bluuebunny/crossref_metadata_2025 huggingface dataset:
Wake meandering in a model wind turbine array in a high Reynolds number turbulent boundary layer
Authors: Turner V John J. , Wosnik Martin
Published: March 2020

Wake meandering is the dynamic shift observed in the spatial location of a wind turbine wake as it evolves downstream, considered to be caused primarily by the interaction of large flow structures in the atmospheric boundary layer with the turbulent wake. Experiments were conducted in a large boundary layer wind tunnel to investigate meandering in the wakes of both individual model wind turbines and in a wind turbine array with a large number of model turbines (19 rows x 5 columns = 95 model turbines). Unlike bluff body vortex shedding, the meandering phenomenon for a turbine wake is not characterized by a well-pronounced peak in the frequency domain, but rather by a broad spread over a low-frequencies range. For individual turbine models, both rotating three-bladed models and non-rotating porous disks, frequencies and peak energies observed in the velocity spectrum in the wake return to those of the incoming high Reynolds number turbulent boundary layer. Wake meandering also presents itself in the large wind turbine array. Here, frequencies and peak energies observed in the velocity spectrum in the wake do not return to those of the incoming turbulent boundary layer. Instead, a lower dominant frequency corresponding to the wind velocity at hub height and array spacing is observed within the array, indicating forcing of the meandering by the array itself (a type of resonance). Higher peak energies are observed in the array due to large flow structures representative of the turbine spacing.
Large-eddy simulations of idealized atmospheric boundary layers using Nalu-Wind
Authors: Kaul C M , Ananthan S , Churchfield M J , Mirocha J D , Berg L K , Rai R
Published: March 2020

Accurate prediction of wind-plant performance relies, in part, on properly characterizing the turbulent atmospheric boundary layer (ABL) flow in which wind turbines operate. Large-eddy simulation (LES) is a powerful tool for simulating ABLs because it resolves the largest, most energetic scales of three-dimensional turbulent motions. Yet LES predictions are well known to depend on modeling choices such as grid resolution, numerical discretization schemes, and closures for unresolved scales of turbulence. Here, we evaluate how these choices influence predictions of ABL winds using Nalu-Wind, a wind-specific fork of the open-source, generalized, unstructured, massively parallel flow solver NaluCFD/Nalu.
Short-term wind forecasting using statistical models with a fully observable wind flow
Authors: Perr-Sauer J. , Tripp C. , Optis M. , King J.
Published: March 2020

The utility of model output data from the Weather Research and Forecasting mesoscale model is explored for very short-term forecasting (5-30 minutes horizon) of wind speed to be used in large scale simulations of an autonomous electric power grid. Using this synthetic data for the development and evaluation of short-term forecasting algorithms offer many unique advantages over observational data, such as the ability to observe the full wind flow field in the surrounding region. Several short-term forecasting algorithms are implemented and evaluated using the synthetic data at several different time horizons and for three different geographic locations. Comparison is made with observational data from one location. We find that short-term forecasts of the synthetic data considering wind flow from the surrounding region perform 26% better than persistence in terms of root mean square error at the 5-minute time horizon. This improvement is comparable to studies of observational data in the literature. These results provide motivation to use synthetic data for short term forecasting in grid simulations, and open the door to future algorithmic improvements.
A Comparative Analysis of Three Supervised Learning Algorithms in Stock Selection
Authors: Sun Zhen , Zhao Shangmei
Published: March 2020

In this paper, our goal is to judge which algorithm is the best, through comparing the classification accuracy of the three supervised machine learning algorithms, using the data of four financial factors which can reflect the intrinsic value of corporate stock. Our empirical results show that Support Vector Machine got the extremely high classification accuracy in the test both inside and outside the samples; Random Forest achieved the highest classification accuracy in the test within the samples, but it’s accuracy was not as good as Support Vector Machine in the test outside the samples, it means Random Forest was prone to over-fitting; The classification accuracy of Naive Bayes was very low in the test both inside and outside the samples. According to the Bayesian hypothesis, we can see that financial factors are not independent of each other. As a result, the optimal algorithm is Support Vector Machine, followed by the Random Forest, and it is not advisable to use the Naive Bayes, when we selecting the stocks using financial factors data.
Research on Augmented Reality Method Based on Improved ORB Algorithm
Authors: Xiaokang Ren , Danling Cao , Jie Ren , Bianli Du
Published: March 2020

