bluuebunny/crossref_metadata_2025_split huggingface dataset:
Study of Student Learning Habits and Their Relationship with Learning Outcomes in Elementary Linear Algebra Courses
Authors: Murni D , Helma H 
Published: January 2021

Abstract
The Elementary Linear Algebra (ELA) course is a compulsory and basic course for several other subjects. Most students have not mastered this material well. One of the contributing factors is the students' not good enough study habits. The purpose of this study was to analyze student study habits and their relationship with learning outcomes in the ELA course. This type of research is comparative causal research. The research instrument was a questionnaire and learning outcome test. The populations are students of the mathematics study program for the 2018 academic year. Students are divided into three groups based on their learning outcomes (x), namely groups: high (x ≥75), medium (60 ≤x <75), and low (x <60). The results showed that in general, student learning outcomes were at a good level, but study habits affected student learning outcomes only by 30%, meaning that there were other variables that influenced student learning outcomes. From the average study habits, it is known that students in the high group do better than the medium and low groups.
Analysis of Local Stability and Bifurcation in Cervical Cancer and Immune Cells Interaction
Authors: Winanda R S , Ahmad D 
Published: January 2021

Abstract
The dynamics of cervical cancer cells and immune cell interaction are modeled into a three-dimensional nonlinear differential equation system. It is a representation of the interaction model between one prey and two predators, with cervical cancer cells as prey and two types of immune cells as predators. The nature between these predators is a supportive relationship. Based on the mathematical model is obtained that there are six steady states in which three of them exist and the others do not exist for biological cases. Based on the analysis of stability near these steady states there has a bifurcation point about the steady states. By modifying some parameters value, there is a possibility to heal the cervical cancer sufferers.
The development of mathematics learning devices for junior high school students: a preliminary research
Authors: Santri F , Asmar A , Arnawa I M 
Published: January 2021

Abstract
Students’ problem solving skills (PSS) at SMPN 1 Teluk Kuantan and SMPN 3 Teluk Kuantan still low. This type of research is descriptive research with a qualitative approach. This preliminary research aims to know, review and explain: (1) Students’ PSS at grade viii of SMPN 1 Teluk Kuantan and SMPN 3 Teluk Kuantan (2) The Conditions of mathematics learning devices was used by teachers (3) whether to continue the development of research based on problem based learning to improve PPS. Based on observations from SMPN 1 Teluk Kuantan and SMPN 3 Teluk Kuantan, concluded that the learning devices used have not been able to facilitate students to learning mathematics. So it is necessary to develop learning tools based on problem based learning.
The development of mathematics learning devices based on problem-based Learning on equation system of three variables for tenth-grade senior high school students school
Authors: Arizon  , Irwan  
Published: January 2021

Abstract
This research aims to develop the learning device in the form of RPP (lesson plan) and LKPD (student's worksheets) based on problem-based Learning (PBL) for the material of Linear Equation System of Three Variables for tenth-grade senior high school student, which are valid, practical, and effective. The type of this research is development research. This research used a Plomp's model, which consists of three phases, namely preliminary research, prototyping phase, and assessment phase. This research has not been produced the learning devices that meet the criteria valid, practical, and effective. The result of the lesson plan and students' worksheets validation sheet showed that is developed was not valid. The learning devices are not also practical yet. While the effectiveness of the learning devices has not been seen in problem-solving and self-regulated Learning yet.
The development of mathematical learning devices based on model-eliciting activities and geogebra
Authors: Meisya S , Arnawa I M 
Published: January 2021

Abstract
This research aims to produce learning devices in the form of lesson plan (RPP) and students worksheet (LKPD) based on Model-Eliciting Activities and GeoGebra (MEA & GEO) to promote students’mathematical communication skills. The development model used is a Plomp model. The research data was collected through questionnaires, observation sheets, mathematical communication skills test, and interviews. The results showed that the learning devices based on MEA & GEO are valid, practical, and effective categories.
The Development of statistics learning design based on realistic mathematics education for grade VIII junior high school
Authors: Yuliasari N , Yerizon  , Arnawa I M 
Published: January 2021

