bluuebunny/crossref_metadata_2025_split huggingface dataset:
Theme Evolution of Researches on Knowledge Graphs Based on Visualization Analyses of Data
Authors: Chen Kejun , Xie Boyang , Deng Sanhong 
Published: February 2021

Abstract
The knowledge graph, as a significant branch of Library and Information Science, has also become a vital part of Computer Science. In a bid to reveal the research trend and hot topics of the knowledge graph domain, this paper collected latest data about literature on knowledge graphs from SCI-Expanded and EI Compendex database. This paper took advantage of Citespace for visualization analyses of data, which discerned the research topics, hot issues and theme changes of the knowledge graph domain over time. Through analyses, we conclude that the knowledge graph has developed greatly in both Library and Information Science and Computer Science. In Library and Information Science domain, researches focus on the issues like the plotting of knowledge graphs and visualization of knowledge. In Computer Science domain, hot issues are the techniques of constructing knowledge graphs, which include entity recognition, knowledge integration, etc., and their applications in Semantic Web. Among all the research topics, the domain knowledge graph is one of the paramount research trends. Compared with previous researches, this paper keeps up with the times and can reveal the theme evolution of researches on knowledge graphs more precisely.
Application of Collaborative Filtering Personalized Recommendation Algorithms to Website Navigation
Authors: Wu Hao 
Published: February 2021

Abstract
This article builds a personalized management and push design for the functional and performance requirements of website personalized recommendations. The system uses PHPstorm as the development platform and Hadoop distributed file system combined with DBMS design algorithm to achieve data level research, and uses a combination of customer-based collaborative filtering and project-based collaborative filtering to categorize clients and web pages in personalized recommendation, which improves the calculation and personalization of website navigation to a certain extent.
Technical Route and Application Data Analysis of New Energy Vehicle
Authors: Wang Zhibin , Zhang Shouzhen , Yan Jian , Pan Xiaobing , Xiang Chengxuan , Xu Jiafeng 
Published: February 2021

Abstract
With the gradual depletion of fossil fuels and the increasingly severe form of environmental protection, data analysis shows that the new energy vehicle industry has become the future industry competing for development all over the world. China has also established the development strategy and goal of the new energy vehicle in the future. This paper analyzes the technical route and application data of new energy vehicle and puts forward the development strategy of new energy vehicle industry in view of the current situation and existing problems of the development of new energy vehicle in China. It is necessary to strengthen the formulation of national standards for energy vehicle industry, pay attention to core technology breakthroughs and parts research, improve infrastructure construction, constantly improve the business promotion mode, so as to promote the rapid development of new energy vehicle industry in China.
Research on Intelligent Route Planning Based on Ant Colony Algorithm
Authors: Li Haiying 
Published: February 2021

Abstract
In this paper, we propose a zoning plan for reasonable travel time for self driving travelers. There are 201 5A scenic spots in the country. Travelers who want to visit all scenic spots in the face of many time constraints need to optimize travel routes to ensure maximum travel income. Based on this idea, an optimal path analysis based on ant colony algorithm is proposed. After considering time constraints, the time window constraint is transformed into a target function. Constraint, the hard time constraints which must satisfy the limit of driving time limit and the limit of the opening time of the scenic spots are transformed into soft constraints, and the improved ant colony algorithm is used to iterate.With the help of the improved ant colony algorithm, the optimal path selection satisfying the time constraint is obtained. Taking Jiangsu Province as an example, this article draws a tourist route map of Jiangsu province.
Regional Credit Environment Evaluation Based on Analytic Hierarchy Process (AHP) Method and Fuzzy Comprehensive Evaluation (FCE)
Authors: Xie Hengxin , Ma Jun , Fu Xiaoran , Tian Yuanjun 
Published: February 2021

