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R. Bhaskaran¹, P. S. Sujith Kumar², G. Shanthi³, L. Raja⁴, Gyanendra Prasad Joshi⁵, Woong Cho^6,*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 1-17, 2023, DOI:10.32604/csse.2023.024973
Abstract In recent times, real time wireless networks have found their applicability in several practical applications such as smart city, healthcare, surveillance, environmental monitoring, etc. At the same time, proper localization of nodes in real time wireless networks helps to improve the overall functioning of networks. This study presents an Improved Metaheuristics based Energy Efficient Clustering with Node Localization (IM-EECNL) approach for real-time wireless networks. The proposed IM-EECNL technique involves two major processes namely node localization and clustering. Firstly, Chaotic Water Strider Algorithm based Node Localization (CWSANL) technique to determine the unknown position of the nodes. Secondly, an Oppositional Archimedes Optimization… More >

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P. Vasuki^*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 19-33, 2023, DOI:10.32604/csse.2023.024441
Abstract Automatic Speech Emotion Recognition (SER) is used to recognize emotion from speech automatically. Speech Emotion recognition is working well in a laboratory environment but real-time emotion recognition has been influenced by the variations in gender, age, the cultural and acoustical background of the speaker. The acoustical resemblance between emotional expressions further increases the complexity of recognition. Many recent research works are concentrated to address these effects individually. Instead of addressing every influencing attribute individually, we would like to design a system, which reduces the effect that arises on any factor. We propose a two-level Hierarchical classifier named Interpreter of responses… More >

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722

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Mahmoud M. Khattab^1,2,*, Akram M Zeki¹, Ali A. Alwan³, Belgacem Bouallegue², Safaa S. Matter⁴, Abdelmoty M. Ahmed²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 35-54, 2023, DOI:10.32604/csse.2023.025251
Abstract The prime purpose for the image reconstruction of a multi-frame super-resolution is to reconstruct a higher-resolution image through incorporating the knowledge obtained from a series of relevant low-resolution images, which is useful in numerous fields. Nevertheless, super-resolution image reconstruction methods are usually damaged by undesirable restorative artifacts, which include blurring distortion, noises, and stair-casing effects. Consequently, it is always challenging to achieve balancing between image smoothness and preservation of the edges inside the image. In this research work, we seek to increase the effectiveness of multi-frame super-resolution image reconstruction by increasing the visual information and improving the automated machine perception,… More >

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P. Gnanasivam¹, G. T. Bharathy^1,*, V. Rajendran², T. Tamilselvi¹
Computer Systems Science and Engineering, Vol.44, No.1, pp. 55-65, 2023, DOI:10.32604/csse.2023.023374
Abstract Wireless Communication is a system for communicating information from one point to other, without utilizing any connections like wire, cable, or other physical medium. Cognitive Radio (CR) based systems and networks are a revolutionary new perception in wireless communications. Spectrum sensing is a vital task of CR to avert destructive intrusion with licensed primary or main users and discover the accessible spectrum for the efficient utilization of the spectrum. Centralized Cooperative Spectrum Sensing (CSS) is a kind of spectrum sensing. Most of the test metrics designed till now for sensing the spectrum is produced by using the Sample Covariance Matrix… More >

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639

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Saraswathi Shunmuganathan^*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 67-79, 2023, DOI:10.32604/csse.2023.023858
Abstract The exponential advancement in telecommunication embeds the Internet in every aspect of communication. Interconnections of networks all over the world impose monumental risks on the Internet. A Flooding Attack (FA) is one of the major intimidating risks on the Internet where legitimate users are prevented from accessing network services. Irrespective of the protective measures incorporated in the communication infrastructure, FA still persists due to the lack of global cooperation. Most of the existing mitigation is set up either at the traffic starting point or at the traffic ending point. Providing mitigation at one or the other end may not be… More >

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711

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Joe Louis Paul Ignatius^1,*, Sasirekha Selvakumar¹, Kavin Gabriel Joe Louis Paul², Aadhithya B. Kailash¹, S. Keertivaas¹, S. A. J. Akarvin Raja Prajan¹
Computer Systems Science and Engineering, Vol.44, No.1, pp. 81-97, 2023, DOI:10.32604/csse.2023.025195
Abstract Tuberculosis (TB) is a severe infection that mostly affects the lungs and kills millions of people’s lives every year. Tuberculosis can be diagnosed using chest X-rays (CXR) and data-driven deep learning (DL) approaches. Because of its better automated feature extraction capability, convolutional neural networks (CNNs) trained on natural images are particularly effective in image categorization. A combination of 3001 normal and 3001 TB CXR images was gathered for this study from different accessible public datasets. Ten different deep CNNs (Resnet50, Resnet101, Resnet152, InceptionV3, VGG16, VGG19, DenseNet121, DenseNet169, DenseNet201, MobileNet) are trained and tested for identifying TB and normal cases. This… More >

