bluuebunny/crossref_metadata_2025 huggingface dataset:
Graphic communication in detecting outlier cases in time column control diagram
Authors: Enjang E , Aliyudin M , Nurdin F S , Laksana M W , Sarbini S
Published: April 2021

Control diagrams are graphical communication media that can be used as tools in the process of controlling statistics statistically to assist in monitoring and improving a quality process by helping to separate specific cause and general cause variables. Basically the control diagram plots the area of acceptance of a hypothesis test. This study aims to detect disruptive causes in the control diagram in time series cases and to justify the statistical model in accordance with the procedure. A process is said to be controlled if the observational data from that process behaves like random iid variables (independent identically distributed), and if it is not controlled, it is out of control. The study uses 25 days’ time series observational data in PT. Guccitex Cimahi. In this time frame analysis, research that is influenced by specific causes can be treated as outliers of the time series model and can be detected by outlier detection methods. The results in this study explain that a traditional control diagram is very dependent on the assumption of iid (independent identically distributed). Application in real life faces observations that are not iid (independent identically distributed), which show the effects of trends, seasonality, and other influences. The control diagram is in principle the same, using time series analysis to overcome these effects by plotting the area of acceptance of a hypothesis test, but if the process is not controlled, the control diagram cannot provide any guidance, so it is necessary to do a data analysis using analysis time series.
Generalized Linear Mixed Models by penalized Lasso in modelling the scores of Indonesian students
Authors: Santi V M , Notodiputro K A , Sartono B , Rahyu W
Published: April 2021

The Generalized linear mixed model (GLMM) is an extension of the generalized linear model by adding random effects to linear predictors to accommodate clustered or over dispersion. Severe computational problems in the GLMM modelling cause its use restricted for only a few predictors. When many predictors are available, the estimators become very unstable. Therefore, the procedure for selecting relevant variables is essential in modelling. The use of penalty techniques for selecting variables in mixed models is still rarely applied. In this article, the penalizedLassoapproach proposed to handle these kinds of problems. The proposed methods select variables and estimate coefficients simultaneously in GLMM. Based on the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), and standard error criteria, it was found thatglmmLassohas a better performance than GLMM. For the factors affecting Indonesian’s student scores, whereglmmLassoproduces three significant covariates for the GLMM model while GLMM without penalizedLassohas five covariates, which means that the GLMM model is more complicated thanglmmLasso.Gender, school quality based on National Examination (UN) scores and the opportunity for students to investigate to test their ideas are essential covariates as factors that influence the rating of Indonesian students.
Selection of variables in generalized linear mixed model for smoker in Jambi Province
Authors: Warti R , Notodiputro K A , Sartono B
Published: April 2021

Smoking is one of the health problems in Indonesia. Many factors cause a person to smoke, both originating from oneself and the environment. The statistical question that arises is how to choose the factors that are most significant in influencing people to smoke. These factors are the variables that will sed in modeling. This study aims to select the variables in the compressed linear mixed model using the Lasso penalty and the Boosting function, using the EM and REML algorithms. Respondents in this study were 160 smokers in Jambi Province. Based on the AIC value, the best model obtained from the selection of variables with the Boosting function and REML algorithm. The analysis shows that work, welfare level, and family members who smoke are the factors that influence people smoking in Jambi Province.
Experimental review of a travelling-wave thermoacoustic system device
Authors: Kharismawati I , Achmadin W N , Trianggono M M
Published: April 2021

The thermoacoustic travelling wave device system has been designed and we have tested, this thermoacoustic device consists of loud-speakers as a sound wave source with a capacity of 120 W, branched-tubes resonator, and loop-tube resonator that have a regenerator with a length of 8 cm placed inside loop-tube. Regenerator is made of acrylic material which has a size of 1 mm and the distance between pores and other pores also has a distance of 1 mm. The performance of the thermoacoustic travelling wave device is observed from the temperature changes it has and is reflected in how much changes in cold reservoir temperature and hot reservoirs it can achieve. The results of the experiments obtained will be analyzed in the form of temperature charts showing temperatures in hot reservoir and cold reservoir as a function of time. The temperature difference between the two sides of the regenerator reaches 26,3°C with details of the temperature rise of the heat side of the regenerator (Th
) up to δTh
= 13,4°C and the temperature drop of the cold side of the regenerator (Tc
) down to δTc
= 12,9°C.
Identification students’ misconception using four-tier diagnostic test on Newton Law subject
Authors: Sundaygara C , Gusi L A R P , Pratiwi H Y , Ayu H D , Jufriadi A , Hudha M N
Published: April 2021

