bluuebunny/crossref_metadata_2025 huggingface dataset:
Mesoscale to Microscale Coupling for Wind Energy Applications: Addressing the Challenges
Authors: Haupt S E , Berg L , Churchfield M , Kosovic B , Mirocha J , Shaw W
Published: March 2020

The purpose of the US DOE’s Mesoscale to Microscale Coupling (MMC) Project is to develop, verify, and validate physical models and modeling techniques that bridge the most important atmospheric scales that determine wind plant performance and reliability. The project seeks to create a new predictive numerical simulation capability that represents a range of dynamic atmospheric flow conditions impacting wind plant performance.
Wind LiDAR Measurements of Wind Turbine Wakes Evolving over Flat and Complex Terrains: Ensemble Statistics of the Velocity Field
Authors: Zhan Lu , Letizia Stefano , Iungo Giacomo Valerio
Published: March 2020

Wind velocity measurements of wakes generated by utility-scale wind turbines were performed with the University of Texas at Dallas (UTD) mobile LiDAR station for wind farms in flat and complex terrains. Single-wake LiDAR measurements are clustered according to incoming wind speed at hub height and atmospheric stability regime through the wind shear exponent. Ensemble statistics of the LiDAR data shows that the velocity field in the near-wake is mainly affected by the rotor thrust coefficient, while atmospheric stability is the prevailing factor governing wake recovery. For the wind farm in complex terrain, the wind field is significantly affected by the local orography, showing either local speed-up or low-velocity regions. The analysis of the SCADA data corroborates the occurrence of these wind features and enables quantifying their effects on the wind plant performance.
Three-Dimensional Planetary Boundary Layer Parameterization for High-Resolution Mesoscale Simulations
Authors: Kosović B , Jimenez Munoz P , Juliano T W , Martilli A , Eghdami M , Barros A P , Haupt S E
Published: March 2020

Wind energy applications including wind resource assessment, wind power forecasting, and wind plant optimization require high-resolution mesoscale simulations. High resolution mesoscale simulations are essential for accurate characterization of atmospheric flows over heterogeneous land use and complex terrain. Under such conditions, the assumption of grid-cell homogeneity, used in one-dimensional planetary boundary layer (1D PBL) parameterizations, breaks down. However, in most numerical weather prediction (NWP) models, boundary layer turbulence is parameterized using 1D PBL parameterizations. We have therefore developed a three-dimensional (3D) PBL parameterization to better account for horizontal flow heterogeneities. We have implemented and tested the 3D PBL parameterization in the Weather Research and Forecasting (WRF) numerical weather prediction model. The new parameterization is validated using observations from the Wind Forecast Improvement 2 (WFIP 2) project and compared to 1D PBL results.
Assessing the stability of wind resource and operating conditions
Authors: Pryor S C , Shepherd T J , Bukovsky M , Barthelmie R J
Published: March 2020

Wind energy is both a key potential mechanism to reduce climate forcing and a ‘weather-dependent’ energy source. Thus, while wind energy is making an increasing contribution to mitigation of human-induced climate change, climate variability and change have the potential to induce changes in both the average (expected) wind resource, the inter-annual variability in power production and the conditions in which wind turbines will operate. We present simulations with the Weather Research and Forecasting (WRF) model conducted at 12 km grid-spacing (resolution) over the eastern USA and use them to quantify the spatiotemporal variability in one aspect of wind turbine operating conditions (extreme wind speeds) and possible changes in the magnitude and interannual variability of expected wind power generation. We also discuss possible approaches that can be applied to assess the differential credibility of model-derived assessment of these properties at different locations using examples drawn from the eastern US.
Selective and Coverage Multi-head Attention for Abstractive Summarization
Authors: Zhang Xuwen , Liu Gongshen
Published: March 2020

Although the Transformer model has outperformed traditional sequence-to-sequence model in a variety of natural language processing (NLP) tasks, it still suffers from semantic irrelevance and repetition for abstractive text summarization. The main reason is that the long text to be summarized is usually composed of multi-sentences and has much redundant information. To tackle this problem, we propose a selective and coverage multi-head attention framework based on the original Transformer. It contains a Convolutional Neural Network (CNN) selective gate, which combines n-gram features with whole semantic representation to obtain core information from the long input sentence. Besides, we use a coverage mechanism in the multi-head attention to keep track of the words which have been summarized. The evaluations on Chinese and English text summarization datasets both demonstrate that the proposed selective and coverage multi-head attention model outperforms the baseline models by 4.6 and 0.3 ROUGE-2 points respectively. And the analysis shows that the proposed model generates the summary with higher quality and less repetition.
Research on Image Segmentation Algorithm Based on Information Theory
Authors: Ding Shuhan , Yang Yuan
Published: March 2020

