity (creative).
Geometry learning in vocational high school: Investigating the students’ difficulties and levels of thinking
Authors: Barut M E O , Retnawati H 
Published: September 2020

Abstract
Student’s difficulties and low-level thinking in geometry topic is not a new problem in mathematics education. It is portrayed on student’s low achievement both on national and international tests. Van Hiele’s model has been used as a useful framework to justify student’s difficulties as well as their level of thinking in geometry. Therefore, the aim of this study to investigate student’s difficulties and level of thinking using Van Hiele’s theory. Participants in this study were 12th grades vocational high school students. This study is descriptive qualitative research with a phenomenology approach. Data has been collected through a test and interviews. Further, the obtained data were analyzed by looking for a specific theme, then, the researcher found the inter-theme relationship in order to gain a proper understanding of student’s difficulties in geometry and level of student’s geometrical thinking. Based on data analysis, there are some difficulties faced by the student such as, unable to properly identify the geometry shapes based on their formal definition, lack of visualization ability, failed to understand specific terms or symbols of geometry, insufficiency in providing proper reasoning related relationship within geometric shapes. Moreover, it can be concluded that most of the students are on Level 1 of geometry thinking.
Comparison of image edge detection methods on potholes road images
Authors: Indriyani Tutuk , Utoyo Imam , Rulaningtyas Riries 
Published: September 2020

Abstract
Dinas pekerjaan Umum (DPU) in Surabaya in carrying out road repairs, especially in potholes, must know the position, area and depth. So it is important to do research to find out the surface area of potholes. To find out the surface area of the hole, the edge detection process is done first. Edge detection functions to get the edge of an object. Edge detection is obtained by utilizing a drastic change in the intensity value at the boundary of two areas. In this study, to determine the edge of an object (potholes road) by comparing three edge detection methods consisting of the Frei-Chen, Laplacian and Laplacian of Gaussian (LoG) methods. From the results of testing the Laplacian of Gaussian method has an average value of accuracy of 67%, sensitivity of 81.97% and specificity of 65.16%.The measurement results obtained by the Lapalacian of Gaussian method which is the best method for edge detection in potholes road images, because it produces the highest accuracy, sensitivity and specificity.
Open-ended mathematics module to improve students’ higher order thinking skill
Authors: Kurniawati S , Budiyono  , Saputro D R S 
Published: September 2020

Abstract
Higher order thinking skill (HOTS) is a more complex thinking skill using cognitive domains in C4 (analyzing), C5 (evaluating), and C6 (creating). This study aims to develop an initial mathematical module based on a valid prototype of open-ended mathematics module to help students to improve HOTS on the material of linear equation system in two variables. An open-ended approach is one of the learning approaches that can be used to increase HOTS students. This type of study was research and development (R&D). There are three stages of development research, namely (1) preliminary study consisting of 3 steps, namely initial research, analysis of the needs, and literature study, (2) product development consisting of three steps namely planning, initial product development, product testing and revision, (3) product efficacy testing, which is the stage of comparing modules developed with existing products. This research was conducted on the eighth-grade students of a public junior high school in Surakarta. The results obtained from this study was the average results of each initial module validation by media experts, material experts, and language experts are 3.27, 3.21, and 3.77. The product prototype is valid so it can be used to measure students’ HOTS.
FCM using squared euclidean distance for e-commerce classification in Indonesia
Authors: Khulaidah E Z , Irsalinda N 
Published: September 2020

Abstract
Clustering is a method of grouping data into several clusters so that the data in one cluster has a high level of similarity while the data between other clusters have a low level of similarity. One method used in clustering is Fuzzy C-Means (FCM) which is a data clustering technique in which the existence of each data point in a cluster is determined by the degree of membership in each cluster. The FCM algorithm has an objective function that requires distance. The distance used in this study is Squared Euclidean distance. The clustering conducted is the clustering of the popularity of e-commerce in Indonesia in 2019 using the variable average number of monthly visitors, number of website visitors, number of social media followers (Twitter, Instagram, and Facebook) as well as the number of workers. The result of this method is the level of popularity of e-commerce in Indonesia, which is divided into gold, silver, and bronze. Clustering results were tested with the Partition Entropy Index (PEI) and Classification Entropy (CE) if the results are getting closer to 0, the results are getting better. The result of PEI is 2.9697e-0, and CE is 2.5710e-04. So, based on the two indexes It can be concluded that FCM using Squared Euclidean distance is good to clustering.
Four-Tier Diagnostic Test Method to Identify Conceptual Understanding in Calculus
Authors: Fadhilatullathifi Z N , Ardiyanto B , Rahayu D D , Almukholani T , Rinayah I , Rahmawati F 
Published: September 2020

