bluuebunny/crossref_metadata_2025 huggingface dataset:
Research Based on The Improved Grey Wolf Optimization Algorithm
Authors: Jia Shaoyong , Sun Shibao , Wang Jing , Xu Fengkui
Published: April 2021

With the continuous progress of machine learning methods, more and more methods are widely used in various fields. Grey Wolf Optimization Algorithm (GWO), as a kind of population algorithm, has become a research hotspot in recent years because of its good optimization ability. Similar to other population algorithms, gray wolf optimization algorithm itself has the problem of imbalance between global search and local search capabilities. In order to solve this problem, the following improvements are proposed to the standard gray wolf optimization algorithm: First, change the decrement method of the convergence factor and adopt a non-linear decrement method to meet the actual search process; At the same time, a weighting strategy is introduced to dynamically assign weights to the guide wolves. It can ensure that the population jumps out of the local optimal solution. In order to verify the effectiveness of the improved algorithm, an international general test function is selected for simulation. The simulation results show that the improved gray wolf optimization algorithm has faster convergence speed, higher solution accuracy and better stability.
Statistical measure researches for the impacts of COVID-19 on Shanghai Securities Composite Index: based on mode regression model using skew-normal distribution
Authors: Zeng Xin , Ju Yuanyuan , Wu Liucang
Published: April 2021

The economy of China has been affected by the COVID-19 and it is necessary to measure and investigate it. The mode regression model and its data deletion model using skew-normal distribution are established via the industry sub-index data of Shanghai Stock Exchange. Statistical diagnosis method of the model is proposed by using Pena distance diagnosis statistics, and the unknown parameters are estimated by the EM algorithm facilitated by gradient descent (GDEM) method. The results show that the outliers are accurately identified by the proposed statistical diagnostic method, and parameter estimation results indicate that the contribution of all industries to economy during the COVID-19 is lower than before, among which industry and commerce are the hardest hit.
OCR Service Platform Based on OpenCV
Authors: Cai Jianjun , Sun Erxin , Chen Zongjuan
Published: April 2021

This paper builded an ocr service platform based on opencv. Cut images of license plates and characters were generated by analyzing and processing the images based on the opencv algorithm and utilizing the image big data accumulated in the production of application software in the automobile industry. Label these cut images as training data and input SVM, ANN and other trainers to train the model to recognize the characters in the new license plate image. In addition to license plate recognition, vin code recognition, driver’s license number recognition and other ocr functions can also be developed in a similar way. The platform is developed based on java language and springboot framework in order to be technically unified with other automotive industry application software. It needs to use java to call opencv c++ interface implementation, and the platform provides rest interface externally.
Research on Performance Testing Technology Based on Scenario Design
Authors: Hui Zhang
Published: April 2021

With the rapid development of web system application, performance testing is very important to ensure the fault free operation of web system. The scenario design in performance testing is the basis of performance testing. Only reasonable design of test scenarios can obtain valuable test data. This paper starts from the web performance testing, explains the function and design of performance testing scenarios, then analyzes the common performance testing scenarios, and finally carries out web performance testing practice through testing tools. The experimental results show that the performance test of different scenarios can help to find out and solve the main problems in the web system, and provide an effective basis for system optimization.
Structural Change and Mode Innovation Based on Recommendation Algorithm and 5G Technology -- a New Format Brought by Streaming Media for China’s Documentary Industry
Authors: yinjun Wu
Published: April 2021

The streaming media platform represented by Netflix is constantly promoting the vertical integration of content and platform providers by using algorithms and data, changing the previous transmission mode of documentary. Documentary is no longer limited by the schedule threshold of traditional media and film festivals. It has a wider transmission channel and obtains positive marketing under the agenda setting. Virtual reality technology and Web online interaction technology will also change documentary from recording the reality to experiencing the reality in the future. With the introduction of Netflix algorithm and mode, the industrial trend in North America will also affect the documentary production in Chinese speaking areas. Compared with the documentary industry in North America, this paper predicted the structural changes and mode innovation of Chinese documentary industry brought by streaming media algorithm and technology, and discussed the opportunities and challenges that Chinese documentary creation will face in the streaming media era.
Analysis of Mobile Push Service Model of Smart Library Based on Big Data
Authors: Shu Zongying , Jiang Yiqun , Liu Jia , Wang Maohan
Published: April 2021

[Purpose / Significance] With the development of big data, massive data resources appear. Smart library should provide more personalized services to better meet the needs of users. [Method/Process] This article analyzes the characteristics of smart library services. It includes precision, timeliness, interactivity and personalization. [Result / Conclusion] This paper analyzes the development opportunities of knowledge push service in Smart Library, and establishes the mobile push service model of Smart Library.
Analysis of shock calculation based on Newmark integral method
Authors: Chen Benlan
Published: April 2021

