bluuebunny/crossref_metadata_2025 huggingface dataset:
Computer-Aided Diagnosis (CAD) to Detect Abnormality on CT Image of Liver
Authors: Wahyuni W S , Prajitno P , Soejoko D S
Published: June 2020

Liver cancer on CT-scan image has different shapes, locations and textures in every image. The contrast difference between abnormal and healthy liver is often indistinguishable, making it difficult to evaluate. Liver abnormalities are such as swelling, fibrosis, and the presence of benign or malignant tumor. The difference of low contrast with wide size on the image is easily known as abnormality, but it is very hard to evaluate for small mass and low contrast. In this research, CAD was conducted to help the evaluation on liver abnormality, especially abnormality in small size. The research method used was active contour-based segmentation method. The research data were secondary data, the abdomen image was produced from the modality of Computed Tomography Scanner (CT-Scan) in Regional Public Hospital of Cibinong, Bogor. The data collection techniques were through observation on the image data of abnormal liver from either liver cancer patients, normal liver patients, as well as patients of other diseases as diagnosed by the doctor. Meanwhile, the data was processed through feature extraction process using the texture analysis of Gray-Level Co-occurrence Matrix (GLCM) with machine learning of Artificial Neural Network (ANN) to detect abnormality on image. The research stated that ANN can be used to categorize the images into normal and abnormal groups at 89% accuracy, 86% sensitivity, 92% specificity, 91% precision, and 10% overall error.
Prediction of excess volume in implementing the ABC system for breath-hold treatment: A preliminary study
Authors: Hoang A T , Jong W L , Ung N M
Published: June 2020

Deep inspiration breath-hold (DIBH) is a clinical technique intended to reproduce organ position at the chest or abdominal region during radiotherapy sessions [1]. Active Breathing CoordinatorTM (ABC) is a system that is used for the implementation of DIBH which has shown to reduce heart dose in breast cancer radiotherapy [2]. Since the ABC system’s main function is motion control of the torso region, attempts were made to apply the system to other cancer cases such as lung, liver, lymphoma and pancreas, in which treatment margins are stricter than in breast cancer. Hence, an evaluation on the technical aspects of the ABC system is essential. Data collection on patients treated with the assistance of the ABC system at the University of Malaya Medical Centre have been carried out since September 2018. The volume at the start of breath-hold moment, the maximum volume in the breath-hold session, the time delay between those two moments, the discrepancy in volume between those two moments, and the air flow rate leading to the breath-hold moment were all extracted from the data. The distribution and correlation of these parameters were evaluated between different groups of nominal threshold volume. The performance of the ABC system was characterised based on the discrepancy between the nominal volume and the real volume (excess volume) of a breath-hold session. The correlation coefficient of multiple regression of excess volume on nominal volume, air flow rate and time delay were 0.760, 0.714, 0.688 in group of nominal volume of 1.2 L, 1.3 L, 1.4 L, respectively. The correlation coefficient of regression of excess volume on air flow rate were 0.883 in group of nominal volume of 2.0 L. The excess volume can potentially be predicted by the nominal volume, the air flow rate and the time delay. Further investigation on assessing these parameters separately and on how the excess volume affects the treatment outcome is needed.
Monte Carlo Investigation of the Depth-dose Profile of Proton Beams and Carbon Ions in Water, Skeletal Muscle, Adipose Tissue, and Cortical Bone for Hadron Therapy Applications
Authors: Pamisa D R , Convicto V , Lintasan A , Quiñones C T
Published: June 2020

In this study, the depth-dose profile in water, skeletal muscle, adipose tissue, and cortical bone irradiated using incident beams of protons and carbon ions were simulated at different incident energies using the open source software GEANT4 version 10.3.2 via GATE v.8.0. The depth where the Bragg peaks of protons with incident energies of 75 MeV, 100 MeV, 130 MeV, 150 MeV, and 160 MeV in different materials were determined and the results were compared with the experimental data from the National Institute of Standards and Technology (NIST) database. The corresponding energy for incident carbon ion beam that yields the same Bragg peak position as the incident proton beams were also investigated. The depth-dose profile obtained using carbon ions show better dose conformation, but the presence of dose tail was observed. This suggests that further investigation of the RBE of the secondary fragments is necessary to understand their underlying impact to the carbon ion treatment in general.
Dose-volume Histograms Comparison From Two Different Beam Configurations In The Monte Carlo Simulation of 6MV Clinac2100 Using PRIMO Program
Authors: Bacala H , Peralta A , Nawang S , Bacala A
Published: June 2020