Abstract
The study aims to identify the ability to understand concepts with four-tier diagnostics test method. Every student has a different ability to understand mathematical concept. It is influenced by various factors such as intelligence, emotional conditions, environment, etc. This research uses the qualitative method with study case strategy. The data obtained from the four-tier diagnostic test on the calculus chapter. The subjects in this research are XIIth grade students. There are four stages of work in a four-tier diagnostic test, 1) question, 2) level of confidence in the answers, 3) reason, and 4) level of confidence in the reason. The result of this research show that most students have low ability to understand concepts. Most students are not sure of the answers to calculus problems given. Students also do not give the correct reason for the answer.
Relational Thinking Skills of Junior High School Students and Their Relationship with Creativity in Solving Mathematical Problems
Authors: Usodo Budi , Mardiyana  , Pramudya Ikrar , Sutopo  , Setiyawan Rubono 
Published: September 2020

AbstractRelational thinking skills are the ability of children to see and use possible variations between numbers in one number sentence. This study aims to describe relational thinking skills and their relationship with the creativity of junior high school students in solving mathematical problems. This research uses quantitative and qualitative descriptive research methods. The subjects of this study were several 8th grade students in one of junior high schools in the city of Surakarta. Data collection methods used are test and interview methods. Analysis of the data used is quantitative and qualitative descriptive analysis. The results of the study showed that the relational thinking ability of junior high school students was less than 12,5 %. Most students only use computational thinking to solve math problems. From the interview results show that the low ability of students’ relational thinking, because the students have never been taught the use of relational thinking to solve mathematical problems. After giving several examples of the use of ways of thinking in solving problems, students can solve this problem in more than one way. The interview results show that students have creativity in solving mathematical problems.
Cooperative learning based on probabilistic thinking profile SMP Muhammadiyah 3 Mlati regency of Sleman
Authors: Taram Abdul , Sukestiyarno Y L , Rochmad  , Junaedi Iwan 
Published: September 2020

Abstract
The probabilistic thinking includes high order thinking skills (HOTS), which need to be trained to students through learning models. The probabilistic thinking Level of the students varies. So the purpose of the research is: (1) Want to know the high level of probabilistic thinking students SMP Muhammadiyah 3 Mlati Kabupaten Sleman, before and after following the model Prmbelajaran; (2) Want to know the effectiveness of cooperative learning model with peer tutor on heterogeneous group in raising the level of Probabilitik students of SMP Muhammadiyah 3 Mlati Kabupaten Sleman. The design of this research is research with the method of combination model or design concurrent trianggulation. The method of blending qualitative and quantitative analyses. The subject in this study was a grade IX students A and B of the odd semester of SMP Muhammadiyah 3 Mlati Kabupaten Sleman. Class IX A applies cooperative learning of NHT type and KLS IX B Implementing Cooperative learning of TGT type. With heterogeneous groups and peer tutors. The results of the study and its discussion gained interesting findings in this study, which is an effective learning Model to increase the level of probability thinking of SMP Muhammadyah 3 Mlati Sleman in solving probabilistic problems, is a learning model that blends three components (1) Cooperative Learning, (2) Heterorogative groups, and (3) peer tutors. This study was named the Learning model “Koophetebaya”.
Influence of cracks on the buckling of wind turbine towers
Authors: Capaldo M. , Orsatelli J. B. , Curt J. , Julan E. 
Published: September 2020

Abstract
The collapse of a wind turbine can be caused by the buckling of the tower when it is subjected to a critical load. This load is related, for instance, to a strong storm or a blade impact on the tower. Buckling occurs when the elastic limit is reached in part of the tower. Plasticity leads to bending with large rotations and large displacements. Structures are designed to avoid this phenomenon. However, a wind turbine is subjected during its entire service life to operation loads which cause fatigue of the structure. This results in the initiation of cracks and their propagation in the tower. These cracks can reduce the tower strength and it is, thus, interesting to study how the presence of such damage can affect the resistance of a wind turbine tower to the buckling. The influence of different parameters, such as position and length of the crack, is analyzed. Finally, the critical buckling load is related to wind site condition by considering an aero-elastic modeling of the wind turbine.
Validated extrapolation of measured damage within an offshore wind farm using instrumented fleet leaders
Authors: Noppe Nymfa , Hübler Clemens , Devriendt Christof , Weijtjens Wout 
Published: September 2020

Abstract
As the older wind farms are slowly reaching their design lifetime, topics like fatigue and lifetime assessment gain importance. To decide on a possible lifetime extension of the turbine and its foundation, an accurate fatigue assessment for every wind turbine in the farm is needed. As the installation of specific sensors needed for a fatigue assessment is too time consuming and costly, the “Fleet Leader Concept” is applied and validated in this paper. Here, a few turbines are instrumented and a fatigue assessment based on rainflow counting and Miner’s rule can be performed. For a farm-wide fatigue assessment, the obtained damage is extrapolated towards the other turbines. Sample based bootstrapping is performed to introduce an uncertainty on the results. A successful extrapolation was obtained for in-field measurements at an older offshore wind farm. In general, relative errors of less than 5% on damage were found.
An initial study into the potential of wind farm control to reduce fatigue loads and extend asset life
Authors: Harrison Matt , Bossanyi Ervin , Ruisi Renzo , Skeen Nick 
Published: September 2020

