bluuebunny/crossref_metadata_2025 huggingface dataset:
Variant component principal linear reduction for prediction of hypothyroid disease using machine learning
Authors: Shyamala Devi M. , Swathi P. , Jahangir Ayesha , Kumar A. Dhanunjai Sai , Naidu A. Naga Bhushan , Manas M. Raghuram
Published: February 2021

With the tremendous technological growth, the world is shifted to adapt the different food and life style by the people that results in the improper working of the body organs. The change in the food habits leads to a major problems that we face in the current scenario is the presence of hypothyroid in the body. The likelihood of hypothyroid still ruins as a challenging issue due to the uncertainty of proper symptoms. With this background, the machine learning can be used towards health care scenarios for the prediction of disease based on the patients past history. This paper focus on predicting the existence of hypothyroid with respect to the patients’ medical parameters. The hypothyroid patient dataset is taken from the UCI Metadata repository with 24 columns and 3163 unique patient’s records is used for the experimentation of hypothyroid with the following contributions. Firstly, the hypothyroid dataset from UCI machine repository is subjected with the data processing and exploratory analysis of the dataset. Secondly, the unrefined data set is fixed with different classifier algorithm to find the presence of hypothyroid and to examine the efficiency metrics before and after feature scaling. Thirdly, the data is processed to PCA with various combination of components as 5, 7 and 10 and is fixed with different classifier algorithm to examine the efficiency metrics before and after feature scaling. Fourth, the data is processed to LDA with various combination of components as 5, 7 and 10 and is fixed with different classifier algorithm to examine the efficiency metrics before and after feature scaling. Experimental results show that the Kernel Support Vector Machine classifier is found to have the accuracy of 99.52% for all the 10, 7, 5 component reduced PCA dataset. Similarly, the Logistic Regression, Kernel Support Vector Machine and Gaussian Naïve Bayes classifier is found to have the accuracy of 99.52% for all the 10, 7, 5 component reduced LDA dataset.
Transfer Learning approach for grading of Diabetic Retinopathy
Authors: Aswathi T , Swapna T R , Padmavathi S
Published: February 2021

There has been a wide interest in applying Deep Learning (DL) algorithms for automated binary and multi class classification of colour fundus images affected with Diabetic Retinopathy (DR). These algorithms have shown high sensitivity and specificity for detecting DR in non-clinical setup. Transfer learning has been successfully tested in many medical imaging applications like skin cancer detection, pulmonary nodule detection, Alzheimer’s disease etc. This paper experiments with the different DL architectures such as VGG19, InceptionV3, ResNet50, MobileNet and NASNet for automated DR classification (binary and multi class) on Messidor dataset. The dataset is publicly available, and comprises of 1200 retinal fundus images. The images belong to four different classes of DR namely, normal (class 0), mild (class 1), moderate (class 2) and severe (class 3), graded based on the severity level of DR. In our experiment, we have enhanced the quality of input images by applying algorithms like CLAHE (Contrast Limited Adaptive Histogram Equalisation) algorithm and Powerlaw transformation as pre-processing techniques, which work on the small image patches with high accuracy, contrast limiting and image sharpening. Hyper parameter tuning on pretrained InceptionV3 architecture, resulted in enhancing the accuracy of the model. Both binary and multi class results were analysed considering inter class (one class with another class) accuracies. We achieved an accuracy of 78% between class 0 and class 1, the accuracy between class 0 and class 2 further reduced to 69%, while class 1 and class 2 showed an accuracy of 61%. Moreover, the interclass class accuracy between class 1 and class 3 was 62%, class 2 and class 3 further reduced to 49%. The accuracy further diminished between class 0 and class 3 to 32%. These experiments suggest that the pretrained models provided better results in classifying normal and mild, but they were not that much efficient in classifying moderate-severe and normal-severe binary classifications.
Comparative analysis of glioma tumor in brain using machine learning and deep learning techniques
Authors: Sangeetha J. , Vaishnavi D. , Premalatha J.
Published: February 2021

Brain tumour is one of the major causes of the increasing mortality rate. There is an emerging need for precise diagnosis from the pathology, as human prediction is prone to errors. Brain pathology is captured using Magnetic Resonance Imaging (MRI) which gives high quality images of the blood vessels. These MRI images can be used to extract features and predict the tumor. The extracted features can be classified using Machine leaning (ML) algorithms. In this advanced and emerging deep learning era, images can be fed directly to the prediction system and the system itself extracts features at higher level of abstraction and classifies the images. This article presents a comparative analysis for classifying the MRI images of Glioma (a type of brain tumor) and healthy brain using convolutional neural networks (CNN) and ML algorithms like support vector machines (SVM), random forests, and bagging. CNN and the ML algorithms were implemented on BRATS 2013 challenge dataset and it is found that CNN has achieved highest accuracy of 95%.
Optical Chaos KEY generator for Cryptosystems
Authors: Baby H T , Sujatha B R
Published: February 2021