In this paper, the time domain method for the calculation of impact resistance is studied. Firstly, the central difference method and the Newmark integration method based on the analysis of the linear equations and the solution of the nonlinear equations are educed. Then, the advantages and disadvantages of these two methods are compared and analyzed, and the conclusion is that the Newmark integral method is suitable for the calculation of the non dynamic equation.
Asymmetry analysis of melanoma based on ABCD rule
Authors: Zhang Guolan , Guo Siwen
Published: April 2021

Malignant melanoma is a malignant tumor that is extremely harmful and prone to lymphatic metastasis. If it cannot be diagnosed and effectively treated at an early stage, it will cause irreversible consequences. There is a lot of evidence that if you can get the exact treatment in the early stage, it can effectively improve the recovery rate. At this stage, clinical diagnosis of melanoma is mainly performed manually, which has defects such as low overall efficiency. This article is based on ABCD rule, combined with the clinical features of melanoma in dermoscopic images, to determine the benign and malignant melanocytes. Firstly, the image processing technology and pattern recognition technology are used to acquire and preprocess the dermoscopic image, and the image feature points are extracted. Then, the microscopic asymmetry and macroscopic asymmetry of the image were analyzed. Finally, the symmetry score was calculated by TDS to judge the benign and malignant of melanocytes. It is expected to assist dermatologists in diagnosing melanoma, provide timely feedback information to patients and provide targeted treatment for patients, improve the efficiency and accuracy of medical clinical diagnosis, achieve the purpose of curing, and reduce the harm of melanoma to human health.
Global asymptotic stability for neutral-type Hopfield neural networks with multiple delays
Authors: Wu Fei
Published: April 2021

This paper aims to study stability problem for neutral-type Hopfield neural networks including multiple time delays in states and multiple neutral delays in time derivative of states. The stability criteria cannot be derived by linear matrix inequality since the networks cannot be transformed into the vector-matrix form. By constructing LyapunovKrasovskii functional and using inequality techniques, novel stability criteria of global asymptotic stability are established. Finally, an example is given to show the effectiveness of the theoretical result.
RETRACTED: A Practical Research on the Online Learning Mode of Business English Majors under the Background of “Internet+”
Authors: Tang Jianfeng
Published: April 2021

In the context of “Internet +”, we need to strengthen research on the application of the online learning model for business English majors. This article analyzes the various effects of online learning models on business English majors. This article will discuss the shortcomings in the application of the current online learning model for business English majors. Only by mastering relevant materials can we propose effective practical strategies, improve the application level of online learning models and students’ learning effects, and give full play to the positive role of Internet technology in the teaching of business English.
Research on the relationship between e-commerce ratings and reviews based on Naive Bayes
Authors: Qin Zeqing , Wang Zesong
Published: April 2021

With the popularization of the Internet, online shopping has gradually replaced traditional shopping methods. Product ratings and comments from buyers have become important indicators for users when purchasing products. Because of this, the behavior of employing someone to rate high, known as click farming, has gradually risen. To deal with this phenomenon, users pay more attention to the content of the review itself rather than the score to make judgments. Then why are the stores still keen on employing click farm? We think that the high scores seem to play a guiding role in the user’s comments. To explore whether this phenomenon exists, we crawled sales information from Amazon and built a mathematical model. A Naive Bayes Classifier is employed to screen out the high-frequency vocabulary from the comments. And we defined the important concept of Irrational Discrimination base on Multiple Linear Regression. After analyzing the data for the whole year, we found that discrimination does exist. The specific vocabulary appearing in the review has a large star rating relevance shows that not only the time guiding role exists between star ratings and reviews, but also a strong interaction.
Research on Composition and Topology of Wireless Sensor Network
Authors: Li Yijie
Published: April 2021

Wireless sensor network is a kind of computer network which is composed of many automatic devices distributed in space. These devices use sensors to collaboratively monitor physical or environmental conditions (such as temperature, sound, vibration, pressure, motion, or contaminants) at different locations. Based on the composition of sensor nodes, sensor network is composed of intelligent sensors with multiple wireless communication modules. This paper studies the distribution and arrangement of sensor nodes in the sensor network, which is used to sense and monitor the physical information of the environment, so that the sensor network has higher reliability and availability.
The Study on High-Value User Identification of Localized Information Platform
Authors: Li Jinyi , Cao Sheng
Published: April 2021

