Open Access
ISSN:0267-6192(print)
Publication Frequency:Monthly
The Computer Systems Science and Engineering journal is devoted to the publication of high quality papers on theoretical developments in computer systems science, and their applications in computer systems engineering. Original research papers, state-of-the-art reviews and technical notes are invited for publication. Computer Systems Science and Engineering is published monthly by Tech Science Press.
Scopus Cite Score (Impact per Publication 2022): 2.7; SNIP (Source Normalized Impact per Paper 2022): 0.753; ACM Digital Library.
Refers to the articles published on the journal within the last three years that have gained the most viewing times to date (Statistics provided by TSP database)
Refers to articles published on the journal since 2020 that have received the most frequent citation to date (Statistics provided by TSP database)
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1321-1347, 2023, DOI:10.32604/csse.2023.038089
Abstract Information security has emerged as a key problem in encryption because of the rapid evolution of the internet and networks. Thus, the progress of image encryption techniques is becoming an increasingly serious issue and considerable problem. Small space of the key, encryption-based low confidentiality, low key sensitivity, and easily exploitable existing image encryption techniques integrating chaotic system and DNA computing are purposing the main problems to propose a new encryption technique in this study. In our proposed scheme, a three-dimensional Chen’s map and a one-dimensional Logistic map are employed to construct a double-layer image encryption scheme. In the confusion stage,… More >
Open Access
REVIEW
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1349-1364, 2023, DOI:10.32604/csse.2023.033596
Abstract Acute leukemia is an aggressive disease that has high mortality rates worldwide. The error rate can be as high as 40% when classifying acute leukemia into its subtypes. So, there is an urgent need to support hematologists during the classification process. More than two decades ago, researchers used microarray gene expression data to classify cancer and adopted acute leukemia as a test case. The high classification accuracy they achieved confirmed that it is possible to classify cancer subtypes using microarray gene expression data. Ensemble machine learning is an effective method that combines individual classifiers to classify new samples. Ensemble classifiers… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1365-1384, 2023, DOI:10.32604/csse.2023.037033
Abstract A considerable portion of the population now experiences osteoarthritis of the knee, spine, and hip due to lifestyle changes. Therefore, early treatment, recognition and prevention are essential to reduce damage; nevertheless, this time-consuming activity necessitates a variety of tests and in-depth analysis by physicians. To overcome the existing challenges in the early detection of Knee Osteoarthritis (KOA), an effective automated technique, prompt recognition, and correct categorization are required. This work suggests a method based on an improved deep learning algorithm that makes use of data from the knee images after segmentation to detect KOA and its severity using the Kellgren-Lawrence… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1385-1413, 2023, DOI:10.32604/csse.2023.036144
Abstract The detection of rice leaf disease is significant because, as an agricultural and rice exporter country, Pakistan needs to advance in production and lower the risk of diseases. In this rapid globalization era, information technology has increased. A sensing system is mandatory to detect rice diseases using Artificial Intelligence (AI). It is being adopted in all medical and plant sciences fields to access and measure the accuracy of results and detection while lowering the risk of diseases. Deep Neural Network (DNN) is a novel technique that will help detect disease present on a rice leave because DNN is also considered… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1415-1432, 2023, DOI:10.32604/csse.2023.040039
Abstract Data hiding (DH) is an important technology for securely transmitting secret data in networks, and has increasing become a research hotspot throughout the world. However, for Joint photographic experts group (JPEG) images, it is difficult to balance the contradiction among embedded capacity, visual quality and the file size increment in existing data hiding schemes. Thus, to deal with this problem, a high-imperceptibility data hiding for JPEG images is proposed based on direction modification. First, this proposed scheme sorts all of the quantized discrete cosine transform (DCT) block in ascending order according to the number of non-consecutive-zero alternating current (AC) coefficients.… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1433-1449, 2023, DOI:10.32604/csse.2023.040132
Abstract An action recognition network that combines multi-level spatiotemporal feature fusion with an attention mechanism is proposed as a solution to the issues of single spatiotemporal feature scale extraction, information redundancy, and insufficient extraction of frequency domain information in channels in 3D convolutional neural networks. Firstly, based on 3D CNN, this paper designs a new multilevel spatiotemporal feature fusion (MSF) structure, which is embedded in the network model, mainly through multilevel spatiotemporal feature separation, splicing and fusion, to achieve the fusion of spatial perceptual fields and short-medium-long time series information at different scales with reduced network parameters; In the second step,… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1451-1469, 2023, DOI:10.32604/csse.2023.039957
Abstract With the widespread use of the internet, there is an increasing need to ensure the security and privacy of transmitted data. This has led to an intensified focus on the study of video steganography, which is a technique that hides data within a video cover to avoid detection. The effectiveness of any steganography method depends on its ability to embed data without altering the original video’s quality while maintaining high efficiency. This paper proposes a new method to video steganography, which involves utilizing a Genetic Algorithm (GA) for identifying the Region of Interest (ROI) in the cover video. The ROI… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1471-1491, 2023, DOI:10.32604/csse.2023.037366
Abstract Rubber producers, consumers, traders, and those who are involved in the rubber industry face major risks of rubber price fluctuations. As a result, decision-makers are required to make an accurate estimation of the price of rubber. This paper aims to propose hybrid intelligent models, which can be utilized to forecast the price of rubber in Malaysia by employing monthly Malaysia’s rubber pricing data, spanning from January 2016 to March 2021. The projected hybrid model consists of different algorithms with the symbolic Radial Basis Functions Neural Network k-Satisfiability Logic Mining (RBFNN-kSAT). These algorithms, including Grey Wolf Optimization Algorithm, Artificial Bee Colony… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1493-1505, 2023, DOI:10.32604/csse.2023.037976
