Volume-8 , Issue-3 , Sep 2021, ISSN 2348-635X Go Back

• Open Access   Article

  Energy-Aware Routing in UWSNs Using Cuckoo Algorithms for Improving Network Lifetime

  Musa Mojarad, Fariba Sarhangnia, Amin Rezaeipanah

  Research Paper | Journal-Paper (WAJES)

  Vol.8 , Issue.3 , pp.1-5, Sep-2021

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  Today, the use of Wireless Sensor Networks (WSNs) is increasingly growing. The WSN consists of a number of sensor nodes that are spread across an environment and communicate with each other to collect information about the target environment. Underwater Wireless Sensor Networks (UWSNs) are a type of sensor network that is located in the underwater environment and communicates with each other by sound waves. These networks have a big number of limited energy nodes scattered in a limited area. Due to the limited energy in this type of networks, increasing the lifetime by reducing energy consumption has always been considered. Most of the nodes’ energy is used to send information to the central station. Given that our country has long water borders in the Persian Gulf region, it is worthwhile to be able to monitor this environment. The aim of this paper is to present a cuckoo routing algorithm based on fuzzy clustering in order to properly distribute energy consumption. The results of the simulations indicate the benefit of the proposed method in the number of packets sent and the network lifetime compared to other similar methods. The results show an 18.13% advantage of the proposed algorithm in sending messages and also a 10.34% increase in network lifetime over the SH-FEER protocol.

  Key-Words / Index Term
  Underwater Wireless Sensor Networks, Cuckoo Algorithm, Routing, Fuzzy Clustering

  References
  [1] Nguyen, N. T., Le, T. T., Nguyen, H. H., & Voznak, M.. Energy-efficient clustering multi-hop routing protocol in a UWSN. Sensors, 21(2), 627, 2021.
  [2] Ahmed, M., Salleh, M., Channa, M. I., & Rohani, M. F.. Energy efficient routing protocols for UWSN: A Review. Telkomnika, 15(1), 212, 2017.
  [3] Wang, J., Shen, J., Shi, W., Qiao, G., Wu, S., & Wang, X.. A Novel Energy-Efficient Contention-Based MAC Protocol Used for OA-UWSN. Sensors, 19(1), 183, 2019.
  [4] Prakash, P. S.. Machine Learning-Based Optimized Hierarchical Routing Protocols for WSN Lifetime: A Review. Information Technology In Industry, 9(2), 289-307, 2021.
  [5] Prasanna, K., Hegde, S., & Murthy, S.. Energy efficient load sharing mechanism for multipath routing protocol in wireless sensor networks. In International Conference on Information Processing . Springer, Berlin, Heidelberg. pp. 422-427, August, 2011.
  [6] Priya, M. M., & Kumari, A.. Traffic aware multipath communication for time-critical applications in underwater acoustic sensor networks. Int J Manag IT Eng, 2(7), 66-73, 2012.
  [7] Kumar, V. N., Kumar, M. S., Rajakumari, J., & Mohanarangan, S.. Opportunistic void avoidance routing for underwater sensor networks. Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol, 2, 924-930, 2017.
  [8] Patil, M. S. A., & Mishra, M. P.. Improved mobicast routing protocol to minimize energy consumption for underwater sensor networks. International Journal of Research In Science & Engineering, 3(2), 201, 2017.
  [9] Gjanci, P., Petrioli, C., Basagni, S., Phillips, C. A., Bölöni, L., & Turgut, D.. Path finding for maximum value of information in multi-modal underwater wireless sensor networks. IEEE Transactions on Mobile Computing, 17(2), 404-418, 2017.
  [10] Abbasi, J. S., Javaid, N., Gull, S., Islam, S., Imran, M., Hassan, N., & Nasr, K.. Balanced energy efficient rectangular routing protocol for underwater wireless sensor networks. In 2017 13th International Wireless Communications and Mobile Computing Conference (IWCMC), pp. 1634-1640, June 2017. IEEE.
  [11] Akbar, M., Javaid, N., Khan, A. H., Imran, M., Shoaib, M., & Vasilakos, A.. Efficient data gathering in 3D linear underwater wireless sensor networks using sink mobility. Sensors, 16(3), 404, 2016.
  [12] Souiki, S., Hadjila, M., & Feham, M.. Fuzzy based clustering and energy efficient routing for underwater wireless sensor networks. International Journal of Computer Networks & Communications, 7(2), 33, 2015.

