Open Access

ARTICLE

Chuiju You¹, Guanjun Lin^1,*, Jinming Qiu¹, Ning Cao¹, Yundong Sun², Russell Higgs³
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1277-1292, 2023, DOI:10.32604/csse.2023.026150
Abstract A sensor graph network is a sensor network model organized according to graph network structure. Structural unit and signal propagation of core nodes are the basic characteristics of sensor graph networks. In sensor networks, network structure recognition is the basis for accurate identification and effective prediction and control of node states. Aiming at the problems of difficult global structure identification and poor interpretability in complex sensor graph networks, based on the characteristics of sensor networks, a method is proposed to firstly unitize the graph network structure and then expand the unit based on the signal transmission path of the core… More >

View

1982

Download

695

Like

3

Open Access

ARTICLE

Mesfer Al Duhayyim^1,*, Heba G. Mohamed², Fadwa Alrowais³, Fahd N. Al-Wesabi⁴, Anwer Mustafa Hilal⁵, Abdelwahed Motwakel⁵
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1293-1310, 2023, DOI:10.32604/csse.2023.035589
Abstract The Internet of Things (IoT) has gained more popularity in research because of its large-scale challenges and implementation. But security was the main concern when witnessing the fast development in its applications and size. It was a dreary task to independently set security systems in every IoT gadget and upgrade them according to the newer threats. Additionally, machine learning (ML) techniques optimally use a colossal volume of data generated by IoT devices. Deep Learning (DL) related systems were modelled for attack detection in IoT. But the current security systems address restricted attacks and can be utilized outdated datasets for evaluations.… More >

View

1314

Download

595

Open Access

ARTICLE

Saravanan Parthasarathy, Arun Raj Lakshminarayanan^*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1311-1336, 2023, DOI:10.32604/csse.2023.034910
Abstract For a long time, legal entities have developed and used crime prediction methodologies. The techniques are frequently updated based on crime evaluations and responses from scientific communities. There is a need to develop type-based crime prediction methodologies that can be used to address issues at the subgroup level. Child maltreatment is not adequately addressed because children are voiceless. As a result, the possibility of developing a model for predicting child abuse was investigated in this study. Various exploratory analysis methods were used to examine the city of Chicago’s child abuse events. The data set was balanced using the Borderline-SMOTE technique,… More >

View

1259

Download

564

Open Access

ARTICLE

José Escorcia-Gutierrez^1,*, Roosvel Soto-Diaz², Natasha Madera³, Carlos Soto³, Francisco Burgos-Florez², Alexander Rodríguez⁴, Romany F. Mansour⁵
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1337-1353, 2023, DOI:10.32604/csse.2023.035253
Abstract Computer-aided diagnosis (CAD) models exploit artificial intelligence (AI) for chest X-ray (CXR) examination to identify the presence of tuberculosis (TB) and can improve the feasibility and performance of CXR for TB screening and triage. At the same time, CXR interpretation is a time-consuming and subjective process. Furthermore, high resemblance among the radiological patterns of TB and other lung diseases can result in misdiagnosis. Therefore, computer-aided diagnosis (CAD) models using machine learning (ML) and deep learning (DL) can be designed for screening TB accurately. With this motivation, this article develops a Water Strider Optimization with Deep Transfer Learning Enabled Tuberculosis Classification… More >

View

1183

Download

495

Like

2

Open Access

ARTICLE

Ali Usman¹, Javed Ferzund¹, Ahmad Shaf¹, Muhammad Aamir¹, Samar Alqhtani^2,*, Khlood M. Mehdar³, Hanan Talal Halawani⁴, Hassan A. Alshamrani⁵, Abdullah A. Asiri⁵, Muhammad Irfan⁶
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1355-1369, 2023, DOI:10.32604/csse.2023.034682
Abstract Assistive devices for disabled people with the help of Brain-Computer Interaction (BCI) technology are becoming vital bio-medical engineering. People with physical disabilities need some assistive devices to perform their daily tasks. In these devices, higher latency factors need to be addressed appropriately. Therefore, the main goal of this research is to implement a real-time BCI architecture with minimum latency for command actuation. The proposed architecture is capable to communicate between different modules of the system by adopting an automotive, intelligent data processing and classification approach. Neuro-sky mind wave device has been used to transfer the data to our implemented server… More >

View

920

Download

455

Open Access

ARTICLE

Manar Ahmed Hamza^1,*, Shaha Al-Otaibi², Sami Althahabi³, Jaber S. Alzahrani⁴, Abdullah Mohamed⁵, Abdelwahed Motwakel¹, Abu Sarwar Zamani¹, Mohamed I. Eldesouki⁶
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1371-1383, 2023, DOI:10.32604/csse.2023.030232
Abstract Internet of things (IoT) and cloud computing (CC) becomes widespread in different application domains such as business, e-commerce, healthcare, etc. The recent developments of IoT technology have led to an increase in large amounts of data from various sources. In IoT enabled cloud environment, load scheduling remains a challenging process which is applied for ensuring network stability with maximum resource utilization. The load scheduling problem was regarded as an optimization problem that is solved by metaheuristics. In this view, this study develops a new Circle Chaotic Chameleon Swarm Optimization based Load Scheduling (C3SOA-LS) technique for IoT enabled cloud environment. The… More >

