A. Arulmary^1,*, V. Rajamani², T. Kavitha²

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1617-1630, 2023, DOI:10.32604/csse.2023.034681

Abstract The method opted for accuracy, and no existing studies are based on this method. A design and characteristic survey of a new small band gap semiconducting Single Wall Carbon Nano Tube (SWCNT) Field Effect Transistor as a photodetector is carried out. In the proposed device, better performance is achieved by increasing the diameter and introducing a new single halo (SH) doping in the channel length of the CNTFET device. This paper is a study and analysis of the performance of a Carbon Nano Tube Field Effect Transistor (CNTFET) as a photodetector using the self-consistent Poisson and Green function method. The… More >

Neenavath Veeraiah^1,*, Youseef Alotaibi², Ahmad F. Subahi³

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1879-1900, 2023, DOI:10.32604/csse.2023.034658

Abstract An abnormality that develops in white blood cells is called leukemia. The diagnosis of leukemia is made possible by microscopic investigation of the smear in the periphery. Prior training is necessary to complete the morphological examination of the blood smear for leukemia diagnosis. This paper proposes a Histogram Threshold Segmentation Classifier (HTsC) for a decision support system. The proposed HTsC is evaluated based on the color and brightness variation in the dataset of blood smear images. Arithmetic operations are used to crop the nucleus based on automated approximation. White Blood Cell (WBC) segmentation is calculated using the active contour model… More >

K. Jayanthi^1,*, A. M. Kalpana²

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1689-1705, 2023, DOI:10.32604/csse.2023.034613

Abstract The fifth-generation (5G) wireless technology is the most recent standardization in communication services of interest across the globe. The concept of Multiple-Input-Multiple-Output antenna (MIMO) systems has recently been incorporated to operate at higher frequencies without limitations. This paper addresses, design of a high-gain MIMO antenna that offers a bandwidth of 400 MHz and 2.58 GHz by resonating at 28 and 38 GHz, respectively for 5G millimeter (mm)-wave applications. The proposed design is developed on a RT Duroid 5880 substrate with a single elemental dimension of 9.53 × 7.85 × 0.8 mm³. The patch antenna is fully grounded and is fed with a 50-ohm stepped impedance… More >

Xiangwei Chen¹, Zhijin Zhao^1,2,*, Xueyi Ye¹, Shilian Zheng², Caiyi Lou², Xiaoniu Yang²

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1385-1400, 2023, DOI:10.32604/csse.2023.034543

Abstract Interference signals recognition plays an important role in anti-jamming communication. With the development of deep learning, many supervised interference signals recognition algorithms based on deep learning have emerged recently and show better performance than traditional recognition algorithms. However, there is no unsupervised interference signals recognition algorithm at present. In this paper, an unsupervised interference signals recognition method called double phases and double dimensions contrastive clustering (DDCC) is proposed. Specifically, in the first phase, four data augmentation strategies for interference signals are used in data-augmentation-based (DA-based) contrastive learning. In the second phase, the original dataset’s k-nearest neighbor set (KNNset) is designed… More >

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 >

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 >

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 >

Saurabh Adhikari¹, Tushar Kanti Gangopadhayay¹, Souvik Pal^2,3, D. Akila⁴, Mamoona Humayun⁵, Majed Alfayad⁶, N. Z. Jhanjhi^7,*

Computer Systems Science and Engineering, Vol.46, No.2, pp. 2123-2140, 2023, DOI:10.32604/csse.2023.034431

Abstract Machine learning is a technique for analyzing data that aids the construction of mathematical models. Because of the growth of the Internet of Things (IoT) and wearable sensor devices, gesture interfaces are becoming a more natural and expedient human-machine interaction method. This type of artificial intelligence that requires minimal or no direct human intervention in decision-making is predicated on the ability of intelligent systems to self-train and detect patterns. The rise of touch-free applications and the number of deaf people have increased the significance of hand gesture recognition. Potential applications of hand gesture recognition research span from online gaming to… More >

A. Francis Saviour Devaraj¹, T. Satyanarayana Murthy², Fayadh Alenezi³, E. Laxmi Lydia⁴, Mohamad Adzhar Md Zawawi⁵, Mohamad Khairi Ishak^5,*

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1431-1445, 2023, DOI:10.32604/csse.2023.034421

Abstract Recently, a trust system was introduced to enhance security and cooperation between nodes in wireless sensor networks (WSN). In routing, the trust system includes or avoids nodes related to the estimated trust values in the routing function. This article introduces Enhanced Metaheuristics with Trust Aware Secure Route Selection Protocol (EMTA-SRSP) for WSN. The presented EMTA-SRSP technique majorly involves the optimal selection of routes in WSN. To accomplish this, the EMTA-SRSP technique involves the design of an oppositional Aquila optimization algorithm to choose safe routes for data communication. For the clustering process, the nodes with maximum residual energy will be considered… More >

S. Rajalakshmi^1,*, S. Nalini², Ahmed Alkhayyat³, Rami Q. Malik⁴

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1673-1688, 2023, DOI:10.32604/csse.2023.034414

Abstract Remote sensing image (RSI) classifier roles a vital play in earth observation technology utilizing Remote sensing (RS) data are extremely exploited from both military and civil fields. More recently, as novel DL approaches develop, techniques for RSI classifiers with DL have attained important breakthroughs, providing a new opportunity for the research and development of RSI classifiers. This study introduces an Improved Slime Mould Optimization with a graph convolutional network for the hyperspectral remote sensing image classification (ISMOGCN-HRSC) model. The ISMOGCN-HRSC model majorly concentrates on identifying and classifying distinct kinds of RSIs. In the presented ISMOGCN-HRSC model, the synergic deep learning… More >