Abstract
Taking the data of the sixteen prefecture-level cities in Shandong Province as an example, this paper attempts to construct regional credit environment indicators and quantify these indicators. The Analytic Hierarchy Process (AHP) method and Fuzzy Comprehensive Evaluation (FCE) have been used to empower the indicators. Meanwhile, this paper has obtained the AHP score through calculation. The corresponding credit ranking has been given using the factor analysis. The research result shows that the credit environment evaluation scores of Shandong eastern coastal cities centered on Qingdao and neighboring cities centered on provincial capital Jinan are often higher than those of inland cities such as southwestern Shandong and northwestern Shandong. The construction of regional credit environment should be based on economy, culture and government. Three aspects go hand in hand. On this basis, this paper puts forward the feasible countermeasures and suggestions for constructing regional credit environment from the perspective of policy.
A Long Short-Term Memory Network-Based Intrusion Detection Method for Power Grid Middle Platform
Authors: Ding Zhengyang , Wang Jijun , Cheng Yiqing 
Published: February 2021

Abstract
The power grid middle platform data has the feature of time-correlation, high dimensionality, and susceptibility to external factors. Based on the inherent characteristics of the power data and the theory of Long Short-Term Memory networks (LSTM), this paper proposed a stacked-LSTM based intrusion detection algorithm for power grid middle platform data. Technically, the strategy of constructing a dataset with replacement is adopted firstly, thus K sets of data is constructed. Then, a three-layer LSTM network is employed to conduct the feature extraction of high-dimensional data. Meanwhile, a two-layer fully connected hidden layer is used to generate a neural network and achieved user feature data matching. The high probability events are used to classify the node that appears the most in the results of the K data sets. Finally, experiments on real dataset proved that compared with traditional algorithms, the proposed algorithm has improved detection accuracy while reduced false alarm rates.
Distance Measurement Method for Obstacles in front of Vehicles Based on Monocular Vision
Authors: Gao Weiyue , Chen Yutuo , Liu Yang , Chen Biao 
Published: February 2021

Abstract
This paper proposes a new method based on monocular vision to detect and range obstacles in front of the vehicle for anti-collision warning during driving. Firstly, the deep learning object detection YOLOv4 algorithm is used to detect various obstacles in front of the vehicle to obtain the category and location information of the obstacles. Then an improved edge detection algorithm is used to adjust the position of the detection frame to improve the object positioning accuracy of the detection algorithm. Next, according to the camera imaging principle and geometric relationship, conversion model from the three-dimensional coordinates of the road surface to the two-dimensional coordinates of the image plane is obtained and distance measurement is performed. Finally, the cubic curve fitting of the obtained measurement data is performed, and the distance measurement process and algorithms are optimized to improve the distance measurement accuracy. The average error in the range of 50m is 0.54m, and the average error in the range of 80m is 0.78m. Through experimental analysis and comparison, the results show that the method in this paper can achieve accurate and effective monocular vision ranging.
A Clock Synchronization Algorithm for the Satellite System Based on MF-TDMA
Authors: Zhang Min , Duan Linlin , Gong Kexian , Liu Xiaoyan , Cheng Qian 
Published: February 2021

Abstract
In order to ensure microsecond slot scheduling, all terminals must maintain high precision of time synchronization in MF-TDMA(Multi-Frequency Time Division Multiple Access) satellite communication system. Due to the different frequency of crystal oscillator at the terminal, the absolute value of the clock deviation is constantly increasing, so a clock synchronization algorithm is required to keep the time synchronization of the satellite system. The traditional satellite clock synchronization algorithm minimizes the clock error through periodic synchronization, but it only considers the phase offset, not the crystal frequency offset, the synchronization accuracy is low and waste of bandwidth resources. Based on the traditional satellite clock synchronization, this paper proposes a gradient descent algorithm for the satellite system based on MF-TDMA(GDAS), adding clock frequency offset prediction and compensation mechanism to improve clock synchronization accuracy and bandwidth resource utilization rate. The simulation results of the proposed algorithm has optimized the precision performance of clock synchronization.
A Low Noise 28Gbaud/s Linear PAM4 Receiver Front-End for Optical Communication Applications in 0.13μm BiCMOS Technology
Authors: Li Ming , Chen Yingmei , Hu Junpeng , Guo Chao 
Published: February 2021

