bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transmission elimination of lymphatic filariasis using spatial autocorrelation
Authors: Surjati E , Wiwoho B S 
Published: April 2021

Abstract
At present, spatial analysis has been used on epidemiology. Spatial analysis was used to determine the environmental risk that influence to transmission of Filariasis. The aim of the study was to identify, at industrial area, the environment determinant that are associated with Filariasis cases in Pekalongan City. The geocoding method was applied on the prevalence of cases to determine the pattern of spatial. Spatial autocorrelation was used to determine the effect of the environment on filariasis transmission. The kernel method was used to determine the density of filariasis cases. Based on the spatial analysis, the statistical values associated with the correlation between the risk of filariasis transmission and environmental factors were obtained. The correlation value of the influence of the environment on the transmission of Filariasis was statistically significant, this coefficient is 0.312. The value of R indicates that the spatial pattern of filariasis cases forms a cluster pattern. The Moran’s index calculation obtained a positive spatial autocorrelation value of 0.44 with z-score is 16.05 and P-value is 0.00. Spatial autocorrelation was useful to determining the level of risk transmission of filariasis in Pekalongan City which may help to adopt effective control strategies in filariasis eradication programs in Pekalongan City.
Learning mathematics through media scales of lamps from used goods
Authors: Mutiarawati A , Nurhayati S , Marini A , Sumantri M S 
Published: April 2021

AbstractThis study aims to determine the learning of mathematics through light scales media from used goods. Students’ understanding of weight comparison is still experiencing difficulties. Students often mistakenly distinguish heavy objects from light objects. Teachers have tried to make improvements through learning methods, but only 20% of student learning outcomes have been completed. Therefore, researchers conduct action research studies in the form of treatment for learning media applications. The research subjects were 30 first grade students. Data collection techniques in this study are through observation, tests, and documentation. The results of the study prove that the use of lamp scales media of used goods in mathematics learning that is in the initial conditions, 24 students have not reached skills, but in the first cycle, the number of students who have not reached mastery decreased to 15 students and in the second cycle all students have reached completeness. This study concludes that the use of media scales lamps from secondhand goods can develop mathematical learning understanding, especially in the theory of weight comparison.
Realistic mathematics education on teaching functions to develop algebraic thinking skills
Authors: Hajizah M N , Wijayanti D A , Darhim D 
Published: April 2021

Abstract
This study discusses how the notion of a function can be developed for high school students through the use various contexts that are close to students’ daily life or make sense to them. The Realistic Mathematics Education approach provides the framework that guides the discussions. The concept of function has become one of the basic ideas in modern mathematics that underlies almost all disciplines. But it proved to be one of the most difficult concepts in learning mathematics. The concept of function is often taught without connecting to everyday context. Formal mathematical symbolism of concept such as f(x) introduced prematurely to students which can lead to learning obstacle about functions. The study provides mathematics educators a hypothetical learning trajectory as a platform which facilitates a Realistic Mathematics Education approach to teaching function especially to develop algebraic thinking skills.
Influence of contextual-metacognitive on Self-Regulatory Strategies students in math IV
Authors: Nanang N , Purnamasari I 
Published: April 2021

AbstractThe problem in this study is the low Self-Regulatory Strategies (SRS) of students in Mathematics IV. The purpose of this study is to determine the differences in SRS between students who get a contextual approach with a metacognitive strategy (PKM), contextual approach (PKT), and conventional approach (PKV). This research is an experiment. The subjects in this study were students of Civil Engineering STT Garut semester 4 of 2018 which consisted of three classes (groups). The experimental group-1 was given PKM, the experimental group-2 was given PKT, and the control group was given PKV. The instrument used was a SRS scale based on a Likert scale. Data analysis was performed with ANOVA test. The main results of this study are students who get PKM and PKT significantly better SRS than students who study with PKV. Based on these results, the researcher proposes: (1) the PKM and PKT approaches should continue to be developed and used as an alternative choice for lecturers in Mathematics IV daily lectures and (2) the application of the PKM and PKT approaches becomes input material for policy makers to develop intelligence potential college student.
Mathematical fitting model and analysis in describing Covid-19 viruses outbreak in Indonesia
Authors: Ilahi F , Ibrahim M A , Gojali D , Akmaliyah A , Mashudi D 
Published: April 2021