Aiming at the problems of time-consuming three-dimensional registration algorithm in augmented reality system, low accuracy of feature point matching and poor registration effect, an improved ORB (S-ORB) algorithm is proposed and applied to the Majiayao painted pottery augmented reality system. Firstly, the scale space is established by Gaussian filtering and downsampling, and the feature points are extracted by FAST corner detection. Secondly, the descriptors of feature points are calculated by rBFEF algorithm. Finally, the feature matching set is obtained by hamming distance and the mismatching point is eliminated by RANSAC algorithm to complete the three-dimensional registration. Make the virtual information stack correctly added to the real scene. The experimental results show that the S-ORB algorithm is better than the ORB, SURF and BRISK algorithms in time and accuracy when the target position is rotated and scaled. It has better real-time and robustness in the AR system of the painted pottery.
Performance analysis of LDPC decoding algorithm
Authors: Zhou Fan , Niu Linlin , Tian Binghe
Published: March 2020

The LDPC code is the guarantee of reliable information transmission channel coding technology, compared with other coding technology, LDPC code has excellent performance, LDPC decoding algorithm performance is a key, in order to find out the performance of decoding algorithm, compare the BF algorithm and WBF algorithm, BP algorithm and BP algorithm LLR, MS algorithm, NMS algorithm performance, the results show that NMS algorithm has lower complexity and better performance.
Third-party Evaluation of the Flight Control Software
Authors: Yuan Li , Sun Xueyang , Liu Xingyu
Published: March 2020

Flight control software which is the core of missile flight control system guides and controls missile flight along program trajectory. Effective testing of flight control software is an important means to ensure the quality of flight control system. Software testing and evaluation is the comprehensive measurement and assessment of the software quality in according with relevant standards taken by the independent third-party testing and evalution organizations according to the requirements of entrustors. This paper mainly tests the configuration items of flight control software. Firstly, the characteristics of the software under test are introduced. Then, the testing strategies, methods and environment are given. Finally, the test results are analyzed.
The Lattice Sieve Field Selection of Cado-NFS
Authors: Xue Ping , Chen Shaozhen , Fu Zhixin
Published: March 2020

The software application of the discrete logarithms on the “large” finite field is studied. The most effective algorithm for the problem is the general number field sieve (GNFS). Focusing on the theory of GNFS of solving software Cado-NFS and lattice sieves, we find the selection of lattice sieve which improve efficiency of CADO-NFS. This is the first parameter modification suggest. The efficiency of our selection is better than the current by experiment.
Multimodal data fusion algorithm applied to robots
Authors: Zhang Xin , Feng Zhiquan , Tian Jinglan , Yang Xiaohui
Published: March 2020

In recent years, the use of multimodal human-computer interaction technology to achieve the enhancement of human intelligence has become a new topic in human-computer interaction research. When the robot can’t react correctly in a single mode, it is necessary to realize multimodal fusion. To this end, this paper proposes a multimodal fusion algorithm that applies the data obtained by the CNN feature layer to the decision-level. The speech recognition text is semantically matched with the text in the text library, and the similar probability vector is returned. At the same time, the similarity probability vector of the gesture recognition is obtained, and the data is filtered by the threshold, and the set of high probability data codes is assigned to the two modes. The intersection operation, and the final instruction is sent to the robot. The experimental results show that the influence of environmental factors on the single channel result is reduced, and the single mode ambiguity problem is eliminated. The multi-channel fusion algorithm with additional weight is more accurate than the common multi-channel fusion algorithm. At the same time, it has also been well received by many test users.
Tibetan-Chinese cross-lingual word embeddings based on MUSE
Authors: Ma Wei , Yu Hongzhi , Zhao Kun , Zhao Deshun , Yang Jun
Published: March 2020

The idea of word embedding is based on the semantic distribution hypothesis of linguist Harris (1954), who believes that words with the same semantics are distributed in similar contexts. The learning of word embedding is a crucial technology in natural language processing. In recent years, cross-language word vectors have received more and more attention. Cross-language Word vectors can transfer knowledge between different languages. Most importantly, this transfer can occur between rich-resource and low-resource languages. This paper uses the Tibetan-Chinese Wikipedia corpus to train monolingual word vectors. Based on the Tibetan-Chinese bilingual translations, we use the supervised method in the MUSE library to train the Tibetan-Chinese bilingual cross-language word embeddings. In the experiment, we evaluate the result of word representation on the standard lexical semantic evaluation task. The results show that the method has a certain improvement in the semantic representation of the word embedding.
A Propagation Condition Identification and Non-Line of Sight Error Mitigation Algorithm in Wireless Sensor Network
Authors: chu Hao , Lian Siyi , Yang Hao , Wu Rongguang
Published: March 2020