Abstract
This paper presents a low noise 28 Gbaud/s linear receiver front-end for fourth-order pulse amplitude modulation (PAM4) signal applied in the field of optical communication. The designed receiver front-end includes a transimpedance amplifier(TIA), an automatic gain control (AGC) and a DC offset cancellation (DCOC) circuit. The pseudo-differential structure of the TIA is designed to achieve low noise. The resistance and capacitance degradation technology are introduced in the variable gain amplifier(VGA) and the equalizer(EQ) to improve linearity and optimize the bandwidth. In the AGC mode, the feedback loop controls the output amplitude to be a desired value within a large range of input current. The PAM4 optical receiver front-end achieves a maximum differential transimpedance gain of 76 dBΩ and -3dB bandwidth of 27 GHz. The equivalent input noise current density with the front-end circuit is

11.2

pA
/

Hz

. In 0.13µm BiCMOS technology, the PAM4 front-end chip consumes 200 mW with a 3.3V voltage supply.
A0 Mode Excitation and Defect Detection in Aluminum Beam Structure
Authors: Li Ziming 
Published: February 2021

Abstract
As a method to realize the defect detection in beam structure, this paper constructs an EMAT-laser detection system to detect the notch defect in an aluminum beam. EMAT is designed as a transmitter to generate single Lamb wave mode. A high precision laser detector is used as a receiver to obtain the received signals. The defect is localized and quantified with the help of space-frequency-wavenumber analysis. The evaluated depth of the defect is 2.006 mm, while the actual size is 2 mm. It shows good agreement between the evaluated result and actual size, the error is only 0.3%. This method also can be used in the evaluation of defect in other materials.
A Yokeless Axial Flux Induction Motor for Electric Vehicles Based on Grain-oriented Silicon Steel
Authors: Huang Pinglin , Li Hang , Yang Chen 
Published: February 2021

Abstract
A novel axial flux induction motor is proposed as the driving machine for electric vehicle, the motor consists of two rotors and one yokeless stator. Benefit from this structure, grain-oriented silicon steel can be used to reduce the weight and improve efficiency. The present paper provides the basic topology of the motor, discussing the design method and analyzing the performance. A prototype is designed, considering the 3D finite element method is time-consuming and inefficient, analytical calculation method is deduced to calculate the performance of the prototype, the results agree with those obtained by finite element calculation, that verifies the effectiveness of this method.
FACTORS AFFECTING THE EFFECTIVENESS OF MAINTENANCE IN POSTGRADUATE HOSTELS IN HIGHLY RANKED NIGERIAN UNIVERSITIES
Authors: Osazuwa O.N. , Iroham C. O. , Oluwunmi A. O. 
Published: February 2021

Abstract
This paper examined factors affecting efficient maintenance of postgraduate hostels in highly ranked Nigerian Universities. The study population consists of selected top-ranked universities in south-western Nigeria according to times higher education ranking year 2020 namely: Covenant University, University of Ibadan and University of Lagos. The sample size was made up of 120 students, 40 selected from each institution based on convenient sampling techniques. A well self-structured questionnaire was administered as an instrument to collect relevant data appropriate for the survey. Out of the 120 questionnaires distributed, the entire 120 were retrieved. The aim of this paper is to determine the major factors that affect efficient maintenance in Postgraduate hostels. The study which is a survey collated data that were analyzed using descriptive statistics on an excel spreadsheet with the aid of the SPSS software. The findings showed that response time is a major factor that affects efficient maintenance in the hostels which could affect students comfort. The study recommends that the universities should create a special facility management office in each of the postgraduate halls of resident’s order than the existing facility management team and employ facility management professionals. That way, students will conveniently have easy access to the team so as to lay their complaints. The university management should also create an electronic customer service platform for laying down complaints and collecting feedback for progress of work done, while evaluation of Student’s occupancy should be a routine exercise.
Knowledge management capabilities -an empirical investigation
Authors: Ogunbanwo A. S. , Okesola J. O , Sheryl Buckley 
Published: February 2021