Abstract Massive multiple-input multiple-output (MIMO) systems that use the millimeter-wave (mm-wave) band have a higher frequency and more antennas, which leads to significant path loss, high power consumption, and server interference. Due to these issues, the spectrum efficiency is significantly reduced, making spectral efficiency improvement an important research topic for 5G communication. Together with communication in the terahertz (THz) bands, mmWave communication is currently a component of the 5G standards and is seen as a solution to the commercial bandwidth shortage. The quantity of continuous, mostly untapped bandwidth in the 30–300 GHz band has presented a rare opportunity to boost the capacity… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1507-1525, 2023, DOI:10.32604/csse.2023.037493
Abstract Black fungus is a rare and dangerous mycology that usually affects the brain and lungs and could be life-threatening in diabetic cases. Recently, some COVID-19 survivors, especially those with co-morbid diseases, have been susceptible to black fungus. Therefore, recovered COVID-19 patients should seek medical support when they notice mucormycosis symptoms. This paper proposes a novel ensemble deep-learning model that includes three pre-trained models: reset (50), VGG (19), and Inception. Our approach is medically intuitive and efficient compared to the traditional deep learning models. An image dataset was aggregated from various resources and divided into two classes: a black fungus class… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1527-1547, 2023, DOI:10.32604/csse.2023.038951
Abstract Responding to complex analytical queries in the data warehouse
(DW) is one of the most challenging tasks that require prompt attention.
The problem of materialized view (MV) selection relies on selecting the most
optimal views that can respond to more queries simultaneously. This work
introduces a combined approach in which the constraint handling process
is combined with metaheuristics to select the most optimal subset of DW
views from DWs. The proposed work initially refines the solution to enable
a feasible selection of views using the ensemble constraint handling technique
(ECHT). The constraints such as self-adaptive penalty, epsilon (ε)-parameter
and stochastic… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1549-1569, 2023, DOI:10.32604/csse.2023.039410
Abstract Small targets and occluded targets will inevitably appear in the image during the shooting process due to the influence of angle, distance, complex scene, illumination intensity, and other factors. These targets have few effective pixels, few features, and no apparent features, which makes extracting their efficient features difficult and easily leads to false detection, missed detection, and repeated detection, affecting the performance of target detection models. An improved faster region convolutional neural network (RCNN) algorithm (CF-RCNN) integrating convolutional block attention module (CBAM) and feature pyramid networks (FPN) is proposed to improve the detection and recognition accuracy of small-size objects, occluded… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1571-1591, 2023, DOI:10.32604/csse.2023.039701
Abstract Human recognition technology based on biometrics has become a fundamental requirement in all aspects of life due to increased concerns about security and privacy issues. Therefore, biometric systems have emerged as a technology with the capability to identify or authenticate individuals based on their physiological and behavioral characteristics. Among different viable biometric modalities, the human ear structure can offer unique and valuable discriminative characteristics for human recognition systems. In recent years, most existing traditional ear recognition systems have been designed based on computer vision models and have achieved successful results. Nevertheless, such traditional models can be sensitive to several unconstrained… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1593-1609, 2023, DOI:10.32604/csse.2023.039984
Abstract Introducing IoT devices to healthcare fields has made it possible
to remotely monitor patients’ information and provide a proper diagnosis
as needed, resulting in the Internet of Medical Things (IoMT). However,
obtaining good security features that ensure the integrity and confidentiality of patient’s information is a significant challenge. However, due to
the computational resources being limited, an edge device may struggle to
handle heavy detection tasks such as complex machine learning algorithms.
Therefore, designing and developing a lightweight detection mechanism is
crucial. To address the aforementioned challenges, a new lightweight IDS
approach is developed to effectively combat a diverse range… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1611-1632, 2023, DOI:10.32604/csse.2023.038319
Abstract As the demand for used books has grown in recent years, various online/offline market platforms have emerged to support the trade in used books. The price of used books can depend on various factors, such as the state of preservation (i.e., condition), the value of possession, and so on. Therefore, some online platforms provide a reference document to evaluate the condition of used books, but it is still not trivial for individual sellers to determine the price. The lack of a standard quantitative method to assess the condition of the used book would confuse both sellers and consumers, thereby decreasing… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1633-1650, 2023, DOI:10.32604/csse.2023.034769
Abstract Fruit classification utilizing a deep convolutional neural network (CNN) is the most promising application in personal computer vision (CV). Profound learning-related characterization made it possible to recognize fruits from pictures. But, due to the similarity and complexity, fruit recognition becomes an issue for the stacked fruits on a weighing scale. Recently, Machine Learning (ML) methods have been used in fruit farming and agriculture and brought great convenience to human life. An automated system related to ML could perform the fruit classifier and sorting tasks previously managed by human experts. CNN’s (convolutional neural networks) have attained incredible outcomes in image classifiers… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1651-1664, 2023, DOI:10.32604/csse.2023.037449
Abstract Wireless Sensor Networks (WSNs) gather data in physical environments, which is some type. These ubiquitous sensors face several challenges
responsible for corrupting them (mostly sensor failure and intrusions in
external agents). WSNs were disposed to error, and effectual fault detection
techniques are utilized for detecting faults from WSNs in a timely approach.