Misconception is something that causes students fail to understand physics concept intensively. The research aims to identify the students’ misconception on Newton Law concept using four-tier diagnostic test. Method used in the research was descriptive method. Data of students’ misconception was collected using test and interview. The subjects of the research were students of X MIPA 5 in State Senior High 10 Malang in 2019/2020 academic year and they were 32 students. The result of the research shows that the level of students’ misconception of X MIPA 5 in State Senior High 10 Malang is 54% which belongs to medium category. The research found that the misconception which happened to most students was on Newton II Law which is 63%. It also relevead that misconception in students occur because of experiences or events experiences by students in everuday life, students’ initial concepts and teachear teaching methods.
Passively Q-switched erbium-doped fiber laser with graphene oxide film as saturable absorber
Authors: Huda C , Yasin M , Zaidan A H , Harun S W , Jafry A A A , Rosol A H A
Published: April 2021

Passively Q-switched erbium-doped fiber laser (EDFL) have been demonstrated using graphene oxide (GO) film as saturable absorber (SA). The aim of this experiment is to generate and demonstrate passively Q-Switched Erbium-doped fiber laser (EDFL) using GO as a saturable absorber. Stable Q-switched operation can be achieved at 1558.8 nm. By increasing the pump power from 26.32mW to 71.65mW, the repetition rate also increased from 30.58 kHz to 51.81k Hz. The pulse width of the laser were 11.2 – 4.73 µs. The maximum output power and maximum peak power obtained are 128 µW and 521.98 µW respectively at a pump power of 71.65 mW. The pulse energy reaches 2.47nJ. These results show that GO is a new potential SA material for pulsed laser applications.
Physics undergraduate students’ perceptions of online learning during the transition period to the new normal era
Authors: Surahman E , Sujarwanto E
Published: April 2021

The Covid-19 pandemic forced the Indonesian government to release learning from home policy. This policy also applies to the Physics Education of Siliwangi University. This study aims to know undergraduate students’ perceptions of online learning during the transition period from face-to-face learning to online learning in Physics context. Undergraduate students’ perceptions of online learning are seen from aspects of access to technology, technology for learning, online learning readiness, and attitude towards digital technology literacy. The data is collected by an online survey method. This research shows that most undergraduate students have sufficient facilities for online learning and have a positive attitude towards digital technology literacy. Another finding from the study is that the majority of undergraduate students have difficulty accessing the fast internet (83.87%). Undergraduate students like a combination of online media learning and offline media learning (90.32%), but they do not like full online learning (98.06%). This research indicates that teachers should support students at online learning by providing proper Physics learning material and media. This research is expected to suggest better online learning and literacy technology in Physics context in the new normal era.
Physiological responses of the Holstein Friesian dairy cows raised under tropical conditions in Indonesia
Authors: Leondro H , Widyobroto B P , Agus A
Published: April 2021

This study aimed to evaluate the physiological responses of the Holstein Friesian (HF) dairy cows raised under tropical conditions in Indonesia. Twenty-one dry-pregnant cows, approximately 7–8 months of pregnancy, 1-3 of lactation, 500-600 kg of body weight and 3-5 of body condition score were used for that purpose. The cows were fed twice daily in the form of total mixed ration (TMR) and given add libitum amounts of drinking water. Ambient temperature, relative humidity and temperature humidity index (THI) were recorded. Physiological responses i.e. rectal temperature (RT), pulse rate (PR) and respiration rate (RR) and heat tolerance coefficient (HTC) were also recorded. Descriptive statistics such as mean and standard deviation were performed using SPSS software. The results showed that both ambient temperature and THI reached their maximum (26.5±1.520C and 77.1±2.21, respectively) at 01:00 PM and minimum (22.6±0.510C and 71.8±0.90, respectively) at 3:00 AM. Contrarily, the relative humidity was highest (88.9±1.56%) at 03:00 AM and lowest (78.8±2.49) at 01:00 AM. The physiological responses (RT, PR and RR) and HTC increased in line with the increasing ambient temperature and THI. In conclusion, all of the HF cows are exposed to mild stress due to increasing ambient temperature and relative humidity.
Low carbon learning: Logical framework in learning process at elementary schools
Authors: Hudha M N , Hamidah I , Permanasari A , Setiani P , Kustiawan I , Rachman I , Abdullah A G
Published: April 2021

This study aims to identify learning content of low carbon at elementary school level in Indonesia. The method employed in this study was a combination between systematic literature review and content analysis. The results showed that low carbon content at elementary schools was mapped and presented in a simple structure so that the substantial aspects of the learning was easier to understand by the elementary school students. It has also been proven that low carbon learning content was beneficial to develop in learning within elementary school context as it trained the students to get used to living in low carbon since early ages.
Utilization of producing biogas from food waste in anaerob biodegester at thermophilic temperature
Authors: Waris W , Kharismawati I , Aswan M S
Published: April 2021

