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PENGAMANAN POLYALPHABETIC DENGAN AFFINE CIPHER BERDASARKAN BARISAN FIBONACCI
Majalah Ilmiah Matematika dan Statistika Pub Date : 2019-09-02 DOI: 10.19184/mims.v19i2.17274
Lestari Fidi Astuti, Kiswara Agung Santoso, Ahmad Kamsyakawuni
{"title":"PENGAMANAN POLYALPHABETIC DENGAN AFFINE CIPHER BERDASARKAN BARISAN FIBONACCI","authors":"Lestari Fidi Astuti, Kiswara Agung Santoso, Ahmad Kamsyakawuni","doi":"10.19184/mims.v19i2.17274","DOIUrl":"https://doi.org/10.19184/mims.v19i2.17274","url":null,"abstract":"Affine cipher is a classic cryptographic algorithm substitution technique. Substitution technique is the encryption process for every character in the plaintext will be subtituted by another character. Affine cipher uses two types of keys. Each character of plaintext to be encrypted substituted by the same key. This research discusses about modify one of the key affine cipher, to produce a different key that will be substituted with each plaintext character. Key modifications are made by the Fibonacci sequence rules. This study also compares affine cipher and key modification affine cipher by finding corelation coeffiecient values. The results obtained from the comparison of the two algorithms, encryption that uses affine cipher key modification is better than affine cipher. \u0000Keywords: Cryptography, Affine Cipher, Fibonacci, Correlation Value","PeriodicalId":264607,"journal":{"name":"Majalah Ilmiah Matematika dan Statistika","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131456555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
ANALISIS STRUCTURAL EQUATION MODELING (SEM) DENGAN MULTIPLE GROUP MENGGUNAKAN R 分析结构方程模型(sem)邓安多群蒙古纳坎等
Majalah Ilmiah Matematika dan Statistika Pub Date : 2019-09-01 DOI: 10.19184/mims.v19i2.17272
Holipah Holipah, I. Tirta, Dian Anggraeni
{"title":"ANALISIS STRUCTURAL EQUATION MODELING (SEM) DENGAN MULTIPLE GROUP MENGGUNAKAN R","authors":"Holipah Holipah, I. Tirta, Dian Anggraeni","doi":"10.19184/mims.v19i2.17272","DOIUrl":"https://doi.org/10.19184/mims.v19i2.17272","url":null,"abstract":"Structural Equation Model (SEM) is a statistical technique with simultaneous processing involves measurement errors, indicator variables, and latent variables. SEM is used to test hypotheses that state the relationships between latent variables when latent variables have been assessed through each of the indicator variables. Multiple Group SEM is a basic model analysis that uses more than one sample. This analysis aims to determine whether the components or models of measurement and structural models are invariant for the two sample groups. In this study, the data generated by some requirements. First, the data generated with sample size n = 250. The first generated data is homogeneous data where the measurement model is the same as the structural model in group 1 and group 2, while the second data is non-homogeneous data where the measurement model and the structural model in group 1 and group 2 is not the same. The data was analyzed using the help of the lavaan package available in R to obtain SEM estimation results and Goodness of Fit Model from some data that was formed. From the results of the merger of the two groups, it shows that the invariant of the two models with the largest df (63) which is Fit Mean model states the simplest model. However, the smallest df (48) with Fit.configural model states the most complex model. \u0000Keywords: SEM, Multiple Group, R Program","PeriodicalId":264607,"journal":{"name":"Majalah Ilmiah Matematika dan Statistika","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122569829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
PENYANDIAN CITRA MENGGUNAKAN ALGORITMA 4D PLAYFAIR CIPHER DENGAN PEMBANGKITAN KUNCI MODIFIKASI LINEAR FEEDBACK SHIFT REGISTER 使用改进密钥生成线性反馈移位寄存器的 4d playfair 密码算法进行图像编码
