Vibration-induced bias deviation,which is generated by intensity fluctuations and additional phase differences,is one of the vital errors for fiber optic gyroscopes(FOGs)operating in vibration environment and has seve...
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Vibration-induced bias deviation,which is generated by intensity fluctuations and additional phase differences,is one of the vital errors for fiber optic gyroscopes(FOGs)operating in vibration environment and has severely restricted the applications of high-precision *** conventional methods for suppressing vibration-induced errors mostly concentrate on reinforcing the mechanical structure and optical path as well as the compensation under some specific operation parameters,which have very limited effects for high-precision FOGs maintaining performances under *** this work,a technique of suppressing the vibration-induced bias deviation through removing the part related to the varying gain from the rotation-rate output is put ***,the loop gain is extracted out by adding a gain-monitoring *** demodulating the loop gain and the rotation rate simultaneously under distinct frequencies and investigating their quantitative relationship,the vibrationinduced bias error is compensated without limiting the operating parameters or environments,like the applied modulation *** experimental results show that the proposed method has achieved the reduction of bias error from about 0.149°/h to0.014°/h during the random vibration with frequencies from20 Hz to 2000 *** technique provides a feasible route for enhancing the performances of high-precision FOGs heading towards high environmental adaptability.
In view of the insufficient researches on the dynamic change of user trust in existing trust-based recommendation algorithms, a DDPG-TRA algorithm based on deep reinforcement learning and attention mechanism is propos...
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Parkinson’s disease (PD) is a debilitating neurodegenerative disorder affecting millions worldwide. Early detection is vital for effective management, yet remains challenging. In this study, we investigated four dist...
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Under the background of information overload, recommendation system can provide decision-making tools for information producers to promote information and information consumers to obtain personalized preference inform...
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Software is a crucial component in the communication systems,and its security is of paramount ***,it is susceptible to different types of attacks due to potential ***,significant time and effort is required to fix suc...
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Software is a crucial component in the communication systems,and its security is of paramount ***,it is susceptible to different types of attacks due to potential ***,significant time and effort is required to fix such *** propose an automated program repair method based on controlled text generation ***,we utilize a fine-tuned language model for patch generation and introduce a discriminator to evaluate the generation process,selecting results that contribute most to vulnerability ***,we perform static syntax analysis to expedite the patch verification *** effectiveness of the proposed approach is validated using QuixBugs and Defects4J datasets,demonstrating significant improvements in generating correct patches compared to other existing methods.
Seismic activity presents characteristics such as relatively concentrated distribution, high destructiveness, huge secondary hazards, complex change patterns, and unpredictable future activity conditions. It is of gre...
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With the rapid development of blockchain applications, the data that need to be stored increases dramatically, and the blockchain is about to face the problem of storage limitations. To deal with this problem, this pa...
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Click-through rate (CTR) prediction, which aims to estimate the probability of a user to click on a given item, plays a critical role in both recommender systems and online advertising. Recently, a number of deep neur...
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This study employs nine distinct deep learning models to categorize 12,444 blood cell images and automatically extract from them relevant information with an accuracy that is beyond that achievable with traditional **...
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This study employs nine distinct deep learning models to categorize 12,444 blood cell images and automatically extract from them relevant information with an accuracy that is beyond that achievable with traditional *** work is intended to improve current methods for the assessment of human health through measurement of the distribution of four types of blood cells,namely,eosinophils,neutrophils,monocytes,and lymphocytes,known for their relationship with human body damage,inflammatory regions,and organ illnesses,in particular,and with the health of the immune system and other hazards,such as cardiovascular disease or infections,more in *** results of the experiments show that the deep learning models can automatically extract features from the blood cell images and properly classify them with an accuracy of 98%,97%,and 89%,respectively,with regard to the training,verification,and testing of the corresponding datasets.
The study examines the multifaceted determinants influencing a project's community utility, including technological refinement, team dynamics, market feasibility, and funding sources. Crowdfunding, a prominent pat...
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