With the development of science and technology, the requirements of images processing have been greatly improved. When processing complicated images, segmentation can be firstly applied, which makes the characteristics of the image more distinct, and divides the image into multiple regions with homogeneous properties for subsequent processing. And the image segmentation algorithm based on information theory is one significant technology, which can identify, compress, and encode images, with relatively high accuracy. This paper introduces the principles of information theory and image segmentation, and research on image segmentation algorithm based on information theory, hoping to promote the better development of image processing.
Enhancing Dark Images Captured On Camera
Authors: Liu Jiamin , He Ning , Yin Xiaojie
Published: March 2020

In recent years, dark image enhancement technology has emerged as a popular subject of research, and has played an important role in security monitoring, traffic management, military reconnaissance, and film production. To solve the problems posed by images captured in poor lighting such that the target is not visible or is difficult to read, we propose a method to process such images to identify the targets in them. An algorithm is developed that uses the dynamic threshold method to determine the white reference point in the image as well as the brightest ten percent of pixels according to size. It then adjusts the white point and balances the area to obtain the final result. Using this, the gamma transform is used to adjust the brightness of the image. The results of experiments show that the proposed method can enhance image brightness without loss of color in the image to preserve its naturalness and improve object recognition in natural scenes.
Face and occlusion Recognition Algorithm based on Global and Local
Authors: Yu Guanwen , Zhang Zhaogong
Published: March 2020

Nowadays, the face recognition direction of unobstructed has been greatly developed, but there is still a huge deficiency in face recognition with occlusion. In order to improve the recognition rate under occlusion, this paper proposes a global and local occlusion recognition algorithm using deep learning for feature learning. Due to occlusion, local significant features will be missing, the impact will cause the accuracy of global recognition to decrease. Therefore, SIFT and SVM algorithms are used to discriminate partial face occlusion, and cut off the occluded local face to form a global face. Global facial features and unmasked local feature are extracted together. In the feature extraction, the LeNet-5 lightweight convolutional neural network and the improved LeNet-5 lightweight convolutional neural network are combined with SoftMax multi-classification. The final classification results use the improved hierarchical voting method to make final decisions on the face, which speeds up the training and prediction speed of the multi-classifier. This experiment will perform occlusion face verification on the AR dataset. The final experimental results show that the method greatly improves the accuracy of occlusion face recognition and has strong robustness to occlusion.
Grey Wolf algorithm based on S-function and particle swarm optimization
Authors: Liu ChenYang , Wang Yongli
Published: March 2020

Based on the analysis of the shortcomings of the grey wolf optimization algorithm, an improved grey wolf optimization algorithm (SGWO) is proposed. The algorithm uses the convergence factor based on S-function change to balance the global search and local search ability of the algorithm. At the same time, the proportion weight based on Euclidean distance of step size and the individual optimal position of the particle swarm optimization algorithm are introduced to update the grey wolf position, thus speeding up the convergence speed of the algorithm to 8. The simulation results of three classical test functions show that the SGWO algorithm has higher accuracy and better stability.Introduction
Research on college graduates employment prediction model based on C4.5 algorithm
Authors: Zhou Fujie , Xue Lingxiao , Yan Zhiqiang , Wen Yongxian
Published: March 2020

Introducing C4.5 algorithm into graduates’ employment field, organizing and analyzing the collected tremendous amount of historical data, building classify Decision-Tree, generating rule set, constructing graduates’ employment prediction model. Using Cross Validation algorithm to verify the accuracy of the model, and gradually accomplish a high-accuracy and high-practically prediction model, applying this prediction model to the employment related decision making and college major structure optimizing.
Mechanism Research and Equipment Development of Laser Cleaning Rust
Authors: JiNan Liu , YanHe Sun , Yuan Fang , Jun Tie , ChunYu Fan , Hua Zheng , ChengBing Zhang
Published: March 2020

With the continuous development of laser technology, more and more attention has been paid to the research of laser cleaning mechanism and the development of finished equipment. This paper introduces the application of laser cleaning technology in rust removal of iron and steel, summarizes the physical mechanism of laser cleaning, and puts forward the condition of synchronous cleaning and passivation of floating rust layer and the method of double beam wet cleaning and passivation. In addition, a cleaning method and device for wet cleaning and de-rusting with two beams is proposed in this paper.
Multi-sensor fusion localization algorithm for outdoor mobile robot
Authors: Li Chang , Sun Hanxu , Ye Ping
Published: March 2020

In this paper, the multi-sensor fusion positioning technology of outdoor mobile robot is studied, and a real-time outdoor positioning algorithm combining GPS and lidar odometry is proposed. Lidar odometry based on 3D lidar for point cloud feature matching is realized. At the same time, a covariance matrix reflecting the local positioning information of the lidar odometry is constructed in real time according to the matching distance and the absolute median difference, and the accuracy factor, the circular probability error, etc. are used as the standard GPS. The positioning effect is evaluated to measure the respective positioning effects of the lidar odometry and GPS. On this basis, the GPS is used as the global factor in the pose structure, and the lidar odometry is used as the local factor to construct the pose observation constraint, and the global nonlinear trajectory optimization is carried out to realize the outdoor real-time positioning of the mobile robot. Experimental results and data analysis verify the effectiveness and practicability of the proposed method.
AI based systems for diabetes treatment: a brief overview of the past and plans for the future
Authors: Zhou Huaping , Myrzashova Raushan
Published: March 2020