Abstract
Many authors have worked on the impacts of KM in business sector but very few on its influence on academic performance (AP). The studies on KM concept and its applications suggested that both process capability and strategy capability could drive innovation and improve institutional performance. However, these studies were not empirically validated thereby subjecting their findings to dispute. Grouping KM Capabilities into three, and adopting Survey method where questionnaires were administered to extract data from 10 Nigerian universities, this study empirically examines the relationship amongst the KM capabilities components and their influence on AP. SPSS was used to the data. Frequency and percentage count were used to analyse the demographic data while factor analysis, Pearson correlation and multiple linear regression were used for the hypotheses. The results showed that there is a significant relationship amongst the KM capabilities components and that a positive linear relationship exists between the KM capabilities and the key AP indicators thereby suggesting that KM capabilities has a positive influence on AP. Nigerian institutions are to be giving more attention to Enabler Capabilities which proved to be the most influencing factor amongst the indicators.
Seasonal surface refractivity patterns in the part of Lagos-Nigeria
Authors: Emetere M.E. , Afolalu S.A. , Abodunrin T.J. 
Published: February 2021

Abstract
The surface refractivity(SF) is essential in estimating the performance of terrestrial radio links. In the troposphere, there are lots of meteorological updraft and downdraft that influence the refractive index. In this study, we examine the seasonal variation of an emerging community in Lagos to design a reliable and efficient radio communication system based on the meteorological parameters.Thirty-nine years dataset between 1980-2018 was used to examine both the surface refractivity and the meteorological drivers that determine the SF patterns. It was observed that early wet season and late dry season were seen to have higher SF values, i.e., 262.03 N-unit and 262.07 N-unit respectively, while early dry and late wet had lower SF, i.e., 261.71 and 261.76 respectively. It is now possible to use the weather forecast to predict the likely SF pattern over the tropics.
Assessing Transportation Logistics for White Shrimp (Nematopalaemon hastatus) Marketing Using ArcGIS Network Analysis
Authors: Omobepade B. P. , Adelabu S. , Okello T. , Adagbasa E. 
Published: February 2021

Abstract
This study assessed transportation logistics for prospective consumers and marketers of white shrimp (Nematopalaemon hastatus) within a 500 km buffer to processing and marketing areas in Ondo State, Nigeria using ArcGIS network analyst tool. The result indicated that shorter routes between the towns and major shrimp market at Igbokoda provided buyers with a lower budget for logistics and product cost compared with higher budget computed for longer routes between the towns and Ugbonla waterside, Nigeria. However, due to lower price of smoked shrimp at processing areas, shrimp product would get to the towns/cities within the buffer per kilogramme at a lower cost compared to products directly sourced from marketing areas (Igbokoda). Thus a typical consumer/marketer within the buffer was expected to budget an average of $42-$110 (12,810-35,500) and $59-$123 (17,995-37,515) for 10.42kg of smoked shrimp from processing areas in a typical peak and off-peak month respectively. In the alternative, they are expected to budget an average of $50-$110 (15,250-33,550) and $60-$125 (18,300-38,125) to source same quantity of the species from Igbokoda in a typical peak and off-peak month respectively. Developing a shrimp market at Ugbonla waterside, Nigeria would open the community for more economic development and attraction due to easy accessibility to shrimping and processing areas. Therefore, prospective shrimp marketers and consumers within the 500km buffer who are interested in accessing this highly nutritional species and other aquatic products from the processing and marketing areascould be guided by this information for effective trade and marketing.
Comparative Analysis of Machine Learning techniques for Network Traffic Classification
Authors: Jonathan Oluranti , Misra Sanjay , Osamor Victor 
Published: February 2021

