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Volume-5 Issue 8: Published on January 10, 2016
14
Volume-5 Issue 8: Published on January 10, 2016

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S. No

Volume-5 Issue-8, January 2016, ISSN:  2278-3075 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

Bhavana Arora, Shakti Kumar

Paper Title:

Study of Non Point Pollution of Water Resources of Kaithal District

Abstract:  Kaithal district is one of the 21 districts of Haryana state in northern India. Kaithal town is the district headquarters. Kaithal district is situated in the North- West of the state . The district occupies an area of 2317 km² located between 29o31’: 30o12’ north latitudes and 76o10’: 76o42’ east longitudes. The Kaithal city, occupies an area of 43.76 sq. km within the municipal limit. This district came into existence on 1 November 1989. There are 277 villages and 253 Panchayats in Kaithal districts. Kaithal district comprises of five administrative blocks including  Pundri, Rajaund, Kaithal, Kalayat and Siwan.. According to the 2011 census Kaithal district has a population of 1,072,861. This gives it a ranking of 423rd in India (out of a total of 640). The study is carried in the Kaithal district of Haryana. Since the Kaithal district in Haryana state of India .The district has a population density of 463 inhabitants per square kilometre (1,200 /sq mi). Its population growth rate over the decade 2001-2011 was 13.39%. Mainly villages of Pundri block showed problem of Total dissolved solids and Hardness in water samples. One or two villages showed high value of fluoride content also.Five to six villages out of fifteen villages chosen showed high content of total dissolved solids , sulphates and alkalinity. In Rajaund block out of seven sample stations two to three stations showed high values of alkalinity and sulphates. Two villages had high fluoride content..In Kalayat block out of four village stations  one station showed high value of hardness, total dissolved solids ,sulphates and fluorides.

Keywords:
Pollution, Ground Water, River, Contaminated, Sub Area: Civil Engineering, Broad Area: Environment Engineering


References:

1.       APHA (2005). Standard Methods for the Examination of Water and Waste Water   (21th ed.). Washington DC: American Public Health Association.
2.       Bishnoi, M., and Malik, R. (2008) “Ground water quality in environmentally degraded localities of Panipat city, India”, Journal of Environmental Biology, Vol 29(6), pg 881-886.

3.       Goyal, S.K, and Chaudhary , B.S., (2010),“ GIS based study of Spatio-Temporal changes in groundwater depth and quality in Kaithal district of Haryana, India”, Journal of Ind. Geophysics Union, Volume 14(2), pg 75-87.

4.       Gupta, D. P., Saharan, S., and Saharan, J. P., (2009) “Physico chemical analysis of ground water of selected area of Kaithal city (Haryana), India”, Researcher, Vol. 1(2), pg1-5.

5.       Jain, C.K., Bhatia, K.K.S., and Vijay, T. (1994-1995) Technical Report, CS (AR) 172, National Institute of Hydrology, Roorkee.

6.       Mittal, S., and Sharma, S. (2008) “Assessment of drinking ground water quality at Moga, Punjab (India): An overall approach”, Journal of Environmental Research And
Development, Vol 3(1), pg 129-136.

7.       Mukherjee, S., and Nelliyat, P., (2007) “Ground Water Pollution and Emerging Environmental Challenges Of Industrial Effluent Irrigation: A Case Study Of Mettupalayam Taluk, Tamilnadu”, IWMI-(Comprehensive Assessment of Water Management in Agriculture Discussion Paper 4).

8.       Rajmohan, N., and Elango, L. (2005) “Nutrient chemistry of groundwater in an intensively irrigated region of southern India”, Environmental Geology, Vol 47, pg 820-830.

9.       Rao, N. S. (2006) “Seasonal variation of groundwater quality in a part of Guntur District, Andhra Pradesh India”, Environmental Geology, Vol. 49, pg 413-429.

10.    Reza, R., and Singh, G. (2010) “Heavy metal contamination and its indexing approach for river water”, International Journal of Environmental Science and Technology, Vol 4, pg 785-792.

