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G. Madhu^1,*, A. Govardhan², B. Sunil Srinivas³, Kshira Sagar Sahoo⁴, N. Z. Jhanjhi⁵, K. S. Vardhan¹, B. Rohit⁶
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 903-919, 2021, DOI:10.32604/cmc.2021.016114
Abstract Malaria is a severe epidemic disease caused by Plasmodium falciparum. The parasite causes critical illness if persisted for longer durations and delay in precise treatment can lead to further complications. The automatic diagnostic model provides aid for medical practitioners to avail a fast and efficient diagnosis. Most of the existing work either utilizes a fully connected convolution neural network with successive pooling layers which causes loss of information in pixels. Further, convolutions can capture spatial invariances but, cannot capture rotational invariances. Hence to overcome these limitations, this research, develops an Imperative Dynamic routing mechanism with fully trained capsule networks for… More >

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Bader Rasheed¹, Adil Khan¹, S. M. Ahsan Kazmi², Rasheed Hussain², Md. Jalil Piran^3,*, Doug Young Suh⁴
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 921-939, 2021, DOI:10.32604/cmc.2021.015452
（This article belongs to the Special Issue: AI for Wearable Sensing--Smartphone / Smartwatch User Identification / Authentication)
Abstract Detecting malicious Uniform Resource Locators (URLs) is crucially important to prevent attackers from committing cybercrimes. Recent researches have investigated the role of machine learning (ML) models to detect malicious URLs. By using ML algorithms, first, the features of URLs are extracted, and then different ML models are trained. The limitation of this approach is that it requires manual feature engineering and it does not consider the sequential patterns in the URL. Therefore, deep learning (DL) models are used to solve these issues since they are able to perform featureless detection. Furthermore, DL models give better accuracy and generalization to newly… More >

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Raed Alsaqour¹, Saif Kamal², Maha Abdelhaq^3,*, Yazan Al Jeroudi⁴
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 941-960, 2021, DOI:10.32604/cmc.2021.015921
Abstract Mobile ad hoc network (MANET) is a dynamically reconfigurable wireless network with time-variable infrastructure. Given that nodes are highly mobile, MANET’s topology often changes. These changes increase the difficulty in finding the routes that the packets use when they are routed. This study proposes an algorithm called genetic algorithm-based location-aided routing (GALAR) to enhance the MANET routing protocol efficiency. The GALAR algorithm maintains an adaptive update of the node location information by adding the transmitting node location information to the routing packet and selecting the transmitting node to carry the packets to their destination. The GALAR was constructed based on… More >

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Oday Ali Hassen¹, Sarmad Omar Abter², Ansam A. Abdulhussein³, Saad M. Darwish^4,*, Yasmine M. Ibrahim⁴, Walaa Sheta⁵
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 961-981, 2021, DOI:10.32604/cmc.2021.014404
（This article belongs to the Special Issue: Digital Technology and Artificial Intelligence in Medicine and Dentistry)
Abstract Medical image segmentation has consistently been a significant topic of research and a prominent goal, particularly in computer vision. Brain tumor research plays a major role in medical imaging applications by providing a tremendous amount of anatomical and functional knowledge that enhances and allows easy diagnosis and disease therapy preparation. To prevent or minimize manual segmentation error, automated tumor segmentation, and detection became the most demanding process for radiologists and physicians as the tumor often has complex structures. Many methods for detection and segmentation presently exist, but all lack high accuracy. This paper’s key contribution focuses on evaluating machine learning… More >

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Ajay Arunachalam^1,*, Vinayakumar Ravi², Moez Krichen³, Roobaea Alroobaea⁴, Jehad Saad Alqurni⁵
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 983-1001, 2021, DOI:10.32604/cmc.2021.015371
（This article belongs to the Special Issue: Intelligent Communication Systems: Smart Wireless Digital Devices and IoT)
Abstract One of the key challenges in ad-hoc networks is the resource discovery problem. How efficiently & quickly the queried resource/object can be resolved in such a highly dynamic self-evolving network is the underlying question? Broadcasting is a basic technique in the Mobile Ad-hoc Networks (MANETs), and it refers to sending a packet from one node to every other node within the transmission range. Flooding is a type of broadcast where the received packet is retransmitted once by every node. The naive flooding technique floods the network with query messages, while the random walk scheme operates by contacting subsets of each… More >

