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J. Prabakaran^1,*, P. Selvaraj²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2141-2157, 2023, DOI:10.32604/csse.2023.034210
Abstract In healthcare systems, the Internet of Things (IoT) innovation and development approached new ways to evaluate patient data. A cloud-based platform tends to process data generated by IoT medical devices instead of high storage, and computational hardware. In this paper, an intelligent healthcare system has been proposed for the prediction and severity analysis of lung disease from chest computer tomography (CT) images of patients with pneumonia, Covid-19, tuberculosis (TB), and cancer. Firstly, the CT images are captured and transmitted to the fog node through IoT devices. In the fog node, the image gets modified into a convenient and efficient format… More >

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C. Vairavel^1,*, N. S. Nithya²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2159-2175, 2023, DOI:10.32604/csse.2023.036598
Abstract The immune system goes through a profound transformation during pregnancy, and certain unexpected maternal complications have been correlated to this transition. The ability to correctly examine, diagnoses, and predict pregnancy-hastened diseases via the available big data is a delicate problem since the range of information continuously increases and is scalable. Many approaches for disease diagnosis/classification have been established with the use of data mining concepts. However, such methods do not provide an appropriate classification/diagnosis model. Furthermore, single learning approaches are used to create the bulk of these systems. Classification issues may be made more accurate by combining predictions from many… More >

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332

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A. Ramachandran^1,*, K. Gayathri², Ahmed Alkhayyat³, Rami Q. Malik⁴
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2177-2194, 2023, DOI:10.32604/csse.2023.034438
Abstract Cyber-physical system (CPS) is a concept that integrates every computer-driven system interacting closely with its physical environment. Internet-of-things (IoT) is a union of devices and technologies that provide universal interconnection mechanisms between the physical and digital worlds. Since the complexity level of the CPS increases, an adversary attack becomes possible in several ways. Assuring security is a vital aspect of the CPS environment. Due to the massive surge in the data size, the design of anomaly detection techniques becomes a challenging issue, and domain-specific knowledge can be applied to resolve it. This article develops an Aquila Optimizer with Parameter Tuned… More >

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504

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Naseer Ahmed Sajid¹, Munir Ahmad¹, Atta-ur Rahman^2,*, Gohar Zaman³, Mohammed Salih Ahmed⁴, Nehad Ibrahim², Mohammed Imran B. Ahmed⁴, Gomathi Krishnasamy⁶, Reem Alzaher², Mariam Alkharraa², Dania AlKhulaifi², Maryam AlQahtani², Asiya A. Salam⁶, Linah Saraireh⁵, Mohammed Gollapalli⁶, Rashad Ahmed⁷
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2195-2214, 2023, DOI:10.32604/csse.2023.033844
Abstract From the beginning, the process of research and its publication is an ever-growing phenomenon and with the emergence of web technologies, its growth rate is overwhelming. On a rough estimate, more than thirty thousand research journals have been issuing around four million papers annually on average. Search engines, indexing services, and digital libraries have been searching for such publications over the web. Nevertheless, getting the most relevant articles against the user requests is yet a fantasy. It is mainly because the articles are not appropriately indexed based on the hierarchies of granular subject classification. To overcome this issue, researchers are… More >

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Younghoon Ban, Jeong Hyun Yi, Haehyun Cho^*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2215-2230, 2023, DOI:10.32604/csse.2023.036555
Abstract Android malware has evolved in various forms such as adware that continuously exposes advertisements, banking malware designed to access users’ online banking accounts, and Short Message Service (SMS) malware that uses a Command & Control (C&C) server to send malicious SMS, intercept SMS, and steal data. By using many malicious strategies, the number of malware is steadily increasing. Increasing Android malware threats numerous users, and thus, it is necessary to detect malware quickly and accurately. Each malware has distinguishable characteristics based on its actions. Therefore, security researchers have tried to categorize malware based on their behaviors by conducting the familial… More >

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Hae Sun Jung¹, Seon Hong Lee¹, Haein Lee¹, Jang Hyun Kim^2,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2231-2246, 2023, DOI:10.32604/csse.2023.034466
Abstract Predicting Bitcoin price trends is necessary because they represent the overall trend of the cryptocurrency market. As the history of the Bitcoin market is short and price volatility is high, studies have been conducted on the factors affecting changes in Bitcoin prices. Experiments have been conducted to predict Bitcoin prices using Twitter content. However, the amount of data was limited, and prices were predicted for only a short period (less than two years). In this study, data from Reddit and LexisNexis, covering a period of more than four years, were collected. These data were utilized to estimate and compare the… More >

