Journal of Computational Methods in Sciences and Engineering - Volume 24, issue 3

Authors: Wang, Fei | Fan, Zikai | Miao, Yun | Ren, Jiayi | Luo, Yuchao

Article Type: Research Article

Abstract: Generating as-built Building information models (BIMs) is promising in power substation construction projects because they can reflect the actual conditions of facilities. However, traditional manual-designed BIMs are different from real-world scenarios due to reality gaps. In this paper, we present a new method of reconstructing the layout of power equipment and facilities in substations using LIDAR point clouds. The proposed method extracts electric equipment and facilities via object segmentation and model retrieval. In particular, we investigate PFH, FPFH and SHOT descriptors for the 3D-SIFT keypoints in the 3D shape retrieval of complex electric equipment and facilities. After the best-match model …is retrieved from a model library, the layout of typical electric equipment and facilities is reconstructed by aligning the model to the scene point cloud via point cloud registration. Experimental results validate the effectiveness of the proposed method. The proposed method enhances the efficiency of generating 3D models of power substations. Show more

Keywords: Reconstruction, substation, point cloud registration, point cloud segmentation

DOI: 10.3233/JCM-247162

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 3, pp. 1269-1281, 2024

Authors: Sun, Yong | Yang, Yiwei | Chen, Jing | Xue, Keli | Li, Min

Article Type: Research Article

Abstract: This paper addresses prevalent issues of suboptimal compatibility between the heating exchanger and the thermal storage unit, poor safety performance, and overall insufficient heat exchange efficiency within the application of heating exchangers in electric heating solid energy storage heating systems. Experimental testing and numerical simulation studies were conducted. The research investigates the effect of the temperature of inlet air as well as velocity on the heat exchange performance of the heating exchanger as well as temperature variations of single-row heat pipes. Drawing upon these change patterns, an optimized heating exchanger structure is proposed and subsequently investigated through optimization simulation studies. …The study results indicate that the best overall optimization effect is achieved with a heating exchanger arranged with finned tube combinations of 4 mm in two rows, 6 mm in two rows, 8 mm in two rows, 10 mm in two rows, 12 mm in two rows, and 14 mm in ten rows arranged successively from front to back. When the heating exchanger’s inlet air speed is relatively high, this combination’s heat exchange capacity surpasses the original structure. Additionally, the uniformity of air-side temperature drop improved by 44.89%, while the finned area was reduced by 25.62%. Show more

Keywords: Electric heating solid energy storage heating system, finned tube heating exchanger, heat exchange performance, temperature non-uniformity coefficient

DOI: 10.3233/JCM-247137

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 3, pp. 1283-1302, 2024

Authors: Zhao, Wei | Qi, Jian

Article Type: Research Article

Abstract: With the rapid development of information technology, the field of education is undergoing a profound change, in which intelligent hybrid learning and virtual reality technology are increasingly valued. This study proposes an intelligent hybrid learning method based on virtual reality for student performance improvement. This paper reveals the limitations of traditional learning methods in meeting the needs of modern education, and expounds the theoretical basis of intelligent hybrid learning and virtual reality technology. This paper collects and processes a large amount of learning data, based on which a new model of student learning performance prediction is established. The verification results …of the model show that the model in this study has excellent performance in predicting students’ learning performance. This paper gives some suggestions for future educational practice and research. In general, this study provides a new learning method for the field of education and has important reference value for education reform and teaching practice. Show more

Keywords: Intelligent blended learning, virtual reality technology, student learning performance

DOI: 10.3233/JCM-247198

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 3, pp. 1303-1316, 2024

Authors: Cen, Haifeng | Xu, Yuan | Sun, Kaiyuan | Tian, Hao | Chen, Kun | Lin, Lin

Article Type: Research Article

Abstract: This paper examines the use of an Uninterruptible Power Supply (UPS) to enhance the operational efficiency of data centers. It focuses on developing an optimal energy scheduling strategy for a data center equipped with UPS, using the Markov decision process (MDP) framework. The MDP framework simulates the decision-making process involved in minimizing energy costs. Each unit’s available power output in the data center is treated as a Markov state, taking into account the uncertainty associated with renewable distributed generation. This uncertainty drives the system to transition to other Markov states in subsequent decision times. A recursive optimization model is established …for each Markov state at each decision time to guide state-based operations, which includes determining the unit output while considering both current and future costs. The challenge of dealing with high dimensionality, arising from a substantial number of states and actions in the model, is effectively addressed by adopting an approximate dynamic programming (ADP) method. This approach incorporates decision-state and forwards dynamic algorithms to tackle the complexity of the MDP-based model. By employing ADP, the computational burden is reduced, enabling efficient and practical solutions to be obtained. Show more