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742

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D. Loganathan^1,*, M. Balasubramani¹, R. Sabitha², S. Karthik²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 99-112, 2023, DOI:10.32604/csse.2023.023120
Abstract Sensors are considered as important elements of electronic devices. In many applications and service, Wireless Sensor Networks (WSNs) are involved in significant data sharing that are delivered to the sink node in energy efficient manner using multi-hop communications. But, the major challenge in WSN is the nodes are having limited battery resources, it is important to monitor the consumption rate of energy is very much needed. However, reducing energy consumption can increase the network lifetime in effective manner. For that, clustering methods are widely used for optimizing the rate of energy consumption among the sensor nodes. In that concern, this… More >

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546

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Aakib Jawed Khan^*, Shabana Mehfuz
Computer Systems Science and Engineering, Vol.44, No.1, pp. 113-128, 2023, DOI:10.32604/csse.2023.023378
Abstract Cloud computing belongs to a set of policies, protocols, technologies through which one can access shared resources such as storage, applications, networks, and services at relatively low cost. Despite the tremendous advantages of cloud computing, one big threat which must be taken care of is data security in the cloud. There are a dozen of threats that we are being exposed to while availing cloud services. Insufficient identity and access management, insecure interfaces and Applications interfaces (APIs), hijacking, advanced persistent threats, data threats, and many more are certain security issues with the cloud platform. APIs and service providers face a… More >

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664

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Fuad A. M. Al-Yarimi^*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 129-142, 2023, DOI:10.32604/csse.2023.024297
Abstract A critical component of dealing with heart disease is real-time identification, which triggers rapid action. The main challenge of real-time identification is illustrated here by the rare occurrence of cardiac arrhythmias. Recent contributions to cardiac arrhythmia prediction using supervised learning approaches generally involve the use of demographic features (electronic health records), signal features (electrocardiogram features as signals), and temporal features. Since the signal of the electrical activity of the heartbeat is very sensitive to differences between high and low heartbeats, it is possible to detect some of the irregularities in the early stages of arrhythmia. This paper describes the training… More >

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638

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M. Hema^1,*, S. Kanaga Suba Raja²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 143-156, 2023, DOI:10.32604/csse.2023.024895
Abstract In cloud data centers, the consolidation of workload is one of the phases during which the available hosts are allocated tasks. This phenomenon ensures that the least possible number of hosts is used without compromise in meeting the Service Level Agreement (SLA). To consolidate the workloads, the hosts are segregated into three categories: normal hosts, under-loaded hosts, and overloaded hosts based on their utilization. It is to be noted that the identification of an extensively used host or underloaded host is challenging to accomplish. Threshold values were proposed in the literature to detect this scenario. The current study aims to… More >

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524

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J. S. Sujin^1,*, S. Sophia²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 157-171, 2023, DOI:10.32604/csse.2023.023747
Abstract Digital picture forgery detection has recently become a popular and significant topic in image processing. Due to advancements in image processing and the availability of sophisticated software, picture fabrication may hide evidence and hinder the detection of such criminal cases. The practice of modifying original photographic images to generate a forged image is known as digital image forging. A section of an image is copied and pasted into another part of the same image to hide an item or duplicate particular image elements in copy-move forgery. In order to make the forgeries real and inconspicuous, geometric or post-processing techniques are… More >

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B. Lalitha^1,*, V. Gomathi²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 173-189, 2023, DOI:10.32604/csse.2023.024118
Abstract IC (Image Captioning) is a crucial part of Visual Data Processing and aims at understanding for providing captions that verbalize an image’s important elements. However, in existing works, because of the complexity in images, neglecting major relation between the object in an image, poor quality image, labelling it remains a big problem for researchers. Hence, the main objective of this work attempts to overcome these challenges by proposing a novel framework for IC. So in this research work the main contribution deals with the framework consists of three phases that is image understanding, textual understanding and decoding. Initially, the image… More >

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569

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Deependra Sharma^*, Zainul Abdin Jaffery
Computer Systems Science and Engineering, Vol.44, No.1, pp. 191-204, 2023, DOI:10.32604/csse.2023.023728
Abstract This paper discusses about the new approach of multiple object tracking relative to background information. The concept of multiple object tracking through background learning is based upon the theory of relativity, that involves a frame of reference in spatial domain to localize and/or track any object. The field of multiple object tracking has seen a lot of research, but researchers have considered the background as redundant. However, in object tracking, the background plays a vital role and leads to definite improvement in the overall process of tracking. In the present work an algorithm is proposed for the multiple object tracking… More >

