Open Access

ARTICLE

S. Sandhya¹, A. Balasundaram^2,*, Ayesha Shaik¹
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2331-2343, 2023, DOI:10.32604/cmc.2023.032715 - 31 October 2022
Abstract Occurrence of crimes has been on the constant rise despite the emerging discoveries and advancements in the technological field in the past decade. One of the most tedious tasks is to track a suspect once a crime is committed. As most of the crimes are committed by individuals who have a history of felonies, it is essential for a monitoring system that does not just detect the person’s face who has committed the crime, but also their identity. Hence, a smart criminal detection and identification system that makes use of the OpenCV Deep Neural Network… More >

View

3920

Download

1278

Like

1

Open Access

ARTICLE

Fazal Dayan^1,*, Dumitru Baleanu^2,3,4, Nauman Ahmed⁵, Jan Awrejcewicz⁶, Muhammad Rafiq⁷, Ali Raza⁸, Muhammad Ozair Ahmad⁵
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2345-2361, 2023, DOI:10.32604/cmc.2023.033261 - 31 October 2022
Abstract The application of fuzzy theory is vital in all scientific disciplines. The construction of mathematical models with fuzziness is little studied in the literature. With this in mind and for a better understanding of the disease, an SEIR model of malaria transmission with fuzziness is examined in this study by extending a classical model of malaria transmission. The parameters and , being function of the malaria virus load, are considered fuzzy numbers. Three steady states and the reproduction number of the model are analyzed in fuzzy senses. A numerical technique is developed in a fuzzy More >

View

1876

Download

816

Like

2

Open Access

ARTICLE

Sajjad Ahmad¹, Imran Raza¹, M. Hasan Jamal¹, Sirojiddin Djuraev², Soojung Hur³, Imran Ashraf^3,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2363-2377, 2023, DOI:10.32604/cmc.2023.032694 - 31 October 2022
Abstract Vehicle-to-grid technology is an emerging field that allows unused power from Electric Vehicles (EVs) to be used by the smart grid through the central aggregator. Since the central aggregator is connected to the smart grid through a wireless network, it is prone to cyber-attacks that can be detected and mitigated using an intrusion detection system. However, existing intrusion detection systems cannot be used in the vehicle-to-grid network because of the special requirements and characteristics of the vehicle-to-grid network. In this paper, the effect of denial-of-service attacks of malicious electric vehicles on the central aggregator of… More >

View

2184

Download

763

Open Access

ARTICLE

Doaa Sami Khafaga¹, El-Sayed M. El-kenawy^2,3, Faten Khalid Karim^1,*, Sameer Alshetewi⁴, Abdelhameed Ibrahim⁵, Abdelaziz A. Abdelhamid^6,7, D. L. Elsheweikh⁸
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2379-2395, 2023, DOI:10.32604/cmc.2023.032886 - 31 October 2022
Abstract Electrocardiogram (ECG) signal is a measure of the heart’s electrical activity. Recently, ECG detection and classification have benefited from the use of computer-aided systems by cardiologists. The goal of this paper is to improve the accuracy of ECG classification by combining the Dipper Throated Optimization (DTO) and Differential Evolution Algorithm (DEA) into a unified algorithm to optimize the hyperparameters of neural network (NN) for boosting the ECG classification accuracy. In addition, we proposed a new feature selection method for selecting the significant feature that can improve the overall performance. To prove the superiority of the More >

View

1309

Download

780

Open Access

ARTICLE

Ahmed Abdu Alattab^1,*, Mohammed Eid Ibrahim¹, Reyazur Rashid Irshad¹, Anwar Ali Yahya², Amin A. Al-Awady³
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2397-2413, 2023, DOI:10.32604/cmc.2023.030924 - 31 October 2022
Abstract This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop rotation. In case-based reasoning systems, case representation is critical, and thus, researchers have thoroughly investigated textual, attribute-value pair, and ontological representations. As big databases result in slow case retrieval, this research suggests a fast case retrieval strategy based on an associated representation, so that, cases are interrelated in both either similar or dissimilar cases. As soon as a new case is recorded, it is compared to prior data to find a relative match. The proposed More >

View

1632

Download

886

Like

1

Open Access

ARTICLE

Narongsak Yotha¹, Qusain Hiader², Zulqurnain Sabir³, Muhammad Asif Zahoor Raja⁴, Salem Ben Said⁵, Qasem Al-Mdallal⁵, Thongchai Botmart⁶, Wajaree Weera^6,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2415-2430, 2023, DOI:10.32604/cmc.2023.031352 - 31 October 2022
Abstract This study aims to solve the nonlinear fractional-order mathematical model (FOMM) by using the normal and dysregulated bone remodeling of the myeloma bone disease (MBD). For the more precise performance of the model, fractional-order derivatives have been used to solve the disease model numerically. The FOMM is preliminarily designed to focus on the critical interactions between bone resorption or osteoclasts (OC) and bone formation or osteoblasts (OB). The connections of OC and OB are represented by a nonlinear differential system based on the cellular components, which depict stable fluctuation in the usual bone case and… More >

