Khawaja Tahir Mehmood^1,2,*, Shahid Atiq¹, Intisar Ali Sajjad³, Muhammad Majid Hussain⁴, Malik M. Abdul Basit²

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1673-1708, 2024, DOI:10.32604/cmes.2024.053903 - 27 September 2024

Abstract Software-Defined Networking (SDN), with segregated data and control planes, provides faster data routing, stability, and enhanced quality metrics, such as throughput (T_h), maximum available bandwidth (B_d(max)), data transfer (D_Transfer), and reduction in end-to-end delay (D_(E-E)). This paper explores the critical work of deploying SDN in large­scale Data Center Networks (DCNs) to enhance its Quality of Service (QoS) parameters, using logically distributed control configurations. There is a noticeable increase in Delay_(E-E) when adopting SDN with a unified (single) control structure in big DCNs to handle Hypertext Transfer Protocol (HTTP) requests causing a reduction in network quality parameters (B_d(max), T_h, D_Transfer, D_(E-E),… More > Graphic Abstract

SUBHAYAN SUR^1,*, DIMPLE DAVRAY², SOUMYA BASU¹, SUPRIYA KHEUR³, JAYANTA KUMAR PAL¹, SHUCHI NAGAR², AVINASH SANAP³, BHIMAPPA M. RUDAGI³, SAMIR GUPTA⁴

Oncology Research, Vol.32, No.10, pp. 1589-1612, 2024, DOI:10.32604/or.2024.052120 - 18 September 2024

Abstract Oral squamous cell carcinoma (OSCC) is one of the most prevalent forms of head and neck squamous cell carcinomas (HNSCC) with a poor overall survival rate (about 50%), particularly in cases of metastasis. RNA-based cancer biomarkers are a relatively advanced concept, and non-coding RNAs currently have shown promising roles in the detection and treatment of various malignancies. This review underlines the function of long non-coding RNAs (lncRNAs) in the OSCC and its subsequent clinical implications. LncRNAs, a class of non-coding RNAs, are larger than 200 nucleotides and resemble mRNA in numerous ways. However, unlike mRNA,… More >

Soha A. Shaban^*, Amira A. Atta, Dalia L. Elsheweikh

Computer Systems Science and Engineering, Vol.48, No.5, pp. 1213-1250, 2024, DOI:10.32604/csse.2024.052603 - 13 September 2024

Abstract Field training is the backbone of the teacher-preparation process. Its importance stems from the goals that colleges of education aim to achieve, which include bridging the gap between theory and practice and aligning with contemporary educational trends during teacher training. Currently, trainee students attendance in field training is recorded manually through signatures on attendance sheets. However, this method is prone to impersonation, time wastage, and misplacement. Additionally, traditional methods of evaluating trainee students are often susceptible to human errors during the evaluation and scoring processes. Field training also lacks modern technology that the supervisor can… More >

Cuiwei Peng¹, Jiahui Chen^2,*, Shicheng Wan³, Guotao Xu⁴

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4341-4360, 2024, DOI:10.32604/cmc.2024.054109 - 12 September 2024

Abstract In today’s highly competitive retail industry, offline stores face increasing pressure on profitability. They hope to improve their ability in shelf management with the help of big data technology. For this, on-shelf availability is an essential indicator of shelf data management and closely relates to customer purchase behavior. RFM (recency, frequency, and monetary) pattern mining is a powerful tool to evaluate the value of customer behavior. However, the existing RFM pattern mining algorithms do not consider the quarterly nature of goods, resulting in unreasonable shelf availability and difficulty in profit-making. To solve this problem, we… More >

Ahmad Nahar Quttoum^1,*, Muteb Alshammari²

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4577-4601, 2024, DOI:10.32604/cmc.2024.054102 - 12 September 2024

Abstract Cloud Datacenter Network (CDN) providers usually have the option to scale their network structures to allow for far more resource capacities, though such scaling options may come with exponential costs that contradict their utility objectives. Yet, besides the cost of the physical assets and network resources, such scaling may also impose more loads on the electricity power grids to feed the added nodes with the required energy to run and cool, which comes with extra costs too. Thus, those CDN providers who utilize their resources better can certainly afford their services at lower price-units when… More >