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467

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N. Sharmili¹, Saud Yonbawi², Sultan Alahmari³, E. Laxmi Lydia⁴, Mohamad Khairi Ishak⁵, Hend Khalid Alkahtani^6,*, Ayman Aljarbouh⁷, Samih M. Mostafa⁸
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2247-2262, 2023, DOI:10.32604/csse.2023.036377
Abstract Facial expression recognition (FER) remains a hot research area among computer vision researchers and still becomes a challenge because of high intra-class variations. Conventional techniques for this problem depend on hand-crafted features, namely, LBP, SIFT, and HOG, along with that a classifier trained on a database of videos or images. Many execute perform well on image datasets captured in a controlled condition; however not perform well in the more challenging dataset, which has partial faces and image variation. Recently, many studies presented an endwise structure for facial expression recognition by utilizing DL methods. Therefore, this study develops an earthworm optimization… More >

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Amel Austine^*, R. Suji Pramila
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2263-2276, 2023, DOI:10.32604/csse.2023.032323
Abstract In a cellular network, direct Device-to-Device (D2D) communication enhances Quality of Service (QoS) in terms of coverage, throughput and amount of power consumed. Since the D2D pairs involve cellular resources for communication, the chances of interference are high. D2D communications demand minimum interference along with maximum throughput and sum rate which can be achieved by employing optimal resources and efficient power allocation procedures. In this research, a hybrid optimization model called Genetic Algorithm-Adaptive Bat Optimization (GA-ABO) algorithm is proposed for efficient resource allocation in a cellular network with D2D communication. Simulation analysis demonstrates that the proposed model involves reduced interference… More >

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336

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Junjie Zhou, Hongkui Xu^*, Zifeng Zhang, Jiangkun Lu, Wentao Guo, Zhenye Li
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2277-2297, 2023, DOI:10.32604/csse.2023.036419
Abstract Fraud cases have been a risk in society and people’s property security has been greatly threatened. In recent studies, many promising algorithms have been developed for social media offensive text recognition as well as sentiment analysis. These algorithms are also suitable for fraudulent phone text recognition. Compared to these tasks, the semantics of fraudulent words are more complex and more difficult to distinguish. Recurrent Neural Networks (RNN), the variants of RNN, Convolutional Neural Networks (CNN), and hybrid neural networks to extract text features are used by most text classification research. However, a single network or a simple network combination cannot… More >

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354

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Mohamed Ezz, Waad Alanazi, Ayman Mohamed Mostafa^*, Eslam Hamouda, Murtada K. Elbashir, Meshrif Alruily
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2299-2317, 2023, DOI:10.32604/csse.2023.036567
Abstract Palmprint identification has been conducted over the last two decades in many biometric systems. High-dimensional data with many uncorrelated and duplicated features remains difficult due to several computational complexity issues. This paper presents an interactive authentication approach based on deep learning and feature selection that supports Palmprint authentication. The proposed model has two stages of learning; the first stage is to transfer pre-trained VGG-16 of ImageNet to specific features based on the extraction model. The second stage involves the VGG-16 Palmprint feature extraction in the Siamese network to learn Palmprint similarity. The proposed model achieves robust and reliable end-to-end Palmprint… More >

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380

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Saud Yonbawi¹, Sultan Alahmari², B. R. S. S. Raju³, Chukka Hari Govinda Rao⁴, Mohamad Khairi Ishak⁵, Hend Khalid Alkahtani⁶, José Varela-Aldás^7,*, Samih M. Mostafa⁸
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2319-2335, 2023, DOI:10.32604/csse.2023.036721
Abstract Artificial intelligence (AI) technologies and sensors have recently received significant interest in intellectual agriculture. Accelerating the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart agriculture. Automatic irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation techniques. Automatic learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an agronomist. With this motivation, this study develops a modified black widow optimization with a… More >

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Basanta Kumar Swain¹, Mohammad Zubair Khan^2,*, Chiranji Lal Chowdhary³, Abdullah Alsaeedi⁴
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2337-2349, 2023, DOI:10.32604/csse.2023.036192
Abstract This research is focused on a highly effective and untapped feature called gammatone frequency cepstral coefficients (GFCC) for the detection of COVID-19 by using the nature-inspired meta-heuristic algorithm of deer hunting optimization and artificial neural network (DHO-ANN). The noisy crowdsourced cough datasets were collected from the public domain. This research work claimed that the GFCC yielded better results in terms of COVID-19 detection as compared to the widely used Mel-frequency cepstral coefficient in noisy crowdsourced speech corpora. The proposed algorithm's performance for detecting COVID-19 disease is rigorously validated using statistical measures, F1 score, confusion matrix, specificity, and sensitivity parameters. Besides,… More >