The Monte Carlo (MC) method is widely considered to provide the most accurate dose distribution in external beam radiotherapy. A self-contained, full MC linac simulator and dose calculator, PRIMO is a windows-based, freely-distributed software which allows the importation of external compliant phase-space files among its many capabilities. Using PRIMO, a Varian Clinac2100 is simulated at 6 MV nominal energy for 108 number of histories. The dose calculations are compared using two different initial electron beam configurations. The tuned-beam profile has initial electron beam energy of 6.26 MeV, 0.150 MeV full-width-half-maximum (FWHM), 0.150 cm focal spot FWHM and 2 degrees beam divergence. The default configuration given in PRIMO has 5.40 MeV as initial electron beam energy and zero values for all the other beam parameters. A brain computerized tomography (CT) volume is imported into PRIMO and using its contouring tools, these structures are delineated: a hypothetical grosstumor volume (GTV), the brain, the left and right eye lens. The CT volume is irradiated with two parallel-opposed fields of size 10 cm by 10 cm with the brain conformed using the 52-leaf MLC. The dose-volume histogram (DVH) of the GTV and the brain for the tuned-beam profile has a larger extent into the high dose region compared to the DVHs of the default beam configuration. The dose given to 95% of the volume (D95) and the percentage of the volume receiving a dose equal to 95% (V95) are also compared. The GTV for the default beam profile has D95 = 86.31% with V95 = 0.44%, while for the tuned-beam profile, D95 = 88.30% with V95 = 0.95%. For the brain, D95 = 2.55% with V95 = 1.13% for the default profile while the tuned beam profile gives D95 = 2.43% with V95 = 2.33%. For the left [right] lens, D95 = 0.15% [D95 = 0.11%] for the default profile and D95 = 0.16% [D95 = 0.081%] for the tuned-beam profile. Both beam profiles give V95 = 0% for the left- and right- eye lens.
Computer-Aided Detection of Mediastinal Lymph Nodes using Simple Architectural Convolutional Neural Network
Authors: Kurniawan E , Prajitno P , Soejoko D S
Published: June 2020

Lung cancer is the most common and the deadliest cancer in the world. Lung cancer staging usually was done by radiologist by detecting mediastinal lymph node (LN) enlargement. Mediastinal LN is difficult to be detected visually due to its low contrast to the surrounding tissues, various size and shape, and sparse location. Therefore, computer-aided detection (CADe) system has been developed as a tool for radiologist to detect mediastinal LN automatically. The state of the art mediastinal LN CADe system use complex architectural convolutional neural network (CNN). However, more simple architecture of the CNN is needed to reduce the computational complexity of the CADe system, especially if the system was intended to be used in a regular computer. Therefore, in this experiment we used simple architectural 2D CNN which is converted to fully convolutional network (FCN) to detect mediastinal LN candidate in a stack of CT images. Then, the mediastinal LN candidates were classified using 3D CNN to reduce the false positive (FP). The best performance of this CADe system was 65% of sensitivity at 5 FP/patient.
Evaluation of Adaptive Planning of Lung Cases based on Cone Beam CT Images
Authors: Tarigan S.T. , Nainggolan A. , Fadli M. , Liura S. , Pawiro S.A.
Published: June 2020

The purpose of this study was to evaluate the accuracy of dose calculation based on Cone Beam Computed Tomography (CBCT) as adaptive planning for lung cancer. Dose calculation based on CBCT images was compared to Computed Tomography (CT) simulator images as references. Treatment planning was generated for 7 patients of lung using Intensity Modulated Radiotherapy (IMRT) technique and Volumetric Arc Therapy (VMAT) technique. Eclipse v13.6 Treatment Planning System (TPS) with Analytical Anisotropic Algorithm (AAA) and Acuros External Beam (AXB) algorithm were used to calculate the dose. This study was divided into three major parts: (1) Hounsfield Unit (HU) calibration for CBCT images by using CIRS 002LFC phantom; (2) analysis of Dose Volume Histogram (DVH); (3) analysis of Passing Rate Gamma with criteria Dose Difference (DD) 2%/Distance To Agreement (DTA) 2mm and DD 3%/DTA 3mm using Electronic Portal Imaging Device (EPID). The DVH analysis for D98%, D50% and D2% deviation was evaluated and compared to the DVH for CT images with AAA algorithm as reference. The deviation of D98%, D50% and D2% for lung cancer was less than 2%. The range of conformity index based on CBCT images for all planning was 0,923-0,999 and the homogeneity index was in the range of 0,042-0,197. The gamma criteria (DD/DTA) of dose difference and distance to agreement for 2%/2mm are 87% - 94% and for 3%/3mm were 96% -98% for IMRT techniques. Passing Rate Gamma for VMAT with 2%/2mm criteria were 87% -96% and 3%/3mm criteria were 96% - 98%. The results of this study showed that dose calculation based on CBCT image was similar to dose calculation using CT image with descrepancy less than 2%.
Evaluation of conformal radiotherapy treatment planning of breast cancer patients: Preliminary case study patients from Persahabatan Central Hospital
Authors: Sugiyantari  , Rofikoh  , Rafliansyah A , Soejoko D S
Published: June 2020