Chaotic structures are ideally appropriate for the construction of cryptographic schemes, because random numbers are an inseparable part of every encryption scheme as a safety mechanism. The optical chaotic circuit is an ultra-fast physical Random number generator, which is illustrated using the CW laser that generates optical signal at 193.1 THz and M-Z modulator that works on an interferometric principle. The circuit generates truly high random bit sequences at different higher bit rates of 320Gb/s and 640 Gb/s. These generated random bits have passed the NIST statistical tests and Diehard battery tests, indicating their randomness for different practical applications. Further, the random number generated by optical chaos circuit is used to secure the image data using RC4 ciphering method.
A responsiveness model for privacy conservation against antagonist and fake user in cyber- physical and online social networks
Authors: Vanitha A , Balakrishnan N
Published: February 2021

The enormous numbers of users are interacted with Social networking sites throughout the world. They are consistently engaging with Social Medias are Twitter, Instagram and Facebook have an incredible impression and rarely objectionable consequences for daily life. Recently, the detection of spammers and identification of fake users on Twitter has become a common area of research in contemporary online social Networks (OSNs). This paper proposes to perform a review of techniques used for detecting spammers on social media like Twitter, Facebook, Instagram, etc. Furthermore, a taxonomy of alerting spam message methodologies is presented that classifies the techniques based on their ability to detect: fake content, spam message or junk mail depends on either url or trendy news, and identifying unauthenticated users. The proposed techniques are also compared based on historical features that comprise the characteristics of user profile, wish-list, content usage, methodology used, and physical context, logging activities. This research paper contributes the study on identifying appropriate users against fake users and spam or junk mail detection using Adversary-Privacy evaluation model that helpful to preserving private data in Cyber-Physical Social Systems.
Resolving ownership rights of video data using visible and invisible watermarking in DWT-SVD domain
Authors: Ponni alias sathya S , Ramakrishnan S , Sumathi T , Sasidharan S
Published: February 2021

This paper addresses the concern of video piracy and also resolves ownership rights. Piracy entails utilizing, modifying and sharing the data without owner concern. Identifying the owner of the piracy and also the legal owner is difficult. For resolving these problems, this paper employs the prominent technique like watermarking with legal data base creation and SVD in wavelet domain. In addition to that, master key frame selection concept is used for identifying the key frames. Here the problem is resolved by two approaches. That is visible and invisible watermark to the authorized data. The watermark may be legal information about the owner like photo, thumb impression, signature of the owner and legal id. The legal id is the visible watermark and photo, thumb impression or signature of the owner is inserted as an invisible watermark. This methodology resists several video and image processing attacks. The experimental results show that the algorithm produces good perceptual quality and robustness to the watermarked video as well as watermark.
Design of Compact S Box for Resource Constrained Applications
Authors: Sherine Jenny R. , Sudhakar R. , Karthikpriya M.
Published: February 2021

The era of IoT has brought huge impact in the lives of people. It changed the way the people interact with the outside world and led to the development of many smart devices. The important factor to be considered in smart devices is security as the sensor nodes are prone to vulnerable attacks. To incorporate security in IoT lightweight block ciphers are preferred. Lightweight block ciphers can be tuned according to applications. This can be motivated by optimizing the S-box since S-box has significant impact on area. Reducing the area produces an impact on power, delay and memory. Here area optimized S-box of lightweight ciphers that serves for IoT devices is proposed. The S-box of PRESENT, GIFT and LED are optimized using karnaugh mapping. Further factorization is carried out to utilize the redundant terms which in turn reduces the gate count. The proposed method is found to be optimum when compared with previous works and it also consumes less area and power.
Efficient Feature Extraction from Multispectral Images for Face Recognition Applications: A Deep Learning Approach
Authors: Sudharsanan R , Gopirajan PV , Suresh Kumar K
Published: February 2021

In recent years many face recognition algorithms were used for the identification and authentication of a person to a system. However, still, feature extraction from multispectral images was considered to be a challenging task. Feature extraction, including highlight location and portrayal, assumes a significant job in real-time security-based applications. In this paper, a novel Geometric Algebra-based Multivariate Regression Feature Extraction (GA-MVRFE) algorithm was proposed to extract features from a huge dataset stored in the cloud efficiently. This proposed algorithm works with the supreme expedient deep learning approach - Convolutional Neural Network (CNN) for image classification. CNN will automatically detect significant features from the multispectral images without any human intrusion from a huge database. Real-time images were captured with three different cameras and applied filters over the images and were created as a dataset. To show the competence of the proposed algorithm, an exclusively created dataset with a set of 14,400 image data was applied in the proposed and other existing algorithms, and their efficiency and robustness were noted. Providentially, GA-MVRFE produced better accuracy in ‘Face Recognition’ with a less time fraction compared with former algorithms. Obtained accuracy % for Geometric Algebra Oriented fast and Rotated Brief (GA-ORB), Geometric Algebra Fast Retina key-point Extraction Algorithm (GA-FREAK), Trilateral Smooth Filtering (TRSF), Cross Regression Multiple View Features extraction (CRMVF) and GA-MVRFE was 87.81, 83.23, 90.72, 91.67 and 97.57 respectively.
Study on Fissile Material Usage for 50 MWt High Temperature Gas Reactor using (Pu-U)O2 Fuel
Authors: Pratama Ayu Lia , Irwanto Dwi
Published: February 2021