Abstract
Network traffic classification is the operation of giving appropriate identification to the every traffic flowing through a network. Several methods have been applied in the past to achieve network traffic classification including port-based, payload-based, behavior based and so on. These methods have been found to one limitation or the other. Nowadays, attention is now on Machine Learning(ML) methods that rely on the statistical properties of the traffic flows generated. However, ML methods do not perform well when confronted with large-scale traffic data having large number of features and instances. Feature selection is employed to remove non-relevant and redundant features before passing the data to ML classifiers. In this study, network traffic classification using ML methods is demonstrated from two perspectives: one that involves feature selection and one that does not. A number of performance metrics are considered including runtime, accuracy, recall, precision and F- score. The experimental results indicate that the classification without features has an average accuracy and runtime of 94.14% and 0.52 seconds respectively. On the other hand, the method with feature selection has accuracy of 95.61% and average of 0.25 seconds for the runtime. The improvement obtained reflects the importance of applying only relevant and non-redundant features to the ML methods. Thus it recommended that feature selection be included in the network classification process to guarantee an optimal accuracy result.
A two-stage coupling process for the recovery of base oils from used lubricating oils
Authors: Ayeni Augustine O. , Tagwai Sarah , Dick Deima T. , Agboola Oluranti , Ayoola Ayodeji A. , Babatunde Damilola E. , Oni Babalola A. 
Published: February 2021

Abstract
This study aims to apply a two-stage solvent extraction and adsorption principles for base oil recovery from used lubricating oils (UBO). Methyl-ethyl ketone was utilized as the solvent for extraction and activated carbon (AC) from unripe plantain peels as the adsorbent. The activities of the solvent to oil proportions from 1:1 to 5:1 on lube oil recovery were analyzed in terms viscosity of the oil, total base number (TBN) of lubricating oil, and percent weight of metallic contents removal from used oil. The results confirm that solvent to oil ratio of 3:1 gave excellent efficiencies relating the UBO to a treated base oil (TBO) with the highest removal of contaminants, increased viscosity, high TBN after the two-stage treatments. The results after solvent extraction at varying temperatures of 30, 45, 60 °C showed the TBN increased to 32% (10.21 mgKOH/g from an initial UBO value of 6.90 mgKOH/g) at 60 °C extraction temperature. After the adsorption stage, the removal of metallic contaminants at the 60 °C extractive temperature and AC 15 wt% loading was 91% for calcium and over 91% for zinc. The optimum solvent to oil ratio of 3:1 at 60 °C yielded a base oil with a kinematic viscosity of 90.23 centiStokes, a flashpoint of 203 °C, the density of 0.909 g/ml and sulphur content of 0.64 wt%. This refined base oil obtained had close similarities with fresh Ram SN500 base oil.
Wireless power transfer: a review
Authors: Okoyeigbo O. , Olajube A. A. , Shobayo O. , Aligbe A. , Ibhaze A. E. 
Published: February 2021

Abstract- The ubiquitous nature and the proliferation of mobile devices has made wireless power transfer (WPT) a very important area of research. The flexibility and cost effectiveness of charging these enormous devices in our world without having to connect physically to any electrical port especially when the user is indisposed to do so is a very attractive characteristic of WPT. Conventional means of charging the batteries of these mobile devices are wired which invariably meansthey requirephysical connection to power sources through electrical cables. Electric power istransmitted wirelessly when a magnetic field produced by the inductive coupling of coils or electrical field produced by the capacitive coupling between electrodes is transferred over a short distance through the air interface and later received by an antenna for utilisation. This article gives a detailed review of the existing wireless power transfer technologies, principles of operation, applications and the opportunities for future research in this area of emerging technology. However, WPT has some drawbacks but it is a disruptive technology with the ability to revolutionise the dynamics of mobile wireless systems, internet of things and otherallied future technologies.