bluuebunny/crossref_metadata_2025_split huggingface dataset:
SSP-Structure of k-Sun Flower, Friendship and Jahangir Graphs
Authors: Mary Jeya Jothi R , Revathi R , Angel D 
Published: April 2021

Abstract
A graph is SSP (Super Strongly Perfect) if all of its (induced) subgraph H in G obsesses a (minimal dominating set) MDS that link up all of its cliques (maximal) in H. It is offered the cyclic structure of k-sun flower graph, friendship and Jahangir graphs and later explored their SSP parameters like counting of colourability, MDS (minimal dominating set) and cliques (maximal) of these graphs.
Modelling and Reliability Analysis of Power Cables Used as a Two Unit Hot Standby System with Preference of Repair over Replacement in the Metro Railways
Authors: Pandey R , Parashar B , Khemchandani V , Pandey P , Bhardwaj N 
Published: April 2021

Abstract
In this study we aim to do an analysis of the profitability and reliability of a system used primarily in Metro Train Networks consisting of a power cable rated for 33KV. The wires for the feed to each substation are laid in loops. As a starting point, two cables of the same voltage are laid with one being operational and another being a hot standby for backup. The moment the primary operational cable fails the backup cable immediately becomes operational. In the situation of a cable failure, it is considered if repairing the damaged cable can be done as opposed to repairing it. The moment both the operational as well as the back-up cables fail, the system is brought to a complete halt. Cable failures are categorized in two groups viz. irreparable failures & repairable failures. Regenerative Point Technique & Semi-Markov Processes are the methodologies used to derive the data that depicts real-failure situations or any other parameters of system effectiveness. This analysis is being done to enable multiple cases to detect and realize essential profit-analysis results for the system in question.
A Hybrid Model Approach for the Prediction of Rainfall
Authors: Mallika M. , Nirmala M. 
Published: April 2021

Abstract
For maintaining the atmospheric balance, precipitation is very much helpful. Rainfall is one of the forms of precipitation Though excess rainfall causes several damages to the earth in various ways, it is considered very precious as it is one of the essentials for the existence of human beings. As a result, a prediction of rainfall also forms a major part in planning things. This paper proposes a new hybrid model Moving average-kNN for doing the prediction. Error measures Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) have been used for the validity of the model.
Leaf Classification Based on Convolutional Neural Network
Authors: Wu Peng , Qian Zhou 
Published: April 2021

Abstract
Convolutional Neural Network (CNN), a very important neural network structure in deep learning, is a network model often used in image classification, target recognition and other fields. In botany, leaf classification and recognition is very important for identifying new or scarce tree species. In nature, plants are widely distributed, and the survival and development of all living things on the earth depend on plants. Identification of species by leaves and related research are of great help to the study the evolution law of plants, the protection of plant species and the development of agriculture. This paper uses convolutional neural network in artificial intelligence to identify the leaves of several kinds of trees collected by Kunming Institute of Botany, Yunnan Province, which can realize the automatic extraction of leaf image features, reduce tedious labor costs, and realize the use of artificial intelligence to classify leaves, thus providing an auxiliary means of artificial intelligence for botany research.
High Value Bit Model Reconstruction and Damage Identification Based on Binocular Robot
Authors: Yan Jingsen , Hao Weidong , Yang Daoguo , Wang Ruiqing 
Published: April 2021

Abstract
In order to achieve high value bit repair, bit model reconstruction and damage identification must be carried out. In this paper, the binocular camera and the industrial robot were combined to realize the point cloud acquisition, model reconstruction and damage identification of the bit. The bit damage data obtained by this method was applied to the repair experiment of the bit and the repaired bit met the requirements of re-use.
Research on Database Programming Technology in Computer Software Engineering
Authors: Quan Zhi , Pu Caiyun 
Published: April 2021

