Select one behavior. Every returned turn has one binary label: Present or Absent. Source: final dense boolean release.
fd54abcf198efcd5657d6498还有什么网址可以免费使用chat-gpt?
对于免费使用ChatGPT，您可以尝试以下网站： 1. OpenAI Playground：这是OpenAI官方提供的一个在线平台，您可以在其中免费使用ChatGPT模型进行文本交互。访问https://play.openai.com/ 进入OpenAI Playground。 2. ChatGPT API Sandbox：OpenAI还提供了一个API沙盒，让您可以免费尝试使用ChatGPT API进行模型交互。更多详细信息和使用说明，请访问https://sandbox.openai.com/。 请注意，这些免费使用选项可能有一些限制，如每分钟的请求次数限制或功能上的限制。如果您需要更大的使用量或更多的功能，请参考OpenAI的定价和许可页面，以了解有关付费计划的详细信息。
12d3f976a5ce67d6a01a0f70
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8"/>
<title>Multiplayer Chat Server</title>
<style>
#publishChat{
background-color: #f2f2f2;
padding: 10px;
border: 1px solid #ccc;
width: 300px;
height: 200px;
overflow-y: scroll;
}
#chatInput{
width: 300px;
padding: 10px;
border: 1px solid #ccc;
}
button{
margin-top: 10px;
padding: 8px 12px;
background-color: #4CAF50;
border: none;
color: white;
cursor: pointer;
}
button:hover{
background-color: #45a049;
}
</style>
</head>
<body>
<h1>Multiplayer Chat Server</h1>
<div id="publishChat"></div>
<input type="text" id="chatInput" placeholder="Type your message here…" />
<button id="sendButton">Send</button>
<script id="chat-app">
var chatApp = new function(){
var publishChatElement = document.getElementById("publishChat");
var chatInputElement = document.getElementById("chatInput");
var sendButtonElement = document.getElementById("sendButton");
this.init = function(){
sendButtonElement.addEventListener("click", sendMessage);
chatInputElement.addEventListener("keyup", function(event){
if(event.key === "Enter"){
sendMessage();
}
});
};
function sendMessage(){
var message = chatInputElement.value.trim();
if(message !== ""){
publishChatElement.innerHTML += "<p>" + message + "</p>";
publishChatElement.scrollTop = publishChatElement.scrollHeight;
chatInputElement.value = "";
}
}
};
chatApp.init();
</script>
</body>
</html>8266c10e492847bd5b971b6bHelp me rewrite the slide notes, Welcome to licensing project readout. In this presentation, I am going to discuss how we apply artificial intelligence and machine learning to the hiring and onboarding process. What we did for this project including personalizing the onboarding process by leveraging new hire resumes, predicting licensing throughput dynamically and improving total cycle time estimate.
Welcome to the licensing project readout. In this presentation, I will be sharing our use of artificial intelligence and machine learning to enhance the hiring and onboarding process. During this project, we focused on personalizing the onboarding experience by analyzing new hire resumes, predicting licensing throughput in real-time, and enhancing the accuracy of cycle time estimation.
e0138ec1683a640cb27196fdAlong the way to build these three models, we have some key findings. First, it is about the resume. They are two reasons we think why resume is important. Early estimation when they accepted offered, and improve current throughput and total cycle time model. Therefore, streamlining the resume data would be important for us. Second, we found some licensing exam have a larger impact on success rate. By putting additional focus on the moments may improve the licensing passing rate. Third, the current licensing cycle time varies greatly and have a negative impacts on the prediction, we think additional process standardization can enhance the ability to know when new hires will finish the licensing process. We already have some great prediction results, we would like to start to generate monthly predictions to WFP, probably using a report format to begin with. If we have the automatic LARS data input process ready, we can provide daily results to the business through the new licensing UI. Of course, we will continue data cleaning and model improvement. In order to , we do request some help from you. First is addition resume data. Second is historical LARS data, these help us clean the data and improve two models. Third, maybe some licensing training data.
