COMPARING FORECASTS OF AGRICULTURAL SECTOR EXPORT VALUES USING SARIMA AND LONG SHORT-TERM MEMORY MODELS by Aleytha Ilahnugrah Kurnadipare, Sri Amaliya, Khairil Anwar Notodiputro, Yenni Angraini, Laily Nissa Atul Mualifah

“…The best SARIMA model generated was (1,1,1)(0,1,1)12, while the optimal parameters for the LSTM model were neuron: 50, dropout rate: 0.3, number of layers: 2, activation function: relu, epochs: 500, batch size: 64, optimizer: Adam, and learning rate: 0.01. …”
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Short communication: Substantial heritability of larval size in the black soldier fly reveals potential for selective breeding by R.M. Zaalberg, L.B. Andersen, L.S. Hansen, G. Gebreyesus, M. Henryon, K. Jensen, H.M. Nielsen

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Short-chain fatty acids from lysis liquid of residual sludge anaerobic fermentation enhanced by microbial electrolysis by MENG Qingjie, WANG Hui, KANG Xu, LIU Wenzong*

“…The COD removal rate was 40.2% in the renewal batch cycle, which was 15.6% higher than the conventional anaerobic conversion. …”
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Effects of high-temperature, short-time pasteurization on milk and whey during commercial whey protein concentrate production by Joanna Haas, Bum Jin Kim, Zeynep Atamer, Chao Wu, David C. Dallas

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Long short-term memory (LSTM) networks for precision prediction of Schottky barrier photodiode behavior at different illumination levels by Gökalp Tulum, Sajjad Nematzadeh, İlke Taşçıoğlu, Şemsettin Altındal, Fahrettin Yakuphanoğlu

“…Hyperparameters, including the number of epochs (150) and batch size (64), were determined empirically to balance computational efficiency and model performance. …”
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Multivariate Data Analysis to Assess Process Evolution and Systematic Root Causes Investigation in Tablet Manufacturing at an Industrial Scale—A Case Study Focused on Improving Tab... by Rita Mathe, Tibor Casian, Ioan Tomuta

“…The purpose of this work was to identify the root causes for the low and variable hardness of core tablets prepared using high-shear wet granulation through batch statistical modeling and to verify the short- and long-term effectiveness of the improvement actions. …”
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Analysis of Tolerance to Heavy Metal Ions and Their Oxides on Endogenous Short-Range Denitrification Systems Domesticated by Different Valence Iron by JIN Baodan, YAN Yeyu, BAI Zhixuan, LIU Ye, WANG Baogui, DU Jingjing, PANG Long, JI Jiantao, Ma Chuang

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Short communication: The effect of Propolis extract treatment on the Lee index and brain-body weight ratio in diet-induced obesity rats by Andreas Christoper, Herry Herman, Rizky Abdulah, Felix Zulhendri, Ronny Lesmana

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Forecasting Stock Returns Using Long Short-Term Memory (LSTM) Model Based on Inflation Data and Historical Stock Price Movements by Nur Faid Prasetyo, Wina Witanti, Asep Id Hadiana

“…The dataset was split into 80% for training and 20% for testing, with hyperparameter tuning conducted using the RMSprop optimizer under varying batch sizes and epoch settings. Experimental results show that the configuration using RMSprop with a batch size of 8 and 200 epochs delivered the best performance, achieving a Root Mean Squared Error (RMSE) of 0.0167 and a Mean Absolute Percentage Error (MAPE) of 25.89%. …”
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Short-term solar irradiance forecasting model based on hyper-parameter tuned LSTM via chaotic particle swarm optimization algorithm by V Ashok Gajapati Raju, Janmenjoy Nayak, Pandit Byomakesha Dash, Manohar Mishra

“…The proposed DL architecture leverages the power of LSTM to learn complex temporal patterns in short-wave solar irradiance data. The main objective of the CPSO is to minimize the prediction error through optimizing the LSTM's hyper-parameters such as neurons in hidden layers, learning rate, batch size, dropout rate and activation function. …”
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Introducing a Novel Figure of Merit for Evaluating Stability of Perovskite Solar Cells: Utilizing Long Short-Term Memory Neural Networks by Zahraa Ismail, Ahmet Sait Alali, Ahmad Muhammad, Mahmoud Ashraf, Sameh O. Abdellatif

