bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mobile Augmented Reality Application for Component Identification
Authors: Hatmojo Y. I. , Maryadi T. H.T. , Badarudin R. , Indrawati B. 
Published: December 2021

Abstract
This article discusses the development of augmented reality (AR) based object identification applications. The purpose of this study is to improve the distribution station component identification workbook. Through the implementation of the developed application, it is assumed that it will be easier to understand the functionality of the components of the distributing station. The augmented reality application was developed for the android platform. The result showed the application of Distributing Station-AR has been developed by applying a marker-based tracking method. The application test has successfully displayed the three-dimension components of distributing station using a marker on the component identification workbook of distributing station. Product performance is known to be very good and product validation is also very good, including material validation, media validation, and first user responses. For further development, this application is expected to add animation of the working principle of AR-based components.
Development of Electrical Circuit Learning Media Using Virtual Simulation
Authors: Damarwan E S , Hakim M L , Wardhana A S J , Kholis N 
Published: December 2021

Abstract
The Covid-19 pandemic has had a major impact on the world of education. One of the impacts is related to the learning process of electrical circuits. Online lectures make students have difficulty in studying electrical circuit courses. An appropriate learning media is needed as a solution to overcome these problems. This study aims to develop electrical circuit learning media using virtual simulations and determine the feasibility of applying the media. This type of research is research and development with the ADDIE model. The stages of development carried out are Analyze, Design, Development, Implementation, and Evaluation. The research was conducted at the Electrical Engineering Education Study Program, Faculty of Engineering, UNY. The virtual simulation used is a Falstad circuit simulation. This simulation can be accessed online or offline. In this research, the focus is on developing learning media using online Falstad simulation. The results showed that 1) the electric circuit learning media using virtual simulations can run well, 2) based on user trials, the electrical circuit learning media using virtual simulation is classified as very feasible.
The Design of Sensor and Transducer Learning Media based on Augmented Reality
Authors: Hariyanto D , Zamtinah  , Triasih T , Wati M S , Kassymova G K 
Published: December 2021

Abstract
This study aimed at determining the design stage of the augmented reality-based learning media for sensors and transducers course. This study employed the Research and Development method with the ADDIE model with the stages of analysis, design, development, implementation, and evaluation. This article focuses on the design stage during the process of media development. The developed learning media can be used among vocational students by visualizing the sensor and transducer components like in the real laboratory setting. The design of the developed learning media contained application storyboards and animation storyboards for practicing the six sensors. This augmented reality learning media is designed to support online learning and students’ autonomous learning in the practical course of sensors and transducers.
Design of Robust Heart Abnormality Detection System based on Wavelet Denoising Algorithm
Authors: Winursito A , Arifin F , Nasuha A , Priambodo A S , Muslikhin  
Published: December 2021

Abstract
The technology that continues to be developed by many researchers today is an automatic heart attack detection system based on an Electrocardiogram (ECG) signal. Several other studies have been carried out to build an Internet of Things (IoT) based heart abnormality detection system. Based on the analysis of related studies that have been carried out previously, several researchers have developed an ECG signal-based heart abnormality detection system using clean ECG signal data. While the reality of the concept of an IoT-based detection system, the process of recording ECG signal data on the sensor, the process of sending data to the server, and the process of retrieving data from the server are vulnerable to noise exposure. ECG signal containing noise will greatly affect the accuracy of system detection. This paper proposes the development of a noise-resistant heart condition detection system using a wavelet denoising algorithm. The process of denoising ECG signals using the Wavelet algorithm is generally able to improve the accuracy of detecting noisy ECG signals. The most significant increase in accuracy is seen in the low SNR value. The Daubechies 4 (db4) denoising algorithm is the best-performing algorithm. The ECG signal classification method uses the Artificial Neural Network (ANN) algorithm. Detection system hardware is also designed in this research using the concept based on the Internet of Things.
Development of Unmanned Aerial Vehicle (UAV) Fixed-Wing for Monitoring, Mapping and Dropping applications on agricultural land
Authors: Hakim ML , Pratiwi H , Nugraha AC , Yatmono S , Wardhana ASJ , Damarwan ES , Agustianto T , Noperi S 
Published: December 2021

