This study investigated the groundwater for drinking purposes in the Malwathu Oya tank cascade landscape using water quality index (WQI). A total number of twenty wells were selected, and two sets of samples were collected from each location in December (to represent the wet season) and August (to represent the dry season) in the study area. Based on the Sri Lankan drinking water quality standards and previous studies, the weights were assigned for each water quality parameter. Thereafter, relative weight was calculated and using the observed concentration and the relative weight of each parameter, the WQI values were computed. The elevated concentration of all the parameters was observed during the dry season compared to the wet season. Hardness and the alkaline nature of the groundwater were the main issues encountered in the collected samples of the study area. An excellent type of water for drinking was found only in the wet season. Eighty percent of the total area was categorized as good type of water during the wet season, and it was decreased up to 37.7% during the dry season. Moreover, the total area under the poor type of water was increased significantly during the dry season than in the wet season. Accordingly, the majority of the groundwater in the study area is not suitable for drinking without proper treatment. Hence, it is essential to install proper water treatment plants with proper management and maintenance practices.
- Page(s): 01-05
- Date of Publication: 19 August 2020
- M.K.N. Kumari Dept. of Agricultural Engineering and Soil Science, Faculty of Agriculture, Rajarata University of Sri Lanka
References
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M.K.N. Kumari "Evaluation of Groundwater Quality Index for Drinking Water in Tank Cascade Landscape" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.9 issue 8, August 2020, pp.01-05 URL: www.ijltemas.in/DigitalLibrary/Vol.9Issue8/01-05.pdf
Vinyl chloride (VC) is a colorless, nonirritating gas at standard temperature and pressure; and highly stable in the absence of oxygen or sunlight. Vinyl chloride finds its primary applications in the production of polyvinyl chloride (PVC), which covers 12% of the total use of plastic in the world. The widest application of the PVC is the manufacture of plastic piping. Additional significant importance are found in consumer goods, electrical applications, transport sector and floor coverings. This paper is focused on synthesis of Vinyl chloride from Acetylene (vinylation) via Aspen HYSYS simulation. Second order regression models were developed in order to predict the statistical correlation between actual predictors’ value (acetylene and HCl flow rates, kgmole/hr) and the dependent variables (conversion of acetylene (%), conversion of HCl (%) and yield of Vinyl chloride (%)) from central composite design of response surface methodology. The reaction simulation process is found to be exothermic with reaction heat of -2.4 x 104 kcal/kgmole. The computer simulation results were analyzed statistically using response surface methodology of Design Expert 10.0.3. Optimum flow rates of 100 kgmole/hr of acetylene and 95.312 kgmole/hr of HCl gives optimum conversions (%) of acetylene and HCl to be 89.0238 % and 93.089 %, respectively; and the optimum yield of vinyl chloride is observed to be 45.7696 %. Hence, approximately equimolar flow rates of the two reactants is needed for maximum conversion and maximum yield in the vinylation process. Validating the second order regression models, against design values obtained from the computer simulation, it is observed that good agreement is achieved.
- Page(s): 06-12
- Date of Publication: 21 August 2020
- Akintola, J.T.Department of Chemical Engineering, Lagos State Polytechnic, Ikorodu, Lagos, Nigeria
- Odunlami, M.O.Department of Chemical Engineering, Lagos State Polytechnic, Ikorodu, Lagos, Nigeria
- Akintola, O.EDepartment of Chemical Engineering, Lagos State Polytechnic, Ikorodu, Lagos, Nigeria
- Abdulkareem, Y.T.Department of Chemical Engineering, Lagos State Polytechnic, Ikorodu, Lagos, Nigeria
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Akintola, J.T., Odunlami, M.O., Akintola, O.E, Abdulkareem, Y.T. "Statistical Analysis and Optimization of the Synthesis of Vinyl Chloride from Acetylene via Simulation" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.9 issue 8, August 2020, pp.06-12 URL: www.ijltemas.in/DigitalLibrary/Vol.9Issue8/06-12.pdf
Several situations of science, engineering, physics, biology, astronomy, radiology and statistics lead to Volterra integro-differential equations such as process of glass forming, diffusion problem, radiation transfer problem, growth of cells and describing the motion of satellite. In this paper, authors gave the application of Sawi transform for solving convolution type Volterra integro-differential equation of first kind. Some numerical problems have been considered and solved with the help of Sawi transform for explaining the complete methodology. Results of numerical problems show that Sawi transform is very effective integral transform for solving convolution type Volterra integro-differential equation of first kind.
- Page(s): 13-19
- Date of Publication: 28 August 2020
- Sudhanshu Aggarwal Assistant Professor, Department of Mathematics, National P.G. College, Barhalganj, Gorakhpur-273402, U.P., India
- Swarg Deep Sharma Assistant Professor, Department of Mathematics, Nand Lal Singh College Jaitpur Daudpur Constituent of Jai Prakash University Chhapra-841205, Bihar, India
- Aakansha Vyas Assistant Professor, Noida Institute of Engineering & Technology, Greater Noida-201306, U.P., India
References
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R., & Khandelwal, A. (2018). A new application of Mahgoub transform for solving linear ordinary differential equations with variable coefficients. Journal of Computer and Mathematical Sciences, 9(6), 520-525. [41]. Aggarwal, S., & Sharma, S. D. (2019). Application of Kamal transform for solving Abel’s integral equation. Global Journal of Engineering Science and Researches, 6(3), 82-90. [42]. Aggarwal, S., & Gupta, A. R. (2019). Sumudu transform for the solution of Abel’s integral equation. Journal of Emerging Technologies and Innovative Research, 6(4), 423-431. [43]. Aggarwal, S., Sharma, S. D., & Gupta, A. R. (2019). A new application of Mohand transform for handling Abel’s integral equation. Journal of Emerging Technologies and Innovative Research, 6(3), 600-608. [44]. Aggarwal, S., & Sharma, S. D. (2019). Solution of Abel’s integral equation by Aboodh transform method. Journal of Emerging Technologies and Innovative Research, 6(4), 317-325. [45]. Aggarwal, S., & Gupta, A. R. (2019). Shehu Transform for Solving Abel’s Integral Equation. Journal of Emerging Technologies and Innovative Research, 6(5), 101-110. [46]. Aggarwal, S., Chauhan, R., & Sharma, N. (2018). Mohand transform of Bessel’s functions. International Journal of Research in Advent Technology, 6(11), 3034-3038. [47]. Aggarwal, S., Gupta, A. R., & Agrawal, D. (2018). Aboodh transform of Bessel’s functions. Journal of Advanced Research in Applied Mathematics and Statistics, 3(3), 1-5. [48]. Aggarwal, S., Sharma, N., & Chauhan, R. (2018). Mahgoub transform of Bessel’s functions. International Journal of Latest Technology in Engineering, Management & Applied Science, 7(8), 32-36. [49]. Aggarwal, S. (2018). Elzaki transform of Bessel’s functions. Global Journal of Engineering Science and Researches, 5(8), 45-51. [50]. Chaudhary, R., Sharma, S.D., Kumar, N., & Aggarwal, S. (2019). Connections between Aboodh transform and some useful integral transforms. International Journal of Innovative Technology and Exploring Engineering, 9(1), 1465-1470. [51]. Aggarwal, S., Chauhan, R., & Sharma, N. (2018). Application of Elzaki transform for solving linear Volterra integral equations of first kind. International Journal of Research in Advent Technology, 6(12), 3687-3692. [52]. Aggarwal, S., Sharma, N., & Chauhan, R. (2018). Application of Kamal transform for solving linear Volterra integral equations of first kind. International Journal of Research in Advent Technology, 6(8), 2081-2088. [53]. Aggarwal, S., Asthana, N. & Singh, D.P. (2018). Solution of population growth and decay problems by using Aboodh transform method. International Journal of Research in Advent Technology, 6(10), 2706-2710. [54]. Aggarwal, S., & Bhatnagar, K. (2019). Sadik transform for handling population growth and decay problems. Journal of Applied Science and Computations, 6(6), 1212-1221. [55]. Aggarwal, S., & Sharma, S.D. (2019). Sadik transform of error function (probability integral). Global Journal of Engineering Science and Researches, 6(6), 125-135. [56]. Aggarwal, S., Gupta, A.R., & Sharma, S.D. (2019). Application of Sadik transform for handling linear Volterra integro-differential equations of second kind. Universal Review, 10(7), 177-187. [57]. Aggarwal, S., & Bhatnagar, K. (2019). Solution of Abel’s integral equation using Sadik transform. Asian Resonance, 8(2), (Part-1), 57-63. [58]. Aggarwal, S. (2019). A comparative study of Mohand and Mahgoub transforms. Journal of Advanced Research in Applied Mathematics and Statistics, 4(1), 1-7. [59]. Aggarwal, S. (2018). Kamal transform of Bessel’s functions. International Journal of Research and Innovation in Applied Science, 3(7), 1-4. [60]. Chauhan, R., & Aggarwal, S. (2019). Laplace transform for convolution type linear Volterra integral equation of second kind. Journal of Advanced Research in Applied Mathematics and Statistics, 4(3&4), 1-7. [61]. Sharma, N., & Aggarwal, S. (2019). Laplace transform for the solution of Abel’s integral equation. Journal of Advanced Research in Applied Mathematics and Statistics, 4(3&4), 8-15. [62]. Aggarwal, S., & Sharma, N. (2019). Laplace transform for the solution of first kind linear Volterra integral equation. Journal of Advanced Research in Applied Mathematics and Statistics, 4(3&4), 16-23. [63]. Mishra, R., Aggarwal, S., Chaudhary, L., & Kumar, A. (2020). Relationship between Sumudu and some efficient integral transforms. International Journal of Innovative Technology and Exploring Engineering, 9(3), 153-159. [64]. Mahgoub, M.M.A. (2019). The new integral transform ''Sawi Transform''. Advances in Theoretical and Applied Mathematics, 14(1), 81-87.