Humanity continues to suffer from deadly diseases. Successes of science are great, but diseases that cannot be treated still exist. The only solution is to continue research in the search for drugs, as well as in methods of treating and preventing the onset of these diseases. This article is an overview of the development of AI on the issue of diabetes in a larger population of the planet over the past couple of years. The article contains information about the latest existing innovations of medical AI that helps in the fight against type 1 and type 2 of diabetes in 2019. A general assessment of existing AI systems and research has been conducted, as well as statistics on the distribution and usage of these technologies in the world today. The main problems that have not yet found a solution in the field of diagnosing and treating diabetes of both types are presented in conclusion.
RETRACTED: Research on Smart Grid Data Layout Strategy Based on Cloud Computing
Authors: Bin Chen , Xiaoyi Yu
Published: March 2020

This paper first analyzes the experimental conditions of smart grid data layout based on cloud computing. Then the specific experimental content is analyzed, mainly including global layout and dynamic layout. Finally, taking performance and load balance degree as breakthrough points, the advantages and disadvantages of different layout schemes are analyzed. The purpose is to gives a reference to the related personnel so that they can master reasonable data layout strategy and realize reasonable application of cloud computing technology.
Multimodal Fusion of Speech and Gesture Recognition based on Deep Learning
Authors: Qiu Xiaoyu , Feng Zhiquan , Yang Xiaohui , Tian Jinglan
Published: March 2020

This paper proposes a multimodal fusion architecture based on deep learning. The architecture consists of two forms: speech command and hand gesture. First, the speech and gesture commands input by users are recognized by CNN for speech command recognition and LSTM for hand gesture recognition respectively. Secondly, the obtained results are searched by keywords and compared by similarity degree to obtain recognition results. Finally, the two results are fused to output the final instructions. Experiments show that the proposed multi-mode fusion model is superior to the single-mode fusion model.
Real-time multimodal emotion recognition system based on elderly accompanying robot
Authors: Dou Shaosong , Feng Zhiquan , Yang Xiaohui , Tian Jinglan
Published: March 2020

In recent years, people have been paying more attention to the impact of technological development on human emotion recognition. At the same time, China has become the country with the most elderly population in the world. However, due to the lack of real-time multimodal emotion recognition technology for the elderly accompany robots, this paper proposes a deep learning decision-level fusion of real-time emotion analysis model which is based on the background of the elderly care. The results of image and audio recognition are used for intersection and union operation to get emotional classification result, and the obtained emotional result is corresponding to the feedback behavior of the accompany robot.And after the experiment, the recognition algorithm proposed in this paper accuracy can reach about 90%, which is nearly 10% higher than the single mode, and the feedback of the robot has achieved the expected effect.
Research on Application of Key IoT Technology and Computer IoT Technology
Authors: Maliping
Published: March 2020

China has enjoyed breakneck development of technology in these years, Internet technology is widely used in diverse industries, and by virtue of its advantages, draws wide attention and becomes the modern society’s key technologies. Adoption of key IoT technology and computer IoT has boosted advancement of medical service, traffic and transportation, power grid management, people’s daily lives and agriculture, so they are indispensable support for smart cities. In this context, this paper first introduces the definition, features, and structure of Internet of things, and from the perspective of reality, makes in-depth analysis of key technology of Iot and its application in hopes of giving the value of IoT full play in people’s daily lives.
Research on Linux Real-time and performance Evaluation for Loongson 3A3000 processor
Authors: Chen Xuebing
Published: March 2020

In order to solve the real-time problem of Linux system for loongson3A, the real-time enhancement design of Linux kernel is carried out by using the idea of PREEMPT_RT patch, the performance analysis support based on ftrace tool is improved, and the real-time optimization method based on reserved core scheduling is proposed. The real-time performance of the system is tested from four aspects: context switching, interrupt response, scheduling latency and network latency. Five context switching methods are proposed, including active switching, priority preemptive switching, semaphores, message queuing and signal distribution latency. A test method based on the internal timer of the PCI board is designed. The test results show that the maximum latency of real-time Linux system based on Loongson3A3000 is less than 30us, the reserved core scheduling latency is the minimum, and the maximum jitter of network communication latency is less than 120us. In conclusion, the system based on loongson3A3000 can meet the demand for hard real-time applications at millisecond level.
Security Threats Caused by Public Event Callback in Android Application
Authors: Guo Chenkai , Zhu Jingwen , Yan Xiaoyu , Li Yan
Published: March 2020