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1269

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Muhammad Attique Khan¹, Abdul Majid¹, Tallha Akram², Nazar Hussain¹, Yunyoung Nam^3,*, Seifedine Kadry⁴, Shui-Hua Wang⁵, Majed Alhaisoni⁶
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1003-1019, 2021, DOI:10.32604/cmc.2021.015541
（This article belongs to the Special Issue: Artificial Intelligence and IoT based intelligent systems using high performance computing for Medical applications.)
Abstract Here, we use multi-type feature fusion and selection to predict COVID-19 infections on chest computed tomography (CT) scans. The scheme operates in four steps. Initially, we prepared a database containing COVID-19 pneumonia and normal CT scans. These images were retrieved from the Radiopaedia COVID-19 website. The images were divided into training and test sets in a ratio of 70:30. Then, multiple features were extracted from the training data. We used canonical correlation analysis to fuse the features into single vectors; this enhanced the predictive capacity. We next implemented a genetic algorithm (GA) in which an Extreme Learning Machine (ELM) served… More >

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Mahdi H. Miraz^1,2,*, Maaruf Ali³, Peter S. Excell², Sajid Khan⁴
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1021-1039, 2021, DOI:10.32604/cmc.2021.015405
Abstract This paper explains the development of a culturally inclusive ubiquitous M-Learning platform (“Mobile Academy”) with an AI-based adaptive user interface. The rationale and need for this research and development are justified by the continuing widespread adoption of the Internet and Internet enabled devices, especially smartphones. The M-learning platform was designed from the onset for the global traveller. The characteristics and limitations of the application are also discussed. The Mobile Academy, proof of concept prototype, was created to facilitate teaching and learning on the move or in environments where the use of a desktop computer is inconvenient or simply impossible. The… More >

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Muhammad Attique Khan¹, Tallha Akram², Muhammad Sharif¹, Seifedine Kadry³, Yunyoung Nam^4,*
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1041-1064, 2021, DOI:10.32604/cmc.2021.016307
（This article belongs to the Special Issue: Intelligent Decision Support Systems for Complex Healthcare Applications)
Abstract In this work, we propose a new, fully automated system for multiclass skin lesion localization and classification using deep learning. The main challenge is to address the problem of imbalanced data classes, found in HAM10000, ISBI2018, and ISBI2019 datasets. Initially, we consider a pre-trained deep neural network model, DarkeNet19, and fine-tune the parameters of third convolutional layer to generate the image gradients. All the visualized images are fused using a High-Frequency approach along with Multilayered Feed-Forward Neural Network (HFaFFNN). The resultant image is further enhanced by employing a log-opening based activation function to generate a localized binary image. Later, two… More >

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Rihem Farkh^1,5,*, Mohammad Tabrez Quasim², Khaled Al jaloud¹, Saad Alhuwaimel³, Shams Tabrez Siddiqui⁴
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1065-1079, 2021, DOI:10.32604/cmc.2021.016600
（This article belongs to the Special Issue: Machine Learning for Data Analytics)
Abstract With the development of artificial intelligence technology, various sectors of industry have developed. Among them, the autonomous vehicle industry has developed considerably, and research on self-driving control systems using artificial intelligence has been extensively conducted. Studies on the use of image-based deep learning to monitor autonomous driving systems have recently been performed. In this paper, we propose an advanced control for a serving robot. A serving robot acts as an autonomous line-follower vehicle that can detect and follow the line drawn on the floor and move in specified directions. The robot should be able to follow the trajectory with speed… More >

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Xiuyu Yang^1,*, Qi Guo¹, Jianzhong Gui², Renyong Chai³, Xueyuan Liu¹
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1081-1097, 2021, DOI:10.32604/cmc.2021.016375
Abstract Centralized delivery has become the main operation mode under the scaled development of wind power. Transmission channels are usually the guarantee of out-delivered wind power for large-scale wind base. The configuration of transmission capacity, which has the features of low utilization and poor economy, is hardly matching correctly due to the volatility and low energy density of wind. The usage of energy storage can mitigate wind power fluctuations and reduce the requirement of out-delivery transmission capacity, but facing the issue of energy storage cost recovery. Therefore, it is necessary to optimize the allocation of energy storage while considering the problem… More >

