Zeyi Wang¹, Mingxi Jiao¹, Daliang Wang¹, Minxu Liu¹, Minglei Jiang², He Wang³, Shiqiang Li^3,*

Energy Engineering, Vol.121, No.8, pp. 2275-2291, 2024, DOI:10.32604/ee.2024.028223

Abstract This paper addresses the problem of complex and challenging disturbance localization in the current power system operation environment by proposing a disturbance localization method for power systems based on group sparse representation and entropy weight method. Three different electrical quantities are selected as observations in the compressed sensing algorithm. The entropy weighting method is employed to calculate the weights of different observations based on their relative disturbance levels. Subsequently, by leveraging the topological information of the power system and pre-designing an overcomplete dictionary of disturbances based on the corresponding system parameter variations caused by disturbances,… More >

Muhammad S. Alam^1,5,*, Farhan B. Mohamed^1,3, Ali Selamat², Faruk Ahmed⁴, AKM B. Hossain^6,7

Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 417-436, 2024, DOI:10.32604/iasc.2024.051999

Abstract Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems. The scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and speed. This research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image sequence. An annotated image dataset trains the proposed system and predicts the camera pose in real-time. The system mainly improved the localization performance of indoor cameras by more accurately predicting the camera More >

Sana Jawarneh^*

Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 511-525, 2024, DOI:10.32604/iasc.2024.047126

Abstract High-dimensional datasets present significant challenges for classification tasks. Dimensionality reduction, a crucial aspect of data preprocessing, has gained substantial attention due to its ability to improve classification performance. However, identifying the optimal features within high-dimensional datasets remains a computationally demanding task, necessitating the use of efficient algorithms. This paper introduces the Arithmetic Optimization Algorithm (AOA), a novel approach for finding the optimal feature subset. AOA is specifically modified to address feature selection problems based on a transfer function. Additionally, two enhancements are incorporated into the AOA algorithm to overcome limitations such as limited precision, slow More >

Heng Zhang^1,2, Chao Su^2,*, Xiaohu Chen¹, Zhizhong Song¹, Weijie Zhan³

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2977-3000, 2024, DOI:10.32604/cmes.2024.047972

Abstract Temperature-induced cracking during the construction of mass concrete is a significant concern. Numerical simulations of concrete temperature have primarily assumed that the concrete is placed in an open environment. The problem of heat transfer between the air and concrete has been simplified to the concrete’s heat dissipation boundary. However, in the case of tubular concrete structures, where air inlet and outlet are relatively limited, the internal air temperature does not dissipate promptly to the external environment as it rises. To accurately simulate the temperature and creep stress in tubular concrete structures with enclosed air spaces… More >

Weiwei Zhang¹, Jiaqiang Li¹, Chao Wang², Meng Li³, Zhi Rao^4,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4237-4257, 2024, DOI:10.32604/cmc.2024.050430

Abstract In practical engineering, multi-objective optimization often encounters situations where multiple Pareto sets (PS) in the decision space correspond to the same Pareto front (PF) in the objective space, known as Multi-Modal Multi-Objective Optimization Problems (MMOP). Locating multiple equivalent global PSs poses a significant challenge in real-world applications, especially considering the existence of local PSs. Effectively identifying and locating both global and local PSs is a major challenge. To tackle this issue, we introduce an immune-inspired reproduction strategy designed to produce more offspring in less crowded, promising regions and regulate the number of offspring in areas… More >

Suyi Liu^1,*, Jianning Chi¹, Chengdong Wu¹, Fang Xu^2,3,4, Xiaosheng Yu¹

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4471-4489, 2024, DOI:10.32604/cmc.2024.049450

Abstract In recent years, semantic segmentation on 3D point cloud data has attracted much attention. Unlike 2D images where pixels distribute regularly in the image domain, 3D point clouds in non-Euclidean space are irregular and inherently sparse. Therefore, it is very difficult to extract long-range contexts and effectively aggregate local features for semantic segmentation in 3D point cloud space. Most current methods either focus on local feature aggregation or long-range context dependency, but fail to directly establish a global-local feature extractor to complete the point cloud semantic segmentation tasks. In this paper, we propose a Transformer-based… More >

