We present the models implemented by the NICA group for the Quantum Computing (QuantumCLEF) Shared Task at CLEF 2024. Our participation focused on Task 1A: Feature Selection (Information Retrieval Task). We propose a ...
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In the fields of intelligent transportation and multi-task cooperation, many practical problems can be modeled by colored traveling salesman problem (CTSP). When solving large-scale CTSP with a scale of more than 1000...
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In the fields of intelligent transportation and multi-task cooperation, many practical problems can be modeled by colored traveling salesman problem (CTSP). When solving large-scale CTSP with a scale of more than 1000 dimensions, their convergence speed and the quality of their solutions are limited. This paper proposes a new hybrid ITÖ (HITÖ) algorithm, which integrates two new strategies, crossover operator and mutation strategy, into the standard ITÖ. In the iteration process of HITÖ, the feasible solution of CTSP is represented by the double chromosome coding, and the random drift and wave operators are used to explore and develop new unknown regions. In this process, the drift operator is executed by the improved crossover operator, and the wave operator is performed by the optimized mutation strategy. Experiments show that HITÖ is superior to the known comparison algorithms in terms of the quality solution.
With the increasing number of Web services, how to provide developers with Web APIs that meet their Mashup requirements accurately and efficiently has become a challenge. Even though the existing methods show improvem...
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Network traffic anomaly detection plays a crucial role in today's network security and performance management. In response to the challenges in current network traffic data processing, such as insufficient structu...
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Chinese Named Entity Recognition (NER) for Electronic Medical Records (EMR) is a fundamental task in building a digital hospital and is widely considered to be a sequence annotation problem in the Natural Language Pro...
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Cloud computing has emerged as a promising mode for storaging vast quantities of big data, which is vulnerable to potential security threats, making it urgent to ensure data confidentiality and integrity auditing. In ...
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Delineation of retinal vessels in fundus images is essential for detecting a range of eye disorders. An automated technique for vessel segmentation can assist clinicians and enhance the efficiency of the diagnostic pr...
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Background:The global impact of the highly contagious COVID-19 virus has created unprecedented challenges,significantly impacting public health and economies *** research article conducts a time series analysis of COV...
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Background:The global impact of the highly contagious COVID-19 virus has created unprecedented challenges,significantly impacting public health and economies *** research article conducts a time series analysis of COVID-19 data across various countries,including India,Brazil,Russia,and the United States,with a particular emphasis on total confirmed ***:The proposed approach combines auto-regressive integrated moving average(ARIMA)'s ability to capture linear trends and seasonality with long short-term memory(LSTM)networks,which are designed to learn complex nonlinear dependencies in the *** hybrid approach surpasses both individual models and existing ARIMA-artificial neural network(ANN)hybrids,which often struggle with highly nonlinear time series like COVID-19 *** integrating ARIMA and LSTM,the model aims to achieve superior forecasting accuracy compared to baseline models,including ARIMA,Gated Recurrent Unit(GRU),LSTM,and ***:The hybrid ARIMA-LSTM model outperformed the benchmark models,achieving a mean absolute percentage error(MAPE)score of 2.4%.Among the benchmark models,GRU performed the best with a MAPE score of 2.9%,followed by LSTM with a score of 3.6%.Conclusions:The proposed ARIMA-LSTM hybrid model outperforms ARIMA,GRU,LSTM,Prophet,and the ARIMA-ANN hybrid model when evaluating using metrics like MAPE,symmetric mean absolute percentage error,and median absolute percentage error across all countries *** findings have the potential to significantly improve preparedness and response efforts by public health authorities,allowing for more efficient resource allocation and targeted interventions.
The prime goal of parallel computing is the simultaneous parallel execution of several program instructions. Consequently, to accomplish this, the program should be divided into independent sets so that each processor...
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Load Forecast (LF) is an important task in the planning, control and application of public power systems. Accurate Short Term Load Forecast (STLF) is the premise of safe and economical operation of a power system. In ...
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