Abstract
UAV technology is used in various fields, namely the military, to strengthen defence, surveillance, dropping logistics. In addition, UAV applications are also used in agriculture. In this study, a fixed-wing UAV will be developed as a monitoring, mapping and dropping process. Several things were carried out in the development process, namely design, manufacturing, installing electronic components, and test flights. The results showed that the vehicle could carry out the mission well. The monitoring process is carried out to review land security. Besides that, it can monitor if there is a fire in agricultural land. In the mapping process, photo data processing taken in the context of the mapping is carried out into an orthophoto map. Meanwhile, in the dropping stage, the aircraft managed to drop a payload weighing 0.5 kg with a distance of 20m from a predetermined centre point. The dropped payload is also equipped with a parachute for increased safety and reduced speed when the payload is dropped.
Analysis of Energy Consumption and Energy Efficiency in Government Office Buildings of Bengkulu, Indonesia
Authors: Rahardjo I A , Djaohar M , Subekti M , Parjiman  , Zakir I , Mahir I , Sakirah  , Lubis A 
Published: December 2021

Abstract
This article aimed to analyze the energy consumption and energy efficiency in government office buildings of Bengkulu, Indonesia. This research was conducted using a quantitative descriptive method. The research step begins by observing the initial conditions of Energy Consumption Intensity (ECI) to determine the category of buildings that are efficient or not in terms of energy use, then collecting data on the profile of the use of the building and its rooms, recapitulation of the use of energy sources (both electrical energy and other chemical energy), a list of equipment that consumes electrical energy (lighting, air conditioning, and others). Furthermore, measuring the performance of systems and equipment that consumes energy and conducting efficiency analysis to then make recommendations with operating settings, to replace inefficient equipment with more efficient equipment. The final step is to draw conclusions about the final Energy Consumption Intensity (ECI) obtained based on the results of the analysis and recommendations obtained on the previous Energy Consumption Intensity (ECI) value. It can be concluded that the final Energy Consumption Intensity (ECI) of government office buildings of Bengkulu based on the results of the analysis and recommendations such as performing preventive maintenance on air conditioners, the temperature of the air conditioner is set to always be at 24°C, replacing the type of lamp in the artificial lighting system that still uses TLD lamps with LED lamps, and efforts in organizing energy management systems will decrease around 13 percent from the previous Energy Consumption Intensity (ECI) or down from 40.9 kWh/m2/year to be 35.6 kWh/m2/year.
Development of Ball Detection System with YOLOv3 in a Humanoid Soccer Robot
Authors: Nugraha A C , Hakim M L , Yatmono S , Khairudin M 
Published: December 2021

Abstract
One of the practical researches of humanoid robots is research on the use of humanoid robots to play soccer. Research in this field is also encouraged by the existence of various humanoid robot soccer competitions. In humanoid robots for soccer, one of the important aspects is the robot’s ability to detect the ball, goal, field boundaries and other players, both friend players and opposing players. This study focuses on the ball detection system which is a basic ability that humanoid robots need to have. The ball detection system developed in this study uses the YOLOv3 method. The test results show that the system built and trained with 3000 image samples can detect balls at a distance of 50 to 900 cm. The time it takes to detect the ball is about 0.033 seconds.
Reliability Design and Simulation of High Density Packaging T/R Module
Authors: Zhao Hailong , Zhang Yu , Ran Honglei , Peng Hao , Zhang Kui , Yin Lijing 
Published: December 2021

Abstract
The requirements, development, packaging characteristics and existing reliability problems of high density packaging T/R modules are introduced, and the importance of reliability design is recognized. Aiming at the reliability problems of Electro Magnetic Compatibility (EMC), heat dissipation and electrostatic discharge, the reliability design and simulation scheme are given, and some cases are provided. Through design analysis and improvement, the reliability of 3D high density packaging T/R modules can be effectively improved.
Research on tomography algorithm of furnace flame temperature field based on acoustic method in thermal power station
Authors: Kan Zhe , Ding Shuqiang , Wang Xiaolei 
Published: December 2021

Abstract
An improved Tikhonov regularization algorithm MCTR based on Markov radial basis function is proposed to obtain the feedback of closed-loop control for pulverized coal injection process in thermal power plant, so as to solve the ill posed problem in temperature field reconstruction in furnace. The algorithm constructs a new regularization matrix to replace the standard Tikhonov regularization element matrix, so as to achieve the correction effect of the new algorithm. MCTR algorithm determines the boundary singular value of small singular value defined in this paper by determining the proportion between the standard deviation component corresponding to small singular value and the sum of standard deviation components corresponding to all singular values after singular value decomposition of coefficient matrix. After determining the boundary, a new regularization matrix is constructed according to the eigenvector corresponding to small singular value. Compared with the MTR algorithm using the identity matrix as the regularization matrix, MCTR algorithm only selectively modifies the parameters corresponding to small singular values after determining the regularization parameters, which improves the stability of the parameter solution and the reconstruction accuracy of the temperature field, and is helpful to the automatic control of thermal power plants and the efficiency of coal combustion.
Power system transient stability assessment based on rough set and deep residual neural network
Authors: Chai Jian , Wang Xihuai , Xiao Jianmei 
Published: December 2021

