Volume 15 - Issue 3

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IJERD : Volume 15 - Issue 3

(March - 2019)


Anitha K, Dr Parameshachari B D

An Overview of Musical Therapy for Mind and Body Using Various Ragas
  • Abstract
  • Keywords
  • Reference
  • Full Article
Cure the illness or diseases through medicine is a main part of healing process but body and mind response to healing process plays the major role for complete heal. The research work the body and mind response to healing process for a particular illness or diseases with musical therapy is a new domain. In musical therapy Identifying which rage for a particular healing illness or diseases, how much time to play and what time to play are the challenging issue. The mentioned challenges were addressed by notes or swara movement of raga which can be adopt feature extraction techniques from Digital Signal Processing and classification of raga play to a particular healing illness or diseases through various machine learning algorithm. The research work carried on feature extraction techniques from Digital Signal Processing and classification of raga play through various machine learning algorithm review literature and percentage of accuracy in each technique are presented in this paper.
Disease, Music Therapy, Raga, Feature exaction by digital Signal Processing, Machine Learning classification.

[1]. A. Bhattacharjee and N. Sriniwasan, "Hindustani Raga representation and identification: A transition probability based approach," International Journal of Mind, Brain and Cognition, vol. 2, pp. 65-93, 2011.
[2]. Deore, P. J. , "RAGA Identification: A Review" , International Journal of Management and Applied Science (IJMAS), pp. 94 –96 (2016).
[3]. G. K. Koduri, S. Gulati, and P. Rao, "A survey of Raga recognition techniques and improvements to the state of art," in Proc. Conference on Sound and Music Computing, Padova Italy, 2011, pp. 33-40.
[4]. G. Pandey, C. Mishra, and P. Ipe, "Tansen: A system for automatic Raga identification," in Proc. 1st Indian International Conference on Artificial Intelligence, Hyderabad, India, 2003, pp. 1350-1363.
[5]. Koduri, G. K., Gulati, S., &Rao, P. " A Survey Of Raaga Recognition Techniques And Improvements To The State-Of-The-Art", Sound and Music Computing, 2011.

Citation
Anitha K, Dr Parameshachari B D "An Overview of Musical Therapy for Mind and Body Using Various Ragas" published at International Journal of Engineering Research and Development, Volume 15, Issue 3 (March 2019)
MID 1503.067X.0001. India
Page 01-16
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Hala N. Elia, Zeid A. Nima

Self-cleaning concrete doped with nano and micro-size zinc oxide particles
  • Abstract
  • Keywords
  • Reference
  • Full Article
Nano- and micro scale zinc oxide (ZnO) particles were added to a concrete mix to study the effect on the self-cleaning ability of concrete given ZnO'photocatalytic abilities. Real sunlight was used to mimic environmental conditions, and two organic dyes (rhodamine B) and (methylene blue) were utilized as a model for organic pollutants in the air. ZnO particles were prepared in different concentrations (3, 6, 9, 12, 15%) in a proportional ratio to the cement. The results indicated that 6% microscale ZnO was the optimal amount to remove rhodamine B, with the removal efficiency reaching up to 94.5%, and 3% micro ZnO was optimal to remove methylene blue with removal reaching 87%. In contrast, 15% was the optimum concentration of nanoscale ZnO to remove both rhodamine B and methylene blue, with removal efficiency reaching up to 90% and 84.4%, respectfully. Scanning tunneling electron microscopy was used to see ZnO particle distribution on the surface of the prepared concrete.
Zinc oxide, Self-cleaning concrete, Photocatalytic process, rhodamine B, methylene blue.

[1]. Khitab, A.;Alam, M.; Riaz, H. and Rauf, S. ; "Smart Concrete: Review. " ; International Journal of advances in Life Science and Technology, 1 (4): 47-53 (2014).
[2]. Mc Grow-Hill Companies, Inc.; "Concrete"; Reprinted from the McGraw-Hill Encyclopedia of Science and Technology, 10th Edition (2003).
[3]. Kelly, F.J. and Fussell, J.C.; "Air pollution and public health: emerging hazards and improved understanding of risk"; 37(4); pp: 631-649 (2015).
[4]. Adam, L.K.; Lyon, D.Y. and Alvarez, P.J.J. ; "Comparative eco-toxicity of nanoscale TiO2, SiO2 and ZnO water suspensions. " ; Water Research VOl.40 , Issue 19, November (2006).
[5]. Fu, G.; Vary, P.S. and Lin, C-T. ; "Anatase TiO2 nanocomposites for antimicrobial coatings. ; Journal of physical chemistry B, VOl. 109, NO.18 (2005).