In the current business environment, enterprise competition is fierce, high value customers are increasingly important to enterprises. However, with the development of social networks, the traditional RFM model of user value stratification is not accurate enough. Therefore, this paper introduces the characteristics of customer social attributes and establishes RFMS model to classify customer groups more accurately and effectively and identify high-value customers. Thus, it can help enterprises allocate resources reasonably and carry out customer operation in a targeted way.
Application of Robust Digital Watermarking Technology in Image Copyright Disputes
Authors: Cheng Bin , Zhang Bo
Published: April 2021

In recent years, with the increasing application of computer technology in daily life, the phenomenon of data transmission or transaction on the network is becoming more and more common. On the one hand, it brings great convenience to our life, on the other hand, there are also great hidden dangers, such as information replication, forwarding, and even tampering. Based on the research of DWT dual color image digital watermarking algorithm based on HVS, this paper introduces Arnold transform to improve the robustness of the algorithm, and studies the application of the improved algorithm in e-commerce image disputes.
An efficient method for compressing neuron morphology data
Authors: Li Longfei
Published: April 2021

The human brain has a very complex network structure. In order to understand the information integration process of the neural network in the brain, the current research of computational neurology focuses on studying the laws of neuron morphology. In recent years, the reconstruction technology in the field has developed rapidly, and the production speed of neuron data has been greatly accelerated. The problem of neuron data management under the background of Big-Data has gradually emerged. This paper proposes a method for compressing neuron morphology data based on binary coding, so as to efficiently store neuron morphology data. Relevant experimental results prove that the method in this paper is widely applicable to various types and sizes of neuron data.
The relationship between the corresponding author and its byline position: An investigation based on the academic big data
Authors: Yu Jianfei , Yin Chunxiao
Published: April 2021

With the increase of international collaboration, author contribution is becoming a key issue in research evaluation. Different counting methods may result in different results. Given the importance of the byline position and the significant role of the corresponding author, this study investigates the relationship between corresponding author and its byline position. By analyzing over 11 million papers from Web of Science published from 2000 to 2008, we find that the relationship between the corresponding author and byline position varies with year, the number of authors, countries and research fields. Our findings can provide insights to scientific research evaluation.
LSTM-CNN network for human activity recognition using WiFi CSI data
Authors: Shang Shunuo , Luo Qingyao , Zhao Jinjin , Xue Ran , Sun Weihao , Bao Nan
Published: April 2021

Human Activity Recognition (HAR) has had a diverse range of applications in various fields such as health, security and smart homes. Among different approaches of HAR, WiFi-based solutions are getting popular since it solves the problem of deployment cost, privacy concerns and restriction of the applicable environment. In this paper, we propose a WiFi-based human activity recognition system that can identify different activities via the channel state information from WiFi devices. A special deep learning framework, Long Short-Term Memory-Convolutional Neural Network (LSTM-CNN), is designed for accurate recognition. LSTM-CNN is going to be compared with the LSTM network and the experimental results demonstrate that LSTM-CNN outperforms existing models and has an average accuracy of 94.14% in multi-activity classification.
Design of Intelligent Safety Protection Robot Based on Global Position System and Machine Vision
Authors: Ming Yang , Yufei Li
Published: April 2021

In this paper, an intelligent safety protection robot based on the integration of Global Position System(GPS) and machine vision is designed. The robot takes STM32F407 as the control core and is equipped with a variety of environmental monitoring sensors to realize real-time monitoring of the surrounding environment and alarm for potential safety hazards. In order to realize the stable and accurate autonomous navigation of robot, a system combining GPS technology with visual simultaneous localization and mapping (V-SLAM) technology is designed. GPS module collects longitude and latitude information, driving speed and heading Angle to complete the absolute positioning of the robot. Machine vision device collects image information, and the relative positioning of the robot is completed through digital image processing technology. The two positioning information was fused and output new positions and postures through Unscented Kalman Filter (UKF). Through the experimental verification of the combined navigation and positioning effect, the GPS and machine vision integrated navigation device has high precision, and the maximum error is controlled within 0.1 meters.
Research on the Reform of Investigation Methods Guided by Dynamic Data Forecast
Authors: Tang Liangyan
Published: April 2021

This article analyzes the constituent elements of dynamic data forecasting and guiding investigation. The research content of this article includes technical elements, resource elements, thinking elements, etc. The author combined with dynamic data to predict the attributes of guiding investigations, and studied content including dynamics, openness, diversity, and integrity. This paper studies the spatial analysis method, detection analysis method, matrix analysis method, predictive analysis method, risk assessment analysis method, node analysis method and so on. The purpose of this article is to guide the reform of investigation methods, speed up the development of investigation work, and improve the practicability of investigation results.
Design of Face Recognition Access Entrance Guard System with Mask Based on Embedded Development
Authors: Ruiqin Lin , Wenan Tan , Zhenyu Chen , Qinqin
Published: April 2021