One of the most potential nuclear power plants is High Temperature Gas-cooled Reactor (HTGR). It is a reactor system designed using TRISO (Tristructural-Isotropic) coated fuel and has very high outlet temperature to produce electricity and many co-generation application processes. The present study aims to analyze fissile material usage for 50 MWt prismatic-type HTGR using (Pu-U)O2 fuel. Calculations were performed using neutron diffusion method that applied in SRAC2006 code, and nuclear data based on JENDL 4.0. Selected neutronic parameters are analyzed to study the effect of the number of fissile enrichment and number of Coated Fuel Particle (CFP) to the reactor system. The results of the parametric survey show that for prismatic-type of 50 MWt HTGR, 10% of enrichment and 8950 of number CFP give the best performance in term of fissile material usage during reactor operation.
The Effect of Sn Dopant on the Electrical and Optical Properties of ZnO Thin Films
Authors: Hendri Yasni Novi , Kenichi Purbayanto Muhammad Abiyyu , Pratama Sendi Nugraha , Zuhairah Nabilah , Darma Yudi
Published: February 2021

We study the electrical and optical properties of Sn-doped ZnO (SZO) films grown by DC-unbalanced magnetron sputtering. To study the electrical properties of the films, we perform current-voltage (I-V) measurement by using metal-semiconductor-metal configuration with Ag as a metal contact. The measurement is performed in the dark and under UV exposure condition to study the photodetection properties of the films. From the I-V curve, it shows that the sensitivity of SZO is dramatically enhanced compared to the undoped film. This enhancement is due to the role of Sn dopant, which gives more electrons to the system. Furthermore, UV-Visible spectra reveal that the band gap increase by introducing the Sn dopant. Photoluminescence spectra show SZO film exhibits a higher green emission intensity compared to ZnO film, which is related to the presence of oxygen vacancy. Our result is important to improve the functionality of ZnO for optoelectronic devices applications.
The Turbine Heat Waste of RDE for Desalination Laboratory Plant
Authors: Sriyono  , Kusumastuti Rahayu , Pancoko M. , Sunaryo Geni R. , Setiadiapura Topan , Subekti M. , Hafid Abdul , Salimy Djati H. , Irianto Ign. Djoko , Susmikanti Mike , Merita
Published: February 2021

Reaktor Daya Eksperimental (RDE) is currently being developed by Batan. This reactor uses HTGR technology as the basis for its development. It has an indirect cycle power conversion with primary coolant is helium and its secondary is water. The RDE will be operated not only for an electrical generation but also for cogeneration purposes. One process can be supported in the cogeneration scheme is seawater desalination. Water is the main source of life and its availability must be maintained on earth. Therefore, to overcome the scarcity of freshwater at the remote islands in Indonesia, it needs nuclear cogeneration by coupling of RDE and desalination. With this technology, it can simultaneously produce electricity and freshwater. A variety of desalting technologies has been developed over the years, including primarily thermal and membrane processes. This paper discusses the simulation of RDE for desalination purposes. The methodology used in this research is modeled and simulation by using ChemCAD. The desalination plant is simulated by the heat exchanger unit operation. The RDE primary mass flow rate is 4.3 kg/s, 700°C of temperature and 30 bars of pressure. The secondary coolant mass flow rate is 3.8 kg/s, 60 bars, and 350°C respectively. Depending upon the specific designs the temperature ranges of the waters in this exchanger could be between 80-130°C. The extraction point of the desalination process is at turbine output, with 300.16°C, 8 bars and 3.7 kg/s of mass flow rate. The total amount of freshwater will generate is 4.09 m3/h equal to 98.16 m3/day.
Analysis of oxide fuel element temperature of RSG-GAS by using experiment and calculation
Authors: Sudarmono  , Bakhri Syaiful , Hastuti Endiah Puji
Published: February 2021

Multipurpose Reactor GA Siwabessy is a research reactor designed to have nominal power of 30 MWth, located in PUSPIPTEK area Serpong and operated by BATAN. RSG GAS utilizes LEU-MTR with enrichment 19.75% and uranium density of 2.96 g U/cm3, 40 fuel rods and 8 control rods, 4 irradiation position (IP) and 1 central irradiation position (CIP) in 2 × 2 lattice, and reactor core surrounded by beryllium reflector. Forced convection cooling mode is applied to remove heat of fission product at normal operation, while natural convection cooling mode is used for reactor physics experiment, or cooling after transient condition. Forced convection cooling mode does not employ primary cooling system, where power is limited to 1% of the nominal power, while natural convection cooling occurs after transient process due to loss of coolant. Heat transfer occurs because of difference in coolant flow density where coolant flows upward since natural circulation valve is opened. This research is aimed to analyze heat removal capability in natural convection cooling mode at the most severe condition following reactor scram. The experiment of cladding and coolant temperature measurement is carried out in fuel coolant channel using instrumented oxide fuel element. Capability of generating reactor power in natural convection cooling is calculated using NATCON code. The measurement result of the highest temperature of plate fuel element is 121°C. Meanwhile, the calculation results of NATCON show that the initial temperature of nucleate boiling TONB occurs at power 685.86 kW and cladding temperature is 126.35 °C. These experiment results indicate that nucleate boiling does not occur in natural convection cooling due to scram or in other words safety margin has been met.
Hot deformation behavior of hard-to-deform Ni-based Alloy
Authors: Lu X D , Zhang Y W , Shi S Y , Wen B , Su X , Du J H
Published: February 2021