Majalah Ilmiah Matematika dan Statistika Pub Date : 2019-05-13 DOI: 10.19184/mims.v19i1.17261
Rivi Tri Rahayu
{"title":"PENYANDIAN CITRA MENGGUNAKAN ALGORITMA 4D PLAYFAIR CIPHER DENGAN PEMBANGKITAN KUNCI MODIFIKASI LINEAR FEEDBACK SHIFT REGISTER","authors":"Rivi Tri Rahayu","doi":"10.19184/mims.v19i1.17261","DOIUrl":"https://doi.org/10.19184/mims.v19i1.17261","url":null,"abstract":"The fast development of sophisticated technology make it easier for someone to send a message to other but can also make it easier for third parties to sabotage the content of the message, so a technique called cryptography is needed to secure the message. Image encoding is one of the techniques for securing messages in cryptography. In enhancing security in image encoding, this study discusses about Playfair Cipher, 3D Playfair Cipher and 4D Playfair Cipher with key generation using LFSR Modification. The encryption process using 4D Playfair Cipher with key generation using LFSR Modification visually produces cipher image that is different from the original image compared to using Playfair Cipher and 3D Playfair Cipher. In the decryption process using Playfair Cipher, 3D Playfair Cipher and 4D Playfair Cipher-Modification LFSR can return cipher image to its original image. The result of the study shows that the proposed method can be used to secure the message. \u0000Keywords: Playfair Cipher, 3D Playfair Cipher, 4D Playfair Cipher, LFSR","PeriodicalId":264607,"journal":{"name":"Majalah Ilmiah Matematika dan Statistika","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133992414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
PENERAPAN ALGORITMA PENGUINS SEARCH OPTIMIZATION (PeSOA) DAN ALGORITMA MIGRATING BIRDS OPTIMIZATION (MBO) PADA PERMASALAHAN KNAPSACK 0-1
Majalah Ilmiah Matematika dan Statistika Pub Date : 2019-04-05 DOI: 10.19184/mims.v19i2.17270
R. Abdullah
{"title":"PENERAPAN ALGORITMA PENGUINS SEARCH OPTIMIZATION (PeSOA) DAN ALGORITMA MIGRATING BIRDS OPTIMIZATION (MBO) PADA PERMASALAHAN KNAPSACK 0-1","authors":"R. Abdullah","doi":"10.19184/mims.v19i2.17270","DOIUrl":"https://doi.org/10.19184/mims.v19i2.17270","url":null,"abstract":"Every person would want maximum profit with as little as possible resources or capital. One example in everyday life is the problem of limited storage media but is required to get the maximum benefit. From this problem comes the term known as the knapsack problem. One of the problems with Knapsack is knapsack 0- 1, where knapsack 0-1 is a problem of storing goods where the item will be completely inserted or not at all. Completion of knapsack 0-1 problems can be helped using a metaheuristic algorithm. Metaheuristic algorithms include the Penguins Search Optimization (PeSOA) algorithm and the Migration Birds Optimization (MBO) algorithm. This study aims to determine the resolution of knapsack 0-1 problems using the Penguins Search Optimization (PeSOA) algorithm and the Migration Birds Optimization (MBO) algorithm and compare the optimal solutions obtained. This research method is divided into three main parts. First take data that includes the name of the item, the purchase price, the selling price and the weight of each item. The second is applying the Penguins Search Optimization (PeSOA) algorithm and the Migration Birds Optimization algorithm (MBO) on 0-1 knapsack problems. The third program is made to facilitate the calculation of data with the help of Matlab R2015b software. The results of this study found that both algorithms both reached the optimal solution, but the convergence and running time obtained were different. The Migrating Birds Optimization (MBO) algorithm is faster converging than the Penguins Search Optimization (PeSOA) algorithm to get the optimal solution. And also the Migrating Birds Optimization (MBO) algorithm has better running time than the Penguins Search Optimization (PeSOA) algorithm to achieve maximum iteration. \u0000Keywords: Whale optimization algorithm, multi knapsack 0-1 problem with multiple constraints.","PeriodicalId":264607,"journal":{"name":"Majalah Ilmiah Matematika dan Statistika","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115443223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
