Life Cycle Assessment and Activity-Based Costing for Low-Cost Aluminum die manufacturing: A comparative study of machining process, conventional and rapid investment casting by Samina Bibi, Muhammad Sajid, Wasim Ahmad, Muhammad Asad Ali, Mirza Jahanzaib, Salman Hussain

“…This study conducts a comparative life cycle assessment (LCA) of MP, CIC, and RIC, evaluating their impact on production time, cost, energy usage, and carbon emissions. A gate-to-gate system boundary was adopted for the LCA, focusing exclusively on internal production processes from material input to the completion of the aluminum mold. …”
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Perception about and Effect of Adaptive Educational Application on Electronics Topics on Students’ Virtual Spaces, Motivation, Satisfaction and Active Role by Ricardo-Adán Salas-Rueda

“… Currently, educators seek to offer personalised contents to facilitate autonomy during the educational process. The aim of this mixed study (quantitative and qualitative approach) was to build and analyse the effectiveness of the Adaptive Educational application on electronics topics (AEET) considering Data Science (machine learning algorithm on linear regression). …”
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Evaluating GRU Algorithm and Double Moving Average for Predicting USDT Prices: A Case Study 2017-2024 by Rahmat Rizky, Munirul ula, Zara Yunizar

“…GRU, a deep learning-based recurrent neural network, processes sequential data using a gating mechanism, making it effective for capturing short-term price dynamics. …”
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TCN-QRNN model for short term energy consumption forecasting with increased accuracy and optimized computational efficiency by Lesia Mochurad, Roman Levkovych

“…Experimental results show that the proposed TCN-QRNN model outperforms traditional methods by 40% in accuracy compared to LSTM and by 8% in terms of metrics such as Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) compared to TCN-LSTM, while reducing data processing time by 30%. Additionally, the model has a significantly smaller number of parameters than LSTM and GRU, making it suitable for environments with limited computational resources. …”
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Data Integration of Health Financing Systems as a Critical Enabler for Objective-Oriented Health System Reform: A Scoping Review from India by Grace Achungura, Arif Raza, Vijendra Katre, Jaidev Singh Anand, Nirmala Ravishankar, Rathan Kelkar

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Design and development of SHINE accelerator fast interlock system by YU Chunlei, CHEN Guanghua, DING Jianguo, LI Ming, XIAO Qingwen, YAN Yingbing

“…Due to 1 MHz repetition rate and thousands of kilometers length of SHINE, the accelerator interlock system should be a large system with response speed in microsecond magnitude and capable of processing tens of thousands of signals simultaneously.PurposeThis study aims to design and implement fast interlock system integrated with the conventional slow interlock system for SHINE accelerator.MethodThrough the analysis of SHINE requirements, FPGA (Field Programmable Gate Array) technology, distributed control technology, and network communication technology were adopted to complete the design of the fast interlock system. …”
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Research on Prediction and Optimization of Airport Express Passenger Flow Based on Fusion Intelligence Network Model by Jin He, Yinzhen Li, Yuhong Chao

“…Secondly, bidirectional long short-term memory networks are used to process the sequence data, capture the global information and its context relationship, and enhance the model’s understanding of the dependence of time series data. …”
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High resolution weld semantic defect detection algorithm based on integrated double U structure by Xiaoyan Li, Yi Wei, Zhigang Lv, Peng Wang, Liangliang Li, Mengyu Sun, Chu Wang

“…Then, a multi-image hybrid stitching technology was proposed to reconstruct the long weld into a standard size of 1500 × 1500, which not only expanded the WSCR data set, but also effectively improved the data imbalance problem. …”
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A novel framework for sentiment classification employing Bi-GRU optimized by enhanced human evolutionary optimization algorithm by Xi Wang, Samad Nourmohammadi

“…In this study, Bidirectional Gated Recurrent Unit was employed, since there were two polarities, including positive and negative. …”
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Trade-offs between machine learning and deep learning for mental illness detection on social media by Zhanyi Ding, Zhongyan Wang, Yeyubei Zhang, Yuchen Cao, Yunchong Liu, Xiaorui Shen, Yexin Tian, Jianglai Dai