The very poor hot workability of hard-to-deform GH4742 alloy is represented in the aspects of very narrow available deformation temperature range, high deformation-resistant force and low thermoplasticity. In this paper, the hot deformation behavior of a Ni-based superalloy was studied in the temperature range of 1060-1160°C and strain rate range of 0.05-0.5 s−1 using hot compression tests. A hot deformation equation is given to characterize the dependence of peak stress on the temperature and strain rate. Results of hot compression test of the GH4742 alloy were indicated that the hot deformation is sensitive to temperature and strain rate. A special heat treatment to change the ingot microstructure is proposed to improve the hot workability of the GH4742 alloy. Modified microstructure induces that the hot deformation flow stress of GH4742 alloy was decreased effectively and hot deformation plasticity was increased obviously.
Bench experimental research of cylinder oil on large marine diesel engines
Authors: Lin J H , Wang B X , Wei L D
Published: February 2021

To lower the risks of the real ship test of the cylinder oil of large marine low-speed two-stroke marine diesel engine, A 6S50ME marine diesel engine was selected to do bench test about cylinder oil. In the calibration condition, the test cylinder oil and the reference cylinder oil were compared. The test results show that the wear amount of cylinder liners, piston rings and piston-ring-grooves is consistent with the wear condition judged by the metal element content detected by the residual oil of the cylinder. At the same time, combined with the evaluation result of the detergency and dispersibility of the cylinder oil, it can effectively judge whether the oil product can be tested on the ship. Since wear volume of element Cr and Fe tends to the stabilization after 60 hours, so it is feasible to set the diesel engine bench test at 100 hours. In addition, special attention should be paid to the control of water outlet temperature and exhaust gas temperature in the test. The cylinder oil evaluated in the above way meets the requirements of OEM after the actual ship test. Thus, the assessment method of cylinder oil based on the bench test is feasible, and can greatly shorten the test time and reduce the test cost.
Anti-galling β-SiC coating dies for fine cold forging of titanium
Authors: Aizawa Tatsuhiko , Yoshino Tomoaki , Shiratori Tomomi , Dohda Kuniaki
Published: February 2021

β-SiC coating die and punch were employed for forging of titanium wire to triangular bar in high reduction of thickness by 35 %. CNC (computer numerical control) stamper was utilized to describe the elasto-plastic behavior of titanium wire in dry forging. Precise analyses on the contact interface between SiC coating and titanium work were made to investigate the mass transfer of metallic titanium as well as titanium oxide debris particles onto SiC coating surface. In particular, element mapping and Raman spectroscopic analyses were performed to describe the formation of thin titanium oxide film as well as the agglomeration of unbound carbon on the SiC coating punch.
The convergence rate of a polygonal finite element for Stokes flows on different mesh families
Authors: Vu-Huu T , Le-Thanh C , Pham-Van Sy , Hoan Pham Q , Nguyen-Xuan H , Abdel-Wahab M
Published: February 2021

This paper introduces an evaluation to consider the convergence rate of a polygonal finite element (PFE) to solve two-dimensional (2D) incompressible steady Stokes flows on different mesh families. For this purpose, a numerical example of 2D incompressible steady Stokes flows programmed and coded by MATLAB is deployed. Furthermore, the mixed equal-order PFE, i.e., Pe1Pe1, is utilised for this research. Additionally, five different mesh families, i.e., triangular, quadrilateral, hexagonal, random Voronoi, centroidal Voronoi meshes, are applied for this research. Moreover, an interesting evaluation of the CPU time for the performance of our proposed PFE in this research is employed as well. From these tests, differences in convergence rate, as well as CPU time of using Pe1Pe1 on different mesh families, are indicated.
Research on Encrypted Text Classification Based on Natural Language Processing
Authors: Ren Qiuyi
Published: February 2021

In reality, data encryption technology is mostly used to protect the security of text data in the network, but when we need to obtain these data, this layer of encryption becomes an obstruction to obtaining data. The general method uses data mining and data decryption to extract effective information. The experimental data in this article selected 20 categories of text information, and obtained a data set with a difficulty of 1 to classify the encrypted text information. In order to classify encrypted text more effectively, this paper studies the method of using the logistic regression model and the LightGBM model algorithm to directly process encrypted text, which can directly extract and classify the text in the encrypted state. Model evaluation results show that LightGBM is more effective. In addition, this article provides a basic framework for the classification of encrypted text based on natural language processing.
An Agile Testing Framework of Four Quadrants
Authors: Yu Jiujiu , Zhu Shaomin , Zhang Jishan , Chen Yun , Wu Ning , Mei Yingying , Zhang Deqing , Zhu Lili
Published: February 2021

