bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design and Development of Smart Irrigation and Water Management System for Conventional Farming
Authors: Rafique M A Z M , Tay F S , Then Y L 
Published: March 2021

Abstract
The intention of this project is to develop a smart irrigation and water management system for conventional farming. The project is conducted mainly to improve the irrigation scheduling and also to solve the over watering and under watering issues in traditional irrigation system. These problems can be solved by implementing soil moisture sensor as a smart component in the irrigation system. Smart irrigation system with the implementation of sensory-based system will be able to provide a proper irrigation scheduling, by monitoring the soil and weather condition of the farm. In this project, the sensory system consists of soil moisture sensor, temperature sensor and light intensity sensor, which basically used to monitor soil moisture level, temperature level, and light intensity level at the separate test area. Arduino Mega 2560 microcontroller will process the data from these sensors and a proper irrigation scheduling will be developed based on the data collected. Type of irrigation system that been used in this project is a sprinkler system because it has high uniformity of water distribution to the plant, which able to spread water efficiency and further optimize the water usage during irrigation process. Ultrasonic sensor is also implemented in the system to measure the amount of water used in each irrigation process performed. An offline data storage will be implemented in this project using a micro SD card module, which all the essential information such as sensory system readings and the amount of water used will be recorded and stored into a micro SD card. Thus, it allows user to monitor their farm’s condition, and also gives a better view on what is really happening at their farm.
Automated Classification of Alzheimer’s Disease Based on MRI Image Processing using Convolutional Neural Network (CNN) with AlexNet Architecture
Authors: Fu’adah Y N , Wijayanto I , Pratiwi N K C , Taliningsih F F , Rizal S , Pramudito M A 
Published: March 2021

Abstract
Alzheimer’s disease is a type of brain disease that indicate with memory impairment as the early symptoms. These symptoms occur because the nerve in the brain involved in learning, thinking and memory as cognitive function have been damaged. Alzheimer is one of diseases as the leading cause of death and cannot be cured, but the proper medical treatment can delay the severity of the disease. This study proposes the Convolutional Neural Network (CNN) using AlexNet architecture as a method to develop automated classification system of Alzheimer’s disease. The experiment is conducted using Magnetic Resonance Imaging (MRI) datasets to classify Non-Demented, Very Mild Demented, Mild Demented, and Moderate Demented from 664 MRI datasets. From the experiment, this study achieved 95% of accuracy. The automated Alzheimer’s disease classification can be helpful as assisting tool for medical personnel to diagnose the stage of Alzheimer’s disease so that the appropriate medical treatment can be provided.
A Stunting Prevention Application “Nutrimo” (Nutrition Monitoring)
Authors: Permana A A , Perdana A T , Handayani N , Destriana R 
Published: March 2021

Abstract
A total of 11 % of children under the age of five years (toddlers) in Tangerang City experienced stunting. Stunting reflects chronic malnutrition during the most critical period of growth and development in early life, the first 1000 days of life. Monitoring the nutritional status is able to prevent stunting especially through Kartu Menuju Sehat (KMS) at an integrated service post (posyandu). Most of the data in KMS is recorded manually, so the risk of data loss or damage is very high. Therefore, mobile application that can monitor the nutritional status automatically is needed to develop. The nutrition monitoring application “Nutrimo” which monitors children’s nutritional status was developed based on Android with anthropometric method and the Waterfall system development method. This application was completed with track record feature and suggestions that parents should take about the nutritional recommendations based on their respective nutritional status. The evaluation results showed that Nutrimo application was easy to use, informative and help to prevent stunting.
Development of Automated Monitoring System for Hydroponics Vertical Farming
Authors: Michael G W , Tay F S , Then Y L 
Published: March 2021

Abstract
Proposed is an automated monitoring system for hydroponics vertical farming. This project aims to design and develop an automated system to monitor and maintain the level of nutrition solution for the vertical farming process. The monitoring condition includes Electrical Conductivity (EC), pH value, the liquid level as well as the water temperature of the nutrient solution stored in the rectangular PVC. Instead of using soil as the growing medium, the project used hydroponics method to grow the leafy vegetables, Bok Choy. The data monitored will be sent and processed by Arduino Mega microcontroller and upload to Ubidots Cloud using the ESP8266 NodeMCU. The system also provides control function to maintain the nutrient level and amount of solution flows into each layer of vegetables. It is expected that the implemented system would reduce the water and electrical consumption and allows the growth of the plant to be supervised from time to time without having a person to look after.
Application of the Abel-inversion method for the hard X-ray camera on the HL-2A tokamak
Authors: Zhang J. , Zhang Y. , Li Y. , Gao J. , Yuan G. , Yang J. , Li X. , Song X. , Shi Z. , Liu Y. 
Published: March 2021