Abstract
With the continuous progress of economy and society and the development of science and technology, the application of computer has entered all aspects of people’s life, integrated into various industries, and then promoted the development of the industry. The core technology in computer technology is mainly computer software engineering, while the core technology in computer software engineering is database programming technology.Therefore, a large number of software staff are needed to study this, so as to promote the continuous progress and sustainable development of database programming technology.
Research on high security of IP tunnel in virtual private network
Authors: Gan Weimin , Yin Xiaogui 
Published: April 2021

Abstract

IPSec encrypts and authenticates the packets of IP protocol. Both sides of IP network layer communication use encryption authentication, data source authentication and integrity verification to ensure the integrity, confidentiality and anti replay of IP protocol packet transmission. In enterprise network management, we can usually use IPSec VPN technology to establish a secure channel to realize the secure communication between headquarters and branches.[1]
Research on Key Technologies of Intelligent Operation and Maintenance of Communication Network
Authors: Wang Lu , Zhao Yu , Chen Zhikun 
Published: April 2021

Abstract
Based on the analysis of the challenges faced by the operation and maintenance of communication network, this paper studies the intelligent operation and maintenance architecture of communication network. Using the accumulated massive communication network operation and maintenance data, the research explores the high-speed calculation of intelligent algorithm, rapid splicing of demand components, multi-dimensional visual interaction and other technical methods to effectively deal with the problems such as the surge of business volume, the difficulty of event handling, and the lack of personnel training. Research on key Technologies can ensure the safe and stable operation of information and communication network.
Improve Visual Question Answering Based On Text Feature Extraction
Authors: Wang Jing , Dong Yang 
Published: April 2021

Abstract
VQA requires the machine to be able to answer questions related to the image based on the image. VQA is mainly divided into four modules: text extraction module, image extraction module, text-image feature fusion module and answer prediction module. In this paper, the most mainstream VQA2.0[1] data set is selected for experiment, and the text extraction module is improved on the basis of a baseline model. The Glove vector is used to preprocess the problem text data, and the GRU network replaces the traditional LSTM network encoding and processing text vector. Experimental results show that the improvement of the text extraction module improves by 2.42% on the basis of the original model, and the GRU network can also accelerate the training speed.
Research on network information security penetration test based on IP port service technology
Authors: Wang Xiaoyu , Li Dandan 
Published: April 2021

Abstract
Network information security penetration test is an important means to intercept network information attacks after obtaining user authorization. At present, various network information security penetration testing technology system research work is also constantly improving and updating. However, due to the increasingly complex verification of hacker behavior, the research of network information security penetration test is still difficult to meet the requirements of the current information development. In this environment, this paper proposes a network information security penetration test method based on IP port service technology, and describes a set of penetration test ideas, steps and results, for network managers to reference, to achieve the network information security penetration test Finally, it was confirmed by experiments, The efficiency and ability of penetration test are improved, and the process of penetration test is optimized.
Distributed authentication scheme for Industry Internet Platform application based on consortium blockchain
Authors: Yan Min , Huang Haibo , Yang Shuaifeng 
Published: April 2021

Abstract
With the rapid development of industrial internet services, the integration of IT/OT has enabled the continuous expansion of network security boundaries and put forward higher requirements for platform application cross-domain identity authentication. Aiming at the insufficient security of existing user-centric identity authentication schemes, this paper proposes a distributed authentication scheme based on the consortium blockchain in industrial Internet platform. The solution analyzes its applicability to the Industry Internet Platform from three perspectives: network architecture, industrial Internet platform user identity control, and user privacy. It defines the identity composed of consortium ID and consortium digital identity credentials, and builds distributed authentication architecture. The consortium blockchain is used to record the digital identity information of the industrial Internet platform users, and the consortium ID and the consortium digital identity credential are designed to realize the industrial Internet platform business securely access.
Research on Structure Data Link Detection Method Based on Internet of Things System
Authors: Yu Wenwu , Zhai Yue , Guo Yang , Ji Meijiao 
Published: April 2021

