Software as a service (SaaS) provides software application vendors Web based delivery model to serve big amount of clients with multi-tenancy infrastructure and sharing architecture so get great benefit from the economy scale. Though SaaS is usually developed highly standardized functionalities many possible, still ask for function variants according their unique business needs through easy configuration customization. Due subscription model, need take well designed strategy enable self...

Traditional music recommender systems are mainly based on users’ interactions, which limit their performance. Particularly, various kinds of content information, such as metadata and description can be used to improve recommendation. However, it remains addressed how fully incorporate the rich auxiliary/side information effectively deal with heterogeneity in it. In this paper, we propose a M ulti-view E nhanced G raph A ttention N etwork (named MEGAN ) for session-based learn informative...

Traditional recommendation methods suffer from limited performance, which can be addressed by incorporating abundant auxiliary/side information. This article focuses on a personalized music recommender system that incorporates rich content and context data in unified adaptive way to address the abovementioned problems. The information includes textual content, such as metadata, tags, lyrics, incorporate users' behaviors, including listening records, playing sequences, sessions. Specifically,...

ABSTRACT Background Problem‐solving ability is an important skill for students to develop in the 21st century. Many previous studies have focused on impact of diverse digital educational games problem‐solving ability. However, there inconsistency findings, with some reporting positive effects game‐based learning (DGBL) ability, while others either found no significant improvement or reported negative effects. Objectives The objective this study was conduct a three‐level meta‐analysis...

Small object detection remains a challenging task due to limited pixel resolution, complex backgrounds, and high sensitivity bounding box variations in aerial images. This study proposed PF DETR, model specifically designed refine small through progressive feature fusion techniques. Central our approach is the S2-CCFF (Cross-Scale Feature Fusion with S2) module, which integrates multi-level features an S2 layer preserve details. Coupled SPDConv downsampling, this module reduces computational...

Large Language Models (LLMs) offer groundbreaking advancements in recommender systems through superior text analysis and decision-making support. However, integrating LLMs into still suffers from the problems of identifier uninterpretability lack transparency. To address these issues fully leverage capabilities LLMs, we propose a chain thought (CoT) based recommendation framework called CoT4Rec which employs as data enhancers for user preference analysis. Initially, design CoT reasoning...

Recommender systems, which aim to provide personalized suggestions for users, have proven be an effective approach cope with the information overload problem existing in many online applications and services. In this paper, we target two specific sequential recommendation tasks, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">next music next new recommendation</i> , predict (new) piece that users would like based on their historical listening...

Various consumer electronics have become indispensable for our daily lives, and they rely heavily on visual content, such as image, to deliver immersive experiences users. However, electronic devices may encounter issues like image corruption, noise interference, or object occlusion, images in be subjected various imperfections, which can addressed by inpainting techniques enhance the experience. In this work, we propose a Flexible Multi-Grained Dilation Network (FMGDN) capture multi-grained...

Interaction testing offers a stable cost-benefit ratio in identifying faults. But many scenarios, the entire test suite cannot be fully executed due to limited time or cost. In these situations, it is essential take importance of interactions into account and prioritize tests. To tackle this issue, biased covering array proposed Weighted Density Algorithm (WDA) developed. find better solution, paper we adopt ant colony optimization (ACO) build prioritized pairwise interaction (PITS). our...

Contextual factors can benefit music recommendation and retrieval tasks remarkably. However, how to acquire utilize the contextual information still need be studied. In this paper, we propose a context aware approach, which recommend appropriate for users' preference music. analogy matrix factorization methods collaborative filtering, proposed approach does not require songs described by features beforehand, but it learns pieces' embeddings (vectors in low-dimensional continuous space) from...

The acoustic recognition module of the unattended ground sensor (UGS) system applied in wild environments is faced with challenge complicated noise interference. In this paper, a small-aperture microphone array (MA)-based target classification system, including hardware architecture and algorithm scheme, designed as node-level for application UGS noisy situation. Starting from analysis signature signal merits reduction, closely arranged microelectromechanical systems MA to improve quality....

Abstract Trajectory inference is a crucial task in single-cell RNA-sequencing downstream analysis, which can reveal the dynamic processes of biological development, including cell differentiation. Dimensionality reduction an important step trajectory process. However, most existing methods rely on features derived from traditional dimensionality methods, such as principal component analysis and uniform manifold approximation projection. These are not specifically designed for fail to fully...

Recently, communication, digital music creation, and computer storage technology has led to the dynamic increasing of online repositories in both number size, where automatic content-based indexing is critical for users identify possible favorite pieces. Timbre recognition one important subtasks such an purpose. Lots research been carried out exploring new sound features describe characteristics a musical sound. The moving picture expert group (MPEG) provides standard set multimedia...

Practical programs share large modules of code. However, many program analyses are ineffective at reusing analysis results for shared code across programs. We present POLYMER, an optimizer to address this problem. POLYMER runs the offline on a corpus training and learns facts over It prunes learnt eliminate intermediate computations then reuses these pruned accelerate other that with corpus. have implemented specified in Datalog, apply it optimize two Java programs: call-graph is flow-...

Recommender systems are important approaches for dealing with the information overload problem in big data era, and various kinds of auxiliary information, including time sequential can help improve performance retrieval recommendation tasks. However, it is still a challenging how to fully exploit such achieve high-quality results users' experience. In this work, we present novel model, called multivariate Hawkes process embedding attention (MHPE-a), which combines temporal point mechanism...

Abstract Ship path planning plays an important role in the intelligent decision-making system which can provide navigation information for ship and coordinate with other ships via wireless networks. However, existing methods still suffer from slow low security problems. In this paper, we propose a second-order model, consists of two main steps, i.e., first-order static global dynamic local planning. Specifically, first create raster map using ArcGIS. Second, is performed on based Dyna-Sarsa(...

In this paper, we introduce a sub-band direction-of-arrival (DOA) estimation method suitable for employment within an automatic bearing tracking system. Inspired by the magnitude-squared coherence (MSC), extend MSC to and propose (SMSC) measure between frequency sub-bands of wideband signals. Then, design DOA which chooses from signals SMSC The simulations demonstrate that has good tradeoff methods narrowband in terms accuracy, spatial resolution, computational cost. proposed was also tested...