11.    Singh, B., and Garg, V.K. (2012) “Fluoride Quantification in Groundwater of Rural Habitations of Faridabad, Haryana, India”, International Journal of Environmental Protection, Vol. 2 (10), pg. 8-17

12.    Singh, M.K., Jha, D., and Jadoun, J. (2012) “Assessment of Physico-chemical Status of Groundwater Samples of Dholpur District, Rajasthan, India”, International Journal of Chemistry, Vol 4, No 4, pg 96-104

13.    Trivedi, R.K., and Goel, P.K. (1984) “Chemical and biological methods for pollution”, Karad (INDIA): Environmental publication.


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2.

Authors:

Abhishek Shah, Rushabha Maru, Kinjal Shah, Khushali Deulkar

Paper Title:

Generation of Pathology Reference Intervals for Indian Population

Abstract: Almost all reference intervals currently used in India are developed by Western, European and other Asia Pacific countries. The use of these reference intervals can be misleading as India is a huge nation with enormous racial and ethnic diversity. The international guidelines on reference intervals suggest the generation of new reference intervals for local homogeneous population. This paper illustrates the  literature review done on  various papers having similar subject and also enlightens a solution for generation of new reference interval.  General Terms- Big data processing, Data mining, Hadoop application for clinical laboratory

Keywords:
 CLSI, clinical laboratory, Reference Interval Generation, Reference Population


References:
1.     “Defining, Establishing, and Verifying Reference Intervals in the Clinical Laboratory”, Third Edition, C28 – A3c, Vol. 28 No. 30.
2.     T Malati, “Whether Western Normative Laboratory Values Used For Clinical Diagnosis Are Applicable To Indian Population? An Overview On Reference Interval”, Indian Journal of Clinical Biochemistry, 2009.

3.     Abhijit Banerjee, Diganta Dey, Parbati Banerjee, Sudarshan Ray, Ratnamala Ray, Banasri Hazra, “CLSI-Derived Hematology Reference Intervals for Healthy Males in Eastern India”, Global Journal Of Medicine And Public Health, 2013.

4.     Tanzeel Huma, Usman Waheed , “The Need To Establish Reference Ranges”, Journal of Public Health and Biological Sciences, Vol. 2, No. 2, ISSN 2305-8668 (Print) 2307-0625 (Online), 2013

5.     Yuthika Agrawal, Vipin Goyal, Kiran Chugh, Vijay Shanker , “Reference Values of Lipid Profile for Population of Haryana Region”, Scholars Journal of Applied Medical Sciences, 2014.

6.     Alex Katayev, MD, Claudiu Balciza,and David W. Seccombe, MD, PhD , “Establishing Reference Intervals for Clinical Laboratory Test Results - Is There a Better Way?”, American Journal for Clinical Pathology, 2010.

7.     Richard C. Friedberg, MD, PhD; Rhona Souers, MS; Elizabeth A. Wagar, MD; Ana K. Stankovic, MD, PhD, MPH; Paul N. Valenstein, MD, “The Origin of Reference Intervals A College of American Pathologists Q-Probes Study of ‘‘Normal Ranges’’ Used in 163 Clinical Laboratories”, Archives of Pathology & Laboratory Medicine —Vol 131, March 2007.

8.     Hyung Hoi Kim, MD, PhD , Hae Sook Hong, RN, PhD , Shine Young Kim, MD, MS, Tung Tran, PhD, Ji Min Lee, RN, MS, Hwa Sun Kim, RN, PhD, Hune Cho, PhD, “An Improved Auto-Generation System to Obtain Reference Intervals for Laboratory Medicine”, Healthcare Informatics Research, 2010.

9.     Yuthika Agrawal, Vipin Goyal, Kiran Chugh, Vijay Shanker , “Reference Values of Lipid Profile for Population of Haryana Region”, Scholars Journal of Applied Medical Sciences,2014


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3.