The research is based on the idea of agile testing, taking the “order cancelled” module of an e-commerce website as an application case, this study is devoted to exploring a feasible and scientific agile testing framework of four quadrants to form an anticlockwise closed loop for guiding the software agile testing process. Furthermore, further work is put forward to establish of a special defect management database for bug definition and analysis, and build the particular test process models for each quadrant of this agile testing framework gradually.
Multi-MEC server multi-user resource allocation in heterogeneous network
Authors: ZhenQin  , Liao Yuanxiu , Shen Dejin
Published: February 2021

Aiming at the coexistence of large and small cells in heterogeneous cellular networks, the difference of computing resources between mobile equipment and base stations, and the diversity of service quality demands of users, a resource allocation algorithm based on matching game theory was proposed. We assume that some users have computing needs and can perform MEC offloading or D2D offloading. We define cost performance as the ratio of the data rate per user to its price cost, and resource allocation as the cost performance maximization problem. Considering that the formulation problem is a mixed integer nonlinear problem and it is difficult to obtain the optimal solution, we design an improved Gale-Shapley algorithm based on matching game theory to obtain the feasible solution of the problem. Simulation results show that the proposed multi-MEC server multi-user resource allocation strategy can effectively reduce user service delay and improve system performance in heterogeneous cellular networks.
A Non-Foster UWB Electrically Small Planar Monople Antenna (ESPMA)
Authors: Zhang Chungang , Xie Yongjun , Ren Haiping
Published: February 2021

Electrically small antennas (ESAs) may be employed instead of full-size antennas in a limited space for many communication networks such as the very high-frequency (VHF) band applications and ultra high-frequency (UHF)band applications. However, ESAs can not simultaneously achieve high gain and broadband by passive matching due to the gain-bandwidth theory. This paper presents a ultra wide-band (UWB) transmit electrically small planar monople antenna (ESPMA) with a non-foster impedance matching to bypass the restriction of the gain-bandwidth theory. The proposed antenna is composed of a planar monopole antenna with a height of 10 cm in profile and a non-Foster circuit. The plane monople antenna is chosen because of its better impedance performance than a cylindrical monople. The proposed antenna can operate in the band range of 80 MHz - 500 MHz (145%, VSWR<2.5) much greater than the maximum bandwidth of 0.285% in the theory of matching with the conventional passive circuit. The transmission efficiency of the antenna is improved by as much as 31dB compared with the same antenna without the proposed matching network. Besides, the stability of the proposed matching network is remained within the operating band.
Deep Learning Method for Buffer Layer Defect Detection in High Voltage Cable
Authors: Yi Xie , Jun Zhang , Le Zhang , Jianjia Duan , Xiaoli Duan , Fuyong Huang
Published: February 2021

A deep learning method based on the convolution neural network is proposed to replace the manual inspection for the buffer layer defect detection in high voltage cable. One hundred seventy-seven high-resolution images of defects are collected. The VGG16 network is adopted. The results indicated that the VGG16 achieves the F1 score to 0.68 on the test set, proving to be an efficient way to detect the buffer layer defects.
Research on Fire Alarm Monitoring System of Fire Engineering Based on Network
Authors: Cai Liu Rong , Ning Tao Hua , Chao Liu Rong
Published: February 2021

Under the background of rapid development of information technology, the design of fire alarm devices in fire engineering in China is becoming more modern and humanized. At present, under the traditional alarm function, the fire alarm system device embodies the functions of centralized alarm monitoring, fire linkage, automatic prevention and control, data transmission and so on, which lays a good foundation for the fire alarm construction of the new generation fire protection engineering. In this paper, the operation status of the fire alarm monitoring system of network fire protection engineering in China is studied and analyzed, hoping to provide reference for the corresponding units.
Agile development technology of test application program suitable for semiconductor device testing
Authors: Yan Tao , Guo Min , Zhu Xuebo , Yang Yang
Published: February 2021

The semiconductor devices (especially integrated circuits/chips) test field involves a wide range of device types and test parameters, which leads to low development efficiency, poor stability, weak reuse, long development cycle and repetitive work in application development. Therefore, a test application development method based on reusable component technology is proposed in this paper. Firstly, this paper introduces the basic concepts and characteristics of the reusable component technology. Then, according to the current situation of semiconductor device testing, the design method of component-based test application program is described. Finally, the typical semiconductor device test application program is designed and developed by using LabWindows/CVI integrated development environment. Practice has proved that the component-based test application program design can speed up the R&D and ensure the software quality at the same time. The agile development requirement of application program for semiconductor device test system can be satisfied.
Prediction of fishing vessel operation mode based on Stacking model fusion
Authors: Fu Huaichun , Gao Shouwei , Peng Yan , Zhao Nan
Published: February 2021