View

1350

Download

729

Open Access

ARTICLE

Bich Nguyen¹, Binh Nguyen¹, Hai Tran², Vuong Pham¹, Le Nhi Lam Thuy¹, Pham The Bao^1,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2431-2441, 2023, DOI:10.32604/cmc.2023.029618 - 31 October 2022
Abstract 3-dimension (3-D) printing technology is growing strongly with many applications, one of which is the garment industry. The application of human body models to the garment industry is necessary to respond to the increasing personalization demand and still guarantee aesthetics. This paper proposes a method to construct 3-D human models by applying deep learning. We calculate the location of the main slices of the human body, including the neck, chest, belly, buttocks, and the rings of the extremities, using pre-existing information. Then, on the positioning frame, we find the key points (fixed and unaltered) of More >

View

1384

Download

623

Open Access

ARTICLE

Amani Abdulrahman Albraikan¹, Nadhem NEMRI², Mimouna Abdullah Alkhonaini³, Anwer Mustafa Hilal^4,*, Ishfaq Yaseen⁴, Abdelwahed Motwakel⁴
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2443-2459, 2023, DOI:10.32604/cmc.2023.026379 - 31 October 2022
Abstract Melanoma remains a serious illness which is a common form of skin cancer. Since the earlier detection of melanoma reduces the mortality rate, it is essential to design reliable and automated disease diagnosis model using dermoscopic images. The recent advances in deep learning (DL) models find useful to examine the medical image and make proper decisions. In this study, an automated deep learning based melanoma detection and classification (ADL-MDC) model is presented. The goal of the ADL-MDC technique is to examine the dermoscopic images to determine the existence of melanoma. The ADL-MDC technique performs contrast… More >

View

1722

Download

693

Like

1

Open Access

ARTICLE

Pradeep Krishnadoss^*, Vijayakumar Kedalu Poornachary, Parkavi Krishnamoorthy, Leninisha Shanmugam
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2461-2478, 2023, DOI:10.32604/cmc.2023.031614 - 31 October 2022
Abstract Well organized datacentres with interconnected servers constitute the cloud computing infrastructure. User requests are submitted through an interface to these servers that provide service to them in an on-demand basis. The scientific applications that get executed at cloud by making use of the heterogeneous resources being allocated to them in a dynamic manner are grouped under NP hard problem category. Task scheduling in cloud poses numerous challenges impacting the cloud performance. If not handled properly, user satisfaction becomes questionable. More recently researchers had come up with meta-heuristic type of solutions for enriching the task scheduling… More >

View

1091

Download

643

Open Access

ARTICLE

Pongsakorn Tatongjai¹, Tossapon Boongoen^2,*, Natthakan Iam-On², Nitin Naik³, Longzhi Yang⁴
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2479-2498, 2023, DOI:10.32604/cmc.2023.024858 - 31 October 2022
Abstract As more business transactions and information services have been implemented via communication networks, both personal and organization assets encounter a higher risk of attacks. To safeguard these, a perimeter defence like NIDS (network-based intrusion detection system) can be effective for known intrusions. There has been a great deal of attention within the joint community of security and data science to improve machine-learning based NIDS such that it becomes more accurate for adversarial attacks, where obfuscation techniques are applied to disguise patterns of intrusive traffics. The current research focuses on non-payload connections at the TCP (transmission… More >

View

2375

Download

726

Like

1

Open Access

ARTICLE

Sultan Alkaabi^1,*, Salman Yussof¹, Sameera Al-Mulla²
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2499-2516, 2023, DOI:10.32604/cmc.2023.029914 - 31 October 2022
Abstract Age estimation using forensics odontology is an important process in identifying victims in criminal or mass disaster cases. Traditionally, this process is done manually by human expert. However, the speed and accuracy may vary depending on the expertise level of the human expert and other human factors such as level of fatigue and attentiveness. To improve the recognition speed and consistency, researchers have proposed automated age estimation using deep learning techniques such as Convolutional Neural Network (CNN). CNN requires many training images to obtain high percentage of recognition accuracy. Unfortunately, it is very difficult to… More >

View

1183

Download

989

Like

1

Open Access

ARTICLE

Wasi Ur Rehman Khan¹, Muhammad Fawad Khan¹, Muhammad Irfan², Sadiq Ullah¹, Naveed Mufti¹, Usman Ali¹, Rizwan Ullah¹, Fazal Muhammad^3,*, Saifur Rahman², Faisal Althobiani⁴, Mohammed Alshareef⁵, Mohammad E. Gommosani⁶
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2517-2530, 2023, DOI:10.32604/cmc.2023.031833 - 31 October 2022
Abstract A compact, reconfigurable antenna supporting multiple wireless services with a minimum number of switches is found lacking in literature and the same became the focus and outcome of this work. It was achieved by designing a Th-Shaped frequency reconfigurable multi-band microstrip planar antenna, based on use of a single switch within the radiating structure of the antenna. Three frequency bands (i.e., 2007–2501 MHz, 3660–3983 MHz and 9341–1046 MHz) can be operated with the switch in the ON switch state. In the OFF state of the switch, the antenna operates within the 2577–3280 MHz and 9379–1033 MHz Bands. The proposed antenna… More >