Abstract
In order to improve the fault diagnosis and analysis capabilities of the cyber-physical system in the Internet of Things, it is necessary to detect and identify the vicious data chain of the cyber-physical system in the Internet of Things. Moreover, to realize the detection and identification of the vicious data link in the cyber-physical system in the Internet of Things, a fast extraction algorithm for the vicious data link of the cyber-physical system in the Internet of Things is proposed in the paper to collect vicious data from the cyber-physical system in the Internet of Things. In addition, the malignant data generated during the factor adjustment of the Internet of Things can be divided into periodic structure and non-periodic structure in structure, and the malignant data sensor network model of the cyber-physical system in the Internet of Things is constructed. Therefore, through simulation experiment analysis, the method proposed in the paper has superior performance in the detection and identification of vicious data links in the cyber-physical system of the Internet of Things.
Application and Practice of VR Technology in Basic Computer Teaching in Art Colleges
Authors: Liu Juan 
Published: April 2021

Abstract
In the process of basic computer teaching in art colleges, the use of virtual reality technology can improve the efficiency of basic computer teaching and ensure the quality of teaching. At present, virtual reality technology is also constantly maturing and improving. The full application of virtual reality technology in the basic computer teaching of art colleges is conducive to saving teaching costs. This can not only give full play to the application value of virtual reality equipment, but also reduce the loss caused by teachers’ continuous operation in the teaching process, and improve the teaching effect. However, it should be noted that in the process of basic computer teaching in art colleges, there are also some problems in virtual reality technology. We need to conduct in-depth research and analysis on these problems. This article discusses the practical strategies of virtual reality technology in the basic computer teaching of art colleges, hoping that these strategies can really improve the basic computer teaching level of art colleges.
Research on spectrum scheduling based on discrete artificial bee colony algorithm
Authors: Xiao Ying , Chen Dianjun , Zhang Lu Yong 
Published: April 2021

Abstract
With the increasing shortage of spectrum resources on the earth, how to ensure the high-quality transmission of satellite wireless signals to the ground has become one of the most important problems in the current satellite ground communication system. In order to schedule spectrum resources more reasonably and efficiently, we propose a spectrum resource scheduling model based on adaptive chaotic distributed differential artificial bee colony algorithm. The algorithm uses chaotic distribution to generate initial solution. In the search phase, differential evolution strategy and artificial bee colony algorithm are used to work in parallel to find the local optimal solution. The selection operator is used to calculate the probability of selecting new bee sources, which improves the reliability and convergence speed of the algorithm. Finally, the results show that in single-channel and multi-channel scenes, the algorithm can help to improve the fairness and throughput.
Bridge defect detection technology based on machine vision and embedded
Authors: Xie Yufei , Ming Sheng 
Published: April 2021

Abstract
In order to improve the degree of intelligence of bridge body maintenance, reduce the consumption of manpower and material resources, and improve inspection efficiency, the technology of machine vision inspection is proposed, and a method of detecting bridge body surface defects and embedded design image transmission and positioning is studied. This paper introduced the existing detection methods and technologies of bridge cracks, and analyzed the detection methods of bridge cracks based on image processing and convolutional neural networks. On the basis of this research, the project collected information and processed and analyzed the cracks on the actual bridge deck, and obtained the image preprocessing results of grayscale, removed background noise, thresholded segmentation, and retained edge information and high-frequency signals. And further, the project used drones to capture image data and used deep learning algorithms to achieve automatic detection of aerial crack images. This scheme can effectively reduce the impact of road background and noise on the detection of bridge surface defects.
Research on Sentiment Analysis Model Due to COVID-19 Using Social Media
Authors: Li Zhijie , Wang Xiaodan 
Published: April 2021