Abstract
The results of the preliminary study indicated that there are problems in learning Statistics at grade VIII SMP/MTs. The students tend to be introduced to the use of formulas without involving the discovery of the concept itself and learning apart from the students’ daily experience. This underlies the design of the learning trajectory for Statistics topic and links them to activities based on students’ experience (experience-based activities). The purpose of this study was to design a learning trajectory of Statistics topic for grade VIII SMP/MTs based on the Realistic Mathematics Education (RME) approach, that equipped with a teachers’ and students’ books. This study was a design research that combines the Plomp model with the Gravemeijer & Cobb model. The subjects of this study were the students grade viii MTs Negeri Bangko. This study revealed a Statistics topic-learning design based on RME approach with the learning trajectory that were finding the mean concept, finding the mode concept, finding the median concept, and finding the five series statistical concept. The learning trajectories were implemented through the teachers’ book and students’ book. The results of conducting experiments showed that the context contained in a students’ book that can stimulate the students to develop their knowledge in finding statistical concepts. All strategies was found and discussed by students, show how the construction or contribution of students in finding the statistical concepts from informal to formal level. The results showed that the learning design of Statistics topic basd on RME approach was valid and practical. It was valid in terms of content and language and it was practical in terms of implementation, convenience and time required.
Problem-based learning in real number topic for practising critical and creative thinking
Authors: Adamura F 
Published: January 2021

Abstract
Research has been done is experiment research. Research has been done for knowing the effectiveness of problem-based learning in real number topic of Real Analysis 1. Applied learning devices have been developed in the last development research. This research is done in class VI B of Mathematics Education Program even semester of 2019/2020. Research outcomes show that implementation problem based learning in real number topic was effective. This is because lecturer capability in learning management was good, student activities were significant, student responses were positive, and classical student learning achievement was reached.
The Factors Encouraging Students to take Mathematics tutoring outside of School
Authors: Rada G , Fauzan A 
Published: January 2021

AbstractThe growth of tutoring is proliferating. Several studies showed that the development of the tutoring business could not be separated from the diminishing trust of informal public education in Indonesia. In addition, the program carried out by the tutoring trains to answer questions that might be tested in each test, both for national exams and college tests. This causes some students to try to take courses, so they can enter well-known schools and also to be able to continue their studies at favourite universities. The purpose of this study was to investigate the factors that encourage students to take tutoring outside of school. This type of research was qualitative research. The data collection technique used was snowball by using an interview guide as the research instrument. The research subjects consisted of a student who participated in the tutoring as the key informant and other informants, namely her parent, her school mathematics teacher, her classmates, and other students who took tutoring in the same place. The collected data were analyzed descriptively and qualitatively. The technique of ensuring data validity was triangulation. The results revealed that four factors encouraged students to take mathematics tutoring outside of school, namely: (1) Parent' desire, (2) Student' desire to be an excellent student like her classmates, (3) Difficulties in understanding the material explained in the classroom, and (4) Realizing ideals.
The Development of Learning Device Based on the Discovery Learning Model Which is Oriented with Natural Disaster Mitigation Towards Mathematical Analyzing Ability of Pupils in Grade VIII of Middle School
Authors: Tusa’diah R , Yerizon  , Asmar A 
Published: January 2021

Abstract
This study aims to produce mathematics learning media based on the discovery learning model, which is oriented to natural disaster mitigation towards the mathematical analyzing abilities of grade VIII in Junior High School students. This media was developed based on the results of a mathematical analyzing skills test and the results of a questionnaire on disaster mitigation at MTsN 1 Padang. Based on the results, it can be concluded that the mathematical analyzing abilities of students were still very low by the achievements of 20.7%. However, in natural disaster mitigation, the survey results showed that 88.9% of MTsN 1 Padang students showed that there was no socialization and learning treatment about natural disaster mitigation. This research is development research. The development model used in this research was the Plomp model, which consists of three phases: preliminary research, prototyping phase, and assessment phase. The results of the analysis of the data based on the lesson plan (RPP) and (LKPD) validation sheets showed that the mathematics Learning media based on the discovery learning model which oriented to natural disaster mitigation on the mathematical analyzing abilities of students have been valid in terms of construct and content and have also been practical in terms of implementation and easiness of use. which an average of 80.3% and it was also effective for improving students' mathematical analyzing abilities by achievement of 73.84%.
Problem based learning and mathematical problems solving skills of junior high school students: a preliminary research
Authors: Isriani W P , Musdi E , Arnawa I M , Asmar A 
Published: January 2021

Abstract
This study is research and development (R & D). A preliminary research of this R & D aims to get information about students' Mathematical Problem Solving Skills (MPSS) and learning device (known as RPP and LKPD) that the teacher used in learning. Initial observations at SMPN 1 Pariaman and SMPN 2 Pariaman show that: (1) students' MPSS is still low, (2) only a small portion of students are actively involved in the learning process and only some of the students take the learning seriously, (3) The LKPD that the teacher used in learning can’t help students in learning mathematics. Based on this, follow-up is needed in the form of R & D to develop mathematics learning devices based on problem-based learning for junior high school students.
The validity of inquiry-based mathematics learning tools using the Malay context of Rengat to improve mathematical reasoning skills
Authors: Sefni P , Yerizon  , Asmar A 
Published: January 2021