Abstract
The hard X-ray camera on the HL-2A tokamak has been used to study the behavior of energetic electrons in fusion plasma. In order to get precise hard X-ray emissivity information from the camera, a new hard X-ray emission profile reconstruction procedure based on the Abel-inversion method has been developed in the present paper. According to the verification results, the accuracy of the Abel-inverted profile depends on the accuracy of the interpolation and fitting processes. However, the error of the Abel-inverted profile is acceptable for the hard X-ray camera in general. For its applications, the procedure has been used to calculate the experimental local hard X-ray emission profiles. The calculation results show that the hard X-ray emission profiles were peaked at the center of the plasma, indicating the main energy of the lower hybrid wave was deposited at the center producing more energetic electrons than elsewhere. In addition, the calculation results can also indicate the confinement quality for energetic electrons, which can also be supported by statistical analyses for the line-integrated HXR emission profiles. The present paper lays a good foundation for the application of the hard X-ray camera on the HL-2A tokamak.
Quaternary alkylammonium disinfectant concentrations in soils rise exponentially after long-term wastewater irrigation
Authors: Heyde Benjamin Justus , Anders Anja , Siebe Christina , Siemens Jan , Mulder Ines 
Published: March 2021

Abstract
Quaternary alkylammonium compounds (QAACs) are used as disinfectants and surfactants worldwide, with their usage currently increasing as a result of the COVID-19 pandemic. QAACs are released into the environment with manure, sewage sludge and wastewater. The fate of QAACs in soils is poorly understood, although QAACs are inflicted in the selection of antibiotic-resistant bacteria. We studied the temporal accumulation of QAACs in soils of the Mezquital Valley that have been irrigated with Mexico City wastewater from 0 to 88 years. Concentrations of 16 QAACs, including alkyltrimethylammonium compounds (ATMACs), dialkyldimethylammonium compounds (DADMACs) and benzylalkyldimethylethylammonium compounds (BACs), were determined using HPLC-MS/MS after ultrasonic extraction. The most abundant QAAC-homologues in the soils were BACs > ATMACs > DADMACs. The concentrations of QAACs increased linearly and slowly during the first years of irrigation (∑QAAC: 2–23 µg kg−1), but after 40 years of wastewater irrigation we observed an exponential increase in QAAC concentrations (up to 155 µg kg−1). QAACs accumulate in soils of the Mezquital Valley during long-term wastewater irrigation. In contrast to pharmaceuticals, no apparent ‘steady state’ concentration is reached after decades of wastewater irrigation.
Three-Dimensional Microscopic Model of Solid Oxide Fuel Cell Anode
Authors: Li Q Q , Li G J 
Published: March 2021

Abstract
In this paper, a three-dimensional microscopic model of the solid oxide fuel cell (SOFC) anode is established based on the SOFC anode microstructure reconstructed by Nano-CT, and the characterization parameters of the electrode are calculated. The electrochemical reaction is defined on the three-phase boundaries of the microstructure, and the polarization characteristic at different temperatures is explored. Results show that the anode polarization loss increase with the increase of temperature. The activation loss and the ohmic loss are of the same magnitude and occupy the main part of the total polarization loss. The pore microstructure directly affects the gas transfer in the anode, and there is a large mass transfer resistance in the small throat, which causes obvious concentration polarization loss and affects the activation loss. Due to the uneven microstructure, the electrochemical reaction rate of the electrodes at the same depth is not consistent. The closer to the electrode-electrolyte interface, the more obvious the unevenness of activation polarization and concentration polarization.
Analysis on aroma components of flowers of five Magnolia denudata cultivars
Authors: Zhang Jianguo , Wu Miaowei , Zhang Mingru , Chen Xifan , Yang Jie 
Published: March 2021

Abstract
Aroma components in fresh flowers fromfive Magnolia denudata Desr are analyzed with Head Space Solid PhaseMicro-extraction (HS-SPME) and Gas Chromatograph-Mass Spectrometer (GC-MS) technology. The results show that 45 compounds are detected in the flowers offive germplasm of genus Magnolia denudata Desr, including 19 alkenes, 5 alcohols, 5 benzenes, 4 ketones, 3 esters, 2 ethers, 1 acid, 5 alkanes and 1 other compound. The type number of volatile organic compounds (VOCs)from more to less in order are: Yulania denudata ‘5#’ (22 species), Yulania denudata ‘Fei Huang’ (21 species), Yulania stellata (15 species), Magnolia liliflora Desr(12 species), Magnolia liliiflora ‘Hong Yuanbao’ (10 species);The content of volatile organic compounds from high to low areYulania stellata (28%), Yulania denudata ‘Fei Huang’ (26%), Magnolia liliflora Desr (17%), Magnolia liliiflora ‘Hong Yuanbao’ (15%) and Yulania denudata ‘5#’(14%). The type and content differences of volatile organic compounds (VOCs) in the flowers offive germplasm of genus Magnolia denudata Desr are comparatively big. There has been no research reports about the contents of volatile organic compounds in the flowers of Yulania stellata, Magnolia liliiflora ‘Hong Yuanbao’ and Yulania denudata ‘5#’. In conclusion, this study is expected to better clarify the component and content of VOCs from the flowers of different Magnolia denudata Desrcultivars, and provide the scientific basis for the health-care type garden green space building.
Effect of CaCl2 on the stability and antimicrobial activity of nisin
Authors: Li Wenchao , Liu Yang , Zhang Qian , Tan Zhilei , Jia Shiru 
Published: March 2021

