With the development of AI technology in recent years, Neural Networks have been used task algorithmic music composition and achieved desirable results. Music is highly associated with human emotion, however, there are few attempts intelligent scene expressing different emotions. In this work, Biaxial LSTM networks to generate polyphonic music, thought LookBack also introduced into architecture improve long-term structure. Above all, we design a novel system for emotional generation manner...

In low signal-to-noise ratio (SNR) acoustic scenarios, it remains fairly challenging to extract the target speech from its noisy mixture. this paper, we propose a collaborative-style framework, namely, filtering and refining network (FRNet) for single-channel enhancement, recovering complex spectrum of coarse fine-grained perspectives. Specifically, devise two-branch structure dubbed filtering-refining module (FRM). block, phase impact is ignored, only focus on in magnitude domain. instead...

Existing news recommendation methods suffer from sparse and weak interaction data, leading to reduced effectiveness explainability. Knowledge reasoning, which explores inferential trajectories in the knowledge graph, can alleviate data sparsity provide explicitly recommended explanations. However, brute-force pre-processing approaches used conventional are not suitable for fast-changing recommendation. Therefore, we propose an explainable model: Reinforced Contrastive Heterogeneous Network...

Objectives This study aimed to conduct a thorough analysis of fluid retention-associated adverse events (AEs) associated with BCR::ABL inhibitors. Design A retrospective pharmacovigilance study. Setting Food and Drug Administration Adverse Event Reporting System (FAERS) database for inhibitors was searched from 1 January 2004 30 September 2021. Main outcome measures OR (ROR) 95% CI were used detect the signals. ROR calculated by dividing odds retention event reporting target drug all other...

Traditional text document clustering methods represent documents with uncontextualized word embeddings and vector space model, which neglect the polysemy semantic relation between words. This paper presents a novel method to deal these problems. Firstly, pre-trained language representation model Bidirectional Encoder Representations from Transformers (BERT) is utilized generate sentence embeddings. Then, two sentence-level weighting schemes based on named entity are designed enhance...

Topic Detection and Tracking technique (TDT) has been commonly used to identify the hot topics from huge volume of Internet news information keep up with news. However, traditional topic detection tracking methods have shown low accuracy efficiency. In this paper, a system driven by big data is built on Spark platform, which aims at improving efficiency collecting tasks. This can be easily employed in distributed architecture work as parallelized system. An improved density-based spatial...

Bone conduction devices are used in audiometric tests, hearing rehabilitation, and communication systems. The mechanical impedance of the stimulated skull location affects performance bone devices. In present study, impedances mastoid condyle were measured 100 Chinese subjects aged from 22 to 67 years. results show that within same subject differ significantly differences between at stimulation position mainly below resonance frequency. is influenced by age, not related gender or body mass...

There are many features that make music composition a challenging task for computer science. people trying to generate in different methods which generated do not match rules. This paper uses theory grammar combined with LSTM neural network jazz music. We use the interval, duration, and note category information as input data of model what parsed from midi files. The generates sequence notes according transition probability, then parse it grammar. Through improve aspect our system can...

Existing knowledge graph-based recommendation algorithms either use Knowledge Graphs (KGs) as auxiliary information or KG prediction tasks regular terms to constrain with multi-task learning. However, the first method, which introduces multi-hop neighbors enhance item representations, also weakens relationship within individual triples some extent. The second method ignores neighboring and thus fails capture long-range connectivity between items, leads a lack of utilization structural in KG....

Recommendation system has been paid growing attention in the academia community and industry because it can solve problem of information overload. Among a variety methods, click-through rate prediction model plays an important role predicting user's to specific item. To predict rate, high-dimensional sparse features are usually adopted, accuracy result depends on combination high-order great extent. Therefore, many methods have proposed find low-dimensional representation from original...

Abstract Pattern synthesis of the sparse linear array (SLA) has played an important role when antenna size is extremely limited. Although grid‐based compressed sensing (CS) algorithms have been widely utilised to synthesise SLA, performance greatly affected by grid mismatch problem. To solve problem, a reweighted gridless CS (RGCS) algorithm based on atomic norm minimisation and rotational invariance propagator method introduced. In RGCS algorithm, number elements can be efficiently reduced...