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J. Jean Justus¹, U. Sakthi², K. Priyadarshini³, B. Thiyaneswaran⁴, Masoud Alajmi⁵, Marwa Obayya⁶, Manar Ahmed Hamza^7,*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 205-219, 2023, DOI:10.32604/csse.2023.025256
Abstract The developments of multi-core systems (MCS) have considerably improved the existing technologies in the field of computer architecture. The MCS comprises several processors that are heterogeneous for resource capacities, working environments, topologies, and so on. The existing multi-core technology unlocks additional research opportunities for energy minimization by the use of effective task scheduling. At the same time, the task scheduling process is yet to be explored in the multi-core systems. This paper presents a new hybrid genetic algorithm (GA) with a krill herd (KH) based energy-efficient scheduling technique for multi-core systems (GAKH-SMCS). The goal of the GAKH-SMCS technique is to… More >

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657

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İhsan Uluocak^1,*, Hakan Yavuz²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 221-234, 2023, DOI:10.32604/csse.2023.025426
Abstract The recent studies on Artificial Intelligence (AI) accompanied by enhanced computing capabilities supports increasing attention into traditional control methods coupled with AI learning methods in an attempt to bringing adaptiveness and fast responding features. The Model Predictive Control (MPC) technique is a widely used, safe and reliable control method based on constraints. On the other hand, the Eddy Current dynamometers are highly nonlinear braking systems whose performance parameters are related to many processes related variables. This study is based on an adaptive model predictive control that utilizes selected AI methods. The presented approach presents an updated the mathematical model of… More >

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504

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R. Bhaskaran^1,*, S. Saravanan¹, M. Kavitha², C. Jeyalakshmi³, Seifedine Kadry⁴, Hafiz Tayyab Rauf⁵, Reem Alkhammash⁶
Computer Systems Science and Engineering, Vol.44, No.1, pp. 235-247, 2023, DOI:10.32604/csse.2023.024399
Abstract Sentiment Analysis (SA) is one of the subfields in Natural Language Processing (NLP) which focuses on identification and extraction of opinions that exist in the text provided across reviews, social media, blogs, news, and so on. SA has the ability to handle the drastically-increasing unstructured text by transforming them into structured data with the help of NLP and open source tools. The current research work designs a novel Modified Red Deer Algorithm (MRDA) Extreme Learning Machine Sparse Autoencoder (ELMSAE) model for SA and classification. The proposed MRDA-ELMSAE technique initially performs preprocessing to transform the data into a compatible format. Moreover,… More >

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N. Dharini^1,*, Jeevaa Katiravan², S. M. Udhaya Sankar³
Computer Systems Science and Engineering, Vol.44, No.1, pp. 249-264, 2023, DOI:10.32604/csse.2023.024419
Abstract This work utilizes a statistical approach of Principal Component Analysis (PCA) towards the detection of Methane (CH₄)-Carbon Monoxide (CO) Poisoning occurring in coal mines, forest fires, drainage systems etc. where the CH₄ and CO emissions are very high in closed buildings or confined spaces during oxidation processes. Both methane and carbon monoxide are highly toxic, colorless and odorless gases. Both of the gases have their own toxic levels to be detected. But during their combined presence, the toxicity of the either one goes unidentified may be due to their low levels which may lead to an explosion. By using PCA,… More >

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770

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M. Rajakani^1,*, R. J. Kavitha², A. Ramachandran³
Computer Systems Science and Engineering, Vol.44, No.1, pp. 265-280, 2023, DOI:10.32604/csse.2023.024994
Abstract Feature extraction is the most critical step in classification of multispectral image. The classification accuracy is mainly influenced by the feature sets that are selected to classify the image. In the past, handcrafted feature sets are used which are not adaptive for different image domains. To overcome this, an evolutionary learning method is developed to automatically learn the spatial-spectral features for classification. A modified Firefly Algorithm (FA) which achieves maximum classification accuracy with reduced size of feature set is proposed to gain the interest of feature selection for this purpose. For extracting the most efficient features from the data set,… More >

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1404

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589

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R. Prabhu^1,*, S. Rajesh²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 281-295, 2023, DOI:10.32604/csse.2023.024339
Abstract Cloud computing distributes task-parallel among the various resources. Applications with self-service supported and on-demand service have rapid growth. For these applications, cloud computing allocates the resources dynamically via the internet according to user requirements. Proper resource allocation is vital for fulfilling user requirements. In contrast, improper resource allocations result to load imbalance, which leads to severe service issues. The cloud resources implement internet-connected devices using the protocols for storing, communicating, and computations. The extensive needs and lack of optimal resource allocating scheme make cloud computing more complex. This paper proposes an NMDS (Network Manager based Dynamic Scheduling) for achieving a… More >