Node localization is one of key technologies in wireless sensor networks (WSN). In practice, the occlusion of obstacles often leads to large non-line-of-sight (NLOS) error. Therefore, the misidentification of LOS (line-of-sight)/NLOS conditions can seriously reduce the accuracy of localization algorithms in WSN. In this paper, we propose a novel localization algorithm based on hypothesis testing method, which combines the NLOS condition identification algorithm and the extended Kalman filter method to mitigate the NLOS error. Moreover, we introduce the false alarm rate fa to fuse the estimated values in the LOS/NLOS condition to obtain more accurate results. The simulations demonstrate that the proposed algorithm can effectively reduce the influence of NLOS error and improve the localization accuracy.
Field-aware User Influence Recommendation Model Based on Trust Relationship
Authors: Yun Bai , Wandong Cai
Published: March 2020

In current determining of user influence based on network structure, the overall importance of user node in network usually attracts great attention. However, the significance of the users in specific field has not been fully studied, which result in low accuracy and reliability in user influence measurement. In order to resolve these problems, this research proposes a field-aware user influence model, which constructs user influence for specific fields, and analyses the global influence of users in the whole network on a network structure basis. The model, assisted by historical behaviour data, not only considers the spread of user influence, but also takes the relationship between user influence and fields into account. Referring to the global influence, the model is able to optimize the composition of user influence, and further improve the accuracy of recommendation. The experiments based on real data sets conducted in this research unexceptionally proved that the field-aware user influence model proposed in this paper, compared with other methods, can effectively improve the recommendation accuracy.
Semantic Dependency Graph Parsing of Financial Domain Questions Based on Deep Learning
Authors: Xin Peng , Qiujun Li
Published: March 2020

In order to effectively solve the problems of limited accuracy of semantic parsing and ambiguous semantic recognition in the current Question-Answer System based on Chinese Knowledge Map in intention recognition. This paper presents a method about Dependency Reduction in language dependency analysis(DR-BLSTM-CRF) based on Semantic Dependency Graph Parsing(SDGP), Bidirectional Long Short-term Memory(BLSTM) model and Conditional Random Field(CRF) of Xunfei Open Platform. The semantic dependency graph dependency reduction method is as follows:1) Semantic Dependency Graph Parsing of interrogative sentences based on Web API of Xunfei Open Platform to obtain a sentence representation containing semantic dependency information. 2) Named Entity Recognition (NER) algorithm combined with BLSTM and CRF is used to identify the named entity of the interrogative sentence to gain a sequence containing character label information, and then combine the analysis results of semantic dependency graph to obtain a more accurate semantic dependency graph through dependency reduction. The experimental results show that the precision, recall and F1 value of the model proposed in this paper are 33.4%, 33.9% and 34.2% higher than those of LTP in terms of the semantic dependency analysis on the 140,000 self-built data sets of financial domain questions. The model can effectively analyze the semantic dependency of financial domain questions.
Understanding the future of Deep Reinforcement Learning from the perspective of Game Theory
Authors: Gao Ziyi
Published: March 2020

This paper is to discuss the development of Deep Reinforcement Learning and the future of it from the perspective of Game Theory. The relationship and potential interaction between these two areas are also introduced, especially the optimization method. This paper discusses about the situations both under non-cooperative and cooperative game. Recently, Artificial Intelligence (AI) and Machine Learning (ML) have grasp sufficient attention from various research areas. Deep Reinforcement Learning, as one of the most promising ML methods, enlighten more researchers to devote themselves in this area. However, even such accomplishment could not belie that, for most kinds of real-life problems, DRL is still unable to provide with an optimal strategy. Because unlike the well-adjusted environment in laboratory, real life problems are not always able to be converted into mathematical problems. Under such circumstances, most of real-life problems have no nominal “optimal solution”. Game Theory provides potential solutions to covert “real issues” into “mathematical problems”, then it is easier for researchers to handle.
Guidance of Computer-aided Self-teaching and Practice of English Pronunciation for Chinese Adult English Learners
Authors: Zhou Qian , Li Yonghong , Guo Lei
Published: March 2020

As the difference of pronunciation between English and Chinese are huge, it is difficult for Adult English Learners to correct their pronunciation and get better communication results. This passage has provided very basic but necessary phonetic knowledge, the methods of practice aided by computer and some software, which are all very helpful for the adult English learner who want to improve their pronunciation.
Sliding Mode Steering Control of Spherical Underwater Robot
Authors: Liu Zhimin , Zhou Yiyang
Published: March 2020

From the point of view of motion control, considering the effects of inertia mass, additional mass, secondary resistance, gravity and buoyancy on the robot, a relatively complete dynamic model of the spherical underwater vehicle is established. On this basis, the steering controller of the spherical underwater vehicle is designed based on the principle of sliding mode exponential reaching law. The control performance is compared with that of ordinary PID control algorithm. From the simulation results, it can be seen that the steering control of the spherical underwater vehicle with the designed sliding mode control method can make the robot have faster steering ability and stronger anti-jamming ability.
Research and Application of Label Defect Detection Method Based on Machine Vision
Authors: Ren Xiaokang , Wang Wenqiao , Ren Jie , Mao Xuetao , Zhang Mai
Published: March 2020