Persahabatan Central Hospital has served radiotherapy treatment for cancer patients using linac, Elekta Precise and XiO treatment planning system (TPS) since May 2017. This study collected 91 breast cancer patients treated from May 2017 until January 2019. Most patients were preceded by surgery either mammae radical mastectomy (MRM) (83.5%) or breast conservative surgery (BCS) (16.5%). Conformal treatment planning generally performed with 2 tangential fields and most included oblique fields for treating axillary lymph nodes. Percentage of patients with clinical tumor volumes >400 cm3 was 29%, in the range of 200-400 cm3 was 36%, and the rest was <200 cm3. The lung volume irradiated with dose ≥20 Gy was used as one of parameters for treatment optimization. The mrm patient number with lung volume irradiated >30% was 9 persons (11.8%), in the range of 20-30% was 65 persons (85.5%), and <20% was 2 persons (2.6%). For the bcs patients, the number followed these criteria with lung volume of 20-30% was 13 persons (86.7%), and <20% was 2 persons (13.3%). Most breast cancer patients treated with radiotherapy were advanced stage preceded by mrm, treatment planning was difficult for achieving lung volume <30% that irradiated with the dose ≥20 Gy.
A Comparative Study of Dosimetric Characterization of Bolus Based on Natural Rubber (Hevea Brasiliensis) and Clinical Bolus for Therapy with Megavolt Electron Radiation
Authors: Aisyah S , Carina C C C , Nazara T , Sekartaji G , Nainggolan A , Endarko
Published: June 2020

The aim of this study is to evaluate the dosimetry properties of the synthesized bolus material from natural rubber compared to clinical boluses (Play-Doh and Paraffin Wax), involving the values of relative electron density (RED), transmission factor value (TF), mass attenuation coefficient (MAC), percentage surface dose (PSD), and curve of percentage depth dose. In this study, all boluses have dimensions of 11×11×0.5 cm3. Bolus density was measured and analyzed using a CT SCAN and treatment planning system. On the other side, the dosimetry test was performed using Linear Accelerator (LINAC) and detector plan parallel chamber (PPC-40) with an electron beam energy source (6, 9, 12 MeV). Relative electron density for natural rubber bolus, Play-Doh, and paraffin wax were obtained around 0.80, 0.91, and 0.79, respectively. These results indicate that the natural rubber bolus has close to the value of soft tissues such as the lung. Based on the calculation, the transmission factor and the mass attenuation coefficient of natural rubber have the best absorber properties achieved at 12 MeV energy with the results of 99.83% and 0.0045 cm2/g; this also occurred in the clinical boluses. The surface dose experienced an increase in each addition of energy as much as 8.73, 5.35, and 4.79% for energy sources 6, 9, and 12 MeV, respectively. Therefore it can be concluded that the bolus synthesized by natural rubber can be used as an alternative bolus alongside the clinical bolus in this study (paraffin wax and Play-Doh) in the treatment of superficial cancer using megavolt electron energy.
Effect of Iterative Reconstruction Algorithm Associated with Low Contrast Detectability Performance from CT Pulmonary Angiography Examinations
Authors: Harun H H , Karim M K A , Muhammad N A , Razak H R A , Sabarudin A , Muniandy S C
Published: June 2020

Iterative reconstruction (IR) in Computed Tomography (CT) scan examinations are known for noise reduction to achieve a higher level of diagnostic. This study aims to evaluate the radiation dose and image quality performance in different iterative reconstruction levels on CT Pulmonary Angiography (CTPA) examination and to establish a figure of merit (FOM) between both parameters. Thirty adult patients who underwent CTPA examinations were retrospectively included in the present study. Scanning acquisition protocol and radiation dose information, together with patient habitus information, was collected and recorded. The vessel attenuation was measured in five consecutive areas surrounding the pulmonary artery for each iterative reconstruction image. Results of radiation dose were presented in terms of Computed Tomography Dose Index (CTDIvol) obtained from CT-console and SSDE that was calculated by the AAPM report 204 recommendation method. Meanwhile, image quality was estimated by contrast-to-noise ratio (CNR) on average from five consecutive areas of CNR. The mean values of CTDIvol and SSDE were 13.79 ± 7.72 mGy and 17.25 ± 8.92 mGy, respectively. The amount of CNR was significantly different within the iterative reconstruction level (p <0.001). There was a significant difference in the figure of merit for both CNR2/SSDE and CNR2/CTDIvol attained in different iterative reconstruction levels, (p <0.001) and (p <0.001), respectively. In conclusion, we successfully evaluate the value of radiation dose and image quality performance and establish a figure of merit for both parameters to aid further verification of scanning protocols by radiology staff.
A Potential Biomarker from Diffusion Weighted Imaging and Parametric Response Map Analysis for Treatment Response Prediction in Nasopharyngeal Cancer
Authors: Jirawatwanith T , Tangyoosuk T , Lertbutsayanukul C , Jittapiromsak N , Rakvongthai Y
Published: June 2020