Abstract
Nisin is a natural and safe biological preservative which has great potential in cosmetics and food industry. However, the low thermostability of nisin at high pH limits its commercial applications. In this study, the effect of CaCl2 on the stability and antimicrobial activity of nisin was studied. The results showed that CaCl2 has a strong protective effect on nisin at weak acid environment (pH of 4.0-6.0) and heat treatment. The results of X-ray diffraction (XRD) and scanning electron microscopy (SEM) showed that the crystalline particles of nisin increased size and decreased peak and a stable structure was formed by CaCl2 with nisin. The thermogravimetric analysis (TGA) presented that CaCl2 led to the temperature of initial (T5) and complete decomposition (T95) of nisin increased by 8 °C and 13 °C, respectively, and enhanced the thermostability of nisin. The result of Fourier-transform infrared spectroscopy (FT-IR) confirmed that CaCl2 could promote the formation of hydrogen bonds and increase the stability of proteins. The changes of secondary structure of nisin with CaCl2 was revealed by circular dichroism (CD) spectroscopy. At pH 4.0, the proportion of α-helix, β-sheet and β-turn were same as to that of pH 2.0 without CaCl2. At pH6.0, the proportion of secondary structure changed a little by heat treatment. This indicated that the addition of CaCl2 protected the secondary structure of nisin.
Analysis on the causes of water contaminated by toxic and harmful substances in the Yangtze River Delta
Authors: Yuan Sheng-Yu 
Published: March 2021

Abstract
In recent years, with the rapid development of economy in the Yangtze River Delta, the water pollution are becoming more and more serious. The expansion of urban agglomeration also makes water pollution show significant regional and complex nature. This paper takes water quality of the Yangtze River Delta as an example, the toxic and harmful substances such as ammonia nitrogen, petroleum, volatile phenol and cyanide discharged from waste water were analysed, which has led to increasing attention being paid to the phenomenon of water contaminated by toxic and harmful substances. The causes of water pollution in the Yangtze River Delta are considered to solve the problem of subsequent pollution control. In conclusion, this paper analyzed the causes of water pollution in this area from the angles of geographical environment, legal system, economic development model and so on, and expected to provide the basis for water pollution control.
Study of the characteristics of the synchronization algorithm for a quantum key distribution system based on comparing the number of samples from an adjacent pair of time windows with a threshold level
Authors: Mironov Y K , Mironova P D , Rumyantsev K E 
Published: March 2021

Abstract
The analysis of time and probabilistic characteristics is carried out for a two-stage synchronization algorithm in a quantum key distribution (QKD) system with automatic compensation of polarization distortions. Formulas are obtained for calculating the missing probabilities a signal pair of windows, false alarm and successful synchronization. The dependences of the missing probability a signal pair on the average number of photons and noise pulses are investigated during the analysis of a pair of windows for different threshold levels. The numerical material obtained in the course of the study indicates the possibility of using for express calculations the probability of detecting a signal pair of windows formulas oriented to the normal distribution of the number of recorded pulses at the output of a single-photon avalanche photodiode.
A method for transmitting information based on the stochastic use of binary quasi orthogonal code sequences
Authors: Zhuk A P , Orel D V , Pashintsev V P , Kalmykov I A 
Published: March 2021

Abstract
The objective of the article is to develop the structure of a system for transmitting information with code division of channels and stochastic usage of systems of binary quasiorthogonal code sequences obtained on the basis of functional transformations of pseudo-random arguments, as well as a description of the principle of its functioning. The aim of the article is to develop a method for transmitting information in satellite communication systems and global navigation satellite systems with code division of channels and stochastic usage of binary quasiorthogonal code sequences obtained on the basis of functional transformations of pseudo-random arguments, providing an increase in structural secrecy. The elements of novelty are obtaining a new structure of an information transmission system with code division of channels and increased structural secrecy, as well as a description of the main stages of the information exchange method based on this system. The method differs from the known ones by stochastic use of binary quasi-orthogonal code sequences obtained on the basis of functional transformations of pseudo-random arguments. The main result of the article is that the presented method of information transmission makes it possible to reduce the impact of deliberate imitating interference and cases of substitution of the signals used by increasing the structural (signal) secrecy of the information transmission system with code division multiplexing and stochastic usage of systems of binary quasi-orthogonal code sequences.
Detection of compromising radiation from modern data transfer interfaces using the example of high definition multimedia interface
Authors: Durakovskiy A P , Kessarinskiy L N , Simakhin E A 
Published: March 2021