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Kainat Ibrar¹, Abdul Muiz Fayyaz¹, Muhammad Attique Khan², Majed Alhaisoni³, Usman Tariq⁴, Seob Jeon⁵, Yunyoung Nam^6,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2351-2368, 2023, DOI:10.32604/csse.2023.036185
Abstract Human personality assessment using gait pattern recognition is one of the most recent and exciting research domains. Gait is a person’s identity that can reflect reliable information about his mood, emotions, and substantial personality traits under scrutiny. This research focuses on recognizing key personality traits, including neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness, in line with the big-five model of personality. We inferred personality traits based on the gait pattern recognition of individuals utilizing built-in smartphone sensors. For experimentation, we collected a novel dataset of 22 participants using an android application and further segmented it into six data chunks… More >

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Hoon Ko¹, Chul Park², Wu Seong Kang³, Yunyoung Nam⁴, Dukyong Yoon⁵, Jinseok Lee^1,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2369-2381, 2023, DOI:10.32604/csse.2023.035641
Abstract Adequate oxygen in red blood cells carrying through the body to the heart and brain is important to maintain life. For those patients requiring blood, blood transfusion is a common procedure in which donated blood or blood components are given through an intravenous line. However, detecting the need for blood transfusion is time-consuming and sometimes not easily diagnosed, such as internal bleeding. This study considered physiological signals such as electrocardiogram (ECG), photoplethysmogram (PPG), blood pressure, oxygen saturation (SpO2), and respiration, and proposed the machine learning model to detect the need for blood transfusion accurately. For the model, this study extracted… More >

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319

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Lingyun Xiang^1,*, Rong Wang¹, Yuhang Liu¹, Yangfan Liu¹, Lina Tan^2,3
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2383-2399, 2023, DOI:10.32604/csse.2023.037067
Abstract Prevailing linguistic steganalysis approaches focus on learning sensitive features to distinguish a particular category of steganographic texts from non-steganographic texts, by performing binary classification. While it remains an unsolved problem and poses a significant threat to the security of cyberspace when various categories of non-steganographic or steganographic texts coexist. In this paper, we propose a general linguistic steganalysis framework named LS-MTL, which introduces the idea of multi-task learning to deal with the classification of various categories of steganographic and non-steganographic texts. LS-MTL captures sensitive linguistic features from multiple related linguistic steganalysis tasks and can concurrently handle diverse tasks with a… More >

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750

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Mohammed S. Alshehri¹, Sultan Almakdi^1,*, Mimonah Al Qathrady², Jawad Ahmad³
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2401-2414, 2023, DOI:10.32604/csse.2023.036152
Abstract Chaos-based cryptosystems are considered a secure mode of communication due to their reliability. Chaotic maps are associated with the other domains to construct robust encryption algorithms. There exist numerous encryption schemes in the literature based on chaotic maps. This work aims to propose an attack on a recently proposed hyper-chaotic map-based cryptosystem. The core notion of the original algorithm was based on permutation and diffusion. A bit-level permutation approach was used to do the permutation row-and column-wise. The diffusion was executed in the forward and backward directions. The statistical strength of the cryptosystem has been demonstrated by extensive testing conducted… More >

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402

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Muhammad Rizwan Rashid Rana^1,*, Saif Ur Rehman¹, Asif Nawaz¹, Tariq Ali¹, Azhar Imran², Abdulkareem Alzahrani³, Abdullah Almuhaimeed^4,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2415-2428, 2023, DOI:10.32604/csse.2023.035149
Abstract People utilize microblogs and other social media platforms to express their thoughts and feelings regarding current events, public products and the latest affairs. People share their thoughts and feelings about various topics, including products, news, blogs, etc. In user reviews and tweets, sentiment analysis is used to discover opinions and feelings. Sentiment polarity is a term used to describe how sentiment is represented. Positive, neutral and negative are all examples of it. This area is still in its infancy and needs several critical upgrades. Slang and hidden emotions can detract from the accuracy of traditional techniques. Existing methods only evaluate… More >

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Tariq Ahamed Ahanger^1,*, Fadl Dahan^2,3, Usman Tariq¹
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2429-2445, 2023, DOI:10.32604/csse.2023.037692
Abstract In the Internet of Things (IoT), the users have complex needs, and the Web Service Composition (WSC) was introduced to address these needs. The WSC’s main objective is to search for the optimal combination of web services in response to the user needs and the level of Quality of Services (QoS) constraints. The challenge of this problem is the huge number of web services that achieve similar functionality with different levels of QoS constraints. In this paper, we introduce an extension of our previous works on the Artificial Bee Colony (ABC) and Bat Algorithm (BA). A new hybrid algorithm was… More >