Diffusion-weighted imaging (DWI) is an MRI technique which provides functional information of tissue by detecting microscopic motion of water molecules. The change of apparent diffusion coefficient (ADC) derived from DWI was used as an imaging biomarker for treatment response prediction in cancers [1]. However, it was based on whole-tumor analysis which did not reflect heterogeneity within the tumor. To overcome this limitation, a new method called parametric response map (PRM) analysis was proposed to evaluate response by quantifying voxel-wise changes in ADC [2]. Here we investigated the use of PRM analysis on ADC from DWI as an imaging biomarker for treatment response prediction in nasopharyngeal cancer (NPC) patients. We collected thirteen patient datasets including ten complete response (CR) patients and three partial response (PR) patients at King Chulalongkorn Memorial Hospital where one patient dataset consisted of DWI and ADC data acquired before (i.e. pre-treatment) and at five weeks after (i.e. mid-treatment) initiation of chemoradiation therapy. For each dataset, we compared pre-treatment ADC image with co-registered mid-treatment ADC image, and calculated the percentage of voxels with increased ADC values with respect to total voxels within the tumor ROI, defined as PRM+. To validate the feasibility of the PRM biomarker, we computed the mean and standard deviation (SD) of percentage change in tumor volume (%AVol ) and in ADC (%AADC) and PRM+ across CR and PR patients, where tumor response was from 6-month follow-up data using RECIST1.1 guideline. The results showed that %AVol as well as %AADC between both groups was not significantly different. In contrast, PRM+ was significantly different between both groups (p < 0.05, 82.7±7.8% in CR vs 66.7±6.5% in PR). Our results implied that the proposed PRM+ biomarker could be a potential biomarker for early treatment response prediction in NPC patients.
Synthesis of Hidroxyapatite Using Microwave Irradiation and Sintering with Variation pH and Time
Authors: Amalia T R , Nurlely  , Sari Y W
Published: June 2020

Hydroxyapatite (HAp) with the formula of chemical compound Ca10(PO4)6(OH)2 is a bone replacement material used in alternative bone graft technology. This study aims to analyze the effect of variations in pH and time on Hydroxyapatite synthesis using microwave irradiation and sintering. The results show variations in pH and time affect crystal size, degree of crystallinity and morphological forms. XRD characterization showed that the samples irradiated by microwaves with time variations produced a crystal size of around 15 until 21 nm. The addition of the sintering process results in three times the crystal size be compared to the microwave process. XRD characterization also shows that variations in pH give rise to a secondary phase in the form of chlorapatite. FTIR characterization shows that the sintering process removes carbonate groups and SEM-EDX characterization of pH 11 samples which are only irradiated by microwaves produces a particle size of about 63.43 nm with a Ca / P ratio of 1.59 and the addition of the sintering process produces a particle size of around 180.62 nm with a Ca / P ratio of 1.48. The use of high temperatures affects the growth of crystals in the synthesis of Hydroxyapatite.
Preliminaries Methods for Detecting Urine Crystalline by Nanoparticle Size Analyzer
Authors: Warty Yuni , Haryanto Freddy , Aziyus Fitri Leni , Sunu Agung Nugroho Tri , Herman
Published: June 2020

Urine crystals can be found in healthy urine and unhealthy urine (urolithiasis). Size analysis, in both with the nanoparticle size analyzer (PSA) is very useful for distinguishing urine crystallites under 1000 nm. The choice of methods and materials that are appropriate at the preparation stage before measurement will determine the accuracy of the data. The purpose of this study was to establish the right methods and materials for detecting crystals by PSA. PSA was used to compare intensity-autocorrelation curves (mean diameter) and polydispersity index of techniques and materials reviewed. Those: solution concentration; protein-coagulating; distilled water volume; micropore diameter; centrifugation value; and measurement angle. The best processing methods for urine crystallites detection was found. Antiseptics and protein-coagulation with NaN3 (2%) and formaldehyde (2.5%) were added to the urine, respectively. Urine was diluted with 50% ml distilled water then filtered through a 3 µm paper filter to remove the macromolecule. The supernatant was obtained by centrifuging the filtrate at 4000 rpm for 15 minutes. The angle (90°) applied to the measurement with Rayleigh scattering. These processing methods can remove biological cells and macromolecules in the urine. This preparation stage in the next research was applied to detect various types of urine crystals.
Comparison of Wet and Dry EEG Electrodes Based On Brain Signals Characterization In Temporal and Anterior Frontal Areas Using Audio Stimulation
Authors: Faadhilah Afif Nur , Harke Pratama Sra , Haryanto Freddy , Nurul Khotimah Siti , Suprijadi
Published: June 2020

Electroencephalography (EEG) electrodes are divided into two types: dry and wet. In wet electrodes, a gel or saline liquid is used to increase the conductivity value, however, it tends to dry over time. On the contrary, gel or saline liquid is not required on the dry electrode. The use of certain types of electrode in EEG influences Power Spectral Density (PSD) of brain signals. Therefore, this study compared the EEG signal produced by Emotiv using the two different types of electrodes and a specific stimulus. This study was conducted using Emotiv EPOC (wet) and Insight (dry). The Temporal (T7 and T8) and Anterior Frontal (AF3 and AF4) electrodes from both devices were used to be compared. An audio stimulus that contains a story was chosen followed by a small task related to the story. The data acquisition was performed in 36 minutes to maintain the stability of the two types of electrodes. Three minutes of recordings in resting condition were conducted on both before and after given audio stimulus. Audio stimulation followed by a small task was performed for thirty minutes. The data analysis has consisted of EEG data pre-processing using centering and filtering the data, followed by PSD calculation using the Welch periodogram with Hanning window. The result showed that the decrement percentage of PSD after stimulation from wet was higher than dry electrodes.
Face pose estimation of SDM based on multi-template matching
Authors: Chen Hu , Gao Chaoqian , Li Tianping
Published: June 2020