The problem of food waste is increasing as food needs increase as a source of human protein. Therefore, biogas conversion can also answer the problem of household food waste treatment. The purpose of this study is to find out the producing of biogas from a mixture of food waste and liquid waste tofu in anaerobic biodegester at thermophylic temperature. The manufacture of biogas in this study using batch feeding, which is a type of digester that replenishes organic matter is done once full and then waited until biogas is produced. The manufacture of biogas is carried out for 5 weeks. The observed parameters are COD, BOD, TS, VS, and the resulting volume of biogas. From the observations obtained that, by varying substrate can decrease COD, BOD, TS, while substrate temperature can increase VS. The volume of biogas produced in the mixture of liquid waste tofu 60% and food waste 30% is 22.600 ml. The results showed that the percentage of substrate from the mixture of food waste with liquid waste tofu had an effect on increasing biogas production.
Analysis effect of winding on radiation-electromagnetic field on the tesla coil
Authors: Mulhayatiah D , Setiawan Y , Rizaldi M F , Siregar H S , Suherdiana D , Nurdini S D
Published: April 2021

Utilization of modern technology has been widely felt by the public as well as utilizing wireless charging technology on android phones. The charging, of course, uses the concept of Tesla coil, namely the transfer of electricity without wires. The Tesla coil can emit electromagnetic radiation which depends on its input. This study aims to design a miniature tesla coil as a magnetic inductor. In this design, measuring electromagnetic radiation with a coil diameter of 0.3 mm, 0.4 mm and 0.5 mm with the same number of turns is 500 turns. The method used is an experimental method using determinants such as the diameter of the coil, the height of the measurement of electromagnetic radiation, and the distance measurement of electromagnetic radiation. Experiments carried out varying independent variables including diameter of the coil, measurement distance, height and number of turns as a constant quantity. The measurement uses the electromagnetic radiation detector DT-1130 to measure the electromagnetic radiation at several heights of the Tesla coil. The results showed that electromagnetic radiation which has the highest value is at the top or at the end of the coil for the position near the primary coil obtained the lowest electromagnetic radiation results among the three measurements, whereas for distance researchers get the result that the further measurement between the electromagnetic sensor and the Tesla coil electromagnetic radiation is getting weaker. At a winding diameter of 0.3 mm which produces the smallest radiation but when brought closer to the Neon lamp the light intensity of the Neon lamp is brighter compared to the diameter of the winding 0.5 mm which has the most radiation.
The development of harmonic oscillation e-module based on problem based learning (pbl) for helping improvement of students’ higher order thinking skills (hots)
Authors: Rustana C E , Aminah S , Budi A S
Published: April 2021

This study aims to develop a harmonic oscillation e-module based on pbl for helping hots improvement of senior high school students at SMA N 23 Jakarta. The ADDIE Model of research and development was applied in developing such e-module prior to measure improvement of students’ hots. The validation results of experts indicated the values of 78.1%, 77.7% and 93.8% for media, learning model and content, respectively. The trial result of teachers and a small and big groups of students respectively indicated an average score of 93.95% and 95.1% and 86.5% for all aspects of content eligibility, presentation, language and graphical eligibilities. Furthermore, The tgain test calculation shown that the tgain count (2.58) was bigger than tgain table (1.67) with 5% significance level. The analyzed result indicated that the improvement of hots of students which was taught with the pbl based e-module was better than those who utilized the non pbl based e-module of the harmonic oscillation. Whiles, the result of d’Cohen test indicated that the developed e-module was very decent to be utilized as learning media with contribution category of medium (based on d’Cohen test result of 0.64) for improving hots of senior high school students.
Energy efficency analysis for various type of electric cooker
Authors: Aisyah S , Triani M , Rasgianti R
Published: April 2021

Efficiency is one of the important things to consider when choosing household appliances, especially cooking equipment. Currently the community is starting to switch from from liquefied petroleum gas-based cookers to electric cookers. Therefore analysis is needed to determine the selection of electric cookers that are efficient in accordance with consumer needs. To accomplish this study, testing with boiling water was carried out on three types of electric cookers namely induction cooker, halogen and electric coil. This test is carried out to obtain input and output energy from each stove so that efficiency can be obtained. From the test results, it has been found that the induction cooker has the highest efficiency among the electric cooker.
Enhancing science literacy capabilities of prospective primary school teachers through the STEM Project Learning Model
Authors: B Amiruddin , Budi A S , Sumantri M S
Published: April 2021

The STEM Project is a learning model that can be used by lecturers in the learning process so that students can get used to analyzing and synthesizing, to come up with an idea that can develop the competence and science literacy abilities of elementary school teacher candidates in the framework of learning in the 21st century. The study aims to improve the ability of the science literacy of Pre-service elementary school teachers by using the STEM Project Learning Model. This study was conducted on Pre-service elementary school teachers as elementary school teacher education students at the University of Halu Oleo Kendari. The results obtained indicate that the science literacy ability of Pre-service elementary school teachers has increased significantly. The increase is based on the results of statistical analysis which shows a significant increase in the ability of the science literacy of Pre-service elementary school teachers, after participating in learning using the STEM Project model. For this reason, the use of the STEM Project model in learning science enables prospective teachers to become accustomed to conducting comprehensive analyzes of problems and their solutions.
Diagnostic analysis of student concept in environmental physics
Authors: Ayu H D , Saputra S , Sarwanto S , Mulyani S
Published: April 2021