For the problems of scratches and false detections such as wrinkles and other defects in the printing process, the HALCON software is used for programming, and the product label defects are detected in real time based on the photometric stereo vision technology. Firstly, by dimming the product labels of four different orientations, different orientation maps are obtained, the illumination map is calculated to obtain the albedo map, and then the four-source photometric stereo technology is used on the basis of the traditional photometric stereo technology. After obtaining the surface gradient information of the tag to be tested, the measurement image is subjected to morphological processing using the gradient information to obtain a curvature image. The curvature image is then image processed. Finally, the defective portion is filtered to effectively segment the surface defect area of the label. This method is implemented using HALCON software and is implemented in conjunction with C# mixed programming.
The integration design of artificial intelligence and normal students’ Education
Authors: Yang Shuai , Bai Haicheng
Published: March 2020

With the coming of the era of intelligence, the deep integration of artificial intelligence and normal education will become an important trend of education development. Normal students, as future teachers, are the key force to cultivate innovative talents in the era of intelligence. It is the current work and research focus to actively use artificial intelligence to improve the comprehensive quality of normal students. However, in the current rapid development of education informatization and intelligence, the development of normal education in China still faces four practical problems: the characteristics of normal students are not fully considered in teaching, and the quality of normal education needs to be improved; teachers’ level of education informatization and intelligence need to be strengthened; lack of comprehensive understanding of students’ personalized characteristics, and personalized teaching still needs efforts. Therefore, we try to build a deep integration framework of artificial intelligence and normal education, and explore the idea of using artificial intelligence technology to solve the four major problems of normal education development. Finally, combined with the design idea of the integration of artificial intelligence and normal education, this paper reflects on the problems that may be faced in the process of practice, and puts forward the corresponding solutions.
A Research on Dynamic Target Tracking with Camera Based on Kalman Filter
Authors: Ma Yimeng
Published: March 2020

With the popularization of the camera, all kinds of video network communication technologies have developed towards civil use and become increasingly popular. For household application, a common PC is used to obtain the frame data from the home network, while the constant frame is set as the background. The update function is used to update background in real time, and thereby forming an inter-frame relation matrix. Based on the matrix, Kalman filter can match and track targets. This method can effectively complete the calculation on the PC, perform precise detection and deal with the complexity of the household application. Finally, with the test results, this paper further proves that the method is feasible and can be used in actual situations.
Background Spatial Correlation Filter in Multi-Channel Object Tracking
Authors: Lyu Jiayi , He Ning , Sun Xin , Xue Jian
Published: March 2020

Traditional correlation filters have high tracking efficiency, but because of the negative samples in the correlation filter that are obtained by moving the object patch itself, the real background information is not included in the sample composition. In this paper, the method for obtaining and detecting the background spatial information in multiple channel is given. A method that combines the background spatial information is integrated into the framework of correlation filter, and an experiment was carried out on existing publicly available datasets. The experimental results show that the tracking effect in some complicated scenes (e.g., illumination changes, fast motion, scale changes, and occlusion) is improved. This approach can effectively improve the success rate and accuracy of object tracking in complicated scenes without affecting the frame rate, obtaining a performance that is superior to that of other correlation filters.
NAO Robot Walking Control System Based on Motor Imagery
Authors: Chen Kun , Ai Qingsong , Chen Jiaxi , Zhou Shaokun , Zhao Yuyang
Published: March 2020

Brain-computer interface (BCI) technology refers to the spontaneous imagination of a certain mode of movement in the brain to communicate with the computer or control external equipment. This technology helps the limb rehabilitation of paralysed and stroke patients. BCI system will fix electrodes on the experimenter’s brain. This paper designs a brain-computer interface system based on motor imagery, and uses it to control the movement of NAO robot. The system is mainly divided into three modules: signal acquisition, signal processing and robot control. In the aspect of signal acquisition, EEG cap, conductive paste, EEG amplifier and the designed upper computer software system are used to realize the design. Computer storage and processing of data. In signal processing, this paper designs a signal feature method based on Common Spatial Pattern (CSP) and Local Characteristic Scale Decomposition (LCD), and then classifies the features into commands to control NAO robots. In the aspect of communication control, the instruction coding is set in advance, and the classification result is set as the instruction to control the different actions of the robot. Socket communication is carried out by client-server mode using UDP protocol. The experimental results of the study also obtained a high accuracy.
Interlocking Train Control Integrated System Modeling Design Based on AADL
Authors: Song Zeyu , Li Guoning
Published: March 2020

