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Performance Evaluation of Multiple Classifiers for Predicting Fake News
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作者 Arzina Tasnim Md. Saiduzzaman +2 位作者 Mohammad Arafat Rahman jesmin akhter Abu Sayed Md. Mostafizur Rahaman 《Journal of Computer and Communications》 2022年第9期1-21,共21页
The rise of fake news on social media has had a detrimental effect on society. Numerous performance evaluations on classifiers that can detect fake news have previously been undertaken by researchers in this area. To ... The rise of fake news on social media has had a detrimental effect on society. Numerous performance evaluations on classifiers that can detect fake news have previously been undertaken by researchers in this area. To assess their performance, we used 14 different classifiers in this study. Secondly, we looked at how soft voting and hard voting classifiers performed in a mixture of distinct individual classifiers. Finally, heuristics are used to create 9 models of stacking classifiers. The F1 score, prediction, recall, and accuracy have all been used to assess performance. Models 6 and 7 achieved the best accuracy of 96.13 while having a larger computational complexity. For benchmarking purposes, other individual classifiers are also tested. 展开更多
关键词 Fake News Machine Learning TF-IDF CLASSIFIER Estimator F1 Score RECALL Precision Voting Classifiers Stacking Classifier Soft Voting Hard Voting
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Data Classification Using Combination of Five Machine Learning Techniques
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作者 Md. Habibur Rahman jesmin akhter +1 位作者 Abu Sayed Md. Mostafizur Rahaman Md. Imdadul Islam 《Journal of Computer and Communications》 2021年第12期48-62,共15页
Data clustering plays a vital role in object identification. In real life we mainly use the concept in biometric identification and object detection. In this paper we use Fuzzy Weighted Rules, Fuzzy Inference System (... Data clustering plays a vital role in object identification. In real life we mainly use the concept in biometric identification and object detection. In this paper we use Fuzzy Weighted Rules, Fuzzy Inference System (FIS), Fuzzy C-Mean clustering (FCM), Support Vector Machine (SVM) and Artificial Neural Network (ANN) to distinguish three types of Iris data called Iris-Setosa, Iris-Versicolor and Iris-Virginica. Each class in the data table is identified by four-dimensional vector, where vectors are used as the input variable called: Sepal Length (SL), Sepal Width (SW), Petal Length (PL) and Petal Width (PW). The combination of five machine learning methods provides above 98% accuracy of class identification. 展开更多
关键词 Co-Variance of Fuzzy Rule Objective Function Surface Plot Confusion Matrix Scatterplot and Accuracy of Detection
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Traffic Modelling of Low Dense Femtocellular Network for Long Term Evolution
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作者 jesmin akhter Abu Sayed Md. Mostafizur Rahaman +1 位作者 Md. Imdadul Islam M. R. Amin 《Journal of Computer and Communications》 2019年第12期88-101,共14页
One of the features of Long Term Evolution (LTE) is the deployment of femtocells as the underlain cell of a macrocell without any intervention of frequency planning to offload the traffic. In this paper we used Markov... One of the features of Long Term Evolution (LTE) is the deployment of femtocells as the underlain cell of a macrocell without any intervention of frequency planning to offload the traffic. In this paper we used Markov chain to derive the expression of blocking probability for both macro and femtocell in terms of traffic parameters of the network. We developed an analytical model to find the expression of probability of forced termination (FT) using combination of mobility model and probability tree considering low dense femtocellular network. Two different trees were designed: a newly originating call which starts its session in a femtocell and that of in a macro cell. The link parameters of small scale fading of wireless network under Multiple Input Multiple Output (MIMO) are combined with the proposed traffic model to get the probability of FT of a real-life network. A new state transition chain was also developed including its solution for LTE traffic of variable bandwidth (BW) and a comparison was made with Erlang’s traffic model. 展开更多
关键词 RAYLEIGH and Nakagami-m FADING MIMO RB FORCED Termination OUTAGE Probability
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Determination of Array Gain of Single Hop to Achieve the Performance of a 2-Hop Wireless Link
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作者 Abu Sayed Md. Mostafizur Rahaman jesmin akhter +1 位作者 Md. Rafsan Jani Md. Imdadul Islam 《Journal of Computer and Communications》 2018年第7期84-98,共15页
In adaptive beamforming system adaptive algorithm of digital filter is applied to update the weighting vector of the antenna elements to get antenna gain along the desired direction and attenuation along the jammer. T... In adaptive beamforming system adaptive algorithm of digital filter is applied to update the weighting vector of the antenna elements to get antenna gain along the desired direction and attenuation along the jammer. The objective of the paper is to evaluate the threshold gain of the adaptive beam former along the line of sight (LOS) between the transmitter and the receiver (including jammer suppression) to make the single hop link comparable with 2-hop link. The single hop and 2-hop communication systems are compared in context of symbol error rate (SER) under fading condition theoretically and verified by simulation. Finally we evaluate the numerical value of threshold gain of adaptive beamformer of two antenna elements under Rayleigh and Nakagami-m fading conditions. 展开更多
关键词 ARRAY Antenna System BER THRESHOLD ARRAY GAIN Side LOBE Canceller Path Loss
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