The purpose of this study is to diagnose student concepts in environmental physics courses. This study has used a mixed method. Data has been obtained from interviews, observations, questionnaires, and tests. Study subjects were 78 physics education students who had passed environmental physics courses and 4 lecturers. The results of the study have shown that the chapter in the bad category is the chapter “External factors that influence life on earth”. This answered with the percentage of students who answered correctly there were 44.8. And the chapter “Association of physical principles with soil characteristics” is also in the bad category with a percentage of 46.2. This study has been able to provide a description of the material content that is not understood by students in experimental physics subjects, especially related to the concept of physics.
Development of web-based learning media for physics materials using Moodle in high school
Authors: Afrilia A , Rusli F , Tanti T , Mutamasikin M , Yusuf M
Published: April 2021

Education systems in various countries have experienced massive transformation since the development of information technology. The learning environment has shifted from face to face learning to web-based education or e-learning. There are multiple free online learning platforms available on the internet, one of which is Moodle. The main aim of this study is to develop physics learning media with Moodle to improve student’s motivation in learning physics. The ADDIE model framework is used to create web-based physics learning media, which consists of four stages, namely analysis, design, develop, implement, and evaluation. The product was validated by material and media experts, as well as two physics teachers as practitioners. The validation and practicality test results show that the web-based learning media is valid and practical as teaching media to improve student’s motivation in learning physics. The results of the effectiveness test using the design of one class pre-test and post-test showed an increase in students’ motivation with an N-gain value of 0.80 with categories high. The results of this study give insight for physics teachers on how to design technology-based learning to increase student motivation in learning physics.
Development of animation-based learning media to increase student’s motivation in learning physics
Authors: Sastradika D , Iskandar I , Syefrinando B , Shulman F
Published: April 2021

The difficulty of students in understanding concepts in physics has a significant effect on students’ motivation. The purpose of this study is to develop animation media that make students easier to understand the abstract concept of Newton’s law and find out students’ responses to the use of instructional media. The 4D framework is used to develop animation-based learning media, which consists of four-phase, namely: define, design, develop, and disseminate. The instruments used are a questionnaire and interviews. The results showed that (1) Based on expert judgment Animation-based learning media was appropriate and feasible to be implemented in the physics class; (2) used of media animation in learning physics could facilitate students in understanding the abstract concept of Newton’s Law, especially in describing the direction of the force and gave opportunity to the student’s to increase their motivation to learning physics where average score of the motivation was 70% in the “High” category.
Structural, magnetic and microwave absorption properties of natural iron sand
Authors: Handoko E , Sugihartono I , Marpaung M A , Budi S , Fahdiran R , Jalil Z , Alaydrus M
Published: April 2021

This paper presents the development and characterization of the natural iron sand as a microwave absorber. To develop a new microwave absorbing paints in the 7–13 GHz range, the iron sand sample was prepared through the mechanical milling process and characterized with X-ray diffraction (XRD), scanning electron microscopy (SEM), Permagraph and vector network analyzer (VNA). The reflection loss (RL) was calculated and simulated for different thicknesses of the material using the complex permittivity and permeability and found the broadband characteristics with minimum absorption. The results indicated that the natural iron sand is beneficial as potential candidates for military applications.
The simulation of granular attachment on the porous vertical surfaces
Authors: Muliyati D , Sumardani D , Siswoyo S , Viridi S , Bakri F , Handoko E , Permana H
Published: April 2021

Granular simulations have been carried out to visualize attached to porous vertical surfaces. We simulate the optimal ratio of dry surfaces. This simulation uses the uFlex particle with three pore sizes. The movement particle using parabolic motion with the initial horizontal speed only. The simulation results show that for uniform particle velocities, the number of particles that are attached depends on the size of the particle sphere itself. These results can combine with the previous study to use in future research.
Application of relativistic quantum mechanics in radial problems and E/M equations
Authors: Arygunartha G Y , Janurianti N M D , Situmeang Y P
Published: April 2021

This research is pure research in the field of pure physics. The background of the research that I did there was doing pure research in the field of physics. The subject of this research is to use the e/m measurement tool. This study aims to (1) study the influence of the magnitude of the electron velocity and the magnitude of the magnetic field on the electron path, (2) determine the e/m ratio in calculations. The results showed that the magnitude of the electron path radius is directly proportional to the magnitude of the electron velocity and inversely proportional to the magnitude of the magnetic field acting on it. Meanwhile, the calculation result for fixed current is 16.84% and the fixed voltage is 14.15%, in this case the size of the electron path is directly proportional to the magnitude of the speed of the electron path, and inversely proportional to the magnitude of the magnetic field acting on the electron.
Dynamical system of relativistic particle under one dimensional harmonic oscillator potential
Authors: Sanjaya L A , Prayitno T B , Widyanirmala W , Astra I M
Published: April 2021