In view of the characteristics of high-speed railway signal system due to its huge structure and complex fault phenomenon, the structure and function of the interlocking train control integrated system was designed by analyzing the important components of the computer interlocking and train control center. The computer interlocking, train control center and interlocking train control integrated system are designed and modeled by architecture analysis and design language (AADL). According to the specific requirements of high-speed railway signal system, reasonable AADL components are adopted in the modeling.
Semi-automatic road lane marking detection based on point-cloud data for mapping
Authors: Kang Zhen , Zhang Qiao
Published: March 2020

Traditional manual method for mapping is time consuming and has low precision. In order to increase the efficiency, this paper proposes a semi-automatic road lane marking detection based on point-cloud data. This approach requires simple interface interaction, and since point cloud data is memory intensive, we convert it to RGB images using the intensity and height of the 3D point cloud. Then, in the interface, the user needs to click a point around the detection line and generate image regions of interest. Finally, the image is filtered using a specific filter to obtain a convolved value for each point, and the position with the largest convolution value is the point at the position of the reticle. In this way, we get a point on the road marking, and multiple point connections generate the road markings on the map. Multiple experiments were performed on data from different routes obtained by different sensors, such as veledyne-64, veledyne-16, to verify the effectiveness of road lane marking detection based on point cloud data for mapping..
Based on Polarized Light Navigation: According to The Analysis of Bias of Polarized Angle Measurement
Authors: Shen Xiaofang , Xu Jun , Zhou Zhanrong , Gao Yang , Xu Jiating
Published: March 2020

Polarized light navigation is a interesting research hotspot in the world today. People study the mechanism of polarized light navigation for a long time. However, less progress has been done on the navigation precision. This article discussed on azimuth calculation and polarized angle measurement. Polarized angle measuring system is designed to detect polarized light information. The bias of polarized angle measurement is analyzed based on the system, from qualitative and quantitative point of view. The quantitative influence on polarized angle measurement and polarized navigation are achieved.
Fire Video Image Detection Based on a Convolutional Neural Network
Authors: Wang Wen , Li Tianping
Published: March 2020

Computer vision-based and real-time flame detection is very important to inmodern surveillance system. At present, convolutional neural network (CNN) has become a topic discussed by more and more researchers because of its high recognition accuracy and wide application. The preprocessind process of the traditional image processing method is complicated and the false positive rate is high. So, in this paper we proposed an algorithm for detecting flame in real time using CNN technology. Firstly, to improve the accuracy of detection, we proposed a suspicious target regions segmentation for disposing the suspected flame regions. This algorithm could locate the target area and segment the target area to improve the flame detection and recognition accuracy. Then, we designed a model based on CNN to classify the extracted feature maps of candidate areas. Finally, we could get the detection of flame according to the the classification results. The experimental results show that the approach has high recognition accuracy.
Improving students’ mathematical creative thinking and motivation through GeoGebra assisted problem based learning
Authors: Selvy Y , Ikhsan M , Johar R , Saminan
Published: March 2020

Most teachers, in their teaching and learning practices, tend only to assess lower order thinking skills so that higher order thinking processes, including creative thinking, is rarely done. This study aimed to examine the increase of students’ mathematical creative thinking and motivation through Problem Based Learning (PBL) model using GeoGebra. This research employed an experimental method with randomised pre-test post-test control group design. The sample of the study were two classes of Year 11 students in one of the senior high schools in Lhokseumawe, Aceh, Indonesia. The data were analysed using t-test. The result showed that there was an increase of students’ ability of mathematical creative thinking and motivation taught using the PBL model with GeoGebra; it was higher than those who are taught using PBL model without the software. GeoGebra assisted learning is a useful tool for constructing mathematical concepts such as geometry and making positive contributions to improve mathematical creative thinking skills. The use of GeoGebra is highly recommended to enhance mathematical learning as it shifts mathematics learning to be more fun and interesting.
Mathematical problem-solving skills of junior high school students
Authors: Meutia C I , Ikhsan M , Saminan
Published: March 2020

Student problem-solving skill is the focus of mathematics learning. Students are expected to have specified skills to solve mathematical problems. This study aimed to describe students’ mathematical problem-solving skills at a junior high school in Calang. The method used in this study was qualitative. Two year-9 students were selected by purposive sampling as the participants. Data collection was conducted using a test and interview. The test comprised mathematical problems, aiming to determine students’ ability to solve the problems. The interview was conducted to verify the students’ answer, as some indicators were not fulfilled without the interview. The results showed that the students’ mathematical problem-solving skills were poor. The students did not understand the problems well. They had a plan for solving the problems, but it was not in line with the concept. Their problem-solving implementation was not in order, and they did not recheck their solution. This finding implies that teachers need to pay attention to students’ skills in solving non-routine problems. Teachers should use contextual word problems that are directly related to students’ daily life so that students feel familiar with the questions.
Mathematics problem-solving skills of vocational high school students related to the 21st-century education
Authors: Mailisman N , Ikhsan M , Hajidin
Published: March 2020