“…This study introduces a novel figure of merit for evaluating the stability of perovskite solar cells (PSCs) by employing advanced Long Short-Term Memory (LSTM) neural networks to investigate degradation mechanisms. …”
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Short-Chain Fatty Acid Utilization in <i>Cyberlindnera jadinii</i> for Single-Cell Protein and Odd-Chain Fatty Acid Production by Christian Hermansen, Rowanne Siao, Gi Gi Chua, Mikko Ru Xuan Lee, Aaron Thong, Melanie Weingarten, Nic Lindley, Eric Charles Peterson

“…Bioprocess development was conducted in stirred tank bioreactors, where a fed-batch pH-stat bioprocess led to improved efficiency without substrate inhibition. …”
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A Temporal Convolutional Network–Bidirectional Long Short-Term Memory (TCN-BiLSTM) Prediction Model for Temporal Faults in Industrial Equipment by Jinyin Bai, Wei Zhu, Shuhong Liu, Chenhao Ye, Peng Zheng, Xiangchen Wang

“…It is designed to handle continuous processes but can also be applied to batch and hybrid processes due to its flexible architecture. …”
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Research on Thickness Error Optimization Method of Rolling System Based on Improved Sparrow Search Algorithm–Bidirectional Long Short-Term Memory Network–Attention by Qingyun Wu, Xinchen Li, Jiafei Ji, Bowen Xing

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Effectiveness of a short-structured training programme on knowledge of healthcare providers and programme managers involved in maternal and child health programmes in Odisha, India... by Vikas Bhatia, Arvind Kumar Singh, Prajna Paramita Giri, Durgesh Prasad Sahoo

“…Objective To evaluate the effectiveness of training programme on knowledge related to new interventions proposed under India Newborn Action Plan (INAP) and Integrated Action Plan against Pneumonia and Diarrhoea (IAPPD).Design Quality improvement study with pre-evaluation and post evaluation.Setting The study was conducted in 17 districts of Odisha, India.Participants and interventions The participants were healthcare providers and programme managers involved in maternal and child health programmes. Intervention was a short-structured (8 hours) training delivered to 127 batches with expected participation of 30 trainees in each batch. …”
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Implementation of LSTM Method on Tidal Prediction in Semarang Region by Panreshma Rizkha Ambadar, Dian C Rini Novitasari, Yuniar Farida, Moh Hafiyusholeh, Fajar Setiawan

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Forecasting the Stock Price of PT Astra International Using the LSTM Method by Edwin Setiawan Nugraha, Zalfani Alika, Dadang Amir Hamzah

“…The forecasting results show that the best performances have MSE, MSE, MAE and MAPE are 151.910, 23076.561, 118.128, and 2.3%, respectively. The model has a batch size of 4 and epochs of 50. This research recommends that other parties consider this method when they need to manage their investment risk in stocks.…”
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Deep Learning Based LSTM Model for Predicting the Number of Passengers for Public Transport Bus Operators by Joko Siswanto, Danny Manongga, Irwan Sembiring, Sutarto Wijono

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An Optimized 1-D CNN-LSTM Approach for Fault Diagnosis of Rolling Bearings Considering Epistemic Uncertainty by Onur Can Kalay

“…Moreover, grid search was utilized to optimize (1) the number of epochs, (2) batch size, and (3) dropout ratio and further enhance the efficacy of the proposed 1-D CNN-LSTM network. …”
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Research on the Lossless Data Compression System of the Argo Buoy Based on BiLSTM-MHSA-MLP by Sumin Guo, Wenqi Zhang, Yuhong Zheng, Hongyu Li, Yilin Yang, Jiayi Xu

“…Experiments conducted on multiple 4000 m single-batch profile datasets from both the PC and Jetson nano platforms demonstrate that this method achieves a lower compression ratio, shorter compression time, and greater specificity. …”
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