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  • Open Access

    ARTICLE

    Intelligent Multiclass Skin Cancer Detection Using Convolution Neural Networks

    Reham Alabduljabbar*, Hala Alshamlan

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 831-847, 2021, DOI:10.32604/cmc.2021.018402

    Abstract The worldwide mortality rate due to cancer is second only to cardiovascular diseases. The discovery of image processing, latest artificial intelligence techniques, and upcoming algorithms can be used to effectively diagnose and prognose cancer faster and reduce the mortality rate. Efficiently applying these latest techniques has increased the survival chances during recent years. The research community is making significant continuous progress in developing automated tools to assist dermatologists in decision making. The datasets used for the experimentation and analysis are ISBI 2016, ISBI 2017, and HAM 10000. In this work pertained models are used to… More >

  • Open Access

    ARTICLE

    Competency Driven Resource Evaluation Method for Business Process Intelligence

    Abid Sohail1,*, Dhanapal Durai Dominic2, Mohammad Hijji3, Muhammad Arif Butt4

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1141-1157, 2021, DOI:10.32604/cmc.2021.018023

    Abstract Enterprises are continuously aiming at improving the execution of processes to achieve a competitive edge. One of the established ways of improving process performance is to assign the most appropriate resources to each task of the process. However, evaluations of business process improvement approaches have established that a method that can guide decision-makers to identify the most appropriate resources for a task of process improvement in a structured way, is missing. It is because the relationship between resources and tasks is less understood and advancement in business process intelligence is also ignored. To address this More >

  • Open Access

    ARTICLE

    Hep-Pred: Hepatitis C Staging Prediction Using Fine Gaussian SVM

    Taher M. Ghazal1,2, Marrium Anam3, Mohammad Kamrul Hasan1, Muzammil Hussain4,*, Muhammad Sajid Farooq5, Hafiz Muhammad Ammar Ali4, Munir Ahmad6, Tariq Rahim Soomro7

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 191-203, 2021, DOI:10.32604/cmc.2021.015436

    Abstract Hepatitis C is a contagious blood-borne infection, and it is mostly asymptomatic during the initial stages. Therefore, it is difficult to diagnose and treat patients in the early stages of infection. The disease’s progression to its last stages makes diagnosis and treatment more difficult. In this study, an AI system based on machine learning algorithms is presented to help healthcare professionals with an early diagnosis of hepatitis C. The dataset used for our Hep-Pred model is based on a literature study, and includes the records of 1385 patients infected with the hepatitis C virus. Patients More >

  • Open Access

    ARTICLE

    Supervised Machine Learning-Based Prediction of COVID-19

    Atta-ur-Rahman1, Kiran Sultan3, Iftikhar Naseer4, Rizwan Majeed5, Dhiaa Musleh1, Mohammed Abdul Salam Gollapalli2, Sghaier Chabani2, Nehad Ibrahim1, Shahan Yamin Siddiqui6,7, Muhammad Adnan Khan8,*

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 21-34, 2021, DOI:10.32604/cmc.2021.013453

    Abstract COVID-19 turned out to be an infectious and life-threatening viral disease, and its swift and overwhelming spread has become one of the greatest challenges for the world. As yet, no satisfactory vaccine or medication has been developed that could guarantee its mitigation, though several efforts and trials are underway. Countries around the globe are striving to overcome the COVID-19 spread and while they are finding out ways for early detection and timely treatment. In this regard, healthcare experts, researchers and scientists have delved into the investigation of existing as well as new technologies. The situation… More >

  • Open Access

    ARTICLE

    An Efficient Utilization of Blackboard Ally in Higher Education Institution

    Ahmad Almufarreh, Muhammad Arshad*, Sameer Hassan Mohammed

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 73-87, 2021, DOI:10.32604/iasc.2021.017803

    Abstract Without the constraints of time and place, e-learning can offer a strong learning environment. The notion of e-learning has taken on a new sense with the advent and popularization of mobile devices and ubiquitous computing, enabling students to have access to several diverse opportunities for communicating with e-learning programs. Around the same time, it has prompted the course’s planners to select the most suitable technology from among the various innovations required for the storing and dissemination of information representation. As a Learning Management System (LMS), the Blackboard system now has a recognized role in the… More >