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Mingguang Yu^1,2, Xia Zhang^1,2,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2447-2469, 2023, DOI:10.32604/csse.2023.037506
Abstract Modern cloud services are monitored by numerous multidomain and multivendor monitoring tools, which generate massive numbers of alerts and events that are not actionable. These alerts usually carry isolated messages that are missing service contexts. Administrators become inundated with tickets caused by such alert events when they are routed directly to incident management systems. Noisy alerts increase the risk of crucial warnings going undetected and leading to service outages. One of the feasible ways to cope with the above problems involves revealing the correlations behind a large number of alerts and then aggregating the related alerts according to their correlations.… More >

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Ansar Munir Shah¹, Mohammed Aljubayri², Muhammad Faheem Khan¹, Jarallah Alqahtani^2,*, Mahmood ul Hassan³, Adel Sulaiman², Asadullah Shaikh²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2471-2488, 2023, DOI:10.32604/csse.2023.034951
Abstract In the network field, Wireless Sensor Networks (WSN) contain prolonged attention due to afresh augmentations. Industries like health care, traffic, defense, and many more systems espoused the WSN. These networks contain tiny sensor nodes containing embedded processors, Tiny OS, memory, and power source. Sensor nodes are responsible for forwarding the data packets. To manage all these components, there is a need to select appropriate parameters which control the quality of service of WSN. Multiple sensor nodes are involved in transmitting vital information, and there is a need for secure and efficient routing to reach the quality of service. But due… More >

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4

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MD. Yasar Arafath^1,*, A. Niranjil Kumar²
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2489-2508, 2023, DOI:10.32604/csse.2023.035732
Abstract For intelligent surveillance videos, anomaly detection is extremely important. Deep learning algorithms have been popular for evaluating real-time surveillance recordings, like traffic accidents, and criminal or unlawful incidents such as suicide attempts. Nevertheless, Deep learning methods for classification, like convolutional neural networks, necessitate a lot of computing power. Quantum computing is a branch of technology that solves abnormal and complex problems using quantum mechanics. As a result, the focus of this research is on developing a hybrid quantum computing model which is based on deep learning. This research develops a Quantum Computing-based Convolutional Neural Network (QC-CNN) to extract features and… More >

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420

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Salahahaldeen Duraibi^*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2509-2525, 2023, DOI:10.32604/csse.2023.036119
Abstract With the growth of the discipline of digital communication, the topic has acquired more attention in the cybersecurity medium. The Intrusion Detection (ID) system monitors network traffic to detect malicious activities. The paper introduces a novel Feature Selection (FS) approach for ID. Reptile Search Algorithm (RSA)—is a new optimization algorithm; in this method, each agent searches a new region according to the position of the host, which makes the algorithm suffers from getting stuck in local optima and a slow convergence rate. To overcome these problems, this study introduces an improved RSA approach by integrating Cauchy Mutation (CM) into the… More >

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405

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Ahmed Najat Ahmed¹, JinHyung Kim², Yunyoung Nam^3,*, Mohamed Abouhawwash^4,5
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2527-2542, 2023, DOI:10.32604/csse.2023.036106
Abstract In this current century, most industries are moving towards automation, where human intervention is dramatically reduced. This revolution leads to industrial revolution 4.0, which uses the Internet of Things (IoT) and wireless sensor networks (WSN). With its associated applications, this IoT device is used to compute the received WSN data from devices and transfer it to remote locations for assistance. In general, WSNs, the gateways are a long distance from the base station (BS) and are communicated through the gateways nearer to the BS. At the gateway, which is closer to the BS, energy drains faster because of the heavy… More >

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461

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Sungjin Lee¹, Ahyoung Lee², Min Hong^3,*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2543-2554, 2023, DOI:10.32604/csse.2023.037055
Abstract Specific medical data has limitations in that there are not many numbers and it is not standardized. to solve these limitations, it is necessary to study how to efficiently process these limited amounts of data. In this paper, deep learning methods for automatically determining cardiovascular diseases are described, and an effective preprocessing method for CT images that can be applied to improve the performance of deep learning was conducted. The cardiac CT images include several parts of the body such as the heart, lungs, spine, and ribs. The preprocessing step proposed in this paper divided CT image data into regions… More >