This paper investigates all kinds of access entrance guard control systems at home and abroad and analyzes their advantages and disadvantages. COVID-19 epidemic has a serious impact on life, travel must wear a mask, so that the access entrance guard control system can not carry out face recognition under the mask. In view of this kind of situation, an embedded face recognition access entrance guard control system with mask based on EAIDK-310 development board is designed. The system can complete face recognition and body temperature measurement without contact, and drive the motor to open the gate. After testing, the system is suitable for deployment in companies, communities, campuses and other small application scenarios. It is convenient to travel and can reduce the impact of the epidemic.
Bibliometric research in the field of artificial intelligence
Authors: Tu Wenyan , Fang Ji , Fangyu  , Jiao  , Ci Yutong
Published: April 2021

This paper analyzes the development trend of global artificial intelligence from the perspective of bibliometrics. From the publishing trend, the number of papers published in the field of artificial intelligence is growing rapidly. China and the United States are among the top countries in the output of scientific research papers, and India has the fastest cumulative growth rate. In the research direction, the research on computer vision, image, deep learning and neural network is the research hotspot in recent years.
Application Research of Automatic Garbage Sorting Based on TensorFlow and OpenCV
Authors: Hu Jing , Zhang Bo
Published: April 2021

Relying on manual garbage classification, the classification efficiency is low, and because of the classification environment is bad, the classification task is heavy, it is very adverse to the health of the classification personnel. With the development of artificial intelligence, artificial intelligence technology has advanced by leaps and bounds. After the concept of deep learning was proposed, the development of artificial intelligence was driven to practical application. And the advantages of deep learning are obvious, which also makes automatic garbage sorting possible. With the development of deep learning, a large number of deep learning network framework structures have gradually emerged, and a group of open source frameworks represented by TensorFlow and Keras have been widely applied. This paper proposes an application research on automatic garbage sorting based on TensorFlow and OpenCV, an open source image library, in order to realize automatic garbage recycling.
Research on intelligent perception and human activity monitoring for people with inconvenient movement
Authors: Zhang Tianping , Tang Xiaoping , Li Lijie
Published: April 2021

Aiming at the problems of various sensors, complex recognition algorithm poor implement ability and real-time performance in current human activity state recognition methods, a human activity monitor based on single three-axis acceleration sensor is designed. By collecting acceleration data of human waist, using sliding time window method to extract time domain features, four active states are identified: long-term violent active state. Long-term static state, fall state and normal active state. The technical development and the existing difficulties and problems are discussed for future related research.
Deep research on big data index analysis method in intelligent manufacturing industry
Authors: Song YuXiang
Published: April 2021

Big data analysis is widely used in intelligent manufacturing industry. Data analysis refers to analyzing a large amount of data collected by appropriate statistical and analytical methods, summarizing and understanding them, and digesting them, so as to maximize the development of data functions, give full play to the role of data, and improve and strengthen the intelligent level of manufacturing system. Data analysis is to extract useful information and form conclusions, and to study and summarize the data in detail. The data of intelligent manufacturing system is also called observation value, which is the result of experiment, measurement, observation and investigation. The data processed in data analysis is divided into qualitative data and quantitative data. The results of data analysis are of great significance in the intelligent manufacturing industry.
Real-time workshop digital twin scheduling platform for discrete manufacturing
Authors: Zhifeng LIU , Yueze ZHANG , Caixia ZHANG , Jun YAN , Shiyao GUO
Published: April 2021

Compared with other production methods, multi-variety, small-batch production driven by order become a lot more sensitive to the disturbances of workshop environment, orders, and processing equipment. This makes a great impact on workshop scheduling. Aiming at this problem, this paper designs a real-time workshop digital twin scheduling platform for discrete manufacturing. It improves the flexibility of the intelligent workshop and the response processing speed after dynamic disturbance. The platform can real-time monitor of the physical workshop and track orders, products, equipment and other information. Further, the platform and visualization technology were explored to work together. Then, the true display of changes after production line decision was displayed. It enables managers to carry out production scheduling verification in the virtual workshop, which reduces the repeated changes of physical workshop production scheduling. Finally, the platform was verified in a discrete manufacturing workshop. The scheduling platform based on digital twins helps manager to immersivity develop factory production strategies. The production efficiency was then enhanced. The platform can ensure the effective operation of the manufacturing system.
Applications and Prospects of Mems Sensors in Automotive
Authors: Jin Li
Published: April 2021

