bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differentiation between TPACK level in junior and senior pre-service teacher to design science lesson
Authors: Terra I W A , Ridlo Z R , Indrawati  , Hidayah S 
Published: June 2020

Abstract
Technological development provides enormous opportunities for efficient and active learning. Advance in technology-based learning should be inline with the ability of teachers to teach science using technology. Preservice teachers should be equipped with an appropriate college curriculum. TPACK can be used to see the abilities of prospective science teachers. This study was examining different TPACK levels at junior and senior-level. This study involved a sample of students majoring in a bachelor's degree in science teacher program. The results of the questionnaire showed that junior-level students have higher TPACK than senior-level. Based on the results of a lesson plan analysis, junior-level students tend to use technology in the classroom. Students at the senior-level have been experienced in classroom teaching. However, classroom management and time management skills of maybe affects the TPACK level in junior and senior-level students.
The effectuality of animated media for teaching biotechnology materials in indonesian rural primary schools
Authors: Fitriyah S M , Imamyartha D , Bilqis M , Finali Z , Latifah A A , Harfiyani A I 
Published: June 2020

Abstract
Learning technology has been an intriguing medium which may escalate class engagement and students’ interests into learning. However, not every student is entitled to equal opportunity to be able to benefit from this often considered luxury for some, for instance for those living in the rural areas of Indonesia. This study aims to measure the effectiveness of animated media developed for teaching biotechnology materials in rural primary schools in Indonesia. Four teachers from two rural primary schools in the east of Java, Indonesia participated in this study. The teachers and research team collaborated in a lesson study style activities and take turn to use the media to teach materials regarding biotechnology for their students. This mixed method study utilised data gathered from students’ pre-test and post test and the results of interviews with the four teachers, and participatory observation reports of the activities. The results of this study indicated that the media were significantly effective to improve students’ mastery of biotechnology materials, which was facilitated by the affordance of the media to alleviate students’ excitement, autonomy, and focus on learning.
The analysis of learning materials implementation based on research-based learning to improve the elementary school student’s creative thinking skills in solving “polamatika” problems
Authors: Wahyuni S I , Dafik  , Farisi M I 
Published: June 2020

Abstract
The student's creative thinking skills are very important, but in fact, it has not met an expectation. In this study, researchers tried to apply learning materials base on research-based learning to improve their creative thinking skills. This research is using a mixed method, namely a combination of quantitative and qualitative methods. Quantitative method will be used to analyze the type of interval data of student learning outcomes, while the qualitative method will be used to analyze an ordinal data of creative thinking skills. The research respondents consist of two classes, namely a control class as many as 31 students and an experimental class as many as 30 students. The score of the independent sample t-test from post-test shows that between the control class and the experimental class has a significant difference with the sig (2-tailed) value is 0.000 (p = <0.05). It can be concluded that the implementation of learning materials based on research-based learning can improve the elementary school students creative thinking skills in solving “polamatika” problems.
The development of Islamic-based PISA question models on the topics concerning quantity and its enhancement to improve student problem solving skills
Authors: Indahwati T , Dafik  , Irvan M 
Published: June 2020

Abstract
Problem Solving skills are very important to facilitate students in understanding and solving mathematical problems and in everyday life. But what is often found is low student problem solving skills, and even Indonesian students' PISA math results are ranked low. This study aims to: (1) describe the process of developing Islamic-based PISA model questions on content quantity and enrichment to improve students' problem solving skills; (2) describe the results of the development of Islamic-based PISA model problems on topics concerning Quantity and enrichment in a valid and practical manner; and (3) reveal the improvement of students' problem solving skills after applying the Islamic-based PISA model questions on the content quantity and enrichment. The research subjects were students of class VIII-A MTs Plus Baitussalam Toyamas, Banyuwangi regency in the even semester of the 2018/2019 academic year. The research design used two stages, namely the preliminary stage and formative evaluation. The stages of formative evaluation include the stages of self evaluation, prototyping (expert review, one-to-one, and small groups), and field tests. The research instrument used was a validation sheet; Observation sheet and student response questionnaire, and student learning outcomes test. Data analysis techniques include data analysis process development questions, validity, reliability, and problem solving skills of students. The question development design consists of two stages, namely preliminary and formative evaluation. The formative evaluation stage includes self evaluation, prototyping (expert review, one-to-one, and small groups), and field tests. The results showed that the development of a prototype device produced 10 items of Islamic-based PISA mathematical problems that were valid and practical. The results of the prototype validation test have validity values above 0.361 and the results from the table show r-count> r-table so that the questions have high reliability, implying that they can be used to determine the level of problem solving skills of students. The average results of the problem solving skills in field test are 9 students (28.13%) very good category; there are 13 students (40.63%) in the good category; there are 7 students (21.88%) in the sufficient category; and there are 3 students (9.40%) included in the less category. Overall, the average problem solving skills of students reached 35.43% with a good category. An increase in students' problem solving skills after students have been trained to solve PISA model problems, so students are able to understand and solve material on quantity problems; they have applied the correct problem-solving strategy.
The analysis of the implementation of discovery-based learning to improve students’ creative thinking skills in solving the number multiplication problems
Authors: Sumartiningsih  , Dafik  , Suparti  
Published: June 2020