  • Open Access

    REVIEW

    Supervision of Milling Tool Inserts using Conventional and Artificial Intelligence Approach: A Review

    Nilesh Dhobale1, Sharad Mulik2, R. Jegadeeshwaran3,*, Abhishek Patange4

    Sound & Vibration, Vol.55, No.2, pp. 87-116, 2021, DOI:10.32604/sv.2021.014224

    Abstract Due to continuous cutting tool usage, tool supervision is essential for improving the metal cutting industry. In the metal removal process tool, supervision is carried out either by an operator or online tool supervision. Tool supervision helps to understand tool condition, dimensional accuracy, and surface superiority. For downtime in the metal cutting industry, the main reasons are tool breakage and excessive wear, so it is necessary to supervise tool which gives better tool life and enhance productivity. This paper presents different conventional and artificial intelligence techniques for tool supervision in the processing procedures that have More >

  • Open Access

    ARTICLE

    Machine Learning Approach for COVID-19 Detection on Twitter

    Samina Amin1,*, M. Irfan Uddin1, Heyam H. Al-Baity2, M. Ali Zeb1, M. Abrar Khan1

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2231-2247, 2021, DOI:10.32604/cmc.2021.016896

    Abstract Social networking services (SNSs) provide massive data that can be a very influential source of information during pandemic outbreaks. This study shows that social media analysis can be used as a crisis detector (e.g., understanding the sentiment of social media users regarding various pandemic outbreaks). The novel Coronavirus Disease-19 (COVID-19), commonly known as coronavirus, has affected everyone worldwide in 2020. Streaming Twitter data have revealed the status of the COVID-19 outbreak in the most affected regions. This study focuses on identifying COVID-19 patients using tweets without requiring medical records to find the COVID-19 pandemic in… More >

  • Open Access

    ARTICLE

    Face Recognition Based on Gabor Feature Extraction Followed by FastICA and LDA

    Masoud Muhammed Hassan1,*, Haval Ismael Hussein1, Adel Sabry Eesa1, Ramadhan J. Mstafa1,2

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1637-1659, 2021, DOI:10.32604/cmc.2021.016467

    Abstract Over the past few decades, face recognition has become the most effective biometric technique in recognizing people’s identity, as it is widely used in many areas of our daily lives. However, it is a challenging technique since facial images vary in rotations, expressions, and illuminations. To minimize the impact of these challenges, exploiting information from various feature extraction methods is recommended since one of the most critical tasks in face recognition system is the extraction of facial features. Therefore, this paper presents a new approach to face recognition based on the fusion of Gabor-based feature… More >

  • Open Access

    ARTICLE

    VGG-CovidNet: Bi-Branched Dilated Convolutional Neural Network for Chest X-Ray-Based COVID-19 Predictions

    Muhammed Binsawad1,*, Marwan Albahar2, Abdullah Bin Sawad1

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2791-2806, 2021, DOI:10.32604/cmc.2021.016141

    Abstract The coronavirus disease 2019 (COVID-19) pandemic has had a devastating impact on the health and welfare of the global population. A key measure to combat COVID-19 has been the effective screening of infected patients. A vital screening process is the chest radiograph. Initial studies have shown irregularities in the chest radiographs of COVID-19 patients. The use of the chest X-ray (CXR), a leading diagnostic technique, has been encouraged and driven by several ongoing projects to combat this disease because of its historical effectiveness in providing clinical insights on lung diseases. This study introduces a dilated… More >

  • Open Access

    ARTICLE

    Enhancement of Sentiment Analysis Using Clause and Discourse Connectives

    Kumari Sheeja Saraswathy, Sobha Lalitha Devi*

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1983-1999, 2021, DOI:10.32604/cmc.2021.015661

    Abstract The sentiment of a text depends on the clausal structure of the sentence and the connectives’ discourse arguments. In this work, the clause boundary, discourse argument, and syntactic and semantic information of the sentence are used to assign the text’s sentiment. The clause boundaries identify the span of the text, and the discourse connectives identify the arguments. Since the lexicon-based analysis of traditional sentiment analysis gives the wrong sentiment of the sentence, a deeper-level semantic analysis is required for the correct analysis of sentiments. Hence, in this study, explicit connectives in Malayalam are considered to More >

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