Abstract
Machine learning algorithms have been widely used in power system transient stability evaluation. The combined application of data analysis and evaluation and neural network provides a new direction for power system transient stability analysis. After the actual power grid is running, there is obviously an imbalance between stable samples and unstable samples. The current deep learning network realizes the power system transient stability assessment method with too many redundant attributes, and the characteristics will inevitably be lost during the data transmission process. This leads to serious problems with the tendency of the training of the data-driven transient stability assessment model. The rough set theory algorithm is introduced to reduce the redundant attributes of power system transient data sets, which simplifies the difficulty of data training. At the same time, as the neural network deepens, the deep residual neural network model has a higher accuracy rate and effectively avoids the “gradient explosion” and “gradient dispersion” problems. Compared with the traditional neural network, it has better Evaluate performance.
Optimization of integrated energy system for combined cooling, heating and power supply of new energy based on energy storage
Authors: Zhang Tieyan , Yang Junbao , Wang Yaru , Li Min , Zhang Dawei , Wang Yuri 
Published: December 2021

Abstract
With the development of science and technology, people also pay more and more attention to the development of new energy. Although there are also many studies on integrated energy systems now, integrated energy systems containing energy storage should also be further studied. This paper proposes an optimization of integrated energy system for combined cooling, heating and power supply of new energy based on energy storage, which analyzes the gas turbine, absorption refrigerating machine, electric refrigerator, photovoltaic power generation units, wind turbine and the work characteristics of the energy storage device. In this paper, an integrated energy system optimization model of new energy cogeneration with energy storage equipment is established. An example shows that the integrated energy system with energy storage can effectively solve the independent decoupling operation relationship among cool, heat and electricity. At the same time, the proposed model can also solve the energy interaction among cool, heat and electricity. In this way, the optimal operation of the integrated energy system can be realized.
Design of meteorological intelligent sensor based on POE Technology
Authors: Liu Qiangjun , Liang Yun , Zhang Junlin , Qi Liangbo 
Published: December 2021

Abstract
An application scheme of Poe based Ethernet technology in meteorological intelligent sensor system is designed. The working principle and implementation method of Ethernet power supply system (POE) based on IEEE802.3af Ethernet power supply industry standard are experimentally analyzed. The power supply part of the meteorological intelligent sensor makes full use of Poe technology to provide current on the network cable transmitting data, which greatly reduces the complexity of the power supply system and improves the reliability of the system power supply design. Through the test of the actual system, the function and performance of the meteorological intelligent transmission system have achieved the expected results.
Sorting path optimization of parallel robot based on improved Genetic Algorithm
Authors: Xia Feize , Sun Yuan , Wang Meng 
Published: December 2021

Abstract
In industrial production, parallel robot is often used for sorting, battery clamp is divided into two structures, the classification and sorting, for multi-target sorting problems. The motion path of end-effector is planned, the overall sorting path is planned, and the practical problem is transformed into a similar traveling salesman problem. The improved genetic algorithm is proposed to optimize the sorting time sequence, and the optimized path shortens 10.23% total distance on average compared with random sorting and 5.37% total distance compared with fixed longitudinal sorting. The shortening of the total distance can lead to higher sorting efficiency in sorting and increase productivity.
Research on voltage stability and control strategy of power system considering grid connected charging of electric vehicles
Authors: Fang Weidong , Lv Hao , Jiang Yiting , Li Lingzhi 
Published: December 2021

Abstract
The development of new energy vehicles is an important measure to deal with the growing energy demand and climate change. Especially in recent years, with the support of national policies and the maturity of electric vehicles(EVs) related technologies, the number of EVs has increased explosively, and the situation is very good. However, it also means that a large number of charging loads will be connected to the power grid, which will put great pressure on the safe and stable operation of the power grid. Although there have been many studies on the impact of EVs integration into modern power grid, most of the EVs load models are based on probability function and lack accuracy. Therefore, starting with the actual operation data of EVs charging station, this paper studies the influence of a large number of EVs charging loads on the static voltage stability of power grid. It is found that the charging load of large-scale EVs is added to the power grid, which significantly reduces the stability of power grid voltage, especially at the place connected to the EVs load and far away from the balance node. In addition, when the charging station adopts the time-of-use(TOU) price strategy, it can effectively improve the voltage stability of the whole network.
Design of the Power System and Remote Control System for the Unmanned Ship
Authors: Zhang Hao , Zhang Zeyu 
Published: December 2021

