OpenAI and ChatGPT, as state-of-the-art languagemodels driven by cutting-edge artificial intelligence technology,have gained widespread adoption across diverse industries. In the realm of computer vision, these models...
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OpenAI and ChatGPT, as state-of-the-art languagemodels driven by cutting-edge artificial intelligence technology,have gained widespread adoption across diverse industries. In the realm of computer vision, these models havebeen employed for intricate tasks including object recognition, image generation, and image processing, leveragingtheir advanced capabilities to fuel transformative breakthroughs. Within the gaming industry, they have foundutility in crafting virtual characters and generating plots and dialogues, thereby enabling immersive and interactiveplayer experiences. Furthermore, these models have been harnessed in the realm of medical diagnosis, providinginvaluable insights and support to healthcare professionals in the realmof disease detection. The principal objectiveof this paper is to offer a comprehensive overview of OpenAI, OpenAI Gym, ChatGPT, DALL E, stable diffusion,the pre-trained clip model, and other pertinent models in various domains, encompassing CLIP Text-to-Image,education, medical imaging, computer vision, social influence, natural language processing, software development,coding assistance, and Chatbot, among others. Particular emphasis will be placed on comparative analysis andexamination of popular text-to-image and text-to-video models under diverse stimuli, shedding light on thecurrent research landscape, emerging trends, and existing challenges within the domains of OpenAI and *** a rigorous literature review, this paper aims to deliver a professional and insightful overview of theadvancements, potentials, and limitations of these pioneering language models.
Hybrid switch reluctance motors are the family of switch reluctance motors (SRMs) that attenuate the magnetic saturation and increase the air gap magnetic flux by exploiting permanent magnets. The permanent magnet aux...
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The photovoltaic cell produces DC power, while residential, industrial loads and most modern equipment typically require AC power. Thus, there is a need for power converters that can efficiently convert DC to AC. Alth...
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The subsynchronous oscillations(SSOs)related to renewable generation seriously affect the stability and safety of the power *** realize the dynamic monitoring of SSOs by utilizing the high computational efficiency and...
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The subsynchronous oscillations(SSOs)related to renewable generation seriously affect the stability and safety of the power *** realize the dynamic monitoring of SSOs by utilizing the high computational efficiency and noise-resilient features of the matrix pencil method(MPM),this paper propos es an improved MPM-based parameter identification with syn *** MPM is enhanced by the angular frequency fitting equations based on the characteristic polynomial coeffi cients of the matrix pencil to ensure the accuracy of the identi fied parameters,since the existing eigenvalue solution of the MPM ignores the angular frequency conjugation constraints of the two fundamental modes and two oscillation ***,the identification and recovery of bad data are proposed by uti lizing the difference in temporal continuity of the synchropha sors before and after noise *** proposed parameter identification is verified with synthetic,simulated,and actual measured phase measurement unit(PMU)*** with the existing MPM,the improved MPM achieves better accuracy for parameter identification of each component in SSOs,better real-time performance,and significantly reduces the effect of bad data.
With the increasing proportion of renewable energy sources(RESs)in power grid,the reserve resource(RR)scarcity for correcting power deviation of RESs has become a potential ***,the power curve of RES needs to be more ...
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With the increasing proportion of renewable energy sources(RESs)in power grid,the reserve resource(RR)scarcity for correcting power deviation of RESs has become a potential ***,the power curve of RES needs to be more rigorously *** RR scarcity varies during different time periods,so the values of assessment indicators should be dynamically *** assessment indicators in this paper include two aspects,i.e.,deviation exemption ratio and penalty ***,this paper proposes a method for dynamically calculating the supply capacity and RR cost,primarily taking into account the operating status of thermal units,forecast information of RES,and load ***,after clarifying the logical relationship between the degree of RR scarcity and the values of assessment indicators,this paper establishes a mapping function between *** on this mapping function,a dynamic setting method for assessment indicators is *** the future,RES will generally be equipped with battery energy storage systems(BESSs).Reasonably utilizing BESSs to reduce the power deviation of RESs can increase the expected income of ***,this paper proposes a power curve optimization strategy for RESs considering self-owned *** case study demonstrates that the dynamic setting method of assessment indicators can increase the revenue of RESs while ensuring that the penalty fees paid by RESs to the grid are sufficient to cover the RR ***,the power curve optimization strategy can help RESs further increase income and fully utilize BESSs to reduce power deviation.
Roads are an important part of transporting goods and products from one place to another. In developing countries, the main challenge is to maintain road conditions regularly. Roads can deteriorate from time to time. ...
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Sampling and communication are both crucial for coordination in multi-agent systems(MASs), with sampling capturing raw data from the environment for control decision making, and communication ensuring the data is shar...
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Sampling and communication are both crucial for coordination in multi-agent systems(MASs), with sampling capturing raw data from the environment for control decision making, and communication ensuring the data is shared effectively for synchronized and informed control decisions across agents. However, practical MASs often operate in environments where continuous and synchronous data samplings and exchanges are impractical, necessitating strategies that can handle intermittent sampling and communication constraints. This paper provides a comprehensive survey of recent advances in distributed coordination control of MASs under intermittent sampling and communication, focusing on both foundational principles and state-of-the-art techniques. After introducing fundamentals, such as communication topologies,agent dynamics, control laws, and typical coordination objectives, the distinctions between sampling and communication are elaborated, exploring deterministic versus random, synchronous versus asynchronous, and instantaneous versus sequential scenarios. A detailed review of emerging trends and techniques is then presented, covering time-triggered, event-triggered,communication-protocol-based, and denial-of-service-resilient coordination control. These techniques are analyzed across various attack models, including those based on data loss, sampled data, time constraints, and topology switching. By synthesizing these developments, this survey aims to equip researchers and practitioners with a clearer understanding of current challenges and methodologies, concluding with insights into promising future directions.
The increasing number of electronic transactions on the Internet has given rise to the design of recommendation systems. The main objective of these systems is to give recommendations to the users about the items (i.e...
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Content-based image retrieval (CBIR) using visual saliency in the pixel domain has shown promising retrieval results at lesser computational cost as features are extracted only from salient regions. CBIR in the JPEG c...
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This study investigates a safe reinforcement learning algorithm for grid-forming(GFM)inverter based frequency *** guarantee the stability of the inverter-based resource(IBR)system under the learned control policy,a mo...
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This study investigates a safe reinforcement learning algorithm for grid-forming(GFM)inverter based frequency *** guarantee the stability of the inverter-based resource(IBR)system under the learned control policy,a modelbased reinforcement learning(MBRL)algorithm is combined with Lyapunov approach,which determines the safe region of states and *** obtain near optimal control policy,the control performance is safely improved by approximate dynamic programming(ADP)using data sampled from the region of attraction(ROA).Moreover,to enhance the control robustness against parameter uncertainty in the inverter,a Gaussian process(GP)model is adopted by the proposed algorithm to effectively learn system dynamics from *** simulations validate the effectiveness of the proposed algorithm.
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