Editor-In-Chief Chair Dr. Shiv Kumar

Ph.D. (CSE), M.Tech. (IT, Honors), B.Tech. (IT)

Director, Blue Eyes Intelligence Engineering & Sciences Publication, Bhopal (M.P.), India

Professor, Department of Computer Science & Engineering, Lakshmi Narain College of Technology-Excellence (LNCTE), Bhopal

(M.P.), India

Associated Editor-In-Chief Chair Dr. Dinesh Varshney

Director of College Development Counseling, Devi Ahilya University, Indore (M.P.), Professor, School of Physics, Devi Ahilya

University, Indore (M.P.), and Regional Director, Madhya Pradesh Bhoj (Open) University, Indore (M.P.), India

Associated Editor-In-Chief Members Dr. Hai Shanker Hota

Ph.D. (CSE), MCA, MSc (Mathematics)

Professor & Head, Department of CS, Bilaspur University, Bilaspur (C.G.), India

Dr. Gamal Abd El-Nasser Ahmed Mohamed Said

Ph.D(CSE), MS(CSE), BSc(EE)

Department of Computer and Information Technology , Port Training Institute, Arab Academy for Science ,Technology and Maritime

Transport, Egypt

Dr. Mayank Singh

PDF (Purs), Ph.D(CSE), ME(Software Engineering), BE(CSE), SMACM, MIEEE, LMCSI, SMIACSIT

Department of Electrical, Electronic and Computer Engineering, School of Engineering, Howard College, University of KwaZulu-

Natal, Durban, South Africa.

Scientific Editors Prof. (Dr.) Hamid Saremi

Vice Chancellor of Islamic Azad University of Iran, Quchan Branch, Quchan-Iran

Dr. Moinuddin Sarker

Vice President of Research & Development, Head of Science Team, Natural State Research, Inc., 37 Brown House Road (2nd Floor)

Stamford, USA.

Dr. Shanmugha Priya. Pon

Principal, Department of Commerce and Management, St. Joseph College of Management and Finance, Makambako, Tanzania, East

Africa, Tanzania

Dr. Veronica Mc Gowan

Associate Professor, Department of Computer and Business Information Systems,Delaware Valley College, Doylestown, PA, Allman,

China.

Dr. Fadiya Samson Oluwaseun

Assistant Professor, Girne American University, as a Lecturer & International Admission Officer (African Region) Girne, Northern

Cyprus, Turkey.

Dr. Robert Brian Smith

International Development Assistance Consultant, Department of AEC Consultants Pty Ltd, AEC Consultants Pty Ltd, Macquarie

Centre, North Ryde, New South Wales, Australia

Dr. Durgesh Mishra

Professor & Dean (R&D), Acropolis Institute of Technology, Indore (M.P.), India

Executive Editor Chair Dr. Deepak Garg

Professor & Head, Department Of Computer Science And Engineering, Bennett University, Times Group, Greater Noida (UP), India

Executive Editor Members Dr. Vahid Nourani

Professor, Faculty of Civil Engineering, University of Tabriz, Iran.

Dr. Saber Mohamed Abd-Allah

Associate Professor, Department of Biochemistry, Shanghai Institute of Biochemistry and Cell Biology, Shanghai, China.

Dr. Xiaoguang Yue

Associate Professor, Department of Computer and Information, Southwest Forestry University, Kunming (Yunnan), China.

Dr. Labib Francis Gergis Rofaiel

Associate Professor, Department of Digital Communications and Electronics, Misr Academy for Engineering and Technology,

Mansoura, Egypt.

Dr. Hugo A.F.A. Santos

ICES, Institute for Computational Engineering and Sciences, The University of Texas, Austin, USA.

Dr. Sunandan Bhunia

Associate Professor & Head, Department of Electronics & Communication Engineering, Haldia Institute of Technology, Haldia

(Bengal), India.

Dr. Awatif Mohammed Ali Elsiddieg

Assistant Professor, Department of Mathematics, Faculty of Science and Humatarian Studies, Elnielain University, Khartoum Sudan,

Saudi Arabia.

Technical Program Committee Chair Dr. Mohd. Nazri Ismail

Associate Professor, Department of System and Networking, University of Kuala (UniKL), Kuala Lumpur, Malaysia.

Technical Program Committee Members Dr. Haw Su Cheng

Faculty of Information Technology, Multimedia University (MMU), Jalan Multimedia (Cyberjaya), Malaysia.

Dr. Hasan. A. M Al Dabbas

Chairperson, Vice Dean Faculty of Engineering, Department of Mechanical Engineering, Philadelphia University, Amman, Jordan.