View

804

Download

472

Open Access

ARTICLE

Xiangwei Chen¹, Zhijin Zhao^1,2,*, Xueyi Ye¹, Shilian Zheng², Caiyi Lou², Xiaoniu Yang²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1385-1400, 2023, DOI:10.32604/csse.2023.034543
Abstract Interference signals recognition plays an important role in anti-jamming communication. With the development of deep learning, many supervised interference signals recognition algorithms based on deep learning have emerged recently and show better performance than traditional recognition algorithms. However, there is no unsupervised interference signals recognition algorithm at present. In this paper, an unsupervised interference signals recognition method called double phases and double dimensions contrastive clustering (DDCC) is proposed. Specifically, in the first phase, four data augmentation strategies for interference signals are used in data-augmentation-based (DA-based) contrastive learning. In the second phase, the original dataset’s k-nearest neighbor set (KNNset) is designed… More >

View

989

Download

564

Open Access

ARTICLE

Mingyong Li, Qiqi Li, Zheng Jiang, Yan Ma^*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1401-1414, 2023, DOI:10.32604/csse.2023.034757
Abstract In recent years, the development of deep learning has further improved hash retrieval technology. Most of the existing hashing methods currently use Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to process image and text information, respectively. This makes images or texts subject to local constraints, and inherent label matching cannot capture fine-grained information, often leading to suboptimal results. Driven by the development of the transformer model, we propose a framework called ViT2CMH mainly based on the Vision Transformer to handle deep Cross-modal Hashing tasks rather than CNNs or RNNs. Specifically, we use a BERT network to extract text… More >

View

1194

Download

528

Like

4

Open Access

ARTICLE

R. Sheeba^1,*, R. Sharmila², Ahmed Alkhayyat³, Rami Q. Malik⁴
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1415-1429, 2023, DOI:10.32604/csse.2023.034321
Abstract Lately, the Internet of Things (IoT) application requires millions of structured and unstructured data since it has numerous problems, such as data organization, production, and capturing. To address these shortcomings, big data analytics is the most superior technology that has to be adapted. Even though big data and IoT could make human life more convenient, those benefits come at the expense of security. To manage these kinds of threats, the intrusion detection system has been extensively applied to identify malicious network traffic, particularly once the preventive technique fails at the level of endpoint IoT devices. As cyberattacks targeting IoT have… More >

View

930

Download

440

Open Access

ARTICLE

A. Francis Saviour Devaraj¹, T. Satyanarayana Murthy², Fayadh Alenezi³, E. Laxmi Lydia⁴, Mohamad Adzhar Md Zawawi⁵, Mohamad Khairi Ishak^5,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1431-1445, 2023, DOI:10.32604/csse.2023.034421
Abstract Recently, a trust system was introduced to enhance security and cooperation between nodes in wireless sensor networks (WSN). In routing, the trust system includes or avoids nodes related to the estimated trust values in the routing function. This article introduces Enhanced Metaheuristics with Trust Aware Secure Route Selection Protocol (EMTA-SRSP) for WSN. The presented EMTA-SRSP technique majorly involves the optimal selection of routes in WSN. To accomplish this, the EMTA-SRSP technique involves the design of an oppositional Aquila optimization algorithm to choose safe routes for data communication. For the clustering process, the nodes with maximum residual energy will be considered… More >

View

801

Download

417

Open Access

ARTICLE

G. Augusta Kani^*, P. Geetha
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1447-1469, 2023, DOI:10.32604/csse.2023.035969
Abstract Human Activity Recognition (HAR) from video data collections is the core application in vision tasks and has a variety of utilizations including object detection applications, video-based behavior monitoring, video classification, and indexing, patient monitoring, robotics, and behavior analysis. Although many techniques are available for HAR in video analysis tasks, most of them are not focusing on behavioral analysis. Hence, a new HAR system analysis the behavioral activity of a person based on the deep learning approach proposed in this work. The most essential aim of this work is to recognize the complex activities that are useful in many tasks that… More >

View

775

Download

504

Like

1

Open Access

ARTICLE

Mesfer Al Duhayyim^1,*, Jaber S. Alzahrani², Hanan Abdullah Mengash³, Mrim M. Alnfiai⁴, Radwa Marzouk³, Gouse Pasha Mohammed⁵, Mohammed Rizwanullah⁵, Amgad Atta Abdelmageed⁵
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1471-1485, 2023, DOI:10.32604/csse.2023.034137
Abstract The Internet of Things (IoT) environment plays a crucial role in the design of smart environments. Security and privacy are the major challenging problems that exist in the design of IoT-enabled real-time environments. Security susceptibilities in IoT-based systems pose security threats which affect smart environment applications. Intrusion detection systems (IDS) can be used for IoT environments to mitigate IoT-related security attacks which use few security vulnerabilities. This paper introduces a modified garden balsan optimization-based machine learning model for intrusion detection (MGBO-MLID) in the IoT cloud environment. The presented MGBO-MLID technique focuses on the identification and classification of intrusions in the… More >