  Citation
  Musa Mojarad, Fariba Sarhangnia, Amin Rezaeipanah, "Energy-Aware Routing in UWSNs Using Cuckoo Algorithms for Improving Network Lifetime," World Academics Journal of Engineering Sciences, Vol.8, Issue.3, pp.1-5, 2021

• Open Access   Article

  Linguistic Based Pareto Guided Fuzzy Multi-Objective Optimization

  Hemant Kumar, Narendra Swami

  Research Paper | Journal-Paper (WAJES)

  Vol.8 , Issue.3 , pp.6-10, Sep-2021

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  In principle, a problem consists of mutually conflicting objectives in an engineering system design generates multiple solutions instead of a single solution. A set of solutions is required to satisfy such types of problems. These solutions are popularly known as Pareto-optimal solutions. An engineer always interests in reducing the cost and improving the reliability of the system simultaneously. This paper proposes linguistic fuzzy multi-objective models where reliability and cost are involved in the system design. Such types of formulations give an idea to find out the best compromise solution as per the demand of the decision-maker. At the same time, it removes the uncertainty confronted by a system design engineer in formulating the system design at the initial stage. The Pareto-optimal solutions are obtained by an efficient multi-objective evolutionary technique, namely NSGA-II. A designer finds the guided Pareto-optimal solutions as per the formulated models of the problem in linguistic forms. The best compromise solution is found by the decision-maker while analyzing the different cases of fuzzy models. The proposed approach is shown by taking a numerical example.

  Key-Words / Index Term
  Reliability, Fuzzy multi-objective optimization problem (FMOOP), Linguistic hedges, NSGA-II

  References
  [1] K. Deb, “Multi-objective optimization using evolutionary algorithms”, John Wiley & Sons, USA, pp. 1-9, 2001.
  [2] H. Kumar, S. P. Yadav, “NSGA-II based decision-making in fuzzy multi-objective optimization of system reliability”. In: Deep K, Jain M, Salhi S (eds) Decision science in action. Asset analytics (performance and safety management). Springer, pp. 105–117, 2019.
  [3] K. Deb, S. Agarwal, A. Pratap, T. Meyarivan, “A fast and elitist multi-objective genetic algorithm: NSGA-II”, IEEE Trans. Evol. Comput., Vol. 6, pp. 182-197, 2002.
  [4] H. Garg, S.P. Sharma, “Multi-objective reliability-redundancy allocation problem using particle swarm optimization”, Computers & Industrial Engineering, Vol. 64, No. 1, pp. 247-255, 2012.
  [5] H. Kumar, S. P. Yadav, “NSGA-II based fuzzy multi-objective reliability analysis”, International Journal of System Assurance Engineering and Management, Vol. 8, pp. 817-825, 2017.
  [6] H. Kumar, “Using Reference Point-Based NSGA-II to System Reliability”, International Journal of Computer Science and Engineering, Vol. 5, Issue.12, pp. 7-14, 2017.
  [7] H. Kumar, A. P. Singh, S. P. Yadav, “NSGA-II Based Analysis of Fuzzy Multi-objective Reliability-Redundancy Allocation Problem Using Various Membership functions”, INAE Letters, Vol. 4, pp. 191-206, 2019.
  [8] H. Z. Huang, “Fuzzy multi-objective optimization decision-making of reliability of series system”, Microelectronics Reliability, Vol. 37, pp. 447-449, 1997.
  [9] H. J. Zimmermann, “Fuzzy set theory and its applications”, Kluwer, Boston, ISBN 0-7923-9624-3, USA, pp. 1-10, 1996.
  [10] A. K. Dhingra, H. Moskowitz, “Application of fuzzy theories to multiple objective decision-making in system design”, European Journal of Operational Research, Vol. 53, pp. 348-361, 1991.
  [11] H. Kumar, S. P. Yadav, “Fuzzy rule-based reliability analysis using NSGA-II”, International Journal of System Assurance Engineering and Management, Vol. 10, pp. 953-972, 2019.

