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Huiping Jiang^1,*, Rui Jiao¹, Demeng Wu¹, Wenbo Wu²
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2315-2327, 2021, DOI:10.32604/cmc.2021.016832
Abstract With the rapid development of deep learning and artificial intelligence, affective computing, as a branch field, has attracted increasing research attention. Human emotions are diverse and are directly expressed via non-physiological indicators, such as electroencephalogram (EEG) signals. However, whether emotion-based or EEG-based, these remain single-modes of emotion recognition. Multi-mode fusion emotion recognition can improve accuracy by utilizing feature diversity and correlation. Therefore, three different models have been established: the single-mode-based EEG-long and short-term memory (LSTM) model, the Facial-LSTM model based on facial expressions processing EEG data, and the multi-mode LSTM-convolutional neural network (CNN) model that combines expressions and EEG. Their… More >

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Kanwal Imran^1,*, Nasreen Anjum³, Saeed Mahfooz¹, Muhammad Zubair², Zhahoui Yang³, Abdul Haseeb Malik¹, Qazi Ejaz Ali¹, Madeeha Aman¹
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2329-2347, 2021, DOI:10.32604/cmc.2021.017177
Abstract IPv6 over Low Power Wireless Personal Area Network (6LoWPAN) connects the highly constrained sensor nodes with the internet using the IPv6 protocol. 6LoWPAN has improved the scalability of the Internet of Things (IoTs) infrastructure and allows mobile nodes to send packets over the IEEE 802.15.4 wireless network. Several mobility managements schemes have been suggested for handling the registration and handover procedures in 6LoWPAN. However, these schemes have performance constraints, such as increased transmission cost, signalling overhead, registration, and handover latency. To address these issues, we propose a novel cluster-based group mobility scheme (CGM6) for 6LoWPAN. To reduce the signalling cost… More >

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Mohamed F. El-Amin^1,5, Abdulhamit Subasi², Mahmoud M. Selim^3,*, Awad Mousa⁴
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2349-2362, 2021, DOI:10.32604/cmc.2021.017102
（This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
Abstract In the process of oil recovery, experiments are usually carried out on core samples to evaluate the recovery of oil, so the numerical data are fitted into a non-dimensional equation called scaling-law. This will be essential for determining the behavior of actual reservoirs. The global non-dimensional time-scale is a parameter for predicting a realistic behavior in the oil field from laboratory data. This non-dimensional universal time parameter depends on a set of primary parameters that inherit the properties of the reservoir fluids and rocks and the injection velocity, which dynamics of the process. One of the practical machine learning (ML)… More >

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Muhammad Usman Ghani Khan^1,2, Zubaira Naz¹, Javeria Khan¹, Tanzila Saba³, Ibrahim Abunadi³, Amjad Rehman³, Usman Tariq^4,*
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2363-2376, 2021, DOI:10.32604/cmc.2021.014550
（This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
Abstract The National Health Interview Survey (NHIS) shows that there are 13.2% of children at the age of 11 to 17 who are suffering from Attention Deficit Hyperactivity Disorder (ADHD), globally. The treatment methods for ADHD are either psycho-stimulant medications or cognitive therapy. These traditional methods, namely therapy, need a large number of visits to hospitals and include medication. Neurogames could be used for the effective treatment of ADHD. It could be a helpful tool in improving children and ADHD patients’ cognitive skills by using Brain–Computer Interfaces (BCI). BCI enables the user to interact with the computer through brain activity using… More >

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Mueen Uddin^1,*, M. S. Memon², Irfana Memon², Imtiaz Ali², Jamshed Memon³, Maha Abdelhaq⁴, Raed Alsaqour⁵
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2377-2397, 2021, DOI:10.32604/cmc.2021.015354
（This article belongs to the Special Issue: AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems)
Abstract Background: Electronic Health Record (EHR) systems are used as an efficient and effective technique for sharing patient’s health records among different hospitals and various other key stakeholders of the healthcare industry to achieve better diagnosis and treatment of patients globally. However, the existing EHR systems mostly lack in providing appropriate security, entrusted access control and handling privacy and secrecy issues and challenges in current hospital infrastructures. Objective: To solve this delicate problem, we propose a Blockchain-enabled Hyperledger Fabric Architecture for different EHR systems. Methodology: In our EHR blockchain system, Peer nodes from various organizations (stakeholders) create a ledger network, where… More >

