Anman Zhang¹, Bohan Li^{1, 2, 3, *}, Wenhuan Wang¹, Shuo Wan¹, Weitong Chen⁴

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1499-1514, 2020, DOI:10.32604/cmc.2020.09962

Abstract Active learning has been widely utilized to reduce the labeling cost of supervised learning. By selecting specific instances to train the model, the performance of the model was improved within limited steps. However, rare work paid attention to the effectiveness of active learning on it. In this paper, we proposed a deep active learning model with bidirectional encoder representations from transformers (BERT) for text classification. BERT takes advantage of the self-attention mechanism to integrate contextual information, which is beneficial to accelerate the convergence of training. As for the process of active learning, we design an instance selection strategy based on… More >

Hongping Wu¹, Yuling Liu^{1, *}, Jingwen Wang²

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1309-1321, 2020, DOI:10.32604/cmc.2020.010172

Abstract Text classification has always been an increasingly crucial topic in natural language processing. Traditional text classification methods based on machine learning have many disadvantages such as dimension explosion, data sparsity, limited generalization ability and so on. Based on deep learning text classification, this paper presents an extensive study on the text classification models including Convolutional Neural Network-Based (CNN-Based), Recurrent Neural Network-Based (RNN-based), Attention Mechanisms-Based and so on. Many studies have proved that text classification methods based on deep learning outperform the traditional methods when processing large-scale and complex datasets. The main reasons are text classification methods based on deep learning… More >

Zhichun Jia^{1, 2}, Qiuyang Han¹, Yanyan Li¹, Yuqiang Yang¹, Xing Xing^{1, 2, *}

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1221-1235, 2020, DOI:10.32604/cmc.2020.09722

Abstract With the development of the service-oriented computing (SOC), web service has an important and popular solution for the design of the application system to various enterprises. Nowadays, the numerous web services are provided by the service providers on the network, it becomes difficult for users to select the best reliable one from a large number of services with the same function. So it is necessary to design feasible selection strategies to provide users with the reliable services. Most existing methods attempt to select services according to accurate predictions for the quality of service (QoS) values. However, because the network and… More >

Ravi Samikannu^{1, *}, Rohini Ravi², Sivaram Murugan³, Bakary Diarra⁴

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1133-1142, 2020, DOI:10.32604/cmc.2020.08578

Abstract The identification of brain tumors is multifarious work for the separation of the similar intensity pixels from their surrounding neighbours. The detection of tumors is performed with the help of automatic computing technique as presented in the proposed work. The non-active cells in brain region are known to be benign and they will never cause the death of the patient. These non-active cells follow a uniform pattern in brain and have lower density than the surrounding pixels. The Magnetic Resonance (MR) image contrast is improved by the cost map construction technique. The deep learning algorithm for differentiating the normal brain… More >

Muhammad Zubair Asghar¹, Fazli Subhan², Muhammad Imran¹, Fazal Masud Kundi¹, Adil Khan³, Shahboddin Shamshirband^{4, 5, *}, Amir Mosavi^{6, 7, 8}, Peter Csiba⁸, Annamaria R. Varkonyi Koczy⁸

CMC-Computers, Materials & Continua, Vol.63, No.3, pp. 1093-1118, 2020, DOI:10.32604/cmc.2020.07709

Abstract Emotion detection from the text is a challenging problem in the text analytics. The opinion mining experts are focusing on the development of emotion detection applications as they have received considerable attention of online community including users and business organization for collecting and interpreting public emotions. However, most of the existing works on emotion detection used less efficient machine learning classifiers with limited datasets, resulting in performance degradation. To overcome this issue, this work aims at the evaluation of the performance of different machine learning classifiers on a benchmark emotion dataset. The experimental results show the performance of different machine… More >

Brian A. Boe, Sharon L. Cheatham, Aimee K. Armstrong, Darren P. Berman, Joanne L. Chisolm, John P. Cheatham

