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Vol. 04, No. 09 [September 2018]

Paper Title :: The Relationship between stock market and Bond Market
Author Name :: Jieyu Long || Wen-huiLi
Country :: China
Page Number :: 01-10
As we know, stock market and bond market are the important component of financial market. The relationship between them is close. We take the weekly returns of the new composite index and Shanghai Stock Exchange index, From January 1, 2012 to December 31, 2017, established a vector autoregressive model to explore the relationship between them. The empirical results show that the return of stock market just have a little impact on the return of bond market, and the impact has a certain lag. the return of bond market has strong autocorrelation.
Keywords:Stock market; bond market; yield; correlation
[1]. Chiang, T. C. J. Li, and S. Y. Yang, Dynamic Stock-Bond Return Correlations and Financial Market Uncertainty [J]. Review of Quantitative Finance and Accounting, 2015,45(1):1-30.
[2]. Bansal, N. R. A. Connolly, and C. Stivers, The Stock-Bond Return Relation, the Term Structure’s Slope, and Asset-Class Risk Dynamics[J]. Journal of Financial and Quantitative Analysis,2014,49(3):699-724.
[3]. Wu, Chih-Chiang and Zih-Ying Lin, An Economic Evaluation of Stock-Bond Return Comovements with Copula-based GARCH Models[J]. Quantitative Finance,2014,14(7):1283-1296.
[4]. Wang Lu. A Study on the Quantity of Markov System Transformation Characteristics in Stock Market and Bond Market[J]. Economic Mathematics, 2013, (02): 78-84.
[5]. Wang Binhui, Zheng Hui, Chen Jinfei. An Empirical Study on the Spillover Effects between China's Stock Market, Foreign Exchange Market and Bond Market[J]. Journal of Jinan University(Philosophy and Social Sciences), 2010, (04): 37-45.

Paper Title :: Development and Fabrication of Foldable Portable Hybrid Crutches
Author Name :: Sagar P. Hubballi || Ayyappa T
Country :: India
Page Number :: 11-17
Crutches and canes are widely used around the world as a means of providing stability and support for those who need them; the elderly population in particular utilizes these devices the most. It is very difficult for people with physical disability to maneuver. They always need a support or they use crutches to move. Moving using crutches is a very hard task. This task is very straining since this involves lot of manual effort. This is even difficult for a long distance.There are numerous products in the market that attempt to add a seat to the crutch or cane in an effort to alleviate the stress of standing for too long. However, there is no product involving electrical assistance to the crutches.Here is a step ahead to build a device which can accommodate both manual and motorized version. The goal of this workt is to design and build a device that can be used as either as crutch or as a electric scooter so that when user is tire, it can be unfolded and be used as electric scooter reducing strain on user. A first generation prototype was successfully fabricated using available mild steel raw material, motor, battery, control system etc. The prototype underwent load and dynamic tests in addition to this overall usability tests.
Keywords:Portable Hybrid Crutch, foldable, morised crutch, Advance Breaking, Throttle system
[1]. YiminGao and MehrdadEhsani, John M. Miller, Hybrid Electric Vehicle: Overview and State of the Art, IEEE ISIE 2005, June 20-23, 2005, Dubrovnik, Croatia
[2]. Shih-Wen Hsiao and Jyh-Rong Chou. 2004. A creativity-based design process for innovative product design, International Journal of Industrial Ergonomics.34: 421-443.
[3]. Lambroslaios and John giannatsis, “Ergonomic evaluation and redesign of children bicycle based on anthropometric data”, Applied Ergonomics 41(2010) 428-435.
[4]. Shigley, J.E., Mischke, C.R. and Budynas, R.G. (2004): Mechanical Engineering Design. 7th Edition. New York(USA). McGraw-Hill Education. pp. 394-867.
[5]. Arunachalam M, ArunPrakash R, Rajesh R, A Typical Approach in Conceptual and Embodiment Design of Foldable Bicycle,International Journal of Computer Applications (0975 – 8887) Volume 87 – No.19, February 2014

Paper Title :: BrainTumor Classification Using Deep Learning
Author Name :: Abdelmonim Naway || Yuancheng LI
Country :: China
Page Number :: 18-24
A brain tumor is a serious disease that takes numerous life annually. Identification and classification from magnetic resonance imaging (MRI) are valuable for a particular medical care. Identification of a brain tumor in MRI is still a decisive and complicated job for physicians. This work is seeking to produce an automated system for segmentation and classification of a tumor in theMRI image. A methodology based on the Fuzzy C-means algorithm for segmentation which, is a substantive step in medical image analysis, the Grey Level Co-occurrence Matrices (GLCM) for feature extraction, and Deep Neural Network (DNN) for classification. The proposed system has been tested with datasets and the experimental results demonstrate good performance.
Keywords:Brain tumor detection, Deep Learning,FCM, Image segmentation
[1]. Harald Sontheimer.: ‘Clinical presentation/ diagnosis/ epidemiology’, in Diseases of the Nervous System’, (Academic Press2015), pp. 263
[2]. A. R. Mathew, P. B. Anto and N. K. Thara.: ‘Brain tumor segmentation and classification using DWT, Gabor wavelet and GLCM’, 2017 International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT), Kannur, 2017, pp. 1744-1750.
[3]. A. Hebli and S. Gupta, 'Brain tumor prediction and classification using support vector machine', 2017 International Conference on Advances in Computing, Communication and Control (ICAC3), Mumbai, 2017, pp. 1-6.
[4]. Sanjeev Kumar, Chetna Dabas, SunilaGodara.: ‘Classification of Brain MRI Tumour Images: A Hybrid Approach’, Procedia Computer Science, Volume 122,2017, Pages 510-517
[5]. V. Anitha and S. Murugavalli.: ‘Brain tumor classification using two-tier classifier with adaptive segmentation technique’, in IET Computer Vision, vol. 10, no. 1, pp. 9-17, 2 2016

