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  • Open Access

    ARTICLE

    Design of Intelligent Alzheimer Disease Diagnosis Model on CIoT Environment

    Anwer Mustafa Hilal1, Fahd N. Al-Wesabi2,3, Mohamed Tahar Ben Othman4, Khaled Mohamad Almustafa5, Nadhem Nemri6, Mesfer Al Duhayyim7, Manar Ahmed Hamza1,*, Abu Sarwar Zamani1

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5979-5994, 2022, DOI:10.32604/cmc.2022.022686 - 14 January 2022

    Abstract Presently, cognitive Internet of Things (CIoT) with cloud computing (CC) enabled intelligent healthcare models are developed, which enables communication with intelligent devices, sensor modules, and other stakeholders in the healthcare sector to avail effective decision making. On the other hand, Alzheimer disease (AD) is an advanced and degenerative illness which injures the brain cells, and its earlier detection is necessary for suitable interference by healthcare professional. In this aspect, this paper presents a new Oriented Features from Accelerated Segment Test (FAST) with Rotated Binary Robust Independent Elementary Features (BRIEF) Detector (ORB) with optimal artificial neural network… More >

  • Open Access

    ARTICLE

    An Efficient Machine Learning Based Precoding Algorithm for Millimeter-Wave Massive MIMO

    Waleed Shahjehan1, Abid Ullah1, Syed Waqar Shah1, Ayman A. Aly2, Bassem F. Felemban2, Wonjong Noh3,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5399-5411, 2022, DOI:10.32604/cmc.2022.022034 - 14 January 2022

    Abstract Millimeter wave communication works in the 30–300 GHz frequency range, and can obtain a very high bandwidth, which greatly improves the transmission rate of the communication system and becomes one of the key technologies of fifth-generation (5G). The smaller wavelength of the millimeter wave makes it possible to assemble a large number of antennas in a small aperture. The resulting array gain can compensate for the path loss of the millimeter wave. Utilizing this feature, the millimeter wave massive multiple-input multiple-output (MIMO) system uses a large antenna array at the base station. It enables the… More >

  • Open Access

    ARTICLE

    Machine Learning-Based Predictions on the Self-Heating Characteristics of Nanocomposites with Hybrid Fillers

    Taegeon Kil1, D. I. Jang1, H. N. Yoon1, Beomjoo Yang2,*

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4487-4502, 2022, DOI:10.32604/cmc.2022.020940 - 14 January 2022

    Abstract A machine learning-based prediction of the self-heating characteristics and the negative temperature coefficient (NTC) effect detection of nanocomposites incorporating carbon nanotube (CNT) and carbon fiber (CF) is proposed. The CNT content was fixed at 4.0 wt.%, and CFs having three different lengths (0.1, 3 and 6 mm) at dosage of 1.0 wt.% were added to fabricate the specimens. The self-heating properties of the specimens were evaluated via self-heating tests. Based on the experiment results, two types of artificial neural network (ANN) models were constructed to predict the surface temperature and electrical resistance, and to detect More >

  • Open Access

    ARTICLE

    Federated Learning for Privacy-Preserved Medical Internet of Things

    Navod Neranjan Thilakarathne1, G. Muneeswari2, V. Parthasarathy3, Fawaz Alassery4, Habib Hamam5, Rakesh Kumar Mahendran6, Muhammad Shafiq7,*

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 157-172, 2022, DOI:10.32604/iasc.2022.023763 - 05 January 2022

    Abstract Healthcare is one of the notable areas where the integration of the Internet of Things (IoT) is highly adopted, also known as the Medical IoT (MIoT). So far, MIoT is revolutionizing healthcare because it provides many advantages for the benefit of patients and healthcare personnel. The use of MIoT is becoming a booming trend, generating a large amount of IoT data, which requires proper analysis to infer meaningful information. This has led to the rise of deploying artificial intelligence (AI) technologies, such as machine learning (ML) and deep learning (DL) algorithms, to learn the meaning… More >

  • Open Access

    ARTICLE

    Requirements Engineering: Conflict Detection Automation Using Machine Learning

    Hatim Elhassan1, Mohammed Abaker1, Abdelzahir Abdelmaboud2, Mohammed Burhanur Rehman1,*

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 259-273, 2022, DOI:10.32604/iasc.2022.023750 - 05 January 2022