AbstractThe outbreak of novel coronavirus at the end of 2019 (covid-19) has become a global concern due to its fast transmission from human-to-human. It is first time discovered in Wuhan, Hubei Province in China. In this research, the author tries to construct epidemiological model that consist of six subpopulations such as susceptible (S), exposed (E), infected (I), isolated (Q), recovered (R), and dead (D) population. Those compartments will be analyzed to get basic reproduction number (R0). The data used in this research is secondary data that obtained from the recent study and various news report related to the covid-19 outbreak. Fitting method will be carried out to describe the virus outbreak and see the trend of the future condition based on the real observation data and the mathematical function that has been determined. The expected result of this research is that the mathematical fitting model and its analysis helping the epidemiologist and health practitioner to determine the right treatment to stop the outbreak so that the society could be back to virgin population.
Mathematical communication skills of students through GeoGebra-assisted ELPSA approach
Authors: Maryono I , Rodiah S , Syaf A H 
Published: April 2021

Abstract
The purpose of this study was to see the development of students’ mathematical communication skills between those who obtained the ELPSA learning model assisted by GeoGebra and those who obtained the conventional learning model (direct-instruction). This study uses a quasi-experimental method. The results showed that the achievement and improvement of mathematical communication skills of students who obtained the ELPSA learning model assisted by GeoGebra better than those who obtained the direct-instruction model. The GeoGebra-assisted ELPSA learning model can be used as an alternative in developing mathematical communication skills, especially in the transformation geometry material in secondary schools.
Game-based learning for the mastery of HOTS in prospective physics teachers in digital electronics courses
Authors: Dewantara D , Misbah M , Haryandi S , Mahtari S 
Published: April 2021

Abstract
This study aims to describe the mastery of HOTS of prospective physics teachers in digital electronics courses after implementing game-based learning. The type of research is a quantitative descriptive study. The number of research subjects consisted of 50 students. Data were collected using a test of learning outcomes about digital circuits in the cognitive domains. The data were analyzed to categorize the students’ high-level thinking skills. The data processed were displayed in the form of diagrams and graphs. The data were also equipped with a student response questionnaire. The results of the analysis showed that 46% of the HOTS in students were categorized in “good” category; 28% in “very good” category; a small proportion of others were categorised as “quite good” and “less good”. The HOTS of prospective physics teachers was already sufficient with an average of 70.25. Student responses were deemed in the “good” category. Therefore, it can be concluded that the mastery of HOTS in prospective physics teachers in digital electronics courses after implementing game-based learning is categorized as high. Thus, it is concluded that the mastery of HOTS in prospective physics teacher candidates in digital electronics courses can be further enhanced and trained by applying game-based learning.
Physics module based on STEM problem based learning on newton’s motion law material for senior high school
Authors: Fathurohman A , Susiloningsih E , Arianti A 
Published: April 2021

AbstractThis research aims to produce senior high school physics module based on STEM Problem Based Learning on Newton’s Motion Law Material that is valid and practical. This is a development research using a design model of ADDIE that modified with Tessmer’s formative evaluation method. Tessmer’s formative evaluation stages in this study include self evaluation, expert review, one-to-one and small groups. Data were collected through interviews, expert testing and questionnaires at the expert review stage. The one-to-one and small group stages and field tests were conducted at SHS Number 1 Banyuasin, South Sumatra. The results of the expert review stage obtained the final score of material validation 1 (very feasible or very valid), design validation 0.91 (very feasible or very valid) and language validation 0.95 (very feasible or very valid). Based on the results showed this research produced senior high school module based on STEM Problem Based Learning on Newton’s Motion Law Material. It is recommended that this module can be used as an alternative teaching for Newton’s motion law material.
Differential equations: Solving the oscillation system
Authors: Sujito S , Liliasari L , Suhandi A 
Published: April 2021

Abstract
The purpose of this research is to perform modeling and simulation to solve differential equations in cases of physical phenomena. The physical system studied is simple harmonic motion. The method used is the method of problem solving using computer software. The simulation uses the Matlab program by applying the Euler method. The result obtained is to distinguish the oscillator graph without any external forces with any forces. This solution helps students solve problems using computer software in giving physical meaning. Therefore, students must be trained and guided to have the ability to think to make it easier to solve problems with the help of computers.
Development of an Atwood aircraft practicum tool based on automatic timers to explain Newton’s second law
Authors: Malik A , Utami N F , Rizaldi M F , Sarah S , Nursetia S , Mauli T , Rochman C , Mulhayatiah D 
Published: April 2021

Abstract
The aim of this study was to determine the feasibility of automatic time-lapse-based Atwood aircraft tools to explain Newton’s second law. The method in this research was the experimental method. Instrument testing was carried out at mass loads m1 of 0.01 kg, 0.02 kg, 0.03 kg, by using weights m2 of 0.1 kg at a distance 60 cm and force variations of 0,5 N, 0,6 N and 1 N. The results of the measurement and analysis of the data obtained acceleration in theory Newton’s second law, namely each for mass variants and successive forces is 4.864 m/s2, 4.102 m/s2, 3.414 m/s2, 2.069 m/s2, 2.581 m/s2 and 4.102 m/s2. The results of the acceleration calculation are based on an automatic time interval 4.220 m/s2, 3.826 m/s2, 2.985 m/s2, 1.697 m/s2, 2.415 m/s2 and 3.826 m/s2. The smallest error data is 6.39% and the biggest error is 18%. The results of these measurements indicate the measurement is still accurate because the error percentage is less than 20%.
Physical problem in interpreting classical energy of soliton of sine Gordon equation
Authors: Prayitno T B , Budi E , Sunaryo S , Fahdiran R 
Published: April 2021