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652

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J. Avila Selvi Therase^1,*, S. Allwin¹, A. Ahilan²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 297-309, 2023, DOI:10.32604/csse.2023.023515
Abstract Intelligent communication technologies beyond the network are proposed by using a new full-duplex protocol. The Media Access Control (MAC) is a data interaction network protocol, which outperforms the IEEE 802.15.4e. This research discusses the planning and execution of full-duplex (FD) pipeline MAC protocol for multihop wireless networks (MWN). The design uses a combination of Radio frequency and baseband methods to realize full-duplexing with smallest impact on cross layer functions. The execution and trial results specify that Pipeline Media Access Control (PiMAC) protocol considerably develops network implementation in terms of transmission protocol (TP) and transmission delay. The advantage of using FD-MAC… More >

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1169

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530

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Priti Shaw¹, Kaustubh Pachpor², Suresh Sankaranarayanan^3,*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 311-325, 2023, DOI:10.32604/csse.2023.025281
Abstract Neonatal sepsis is the third most common cause of neonatal mortality and a serious public health problem, especially in developing countries. There have been researches on human sepsis, vaccine response, and immunity. Also, machine learning methodologies were used for predicting infant mortality based on certain features like age, birth weight, gestational weeks, and Appearance, Pulse, Grimace, Activity and Respiration (APGAR) score. Sepsis, which is considered the most determining condition towards infant mortality, has never been considered for mortality prediction. So, we have deployed a deep neural model which is the state of art and performed a comparative analysis of machine… More >

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718

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K. Chitra^*, A. Tamilarasi
Computer Systems Science and Engineering, Vol.44, No.1, pp. 327-337, 2023, DOI:10.32604/csse.2023.023920
Abstract The structure and dynamic nature of real-world networks can be revealed by communities that help in promotion of recommendation systems. Social Media platforms were initially developed for effective communication, but now it is being used widely for extending and to obtain profit among business community. The numerous data generated through these platforms are utilized by many companies that make a huge profit out of it. A giant network of people in social media is grouped together based on their similar properties to form a community. Community detection is recent topic among the research community due to the increase usage of… More >

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762

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R. Rajadevi¹, K. Venkatachalam², Mehedi Masud³, Mohammed A. AlZain⁴, Mohamed Abouhawwash^5,6,*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 339-350, 2023, DOI:10.32604/csse.2023.024537
Abstract The Internet of Medical Things (IoMT) is an online device that senses and transmits medical data from users to physicians within a time interval. In, recent years, IoMT has rapidly grown in the medical field to provide healthcare services without physical appearance. With the use of sensors, IoMT applications are used in healthcare management. In such applications, one of the most important factors is data security, given that its transmission over the network may cause obtrusion. For data security in IoMT systems, blockchain is used due to its numerous blocks for secure data storage. In this study, Blockchain-assisted secure data… More >

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571

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Iyyappan. M¹, Arvind Kumar¹, Sultan Ahmad^2,*, Sudan Jha³, Bader Alouffi⁴, Abdullah Alharbi⁵
Computer Systems Science and Engineering, Vol.44, No.1, pp. 351-365, 2023, DOI:10.32604/csse.2023.025163
Abstract Component-based software engineering is concerned with the development of software that can satisfy the customer prerequisites through reuse or independent development. Coupling and cohesion measurements are primarily used to analyse the better software design quality, increase the reliability and reduced system software complexity. The complexity measurement of cohesion and coupling component to analyze the relationship between the component module. In this paper, proposed the component selection framework of Hexa-oval optimization algorithm for selecting the suitable components from the repository. It measures the interface density modules of coupling and cohesion in a modular software system. This cohesion measurement has been taken… More >

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784

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S. Meenakshi Ammal^*, P. S. Manoharan
Computer Systems Science and Engineering, Vol.44, No.1, pp. 367-390, 2023, DOI:10.32604/csse.2023.025230
Abstract Worldwide, many elders are suffering from Alzheimer’s disease (AD). The elders with AD exhibit various abnormalities in their activities, such as sleep disturbances, wandering aimlessly, forgetting activities, etc., which are the strong signs and symptoms of AD progression. Recognizing these symptoms in advance could assist to a quicker diagnosis and treatment and to prevent the progression of Disease to the next stage. The proposed method aims to detect the behavioral abnormalities found in Daily activities of AD patients (ADP) using wearables. In the proposed work, a publicly available dataset collected using wearables is applied. Currently, no real-world data is available… More >