Abstract
In lakes and reservoirs with high environmental protection requirements, it is necessary to adopt pure electric intelligent water quality monitoring ships, adopt pure electric power systems and intelligent remote control systems. This article specifically completed the design of the power system and remote control system of the smart ship, and elaborated the design method in detail. The system has the characteristics of high reliability, miniaturization, and modularization. The successful development of the system has greatly improved the intelligence of water quality monitoring ships, and has a positive effect on small intelligent ships in lakes and reservoirs.
Research and Application of Automatic Measurement of Resistance Value Based on a Thermal Control Device
Authors: Feng Tao , Huang Lei , Guo Mingyu , Xu Zhen , Fu Guanghui , Yu Yue 
Published: December 2021

Abstract
The resistance measurement system of thermal control device is mainly composed of four parts: fixture, interface circuit board, switches module and data acquisition system. The main contents of the system design are as follows: To make the system realize the automatic resistance measurement function of thermocouple, heating belt and heating plate, and improves the measurement speed and robustness of the software; To achieve the friendliness of human-machine interface;
At room temperature, it can collect 40 output voltage signals of thermocouple, and judge whether the temperature collection of thermocouple is accurate or not.
Research on Key Technology of Tile T/R Module Design
Authors: Zhang Yu , Zhao Hailong , Song Xuefeng , Li Zenglu 
Published: December 2021

Abstract
Tile T/R module has the characteristics of miniaturization, lightweight, high integration and high performance, which are very difficult to develop. This paper studies the key technologies involved in the development of T/R module, and focuses on the key technologies such as high integrated multifunction chip technology, high performance Radio Frequency (RF) 3D interconnection technology, high integrated multichannel RF design technology and thermal design technology. Through research and analysis, a design scheme of tile T/R module with miniaturization, high performance and high reliability is proposed.
Orderly grid-connected cooperative scheduling control strategy based on distributed energy storage for electric vehicles
Authors: Li Xiaomei , Cao Rong , Hao Wenbo , Xu Mingyu , Hu Heng , Jiang Peng , Zhou Feng 
Published: December 2021

Abstract
Aiming at the problem that large-scale disorderly grid connection of electric vehicles negatively affects grid operation and causes a large amount of abandoned wind and abandoned light, an orderly grid connection cooperative scheduling control strategy based on distributed energy storage of electric vehicles is proposed. The strategy takes the charging and discharging price as the lever to guide the users to charge and discharge in an orderly manner, takes the optimal economics on the user side and the optimal cost of power generation on the grid side as the objective function, and uses linear weighting normalization to convert the multi-objective function into a single objective function for simulation solution. The simulation results show that the effect of peak shaving and valley filling can be achieved on the basis of satisfying users’ demand, and renewable energy can be effectively consumed.
Single-ended fault location and early warning method of transmission line based on back propagation neural network
Authors: Zhou Han , Liu Minghui , Yu Xin , Wang Weiyang , Gao Jingyao 
Published: December 2021

Abstract
For power transmission systems, accurate and reliable fault location methods can ensure rapid recovery of faulty lines and improve power supply reliability. In order to solve the problems of the structural complexity of the transmission system and the difficulty of line fault location, a single-ended fault location and early warning method of transmission line based on back propagation neural network is proposed. First, the fault line selection is performed quickly when the fault occurs. Then, the voltage fault components collected at the measuring point when the fault occurs are decomposed and reconstructed by wavelet packet to obtain the wavelet packet energy, which is used as the input sample to train through the nonlinear fitting ability of back propagation. With the help of backpropagation neural network, arbitrary complex functions can be processed, and the learning results can be accurately used for new knowledge, and circuit faults can be diagnosed conveniently and quickly. Finally, the corresponding fault distance can be output by substituting the wavelet packet energy reflecting the fault location. The simulation results show that the method has strong resistance to transition resistance and high positioning accuracy.
VSG damping adaptive adjustment based on BP neural network
Authors: Zhang Mengzhao , Guo Chunlin 
Published: December 2021

Abstract
The moment of inertia and damping of virtual synchronous generator (VSG) can be adjusted flexibly, which also has a significant impact on the transient performance of VSG. Constant damping or moment of inertia can not reduce frequency overshoot and fast response performance, so it is necessary to introduce adaptive damping control. Based on universal approximation theorem, BP neural network can fit continuous nonlinear function well. At the same time, it has the advantages of simple algorithm, powerful learning ability and fast learning speed. Based on the characteristics of the control object, the BP neural network is improved and a new adaptive control strategy is designed. The strategy uses improved BP neural network to adjust VSG virtual damping D online. Python-MATLAB-Simulink was used for co-simulation, BP neural network algorithm was integrated into the control object to establish an adaptive simulation model, and the proposed control strategy was simulated and verified. Simulation results show that the adaptive control strategy can eliminate overshoot and respond quickly when the frequency and active power of virtual synchronous generator change.