  Citation
  Hemant Kumar, Narendra Swami, "Linguistic Based Pareto Guided Fuzzy Multi-Objective Optimization," World Academics Journal of Engineering Sciences, Vol.8, Issue.3, pp.6-10, 2021

• Open Access   Article

  Exotic Ratio of some Noncircular Solids subjected to Torsion Loads using Lagrange Undetermined Multipliers

  Opeyemi David Alli, Tajudeen Kolawole Ajiboye

  Research Paper | Journal-Paper (WAJES)

  Vol.8 , Issue.3 , pp.11-14, Sep-2021

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  Abstract
  A parameter to aid machine designers was established using a mathematical analysis based on the theory of a single Lagrange multiplier for the maximum shear stresses developed during the torsion loading of non-circular elements. The maximum shear stress functions were based on formulas developed by the normal torsion theory for circular shafts, the Prandtl stress function and the Prandtl membrane analogy for four non-circular cross-sections and was used to develop a mathematical ratio known as the exotic ratio for elliptical, rectangular, thin walled tubes and hexagonal cross sections. The exotic ratio depends on two envelope points (x, y) for a minimum and a graph is plotted to show the cross sections with more exotic ratios. Also, from a radar chart, it is observed that the exotic ratio decreases in the order from a thin walled tube to a hexagon, then a rectangle and finally the elliptical solid respectively.

  Key-Words / Index Term
  Lagrange multiplier; torsion; geometry; maximum shear stress; exotic ratio

  References
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  [8] S. Timoshenko. Strength of Materials (3rded.). Part 1 Elementary Theory and Problems, Van Nostrand, New York. pp.183, 2002
  [9]R.J. Roark, W.C. Young. Formulae for Stress and Strain (5thed.). McGraw-Hill,Kogakusha pp.233-288.2002
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  Citation
  Opeyemi David Alli, Tajudeen Kolawole Ajiboye, "Exotic Ratio of some Noncircular Solids subjected to Torsion Loads using Lagrange Undetermined Multipliers," World Academics Journal of Engineering Sciences, Vol.8, Issue.3, pp.11-14, 2021

• Open Access   Article

  An Analytical Study on Music Listener Emotion through Logistic Regression

  Md. Anzir Hossain Rafath, Fatema Tuz Zohura Mim, Md. Shafiur Rahman

  Research Paper | Journal-Paper (WAJES)

  Vol.8 , Issue.3 , pp.15-20, Sep-2021

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  Abstract
  Now-a-days music listeners face immense obstacles when trying to find suitable music for a specific context. This is what actually motivated us to find a suitable solution on it. Here we presented a music classification system that provides the listener an opportunity to browse their music by mood. Mood classification while listening to music is an emerging domain of music information retrieval. This paper investigates the challenging issue of recognizing emotions while listening to music. Specifically, we formulate the music types as a regression problem to predict the human emotional state. No categorical taxonomy is used that’s why the regression approach is free of the ambiguity inherent to conventional categorical approaches. This will help to build an intuitive and contextually aware playlist generation tool. Talking of play list tool we have come to the point that most people are not sure that if their mood has been changed or not while listening to their favorite music, people tend to listen to emotional music when they deal with sorrow or disgust. In the time fear and anger they don’t listen any music. In the contrast they listen to music while having good feelings. We have achieved 78% of accuracy by taking the regression approach for the research.