    Abstract The research community has well recognized the importance of requirement elicitation. Recent research has shown the continuous decreasing success rate of IS projects in the last five years due to the complexity of the requirement conflict refinement process. Requirement conflict is at the heart of requirement elicitation. It is also considered the prime reason for deciding the success or failure of the intended Information System (IS) project. This paper introduces the requirements conflict detection automation model based on the Mean shift clustering unsupervised machine learning model. It utilizes the advantages of Artificial Intelligence in detecting… More >

  • Open Access

    ARTICLE

    Efficient Urban Green Space Destruction and Crop Stress Yield Assessment Model

    G. Chamundeeswari1, S. Srinivasan1,*, S. Prasanna Bharathi1,2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 515-534, 2022, DOI:10.32604/iasc.2022.023449 - 05 January 2022

    Abstract Remote sensing (RS) is a very reliable and effective way to monitor the environment and landscape changes. In today’s world topographic maps are very important in science, research, planning and management. It is quite possible to detect the changes based on RS data which is obtained at two different times. In this paper, we propose an optimal technique that handles problems like urban green space destruction and detection of crop stress assessment. Firstly, the optimal preprocessing is performed on the given RS dataset, for image enhancement using geometric correction and image registration. Secondly, we propose… More >

  • Open Access

    ARTICLE

    To Control Diabetes Using Machine Learning Algorithm and Calorie Measurement Technique

    T. Viveka1,*, C. Christopher Columbus2, N. Senthil Velmurugan3

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 535-547, 2022, DOI:10.32604/iasc.2022.022976 - 05 January 2022

    Abstract Because of the increasing workload, people are having several clinical examinations to determine their health status, resulting in limited time. Here, we present a healthful consuming device based on rule mining that can modify your parameter dependency and recommend the varieties of meals that will boost your fitness and assist you to avoid the types of meals that increase your risk for sicknesses. Using the meals database, the data mining technique is useful for gathering meal energy from breakfast, after breakfast, lunch, after lunch, dinner, after dinner, and bedtime for ninety days. The purpose of… More >

  • Open Access

    ARTICLE

    An Advanced Integrated Approach in Mobile Forensic Investigation

    G. Maria Jones1,*, S. Godfrey Winster2, P. Valarmathie3

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 87-102, 2022, DOI:10.32604/iasc.2022.022972 - 05 January 2022

    Abstract Rapid advancement of digital technology has encouraged its use in all aspects of life, including the workplace, education, and leisure. As technology advances, so does the number of users, which leads to an increase in criminal activity and demand for a cyber-crime investigation. Mobile phones have been the epicenter of illegal activity in recent years. Sensitive information is transferred due to numerous technical applications available at one’s fingertips, which play an essential part in cyber-crime attacks in the mobile environment. Mobile forensic is a technique of recovering or retrieving digital evidence from mobile devices so… More >

  • Open Access

    ARTICLE

    Insider Threat Detection Based on NLP Word Embedding and Machine Learning

    Mohd Anul Haq1, Mohd Abdul Rahim Khan1,*, Mohammed Alshehri2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 619-635, 2022, DOI:10.32604/iasc.2022.021430 - 05 January 2022

    Abstract The growth of edge computing, the Internet of Things (IoT), and cloud computing have been accompanied by new security issues evolving in the information security infrastructure. Recent studies suggest that the cost of insider attacks is higher than the external threats, making it an essential aspect of information security for organizations. Efficient insider threat detection requires state-of-the-art Artificial Intelligence models and utility. Although significant have been made to detect insider threats for more than a decade, there are many limitations, including a lack of real data, low accuracy, and a relatively low false alarm, which… More >

  • Open Access

    REVIEW

    Deep Learning-Based Cancer Detection-Recent Developments, Trend and Challenges

    Gulshan Kumar1,*, Hamed Alqahtani2

    CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1271-1307, 2022, DOI:10.32604/cmes.2022.018418 - 30 December 2021

    Abstract Cancer is one of the most critical diseases that has caused several deaths in today’s world. In most cases, doctors and practitioners are only able to diagnose cancer in its later stages. In the later stages, planning cancer treatment and increasing the patient’s survival rate becomes a very challenging task. Therefore, it becomes the need of the hour to detect cancer in the early stages for appropriate treatment and surgery planning. Analysis and interpretation of medical images such as MRI and CT scans help doctors and practitioners diagnose many diseases, including cancer disease. However, manual… More >

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