Machine Learning-Based Anomaly Prediction for Proactive Monitoring in Data Centers: A Case Study on INFN-CNAF by Andrea Asperti, Gabriele Raciti, Elisabetta Ronchieri, Daniele Cesini

“…We evaluate several methods, including Long Short-Term Memory, Random Forest, and various neural networks, assessing their Accuracy and sensitivity in distinguishing normal from anomalous behaviors. …”
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AReLU: Agile Rectified Linear Unit for Improving Lightweight Convolutional Neural Networks by Fu Chen, Yepeng Guan

“…But the improvements are achieved with extra memory and computational cost, which is non-negligible for lightweight convolutional networks. …”
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Research on the Indoor Thermal Environment of Industrial Architectural Heritage Based on Human Thermal Comfort—A Case Study in Hefei (China) During Winter by Qiguo Li, Yao Zhang, Chao Wen

“…Considering the increasing demand for urban land and the renewal of idle sites, the reuse of industrial architectural heritage has become an important measure for urban development, while preserving the city’s industrial memory and the authenticity of architectural heritage. …”
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Computerized Adaptive Testing Framework Based on Excitation Block and Gumbel-Softmax by Chengsong Liu, Yan Wei

“…The current algorithms inadequately consider the impact of knowledge concept weights in question and student potential factors (e.g., memory) on question selection. In addition, most algorithms primarily focus on accurately predicting students’ abilities, neglecting critical factors such as concept diversity and question exposure rate, which are essential for model effectiveness. …”
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Management of Complex Root Canal Curvature of Bilateral Radix Entomolaris: Three-Dimensional Analysis with Cone Beam Computed Tomography by Muktishree Mahendra, Anand Verma, Sanjeev Tyagi, Santosh Singh, Kapil Malviya, Ramit Chaddha

“…All canals were instrumented with controlled memory nickel titanium instruments and obturation was done with single cone technique.…”
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Short-Term Inbound and Outbound Passenger Flow Prediction for New Metro Stations Based on Clustering and Deep Learning by Zihe Wang, Yongsheng Zhang, Enjian Yao, Yue Wang, Juncheng Li, Jiantao He

“…In order to solve the above problems, this paper proposes a short-term inbound and outbound passenger flow prediction model for new metro stations at the early stage of operation by combining the K-means clustering algorithm, an improved spatiotemporal long short-term memory model (Sp-LSTM), and a real-time feedback error model (mean absolute error, MAE), where passenger flows’ spatial-temporal characteristics and land-use relevance are considered. …”
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Fractal-Based Robotic Trading Strategies Using Detrended Fluctuation Analysis and Fractional Derivatives: A Case Study in the Energy Market by Ekaterina Popovska, Galya Georgieva-Tsaneva

“…This paper presents an integrated robotic trading strategy developed for the day-ahead energy market that includes different methods for time series analysis and forecasting, such as Detrended Fluctuation Analysis (DFA), Rescaled Range Analysis (R/S analysis), fractional derivatives, Long Short-Term Memory (LSTM) Networks, and Seasonal Autoregressive Integrated Moving Average (SARIMA) models. …”
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Compliance of an Attorney’s Professional Profile with the Current Legislation by O. G. Yushkevych

“…The author has emphasized on the lack of legal enshrinement of such qualities of an attorney as justice, depth of thinking (ability to penetrate into the essence of facts) and breadth of mind (ability to cover a wide range of issues), adherence to principles, presence of own opinion and ability to defend it, memory, critical thinking, imagination, strength of will, independence, persistence, determination, categoricalness, persuasiveness, knowledge of the client’s psyche, anticipation of his possible reactions, oratory skills, accuracy, etc. …”
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A Data-Driven Method for Predicting the Cutterhead Torque of EPB Shield Machine by Kairong Hong, Fengyuan Li, Zhenjian Zhou, Feng Li, Xunlin Zhu

“…Meanwhile, for the stationary driving stage, considering the fact that the key parameters vary smoothly and show obvious inertia, the long short-term memory (LSTM) network method can be used to establish the relationship model between cutterhead torque and other key parameters, such as the thrust force. …”
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A Deployment Method for Motor Fault Diagnosis Application Based on Edge Intelligence by Zheng Zhou, Yusong Qiao, Xusheng Lin, Purui Li, Nan Wu, Dong Yu