Abstract
A quasi-static open loop wind farm control approach is considered, where optimisation is carried out offline in a simulation environment to create a lookup table of yaw setpoints implemented by a central wind farm controller. The objective of the optimisation is to reduce blade root bending moment for all turbines on the site, thereby increasing the asset life, and this is achieved by querying a fatigue loads database in DNV GL’s LongSim software for wind farm control design, optimisation and verification. The Lillgrund 48-turbine layout is used for this example. The optimisation results in a small increase in annual energy production of 0.13% which is combined with a 0.4% increase in blade life, which is translated to an increase in asset life to yield a 0.5% increase in energy production over the farm lifetime. In this case we make the simplistic assumption that blades have the minimum life of all turbine components, and limit fatigue life. The results are a step towards wind farm control techniques which maintain and extend wind farm life, whilst simultaneously increasing energy production.
DTUWEC: an open-source DTU Wind Energy Controller with advanced industrial features
Authors: Meng Fanzhong , Lio Wai Hou , Barlas Thanasis 
Published: September 2020

Abstract
An open-source wind turbine controller, DTU Wind Energy Controller (DTUWEC), developed by Technical University of Denmark (DTU), is presented. The DTUWEC includes many advanced features and it is publicly available to the wind energy community. It is envisioned that this research work converts the old version of Basic DTU Wind Energy Controller into a generic, powerful and robust open-source wind turbine controller with a large number of developers and users in both research institutions and industries. DTUWEC is implemented in Fortran and offers the DNV-GL Bladed/OpenFAST style interface. Because of its open-source and modular characters, researchers are able to couple DTUWEC with different aero-elastic simulation codes to investigate the effect of different controllers on the wind turbine structural loads and power output, and to collaborate for future potential improvements.
Development and embedded deployment of a virtual load sensor for wind turbine gearboxes
Authors: Bosmans Jelle , Vanommeslaeghe Yon , Geens Luk , Fiszer Jakob , Croes Jan , Kirchner Matteo , Denil Joachim , Meulenaere Paul De , Desmet Wim 
Published: September 2020

AbstractThe loads to which a wind turbine gearbox is subjected during its lifetime can be a valuable source of information to decrease maintenance cost and downtime through enhanced monitoring, control and design. However, this load information is difficult to acquire since suitable direct load sensors are intrusive and expensive. Therefore, this paper focuses on indirect load measurement through a virtual sensing algorithm. The resulting virtual load sensor estimates the incoming load on the low speed planetary stage of the gearbox by combining strain measurements on the external surface of the ring gear with a physics-based model. The algorithm is deployed for real-time execution on low-cost embedded hardware to make a cost-effective load sensor. The effect of the configuration parameters of the virtual load sensor on the execution time and memory usage is examined in order to verify which configurations can be deployed. Since these configuration parameters also affect the estimation accuracy, the design of the virtual load sensor is tackled as a co-design problem. The resulting virtual load sensor, which is deployable for real-time execution, achieves an RMS estimation error of 0.6% in a numerical validation, using 4 strain gauges on the ring gear.
Wind Turbine Failure Prediction Using SCADA Data
Authors: Lima L A M , Blatt A , Fujise J 
Published: September 2020

Abstract
This paper proposes a failure prediction system for wind turbines using the Normal Behavior Model (NBM) approach. By using available SCADA data, the NBMs are trained to make predictions that reflect what would be a turbine’s normal operating condition. They are able to identify when a given operating condition is abnormal, which points towards probable component degradation. Alerts are raised based on the daily-averaged prediction error to help the O&M team in identifying turbines that need maintenance. The NBMs are comprised of numerous linear models with different inputs and training sets, according to an ensemble approach that aims to avoid overfitting and to reduce the amount of false-positive predictions.
Description and insights on various development steps are presented, such as data treatment, model selection, error calculation and alerts generations. Two test cases are shown using operational data from existing wind turbines, highlighting the system’s ability to generate alerts weeks before a severe fault occurs.
SCADA-based neural network thrust load model for fatigue assessment: cross validation with in-situ measurements
Authors: Santos Francisco d N , Noppe Nymfa , Weijtjens Wout , Devriendt Christof 
Published: September 2020

Abstract
In this contribution SCADA data and thrust attained through strain measurements are used to train a neural network model which predicts the thrust load of an offshore wind turbine. The model is subsequently cross-validated for different turbines with SCADA data outside of the training period as input and the thrust load from strain measurements as the expected output, and the impact of wind speed and different operating conditions studied. The results for the model, such as MAE, are kept generally under 2 %. The estimated thrust load signal is then converted into the damage equivalent stress caused by the quasi-static load, allowing to quantify the damage induced by the thrust load. The model performed, in general, well, but some over-/underpredictions are severely amplified when converting the loads into the damage equivalent stress.