Machine learning (ML) was extremely utilized for detecting faults in WSNs.
Therefore, this study proposes a billiards optimization algorithm with modified deep learning for fault detection (BIOMDL-FD) in WSN. The BIOMDLFD technique mainly concentrates on identifying sensor faults to enhance
network efficiency. To do so, the presented BIOMDL-FD… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1665-1690, 2023, DOI:10.32604/csse.2023.038871
Abstract Blockchain is one of the innovative and disruptive technologies that has a wide range of applications in multiple industries beyond cryptocurrency. The widespread adoption of blockchain technology in various industries has shown its potential to solve challenging business problems, as well as the possibility to create new business models which can increase a firm’s competitiveness. Due to the novelty of the technology, whereby many companies are still exploring potential use cases, and considering the complexity of blockchain technology, which may require huge changes to a company’s existing systems and processes, it is important for companies to carefully evaluate suitable use… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1691-1707, 2023, DOI:10.32604/csse.2023.034798
Abstract Applied linguistics is one of the fields in the linguistics domain and deals with the practical applications of the language studies such as speech processing, language teaching, translation and speech therapy. The ever-growing Online Social Networks (OSNs) experience a vital issue to confront, i.e., hate speech. Amongst the OSN-oriented security problems, the usage of offensive language is the most important threat that is prevalently found across the Internet. Based on the group targeted, the offensive language varies in terms of adult content, hate speech, racism, cyberbullying, abuse, trolling and profanity. Amongst these, hate speech is the most intimidating form of… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1709-1732, 2023, DOI:10.32604/csse.2023.039186
Abstract With the popularity of online learning and due to the significant influence of emotion on the learning effect, more and more researches focus on emotion recognition in online learning. Most of the current research uses the comments of the learning platform or the learner’s expression for emotion recognition. The research data on other modalities are scarce. Most of the studies also ignore the impact of instructional videos on learners and the guidance of knowledge on data. Because of the need for other modal research data, we construct a synchronous multimodal data set for analyzing learners’ emotional states in online learning… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1733-1750, 2023, DOI:10.32604/csse.2023.039296
Abstract A cataract is one of the most significant eye problems worldwide that does not immediately impair vision and progressively worsens over time. Automatic cataract prediction based on various imaging technologies has been addressed recently, such as smartphone apps used for remote health monitoring and eye treatment. In recent years, advances in diagnosis, prediction, and clinical decision support using Artificial Intelligence (AI) in medicine and ophthalmology have been exponential. Due to privacy concerns, a lack of data makes applying artificial intelligence models in the medical field challenging. To address this issue, a federated learning framework named CD-FL based on a VGG16… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1751-1773, 2023, DOI:10.32604/csse.2023.038514
Abstract Photovoltaic (PV) systems are environmentally friendly, generate green energy, and receive support from policies and organizations. However, weather fluctuations make large-scale PV power integration and management challenging despite the economic benefits. Existing PV forecasting techniques (sequential and convolutional neural networks (CNN)) are sensitive to environmental conditions, reducing energy distribution system performance. To handle these issues, this article proposes an efficient, weather-resilient convolutional-transformer-based network (CT-NET) for accurate and efficient PV power forecasting. The network consists of three main modules. First, the acquired PV generation data are forwarded to the pre-processing module for data refinement. Next, to carry out data encoding, a… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1775-1791, 2023, DOI:10.32604/csse.2023.039007
Abstract Pneumothorax is a thoracic condition that occurs when a person’s lungs collapse, causing air to enter the pleural cavity, the area close to the lungs and chest wall. The most persistent disease, as well as one that necessitates particular patient care and the privacy of their health records. The radiologists find it challenging to diagnose pneumothorax due to the variations in images. Deep learning-based techniques are commonly employed to solve image categorization and segmentation problems. However, it is challenging to employ it in the medical field due to privacy issues and a lack of data. To address this issue, a… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1793-1817, 2023, DOI:10.32604/csse.2023.039648
Abstract Artificial Intelligence (AI) has gained popularity for the containment of COVID-19 pandemic applications. Several AI techniques provide efficient mechanisms for handling pandemic situations. AI methods, protocols, data sets, and various validation mechanisms empower the users towards proper decision-making and procedures to handle the situation. Despite so many tools, there still exist conditions in which AI must go a long way. To increase the adaptability and potential of these techniques, a combination of AI and Bigdata is currently gaining popularity. This paper surveys and analyzes the methods within the various computational paradigms used by different researchers and national governments, such as… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1819-1838, 2023, DOI:10.32604/csse.2023.040729
Abstract 3D models are essential in virtual reality, game development, architecture design, engineering drawing, medicine, and more. Compared to digital images, 3D models can provide more realistic visual effects. In recent years, significant progress has been made in the field of digital image encryption, and researchers have developed new algorithms that are more secure and efficient. However, there needs to be more research on 3D model encryption. This paper proposes a new 3D model encryption algorithm, called the 1D map with sin and logistic coupling (1D-MWSLC), because existing digital image encryption algorithms cannot be directly applied to 3D models. Firstly, this… More >
Open Access
REVIEW
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1839-1879, 2023, DOI:10.32604/csse.2023.040456
