Guosheng Li¹, Qingquan Lv², Zhenzhen Zhang², Haiying Dong^1,*

Energy Engineering, Vol.120, No.4, pp. 1045-1065, 2023, DOI:10.32604/ee.2023.023770

Abstract Aiming at the problems of output voltage fluctuation and current total harmonic distortion (THD) in the front stage totem-pole bridgeless PFC of two-stage V2G (Vehicle to Grid) vehicle-mounted bi-directional converter, a fuzzy linear active disturbance rejection control strategy for V2G front-stage AC-DC power conversion system is proposed. Firstly, the topological working mode of the totem-pole bridgeless PFC is analyzed, and the mathematical model is established. Combined with the system model and the linear active disturbance rejection theory, a double closed-loop controller is designed with the second-order linear active disturbance rejection control as the voltage outer loop and PI control as… More > Graphic Abstract

UROS BUMBASIREVIC^1,2,*, MARKO ZIVKOVIC¹, MILOS PETROVIC¹, VESNA CORIC^2,3, NIKOLA LISICIC¹, NEBOJSA BOJANIC^1,2

Oncology Research, Vol.30, No.3, pp. 117-128, 2022, DOI:10.32604/or.2022.027511

Abstract Seminomas are most commonly diagnosed in clinical stage I (CSI). After orchiectomy, approximately 15% of patients in this stage have subclinical metastases. Adjuvant radiotherapy (ART) delivered to the retroperitoneum and ipsilateral pelvic lymph nodes has been the mainstay of treatment for many years. Although highly efficient, with long-term cancer-specific survival (CSS) rates approaching almost 100%, ART is associated with considerable long-term consequences, particularly cardiovascular toxicity and increased risk of secondary malignancies (SMN). Therefore, active surveillance (AS) and adjuvant chemotherapy (ACT) were developed as alternative treatment options. While AS prevents patient overtreatment, it is associated with strict follow-up regimens and increased… More >

D. Palanikkumar¹, R. Ramesh Kumar², Mehedi Masud³, Mrim M. Alnfiai⁴, Mohamed Abouhawwash^5,6,*

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2425-2440, 2023, DOI:10.32604/iasc.2023.033879

Abstract The major environmental hazard in this pandemic is the unhygienic disposal of medical waste. Medical wastage is not properly managed it will become a hazard to the environment and humans. Managing medical wastage is a major issue in the city, municipalities in the aspects of the environment, and logistics. An efficient supply chain with edge computing technology is used in managing medical waste. The supply chain operations include processing of waste collection, transportation, and disposal of waste. Many research works have been applied to improve the management of wastage. The main issues in the existing techniques are ineffective and expensive… More >

Qiang Zhi¹, Wanxu Pu¹, Jianguo Ren¹, Zhengshu Zhou^2,*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5141-5155, 2023, DOI:10.32604/cmc.2023.035846

Abstract In the early stage of software development, a software requirements specification (SRS) is essential, and whether the requirements are clear and explicit is the key. However, due to various reasons, there may be a large number of misunderstandings. To generate high-quality software requirements specifications, numerous researchers have developed a variety of ways to improve the quality of SRS. In this paper, we propose a questions extraction method based on SRS elements decomposition, which evaluates the quality of SRS in the form of numerical indicators. The proposed method not only evaluates the quality of SRSs but also helps in the detection… More >

S. Sandhiyaa^*, C. Gomathy

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 4747-4768, 2023, DOI:10.32604/cmc.2023.032298

Abstract The nodes in the sensor network have a wide range of uses, particularly on under-sea links that are skilled for detecting, handling as well as management. The underwater wireless sensor networks support collecting pollution data, mine survey, oceanographic information collection, aided navigation, strategic surveillance, and collection of ocean samples using detectors that are submerged in water. Localization, congestion routing, and prioritizing the traffic is the major issue in an underwater sensor network. Our scheme differentiates the different types of traffic and gives every type of traffic its requirements which is considered regarding network resource. Minimization of localization error using the… More >

Zhengtao Xi¹, Chaofan Song², Jiahui Zheng³, Haifeng Shi³, Zhuqing Jiao^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2243-2266, 2023, DOI:10.32604/cmes.2023.023544