View

801

Download

399

Open Access

ARTICLE

Lei Feng¹, Bo Wang^1,*, Fuqi Ma¹, Hengrui Ma², Mohamed A. Mohamed³
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1487-1501, 2023, DOI:10.32604/csse.2023.035377
Abstract As the scale of the power system continues to expand, the environment for power operations becomes more and more complex. Existing risk management and control methods for power operations can only set the same risk detection standard and conduct the risk detection for any scenario indiscriminately. Therefore, more reliable and accurate security control methods are urgently needed. In order to improve the accuracy and reliability of the operation risk management and control method, this paper proposes a method for identifying the key links in the whole process of electric power operation based on the spatiotemporal hybrid convolutional neural network. To… More >

View

733

Download

394

Open Access

ARTICLE

S. Hema^1,*, Y. Sukhi²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1503-1519, 2023, DOI:10.32604/csse.2023.036577
Abstract Smart grids and their technologies transform the traditional electric grids to assure safe, secure, cost-effective, and reliable power transmission. Non-linear phenomena in power systems, such as voltage collapse and oscillatory phenomena, can be investigated by chaos theory. Recently, renewable energy resources, such as wind turbines, and solar photovoltaic (PV) arrays, have been widely used for electric power generation. The design of the controller for the direct Current (DC) converter in a PV system is performed based on the linearized model at an appropriate operating point. However, these operating points are ever-changing in a PV system, and the design of the… More >

View

1020

Download

412

Open Access

ARTICLE

Yunyoung Nam¹, Seong Jun Choi², Jihwan Shin¹, Jinseok Lee^3,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1521-1532, 2023, DOI:10.32604/csse.2023.034192
Abstract An otoscope is traditionally used to examine the eardrum and ear canal. A diagnosis of otitis media (OM) relies on the experience of clinicians. If an examiner lacks experience, the examination may be difficult and time-consuming. This paper presents an ear disease classification method using middle ear images based on a convolutional neural network (CNN). Especially the segmentation and classification networks are used to classify an otoscopic image into six classes: normal, acute otitis media (AOM), otitis media with effusion (OME), chronic otitis media (COM), congenital cholesteatoma (CC) and traumatic perforations (TMPs). The Mask R-CNN is utilized for the segmentation… More >

View

1022

Download

459

Open Access

ARTICLE

Saud Yonbawi¹, Sultan Alahmari², T. Satyanarayana Murthy³, Padmakar Maddala⁴, E. Laxmi Lydia⁵, Seifedine Kadry^6,7,8,*, Jungeun Kim⁹
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1533-1547, 2023, DOI:10.32604/csse.2023.036296
Abstract Precision agriculture includes the optimum and adequate use of resources depending on several variables that govern crop yield. Precision agriculture offers a novel solution utilizing a systematic technique for current agricultural problems like balancing production and environmental concerns. Weed control has become one of the significant problems in the agricultural sector. In traditional weed control, the entire field is treated uniformly by spraying the soil, a single herbicide dose, weed, and crops in the same way. For more precise farming, robots could accomplish targeted weed treatment if they could specifically find the location of the dispensable plant and identify the… More >

View

778

Download

432

Open Access

ARTICLE

Divya Sharma^1,*, Sanjay Jain², Vivek Maik³
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1549-1561, 2023, DOI:10.32604/csse.2023.035031
Abstract Interconnected devices and intelligent applications have slashed human intervention in the Internet of Things (IoT), making it possible to accomplish tasks with less human interaction. However, it faces many problems, including lower capacity links, energy utilization, enhancement of resources and limited resources due to its openness, heterogeneity, limited resources and extensiveness. It is challenging to route packets in such a constrained environment. In an IoT network constrained by limited resources, minimal routing control overhead is required without packet loss. Such constrained environments can be improved through the optimal routing protocol. It is challenging to route packets in such a constrained… More >

View

619

Download

444

Open Access

ARTICLE

R. Bala Krishnan¹, D. Yuvaraj², P. Suthanthira Devi³, Varghese S. Chooralil⁴, N. Rajesh Kumar¹, B. Karthikeyan⁵, G. Manikandan^5,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1563-1576, 2023, DOI:10.32604/csse.2023.035307
Abstract With the improvement of current online communication schemes, it is now possible to successfully distribute and transport secured digital Content via the communication channel at a faster transmission rate. Traditional steganography and cryptography concepts are used to achieve the goal of concealing secret Content on a media and encrypting it before transmission. Both of the techniques mentioned above aid in the confidentiality of feature content. The proposed approach concerns secret content embodiment in selected pixels on digital image layers such as Red, Green, and Blue. The private Content originated from a medical client and was forwarded to a medical practitioner… More >

View

945

Download

440

Open Access

ARTICLE

Ping-Huan Kuo^1,2, Sing-Yan Chen¹, Her-Terng Yau^1,2,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1577-1596, 2023, DOI:10.32604/csse.2023.036292
Abstract Cars are regarded as an indispensable means of transportation in Taiwan. Several studies have indicated that the automotive industry has witnessed remarkable advances and that the market of used cars has rapidly expanded. In this study, a price prediction system for used BMW cars was developed. Nine parameters of used cars, including their model, registration year, and transmission style, were analyzed. The data obtained were then divided into three subsets. The first subset was used to compare the results of each algorithm. The predicted values produced by the two algorithms with the most satisfactory results were used as the input… More >