Congenital Heart Disease, Vol.14, No.2, pp. 297-304, 2019, DOI:10.1111/chd.12728

Abstract Objective: We sought to describe the leaflet morphology variation in the Melody Transcatheter Pulmonary Valve (TPV) and evaluate associated outcomes. The Melody TPV is constructed from harvested bovine jugular venous valves which have been rigorously tested. Natural anatomic leaflet variations are seen in the Melody TPV but have not been evaluated.
Design: A Melody TPV leaflet morphology classification system was devised after reviewing a subset of photographed and implanted TPVs. All images were blindly re‐ viewed by implanters and classified. Midterm hemodynamic outcomes and complica‐ tions of the Melody TPVs were compared by leaflet morphology.
Results: Photographed Melody TPVs implanted… More >

Chao Luo¹, Canghong Shi¹, Xiaojie Li^{1, *}, Xin Wang⁴, Yucheng Chen³, Dongrui Gao¹, Youbing Yin⁴, Qi Song⁴, Xi Wu¹, Jiliu Zhou¹

CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 995-1012, 2020, DOI:10.32604/cmc.2020.07968

Abstract Myocardial segmentation and classification play a major role in the diagnosis of cardiovascular disease. Dilated Cardiomyopathy (DCM) is a kind of common chronic and life-threatening cardiopathy. Early diagnostics significantly increases the chances of correct treatment and survival. However, accurate and rapid diagnosis of DCM is still challenge due to high variability of cardiac structure, low contrast cardiac magnetic resonance (CMR) images, and intrinsic noise in synthetic CMR images caused by motion artifact and cardiac dynamics. Moreover, visual assessment and empirical evaluation are widely used in routine clinical diagnosis, but they are subject to high inter-observer variability and are both subjective… More >

Guangyong Yang¹, Jianqiu Zeng¹, Mengke Yang^{2, *}, Yifei Wei³, Xiangqing Wang³, Zulfiqar Hussain Pathan⁴

CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 769-785, 2020, DOI:10.32604/cmc.2020.07528

Abstract A vast amount of information has been produced in recent years, which brings a huge challenge to information management. The better usage of big data is of important theoretical and practical significance for effectively addressing and managing messages. In this paper, we propose a nine-rectangle-grid information model according to the information value and privacy, and then present information use policies based on the rough set theory. Recurrent neural networks were employed to classify OTT messages. The content of user interest is effectively incorporated into the classification process during the annotation of OTT messages, ending with a reliable trained classification model.… More >

Junseob Kim¹, Beanbonyka Rim¹, Nak-Jun Sung¹, Min Hong^{2, *}

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 17-30, 2020, DOI:10.32604/cmc.2020.09044

Abstract Fingerprint security technology has attracted a great deal of attention in recent years because of its unique biometric information that does not change over an individual’s lifetime and is a highly reliable and secure way to identify a certain individuals. AFIS (Automated Fingerprint Identification System) is a system used by Korean police for identifying a specific person by fingerprint. The AFIS system, however, only selects a list of possible candidates through fingerprints, the exact individual must be found by fingerprint experts. In this paper, we designed a deep learning system using deep convolution network to categorize fingerprints as coming from… More >

Lamia Bouafif¹, Noureddine Ellouze^2,*

Sound & Vibration, Vol.54, No.1, pp. 1-15, 2020, DOI:10.32604/sv.2020.08665

Abstract In order to assist physically handicapped persons in their movements, we developed an embedded isolated word speech recognition system (ASR) applied to voice control of smart wheelchairs. However, in spite of the existence in the industrial market of several kinds of electric wheelchairs, the problem remains the need to manually control this device by hand via joystick; which limits their use especially by people with severe disabilities. Thus, a significant number of disabled people cannot use a standard electric wheelchair or drive it with difficulty. The proposed solution is to use the voice to control and drive the wheelchair instead… More >