Abstract Smart environments offer various services, including smart cities, e-healthcare, transportation, and wearable devices, generating multiple traffic flows with different Quality of Service (QoS) demands. Achieving the desired QoS with security in this heterogeneous environment can be challenging due to traffic flows and device management, unoptimized routing with resource awareness, and security threats. Software Defined Networks (SDN) can help manage these devices through centralized SDN controllers and address these challenges. Various schemes have been proposed to integrate SDN with emerging technologies for better resource utilization and security. Software Defined Wireless Body Area Networks (SDWBAN) and Software Defined Internet of Things (SDIoT)… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1881-1899, 2023, DOI:10.32604/csse.2023.034853
Abstract With the development of Internet technology, the explosive growth of Internet information presentation has led to difficulty in filtering effective information. Finding a model with high accuracy for text classification has become a critical problem to be solved by text filtering, especially for Chinese texts. This paper selected the manually calibrated Douban movie website comment data for research. First, a text filtering model based on the BP neural network has been built; Second, based on the Term Frequency-Inverse Document Frequency (TF-IDF) vector space model and the doc2vec method, the text word frequency vector and the text semantic vector were obtained… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1901-1917, 2023, DOI:10.32604/csse.2023.039395
Abstract With the rapid development of urban road traffic and the increasing number of vehicles, how to alleviate traffic congestion is one of the hot issues that need to be urgently addressed in building smart cities. Therefore, in this paper, a nonlinear multi-objective optimization model of urban intersection signal timing based on a Genetic Algorithm was constructed. Specifically, a typical urban intersection was selected as the research object, and drivers’ acceleration habits were taken into account. What’s more, the shortest average delay time, the least average number of stops, and the maximum capacity of the intersection were regarded as the optimization… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1919-1935, 2023, DOI:10.32604/csse.2023.039599
Abstract Artificial Intelligence (AI) technology has been extensively researched in various fields, including the field of malware detection. AI models must be trustworthy to introduce AI systems into critical decision-making and resource protection roles. The problem of robustness to adversarial attacks is a significant barrier to trustworthy AI. Although various adversarial attack and defense methods are actively being studied, there is a lack of research on robustness evaluation metrics that serve as standards for determining whether AI models are safe and reliable against adversarial attacks. An AI model’s robustness level cannot be evaluated by traditional evaluation indicators such as accuracy and… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1937-1966, 2023, DOI:10.32604/csse.2023.039788
Abstract The process of selecting features or reducing dimensionality can be viewed as a multi-objective minimization problem in which both the number of features and error rate must be minimized. While it is a multi-objective problem, current methods tend to treat feature selection as a single-objective optimization task. This paper presents enhanced multi-objective grey wolf optimizer with Lévy flight and mutation phase (LMuMOGWO) for tackling feature selection problems. The proposed approach integrates two effective operators into the existing Multi-objective Grey Wolf optimizer (MOGWO): a Lévy flight and a mutation operator. The Lévy flight, a type of random walk with jump size… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1967-1986, 2023, DOI:10.32604/csse.2023.040345
Abstract Image authentication techniques have recently received a lot of attention for protecting images against unauthorized access. Due to the wide use of the Internet nowadays, the need to ensure data integrity and authentication increases. Many techniques, such as watermarking and encryption, are used for securing images transmitted via the Internet. The majority of watermarking systems are PC-based, but they are not very portable. Hardware-based watermarking methods need to be developed to accommodate real-time applications and provide portability. This paper presents hybrid data security techniques using a zero watermarking method to provide copyright protection for the transmitted color images using multi-channel… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 1987-2006, 2023, DOI:10.32604/csse.2023.040381
Abstract Rockburst is a phenomenon in which free surfaces are formed during excavation, which subsequently causes the sudden release of energy in the construction of mines and tunnels. Light rockburst only peels off rock slices without ejection, while severe rockburst causes casualties and property loss. The frequency and degree of rockburst damage increases with the excavation depth. Moreover, rockburst is the leading engineering geological hazard in the excavation process, and thus the prediction of its intensity grade is of great significance to the development of geotechnical engineering. Therefore, the prediction of rockburst intensity grade is one problem that needs to be… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2007-2025, 2023, DOI:10.32604/csse.2023.037723
Abstract Agriculture plays an important role in the economy of any country. Approximately half of the population of developing countries is directly or indirectly connected to the agriculture field. Many farmers do not choose the right crop for cultivation depending on their soil type, crop type, and climatic requirements like rainfall. This wrong decision of crop selection directly affects the production of the crops which leads to yield and economic loss in the country. Many parameters should be observed such as soil characteristics, type of crop, and environmental factors for the cultivation of the right crop. Manual decision-making is time-taking and… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2027-2047, 2023, DOI:10.32604/csse.2023.040327
Abstract Intelligent vision-based surveillance systems are designed to deal with the gigantic volume of videos captured in a particular environment to perform the interpretation of scenes in form of detection, tracking, monitoring, behavioral analysis, and retrievals. In addition to that, another evolving way of surveillance systems in a particular environment is human gait-based surveillance. In the existing research, several methodological frameworks are designed to use deep learning and traditional methods, nevertheless, the accuracies of these methods drop substantially when they are subjected to covariate conditions. These covariate variables disrupt the gait features and hence the recognition of subjects becomes difficult. To… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2049-2060, 2023, DOI:10.32604/csse.2023.040473