Abstract
Students' low ability in mathematical reasoning is influenced by the learning model applied in the classroom. Such as the use of learning tools with a context that is closer to students' life. The purpose of this research is to produce inquiry-based learning tools with a Malay Rengat context that is valid in improving students' mathematical reasoning abilities. This development research uses the Plomp model which consists of three phases, namely preliminary research, prototyping, and the assessment phase. The validation of the tools was carried out by three mathematics education experts, one educational technology expert, and one Indonesian language expert. The average scores obtained from the validation are 3.57 for the validity of the lesson plans and 3.55 for the validity of the worksheet. With these results it can be concluded that the development of inquiry-based mathematics learning tools with the Malay Rengat context is valid.
The Application of Cloud Computing in College English Teaching
Authors: Liu Yang 
Published: January 2021

Abstract
In the era of Internet linking everything, education faces all-round multi-dimensional challenges and opportunities. In order to utilize the advantages of technology, college English educators should extend the traditional classroom aided by big data and Cloud computing in education. Cloud computing is emerging as a powerful computing paradigm with its aim of efficient resource utilization, providing a new solution for online English teaching and learning. With specific teaching targets of college English, the pre-class, in-class and after-class teaching phases aided by Cloud computing are presented, which aims to provide inspiration for educators, administrators and learners.
Research on SLAM of Large-scale Space Point Cloud Topological Robot
Authors: Wu Changzhong , Ge Fan , Shang Guangchao , Wu Liang , Guo Hengshuai , Zhao Mingpeng , Wang Guitao 
Published: January 2021

Abstract
This paper focuses on the cutting-edge and difficult issues in the field of navigation and positioning of service robots. By exploring the technical approach to practical service robot environment modeling and positioning, a new topology SLAM method is proposed. This paper focus on the key technologies involved in 3D SLAM of robots based on large-scale spatial point clouds, including back-end optimization and closed-loop, high-precision sensor calibration technology. Further propose topological map construction strategies, and focus on designing map-generating algorithms based on graphs or tree structures. The research results will provide innovative ideas and practical solutions for environmental modeling and navigation control of service robots, and strongly support technological advances in related research fields based on three-dimensional environmental perception.
Faster Finding of Optimal Path in Robotics Playground Using Q-Learning with “Exploitation-Exploration Trade-Off”
Authors: Yuan Xiaosong 
Published: January 2021

Abstract
It has been a challengeable task to use algorithms designed for specific situations to plan path in real-world environments, because of the uncertainty and unpredictability of the real world. However, learning algorithms have an effective adaptability to deal with real-world problems such as path planning. Because rules of how to work specifically are not preestablished but to be learnt. In this research, q-learning is modified with “Exploitation-Exploration Trade-Off” to find an optimal path faster in Robotics Playground, which is a real-world simulation in Simulink. “Exploitation-Exploration Trade-Off” is a strategy that enables q-learning to explore more parts of the environment so that it is able to learn more information within the same number of episodes. Four kinds of exploration probability are analyzed, which are linear (to episode), quadratic, hyperbolic and no exploration. The results show that the quadratic one has the best behavior among the four kinds of exploration probability when α and γ (two parameters in Bellman equation used to update q-table) are both 0.9. When α and γ are 0.9, the quadratic one is 27.41%, 32.53% and 36.66% faster than linear, hyperbolic and no exploration one with respect to the number of episodes used to find an optimal path. Effectiveness of balancing exploitation and exploration in q-learning is already proved in previous works, but the novelty of this research lies in testing specific exploration probabilities with different parameters (α and γ) and finding the most effective one as well as combining q-learning with real-world simulations. This research can help other q-learning-related works to save time and get a better result.
Video stabilization algorithm for tunnel robots based on improved Kalman filter
Authors: Liu He , Cui Shiyi 
Published: January 2021