View

992

Download

420

Open Access

ARTICLE

Mohamed Maher Ata¹, Reem N. Yousef², Faten Khalid Karim^3,*, Doaa Sami Khafaga³
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1597-1616, 2023, DOI:10.32604/csse.2023.034375
Abstract Brain neoplasms are recognized with a biopsy, which is not commonly done before decisive brain surgery. By using Convolutional Neural Networks (CNNs) and textural features, the process of diagnosing brain tumors by radiologists would be a noninvasive procedure. This paper proposes a features fusion model that can distinguish between no tumor and brain tumor types via a novel deep learning structure. The proposed model extracts Gray Level Co-occurrence Matrix (GLCM) textural features from MRI brain tumor images. Moreover, a deep neural network (DNN) model has been proposed to select the most salient features from the GLCM. Moreover, it manipulates the… More >

View

774

Download

395

Open Access

ARTICLE

A. Arulmary^1,*, V. Rajamani², T. Kavitha²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1617-1630, 2023, DOI:10.32604/csse.2023.034681
Abstract The method opted for accuracy, and no existing studies are based on this method. A design and characteristic survey of a new small band gap semiconducting Single Wall Carbon Nano Tube (SWCNT) Field Effect Transistor as a photodetector is carried out. In the proposed device, better performance is achieved by increasing the diameter and introducing a new single halo (SH) doping in the channel length of the CNTFET device. This paper is a study and analysis of the performance of a Carbon Nano Tube Field Effect Transistor (CNTFET) as a photodetector using the self-consistent Poisson and Green function method. The… More >

View

563

Download

382

Open Access

ARTICLE

Pramote Charongrattanasakul¹, Wimonmas Bamrungsetthapong^2,*, Poom Kumam³
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1631-1651, 2023, DOI:10.32604/csse.2023.036179
Abstract A novel adaptive multiple dependent state sampling plan (AMDSSP) was designed to inspect products from a continuous manufacturing process under the accelerated life test (ALT) using both double sampling plan (DSP) and multiple dependent state sampling plan (MDSSP) concepts. Under accelerated conditions, the lifetime of a product follows the Weibull distribution with a known shape parameter, while the scale parameter can be determined using the acceleration factor (AF). The Arrhenius model is used to estimate AF when the damaging process is temperature-sensitive. An economic design of the proposed sampling plan was also considered for the ALT. A genetic algorithm with… More >

View

702

Download

591

Open Access

ARTICLE

Hiam Alquran^1,2, Yazan Al-Issa³, Mohammed Alslatie⁴, Isam Abu-Qasmieh¹, Amin Alqudah³, Wan Azani Mustafa^5,7,*, Yasmin Mohd Yacob^6,7
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1653-1671, 2023, DOI:10.32604/csse.2023.033861
Abstract Liver cancer is the second leading cause of cancer death worldwide. Early tumor detection may help identify suitable treatment and increase the survival rate. Medical imaging is a non-invasive tool that can help uncover abnormalities in human organs. Magnetic Resonance Imaging (MRI), in particular, uses magnetic fields and radio waves to differentiate internal human organs tissue. However, the interpretation of medical images requires the subjective expertise of a radiologist and oncologist. Thus, building an automated diagnosis computer-based system can help specialists reduce incorrect diagnoses. This paper proposes a hybrid automated system to compare the performance of 3D features and 2D… More >

View

887

Download

409

Open Access

ARTICLE

S. Rajalakshmi^1,*, S. Nalini², Ahmed Alkhayyat³, Rami Q. Malik⁴
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1673-1688, 2023, DOI:10.32604/csse.2023.034414
Abstract Remote sensing image (RSI) classifier roles a vital play in earth observation technology utilizing Remote sensing (RS) data are extremely exploited from both military and civil fields. More recently, as novel DL approaches develop, techniques for RSI classifiers with DL have attained important breakthroughs, providing a new opportunity for the research and development of RSI classifiers. This study introduces an Improved Slime Mould Optimization with a graph convolutional network for the hyperspectral remote sensing image classification (ISMOGCN-HRSC) model. The ISMOGCN-HRSC model majorly concentrates on identifying and classifying distinct kinds of RSIs. In the presented ISMOGCN-HRSC model, the synergic deep learning… More >

View

755

Download

448

Like

1

Open Access

ARTICLE

K. Jayanthi^1,*, A. M. Kalpana²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1689-1705, 2023, DOI:10.32604/csse.2023.034613
Abstract The fifth-generation (5G) wireless technology is the most recent standardization in communication services of interest across the globe. The concept of Multiple-Input-Multiple-Output antenna (MIMO) systems has recently been incorporated to operate at higher frequencies without limitations. This paper addresses, design of a high-gain MIMO antenna that offers a bandwidth of 400 MHz and 2.58 GHz by resonating at 28 and 38 GHz, respectively for 5G millimeter (mm)-wave applications. The proposed design is developed on a RT Duroid 5880 substrate with a single elemental dimension of 9.53 × 7.85 × 0.8 mm³. The patch antenna is fully grounded and is fed with a 50-ohm stepped impedance… More >