Paper Title :: The Controlled Human Gyroscope – Virtual Reality Motion Base Simulatort
Author Name :: Randy C. Arjunsingh || Matthew J. Jensen || Razvan Rusovici || Ondrej Doule
Country :: United States
Page Number :: 25-32/td>
Flight motion simulators are currently used for flight training and research, but there are many limitations to these existing systems. This paper presents a low-cost design for a rotational motion platform titled, ‘The Controlled Human Gyroscope’. It uses a 4-axis system instead of the conventional 3-axis system to avoid gimbal lock and prevent the unnecessary motion of the user. The Human Gyroscope features unlimited rotation about the roll, pitch and yaw axes regardless of the occupant’s orientation. It will therefore provide high fidelity motion simulation and if it is paired with a translational motion platform, it can provide up to 6 degrees of freedom. Equations of motion for this specific system are presented in this paper and can be used to develop a control algorithm.
Keywords: Flight motion simulator, Gimbal lock, Human gyroscope, Full rotational control, Rotational Motion
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[2]. Stroud, K. J., Harm, D. L., and Klaus, D. M., Using Virtual Reality for Predicting and Preventing Space Motion Sickness, Proceedings of the 54th International Astronautical Congress of the International Astronautical Federation, the International Academy of Astronautics, and the International Institute of Space Law, Bremen, Germany, 2003.
[3]. Chen, W., Chao, J. G., Wang, J. K., Chen, X. W., and Tan, C., Subjective Vertical Conflict Theory and Space Motion Sickness,Aerospace Med Hum Perform., 87(2), 2016, 128-136
[4]. Lawson, B. D., Rupert, A. H., and McGrath, B. J., The Neurovestibular Challenges of Astronauts and Balance Patients: Some Past Countermeasures and Two Alternative Approaches to Elicitation, Assessment and Mitigation, Frontiers in Systems Neuroscience,10, 2016, 1-96.
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Paper Title :: Swarm-technology for Large-area Photogrammetry Survey and Spatially Complex 3D Modelling
Author Name :: Lukas Auer || Andreas Feichtner || Friedrich Steinhäusler || Robert Delleske || Markus Keuschnig
Country :: Austria
Page Number :: 33-39
Swarm technology represents a breakthrough in the creation of 3D models using drone-based photogrammetry. The traditional single-drone approach for modelling of large areas(area >5 km²) or spatially complex objects (e.g., buildings, infrastructures) requires long flight times and is frequently associated with variable light- and meteorological conditions during periods spanning several days. This is especially true for drone copters. In this EU-supported project (www.target-h2020.eu) COTSdrones have been evaluated and the drone DJI Mavic Pro (MP) has been selected for optimal performance. Based on MP, the Photogrammetry Swarm Kit (PSK) has been developed, offering considerable time- and cost savings as compared to the traditional single drone approach.PSK is comprised of five MP drones housed in a specially designed, portable container, together with control unit and power supplyand aground control station.PSK uses WiFi communication and is adjusted to a Digital Elevation Model to ensure a precise flight. It offers three modes of data acquisition (Area Mode, Highlight Mode, Angle Mode). PSK has been field-tested in the European Union and the Republic of Kyrgyzstan and received the DRONE HERO EUROPE Award 2018.
Keywords: Drone, Swarm, Photogrammetry, 3D Modelling.
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[2]. Teng Long et al., Energy Neutral Internet of Drones, IEEE Communications Mag., vol. 56, no. 1, pp. 22 – 28, Jan. 2018, DOI: 10.1109/MCOM.2017.1700454.
[3]. U.S. Department of Defense, Department of Defense Announces Successful Micro-Drone Demonstration, Department of Defense Release No.: NR-008-17, 9 January 2017, https://www.defense.gov/News/News-Releases/News-Release-View/Article/1044811/department-of-defense-announces-successful-micro-drone-demonstration/;last visited 23 July 2018.
[4]. NASA, NASA Selects University Partners for Small Spacecraft Collaboration, 1 December 2017, https://www.nasa.gov/directorates/spacetech/small_spacecraft/feature/NASA_Selects_University_Partners_for_Small_Spacecraft_Collaboration; last visited 23 July 2018..
[5]. Megan Scudellari, The Tiny Robots Will See You Now, IEEE Spectrum, 1 March 2017, https://spectrum.ieee.org/the-human-os/biomedical/devices/the-tiny-robots-will-see-you-now; last visited 23 July 2018..
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