Abstract
The application of tunnel robots in power tunnels is becoming more and more extensive. Due to various reasons, video jitter will inevitably occur during the inspection process, which will affect the real-time processing of subsequent images. In order to reduce the impact of video jitter and meet the requirements of real-time image processing, it is necessary to study fast video image stabilization methods. The traditional Kalman filtering algorithm has less computational cost, but it will cause a large estimation error when the system motion state changes. In this regard, the paper proposes an improved Kalman filtering algorithm, which changes the corresponding filter parameters by real-time estimation of a system in motion to reduce the estimation error. And this algorithm performs Harris corner extraction in the set feature dense area, and combines the PyrLK optical flow algorithm with the homography matrix to calculate the motion trajectory, which improves the calculation speed and accuracy of the algorithm. Experimental results show that this algorithm has better video stabilization effect and faster calculation speed compared with the traditional Kalman filtering algorithm, and can better meet the real-time image processing requirements in the inspection process.
Weakly supervised object detection based on deep metric learning
Authors: Dong Weiming , Zhang Xiaoming , Zhao Ping 
Published: January 2021

Abstract
Weakly supervised object detection is a hot issue in the computer vision field, which aims to train a high performance detection model with low cost annotation data. The existing methods of weakly supervised object detection only summarize the object category but don’t consider the similarity between the objects in the optimization process. For solving this problem to improve detection accuracy, this paper proposes a weakly supervised object detection model based on deep metric learning. In the initial training phase, an initial metric has been learned in advance to measure the similarity between these objects; in the correction phase, we propose an adjacent instance mining method based on proxy samples, this approach expands the model’s recognition view, and prevents premature locking the wrong object position. We design a series of experiments on the PASCAL VOC2007 dataset to prove the effectiveness of this method.
Modelling and Calculation of Seismic Wave Field Caused by Moving Ship
Authors: Peng Fei , Lv Junjun , Wang Xu 
Published: January 2021

Abstract
In order to study the frequency characteristics of seafloor seismic waves generated by sailing ships. The finite element numerical simulation method is adopted and COMSOL Multiphysics software is used to establish a two-dimensional axisymmetric model to calculate the distribution of seismic wave fields and compare the correlation between horizontal and vertical components at different depths when the depth of seawater is same. The results show that the frequency characteristics of the horizontal and vertical components become larger and larger as the sound source approaches the seabed, and the influence of seawater on the vertical direction is more and more significant. According to the research results, the seismic wave characteristics of different components can be used to judge the specific information of the sailing ship more accurately.
Study on the Performance of Light and Shadow Effect in Computer Aided Interior Design
Authors: Li Siyuan , Huang Jian 
Published: January 2021

Abstract
With the rapid development of computer technology in China, interior design has also ushered in a broader space for development. Light and shadow effect is an important trend in art design. Through the designer’s artistic accomplishment, we can further enhance the presentation ability of interior design lighting effect. In practical design, we need to fully consider the physical properties of real life materials. Through reasonable rendering, we can achieve the best performance of light and shadow art. This paper first analyses the significance of Computer Aided Interior design. Then, this paper analyses the light and Shadow form and artistic expression of computer-aided interior design. Finally, this paper designs the interior lighting design effect of a hotel.
Sentiment analysis of Chinese text based on Elmo-RNN model
Authors: Yang Min , Xu Junwu , Luo Kai , Zhang Yiping 
Published: January 2021

Abstract
Traditional word embedding technologies such as Word2Vec and GloVe can only produce a single semantic vector, and can not get the specific meaning of polysemous words in the text combined with context. To solve this problem, a sentiment analysis model of Chinese text based on Elmo and recurrent neural network is proposed. The model uses Elmo model to learn the pre training corpus, and the BiLSTM network structure in Elmo model makes the word vector generated by Elmo model have context sensitive characteristics, which is more accurate in the expression of polysemous words, and this is not achieved by the traditional word embedding technology. Then, the model uses the recurrent neural network to extract the deep-seated features of the word vector and fuse the features. Finally, the softmax function is used to realize the sentiment classification of text. Experimental results show that Elmo-RNN can effectively improve the accuracy of text sentiment analysis.
An Robot Vision Grasping Network Based on Inception-Lite
Authors: Xu Liang , Zhou Ziwei , Wang Chaoyang 
Published: January 2021

Abstract
Using computer vision algorithms to find the grasping position of unknown objects is a key issue in the development of intelligent robot technology. In order to address the problem of robot grasping, firstly, based on the analysis of Inception-v1, a novel Inception-Lite convolution module is proposed, and then a grasping network GRASPNET-CLF is designed based on the convolution module. Finally, the grasping network GRASPNET-CLF is trained and verified by GPU on Cornell grasping dataset. The experimental results show that the GRASPNET-CLF has better performance in the same kind of network, and meets the real-time requirements.