Sudhanshu Aggarwal, Swarg Deep Sharma, Aakansha Vyas "Application of Sawi Transform for Solving Convolution Type Volterra Integro-Differential Equation of First Kind" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.9 issue 8, August 2020, pp.13-19 URL: www.ijltemas.in/DigitalLibrary/Vol.9Issue8/13-19.pdf
Heart attack is the deadliest cardiovascular disease amongst others and is one of the major causes of death recently, both in developed or developing countries of the world. Most of the cardiac disorders arises as a result of irregular rhythm of the heart. As a matter of fact, irregular heartbeats often lead to abnormal PQRST values which can be traced from patient’s Electrocardiogram (ECG). The need to predict or detect this has been a major necessity for the improvement of human lives across the globe. This paper presents heart attack detection using ECG signal processing. The methodology adopted for this work is the Dynamic Software Development Methodology. The system was designed using Python programming language and it acquires ECG signal in the form of datasets, processes it and extracts important parameters like PQRST to detect heart abnormalities.
- Page(s): 20-25
- Date of Publication: 28 August 2020
- Grace O. DiriDepartment of Computer Science, Ignatius Ajuru University of Education, Rivers State, Nigeria
- Ledisi G. KabariDepartment of Computer Science, Ken Saro-wiwa Polytechnic, Rivers State, Nigeria
References
[1]. Vaidehi, A.D., and Thorat, P.R. (2017). ECG Detection Using Controller. International Journal of Innovative Research in Science, Engineering and Technology, 6(11), 21586 – 21600. [2]. Joseph, J.O. (2007). Portable Heart Attack Warning System by Monitoring the ST Segment via Smartphone Electrocardiogram Processing. Retrieved on the 25th of February, 2020 from:https://core.ac.uk/download/pdf/12207951.pdf [3]. Gertsch, M. (2009). The ECG Manual. London: Springer-Verlag. [4]. Khan, M. (2008). Rapid ECG Interpretation, Totowa, NJ: Humana Press Inc. [5]. Channappa, B. and Nishat, A. (2017). ECG Signal Based Heart Disease Detection System for Telemedicine Application Using LabVIEW. International Journal of Research and Scientific Innovation (IJRSI), 4(9), 54 – 59. [6]. Nikita, S. (2018). A Key to Your Heart: Biometric Authentication Based on ECG Signals. A 4th Year Project Report submitted to the Department of Computer Science, School of Informatics University of Edinburgh. [7]. Euan, A. and Josef, N. (2004). Cardiology Explained. Remedica. Retrieved on the 25th of February, 2020 from: https://groups.inf.ed.ac.uk/tulips/projects/1718 /samarin.pdf [8]. Komeili, M., Louis, W., Armanfard, N. and Hatzinakos, D. (2016). On Evaluating Human Recognition Using Electrocardiogram Signals: From Rest to Exercise. IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), pages 1 – 4. [9]. Gautam, A. and Kaur, M. (2012). ECG Analysis using Continuous Wavelet Transforms (CWT), IOSR Journal of Engineering, 2 (4), 632 – 635. [10]. Rajni, P. and Kaur, I. (2013). Electrocardiogram Signal Analysis - An Overview. International Journal of Computer Applications, 84(7), 0975 – 8887. [11]. Nagendra, S. and Kumar, V. (2011). Application of Wavelet Techniques in ECG Signal Processing: An Overview, International Journal of Engineering Science and Technology (IJEST), 3(10), 7432 – 7443. [12]. Adam, J. and Remigiusz J. (2005). Effective Simulation of Signals for Testing ECG Analyzer, IEEE Transactions on Instrumentation and Measurement, 54(3), 1019 – 1024. [13]. Shital, L. and Nivedita D. (2014).Detection of Various Diseases Using ECG Signal in MALAB. International Journal of Recent Technology and Engineering (IJRTE), 3(1), 120 – 123. [14]. Anuradha, B., Kumar, K. and Veera R. (2008). Classification of Cardiac Signals usingTime Domain Methods, ARPN Journal of Engineering and Applied Sciences, 3(3), 7 – 12. [15]. Saritha, C., Sukanya, V. and Narsimha M. (2008). ECG Signal Analysis Using Wavelet Transforms, ARPN Journal of Engineering and Applied Sciences, 3(4), 68 – 77. [16]. Kalpana and Panchal (2015). Heart Attack Warning System Using ECG Processing. International Journal of Advances in Electronics and Computer Science, 2(6), 63 – 66. [17]. Harini, R., Murthy B., and Tanveer K (2017). Development of ECG Monitoring System using Android App. International Journal of Electronics and Electrical Engineering (IJEEE), 9(2), 699 – 707. [18]. Chowdhury, E., Alzoubi, K., Khandakar, A., and Khalifa, R. (2019). WearableReal-Time Heart Attack Detection and Warning System to Reduce Road Accidents. Multidisciplinary Digital Publishing Institute, 1 – 22. Retrieved on the 25th of February, 2020 from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6632021 [19]. Okada, Y., Yi-Tsuyoshi, Y., Suzuki, T., and Sugiura, T. (2010). Development of aWearable ECG Recorder for Measuring Daily Stress. International Conference on Information Science and Applications (ICISA) Seoul, Korea, pp 1-5.
Grace O. Diri, Ledisi G. Kabari "Abnormal Heart Rate Detection Using Signal Processing" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.9 issue 8, August 2020, pp.20-25 URL: www.ijltemas.in/DigitalLibrary/Vol.9Issue8/20-25.pdf
Volterra integral equation occurs widely in diverse areas of applied mathematics, physics, mechanics, statistics, biology, economics and theory of control systems. Many initial value problems associated with ordinary differential equation and partial differential equation can be transformed into a single Volterra integral equation. In this paper, authors determined the primitive of second kind linear Volterra integral equation using Shehu transform. In this work, authors have considered that the kernel of second kind linear Volterra integral equation is a convolution type kernel. Some numerical problems have been considered and solved with the help of Shehu transform for explaining the complete methodology. Results of numerical problems show that Shehu transform is very effective integral transform for determining the primitive of second kind linear Volterra integral equation.