  Key-Words / Index Term
  Data Mining, Machine learning, Regression approach, Emotion prediction, Music analysis

  References
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  [8] Y.H. Yang, Y.C. Lin, Y.F. Su, and H. H. Chen, “A regression approach to music emotion recognition," IEEE Transactions on audio, speech, and language processing, vol. 16, no. 2, pp. 448-457, 2008.
  [9] T. Li and M. Ogihara, “Content-based music similarity search and emotion detection,” in 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, vol. 5, pp. V-705, 2004.
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  [11] G. Tzanetakis and P. Cook, “Musical genre classification of audio signals,” IEEE Transactions on speech and audio processing, vol. 10, no. 5, pp. 293-302, 2002.
  [12] A. Sen and M. Srivastava, Regression analysis: theory, methods, and applications. Springer Science & Business Media, 2012.
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  [14] D. P. Solomatine and D. L. Shrestha, “Adaboost. rt: A boosting algorithm for regression problems,” in 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No. 04CH37541), IEEE, vol. 2, pp. 1163-1168, 2004.
  [15] E. Schubert, Measurement and time series analysis of emotion in music. University of New South Wales Sydney, vol. 1, 1999.
  [16] A. Hanjalic and L.-Q. Xu, “Affective video content representation and modeling,” IEEE transactions on multimedia, vol. 7, no. 1, pp. 143-154, 2005.
  [17] Y.H. Yang, C.C. Liu, and H. H. Chen, “Music emotion classification: A fuzzy approach,” in Proceedings of the 14th ACM international conference on Multimedia, pp. 81-84, 2006.
  [18] M. D. Korhonen, D. A. Clausi, and M. E. Jernigan, “Modeling emotional content of music using system identification,” IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 36, no. 3, pp. 588-599, 2006.
  [19] B.j. Han, S. Rho, R. B. Dannenberg, and E. Hwang, “Smers: Music emotion recognition using support vector regression.,” in ISMIR, Citeseer, pp. 651-656, 2009.
  [20] P. N. Juslin and J. A. Sloboda, Music and emotion: Theory and research. Oxford University Press, 2001.
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  Citation
  Md. Anzir Hossain Rafath, Fatema Tuz Zohura Mim, Md. Shafiur Rahman, "An Analytical Study on Music Listener Emotion through Logistic Regression," World Academics Journal of Engineering Sciences, Vol.8, Issue.3, pp.15-20, 2021

• Open Access   Article

  Project ECHHO (Electrolysis Complex with Hyper-Hydrogen Output): A Device Prototype for Inducing Oryza sativa’s Seed Germination and Growth

  Michael B. Bibon

  Research Paper | Journal-Paper (WAJES)

  Vol.8 , Issue.3 , pp.21-27, Sep-2021

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  Abstract
  The economic need for rice has prompted many agriculturists to innovate methods on hastening its growth to supply the increasing demand with limited agricultural space for farming. To present, fertilizers and soaking of rice grains were the common treatments to induce rice germination and growth. In this study, the innovated device called Project ECHHO, produces increased levels of Hydrogen gas through electrolysis of water tested via quasi-experimental approach with control set-ups of Hydrogen peroxide and water (seed germination), and NPK fertilizer and no fertilizer treatment (seed growth). This study primarily aims to test the effectiveness of the developed Project ECHHO in inducing rice grains’ germination and growth through Hydrogen misting. Hydrogen misting of rice grains via Project ECHHO revealed statistical no difference to Hydrogen peroxide on seed germination (p>0.05) and NPK fertilizer on seed growth (p>0.05). Furthermore, these findings were supported by the statistical difference on the seed germination of rice grains between Project ECHHO and water (p<0.05), and seed growth of rice grains between Project ECHHO and no fertilizer treatment (p<0.05). It was concluded that the use of Project ECHHO holds promising future in the field of agriculture for inducing rice grains’ germination and growth with minimal costing for development, and reusable green device for successive seed treatment. The device can be used as alternative to fertilizers and other chemicals used for farming. It was recommended to alter the design of Project ECHHO by improving the module of electrolysis complex to harness greater amounts of Hydrogen in water. Also, the need for testing the Project ECHHO in other seeds is recommended.