Citation
Hala N. Elia, Zeid A. Nima "Self-cleaning concrete doped with nano and micro-size zinc oxide particles" published at International Journal of Engineering Research and Development, Volume 15, Issue 3 (March 2019)
MID 1503.067X.0002. USA
Page 17-22
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Khaldoon H. Alhussayni, Alexander Zamyatin, Ghassan Khazal

Dialogue State Tracking Accuracy Enhancement by Distinguishing Candidate Slot-Value Pairs
  • Abstract
  • Keywords
  • Reference
  • Full Article
Dialogue state tracking (DST) playsa critical role ina task-oriented dialogue system's cycle life. DST follows the goals of the user at each turn through dialogue and summarizes these goals as a semantic frame containing slot-value pairs and dialogue acts, which directly affect the performance and effectiveness of dialogue systems. There are different challenges in DST such as linguistics diversity, dynamic context, and distribution of the dialogue state over candidate values in both slotvalue and dialogue acts that are defined in the ontology.In this paper,we focus on these challenges by combining current and previous user utteranceto figure the distribution of the slot-value pairs and dialogue acts to increase the performance. The WoZ dataset was used for evaluating the proposed model;the implementationof a two-variant was attempted, first by using previous user utterance as an additional encoder in the dialogue and, second, by using the additional score that combines the context of previous user utterance and current user utterance with all candidate slotvalue pairs. The proposed model achieved outperforming results compared with all the state-ofthe- art approaches in the joint goal accuracy by 0.8%, but that is not in the request turn task.
........

[1]. Abhinav Rastogi , Dilek Hakkani-T ¨ ur, L. H. (2017). SCALABLE MULTI-DOMAIN DIALOGUE STATE TRACKING, 561– 568.

[2]. Bohus, D., & Rudnicky, A. (2006). K hypotheses + other" belief updating model. Proceedings of AAAI Workshop on Statistical and Empirical Approaches to Spoken Dialogue Systems, 13–18. Retrieved from https://sites.google.com/site/yiqunhu/Home/distance-metric-learning

[3]. Casanueva, I., Budzianowski, P., Su, P.-H., Mrkšić, N., Wen, T.-H., Ultes, S., … Gašić, M. (2017). A Benchmarking Environment for Reinforcement Learning Based Task Oriented Dialogue Management. CoRR, abs/1711.1. Retrieved from http://arxiv.org/abs/1711.11023

[4]. Hashimoto, K., Xiong, C., Tsuruoka, Y., & Socher, R. (2016). A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks. Retrieved from http://arxiv.org/abs/1611.01587

[5]. Henderson, M., Thomson, B., & Young, S. (2013). Deep neural network approach for the dialog state tracking challenge. SIGDIAL 2013 - 14th Annual Meeting of the Special Interest Group on Discourse and Dialogue, Proceedings of the Conference, 467–471..

Citation
Khaldoon H. Alhussayni, Alexander Zamyatin, Ghassan Khazal "Dialogue State Tracking Accuracy Enhancement by Distinguishing Candidate Slot-Value Pairs" published at International Journal of Engineering Research and Development, Volume 15, Issue 3 (March 2019)
MID 1503.067X.0003. Iraq
Page 23-28
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Sedanur Toraman, T. Y. Katırcıoğlu

Further Characteristic Analysis of the High-Power AC Plasmatron
  • Abstract
  • Keywords
  • Reference
  • Full Article
With our previous publication, characterization of the high-power arc-jet plasma torch was studied. This article attempts to carry out further characterization of the plasma jet using different experimentalresults mainly obtained from different distances ofoptical emission spectroscopy (OES) and different arc power values. Plasmatron works under atmospheric (about one atm) pressure with high-power three phase alternating-current (AC) established in AR&TeCS (ARTECS Anadolu R&D Technology Engineering and Consultancy Company, Ankara University Technopolis). In order to characterize the plasma, the electron temperature (Te) and electron density (ne) were determined by using OES in the range 200 – 1100 nm as defined in the experiment section.......
Plasma diagnostic, Atmospheric plasma, OES, Electron temperature,Electron density

[1]. Tendero C., Tixier C., Tristant P., Desmaison J., Leprince P., Atmospheric pressure plasmas: A review,Spectrochimica Acta Part B 61 2 – 30 (2006).
[2]. Toraman S, Katırcıoğlu T. Y., Terzi Ç., The High-Power Arc-Jet Plasma Generator (Plasma Torch) Characteristics and Performance,International Journal of Engineering Technology and Scientific Innovation, ISSN: 2456-1851, Volume:02, Issue: 04, pp.680-699 (2017).
[3]. Ley H. H., Yahaya A., Raja Ibrahim R. K., Analytical Methods in Plasma Diagnostic by Optical Emission Spectroscopy: A Tutorial Review,Journal of Science and Technology, ISSN: 2229-8460, Vol 6, No 1 (2014).
[4]. Bogaerts A., Neyts E., Gijbels R, Mullen J., Gas Discharge Plasmas and Their Applications,Spectrochimica Acta Part B 57 609-658 (2002).
[5]. Ricard A, Plasmas reactifs, Edition SFV, Paris, 117 pp (1995).

Citation
Sedanur Toraman, T. Y. Katırcıoğlu "Further Characteristic Analysis of the High-Power AC Plasmatron" published at International Journal of Engineering Research and Development, Volume 15, Issue 3 (March 2019)
MID 1503.067X.0004.
Page 29-39
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