- Page(s): 26-32
- Date of Publication: 28 August 2020
- Sudhanshu Aggarwal Assistant Professor, Department of Mathematics, National P.G. College, Barhalganj, Gorakhpur-273402, U.P., India
- Aakansha Vyas Assistant Professor, Noida Institute of Engineering & Technology, Greater Noida-201306, U.P., India
- Swarg Deep Sharma Assistant Professor, Department of Mathematics, Nand Lal Singh College Jaitpur Daudpur Constituent of Jai Prakash University Chhapra-841205, Bihar, India
References
[1] Aggarwal, S., Chauhan, R., & Sharma, N. (2018). A new application of Mahgoub transform for solving linear Volterra integral equations. Asian Resonance, 7(2), 46-48. [2] Aggarwal, S., Sharma, N., & Chauhan, R. (2018). Application of Mahgoub transform for solving linear Volterra integral equations of first kind. Global Journal of Engineering Science and Researches, 5(9), 154-161. [3] Aggarwal, S., Sharma, N., & Chauhan, R. (2018). A new application of Aboodh transform for solving linear Volterra integral equations. Asian Resonance, 7(3), 156-158. [4] Aggarwal, S., Gupta, A. R., & Sharma, S. D. (2019). A new application of Shehu transform for handling Volterra integral equations of first kind. International Journal of Research in Advent Technology, 7(4), 439-445. [5] Aggarwal, S., Chauhan, R., & Sharma, N. (2018). Application of Elzaki transform for solving linear Volterra integral equations of first kind. International Journal of Research in Advent Technology, 6(12), 3687-3692. [6] Aggarwal, S., Sharma, N., & Chauhan, R. (2018). Application of Aboodh transform for solving linear Volterra integral equations of first kind. International Journal of Research in Advent Technology, 6(12), 3745-3753. [7] Aggarwal, S., Sharma, N., & Chauhan, R. (2018). Solution of linear Volterra integral equations of second kind using Mohand transform. International Journal of Research in Advent Technology, 6(11), 3098-3102. [8] Aggarwal, S., Chauhan, R., & Sharma, N. (2018). A new application of Kamal transform for solving linear Volterra integral equations. International Journal of Latest Technology in Engineering, Management & Applied Science, 7(4), 138-140. [9] Aggarwal, S., Sharma, N., & Chauhan, R. (2018). Solution of linear Volterra integro-differential equations of second kind using Mahgoub transform. International Journal of Latest Technology in Engineering, Management & Applied Science, 7(5), 173-176. [10] Aggarwal, S., & Gupta, A. R. (2019). Solution of linear Volterra integro-differential equations of second kind using Kamal transform. Journal of Emerging Technologies and Innovative Research, 6(1), 741-747. [11] Aggarwal, S., Sharma, N., & Chauhan, R. (2018). Application of Aboodh transform for solving linear Volterra integro-differential equations of second kind. International Journal of Research in Advent Technology, 6(6), 1186-1190. [12] Chauhan, R., & Aggarwal, S. (2018). Solution of linear partial integro-differential equations using Mahgoub transform. Periodic Research, 7(1), 28-31. [13] Gupta, A. R., Aggarwal, S., & Agrawal, D. (2018). Solution of linear partial integro-differential equations using Kamal transform. International Journal of Latest Technology in Engineering, Management & Applied Science, 7(7), 88-91. [14] Singh, G. P., & Aggarwal, S. (2019). Sawi transform for population growth and decay problems. International Journal of Latest Technology in Engineering, Management & Applied Science, 8(8), 157-162. [15] Aggarwal, S., Sharma, N., & Chauhan, R. (2018). Solution of population growth and decay problems by using Mohand transform. International Journal of Research in Advent Technology, 6(11), 3277-3282. [16] Aggarwal, S., Gupta, A. R., Asthana, N., & Singh, D. P. (2018). Application of Kamal transform for solving population growth and decay problems. Global Journal of Engineering Science and Researches, 5(9), 254-260. [17] Aggarwal, S., Sharma, S. D., & Gupta, A. R. (2019). Application of Shehu transform for handling growth and decay problems. Global Journal of Engineering Science and Researches, 6(4), 190-198. [18] Aggarwal, S., Singh, D. P., Asthana, N., & Gupta, A. R. (2018). Application of Elzaki transform for solving population growth and decay problems. Journal of Emerging Technologies and Innovative Research, 5(9), 281-284. [19] Aggarwal, S., Gupta, A. R., Singh, D. P., Asthana, N., & Kumar, N. (2018). Application of Laplace transform for solving population growth and decay problems. International Journal of Latest Technology in Engineering, Management & Applied Science, 7(9), 141-145. [20] Aggarwal, S., Pandey, M., Asthana, N., Singh, D. P., & Kumar, A. (2018). Application of Mahgoub transform for solving population growth and decay problems. Journal of Computer and Mathematical Sciences, 9(10), 1490-1496. [21] Aggarwal, S., Sharma, N., & Chauhan, R. (2020). Duality relations of Kamal transform with Laplace, Laplace–Carson, Aboodh, Sumudu, Elzaki, Mohand and Sawi transforms. SN Applied Sciences, 2(1), 135. [22] Aggarwal, S., & Bhatnagar, K. (2019). Dualities between Laplace transform and some useful integral transforms. International Journal of Engineering and Advanced Technology, 9(1), 936-941. [23] Chauhan, R., Kumar, N., & Aggarwal, S. (2019). Dualities between Laplace-Carson transform and some useful integral transforms. International Journal of Innovative Technology and Exploring Engineering, 8(12), 1654-1659. [24] Aggarwal, S., & Gupta, A. R. (2019). Dualities between Mohand transform and some useful integral transforms. International Journal of Recent Technology and Engineering, 8(3), 843-847. [25] Aggarwal, S., & Gupta, A. R. (2019). Dualities between some useful integral transforms and Sawi transform. International Journal of Recent Technology and Engineering, 8(3), 5978-5982. [26] Aggarwal, S., Bhatnagar, K., & Dua, A. (2019). Dualities between Elzaki transform and some useful integral transforms. International Journal of Innovative Technology and Exploring Engineering, 8(12), 4312-4318. [27] Aggarwal, S., Sharma, N., Chaudhary, R., & Gupta, A. R. (2019). A comparative study of Mohand and Kamal transforms. Global Journal of Engineering Science and Researches, 6(2), 113-123. [28] Aggarwal, S., Mishra, R., & Chaudhary, A. (2019). A comparative study of Mohand and Elzaki transforms. Global Journal of Engineering Science and Researches, 6(2), 203-213. [29] Aggarwal, S., & Sharma, S. D. (2019). A comparative study of Mohand and Sumudu transforms. Journal of Emerging Technologies and Innovative Research, 6(3), 145-153. [30] Aggarwal, S., & Chauhan, R. (2019). A comparative study of Mohand and Aboodh transforms. International Journal of Research in Advent Technology, 7(1), 520-529. [31] Aggarwal, S., & Chaudhary, R. (2019). A comparative study of Mohand and Laplace transforms. Journal of Emerging Technologies and Innovative Research, 6(2), 230-240. [32] Aggarwal, S., Gupta, A. R., & Kumar, A. (2019). Elzaki transform of error function. Global Journal of Engineering Science and Researches, 6(5), 412-422. [33] Aggarwal, S., & Singh, G. P. (2019). Aboodh transform of error function. Universal Review, 10(6), 137-150. [34] Aggarwal, S., & GP, S. (2019). Shehu Transform of Error Function (Probability Integral). Int J Res Advent Technol, 7, 54-60. [35] Aggarwal, S., & Sharma, S. D. (2019). Sumudu transform of error function. Journal of Applied Science and Computations, 6(6), 1222-1231. [36] Aggarwal, S., Gupta, A. R., & Kumar, D. (2019). Mohand transform of error function. International Journal of Research in Advent Technology, 7(5), 224-231. [37] Aggarwal, S., & Singh, G. P. (2019). Kamal