MEMS sensor is a new type of sensor and is made by micro-electronic and micro-mechanical processing technology. It has many advantages such as small volume, light weight, low cost, low power consumption, high reliability, suitable for mass production, easy integration and intelligent realization. It is widely used in the automobile, effectively improving the performance of the automobile sensor, promoting the progress of the automobile industry and the intelligent automobile. This paper mainly discusses the market size of MEMS sensors and their applications in the automotive field, focusing on MEMS pressure sensors, MEMS acceleration sensors and gyroscope sensors. The development direction of MEMS sensors in the automotive field is forecasted.
Digital twin-based smart manufacturing cell: Application Case, System Architecture and Implementation
Authors: Zhang Jiyuan , Li Pengzhong , Luo Liang
Published: April 2021

Smart manufacturing is considered to be a universal solution for upgrading manufacturing. Currently, the manufacturing tasks are becoming more personalized and the complexity of the manufacturing environment is increasing. Therefore, the manufacturing system needs to have a high level of learning and cognitive abilities. In order to cope with changes in the manufacturing environment, this paper proposes a system architecture of a smart manufacturing cell, which can intelligently sense, analyze, and make decisions to support autonomous manufacturing. Through the implementation in the experiment, it is verified that the proposed architecture is reasonable.
An adaptive slicing approach for processing STL massive data model in batches based on layer merging
Authors: Shao Minghao , Wei Chao , Cui Bin , Li Yongkang , Zheng Tengfei
Published: April 2021

Slicing is one of the core parts of the additive manufacturing software system, which completes the function of transforming the 3D model into a 2D profile. The adaptive slicing algorithm uses different layer thicknesses for layering in different areas according to the changes in the geometry of the mesh model. Where the model is more complex and the curvature changes a lot, a smaller layer thickness is used to approximate the model. In areas of large curvature of the model, maximum layer thickness is used to improve printing efficiency. With the development of additive manufacturing technology, grid model files such as STL have become larger and larger, and the amount of data needed to be processed by slicing software has increased dramatically. Existing slicing software is limited by computer hardware and cannot process massive data model. It greatly limits the development of additive manufacturing technology, so it is urgent to propose a new method to solve the rapid stratification of mass data model. In this paper, we proposed an adaptive slicing approach for processing STL massive data model in batches based on layer merging. At the same time, it is compared with the fixed-layer thickness slicing method, which shows that the algorithm can improve printing efficiency under the premise of ensuring accuracy.
The Software Design of Intelligent Campus Safety Cabinet under Epidemic Situation
Authors: Zhaofan Zhou , Lingying Tu
Published: April 2021

During the outbreak and future public health security, the safety cabinet industry gradually took to the forward momentum of development, the safe cabinet from the normal delivery tank through the software design to implement the "sell" face-to-face in universities. According to the survey, most students lose some take-out. Safety cabinets not only solve the problem of the safety delivery courier, also pay attention to public health in this era of successful implementation without personnel contact. Through the software design, the dining room also unified blocks with the school management, and students can order food through the canteen they want to go to, which provides a large number of different choices for students so that they won't get tired of eating in the same area. With the popularization of 5G in the future, the combination of "unmanned delivery mode" can reduce more risks in terms of public health and make people's lives more convenient.
Intelligent detection device of pavement disease based on image recognition technology
Authors: Guo Wentong
Published: April 2021

In recent years, the continuous progress and development of artificial intelligence technology, especially the technology represented by deep learning and image recognition, have made great breakthroughs, and put forward new methods for road surface disease detection. In this paper, image recognition technology is applied to the direction of high-level pavement detection, and an intelligent disease detection robot is developed based on GPS navigation technology, which realizes the integration process of pavement disease from detection to location.
On-line monitoring of penetration state in laser-arc hybrid welding based on keyhole and arc features
Authors: Zhang Minghai , Shu Leshi , Zhou Qi , Jiang Ping , Gong Zhaoliang
Published: April 2021

Incomplete penetration is a typical defect in laser-arc hybrid welding. On-line monitoring of welding process is an important method to assess welding quality. In laser-arc hybrid welding, there is a strong correlation between keyhole, arc and incomplete penetration. Therefore, an on-line monitoring method of penetration state based on keyhole and arc features is proposed in this paper. In the proposed method, the images of keyhole and arc in laser-arc hybrid welding are captured by high-speed camera, and then the keyhole and arc features are extracted by image processing algorithm. Finally, the features are used as input to classify the penetration state using SVM model. The results show that the SVM model based on keyhole and arc features can accurately identify the penetration state.
Trajectory tracking control method of robotic intra-oral treatment
Authors: Cheng Qiang , Xu Wenxiang , Wang Yi , Liu Zhifeng , Hao Xiaolong
Published: April 2021