21st-century education demands critical thinking, problem-solving, communication, and collaboration skills, as well as creativity and innovation. National Council of Teachers of Mathematics has set five standards on student mathematical skills required by students; one of them is problem-solving. Programme for International Student Assessment showed the lack of Indonesian student problem-solving skills. There is a need for revamping the education system to improve the quality of human resources so that Indonesian students’ problem-solving skills can be better. This qualitative descriptive research aimed to examine the mathematics problem-solving skills of vocational high school students. The research subjects were 22 vocational high school students and the data collection involved a problem-solving test and interview. The results showed that out of 22 subjects (11 groups) in the research, no subject achieved the ‘very good’ and ‘good’ category of problem-solving skills. Four groups had ‘adequate’ problem-solving skills and seven groups had ‘poor’ problem-solving skills. The results showed that students had difficulty in solving problems because they did not understand the problems, and thus they can not solve problems. They were also not accustomed to non-routine problems and had a lack of understanding of designing mathematical models and connecting mathematics to the real world.
Junior secondary school teachers and students’ needs for the use of digital comics in learning mathematics
Authors: Rohaizati U , Mailizar  , Hajidin
Published: March 2020

Digital comics are media presented in the form of visual images that can raise students’ motivation and interest in learning. In Indonesia, it is difficult to find comics relevant to mathematics learning and very few international journals discuss comics in mathematics learning. The purpose of this study was to develop digital comics as a medium for learning mathematics in junior high schools. This study is an early stage of developmental research using the ADDIE model, that is, analysis stage. In this stage, the needs of teachers and students towards the development of digital comics as a medium for learning mathematics were analyzed. Participants in this study involved three mathematics teachers, three vice-principals of curriculum and six students from three junior high schools in Banda Aceh with high, medium, and low national exam scores. Data were analyzed by using a descriptive qualitative method. The results showed that students were less interested in learning mathematics. Moreover, all teachers and students responded positively to the need for developing digital comics as a medium for learning mathematics. The study findings indicate that it is necessary to conduct further research on the development of digital comics as a medium for learning mathematics.
Students’ mathematical connection ability in the learning employing contextual teaching and learning
Authors: Khairunnisak C , Hasbi M , Mustika A , Elizar E
Published: March 2020

Mathematics consists of a variety of topics requiring students to have the mathematical connection ability to link the concepts learned for a better understanding. This study aimed to identify students’ mathematical connection ability in the mathematics learning employing Contextual Teaching and Learning (CTL). It employed a mathematical connection ability test as instrument to achieve the objective. This study was conducted in a junior high school in Aceh Besar regency, Indonesia. The participant of this study were 23 Year 9 students. Students test results were then scored and compared to the indicators of the mathematical connection ability. The results showed that 17 students have poor mathematical connection ability, while the other six students have fair ability.
Indonesian junior high school students’ higher order thinking skills in solving mathematics problems
Authors: Pahdi R , Mailizar  , Abidin Z
Published: March 2020

Higher order thinking skills are important for students to help them solve various problems faced over time. Several previous studies on higher order thinking skills have been conducted, but no one focuses on higher order thinking skills at junior high school level in the regions where the average of computer-based national exam results are relatively low in Indonesia. The purpose of this study is to find out categories of and describe students’ higher order thinking skills in solving PISA problems based on determined indicators. This study used a descriptive qualitative methodology. The instruments used in this study were the PISA test and interview guide. The participants were students in the age range of 15 years randomly selected from several junior high schools in Banda Aceh. At this age, the students’ knowledge and abilities could be assessed. Data were collected from the test, interview and documentation that involved 40 participants. This study found that, generally, students had low level of higher order thinking skills, and there were no students who achieved a high level. Therefore, it is recommended to address this issue by developing and improving the students’ abilities that require higher order thinking skills so that the students are able to apply their knowledge and skills to solve new problems and implement them in real life situations.
Media application in anchored instruction to support mathematics teachers’ pedagogical content knowledge
Authors: Saputra E , Ulya K , Wahyuni S , Rahmadhani E , Hakim H
Published: March 2020

A recent development in science and technology encourages teachers to apply technological information to deal with their duties and obligations of their professional development. The teachers are expected to apply the demands and responsibilities in their learning process. Learning by using interactive media is a solution to answer the recent challenges. This research aims to develop interactive media based on Anchored Instruction to support teacher learning. This study employed a 4-D research design consisting of 4 stages, namely: Define, Design, Develop, and Disseminate. Ten mathematics teachers selected with purposive sampling technique were involved in this study. Data collection comprises questionnaires and observation form. Data was analysed by using research and development procedures and triangulation techniques of data sourced from teacher contents on CoRe sheets, percentage data from student questionnaires, and percentage data from the school principal’s supervision sheet. This development research produced valid learning tools related to Anchored Instruction as valid media to be used in public high schools in Central Aceh. This study also found that Anchored Instruction learning model could help mathematics teachers in improving PCK’s in Geometry subject.
Enhancing student’s creativity by implementing Project-based Learning (PjBL) in biodiversity concept
Authors: Nurmaliah C , Syukriah  , Abdullah  , Khairil  , Safrida  , Artika W , Huda I
Published: March 2020

