The social ideal of “Datong”: ancient China social utopia, or modern foresight project by M. Yu. Zakharov

“…To solve modern grand socio-economic tasks, China needs not only a human being with a more perfect nature and good historical memory, but also the society potential in which all heterogeneous forces will be harmonically united. …”
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Des fromages en friches. Le difficile renouveau de la production fromagère dans une vallée post-industrielle ariégeoise by Tristan Fournier, Olivier Lepiller, Guillaume Simonet

“…It analyzes the conditions of the decline of its production and the blurring of its memory. While, for the last twenty years, this post-industrial valley has turned towards the development of tourism, the article provides an understanding of the constraints that have prevented any renewal of cheese production until recently. …”
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ST-LSTM: A Deep Learning Approach Combined Spatio-Temporal Features for Short-Term Forecast in Rail Transit by Qicheng Tang, Mengning Yang, Ying Yang

“…Therefore, it is significant to develop a more accurate forecast model. Long short-term memory (LSTM) network has been proved to be effective on data with temporal features. …”
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A Description of the Transverse Momentum Distributions of Charged Particles Produced in Heavy Ion Collisions at RHIC and LHC Energies by Jia-Qi Hui, Zhi-Jin Jiang, Dong-Fang Xu

“…By assuming the existence of memory effects and long-range interactions, nonextensive statistics together with relativistic hydrodynamics including phase transition are used to discuss the transverse momentum distributions of charged particles produced in heavy ion collisions. …”
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Traffic Flow Prediction with Rainfall Impact Using a Deep Learning Method by Yuhan Jia, Jianping Wu, Ming Xu

“…Inspired by deep learning methods with more complex model architectures and effective data mining capabilities, this paper introduces the deep belief network (DBN) and long short-term memory (LSTM) to predict urban traffic flow considering the impact of rainfall. …”
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An RBF-LOD Method for Solving Stochastic Diffusion Equations by Samaneh Mokhtari, Ali Mesforush, Reza Mokhtari, Rahman Akbari

“…We apply our approach to tackle challenging problems, including two-dimensional convection-diffusion and Burgers’ equations, resulting in reduced computational and memory requirements. Through rigorous testing against diverse problem sets, our methodology demonstrates efficiency and reliability, underscoring its potential as a valuable tool in solving complex multidimensional stochastic equations. …”
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Accelerated computational implementation of reconciliation for continuous variable quantum key distribution on GPU by Shao-ting LIU, Xiao-kai WANG, Da-bo GUO

“…For the low computing speed of reconciliation for current continuous variable quantum key distribution， CPU＆amp;GPU-parallel reconciliation algorithms was designed based on LDPC of SEC protocol to speed up decoding computing.In order to raise decoding speed without sacrifice reconciliation efficiency,a static two-way cross linked list to efficiently store large scale sparse parity matrix was employed.The simulation experimental results show that the speed of the decoding rate reaches 16.4 kbit/s when the channel SNR is over 4.9 dB and the reliability of the 2×10⁵continuous variable quantum sequence,with reconciliation efficiency of 91.71%.The experimental based on the Geforce GT 650 MB GPU and the 2.5 GHz and 8 GB memory CPU hardware platform.Relative to the only CPU platform,computing speed increased by more than 15 times.…”
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Cardiac Sarcoidosis as an Uncommon Etiology for Posterior Circulation Stroke Presenting with Alexia without Agraphia by Mohankumar Kurukumbi, Lauren Gardiner, Shevani Sahai, John W. Cochran

“…His presenting symptoms included right partial hemianopia, difficulty with naming, memory, and recall, and alexia without agraphia. Cardiogenic stroke is an uncommon manifestation of cardiac sarcoidosis, and given the disabling nature of these sequelae, the importance of early diagnosis and prevention with anticoagulation is crucial to prevent morbidity and mortality.…”
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LSTM vs. Prophet: Achieving Superior Accuracy in Dynamic Electricity Demand Forecasting by Saleh Albahli

“…This study presents a novel hybrid forecasting model that integrates Long Short-Term Memory (LSTM) networks and Prophet models, leveraging their complementary strengths through a dynamic weighted ensemble methodology. …”
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Writing UX requirements in acceptance criteria: extended version of a case study in startups by Jonathan Souza, Luciana Zaina

