Application of Music Information Analytic Guiding System Based on HCI and 3D Data Mining

Author(s):  
Minghui Niu
2014 ◽  
Vol 543-547 ◽  
pp. 1799-1802
Author(s):  
Yi Liu

This paper introduces the system structure of computer statistical perspective virtual simulation, and establishes an application database using parameter modification and optimization method. Then, a complex computer fluid solid coupling simulation model is established by using ANSYS software, and the mining results of computer streamline 3D data is obtained by the establishment of the fluid and solid domains data interface. At the same time, the computer virtual simulation system of statistical perspective is applied to the process of handball players training index data mining, and we will get the analysis curve of computer training resistance data mining. Finally, we establish the handball training intensity parameter storage library, to provide the technical reference for the handball athletes.


Author(s):  
Li Shen ◽  
Fillia Makedon

Recent technological advances in 3D digitizing, noninvasive scanning, and interactive authoring have resulted in an explosive growth of 3D models in the digital world. There is a critical need to develop new 3D data mining techniques for facilitating the indexing, retrieval, clustering, comparison, and analysis of large collections of 3D models. These approaches will have important impacts in numerous applications including multimedia databases and mining, industrial design, biomedical imaging, bioinformatics, computer vision, and graphics. For example, in similarity search, new shape indexing schemes (e.g. (Funkhouser et al., 2003)) are studied for retrieving similar objects from databases of 3D models. These shape indices are designed to be quick to compute, concise to store, and easy to index, and so they are often relatively compact. In computer vision and medical imaging, more powerful shape descriptors are developed for morphometric pattern discovery (e.g., (Bookstein, 1997; Cootes, Taylor, Cooper, & Graham, 1995; Gerig, Styner, Jones, Weinberger, & Lieberman, 2001; Styner, Gerig, Lieberman, Jones, & Weinberger, 2003)) that aims to detect or localize shape changes between groups of 3D objects. This chapter describes a general shape-based 3D data mining framework for morphometric pattern discovery.


2021 ◽  
Vol 20 (2) ◽  
pp. 265
Author(s):  
Tria Hikmah Fratiwi ◽  
Made Sudarma ◽  
Nyoman Pramaita

Musik instrumen gamelan angklung Bali lewat gelombang bunyi yang dihasilkannya mampu menginterferensi gelombang pikiran manusia untuk menurunkan frekuensi gelombang yang dipancarkan oleh otak. Tujuannya untuk mempengaruhi kondisi psikologi yang berkaitan dengan suasana hati agar mengarah pada tingkat stress positif dengan tingkat energi rendah maupun tinggi. Musik dengan tingkat stress positif dan tingkat energi rendah masuk ke dalam kategori suasana hati tenang atau contentment, jika tingkat stress positif dan tingkat energi tinggi masuk ke dalam kategori suasana hati senang atau exuberance. MIR (Music Information Retrieval) adalah bagian dari Data Mining yang menggali informasi mengenai data musik, salah satunya yaitu klasifikasi suasana hati yang diinterpretasikan oleh potongan data musik. Penelitian ini merancang dan membangun sistem klasifikasi untuk mendeteksi suasana hati musik instrumen gamelan angklung Bali menggunakan algoritma K-NN dan K-NN berbasis Algoritma Genetika. K-NN dapat mengatasi masalah klasifikasi dengan baik, namun dibalik keunggulannya, pengaturan nilai k yang sangat sensitif menjadi sebuah kelemahan.  Menerapkan operasi genetika oleh Algoritma Genetika pada sistem klasifikasi K-NN berhasil mengoptimasi penentuan nilai k optimal, serta memperbaiki hasil akurasi klasifikasi. Berdasarkan dataset training dan dataset testing yang sama, K-NN memberikan persentase akurasi tertinggi sebesar 81,08% (k=6), sedangkan K-NN berbasis Algoritma Genetika memberikan persentase akurasi tertinggi sebesar 89,19% (k=4).


Author(s):  
Douglas L. Dorset

The quantitative use of electron diffraction intensity data for the determination of crystal structures represents the pioneering achievement in the electron crystallography of organic molecules, an effort largely begun by B. K. Vainshtein and his co-workers. However, despite numerous representative structure analyses yielding results consistent with X-ray determination, this entire effort was viewed with considerable mistrust by many crystallographers. This was no doubt due to the rather high crystallographic R-factors reported for some structures and, more importantly, the failure to convince many skeptics that the measured intensity data were adequate for ab initio structure determinations.We have recently demonstrated the utility of these data sets for structure analyses by direct phase determination based on the probabilistic estimate of three- and four-phase structure invariant sums. Examples include the structure of diketopiperazine using Vainshtein's 3D data, a similar 3D analysis of the room temperature structure of thiourea, and a zonal determination of the urea structure, the latter also based on data collected by the Moscow group.


2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  

2010 ◽  
Vol 24 (2) ◽  
pp. 112-119 ◽  
Author(s):  
F. Riganello ◽  
A. Candelieri ◽  
M. Quintieri ◽  
G. Dolce

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.


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