Xiaobin Hou^*1, Tinghui Li^†1, Zhipeng Ren^*, Yang Liu^*

Oncology Research, Vol.24, No.4, pp. 247-253, 2016, DOI:10.3727/096504016X14652175055765

Abstract Mutation of breast cancer 2, early onset (BRCA2) has been identified as a vital risk factor for esophageal cancer (EC). To date, several proteins have been reported as BRCA2-interacting proteins and are associated with multiple biological processes. This study's aim was to identify a novel interactive protein of BRCA2 and to explore its functional roles in EC. A yeast two-hybrid screening was performed to identify a novel BRCA2-interacting protein. Glutathione-S-transferase (GST) pull-down analysis was performed to find out how the binding domain of BRCA2 interacts with LIM domains containing 1 (LIMD1). The interaction between LIMD1… More >

Kristamtini¹, Sugeng Widodo², Heni Purwaningsih³, Arlyna Budi Pustika¹, Setyorini Widyayanti¹, Arif Muazam¹, Arini Putri Hanifa^1,*, Joko Triastono², Dewi Sahara², Heni Sulistyawati Purwaning Rahayu², Pandu Laksono², Diah Arina Fahmi², Sutardi¹, Joko Pramono⁴, Rachmiwati Yusuf¹

Phyton-International Journal of Experimental Botany, Vol.93, No.5, pp. 1007-1021, 2024, DOI:10.32604/phyton.2024.048770

Abstract Sorghum (Sorghum bicolor L. Moench) is an essential food crop for more than 750 million people in tropical and sub-tropical dry climates of Africa, India, and Latin America. The domestic sorghum market in Indonesia is still limited to the eastern region (East Nusa Tenggara, West Nusa Tenggara, Java, and South Sulawesi). Therefore, it is crucial to carry out sorghum research on drylands. This research aimed to investigate the effect of sorghum genotype and planting distance and their interaction toward growth and sorghum’s productivity in the Gunungkidul dryland, Yogyakarta, Indonesia. In addition, the farm business analysis, including… More >

Li Deng¹, Jiafei Huan¹, Wei Wang¹, Weitao Zhang¹, Liangbin Xie², Lun Dong², Jingrong Guo², Zhongping Li², Yuan Huang^2,*, Yue Xiang²

Energy Engineering, Vol.121, No.6, pp. 1403-1437, 2024, DOI:10.32604/ee.2024.046393

Abstract As a flexible resource, energy storage plays an increasingly significant role in stabilizing and supporting the power system, while providing auxiliary services. Still, the current high demand for energy storage contrasts with the fuzzy lack of market-oriented mechanisms for energy storage, the principle of market-oriented operation has not been embodied, and there is no unified and systematic analytical framework for the business model. However, the dispatch management model of energy storage in actual power system operation is not clear. Still, the specific scheduling process and energy storage strategy on the source-load-network side could be more… More >

Hela Elmannai^1,*, Monia Hamdi¹, Souham Meshoul¹, Amel Ali Alhussan², Manel Ayadi³, Amel Ksibi³

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1429-1457, 2024, DOI:10.32604/cmes.2024.048557

Abstract Glaucoma disease causes irreversible damage to the optical nerve and it has the potential to cause permanent loss of vision. Glaucoma ranks as the second most prevalent cause of permanent blindness. Traditional glaucoma diagnosis requires a highly experienced specialist, costly equipment, and a lengthy wait time. For automatic glaucoma detection, state-of-the-art glaucoma detection methods include a segmentation-based method to calculate the cup-to-disc ratio. Other methods include multi-label segmentation networks and learning-based methods and rely on hand-crafted features. Localizing the optic disc (OD) is one of the key features in retinal images for detecting retinal diseases,… More >