


Open a file in a javascript iframe and detect whether the iframe exists_javascript skills
But if it is iframe[name], it involves onload issues... So it is a lot of trouble....
The following just adds a delay... and does not "really" deal with onload issues... .In fact, it can be solved by looping window.open, but I’m too lazy to do it...^^
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The performance of i77700 is completely sufficient to run win11, but users find that their i77700 cannot be upgraded to win11. This is mainly due to restrictions imposed by Microsoft, so they can install it as long as they skip this restriction. i77700 cannot be upgraded to win11: 1. Because Microsoft limits the CPU version. 2. Only the eighth generation and above versions of Intel can directly upgrade to win11. 3. As the 7th generation, i77700 cannot meet the upgrade needs of win11. 4. However, i77700 is completely capable of using win11 smoothly in terms of performance. 5. So you can use the win11 direct installation system of this site. 6. After the download is complete, right-click the file and "load" it. 7. Double-click to run the "One-click

Python provides the following options to open downloaded files: open() function: open the file using the specified path and mode (such as 'r', 'w', 'a'). Requests library: Use its download() method to automatically assign a name and open the file directly. Pathlib library: Use write_bytes() and read_text() methods to write and read file contents.

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Today I would like to introduce to you an article published by MIT last week, using GPT-3.5-turbo to solve the problem of time series anomaly detection, and initially verifying the effectiveness of LLM in time series anomaly detection. There is no finetune in the whole process, and GPT-3.5-turbo is used directly for anomaly detection. The core of this article is how to convert time series into input that can be recognized by GPT-3.5-turbo, and how to design prompts or pipelines to let LLM solve the anomaly detection task. Let me introduce this work to you in detail. Image paper title: Largelanguagemodelscanbezero-shotanomalydete

WebSocket and JavaScript: Key technologies for realizing real-time monitoring systems Introduction: With the rapid development of Internet technology, real-time monitoring systems have been widely used in various fields. One of the key technologies to achieve real-time monitoring is the combination of WebSocket and JavaScript. This article will introduce the application of WebSocket and JavaScript in real-time monitoring systems, give code examples, and explain their implementation principles in detail. 1. WebSocket technology

Mobile phone PSD files are opened using Photoshop software. PSD is Photoshop's proprietary file format and can retain information such as layers, channels, paths, transparency, etc. Therefore, if you want to open a mobile phone PSD file, first make sure you have installed Photoshop software. First, open the Photoshop software, then click the "File" option in the menu bar, and select "Open" in the pop-up drop-down menu. Next, you need to browse your folders to find the phone where you saved

How to use WebSocket and JavaScript to implement an online reservation system. In today's digital era, more and more businesses and services need to provide online reservation functions. It is crucial to implement an efficient and real-time online reservation system. This article will introduce how to use WebSocket and JavaScript to implement an online reservation system, and provide specific code examples. 1. What is WebSocket? WebSocket is a full-duplex method on a single TCP connection.

01 Outlook Summary Currently, it is difficult to achieve an appropriate balance between detection efficiency and detection results. We have developed an enhanced YOLOv5 algorithm for target detection in high-resolution optical remote sensing images, using multi-layer feature pyramids, multi-detection head strategies and hybrid attention modules to improve the effect of the target detection network in optical remote sensing images. According to the SIMD data set, the mAP of the new algorithm is 2.2% better than YOLOv5 and 8.48% better than YOLOX, achieving a better balance between detection results and speed. 02 Background & Motivation With the rapid development of remote sensing technology, high-resolution optical remote sensing images have been used to describe many objects on the earth’s surface, including aircraft, cars, buildings, etc. Object detection in the interpretation of remote sensing images