transform of error function. Journal of Applied Science and Computations, 6(5), 2223-2235. [38] Aggarwal, S., Gupta, A. R., Sharma, S. D., Chauhan, R., & Sharma, N. (2019). Mahgoub transform (Laplace-Carson transform) of error function. International Journal of Latest Technology in Engineering, Management & Applied Science, 8(4), 92-98. [39] Aggarwal, S., Singh, A., Kumar, A., & Kumar, N. (2019). Application of Laplace transform for solving improper integrals whose integrand consisting error function. Journal of Advanced Research in Applied Mathematics and Statistics, 4(2), 1-7. [40] Aggarwal, S., Sharma, N., Chauhan, R., Gupta, A. R., & Khandelwal, A. (2018). A new application of Mahgoub transform for solving linear ordinary differential equations with variable coefficients. Journal of Computer and Mathematical Sciences, 9(6), 520-525. [41] Aggarwal, S., & Sharma, S. D. (2019). Application of Kamal transform for solving Abel’s integral equation. Global Journal of Engineering Science and Researches, 6(3), 82-90. [42] Aggarwal, S., & Gupta, A. R. (2019). Sumudu transform for the solution of Abel’s integral equation. Journal of Emerging Technologies and Innovative Research, 6(4), 423-431. [43] Aggarwal, S., Sharma, S. D., & Gupta, A. R. (2019). A new application of Mohand transform for handling Abel’s integral equation. Journal of Emerging Technologies and Innovative Research, 6(3), 600-608. [44] Aggarwal, S., & Sharma, S. D. (2019). Solution of Abel’s integral equation by Aboodh transform method. Journal of Emerging Technologies and Innovative Research, 6(4), 317-325. [45] Aggarwal, S., & Gupta, A. R. (2019). Shehu Transform for Solving Abel’s Integral Equation. Journal of Emerging Technologies and Innovative Research, 6(5), 101-110. [46] Aggarwal, S., Chauhan, R., & Sharma, N. (2018). Mohand transform of Bessel’s functions. International Journal of Research in Advent Technology, 6(11), 3034-3038. [47] Aggarwal, S., Gupta, A. R., & Agrawal, D. (2018). Aboodh transform of Bessel’s functions. Journal of Advanced Research in Applied Mathematics and Statistics, 3(3), 1-5. [48] Aggarwal, S., Sharma, N., & Chauhan, R. (2018). Mahgoub transform of Bessel’s functions. International Journal of Latest Technology in Engineering, Management & Applied Science, 7(8), 32-36. [49] Aggarwal, S. (2018). Elzaki transform of Bessel’s functions. Global Journal of Engineering Science and Researches, 5(8), 45-51. [50] Chaudhary, R., Sharma, S.D., Kumar, N., & Aggarwal, S. (2019). Connections between Aboodh transform and some useful integral transforms. International Journal of Innovative Technology and Exploring Engineering, 9(1), 1465-1470. [51] Aggarwal, S., Chauhan, R., & Sharma, N. (2018). Application of Elzaki transform for solving linear Volterra integral equations of first kind. International Journal of Research in Advent Technology, 6(12), 3687-3692. [52] Aggarwal, S., Sharma, N., & Chauhan, R. (2018). Application of Kamal transform for solving linear Volterra integral equations of first kind. International Journal of Research in Advent Technology, 6(8), 2081-2088. [53] Aggarwal, S., Asthana, N. & Singh, D.P. (2018). Solution of population growth and decay problems by using Aboodh transform method. International Journal of Research in Advent Technology, 6(10), 2706-2710. [54] Aggarwal, S., & Bhatnagar, K. (2019). Sadik transform for handling population growth and decay problems. Journal of Applied Science and Computations, 6(6), 1212-1221. [55] Aggarwal, S., & Sharma, S.D. (2019). Sadik transform of error function (probability integral). Global Journal of Engineering Science and Researches, 6(6), 125-135. [56] Aggarwal, S., Gupta, A.R., & Sharma, S.D. (2019). Application of Sadik transform for handling linear Volterra integro-differential equations of second kind. Universal Review, 10(7), 177-187. [57] Aggarwal, S., & Bhatnagar, K. (2019). Solution of Abel’s integral equation using Sadik transform. Asian Resonance, 8(2), (Part-1), 57-63. [58] Aggarwal, S. (2019). A comparative study of Mohand and Mahgoub transforms. Journal of Advanced Research in Applied Mathematics and Statistics, 4(1), 1-7. [59] Aggarwal, S. (2018). Kamal transform of Bessel’s functions. International Journal of Research and Innovation in Applied Science, 3(7), 1-4. [60] Chauhan, R., & Aggarwal, S. (2019). Laplace transform for convolution type linear Volterra integral equation of second kind. Journal of Advanced Research in Applied Mathematics and Statistics, 4(3&4), 1-7. [61] Sharma, N., & Aggarwal, S. (2019). Laplace transform for the solution of Abel’s integral equation. Journal of Advanced Research in Applied Mathematics and Statistics, 4(3&4), 8-15. [62] Aggarwal, S., & Sharma, N. (2019). Laplace transform for the solution of first kind linear Volterra integral equation. Journal of Advanced Research in Applied Mathematics and Statistics, 4(3&4), 16-23. [63] Mishra, R., Aggarwal, S., Chaudhary, L., & Kumar, A. (2020). Relationship between Sumudu and some efficient integral transforms. International Journal of Innovative Technology and Exploring Engineering, 9(3), 153-159. [64] Maitama, S., & Zhao, W. (2019). New integral transform: Shehu transform a generalization of Sumudu and Laplace transform for solving differential equations. International Journal of Analysis and Applications, 17(2), 167-190.
Sudhanshu Aggarwal, Aakansha Vyas, Swarg Deep Sharma, "Primitive of Second Kind Linear Volterra Integral Equation Using Shehu Transform" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.9 issue 8, August 2020, pp.26-32 URL: www.ijltemas.in/DigitalLibrary/Vol.9Issue8/26-32.pdf
There are growing numbers of countries in the world whose sources of their energy still largely depend on fossil fuels. Unfortunately, these are non-renewable fuels and their integrity is being questioned because of their high carbon emissions and the link they have with global warming. Researchers therefore find it necessary to find different energy sources that have no or low carbon emissions; and one of such alternative sources found to mitigate global warming syndrome is the use of biodiesel to either compliment or replace fossil fuels in Compression ignition engines. Also; emissions characteristics of CI engines have been found to be affected by fuel injection parameters, and this is specific for each type of fuel run on the engine. This work therefore employed the use of GT-Power computer simulation package to study the impact of varying injection timing on emission characteristics of a compression ignition engine fueled with Tropical Almond Seed based Biodiesel and its blends. At compression ratio of 17.5 and varying engine speed of 1000 rpm to 5000rpm; the study examined the impact over a Kirloskar four-stroke, single-cylinder, water-cooled, direct-ignition, compression-ignition engine fueled with tropical almond seed oil-based biodiesel and its blends B0 to B100 at 5% incremental step and four separate injection timings (21◦, 23◦, 25◦, 27◦CA BTDC). The results showed a considerable increase of CO2; and decrease in HC and CO and for tropical almond oil-based biodiesel and its blends at advanced injection timing of 27 bTDC. NOx emissions also slightly increased with the increase in biodiesel content and injection timing at higher speeds. For all blends tested, B35 provides the best result in terms of lowest HC for all investigated injection timings. The study therefore concludes that for better emission profile, Tropical almond seed oil-based biodiesel blend; B35 at 27◦CA BTDC CI engine injection timing provides a good mix.