This paper presents the face pose research of SDM algorithm and POSIT algorithm with multiple template matching. Firstly we detect the input face image, locate the feature points in the detected facial area, then compare the traditional SDM algorithm with the improved multi-template SDM algorithm, and then select the multi-template SDM algorithm. Feature point location is finally applied to the POSIT algorithm. Experimental results prove the effectiveness of the method and make it competitive.
Ultrasonic signal denoising technology based on SMP algorithm
Authors: Ailing Qi , Bingwen Bai , Guangming Zhang
Published: June 2020

Flip chip technology has been rapidly developed and widely used in the field of microelectronic packaging, and defect detection has received increasing attention. The ultrasonic detection method is used to detect the defect information of the packaged chip. However, the ultrasonic signal obtained during the detection process is disturbed by noise, which seriously affects the true information of the defect signal. For this problem, the matching matching pursuit (SMP) algorithm is used in combination with Gabor. The atomic library realizes adaptive matching of noisy ultrasonic signals. The linear combination of selected atoms is used to represent the denoised signals to achieve the denoising effect of noisy ultrasonic signals. The denoising effect of the SMP algorithm in the experiment is compared with the MP algorithm, and the results show that the denoising effect of the SMP algorithm is better.
An Improved Naive Bayesian Classification Model Based on Attribute Weighting
Authors: Yue Xi , Tang Mengxuan
Published: June 2020

Naive Bayesian model has good classification accuracy and efficiency, which makes it show good performance in many fields, especially in data mining and artificial intelligence. However, the traditional Naive Bayesian classification model ignores the attributes’ independence, resulting in the reduction of classification accuracy. For this reason, an improved model based on attribute fusion and weighting(AWNBC) is proposed, in which data fusion is realized by Spearman coefficient and weighting is realized by average confidence and ReliefF coefficient. The experiment classifies the selected data in UCI database. The result of experiments show that the improved classification model has good classification accuracy and efficiency.
Application of particle swarm optimization BP neural network algorithm in image compression
Authors: Wang Hai-jun , Jin Tao
Published: June 2020

In order to overcome the problems of weak global search ability, slow convergence speed and easy to fall into local minima in the process of image compression of BP neural network model, an image compression model based on particle swarm optimization algorithm and improved BP algorithm is proposed. In this model, a group of optimal approximate solutions of weights and thresholds of BP network are obtained through global search of particle swarm optimization according to objective function, and then the approximate solution is taken as the initial value of BP model, and the improved BP algorithm is used to conduct quadratic optimization training on these weights and thresholds to obtain the final image compression model. The experimental results show that with the same error accuracy, the quality of model compressed image reconstruction based on particle swarm BP neural network algorithm is significantly higher than that of BP and improved BP algorithm models.
Research on Internet of Things Technology and Its Application in Building Smart Communities
Authors: Huang Lu , Yuan Xiaoyu , Zhang Junyuan , Zhang Nannan , Li Jin , Wang Le
Published: June 2020

The Internet of Things technology is widely used in many industries and fields, including smart production and management, smart transportation and environmental protection, industrial monitoring and social security. Community construction is turning to smart communities. The construction of smart communities mainly uses network communication system facilities to realize the integrated networking of community residents and public facilities, to carry out information management of community residents, living and service facilities, and to improve the living environment by using modern technical measures. Aiming at the decentralization of IoT technology and smart community fusion products, an integrated information system platform needs to be built. In this article, the overall design framework of smart communities based on Internet of Things technologies is studied, and the smart community information management platform is divided into several main parts; Each part as Subsystem, discusses the basic functions of the subsystem, and finally realizes the intelligent construction of the smart community as a whole. We start work from the reality of the systematic construction of smart communities, combining with the latest Internet of Things technology, research and build a smart community information management platform with a unified architecture to achieve unified management and scheduling of smart community sub-products.
Research on Computer Security Guarantee Measures in Network Environment
Authors: Shi Zi-xin
Published: June 2020

In recent years, computer network technology has been rapidly developed and popularized, and it also plays an important role in people’s life and work. However, because the computer network itself has the characteristics of openness, it is easy to cause some security problems in the process of use. Computer networks not only affect people’s experience of using computer networks, but also cause certain economic losses in severe cases. Therefore, how to do a good job of computer security protection in the network environment has become an important issue that relevant technical personnel need to pay attention to.
Clustering algorithm based on analytic hierarchy process in LTE-V2V
Authors: Chang Xin , Yu Jianguo
Published: June 2020

As a hot area of urban transportation, the development of internet of vehicles and related technologies has received widespread attention. This paper proposes an analytic hierarchy process clustering algorithm (AHP-CA) based on the analytic hierarchy process in the LTE vehicle self-organizing network in the scenario of urban two-direction road intersections. The AHP-CA algorithm introduces the average distance between vehicles, normalizes the average relative speed, and uses the average relative motion direction as the vehicle eigenvalue for the clustering index. The analytic hierarchy process (Analytic Hierarchy Process, AHP) is used to determine the weights of different vehicle feature values, and the appropriate nodes are selected as cluster heads by combining the weights. The simulation results verify the stability of the cluster head under different vehicle speeds and communication distances.
A Variable Threshold Image Secret Sharing Method
Authors: Liu Shanzheng , Zhang Hang , Yu Ying , Cai Hongliang , Tang Dan
Published: June 2020