Abstract
This study aims to investigate the analysis of the implementation of discovery-based learning to improve students’ creative thinking skills in solving the number multiplication problems. Students' creative thinking skills are very important, even though the current condition is not as well as the expectation. This type of research used is a mixed method, which is a combination of quantitative and qualitative methods. Quantitative methods are used to analyze interval data types for student learning outcomes, while qualitative methods will be used to analyze ordinal data of creative thinking skills. The research respondents consisting of two classes, namely 30 students for control class and 30 students for experimental class. The results showedthat implementation of discovery-based learning to improve students’ creative thinking skills in solving the number multiplication problemsin the experimental class is more effective than control class used conventional learning. The independent sample t-test from the post-test showed that there was a significant difference between the control class and the experimental class with the sig (2-tailed) value is 0.000 (p = <0.05). It can be concluded that implementation of discovery-based learning can improve students’ creative thinking skills in solving the number multiplication problems.
The analysis of application of learning materials based on inquiry based learning and its effect on critical thinking skills of students in solving fractions problems
Authors: Chususiyah S , Dafik  , Prastiti T D 
Published: June 2020

Abstract
Critical thinking skills are needed to improve mathematical abilities in 21st century. However, with the current learning model, showing students' critical thinking skills did not increase significantly. This study aims to analyze usage inquiry-based learning and find out their effects on students' critical thinking skills in solving fractions problems. Research design using research a mixed methods that is a combination of quantitative research and qualitative research. Research respondents from class 3 were divided into a control class of 22 students and an experimental class of 20 students. Data collection is done through observation sheets, tests, documentation and interviews. The results showed that after the implementation of inquiry-based learning, the percentage of students' critical thinking for the control class was a very critical of 0%, critical 9%, 45% for quite critical, and 46% for less critical and not critical. Starting while for the experimental class the results were very critical 25%, critical 50%, quite critical 15%, less critical 10%, not critical 0%.. The t-test score of the independent samples from the post-test showed that there was a significant difference between the control class and the experimental class with a sig (2-tailed) value of 0.001 (p = <0.05). It can be concluded that the application of inquiry-based learning can influences students' critical thinking skills in solving fractions problems.
The implementation of project-based learning in STEM activity (water filtration system) in improving creative thinking skill
Authors: Ridlo Z R , Nuha U , Terra I W A , Afafa L 
Published: June 2020

Abstract
This research is concerned with STEM activity making water purifier filter. The experiment class applies project-based learning, while the traditional class is taught using conventional teacher talk or explanation. This research used triangulation methods. The quantitative methods were applied to analyze student achievement tests according to creative thinking skills in making water filtration design. The qualitative method was applied using observation of student activity, presentations, and interviews for selected students. The student achievement test was analyzed and coupled with pretest and post-test quasi-experimental research. The collected data were analyzed using inferential statistics in the form of an independent sample t-test to express creative thinking skills. The result of the pre-test indicated the sig (2-tailed) of 0.965, with a significant value of 5% (p>0.05). This result indicated two classes were homogenous. The data analysis of the post-test indicated value of sig (2-tailed) 0.00 where p≤0.05, which implied the student achievement test on creative thinking skills criteria in the experimental class was better than that in the control class.
Cloud Platform Task Scheduling Strategy for Power Dispatching Automation System Based on Artificial Intelligence Algorithm
Authors: Li Shiming , Li Bo , Wang Ke , Guo Wenxin , Liu Yang , Zhao Ruifeng , Zeng Jianyong , Li Haobin , Lin Yueting 
Published: June 2020

Abstract
As the command and control center of the whole power grid operation, the power dispatching system has huge and complex data information, which makes the traditional power grid dispatching information platform difficult to meet the needs of power grid operation monitoring in information integration, analysis, calculation and storage. Therefore, cloud platform is introduced into the construction of power dispatching automation system. This paper takes the power dispatching automation cloud platform as the research object, studies its architecture, and proposes a cloud platform task scheduling model based on improved particle swarm optimization, aiming to improve the efficiency of cloud computing resource allocation, improve the quality of cloud services, and solve the task scheduling problem of the power dispatching automation system.
Research on Tibetan Speech Recognition Speech Dictionary and Acoustic Model Algorithm
Authors: Gong Chunwei , Li Guanyu , Luo Lisai 
Published: June 2020

