Рівні сформованості музично-артистичного досвіду майбутніх учителів музики та хореографії

The article examines the problem of forming the musical and artistic experience of students of art faculties of pedagogical universities. The importance of future teachers of music and choreography acquiring musical and artistic experience is highlighted, which is animportant problem today, which significantly affects the development of the irinternal and external culture. The structural construction of musical-artistic experience is presented, the important components of which are motivational-directed, competence-informative, andexecutive-projective components.In the process of ascertaining experiment, the levels of formation of musical and artistic experience of students of arts faculties were determined, namely: high, medium, low, which were given qualitative and quantitative characteristics. The powerful influence of aneffective integrative combination of music and movements on the formation of the musical and artistic experience of future teachers of musical art and choreography has been determined, which allows to more intensively perceive the artistic and musical images of artistic works, to find effective means for their more vividembodiment.Keywords: musical and artistic experience, future teachers of music and choreography, for mation of levels, structural construction, creative and executive activity.У статті розглядається проблема формування музично-артистичного досвіду студентів факультетів мистецтв педагогічних університетів. Виокремлено значення набуття майбутніми вчителями музики та хореографії  музично-артистичного досвіду, що є важливою проблемою сьогодення, яка значно впливає на розвиток їх внутрішньої та зовнішньої культури. Наведено  структурну побудову музично-артистичного досвіду, важливими складовими якого виступають мотиваційно-спрямований, компетентнісно-інформативний, та виконавсько-проективний компоненти. У процесі констатувального експерименту визначено рівні сформованості музично-артистичного досвіду студентів факультетів мистецтв, а саме:високий, середній, низький, яким надано якісні та кількісні характеристики. Визначено могутній вплив ефективного інтегративного поєднання музики та рухів на формування музично-артистичного досвіду майбутніх учителів музичного мистецтва і хореографії, що дозволяє інтенсивніше сприймати художньо-музичні образи мистецьких творів, знаходити дієві засоби для їх більш яскравого втілення. Ключові слова: музично-артистичний досвід, майбутні вчителі музики та хореографії, сформованість рівнів, структурна побудова, творчо-виконавська діяльність

How can Deep Learning Retrieve the Write-Missing Additional Diagnosis from Chinese Electronic Medical Record For DRG

The purpose of write-missing diagnosis detection is to find diseases that have been clearly diagnosed from medical records but are missed in the discharge diagnosis. Unlike the definition of missed diagnosis, the write-missing diagnosis is clearly manifested in the medical record without further reasoning. The write-missing diagnosis is a common problem, often caused by physician negligence. The write-missing diagnosis will result in an incomplete diagnosis of medical records. While under DRG grouping, the write-missing diagnoses will miss important additional diagnoses (CC, MCC), thus affecting the correct rate of DRG enrollment. Under the circumstance that countries generally start to adopt DRG enrollment and payment, the problem of write-missing diagnosis is a common and serious problem. The current manual-based method is expensive due to the complex content of the full medical record. We think this problem is suitable to be solved as natural language processing. But to the best of our knowledge, no researchers have conducted research on this problem based on natural language processing methods. We propose a framework for solving the problem of write-missing diagnosis, which mainly includes three modules: disease recall module, disease context logic judgment module, and disease relationship comparison module. Through this framework, we verify that the problem of write-missing diagnosis can be solved well, and the results are interpretable. At the same time, we propose advanced solutions for the disease context logic judgment module and disease relationship comparison module, which have obvious advantages compared with the mainstream methods of the same type of problems. Finally, we verified the value of our proposed framework under DRG medical insurance payment in a tertiary hospital

Improved Total Variation based Image Compressive Sensing Recovery by Nonlocal Regularization

Recently, total variation (TV) based minimization algorithms have achieved great success in compressive sensing (CS) recovery for natural images due to its virtue of preserving edges. However, the use of TV is not able to recover the fine details and textures, and often suffers from undesirable staircase artifact. To reduce these effects, this letter presents an improved TV based image CS recovery algorithm by introducing a new nonlocal regularization constraint into CS optimization problem. The nonlocal regularization is built on the well known nonlocal means (NLM) filtering and takes advantage of self-similarity in images, which helps to suppress the staircase effect and restore the fine details. Furthermore, an efficient augmented Lagrangian based algorithm is developed to solve the above combined TV and nonlocal regularization constrained problem. Experimental results demonstrate that the proposed algorithm achieves significant performance improvements over the state-of-the-art TV based algorithm in both PSNR and visual perception.Comment: 4 Pages, 1 figures, 3 tables, to be published at IEEE Int. Symposium of Circuits and Systems (ISCAS) 201

Selective Combining for Hybrid Cooperative Networks

In this study, we consider the selective combining in hybrid cooperative networks (SCHCNs scheme) with one source node, one destination node and $N$ relay nodes. In the SCHCN scheme, each relay first adaptively chooses between amplify-and-forward protocol and decode-and-forward protocol on a per frame basis by examining the error-detecting code result, and $N_c$ ($1\leq N_c \leq N$) relays will be selected to forward their received signals to the destination. We first develop a signal-to-noise ratio (SNR) threshold-based frame error rate (FER) approximation model. Then, the theoretical FER expressions for the SCHCN scheme are derived by utilizing the proposed SNR threshold-based FER approximation model. The analytical FER expressions are validated through simulation results.Comment: 27 pages, 8 figures, IET Communications, 201