Abstract In many IIoT architectures, various devices connect to the edge cloud via gateway systems. For data processing, numerous data are delivered to the edge cloud. Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency. There are two types of costs for this kind of IoT network: a communication cost and a computing cost. For service efficiency, the communication cost of data transmission should be minimized, and the computing cost in the edge cloud should be also minimized. Therefore, in this paper, the communication cost for data transmission is defined as the delay factor, and the… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2061-2078, 2023, DOI:10.32604/csse.2023.040483
Abstract Wireless body area networks (WBANs) are an emerging technology for the real-time monitoring of physiological signals. WBANs provide a mechanism for collecting, storing, and transmitting physiological data to healthcare providers. However, the open wireless channel and limited resources of sensors bring security challenges. To ensure physiological data security, this paper provides an efficient Certificateless Public Key Infrastructure Heterogeneous Ring Signcryption (CP-HRSC) scheme, in which sensors are in a certificateless cryptosystem (CLC) environment, and the server is in a public key infrastructure (PKI) environment. CLC could solve the limitations of key escrow in identity-based cryptography (IBC) and certificate management for public… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2079-2095, 2023, DOI:10.32604/csse.2023.038322
Abstract Skin cancer is one of the most dangerous cancer. Because of the high melanoma death rate, skin cancer is divided into non-melanoma and melanoma. The dermatologist finds it difficult to identify skin cancer from dermoscopy images of skin lesions. Sometimes, pathology and biopsy examinations are required for cancer diagnosis. Earlier studies have formulated computer-based systems for detecting skin cancer from skin lesion images. With recent advancements in hardware and software technologies, deep learning (DL) has developed as a potential technique for feature learning. Therefore, this study develops a new sand cat swarm optimization with a deep transfer learning method for… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2097-2118, 2023, DOI:10.32604/csse.2023.039262
Abstract Neurodegeneration is the gradual deterioration and eventual death of brain cells, leading to progressive loss of structure and function of neurons in the brain and nervous system. Neurodegenerative disorders, such as Alzheimer’s, Huntington’s, Parkinson’s, amyotrophic lateral sclerosis, multiple system atrophy, and multiple sclerosis, are characterized by progressive deterioration of brain function, resulting in symptoms such as memory impairment, movement difficulties, and cognitive decline. Early diagnosis of these conditions is crucial to slowing down cell degeneration and reducing the severity of the diseases. Magnetic resonance imaging (MRI) is widely used by neurologists for diagnosing brain abnormalities. The majority of the research… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2119-2134, 2023, DOI:10.32604/csse.2023.040620
Abstract Kidney infection is a severe medical issue affecting individuals worldwide and increasing mortality rates. Chronic Kidney Disease (CKD) is treatable during its initial phases but can become irreversible and cause renal failure. Among the various diseases, the most prevalent kidney conditions affecting kidney function are cyst growth, kidney tumors, and nephrolithiasis. The significant challenge for the medical community is the immediate diagnosis and treatment of kidney disease. Kidney failure could result from kidney disorders like tumors, stones, and cysts if not often identified and addressed. Computer-assisted diagnostics are necessary to support clinicians’ and specialists’ medical assessments due to the rising… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2135-2152, 2023, DOI:10.32604/csse.2023.041030
Abstract Artificial intelligence is increasingly being applied in the field of video analysis, particularly in the area of public safety where video surveillance equipment such as closed-circuit television (CCTV) is used and automated analysis of video information is required. However, various issues such as data size limitations and low processing speeds make real-time extraction of video data challenging. Video analysis technology applies object classification, detection, and relationship analysis to continuous 2D frame data, and the various meanings within the video are thus analyzed based on the extracted basic data. Motion recognition is key in this analysis. Motion recognition is a challenging… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2153-2170, 2023, DOI:10.32604/csse.2023.038917
Abstract Social engineering attacks are considered one of the most hazardous cyberattacks in cybersecurity, as human vulnerabilities are often the weakest link in the entire network. Such vulnerabilities are becoming increasingly susceptible to network security risks. Addressing the social engineering attack defense problem has been the focus of many studies. However, two main challenges hinder its successful resolution. Firstly, the vulnerabilities in social engineering attacks are unique due to multistage attacks, leading to incorrect social engineering defense strategies. Secondly, social engineering attacks are real-time, and the defense strategy algorithms based on gaming or reinforcement learning are too complex to make rapid… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2171-2185, 2023, DOI:10.32604/csse.2023.039931
Abstract The recent adoption of satellite technologies, unmanned aerial vehicles (UAVs) and 5G has encouraged telecom networking to evolve into more stable service to remote areas and render higher quality. But, security concerns with drones were increasing as drone nodes have been striking targets for cyberattacks because of immensely weak inbuilt and growing poor security volumes. This study presents an Archimedes Optimization with Deep Learning based Aerial Image Classification and Intrusion Detection (AODL-AICID) technique in secure UAV networks. The presented AODL-AICID technique concentrates on two major processes: image classification and intrusion detection. For aerial image classification, the AODL-AICID technique encompasses MobileNetv2… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2187-2200, 2023, DOI:10.32604/csse.2023.040624
Abstract Federated learning has recently attracted significant attention as a cutting-edge technology that enables Artificial Intelligence (AI) algorithms to utilize global learning across the data of numerous individuals while safeguarding user data privacy. Recent advanced healthcare technologies have enabled the early diagnosis of various cognitive ailments like Parkinson’s. Adequate user data is frequently used to train machine learning models for healthcare systems to track the health status of patients. The healthcare industry faces two significant challenges: security and privacy issues and the personalization of cloud-trained AI models. This paper proposes a Deep Neural Network (DNN) based approach embedded in a federated… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2201-2217, 2023, DOI:10.32604/csse.2023.039893
