T. Sivaranjani^1,*, S. P. Vimal²

Computer Systems Science and Engineering, Vol.47, No.1, pp. 153-170, 2023, DOI:10.32604/csse.2023.036724 - 26 May 2023

Abstract Crop Yield Prediction (CYP) is critical to world food production. Food safety is a top priority for policymakers. They rely on reliable CYP to make import and export decisions that must be fulfilled before launching an agricultural business. Crop Yield (CY) is a complex variable influenced by multiple factors, including genotype, environment, and their interactions. CYP is a significant agrarian issue. However, CYP is the main task due to many composite factors, such as climatic conditions and soil characteristics. Machine Learning (ML) is a powerful tool for supporting CYP decisions, including decision support on which… More >

Bashar Tahayna, Ramesh Kumar Ayyasamy^*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 37-54, 2023, DOI:10.32604/csse.2023.036648 - 26 May 2023

Abstract Millions of people are connecting and exchanging information on social media platforms, where interpersonal interactions are constantly being shared. However, due to inaccurate or misleading information about the COVID-19 pandemic, social media platforms became the scene of tense debates between believers and doubters. Healthcare professionals and public health agencies also use social media to inform the public about COVID-19 news and updates. However, they occasionally have trouble managing massive pandemic-related rumors and frauds. One reason is that people share and engage, regardless of the information source, by assuming the content is unquestionably true. On Twitter,… More >

G. Anitha¹, N. Supriya², Fayadh Alenezi³, E. Laxmi Lydia⁴, Gyanendra Prasad Joshi⁵, Jinsang You^6,*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 221-238, 2023, DOI:10.32604/csse.2023.036479 - 26 May 2023

Abstract Rooftop units (RTUs) were commonly employed in small commercial buildings that represent that can frequently do not take the higher level maintenance that chillers receive. Fault detection and diagnosis (FDD) tools can be employed for RTU methods to ensure essential faults are addressed promptly. In this aspect, this article presents an Optimal Deep Belief Network based Fault Detection and Classification on Packaged Rooftop Units (ODBNFDC-PRTU) model. The ODBNFDC-PRTU technique considers fault diagnosis as a multi-class classification problem and is handled using DL models. For fault diagnosis in RTUs, the ODBNFDC-PRTU model exploits the deep belief More >

Sultan Alahmari¹, Saud Yonbawi², Suneetha Racharla³, E. Laxmi Lydia⁴, Mohamad Khairi Ishak⁵, Hend Khalid Alkahtani^6,*, Ayman Aljarbouh⁷, Samih M. Mostafa⁸

Computer Systems Science and Engineering, Vol.47, No.1, pp. 375-391, 2023, DOI:10.32604/csse.2023.036362 - 26 May 2023

Abstract Hyperspectral imaging instruments could capture detailed spatial information and rich spectral signs of observed scenes. Much spatial information and spectral signatures of hyperspectral images (HSIs) present greater potential for detecting and classifying fine crops. The accurate classification of crop kinds utilizing hyperspectral remote sensing imaging (RSI) has become an indispensable application in the agricultural domain. It is significant for the prediction and growth monitoring of crop yields. Amongst the deep learning (DL) techniques, Convolution Neural Network (CNN) was the best method for classifying HSI for their incredible local contextual modeling ability, enabling spectral and spatial… More >

S. Sureshkumar^1,*, G .K. D. Prasanna Venkatesan², R. Santhosh³

Computer Systems Science and Engineering, Vol.47, No.1, pp. 1109-1123, 2023, DOI:10.32604/csse.2023.036267 - 26 May 2023

Abstract Cloud computing technology provides flexible, on-demand, and completely controlled computing resources and services are highly desirable. Despite this, with its distributed and dynamic nature and shortcomings in virtualization deployment, the cloud environment is exposed to a wide variety of cyber-attacks and security difficulties. The Intrusion Detection System (IDS) is a specialized security tool that network professionals use for the safety and security of the networks against attacks launched from various sources. DDoS attacks are becoming more frequent and powerful, and their attack pathways are continually changing, which requiring the development of new detection methods. Here… More >

Hassan Shokouhandeh¹, Mehrdad Ahmadi Kamarposhti^2,*, William Holderbaum³, Ilhami Colak⁴, Phatiphat Thounthong⁵

