Abstract.Digital Radio Mondiale (DRM) standard is the most mature digital broadcasting system standard all over the world. Due to the limited spectrum characteristics of DRM communication systems, pilot-based DRM channel estimation brings great challenges. In this paper, the channel estimation problem is transformed into a sparse recovery problem by leveraging the compressed sensing problem. Subsequently, the orthogonal matching pursuit (OMP) sparse recovery algorithm is employed to obtain accurate estimation performance with a lower pilot overhead. Compared with the traditional least square algorithm, … Read more →

Abstract.The used car export industry has shown a trend of rapid growth in recent years. The export of used cars involves data pertaining to vehicle information, market demand, logistics, customs, and numerous other aspects. These data are constantly generated in the form of streams, posing challenges to the data processing capabilities of service platforms. Traditional data processing methods struggle to meet the requirements of real-time and large-scale data processing, thus necessitating an efficient streaming data processing architecture. Based on this, this paper proposes a streaming data … Read more →

Abstract.This paper presents a multi-model approach to legal judgment prediction, emphasizing the integration of advanced knowledge techniques to enhance predictive accuracy and interpretability. As the volume of legal data continues to grow, traditional prediction methods often fall short in capturing the complexities of legal reasoning and case outcomes. By combining various modeling strategies, including rule-based systems and machine learning algorithms, this research demonstrates how a multi-model framework can leverage the strengths of different methodologies to provide more reliable predictions. … Read more →

Abstract.The management of legal documents is a paramount challenge for law firms and legal departments, necessitating efficient retrieval methods to enhance productivity and decision-making. Traditional keyword-based search techniques often fall short in addressing the complexities of legal language and context, leading to inefficiencies in accessing relevant information. This paper presents a novel machine learning framework designed specifically for legal document recommendations, aimed at overcoming the limitations of existing retrieval methods. The framework operates through a multi-stage process … Read more →

Abstract.This paper discusses the importance of networked intelligent language laboratory as a new path for language education innovation. It elaborates on its background, technical support (Internet of Things, big data, cloud computing, artificial intelligence technology), advantages (resource sharing and utilization efficiency improvement, personalized learning support, enhanced teaching interaction and feedback, environmental perception and intelligent management), innovative applications (diversified teaching models, intelligent learning assessment, integration of language practice and cultural … Read more →

Abstract.Multi-material 3D printing has revolutionized pharmaceutical tablet manufacturing by enabling unprecedented control over the spatial arrangement of active pharmaceutical ingredients (APIs) and excipients. This systematic review analyzes the significant advances in computational methods and 3D printing technologies for pharmaceutical applications from 2005 to 2024. The review explores the integration of artificial intelligence and evolutionary algorithms in solving complex inverse problems of tablet design, where computational methods achieve better accuracy in predicting drug release profiles. … Read more →

Abstract.Highway travel time, defined as the time difference between a vehicle entering and exiting the highway, is primarily influenced by factors such as the highway's characteristics, current road conditions, and the driver's behavior. Travel time is a crucial parameter for assessing the operational state of a highway and serves as an important reference for both drivers when selecting routes and for traffic managers in implementing control measures. Therefore, predicting highway travel time is of significant importance. Long Short-Term Memory (LSTM) is a type of recurrent neural network, an … Read more →

Abstract.A dial correction method based on perspective and affine transformations for pointer instrument reading recognition using the angle method is proposed to address the error caused by image capture angles. Firstly, Hough circle detection is used to locate the circular instrument and remove background interference. Then, Canny edge detection and least squares method are applied to detect the contour of the instrument dial, and the inner contour is used to extract the dial area. Finally, to correct the distortion of the circular dial into an ellipse due to different shooting angles, projection … Read more →