Abstract Over the past few years, rapid advancements in the internet and communication technologies have led to increasingly intricate and diverse networking systems. As a result, greater intelligence is necessary to effectively manage, optimize, and maintain these systems. Due to their distributed nature, machine learning models are challenging to deploy in traditional networks. However, Software-Defined Networking (SDN) presents an opportunity to integrate intelligence into networks by offering a programmable architecture that separates data and control planes. SDN provides a centralized network view and allows for dynamic updates of flow rules and software-based traffic analysis. While the programmable nature of SDN makes… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2219-2239, 2023, DOI:10.32604/csse.2023.040212
Abstract The use of the internet is increasing all over the world on a daily basis in the last two decades. The increase in the internet causes many sexual crimes, such as sexual misuse, domestic violence, and child pornography. Various research has been done for pornographic image detection and classification. Most of the used models used machine learning techniques and deep learning models which show less accuracy, while the deep learning model ware used for classification and detection performed better as compared to machine learning. Therefore, this research evaluates the performance analysis of intelligent neural-based deep learning models which are based… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2241-2257, 2023, DOI:10.32604/csse.2023.040603
Abstract As millimeter waves will be widely used in the Internet of Things (IoT) and Telematics to provide high bandwidth communication and mass connectivity, the coverage optimization of base stations can effectively improve the quality of communication services. How to optimize the convergence speed of the base station coverage solution is crucial for IoT service providers. This paper proposes the Muti-Fusion Sparrow Search Algorithm (MFSSA) optimize the situation to address the problem of discrete coverage maximization and rapid convergence. Firstly, the initial swarm diversity is enriched using a sine chaotic map, and dynamic adaptive weighting is added to the discoverer location… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2259-2274, 2023, DOI:10.32604/csse.2023.041454
Abstract To serve various tasks requested by various end devices with different requirements, end-edge-cloud (E2C) has attracted more and more attention from specialists in both academia and industry, by combining both benefits of edge and cloud computing. But nowadays, E2C still suffers from low service quality and resource efficiency, due to the geographical distribution of edge resources and the high dynamic of network topology and user mobility. To address these issues, this paper focuses on task offloading, which makes decisions that which resources are allocated to tasks for their processing. This paper first formulates the problem into binary non-linear programming and… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2275-2291, 2023, DOI:10.32604/csse.2023.039272
Abstract When applied to Unmanned Aerial Vehicles (UAVs), existing Simultaneous Localization and Mapping (SLAM) algorithms are constrained by several factors, notably the interference of dynamic outdoor objects, the limited computing performance of UAVs, and the holes caused by dynamic objects removal in the map. We proposed a new SLAM system for UAVs in dynamic environments to solve these problems based on ORB-SLAM2. We have improved the Pyramid Scene Parsing Network (PSPNet) using Depthwise Separable Convolution to reduce the model parameters. We also incorporated an auxiliary loss function to supervise the hidden layer to enhance accuracy. Then we used the improved PSPNet… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2293-2311, 2023, DOI:10.32604/csse.2023.040312
Abstract Numerous types of research on healthcare monitoring systems have been conducted for calculating heart rate, ECG, nasal/oral airflow, temperature, light sensor, and fall detection sensor. Different researchers have done different work in the field of health monitoring with sensor networks. Different researchers used built-in apps, such as some used a small number of parameters, while some other studies used more than one microcontroller and used senders and receivers among the microcontrollers to communicate, and outdated tools for study development. While no efficient, cheap, and updated work is proposed in the field of sensor-based health monitoring systems. Therefore, this study developed… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2313-2336, 2023, DOI:10.32604/csse.2023.039682
Abstract Intelligent transportation systems (ITSs) are becoming increasingly popular as they support efficient coordinated transport. ITSs aim to improve the safety, efficiency and reliability of road transportation through integrated approaches to the exchange of relevant information. Mobile ad-hoc networks (MANETs) and vehicle ad-hoc networks (VANETs) are integral components of ITS. The VANET is composed of interconnected vehicles with sensitivity capabilities to exchange traffic, positioning, weather and emergency information. One of the main challenges in VANET is the reliable and timely dissemination of information between vehicular nodes to improve decision-making processes. This paper illustrates challenges in VANET and reviews possible solutions to… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2337-2360, 2023, DOI:10.32604/csse.2023.040410
Abstract Human Suspicious Activity Recognition (HSAR) is a critical and
active research area in computer vision that relies on artificial intelligence
reasoning. Significant advances have been made in this field recently due
to important applications such as video surveillance. In video surveillance,
humans are monitored through video cameras when doing suspicious activities such as kidnapping, fighting, snatching, and a few more. Although
numerous techniques have been introduced in the literature for routine human
actions (HAR), very few studies are available for HSAR. This study proposes a deep convolutional neural network (CNN) and optimal featuresbased framework for HSAR in video frames. The… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2361-2380, 2023, DOI:10.32604/csse.2023.038439
Abstract Patient privacy and data protection have been crucial concerns in E-healthcare systems for many years. In modern-day applications, patient data usually holds clinical imagery, records, and other medical details. Lately, the Internet of Medical Things (IoMT), equipped with cloud computing, has come out to be a beneficial paradigm in the healthcare field. However, the openness of networks and systems leads to security threats and illegal access. Therefore, reliable, fast, and robust security methods need to be developed to ensure the safe exchange of healthcare data generated from various image sensing and other IoMT-driven devices in the IoMT network. This paper… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2381-2396, 2023, DOI:10.32604/csse.2023.040030