- Page(s): 33-49
- Date of Publication: 03 September 2020
- N. B. JagunmoluDepartment of Mechanical Engineering, University of Ibadan, Ibadan, NigeriaCentre for Petroleum, Energy Economics and Law, University of Ibadan, Nigeria
- S. K. FasogbonDepartment of Mechanical Engineering, University of Ibadan, Ibadan, Nigeria
References
[1] B. A. Orhevba, S. E. Adebayo, and A. O. Salihu, “Synthesis of Biodiesel from Tropical Almond (Terminalia Catappa) Seed Oil,” Curr. Res. Agric. Sci., vol. 3, no. 4, pp. 57–63, 2016. [2] P. Lingfa, “A Comparative Study on Performance and Emission Characteristics of Compression Ignition Engine using Biodiesel Derived from Castor oil Abstract :,” Int. J. Innov. Res. Sci. Eng. Technol., vol. 3, no. 4, pp. 124–128, 2014. [3] K. S. Babulal, A. Pradeep, and P. Muthukumar, “Experimental Performance and Emission Analysis of C . I Engine Fuelled with Biodiesel,” Int. J. Innov. Res. Sci. Eng. Technol., vol. 4, no. 2, pp. 133–138, 2015. [4] R. Narsinga and K. Ranjith, “Effect of Fuel Injection Pressure and Injection Timing on Performance and Emissions of Diesel Engine Using Nanoadditive Blends,” J. Appl. Sci. Innov., vol. 1, no. 4, pp. 5–13, 2017. [5] J. Hwang, D. Qi, Y. Jung, and C. Bae, “Effect of injection parameters on the combustion and emission characteristics in a common-rail direct injection diesel engine fueled with waste cooking oil biodiesel,” Renew. Energy, vol. 63, pp. 9–17, 2014. [6] G. R. Kannan and R. Anand, “Effect of injection pressure and injection timing on DI diesel engine fuelled with biodiesel from waste cooking oil,” Biomass and Bioenergy, vol. 46, pp. 343–352, 2012. [7] R. L. Krupakaran, T. Hariprasasd, and A. Gopalakrishna, “Influence of injection timing on engine performance, emission characteristics of Mimusops Elangi methyl ester,” Int. J. Ambient Energy, vol. 0750, no. May, pp. 1–10, 2018. [8] G. J. Rani, Y. V. H. Rao, and B. Balakrishna, “Fuel Injection Timing impact on diesel engine performance , combustion and emission characteristics of nano additive biodiesel blends,” Int. J. Ambient Energy, vol. 0, no. 0, pp. 1–21, 2020. [9] N. Karthik, R. Rajasekar, R. Siva, and G. Mathiselvan, “Experimental investigation of injection timing on the performance and exhaust emissions of a rubber seed oil blend fuel in constant speed diesel engine,” Int. J. Ambient Energy, vol. 40, no. 3, pp. 292–294, 2019. [10] J. Jayaprabakar, A. Karthikeyan, and V. Rameshkumar, “Effect of injection timing on the combustion characteristics of rice bran and algae biodiesel blends in a compression-ignition engine,” Int. J. Ambient Energy, vol. 38, no. 2, pp. 116–121, 2017. [11] M. Harun Kumar, V. Dhana Raju, P. S. Kishore, and H. Venu, “Influence of injection timing on the performance, combustion and emission characteristics of diesel engine powered with tamarind seed biodiesel blend,” Int. J. Ambient Energy, vol. 0, no. 0, pp. 1–31, 2018. [12] P. Karthikeyan, P. Lokesh, and P. Suneel, “Performance and emission characteristics of direct injection diesel engine using linseed oil as biodiesel by varying injection timing,” Int. J. Ambient Energy, vol. 40, no. 1, pp. 35–39, 2019. [13] S. K. Fasogbon, O. O. Laosebikan, and C. U. Owora, “ANN Analysis of Injection Timing on Performance Characteristics of Compression Ignition Engines Running on the Blends of Tropical Almond Based Biodiesel,” Am. J. Mod. Energy, vol. 5, no. 2, pp. 40–48, 2019. [14] R. Rahim, R. Mamat, and M. Y. Taib, “Comparative Study on Diesel Engine Performance Operating With Biodiesel and Diesel Fuel,” Natl. Conf. Mech. Eng. Res. Postgrad. Stud. (2nd NCMER 2010), no. December, pp. 863–870, 2010. [15] S. K. Fasogbon and M. F. Odia, “Modelling Combustion Characteristics of a Turbocharged Low Heat Rejection Direct Injection Compression Ignition Engine Fuelled with methyl Ester of Seed Oil of Terminalia Catappa L . and its Blends,” Int. J. Latest Technol. Eng. Manag. Appl. Sci., vol. VIII, no. Iii, pp. 49–54, 2019. [16] S. N. Sahasrabudhe, V. Rodriguez-Martinez, M. O’Meara, and B. E. Farkas, “Density, viscosity, and surface tension of five vegetable oils at elevated temperatures: Measurement and modeling,” Int. J. Food Prop., vol. 20, no. 2, pp. 1965–1981, 2017. [17] O. O. Fasina and Z. Colley, “Viscosity and specific heat of vegetable oils as a function of temperature: 35°C to 180°C,” Int. J. Food Prop., vol. 11, no. 4, pp. 738–746, 2008. [18] E. E. G. Rojas, J. S. R. Coimbra, and J. Telis-Romero, “Thermophysical properties of cotton, canola, sunflower and soybean oils as a function of temperature,” Int. J. Food Prop., vol. 16, no. 7, pp. 1620–1629, 2013. [19] E. Performance and A. Manual, “GT-SUITE,” 2016. [20] Gamma Technology, “Highlights : GT-POWER Engine Simulation Software Features and Applications.” [21] T. Morel and S. Wahiduzzaman, “morel denge.pdf,” Modeling of diesel combustion and emissions. FISITA Congress, June 1996., 1996. [22] S. K. Chen and P. F. Flynn, “Development of a single cylinder compression ignition research engine,” SAE Tech. Pap., 1965. [23] M. Bhuiya, M. Rasul, M. Khan, and N. Ashwath, “Performance and emission characteristics of a compression ignition Performance and emission characteristics of a compression ignition (CI) engine operated with beauty leaf biodiesel The 15th International Symposium on District Heating and Cooling Assessin,” Energy Procedia, vol. 160, no. 2018, pp. 641–647, 2019. [24] B. Ashok and K. Nanthagopal, Eco friendly biofuels for CI engine applications. Elsevier Ltd., 2019. [25] B. Sudarmanta, “Influence of the compression ratio and ignition timing on Sinjai engine performance with 50 % bioethanol-gasoline blended fuel INFLUENCE OF THE COMPRESSION RATIO AND IGNITION TIMING ON SINJAI ENGINE PERFORMANCE WITH 50 % BIOETHANOL-,” ARPN J. Eng. Appl. Sci., vol. 11, no. February, 2016. [26] M. I. Arbab, H. H. Masjuki, M. Varman, M. A. Kalam, S. Imtenan, and H. Sajjad, “Experimental Investigation of Optimum Blend Ratio of Jatropha , Palm and Coconut Based Biodiesel to Improve Fuel Properties , Engine Performance and Emission Characteristics,” in SAE Technical Paper Series, 2013, no. October. [27] P. Mccarthy, M. G. Rasul, and S. Moazzem, “Comparison of the performance and emissions of different biodiesel blends against petroleum diesel,” Int. J. Low-Carbon Technol., vol. 6, no. 4, pp. 255–260, 2011. [28] C. R. Ferguson and A. T. Kirkpatrick, Internal Combustion Engines Applied Thermosciences, Third. John The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, United Kingdom: John Wiley & Sons, Ltd, 2016. [29] I. Kalargaris, G. Tian, and S. Gu, “Influence of Advanced Injection Timing and Fuel Additive on Combustion , Performance , and Emission Characteristics of a DI Diesel Engine Running on Plastic Pyrolysis Oil,” J. Combust., vol. 2017, p. 9, 2017. [30] C. L. PETERSON, D. L. REECE, J. C. THOMPSON, S. M. BECK, and C. CHASES, “ETHYL ESTER OF RAPESEED USED AS A BIODIESEL FUEL-A CASE STUDY *,” Biomass and Bioenergy, vol. 10, no. 5–6, pp. 331–336, 1996. [31] J. Sheehan, V. Camobreco, J. Duffield, M. Graboski, and H. Shapouri, “Life Cycle Inventory of Biodiesel and Petroleum Diesel for Use in an Urban Bus,” 1998.