View

977

Download

593

Open Access

ARTICLE

Husam Yahya¹, Dumitru Baleanu^2,3,4, Rabha W. Ibrahim^5,*, Nadia M.G. Al-Saidi⁶
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2531-2539, 2023, DOI:10.32604/cmc.2023.033282 - 31 October 2022
Abstract The current study provides a quantum calculus-based medical image enhancement technique that dynamically chooses the spatial distribution of image pixel intensity values. The technique focuses on boosting the edges and texture of an image while leaving the smooth areas alone. The brain Magnetic Resonance Imaging (MRI) scans are used to visualize the tumors that have spread throughout the brain in order to gain a better understanding of the stage of brain cancer. Accurately detecting brain cancer is a complex challenge that the medical system faces when diagnosing the disease. To solve this issue, this research… More >

View

1070

Download

701

Open Access

ARTICLE

Amitoj Bir Singh¹, Lalit Kumar Awasthi¹, Urvashi¹, Mohammad Shorfuzzaman², Abdulmajeed Alsufyani², Mueen Uddin^3,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2541-2555, 2023, DOI:10.32604/cmc.2023.032795 - 31 October 2022
Abstract Neural networks play a significant role in the field of image classification. When an input image is modified by adversarial attacks, the changes are imperceptible to the human eye, but it still leads to misclassification of the images. Researchers have demonstrated these attacks to make production self-driving cars misclassify Stop Road signs as 45 Miles Per Hour (MPH) road signs and a turtle being misclassified as AK47. Three primary types of defense approaches exist which can safeguard against such attacks i.e., Gradient Masking, Robust Optimization, and Adversarial Example Detection. Very few approaches use Generative Adversarial… More >

View

1306

Download

685

Open Access

ARTICLE

Nayef Alqahtani^1,2,*, Ali Alqahtani³
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2557-2573, 2023, DOI:10.32604/cmc.2023.026316 - 31 October 2022
Abstract Phasor Measurement Units (PMUs) provide Global Positioning System (GPS) time-stamped synchronized measurements of voltage and current with the phase angle of the system at certain points along with the grid system. Those synchronized data measurements are extracted in the form of amplitude and phase from various locations of the power grid to monitor and control the power system condition. A PMU device is a crucial part of the power equipment in terms of the cost and operative point of view. However, such ongoing development and improvement to PMUs’ principal work are essential to the network… More >

View

802

Download

599

Open Access

ARTICLE

Sakda Noinang¹, Zulqurnain Sabir², Muhammad Asif Zahoor Raja³, Soheil Salahshour⁴, Wajaree Weera^5,*, Thongchai Botmart⁵
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2575-2588, 2023, DOI:10.32604/cmc.2023.029046 - 31 October 2022
Abstract The current investigations are presented to solve the fractional order HBV differential infection system (FO-HBV-DIS) with the response of antibody immune using the optimization based stochastic schemes of the Levenberg-Marquardt backpropagation (LMB) neural networks (NNs), i.e., LMBNNs. The FO-HBV-DIS with the response of antibody immune is categorized into five dynamics, healthy hepatocytes (H), capsids (D), infected hepatocytes (I), free virus (V) and antibodies (W). The investigations for three different FO variants have been tested numerically to solve the nonlinear FO-HBV-DIS. The data magnitudes are implemented 75% for training, 10% for certification and 15% for testing More >

View

1173

Download

713

Open Access

ARTICLE

Muhammad Aasim Qureshi¹, Muhammad Asif², Saira Anwar³, Umar Shaukat¹, Atta-ur-Rahman⁴, Muhammad Adnan Khan^5,*, Amir Mosavi^6,7,8
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2589-2605, 2023, DOI:10.32604/cmc.2023.032173 - 31 October 2022
Abstract With the advancements in internet facilities, people are more inclined towards the use of online services. The service providers shelve their items for e-users. These users post their feedbacks, reviews, ratings, etc. after the use of the item. The enormous increase in these reviews has raised the need for an automated system to analyze these reviews to rate these items. Sentiment Analysis (SA) is a technique that performs such decision analysis. This research targets the ranking and rating through sentiment analysis of these reviews, on different aspects. As a case study, Songs are opted to More >

View

1368

Download

604

Open Access

ARTICLE

Muhammad Sajid Farooq¹, Sagheer Abbas¹, Atta-ur-Rahman², Kiran Sultan³, Muhammad Adnan Khan^4,*, Amir Mosavi^5,6,7
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2607-2623, 2023, DOI:10.32604/cmc.2023.032617 - 31 October 2022
Abstract The rapid growth in data generation and increased use of computer network devices has amplified the infrastructures of internet. The interconnectivity of networks has brought various complexities in maintaining network availability, consistency, and discretion. Machine learning based intrusion detection systems have become essential to monitor network traffic for malicious and illicit activities. An intrusion detection system controls the flow of network traffic with the help of computer systems. Various deep learning algorithms in intrusion detection systems have played a prominent role in identifying and analyzing intrusions in network traffic. For this purpose, when the network More >

View

1743

Download

916

Open Access

ARTICLE

Muhammad Nadeem¹, Ali Arshad², Saman Riaz², Syeda Wajiha Zahra¹, Shahab S. Band³, Amir Mosavi^4,5,6,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2625-2640, 2023, DOI:10.32604/cmc.2023.030899 - 31 October 2022
Abstract Many organizations have insisted on protecting the cloud server from the outside, although the risks of attacking the cloud server are mostly from the inside. There are many algorithms designed to protect the cloud server from attacks that have been able to protect the cloud server attacks. Still, the attackers have designed even better mechanisms to break these security algorithms. Cloud cryptography is the best data protection algorithm that exchanges data between authentic users. In this article, one symmetric cryptography algorithm will be designed to secure cloud server data, used to send and receive cloud… More >

