Yolotzin Apatzingán Palomino-Hermosillo¹, Ángel Elpidio Díaz-Jasso², Rosendo Balois-Morales¹, Verónica Alhelí Ochoa-Jiménez^1,3, Pedro Ulises Bautista-Rosales¹, Guillermo Berumen-Varela^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1717-1732, 2024, DOI:10.32604/phyton.2024.052216 - 30 July 2024

Abstract Soursop (Annona muricata L.) is a tropical fruit highly valued for its unique flavor, nutritional value, and health-promoting properties. The ripening process of soursop involves complex changes in gene expression and metabolite accumulation, which have been studied using various omics technologies. Transcriptome analysis has provided insights into the regulation of key genes involved in ripening, while metabolic compound analysis has revealed the presence of numerous bioactive compounds with potential health benefits. However, the integration of transcriptome and metabolite compound data has not been extensively explored in soursop. Therefore, in this paper, we present a comprehensive analysis… More >

Bingfei Fu^*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1407-1424, 2024, DOI:10.32604/cmc.2024.052656 - 18 July 2024

Abstract Discovering floating wastes, especially bottles on water, is a crucial research problem in environmental hygiene. Nevertheless, real-world applications often face challenges such as interference from irrelevant objects and the high cost associated with data collection. Consequently, devising algorithms capable of accurately localizing specific objects within a scene in scenarios where annotated data is limited remains a formidable challenge. To solve this problem, this paper proposes an object discovery by request problem setting and a corresponding algorithmic framework. The proposed problem setting aims to identify specified objects in scenes, and the associated algorithmic framework comprises pseudo… More >

Yifei Zhao, Zhaohui Li, Siyi Lv^*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 217-234, 2024, DOI:10.32604/cmc.2024.052310 - 18 July 2024

Abstract The EU’s Artificial Intelligence Act (AI Act) imposes requirements for the privacy compliance of AI systems. AI systems must comply with privacy laws such as the GDPR when providing services. These laws provide users with the right to issue a Data Subject Access Request (DSAR). Responding to such requests requires database administrators to identify information related to an individual accurately. However, manual compliance poses significant challenges and is error-prone. Database administrators need to write queries through time-consuming labor. The demand for large amounts of data by AI systems has driven the development of NoSQL databases.… More >

Seolhee Kim¹, Sang-Duck Lee^2,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 195-215, 2024, DOI:10.32604/cmc.2024.052070 - 18 July 2024

Abstract Damage to parcels reduces customer satisfaction with delivery services and increases return-logistics costs. This can be prevented by detecting and addressing the damage before the parcels reach the customer. Consequently, various studies have been conducted on deep learning techniques related to the detection of parcel damage. This study proposes a deep learning-based damage detection method for various types of parcels. The method is intended to be part of a parcel information-recognition system that identifies the volume and shipping information of parcels, and determines whether they are damaged; this method is intended for use in the… More >

Fatma S. Alrayes¹, Mohammed Zakariah², Syed Umar Amin^3,*, Zafar Iqbal Khan³, Jehad Saad Alqurni⁴

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1457-1490, 2024, DOI:10.32604/cmc.2024.051996 - 18 July 2024

Abstract This study describes improving network security by implementing and assessing an intrusion detection system (IDS) based on deep neural networks (DNNs). The paper investigates contemporary technical ways for enhancing intrusion detection performance, given the vital relevance of safeguarding computer networks against harmful activity. The DNN-based IDS is trained and validated by the model using the NSL-KDD dataset, a popular benchmark for IDS research. The model performs well in both the training and validation stages, with 91.30% training accuracy and 94.38% validation accuracy. Thus, the model shows good learning and generalization capabilities with minor losses of… More >

Zhan Shi^*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 973-994, 2024, DOI:10.32604/cmc.2024.051530 - 18 July 2024

Abstract The convergence of Internet of Things (IoT), 5G, and cloud collaboration offers tailored solutions to the rigorous demands of multi-flow integrated energy aggregation dispatch data processing. While generative adversarial networks (GANs) are instrumental in resource scheduling, their application in this domain is impeded by challenges such as convergence speed, inferior optimality searching capability, and the inability to learn from failed decision making feedbacks. Therefore, a cloud-edge collaborative federated GAN-based communication and computing resource scheduling algorithm with long-term constraint violation sensitiveness is proposed to address these challenges. The proposed algorithm facilitates real-time, energy-efficient data processing by More >

Xialin Liu^1,2,3,*, Junsheng Wu⁴, Lijun Chen^2,3, Jiyuan Hu⁵

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1601-1631, 2024, DOI:10.32604/cmc.2024.050626 - 18 July 2024

Abstract Virtual machine (VM) consolidation aims to run VMs on the least number of physical machines (PMs). The optimal consolidation significantly reduces energy consumption (EC), quality of service (QoS) in applications, and resource utilization. This paper proposes a prediction-based multi-objective VM consolidation approach to search for the best mapping between VMs and PMs with good timeliness and practical value. We use a hybrid model based on Auto-Regressive Integrated Moving Average (ARIMA) and Support Vector Regression (SVR) (HPAS) as a prediction model and consolidate VMs to PMs based on prediction results by HPAS, aiming at minimizing the More >

Saad Abdalla Agaili Mohamed^*, Sefer Kurnaz

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 819-841, 2024, DOI:10.32604/cmc.2024.050474 - 18 July 2024

Abstract VPNs are vital for safeguarding communication routes in the continually changing cybersecurity world. However, increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorize VPN network data. We present a novel VPN network traffic flow classification method utilizing Artificial Neural Networks (ANN). This paper aims to provide a reliable system that can identify a virtual private network (VPN) traffic from intrusion attempts, data exfiltration, and denial-of-service assaults. We compile a broad dataset of labeled VPN traffic flows from various apps and usage patterns. Next, we create an ANN architecture that can… More >

G. Sunil Santhosh Kumar^1,2,*, M. Rudra Kumar³

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 695-713, 2024, DOI:10.32604/cmc.2024.050143 - 18 July 2024

Abstract This article presents an innovative approach to automatic rule discovery for data transformation tasks leveraging XGBoost, a machine learning algorithm renowned for its efficiency and performance. The framework proposed herein utilizes the fusion of diversified feature formats, specifically, metadata, textual, and pattern features. The goal is to enhance the system’s ability to discern and generalize transformation rules from source to destination formats in varied contexts. Firstly, the article delves into the methodology for extracting these distinct features from raw data and the pre-processing steps undertaken to prepare the data for the model. Subsequent sections expound… More >

Ahmed Khalid¹, Rana Asif Rehman¹, Byung-Seo Kim^2,*

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 61-103, 2024, DOI:10.32604/cmc.2024.049981 - 18 July 2024

Abstract Wireless Ad Hoc Networks consist of devices that are wirelessly connected. Mobile Ad Hoc Networks (MANETs), Internet of Things (IoT), and Vehicular Ad Hoc Networks (VANETs) are the main domains of wireless ad hoc network. Internet is used in wireless ad hoc network. Internet is based on Transmission Control Protocol (TCP)/Internet Protocol (IP) network where clients and servers interact with each other with the help of IP in a pre-defined environment. Internet fetches data from a fixed location. Data redundancy, mobility, and location dependency are the main issues of the IP network paradigm. All these… More >