THE NUREMBERG TRIAL AND CONTRIBUTIONS TO THE DEVELOPMENT OF INTERNATIONAL HUMANITARIAN LAW: AN APPRAISAL by ANDREW BUYENGUM JACKSON, GAMBO NELSON

“…Closely, the Lieber code of 1863, customary international law, and Briand Kellog pact of 1928 provided a very good playground for international peace and order and it was on this basis that the Nuremberg trial took its shape fostered by Henry Dunant’s book; A Memory of Solferino in 1864. The book codifies international humanitarian law and is a reference for the codes of the military tribunal at Nuremberg for the trial of the Nazi leaders for war crimes against humanity after the Second World War. …”
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Short-Term Forecasting of Dockless Bike-Sharing Demand with the Built Environment and Weather by Yang Yang, Xin Shao, Yuting Zhu, Enjian Yao, Dongmei Liu, Feng Zhao

“…We use a multigraph convolution network (GCN) to model the built environment, utilize a long short-term memory (LSTM) network to extract temporal features, and utilize a fully connected network (FCN) to model weather influence. …”
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Short-Term Traffic Flow Prediction of Expressway: A Hybrid Method Based on Singular Spectrum Analysis Decomposition by Chunyan Shuai, Zhengyang Pan, Lun Gao, HongWu Zuo

“…Singular Spectrum Analysis (SSA) decomposes the traffic flow into one principle component and three random components, and then in terms of different characteristics of these components, Long Short-Term Memory (LSTM) and Support Vector Regression (SVR) are applied to make prediction of different components, respectively. …”
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Monitoring the reliability of integrated circuits protection against Trojans: encoding and decoding of combinational structures by L. A. Zolotorevich, V. A. Ilyinkov

“…The initial data for decoding the structure of a digital device is the structural implementation of encoded circuit, obtained, for example, by reverse engineering (prototype design), as well as an activated physical sample of an integrated circuit, when into protected from unauthorized access memory the correct key value is loaded. This sample can be used as a black box model. …”
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An efficient way to represent the processors and their connections in omega networks by Savari Prabhu, T. Jenifer Janany, Paul Manuel

“…Omega networks provide a structured and scalable interconnect solution for distributed memory architectures. In large-scale data centers where massive amounts of data are processed and analyzed, omega networks are used in the network infrastructure to interconnect servers and storage systems. …”
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Runoff Forecasting Research Coupling Quadratic Factor Screening and Deep Learning by CHENG Liwen, HUANG Shengzhi, LI Pei, LI Ziyan, JIA Songtao, HUANG Qiang

“…The effective screening of factors influencing runoff is a key aspect of runoff forecasting research.However,there are many factors affecting runoff,and these factors have complex interactions.Most of the existing studies use numerically driven models with primary factor screening,and the results show that the input factors are spatially redundant,leading to poor forecasting results.In view of this,the support vector regression (SVR) and the long-short memory network model (LSTM) are compared with Weihe River Basin as an example,and the LSTM model is selected as the optimal forecasting model.Principal component analysis and gray correlation analysis are used for secondary screening of the input terms to form a model coupling principal component analysis,gray correlation analysis,and LSTM.The results show that:①the fitting accuracy of LSTM is higher than that of SVR;②the secondary screening of the input terms improves the forecast accuracy,and the forecast accuracy of the coupled model is better than that of the single model,specifically,the model accuracy evaluation indexes of the coupled model are substantially improved compared with those of the single model;③the Nash efficiency coefficient and deterministic coefficient of the coupled model of gray system correlation analysis are improved by 0.13% and 0.03%,respectively,compared with those of the coupled model of principal component analysis,and the standard deviation ratio of observed values is improved by 42.9%.The study shows that the secondary factor screening by using gray correlation can effectively improve forecast accuracy.…”
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Correction of delays in channels of information-measuring system by methods of digital signal processing by analysis of harmonics of current and voltage by B. V. Chuvykin, M. M. Nikiforov

“…In conclusion, recommendations are given to reduce the amount of processor memory in the implementation of the algorithm.…”
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Asymptotic stability analysis of a fractional epidemic model for Ebola virus disease in Caputo sense by Samson Olaniyi, Furaha M. Chuma, Sulaimon F. Abimbade

“…This result is significant for fighting and preventing Ebola epidemic in the population, since the Caputo derivative operator allows for effective description of the disease dynamics with memory, where the future evolution of the disease is governed by its prior history. …”
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Diagnosis of depression based on facial multimodal data by Nani Jin, Renjia Ye, Peng Li