View

1528

Download

590

Open Access

ARTICLE

Muhammad Nadeem¹, Ali Arshad², Saman Riaz², SyedaWajiha Zahra¹, Muhammad Rashid², Shahab S. Band^3,*, Amir Mosavi^4,5,6
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2641-2659, 2023, DOI:10.32604/cmc.2023.028796 - 31 October 2022
Abstract Cloud computing is one of the most attractive and cost-saving models, which provides online services to end-users. Cloud computing allows the user to access data directly from any node. But nowadays, cloud security is one of the biggest issues that arise. Different types of malware are wreaking havoc on the clouds. Attacks on the cloud server are happening from both internal and external sides. This paper has developed a tool to prevent the cloud server from spamming attacks. When an attacker attempts to use different spamming techniques on a cloud server, the attacker will be More >

View

2735

Download

687

Open Access

ARTICLE

Ademola Olusola Adesina¹, Patrick Seun Ayobioloja², Ibidun Christiana Obagbuwa³, Tola John Odule¹, Adenrele A. Afolorunso², Sunday Adeola Ajagbe^4,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2661-2675, 2023, DOI:10.32604/cmc.2023.031245 - 31 October 2022
Abstract CAPTCHA is an acronym that stands for Completely Automated Public Turing Test to tell Computers and Humans Apart (CAPTCHA), it is a good example of an authentication system that can be used to determine the true identity of any user. It serves as a security measure to prevent an attack caused by web bots (automatic programs) during an online transaction. It can come as text-based or image-based depending on the project and the programmer. The usability and robustness, as well as level of security, provided each of the varies and call for the development of… More >

View

1209

Download

589

Like

1

Open Access

ARTICLE

Reem Alkanhel¹, El-Sayed M. El-kenawy², Abdelaziz A. Abdelhamid^3,4, Abdelhameed Ibrahim⁵, Manal Abdullah Alohali⁶, Mostafa Abotaleb⁷, Doaa Sami Khafaga^8,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2677-2693, 2023, DOI:10.32604/cmc.2023.033273 - 31 October 2022
Abstract Applications of internet-of-things (IoT) are increasingly being used in many facets of our daily life, which results in an enormous volume of data. Cloud computing and fog computing, two of the most common technologies used in IoT applications, have led to major security concerns. Cyberattacks are on the rise as a result of the usage of these technologies since present security measures are insufficient. Several artificial intelligence (AI) based security solutions, such as intrusion detection systems (IDS), have been proposed in recent years. Intelligent technologies that require data preprocessing and machine learning algorithm-performance augmentation require… More >

View

1552

Download

698

Open Access

ARTICLE

Reem Alkanhel^1,*, Doaa Sami Khafaga², El-Sayed M. El-kenawy³, Abdelaziz A. Abdelhamid^4,5, Abdelhameed Ibrahim⁶, Rashid Amin⁷, Mostafa Abotaleb⁸, B. M. El-den⁶
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2695-2709, 2023, DOI:10.32604/cmc.2023.033153 - 31 October 2022
Abstract The Internet of Things (IoT) is a modern approach that enables connection with a wide variety of devices remotely. Due to the resource constraints and open nature of IoT nodes, the routing protocol for low power and lossy (RPL) networks may be vulnerable to several routing attacks. That’s why a network intrusion detection system (NIDS) is needed to guard against routing assaults on RPL-based IoT networks. The imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network attacks. Therefore, we propose in this paper… More >

View

1037

Download

609

Like

1

Open Access

ARTICLE

Wajaree Weera¹, Thongchai Botmart^1,*, Charuwat Chantawat¹, Zulqurnain Sabir^2,3, Waleed Adel^4,5, Muhammad Asif Zahoor Raja⁶, Muhammad Kristiawan⁷
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2711-2724, 2023, DOI:10.32604/cmc.2023.033233 - 31 October 2022
Abstract The main purpose of the study is to present a numerical approach to investigate the numerical performances of the fractional 4-D chaotic financial system using a stochastic procedure. The stochastic procedures mainly depend on the combination of the artificial neural network (ANNs) along with the Levenberg-Marquardt Backpropagation (LMB) i.e., ANNs-LMB technique. The fractional-order term is defined in the Caputo sense and three cases are solved using the proposed technique for different values of the fractional order α. The values of the fractional order derivatives to solve the fractional 4-D chaotic financial system are used between… More >

View

977

Download

576

Open Access

ARTICLE

Mohammad Alamgeer¹, Amal Al-Rasheed², Ahmad Alhindi³, Manar Ahmed Hamza^4,*, Abdelwahed Motwakel⁴, Mohamed I. Eldesouki⁵
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2725-2738, 2023, DOI:10.32604/cmc.2023.029163 - 31 October 2022
Abstract Data mining process involves a number of steps from data collection to visualization to identify useful data from massive data set. the same time, the recent advances of machine learning (ML) and deep learning (DL) models can be utilized for effectual rainfall prediction. With this motivation, this article develops a novel comprehensive oppositional moth flame optimization with deep learning for rainfall prediction (COMFO-DLRP) Technique. The proposed CMFO-DLRP model mainly intends to predict the rainfall and thereby determine the environmental changes. Primarily, data pre-processing and correlation matrix (CM) based feature selection processes are carried out. In More >