Abstract
This paper mainly conducts related research on the algorithm of the Tibetan acoustic model. Firstly, a Tibetan Lhasa pronunciation dictionary is constructed based on words and monossssyllables, and then compared. The experimental results show that the phonetic dictionary constructed by words is superior to the phonetic dictionary constructed by monosyllables. At the same time, taking phonemes and single syllables as the modeling unit of the acoustic model, the modeling unit of the acoustic model was studied and a comparative experiment was carried out. Experimental results show that phonemes are better than single syllables as acoustic model modeling units.
Automatic retrieval of network hotspot information based on improved DBSCAN clustering algorithm
Authors: Deng Dingsheng 
Published: June 2020

Abstract
With the continuous development of the Internet in the world today, the proliferation of network information makes it difficult for people to effectively screen out current hotspot information. In order to solve the problem of how to retrieve the current hot information quickly and accurately under the massive network information, an automatic network information retrieval method based on the improved DBSCAN clustering algorithm is proposed. The retrieved related keywords are combined to reduce the feature terms, which effectively solves the problem of repeated acquisition of public resource object neighbourhoods, greatly improves the accuracy and efficiency of the clustering algorithm, and realizes automatic retrieval of network information hot spots. The results show that the automatic network information retrieval method based on the improved DBSCAN clustering algorithm proposed in this paper can quickly and accurately find the current information hotspots on the Internet, help users to obtain the hotspot information of their own most interest, and promote the progress and development of the Internet.
The Application of BP Neural Network Algorithm in Rapid Design of the Vertical Boom of Bridge Inspection Vehicle
Authors: Zhao Jian , Li XueLing , Ma HongFeng 
Published: June 2020

Abstract
During the analysis of the vertical boom of bridge inspection vehicle, it is not easy for the designer to provide a good design scheme quickly. In order to find a professional CAD software which can quickly obtain the ideal design scheme, the BP neural network algorithm is adopted to obtain the design solution by means of mapping. The better schemes of vertical boom are selected for different types of bridge inspection vehicles. These schemes are used as sample data to train the BP neural network for obtaining weights and thresholds. The trained neural network is used for the rapid design of the vertical boom of bridge inspection vehicle. As long as the design parameters are input, the design scheme of the vertical boom can be output directly.
Data association rules mining method based on genetic optimization algorithm
Authors: Xu Binghui , Ding Sizhe , Li You 
Published: June 2020

Abstract
Traditional data mining methods usually need to visit the database repeatedly to determine the frequent item set, which makes the data server burden heavier and reduces the efficiency of data mining. To solve this problem, this paper combines the immune mechanism and genetic algorithm dynamically to improve the traditional genetic algorithm (GA), and proposes a data association rule mining method based on improved immune genetic algorithm (IIGA), which realize the effective analysis of big data. The experimental results show that the algorithm we proposed is better than immune genetic algorithm and Apriori algorithm in data mining time and association rules mining accuracy, which can be better applied to data analysis. The research results have positive reference significance for the field of data mining.
Research and Application of Path Planning Algorithm in Complex Terrain
Authors: Liu Yunxiang , Xu Wei 
Published: June 2020

Abstract
Aiming at the failure of path planning in complex three-dimensional terrain, a path planning algorithm based on Hopfield neural network is proposed. According to the three-dimensional terrain, the undulating terrain and obstacles are transformed into a calculable regular figure, and the terrain function model is established according to the flow field control equation; the terrain function model is effectively integrated with Hopfield neural network algorithm. The algorithm is applied to complex three-dimensional terrain environment, can avoid undulating terrain and obstacles, and find an optimal path, which lays an important foundation for the navigation vehicle path planning.
A multicast routing restoration algorithm based on the n-person non-cooperative game in multi-domain optical networks
Authors: Wu Qiwu , Cheng Hao , Zhou Yang , Long Zhang , Jiang Lingzhi 
Published: June 2020

Abstract
Aiming at the restoration problems for multicast service in multi-domain optical networks, a multicast routing restoration algorithm in multi-domain optical networks based on the n-person non-cooperative game is proposed by adopting the Breadth First Search (BFS) strategy and n-person non-cooperative game theory. This algorithm optimizes the searching sequence of BFS algorithm and reduces the searching scope by the competitive selection relation of the game theory. The algorithm analysis and experimental results show that the algorithm has low time complexity, reduces the computational time of the restoration path, and reduces the blocking rate of the multicast restoration service.
AGA-LSTM: An Optimized LSTM Neural Network Model Based on Adaptive Genetic Algorithm
Authors: Bai Chenyao 
Published: June 2020