“…We use spatiotemporal attention module to enhance the extraction of visual features and combine the Graph Convolutional Network (GCN) and the Long and Short Term Memory (LSTM) to analyze the audio features. Through the multi-modal feature fusion, the model can effectively capture different feature patterns related to depression.ResultsWe conduct extensive experiments on the publicly available clinical dataset, the Extended Distress Analysis Interview Corpus (E-DAIC). …”
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A Novel Deep Learning-Based Data Analysis Model for Solar Photovoltaic Power Generation and Electrical Consumption Forecasting in the Smart Power Grid by Camille Franklin Mbey, Felix Ghislain Yem Souhe, Vinny Junior Foba Kakeu, Alexandre Teplaira Boum

“…Moreover, we have proposed a novel hybrid deep learning method based on multilayer perceptron (MLP), long short-term memory (LSTM), and genetic algorithm (GA). We then simulated all the deep learning methods on a climate and electricity consumption dataset for the city of Douala. …”
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Enigma of Retrotransposon Biology in Mammalian Early Embryos and Embryonic Stem Cells by Ying Yin, Liquan Zhou, Shuiqiao Yuan

“…In addition, retrotransposons may mediate epigenetic memory, regulate gene expression posttranscriptionally, defend virus infection, and so on. …”
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An Automatic System for Atrial Fibrillation by Using a CNN-LSTM Model by Fengying Ma, Jingyao Zhang, Wei Chen, Wei Liang, Wenjia Yang

“…The model combines convolutional neural networks (CNN) to extract local correlation features and uses long short-term memory networks (LSTM) to capture the front-to-back dependencies of electrocardiogram (ECG) sequence data. …”
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Improving Network Security: An Intelligent IDS with RNN-LSTM and Grey Wolf Optimization by murtadha ali

“…Therefore, for such we recommend an IDS that merges the Grey Wolf Optimization (GWO) algorithm and Recurrent Neural Networks with Long Short-Term Memory (RNN-LSTM). RNN-LSTM to Handle Dynamic Network data, but not provided enough complain details in model training. …”
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Television in and After the Archive: Catalogues, Databases, Interfaces and Other Ways to Organize Audiovisual Records by Giulia Taurino, Georgia Aitaki

“…Significant attention is given to the technocultural transformation of the archival work in light of digital and algorithmic practices, emphasizing how these innovations contribute to the making of cultural identities and collective memory while also raising questions on the circulation of television content after its initial broadcasting lifecycle. …”
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A Spatiotemporal Graph Transformer Network for real-time ball trajectory monitoring and prediction in dynamic sports environments by Zujian Li, Dan Yu

“…Our future work aims to enhance memory efficiency and optimize multi-scenario inference speed to broaden the model’s deployment in edge computing environments.…”
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Safeguards-related event detection in surveillance video using semi-supervised learning approach by Se-Hwan Park, Byung-Hee Won, Seong-Kyu Ahn

“…Each module utilizes an autoencoder with a memory module positioned between an encoder and an decoder of the autoencoder. …”
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An Efficient Approach to Mining Maximal Contiguous Frequent Patterns from Large DNA Sequence Databases by Md. Rezaul Karim, Md. Mamunur Rashid, Byeong-Soo Jeong, Ho-Jin Choi

“…The experimental results show that our proposed approach is memory-efficient and mines maximal contiguous frequent patterns within a reasonable time.…”
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Poetry is a subject as precise as geometry: A poetic deconstruction of Psalms 23, 51 and 137 by Mlamli Diko, Adelheid Bechtold Celliers

“…The hideous imagery of dashing infants against rocks mirrors the profundity of their suffering and the complex interplay between memory, loss and the pursuit of justice. This scholarly discourse navigates the intricate tapestry of these Psalms, uncovering the profound themes, sensibilities and transformative power that are profoundly entrenched within the poetic expressions of these ancient voices. …”
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Application of CNN-LSTM Model for Vehicle Acceleration Prediction Using Car-following Behavior Data by Shuning Tang, Yajie Zou, Hao Zhang, Yue Zhang, Xiaoqiang Kong

“…Then the convolutional neural network (CNN) and long short-term memory (LSTM) network are applied to predict vehicle acceleration. …”
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DLD: An Optimized Chinese Speech Recognition Model Based on Deep Learning by Hong Lei, Yue Xiao, Yanchun Liang, Dalin Li, Heow Pueh Lee

“…To improve the performance of offline Chinese speech recognition, we propose a hybrid acoustic model of deep convolutional neural network, long short-term memory, and deep neural network (DCNN-LSTM-DNN, DLD). …”
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