Image secret sharing has been widely discussed in recent years because of its high security. The threshold variable image secret sharing method is a hot research topic recently. The Lagrange interpolation method is easy to establish. Therefore, most of the existing secret sharing schemes are based on Lagrange interpolation polynomials. However, when the secret is updated, the existing secret sharing scheme needs to re-establish the polynomial, and the original computing resources cannot be utilized. When the cheater is found, it is not convenient to add or delete participants flexibly, resulting in a large waste of computer resources. Therefore, an image secret sharing method with variable threshold based on Newton interpolation method is proposed, which can reduce the computational complexity of the system and the amount of repeated computation. The experimental results show that the method is superior when the threshold is changed.
Research on the management information of scientific research institutes
Authors: Zhang Yun-jie
Published: June 2020

Through the analysis of the management information system, this paper analyzes the pain points in the process of enterprise information construction, and puts forward solutions from the aspects of master data management, process management, the application of ESB and other basic common platform construction. Finally, this paper analyzes the special situation of informatization construction in military research institutes, and probes into the difficulties and development direction of informatization construction.
Research on Surface Crack Detection Technology Based on Digital Image Processing
Authors: Xiao Yuling , Zhang Haoran
Published: June 2020

Digital image technology is used to monitor the fatigue and fracture of components under the operating conditions of mechanical parts, which is beneficial to monitor the causes of shallow cracks and whether the test results affect the life and safety of parts. The detection technology based on the digital image processing mechanism belongs to the category of non-destructive testing. It can quickly detect the surface cracks of mechanical parts and achieve accurate and effective evaluation of the surface defects of the parts. Based on the application of actual digital image processing technology, this paper presents an effective evaluation system for the defect detection of component surface cracks in image processing technology for programming tools used in simulation experiments, digital image processing algorithms, and design experimental software features, calculation methods and steps. After the above argument, the digital image processing method for surface cracks of parts is proposed. We can properly process the acquired images on the spot, obtain the values of piecewise linear stretching mean, median filtering, etc., and prove that digital image processing technology has the advantages of image detail processing the advantage is that it can realize rapid judgment and accurate detection of surface crack defects.
Target Tracking Based on Camshift Algorithm and Multi-feature Fusion
Authors: Chaoqian Gao , Hu Chen , Tianping Li
Published: June 2020

This paper proposes a new algorithm on the basics of Camshift algorithm and multi-feature fusion. First, the target area is weighted by the Gaussian function. Then LBP is used to extract local texture features, next fuse the texture features with the color features to obtain the color and texture histogram. Finally, for the purpose of tracking the target accurately and preventing occlusion, the Kalman filter is used to forecast the position of the moving target. From the comparison of the experimental results, the conclusion can be drawn that the new algorithm can effectively overcome the interference of objects and track the target accurately in a more complex environment.
Research on Weather Condition Influence Factors on Intelligent Connected Vehicle
Authors: Ma Bingbing , Li Wenqiang , Zhang Zhiguo , Song Rui
Published: June 2020

Now, there is no standard test method and flow for the performance of Intelligent Connected Vehicle under the complex weather conditions, which has greatly limited the development of Intelligent Connected Vehicle. This paper test and study the weather conditions that affect the performance of the on-board sensors, then analyse the weather conditions that affect Intelligent Connected Vehicle, the meteorological factors which affect Intelligent Connected Vehicle performance are obtained. It turns out that different conditions such as rain, fog, snow and light have different influence on the Intelligent Connected Vehicle, which provides the foundation for the performance test of Intelligent Connected Vehicle.
Active Defense Technology Based on Natural Software Diversity in Java Web Services
Authors: Liu Zhenwu , Zhang Zheng , Liu Hao , Zhang Gaofei , Chen Yuan
Published: June 2020

With the popular use of network application services and the growing number of users, web services have become the main target of hackers. Traditional single software has insufficient security protection against unknown threats and is prone to various vulnerabilities. In this paper, we adopt a new type of active defense strategy in java web services. At different application layers, we use existing components based on the natural software diversity to form different software stacks, and use dynamic scheduling mechanisms to change the attack surface at all times to obtain security protection. Our analysis shows that the flexibility of java web services using this defense strategy is enhanced, and the exploitability of its vulnerabilities is effectively reduced.
Research on Radar Servo System Based On Disturbance Observer Sliding Mode Control
Authors: Chen Siyuan , Guan Tao , Wang Yibo , Liu Yunfeng
Published: June 2020