Abstract Nowadays, wood identification is made by experts using hand lenses, wood atlases, and field manuals which take a lot of cost and time for the training process. The quantity and species must be strictly set up, and accurate identification of the wood species must be made during exploitation to monitor trade and enforce regulations to stop illegal logging. With the development of science, wood identification should be supported with technology to enhance the perception of fairness of trade. An automatic wood identification system and a dataset of 50 commercial wood species from Asia are established, namely, wood anatomical images collected… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2397-2415, 2023, DOI:10.32604/csse.2023.040529
Abstract X-Ray knee imaging is widely used to detect knee osteoarthritis due to ease of availability and lesser cost. However, the manual categorization of knee joint disorders is time-consuming, requires an expert person, and is costly. This article proposes a new approach to classifying knee osteoarthritis using deep learning and a whale optimization algorithm. Two pre-trained deep learning models (Efficientnet-b0 and Densenet201) have been employed for the training and feature extraction. Deep transfer learning with fixed hyperparameter values has been employed to train both selected models on the knee X-Ray images. In the next step, fusion is performed using a canonical… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2417-2437, 2023, DOI:10.32604/csse.2023.038074
Abstract Renewable energy sources like solar, wind, and hydro are becoming increasingly popular due to the fewer negative impacts they have on the environment. Because, Since the production of renewable energy sources is still in the process of being created, photovoltaic (PV) systems are commonly utilized for installation situations that are acceptable, clean, and simple. This study presents an adaptive artificial intelligence approach that can be used for maximum power point tracking (MPPT) in solar systems with the help of an embedded controller. The adaptive method incorporates both the Whale Optimization Algorithm (WOA) and the Artificial Neural Network (ANN). The WOA… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2439-2453, 2023, DOI:10.32604/csse.2023.033842
Abstract Attacks on fully integrated servers, apps, and communication networks via the Internet of Things (IoT) are growing exponentially. Sensitive
devices’ effectiveness harms end users, increases cyber threats and identity
theft, raises costs, and negatively impacts income as problems brought on by
the Internet of Things network go unnoticed for extended periods. Attacks
on Internet of Things interfaces must be closely monitored in real time for
effective safety and security. Following the 1, 2, 3, and 4G cellular networks,
the 5th generation wireless 5G network is indeed the great invasion of mankind
and is known as the global advancement of cellular… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2455-2479, 2023, DOI:10.32604/csse.2023.039736
Abstract To professionally plan and manage the development and evolution of the Internet of Things (IoT), researchers have proposed several IoT performance measurement solutions. IoT performance measurement solutions can be very valuable for managing the development and evolution of IoT systems, as they provide insights into performance issues, resource optimization, predictive maintenance, security, reliability, and user experience. However, there are several issues that can impact the accuracy and reliability of IoT performance measurements, including lack of standardization, complexity of IoT systems, scalability, data privacy, and security. While previous studies proposed several IoT measurement solutions in the literature, they did not evaluate… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2481-2496, 2023, DOI:10.32604/csse.2023.040817
Abstract
The high dimensionalhyperspectral image classification is a challenging task due to the spectral feature vectors. The high correlation between these features and the noises greatly affects the classification performances. To overcome this, dimensionality reduction techniques are widely used. Traditional image processing applications recently propose numerous deep learning models. However, in hyperspectral image classification, the features of deep learning models are less explored. Thus, for efficient hyperspectral image classification, a depth-wise convolutional neural network is presented in this research work. To handle the dimensionality issue in the classification process, an optimized self-organized map model is employed using a water strider optimization… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2497-2512, 2023, DOI:10.32604/csse.2023.041446
Abstract The Internet of Things (IoT) system has confronted dramatic growth in high dimensionality and data traffic. The system named intrusion detection systems (IDS) is broadly utilized for the enhancement of security posture in an IT infrastructure. An IDS is a practical and suitable method for assuring network security and identifying attacks by protecting it from intrusive hackers. Nowadays, machine learning (ML)-related techniques were used for detecting intrusion in IoTs IDSs. But, the IoT IDS mechanism faces significant challenges because of physical and functional diversity. Such IoT features use every attribute and feature for IDS self-protection unrealistic and difficult. This study… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2513-2528, 2023, DOI:10.32604/csse.2023.040305
Abstract Information and communication technologies are spreading rapidly due to their fast proliferation in many fields. The number of Internet users has led to a spike in cyber-attack incidents. E-commerce applications, such as online banking, marketing, trading, and other online businesses, play an integral role in our lives. Network Intrusion Detection System (NIDS) is essential to protect the network from unauthorized access and against other cyber-attacks. The existing NIDS systems are based on the Backward Oracle Matching (BOM) algorithm, which minimizes the false alarm rate and causes of high packet drop ratio. This paper discussed the existing NIDS systems and different… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2529-2545, 2023, DOI:10.32604/csse.2023.041488
Abstract Nowadays, Web browsers have become an important carrier of 3D model visualization because of their convenience and portability. During the process of large-scale 3D model visualization based on Web scenes with the problems of slow rendering speed and low FPS (Frames Per Second), occlusion culling, as an important method for rendering optimization, can remove most of the occluded objects and improve rendering efficiency. The traditional occlusion culling algorithm (TOCA) is calculated by traversing all objects in the scene, which involves a large amount of repeated calculation and time consumption. To advance the rendering process and enhance rendering efficiency, this paper… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2547-2562, 2023, DOI:10.32604/csse.2023.040855