View

1237

Download

669

Open Access

ARTICLE

Iram Arshad^1,*, Saeed Hamood Alsamhi¹, Wasif Afzal²
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2739-2770, 2023, DOI:10.32604/cmc.2023.030266 - 31 October 2022
Abstract Big Data is reforming many industrial domains by providing decision support through analyzing large data volumes. Big Data testing aims to ensure that Big Data systems run smoothly and error-free while maintaining the performance and quality of data. However, because of the diversity and complexity of data, testing Big Data is challenging. Though numerous research efforts deal with Big Data testing, a comprehensive review to address testing techniques and challenges of Big Data is not available as yet. Therefore, we have systematically reviewed the Big Data testing techniques’ evidence occurring in the period 2010–2021. This… More >

View

1421

Download

680

Like

5

Open Access

ARTICLE

Van-Truong Nguyen^*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2771-2787, 2023, DOI:10.32604/cmc.2023.033460 - 31 October 2022
Abstract In this paper, a non-negative adaptive mechanism based on an adaptive nonsingular fast terminal sliding mode control strategy is proposed to have finite time and high-speed trajectory tracking for parallel manipulators with the existence of unknown bounded complex uncertainties and external disturbances. The proposed approach is a hybrid scheme of the online non-negative adaptive mechanism, tracking differentiator, and nonsingular fast terminal sliding mode control (NFTSMC). Based on the online non-negative adaptive mechanism, the proposed control can remove the assumption that the uncertainties and disturbances must be bounded for the NFTSMC controllers. The proposed controller has More >

View

1101

Download

628

Open Access

ARTICLE

Xiangyan Tang^1,2, Dengfang Feng^2,*, KeQiu Li¹, Jingxin Liu², Jinyang Song³, Victor S. Sheng⁴
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2789-2802, 2023, DOI:10.32604/cmc.2023.031304 - 31 October 2022
Abstract Data prediction can improve the science of decision-making by making predictions about what happens in daily life based on natural law trends. Back propagation (BP) neural network is a widely used prediction method. To reduce its probability of falling into local optimum and improve the prediction accuracy, we propose an improved BP neural network prediction method based on a multi-strategy sparrow search algorithm (MSSA). The weights and thresholds of the BP neural network are optimized using the sparrow search algorithm (SSA). Three strategies are designed to improve the SSA to enhance its optimization-seeking ability, leading More >

View

1177

Download

580

Open Access

ARTICLE

Shijie Hu¹, Xiaoyu Li^1,*, Jiayu Bai¹, Hang Lei¹, Weizhong Qian¹, Sunqiang Hu¹, Cong Zhang², Akpatsa Samuel Kofi¹, Qian Qiu^2,3, Yong Zhou⁴, Shan Yang⁵
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2803-2815, 2023, DOI:10.32604/cmc.2023.032732 - 31 October 2022
Abstract When the Transformer proposed by Google in 2017, it was first used for machine translation tasks and achieved the state of the art at that time. Although the current neural machine translation model can generate high quality translation results, there are still mistranslations and omissions in the translation of key information of long sentences. On the other hand, the most important part in traditional translation tasks is the translation of key information. In the translation results, as long as the key information is translated accurately and completely, even if other parts of the results are… More >

View

1321

Download

572

Open Access

ARTICLE

Noureldin Eissa^1,2,*, Uswah Khairuddin^1,3, Rubiyah Yusof¹, Ahmed Madani²
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2817-2838, 2023, DOI:10.32604/cmc.2023.033632 - 31 October 2022
Abstract Epigenetics is the study of phenotypic variations that do not alter DNA sequences. Cancer epigenetics has grown rapidly over the past few years as epigenetic alterations exist in all human cancers. One of these alterations is DNA methylation; an epigenetic process that regulates gene expression and often occurs at tumor suppressor gene loci in cancer. Therefore, studying this methylation process may shed light on different gene functions that cannot otherwise be interpreted using the changes that occur in DNA sequences. Currently, microarray technologies; such as Illumina Infinium BeadChip assays; are used to study DNA methylation… More >

View

808

Download

553

Open Access

ARTICLE

Slim Ben Chaabane^1,2,*, Anas Bushnag¹
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2839-2852, 2023, DOI:10.32604/cmc.2023.032760 - 31 October 2022
Abstract A new model is proposed in this paper on color edge detection that uses the second derivative operators and data fusion mechanism. The second-order neighborhood shows the connection between the current pixel and the surroundings of this pixel. This connection is for each RGB component color of the input image. Once the image edges are detected for the three primary colors: red, green, and blue, these colors are merged using the combination rule. Then, the final decision is applied to obtain the segmentation. This process allows different data sources to be combined, which is essential More >