Creativity is one of the things that becomes a benchmark for the success of the teaching and learning process in the 21st century. One effort to develop students’ creativity is by implementing the Project Based Learning (PjBL) model. This study aims to determine the creativity of students in applying the PjBL model to the concept of biodiversity at SMAN 5 Banda Aceh. This research was conducted at SMAN 5 Banda Aceh from September to October 2018. The method of this research was descriptive. The study population included all students of class X IPA SMAN 5 Banda Aceh. The sample in this study were students from X IPA3. The instrument used in this study is about the observation sheet of creativity of students. Creativity data were analysed by percentage formula. The average percentage of creativity in group students is 68.33% with good categories. Thus it can be concluded that the average percentage of creativity of group students in the implementation of the PjBL model on the concept of biodiversity in SMAN 5 Banda Aceh has a good category.
Antioxidant and anti-termite activities of the ethanol extract of cibotium barometz (L.) J. Sm.
Authors: Musman M , Widayanti P , Erlidawati E
Published: March 2020

The antioxidant and anti-termite activities have been considered on the ethanol extract ofCibotium barometz(L.) J. Sm rhizome. An antioxidant assessment was carried out using the DPPH (2,2-diphenyl-1-picrylhydrazyl) method and measured the absorbance at λ = 517 nm. An anti-termite assay was carried out by the force-feeding method using concentrations of 0, 10, 20, and 30 ppm. The results of phytochemical screening indicated that the extracts contained secondary metabolites of flavonoids, polyphenols, tannins, saponins, steroids, and triterpenoids. The antioxidant trial for which data were processed by the linear regression showed IC50 values of 8.20 and 5.04 ppm for the extracts and the vitamin C (as a standard) respectively. The IC50 value of the ethanol extract of theC. barometzrhizome exhibited the strongest antioxidant activity. The anti-termite assay whose data was processed by the Trimmed Spearman-Karber (TSK) program showed an LC50 value of 28.88 ppm. The termite mortality data for 96 hours were analyzed statistically using one way ANOVA with α = 0.05 demonstrated that the given treatments exposed very significant differences in termite mortality [F(3, 16) = 293, p <0.0001]. Based on the results of the study, it might be firmed that the ethanol extract ofC. barometzrhizome could be exploited as antioxidant and anti-termite stuff.
A Development of project-based learning (PBL) chemistry worksheet to form students’ habits of mind
Authors: Sari R P , Hasibuan M P , Haji A G , Nahadi  , Sofiyan
Published: March 2020

This study aims to develop a valid and effective chemistry worksheet on project-based learning (PBL) in order to shape and train students’ habits of mind. This is research and development (R & D) study with reference to the ADDIE procedural model that has been modified in previous studies with steps: potential problem observation, product design, design validation, implementation and evaluation. Worksheet validation is conducted by 2 validators with 3.8 validation results with a valid category. The result of this study on the implementation test on 20 students showed that the N-Gain test results of 0.73 with high categories and students’ habits of mind assessed through questionnaires. It also had an average score of 74.5 with good categories. The result of students’ habits of mind observation indicated that an increase in the three indicators from the first meeting to the last meeting. Based on the results of the study, it can be concluded that the development of chemistry worksheet on project-based learning is valid and effective to train and form students’ habits of mind. This research finding also indicated that there is a positive effect between habits of mind and student learning outcomes with a total effect of 68.4%.
Application of the 5E learning cycle model to overcome misconception and increase student learning activities in learning chemical bonding
Authors: Salyani R , Nurmaliah C , Mahidin M
Published: March 2020

This research aims to determine the use of the 5E learning cycle (LC) model in reducing student misconceptions and increasing student learning activities in learning of chemical bonding. The research method used was experimental design with the research design was pretest-posttest control group design. The study population was high school class X students consisting of four classes, and the sample group was determined by purposive sampling technique in order to obtain two classes that became the study sample. The results showed the use of the LC 5E model can reduce student misconceptions, this is indicated from the initial analysis the average percentage of students in the experimental class was 50.66, after applying the LC 5E model to 18.30. Increased student activity in learning activities can also illustrate a decrease in misconceptions. Learning activities of students during the application of the LC 5E model in three meetings obtained by 88%, included in the excellent category. The conclusion in this study is the LC 5E model can reduce misconceptions and increase student learning activities because each stage in the learning process directs students actively and creatively.
Impact of integrated STEM on knowledge and self-efficacy based on teachers’ experience
Authors: Rasul M S , Jalaludin N A , Azidawati
Published: March 2020