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727

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R. Krishnaswamy¹, Kamalraj Subramaniam², V. Nandini³, K. Vijayalakshmi⁴, Seifedine Kadry⁵, Yunyoung Nam^6,*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 391-406, 2023, DOI:10.32604/csse.2023.024901
Abstract Recently, a massive quantity of data is being produced from a distinct number of sources and the size of the daily created on the Internet has crossed two Exabytes. At the same time, clustering is one of the efficient techniques for mining big data to extract the useful and hidden patterns that exist in it. Density-based clustering techniques have gained significant attention owing to the fact that it helps to effectively recognize complex patterns in spatial dataset. Big data clustering is a trivial process owing to the increasing quantity of data which can be solved by the use of Map… More >

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Basit Shahzad¹, Wardah Naeem Awan^1,*, Fazal-e-Amin², Ahsanullah Abro³, Muhammad Shoaib⁴, Sultan Alyahya⁴
Computer Systems Science and Engineering, Vol.44, No.1, pp. 407-422, 2023, DOI:10.32604/csse.2023.022601
Abstract There is an emerging interest in using agile methodologies in Global Software Development (GSD) to get the mutual benefits of both methods. Scrum is currently admired by many development teams as an agile most known methodology and considered adequate for collocated teams. At the same time, stakeholders in GSD are dispersed by geographical, temporal, and socio-cultural distances. Due to the controversial nature of Scrum and GSD, many significant challenges arise that might restrict the use of Scrum in GSD. We conducted a Systematic Literature Review (SLR) by following Kitchenham guidelines to identify the challenges that limit the use of Scrum… More >

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Devakirubai Navulkumar^1,*, Menakadevi Thangavelu²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 423-440, 2023, DOI:10.32604/csse.2023.025166
Abstract Nomadic Vehicular Cloud (NVC) is envisaged in this work. The predominant aspects of NVC is, it moves along with the vehicle that initiates it and functions only with the resources of moving vehicles on the heavy traffic road without relying on any of the static infrastructure and NVC decides the initiation time of container migration using cell transmission model (CTM). Containers are used in the place of Virtual Machines (VM), as containers’ features are very apt to NVC’s dynamic environment. The specifications of 5G NR V2X PC5 interface are applied to NVC, for the feature of not relying on the… More >

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738

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R. Ganesh Babu^1,*, D. Hemanand², V. Amudha³, S. Sugumaran⁴
Computer Systems Science and Engineering, Vol.44, No.1, pp. 441-456, 2023, DOI:10.32604/csse.2023.024049
Abstract In recent decades, several optimization algorithms have been developed for selecting the most energy efficient clusters in order to save power during transmission to a shorter distance while restricting the Primary Users (PUs) interference. The Cognitive Radio (CR) system is based on the Adaptive Swarm Distributed Intelligent based Clustering algorithm (ASDIC) that shows better spectrum sensing among group of multiusers in terms of sensing error, power saving, and convergence time. In this research paper, the proposed ASDIC algorithm develops better energy efficient distributed cluster based sensing with the optimal number of clusters on their connectivity. In this research, multiple random… More >

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D. Palanikkumar¹, Adel Fahad Alrasheedi², P. Parthasarathi³, S. S. Askar², Mohamed Abouhawwash^4,5,*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 457-469, 2023, DOI:10.32604/csse.2023.024884
Abstract Data management becomes essential component of patient healthcare. Internet of Medical Things (IoMT) performs a wireless communication between E-medical applications and human being. Instead of consulting a doctor in the hospital, patients get health related information remotely from the physician. The main issues in the E-Medical application are lack of safety, security and privacy preservation of patient’s health care data. To overcome these issues, this work proposes block chain based IoMT Processed with Hybrid consensus protocol for secured storage. Patients health data is collected from physician, smart devices etc. The main goal is to store this highly valuable health related… More >

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687

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Son-Lam VU, Quang-Hung LE^*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 471-483, 2023, DOI:10.32604/csse.2023.025897
Abstract Recommender systems are similar to an information filtering system that helps identify items that best satisfy the users’ demands based on their preference profiles. Context-aware recommender systems (CARSs) and multi-criteria recommender systems (MCRSs) are extensions of traditional recommender systems. CARSs have integrated additional contextual information such as time, place, and so on for providing better recommendations. However, the majority of CARSs use ratings as a unique criterion for building communities. Meanwhile, MCRSs utilize user preferences in multiple criteria to better generate recommendations. Up to now, how to exploit context in MCRSs is still an open issue. This paper proposes a… More >

