Supporting Multiple USB Ports Simultaneously 2 USB A output ports 1 USB C input/output port 1 USB B input port or Lightning input port or C input/output port Fast Charging Every port supports fast charging Support QC2.0/QC3.0/QC3+ output Support FCP input/output Support AFC input/output Support SCP input/output Support VOOC input/output Support DRP try.SRC, PD3.0 input/output Support BC1.2,Apple Integrated USB PD2.0/PD3.0 Protocol Support PD2.0 input/output protocol Support PD3.0 input/output and PPS output protocol Support 5V/9V/12V/15V/20V input Support 5V/9V/12V/15V/20V output Support adjustable voltage in 20mV increments in PPS Mode Integrate hardware Bi-phase mark codec (BMC) protocol Integrate Physical Layer protocol Integrate hardware CRC Support Hard Reset Integrates recognition and support of emark cable Power Control Integrated bidirectional BUCK-BOOST NMOS driver Integrated charge-pump to control external NMOS Charge Adaptive charging current adjustment支持3.65V/4.15V/4.2V/4.2V/4.3V/4.35V/4.4V电池支持2/3/4/4/5电池串联支持充电磷酸锂磷酸锂电池(3.65V(3.65V)(boost)to(boost)to boost to(boost)最大输出功率100w
1 Student, 2, 3, 4 Professors, 1,2,3,4 Department of Computer Engineering, 1, 2, 3, 4 Trinity College of Engineering and Research Pune, India Abstract: The modelling of an artificial intelligence (AI)-based enterprise callbot integrates Natural Language Processing (NLP) and Machine Learning (ML) algorithms to automate and enhance customer interactions.该系统使企业能够通过提供实时的个性化响应来有效地管理大量客户查询。CallBot使用NLP来理解和解释用户输入,从而使无缝的对话流以多种语言为单位。机器学习算法,包括受监督和无监督的模型,通过从历史互动中学习并完善其决策过程来提高机器人的响应准确性。基于AI的Callbot采用情感分析来评估呼叫者的情感语气和自适应对话管理,以指导对话实现有效决议。由ML提供支持的预测分析有助于确定客户需求,优化对医疗保健,金融和零售等各种行业的响应。通过使常规任务自动化,Callbot可以降低人类干预和运营成本,同时保持高水平的客户满意度。提出的模型着重于整合最新的NLP技术,例如变形金刚和经常性的神经网络(RNNS),以实现动态对话和上下文理解。该系统旨在随着每次交互的发展而发展,为企业通信提供高效,可扩展和以客户为中心的解决方案。索引术语 - 自然语言处理(NLP)和机器学习(ML),人工智能(AI)