N. B. Jagunmolu, S. K. Fasogbon "Modelling Performance and Emissions Characteristics of CI Engines Running on Tropical Almond Seed-Based Biodiesel" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.9 issue 8, August 2020, pp.33-49 URL: www.ijltemas.in/DigitalLibrary/Vol.9Issue8/33-49.pdf
In this paper, work was carried out to investigate the impact of several parameters including tubing pressure, tubing fluid temperature, length of tubing, gas density, liquid density, tubing hold-up and total mass flow on mass fraction of tubing muds. Data points for this investigation were obtained using OLGA multiphase simulator. The results of the simulation (including the trend and plot data) were exported to MATLAB to develop a mud weight model (correlation) using the MATLAB regress function. The correlation was also validated using statistical techniques such as the R square and Significance F values. Comparison of the trend plots of the actual data points from OLGA and the predicted data points was also done to further prove the reliability of the correlation. The correlation predictions agreed with the OLGA results excellently with a relative error of less than 0.001 %. This study revealed that the tubing mud weight is significantly impacted on by variables like tubing holdup, tubing gas density, tubing liquid densities and the total mass flow. Where as the tubing pressure, fluid temperature, and the tubing length have insignificant effects on the tubing mud weight. From the trend plots of the variables, it was deduced that as the tubing pressure increased, the temperature and the mud weight also increased. While, the total mass and volumetric flows reduced with increased tubing pressure. The effect of input data uncertainties on the developed correlation were also tested by using 22 observation points to predict tubing mud weight and calculating the resulting residual values. Over 90% of the residual values were negative and the percentage difference in mud weight between the first and the last observation points was approximately 4%. Hence, the effect of input data uncertainties on the developed correlation is insignificant. This paper could serve as a template for drilling engineers, assisting them with a simple, fast and reliable technique for determining optimum drilling parameters with a minimum engineering effort and drilling experience.
- Page(s): 50-56
- Date of Publication: 03 September 2020
- Paul Tamaragaibi ElijahApplied Mechanics and Design/Production Research Group, Department of Mechanical Engineering, Nigeria Maritime University, Nigeria
- Franklin OKOROClean Script Group, Nigeria
- Chinedum EgwuonwuUniversity of Port Harcourt, Nigeriaa
References
[1] Aadnoy, B. S., Ong, S. (2003). Introduction to special issue on Borehole Stability. J Petrol SciEng, 38[3-4], 79-82. [2] Aadnøy, B.S. (2010). Modern Well Design, second edition. Leiden, The Netherlands: CRC Press/Balkema. [3] Al-Ajmi, A. (2006). Wellbore stability analysis based on a new truetiaxial failure criterion [Ph.D. dissertation], Royal Institute ofTechnology, Stockholm, Sweden. [4] Awal, M. R., Khan, M. S., Mohiuddin, M. A., and Abdulraheem, A. (2001). A new approach to borehole trajectory optimisation for increased hole stability. In: Proc SPE Middle East Oil Show, Bahrain, [5] Bratvold, R. B. and Begg, S. H. (2010). Making Good Decisions. Richardson, Texas, USA, Society of Petroleum Engineers. ISBN 978-1-55563-258-8. [6] Fjær, E., Holt, R.M., Horsrud, P., Raaen A.M, and Risnes, R. (2008). Petroleum Related Rock Mechanics. Developments in Petroleum Science, Elsevier, vol. 53: 61–64. ISBN: 978-0-444-50260-5. [7] John, E. U., Bernt, S. A., Kjell, K. F. (2014) Uncertainty Evaluation of wellbore stability model predictions. Journal of Petroleum Science and Engineering, http://dx.doi.org/10.1016/j.petrol.2014.09.033. [8] Mahmood, R. A., AdelM, A., and Yahya, A. (2016). Probabilistic Approach in Wellbore Stability Analysis during Drilling. Journal of Petroleum Engineering Volume, 13. http://dx.doi.org/10.1155/2016/3472158. [9] Mostafavi, V., Aadnøy, B.S., and Hareland, G. (2011). Model – Based Uncertainty Assessment of Wellbore Stability Analyses and Downhole Pressure Estimations. Paper ARMA 11-127, presented at the 45th US Rock Mechanics / Geomechanics Symposium, San Francisco, CA, 26–29 June. [10] Okoro, F. (2018). Impact of Flood Rate, Salinity, and Wettabiliy on Waterflood Oil Recovery Using Lab-On-A-Chip Method. Society of Petroleum Engineers. doi:10.2118/193403-MS [11] Okoro, F. (2020). Comparison of Waterflood Oil Recovery under Different Oil Viscosities using Siljan and Sherwood Oils. Society of Petroleum Engineers. doi:10.2118/203616-MS [12] Onuka, A. U. & Okoro, F. (2019). Prediction of Oil Reservoir Performance and Original-Oil-in-Place Applying Schilthuis And Hurst-Van Everdingen Modified Water Influx Models. Society of Petroleum Engineers. doi:10.2118/198714-MS
Paul Tamaragaibi Elijah, Franklin OKORO, Chinedum Egwuonwu "Development of a Model for Accurate Determination of Fluid Density and Improvement of Borehole Stability Predictions using a Simulator" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.9 issue 8, August 2020, pp.50-56 URL: www.ijltemas.in/DigitalLibrary/Vol.9Issue8/50-56.pdf
This research paper represents the experimental investigation and analysis of a flat plate collector which incorporates a moderate vacuum enclosure within the system. Flat plate collector with vacuum environment within the system provides various benefits as compared to ordinary collectors such as outstanding thermal characteristics, supreme optical features, highly versatile and also has a capability to provide pure energy which is efficient for basic household, industrial process and space heating application. This paper mainly emphasis on the design of the evacuated collector model in which a absorber plate (0.4 *0.3m) made of copper material which is entirely enclosed by vacuum layer that is installed within the system with supporting inlet and outlet ports for fluid circulation and the temperatures were calibrated at set intervals depending upon the constant mass flow rate. It demonstrated that with the help of employing magnets to create a strong repulsive force between the glazing and absorber surface the designed enclosure was successfully sustained by the overall imposed vacuum pressure and stresses The paper will also explore the various challenges, expectation, requirements and application of the collector model along with the brief discussion of the vacuum evacuated concept which is taken into concern.