At present, people suffer from a high rate of cross-infection of oral diseases, and it is an urgent clinical need to explore effective methods to promote high-security and high-quality imaging. This paper proposes a collaborative robot control strategy that assists in oral diagnosis and treatment. This method can track the dynamic movement of the patient's upper and lower jaw during treatment. According to the small space of the oral cavity and the change of the tooth position, dynamic trajectory tracking with adaptive control is performed on the robotic arm. This control strategy is of great significance for accurate oral diagnosis and treatment and reducing cross-infection between doctors and patients.
Algorithm for detecting brightness differences in noisy images based on the Wilcoxon criterion
Authors: Dudka N , Fedorov E , Ferenets A
Published: April 2021

To detect brightness differences in grayscale images, in previous works it was proposed to use the nonparametric Wilcoxon criterion. At the same time, the obtained research results showed a sufficient effectiveness of the application of the criterion for highlighting the brightness differences in images with noise without preliminary filtering. The application of the criterion involves the transformation of the image into such an attribute as the value of the rank function for each pixel of the analyzed image area. Calculation of the extremum of the rank function makes it possible to establish the location and type of brightness differences in the image. However, as studies have shown, the value of the extremum value depends on the signal-to-noise ratio in the image and, along with the true extrema, local extrema are also distinguished, which complicates the solution of the problem of further image segmentation. This paper presents the results of statistical studies on the use of the Wilcoxon test for detecting brightness differences in images with different signal-to-noise ratios and sample sizes. The minimum signal-to-noise ratio at which the extremum of the rank function tends to its maximum or minimum value has been established. Also, based on the statistical analysis of the behavior of the rank function to exclude the allocation of local extrema, it is proposed to use the difference of the rank functions for the analyzed rows and columns of the processed image
Simulation Complex for Debugging of Control Algorithms of the Test Bench
Authors: Shmidt I A , Ivanov P V , Gribkov I N
Published: April 2021

The object of research and development is an air heating and delivery automatic control system of the test bench for testing of gas turbine engines. It is based on a test bench equipped with a gas turbine engine, a long air duct with dampers regulating the airflow, and the tested mechanism. It must maintain the required airflow characteristics and the air charge motor’s operating mode line. To debug the algorithms of the object of research, a simulation complex was developed, which can reproduce all the features of the test bench’s behavior. The combination of the automatic control system and a simulation complex is a semi-natural model. Purpose is to develop a simulation complex for the debugging of the control algorithms and a mathematical model of the stand and the engine under test. As result, a simulation model based on the implementation of VeriStand technology was created. The program provides a uniform way to access heterogeneous models executed in Simulink. These models display different ways of describing the processes and features of the behavior of the modelled object. The simulation results can be compared to the behavior of a real system, which allows to debug the algorithms of the automatic control system. The developed simulation complex is currently used by specialists to make the mathematical models of the test bench components and the tested product more precise, as well as to debug the control algorithms.
Application of the “Bow-Tie” method to assess the risk of incapacitation of the sucker rod pump
Authors: Bochkarev S , Leyzgold K , Shilova S
Published: April 2021

The article presents one of the methods for assessing the risk of electrical equipment accidents at an oil and gas production and transportation enterprise, in order to improve the smooth operation and efficiency of the use of electrical and technological equipment of oil fields. As an example, the operation of a rod pump is considered.. The concept of a systematic approach for risk analysis at industrial enterprises is proposed.
Virtual Enterprise Approach for teaching students in electrical engineering
Authors: Shaykhutdinov D , Krivtsun A , Gaaber J
Published: April 2021

This article deals with the original approach which is proposed - a “virtual enterprise” that differs from the well-known by a more in-depth focus on the future specialist’s adaptation to the market economy. The methodology of a virtual enterprise is based on a project-oriented approach. The tools for the implementation of information exchange within the educational virtual enterprise, as well as for the implementation of the process of product design and testing has been proposed and considered. To implement the information exchange environment the usage of the training version of the SAP ERP application package has been proposed. To implement the environment for the development and implementation of technical solutions the usage of hardware and software of National Instruments has been proposed for realization of a concept.
New Periodic Table of Elements: Electron Configuration and Motion, and Formation of Simple Compound
Authors: Peng Y B , Lei T , Zhen H T , Yuan Z X , Xu H , Wen F
Published: April 2021

