With the rapid development of Large Language Model (LLM) technology, it has become an indispensable force in biomedical data analysis research. However, biomedical researchers currently have limited knowledge about LL...
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The dynamic advancement and harsh environment of coal mines often result in intermittent or regional wireless connection between sending nodes and receiving nodes and then lead to the decrease of transmission success ...
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Earthquakes pose significant perils to the built environment in urban *** avert the calamitous aftermath of earthquakes,it is imperative to construct seismic resilient *** to the intricacy of the concept of urban seis...
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Earthquakes pose significant perils to the built environment in urban *** avert the calamitous aftermath of earthquakes,it is imperative to construct seismic resilient *** to the intricacy of the concept of urban seismic resilience(USR),its assessment is a large-scale system engineering *** assessment of USR should be based on the notion of urban seismic capacity(USC)assessment,which includes casualties,economic loss,and recovery time as *** loss is also included in the assessment of USR in addition to these *** assessment indicator system comprising five dimensions(building and lifeline infrastructure,environment,society,economy,and institution)and 20 indicators has been devised to quantify *** analytical hierarchy process(AHP)is utilized to compute the weights of the criteria,dimensions,and indicators in the urban seismic resilience assessment(USRA)indicator *** the necessary data for a city are obtainable,the seismic resilience of that city can be assessed using this *** illustrate the proposed methodology,a moderate-sized city in China was selected as a case *** assessment results indicate a high level of USR,suggesting that the city possesses strong capabilities to withstand and recover from potential future earthquakes.
Processing police incident data in public security involves complex natural language processing(NLP)tasks,including information *** data contains extensive entity information—such as people,locations,and events—whil...
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Processing police incident data in public security involves complex natural language processing(NLP)tasks,including information *** data contains extensive entity information—such as people,locations,and events—while also involving reasoning tasks like personnel classification,relationship judgment,and implicit ***,utilizing models for extracting information from police incident data poses a significant challenge—data scarcity,which limits the effectiveness of traditional rule-based and machine-learning *** address these,we propose *** collaboration with public security experts,we used de-identified police incident data to create templates that enable large language models(LLMs)to populate data slots and generate simulated data,enhancing data density and *** then designed schemas to efficiently manage complex extraction and reasoning tasks,constructing a high-quality dataset and fine-tuning multiple open-source *** showed that the fine-tuned ChatGLM-4-9B model achieved an F1 score of 87.14%,nearly 30%higher than the base model,significantly reducing error *** corrections further improved performance by 9.39%.This study demonstrates that combining largescale pre-trained models with limited high-quality domain-specific data can greatly enhance information extraction in low-resource environments,offering a new approach for intelligent public security applications.
This work proposed a LSTM(long short-term memory)model based on the double attention mechanism for power load prediction,to further improve the energy-saving potential and accurately control the distribution of power ...
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This work proposed a LSTM(long short-term memory)model based on the double attention mechanism for power load prediction,to further improve the energy-saving potential and accurately control the distribution of power load into each department of the ***,the key influencing factors of the power loads were screened based on the grey relational degree ***,in view of the characteristics of the power loads affected by various factors and time series changes,the feature attention mechanism and sequential attention mechanism were introduced on the basis of LSTM *** former was used to analyze the relationship between the historical information and input variables autonomously to extract important features,and the latter was used to select the historical information at critical moments of LSTM network to improve the stability of long-term prediction *** the end,the experimental results from the power loads of Shanxi Eye Hospital show that the LSTM model based on the double attention mechanism has the higher forecasting accuracy and stability than the conventional LSTM,CNN-LSTM and attention-LSTM models.
The article deals with the integration of Lo(ng) Ra(nge) Wide Area Network (LoRaWAN) sensors with generic manufacturing applications and Industrial Internet of Things (IIoT) use-cases. The focus is on creating a suita...
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Having the ability to perceive load information is a necessary requirement for the effective operation of home energy routers. In order to improve the load intelligent sensing technology for home energy routers, this ...
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Energy router is the key equipment for coordinated management and efficient utilization of multiple energy sources in the energy Internet. This article proposes an efficient energy optimization scheduling method (SSA-...
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Networked microgrids(NMGs)are critical in theaccommodation of distributed renewable ***,theexisting centralized state estimation(SE)cannot meet the demandsof NMGs in distributed energy *** currentestimator is also not...
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Networked microgrids(NMGs)are critical in theaccommodation of distributed renewable ***,theexisting centralized state estimation(SE)cannot meet the demandsof NMGs in distributed energy *** currentestimator is also not robust against bad *** study introducesthe concepts of relative error to construct an improvedrobust SE(IRSE)optimization model with mixed-integer nonlinearprogramming(MINLP)that overcomes the disadvantage ofinaccurate results derived from different measurements whenthe same tolerance range is considered in the robust SE(RSE).To improve the computation efficiency of the IRSE optimizationmodel,the number of binary variables is reduced based on theprojection statistics and normalized residual methods,which effectivelyavoid the problem of slow convergence or divergenceof the algorithm caused by too many integer ***,an embedded consensus alternating direction of multiplier method(ADMM)distribution algorithm based on outer approximation(OA)is proposed to solve the IRSE optimization *** algorithm can accurately detect bad data and obtain SE resultsthat communicate only the boundary coupling informationwith *** tests show that the proposed algorithmeffectively detects bad data,obtains more accurate SE results,and ensures the protection of private information in all microgrids.
To mitigate the impact of factors such as fluctuations in photovoltaic output power and load switching on the voltage of the DC bus, and to enhance the anti-interference capability and response speed of the energy rou...
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