PERBAIKAN MODEL SEASONAL ARIMA DENGAN METODE ENSEMBLE KALMAN FILTER PADA HASIL PREDIKSI CURAH HUJAN 区域模型改进与可持久性卡尔曼滤波器对降水预测结果的方法
Majalah Ilmiah Matematika dan Statistika Pub Date : 2019-03-12 DOI: 10.19184/mims.v19i1.17262
Dwi Anugrah Wibisono, Dian Anggraeni, Alfian Futuhul Hadi
{"title":"PERBAIKAN MODEL SEASONAL ARIMA DENGAN METODE ENSEMBLE KALMAN FILTER PADA HASIL PREDIKSI CURAH HUJAN","authors":"Dwi Anugrah Wibisono, Dian Anggraeni, Alfian Futuhul Hadi","doi":"10.19184/mims.v19i1.17262","DOIUrl":"https://doi.org/10.19184/mims.v19i1.17262","url":null,"abstract":"Forecasting is a time series analytic that used to find out upcoming improvement in the next event using past events as a reference. One of the forecasting models that can be used to predict a time series is Kalman Filter method. The modification of the estimation method of Kalman Filter is Ensemble Kalman Filter (EnKF). This research aims to find the result of EnKF algorithm implementation on SARIMA model. To start with, preticipation forecast data is changed in the form of SARIMA model to obtain some SARIMA model candidates. Next, this best model of SARIMA applied to Kalman Filter models. After Kalman Filter models created, forecasting could be done by applying pass rainfall data to the models. It can be used to predict rainfall intensity for next year. The quality of this forecasting can be assessed by looking at MAPE’s value and RMSE’s value. This research shows that enkf method relative can fix sarima method’s model, proved by mape and rmse values which are smaller and indicate a more accurate prediction. \u0000Keywords: Ensemble Kalman Filter, Forecast, SARIMA","PeriodicalId":264607,"journal":{"name":"Majalah Ilmiah Matematika dan Statistika","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124299042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
PENERAPAN DRAGONFLY OPTIMIZATION ALGORITHM (DOA) PADA PERMASALAHAN MULTIPLE CONSTRAINTS BOUNDED KNAPSACK 蜻蜓优化算法（Doa）在多约束有界数包中的应用
Majalah Ilmiah Matematika dan Statistika Pub Date : 2019-03-01 DOI: 10.19184/mims.v19i1.17264
Laylatul Febriana Nilasari, K. A. Santoso, Abduh Riski
{"title":"PENERAPAN DRAGONFLY OPTIMIZATION ALGORITHM (DOA) PADA PERMASALAHAN MULTIPLE CONSTRAINTS BOUNDED KNAPSACK","authors":"Laylatul Febriana Nilasari, K. A. Santoso, Abduh Riski","doi":"10.19184/mims.v19i1.17264","DOIUrl":"https://doi.org/10.19184/mims.v19i1.17264","url":null,"abstract":"Optimization is very useful in almost all fields in running a business effectively and efficiently to achieve the desired results. This study solves the problem of multiple constraints bounded knapsack by implementing DOA. The problem of multiple constraints bounded knapsack has more than ones constraint with objects that are entered into the storage media, the dimensions can be partially or completely included, but the number of objects is limited. The purpose of this study is to determine the results of using DOA to solve multiple constraits bounded knapsack and the effectiveness of DOA compared to the results of the Simplex method. The data used in this study are primary data. There are ten parameters to be tested, namely population parameters, maximum iteration, s, a, c, f, e and range. The trial results of the ten parameters show that the best value of the parameters is neither too large nor too small. If the best value is too large then the position of the dragonfly