The feature of event-driven acts as a key role that makes Android application differentiate from traditional PC software. Since many of those events are hardly predicted and could not be observed by other applications, attackers are similarly impossible to engage corresponding attacks by finding the vulnerabilities of such an event-driven mechanism. However, of various kinds of events offered by either user or system, there are still events that can be received by more than one application and further, which could offer important basic resources to predict specific behaviours of targeted application. In this paper, we aim to analyse potential security threats inside them and demonstrate typical kinds of proof-of-concept attack examples. Apart from that, the critical mechanism-public event callback (PEC) that may cause the threat is firstly modelled and studied, where its four main parts are introduced in detail.
A review of methods for text detection in imagery of natural scenes
Authors: Zhang Boyu
Published: March 2020

Text detection in natural scenes plays a key role in recognition and understanding of text in computer vision, while providing the basic possibilities for combining with Natural Language Processing (NLP). The ability of detection for small text and adjacent text is weak although the text detection in natural scenes has evolved from the horizontal text detection initially to the arbitrary shape text detection. Meanwhile, the environment of natural scenes is complex and changeable, which is a huge challenge for text detection. In this paper, we discuss and compare the horizontal and multi-directional detection methods based on target detection, as well as the curved and arbitrary shape detection methods based on the instance segmentation and semantic segmentation. The algorithm ideas are described and their advantages and disadvantages are analysed. Moreover, we found two research routes of curved text and arbitrary shape text detection known as Top-Down and Bottom-Up. According to the evaluations, PMTD [20] performs best in multi-directional text detection, while SPCNet [16] wins in the curve and arbitrary shape text detection.
Research on tidal harmonic analysis based on correlation observation error
Authors: Zhang Jin , Li ShuJun , Jiang HaiGang
Published: March 2020

The analysis and calculation of tides play a very important role in the correction of water level. The analysis and calculation accuracy are directly related to the correction of water level and the calculation of depth reference surface. For the problem that the observation error is not correlated in the tidal harmonic analysis, and the actual situation of the correlation of the observation error is taken into account. On the basis of the traditional harmonic analysis model, the cofactor matrix is derived by calculating the correlation coefficient sequence of different time intervals of residual water level, and the new observation weight matrix is obtained by inversion. The tidal harmonic analysis model based on the correlation of observation errors is derived and improved. The experimental analysis is carried out by tidal data of monthly adjustment and analysis, and the experimental results show that most of the main tidal harmonic constants are closer to the results of 2019, and the forecast tidal level is closer to the real tidal level. The improved method has achieved certain improvement effects.
Study on Test method of Kiwifruit Hardness Based on Hyperspectral Technique
Authors: Chen Xinyuan , Zheng Lina , Kang Zhiliang
Published: March 2020

Flesh hardness is an important index to measure the quality and storage character of fresh fruit. At present, destructive test method is usually used to test kiwifruit hardness by sampling, while a new method based on hyperspectral technique is proposed in this study. Firstly, hyperspectral images of kiwifruit samples are collected in the spectral range of [400nm, 1000nm], then the hyperspectral images are pre-processed by standard normal transformation, and three sub-ranges of the best combination are selected through synergy interval Partial Least Square (siPLS). Secondly, kernel principal component analysis is adopted for dimension reduction of spectral bands of the best combination sub-intervals, and the first two principal components are input into the trained partial least square (PLS) as characteristic spectral bands. Finally, the test results are compared with physicochemical measurement values. The experimental results show that the Cross-validation Root Mean Square Errors (RMSEC) and the correlation coefficients of the training set and the testing set obtained by the proposed method are 0.2698/0.9315, and 0.3573/0.8738 respectively, indicating that it can effectively test kiwifruit hardness.
The Knowledge Map Analysis about the Theme and Trend of Classroom Study in Higher Vocational Education in China
Authors: Zhang Wei , Li Lingli
Published: March 2020

The article searched the periodical literature of classroom research for Higher Vocational Education in CNKI. And used knowledge atlas analysis and other research methods to draw knowledge maps of high-frequency keywords relationship maps and keyword co-occurrence maps based on data analysis software of Bicomb2、 Ucinet and Citespace, and got seven research themes of the classroom of Higher Vocational Education in China. Finally the paper proposed the research trend of classroom research in higher vocational colleges using centrality analysis and multi-dimensional scale analysis Atlas of SPSS.
Analysis of a stochastic regime switching SIRI epidemic model with double saturated rates
Authors: Li Tongtong
Published: March 2020