Dynamical system of a relativistic particle under harmonic oscillator potential was considered through its stability. We first construct the Hamiltonian of the system, which represents the dynamic motion of the relativistic particle. The stability of the system was then determined by the singular point. We found that the relativistic motion under the harmonic oscillator is a stable system where the phase curve forms an ellipse.
Energy momentum tensor of scalar field with higher order derivatives
Authors: Prayitno T B , Budi E , Fahdiran R
Published: April 2021

We considered a formulation of the energy momentum tensor of scalar field containing higher-order derivatives. Starting from the Lagrangian density, we can formulate the Hamiltonian density as well as the three-component momentum density by applying the total variation on the field. We claimed that this formulation can be used to derive some nonlinear wave equation, such as the KdV equation and the Burgers equation.
Radioactive decay model based on augmented reality
Authors: Bakri F , Sumardani D , Muliyati D
Published: April 2021

This article presents a simulation model of radioactive chain decay with augmented reality technology. Radioactive decay is classified as abstract material that is difficult to understand. This simulation will make abstract radioactive decay materials easily understood. In this article will explain the simulation changes to the 4n + 2 radioactive model by utilizing augmented reality technology. This media development uses the black-box testing method to test the accuracy and validity of the software program. Interactive media using augmented reality on radioactive decay have been able to display the U-238 chain decay model (series 4n + 2) by simulating the process of alpha and beta release in each series. This simulation successfully displayed a striking difference between alpha and beta release in the U-238 chain reaction cycle.
A sensitive thick film as a candidate for ethanol gas sensor from Jarosite-based minerals
Authors: Aliah H , Syarif D G , Iman R N , Sawitri A , Setiawan A
Published: April 2021

We report this study that aims to know thick film sensitivity to ethanol gas. The thick film was fabricated from local mineral, is Jarosite as a source of iron oxide, and mixed with zinc oxide and Mangan oxide. The semiconductor mixture powder was synthesized by the sol-gel method, whereas the film was fabricated by a screen printing method. The film sensitivity was known with a gas sensing performance analyzer. An ethanol gas was adsorbed well by a thick film with different electrical resistance values. Due to the difference in the electrical resistance value, the thick film exhibited good sensitivity performance. The highest sensitivity was achieved approximately 91.7% of 4 gas concentration level of ethanol. Besides, the morphology of the thick film was examined by SEM that showed a pyramid-like form with a little impurity around them. The pyramid-like form looks like a spinel structure with a complex spinel-type where this structure is very well utilized for gas sensor device applications. Furthermore, these characteristics of the thick film indicated an opportunity that it can be a candidate for an ethanol gas sensor device.
Crystal structure analysis of Lanthanum Orthoferrite doped Zirconium with sol-gel method for solar cell candidate
Authors: Purnamasari I , Farida I , Nanang N , Zhafirah A
Published: April 2021

Lanthanum Orthoferrite (LaFeO3) is one of the perovskite material which has been studied as a candidate for solar cells. Perovskite doped at site-A and site B was expected to increase efficiency in its application as a solar cell. Zirconium as doping at site-B on LaFeO3 used to reduce the size of crystals with nano size. Therefore, this research has synthesized perovskite lanthanum orthoferrite doped zirconium at site-B (LaFe1-xZrxO3 with x=0.075, 0.1 and 0.15) by the sol-gel method and it has not been studied before. The precursors for these materials are lanthanum Oxide (La2O3), Zirconium (IV) chloride octahydrate (Cl2H12O9Zr), iron nitrate nonahydrate (Fe (NO3)3.9H2O). LaFeZrO3 powder was characterized using X-ray diffraction (XRD) to test the crystal structure properties. The results say that the sample has an orthorhombic structure with Pnma space group. The XRD data has been refined and shows that the lattice parameters for 0.075, 0.1 and 0.15 increase with increasing zirconium concentration and crystal size of LaFeZrO3 decreasing and showing nanosize. Nanosize crystals can maximize the absorption of dyes and it can increase the efficiency of solar cells.
Residual Deep Monocular 3D Human Pose Estimation using CVAE synthetic data
Authors: Jiang Yutong , Liu Xiaofei , Wu Dongyuan , Zhao Pengbiao
Published: April 2021