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Aisha M. Mashraqi, Hanan T. Halawani^*
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2555-2570, 2023, DOI:10.32604/csse.2023.031246
Abstract Sentiment Analysis (SA) is one of the Machine Learning (ML) techniques that has been investigated by several researchers in recent years, especially due to the evolution of novel data collection methods focused on social media. In literature, it has been reported that SA data is created for English language in excess of any other language. It is challenging to perform SA for Arabic Twitter data owing to informal nature and rich morphology of Arabic language. An earlier study conducted upon SA for Arabic Twitter focused mostly on automatic extraction of the features from the text. Neural word embedding has been… More >

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305

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S. Kavi Priya^*, N. Saranya
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2571-2587, 2023, DOI:10.32604/csse.2023.031761
Abstract Around the globe, chronic diseases pose a serious hazard to healthcare communities. The majority of the deaths are due to chronic diseases, and it causes burdens across the world. Through analyzing healthcare data and extracting patterns healthcare administrators, victims, and healthcare communities will get an advantage if the diseases are early predicted. The majority of the existing works focused on increasing the accuracy of the techniques but didn’t concentrate on other performance measures. Thus, the proposed work improves the early detection of chronic disease and safeguards the lives of the patients by increasing the specificity and sensitivity of the classifiers… More >

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P. M. Siva Raja^1,*, S. Brinthakumari², K. Ramanan³
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2589-2599, 2023, DOI:10.32604/csse.2023.028542
Abstract Brain tumor detection and division is a difficult tedious undertaking in clinical image preparation. When it comes to the new technology that enables accurate identification of the mysterious tissues of the brain, magnetic resonance imaging (MRI) is a great tool. It is possible to alter the tumor’s size and shape at any time for any number of patients by using the Brain picture. Radiologists have a difficult time sorting and classifying tumors from multiple images. Brain tumors may be accurately detected using a new approach called Nonlinear Teager-Kaiser Iterative Infomax Boost Clustering-Based Image Segmentation (NTKFIBC-IS). Teager-Kaiser filtering is used to… More >

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V. P. Nithya^*, N. Mohanasundaram, R. Santhosh
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2601-2618, 2023, DOI:10.32604/csse.2023.030503
Abstract The prediction of mild cognitive impairment or Alzheimer’s disease (AD) has gained the attention of huge researchers as the disease occurrence is increasing, and there is a need for earlier prediction. Regrettably, due to the high-dimensionality nature of neural data and the least available samples, modelling an efficient computer diagnostic system is highly solicited. Learning approaches, specifically deep learning approaches, are essential in disease prediction. Deep Learning (DL) approaches are successfully demonstrated for their higher-level performance in various fields like medical imaging. A novel 3D-Convolutional Neural Network (3D-CNN) architecture is proposed to predict AD with Magnetic resonance imaging (MRI) data.… More >

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Manar Ahmed Hamza^1,*, Hala J. Alshahrani², Jaber S. Alzahrani³, Heba Mohsen⁴, Mohamed I. Eldesouki⁵, Mohammed Rizwanullah¹
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2619-2635, 2023, DOI:10.32604/csse.2023.034519
Abstract Aspect-Based Sentiment Analysis (ABSA) on Arabic corpus has become an active research topic in recent days. ABSA refers to a fine-grained Sentiment Analysis (SA) task that focuses on the extraction of the conferred aspects and the identification of respective sentiment polarity from the provided text. Most of the prevailing Arabic ABSA techniques heavily depend upon dreary feature-engineering and pre-processing tasks and utilize external sources such as lexicons. In literature, concerning the Arabic language text analysis, the authors made use of regular Machine Learning (ML) techniques that rely on a group of rare sources and tools. These sources were used for… More >

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Amr Abozeid^1,*, Ahmed I. Taloba^1,2, Rasha M. Abd El-Aziz^1,3, Alhanoof Faiz Alwaghid¹, Mostafa Salem³, Ahmed Elhadad^1,4
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2637-2650, 2023, DOI:10.32604/csse.2023.037761
Abstract Indoor localization methods can help many sectors, such as healthcare centers, smart homes, museums, warehouses, and retail malls, improve their service areas. As a result, it is crucial to look for low-cost methods that can provide exact localization in indoor locations. In this context, image-based localization methods can play an important role in estimating both the position and the orientation of cameras regarding an object. Image-based localization faces many issues, such as image scale and rotation variance. Also, image-based localization’s accuracy and speed (latency) are two critical factors. This paper proposes an efficient 6-DoF deep-learning model for image-based localization. This… More >

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