State of The Art Review: Building Computational Thinking on Science Education by Y. I. Tanjung, M. Azhar, A. Razak, Y. Yohandri, F. Arsih, T. Wulandari, B. Nasution, R. H. Lubis

“…Whereas from a state-of-the-art review of the stages of building CT, it was found that the stages of task decomposition, abstraction, generalization, data structures and algorithms were considered to optimalize the CT construction for science students. …”
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Fault prediction of smart meter based on spatio-temporal convolution neural network by Gao Wenjun, Xue Binbin, Pang Zhenjiang

“…Firstly, the sliding window is used to integrate the time information into the characteristic variables, and the input matrix with space-time characteristics is constructed. Then, combined with CNN, the fault prediction model of smart meter is established, and the model parameters are optimized by adaptive momentum estimation (Adam) algorithm. …”
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A traceability model for upper corner gas in fully mechanized mining faces based on XGBoost-SHAP by SHENG Wu, WANG Lingzi

“…An upper corner gas concentration prediction model was constructed based on XGBoost, and the SHAP algorithm was introduced to calculate the contribution of each feature variable to the prediction results, thereby enhancing the model's transparency and providing a global interpretation for the XGBoost model. …”
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The DEM Registration Method Without Ground Control Points for Landslide Deformation Monitoring by Yunchuan Wang, Jia Li, Ping Duan, Rui Wang, Xinrui Yu

“…Finally, the shape variables are calculated by constructing a DEM differential model. The method was evaluated using simulated data and data from two real landslide cases, and the experimental results revealed that the registration accuracies of the three datasets were 0.963 m, 0.368 m, and 2.459 m, which are 92%, 50%, and 24% better than the 12.189 m, 0.745 m, and 3.258 m accuracies of the iterative closest-point algorithm, respectively. …”
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A Method of Simultaneous Vehicle Localization and Roadside Pole-shaped Object Inventory Creation Based on Integrated LiDAR-IMU-GNSS System by YUAN Chao, PAN Wenbo, CHEN Zhiwei, HUANG Wenyu, LI Yuanzhengyu, YANG Zhenyu

“…Secondly, an optimized fusion positioning algorithm based on sliding windows is constructed, to enhance system robustness through effectively integrating data from multiple sensors. …”
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Blasting Vibration Control Using an Improved Artificial Neural Network in the Ashele Copper Mine by Shida Xu, Tianxiao Chen, Jiaqi Liu, Chenrui Zhang, Zhiyang Chen

“…In this paper, a genetic algorithm (GA) and an artificial neural network (ANN) algorithm were jointly used to construct a neural network model with a 4-5-1 topology to predict the PPV. …”
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Angle Expansion Estimation and Correction Based on the Lindeberg–Feller Central Limit Theorem Under Multi-Pulse Integration by Jiong Cai, Rui Wang, Handong Yang

“…Numerical experiments and radar data in the field verify the impact of target characteristics on the angle measurement under multi-pulse integration and the effectiveness of the angle correction algorithm.…”
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Improvement of table tennis technology based on data mining in the environment of wireless sensor networks by Hongjian Ma

“…At present, the traditional table tennis video mining algorithm has some problems such as low efficiency and poor performance of optimization classification. …”
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Aircraft Multi-stage Altitude Prediction Under Satellite Signal Loss by Mengchan HUANG, Qiang MIAO

“…The relative error ratios of the LTCA–TCN model for all three phases are within 1, indicating that the model’s predictions are generally more accurate than the inertial pressure altitude.Conclusions The results indicated that the LTCA–TCN model achieves high prediction accuracy across multiple stages, outperforming commonly used neural network algorithms in the field and providing optimal predictive performance. …”
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A combined feature selection approach for malicious email detection based on a comprehensive email dataset by Han Zhang, Yong Shi, Ming Liu, Libo Chen, Songyang Wu, Zhi Xue

“…We summarize two major challenges in the current field of malicious email detection using machine learning algorithms. (1) Current works on malicious email detection use different datasets and lack a unified and comprehensive open source dataset standard for evaluating detection performance. …”
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Optimization of fluid control laws through deep reinforcement learning using dynamic mode decomposition as the environment by T. Sakamoto, K. Okabayashi

“…DMDc is a method of modal analysis of a flow field that incorporates external inputs, and we utilize it to represent the time development of flow in the DRL environment. …”
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Diamond-shaped quantum circuit for real-time quantum dynamics in one dimension by Shohei Miyakoshi, Takanori Sugimoto, Tomonori Shirakawa, Seiji Yunoki, Hiroshi Ueda

“…In recent years, quantum computing has evolved as an exciting frontier, with the development of numerous algorithms dedicated to constructing quantum circuits that adeptly represent quantum many-body states. …”
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Numerical Polynomial Homotopy Continuation Method and String Vacua by Dhagash Mehta

“…In this paper, we review a numerical method called the numerical polynomial homotopy continuation (NPHC) method, first used in the areas of lattice field theories, which by construction finds all of the vacua of a given potential that is known to have only isolated solutions. …”
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GA-Based Early Warning Method for Rock Burst with Microseismic and Acoustic Emission in Steeply Inclined Coal Seam by Yarong Xue, Dazhao Song, Zhenlei Li, Jianqiang Chen, Xueqiu He, Shengquan He, Donghui Li

“…Aiming at problem of low efficacy of early warning of rock burst in coal mine, a multisystem and multiparameter integrated early warning method based on genetic algorithm (GA) is proposed. In this method, firstly, the temporal-spatial-intensity information of energy incubation process of rock burst is deeply mined, and the multidimensional precursory characteristic parameter system of rock burst is constructed. …”
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Scene Text Detection Based on Multi-scale Feature Extraction and Bidirectional Feature Fusion by LIAN Zhe, YIN Yanjun, ZHI Min, XU Qiaozhi

“…The proposed algorithm constructs a multi-scale feature extraction module based on convolutional kernels of different sizes to take into account the feature extraction of text targets of different scales and shapes, while capturing contextual information dependencies at different distances. …”
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Rural Landscape Characters and Spatial Correlation Mechanism in the Tiaoxi River – Canal Basin in Zhejiang Province by Lin ZHANG, You ZUO, Binyi LIU

“…Future research will construct a spatio-temporal dynamic dataset of canal heritage landscapes, which aims to enhance the fine-grained character extraction and type classification accuracy of machine learning algorithm models for rural landscapes. …”
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A Study of the Soil–Wall–Indoor Air Thermal Environment in a Solar Greenhouse by Zhi Zhang, Yu Li, Liqiang Wang, Weiwei Cheng, Zhonghua Liu

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Short-term Wind Power Forecasting Based on BWO‒VMD and TCN‒BiGRU by LU Jing, ZHANG Yanru, WANG Rui

“…Its capacity to manage complex time series data is demonstrated, and the advancement and innovation of algorithms and models are supported. New directions for technological progress and practical application in the field of wind power prediction are established.…”
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Saliency Detection via Fusing Color Contrast and Hash Fingerprint by Yin Lv, Xuanrui Zhang, Yong Wang

“…Saliency detection is a technique for automatically extracting regions of interest from the background and has been widely used in the computer vision field. This study proposes a simple and effective saliency detection method combining color contrast and hash fingerprint. …”
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Application of Vehicle Mounted Accelerometers to Measure Pavement Roughness by Yuchuan Du, Chenglong Liu, Difei Wu, Siyu Li

“…Two wireless communication systems (ZigBee and 3G modules) were utilized to transfer the data and construct network between the components. The information platform implemented an acceleration-IRI model to calculate IRI, and a GPS based distance algorithm was employed to segment the measured road per 1 km. …”
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