Abstract
Recently the technical channel of information leakage from electromagnetic emanation more and more interesting for specialists in the field of information security. At the same time, new versions of data transfer interfaces are being developed, that quickly distribute around the world. The use methods to detecting informative frequencies are based on the principles of operation of old data transfer interfaces, consider only the harmonics of the signal, excluding information about its type and interfaces that transmit information to. Accordingly, these methods to detecting informative frequencies of modern data transfer interfaces, such as high definition multimedia interface, do not reflect the completeness and may contain errors, which negatively affects the measurement stage. The article suggests a method to detecting informative signals of compromising emanation from modern data transmission interfaces, such as high definition multimedia interface, using an anechoic chamber, special test program and control program for measuring equipment. The proposed method will be useful both for educational purposes and for beginners in the field of technical information security.
Parallel implementation of algorithm for creating and verifying digital signature based on elliptic curves
Authors: Burtseva P T , Zelenina L I , Khaymina L E , Khaymin E S , Zashikhina I M 
Published: March 2021

Abstract
The article discusses the use of parallel data processing in the implementation in the C ++ programming language using the Visual Studio integrated development environment of an algorithm for information protection and authentication. Data processing is based on the method of discrete logarithm in a group of points of an elliptic curve. The studied case has been developed as Cost Optimization Program for an Oil and Gas Company and includes creating an Optimization Map information system. A part of the system is a module generating and verifying a digital signature. Due to the use of parallel data processing and the ECDSA algorithm for digital signature creation, oil and gas company will be able to increase its working efficiency and information security.
Methods for Modeling Sociopolitical Processes to Address Issues of Integrated Security in Caspian Region
Authors: Markelov K A , Azhmukhamedov I M , Yu Kuznetsova V 
Published: March 2021

Abstract
The article dwells on the issue of ensuring integrated security in the Caspian region. It was noted that this region, due to its geographical location, is strategically important for the implementation of Russia’s internal and foreign policy, so any changes in it should be carefully thought over and analyzed for possible consequences. To address the issues of ensuring integrated security, the authors considered the main methods for modeling social and political processes that can be applied to simulate the consequences of specific managerial decisions in the Caspian region.
Algorithm for predicting the health of an information system after exposure to cyberattacks
Authors: Dushkin A V , Kochedykov S S 
Published: March 2021

Abstract
The presented work proposes a systematic approach to the development of software for cyberattack detection systems and predicting the health of the information system. A formalized descriptive model of an intrusion detection system is presented. A complex of models is described that allow making diagnostic decisions about the state of software performance.
On the using Datamessage as evidence of Cybercrime
Authors: Zharova A , Elin V 
Published: March 2021

Abstract
The article reveals a number of features of using computer data in cybercrime cases. The contradictions between the European and Russian approaches to the question of the equivalence of an electronic document and a paper document are considered. The authors reflect the problem of using an electronic document as evidence in criminal cases in compliance with the principle of admissibility of evidence in the fight against cybercrime. The paper concludes that there is a need for comprehensive legal and technical regulation of the field of IT relations.
Software model for the synthesis of increased volumes of systems of discrete orthogonal code sequences
Authors: Studenikin A V , Zhuk A P 
Published: March 2021

Abstract
To ensure high structural secrecy of information transmission systems with MA and CDM, it is necessary to use many ensembles of stochastic discrete orthogonal code sequences differing from each other. The purpose of the article is to develop a program for studying the correlation and statistical characteristics of ensembles of stochastic discrete orthogonal sequences described by the eigenvectors of symmetric matrices, with random filling of the diagonal coefficients. Assessment of the statistical and correlation indicators of sequence ensembles obtained on the basis of the developed program showed their random nature.
Development of an algorithm for abnormal human behavior detection in intelligent video surveillance system
Authors: Zh Satybaldina D , Glazyrina N S , Kalymova K A , Stepanov V S 
Published: March 2021

Abstract
The aim of the work is to develop algorithms for analyzing video data in real time based on computer vision methods, as well as deep learning technologies for artificial neural networks for abnormal human behavior recognition near critical facilities using ATMs as an example. The article provides an overview of the initial research aimed at the choice of data capture devices, neural network architecture, software implementation and selection of experimental conditions (distance and illumination). Static and dynamic hand gestures were used as object’s movements. Experimental results show that using the Intel RealSense D435 Depth Camera provides more accurate dynamic gesture recognition under different experimental conditions.