- Page(s): 57-67
- Date of Publication: 03 September 2020
- Prathamesh V. Chinta(M.Sc. Mechanical Engineering, DeMontfort University, Leicester, UK)
References
[1] Eaton, C.B. and H.A. Blum. "The Use of Moderate Vacuum Environments As A Means Of Increasing The Collection Efficiencies And Operating Temperatures Of Flat-Plate Solar Collectors". Solar Energy 17.3 (1975): 151-158. Web. [2] Arya, Farid et al. Current Development In Flat Plate Vacuum Solar Thermal Collector. 1st ed. Loughborough: UK Engineering and Physical Sciences Research Control (EPSRC), 2017. Web. 13 Mar. 2017 [3] Beikircher, T., N. Benz, and W. Spirkl. "Gas Heat Conduction In Evacuated Flat-Plate Solar Collectors: Analysis And Reduction". Journal of Solar Energy Engineering 117.3 (1995): 229. Web. [4] BILLY ANAK SUP (2010). EFFECT OF ABSORBER PLATE MATERIAL ON FLAT PLATE COLLECTOR EFFICIENCY. [online] Available at: http://umpir.ump.edu.my/2868/1/CD5897.pdf. [5] Integrated Publishing, I. (2017). Copper-Versus-Aluminum Conductors. [online] Tpub.com. Available at: http://www.tpub.com/neets/book4/11e.htm. [6] Metal Supermarkets UK - Stainless Steel, Aluminum, Bright, Black, Engineering, Bronze, Copper, Brass, Tool, Galvanized. (2017). Which Metals Conduct Heat Best? [online] Available at: https://www.metalsupermarkets.co.uk/which-metals-conduct-heat-best. [7] Leonardo Energy - Knowledge Base. (2017). Thermal expansion: Copper vs. aluminium. [online] Available at: https://help.leonardo-energy.org/hc/en-us/articles/202823322-Thermal-expansion-Copper-vs-aluminium. [8] Amrutkar, S., Ghodke, S. and Patil, D. (2012). Solar Flat Plate Collector Analysis. 2nd ed. [ebook] Bhopal India, pp.207-213.Availablat:http://www.iosrjen.org/Papers/vol2_issue2/F022207213.pdf. [9] Duffe, John. Solar engineering of thermal processes. New Jersey, USA: John wiley & sons inc, 2013. ISBN. [10] Fabio Struckmann, Anon, (2008). Analysis of a Flat - plate Solar Collector. project Report2008 MVK160 Heat and Mass TransportMay08, 2008, Lund, S [11] Manoj Kumar Moningi, Conduction Convection Radiation processes of a solar collector using FEA , University of Massachusetts, Amherst. [12] Agbo, S.N. and G.O. Unachukwu, 2006. Performance evaluation and optimization of the NCERD thermosyphon solar water heater. Proceedings of the World Renewable Energy Congress, August 19-25, 2006, Florence, Italy [13] ) Bakari R, Minja, R Njau NK. (2014)” Effect of Glass Thickness on Performance of Flat Plate Solar Collectors for Fruits Drying” Journal of Energy, pp-8. [14] ) Hematian A, Ajabshirchi Y, and Bakhtiari AB (2012) “Experimental analysis of flat plate solar air collector efficiency. Indian Journal of Science and Technology 5(8), 3183-3189 [15] Xianguang KONG, Yuanying QIU, Jiantao CHANG ,”Research and Implementation of CATIA Tool Integration Technology Based on CAA” PRZEGLĄD ELEKTROTECHNICZNY (Electrical Review), ISSN 0033-2097, R. 88 NR 7b/2012 [16] Dr C Sabarigirinathan,Dr K Vinayagavel ,Dr P Rupkumar,Dr G Sriramprabh,Dr V Harishnath,Dr Vinay Bharti, “RECENT ADVANCES IN SOLDERING/BRAZING AND WELDING IN DENTISTRY, International Journal of Scientific Engineering and Applied Science (IJSEAS) -Volume-1, Issue-4, July 2015ISSN: 2395-3470 [17] NI 9213 16-Channel Thermocouple Module, “National Instruments Corporation 2014”, Available at :www.ni.com [18] APOGEE INSTRUMENTS,INC. NORTH, LOGAN, UTAH 84321, USAP-212/SP-215 and SP-214.: www.apogeeinstruments.com [19] Y. Raja Sekhar, K. V. Sharma and M. Basaveswara Rao.” EVALUATION OF HEATLOSS COEFFICIENTS IN SOLAR FLATPLATE COLLECTORS “ARPN Journal of Engineering andApplied Sciences, VOL.4.NO.5,JULY 2009 , ISSN 1819-6608 [20] Alternative Energy Tutorials. (2017). Flat Plate Collector for use in Solar Hot Water Systems. [online] Available at: http://www.alternative-energy-tutorials.com/solar-hot-water/flat-plate-collector
Prathamesh V. Chinta "Experimental Investigation of High Performance Moderate Vacuum Solar Flat Plate Collector" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.9 issue 8, August 2020, pp.57-67 URL: www.ijltemas.in/DigitalLibrary/Vol.9Issue8/57-67.pdf
Today technology is changing every day and to stay updated with the society and to follow the trends business also need to update themselves with the new advancements of technology, nowadays business does not interact with customers the traditional ways they use digital media platforms to interact with customers which generate data, the customers are now changing they want the personalized experience to achieve that we need to understand every customer. Here is where the role of AI comes in analyzing, segmenting, delivering insights of customers which help businesses to cater to the customers with a personalized experience. AI is a self-learning system which uses data mining and big data analytics to learn, this helps the business in saving lots of time which would be used in analyzing and segmenting the data now they get these things done by AI in just a short period of time without any error, which not only saves them time but also saves cost to the company. In this paper, I have talked about how AI is helping businesses understand consumer behavior thus improving the consumer experience.
- Page(s): 68-71
- Date of Publication: 11 September 2020
- Achyut AwasthiChhatrapati Shahu Ji Maharaj University, Kanpur, Uttar Pradesh, India
References
[1] https://www.pointillist.com/blog/uses-of-artificial-intelligence-to-boost-customer-experience-measurement/ [2] https://www.forbes.com/sites/danielnewman/2019/04/16/5-ways-ai-is-transforming-the-customer-experience/#7e724b4465ad [3] https://insights.revtrax.com/the-power-of-real-time-marketing [4] https://quantamixsolutions.com/blog/47/top-10-ai-tools-and-techniques-for-automated-content-creation-for-seo-in-2019 [5] https://www.business.com/articles/how-ai-is-changing-digital-marketing [6] Kannan, P., & Li, A. (2017). Digital marketing: A framework, review and research agenda. International Journal of Research in Marketing, 34(1), 22-45. Retrieved from https://www.researchgate.net/publication/311393872_ Digital_marketing_A_framework_review_and_resear ch_agenda [7] Agrawal, A., Gans , J., & Goldfarb, A. (2018). Prediction Machines: the simple economics of artificial intelligence. Boston Massachusetts: Harvard Business Review Press. [8] Rao S, Srivatsala V, Suneetha V (2016) Optimizing Technical Ecosystem of Digital Marketing. In: Dash S, Bhaskar M, Panigrahi B, Das S (eds) Artificial Intelligence (AI) and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 394. Springer, New Delhi [9] Spentzouris P, Koutsopoulos I, Madsen KG, Hansen TV (2018) Advertiser Bidding Prediction and Optimization in Online Advertising. In: Iliadis L, Maglogiannis I, Plagianakos V (eds) Artificial Intelligence Applications and Innovations. AIAI 2018. IFIP Advances in Information and Communication
Achyut Awasthi "How Artificial Intelligence (AI) is Helping Digital Media to Understand Consumer Behavior " International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.9 issue 8, August 2020, pp.68-71 URL: www.ijltemas.in/DigitalLibrary/Vol.9Issue8/68-71.pdf
In this study, ARIMA model was used to forecast six sigma level of the results of the examinations for the students of Kut Technical Institute. The time series data in our study was level of six sigma for the results of the examinations of the students in the Institute from academic year 2003-2004 to academic year 2017-2018. The researcher used Box-Jenkins methodology and noted there is a Trend Variation. To remove the non- stationary, the first difference was taken. Using statistical software EVIEWS 9, ARIMA (1,1,1) was the best model chosen based on the SSE, adj R2 , AIC, BIC, and H-Q criteria. A validation check for this model was performed on residuals series, were found white noise, normally distributed, and equal in variance. The predicted results from the selected model were compared with the original data to determine prediction precision. It found that the selected model predicted six sigma level with acceptable accuracy. These results will provide the Institute's managers with decisions on how to upgrade six sigma level.
