Tear film,the outermost layer of the eye,is a complex and dynamic structure responsible for tear *** tear film lipid layer is a vital component of the tear film that provides a smooth optical surface for the cornea an...
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Tear film,the outermost layer of the eye,is a complex and dynamic structure responsible for tear *** tear film lipid layer is a vital component of the tear film that provides a smooth optical surface for the cornea and wetting the ocular *** eye syndrome(DES)is a symptomatic disease caused by reduced tear production,poor tear quality,or excessive *** diagnosis is a difficult task due to its multifactorial *** of several clinical tests available,the evaluation of the interference patterns of the tear film lipid layer forms a potential tool for DES *** instrument known as Tearscope Plus allows the rapid assessment of the lipid layer.A grading scale composed of five categories is used to classify lipid layer *** reported work proposes the design of an automatic system employing light weight convolutional neural networks(CNN)and nature inspired optimization techniques to assess the tear film lipid layer patterns by interpreting the images acquired with the Tearscope *** designed framework achieves promising results compared with the existing state-of-the-art techniques.
Gender detection assumes a vital role in different spaces, including security, promotion, medical care, and the human-PC connection. This examination paper presents a strong, constant gender detection framework in lig...
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This paper proposes an improved version of the Partial Reinforcement Optimizer(PRO),termed *** LNPRO has undergone a learner phase,which allows for further communication of information among the PRO population,changin...
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This paper proposes an improved version of the Partial Reinforcement Optimizer(PRO),termed *** LNPRO has undergone a learner phase,which allows for further communication of information among the PRO population,changing the state of the PRO in terms of ***,the Nelder-Mead simplex is used to optimize the best agent in the population,accelerating the convergence speed and improving the accuracy of the PRO *** comparing LNPRO with nine advanced algorithms in the IEEE CEC 2022 benchmark function,the convergence accuracy of the LNPRO has been *** accuracy and stability of simulated data and real data in the parameter extraction of PV systems are *** to the PRO,the precision and stability of LNPRO have indeed been enhanced in four types of photovoltaic components,and it is also superior to other excellent *** further verify the parameter extraction problem of LNPRO in complex environments,LNPRO has been applied to three types of manufacturer data,demonstrating excellent results under varying irradiation and *** summary,LNPRO holds immense potential in solving the parameter extraction problems in PV systems.
Handwritten documents generated in our day-to-day office work, class room and other sectors of society carry vital information. Automatic processing of these documents is a pipeline of many challenging steps. The very...
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People who lead hectic lives daily suffer from a variety of illnesses, including diabetes, high blood pressure, hypertension, etc. For someone to survive, they must become aware of these illnesses promptly. The Intern...
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3GPP edge and fog computing paradigms provide computational services to users at low latency. These paradigms alone are not enough to fulfill the users’ requirements completely. Therefore, a federation among these co...
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This study introduces a novel multi-context approach to water quality assessment by examining the factors influencing Chemical Oxygen Demand in Varthur Lake, Bangalore. Integrating traditional regression techniques wi...
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作者：
Sharma, MansiPuri, ChetanKumar, Praveen
Department of Computer Science and Design Wardha India
Department of Computer Science and Medical Engineering Wardha India
In today's data-driven world, data visualization has emerged as a powerful tool for transforming raw data into actionable insights. This paper explores the profound impact of data visualization across various indu...
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Recently, Rumor Spreading over Online Social Media is found as one of the serious issue, which causes severe damage to society, organization and individuals. To control the rumor spread, rumor detection is found as on...
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Unmanned Aerial Vehicles (UAVs) have extensive applications such as logistics transportation and aerial photography. However, UAVs are sensitive to winds. Traditional control methods, such as proportional- integral-de...
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Unmanned Aerial Vehicles (UAVs) have extensive applications such as logistics transportation and aerial photography. However, UAVs are sensitive to winds. Traditional control methods, such as proportional- integral-derivative controllers, generally fail to work well when the strength and direction of winds are changing frequently. In this work deep reinforcement learning algorithms are combined with a domain randomization method to learn robust wind-resistant hovering policies. A novel reward function is designed to guide learning. This reward function uses a constant reward to maintain a continuous flight of a UAV as well as a weight of the horizontal distance error to ensure the stability of the UAV at altitude. A five-dimensional representation of actions instead of the traditional four dimensions is designed to strengthen the coordination of wings of a UAV. We theoretically explain the rationality of our reward function based on the theories of Q-learning and reward shaping. Experiments in the simulation and real-world application both illustrate the effectiveness of our method. To the best of our knowledge, it is the first paper to use reinforcement learning and domain randomization to explore the problem of robust wind-resistant hovering control of quadrotor UAVs, providing a new way for the study of wind-resistant hovering and flying of UAVs. IEEE
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