View

769

Download

632

Open Access

ARTICLE

Alaknanda S. Patil^1,*, G. Sundari¹, Arun Kumar Sivaraman²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1707-1721, 2023, DOI:10.32604/csse.2023.034270
Abstract The intact data transmission to the authentic user is becoming crucial at every moment in the current era. Steganography; is a technique for concealing the hidden message in any cover media such as image, video; and audio to increase the protection of data. The resilience and imperceptibility are improved by choosing an appropriate embedding position. This paper gives a novel system to immerse the secret information in different videos with different methods. An audio and video steganography with novel amalgamations are implemented to immerse the confidential auditory information and the authentic user’s face image. A hidden message is first included… More >

View

862

Download

571

Open Access

ARTICLE

Muhammad Irfan¹, Ch. Anwar Ul Hassan², Faisal Althobiani³, Nasir Ayub^4,*, Raja Jalees Ul Hussen Khan⁵, Emad Ismat Ghandourah⁶, Majid A. Almas⁷, Saleh Mohammed Ghonaim³, V. R. Shamji³, Saifur Rahman¹
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1723-1740, 2023, DOI:10.32604/csse.2023.035141
Abstract The smart grid has enabled users to control their home energy more effectively and efficiently. A home energy management system (HEM) is a challenging task because this requires the most effective scheduling of intelligent home appliances to save energy. Here, we presented a meta-heuristic-based HEM system that integrates the Greywolf Algorithm (GWA) and Harmony Search Algorithms (HSA). Moreover, a fusion initiated on HSA and GWA operators is used to optimize energy intake. Furthermore, many knapsacks are being utilized to ensure that peak-hour load usage for electricity customers does not surpass a certain edge. Hybridization has proven beneficial in achieving numerous… More >

View

765

Download

434

Open Access

ARTICLE

P. Malathi^1,*, G. Charlyn Pushpa Latha²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1741-1758, 2023, DOI:10.32604/csse.2023.035185
Abstract Breast cancer (BCa) is a leading cause of death in the female population across the globe. Approximately 2.3 million new BCa cases are recorded globally in females, overtaking lung cancer as the most prevalent form of cancer to be diagnosed. However, the mortality rates for cervical and BCa are significantly higher in developing nations than in developed countries. Early diagnosis is the only option to minimize the risks of BCa. Deep learning (DL)-based models have performed well in image processing in recent years, particularly convolutional neural network (CNN). Hence, this research proposes a DL-based CNN model to diagnose BCa from… More >

View

682

Download

447

Open Access

ARTICLE

Deris Stiawan¹, Ali Bardadi¹, Nurul Afifah¹, Lisa Melinda¹, Ahmad Heryanto¹, Tri Wanda Septian¹, Mohd Yazid Idris², Imam Much Ibnu Subroto³, Lukman⁴, Rahmat Budiarto^5,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1759-1774, 2023, DOI:10.32604/csse.2023.034047
Abstract The Repository Mahasiswa (RAMA) is a national repository of research reports in the form of final assignments, student projects, theses, dissertations, and research reports of lecturers or researchers that have not yet been published in journals, conferences, or integrated books from the scientific repository of universities and research institutes in Indonesia. The increasing popularity of the RAMA Repository leads to security issues, including the two most widespread, vulnerable attacks i.e., Structured Query Language (SQL) injection and cross-site scripting (XSS) attacks. An attacker gaining access to data and performing unauthorized data modifications is extremely dangerous. This paper aims to provide an… More >

View

1040

Download

570

Open Access

ARTICLE

R. Sujatha^1,*, T. Abirami²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1775-1787, 2023, DOI:10.32604/csse.2023.031552
Abstract The digital technologies that run based on users’ content provide a platform for users to help air their opinions on various aspects of a particular subject or product. The recommendation agents play a crucial role in personalizing the needs of individual users. Therefore, it is essential to improve the user experience. The recommender system focuses on recommending a set of items to a user to help the decision-making process and is prevalent across e-commerce and media websites. In Context-Aware Recommender Systems (CARS), several influential and contextual variables are identified to provide an effective recommendation. A substantial trade-off is applied in… More >

View

846

Download

422

Open Access

ARTICLE

Hicham Moujahid¹, Bouchaib Cherradi^1,2,*, Oussama El Gannour¹, Wamda Nagmeldin³, Abdelzahir Abdelmaboud⁴, Mohammed Al-Sarem^5,6, Lhoussain Bahatti¹, Faisal Saeed⁷, Mohammed Hadwan^8,9
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1789-1809, 2023, DOI:10.32604/csse.2023.034022
Abstract Due to the rapid propagation characteristic of the Coronavirus (COVID-19) disease, manual diagnostic methods cannot handle the large number of infected individuals to prevent the spread of infection. Despite, new automated diagnostic methods have been brought on board, particularly methods based on artificial intelligence using different medical data such as X-ray imaging. Thoracic imaging, for example, produces several image types that can be processed and analyzed by machine and deep learning methods. X-ray imaging materials widely exist in most hospitals and health institutes since they are affordable compared to other imaging machines. Through this paper, we propose a novel Convolutional… More >