Keywords: Data center, Markov decision process, reinforcement learning, UPS

DOI: 10.3233/JCM-247149

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 3, pp. 1317-1329, 2024

Authors: Yao, Zhifeng | Xu, Ye

Article Type: Research Article

Abstract: The conventional genetic algorithm (GA) for path planning exists several drawbacks, such as uncertainty in the direction of robot movement, circuitous routes, low convergence rates, and prolonged search time. To solve these problems, this study introduces an improved GA-based path-planning algorithm that adopts adaptive regulation of crossover and mutation probabilities. This algorithm uses a hybrid selection strategy that merges elite, tournament, and roulette wheel selection methods. An adaptive approach is implemented to control the speed of population evolution through crossover and mutation. Combining with a local search operation enhances the optimization capability of the algorithm. The proposed algorithm was compared …with the traditional GA through simulations, demonstrating shorter path lengths and reduced search times. Show more

Keywords: Genetic algorithm, hybrid selection strategy, adaptive strategy, local search

DOI: 10.3233/JCM-247133

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 3, pp. 1331-1340, 2024

Authors: Liang, Junhua | Zhao, Zhisheng | Ma, Sujing | Wang, Jiaju

Article Type: Research Article

Abstract: Blended learning is the latest and inevitable trend in the development of education. Although blended learning research is on the rise, fewer studies examine the learning behaviour of college students in blended learning environments. This study aimed to investigate the learning behaviours of students in the field of computer science and examine these behaviours using data mining algorithms, taking the teaching practice of the Digital Signal Processing course as a case study. A total of 18 behavioural indicators were extracted and divided into three categories: basic learning behaviours, self-regulated learning behaviours, and extended learning behaviours. Data analysis of the …behavioural indicators yielded the following conclusions: (1) Students did not have the habit of watching course playback and were less receptive to multiple online learning platforms; (2) Students’ midterm performance and duration of livestream watching directly affected their basic learning behaviours, with all indicators of self-regulated and extended learning behaviours showing significant correlations; (3) The clustering of learning behaviours yielded four different learner patterns, which calls for personalised teaching strategies; (4) The random forest algorithm had an accuracy of 95.4% in predicting performance of the four types of learners. Show more

Keywords: Behavioural analysis, blended teaching, self-regulated learning, learning behaviour

DOI: 10.3233/JCM-247160

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 3, pp. 1341-1353, 2024

Authors: Wang, Xiaomei | Jing, Huifeng | Guo, Yuyue

Article Type: Research Article

Abstract: To examine the impact and mechanisms of the aerobics exercise on gut flora and gastrointestinal hormones in type 2 diabetes rats. Methods Adult male SD rats aged 8 weeks were divided into 5 groups at random (n = 10): a peaceful comparison group (N), a diabetic comparison group (D), a diabetic low-intensity exercise group (LD), a diabetic middle-intensity exercise group (MD), and a diabetes highintensity exercise group. (HD). The rat groups LD, MD, and HD performed aerobic exercise five times per week for a total of 6 weeks and compared general condition, blood glucose, blood lipids, …insulin, leptin, gastrin (GAS) and motilin ( MOT), gastrointestinal motility, and intestinal flora. Results The levels of insulin, leptin, total cholesterol, triglycerides, E. coli, LDL-cholesterol, LDL-cholesterol, insulin, and gastric residual rate were significantly different from group N. Conclusion: Type 2 diabetic rats have gut flora imbalance and gastrointestinal hormone changes. Aerobic exercise with different intensity can alleviate gastrointestinal hormone imbalance and intestinal flora imbalance in type 2 diabetes rats, and the impact of moderate intensity exercise is the strongest. Show more

Keywords: Aerobic exercise, type 2 diabetes;intestinal flora, gastrointestinal hormones

DOI: 10.3233/JCM-247158

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 3, pp. 1355-1362, 2024

Authors: Li, Qiang | Pan, Xiaoli | Fan, Wenyan | Zhou, Ying | Liu, Yongfu | Yu, Wangxin | Li, Dongyu | Li, Wenyue | Li, Weibin