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983

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K. Sailaja Kumar^*, H. K. Manoj, D. Evangelin Geetha
Computer Systems Science and Engineering, Vol.44, No.1, pp. 485-499, 2023, DOI:10.32604/csse.2023.025390
Abstract Standalone systems cannot handle the giant traffic loads generated by Twitter due to memory constraints. A parallel computational environment provided by Apache Hadoop can distribute and process the data over different destination systems. In this paper, the Hadoop cluster with four nodes integrated with RHadoop, Flume, and Hive is created to analyze the tweets gathered from the Twitter stream. Twitter stream data is collected relevant to an event/topic like IPL- 2015, cricket, Royal Challengers Bangalore, Kohli, Modi, from May 24 to 30, 2016 using Flume. Hive is used as a data warehouse to store the streamed tweets. Twitter analytics like… More >

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575

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K. Nagalakshmi^1,*, S. Dr. Suriya²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 501-517, 2023, DOI:10.32604/csse.2023.022687
Abstract Breast cancer is one of the deadly diseases prevailing in women. Earlier detection and diagnosis might prevent the death rate. Effective diagnosis of breast cancer remains a significant challenge, and early diagnosis is essential to avoid the most severe manifestations of the disease. The existing systems have computational complexity and classification accuracy problems over various breast cancer databases. In order to overcome the above-mentioned issues, this work introduces an efficient classification and segmentation process. Hence, there is a requirement for developing a fully automatic methodology for screening the cancer regions. This paper develops a fully automated method for breast cancer… More >

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Md. Saiful Islam, Shuvo Jyoti Das, Md. Riajul Alam Khan, Sifat Momen^*, Nabeel Mohammed
Computer Systems Science and Engineering, Vol.44, No.1, pp. 519-534, 2023, DOI:10.32604/csse.2023.025282
Abstract COVID-19 has created a panic all around the globe. It is a contagious disease caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), originated from Wuhan in December 2019 and spread quickly all over the world. The healthcare sector of the world is facing great challenges tackling COVID cases. One of the problems many have witnessed is the misdiagnosis of COVID-19 cases with that of healthy and pneumonia cases. In this article, we propose a deep Convolutional Neural Network (CNN) based approach to detect COVID+ (i.e., patients with COVID-19), pneumonia and normal cases, from the chest X-ray images. COVID-19 detection… More >

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Nguyen Tu Trung^1,*, Tran Thi Ngan¹, Tran Manh Tuan¹, To Huu Nguyen²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 535-544, 2023, DOI:10.32604/csse.2023.026011
Abstract Fusing medical images is a topic of interest in processing medical images. This is achieved to through fusing information from multimodality images for the purpose of increasing the clinical diagnosis accuracy. This fusion aims to improve the image quality and preserve the specific features. The methods of medical image fusion generally use knowledge in many different fields such as clinical medicine, computer vision, digital imaging, machine learning, pattern recognition to fuse different medical images. There are two main approaches in fusing image, including spatial domain approach and transform domain approachs. This paper proposes a new algorithm to fusion multimodal images.… More >

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S. Michael Dinesh^1,*, A. R. Kavitha²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 545-561, 2023, DOI:10.32604/csse.2023.024450
Abstract Deep learning has risen in popularity as a face recognition technology in recent years. Facenet, a deep convolutional neural network (DCNN) developed by Google, recognizes faces with 128 bytes per face. It also claims to have achieved 99.96% on the reputed Labelled Faces in the Wild (LFW) dataset. However, the accuracy and validation rate of Facenet drops down eventually, there is a gradual decrease in the resolution of the images. This research paper aims at developing a new facial recognition system that can produce a higher accuracy rate and validation rate on low-resolution face images. The proposed system Extended Openface… More >

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Mahdi Jemmali^1,2,3,*, Lotfi Hidri⁴
Computer Systems Science and Engineering, Vol.44, No.1, pp. 563-577, 2023, DOI:10.32604/csse.2023.022716
Abstract The two-stage hybrid flow shop problem under setup times is addressed in this paper. This problem is NP-Hard. on the other hand, the studied problem is modeling different real-life applications especially in manufacturing and high performance-computing. Tackling this kind of problem requires the development of adapted algorithms. In this context, a metaheuristic using the genetic algorithm and three heuristics are proposed in this paper. These approximate solutions are using the optimal solution of the parallel machines under release and delivery times. Indeed, these solutions are iterative procedures focusing each time on a particular stage where a parallel machines problem is… More >

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V. R. Kavitha¹, K. Nimala², A. Beno³, K. C. Ramya⁴, Seifedine Kadry⁵, Byeong-Gwon Kang⁶, Yunyoung Nam^7,*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 579-593, 2023, DOI:10.32604/csse.2023.024553
Abstract Image Captioning is an emergent topic of research in the domain of artificial intelligence (AI). It utilizes an integration of Computer Vision (CV) and Natural Language Processing (NLP) for generating the image descriptions. It finds use in several application areas namely recommendation in editing applications, utilization in virtual assistance, etc. The development of NLP and deep learning (DL) models find useful to derive a bridge among the visual details and textual semantics. In this view, this paper introduces an Oppositional Harris Hawks Optimization with Deep Learning based Image Captioning (OHHO-DLIC) technique. The OHHO-DLIC technique involves the design of distinct levels… More >