View

803

Download

455

Open Access

ARTICLE

M. Uvaneshwari¹, M. Baskar^2,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1811-1826, 2023, DOI:10.32604/csse.2023.035455
Abstract The Brain Tumor (BT) is created by an uncontrollable rise of anomalous cells in brain tissue, and it consists of 2 types of cancers they are malignant and benign tumors. The benevolent BT does not affect the neighbouring healthy and normal tissue; however, the malignant could affect the adjacent brain tissues, which results in death. Initial recognition of BT is highly significant to protecting the patient’s life. Generally, the BT can be identified through the magnetic resonance imaging (MRI) scanning technique. But the radiotherapists are not offering effective tumor segmentation in MRI images because of the position and unequal shape… More >

View

734

Download

449

Open Access

ARTICLE

Marwa A. Elmenyawi^1,2,*, Radwa M. Tawfeek¹
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1827-1844, 2023, DOI:10.32604/csse.2023.036474
Abstract One of the elementary operations in computing systems is multiplication. Therefore, high-speed and low-power multipliers design is mandatory for efficient computing systems. In designing low-energy dissipation circuits, reversible logic is more efficient than irreversible logic circuits but at the cost of higher complexity. This paper introduces an efficient signed/unsigned 4 × 4 reversible Vedic multiplier with minimum quantum cost. The Vedic multiplier is considered fast as it generates all partial product and their sum in one step. This paper proposes two reversible Vedic multipliers with optimized quantum cost and garbage output. First, the unsigned Vedic multiplier is designed based on… More >

View

871

Download

418

Open Access

ARTICLE

K. Kavin Kumar¹, P. M. Dinesh², P. Rayavel³, L. Vijayaraja⁴, R. Dhanasekar⁴, Rupa Kesavan⁵, Kannadasan Raju⁶, Arfat Ahmad Khan⁷, Chitapong Wechtaisong^8,*, Mohd Anul Haq⁹, Zamil S. Alzamil⁹, Ahmed Alhussen¹⁰
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1845-1861, 2023, DOI:10.32604/csse.2023.033927
Abstract A brain tumor is a lethal neurological disease that affects the average performance of the brain and can be fatal. In India, around 15 million cases are diagnosed yearly. To mitigate the seriousness of the tumor it is essential to diagnose at the beginning. Notwithstanding, the manual evaluation process utilizing Magnetic Resonance Imaging (MRI) causes a few worries, remarkably inefficient and inaccurate brain tumor diagnoses. Similarly, the examination process of brain tumors is intricate as they display high unbalance in nature like shape, size, appearance, and location. Therefore, a precise and expeditious prognosis of brain tumors is essential for implementing… More >

View

1159

Download

598

Open Access

ARTICLE

Abdullah S. AL-Malaise AL-Ghamdi^1,2,3, Sultanah M. Alshammari^3,4, Mahmoud Ragab^3,5,6,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1863-1877, 2023, DOI:10.32604/csse.2023.035869
Abstract Notwithstanding the religious intention of billions of devotees, the religious mass gathering increased major public health concerns since it likely became a huge super spreading event for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Most attendees ignored preventive measures, namely maintaining physical distance, practising hand hygiene, and wearing facemasks. Wearing a face mask in public areas protects people from spreading COVID-19. Artificial intelligence (AI) based on deep learning (DL) and machine learning (ML) could assist in fighting covid-19 in several ways. This study introduces a new deep learning-based Face Mask Detection in Religious Mass Gathering (DLFMD-RMG) technique during the… More >

View

970

Download

468

Open Access

ARTICLE

Neenavath Veeraiah^1,*, Youseef Alotaibi², Ahmad F. Subahi³
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1879-1900, 2023, DOI:10.32604/csse.2023.034658
Abstract An abnormality that develops in white blood cells is called leukemia. The diagnosis of leukemia is made possible by microscopic investigation of the smear in the periphery. Prior training is necessary to complete the morphological examination of the blood smear for leukemia diagnosis. This paper proposes a Histogram Threshold Segmentation Classifier (HTsC) for a decision support system. The proposed HTsC is evaluated based on the color and brightness variation in the dataset of blood smear images. Arithmetic operations are used to crop the nucleus based on automated approximation. White Blood Cell (WBC) segmentation is calculated using the active contour model… More >

View

698

Download

382

Open Access

ARTICLE

Mohammad Yamin^1,*, Sarah Basahel¹, Saleh Bajaba², Mona Abusurrah³, E. Laxmi Lydia⁴
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1901-1916, 2023, DOI:10.32604/csse.2023.036455
Abstract Recently, there has been a considerable rise in the number of diabetic patients suffering from diabetic retinopathy (DR). DR is one of the most chronic diseases and makes the key cause of vision loss in middle-aged people in the developed world. Initial detection of DR becomes necessary for decreasing the disease severity by making use of retinal fundus images. This article introduces a Deep Learning Enabled Large Scale Healthcare Decision Making for Diabetic Retinopathy (DLLSHDM-DR) on Retinal Fundus Images. The proposed DLLSHDM-DR technique intends to assist physicians with the DR decision-making method. In the DLLSHDM-DR technique, image preprocessing is initially… More >