Due to the continuous upgrading and optimization of fishing technology and tools, and the diversification of fishing vessel operation methods, marine fishery resources are continuously depleted. Precise prediction of the operation methods of marine fishing vessels is helpful to realize effective supervision of fishing behavior of fishing vessels. In order to improve the prediction accuracy, when doing feature engineering, this paper uses a vector encoding scheme based on trajectory sequence, and uses text vectors to train the word2vec model to calculate the embedding features of each position. At present, the single method needs to be improved in terms of forecasting accuracy. This paper proposes a forecasting method based on Stacking model fusion in order to further improve the forecasting accuracy of marine fishing vessel operations. The experimental results show that the Stacking fusion model using the vector coding scheme based on the trajectory sequence has a greater improvement in prediction accuracy than a single model.
Theoretical investigation of weight-dependent optical spike timing dependent plasticity based on VCSOA
Authors: Tian Tao , Ni Min , Zhengmao  , Guangqiong Wu , Xiaodong Xia , Tao Deng Lin
Published: February 2021

We propose an implement scheme of the weight-dependent optical spike timing dependent plasticity (STDP) based on the vertical-cavity semiconductor optical amplifiers (VCSOAs) subject to double optical spike injections, and numerically investigate the effects of the internal and external parameters of VCSOAs on the optical STDP curve by the well-known Fabry-Pérot approach. Additionally, the optical weight-dependent STDP is realized by introducing the various bias current according to the feedback signal. The simulation results show that, the width and height of the optical STDP curve window can be effectively controlled by adjusting the relevant parameters of VCSOAs. Moreover, the optical weight-dependent STDP is analogous to the biological STDP synapses and can be used to balance the stability and competition among synapses. These results can offer great potential for constructing a large-scale energy efficient optical spiking neural networks (SNNs).
Research on 3D Pose Measurement Algorithm Based on Binocular Vision
Authors: Shan Fu Qiang , Wang Feng , Zhang Hai Feng
Published: February 2021

Based on binocular vision, this paper proposes an algorithm for fast and accurate three-dimensional measurement. The binocular 3D measurement system is mainly divided into four parts: binocular calibration, binocular correction, binocular matching and pose calculation. In this paper, an international softwareM is used to achieve camera calibration, the FAST algorithm is used to achieve the extraction of feature points, and the matching method that combines gray-level correlation coefficient (cc) and epipolar constraint is selected. Experiments have verified that this algorithm can accurately achieve three-dimensional pose measurement.
Remote monitoring system of branch circuit in the family
Authors: Liu Xu , Li Zhongyu , Chen Yang , Zhang Xu , Li Zhaoming
Published: February 2021

In order to estimate and predict human real-time heating demand and optimize the existing electric heating control methods, a large number of household electricity data samples are required for training. This article mainly introduces the method of obtaining data samples, and realizes the monitoring of household branch circuit information by establishing a modern remote monitoring system. The author gives the detailed hardware design and software function introduction of the system. Each collection terminal in the system uses LAN, LTE and Wi-Fi modes to establish communication with the monitoring center, completing the basic functions of collecting electricity information for each branch circuit in the family, and having a remote upgrade function makes the system more complete. An experiment conducted in a family in Jinan City, Shandong Province, China tested the function of the verification system. The proposed remote monitoring system can be a useful tool to grasp the power consumption of each line of the family and study the energy demand of users.
Performance analysis of Mixed MUD-RF/Multi-aperture FSO Relay Communication System with Co-channel Interference
Authors: Liu Wen-ya , Wang Xiang , Zhao Shang-hong
Published: February 2021

This paper discusses the performance of an improved dual-hop mixed radio frequency (RF) / free space optical (FSO) relay communication system in the present of multiple co-channel interferences (CCIs) at the relay node. Multi-user diversity(MUD) technology has been adopted to improve the RF link performance. In order to improve the performance of the FSO link, multi-aperture receiver scheme has been implemented. The multi-user RF link experiences Nakagami-m fading, while the FSO link is subjected to Exponentiated Weibull distributed atmospheric turbulence. Moreover, the CCIs at the relay node are assumed to undergo Nakagami-m fading. For this proposed system, the exact closed-form expression for the outage probability (OP) has been derived. To quickly understand the effects of different parameters on the system performance, the asymptotic expression for the case of high signal-to-noise (SNR) has been further presented. Results show that the diversity order of this proposed system is min (αβM/2,m
1
K), where M represents the number of receiver apertures; K denotes the number of users; α, β and m
1 are the channel parameters. Additionally, the effects of various parameters on system performance have been investigated. Finally, the numerical results have been validated by Monte-Carlo simulations.
Low Cost and Large Bandwidth Visible Light Communication System Design
Authors: Zhang Ziming , Wang Xichen , Wu Qian , Liu Yuanqin
Published: February 2021

