Yuhong Zhang^1,*, Qinqin Wang¹, Yuling Li¹, Xindong Wu²

CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 285-297, 2018, DOI: 10.3970/cmc.2018.02604

Abstract Recently, the effectiveness of neural networks, especially convolutional neural networks, has been validated in the field of natural language processing, in which, sentiment classification for online reviews is an important and challenging task. Existing convolutional neural networks extract important features of sentences without local features or the feature sequence. Thus, these models do not perform well, especially for transition sentences. To this end, we propose a Piecewise Pooling Convolutional Neural Network (PPCNN) for sentiment classification. Firstly, with a sentence presented by word vectors, convolution operation is introduced to obtain the convolution feature map vectors. Secondly, these vectors are segmented according… More >

Shengqun Fang¹, Zhiping Cai^1,*, Wencheng Sun¹, Anfeng Liu², Fang Liu³, Zhiyao Liang⁴, Guoyan Wang⁵

CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 419-433, 2018, DOI: 10.3970/cmc.2018.02289

Abstract By using efficient and timely medical diagnostic decision making, clinicians can positively impact the quality and cost of medical care. However, the high similarity of clinical manifestations between diseases and the limitation of clinicians’ knowledge both bring much difficulty to decision making in diagnosis. Therefore, building a decision support system that can assist medical staff in diagnosing and treating diseases has lately received growing attentions in the medical domain. In this paper, we employ a multi-label classification framework to classify the Chinese electronic medical records to establish corresponding relation between the medical records and disease categories, and compare this method… More >

Ya Tu¹, Yun Lin¹, Jin Wang^2,3,*, Jeong-Uk Kim⁴

CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 243-254, 2018, DOI:10.3970/cmc.2018.01755

Abstract Deep Learning (DL) is such a powerful tool that we have seen tremendous success in areas such as Computer Vision, Speech Recognition, and Natural Language Pro-cessing. Since Automated Modulation Classification (AMC) is an important part in Cognitive Radio Networks, we try to explore its potential in solving signal modula-tion recognition problem. It cannot be overlooked that DL model is a complex mod-el, thus making them prone to over-fitting. DL model requires many training data to combat with over-fitting, but adding high quality labels to training data manually is not always cheap and accessible, especially in real-time system, which may counter… More >

Ravikumar Gurusamy¹, Dr Vijayan Subramaniam²

CMC-Computers, Materials & Continua, Vol.53, No.2, pp. 91-108, 2017, DOI:10.3970/cmc.2017.053.091

Abstract A new method for the denoising, extraction and tumor detection on MRI images is presented in this paper. MRI images help physicians study and diagnose diseases or tumors present in the brain. This work is focused towards helping the radiologist and physician to have a second opinion on the diagnosis. The ambiguity of Magnetic Resonance (MR) image features is solved in a simpler manner. The MRI image acquired from the machine is subjected to analysis in the work. The real-time data is used for the analysis. Basic preprocessing is performed using various filters for noise removal. The de-noised image is… More >