“…This paper proposes a novel fault diagnosis approach integrating multi-scale convolutional neural networks (MSCNNs), long short-term memory networks (LSTM), and attention mechanisms to address these challenges. …”
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La politique nationale de réconciliation et de relocalisation des populations déplacées dans le Liban d’après-guerre by Dima de Clerck

“…In addition, the process left little room for victims’ personal grieving through testimony and memory. This article looks at the failure of Lebanon’s state reconciliation policy to encourage displaced populations to return to their home villages and to promote a durable pacification.…”
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The Relationship between School Connectedness and Academic Engagement: Mediating Role of Mindfulness by Rouhollah Aghasaleh, Saba Rasouli Amlashi, S. Abdolvahab Samavi

“…Additionally, mindfulness, a pivotal term in the field of PP, offers noteworthy advantages such as enhancing working memory and reducing stress levels, consequently fostering academic involvement. …”
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A data Mining Approach using CNN and LSTM to Predict Divorce before Marriage by Touba Torabipour, Safieh Siadat, Hosein Taghavi

“…In the current work, we proposed a method to predict divorce by combining a convolutional neural network (CNN) and long short-term memory (LSTM). In this hybrid method, key features in a dataset are selected using CNN layers, and then predicted using LSTM layers with an accuracy of 99.67 percent. …”
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MKER: multi-modal knowledge extraction and reasoning for future event prediction by Chenghang Lai, Shoumeng Qiu

“…The visual language reasoning module extracts the object relationships among the most informative objects and the dynamic evolution of the relationship, which comes from the sequence scene graphs and commonsense graphs. The long short-term memory model is employed to explore changes in the object relationships at different times to form a dynamic object relationship. …”
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Stroke after Initiating IV Penicillin for Neurosyphilis: A Possible Jarisch-Herxheimer Reaction by Vineet Punia, Appaji Rayi, Adithya Sivaraju

“…A 57-year-old man presented with worsening memory. His minimental status examination score was 14/30. …”
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Nuclear Spins in a Solid Exceeding 10-Hour Coherence Times for Ultra-Long-Term Quantum Storage by Fudong Wang, Miaomiao Ren, Weiye Sun, Mucheng Guo, Matthew J. Sellars, Rose L. Ahlefeldt, John G. Bartholomew, Juan Yao, Shuping Liu, Manjin Zhong

“…The observed coherence time is longer than that of any other system suitable for an optical quantum memory. Furthermore, at a much higher temperature of 6 K, we have realized a 6-h coherence time, which has been obtainable using single-stage cryocoolers. …”
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Immune System in the Brain: A Modulatory Role on Dendritic Spine Morphophysiology? by Oscar Kurt Bitzer-Quintero, Ignacio González-Burgos

“…Based on these observations, it has been proposed that these immune mediators are also implicated in learning and memory processes.…”
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Sleep-driven prefrontal cortex coordinates temporal action and multimodal integration by Ahmed Z. Ibrahim, Kareem Abdou, Masanori Nomoto, Kaori Yamada-Nomoto, Reiko Okubo-Suzuki, Kaoru Inokuchi

“…Sleep has a crucial role for memory consolidation and promoting cognitive flexibility. …”
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The Linguistic Landscape of Ulaanbaatar: what Signs and People tell about by Erzhen V. Khilkhanova

“…The analysis also showed an ambivalent attitude towards English and Chinese in and outside the linguistic landscape, which is due to both historical memory and potential threats to the ‘small country’ from powerful neighbors and globalization, which jeopardizes national identity. …”
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Middle-age cerebral small vessel disease and cognitive function in later life: a population-based prospective cohort studyResearch in context by Ali Tanweer Siddiquee, Yoon Ho Hwang, Soriul Kim, Sung Jin Shin, Ji Soo Lee, June Christoph Kang, Min-Hee Lee, Hyeon Jin Kim, Seung Ku Lee, Chol Shin

“…The neuropsychological assessment battery included verbal and visual memory, verbal fluency, Digit Symbol–coding, Trail Making Test–A, and Stroop Test. …”
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