Aiming at the problem of insufficient bandwidth of transmitter and receiver of low-cost visible light communication system, this article applies novel-equalization circuits to separately expand the bandwidth of LED and transimpedance amplifier circuit to 114MHz and 95.7MHz. In addition, signal-to-noise ratio and bit error rate of the system are also analyzed by a line of sight model and the feasibility of the designed system is confirmed.
A Study on the EDA-based Classification of News Text
Authors: Shuwei Xu , Xuyang Gao , Ying Wang
Published: February 2021

At present, the commonly used word vector methods for news text classification mostly adopt Word2Vec, Glove, Bert and other word vector models, ignoring the remote context connections of Chinese text itself. TextCNN, RNN, BiLSTM and other neural network classification models lack the extraction of important information features of the text, and the word dependence inside the text is not strong, resulting in inaccurate classification results. To solve the above problems, this paper proposes the DPCNN-Attention news text classification model based on ERNIE’s pre-training model(EDA for short, the following general). The DPCNN neural network model with Mish() activation function is adopted to obtain the maximum length of semantic association between long distance texts in news texts. By adding attention mechanism into EDA model, in the feature extraction process, according to the importance of words to the classification results, different weights are assigned to them to enhance the word dependence relationship within the text, thus greatly improving the classification accuracy. The EDA model was experimentally verified on the THUCNews dataset. The results showed that the EDA model improved by about 6% compared with BERT’s pre-training model, and 0.4% compared with ERNIE’s pre-training model. The loss rate decreased by 0.2 compared with BERT and 0.01 compared with ERNIE’s.
Research on Generation Methods of Test Cases for Pair-wise Covering Combinatorial Test Cases
Authors: Dandan He , Yue Zhai , Lijuan Wang
Published: February 2021

For most software systems, pair-wise combinatorial testing is highly practical and effective. This article mainly starts with the specific research status of the pair-wise covering combinatorial test and the main content of the software test, analyzes and compares the existing main implementation algorithms, and then evaluates their specific performance.
Systematic assessment of food security by recurrent addition of fuzzy cognitive maps
Authors: Rogachev A F
Published: February 2021

The results of an analytical review of the problems of modeling the state and evolution of socio-economic systems solved using the mathematical apparatus of matrix analysis of cognitive maps are presented. The difference between classical and fuzzy cognitive maps (FCM) is shown. The problems, strengths and weaknesses of algorithms and tools for assessing the level of food security (FS) based on a fuzzy cognitive approach are considered. The basic groups of concepts and methods for constructing the FCM that provide a fuzzy integral assessment of the PB level are analyzed. A method of recurrent construction of the NCC by successive addition of a set of concepts is proposed. In the process of adding concepts, experts make step-by-step recurrent adjustments to the values of the mutual influence of concepts. Recommendations for justification are presented, using the example of assessing the level of FS, the choice of tools for building the NCC. The solution of the problem of assessing the level of regional FS is illustrated for a set of economic, environmental and organizational concepts. It is shown that for adjusting the para-meters generated by the FCM, including to take account of their changes over time require the creation of software tools for fuzzy cognitive modeling, taking into account specific tasks and retrospective information together with simulated system factors.
Agricultural crops programmed cultivation using intelligent system of irrigated agrocoenoses productivity analyzing
Authors: Tokarev K E
Published: February 2021

The article considers the possibilities of controlling the programmed cultivation of agricultural crops using an intelligent system for analyzing the productivity of irrigated agrocoenoses. The information support of the intelligent system is standard information about agrometeological conditions, technical parameters of irrigation systems and irrigation machines, as well as information about the amount of water resources allocated for irrigation. The obtained results provide a strict theoretical basis for solving the issues of irrigation water distribution and operational management of the irrigation regime, clarify and simplify the procedure for choosing the optimal variant of the irrigation system design solution, and make it possible to make reasonable decisions related to the rational use of water resources in existing systems.
Raising bio-productivity of agroecosystems using intelligent decision-making procedures for optimization their state management
Authors: Tokarev K E
Published: February 2021

The article deals with the problems of increasing the bio-productivity of agroecosystems with the help of intelligent decision-making procedures to optimize the management of their state. In the course of research, the author developed an algorithm for the interaction of operational and planned. Management of the state of the agroecosystem, characterized in that the values of the controlled parameters change due to changes in the initial formulation of the optimization problem and the actual content of humus at the beginning of rotation. This allows you to manage the state of the agroecosystem, taking into account the need to restore humus. In addition, the author proposes a method and algorithm for decision support system for managing the state of the agroecosystem, which allows to rationalize the process of fertilization, to ensure an increase in crop yields, profitability of agricultural production and preservation of soil fertility. With the help of decision support system (DSS), the conditions for preserving soil fertility (variants of applied mineral and organic fertilizers that stabilize humus) were determined and forecasts of bio-productivity and economic efficiency.
Contrast Limited Adaptive Histogram Equalization for Underwater Image Matching Optimization use SURF
Authors: Suharyanto  , Hasibuan Z A , Andono P N , Pujiono D , Setiadi R I M
Published: February 2021