In this paper, we propose and investigate a stochastic SIRI epidemic model with saturated treatment and incidence rates. Firstly, by constructing a suitable Lyapunov function, we establish the existence and uniqueness condition of the global positive solution of the model. After that, we obtain the thresholds of the random SIRI epidemic model. Then, we consider the asymptotic behavior of the stochastic SIRI model. Lastly, numerical simulations are introduced to illustrate our results.
Research on tracking method of flower target
Authors: Chen Yunqiang , Wang Qing , Chen Hong , Li Xiang , Song Xiaoyu
Published: March 2020

Flowers are a common species in people’s lives, but people’s understanding of flowers is not comprehensive. The traditional UI display method lacks immersion and interactivity. This paper proposes a method based on the deep learning neural network flower recognition algorithm to recognize the flower target information and replace the traditional UI with the AR information to display the flower information. The tracking and positioning technology used in the floral AR display method is a very important underlying technology. This paper focuses on the tracking technology of flower target, and proposes a server-based flower recognition neural network algorithm recognition algorithm. After identifying the flower information and detection frame, it outputs the detection frame parameters of the flower target, and then combines the OpenCV KCF tracker pair. The method of performing AR display of the flower information has high tracking accuracy and stability.
Study on Medication Regularity of Sijunzi Decoction and Its Categorized Prescriptions Based on Attribute Partial Order Structure Diagram
Authors: Song Jialin , Han Xiaoying , Meng Hui
Published: March 2020

Sijunzi decoction is a famous prescription in traditional Chinese medicine (TCM) for the treatment of spleen deficiency syndrome. Spleen deficiency syndrome is manifested in a variety of symptoms. Herbs can be added or replaced on the basis of Sijunzi decoction according to different symptoms, forming Sijunzi categorized prescriptions. In this paper, the medication regularity of Sijunzi decoction and its categorized prescriptions was studied based on attribute partial order structure diagram (APOSD). According to prescription-herb APOSD generated from Sijunzi decoction categorized prescriptions screened from comprehensive TCM database, it can be seen that three herbs are used in all prescriptions, i.e. Renshen, Baizhu and Fuling. Different forms of Sijunzi decoction mainly depend on whether the forth herb is Zhigancao, Chenpi-Gancao, or Gancao. The efficacy of common herbs in the prescriptions for different symptoms can be presented by prescription-herb APOSD and prescription-symptom APOSD generated from different prescription subgroups. The experimental results show that APOSD can effectively reveal the medication regularity of Sijunzi decoction and its categorized prescriptions, and it is an useful tool for theoretical study of TCM.
RETRACTED: The Exploring on the University Student Honor Management System Based on Enterprise Refined Management under the Background of Big Data
Authors: Lv Zuheng , Wang Jinsong
Published: March 2020

Honor management is one of the routine summative work of colleges and universities. It is related to the vital interests of students and plays an important guiding role in promoting the all-round development of college students and establishing good values. In the new era, the honor management of college students should conform to the characteristics of the big data era, use advanced information technology to improve management efficiency, and strive to achieve refined management goals. Based on the major colleges and universities, this paper aims to explore the improvement plan of college students’ honor management based on the fine management of enterprises under the background of big data. It uses literature review method, research method, action research method, object-oriented method and experimental method to analyze. This paper analyzed the current situation of colleges honor work management, summed up the problems existing in the honor management work, and constructed the workflow after the refined management of college students’ honor management.
First-grade junior high school students’ mathematical connection ability
Authors: Rahmi M , Usman  , Subianto M
Published: March 2020

Mathematical connection is an important aspect of learning mathematics. With mathematical connection, learning mathematics will be easier and meaningful because mathematics is structured and interconnected knowledge. This study aimed to describe students’ mathematical connection ability. The subject of this study was 26 first-grade junior high school students. The instruments used in this study were connection ability test and interview guideline. The results of the study showed that only one-third of 26 students fulfilled the mathematical concepts connection indicators. The results also revealed that no student satisfied the indicators of mathematical connection to real life and mathematical connection to other disciplines. These findings provide information that students’ mathematical connection ability is still relatively low. Therefore more attention is needed to increase students’ mathematical connection ability because when the students have good connection ability, they will be able to understand concepts and improve their understanding of other sciences by connecting mathematical concepts with other concepts.
Improving mathematical understanding and disposition of junior high school students through the 5E learning cycle model
Authors: Nopasari W , Ikhsan M , Johar R
Published: March 2020

This study aims to determine the increase in the ability of mathematical understanding and the mathematical disposition learned though this model as well as the correlation between the mathematical understanding and the mathematical disposition in mathematics learning. The population of this study was the entire seventh-grade students in one of the junior high schools in Takengon, Indonesia. The two-class samples were randomly selected for the sampling purpose. The 5E learning cycle model was implemented at the experimental class, while the control class was utilized the conventional model. The instrument used to collect the data consisted of two types of tests, namely the mathematical understanding test and the mathematical disposition questionnaires. Based on the t-test analysis, it was found that the increase of the mathematical understanding and disposition of students who learned with the 5E learning cycle model was better than that of those who learned with the conventional model. Additionally, based on the Pearson product-moment correlation-test, it was concluded that there was a correlation between the students’ mathematical understanding and their mathematical disposition, with the degree of correlation between them is in the sufficient category. Thus, the application of the 5E learning cycle model could improve students’ mathematical understanding and disposition abilities.
Adaptive reasoning and strategic competence through problem based learning model in middle school
Authors: Darwani  , Zubainur C M , Saminan
Published: March 2020