Abstract The rapid advancement of data in web-based communication has created one of the biggest issues concerning the security of data carried over the internet from unauthorized access. To improve data security, modern cryptosystems use substitution-boxes. Nowadays, data privacy has become a key concern for consumers who transfer sensitive data from one place to another. To address these problems, many companies rely on cryptographic techniques to secure data from illegal activities and assaults. Among these cryptographic approaches, AES is a well-known algorithm that transforms plain text into cipher text by employing substitution box (S-box). The S-box disguises the relationship between cipher… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2563-2582, 2023, DOI:10.32604/csse.2023.041228
Abstract Spatio-temporal heterogeneous data is the database for decision-making in many fields, and checking its accuracy can provide data support for making decisions. Due to the randomness, complexity, global and local correlation of spatiotemporal heterogeneous data in the temporal and spatial dimensions, traditional detection methods can not guarantee both detection speed and accuracy. Therefore, this article proposes a method for detecting the accuracy of spatiotemporal heterogeneous data by fusing graph convolution and temporal convolution networks. Firstly, the geographic weighting function is introduced and improved to quantify the degree of association between nodes and calculate the weighted adjacency value to simplify the… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2583-2598, 2023, DOI:10.32604/csse.2023.037265
Abstract The introduction of new technologies has increased communication network coverage and the number of associating nodes in dynamic communication networks (DCN). As the network has the characteristics like decentralized and dynamic, few nodes in the network may not associate with other nodes. These uncooperative nodes also known as selfish nodes corrupt the performance of the cooperative nodes. Namely, the nodes cause congestion, high delay, security concerns, and resource depletion. This study presents an effective selfish node detection method to address these problems. The Price of Anarchy (PoA) and the Price of Stability (PoS) in Game Theory with the Presence of… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2599-2624, 2023, DOI:10.32604/csse.2023.041609
Abstract Heart disease is a primary cause of death worldwide and is notoriously difficult to cure without a proper diagnosis. Hence, machine learning (ML) can reduce and better understand symptoms associated with heart disease. This study aims to develop a framework for the automatic and accurate classification of heart disease utilizing machine learning algorithms, grid search (GS), and the Aquila optimization algorithm. In the proposed approach, feature selection is used to identify characteristics of heart disease by using a method for dimensionality reduction. First, feature selection is accomplished with the help of the Aquila algorithm. Then, the optimal combination of the… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2625-2641, 2023, DOI:10.32604/csse.2023.036626
Abstract The social engineering cyber-attack is where culprits mislead the users by getting the login details which provides the information to the evil server called phishing. The deep learning approaches and the machine learning are compared in the proposed system for presenting the methodology that can detect phishing websites via Uniform Resource Locator (URLs) analysis. The legal class is composed of the home pages with no inclusion of login forms in most of the present modern solutions, which deals with the detection of phishing. Contrarily, the URLs in both classes from the login page due, considering the representation of a real… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2643-2669, 2023, DOI:10.32604/csse.2023.040626
Abstract Supply chain attacks, exemplified by the SUNBURST attack utilizing SolarWinds Orion updates, pose a growing cybersecurity threat to entities worldwide. However, the need for suitable datasets for detecting and anticipating SUNBURST attacks is a significant challenge. We present a novel dataset collected using a unique network traffic data collection methodology to address this gap. Our study aims to enhance intrusion detection and prevention systems by understanding SUNBURST attack features. We construct realistic attack scenarios by combining relevant data and attack indicators. The dataset is validated with the J48 machine learning algorithm, achieving an average F-Measure of 87.7%. Our significant contribution… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2671-2688, 2023, DOI:10.32604/csse.2023.038154
Abstract To improve the tracking accuracy of persons in the surveillance video, we proposed an algorithm for multi-target tracking persons based on deep learning. In this paper, we used You Only Look Once v5 (YOLOv5) to obtain person targets of each frame in the video and used Simple Online and Realtime Tracking with a Deep Association Metric (DeepSORT) to do cascade matching and Intersection Over Union (IOU) matching of person targets between different frames. To solve the IDSwitch problem caused by the low feature extraction ability of the Re-Identification (ReID) network in the process of cascade matching, we introduced Spatial Relation-aware… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2689-2705, 2023, DOI:10.32604/csse.2023.039904
Abstract Hyperspectral images can easily discriminate different materials due to their fine spectral resolution. However, obtaining a hyperspectral image (HSI) with a high spatial resolution is still a challenge as we are limited by the high computing requirements. The spatial resolution of HSI can be enhanced by utilizing Deep Learning (DL) based Super-resolution (SR). A 3D-CNNHSR model is developed in the present investigation for 3D spatial super-resolution for HSI, without losing the spectral content. The 3D-CNNHSR model was tested for the Hyperion HSI. The pre-processing of the HSI was done before applying the SR model so that the full advantage of… More >
Open Access
ARTICLE
Computer Systems Science and Engineering, Vol.47, No.2, pp. 2707-2724, 2023, DOI:10.32604/csse.2023.037351
Abstract Predicting the usage of container cloud resources has always been an important and challenging problem in improving the performance of cloud resource clusters. We proposed an integrated prediction method of stacking container cloud resources based on variational modal decomposition (VMD)-Permutation entropy (PE) and long short-term memory (LSTM) neural network to solve the prediction difficulties caused by the non-stationarity and volatility of resource data. The variational modal decomposition algorithm decomposes the time series data of cloud resources to obtain intrinsic mode function and residual components, which solves the signal decomposition algorithm’s end-effect and modal confusion problems. The permutation entropy is used… More >
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