View

828

Download

447

Open Access

ARTICLE

Ushaa Eswaran^1,*, S. Anand²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1917-1928, 2023, DOI:10.32604/csse.2023.032523
Abstract Colon cancer is the third most commonly diagnosed cancer in the world. Most colon AdenoCArcinoma (ACA) arises from pre-existing benign polyps in the mucosa of the bowel. Thus, detecting benign at the earliest helps reduce the mortality rate. In this work, a Predictive Modeling System (PMS) is developed for the classification of colon cancer using the Horizontal Voting Ensemble (HVE) method. Identifying different patterns in microscopic images is essential to an effective classification system. A twelve-layer deep learning architecture has been developed to extract these patterns. The developed HVE algorithm can increase the system’s performance according to the combined models… More >

View

686

Download

406

Open Access

ARTICLE

Anwer Mustafa Hilal^1,*, Fadwa Alrowais², Fahd N. Al-Wesabi³, Radwa Marzouk^4,5
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1929-1945, 2023, DOI:10.32604/csse.2023.035529
Abstract The problem of producing a natural language description of an image for describing the visual content has gained more attention in natural language processing (NLP) and computer vision (CV). It can be driven by applications like image retrieval or indexing, virtual assistants, image understanding, and support of visually impaired people (VIP). Though the VIP uses other senses, touch and hearing, for recognizing objects and events, the quality of life of those persons is lower than the standard level. Automatic Image captioning generates captions that will be read loudly to the VIP, thereby realizing matters happening around them. This article introduces… More >

View

814

Download

396

Open Access

ARTICLE

Xu Zhang¹, Jianchao Ni², Juxi Hu^3,*, Weisi Chen⁴
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1947-1960, 2023, DOI:10.32604/csse.2023.035118
Abstract Structural reliability is an important method to measure the safety performance of structures under the influence of uncertain factors. Traditional structural reliability analysis methods often convert the limit state function to the polynomial form to measure whether the structure is invalid. The uncertain parameters mainly exist in the form of intervals. This method requires a lot of calculation and is often difficult to achieve efficiently. In order to solve this problem, this paper proposes an interval variable multivariate polynomial algorithm based on Bernstein polynomials and evidence theory to solve the structural reliability problem with cognitive uncertainty. Based on the non-probabilistic… More >

View

813

Download

432

Open Access

ARTICLE

R. Prasanna^1,*, Uma Govindarajan¹, N. S. Bhuvaneswari²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1961-1979, 2023, DOI:10.32604/csse.2023.032424
Abstract In this paper, an optimized Genetic Algorithm (GA) based internal model controller-proportional integral derivative (IMC-PID) controller has been designed for the control variable to output variable transfer function of dc-dc boost converter to mitigate the effect of non-minimum phase (NMP) behavior due to the presence of a right-half plane zero (RHPZ). This RHPZ limits the dynamic performance of the converter and leads to internal instability. The IMC PID is a streamlined counterpart of the standard feedback controller and easily achieves optimal set point and load change performance with a single filter tuning parameter λ. Also, this paper addresses the influences… More >

View

679

Download

469

Open Access

ARTICLE

Pham Huy Thong^1,2,3, Florentin Smarandache⁴, Phung The Huan⁵, Tran Manh Tuan⁶, Tran Thi Ngan^6,*, Vu Duc Thai⁵, Nguyen Long Giang², Le Hoang Son³
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1981-1997, 2023, DOI:10.32604/csse.2023.035692
Abstract Clustering is a crucial method for deciphering data structure and producing new information. Due to its significance in revealing fundamental connections between the human brain and events, it is essential to utilize clustering for cognitive research. Dealing with noisy data caused by inaccurate synthesis from several sources or misleading data production processes is one of the most intriguing clustering difficulties. Noisy data can lead to incorrect object recognition and inference. This research aims to innovate a novel clustering approach, named Picture-Neutrosophic Trusted Safe Semi-Supervised Fuzzy Clustering (PNTS3FCM), to solve the clustering problem with noisy data using neutral and refusal degrees… More >

View

814

Download

415

Open Access

ARTICLE

Qianlei Wang^1,2,3,*, Zaijun Wang³, Renhe Xiong⁴, Xingbin Liao^1,2, Xiaojun Tan⁵
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1999-2020, 2023, DOI:10.32604/csse.2023.034183
Abstract How to accurately recognize the mental state of pilots is a focus in civil aviation safety. The mental state of pilots is closely related to their cognitive ability in piloting. Whether the cognitive ability meets the standard is related to flight safety. However, the pilot's working state is unique, which increases the difficulty of analyzing the pilot's mental state. In this work, we proposed a Convolutional Neural Network (CNN) that merges attention to classify the mental state of pilots through electroencephalography (EEG). Considering the individual differences in EEG, semi-supervised learning based on improved K-Means is used in the model training… More >

View

664

Download

415

Open Access

ARTICLE

Ahmed A. Alsheikhy^1,*, Ahmad S. Azzahrani¹, A. Khuzaim Alzahrani², Tawfeeq Shawly³
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2021-2037, 2023, DOI:10.32604/csse.2023.036107
Abstract A brain tumor is an excessive development of abnormal and uncontrolled cells in the brain. This growth is considered deadly since it may cause death. The brain controls numerous functions, such as memory, vision, and emotions. Due to the location, size, and shape of these tumors, their detection is a challenging and complex task. Several efforts have been conducted toward improved detection and yielded promising results and outcomes. However, the accuracy should be higher than what has been reached. This paper presents a method to detect brain tumors with high accuracy. The method works using an image segmentation technique and… More >