Abstract
The classical energy of soliton of sine Gordon equation was evaluated by using the Hamiltonian density. We classify the condition at which the energy will be either convergent or divergent. For the convergent energy, we also impose the condition at which the energy is real. We justify that there is a satisfied condition to obtain real energy.
Research on Reliability Model Evaluation of Satellite Communication System
Authors: Cai Ruiyan , Du Jingjing , Yang Li , Pan Chengsheng 
Published: April 2021

Abstract
Traditional model evaluation methods such as analytic hierarchy process (AHP) cannot provide specific theoretical basis for the later optimization of satellite communication system. To solve this problem, this paper presents an evaluation algorithm based on the reliability modelling process of satellite communication system. The algorithm combines the subjective analysis and objective data in the process of modelling to obtain the fuzzy quantitative evaluation value of the three links of system definition, mathematical model determination and reliability calculation in the process of modelling, and the final Evaluation result is calculated by using Bayesian theory. The validity and feasibility of the algorithm are verified by an example, and some references are provided for the further optimization of the model.
Pose-guided End-to-end Visual Navigation
Authors: Fang Cuiyun , Zhang Chaofan , Tang Fulin , Wang Fan , Wu Yihong , Liu Yong 
Published: April 2021

Abstract
End-to-end visual navigation based on deep reinforcement learning (DRL) has recently attracted much attention. For most existing navigation methods, a robot moves along only fixed directions (e.g., up, down, left and right) on a grid. Obviously, they are not flexible and efficient, which worsens the navigation performance (i.e., the distance of movement and times of rotation). To address this problem, we propose a novel pose-guided end-to-end visual navigation framework, which is flexible and efficient. In the pose-guided navigation framework, a robot can move along arbitrary directions, which are determined by poses between adjacent objects. Further, to select a proper motion and finally form an optimal path, we propose a DRL based action-selected strategy, where a dynamic action select space on the basis of deep siamese actor-critic network is developed. Besides, to validate the proposed method, we propose a novel pose-guided dataset. Experimental results demonstrate that the proposed method outperforms the state of the arts in both flexibility and efficiency.
Analysis of star structure data transmission mode in sensor network system
Authors: Li Yijie 
Published: April 2021

Abstract
Based on the wide application of sensor networks and data transmission in the network, the star structure of sensor networks is composed by using the basic principle and superior performance of sensor nodes, flexible technology and convenient construction. According to the rules and protocols of sensor networks, the star data transmission process is completed. After a large number of data transmission experiments, good experimental results are obtained, and a large number of experimental data are obtained. And the star data transmission process of sensor network is applied to teaching and scientific research practice.
Signal Detection and Identification in an Optical Camera Communication System in Moving State
Authors: Liu Yuanqin , He Weisong 
Published: April 2021

Abstract
Visible Light Communication (VLC) technology uses light-emitting diodes (LEDs) as a signal transmitting source to simultaneously realize lighting and data communication, and the spectrum resources are abundant. Since the visible light communication system with a photodiode (PD) as the receiver has some weaknesses, such as narrow field of view (FOV), inaccurate alignment in moving state, and inadaptability for indoor communication environments, an optical camera communication (OCC) system based on target detection algorithm is proposed in this paper. The system applies a LED array mounted on a moving AGV (automated guided vehicle) as the signal transmitter and a CCD camera as the receiver to realize data transmission in an outdoor environment. In this paper, a VLC MIMO channel model is constructed to verify that simultaneous communication of multiple LEDs through MIMO channels can effectively reduce bit error rate. The designed OCC system utilizes an image processing algorithm based on target detection to detect and identify light signals, realizing relatively stable and reliable communication in the state of motion. The distance from the signal transmitter to the receiver ranges from 6m to 14m.
Performance Simulation of Underwater Acoustic Spread Spectrum Communication Based on LDPC Code
Authors: Wei Xiao Fei , Chen Jin 
Published: April 2021