Most textbooks that are provided by the government employ a lot of non-routine problems in their exercise practice. However, students are incapable of understanding the non-routine problems and they struggle in using their reasoning power which affects the overall achievement of mathematics. The purpose of this study is to identify the students’ ability in relation to adaptive reasoning and strategic competence through Problem Based Learning (PBL) model. This study involved six seventh graders in middle school. Data on students’ adaptive reasoning capabilities and strategic competencies are collected through tests which were conducted over five learning sessions with the PBL model. The research data was analyzed descriptively by comparing test result and interview with the indicator of adaptive reasoning and strategic competences ability. The results show that students’ adaptive reasoning ability can be initiated through learning by PBL model. Two out of the three strategic competence indicators are met by all students. The two indicators are understanding and presenting math problems to verbal forms and selecting the right formula, approach and/or method to solve the problem. Only one indicator of strategic competence is not achieved, which is checking the truth on the settlement of problems that have been obtained. This study provides an overview of the importance of training students to answer non-routine problems through learning. It is a challenge for teachers to familiarize students with systematic steps through various strategies that involve reasoning.
Developing ethnomathematics-based worksheet to teach linear equations
Authors: Vitoria L , Monawati
Published: March 2020

Ethnomathematics-based learning is using local cultural context within the teaching and learning of mathematics. Using ethnomathematics-based learning sources in the classroom can help create a meaningful learning experience. This article reports a design research conducted to develop an ethnomathematics-based worksheet to be used to teach the concept of linear equations. The target users were first-year students of the primary education department of Syiah Kuala University, Indonesia. The development of the worksheet was carried out in three phases which consisted of preliminary research, developing or prototyping and assessment. Data were gathered using validation sheets and observation sheets. Data analysis was carried out qualitatively where the assessment of the product was based on its validity, practicality and effectivity. In this article, we reported the validity and practicality criteria. Several revisions had been made during the development of the worksheet. The end result of the product satisfied the criteria of validity and practicality. These findings suggest that the development of the product can proceed to the assessment phase to test the effectiveness of the worksheet.
Assessing Validity of Problem-Based Comics for Learning of Social Arithmetic
Authors: Rahmah M , Mailizar  , Yusrizal
Published: March 2020

The use of comics in teaching and learning process is highly important. However, the existing comics do not present problems in students’ daily life. The purpose of this study is to develop valid problem-based comic media on social arithmetic topic. The current research used the development of the Plomp model which consists of preliminary research, prototyping and assessment phase. Nevertheless this paper reports the prototyping and assessment phase only, in which the product was validated by five experts. The instrument utilized in this study was the comic media validation sheet. The results of the validation analysis reached the score of 4.5. This score indicated that the validity of the media was in the highly valid criteria, this the comic media can be tested for small groups of student in a pilot study. Students responded positively to the comic learning media on social arithmetic lesson. With the score of 1333 which is in the ‘strongly agree’ interval.
Improving Year 5 students’ learning outcomes in problem-solving through mathematical literacy
Authors: Monawati  , Fauzi  , Husin M , Maisarah
Published: March 2020

Solving mathematics word problems remains as difficult tasks for elementary students. One way to overcome this problem is by applying mathematical literacy. This study aimed to describe teachers’ ability in managing the learning process and determine the learning outcomes of Year 5 students. This study employed a qualitative approach, specifically Classroom Action Research. The study design was carried out in three cycles. The data collection related to teachers’ ability in learning management was conducted by observation, was analysed using descriptive statistics, with the category of “poor, fair, average, good, and excellent”. On the other hand, students’ learning outcomes were measured by a mathematics test, were analysed by using percentages and referred to the school’s minimum criteria of mastery learning. The results showed the increase in teachers’ learning management ability, the average of cycle I, II and III was 4.3 (good), 4.6, and 4.8 (excellent) respectively. Besides, the students’ learning outcome was also improved, the average of cycle I, II and III were 62.36 (23.5% of classical mastery learning), 66.18 (58.8% of classical mastery learning), and 85 (70.6% of classical mastery learning) respectively. The results showed that mathematical literacy could improve Year 5 students’ learning outcomes in problem-solving.
Improving students’ mathematical communication skills and learning interest through problem based learning model
Authors: Hidayati  , Abidin Z , Ansari B I
Published: March 2020