Authors:

Ebru Alp, Tamer Dag, Taner Arsan

Paper Title:

Indoor Positioning System by Using Triangulation Algorithm

Abstract: In this paper, a Wi-Fi based indoor positioning system (IPS) is developed. IPSs are expected to be used in a vast variety of environments such as shopping malls, hospitals, airports and campuses for navigation purposes, real-time location based advertisements, efficient emergency handling situations. Due to the rapid growth of wireless access points in urban areas and the booming usage of smart phones, Wi-Fi has become one of the key technologies to enable location based services for indoors where GPS technology would not work. This paper introduces least square method based triangulation algorithm for IPSs. The implemented system has been tested under various circumstances in order to achieve the minimum error possible. Wi-Fi channel optimization, filtering, calibration of the relation between the signal strength and distance, using more Wi-Fi modems and the least square method are some of the improvements made on the implemented system. The results show that the location accuracy is significantly improved when compared with the simple triangulation algorithm

Keywords:   Indoor Positioning Development, Triangulation Algorithm, Least Square Method


References:

1.        Z. Selvi, ‘Konum Tabanlı Hizmetler Teknolojisi İle Yönlendirme’, 2011.
2.        R. Jain, ‘Survey of Wireless Based Indoor Localization Technologies’, pp. 1–17, 2014.

3.        C. Chen, J. Yang, G. Tseng, Y. Wu, and R. Hwang, ‘An Indoor Positioning Technique Based on Fuzzy Logic’, Int. MultiConference Eng. Comput. Sci., vol. II, pp. 17–20, 2010.

4.        M. Fak and B. Ya, ‘Mühendislikte Olasılık, İstatistik, Risk ve Güvenilirlik’, pp. 1–6, 2001.

5.        J. Xu, W. Liu, F. Lang, Y. Zhang, and C. Wang, ‘Distance Measurement Model Based on RSSI in WSN’, vol. 2010, no. August, pp. 606–611, 2010.

6.        ‘Wireless sistem - Kablosuz Ağ Sistemleri Kurulumları - internet wireless çözümleri - satışı.’ [Online]. Available: http://www.wirelesssistem.net/Kablosuz-LAN-WLAN-RF-Guc-Degerlenin-Tanimi,DP-10.html.

7.        ‘Normal Distribution.’ [Online]. Available: https://en.wikipedia.org/wiki/Normal_distribution.

8.        ‘The Normal Distribution.’ [Online]. Available: http://www.stat.yale.edu/Courses/1997-98/101/normal.htm.

9.        ‘NORMINV function - Office Support.’ [Online]. Available: https://support.office.com/en-us/article/NORMINV-function-87981ab8-2de0-4cb0-b1aa-e21d4cb879b8.

10.     S. Friedfeld, ‘Tahmin - EKK yöntemi’, no. 2004, pp. 141–143, 2010.

11.     Y. Wang, S. Susheng, X. Yang, and A. Ma, ‘Bluetooth Indoor Positioning using RSSI and Least Square Estimation’, in IEEE ICFCC, 2010, pp. 837 – 842.

12.     ‘Kablosuz ağınıza extra güç!’ [Online]. Available: http://www.chip.com.tr/haber/kablosuz-aginiza-ekstra-guc-1-farkli-kanallari-deneyin_45119_2.html.

13.     ‘Why Channels 1, 6, and 11?’ [Online]. Available: http://www.metageek.com/training/resources/why-channels-1-6-11.html.

14.     ‘FTP Server Hacking: Brute Force Algorithm’, IJCSMC Journal. [Online].Available:http://www.academia.edu/7514911/FTP_Server_Hacking_Brute_Force_Algorithm_.

15.     D. J. Bernstein, ‘Understanding brute force’, ECRYPT STVL Work. Symmetric Key Encryption, pp. 10–19, 2005


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4.

Authors:

Najmuddin Aamer, S. Ramachandran

Paper Title:

Pipelined, High Speed, Low Power Neural Network Controller for Autonomous Mobile Robot Navigation Using FPGA

Abstract:  The demand for autonomous robots which incorporates efficient path planning and obstacle avoidance is increasing rapidly. In this paper, we have proposed a neural network based hardware architecture for autonomous mobile robot which is able to detect and avoid obstacles by using prediction model of neural network and distribution computation techniques using FPGA. Learning and prediction is implemented by using back propagation  method on FPGA Virtex-II pro kit.  For flexibility and accuracy of the neural network, floating point based computation method is applied. The proposed model uses the principle of reconfigurability which reduces the implementation cost and area. In this proposed architecture of autonomous mobile robot, pipelined architecture is used which increases the speed and reduces the delay for the prediction. Simulation is performed by using Xilinx 14.3 ISE simulator. Place and Route results exhibit high throughput and low power consumption achieved using this proposed model for controlling the autonomous robot.