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Youbang Guan^1,2, Bong Jun Choi^3,*
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2399-2411, 2021, DOI:10.32604/cmc.2021.012365
Abstract Smart home technology provides consumers with network connectivity, automation or enhanced services for home devices. With the Internet of Things era, a vast data flow makes business platforms have to own the same computing power to match their business services. It achieves computing power through implementing big data algorithms deployed in the cloud data center. However, because of the far long geographical distance between the client and the data center or the massive data capacity gap, potentially high latency and high packet loss will reduce the usability of smart home systems if service providers deploy all services in the cloud… More >

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1316

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Tapan Kumar Das¹, Pradeep Kumar Roy², Mohy Uddin³, Kathiravan Srinivasan¹, Chuan-Yu Chang^4,*, Shabbir Syed-Abdul⁵
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2413-2429, 2021, DOI:10.32604/cmc.2021.016698
（This article belongs to the Special Issue: Emerging Applications of Artificial Intelligence, Machine learning and Data Science)
Abstract Machine learning based image analysis for predicting and diagnosing certain diseases has been entirely trustworthy and even as efficient as a domain expert’s inspection. However, the style of non-transparency functioning by a trained machine learning system poses a more significant impediment for seamless knowledge trajectory, clinical mapping, and delusion tracing. In this proposed study, a deep learning based framework that employs deep convolution neural network (Deep-CNN), by utilizing both clinical presentations and conventional magnetic resonance imaging (MRI) investigations, for diagnosing tumors is explored. This research aims to develop a model that can be used for abnormality detection over MRI data… More >

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Shada A. Alsalamah^1,2,3,*, Hessah A. Alsalamah^1,4, Thamer Nouh⁵, Sara A. Alsalamah⁶
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2431-2449, 2021, DOI:10.32604/cmc.2021.016618
（This article belongs to the Special Issue: Artificial Intelligence and IoT based intelligent systems using high performance computing for Medical applications.)
Abstract An emerging healthcare delivery model is enabling a new era of clinical care based on well-informed decision-making processes. Current healthcare information systems (HISs) fall short of adopting this model due to a conflict between information security needed to implement the new model and those already enforced locally to support traditional care models. Meanwhile, in recent times, the healthcare sector has shown a substantial interest in the potential of using blockchain technology for providing quality care to patients. No blockchain solution proposed so far has fully addressed emerging cross-organization information-sharing needs in healthcare. In this paper, we aim to study the… More >

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Javaria Amin¹, Muhammad Sharif², Muhammad Almas Anjum³, Yunyoung Nam^4,*, Seifedine Kadry⁵, David Taniar⁶
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2451-2467, 2021, DOI:10.32604/cmc.2021.014199
（This article belongs to the Special Issue: AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems)
Abstract Coronavirus 19 (COVID-19) can cause severe pneumonia that may be fatal. Correct diagnosis is essential. Computed tomography (CT) usefully detects symptoms of COVID-19 infection. In this retrospective study, we present an improved framework for detection of COVID-19 infection on CT images; the steps include pre-processing, segmentation, feature extraction/fusion/selection, and classification. In the pre-processing phase, a Gabor wavelet filter is applied to enhance image intensities. A marker-based, watershed controlled approach with thresholding is used to isolate the lung region. In the segmentation phase, COVID-19 lesions are segmented using an encoder-/decoder-based deep learning model in which deepLabv3 serves as the bottleneck and… More >

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Samira Kanwal¹, Zeshan Iqbal¹, Aun Irtaza¹, Rashid Ali², Kamran Siddique^3,*
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2469-2486, 2021, DOI:10.32604/cmc.2021.014709
（This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
Abstract In IoT networks, nodes communicate with each other for computational services, data processing, and resource sharing. Most of the time huge data is generated at the network edge due to extensive communication between IoT devices. So, this tidal data is transferred to the cloud data center (CDC) for efficient processing and effective data storage. In CDC, leader nodes are responsible for higher performance, reliability, deadlock handling, reduced latency, and to provide cost-effective computational services to the users. However, the optimal leader selection is a computationally hard problem as several factors like memory, CPU MIPS, and bandwidth, etc., are needed to… More >

