scholarly journals Construction of a Soundscape-Based Media Art Exhibition to Improve User Appreciation Experience by Using Deep Neural Networks

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1170
Author(s):  
Youngjun Kim ◽  
Hayoung Jeong ◽  
Jun-Dong Cho ◽  
Jitae Shin
Keyword(s):  
Deep Neural Networks ◽  
Classical Music ◽  
Test Results ◽  
Media Art ◽  
Art Exhibition ◽  
Van Gogh ◽  
Subjective Satisfaction ◽  
Cognitive Absorption ◽  
Time Distortion ◽  
Weakly Supervised

The objective of this study was to improve user experience when appreciating visual artworks with soundscape music chosen by a deep neural network based on weakly supervised learning. We also propose a multi-faceted approach to measuring ambiguous concepts, such as the subjective fitness, implicit senses, immersion, and availability. We showed improvements in appreciation experience, such as the metaphorical and psychological transferability, time distortion, and cognitive absorption, with in-depth experiments involving 70 participants. Our test results were similar to those of “Bunker de Lumières: van Gogh”, which is an immersive media artwork directed by Gianfranco lannuzzi; the fitness scores of our system and “Bunker de Lumières: van Gogh” were 3.68/5 and 3.81/5, respectively. Moreover, the concordance of implicit senses between artworks and classical music was measured to be 0.88%, and the time distortion and cognitive absorption improved during the immersion. Finally, the proposed method obtained a subjective satisfaction score of 3.53/5 in the evaluation of its usability. Our proposed method can also help spread soundscape-based media art by supporting traditional soundscape design. Furthermore, we hope that our proposed method will help people with visual impairments to appreciate artworks through its application to a multi-modal media art guide platform.

scholarly journals Pengaruh Terapi Musik Klasik Beethoven untuk Mengurangi Kecemasan pada Ibu Bersalin Pre Operasi Sectio Caesar

JKEP ◽  
2018 ◽  
Vol 3 (2) ◽  
pp. 96-107
Author(s):  
Keumalahayati Keumalahayati ◽  
Supriyanti Supriyanti
Keyword(s):  
Cesarean Section ◽  
Music Therapy ◽  
Classical Music ◽  
Statistical Test ◽  
Spiritual Health ◽  
Sectio Caesarea ◽  
Test Results ◽  
Control Groups ◽  
Cesarean Section Delivery ◽  
And Control

Anxiety in preoperative patients with Sectio Caesarea is a specific anxiety, namely concern about operating procedures, anesthesia procedures, information deficits, and concerns about family financial problems, concerns about themselves and the baby to be born. Music is applied into therapy, because music can restore, and maintain physical, mental, emotional, social and spiritual health. The provision of classical music therapy can releases pain and reduces stress levels, so that it can cause a decrease in anxiety. The purpose of this study was to determine the effect of Beethoven classical music therapy to reduce anxiety in cesarean section. This study used a pre-experimental design with the design of two group control interventions. The number of samples in this study were 10 people each in the intervention and control groups. Sampling is done using accidental techniques. Data analysis using the t-dependent test. The t-dependent statistical test results can be concluded that there is a significant influence of classical music therapy to reduce anxiety in cesarean section delivery mothers in the intervention and control groups (P = 0.041). From the results of this study it is known that Beethoven classical music therapy is effective for reducing anxiety, so that nurses can apply classical music therapy in providing care to cesarean section mothers.

A Review of Recent Deep Learning Models in COVID-19 Diagnosis

2021 ◽  
Vol 6 (5) ◽  
pp. 10-15
Author(s):  
Ela Bhattacharya ◽  
D. Bhattacharya
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Deep Learning ◽  
Deep Neural Networks ◽  
Test Results ◽  
Learning Models ◽  
Future Directions ◽  
Human Contact ◽  
The World ◽  
Short Span

COVID-19 has emerged as the latest worrisome pandemic, which is reported to have its outbreak in Wuhan, China. The infection spreads by means of human contact, as a result, it has caused massive infections across 200 countries around the world. Artificial intelligence has likewise contributed to managing the COVID-19 pandemic in various aspects within a short span of time. Deep Neural Networks that are explored in this paper have contributed to the detection of COVID-19 from imaging sources. The datasets, pre-processing, segmentation, feature extraction, classification and test results which can be useful for discovering future directions in the domain of automatic diagnosis of the disease, utilizing artificial intelligence-based frameworks, have been investigated in this paper.