Throughout the development of these three models, we have made several key discoveries. Firstly, we recognized the importance of resumes for two reasons. Firstly, they enable early estimation of candidates upon accepting an offer. Secondly, they contribute to improving the accuracy of our throughput and total cycle time models. Therefore, it is crucial for us to streamline the resume data. Secondly, we identified that certain licensing exams have a significant impact on the success rate. By placing additional focus on these critical moments, we can potentially improve the licensing passing rate. Thirdly, we observed a significant variation in current licensing cycle times, which negatively affects our predictions. We believe that additional process standardization can enhance our ability to accurately predict when new hires will complete the licensing process. We have achieved impressive prediction results so far and plan to generate monthly predictions for workforce planning. Initially, we will present these predictions using a report format. Once the automatic LARS data input process is in place, we can provide daily results to the business through the new licensing UI. We are committed to continuing data cleaning and model improvement to further refine our predictions. In order to further enhance our models, we kindly request your assistance in the following areas: 1. Additional resume data to enhance our analysis. 2. Historical LARS data to support data cleaning and improvements in our models. 3. Potentially, licensing training data that can contribute to the development of our models.
05976aed7e19fb19cfb9b3c8Please feel free to jump in any time if you have any questions.
Please feel free to interrupt and ask any questions you may have at any point during this presentation. Your engagement and input are highly encouraged and appreciated.
15121c6cf07620069cc78a02Thank you for the introduction. Before I start, just want you know please feel free to interrupt and ask any questions you may have at any point during this presentation.
Thank you for your introduction. I want to assure everyone here that throughout this presentation, please feel free to interrupt and ask any questions you may have. Your engagement and input are valuable to us, and we encourage an interactive discussion.
2dc3fd7e5412cb746e1d6cac尝试优化以下代码效率： private PackingInfo getNormalPackingInfoM1(String preEpc, String team, Date gmtConfirm, Long productLineId,
Long productId) {
PackingInfo prePackingInfo = packingInfoMapper.selectByEpc(preEpc, productLineId, productId);
if (prePackingInfo == null) {
log.warn("未查询到该箱码:{},产线id:{},产品id:{}", preEpc, productLineId, productId);
return null;
}
log.info("找到上一个正常采集的箱码:{}", preEpc);
if (Strings.isNotEmpty(team) && null == gmtConfirm) {
// 这是瓶箱工位为NoRead,所以team不为null,gmtConfirm为null,这时应该去复检工位找preEpc这个码,
// 但是因为双轨,不一定是依次采集的.所以需要找这个preEpc码的前后各五箱,如果找出来的共10箱中有且只有一箱team为null的箱码,则可以直接合并
// TODO 如果找出来不止一箱,就无法准确匹配...再议
List<PackingInfo> packingInfos = new ArrayList<>(20);
packingInfos.addAll(packingInfoMapper.listByLimitBefore(productLineId, productId, prePackingInfo.getGmtConfirm(), 1));
packingInfos.addAll(packingInfoMapper.listByLimitAfter(productLineId, productId, prePackingInfo.getGmtConfirm(), 1));
return packingInfos.stream()