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Huy Hung Tran^1,2, Khoa Nguyen-Dang^1,2,*, Niamat Hussain³
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2487-2498, 2021, DOI:10.32604/cmc.2021.016027
（This article belongs to the Special Issue: Advances in 5G Antenna Designs and Systems)
Abstract A single-layer design of non-uniform metasurface (MS) based circularly polarized (CP) antenna with wideband operation characteristic is proposed and investigated in this paper. The antenna is excited by a truncated corner squared patch as a primary radiating CP source. Then, a non-uniform MS is placed in the same layer with the driven patch. Besides increasing the impedance bandwidth, the non-uniform MS also generates two additional CP bands in the high frequency band, leading to significantly increase the antenna’s overall performances. The use of non-uniform MS distinguishes our design from the other CP MS based antennas in literature, in which the… More >

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Farhan Aadil¹, Bilal Mehmood¹, Najam Ul Hasan², Sangsoon Lim^3,*, Sadia Ejaz¹, Noor Zaman⁴
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2499-2513, 2021, DOI:10.32604/cmc.2021.014647
（This article belongs to the Special Issue: Emerging Trends in Cyber Security for Communication Networks)
Abstract A wireless body area network (WBAN) consists of tiny health-monitoring sensors implanted in or placed on the human body. These sensors are used to collect and communicate human medical and physiological data and represent a subset of the Internet of Things (IoT) systems. WBANs are connected to medical servers that monitor patients’ health. This type of network can protect critical patients’ lives due to the ability to monitor patients’ health continuously and remotely. The inter-WBAN communication provides a dynamic environment for patients allowing them to move freely. However, during patient movement, the WBAN patient nodes may become out of range… More >

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Ye Mu^1,2,3,4, Ruiwen Ni¹, Yuheng Sun¹, Tong Zhang¹, Ji Li¹, Tianli Hu^1,2,3,4, He Gong^1,2,3,4, Shijun Li^1,2,3,4,*, Thobela Louis Tyasi⁵
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2515-2527, 2021, DOI:10.32604/cmc.2021.016570
Abstract

Radio frequency identification technology is one of the main technologies of Internet of Things (IoT). Through the transmission and reflection of wireless radio frequency signals, non-contact identification is realized, and multiple objects identification can be realized. However, when multiple tags communicate with a singleton reader simultaneously, collision will occur between the signals, which hinders the successful transmissions. To effectively avoid the tag collision problem and improve the reading performance of RFID systems, two advanced tag identification algorithms namely Adaptive M-ary tree slotted Aloha (AMTS) based on the characteristics of Aloha-based and Query tree-based algorithms are proposed. In AMTS, the reader… More >

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Sadiq Akbar¹, Muhammad Asif Zahoor Raja^2,*, Naveed Ishtiaq Chaudhary³, Fawad Zaman⁴, Hani Alquhayz⁵
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2529-2543, 2021, DOI:10.32604/cmc.2021.016097
Abstract For the last few decades, the parameter estimation of electromagnetic plane waves i.e., far field sources, impinging on antenna array geometries has attracted a lot of researchers due to their use in radar, sonar and under water acoustic environments. In this work, nature inspired heuristics based on the flower pollination algorithm (FPA) is designed for the estimation problem of amplitude and direction of arrival of far field sources impinging on uniform linear array (ULA). Using the approximation in mean squared error sense, a fitness function of the problem is developed and the strength of the FPA is utilized for optimization… More >