Computer Systems Science and Engineering, Vol.47, No.1, pp. 809-822, 2023, DOI:10.32604/csse.2023.035827 - 26 May 2023

Abstract The widespread penetration of distributed energy sources and the use of load response programs, especially in a microgrid, have caused many power system issues, such as control and operation of these networks, to be affected. The control and operation of many small-distributed generation units with different performance characteristics create another challenge for the safe and efficient operation of the microgrid. In this paper, the optimum operation of distributed generation resources and heat and power storage in a microgrid, was performed based on real-time pricing through the proposed gray wolf optimization (GWO) algorithm to reduce the… More >

Mohammed Altaf Ahmed¹, T. Satyanarayana Murthy², Fayadh Alenezi³, E. Laxmi Lydia⁴, Seifedine Kadry^5,6,7, Yena Kim⁸, Yunyoung Nam^8,*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 1283-1297, 2023, DOI:10.32604/csse.2023.035786 - 26 May 2023

Abstract Wireless Sensor Networks (WSN) play a vital role in several real-time applications ranging from military to civilian. Despite the benefits of WSN, energy efficiency becomes a major part of the challenging issue in WSN, which necessitate proper load balancing amongst the clusters and serves a wider monitoring region. The clustering technique for WSN has several benefits: lower delay, higher energy efficiency, and collision avoidance. But clustering protocol has several challenges. In a large-scale network, cluster-based protocols mainly adapt multi-hop routing to save energy, leading to hot spot problems. A hot spot problem becomes a problem… More >

Mohamed Yacin Sikkandar^1,*, K. Hemalatha², M. Subashree³, S. Srinivasan⁴, Seifedine Kadry^5,6,7, Jungeun Kim⁸, Keejun Han⁹

Computer Systems Science and Engineering, Vol.47, No.1, pp. 873-889, 2023, DOI:10.32604/csse.2023.035730 - 26 May 2023

Abstract Recently, COVID-19 has posed a challenging threat to researchers, scientists, healthcare professionals, and administrations over the globe, from its diagnosis to its treatment. The researchers are making persistent efforts to derive probable solutions for managing the pandemic in their areas. One of the widespread and effective ways to detect COVID-19 is to utilize radiological images comprising X-rays and computed tomography (CT) scans. At the same time, the recent advances in machine learning (ML) and deep learning (DL) models show promising results in medical imaging. Particularly, the convolutional neural network (CNN) model can be applied to… More >

Dongsheng Li, Chunsheng Li^*, Kejia Zhang, Tao Liu, Fang Liu, Jingsong Yin, Mingyue Liao

Computer Systems Science and Engineering, Vol.47, No.1, pp. 1209-1231, 2023, DOI:10.32604/csse.2023.034395 - 26 May 2023

Abstract Intelligent identification of sandstone slice images using deep learning technology is the development trend of mineral identification, and accurate mineral particle segmentation is the most critical step for intelligent identification. A typical identification model requires many training samples to learn as many distinguishable features as possible. However, limited by the difficulty of data acquisition, the high cost of labeling, and privacy protection, this has led to a sparse sample number and cannot meet the training requirements of deep learning image identification models. In order to increase the number of samples and improve the training effect… More >

Abdelwahed Motwakel^1,*, Najm Alotaibi², Eatedal Alabdulkreem³, Hussain Alshahrani⁴, Mohamed Ahmed Elfaki⁴, Mohamed K Nour⁵, Radwa Marzouk⁶, Mahmoud Othman⁷

Computer Systems Science and Engineering, Vol.47, No.1, pp. 1249-1266, 2023, DOI:10.32604/csse.2023.034227 - 26 May 2023

Abstract Sentiment Analysis (SA) of natural language text is not only a challenging process but also gains significance in various Natural Language Processing (NLP) applications. The SA is utilized in various applications, namely, education, to improve the learning and teaching processes, marketing strategies, customer trend predictions, and the stock market. Various researchers have applied lexicon-related approaches, Machine Learning (ML) techniques and so on to conduct the SA for multiple languages, for instance, English and Chinese. Due to the increased popularity of the Deep Learning models, the current study used diverse configuration settings of the Convolution Neural… More >