View

997

Download

656

Open Access

ARTICLE

Siti Zulaikha Mohd Jamaludin¹, Mohd. Asyraf Mansor², Aslina Baharum^3,*, Mohd Shareduwan Mohd Kasihmuddin¹, Habibah A. Wahab⁴, Muhammad Fadhil Marsani¹
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2853-2870, 2023, DOI:10.32604/cmc.2023.032654 - 31 October 2022
Abstract The effectiveness of the logic mining approach is strongly correlated to the quality of the induced logical representation that represent the behaviour of the data. Specifically, the optimum induced logical representation indicates the capability of the logic mining approach in generalizing the real datasets of different variants and dimensions. The main issues with the logic extracted by the standard logic mining techniques are lack of interpretability and the weakness in terms of the structural and arrangement of the 2 Satisfiability logic causing lower accuracy. To address the issues, the logical permutation serves as an alternative… More >

View

1214

Download

717

Open Access

ARTICLE

Hicham Lamtougui^1,*, Hicham El Moubtahij², Hassan Fouadi¹, Khalid Satori¹
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2871-2888, 2023, DOI:10.32604/cmc.2023.032550 - 31 October 2022
Abstract In recent years, Deep Learning models have become indispensable in several fields such as computer vision, automatic object recognition, and automatic natural language processing. The implementation of a robust and efficient handwritten text recognition system remains a challenge for the research community in this field, especially for the Arabic language, which, compared to other languages, has a dearth of published works. In this work, we presented an efficient and new system for offline Arabic handwritten text recognition. Our new approach is based on the combination of a Convolutional Neural Network (CNN) and a Bidirectional Long-Term More >

View

1483

Download

1119

Like

1

Open Access

ARTICLE

Mahmoud Ragab^1,2,3,*, Mohammed W. Al-Rabia^4,5, Sami Saeed Binyamin⁶, Ahmed A. Aldarmahi^7,8
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2889-2903, 2023, DOI:10.32604/cmc.2023.032192 - 31 October 2022
Abstract With the increasing and rapid growth rate of COVID-19 cases, the healthcare scheme of several developed countries have reached the point of collapse. An important and critical steps in fighting against COVID-19 is powerful screening of diseased patients, in such a way that positive patient can be treated and isolated. A chest radiology image-based diagnosis scheme might have several benefits over traditional approach. The accomplishment of artificial intelligence (AI) based techniques in automated diagnoses in the healthcare sector and rapid increase in COVID-19 cases have demanded the requirement of AI based automated diagnosis and recognition… More >

View

1389

Download

600

Open Access

ARTICLE

Walid El-Shafai^1,2, Noha A. El-Hag³, Ahmed Sedik⁴, Ghada Elbanby⁵, Fathi E. Abd El-Samie¹, Naglaa F. Soliman⁶, Hussah Nasser AlEisa^7,*, Mohammed E. Abdel Samea⁸
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2905-2925, 2023, DOI:10.32604/cmc.2023.031936 - 31 October 2022
Abstract Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and therapy. Deep learning provides a high performance for several medical image analysis applications. This paper proposes a deep learning model for the medical image fusion process. This model depends on Convolutional Neural Network (CNN). The basic idea of the proposed model is to extract features from both CT and MR images. Then, an additional process is executed on the extracted features. After that, the fused feature map is reconstructed to obtain the resulting fused image. More >

View

1454

Download

739

Open Access

ARTICLE

Mostafa Elbaz^1,2,*, Haitham Elwahsh¹, Ibrahim Mahmoud El-Henawy²
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2927-2944, 2023, DOI:10.32604/cmc.2023.033111 - 31 October 2022
Abstract Computer vision is one of the significant trends in computer science. It plays as a vital role in many applications, especially in the medical field. Early detection and segmentation of different tumors is a big challenge in the medical world. The proposed framework uses ultrasound images from Kaggle, applying five diverse models to denoise the images, using the best possible noise-free image as input to the U-Net model for segmentation of the tumor, and then using the Convolution Neural Network (CNN) model to classify whether the tumor is benign, malignant, or normal. The main challenge… More >

View

1073

Download

864

Like

2

Open Access

ARTICLE

Jeonghoon Choi¹, Dongjun Suh^1,*, Marc-Oliver Otto²
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2945-2966, 2023, DOI:10.32604/cmc.2023.033417 - 31 October 2022
Abstract Recently, machine learning-based technologies have been developed to automate the classification of wafer map defect patterns during semiconductor manufacturing. The existing approaches used in the wafer map pattern classification include directly learning the image through a convolution neural network and applying the ensemble method after extracting image features. This study aims to classify wafer map defects more effectively and derive robust algorithms even for datasets with insufficient defect patterns. First, the number of defects during the actual process may be limited. Therefore, insufficient data are generated using convolutional auto-encoder (CAE), and the expanded data are More >

View

1130

Download

685

Open Access

ARTICLE

Seongung Jo¹, Heung-Seon Oh^1,*, Sanghun Im¹, Gibaeg Kim¹, Seonho Kim²
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2967-2980, 2023, DOI:10.32604/cmc.2023.031983 - 31 October 2022
Abstract Analyzing Research and Development (R&D) trends is important because it can influence future decisions regarding R&D direction. In typical trend analysis, topic or technology taxonomies are employed to compute the popularities of the topics or codes over time. Although it is simple and effective, the taxonomies are difficult to manage because new technologies are introduced rapidly. Therefore, recent studies exploit deep learning to extract pre-defined targets such as problems and solutions. Based on the recent advances in question answering (QA) using deep learning, we adopt a multi-turn QA model to extract problems and solutions from… More >