“…The findings revealed that ACUX im-proved team communication and played the role of a reminder for the developers memory about the relevant aspects of UX to be considered in the requirement specification. …”
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On being uniquely human in the world: a reflection on the contributions of J. Wentzel van Huyssteen by H. Musa

“…Now it remains a token of appreciation in memory of his admirable life and lasting legacy. …”
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Monthly Precipitation Prediction Based on Attention-BiLSTM Model by CHENG Yuxiang, XIAO Liying, WANG Pinggen, LIU Xiangzhou, ZHANG Chenhui

“…Combined with the bidirectional long short-term memory neural network (BiLSTM), an improved attention-BiLSTM model was proposed to predict monthly precipitation. …”
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Research on Intelligent Vehicle Operation Risk Assessment and Early Warning Based on Predictive Risk Field by Ruibin Zhang, Yingshi Guo

“…The temporal feature vector composed of the spatiotemporal state characteristics of the ego vehicle and surrounding traffic participants is taken as input data for the Attention-Bidirectional Long-Short Term Memory (Attention-BiLSTM) model, which is trained to establish the desired mapping relationship. …”
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'Los peces de la amargura' de Fernando Aramburu: Un diálogo transnacional y multidireccional by Rosa Pérez Zancas

“…Para ello, se recurre a conceptos como la ‘Multidirectional Memory’ y ‘The Implicated Subject’, desarrollados por Michael Rothberg. …”
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Anomaly Detection in Moving Crowds through Spatiotemporal Autoencoding and Additional Attention by Biao Yang, Jinmeng Cao, Rongrong Ni, Ling Zou

“…A weighted convolutional autoencoder- (AE-) long short-term memory (LSTM) network is proposed to reconstruct raw data and perform anomaly detection based on reconstruction errors to resolve the existing challenges of anomaly detection in complicated definitions and background influence. …”
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Gain-aware caching scheme for information-centric networking by Long CHEN, Hong-bo TANG, Xing-guo LUO, Yi BAI, Zhen ZHANG

“…The in-network caching system of information-centric networking had to deal with the popularity of huge number of content chunks and make efficient usage of storage resources.A content popularity based caching gain opti-mization model aimed to get maximum reduction of content retrieve cost was established,and a gain-aware caching scheme was proposed.By utilizing filtering effect of cache to request flow is scheme achieves caching cooperation and diversity potentially while maximizing caching gain of every single node.Bloom filter based sliding window strategy captures the content chunks with high caching gain according to request arrival interval and retrieval cost from the source.Analysis shows that the method can drastically reduce memory consumption caused by popularity monitoring.The simu-lation results illuminate that this scheme is well aware of content popularity based caching gain,and gets better band-width saving and cache hit ratio when content popularity is changing dynamically.…”
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Research on Nonlinear Dynamics Modeling and Simulation of Harmonic Gear Drive by Yang Luo, Manyi Chen, Jie Zhang, Ran Yang, Han Zhang

“…In order to improve the dynamic analysis accuracy and transmission performance of harmonic gear drive，considering the nonlinear hysteretic stiffness and dynamic friction phenomenon，a dynamics model of harmonic gear drive based on memory characteristic hysteresis stiffness and LuGre dynamic friction is proposed，and the corresponding simulation model is established. …”
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Compensații morale și financiare pentru supraviețuitorii orfelinatelor by Vișinel Costel Bălan, Maria Roth

“…Beyond the social challenges, this issue is closely intertwined with social policies and national legislation, having deep historical and cultural significance. Individual memory plays a crucial role in reconstructing the past and advancing social justice, with recent studies focusing on the psychological traumas endured by survivors after 1960, as well as the ways in which they shape their identities and reintegrate into society. …”
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Research on the Application of Deep Learning Methods in the Field of Image Classification by Peng Yuhui

“…The application of deep learning methods such as Convolutional Neural Network, Recurrent Neural Networks and Long Short-Term Memory in image classification is also discussed. …”
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Estimation of the probability of informed trading models via an expectation-conditional maximization algorithm by Montasser Ghachem, Oguz Ersan

“…Our results indicate that estimations using the ECM algorithm are generally faster, more accurate, and more memory-efficient than the standard methods used in the literature, making it a robust alternative. …”
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