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Debajit Datta¹, Pramod Kumar Maurya¹, Kathiravan Srinivasan², Chuan-Yu Chang^3,*, Rishav Agarwal¹, Ishita Tuteja¹, V. Bhavyashri Vedula¹
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2545-2561, 2021, DOI:10.32604/cmc.2021.015478
（This article belongs to the Special Issue: Artificial Intelligence and Big Data in Entrepreneurship)
Abstract The pandemic situation in 2020 brought about a ‘digitized new normal’ and created various issues within the current education systems. One of the issues is the monitoring of students during online examination situations. A system to determine the student’s eye gazes during an examination can help to eradicate malpractices. In this work, we track the users’ eye gazes by incorporating twelve facial landmarks around both eyes in conjunction with computer vision and the HAAR classifier. We aim to implement eye gaze detection by considering facial landmarks with two different Convolutional Neural Network (CNN) models, namely the AlexNet model and the… More >

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2136

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Ikhlas Ahmad¹, Haris Dildar¹, Wasi Ur Rehman Khan¹, Sadiq Ullah¹, Shakir Ullah¹, Mahmoud A. Albreem², Mohammed H. Alsharif³, Peerapong Uthansakul^4,*
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2563-2578, 2021, DOI:10.32604/cmc.2021.016813
Abstract In this paper, low profile frequency reconfigurable monopole antenna is designed on FR-4 substrate with a compact size of 30 mm³ × 20 mm³ × 1.6 mm³. The antenna is tuned to four different modes through three pin diode switches. In Mode 1 (SW1 to SW3 = OFF), antenna covers a wideband of 3.15–8.51 GHz. For Mode 2 (SW1 = ON, SW2 to SW3 = OFF), the proposed antenna resonates at 3.5 GHz. The antenna shows dual band behavior and covers 2.6 and 6.4 GHz in Mode 3 (SW1 and SW2 = ON, SW3 = OFF). The same antenna covers… More >

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1533

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Jinxin Zuo^1,2, Yueming Lu^1,2,*, Hui Gao^2,3, Tong Peng^1,2, Ziyv Guo^2,3, Tong An^1,2, Enjie Liu⁴
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2579-2595, 2021, DOI:10.32604/cmc.2021.016623
Abstract With the skyrocketing development of technologies, there are many issues in information security quantitative evaluation (ISQE) of complex heterogeneous information systems (CHISs). The development of CHIS calls for an ISQE model based on security-critical components to improve the efficiency of system security evaluation urgently. In this paper, we summarize the implication of critical components in different filed and propose a recognition algorithm of security-critical components based on threat attack tree to support the ISQE process. The evaluation model establishes a framework for ISQE of CHISs that are updated iteratively. Firstly, with the support of asset identification and topology data, we… More >

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Imran Ashraf, Soojung Hur, Yousaf Bin Zikria, Yongwan Park^*
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2597-2620, 2021, DOI:10.32604/cmc.2021.016214
（This article belongs to the Special Issue: Reinforcement Learning Based solutions for Next-Generation Wireless Networks Coexistence)
Abstract Predominantly the localization accuracy of the magnetic field-based localization approaches is severed by two limiting factors: Smartphone heterogeneity and smaller data lengths. The use of multifarious smartphones cripples the performance of such approaches owing to the variability of the magnetic field data. In the same vein, smaller lengths of magnetic field data decrease the localization accuracy substantially. The current study proposes the use of multiple neural networks like deep neural network (DNN), long short term memory network (LSTM), and gated recurrent unit network (GRN) to perform indoor localization based on the embedded magnetic sensor of the smartphone. A voting scheme… More >

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Oakyoung Han¹, Jaehyoun Kim^2,*
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2621-2632, 2021, DOI:10.32604/cmc.2021.014665
Abstract The analysis of large time-series datasets has profoundly enhanced our ability to make accurate predictions in many fields. However, unpredictable phenomena, such as extreme weather events or the novel coronavirus 2019 (COVID-19) outbreak, can greatly limit the ability of time-series analyses to establish reliable patterns. The present work addresses this issue by applying uncertainty analysis using a probability distribution function, and applies the proposed scheme within a preliminary study involving the prediction of power consumption for a single hotel in Seoul, South Korea based on an analysis of 53,567 data items collected by the Korea Electric Power Corporation using robotic… More >