  Key-Words / Index Term
  Germination and Growth Inducer, Agriculture, Device Innovation, Electrolysis, Oryza Sativa

  References
  [1] D.Dawe, “Equity Effects of Rice Trade Liberalization in the Philippines,” In the Proceedings of the International Rice Research Conference, China, pp. 1007-1022, 2005.
  [2] F. Bordey, “The Impacts of Research on Philippine Rice Production,” University of Illinois, Unpublished Dissertation, 2010.
  [3] FAO,“The Future of Food and Agriculture: Trends and Challenges,” Food and Agriculture Organization of the United Nations, Italy, pp.1-145, 2017.
  [4] T. Luna, K. Wilkinson, and R.K. Dumroese, “Seed Germination and Sowing Options,” Agricultural Handbook, USA, pp. 163-183, 2014.
  [5] C. Huei-Kao, “Role of Hydrogen peroxide in Rice Plants,” Crop, Environment and Informatics, Vol. 11, pp. 1-11, 2014.
  [6] T. Wojtyla, K. Lechowska, S. Kubala, and M. Garnczarska, “Different Modes of Hydrogen peroxide Action During Seed Germination,” Front. Plant Sci., 2016.
  [7] R. Budiono, P. Adinurani, and P. Soni, “Effects of New NPK Fertilizer on Lowland Rice (Oryza sativa L.) Growth,” The 2nd International Conference on Natural Resources and Life Sciences, Vol. 239, 2019.
  [8] C. Li, T. Gong, B. Bian, and W. Liao, “Roles of Hydrogen gas in Plants: A Review,” Functional Plant Biology, Vol. 45, Issue 8, pp. 783-792, 2018.
  [9] K. Scott, “Introduction to Electrolysis, Electrolysers, and Hydrogen Production,” Royal Society of Chemistry, UK, pp. 1-27, 2019.
  [10] N.C. Pandey, “An Experiment for Obtaining Hydrogen and Its Mechanism of Burning,” International Journal of Scientific Research in Physics and Applied Sciences, Vol.9, Issue 1, pp.5-10, 2021
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  [13] Y. Zhu and W. Liao, “A positive role for hydrogen gas in adventitious root development,” Plant Signaling and Behavior, Vol. 11, Issue 6, 2016.
  [14] H. Hu, P. Li, Y. Wang, R. Gu, “Hydrogen-rich water delays postharvest ripening and senescence of kiwifruit,” Food Chem., Vol. 156, pp. 100-109, 2014.
  [15] Y. Lin, W. Zhang, F. Qi, W. Cui, Y. Xie, W. Shen, “Hydrogen-rich water regulates cucumber adventitious root development in a heme oxygenase-1/carbon monoxide-dependent manner,” Journal of Plant Physiology, Vol. 171, pp. 1-8, 2014.
  [16] H. Dufkova, M. Berka, M. Luklova, A. Rashotte, B. Brzobohaty, and M. Cerny, “Eggplant Germination is Promoted by Hydrogen peroxide and Temperature in an Independent but Overlapping Manner,” Molecules, Vol. 24, No. 23, p. 4270, 2019.
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  [18] F.A. Gondium, E. Filho, C. Lacerda, J. Prisco, A. Neto, and E. Marques, “Pretreatment with H2O2 in maize seeds: Effects on germination and seedling acclimation to salt stress,” Brazilian Journal of Plant Physiology, Vol. 22, Issue 2, 2010.
  [19] W. Anunkul, and W. Pattanagul, “Effects of hydrogen peroxide application on agronomic traits of rice under drought stress,” Plant, Soil and Environment, Vol. 67, Issue 4, pp. 221-229, 2021.
  [20] Ibid. [8]
  [21] S. Savci, “Investigation of Effect on Chemical Fertilizers on Environment,” Procedia APCBEE, Vol. 2012, pp. 5-7, 2012.
  [22] P. Withers, C. Neal, H. Jarvie, D. Doody, “Agriculture and Eutrophication: Where do we go from here?,” Sustainability, Vol. 2014, Issue 6, pp. 5853-5875, 2014.
  