.filter(o -> null == o.getTeam() && !o.getEpc().contains(EXCEPTION_SIGNAL))
.findFirst()
.orElse(null);
} else if (Strings.isEmpty(team) && null != gmtConfirm) {
// 这是复检工位为NoRead,所以team为null,gmtConfirm不为null,这时应该去瓶箱工位找preEpc这个码,
return packingInfoMapper.listByLimitAfter(productLineId, productId, prePackingInfo.getGmtScan(), 2)
.stream()
.filter(o -> null != o.getTeam() && !o.getEpc().contains(EXCEPTION_SIGNAL) && null == o.getGmtConfirm())
.findFirst()
.orElse(null);
}
return null;
}以下是对代码的优化建议：
1. 在第一行代码中，通过selectByEpc方法查询packingInfo对象，可以考虑使用索引来提高查询性能。可以在数据库中为epc、productionLineId和productId字段创建索引。
2. 在if语句中，使用Strings.isNotEmpty(team)来检查字符串是否为空，这可能导致使用不必要的方法调用。可以直接使用team != null来检查team是否为空。
3. 在if语句中，通过null == gmtConfirm来检查日期是否为空，可以直接使用gmtConfirm != null来检查。
4. 在if和else if语句块中，分别通过packingInfoMapper的listByLimitBefore和listByLimitAfter方法查询数据，并将结果保存在packingInfos列表中。可以考虑在数据库层面上优化这些查询，使用索引来提高查询性能，并限制查询结果的数量。
5. 在filter方法中，使用o.getEpc().contains(EXCEPTION_SIGNAL)来检查epc是否包含异常信号，这可能导致使用不必要的方法调用。可以将异常信号保存在一个常量中，并直接比较两个字符串是否相等。
6. 在filter方法中，使用null == o.getTeam()来检查team是否为空，可以直接使用o.getTeam() == null来检查。
7. 在filter方法中，使用null == o.getGmtConfirm()来检查gmtConfirm是否为空，可以直接使用o.getGmtConfirm() == null来检查。
8. 在返回null之前，可以考虑通过一个条件表达式来合并判断条件，这样可以避免多次return null。
以下是优化后的代码：
```java
private PackingInfo getNormalPackingInfoM1(String preEpc, String team, Date gmtConfirm, Long productLineId, Long productId) {
PackingInfo prePackingInfo = packingInfoMapper.selectByEpc(preEpc, productLineId, productId);
if (prePackingInfo == null) {
log.warn("未查询到该箱码:{},产线id:{},产品id:{}", preEpc, productLineId, productId);
return null;
}
log.info("找到上一个正常采集的箱码:{}", preEpc);
String EXCEPTION_SIGNAL = "EXCEPTION_SIGNAL";
if (team != null && gmtConfirm == null) {
// 这是瓶箱工位为NoRead,所以team不为null,gmtConfirm为null,这时应该去复检工位找preEpc这个码,
// 但是因为双轨,不一定是依次采集的.所以需要找这个preEpc码的前后各五箱,如果找出来的共10箱中有且只有一箱team为null的箱码,则可以直接合并
// TODO 如果找出来不止一箱,就无法准确匹配...再议
List<PackingInfo> packingInfos = new ArrayList<>(20);
packingInfos.addAll(packingInfoMapper.listByLimitBefore(productLineId, productId, prePackingInfo.getGmtConfirm(), 1));
packingInfos.addAll(packingInfoMapper.listByLimitAfter(productLineId, productId, prePackingInfo.getGmtConfirm(), 1));
for (PackingInfo packingInfo : packingInfos) {
if (packingInfo.getTeam() == null && !packingInfo.getEpc().equals(EXCEPTION_SIGNAL)) {
return packingInfo;
}
}
return null;
} else if (team == null && gmtConfirm != null) {
// 这是复检工位为NoRead,所以team为null,gmtConfirm不为null,这时应该去瓶箱工位找preEpc这个码,
List<PackingInfo> packingInfos = packingInfoMapper.listByLimitAfter(productLineId, productId, prePackingInfo.getGmtScan(), 2);
for (PackingInfo packingInfo : packingInfos) {
if (packingInfo.getTeam() != null && !packingInfo.getEpc().equals(EXCEPTION_SIGNAL) && packingInfo.getGmtConfirm() == null) {
return packingInfo;
}
}
return null;
}
return null;
}
```6e92c31f46711dd3681395e4写一篇建筑师年中工作总结，要求写出今年做的有缺憾的方面，根据今年上半年做的建筑项目，分析产生缺憾的问题和不足产生的原因。以及下半年本人的工作重点和需要关注的工作节点和关键事项。从建筑师角度出发，针对本部门和专业发展现状，从提升产品和服务价值、提高团体整体工作效率、加强合规和风险管理等方面提出具体建议。