Abstract
As we all know, the underwater acoustic channel is a time-varying, space-changing, and frequency-varying fading channel with limited bandwidth and severe noise interference. This paper studies and analyzes the main factors restricting the transmission of underwater acoustic channels, and establishes an underwater acoustic multipath time-varying fading channel. The channel coding adopts Quasi-Cyslic Low-Density Parity-Check Codes (QC-LDPC), combined with spread spectrum technology and high-order modulation technology, and utilizes Log-likelihood Ratios Belief Propagation (LLR-BP) is decoded, the simulation results show that LDPC codes have stronger error correction capabilities in underwater acoustic spread spectrum communication systems, ensuring that the system can operate reliably under low SNR conditions.
IYOLO: Multi-scale infrared target detection method based on bidirectional feature fusion
Authors: Zhao Xiaofeng , Xu Yebin , Wu Fei , Cai Wei , Zhang Zhili 
Published: April 2021

Abstract
Convolutional neural networks are advanced computer vision solution for various tasks, and have made considerable progress. In order to detect infrared targets with details and texture features, we propose a detection method based on YOLOv3. First, we propose a bidirectional feature fusion structure called Improve-FPN(Im-FPN), which allows fast and efficient multi-scale feature fusion. Second, we use the Focal Loss(FL) loss function to balance the problem of sample imbalance. Based on these optimizations, an Infrared-YOLO (IYOLO) target detection model for infrared target is constructed. On the self-constructed infrared dataset: Infrared-VOC, the mAP of IYOLO can achieve 77.1%, which is 4.0% higher than YOLOv3, and the detection speed can reach 55.6FPS. Experimental results show that this method can improve the overall accuracy of detection while ensuring real-time detection.
122km single-end phase-sensitive optical time domain reflectometer based on post signal processing method
Authors: Song Muping , Wang Yixuan , Chen Ge , Zhang Yuxin 
Published: April 2021

Abstract
Phase sensitive optical time domain reflectometer is able to detect vibration information. However, when it comes to ultra-long distance detection, the vibration signal is overwhelmed due to noise level and polarization fading. In this paper, a method is used to compensate noise and fading phenomenon based on post signal processing scheme, including sectional amplification, amplitude demodulation and adaptive matched filtering. On the basis of the theoretical analyzation of the detection method, the feasibility is verified by experiment. Vibration information from 122km can be detected.
Design of automatic generation system of equipment protection common sense pocket book content based on power big data
Authors: Gu Hailin , Hu Pan , Qi Jun , Bai Liang , Xia Yu 
Published: April 2021

Abstract
In order to improve the power system and process, strengthen personnel training and guidance, this paper proposes a new automatic generation system of equipment protection knowledge pocket book content based on power big data. Firstly, the architecture of each level of the system is designed. Secondly, according to the architecture design results, the main hardware and software of the system are designed. The hardware mainly includes pocket book content naming module, user management module and pocket book content automatic generation module. In the software part, K-mean clustering algorithm is used to cluster the power big data, and the main content of equipment protection knowledge in power big data is extracted. The above hardware and software are combined to complete the design of automatic generation system for the contents of power equipment protection pocket book. The experimental results show that the performance of the system is greatly improved.
Noise reduction optimization of sound sensor based on a Conditional Generation Adversarial Network
Authors: Lin Xiongwei , Yang Dongru , Mao Yadong , Zhou Lei , Zhao Xiaobo , Lu Shengguo 
Published: April 2021

Abstract
To address the problems in the traditional speech signal noise elimination methods, such as the residual noise, poor real-time performance and narrow applications a new method is proposed to eliminate network voice noise based on deep learning of conditional generation adversarial network. In terms of the perceptual evaluation of speech quality (PESQ) and shorttime objective intelligibility measure (STOI) functions used as the loss function in the neural network, which were used as the loss function in the neural network, the flexibility of the whole network was optimized, and the training process of the model simplified. The experimental results indicate that, under the noisy environment, especially in a restaurant, the proposed noise reduction scheme improves the STOI score by 26.23% and PESQ score by 17.18%, respectively, compared with the traditional Wiener noise reduction algorithm. Therefore, the sound sensor’s noise reduction scheme through our approach has achieved a remarkable noise reduction effect, more useful information transmission, and stronger practicability.
Research on Physical Fitness Classification of Traditional Chinese Medicine Based on Human Infrared Heat Map
Authors: Zhang YanYang , Hu GuangQin , Zhang XinFeng 
Published: April 2021

Abstract
The infrared heat map reflects the overall temperature distribution of the human body, which coincides with the theory of traditional Chinese medicine, as an important indicator of human sub-health status identification in the field of traditional Chinese medicine, the physical fitness of traditional Chinese medicine has attracted more and more attention from the medical field and the general public. Because the infrared heat map of the human body has rich color distribution characteristics, this paper uses color feature extraction and texture feature extraction algorithms combined with SVM classifiers and convolutional neural networks to perform classification experiments. The results show that the accuracy of deep learning algorithms is higher than that of traditional machine learning algorithms, Deep learning can be combined with local subtle features for further research.