View

1213

Download

598

Like

1

Open Access

ARTICLE

Guangjun Liang^1,2, Jianfang Xin^3,*, Linging Xia¹, Xueli Ni^1,4, Yi Cao⁵
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2981-2998, 2023, DOI:10.32604/cmc.2023.028597 - 31 October 2022
Abstract In this work, we consider the performance analysis of state dependent priority traffic and scheduling in device to device (D2D) heterogeneous networks. There are two priority transmission types of data in wireless communication, such as video or telephone, which always meet the requirements of high priority (HP) data transmission first. If there is a large amount of low priority (LP) data, there will be a large amount of LP data that cannot be sent. This situation will cause excessive delay of LP data and packet dropping probability. In order to solve this problem, the data… More >

View

843

Download

600

Open Access

ARTICLE

Safi Ullah^1,2, Seong-Ho Song^1,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2999-3014, 2023, DOI:10.32604/cmc.2023.032326 - 31 October 2022
Abstract Due to highly underdetermined nature of Single Image Super-Resolution (SISR) problem, deep learning neural networks are required to be more deeper to solve the problem effectively. One of deep neural networks successful in the Super-Resolution (SR) problem is ResNet which can render the capability of deeper networks with the help of skip connections. However, zero padding (ZP) scheme in the network restricts benefits of skip connections in SRResNet and its performance as the ratio of the number of pure input data to that of zero padded data increases. In this paper. we consider the ResNet More >

View

2395

Download

937

Like

15

Open Access

ARTICLE

Shrouk H. Hessen^1,2,*, Hatem M. Abdul-kader¹, Ayman E. Khedr³, Rashed K. Salem¹
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3015-3028, 2023, DOI:10.32604/cmc.2023.033212 - 31 October 2022
Abstract According to the advances in users’ service requirements, physical hardware accessibility, and speed of resource delivery, Cloud Computing (CC) is an essential technology to be used in many fields. Moreover, the Internet of Things (IoT) is employed for more communication flexibility and richness that are required to obtain fruitful services. A multi-agent system might be a proper solution to control the load balancing of interaction and communication among agents. This paper proposes a multi-agent load balancing framework that consists of two phases to optimize the workload among different servers with large-scale CC power with various… More >

View

838

Download

846

Open Access

ARTICLE

Abdulrahman M. Qahtani¹, Ahmed S. Ghiduk^1,2,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3029-3044, 2023, DOI:10.32604/cmc.2023.032831 - 31 October 2022
Abstract Recently software industry has paid significant attention to customizing software products across distributed boundaries. Communicating the requirements of multiple clients across distributed borders is a crucial challenge for the software customization process. Local decision-making and local development at the client site are considered methods for reducing difficulties in communicating the requirements of multiple clients across distributed boundaries. This paper introduces a new model called the onshore development model (ODM) for accomplishing the customization requests in the distributed development process of software. This model presents a scenario for enhancing the onsite development of specific requirements to… More >

View

774

Download

536

Open Access

ARTICLE

Ammar Almomani^1,2,*, Mohammed Alweshah³, Waleed Alomoush⁴, Mohammad Alauthman⁵, Aseel Jabai², Anwar Abbass², Ghufran Hamad², Meral Abdalla², Brij B. Gupta^1,6,7
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3045-3062, 2023, DOI:10.32604/cmc.2023.030567 - 31 October 2022
Abstract Voice classification is important in creating more intelligent systems that help with student exams, identifying criminals, and security systems. The main aim of the research is to develop a system able to predicate and classify gender, age, and accent. So, a new system called Classifying Voice Gender, Age, and Accent (CVGAA) is proposed. Backpropagation and bagging algorithms are designed to improve voice recognition systems that incorporate sensory voice features such as rhythm-based features used to train the device to distinguish between the two gender categories. It has high precision compared to other algorithms used in More >

View

1139

Download

638

Open Access

ARTICLE

Sukhendra Singh¹, Sur Singh Rawat, Manoj Gupta³, B. K. Tripathi⁴, Faisal Alanazi⁵, Arnab Majumdar⁶, Pattaraporn Khuwuthyakorn⁷, Orawit Thinnukool^7,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3063-3083, 2023, DOI:10.32604/cmc.2023.032363 - 31 October 2022
Abstract Currently, breast cancer has been a major cause of deaths in women worldwide and the World Health Organization (WHO) has confirmed this. The severity of this disease can be minimized to the large extend, if it is diagnosed properly at an early stage of the disease. Therefore, the proper treatment of a patient having cancer can be processed in better way, if it can be diagnosed properly as early as possible using the better algorithms. Moreover, it has been currently observed that the deep neural networks have delivered remarkable performance for detecting cancer in histopathological… More >

View

1789

Download

601

Open Access

ARTICLE

Saeed Masoud Alshahrani¹, Fatma S. Alrayes², Hamed Alqahtani³, Jaber S. Alzahrani⁴, Mohammed Maray⁵, Sana Alazwari⁶, Mohamed A. Shamseldin⁷, Mesfer Al Duhayyim^8,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3085-3100, 2023, DOI:10.32604/cmc.2023.032972 - 31 October 2022
Abstract Nowadays, Internet of Things (IoT) has penetrated all facets of human life while on the other hand, IoT devices are heavily prone to cyberattacks. It has become important to develop an accurate system that can detect malicious attacks on IoT environments in order to mitigate security risks. Botnet is one of the dreadful malicious entities that has affected many users for the past few decades. It is challenging to recognize Botnet since it has excellent carrying and hidden capacities. Various approaches have been employed to identify the source of Botnet at earlier stages. Machine Learning… More >