View

1001

Download

490

Like

1

Open Access

ARTICLE

Neenavath Veeraiah^1,*, Youseef Alotaibi², Ahmad F. Subahi³
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2039-2058, 2023, DOI:10.32604/csse.2023.036985
Abstract Leukemia, often called blood cancer, is a disease that primarily affects white blood cells (WBCs), which harms a person’s tissues and plasma. This condition may be fatal when if it is not diagnosed and recognized at an early stage. The physical technique and lab procedures for Leukaemia identification are considered time-consuming. It is crucial to use a quick and unexpected way to identify different forms of Leukaemia. Timely screening of the morphologies of immature cells is essential for reducing the severity of the disease and reducing the number of people who require treatment. Various deep-learning (DL) model-based segmentation and categorization… More >

View

816

Download

396

Open Access

ARTICLE

M. F. Mridha¹, Zabir Mohammad², Muhammad Mohsin Kabir², Aklima Akter Lima², Sujoy Chandra Das², Md Rashedul Islam^3,*, Yutaka Watanobe⁴
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2059-2073, 2023, DOI:10.32604/csse.2023.032977
Abstract The writer identification system identifies individuals based on their handwriting is a frequent topic in biometric authentication and verification systems. Due to its importance, numerous studies have been conducted in various languages. Researchers have established several learning methods for writer identification including supervised and unsupervised learning. However, supervised methods require a large amount of annotation data, which is impossible in most scenarios. On the other hand, unsupervised writer identification methods may be limited and dependent on feature extraction that cannot provide the proper objectives to the architecture and be misinterpreted. This paper introduces an unsupervised writer identification system that analyzes… More >

View

1523

Download

401

Open Access

ARTICLE

Savas Takan^1,*, Gokmen Katipoglu²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2075-2089, 2023, DOI:10.32604/csse.2023.036791
Abstract A measure of the “goodness” or efficiency of the test suite is used to determine the proficiency of a test suite. The appropriateness of the test suite is determined through mutation analysis. Several Finite State Machine (FSM) mutants are produced in mutation analysis by injecting errors against hypotheses. These mutants serve as test subjects for the test suite (TS). The effectiveness of the test suite is proportional to the number of eliminated mutants. The most effective test suite is the one that removes the most significant number of mutants at the optimal time. It is difficult to determine the fault… More >

View

725

Download

384

Open Access

ARTICLE

Seog Chung Seo¹, HeeSeok Kim^2,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2091-2107, 2023, DOI:10.32604/csse.2023.035064
Abstract With the rapid development of quantum computers capable of realizing Shor’s algorithm, existing public key-based algorithms face a significant security risk. Crystals-Kyber has been selected as the only key encapsulation mechanism (KEM) algorithm in the National Institute of Standards and Technology (NIST) Post-Quantum Cryptography (PQC) competition. In this study, we present a portable and efficient implementation of a Crystals-Kyber post-quantum KEM based on WebAssembly (Wasm), a recently released portable execution framework for high-performance web applications. Until now, most Kyber implementations have been developed with native programming languages such as C and Assembly. Although there are a few previous Kyber implementations… More >

View

1084

Download

480

Open Access

ARTICLE

Ramya Sridhar^1,*, Vijayalakshimi Patteeswaran²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2109-2122, 2023, DOI:10.32604/csse.2023.036781
Abstract In this paper, the investigation of a novel compact 2 × 2, 2 × 1, and 1 × 1 Ultra-Wide Band (UWB) based Multiple-Input Multiple-Output (MIMO) antenna with Defected Ground Structure (DGS) is employed. The proposed Electromagnetic Radiation Structures (ERS) is composed of multiple radiating elements. These MIMO antennas are designed and analyzed with and without DGS. The feeding is introduced by a microstrip-fed line to significantly moderate the radiating structure’s overall size, which is 60 × 40 × 1 mm. The high directivity and divergence characteristics are attained by introducing the microstrip-fed lines perpendicular to each other. And the… More >

View

839

Download

469

Open Access

ARTICLE

Saurabh Adhikari¹, Tushar Kanti Gangopadhayay¹, Souvik Pal^2,3, D. Akila⁴, Mamoona Humayun⁵, Majed Alfayad⁶, N. Z. Jhanjhi^7,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2123-2140, 2023, DOI:10.32604/csse.2023.034431
Abstract Machine learning is a technique for analyzing data that aids the construction of mathematical models. Because of the growth of the Internet of Things (IoT) and wearable sensor devices, gesture interfaces are becoming a more natural and expedient human-machine interaction method. This type of artificial intelligence that requires minimal or no direct human intervention in decision-making is predicated on the ability of intelligent systems to self-train and detect patterns. The rise of touch-free applications and the number of deaf people have increased the significance of hand gesture recognition. Potential applications of hand gesture recognition research span from online gaming to… More >

View

950

Download

583