Estimating 3D human pose from a monocular RGB image is a challenging task in computer vision because annotating a large number of 3D pose ground-truth data is costly. To address the problem of lack of 3D data, many methods have been proposed. In this paper, we propose to address this issue by synthesizing data. Firstly we exploit Conditional Variational Autodecoder to generate 3D human skeletons data. In CVAE network, we acquire generous 3D pose samples through the predicted 2D pose and the existing 3D ground truth. Secondly, base the generated 3D samples, we obtain the corresponding 2D pose by projection, thus augmenting the data of 2D-3D network. Finally, we train these synthetic data on 3D pose residual estimation network. Extensive experiments show that our approach achieves state-of-the-art accuracy on standard benchmark datasets.
A new deep distortion convolutional neural network for semantic segmentation of panoramic images
Authors: Hu Xing , An Yi , Shao Cheng , Qin Pan
Published: April 2021

Semantic segmentation of panoramic images plays a crucial role in many applications, such as scene understanding, autonomous navigation, and community security. However, the traditional deep learning algorithms achieve lower accuracy for panoramic images due to the serious image distortion. This paper proposes a new deep convolutional neural network to segment panoramic images of outdoor scenes semantically. The proposed network includes two branches: the semantic segmentation sub-branch (SS-branch) and the feature enhancement sub-branch (FE-branch). The SS-branch contains two parts: Encoder and decoder. In the encoder, a new distortion convolution layer (DCL) is defined to reduce the distortion of panoramic images. In the FE-branch, a canny is used to detect the edge and a lightweight network is designed to enhance the features of image boundaries. Finally, a weighted loss function is used. The experimental results show that the proposed semantic segmentation method has better performance for different outdoor scenes.
A multi-point crosstalk attack detection and location Scheme based on distributed PCE in multi-domain optical networks
Authors: Wu Qiwu , Liu Xueyue , Jiang Lingzhi , Gan Bo
Published: April 2021

In order to solve the problem that crosstalk attack propagation leads to a large number of interference alarms in multi domain optical network and difficult positioning, the detection and screening mechanism based on attack optical path state discrimination and the improved MD-PLVM (multi domain parallel and limited vector Matching) algorithm for multi domain optical network are used in this paper, a new crosstalk attack detection and location scheme based on distributed PCE called DP-CADL (distributed PCE crosstalk attack detection and location) is proposed. The experimental results show that this scheme can not only eliminate the interference alarm and screen the original attack optical path accurately, but also realize the fast location of multiple crosstalk attack sources between domains and cross domain optical path, and has high location accuracy.
Research on The Current Situation and Development Trend of Optical Fiber Communication technology
Authors: Yuan Bingjie , Cai Han
Published: April 2021

The technology uses light wave as carrier and optical fiber as transmission medium to realize the function of transmitting information from one end to the other. Optical fiber communication technology has become one of the important means of information transmission in today’s era. It can be imagined that in the near future, optical fiber technology will have more rapid development and application. This paper briefly introduces the principle and characteristics of optical fiber communication technology, analyzes its current application fields, and discusses the future development trend of this technology, so as to let more people understand this technology.
Design of Monitoring System for Electric Vehicle Charging Facilities Based on Cloud Platform
Authors: Jian lv , Li Bo , Chen Jingyun , Han Luyu
Published: April 2021

Faced with the increasingly severe pressure of traditional energy consumption and environmental problems, electric vehicles have become the hotspot and trend of the development of the world automobile industry due to their energy-saving and environmental protection characteristics. The cloud platform in the paper was introduced into the monitoring system of electric vehicle charging facilities, and a model of electric vehicle charging facility monitoring system based on cloud platform was proposed. Aiming at the difficulty of charging facility monitoring system in large concurrent data processing, a M/M/C queuing theory model was presented. Data concurrency control algorithm. The transmission process of the data frame in the monitoring system was analyzed, and the concurrent processing algorithm was applied to the large charging station for analysis experiments. The experimental results showed that the proposed algorithm not only satisfied the real-time and concurrency requirements of data frame transmission, but also proved that the gateway optimization method could accurately derive the optimal number of gateways.
Compression of Person Re-identification Model Based on Depthwise Separable Convolutional Network
Authors: Zhu Liming , Xiao Junsheng
Published: April 2021

In practical application, the network depth and the number of parameters of person re-identification(re-ID) model bring great challenges to its deployment on devices with weak computing capabilities such as cloud desktop, mobile terminal and embedded terminal. To solve the above problem, this paper proposed a model compression method based on a depthwise separable convolutional network. Knowledge distillation is used to the core idea of model compression. Knowledge distillation is to transfer knowledge from a complex model to a simple model. The complex model is called the teacher model. The simple model is called the student model. This paper proposed ResNet18 based on depthwise separable convolution (ResNet18-DSC). ResNet50 is used as a teacher network and ResNet18-DSC is used as a student network. To narrow the performance gap between student and teacher networks. KL divergence loss function is used to approximate the soft label distribution of student network to that of teacher network. With a slight decrease in recognition rate, this method reduces the number of parameters by about 20 times and improves the calculation speed by about 20 times.
Remote sensing image registration based on full convolution neural network and k-nearest neighbor ratio algorithm
Authors: Wang Dongzhen , Chen Ying , Li Jipeng
Published: April 2021