Conditions of the underwater environment have its challenges in the underwater vision research process. Some things that make underwater imagery difficult is that light can be scattered by particles in the sea, besides that light can be absorbed by seawater, as well as the turbidity level of seawater, so special techniques are needed to get clear underwater imagery. In underwater environmental conditions, the images obtained are usually of very poor quality. Backlight and attenuation will occur this is due to water conditions, objects that dissolve easily in water, and other particulate matter so that there is the degradation of the underwater image. Because it is very important if the image is improved in quality to facilitate the process of describing objects. Image matching techniques to determine the key points of image pairs are needed in three-dimensional reconstruction research. Speeded Up Robust Features (SURF) is an image matching technique where the matching results are very dependent on the image quality. This study proposes the Contrast Limited Adaptive Histogram Equalization (CLAHE) method to increase the number of matching images with SURF. The results of the experiment showed that image matching increased by an average of 76,8 %.
Mechanical Properties and Morphological Characterisation of Waste Natural Fiber Composites Reinforced Polyester: Gelam (Melaleuca Leucadendra)
Authors: Laksono A D , Ismail I , Ningrum C R , Sulistijono  , Ernawati L
Published: February 2021

The mechanical (tensile, flexural, and impact) tests and morphology observation were investigated on Natural Fiber Composites (NFCs) formed by strengthening Gelam as a fiber into the polyester as a resin matrix. The samples were prepared up to a maximum volume fraction of 0.70 from the fibers in powder form, hand lay-up method, and compared with pure Gelam and pure polyester. The synthesis results indicate for adding Gelam fiber in volume fraction that the optimum composition is at the addition of 0.70 fiber, with a tensile strength of 14.77 MPa, bending strength of 53.12 MPa, and the impact strength of 755.48 MPa. It was investigated that the impact strength and tensile strength of Gelam-polyester composite increase compare to pure Gelam. However, the result of flexural strength is decreased that can be associated with many factors such as incompatibility between matrix and fiber, instability of the hand lay-up method.
The impact of modern construction technology on the workforce in the construction industry
Authors: Agenbag H , Amoah C
Published: February 2021

This study investigated the impact of the use of construction technology equipment on the workforce in the construction industry. This study made use of the quantitative approach. Questionnaires were sent out to construction industry professionals, such as project managers, quantity surveyors, engineers, and owners of construction companies. Data received was analysed using descriptive statistics. The findings reveal that the use of construction equipment will have a tremendous impact on the workforce as one equipment would be able to execute work that could be done by a sizeable number of labourers. It was also found that the productivity of construction projects in South Africa can be increased by making use of construction technology equipment. However, it will be a herculean task to fully adopt construction technology equipment in project execution in South Africa as respondents believe the construction industry is heavily relied upon by the government to generate employment. There is also a perceived lack of expertise and lack of knowledge regarding the use of construction technology equipment among the workforce in the construction industry of South Africa. It is therefore suggested that construction companies invest in these different equipment, which will surely assist labourers and also speed up construction projects. The government must also look for areas of the economy to create jobs instead of relying heavily on the construction industry.
The structural characteristics of waste tire chars at different pyrolysis temperatures
Authors: Ren Qiangqiang , He Limo , Hu Song , Su Sheng , Wang Yi , Jiang Long , Xiang Jun
Published: February 2021

Pyrolysis was a promising technology to achieve waste tire (WT) dispose and utilization. However, large quantities of low quality waste tire chars (WTCs) would remain after pyrolysis and they could be employed to various applications. Further understanding the structural characteristics of WTCs at different pyrolysis temperatures would benefit to guide their utilizations. Herein, pyrolysis experiments were systematically conducted at 400 °C, 600 °C, 800 °C, and 1000 °C respectively to collect WTCs, whose structural characteristics were detailed analyzed. It was found that higher temperature can promote decrease of large and small aromatic ring systems, alkyl-aryl C-C bonds, defects with ordered arrangements of carbon skeleton structure. Pyrolysis can significantly promote pores formation, higher temperature would promote formation of micropores, while mesopores+macropores destroy before 600 °C and then gradually form. Higher temperature can promote decomposition of pyrrolic nitrogen and sulfur bridge with enrichment of oxidised nitrogen and sulphone bridge. Higher temperature would assist in generation of pyridinic nitrogen before 800 °C and quaternary nitrogen before 600 °C.
Advances in Urban River Landscape Ecology Research
Authors: Xu Surong
Published: February 2021

It is an inevitable trend to realize the sustainable development of “natural-human-water” through multi-scale and multi-disciplinary research on urban rivers with the principle of landscape ecology. Firstly, from the viewpoint of landscape ecology, and combined with the characteristics of urban rivers, the paper puts forward urban river landscape ecological theory and research framework. Secondly, the basic problems of urban river landscape ecology are studied. Finally, the theoretical development of urban river landscape ecology is studied, including the theory of urban river landscape ecosystem complexity, classification method of wetland and riverine ecosystem, and modeling of patch age and heteromorphosis. The research results have certain reference value for ecological river construction and river landscape ecology development.