Abstract
Since the outbreak of the disease in early 2020, it has received worldwide attention and become a hot topic of discussion on social media. This paper crawled more than eight billion tweets from the first inflection point of the global outbreak of the epidemic, extracted several prominent hot topics related to the epidemic through two objective and intuitive means, namely LDA model and generated words, and then compared and analyzed the degree of subjectivity and positivity of their tweets for ‘lockdown’, ‘mental health’ and other topics. The experimental results showed that the number and active degree of global Twitter users’ tweets on the above epidemic hot topics were most correlated with the number of newly diagnosed patients after 12 days. Comments are generally more positive to lockdown than to mental health. For all tweets about the epidemic in India and Wuhan, the positive degree of tweets judged as objective was relatively stable, while the positive degree of subjective tweets fluctuated greatly, which verified the rationality and effectiveness of the model for subjective and objective classification. Among the tweets judged as subjective by the model, the positive component of sentiment analysis was more. Most tweets about the epidemic in India and Wuhan were positive, and the fluctuation degree of subjective and objective curves verified the rationality and effectiveness of the model for subjective and objective classification.
Biocompatibility and degradation of the open-pored magnesium scaffolds LAE442 and La2
Authors: Kleer-Reiter N , Julmi S , Feichtner F , Waselau A-C , Klose C , Wriggers P , Maier H J , Meyer-Lindenberg A 
Published: April 2021

Abstract
Porous magnesium implants are of particular interest for application as resorbable bone substitutes, due to their mechanical strength and a Young’s modulus similar to bone. The objective of the present study was to compare the biocompatibility, bone and tissue ingrowth, and the degradation behaviour of scaffolds made from the magnesium alloys LAE442 (n= 40) and Mg-La2 (n = 40) in vivo. For this purpose, cylindrical magnesium scaffolds (diameter 4 mm, length 5 mm) with defined, interconnecting pores were produced by investment casting and coated with MgF2. The scaffolds were inserted into the cancellous part of the greater trochanter ossis femoris of rabbits. After implantation periods of 6, 12, 24 and 36 weeks, the bone-scaffold compounds were evaluated using ex vivo µCT80 images, histological examinations and energy dispersive x-ray spectroscopy analysis. The La2 scaffolds showed inhomogeneous and rapid degradation, with inferior osseointegration as compared to LAE442. For the early observation times, no bone and tissue could be observed in the pores of La2. Furthermore, the excessive amount of foreign body cells and fibrous capsule formation indicates insufficient biocompatibility of the La2 scaffolds. In contrast, the LAE442 scaffolds showed slow degradation and better osseointegration. Good vascularization, a moderate cellular response, bone and osteoid-like bone matrix at all implantation periods were observed in the pores of LAE442. In summary, porous LAE442 showed promise as a degradable scaffold for bone defect repair, based on its degradation behaviour and biocompatibility. However, further studies are needed to show it would have the necessary mechanical properties required over time for weight-bearing bone defects.
Machine Learning Based Model to Predict Stock Prices: A Survey
Authors: Harikrishnan R , Gupta Aksh , Tadanki Namrata , Berry Ninad , Bardae Ramya 
Published: April 2021

Abstract
In this survey paper, we provide the findings obtained from extensive reading of 35 research papers that span the financial domain (specifically the Stock Market) as well as explore various Machine Learning algorithms and offer a comparative analysis of the same. Through this, we observed that there is a general preference towards Technical Indicators and how a new trend of using Hybridized Indicators is emerging. We also show that Support Vector Machines have been constantly preferred due to their ability to handle complexity but new alternatives like Auto Regressive Integrated Moving Average and Long-Short Term Memory models are on the rise.
Evaluation of trapping parameters of europium doped tristrontium dialuminium oxide phosphor by different thermoluminescent analysis methods
Authors: Jha Piyush , Khare Ayush 
Published: April 2021

Abstract
In the present work, we have synthesized Europium (Eu) doped Tristrontium Dialuminium Oxide (Sr3Al2O6:Eu) phosphor by solid state reaction method in air atmosphere. The thermoluminescence (TL) properties of the synthesized phosphor are investigated and presented. Theoretical analysis of glow curves of Sr3Al2O6:Eu was done by computerized glow curve deconvolution (GCD) method, and the trapping parameters of the synthesized phosphor, such as activation energy, frequency factor, order of kinetics, etc. are discussed and explained. These trapping parameters are determined by different methods, such as Chen’s peak shape method, initial rise method, and Ilich method. The synthesized phosphor is found to be a good candidate for dosimetric applications.
Adsorption isotherms and kinetics study for U(VI) removal by excellent sorbent materials graphene oxide and functionalised graphene oxide
Authors: Patel Khilawan , Sutar Alekha Kumar , Maharana Tungabidya 
Published: April 2021