Keywords:
Autonomous Mobile Robot, FPGA, Neural Network, Pipeline, Reconfigurability, Path Planning and Obstacle Avoidance.


References:

1.     Chakravarthy, N. and Jizhong Xiao, "FPGA-based Control System for Miniature Robots," International Conference on Intelligent Robots and Systems 2006 IEEE/RSJ, pp. 3399-3404, 9-15 Oct. 2006.
2.     Guanghua Zong, Luhua Deng and Wei Wang, "A Method for Robustness Improvement of Robot Obstacle Avoidance Algorithm," IEEE International Conference on Robotics and Biomimetics, ROBIO-06, pp. 115-119, 17-20 Dec. 2006.

3.     Ziemke, T, “Remembering How to Behave-Recurrent Neural Networks for Adaptive Robot Behavior”, in Recurrent Neural Networks: Design and Applications, CRC Press 2000. ISBN 0849371813. pp. 355–390.

4.     Laboratory of Intelligent Systems, Ecole Polytechnique Fdrale de Lausanne, Switzerland [online]. [quoted 2008-08-21].

5.     Amosov, N. M.., Kussul, E. M., Fomenko and  V. D.: “Transport Robot with a Neural Network Control System”, Advance papers of the Fourth Intern Joint Conference
on Artificial intelligence, pp.  1-10, 1975.

6.     Brooks R.., “A Robust System Layered Control System for a Mobile Robot”  IEEE Trans. on robotics and automation RA-2,  14-23, 1986.

7.     Janglova, D,  “Neural Networks in Mobile Robot Motion”,  in International Journal of Advanced Robotic Systems 1(1) (2004) 15-22

8.     W. de la Torre, F. Jurado, M. A. Llama, and R. Garcia-Hernandez, “Takagi-Sugeno fuzzy dynamic regulator for a pendulum on a cart system,” in Proceedings of the 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE '13), pp. 52–57, Mexico City, Mexico, October 2013.

9.     Qin Gao, Zhelong Wang and Hongyi Li, “An Optimization Algorithm with Novel RFA-PSO Cooperative Evolution: Applications to Parameter Decision of a Snake Robot”

10.  Y. Alanis, M. Lopez-Franco, N. Arana-Daniel, and C. LopezFranco, “Discrete-time neural control for electrically driven nonholonomic mobile robots,” International Journal of Adaptive Control and Signal Processing, vol. 26, no. 7, pp. 630–644, 2012

11.  L. A. Vazquez and F. Jurado, “Continuous-time decentralized wavelet neural control for a 2 DOF robot manipulator,” in Proceedings of the 11th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE ’14), pp. 1–6, Campeche, Mexico, September-October 2014

12.  Najmuddin Aamer and S. Ramachandran, “Neural Networks Based Adaptive Approach for Path Planning and Obstacle Avoidance for Autonomous Mobile Robot (AMR)” International Journal of Research in Computer Applications and Robotics(IJRCAR), Vol.3 Issue 12, Pg.: 66-79, December – 2015.

13.  Najmuddin Aamer and S. Ramachandran, “A Novel Algorithm for Autonomous Robot Navigation System Using Neural Network” International Journal of Computational Engineering Research (IJCER), Volume, 05, Issue, 12,December – 2015.

14.  Sara Bouraine, Thierry Fraichard, and Hassen Salhi. Provably safe navigation for mobile robots with limited field-of-views in dynamic environments. Autonomous Robots, 32(3):267–283, 2012.

15.  Farmahini-Farahani, S. M. Fakhraie, and S. Safari, “SOPC-based architecture for discrete particle swarm optimization,” in Electronics, Circuits and Systems, 2007. ICECS 2007. 14th IEEE International Conference on, Marrakech, Dec. 2007, pp. 1003–1006.