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Ayesha Bin T. Tahir¹, Muhamamd Attique Khan¹, Majed Alhaisoni², Junaid Ali Khan¹, Yunyoung Nam^3,*, Shui-Hua Wang⁴, Kashif Javed⁵
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1099-1116, 2021, DOI:10.32604/cmc.2021.015154
（This article belongs to the Special Issue: AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems)
Abstract Background: A brain tumor reflects abnormal cell growth. Challenges: Surgery, radiation therapy, and chemotherapy are used to treat brain tumors, but these procedures are painful and costly. Magnetic resonance imaging (MRI) is a non-invasive modality for diagnosing tumors, but scans must be interpretated by an expert radiologist. Methodology: We used deep learning and improved particle swarm optimization (IPSO) to automate brain tumor classification. MRI scan contrast is enhanced by ant colony optimization (ACO); the scans are then used to further train a pretrained deep learning model, via transfer learning (TL), and to extract features from two dense layers. We fused… More >

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Shankarnarayanan Nalini^1,*, Nagappan Krishnaraj², Thangaiyan Jayasankar³, Kalimuthu Vinothkumar⁴, Antony Sagai Francis Britto⁵, Kamalraj Subramaniam⁶, Chokkalingam Bharatiraja⁷
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1117-1128, 2021, DOI:10.32604/cmc.2021.012431
Abstract Precision Agriculture is a concept of farm management which makes use of IoT and networking concepts to improve the crop. Plant diseases are one of the underlying causes in the decrease in the number of quantity and quality of the farming crops. Recognition of diseases from the plant images is an active research topic which makes use of machine learning (ML) approaches. A novel deep neural network (DNN) classification model is proposed for the identification of paddy leaf disease using plant image data. Classification errors were minimized by optimizing weights and biases in the DNN model using a crow search… More >

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Anh Tuan Hoang¹, Xuan Phuong Nguyen², Osamah Ibrahim Khalaf³, Thi Xuan Tran⁴, Minh Quang Chau⁵, Thi Minh Hao Dong², Duong Nam Nguyen^6,*
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1129-1145, 2021, DOI:10.32604/cmc.2021.015349
（This article belongs to the Special Issue: Application of Big Data Analytics in the Management of Business)
Abstract The type of technology used to strengthen the surface structure of machine parts, typically by carbon-permeation, has made a great contribution to the mechanical engineering industry because of its outstanding advantages in corrosion resistance and enhanced mechanical and physical properties. Furthermore, carbon permeation is considered as an optimal method of heat treatment through the diffusion of carbon atoms into the surface of alloy steel. This study presented research results on the thermodynamic calculation and simulation of the carbon permeability process. Applying Fick’s law, the paper calculated the distribution of carbon concentration in the alloy steel after it is absorbed from… More >

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R. Thamizhamuthu^*, D. Manjula
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1147-1160, 2021, DOI:10.32604/cmc.2021.015503
Abstract The deadliest type of skin cancer is malignant melanoma. The diagnosis requires at the earliest to reduce the mortality rate. In this study, an efficient Skin Melanoma Classification (SMC) system is presented using dermoscopic images as a non-invasive procedure. The SMC system consists of four modules; segmentation, feature extraction, feature reduction and finally classification. In the first module, k-means clustering is applied to cluster the colour information of dermoscopic images. The second module extracts meaningful and useful descriptors based on the statistics of local property, parameters of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model of wavelet and spatial patterns by Dominant… More >

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Said Ali Hassan¹, Khalid Alnowibet^2,3, Prachi Agrawal⁴, Ali Wagdy Mohamed^5,6,*
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1161-1181, 2021, DOI:10.32604/cmc.2021.015494
（This article belongs to the Special Issue: Role of Computer in Modelling & Solving Real-World Problems)
Abstract The optimum delivery of safeguarding substances is a major part of supply chain management and a crucial issue in the mitigation against the outbreak of pandemics. A problem arises for a decision maker who wants to optimally choose a subset of candidate consumers to maximize the distributed quantities of the needed safeguarding substances within a specific time period. A nonlinear binary mathematical programming model for the problem is formulated. The decision variables are binary ones that represent whether to choose a specific consumer, and design constraints are formulated to keep track of the chosen route. To better illustrate the problem,… More >