Aiming at the problem of low accuracy of remote sensing image registration caused by the negative effects of noise and imaging in some traditional algorithms, an effective remote sensing image registration method based on depth feature from coarse to fine is proposed. In the coarse registration stage, the full convolution neural network is used to extract the features of the input image, then the nearest neighbor distance ratio algorithm is used to coarse match the features and finally an approximate transformation matrix is obtained. In the stage of fine registration, firstly, the image features are extracted by the improved convolutional neural network based on shortcut connection, then the affine transform coefficients are obtained by the combination of approximate transform matrix and k-nearest neighbor ratio algorithm. Finally, the image to be registered can be transformed according to the coefficients to achieve the purpose of registration. Experimental results show that, compared with the comparison method, the proposed method can increase the correct matching correspondence, so as to improve the accuracy of registration.
Analysis Of Protocol Convergence For Satellite And 5G Communication
Authors: Xiong Yue , Wang Quan , Chen Xuqiong , Li Yuanjie , Li Wenting
Published: April 2021

In recent years, with the commercial application of fifth-generation mobile communication (5G), the integration of satellite communication and 5G system has become a hot topic in the industry. The first thing to be considered in the integration of two communication systems is the integration and conversion of communication protocols between different systems. However, there is no final conclusion on how to integrate satellite and 5G communication protocol. By analyzing the differences and characteristics of satellite and 5G communication protocol, this paper creates a new protocol stack model from the direction of protocol system integration, and realizes the integration from the protocol level. According to the characteristics of different network applications, three network deployment modes are proposed. Finally, the application scenarios of satellite communication and 5G integration are given.
Real-time Object Tracking Method based on Multi-Core DSP
Authors: Li Lidan , Zhang Yi , Guo Qianya , Lin Qing , Zhou Jing , Wang Yanyong , Zhao Bo
Published: April 2021

In this paper, we propose a fast object tracking method used in real-time application. The tracking method is based on compact kernelized correlation filters. Traditional, gray values are used to describe target feature. In order to achieve relatively fast performance, we adopt Principal Component Analysis (PCA) to simplify Histogram of Gradient (HOG) as feature descriptor, which can significantly reduce computation resources. Our method is implemented on Texas Instruments (TI) multi-core digital signal processor (DSP) TMS320 C6657, which can achieve 60 frame per-second (fps). Finally, we conduct both quantitative and qualitative experiment to show the robustness and real-time performance of our method.
Unsupervised registration of intravascular ultrasound images combined with attention mechanism
Authors: Liu JiRong , Wang YouSheng , Man KaiLiang , Gao Xue
Published: April 2021

For intravascular ultrasound (IVUS) images, the registration technology is used to calculate coronary arteries displacement to analyze vascular elasticity. It not only provides evidence for the prevention and treatment of cardiovascular diseases, but also has important significance for guiding interventional surgery and monitoring the placement of surgical stents. Aiming at the high computational cost of current traditional registration methods and the insufficient accuracy of common deep learning registration methods for IVUS images, this paper proposes a fast unsupervised registration of IVUS images combined with an attention mechanism. The proposed method directly learns to estimate a displacement vector field (DVF) from a pair of input images of the training set. The spatial transform network (STN) uses the DVF to transform the moving image into the fixed image. Finally, the model is trained by minimizing a similarity metric loss function between the deformed moving image and the fixed image. Compared with the previous deep learning method, the registration performance improved after implementing the proposed method. The proposed method can accurately register the inner and outer membranes of IVU S images and provide a reliable basis for vascular elasticity analysis.
Realization of amplitude-type hologram based on nanostructured metasurfaces
Authors: Qu Kening
Published: April 2021

Conventional Amplitude-type holograms are generated by recording the interference fringes on a photosensitive material. In this paper, taking advantage of the characteristics of metasurfaces that can continuously control the amplitude of electromagnetic waves, a silver-nanopolarizer-based metasurface is proposed to realize amplitude-type holograph. An off-axis meta-hologram is designed and fabricated with e-beam lithography. And experimental results show that it can project a holographic image in the far field with high-fidelity, indicating that this amplitude hologram has the ability of continuous amplitude modulation and is safe and stable, so it has application spaces in holography, optical holography, holographic encryption, anti-counterfeiting, etc.
Transfer Learning Technique with VGG-16 for Near-Infrared Facial Expression Recognition
Authors: Atabansi Chukwuemeka C , Chen Tong , Cao Ranlei , Xu Xueming
Published: April 2021