will be randomized so that it is not clear the position of the dragonfly and if it is too small the best value then the change is not visible. In addition, based on the results of the final experiment it can be seen that DOA is less effective in solving multiple constraints bounded knapsack problems, because of many experiments there is no solution similar to Simplex. DOA approach to optimal, seen from a small deviation. \u0000Keywords: DOA, Knapsack, Multiple constraints bounded knapsack problem.","PeriodicalId":264607,"journal":{"name":"Majalah Ilmiah Matematika dan Statistika","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133820175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
PERBANDINGAN ALGORITMA PARTICLE SWARM OPTIMIZATION (PSO) DAN ALGORITMA GLOWWORM SWARM OPTIMIZATION (GSO) DALAM PENYELESAIAN SISTEM PERSAMAAN NON LINIER
Majalah Ilmiah Matematika dan Statistika Pub Date : 2019-03-01 DOI: 10.19184/mims.v19i1.17263
A. Azmi, Rusli Hidayat, M. Arif
{"title":"PERBANDINGAN ALGORITMA PARTICLE SWARM OPTIMIZATION (PSO) DAN ALGORITMA GLOWWORM SWARM OPTIMIZATION (GSO) DALAM PENYELESAIAN SISTEM PERSAMAAN NON LINIER","authors":"A. Azmi, Rusli Hidayat, M. Arif","doi":"10.19184/mims.v19i1.17263","DOIUrl":"https://doi.org/10.19184/mims.v19i1.17263","url":null,"abstract":"Non-linear equation system is one of the mathematics problems which difficult to solve. Several methods have been introduced to solve the problems. Newton-Raphson method is the most common and widely used as the basis for evolving the latest numerical methods. However, this method requires the derivative of each equation with respect to every variable when calculating the Jacobian. Naturally, obtaining the derivative is challenging in certain cases. In addition, it needs a proper initial value to obtain the converged solution. Therefore, the new technique with a simple random initial value is urgently needed. In this study, it is shown the implementation of the two metaheuristic optimization methods, including Particle Swarm Optimization (PSO) and the Glowworm Swarm Optimization (GSO) to estimate the solution of a non-linear equation system. Several examples of nonlinear equation system were used for evaluating and testing the performance and the accuracy of both algorithms. In this simulation, the results show that PSO converged to the exact solution (global optimum) better than Glowworm Swarm Optimization (GSO). \u0000Keywords: Non-Linear Equation Systems, Particle Swarm Optimization (PSO), Glowworm Swarm Optimization (GSO)","PeriodicalId":264607,"journal":{"name":"Majalah Ilmiah Matematika dan Statistika","volume":"296 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114388753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
KAJIAN FRAKTAL i-FIBONACCI WORD GENERALISASI GANJIL DENGAN MENGGUNAKAN L-SYSTEM
Majalah Ilmiah Matematika dan Statistika Pub Date : 2018-11-26 DOI: 10.19184/mims.v19i1.17258
Riza Umami
{"title":"KAJIAN FRAKTAL i-FIBONACCI WORD GENERALISASI GANJIL DENGAN MENGGUNAKAN L-SYSTEM","authors":"Riza Umami","doi":"10.19184/mims.v19i1.17258","DOIUrl":"https://doi.org/10.19184/mims.v19i1.17258","url":null,"abstract":"The i-Fibonacci Words are words over {0,1}. The i-Fibonacci Word can be associated with a fractal curve by using odd-even drawing rule and L-System methods, then also known as an i-Fibonacci Word fractal. L-System is one of methods that is used to create objects with repetitive self-similiarity. Framework of L-System consists of axiom and rules. L-System is a parallel rewriting system with existing rules. The purpose of this research is to look for the LSystem rules of i-Fibonacci Word special for odd i, then look how its characteristics. The LSystem rules for i-Fibonacci Word odd i are divided into two types, the rules for i=1 and the others odd i. The characteristic