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Said Ali Hassan¹, Khalid Alnowibet², Prachi Agrawal³, Ali Wagdy Mohamed^4,5,*
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1183-1202, 2021, DOI:10.32604/cmc.2021.015514
（This article belongs to the Special Issue: Role of Computer in Modelling & Solving Real-World Problems)
Abstract Determining the optimum location of facilities is critical in many fields, particularly in healthcare. This study proposes the application of a suitable location model for field hospitals during the novel coronavirus 2019 (COVID-19) pandemic. The used model is the most appropriate among the three most common location models utilized to solve healthcare problems (the set covering model, the maximal covering model, and the P-median model). The proposed nonlinear binary constrained model is a slight modification of the maximal covering model with a set of nonlinear constraints. The model is used to determine the optimum location of field hospitals for COVID-19… More >

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Yoosef B. Abushark¹, Asif Irshad Khan^1,*, Fawaz Jaber Alsolami¹, Abdulmohsen Almalawi¹, Md Mottahir Alam², Alka Agrawal³, Rajeev Kumar^3,4, Raees Ahmad Khan³
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1203-1218, 2021, DOI:10.32604/cmc.2021.016610
Abstract Most of the security strategies today are primarily designed to provide security protection, rather than to solve one of the basic security issues related to adequate software product architecture. Several models, frameworks and methodologies have been introduced by the researchers for a secure and sustainable software development life cycle. Therefore it is important to assess the usability of the popular security requirements engineering (SRE) approaches. A significant factor in the management and handling of successful security requirements is the assessment of security requirements engineering method performance. This assessment will allow changes to the engineering process of security requirements. The consistency… More >

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Rupkumar Mahapatra¹, Sovan Samanta², Madhumangal Pal¹, Jeong-Gon Lee^3,*, Shah Khalid Khan⁴, Usman Naseem⁵, Robin Singh Bhadoria⁶
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1219-1233, 2021, DOI:10.32604/cmc.2021.015590
（This article belongs to the Special Issue: Recent Trends in Machine Intelligence respected to Medical Field Applications)
Abstract Graph colouring is the system of assigning a colour to each vertex of a graph. It is done in such a way that adjacent vertices do not have equal colour. It is fundamental in graph theory. It is often used to solve real-world problems like traffic light signalling, map colouring, scheduling, etc. Nowadays, social networks are prevalent systems in our life. Here, the users are considered as vertices, and their connections/interactions are taken as edges. Some users follow other popular users’ profiles in these networks, and some don’t, but those non-followers are connected directly to the popular profiles. That means,… More >

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Mohd Effendi Ewan Mohd Matore^*
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1235-1253, 2021, DOI:10.32604/cmc.2021.016143
（This article belongs to the Special Issue: Application of Artificial Intelligence, Internet of Things, and Learning Approach for Learning Process in COVID-19/Industrial Revolution 4.0)
Abstract Assessment using Bloom’s taxonomy levels has evolved in a variety of contexts and uses. In the era of the COVID-19 pandemic, which necessitates use of online assessment, the need for teachers to use digital-based taxonomy skills or Bloom’s Digital Taxonomy (BDT) has increased even more. However, the existing studies on validity and reliability of BDT items are limited. To overcome this limitation, this study aims to test whether BDT has good psychometric characteristics as a teacher’s self-assessment tool using the Rasch model analysis and to investigate the pattern of BDT usage in teaching and learning. By using a quantitative online… More >

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2174

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Ra’ed M. Al-Khatib^1,*, Taha Zerrouki², Mohammed M. Abu Shquier³, Amar Balla⁴, Asef Al-Khateeb⁵
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1255-1269, 2021, DOI:10.32604/cmc.2021.016155
（This article belongs to the Special Issue: Artificial Intelligence and IoT based intelligent systems using high performance computing for Medical applications.)
Abstract This paper introduces a new enhanced Arabic stemming algorithm for solving the information retrieval problem, especially in medical documents. Our proposed algorithm is a light stemming algorithm for extracting stems and roots from the input data. One of the main challenges facing the light stemming algorithm is cutting off the input word, to extract the initial segments. When initiating the light stemmer with strong initial segments, the final extracting stems and roots will be more accurate. Therefore, a new enhanced segmentation based on deploying the Direct Acyclic Graph (DAG) model is utilized. In addition to extracting the powerful initial segments,… More >