16.  D.E. Rumelhart, G .E. Hinton and R. J. Williams, "learning internal representations by error propagation", Parallel Distributed Processing, Vol. I. pp.312-362, MIT press. (1986)

17.  Chaomin Luo, Jiyong Gao, Xinde Li and Hongwei Mo; Qimi Jiang, "Sensor-based autonomous robot navigation under unknown environments with grid map representation," in Swarm Intelligence (SIS), 2014 IEEE Symposium on , vol., no., pp.1-7, 9-12 Dec. 2014

18.  Chaomin Luo, Yang, S.X.,Hongwei Mo and Xinde Li, "Safety aware robot coverage motion planning with virtual-obstacle-based navigation," in Information and Automation, 2015 IEEE International Conference on , vol., no., pp.2110-2115, 8-10 Aug. 2015

19.  X. Jin and A. Ray , "Navigation of autonomous vehicles for oil spill cleaning in dynamic and uncertain environments" ,  International Journal of Control , vol. 87 , no. 4 , pp.787 -801 , 2014

20.  E. Galceran and M. Carreras , "A survey on coverage path planning for robotics" ,  Robotics and Autonomous Systems , vol. 61 , no. 12 , pp.1258 -1276 , 2013

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5.

Authors:

Nasser Rostam Afshar, Ev Rochelle Ashzana Roger Sumail

Paper Title:

Pipelined, High Speed, Low Power Neural Network Controller for Autonomous Mobile Robot Navigation Using FPGA

Abstract:   The construction industry nowadays has higher complexities with increased scope of work, number of parties involved and is technically more advanced. However, the industry does not give adequate attention to proper delay management. The causes of delay need to be identified and assessed. The methods on delay mitigation need to be mapped out to cater for these delays. Even the smallest mistake or unforeseen causes can lead to major lost and even bankruptcy to construction firms. Therefore, the aim of this study is to provide a compilation of causes and effects of delay data for Malaysian construction industry. The discussions related the field of causes and effects of delay in construction projects has been reviewed. Result of delay identification from other countries have been studied and compared to make this paper more comprehensive.The overall discussion will focus on the causes of delay related to each specific group; the direct effects of these delay, and also the correlation between the causes and effects. The data is collected by conducting structured questionnaire surveys and distributing it out to government agencies, consultants, and contractors involved in the construction industry. An in depth study is also done on different methods of delay identification available in project management.

Keywords:
 Delay causes, Delay Effects, Construction Industry,Malaysia,Correlational Analysis


References:

1.        Enas Fathi Tsher, R. P. ,Study of Delay in Project Planning and design Stage of Civil Engineering Projects, International Journal of Engineering and Advanced Technology (IJEAT), Vol 3, 2013, pp,457-458.
2.        Frank D.K, F. a.-B., Delays in Building Construction Project in Ghana. Australian Journal of Construction Economics and Building,vol 10,2010, pp,104-106.

3.        Murali Sambasivan, Y. W., Causes and Effects of delays in Malaysian construction Industry,International Journal of Project Management,  2007, pp, 518-520.

4.        Ismail, T. P., Significant Factors Causing and Effects of Delay in Iranian Construction Projects, Australian Journal of Basic and Applied Science,vol 7, 2011, pp,450-451.

5.        Abisuga A.O, Amusu O.R.O, Salvador K.A, Construction Delay in Nigeria: A Perception of Indigenous and Multinational Construction Firms,Journal of Emerging Trends in Economics and Management Sciences (JETEMS) 5(3), ISSN: 2141, 2014,pp371-378.

6.        Omayma Motaleb1 and Mohammed Kishk2, An investigation of    construction delay and effects in UAE , The Scott Sutherland School of Architecture and Built Environment, Robert Gordon University, Aberdeen AB10 7QB, UK, 2010, pp.1149-1157.

7.        Bharath, S. K., Analysis of Critical Causes of Delay in Indian Infrastructure Project. International Journal of Innovative Research & Development, vol 3, 2013,pp.254-260.

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