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An Empirical Comparison of Machine Learning and Deep Learning Models for Automated Fake News Detection by Yexin Tian, Shuo Xu, Yuchen Cao, Zhongyan Wang, Zijing Wei

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Towards energy-efficient joint relay selection and resource allocation for D2D communication using hybrid heuristic-based deep learning by C. H. Ramesh Babu, S. Nandakumar

“…Then, the data provided as the input to the adaptive residual gated recurrent unit (AResGRU) model for the automatic prediction of an optimal number of relays and allocation of resources. …”
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Flexible and high‐throughput structures of Camellia block cipher for security of the Internet of Things by Bahram Rashidi

“…The inversion operation is implemented over the composite field F(24)2 instead of an inversion over F28 which is an important factor to reduce area consumption. A large number of gates, in the structure, have been implemented by 2‐input NAND and 2‐input NOR gates to reduce delay and area. …”
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Extended evaluation of the effect of real and simulated masks on face recognition performance by Naser Damer, Fadi Boutros, Marius Süßmilch, Florian Kirchbuchner, Arjan Kuijper

“…Abstract Face recognition is an essential technology in our daily lives as a contactless and convenient method of accurate identity verification. Processes such as secure login to electronic devices or identity verification at automatic border control gates are increasingly dependent on such technologies. …”
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Research on intelligent control of coal slime flotation based on the WOA-GRU model by DOU Zhiheng, WANG Ranfeng, QIN Xinkai, CHAI Yuqing, LI Pinyu, LIU Shutong

“…Considering that most existing coal preparation plants use single-input single-output PID controllers, which struggle to manage multi-input multi-output systems, Model Predictive Control (MPC) was introduced to better handle the multivariable coupling in the flotation process. Using production data from the Daichi Dam coal preparation plant, MPC simulations were conducted using both the WOA-GRU and NARX identification models. …”
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Seismic phase recognition model with low SNR based on U-net by Jianxian Cai, Zhongjie Sun, Mengying Zhang, Fenfen Yan, Li Wang, Ling Li

“…Aiming at the problem of low recognition accuracy and high missed detection rate of seismic phase recognition of low signal-to-noise ratio seismic signals, a new seismic phase recognition model UBAN (U-net-Bidirectional Gated Recurrent Unit-Attention Network) is designed based on U-net neural network framework, combined with Bi-GRU bidirectional gated recurrent unit and Attention attention mechanism. …”
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Advanced Supply Chain Management Using Adaptive Serial Cascaded Autoencoder with LSTM and Multi-Layered Perceptron Framework by Aniruddha Deka, Parag Jyoti Das, Manob Jyoti Saikia

“…A data transformation process is used to clean and prepare financial data for analysis. …”
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H-ConvLSTM to Estimate Reference Evapotranspiration From Air Temperature and Relative Humidity by Abdul Haris, M. Marimin, Sri Wahjuni, Budi Indra Setiawan

“…A few deep learning architecture models are employed by researchers in the estimation of evapotranspiration reference (ETo), including Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). These three algorithms have been extensively evaluated and validated due to their ability to predict and estimate ETo data using temperature (T), relative humidity (RH), and solar radiation (Rs) as variables. …”
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CFET Beyond 3 nm: SRAM Reliability Under Design-Time and Run-Time Variability by Sufia Shahin, Swati Deshwal, Anirban Kar, Mahdi Benkhelifa, Yogesh S. Chauhan, Hussam Amrouch

“…At the circuit level, a full array of 6T-static random access memory (SRAM) cells with the requisite peripheral circuits is simulated using SPICE after careful calibration of the industry-standard compact model of gate-all-around (BSIM-CMG) against the TCAD data. …”
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Applying a Parameterized Quantum Circuit to Anomaly Detection by Jehn-Ruey Jiang, Jyun-Sian Li

“…In this study, a parameterized quantum circuit (PQC) is applied for anomaly detection, a crucial process to identify unusual patterns or outliers in data. …”
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