The Media-Art Exhibition TenYearsAfter_v4.0_OuterSpace

Leonardo ◽  
2008 ◽  
Vol 41 (5) ◽  
pp. 454-459
Author(s):  
Soo-jin Lee ◽  
Kwang-yun Wohn
Keyword(s):  
Media Art ◽  
Art Exhibitions ◽  
Art Exhibition ◽  
Research Results ◽  
Mainstream Media ◽  
The Media

TenYearsAfter is an annual media art exhibition based in Korea, begun in 2003, organized by Kwang-yun Wohn and curator Mira Kim to facilitate collaboration among engineers, scientists, artists and designers. Unlike other major media-art exhibitions, TenYearsAfter has included artworks by mainstream media artists, independent experiments, and products and research results by artists and non-artists alike. The fourth exhibition in this series, TenYearsAfter_v4.0_OuterSpace, organized by the authors, was held in 2006. This article elaborates on the process of organizing this event and contemplates the implications of annual media art events in the Korean media art context.

scholarly journals TERAPI MUSIK KLASIK MEMILIKI PENGARUH TERHADAP PERKEMBANGAN KOGNITIF ANAK RETARDASI MENTAL DI SEKOLAH LUAR BIASA (SLB) NEGERI PEMBINA MATARAM

2020 ◽  
Vol 5 (2) ◽  
pp. 123
Author(s):  
Ni Putu Sumartini
Keyword(s):  
Mental Retardation ◽  
Cognitive Development ◽  
Music Therapy ◽  
Classical Music ◽  
Sampling Technique ◽  
P Value ◽  
Test Results ◽  
Purposive Sampling ◽  
Intellectual Function ◽  
Post Test

Anak dengan keterbelakangan mental memiliki fungsi intelektual umum yang secara signifikan berada di bawah rata-rata dan kondisi tersebut memiliki pengaruh terhadap perkembangan kognitif anak. Salah satu terapi yang digunakan untuk meningkatkan kognitif anak terbelakang mental adalah dengan terapi musik. Penelitian ini bertujuan untuk mengetahui pengaruh terapi musik klasik terhadap perkembangan kognitif anak retardasi mental. Penelitian ini dilaksanakan di SLB Negeri Pembina Mataram. Menggunakan preexperimental one group pretest and posttest design dengan jumlah sampel 36 orang dengan teknik purposive sampling. Terapi musik klasik diberikan dua kali selama 30 menit. Pengumpulan data perkembangan kognitif dengan kuesioner pengukuran perkembangan kognitif sederhana, dianalisis menggunakan Wilcoxon Match Pairs Test. Hasil penelitian menunjukkan bahwa perkembangan kognitif anak sebelum intervensi yaitu kategori kurang 61,11%, kategori cukup 25,00%, dan kategori baik 13,89%. Kemudian setelah intervensi menjadi kategori baik 52,78%, kategori cukup 30,55%, dan kategori kurang 16,67%. Berdasarkan hasil uji statistik didapatkan p=0,000. Maka, ada pengaruh terapi musik klasik terhadap perkembangan kognitif anak retardasi mental di SLB Negeri Pembina Mataram. Saran agar terapi musik klasik ini dapat diterapkan sebagai bagian dari terapi pada anak dengan retardasi mental.Child with mental retardation has general intellectual function that is below average significantly and that condition has an effects on the child's cognitive development. One of the therapy used to raises cognitive development of children with mental retardation is music therapy. This research aims to know the effect of classical music therapy on the cognitive development of children with mental retardation. This research has been held in SLB Negeri Pembina Mataram. The design used was quasy experiment with preexperimental one group pre test and post test design. The sample size were 36 samples who selected by purposive sampling technique. Classical music therapy was given twice with the duration of 30 minutes for each session. Data about cognitive development was collected by simple cognitive questionnaire and analyzed with Wilcoxon Match Pairs Test. The average of cognitive development before intervention was 61,11% in the less category, 25,00% in enough category and 13,89% in good category.  And then after intervention in good category is 52,78%, enough category is 30,55% and less category is 16,67%. Statistical test results obtained p value 0,000. Thus, there was an effect of classical music therapy on cognitive development of children with mental retardation. Suggestions that this classical music therapy can applied as part of therapy in children with mental retardation.

scholarly journals A Novel Automated Method for COVID-19 Infection and Lung Segmentation using Deep Neural Networks

2020 ◽  
Author(s):  
Shreyas Mishra
Keyword(s):  
Deep Neural Networks ◽  
Cross Validation ◽  
Automatic Segmentation ◽  
Automated Segmentation ◽  
Test Results ◽  
Similarity Coefficients ◽  
Automated Method ◽  
Learning Techniques ◽  
Near Future ◽  
Lung Ct

Abstract The COVID-19 pandemic first originated in Wuhan, China and has spread to every country in the world. Without a viable cure in the near future, there is an urgent need for rapid diagnosis of COVID-19, faster test results and automated segmentation of infected region in the lungs. The aim of this paper is to assist in the rapid detection and segmentation of COVID-19 patients using deep learning techniques. This paper proposes a method for automatic segmentation of the lung and infected regions of COVID 19 patients using lung CT scan dataset. This has been done using a modified U-Net model along with different cross validation folds. The region of infection which is segmented will contain the lesion, which if identified in the early stages can be beneficial during treatment of the person. This can help doctors to determine the severity of the infection and suggest treatments based on it. A comparative analysis of the proposed architectures has been done against recently published results which proves the superiority of our models in terms of dice similarity coefficients.