Abstract
In this paper, the graphene oxide (GO) and carboxylic functionalized graphene oxide (COOH-GO) were synthesized for the removal of U(VI) ion in samples of water. The structures of prepared GO and COOH-GO were confirmed by X-ray diffraction (XRD), Scanning electron microscope (SEM), Fourier transformed infrared (FTIR) spectroscopy, Raman spectra, and high-resolution transmission electron spectroscopy (HR-TEM). An adsorption study was carried out for these and it has been found that COOH-GO has more excellent adsorption property at 4.5 pH. The batch adsorption was studied successfully by the effect of initial uranium concentration, pH of the medium, sorbent dose, temperature, and contact time efficiency. The adsorption isotherms were studied successfully for Langmuir and Freundlich. The kinetics were studied successfully and fitted for the pseudo-first-order and pseudo-second-order model. The maximum adsorption capacities at pH 4.5 were calculated for COOH-GO, GO, and graphite. The thermodynamic studies revealed that adsorption is endothermic and spontaneous.
Effect of cadmium sources on the structural, morphological, and optical properties of CdS films for solar cell applications
Authors: Sinha Tarkeshwar , Verma Lekha , Khare Ayush 
Published: April 2021

Abstract
The variations in the structural, morphological, and optical properties of three CdS films deposited with different cadmium ion sources namely cadmium acetate, cadmium chloride, and cadmium sulfate are reported in this article. All three CdS films possess cubic crystalline structure with the most prominent cubic phase (111). The CdS film deposited with cadmium acetate showed the best crystallinity among them. The presence of both Cd and S with a difference in the percentage of its existence depending upon the type of cadmium source chosen is obtained in the elemental analysis of the CdS films. CdS film deposited from acetate based chemical solution exhibited broad transmittance behaviour in the visible wavelength region due to its superior surface morphology. The energy band-gap values for CBD-CdS films deposited with cadmium acetate, cadmium chloride, and cadmium sulfate are found as 2.30eV, 2.23eV, and 2.32eV, respectively. The film deposited with cadmium acetate showed better IR response and more intense PL emission peaks as compared to the other two films. The efficiency of the CdTe/CdS cell fabricated with CdS window layer deposited with cadmium acetate is found to be 10.02%.
Effect of pH on structural, optical, and morphological properties of ED-CdTe film
Authors: Verma Lekha , Khare Ayush 
Published: April 2021

AbstractCadmium telluride (CdTe) thin films have been deposited by electrodeposition (ED) technique on fluorine doped tin oxide (FTO) coated glass substrates using an aqueous electrolyte bath solution. The pH-value of the electrolyte solution is one of the most important deposition parameter that should be optimized to achieve high quality photoconductive material. The films have been deposited at different pH values ranging from 1.5 to 3. The structural, optical, and morphological properties of the samples were characterized using X-ray diffraction (XRD), UV– Visible (UV-Vis) spectroscopy, spectroflurophotometer, scanning electron microscopy (SEM), and energy dispersive X-ray analysis (EDX) techniques respectively. The XRD analysis shows that the ED-CdTe films possess the cubic crystalline structure and the diffraction peak intensity increased significantly after changing the pH values. The direct energy band-gap (Eg=1.44eV) is obtained in optical absorption spectra. The SEM analysis shows very good morphological growth by changing the pH values and the film deposited with lower pH showed more intense PL emission peaks as compared to the other two films. CdTe film deposited at pH 1.5 will be better choice as an absorber layer of a CdTe/CdS solar cell.