建筑师年中工作总结 今年上半年，作为一名建筑师，我参与了多个建筑项目的设计和施工过程。在回顾这段时间的工作中，我发现了一些有缺憾的方面，这些缺憾对项目的顺利进行和质量的提升产生了一定的影响。在此总结中，我将分析这些问题的原因，并提出下半年的工作重点和需要关注的事项。 在今年上半年的建筑项目中，我们遇到了一些缺憾的问题。首先，项目进度存在延迟的情况。原因之一是我们在项目计划和任务分配上没有充分考虑到各个环节的耗时，导致一些工作拖延，从而延缓了整个项目的进度。另外，我们还遇到了一些技术问题，例如某些设计方案存在缺陷，需要进行多次修改和调整，这直接影响了项目的进展。 其次，我们在一些项目中遇到了资料和信息不准确的情况。这给我们的设计和施工带来了很大的困扰，因为我们需要花费额外的时间和精力来纠正这些错误。这些问题的根源在于项目前期调研和交流环节不够充分，导致我们无法获取准确的信息和数据。 在下半年的工作中，我将重点关注以下几个方面。首先，我将更加注重时间管理，合理规划项目计划，并根据实际情况进行任务分配和进度控制，以确保项目能够按时完成。 其次，我将加强与客户和团队成员的沟通和交流。我会更加注重项目前期的调研工作，确保获得准确的信息和数据，从而减少设计和施工过程中的错误和瑕疵。 此外，我认为我们的部门和专业发展还需要在以下几个方面进行提升。首先，我们应该努力提升产品和服务的价值，通过不断改进我们的设计和施工流程，提供更高质量的建筑作品，满足客户的需求。 其次，我们应该注重团队整体工作效率的提升。通过加强团队合作和沟通，提高协同工作的效率，充分发挥团队成员的专长，促进项目的顺利进行。 最后，我们还需要加强合规和风险管理。作为建筑师，在设计和施工过程中，我们必须严格遵守相关的法律法规和标准，确保项目的合规性和安全性。 综上所述，我将在下半年的工作中重点关注时间管理和沟通交流，以解决项目进度延迟和资料不准确的问题。同时，我也认识到我们部门和专业发展中存在的问题，并提出了提升产品和服务价值、提高团体整体工作效率、加强合规和风险管理等方面的建议。通过努力改进，我相信我们可以在下半年取得更好的成绩。
d5885540e531207c40112345Sugiérame 25 títulos de publicaciones de blog de 70 caracteres con esta frase incluida: moda 2023 mujer casual
1. "Las tendencias de moda casual para mujer en el 2023: ¡Looks cómodos y glamorosos!" 2. "¿Qué se llevará en la moda casual de mujer para el 2023? Descúbrelo aquí" 3. "Outfits casuales para mujer en el 2023: Estilo y comodidad se unen" 4. "Moda casual para mujeres en el 2023: Así se lucirán los básicos reinventados" 5. "Tendencias imperdibles de moda casual para mujer en el 2023" 6. "Luce a la moda con estilo casual en el 2023: Ideas para mujeres" 7. "Dale un giro a tu estilo casual de mujer en el 2023: Descubre cómo" 8. "Descubre las prendas imprescindibles en la moda casual de mujer para el 2023" 9. "Outfits casuales para mujeres en el 2023: La clave está en los detalles" 10. "Moda casual femenina en el 2023: ¡Prepárate para marcar tendencia!" 11. "Estilo casual de mujer: Las prendas que arrasarán en el 2023" 12. "Conoce las últimas tendencias de moda casual para mujer en el 2023" 13. "Looks informales y chic: Moda casual para mujer en el 2023" 14. "Moda casual para mujeres en el 2023: Crea tu estilo propio y auténtico" 15. "El futuro de la moda casual para mujer en el 2023: Descubre las novedades" 16. "Outfits casuales para mujer en el 2023: Ideales para cada ocasión" 17. "Tendencias que definirán la moda casual femenina en el 2023" 18. "Descubre cómo lucir a la moda casual en el 2023 siendo una mujer activa" 19. "Moda casual para mujeres en el 2023: Los colores de temporada" 20. "Tendencias en moda casual para mujer: Estilo relajado y sofisticado en el 2023" 21. "Outfits casuales para mujeres en el 2023: Elegancia sin perder la comodidad" 22. "Moda casual inspirada en el 2023: Las prendas must-have para mujeres" 23. "Estilo casual y femenino para el 2023: Ideas para un look impecable" 24. "Las mejores combinaciones de moda casual para mujer en el 2023" 25. "Descubre cómo lograr un look casual de moda para mujeres en el 2023"
38b47007e01b57e1495e8abewhat is computer
A computer is an electronic device that is capable of accepting input data, processing it according to a set of instructions (programs), and producing output information. It consists of hardware components such as a central processing unit (CPU), memory, storage devices, input devices (like a keyboard and mouse), output devices (like a monitor and printer), and software programs that enable it to perform various tasks. Computers are used in a wide range of applications, including personal use, business operations, scientific research, communication, entertainment, and more.