  Citation
  Michael B. Bibon, "Project ECHHO (Electrolysis Complex with Hyper-Hydrogen Output): A Device Prototype for Inducing Oryza sativa’s Seed Germination and Growth," World Academics Journal of Engineering Sciences, Vol.8, Issue.3, pp.21-27, 2021

• Open Access   Article

  Detecting Syriatel`s Success Indicators Using Textual Data Mining for Arabic Language

  Hanan Mohsen Wassouf, Mohammad-Bassam Kurdy

  Research Paper | Journal-Paper (WAJES)

  Vol.8 , Issue.3 , pp.28-32, Sep-2021

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  Abstract
  Despite the broad knowledge and skills of the millennial generation, recent studies indicate that 90% of Companies are classified as failing companies, and usually end in bankruptcy due to many factors, including a departure from the market need, as the percentage of companies that built their activity around processing a good idea, but far from the needs of the market to bankruptcy 42% of the total companies. In addition to others reasons like the lack of liquidity and incomes with less capital than necessary, the weakness of the founding team and the emergence of many competing companies. All these reasons lead us to think about studying and identifying the success factors for these emerging companies in order to mitigate the possibility of failure. The target study will be Syriatel Mobile Telecom company which is most famous telecom company in Syria.

  Key-Words / Index Term
  Indicators Success ,Data Mining, Textual Analysis, Topic Modeling

  References
  [1] Saura, Pedro, & Grilo, ”Detecting Indicators for Startup Business Success: Sentiment Analysis Using Text Data Mining”, Sustainability, 11, 917, 2019.
  [2] Saura & Bennett, ” A Three-Stage method for Data Text Mining: Using UGC in Business Intelligence Analysis”, Sustainability 2019.
  [3] Saura, Reyes-Menendez, & Palos-Sanchez, “Are Black Friday Deals Worth It? Mining Twitter Users’ Sentiment and Behavior Response”, 2019
  [4] Vasile-DanielP?v?loaia, Elena-M?d?linaTeodor, DoinaFotache, & MagdalenaDanilet,” Opinion Mining on Social Media Data: Sentiment Analysis of User Preferences” , 2019
  [5] Al-Kabi, Al-Qudah, Dabour, & Izzat Alsmadi,” Arabic / English Sentiment Analysis: An Empirical Study”, 2013)
  [6] Kau?mann, et al .”Managing Marketing Decision-Making with Sentiment Analysis: An Evaluation of the Main Product Features Using Text Data Mining”,2019
  [7] Saura, Reyes-Menendez, & Bennett, “How to Extract Meaningful Insights from UGC: A Knowledge-Based Method Applied to Education”.
  [8] Vasile-DanielP?v?loaia, Elena-M?d?linaTeodor, DoinaFotache, & MagdalenaDanilet.,”Opinion Mining on Social Media Data: Sentiment Analysis of User Preferences”, 2019
  [9] Mohammed N. Al-Kabi, Alsmadi, Gigieh, & Wahsheh ,“Opinion Mining and Analysis for Arabic, 2014
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  [12] ,???? ? ?????? "Based Approach for Personalizing Arabic -Semantic Web News" ,2019

  Citation
  Hanan Mohsen Wassouf, Mohammad-Bassam Kurdy, "Detecting Syriatel`s Success Indicators Using Textual Data Mining for Arabic Language," World Academics Journal of Engineering Sciences, Vol.8, Issue.3, pp.28-32, 2021