Radar turntable servo system has strong friction at low speed, and the traditional PID control method due to its fixed parameters, poor stability and low control accuracy, is difficult to meet the high requirements of modern radar servo system for control quality. In this paper, a sliding mode controller with disturbance observer is proposed for the radar servo system. The friction is estimated by the exponential convergence disturbance observer; meanwhile the exponential approach law sliding mode controller is also designed. The simulation results show that the radar servo system controlled by sliding mode disturbance observer is better than the traditional PID controlled system. It can overcome the friction at low speed and improve the response speed and control accuracy of the radar servo system.
Analysis on the Research Approach and Trends of Medical Image Processing in China
Authors: Feng Yibo , Qiu Dawei , Cao Hui , Zhang Junzhong , Liu Jing
Published: June 2020

In order to explore the research approach and hotspots in the field of medical image processing in China, the authors retrieved related literature in the field of medical image processing in China from 2009 to 2019 in CNKI database, and preprocessed the retrieved data. Then Citespace was used to analyze the retrieved data of 1363 documents from 2009 to 2019, the paper counted the basic situation of the article’s publication time, subject, and analyzed the high frequency keywords, cited literatures with high frequency. The results show that the domestic medical image processing field has a high degree of attention to image segmentation, registration, and fusion. Deep learning, convolutional neural networks and transfer learning have been applied to medical image processing in recent years. This paper revealed domestic research trends in medical image processing, with a view to providing reference for research in medical image processing.
Prediction of Consumer Price Index based on Long Short-Term Memory Model
Authors: Ao Xiqin , Gong Yujie , Zuo Beibei
Published: June 2020

Consumer Price Index(CPI) is the main standard to identify inflation or deflation. Accurate prediction of CPI will help the government to implement macro-control and formulate price stabilization policies, so as to achieve the goal of building a moderately prosperous society. CPI is a non-stationary and non-linear time series, and has relevance in time dimension. In order to fully mine the correlation of CPI sequence in long and short time span, a method of predicting CPI using Long Short-Term Memory(LSTM) model is proposed. Taking historical CPI data of Anhui Province as the empirical analysis object, modeling and predicting are carried out. The prediction effect of LSTM is compared with classic time series model-Autoregressive Integrated Moving Average(ARIMA). According to the predicted results, LSTM model has significantly improvement in RMSE and MAE indicators compared with ARIMA model, indicating the LSTM model has higher prediction accuracy. The SDAE indicator of LSTM model is smaller than ARIMA model, indicating the LSTM model has better prediction stability.
Bearing fault diagnosis based on Empirical Mode Decomposition and Adaptive Network-based Fuzzy Inference System
Authors: Dong Wenzhi , Qi Chundong
Published: June 2020

The early fault characteristics of rolling bearings are weak and time-varying, and there are problems of modal aliasing and end effect in Empirical Mode Decomposition (EMD), and the decomposition effect is unstable. A bearing fault diagnosis method based on EMD and Adaptive Network-based Fuzzy Inference System (ANFIS) is proposed. Firstly, the signal is decomposed into several Intrinsic Mode Functions (IMF) by EMD, then multiple fault feature quantities are obtained from the IMF1 component to construct the fault feature set. Finally, the extracted fault feature set is classified and identified by ANFIS. The experimental results show that the proposed method has high diagnostic accuracy and can effectively identify the fault type.
Research on Power Market Stability and Risk Management Based on Heterogeneous Information Sources
Authors: Chunxiao Liu , Zhiyong Li , Qiang Zhou , Peishen Zhang
Published: June 2020

The development of power markets in various countries in the world and the gradual formation of China’s power market require academic circles to provide research theories related to the power market to support them. In the competitive environment, fundamental changes have taken place in power production, trading and consumption. The operating conditions of the system are harsh and uncertain. The problem of safety and stability is becoming more and more prominent. Judging from the international and domestic development situation, it is a historical necessity for electricity to enter the market. When electric power goes to market, it is necessary to bring electric power industry into the framework of market economy. Stability is the basis for the normal operation and sustainable development of the system, so it is more urgent to promote the healthy development of the power market by the research results of power market stability. The risk analysis method reflects the mathematical expectation of loss by the product of accident probability and accident consequence, so it can effectively unify the stability and economy on the dimension of currency, and realize the analysis and decision-making of technical and economic integration.
Research on Communication Transmission Management Strategy Based on Artificial Neural Network Algorithm
Authors: Zeng Huaxiang
Published: June 2020

Communication engineering technology belongs to a main component of electronic engineering. Its main operation principle is to transmit information in the form of light wave or electronic wave to achieve the effect and purpose of timely transmission and high-speed transmission. The real development of communication enterprises cannot only depend on the development of communication technology transmission, but also need to manage all aspects of communication technology transmission. Communication engineering technology transmission, as a key project of communication engineering, plays a key role in improving the competitiveness and market share of communication enterprises. Optimize and integrate the existing resources, manage the cost of each work in the communication engineering technology transmission, and improve the efficiency of technology transmission to the greatest extent, so as to ensure the transmission speed and quality. This paper analyzes the management problems of communication engineering technology transmission through the artificial neural network algorithm, designs the artificial neural network for information transmission loss prediction, and puts forward the corresponding solutions in order to promote the development of communication enterprises.
Breaking Cause Analysis on a 110 kV Overhead Grounding Wire (OGW)
Authors: Zheng Jianjun , Han Kuo , Wang Yingjun , Shi Xianda
Published: June 2020