- Page(s): 72-78
- Date of Publication: 11 September 2020
- Alla Hussein Omran AnsafAssistant Professor, Kut Technical Institute, Middle Technical University, Baghdad, Iraq
References
[1] Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19 (6), 716–723. [2] Ali, Faisal & Ahmed, Amran (2016). A review on the statistical concepts of six sigma. Proceedings of the 2nd International Conference on Mathematics, Engineering and Industrial Applications. [3] Antony, J. & Banuelas, R. (2001). Six Sigma: A Business Strategy for Manufacturing Organizations. Manufacturing Engineering, 8( 3), 119-121. [4] Asteriou, Dimitrios; Hall, Stephen G. (2011). The Breusch–Godfrey LM test for serial correlation. Applied Econometrics ,2nd edition. New York: Palgrave Macmillan. [5] Box, G.E., Jenkins, G.M., Reinsel, G.C. and Ljung, G.M. (2015). Time Series Analysis: Forecasting and Control, John Wiley & Sons, Hoboken. [6] Brooks, C. (2014). Introductory Econometrics for Finance ,3rd edition. Cambridge University Press. [7] Draper, N.R.; Smith, H. (1998). Applied Regression Analysis, 3rd edition. John Wiley. [8] Engle, Robert F. (1982). Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of U.K. Inflation. Econometrica, 50(4), 987–1008. [9] Hannan, E. J., and B. G. Quinn (1979). The Determination of the order of an autoregression. Journal of the Royal Statistical Society. Series B (Methodological) , 41,190–195. [10] Hyndman, R.J., and Athanasopoulos, G. (2018). Forecasting: principles and Practice, 2nd edition. OTexts: Melbourne, Australia. [11] Jarque, Carlos M.; Bera, Anil K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255–259. [12] Lawrence , A.K. and Paul , I.N. (1978). On Conditional Least Square Estimation for Stochastic Processes. The Annals of Statistics , 6(3) , 629-642. [13] [Ljung, G., and Box, G. E. P. (1978). On a Measure of lack of fit in Time Series Models. Biometrika, 65(2), 297–303. [14] Montgomery, D.C. and Woodall, W.H. (2008). An Overview of Six Sigma. International Statistical Review, 76(3), 329-346. [15] Theil, Henri (1961). Economic Forecasts and Policy. Holland, Amsterdam. [16] Schwarz, Gideon (1978). Estimating the Dimension of a Model. Annals of Statistics . Vol 6, No. 2, 461--464. [17] Sodhi, H.S., Singh, D. and Singh, B. (2017), “Lean and Six Sigma: a combined approach for waste management in Indian SMEs”, International Journal of Latest Technology in Engineering, Management & Applied Science, Vol. 4 No. 5, pp. 7-12. [18] Vivekananthamoorthy, N. and Sankar, S. (2011). Lean Six Sigma, Six Sigma projects and personal Experiences, Prof. Abdurrahman Coskun (Ed.).In Tech. https://www.researchgate.net/publication/215576248_Lean Six Sigma. [19] White, Halbert (1980). A Heteroskedasticity-Consistent Covariance Matrix and Direct Test for Heteroskedasticity. Econometrica, 48(4), 817–838.
Alla Hussein Omran Ansaf "The Use of Box–Jenkins Method to Predict the Six Sigma Level for Kut Technical Institute Examination Results" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.9 issue 8, August 2020, pp.72-78 URL: www.ijltemas.in/DigitalLibrary/Vol.9Issue8/72-78.pdf
In this world of 7.8 billion population, near about 7.5 million population requires wheelchair for their movement.By any means if a person gets physically handicapped, then they are dependent upon others for their day to day maneuvering and their movement gets restricted until and unless someone helps them in moving their wheelchair.Patients having problems such as quadriplegic, cerebral palsy and multiple sclerosis are dependent on others and due to this they don’t have the freedom of mobility and it sometimes become heart wrenching to see them in difficult situations. Till now many technologies has been developed and are available in the market to overcome this problem. In our work, we have designed a voice activated wheelchair system for physically disabled persons which can be operated via simple voice commands with the help of mobile app [1] and assist them completely without any hassle to reach their destination in comfort in which a permanent mapping has also been done with the help of ATmega328P processor used in Arduino in which wheelchair user can reach it’s destination on single command.
- Page(s): 79-84
- Date of Publication: 12 September 2020
- Sayan RoyElectronics & Communication Department, Heritage Institute of Technology, Kolkata, India
- Sourav GoswamiElectronics & Communication Department, Heritage Institute of Technology, Kolkata, India
References
[1]. PramilaKupkar, PrajaktaPandit, Nikita Dhadhere and PP Jadhav, "Android controlled wheelchair", Imperial Journal of Interdisciplinary Research (IJIR) Volume-2 Issue-6 2016 [2]. Apsana S, Renjitha G Nair, "Voice Controlled Wheelchair using Arduino", International Advanced `Research Journal in Science, Engineering and Technology(IARJSET), Vol 3, Issue 3, August 2016 [3]. Ms. S. D. Suryawanshi Mr. J. S. Chitode Ms. S. S. Pethakar, “Voice Operated Intelligent Wheelchair”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 3, Issue 5, pp. 487-490, May - 2013.. [4]. G. Paþnik, K. Benkiþ and B. Breþko, “Voice Operated Intelligent Wheelchair – VOIC”, Proceedings of the IEEE International Symposium on Industrial Electronics, ISIE 2005.pp 1221-1226. [5]. Muhammad Tahir Qadri, Syed Ashfaque Ahmed,” Voice Controlled Wheelchair Using Dsk Tms320c6711”, International Conference on Signal Acquisition and Processing, 2009, ISBN: 978-0-7695-3594-4/09 $25.00 © 2009, IEEE, pp 217-220. [6]. Mr. Tarun Agrawal, "Review on Voice Recognition Module Working", International Journal of Advanced Research in Computer Science and Software Engineering, May 2014 [7]. https://store.arduino.cc/usa/arduino-uno-rev3 [8]. https://www.electronicscomp.com/l293d-motor-driver-board?gclid=Cj0KCQjwhIP6BRCMARIsALu9Lfmodzat25aO-tQPJo3nGC-NSA3PAcH1j5WESpZT-ZeMf_uDCfkF9lEaApQ6EALw_wcB [9]. https://www.indiamart.com/proddetail/bluetooth-hc-05-wireless-uart-ttl-output-module-for-arduino-16417857030.html [10]. https://www.indiamart.com/proddetail/hc-sr04-ultrasonic-module-for-arduino-15148181333.html [11]. https://robu.in/product/chassis-heavy-duty/ [12]. https://www.amazon.in/SHOPEE-BRANDED-COMBO-Long-Carbon/dp/B07WRDTSRQ/ref=asc_df_B07WRDTSRQ/?tag=googleshopdes-21&linkCode=df0&hvadid=397081961918&hvpos=&hvnetw=g&hvrand=2052388656030567075&hvpone=&hvptwo=&hvqmt=&hvdev=c&hvdvcmdl=&hvlocint=&hvlocphy=9061811&hvtargid=pla-866427664684&psc=1&ext_vrnc=hi [13]. https://www.electronicscomp.com/60-rpm-centre-shaft-dc-geared-motor-india?gclid=Cj0KCQjwhIP6BRCMARIsALu9LflNaFCk-lWUZOzn_5t3SXHZ7IArbSCPzEs5OL0KOK6TO5VUwk26nOQaAsp-EALw_wcB [14]. https://apkpure.com/arduino-bluetooth-voice-controller/appinventor.ai_nitinpandit_00.Arduino_bluetooth_voice_controller [15]. https://robu.in/product/170-pts-mini-breadboard-syb-170-white/?gclid=Cj0KCQjwhIP6BRCMARIsALu9LfkZEDALiEPpPbQYWD9dUDn9-MU50JHiBrglfMA7nVuvT0L9CzZz0UsaAhcoEALw_wcB
Sayan Roy, Sourav Goswami "Voice Recognised Wheelchair with Inbuilt Mapping" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.9 issue 8, August 2020, pp.79-84 URL: www.ijltemas.in/DigitalLibrary/Vol.9Issue8/79-84.pdf
In this article, authors discussed the existence of solution of Diophantine equation 〖181〗^x+〖199〗^y=z^2, where x,y,z are non-negative integers. Results show that the consider Diophantine equation of study has no non-negative integer solution.
- Page(s): 85-86
- Date of Publication: 18 September 2020
- Sudhanshu Aggarwal Assistant Professor, Department of Mathematics, National P.G. College, Barhalganj, Gorakhpur-273402, U.P., India
- Swarg Deep Sharma Assistant Professor, Department of Mathematics, Nand Lal Singh College Jaitpur Daudpur Constituent of Jai Prakash University Chhapra-841205, Bihar, India
- Aakansha Vyas Assistant Professor, Noida Institute of Engineering & Technology, Greater Noida-201306, U.P., India
References
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Sudhanshu Aggarwal, Swarg Deep Sharma, Aakansha Vyas "On The Existence of Solution of Diophantine Equation 181^x+ 199^y = z^2" International Journal of Latest Technology in Engineering, Management & Applied Science-IJLTEMAS vol.9 issue 8, August 2020, pp.85-86 URL: www.ijltemas.in/DigitalLibrary/Vol.9Issue8/85-86.pdf