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Mosleh M. Abualhaj^*, Qusai Y. Shambour, Abdelrahman H. Hussein, Qasem M. Kharma
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1271-1283, 2021, DOI:10.32604/cmc.2021.014928
Abstract Voice over Internet Protocol (VoIP) is widely used by companies, schools, universities, and other institutions. However, VoIP faces many issues that slow down its propagation. An important issue is poor utilization of the VoIP service network bandwidth, which results from the large header of the VoIP packet. The objective of this study is to handle this poor utilization of the network bandwidth. Therefore, this study proposes a novel method to address this large header overhead problem. The proposed method is called zero size payload (ZSP), which aims to reemploy and use the header information (fields) of the VoIP packet that… More >

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Jiongzhi Yang, Srivatsa Harish, Candy Li, Hengduo Zhao, Brittney Antous, Pinar Acar^*
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1285-1302, 2021, DOI:10.32604/cmc.2021.016829
Abstract This paper presents a de-novo computational design method driven by deep reinforcement learning to achieve reliable predictions and optimum properties for periodic microstructures. With recent developments in 3-D printing, microstructures can have complex geometries and material phases fabricated to achieve targeted mechanical performance. These material property enhancements are promising in improving the mechanical, thermal, and dynamic performance in multiple engineering systems, ranging from energy harvesting applications to spacecraft components. The study investigates a novel and efficient computational framework that integrates deep reinforcement learning algorithms into finite element-based material simulations to quantitatively model and design 3-D printed periodic microstructures. These algorithms… More >

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Haoran Huang¹, Qinyong Lin², Weitong Chen³, Kai Fang⁴, Huazhou Chen⁵, Ken Cai^2,*
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1303-1320, 2021, DOI:10.32604/cmc.2021.016163
Abstract To better reflect the psychological behavior characteristics of loss aversion, this paper builds a double reference point decision making method for dynamic multi-attribute decision-making (DMADM) problem, taking bottom-line and target as reference pints. First, the gain/loss function is given, and the state is divided according to the relationship between the gain/loss value and the reference point. Second, the attitude function is constructed based on the results of state division to establish the utility function. Third, the comprehensive utility value is calculated as the basis for alternatives classification and ranking. Finally, the new method is used to evaluate the development level… More >

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Mohammed H. Alsharif¹, Abu Jahid², Mahmoud A. Albreem³, Peerapong Uthansakul^4,*, Jamel Nebhen⁵, Khalid Yahya⁶
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1321-1339, 2021, DOI:10.32604/cmc.2021.016738
（This article belongs to the Special Issue: Advanced 5G Communication System for Transforming Health Care)
Abstract The design of green cellular networking according to the traffic arrivals has the capability to reduce the overall energy consumption to a cluster in a cost-effective way. The cell zooming approach has appealed much attention that adaptively offloads the BS load demands adjusting the transmit power based on the traffic intensity and green energy availability. Besides, the researchers are focused on implementing renewable energy resources, which are considered the most attractive practices in designing energy-efficient wireless networks over the long term in a cost-efficient way in the existing infrastructure. The utilization of available solar can be adapted to acquire cost-effective… More >

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Shabib Aftab^1,2, Saad Alanazi³, Munir Ahmad¹, Muhammad Adnan Khan^4,*, Areej Fatima⁵, Nouh Sabri Elmitwally^3,6
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1341-1357, 2021, DOI:10.32604/cmc.2021.016814
Abstract Diabetes mellitus, generally known as diabetes, is one of the most common diseases worldwide. It is a metabolic disease characterized by insulin deficiency, or glucose (blood sugar) levels that exceed 200 mg/dL (11.1 ml/L) for prolonged periods, and may lead to death if left uncontrolled by medication or insulin injections. Diabetes is categorized into two main types—type 1 and type 2—both of which feature glucose levels above “normal,” defined as 140 mg/dL. Diabetes is triggered by malfunction of the pancreas, which releases insulin, a natural hormone responsible for controlling glucose levels in blood cells. Diagnosis and comprehensive analysis of this… More >