An in-serviced 110kV overhead grounding wire (OGW) was found to be broken, and the fracture cause was then studied by means of macroscopic morphology and metallographic observations, fracture microanalysis and mechanical properties testing. The results revealed that the fracture of OGW was mainly resulted from the lightning stroke, which was mainly informed from the craters on the surface of the broken wire steel strand by fracture morphology observation results. The lightning currents led to a rapid temperature rise, which eventually caused the surface OGW to be broken by tension after fusing or partially fusing under high temperature. At last, it was advised that coarser steel strands should be used in areas with frequent lightning strikes to improve the thermal stability of OGW, and the metal technical supervision in the operation process of high voltage transmission lines should also be strengthened.
Based on Randomly Executed Sequence and GA-SVC Applied on Air Quality Analysis
Authors: Wei Fan , Sun Honglin
Published: June 2020

Air quality is a key factor affecting people’s daily travel. In order to analyze and classify air quality, and to solve the problem of low classification accuracy, this paper mainly studied the SVC (multi-classification support vector machine) Algorithm based on the random sequence selection of optimized parameters through Genetic Algorithm. Aiming at the problems of insufficient classification accuracy in current multi-feature sequence analysis and unstable parameter selection in SVC algorithm, comprehensive classification evaluation of data is carried out by analyzing data features and correlation among features and integrating genetic algorithm into SVC to optimize parameter selection, so as to improve classification accuracy. The experimental results show that the classification accuracy has been improved by 5% on average with the current popular decision tree classification algorithm, unoptimized SVC algorithm and KNN algorithm.
Cause Analysis of the Crooked High Voltage End Fittings for a 220kV Composite Insulator in-service
Authors: Zheng Jianjun , Han Kuo , Wang Yingjun , Shi Xianda
Published: June 2020

The high voltage end fitting for an in-serviced 220kV composite insulator was found to be crooked by the transmission line inspector, and the deformed cause was then investigated by digital X-ray imaging, chemical composition analysis, metallographic observation and mechanical properties testing in this paper. The results indicated that both the material quality and mechanical properties of the composite insulator high voltage (HV) end fitting met the standard requirements. And the main reason for the crooking of HV end fitting was the effect of abnormal force, such as falling from high position, impact of heavy objects. At last, it was advised that the supervision on the installation quality of fittings and the inspection of in-service composite insulator fittings should be strengthened. In addition, composite insulator with deformed or fractured end fitting should be timely handled, avoiding similar metal section failures.
Airborne multi-sensor target recognition method based on weighted fuzzy reasoning network and improved DS evidence theory
Authors: Zhang Hubiao , Wang Xing , Wu Xiaotian , Zhou Yipeng , Chen You
Published: June 2020

Difficult obtainment of basic probability assignment (BPA) and inaccurate recognition due to conflicting data are the problems in applying Dempster-Shafer (DS) evidence theory to airborne multi-sensor target recognition. In order to effectively deal with them, an airborne multi-sensor target recognition method based on weighted fuzzy reasoning network (WFRN) and improved Dempster-Shafer (IDS) evidence theory is proposed in this paper. First, the feature vector consisting of 5 feature components is constructed. And then a 4-layer WFRN consisting of 3 kinds of basic units is established to obtain BPA of the feature vector. Finally, conflict data is processed through IDS evidence theory to obtain the final fusion recognition result. The simulation results indicate that the proposed airborne multi-sensor target recognition method is able to obtain BPA reasonably and deal with conflict information.
Automatic Recommendation Method of Network Data Based on Big Data Technology
Authors: Huang Xiaorui , Guo Shuai , Zhang Yunchu , Zhang Peidong , Xu Shiyuan
Published: June 2020

With the advent of the Internet era in modern society, the surge in network data has greatly increased the difficulty for users to obtain demand information. In order to provide customers with information that may be of interest to them, this paper proposes a belief collaborative recommendation optimization algorithm, which introduces DP synthesis rules and Smets synthesis rules to improve traditional DS synthesis rules and establishes network data recommendation models. This method realizes automatic recommendation of network data according to the self-property and historical behavior data of network customers. The experimental results show that the automatic recommendation method for network data proposed in this paper has higher recommendation accuracy.
Visualization Classification and Prediction Based on Data Mining
Authors: Wei Ziyi , Zhang Zhiyong , Gu WeiWei , Fang Nan
Published: June 2020

The paper aims to solve huge amounts and noise of current internet information. In order to better excavate the user’s interests and provide accurate recommendations, improve the Internet environment and services and accurately analyze and evaluate the behavior of large-scale user groups. This article compares web pages with sentences in natural language, and uses the natural language processing algorithm Word2vec to extract the feature vectors of massive web pages browsed by users. PCA has been reduced to two dimensions, and webpage visualization and logistic regression have been implemented to classify webpages. A series of user clicks on webpages can be viewed as a walk in n-dimensional space. Probabilistic language models and Monte Carlo simulations are used as the next step for users. Click behavior to make predictions. Experiments show that the machine learning processing natural language algorithm used in this paper has a good performance in classification and prediction accuracy.