There are many research studies on education have found that students’ interest toward STEM learning has declined globally. In order to improve the trend, needs more trained teachers in STEM. Thus, this study was done to determine the level of knowledge and self-efficacy of the trained teachers towards teaching and learning based on years of teaching experience. Survey research design were used on 816 teachers from training of trainer’s program. Findings shows that teachers, knowledge, attitude and self efficacy towards teaching and learning based on STEM integration are affected by the teachers teaching experience.
Factors that cause students not to choose physics subject in national examination (NE) 2018
Authors: Farhan A , Devy N K , Wahyuni A , Kasli E , Mahzum E
Published: March 2020

The Indonesian Ministry of Education and Culture in Circular Letter No.0204/H/EP/2017, make significant changes in implementation of national examinations; student individually can choose subjects that are tested on the implementation of the national examination. Based on the result of previous studies, there were students from the science department whose first scores in physics were categorized as high, but didn’t choose these lessons as subjects in the national examination. Any factors that affect students didn’t choose physics subject at national examination, which is interesting to aim why that happen it. Descriptive research with a qualitative approach was carried out to reveal the problem, 40 students of public senior high school at Banda Aceh in the 2017/2018 school year were selected by random sampling as the subject. Documentary data and interviews were used in this study. Based on the data and analysis, it was found that family factors had a strong influence and other factors, specifically teacher, peers, self-ability and ideals sufficiently influence the reasons for students didn’t choose 2018 NE physics subjects. The government is advised to review the decision letter on the implementation of the national high school level exams so that students are not too influenced by external factors.
Attention, relevance, confidence, satisfaction (ARCS) model on students’ motivation and learning outcomes in learning physics
Authors: Afjar A M , Musri  , Syukri M
Published: March 2020

The learning outcomes are influenced by several factors, both from the teachers and the student and still many students who are not motivated to learn, so their learning outcomes tend to be lower. One of the learning models that can be used to improve motivation and learning outcomes is by using the ARCS learning model. This research aims to determine the influence of ARCS models on the motivation and learning outcomes of students in optical equipment at Public Senior High School 4 Banda Aceh. The method of research was quantitative method with pretest-posttest control group design. The population in this study was all students of grade eleven. The sample was selected randomly, grade eleven 4 as an experiment class and grade eleven 5 as control class, each consisting of 32 students. Research instruments were written test and motivation questionnaire and the data analyzed used T-test and N-gain. The result of the four indicators consists of attention obtained 4.55, relevance obtained 4.50, confidence obtained 4.60 and satisfaction obtained 4.74, which means there is a significant influence to the learning outcomes and motivation of students through the ARCS model for optical equipment.
The development of students’ worksheets based on a scientific approach on the heat transfer concept
Authors: Hasja Y , Halim A , Musman M
Published: March 2020

This study is aimed to determine the product quality and students’ responses toward heat transfer worksheets based on scientific approach. The research approach uses the R & D method with 4D model and pretest and posttest groups design. The population of the study was all BP2IP Malahayati Aceh students and the sample was chosen by purposive sampling about 61 students. Data collection used assessment sheets, teacher response sheets, and student response sheets. The result showed that the student learning outcomes have increased after using the student’s worksheets based on the scientific approach, with an average score of N-Gain is 0,21 included in the low category. Still, the average value of students has increased in which the average score of the pretest is 3,97 to 6,77 in the posttest. It can be concluded that students’ worksheets based on scientific approach are suitable and effective to be used in Physics learning, especially in heat transfer lesson to. Besides, the students also give a good response to the worksheets.
Technological pedagogical and content knowledge (TPACK) of science teachers in a suburban area
Authors: Wulansari D , Adlim M , Syukri M
Published: March 2020

The aim of this study is to examine junior high school science teachers’ TPACK levels in District Aceh Besar and to find out the differences between teachers’ TPACK according to their educational background, years of teaching experience, and certification. The TPACK data were collected using a survey method with validated questionnaires. The respondents were 71 science teachers from 33 junior high schools representing all science teachers in District Aceh Besar, a suburb of Banda Aceh city. The data were analyzed using descriptive statistical analysis, specially ANOVA and an independent t-test. The research findings indicate that teachers are more knowledgeable about pedagogical and content domains than in technological. Progress of teachers’ TPACK mean score followed the educational degree level but the teaching experience and professional certification did not have a significant effect on TPACK improvement. Based on this study, science teachers in Aceh Besar need to improve their knowledge and skills in technology and TPACK to face the education challenges present in the Industry 4.0 era.