In this paper, we investigate a deep learning vgg-16 network architecture for facial expression recognition under active near-infrared illumination condition and background. In particular, we consider the concept of transfer learning whereby features learned from high resolution images of huge datasets can be used to train a model of relatively small dataset without loosing the generalization ability. The pre-trained vgg-16 network architecture with transfer learning technique has been trained and validated on the Oulu-CASIA NIR dataset comprising of six (6) distinct facial expressions, and average test accuracy of 98.11% was achieved. The validation on our test data using the confusion, the precision, and the recall matrix reveals that our method achieves better results in comparison with the other methods in the literature.
Low power design method of medical image display system based on FPGA
Authors: Yang Qiankun , Yang Yong , Li Guohui , Fan Jiebiao
Published: April 2021

A novel low power design scheme of medical image display system is proposed, based on the research of FPGA(Field Programmable Gate Array) low power design technology and medical image display system. Firstly, the power consumption of video and image processing system based on FPGA is analyzed. Then a method to reduce the dynamic power consumption of FPGA is proposed based on the tonal and spatial characteristics of medical images. Finally, taking radiographic medical images as an example, the signal flip ratio is reduced from 37.95% to 9.68% by using software statistics, which proves that the proposed scheme can effectively reduce the dynamic power consumption of FPGA.
Study On Book Quality Evaluation Based On Neural Network And Data Visualization
Authors: Xiaobin Bi
Published: April 2021

In order to improve the quality of library books evaluation, neural network visualization and feature model technology were used to establish a feature model for the quality evaluation system. Model processing of neural network in the paper was applied to the book information of library, and various information indicators related to the quality of book evaluation were used as neurons. The convergence speed was improved by optimizing global optimization of neural network weights, and the relationship between the meta-nodes nerves were more accurately displayed, and the data analysis function with visual effects was provided, thus, an objective and vivid display of the book quality of library was shown. Finally, the neural network structure algorithm designed in this paper directly represented the mapping relationship between various indicators and evaluation scores, which was a reasonable and feasible method for library book quality evaluation.
UAV ranging method based on monocular vision
Authors: Rong Yicheng , Zhang Zhiyong , Qiu Changzhen , Ye Zezheng
Published: April 2021

Aiming at the problem that the unmanned aerial vehicle (UAV) cannot complete the positioning and ranging in the complex background and the signal is interfered, we proposed a monocular measurement scheme of assigning 4 LED fiducials (also called landmarks) with 3 colors in total on the target UAV. Firstly, feature areas are screened out by using high saturation, high brightness and specific hue range of LED in HSV (Hue, Saturation, Value) color space. After morphological processing, the background that does not meet the features is removed. Then, the mapping relationship between target LED fiducials and image fiducials is established by using the average hue of connected domain and special geometric layout. The improved Lambda-Twist is used to find the distance from the target UAV to the center of the camera, and the performance of the UAV recognition and ranging from 90m to 245m is tested. The experimental results show that the method can quickly and accurately measure the distance to the target, and can be used for UAV auxiliary measurement.
Mutual Attention Learning Network for Domain Adaptive Person Re-identification
Authors: Zhu Liming , Xiao Junsheng
Published: April 2021

Owing to its important role in video surveillance, person re-identification(re-ID) has become a hot research field of computer vision. The purpose of person re-ID is to identify the same person under different cameras. Domain adaptive person re-ID is to transfer the training model from labeled dataset to unlabeled dataset. Due to the neglect of key channels and key regions, the performance of most existing domain adaptive person re-ID methods is limited. To solve the above problem, this paper proposed a mutual attention learning network model (MALNet). It is based on channel attention and spatial attention mechanism. It consists of two channel-spatial attention convolutional neural networks (channel-spatial attention CNNs). Two networks are pre-trained in a source domain. They adapt to the target domain by the mutual attention learning strategy afterward. They distill and supervise each other to enhance the complementarity of MAL-Net. Moreover, a channel-spatial attention loss (CSAL) function is proposed to constrain and approximate the classification prediction distributions and feature triplet distributions. Extensive comparative experiments are carried out on two large-scale re-ID datasets (Market-1501 and DukeMTMC-reID). The performance of MAL-Net is better than other state-of-the-art methods, which proves the superiority and effectiveness of our method.
Historical Corpora Correlation based on RNN and DCNN
Authors: Lin Wei , Lin Zhaoquan
Published: April 2021

Correcting historical corpora in digital version is a crucial task for the historical research, however, scan quality, book layout, visual character similarity can affect the quality of the recognizing. OCR is at the forefront of digitization projects for cultural heritage preservation. The main task is to identify characters from their visual form into their textual representation. In this paper, we propose a model combining recurrent neutral network(RNN) and deep convolutional network(DCNN) to correct OCR transcription errors. The experiment on a historical book corpus in German language shows that the model is very robust in capturing diverse OCR transcription errors greatly.