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Jianyi Liu¹, Ru Zhang^1,*, Jing Li², Lei Guan³, Cheng Jie², Jiaping Gui⁴
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2633-2649, 2021, DOI:10.32604/cmc.2021.016605
Abstract Reversible data hiding in encrypted image (RDHEI) is a widely used technique for privacy protection, which has been developed in many applications that require high confidentiality, authentication and integrity. Proposed RDHEI methods do not allow high embedding rate while ensuring losslessly recover the original image. Moreover, the ciphertext form of encrypted image in RDHEI framework is easy to cause the attention of attackers. This paper proposes a reversible data hiding algorithm based on image camouflage encryption and bit plane compression. A camouflage encryption algorithm is used to transform a secret image into another meaningful target image, which can cover both… More >

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1225

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ARTICLE

Zhen-Zhen Li¹, Zi-Chen Li^1,*, Xiu-Bo Chen², Zhiguo Qu³, Xiaojun Wang⁴, Haizhu Pan⁵
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2651-2663, 2021, DOI:10.32604/cmc.2021.016960
Abstract

In many earlier works, perfect quantum state transmission over the butterfly network can be achieved via quantum network coding protocols with the assist of maximally entangled states. However, in actual quantum networks, a maximally entangled state as auxiliary resource is hard to be obtained or easily turned into a non-maximally entangled state subject to all kinds of environmental noises. Therefore, we propose a more practical quantum network coding scheme with the assist of non-maximally entangled states. In this paper, a practical quantum network coding protocol over grail network is proposed, in which the non-maximally entangled resource is assisted and even… More >

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1047

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Mohammed H. Alsharif¹, Kannadasan Raju², Abu Jahid³, Mahmoud A. Albreem⁴, Peerapong Uthansakul^5,*, Jamel Nebhen⁶, Venkatesan Chandrasekaran²
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2665-2680, 2021, DOI:10.32604/cmc.2021.016836
Abstract

Green wireless networks or energy-efficient wireless networks have gained popularity as a research topic due to the ecological and economic concerns of cellular operators. The specific power supply requirements for the cellular base station, such as cost-effectiveness, efficiency, sustainability, and reliability, can be met by utilizing the technological advances in renewable energy. There are numerous drivers for the deployment of renewable energy technologies and the transition towards green energy. Renewable energy is free, clean, and abundant in most locations throughout the year. Accordingly, this work proposes a novel framework for energy-efficient solar-powered base stations for the Oman site, specifically for… More >

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Haitao Xu¹, Haiwang Zhang¹, Qianqian Li¹, Tao Qin^2,*, Zhen Zhang³
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2681-2691, 2021, DOI:10.32604/cmc.2021.016188
Abstract With the extensive application of software collaborative development technology, the processing of code data generated in programming scenes has become a research hotspot. In the collaborative programming process, different users can submit code in a distributed way. The consistency of code grammar can be achieved by syntax constraints. However, when different users work on the same code in semantic development programming practices, the development factors of different users will inevitably lead to the problem of data semantic conflict. In this paper, the characteristics of code segment data in a programming scene are considered. The code sequence can be obtained by… More >

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Javaria Amin¹, Muhammad Almas Anjum², Muhammad Sharif³, Seifedine Kadry⁴, Yunyoung Nam^5,*, ShuiHua Wang⁶
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2693-2709, 2021, DOI:10.32604/cmc.2021.016871
（This article belongs to the Special Issue: Recent Advances in Deep Learning, Information Fusion, and Features Selection for Video Surveillance Application)
Abstract Recognition of human gait is a difficult assignment, particularly for unobtrusive surveillance in a video and human identification from a large distance. Therefore, a method is proposed for the classification and recognition of different types of human gait. The proposed approach is consisting of two phases. In phase I, the new model is proposed named convolutional bidirectional long short-term memory (Conv-BiLSTM) to classify the video frames of human gait. In this model, features are derived through convolutional neural network (CNN) named ResNet-18 and supplied as an input to the LSTM model that provided more distinguishable temporal information. In phase II,… More >