Based on the number of protons and electrons in the existing element, this paper believes that the electron configuration of the element needs to be changed in order to obtain its new properties and principle of electron pairing. The new electron configuration is the square of the number of periods. The first, second, third, and fourth periods contain 1, 4, 9, and 16 electrons respectively. Atoms evolve by the movement of electrons from the outer core, attracting electrons from different atoms to form compounds. When low hierarchy elements combine with high hierarchy ones, their electrons preferentially choose electrons of higher period of each other for coordination. So H atomic electrons are more likely to attract and pair with electrons of the second period of C, N and O to form bonds, while the outermost electron of O in the third period tends to pair with electrons in the fourth period of P, S and Cl. Then the special structure of ammonia and water molecules can be deduced, and the double bond characteristics of highpriced acids of P, S and Cl can also be explained. New periodic table of elements makes it easy and convenient to explain chemical phenomena and facilitate the understanding of the micro world.
Structural and Electronic Study of Palladium(II) Complexes by a Theoretical Approach
Authors: Saadiah Abdullah Nur Halimatus , Nazirah Ozair Lailatun , Muhammad Anas Muhammad Mus’ab Anas , Mohd Yamin Bohari
Published: April 2021

The established method of synthesising tetraaza macrocyclic ligand by introducing a transition metal ion as a templating agent has demonstrated difficulties in the decomplexation process. Therefore, this study examined the potential of forming the ligand before converting them into transition metal complex and further explored the characteristic of Pd2+ tetraaza macrocyclic complex through density functional theory (DFT) calculation. The results show that the cation successfully fits in the macrocyclic ligand as a result of the electron transfer process.
Application of Pulsed Electric Field for Inactivation of Yeast S. cerevisiae in Apple Juice
Authors: Eshtiaghi M N , Nakthong N
Published: April 2021

Pulsed electric filed (PEF) is a non-thermal food preservation method as alternative to traditional thermal method. The effect of pulsed electric field (PEF) on inactivation of yeast Saccharomyces cerevisiae (S.cerevisiae) in apple juice containing different sugar concentration was studied. The results of this study have shown that, using PEF, the yeast could be inactivated at room temperature (20°C). The inactivation effect of PEF was dependent on pulse number, field strength, and pulse width as well as sugar concentration. Pulse numbers less than 20 pulses (at 12.6kV/cm) had no or very less effect on yeast inactivation. Increasing the pulse number up to 400 pulses resulted about 3 logs yeast inactivation. The most important factor for yeast inactivation was the field strength (10 to 30 kV/cm). Whereas, at 10.2 kV/cm and 100 pulses, less than 2 logs yeast inactivation could be achieved, was the yeast inactivation at filed strength of 30kV/cm and 100 pulses about 5 logs. At given field strength and pulse number, longer pulse width (1 to 2.5 μF) affected positively the inactivation of microorganism. In contrast, increasing the sugar concentration in apple juice higher than 20% negatively affected the inactivation of yeast during PEF treatment at given treatment conditions.
A Study of Interaction Between hWJ-MSCs and SiO2-Coated PDMS Micropattern
Authors: Tan M I , Barlian A , Prajatelistia E , Wahyuni A R , Tanoto H
Published: April 2021

In order to enhance the likelihood of bone healing process from fracture, currently bone graft combined with osteocytes is a new alternative in promoting new bone formation. Silica-based nanoparticles had been proven to induce intrinsic biology activity, especially in promoting bone-formation and differentiation of mesenchymal stem cells towards osteocytes. Previous studies had shown positive results of new bone tissue formation by incorporating SiO2 nanoparticles synthesized using TEOS. In this current study, the experiment was using micropatterning technique, with PDMS as the substrate, which was coated by SiO2 nanoparticle powder with the particle size distribution between 150nm-450nm. The effect of SiO2-coated PDMS on (Wharton’s jelly mesenchymal stem cells) hWJ-MSCs viability was evaluated using MTT cytotoxicity assay for 1, 3, 5, and 7 days, which was compared with two treatments: cells grown with SiO2 powder without patterns and cells on 96 well plate). The MTT assay result showed that SiO2-coated PDMS micropattern was non-toxic to the cells and had the highest increase in cell viability for 7 days in comparison to the two controls used.
Hydrophobic Coating on Woven Material for Personal Protective Equipment
Authors: Hildayani G M , Fahrunisa N , Rachmadhani  , Rachmawati S A , Nugroho A , Saepudin E , Sufiandi S
Published: April 2021

The performance of personal protective equipment fabrics for COVID-19 health care practitioners was improved by polyvinyl alcohol (PVA) coating. The PVA enhances fabric’s resistance to body fluid penetration, on the other hand, also increases its hydrophilic properties. However, hydrophobic is required to prevent microdroplets and body fluid wetting on the fabrics. The hydrophobic effect was increased by immersed the fabrics in silica nanoparticles that resulted in a water contact angle of 133.41° ± 10.8°.
The Comparison between Bulk RNA-seq and Ssingle-cell RNA-seq
Authors: Wanqi Zhang
Published: April 2021