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1135

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D. Banumathy^1,*, Osamah Ibrahim Khalaf², Carlos Andrés Tavera Romero³, P. Vishnu Raja⁴, Dilip Kumar Sharma⁵
Computer Systems Science and Engineering, Vol.44, No.1, pp. 595-612, 2023, DOI:10.32604/csse.2023.025611
Abstract The most salient argument that needs to be addressed universally is Early Breast Cancer Detection (EBCD), which helps people live longer lives. The Computer-Aided Detection (CADs)/Computer-Aided Diagnosis (CADx) system is indeed a software automation tool developed to assist the health professions in Breast Cancer Detection and Diagnosis (BCDD) and minimise mortality by the use of medical histopathological image classification in much less time. This paper purposes of examining the accuracy of the Convolutional Neural Network (CNN), which can be used to perceive breast malignancies for initial breast cancer detection to determine which strategy is efficient for the early identification of… More >

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842

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L. K. Shoba^1,*, P. Mohan Kumar²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 613-628, 2023, DOI:10.32604/csse.2023.024449
Abstract Nowadays in the medical field, imaging techniques such as Optical Coherence Tomography (OCT) are mainly used to identify retinal diseases. In this paper, the Central Serous Chorio Retinopathy (CSCR) image is analyzed for various stages and then compares the difference between CSCR before as well as after treatment using different application methods. The first approach, which was focused on image quality, improves medical image accuracy. An enhancement algorithm was implemented to improve the OCT image contrast and denoise purpose called Boosted Anisotropic Diffusion with an Unsharp Masking Filter (BADWUMF). The classifier used here is to figure out whether the OCT… More >

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1259

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516

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P. Renukadevi^1,*, A. Rajiv Kannan²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 629-645, 2023, DOI:10.32604/csse.2023.024217
Abstract About 170 nations have been affected by the COvid VIrus Disease-19 (COVID-19) epidemic. On governing bodies across the globe, a lot of stress is created by COVID-19 as there is a continuous rise in patient count testing positive, and they feel challenging to tackle this situation. Most researchers concentrate on COVID-19 data analysis using the machine learning paradigm in these situations. In the previous works, Long Short-Term Memory (LSTM) was used to predict future COVID-19 cases. According to LSTM network data, the outbreak is expected to finish by June 2020. However, there is a chance of an over-fitting problem in… More >

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575

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Kyamelia Roy¹, Sheli Sinha Chaudhuri¹, Sayan Pramanik², Soumen Banerjee^2,*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 647-662, 2023, DOI:10.32604/csse.2023.024997
Abstract In recent years, computer vision finds wide applications in maritime surveillance with its sophisticated algorithms and advanced architecture. Automatic ship detection with computer vision techniques provide an efficient means to monitor as well as track ships in water bodies. Waterways being an important medium of transport require continuous monitoring for protection of national security. The remote sensing satellite images of ships in harbours and water bodies are the image data that aid the neural network models to localize ships and to facilitate early identification of possible threats at sea. This paper proposes a deep learning based model capable enough to… More >

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826

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Moonseong Kim¹, Woochan Lee^2,*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 663-675, 2023, DOI:10.32604/csse.2023.025615
Abstract The occurrence of ‘sensing holes’ not only hinders seamless data collection but also leads to misinterpretation of information in certain areas under extensive data analysis. In order to overcome this, various sensor relocation strategies have been proposed, but the existing relocation strategies revealed problems such as the ping-pong, shaded area, network disconnection, etc. This paper conducted research on relocation protocols in a distributed environment that is very suitable for real-world situations and efficiently recovering the problem of sensing holes. First, a simulation was performed on the distribution of the shaded area for data collection, which is a problem with the… More >

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3

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Moeiz Miraoui^1,2,*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 677-692, 2023, DOI:10.32604/csse.2023.025799
Abstract A cerebral vascular accident, known as common language stroke, is one of the main causes of mortality and remains the primary cause of acquired disabilities in adults. Those disabled people spend most of their time at home in their living rooms. In most cases, appliances of a living room (TV, light, cooler/heater, window blinds, etc.) are generally controlled by direct manipulation of a set of remote controls. Handling many remote controls can be disturbing and inappropriate for these people. In addition, in many cases these people could be alone at home and must open the door for visitors after their… More >