View

929

Download

572

Open Access

ARTICLE

Mohammed Maray¹, Hamed Alqahtani², Saud S. Alotaibi³, Fatma S. Alrayes⁴, Nuha Alshuqayran⁵, Mrim M. Alnfiai⁶, Amal S. Mehanna⁷, Mesfer Al Duhayyim^8,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3101-3115, 2023, DOI:10.32604/cmc.2023.032969 - 31 October 2022
Abstract Cloud Computing (CC) is the most promising and advanced technology to store data and offer online services in an effective manner. When such fast evolving technologies are used in the protection of computer-based systems from cyberattacks, it brings several advantages compared to conventional data protection methods. Some of the computer-based systems that effectively protect the data include Cyber-Physical Systems (CPS), Internet of Things (IoT), mobile devices, desktop and laptop computer, and critical systems. Malicious software (malware) is nothing but a type of software that targets the computer-based systems so as to launch cyber-attacks and threaten… More >

View

1223

Download

578

Open Access

ARTICLE

Saeed Masoud Alshahrani¹, Saud S. Alotaibi², Shaha Al-Otaibi³, Mohamed Mousa⁴, Anwer Mustafa Hilal^5,*, Amgad Atta Abdelmageed⁵, Abdelwahed Motwakel⁵, Mohamed I. Eldesouki⁶
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3117-3131, 2023, DOI:10.32604/cmc.2023.033038 - 31 October 2022
Abstract Object detection (OD) in remote sensing images (RSI) acts as a vital part in numerous civilian and military application areas, like urban planning, geographic information system (GIS), and search and rescue functions. Vehicle recognition from RSIs remained a challenging process because of the difficulty of background data and the redundancy of recognition regions. The latest advancements in deep learning (DL) approaches permit the design of effectual OD approaches. This study develops an Artificial Ecosystem Optimizer with Deep Convolutional Neural Network for Vehicle Detection (AEODCNN-VD) model on Remote Sensing Images. The proposed AEODCNN-VD model focuses on… More >

View

1085

Download

741

Open Access

ARTICLE

Mesfer Al Duhayyim^1,*, Mohammed Maray², Ayman Qahmash², Fatma S. Alrayes³, Nuha Alshuqayran⁴, Jaber S. Alzahrani⁵, Mohammed Alghamdi^2,6, Abdullah Mohamed⁷
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3133-3149, 2023, DOI:10.32604/cmc.2023.032740 - 31 October 2022
Abstract Nowadays, security plays an important role in Internet of Things (IoT) environment especially in medical services’ domains like disease prediction and medical data storage. In healthcare sector, huge volumes of data are generated on a daily basis, owing to the involvement of advanced health care devices. In general terms, health care images are highly sensitive to alterations due to which any modifications in its content can result in faulty diagnosis. At the same time, it is also significant to maintain the delicate contents of health care images during reconstruction stage. Therefore, an encryption system is… More >

View

1007

Download

765

Open Access

ARTICLE

Marwa Obayya¹, Nadhem NEMRI², Lubna A. Alharbi³, Mohamed K. Nour⁴, Mrim M. Alnfiai⁵, Mohammed Abdullah Al-Hagery⁶, Nermin M. Salem⁷, Mesfer Al Duhayyim^8,*
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3151-3166, 2023, DOI:10.32604/cmc.2023.032765 - 31 October 2022
Abstract With new developments experienced in Internet of Things (IoT), wearable, and sensing technology, the value of healthcare services has enhanced. This evolution has brought significant changes from conventional medicine-based healthcare to real-time observation-based healthcare. Bio-medical Electrocardiogram (ECG) signals are generally utilized in examination and diagnosis of Cardiovascular Diseases (CVDs) since it is quick and non-invasive in nature. Due to increasing number of patients in recent years, the classifier efficiency gets reduced due to high variances observed in ECG signal patterns obtained from patients. In such scenario computer-assisted automated diagnostic tools are important for classification of… More >

View

1070

Download

616

Open Access

ARTICLE

Mesfer Al Duhayyim^1,*, Hadeel Alsolai², Siwar Ben Haj Hassine³, Jaber S. Alzahrani⁴, Ahmed S. Salama⁵, Abdelwahed Motwakel⁶, Ishfaq Yaseen⁶, Abu Sarwar Zamani⁶
CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3167-3181, 2023, DOI:10.32604/cmc.2023.033054 - 31 October 2022
Abstract Hyperspectral remote sensing/imaging spectroscopy is a novel approach to reaching a spectrum from all the places of a huge array of spatial places so that several spectral wavelengths are utilized for making coherent images. Hyperspectral remote sensing contains acquisition of digital images from several narrow, contiguous spectral bands throughout the visible, Thermal Infrared (TIR), Near Infrared (NIR), and Mid-Infrared (MIR) regions of the electromagnetic spectrum. In order to the application of agricultural regions, remote sensing approaches are studied and executed to their benefit of continuous and quantitative monitoring. Particularly, hyperspectral images (HSI) are considered the… More >

View

1180

Download

664