Article Type: Research Article

Abstract: The study investigates the impact of different drying methods on the selection of thin-layer drying kinetic models, parameters, and quality for Exocarpium Citreic Grandis. This study investigates the drying characteristics, index constituents content, and microscopic structures of Exocarpium Citreic Grandis slices, subjected to three drying techniques: HAD (at 50, 60, 70 ∘ C), VD (at 50, 60, 70 ∘ C), and MVD (at 1000, 1500, 2000W). A thin-layer drying kinetic model was established. The findings demonstrated that the drying process was primarily dominated by the falling rate phase. When the drying temperature was 70 …∘ C and the microwave power was 2000W, the HAD VD, and MVD took 120, 360, and 20 minutes respectively. By fitting six commonly used thin-layer drying models, it was discovered that the optimal mathematical models for HAD, VD, and MVD were the Page model, the Logarithmic model, and the Page model, respectively. The highest average R 2 values were 0.9963, 0.9965, and 0.9964, and the lowest average RMSE values were 0.01782, 0.01704, and 0.0174 respectively. The effective diffusion coefficient increased with the drying temperature and microwave power, with MVD having the maximum coefficient. As the temperature and microwave power increased, the contents of naringin and rhoifolin decreased. However, the naringin content in MVD was 23.05% and 45.71% higher compared to hot air and VD respectively. The cross-section of Exocarpium Citreic Grandis dried via microwave vacuum exhibited a porous honeycomb structure with uniformly distributed spaces and larger pores, reflecting an expansion effect. The HAD process also resulted in a honeycomb-like structure, but with smaller pores. The VD process resulted in a layered structure with significant cell collapse. Microwave vacuum drying demonstrates superior energy efficiency and product quality compared to hot air and vacuum drying methods. The study finds that microwave drying does not have a destructive impact on the active compounds of Exocarpium Citreic Grandis. To facilitate large-scale, continuous production, microwave drying can be practically applied in industrial processing. Show more

Keywords: Exocarpium Citreic Grandis, microwave vacuum, hot air drying, vacuum drying, thin-layer drying model

DOI: 10.3233/JCM-247143

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 3, pp. 1363-1377, 2024

Authors: Liu, Xiaomei | Hu, Xuewei

Article Type: Research Article

Abstract: Conventional brute-force attacks can now be detected and identified based on statistical analysis of logs and traffic data. However, they fail to detect low-frequency and distributed brute-force attack behaviors. To address different attack methods, new detection techniques have emerged. This study compares various machine learning algorithms and selects two methods, namely the clustering algorithm k-means and bdscan, as well as the decision tree algorithm for data learning. In one approach, normal user login data is integrated with enterprise email log data. The data is first statistically analyzed and filtered, followed by quantifying data characteristics using information entropy. Subsequently, machine learning …algorithms are employed for classification, and the results are visualized for display. In another approach, labeled raw data is used to train a model using the decision tree algorithm. By comparing the two analysis results, a more accurate model can be obtained. These analytical methods can help enterprises strengthen email security and defend against low-frequency and distributed brute-force attacks. Show more

Keywords: Brute-force attack, low-frequency, distributed, machine learning algorithms

DOI: 10.3233/JCM-247147

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 3, pp. 1379-1393, 2024

Authors: Sun, Hua | Su, Kaifeng | Yang, Yifan

Article Type: Research Article

Abstract: As an important part of automotive shock absorber, the columnar parts in automotive shock absorber will inevitably have machining defects during the process, which will not only degrade the performance of the parts, but also degrade or even fail the performance of the final shock absorber after assembly. Yolov5, as a target detection algorithm, has received much attention due to its high accuracy and fast operation speed. However, the algorithm faces some challenges when applied in a practical industrial environment. In this paper, improvement measures are proposed to address the limitations of sample collection and the high speed of pipeline …recognition in industrial environments. The network model is optimized and designed. Firstly, the ASPP module is replaced by the SPP module thus improving the viewability throughout the process providing recognition accuracy. Secondly, the Conv and C3 layers of Yolov5s are replaced by Transformer to obtain higher recognition accuracy. By improving and optimizing the above methods, we can better cope with the improvement of detection accuracy under small sample conditions. Experiments show that the method can significantly improve the detection accuracy and operation speed of Yolov5s under the hardware condition of lower computing power, which is more suitable for industrial scenario application scenarios. Show more

Keywords: Target detection, YOLOv5, SPP module, APPF module, Transformer

DOI: 10.3233/JCM-247145

Citation: Journal of Computational Methods in Sciences and Engineering, vol. 24, no. 3, pp. 1395-1404, 2024