Bulk RNA-seq and single cell RNA-seq (Sc-RNA) seq are two well-known methods and are broadly used in biology areas. Even though the two ways are all starting from the mRNA level to do the transcriptional analysis, many differences still show in them, but the differences which are critical for researchers to judge and consider were not addressed clearly in the past studies. Here we summarized the principle, workflow and data presentation of the two methods and compared them comprehensively, which shed a light on the application of high throughput sequencing technique for researchers.
Lockdown strategy worth lives: The SEIRD modelling in COVID-19 outbreak in Indonesia
Authors: Nurlaila I , Hidayat A A , Pardamean B
Published: April 2021

Lockdowns, despite their conflicting restrictions and consequences they might offer when enforced as a national strategy, are deemed to be suggestive for a prompt conquer to the Coronavirus Disease-19 (COVID-19) outbreak. There have been some success stories such as in China, South Korea and our ASEAN member fellow, Vietnam, which exhibited extremely fallen numbers of COVID-19 cases post the enforcement of lockdown. Indonesia, however, remains in the crux of dispute whether or not the lockdown is opted to force COVID-19 transmission down under control. We, in this respect, employ the most popular model which has been broadly applied in the field of epidemiology, referred to as SEIRD (Susceptible, Exposed, Infectious, Recovered, and Death), the extension form of an age-structured SEIR, where the Death (D) is included to provide more factual situation. We modify the I (Infectious) fraction as symp-tomatic (Is) and asymptomatic (Ia) infectives. There are three lockdown scenarios simulated in our modified SEIRD with the starting date are 26 April 2020 when the immediate lockdown was enacted-and a-week and two-week-gaps, respectively. We figured out that by stipulating the lockdown without delay (26 April 2020), the new cases could be kept below 10,000. A week delay escalates case number to 5,000 and delay for one more week results in beyond 20,000 new cases. Furthermore, when the intervention is delayed following the delayed lockdown, normalization would demand a longer period within which dealing with more critical and dying patients is unavoidable and should be more anticipated.
Mobile application design of smart water supply chain based on IoT: A case study in Indonesia
Authors: Suban I B , da Costa J E , Suyoto
Published: April 2021

Some areas in Indonesia often lack clean water even occur drought if the dry season strikes. However, several other regions of Indonesia have pure water abundance despite the dry season. Based on this problem, the authors aimed to design a mobile application of a smart water supply chain based on the Internet of Things (IoT) for admin and users. The app was Control Your Water (C_Water) application. The app developed aimed not only to detect water shortage quickly but also to accommodate online water purchasing. By installing sensors in the water reservoirs, the admin could find out the supply of clean water in the tanks. Information had obtained from the sensor will go to Microcontroller, then the Microcontroller will send it to the database via Wifi. The mobile application displayed information based on data in the database. The authors proposed a data backup process to prevent data loss. The authors designed a water reservoir consisting of positions of ultrasonic sensors and a division of water level. The result of this research finds that this design helps the government (admin) to overcome the problem of real water shortages that occur in Indonesia.
Supply chain green productivity improvement for sugar industry
Authors: Asrol M , Purba F
Published: April 2021

The sugar industry has a vital role in meeting domestic demands; therefore, it is crucial to increase productivity and supply chain efficiency. Productivity improvement should not only focus on economic efficiency but also the environmental impact called the principle of green productivity. This paper aimed to discuss the potential implementation of green productivity improvement activities and determine the level of green productivity that has been achieved in the supply chain of the sugar industry. The analysis began with supply chain configuration analysis, analysis of seven waste sources with Green Value Stream Mapping (GVSM), and inference of the green productivity level with Fuzzy rule-based. The results of the supply chain analysis show that two activities required to be analyzed for productivity, namely the sugarcane cultivation and the sugar milling processing division. The green productivity index in the current state of plantation supply chain activity was 0.90 and processing was 0.61. Green productivity improvement with good housekeeping and efficiency resulted in a GPI of 1.81 for plantation supply chain activities and 2.30 for processing. The fuzzy inference shows an increase in green productivity in the supply chain processing activities from a bad label to normal.
Building maintenance priority assessment for building components
Authors: Arumsari P , Wijayanti Y , Ramadhan N F
Published: April 2021

The aim of the research was to identify the building structure components that needed to be fixed first according to the priority assessment. The object of the research was traditional market buildings in West Jakarta managed by PD Pasar Jaya. The research was conducted through a survey, sending out questionnaires, and conducting interviews with experts. Building components were analysed using relative importance index to identify the most important building components to be maintained. Out of 135 building components there are 32 building components which are identified to be important. Through analytical hierarchy process (AHP), 9 building components need to be mitigated to avoid further damage to the traditional market building.