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Ying Fu^1,2,*, Minxue Gong¹, Guang Yang¹, Hong Wei³, Jiliu Zhou^1,2
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1359-1374, 2021, DOI:10.32604/cmc.2021.016536
Abstract Generative adversarial networks (GANs) have considerable potential to alleviate challenges linked to data scarcity. Recent research has demonstrated the good performance of this method for data augmentation because GANs synthesize semantically meaningful data from standard signal distribution. The goal of this study was to solve the overfitting problem that is caused by the training process of convolution networks with a small dataset. In this context, we propose a data augmentation method based on an evolutionary generative adversarial network for cardiac magnetic resonance images to extend the training data. In our structure of the evolutionary GAN, the most optimal generator is… More >

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1001

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Bozhi Xu¹, Jiarui Liu¹, Jifan Liang¹, Wei Lu^1,*, Yue Zhang²
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1375-1388, 2021, DOI:10.32604/cmc.2021.016760
Abstract In recent years, with the rapid development of deep learning technologies, some neural network models have been applied to generate fake media. DeepFakes, a deep learning based forgery technology, can tamper with the face easily and generate fake videos that are difficult to be distinguished by human eyes. The spread of face manipulation videos is very easy to bring fake information. Therefore, it is important to develop effective detection methods to verify the authenticity of the videos. Due to that it is still challenging for current forgery technologies to generate all facial details and the blending operations are used in… More >

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Pengfei Gong^1,2, Qun Wang^2,*, Junjun Zhu³
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1389-1408, 2021, DOI:10.32604/cmc.2021.016483
Abstract Fatal traffic accidents in urban areas can adversely affect the urban road traffic system and pose many challenges for urban traffic management. Therefore, it is necessary to first classify emergency responses to such accidents and then handle them quickly and correctly. The aim of this paper is to develop an evaluation index system and to use appropriate methods to investigate emergency-response classifications to fatal traffic accidents in Chinese urban areas. This study used a multilevel hierarchical structural model to determine emergency-response classification. In the model, accident attributes, urban road network vulnerability, and institutional resilience were used as classification criteria. Each… More >

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Habib Ullah Khan^1,*, Mohammad Kamel Alomari¹, Sulaiman Khan², Shah Nazir², Asif Qumer Gill³, Alanoud Ali Al-Maadid⁴, Zaki Khalid Abu-Shawish¹, Mostafa Kamal Hassan¹
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1409-1428, 2021, DOI:10.32604/cmc.2021.016058
（This article belongs to the Special Issue: Deep Learning and Parallel Computing for Intelligent and Efficient IoT)
Abstract The revolution in Internet of Things (IoT)-based devices and applications has provided smart applications for humans. These applications range from healthcare to traffic-flow management, to communication devices, to smart security devices, and many others. In particular, government and private organizations are showing significant interest in IoT-enabled applications for smart homes. Despite the perceived benefits and interest, human safety is also a key concern. This research is aimed at systematically analyzing the available literature on smart homes and identifying areas of concern or risk with a view to supporting the design of safe and secure smart homes. For this systematic review… More >

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Luona Song¹, Xiaojuan Wang^1,*, Peng Wei¹, Zikui Lu¹, Xiaojun Wang², Nicolas Merveille³
CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1429-1446, 2021, DOI:10.32604/cmc.2021.016954
Abstract Blockchain is an emerging decentralized distributed technology that can cross the boundaries and guarantee safe and trustworthy value transfers between participants. Combining the blockchain technology with the Internet of Things (IoT) technology to enhance the transparency and sustainability of agricultural supply chains, has attracted researchers from both academia and industry. This paper reviews the latest applications of the blockchain and IoT technologies in the sustainable agricultural supply chain management and explores the design and implementation of a blockchain-based sustainable solution. By placing the sustainable agricultural supply chain management at its core, a blockchain-based framework is designed. Considering the heterogeneity of… More >

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