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1134

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765

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Kingsley A. Ogudo¹, R. Surendran^2,*, Osamah Ibrahim Khalaf³
Computer Systems Science and Engineering, Vol.44, No.1, pp. 693-707, 2023, DOI:10.32604/csse.2023.024154
Abstract Skin lesions have become a critical illness worldwide, and the earlier identification of skin lesions using dermoscopic images can raise the survival rate. Classification of the skin lesion from those dermoscopic images will be a tedious task. The accuracy of the classification of skin lesions is improved by the use of deep learning models. Recently, convolutional neural networks (CNN) have been established in this domain, and their techniques are extremely established for feature extraction, leading to enhanced classification. With this motivation, this study focuses on the design of artificial intelligence (AI) based solutions, particularly deep learning (DL) algorithms, to distinguish… More >

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628

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K. Dinesh Babu^1,*, C. Senthil Singh²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 709-720, 2023, DOI:10.32604/csse.2023.024295
Abstract Brain tumors are potentially fatal presence of cancer cells over a human brain, and they need to be segmented for accurate and reliable planning of diagnosis. Segmentation process must be carried out in different regions based on which the stages of cancer can be accurately derived. Glioma patients exhibit a different level of challenge in terms of cancer or tumors detection as the Magnetic Resonance Imaging (MRI) images possess varying sizes, shapes, positions, and modalities. The scanner used for sensing the location of tumors cells will be subjected to additional protocols and measures for accuracy, in turn, increasing the time… More >

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1297

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561

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Shuying Xu¹, Chin-Chen Chang¹, Ji-Hwei Horng^2,*
Computer Systems Science and Engineering, Vol.44, No.1, pp. 721-739, 2023, DOI:10.32604/csse.2023.026046
Abstract Hiding secret data in digital images is one of the major research fields in information security. Recently, reversible data hiding in encrypted images has attracted extensive attention due to the emergence of cloud services. This paper proposes a novel reversible data hiding method in encrypted images based on an optimal multi-threshold block labeling technique (OMTBL-RDHEI). In our scheme, the content owner encrypts the cover image with block permutation, pixel permutation, and stream cipher, which preserve the in-block correlation of pixel values. After uploading to the cloud service, the data hider applies the prediction error rearrangement (PER), the optimal threshold selection… More >

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1258

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730

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K. Chola Raja^1,*, S. Kannimuthu²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 741-755, 2023, DOI:10.32604/csse.2023.025331
Abstract Autism Spectrum Disorder (ASD) requires a precise diagnosis in order to be managed and rehabilitated. Non-invasive neuroimaging methods are disease markers that can be used to help diagnose ASD. The majority of available techniques in the literature use functional magnetic resonance imaging (fMRI) to detect ASD with a small dataset, resulting in high accuracy but low generality. Traditional supervised machine learning classification algorithms such as support vector machines function well with unstructured and semi structured data such as text, images, and videos, but their performance and robustness are restricted by the size of the accompanying training data. Deep learning on… More >

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684

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Polin Rahman¹, Ahmed Rifat¹, MD. IftehadAmjad Chy¹, Mohammad Monirujjaman Khan^1,*, Mehedi Masud², Sultan Aljahdali²
Computer Systems Science and Engineering, Vol.44, No.1, pp. 757-775, 2023, DOI:10.32604/csse.2023.021469
Abstract Heart failure is now widely spread throughout the world. Heart disease affects approximately 48% of the population. It is too expensive and also difficult to cure the disease. This research paper represents machine learning models to predict heart failure. The fundamental concept is to compare the correctness of various Machine Learning (ML) algorithms and boost algorithms to improve models’ accuracy for prediction. Some supervised algorithms like K-Nearest Neighbor (KNN), Support Vector Machine (SVM), Decision Trees (DT), Random Forest (RF), Logistic Regression (LR) are considered to achieve the best results. Some boosting algorithms like Extreme Gradient Boosting (XGBoost) and CatBoost are… More >

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796

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R. N. Karthika^*, C. Valliyammai, M. Naveena
Computer Systems Science and Engineering, Vol.44, No.1, pp. 777-795, 2023, DOI:10.32604/csse.2023.024086
Abstract The data in the cloud is protected by various mechanisms to ensure security aspects and user’s privacy. But, deceptive attacks like phishing might obtain the user’s data and use it for malicious purposes. In Spite of much technological advancement, phishing acts as the first step in a series of attacks. With technological advancements, availability and access to the phishing kits has improved drastically, thus making it an ideal tool for the hackers to execute the attacks. The phishing cases indicate use of foreign characters to disguise the original Uniform Resource Locator (URL), typosquatting the popular domain names, using reserved characters… More >

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