Farhan Amin, Gyu Sang Choi^*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3507-3521, 2024, DOI:10.32604/cmc.2024.053183 - 12 September 2024

Abstract Mobile networks possess significant information and thus are considered a gold mine for the researcher’s community. The call detail records (CDR) of a mobile network are used to identify the network’s efficacy and the mobile user’s behavior. It is evident from the recent literature that cyber-physical systems (CPS) were used in the analytics and modeling of telecom data. In addition, CPS is used to provide valuable services in smart cities. In general, a typical telecom company has millions of subscribers and thus generates massive amounts of data. From this aspect, data storage, analysis, and processing… More >

Yahia Said^1,*, Yahya Alassaf², Refka Ghodhbani³, Yazan Ahmad Alsariera⁴, Taoufik Saidani³, Olfa Ben Rhaiem⁴, Mohamad Khaled Makhdoum¹, Manel Hleili⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 733-749, 2024, DOI:10.32604/cmes.2024.052369 - 20 August 2024

Abstract Enhancing road safety globally is imperative, especially given the significant portion of traffic-related fatalities attributed to motorcycle accidents resulting from non-compliance with helmet regulations. Acknowledging the critical role of helmets in rider protection, this paper presents an innovative approach to helmet violation detection using deep learning methodologies. The primary innovation involves the adaptation of the PerspectiveNet architecture, transitioning from the original Res2Net to the more efficient EfficientNet v2 backbone, aimed at bolstering detection capabilities. Through rigorous optimization techniques and extensive experimentation utilizing the India driving dataset (IDD) for training and validation, the system demonstrates exceptional More >

Feng Zhao, Xiaotong Zhu^*, Xiaoqiang Chen, Ying Wang

Energy Engineering, Vol.121, No.9, pp. 2585-2601, 2024, DOI:10.32604/ee.2024.049762 - 19 August 2024

Abstract In order to fully utilize the regenerative braking energy of metro trains and stabilize the metro DC traction busbar voltage, a hybrid regenerative braking energy recovery system with a dual-mode power management strategy is proposed. Firstly, the construction of the hybrid regenerative braking energy recovery system is explained. Then, based on the power demand of low-voltage load in metro stations, a dual-mode power management strategy is proposed to allocate the reference power of each system according to the different working conditions, and the control methods of each system are set. Finally, the correctness and effectiveness More > Graphic Abstract

Tareq Hamadneh¹, Khalid Kaabneh², Omar Alssayed³, Gulnara Bektemyssova^4,*, Galymzhan Shaikemelev⁴, Dauren Umutkulov⁴, Zoubida Benmamoun⁵, Zeinab Monrazeri⁶, Mohammad Dehghani^6,*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2005-2030, 2024, DOI:10.32604/cmc.2024.052401 - 15 August 2024

Abstract The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Management (SCM), which is characterized by elevated risks due to inadequate accountability and transparency. To address these challenges and improve operations in green manufacturing, optimization algorithms play a crucial role in supporting decision-making processes. In this study, we propose a solution to the green lot size optimization issue by leveraging bio-inspired algorithms, notably the Stork Optimization Algorithm (SOA). The SOA draws inspiration from the hunting and winter migration strategies employed by storks in nature. The theoretical framework of SOA is… More >

Sameer Qazi^1,*, Muhammad Bilal Kadri², Muhammad Naveed^1,*, Bilal A. Khawaja³, Sohaib Zia Khan⁴, Muhammad Mansoor Alam^5,6,7, Mazliham Mohd Su’ud⁶

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3289-3314, 2024, DOI:10.32604/cmc.2024.048893 - 15 August 2024

Abstract COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus. The foremost and most prime sector among those affected were schools, colleges, and universities. The education system of entire nations had shifted to online education during this time. Many shortcomings of Learning Management Systems (LMSs) were detected to support education in an online mode that spawned the research in Artificial Intelligence (AI) based tools that are being developed by the research community to improve the effectiveness of LMSs. This paper presents a detailed survey of the different enhancements to LMSs, which… More >