One of the objectives of mathematics learning is to improve mathematical communication skills. One learning model that can improve such skills is problem based learning (PBL). This study aimed to examine the improvement of students’ mathematical communication skills and students’ motivation in statistics using PBL. The method used in this study was classroom action research (CAR). Twenty-seven Year 12 students participated in the study. The instruments used included a test for examining students’ mathematical communication skills, observation sheet for observing student activities, and observation sheet for evaluating the ability of teachers in managing the learning. The results showed that there was an increase in students’ mathematical communication skills through PBL model in Cycle I and II, the average score was 68.89 and 75.56, respectively. The students’ interest in learning mathematics through PBL, specifically statistics, was also improved in each Cycle, with an average of 51% and 67% for the Cycle I and II. The finding of this study can be used as a reference to improve students’ mathematical communication skills using the PBL model. The PBL model also has a positive impact on students’ interest to learn mathematics and it can contribute to help students achieving the mastery learning of statistics.
The implementation of problem-based learning with mind mapping to improve students’ learning motivation
Authors: Areeisty K , Hasanuddin  , Sarong M A
Published: March 2020

Students’ learning motivation is as low as indicated by the poor learning outcomes for the topic of environment pollution system. The current teaching and learning process of environmental pollution is lack of the use of innovative learning models. Their learners are merely listening and take notes and thus they are not interested in learning. This research was conducted to determine the impacts of the implementation of problem-based learning models with Mind mapping on the students’ motivation for the environmental pollution topic in Year 10 of two senior high school Banda Aceh, Indonesia. This research employed a quantitative approach, evaluation research. The method was quasi-experiment, with pretest-posttest factorial group design. The sample of this study were 253 students from SMAN 5 and SMAN 7 Banda Aceh, Indonesia. The instrument was a questionnaire to measure students’ motivation. Data analysis involved a non-parametric test, the Mann Whitney test, at a significant level of 0.05. The findings of this study indicated that the influence of the implementation of problem-based learning models with Mind mapping on the motivation_.outcomes of the Year 10 students for the environmental pollution topic.
The implementation of constructivist modules to correct misconceptions on the human reproductive system concept
Authors: Ramadhani R , Abdullah A , Hasanuddin H , Khairil K , Muhibbuddin
Published: March 2020

It is necessary to find appropriate learning solutions to solve students’ misconceptions on the human reproductive system concepts. This study aims to determine whether learning through the implementation of a constructivist module influences the reconstruction of students’ knowledge about the human reproductive system. The method used in this study was experimental with one group pre-test and post-test design. The population consisted of 272 students from science class XI of SMAN 10 Fajar Harapan Banda Aceh and SMAN Modal Bangsa Aceh Province. A total of 107 students were chosen by random sampling. The study was carried out over four months from March to July 2019. The supporting instruments used were the learning media and the data collection instruments in the form of multiple-choice test questions with Certainty of Response Index (CRI). The data collected through a pre-and post-test were analyzed using percentages. The results show that the number of students who understand certain concepts rose by 52.36%, the number of students who had misunderstandings decreased by 43.58%, and the number of students who had misconceptions fell by 9.94%. So, it is concluded that learning through the constructivist module is effective in improving concept reconstruction and students’ learning outcomes.
The availability of open green space and tree architecture at public senior high schools
Authors: Arlianty D , Hasanuddin  , Djufri  , Muhibbuddin  , Supriatno
Published: March 2020

Schools in Banda Aceh city are often traversed by traffic passing vehicles that exhaust emissions such as Pb, CO, NOx, SOx and CO2. The presence of open green space (OGS) is beneficial in cleaning air pollution. Thus, it is necessary to identify the tree architecture model to ensure suitable types of plants in the school’s green space area. This study used an exploratory survey method. To measure the OGS ratio, the GPS was used to collect the data to get the proportion of the school area with canopy and then the result was converted to a percentage. The architectural model was identified according to the guidelines from Halle and Oldeman. The results showed that 12 schools in Banda Aceh city meet ideal requirements for the proportion of OGS according to Law No. 26 of 2007, and only one school (SHS 13) does not satisfy the requirements. The highest OGS was identified at SHS 16 (79%); while the lowest is at SHS 13 (28%). The tree architectural models found in this study are Scarrone, Corner, Attims, Troll, Roux, Leeuwenberg, Koriba, Rauh, Aubreville and Stone. The dominating tree architecture model of those schools is the Troll model (35.7%) with 15 species.
The correlation between students’ interest and learning outcomes in biology
Authors: Dahliani E R , Rahmatan H , Djufri
Published: March 2020