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Amena Mahmoud^1,*, Mahmoud Y. Shams², O. M. Elzeki³, Nancy Awadallah Awad⁴
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2711-2726, 2021, DOI:10.32604/cmc.2021.015293
Abstract Semantic Web (SW) provides new opportunities for the study and application of big data, massive ranges of data sets in varied formats from multiple sources. Related studies focus on potential SW technologies for resolving big data problems, such as structurally and semantically heterogeneous data that result from the variety of data formats (structured, semi-structured, numeric, unstructured text data, email, video, audio, stock ticker). SW offers information semantically both for people and machines to retain the vast volume of data and provide a meaningful output of unstructured data. In the current research, we implement a new semantic Extract Transform Load (ETL)… More >

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Saleem Ibraheem Saleem^1,*, Adnan Mohsin Abdulazeez¹, Zeynep Orman²
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2727-2754, 2021, DOI:10.32604/cmc.2021.016447
（This article belongs to the Special Issue: AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems)
Abstract The writer identification (WI) of handwritten Arabic text is now of great concern to intelligence agencies following the recent attacks perpetrated by known Middle East terrorist organizations. It is also a useful instrument for the digitalization and attribution of old text to other authors of historic studies, including old national and religious archives. In this study, we proposed a new affective segmentation model by modifying an artificial neural network model and making it suitable for the binarization stage based on blocks. This modified method is combined with a new effective rotation model to achieve an accurate segmentation through the analysis… More >

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Geetanjali Rathee¹, Razi Iqbal^2,*, Adel Khelifi³
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2755-2769, 2021, DOI:10.32604/cmc.2021.017000
（This article belongs to the Special Issue: Intelligent Big Data Management and Machine Learning Techniques for IoT-Enabled Pervasive Computing)
Abstract Pervasive schemes are the significant techniques that allow intelligent communication among the devices without any human intervention. Recently Internet of Vehicles (IoVs) has been introduced as one of the applications of pervasive computing that addresses the road safety challenges. Vehicles participating within the IoV are embedded with a wide range of sensors which operate in a real time environment to improve the road safety issues. Various mechanisms have been proposed which allow automatic actions based on uncertainty of sensory and managed data. Due to the lack of existing transportation integration schemes, IoV has not been completely explored by business organizations.… More >

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Izzat Al-Darraji^1,2, Morched Derbali³, Houssem Jerbi⁴, Fazal Qudus Khan³, Sadeeq Jan^5,*, Dimitris Piromalis⁶, Georgios Tsaramirsis⁷
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2771-2790, 2021, DOI:10.32604/cmc.2021.017236
Abstract The autonomous navigation of an Unmanned Aerial Vehicle (UAV) relies heavily on the navigation sensors. The UAV’s level of autonomy depends upon the various navigation systems, such as state measurement, mapping, and obstacle avoidance. Selecting the correct components is a critical part of the design process. However, this can be a particularly difficult task, especially for novices as there are several technologies and components available on the market, each with their own individual advantages and disadvantages. For example, satellite-based navigation components should be avoided when designing indoor UAVs. Incorporating them in the design brings no added value to the final… More >

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Muhammed Binsawad^1,*, Marwan Albahar², Abdullah Bin Sawad¹
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2791-2806, 2021, DOI:10.32604/cmc.2021.016141
（This article belongs to the Special Issue: AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems)
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 bi-branched convoluted neural network (CNN)… More >

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Jing Zhang^1,2, Xin Qi^3,*, San Hlaing Myint³, Zheng Wen⁴
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2807-2824, 2021, DOI:10.32604/cmc.2021.017410
（This article belongs to the Special Issue: Deep Learning and Parallel Computing for Intelligent and Efficient IoT)
Abstract With increasingly more smart cameras deployed in infrastructure and commercial buildings, 3D reconstruction can quickly obtain cities’ information and improve the efficiency of government services. Images collected in outdoor hazy environments are prone to color distortion and low contrast; thus, the desired visual effect cannot be achieved and the difficulty of target detection is increased. Artificial intelligence (AI) solutions provide great help for dehazy images, which can automatically identify patterns or monitor the environment. Therefore, we propose a 3D reconstruction method of dehazed images for smart cities based on deep learning. First, we propose a fine transmission image deep convolutional… More >

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