Abstract The structure and function of brain networks have been altered in patients with end-stage renal disease (ESRD). Manifold regularization (MR) only considers the pairing relationship between two brain regions and cannot represent functional interactions or higher-order relationships between multiple brain regions. To solve this issue, we developed a method to construct a dynamic brain functional network (DBFN) based on dynamic hypergraph MR (DHMR) and applied it to the classification of ESRD associated with mild cognitive impairment (ESRDaMCI). The construction of DBFN with Pearson’s correlation (PC) was transformed into an optimization model. Node convolution and hyperedge convolution superposition were adopted to… More > Graphic Abstract

Anwer Mustafa Hilal^1,*, Amal Al-Rasheed², Jaber S. Alzahrani³, Majdy M. Eltahir⁴, Mesfer Al Duhayyim⁵, Nermin M. Salem⁶, Ishfaq Yaseen¹, Abdelwahed Motwakel¹

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1249-1263, 2023, DOI:10.32604/csse.2023.030603

Abstract Sleep plays a vital role in optimum working of the brain and the body. Numerous people suffer from sleep-oriented illnesses like apnea, insomnia, etc. Sleep stage classification is a primary process in the quantitative examination of polysomnographic recording. Sleep stage scoring is mainly based on experts’ knowledge which is laborious and time consuming. Hence, it can be essential to design automated sleep stage classification model using machine learning (ML) and deep learning (DL) approaches. In this view, this study focuses on the design of Competitive Multi-verse Optimization with Deep Learning Based Sleep Stage Classification (CMVODL-SSC) model using Electroencephalogram (EEG) signals.… More >

Md Zahid Hasan Ontor¹, Md Mamun Ali¹, Kawsar Ahmed^2,3,*, Francis M. Bui³, Fahad Ahmed Al-Zahrani⁴, S. M. Hasan Mahmud⁵, Sami Azam⁶

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3727-3741, 2023, DOI:10.32604/cmc.2023.032794

Abstract Cervical Cancer (CC) is a rapidly growing disease among women throughout the world, especially in developed and developing countries. For this many women have died. Fortunately, it is curable if it can be diagnosed and detected at an early stage and taken proper treatment. But the high cost, awareness, highly equipped diagnosis environment, and availability of screening tests is a major barrier to participating in screening or clinical test diagnoses to detect CC at an early stage. To solve this issue, the study focuses on building a deep learning-based automated system to diagnose CC in the early stage using cervix… More >

Song Zhang¹, Wensheng Li², Zhao Li², Xiaolei Zhang¹, Zhipeng Lu¹, Xiaoning Ge^3,*

Energy Engineering, Vol.120, No.1, pp. 181-199, 2023, DOI:10.32604/ee.2022.022228

Abstract Driven by the goal of “carbon neutrality” and “emission peak”, effectively controlling system carbon emissions has become significantly important to governments around the world. To this end, a novel two-stage low-carbon economic scheduling framework that considers the coordinated optimization of ladder-type carbon trading and integrated demand response (IDR) is proposed in this paper for the integrated energy system (IES), where the first stage determines the energy consumption plan of users by leveraging the price-based electrical-heat IDR. In contrast, the second stage minimizes the system total cost to optimize the outputs of generations with consideration of the uncertainty of renewables. In… More >

Ruizhi Huang¹, Huasheng Yu², Yong Yang¹, Heqin Liu², Xuelong Wu¹, Zhihong Liu¹, Haiyan He¹, Gengwei Wu¹, Wengjia Wang¹, Hua Wang^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.2, pp. 333-348, 2023, DOI:10.32604/phyton.2022.023252

Abstract As global temperature rise, the threat of heat stress to rapeseed production is becoming more obvious. Exploring the response characteristics of two important biological pathways, oil accumulation and photosynthesis, to heat stress during B. napus seed filling is helpful in the genetic improvement of heat-tolerant rapeseed. The effects of heat stress on seed oil accumulation and chlorophyll fluorescence characteristics of 29 B. napus germplasms with different oil content and environmental sensitivity, including 6 rapeseed varieties which exhibited environment-sensitive/insensitive and with high, medium or low oil content, were tested by whole plant heat stress or the in vitro silique culture system.… More >