This study aimed to determine the correlation between students’ interest in learning biology with student learning outcomes in SMTA Banda Aceh. This research was conducted on October to December 2018. This research used quantitative and qualitative approaches with survey methods. Learning outcomes were obtained from grade ten report card in 2018. Research parameter was to see the correlation between students learning interest with student learning outcomes. The study population was all 404 students of nine grade IPA of SMTA in Banda Aceh. Purposive sampling was used for gaining sample consisting of 192 respondents. The data analysis used Product Moment Correlation with a significance level of α 0.05. The results of the study was that there was a significant correlation between students learning interest in learning biology with the learning outcomes of students in SMTA Banda Aceh with a mark of r = 0.229 at SMA N 5 Banda Aceh, a mark of r = 0.246 at SMA Insyafuddin Banda Aceh, a mark of r = 0.040 at MAN 1 Banda Aceh City. The conclusion of this research that it was found a significant correlation between students learning interest in learning biology with students learning outcomes in SMTA Banda Aceh.
Phenetic kinship of eight ferns from Filicinae class based on morphological and anatomical characteristic
Authors: Suryadi  , Muhibuddin  , Hasanuddin  , Samingan  , Nurmaliah C
Published: March 2020

Filicinae is one of the Pteridophyta class with the most species. Thus, the different classification may occur for the same type. Consequently, it is necessary to simplify the classification; one of them is through phenetic kinship analysis. This study aims to identify phenetic kinship of eight ferns from filicinae class based on morphological and anatomical characteristics. The study applied descriptive and survey methods with a qualitative approach. Data was collected in August 2018 and analyzed using an Analysis Cluster method which is presented in the form of a phenogram. The finding suggests that 7 clusters are formed from 8 species of ferns from filicinae class. The closest kinship is shown in the species of Nephrolepis cordifolia (L.) Schott and Nephrolepis biserrata (Sw.) Schott which indicates that both species with the smallest taxonomic distance value have similar morphological and anatomical characters; while the furthest kinship is the species of Nephrolepis cordifolia (L.) Schott, Nephrolepis biserrata (Sw.) Schott., Davalia denticulata (Burm. F) ex. Kuhn., Pteris vitata L., Pyrrosia piloseloides (L.) M.G. Price., and Drynaria bonni. Crist., Adiantum caudatum L., Crypsinus enervis (Cav.) Copel.
Students’ worksheet development on salt hydrolysis material through Problem-Based Learning to improve science process skill
Authors: Fajrina V D , Sulastri  , Gani A
Published: March 2020

This research aims to improve science process skill within the topic of Salt Hydrolysis and to indicate students’ responses upon the implementation. This is an R&D research conducted at a High School in Banda Aceh. The data obtained were analyzed using several techniques, including feasibility test, student science process skill test, and responses of both students and teachers. The result showed that the product was a very feasible category by an average percentage of 93.75%. Limited trial to chemistry teachers at research school exhibited a similar category with an average percentage of 88.17%. For the final result, the comprehensive test was conducted by chemistry teachers among MA/MAS in Banda Aceh expressing the same category with an average percentage of 85.58%. The dissemination and implementation of developing SW for students of MAN Banda Aceh 1 obtained a very good percentage of 86.04% for science process skill. Besides, it showed both students and teachers have positive responses toward the implementation of this technique with an average percentage of 88.50% and 83.33%, respectively. Therefore, it can be concluded that the SW is feasible to be used for practical study on Salt Hydrolysis topic.
The effect of role-playing model on students’ critical thinking skills and interest in learning chemical bonds concept
Authors: Wahyuni S , Rahmatan H , Mahidin  , Sulastri
Published: March 2020

This study aims to determine the effect of using role-playing models on improving critical thinking skills (CTS) and students learning interest on chemical bonding material. The research method used was a quasi-experimental design with pretest posttest control group design. The number of samples used were 135 students majoring science at MAN Banda Aceh, who were selected using purposive sampling technique. The data of this study were obtained from reasoned multiple-choice test questions and student learning interest questionnaires. Data were analyzed using N-gain test, z test and t-test, the results of differences in the increase of CTS in research classes were calculated using Zcount>Ztable with a significant level of 0.05, while the results of students learning interest in the experimental class obtained tcount (5.845) > ttable (1.895) with a significant level of 0.05. Based on the results of the study, it can be concluded that the role-playing model implementation can improve the CTS and learning interest in chemical bond concept.
Enhancing students’ reasoning ability and learning outcomes in the topic of petroleum by using problem-based learning model
Authors: Rasma M , Mahidin M , Gani A
Published: March 2020

This study aims to determine the reasoning abilities and learning outcomes in petroleum material and obtain an overview of students’ responses through the problem-based learning (PBL) model. This research was a quasi-experimental method conducted in a private Islamic Senior High School. The subjects of the study were two groups of students from different classes. Data were collected by written using questions about pre-test, post-test and questionnaire responses of students’ pre-test, post-test, and N-gain the control class obtained values 40.5, 68 and 44.26 respectively, while the experimental class scored 44.67, 80.33 and 63.19 apiece. The reasoning ability of students showed a difference. The students from the experiment class scored higher than the students from the control group. Also, vast majority of students respond positively to PBL learning models.