Curating Lively Objects: Post-disciplinary Affordances for Media Art Exhibition

2016 ◽  
pp. 31-49
Author(s):  
Caroline Seck Langill ◽  
Lizzie Muller
Keyword(s):  
Media Art ◽  
Art Exhibition

scholarly journals Adversarial Erasing method based on graph neural network

2021 ◽  
Vol 2083 (4) ◽  
pp. 042083
Author(s):  
Shuhan Liu
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Loss Function ◽  
Deep Neural Networks ◽  
Ground Truth ◽  
Semantic Segmentation ◽  
Data Sets ◽  
Recent Developments ◽  
Weakly Supervised ◽  
Network Weight

Abstract Semantic segmentation is a traditional task that requires a large number of pixel-level ground truth label data sets, which is time-consuming and expensive. Recent developments in weakly-supervised settings have shown that reasonable performance can be obtained using only image-level labels. Classification is often used as an agent task to train deep neural networks and extract attention maps from them. The classification task only needs less supervision information to obtain the most discriminative part of the object. For this purpose, we propose a new end-to-end counter-wipe network. Compared with the baseline network, we propose a method to apply the graph neural network to obtain the first CAM. It is proposed to train the joint loss function to avoid the network weight sharing and cause the network to fall into a saddle point. Our experiments on the Pascal VOC2012 dataset show that 64.9% segmentation performance is obtained, which is an improvement of 2.1% compared to our baseline.

scholarly journals Weakly-supervised Convolutional Neural Networks of Renal Tumor Segmentation in Abdominal CTA Images

2020 ◽  
Author(s):  
Guanyu Yang ◽  
Chuanxia Wang ◽  
Jian Yang ◽  
Yang Chen ◽  
Lijun Tang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Renal Cancer ◽  
Deep Neural Networks ◽  
Renal Tumor ◽  
Renal Tumors ◽  
Training Dataset ◽  
Tumor Segmentation ◽  
Human Beings ◽  
Weakly Supervised ◽  
Bounding Boxes

Abstract Background: Renal cancer is one of the ten most common cancers in human beings. The laparoscopic partial nephrectomy (LPN) is an effective way to treat renal cancer. Localization and delineation of the renal tumor from pre-operative CT Angiography (CTA) is an important step for LPN surgery planning. Recently, with the development of the technique of deep learning, deep neural networks can be trained to provide accurate pixel-wise renal tumor segmentation in CTA images. However, constructing the training dataset with a large amount of pixel-wise annotations is a time-consuming task for the radiologists. Therefore, weakly-supervised approaches attract more interest in research. Methods: In this paper, we proposed a novel weakly-supervised convolutional neural network (CNN) for renal tumor segmentation. A three-stage framework was introduced to train the CNN with the weak annotations of renal tumors, i.e. the bounding boxes of renal tumors. The framework includes pseudo masks generation, group and weighted training phases. Clinical abdomina CT angiographic images of 200 patients were applied to perform the evaluation. Results: Extensive experimental results show that the proposed method achieves a higher dice coefficient (DSC) of 0.826 than the other two existing weakly-supervised deep neural networks. Furthermore, the segmentation performance is close to the fully supervised deep CNN. Conclusions: The proposed strategy improves not only the efficiency of network training but also the precision of the segmentation.

scholarly journals PENGARUH MUSIK KLASIK DAN PREFERENSI PRIBADI TERHADAP TEST ANXIETY DAN HASIL TES MEMBACA KOMPREHENSIF SISWA [THE EFFECT OF CLASSICAL MUSIC AND PERSONAL MUSIC PREFERENCE ON TEST ANXIETY AND READING COMPREHENSION TEST RESULTS]

2021 ◽  
Vol 1 (2) ◽  
pp. 86
Author(s):  
Andreas Sigit Pamungkas
Keyword(s):  
Reading Comprehension ◽  
Test Anxiety ◽  
Test Performance ◽  
Classical Music ◽  
Human Life ◽  
Anxiety Level ◽  
Test Results ◽  
Personal Preference ◽  
Comprehension Test ◽  
English Class

<p class="1eAbstract-text">Music is part of human life. Studies show that music influences psychological, cognitive, behavior, and emotion sides of human being. Research shows that music also influences students’ performance on reading comprehension test and test anxiety level. The purpose of this study is to investigate the effect of classical and personal preference music on students’ reading comprehension test performance and test anxiety level at grade XII SMAK 4 PENABUR Jakarta. The experiment design of this study is Pretest Posttest Non-Randomly Assigned Design. The students in experiment group get a treatment that is listening to classical music fifteen minutes before and while doing reading comprehension test. Students in another experiment group get a treatment that is listening personal preference music fifteen minutes before and while doing reading comprehension test in English class. Mean obtained from pretest and posttest of experiment class will be compared with mean from pretest and posttest of control class to explain whether or not they are statistically different. The study shows that classical and personal preference music influence students’ reading comprehension performance and test anxiety. Study also shows that there is negative correlation between students’ test anxiety and reading comprehension performance.</p>

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