of i-Fibonacci Word fractal is the more generation and i value of fractal, then the more segments and archs of fractal curve. Next, the words of i-Fibonacci Word fractal segments number is a subwords of the i-Fibonacci Word digit numbers. It is also known that the fractal curve will be stretched as the decreased angle. \u0000Keywords: Fractal, i-Fibonacci Word, L-System","PeriodicalId":264607,"journal":{"name":"Majalah Ilmiah Matematika dan Statistika","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125485313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
PERBAIKAN CITRA INFRA MERAH DENGAN METODE CELLULAR AUTOMATA 用CELLULAR AUTOMATA方法修复红外图像
Majalah Ilmiah Matematika dan Statistika Pub Date : 2018-09-03 DOI: 10.19184/mims.v18i2.17249
Annisa Yuniar Hidayah, Abduh Riski, Ahmad Kamsyakawuni
{"title":"PERBAIKAN CITRA INFRA MERAH DENGAN METODE CELLULAR AUTOMATA","authors":"Annisa Yuniar Hidayah, Abduh Riski, Ahmad Kamsyakawuni","doi":"10.19184/mims.v18i2.17249","DOIUrl":"https://doi.org/10.19184/mims.v18i2.17249","url":null,"abstract":"Image enhancement is needed because not all images have good quality, such as noise, too low contrast or blurry image. These problems are commonly found in images generated from infrared cameras, therefore this study uses infrared imagery as an image to be corrected. The method that will be used to improve the image, namely Cellular Automata method. The edge detection using the Prewitt operator will be used as the initial state of Cellular Automata cells. The results obtained from this research is Cellular Automata method can improve the quality of infrared image well. Visually, the Cellular Automata method successfully improves image contrast and retains the infrared image detail so as not to reduce the value of information from the image. Calculated using the Linear Index of Fuzziness, the results of the Cellular Automata method are better only on some imagery only when compared to the Histogram Equalization mode. \u0000Keywords: Infrared Image, Image Enhancement, Cellular Automata","PeriodicalId":264607,"journal":{"name":"Majalah Ilmiah Matematika dan Statistika","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128089111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
PENERAPAN COCKROACH SWARM OPTIMIZATION ALGORITHM (CSOA) PADA PENYELESAIAN PERSAMAAN POLINOMIAL YANG MEMILIKI AKAR KOMPLEKS
Majalah Ilmiah Matematika dan Statistika Pub Date : 2018-09-03 DOI: 10.19184/mims.v18i2.17251
Ema Fahma Farikha, Rusli Hidayat, M. Arif
{"title":"PENERAPAN COCKROACH SWARM OPTIMIZATION ALGORITHM (CSOA) PADA PENYELESAIAN PERSAMAAN POLINOMIAL YANG MEMILIKI AKAR KOMPLEKS","authors":"Ema Fahma Farikha, Rusli Hidayat, M. Arif","doi":"10.19184/mims.v18i2.17251","DOIUrl":"https://doi.org/10.19184/mims.v18i2.17251","url":null,"abstract":"In this paper, we use a metaheuristic algorithm for solving non-linear equations (polynomial equations) which have a set of complex roots (complex numbers). The metaheuristic algorithm is the Cockroach Swarm Optimization Algorithm (CSOA) which imitate various types of natural cockroach behaviors such as chase-swarming, dispersing and ruthlessness when hunting for food sources. In this study, several examples of non-linear polynomial equations were used for evaluating the accuracy of CSOA. In this simulation, the accuracy comparison has been accomplished. It is shown that CSOA results are more accurate compared to the Newton-Raphson results. \u0000Keywords: Cockroach Swarm Optimization Algorithm, Complex roots of polynomial, Newton-Raphson, Non-Linear equation.","PeriodicalId":264607,"journal":{"name":"Majalah Ilmiah Matematika dan Statistika","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128096517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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