Optimizing Web-Based AI Query Retrieval with GPT Integration in LangChain A CoT-Enhanced Prompt Engineering Approach

Large Language Models have brought a radical change in the process of remote learning students, among other aspects of educative activities. Current retrieval of remote learning resources lacks depth in contextual meaning that provides comprehensive information on complex student queries. This work proposes a novel approach to enhancing remote learning retrieval by integrating GPT-based models within the LangChain framework. We achieve this system in a more intuitive and productive manner using CoT reasoning and prompt engineering. The framework we propose puts much emphasis on increasing the precision and relevance of the retrieval results to return comprehensive and contextually enriched explanations and resources that best suit each student's needs. We also assess the effectiveness of our approach against paradigmatic LLMs and report improvements in user satisfaction and learning outcomes.

An Electrocardiogram Monitoring Device Based on STM32

Cardiovascular diseases remain the leading cause of morbidity and mortality, particularly in aging populations, with rising rates of heart-related incidents in middle-aged and even younger individuals. Currently available electrocardiogram (ECG) monitoring technologies, such as bedside monitors are bulky and cumbersome, limiting their potential accessibility for continuous, real-time monitoring. Therefore, we propose a portable digital ECG monitoring system that can accurately measure heart rate, analyze the ECG in real-time, and wirelessly send data to the cloud platform. The device comprises a custom-designed circuit to capture ECG signals, with analog-to-digital conversion and heart rate measurement performed by an STM32F429 microcontroller. In addition, real-time monitoring is achieved through the L610-4G module, which transmits data to Tencent Cloud, enabling users to access their ECG data remotely while being notified by instant alerts for abnormal heart rates. Moreover, healthcare professionals can view historic ECG data for further clinical analysis of patient progression and make evidence-based decisions. The proposed system features portability and accuracy, enabling the user to access extended ECG data easily. It provides the ability to minimize redundant clinical assessments, thus offering considerable advantages to patients and healthcare practitioners.