With the development of deep neural networks, automatic music composition has made great progress. Although emotional can evoke listeners' different auditory perceptions, only few research studies have focused on generating music. This paper presents EmotionBox -a music-element-driven generator based psychology that is capable composing given a specific emotion, while this model does not require dataset labeled with emotions as previous methods. In work, pitch histogram and note density are...

Abstract Knowledge graph (KG)-based recommendation methods effectively alleviate the data sparsity and cold-start problems in collaborative filtering. Among these methods, neighborhood-based are mainstream methods. However, ignore some meta-information about items, specifically, diversity of item information (e.g., texts) feature interaction between neighboring nodes. In this paper, we propose a Bilinear Knowledge-aware Graph Neural Network Fusing Text Information (BKGNN-TI), which can model...

Personalised news recommendation comprises two crucial components: understanding and user modelling. Previous studies have attempted to model interests using various internal information external knowledge graphs (KG). However, they overlooked the collaborative function of KG among diverse behaviours, resulting in serious cold-start problems poor interpretability interests. To address these issues, this article proposes a novel approach called Relation-Aware Approach based on Multi-view News...

In the era of intelligent media, we all need high quality image or video information. However, due to limitation bandwidth storage resource, usually use low bit rate coding technology for compression. But distortion caused will bring in a visually inferior experience, and actual information obtained is often not sufficient. Therefore, super-resolution reconstructed researched provide higher dynamic variation range. Based on reconstruction, this paper proposes two targeted compression...

Onset detection is the foundation and key to high-level audio processing like music retrieval transcription. Research shows that algorithm associated with instrument category, high accuracy can be achieved in recognition studies. Thus adaptive system based on was proposed this paper. The uses HMM classifier identify input falling into four categories, adaptively adopts suitable for each type, output onset times end. experiment results show evaluation values, such as F-measure value, have...

The ability to localize a sound source is very important in our daily life, specifically analyze auditory scenes complex acoustic environments. concept of minimum audible angle (MAA), which defined as the smallest detectable difference between incident directions two sources, has been widely used research fields perception measure localization ability. Measuring MAAs usually involves reference and either large number loudspeakers or movable order reproduce sources at predefined directions....

Musical information retrieval is one of the hot issues in field. In this paper, we design and implement a musical system by humming based on Bayesian decision. This uses cent as its query feature, adopts decision key algorithm after data mining processing. The experimental results show that has good performance, songs can be retrieved spot.

With the development of mobile internet and improvement culture life standards, people are no longer satisfied with traditional applications based on pictures text. Video audio have gradually become focus development. In this paper, we design implement a karaoke system Android platform. The is typical C/S mode, client has functions song retrieval (including humming search), recording, MV singing score, server uses classic JavaEE three tier architecture which consists Struts, Spring...

Nowadays, news spreads faster than it is consumed. This, alongside the rapid cycle and delayed updates, has led to a challenging cold-start issue. Likewise, user problem, due limited engagement, long hindered recommendations. To tackle both of them, we introduce Symmetric Few-shot Learning framework for Cold-start News Recommendation (SFCNR), built upon self-supervised contrastive enhancement. Our approach employs symmetric few-shot learning towers (SFTs) transform warm user/news attributes...

To convert printed music score into a machine-readable format, system that can automatically decode the symbolic image and play is proposed. The takes as input, segments symbols after preprocessing image, then recognizes their pitch duration. Finally, MIDI files are generated. experiments on Rebelo Database shows proposed method obtains superior recognition accuracy against other methods.

Traditional recommendation algorithms suffer from the problems of cold-start users and data sparsity, which significantly degrade prediction accuracy. This paper proposes a novel method CUNE-bias(Collaborative User Network Embedding with bias) to resolve these issues. Firstly, top-k semantic friends are identified only using information user-item feedbacks. Then, we incorporate generated by CUNE into matrix factorization as regularization term. Finally, bias, independent any interactions, is...

Virtual sound localization tests were conducted to examine the effects of stimulation position (mastoid, condyle, supra-auricular, temple, and bone-anchored hearing aid implant position) frequency band (low frequency, high broadband) on bone-conduction (BC) horizontal localization. Non-individualized head-related transfer functions used reproduce virtual through bilateral BC transducers. Subjective experiments showed that at mastoid gave best performance while temple worst in Stimulation...