Abstract
With the increase of the hidden layer, the weight update of the LSTM neural network model depends heavily on the gradient descent algorithm, and the convergence speed is slow, resulting in the local extremum of the weight adjustment, which affects the prediction performance of the model. Based on this, this paper proposes an optimized LSTM neural network model based on adaptive genetic algorithm (AGA-LSTM). In this model, the mean squared error is designed as the fitness function, and the adaptive genetic algorithm (AGA) is used to globally optimize the weights between neuron nodes of the LSTM model to improve the generalization ability. The experimental results show that, on the UCI dataset, the prediction accuracy of the AGA-LSTM model is greatly improved compared to the standard LSTM model, which verifies the rationality of the model.
A class of numerical methods for determining the inclusion relation of positive invariant sets in linear dynamic systems
Authors: Li Xiaoqian 
Published: June 2020

Abstract
Positive invariant sets play an important role in the system theory and a:lication of dynamic systems. Firstly, in order to judge the inclusion relation between positive invariant sets of systems, the equivalent conditions for judging the inclusion relation of special positive invariant sets are derived for two special positive invariant sets. Three specific positive invariant subsets are discussed, and the verification of the inclusion relation of positive invariant sets can be transformed into a class of numerical problem in the form of optimization, which simplify the conditions of readily implemented. Finally, numerical examples are given to illustrate our conclusion.
Research on user behavior recommendation algorithm for business process
Authors: Li Kunying , Ding Yu , Li Xiaolian , Shi Ying , Zhang Wenting 
Published: June 2020

Abstract
In this paper, ProcessLink is a user behavior judgment and recommendation algorithm based on the information system business process. The purpose is to provide users with reliable unknown process selection. The algorithm idea is as follows: firstly, collect and analyze historical data, establish the relevance feedback set of “Time-Role -Process”, establish the interest relationship decision table of each role according to the process flow link behavior between users. Starting from each process node, the Apriori algorithm completes a round of initial filtering on these relationships, and obtains the similarity association degree of each role node in the process link; finally, the recommendation sorting is carried out through the recommendation algorithm model matching and scenario similarity calculation. This research realizes the accurate prediction of the user’s next link and gives the corresponding opinions. The experimental results show that the algorithm is effective and accurate in the business process.
Target detection algorithm based on improved multi-scale SSD
Authors: Cao Jianying , Kong Yan , Zhang Xinlu , Li Yongjia , Xie Xiaofeng 
Published: June 2020

Abstract
The traditional SSD algorithm has a serious abstraction of feature extraction content, which makes it difficult to achieve effective detection of small targets. At the same time, the problem of feature layer fusion is difficult due to different scales. In this paper, an improved SSD based target detection algorithm is proposed. By introducing feature enhancement method, the adjustment steps of high-level feature size are omitted, Which makes it unnecessary to reduce the dimension of features, and at the same time, it uses the multi-scale candidate area which accords with the proportion of pedestrians in the detection network to enhance the feature extraction ability of small targets, effectively improves the accuracy and operation speed of SSD algorithm, and saves the loss of the network.
Research on Cooperative Encirclement Strategy of Multiple Underwater Robots based on Wolf Swarm Algorithm
Authors: Luan Xiaolin , Sun Yuting 
Published: June 2020

Abstract
The problem of multi underwater vehicle cooperative seizing is an important part of the research of multi-underwater-vehicle cooperative task self-organization, which is widely used in military, rescue and other fields. In this paper, the problem of multiple underwater vehicles (AUVs) encircling is a group of AUVs, which can encircle a target body through cooperative cooperation. The stability of the system can be improved by applying the wolf swarm algorithm to the multi underwater robot system. In this paper, we mainly study the problem of multiple underwater vehicles in two-dimensional space. Wolf swarm algorithm abstracts three kinds of swarm intelligence behaviors, calling wandering behavior, summoning behavior and preying behavior, puts forward a new swarm intelligence algorithm by simulating Wolf-swarm predation. The effectiveness of the algorithm is verified by numerical simulation.
Application of K-means clustering algorithm in the analysis of college students’ online entertainment consumption
Authors: Li Huanqin 
Published: June 2020

Abstract
It is benefit for college students to explore the characteristics of online entertainment consumption and give them appropriate guidance. The Online entertainment consumption of some undergraduate students is investigated in this paper, and the K-means algorithm is used in the survey to carry out clustering analysis. The results show that in terms of online entertainment consumer behaviour, the consumption amount is polarized, consumption is gender-differentiated, consumer contents are diversified, consumer has more copyrighted-awareness., etc. From the clustering results, the K-means algorithm is more effective for analyzing the characteristics of online entertainment consumption behavior.