Dr. Gabil Adilov

Professor, Department of Mathematics, Akdeniz University, Konyaaltı/Antalya, Turkey.

Convener Chair Mr. Jitendra Kumar Sen

International Journal of Soft Computing and Engineering (IJSCE)

Editorial Chair Dr. Sameh Ghanem Salem Zaghloul

Department of Radar, Military Technical College, Cairo Governorate, Egypt.

Editorial Members Dr. Uma Shanker

Professor, Department of Mathematics, Muzafferpur Institute of Technology, Muzafferpur(Bihar), India

Dr. Rama Shanker

Professor & Head, Department of Statistics, Eritrea Institute of Technology, Asmara, Eritrea

Dr. Vinita Kumar

Department of Physics, Dr. D. Ram D A V Public School, Danapur, Patna(Bihar), India

Dr. Brijesh Singh

Senior Yoga Expert and Head, Department of Yoga, Samutakarsha Academy of Yoga, Music & Holistic Living, Prahladnagar,

Ahmedabad (Gujarat), India.

Dr. J. Gladson Maria Britto

Professor, Department of Computer Science & Engineering, Malla Reddy College of Engineering, Secunderabad (Telangana), India.

Dr. Sunil Tekale

Professor, Dean Academics, Department of Computer Science & Engineering, Malla Reddy College of Engineering, Secunderabad

(Telangana), India.

Dr. K. Priya

Professor & Head, Department of Commerce, Vivekanandha College of Arts & Sciences for Women (Autonomous, Elayampalayam,

Namakkal (Tamil Nadu), India.

Dr. Pushpender Sarao

Professor, Department of Computer Science & Engineering, Hyderabad Institute of Technology and Management, Hyderabad

(Telangana), India.

S. No

Volume 8 Issue 2S2, January 2019, ISSN: 2249 – 8958 (Online)

Published By: Blue Eyes Intelligence Engineering & Sciences Publication

Page No.

1.

Authors: Uma Meena, Anand Sharma

Paper Title: An Efficient Hop-by-Hop Message Authentication Scheme and Secure Location Privacy in Wireless

Sensor Networks

Abstract: Wireless sensor network in recent days affected with two main research problem such as message authentication and location privacy. This paper present an Elliptic Curve ElGamal Signature Algorithm scheme

(ECESA) for message authentication and Euclidean Zigzag Bidirectional Tree (EZBT) for location privacy of

both source and sink. ECESA involves three phase: (i) private and public key generation using Elliptic Curve

Cryptography (ECC), (ii) ElGamal signature arrangement for effective message encryption and (iii) matching

the decrypted result with MD5 hash value for authentication of the authorized person. The most important

privacy preserving techniques are the EZBT to send the messages either sink to source or from source to sink

with the location privacy scheme. On account of this, the proxy source and sink is selected while using the

Euclidean distance technique. Finally, the efficiency of the work has been demonstrated through the simulation

results of location privacy and message verification. Then the performance are validated in terms of quality of

service (QoS).

IndexTerms: Elliptic curve cryptography, ElGamal encryption, MD5 hash algorithm, location privacy,

Euclidean distance, Zigzag bidirectional tree

References: 1. D. Boneh, G. D. Crescenzo, R. Ostrovsky, and G. Persiano, “Public key encryption with keyword search,” in In proceedings of

Eurocrypt, 2004, pp. 506–522.

2. B. Waters, D. Balfanz, G. Durfee, and D. K. Smetters, “Building an encrypted and searchable audit log,” in Network and Distributed System Security Symposium, 2004.

3. M. Ding, F. Gao, Z. Jin, and H. Zhang, “An efficient public key encryption with conjunctive keyword search scheme based on pairings,” in IEEE International Conference onNetwork Infrastructure and Digital Content, 2012, pp. 526–530.

4. F. Kerschbaum, “Secure conjunctive keyword searches for unstructured text,” in International Conference on Network and System Security, 2011, pp. 285–289.

5. C. Hu and P. Liu, “Public key encryption with ranked multi-keyword search,” in International Conference on Intelligent Networking and Collaborative Systems, 2013, pp. 109 113.

6. Z. Fu, X. Sun, N. Linge, and L. Zhou, “Achieving effective cloud search services: multi-keyword ranked search over encrypted cloud data supporting synonym query,” IEEE Transactions on Consumer Electronics, vol. 60, pp. 164–172, 2014.

7. C. L. A. Clarke, G. V. Cormack, and E. A. Tudhope, “Relevance ranking for one to three term queries,” Information Processing and Management: an International Journal, vol. 36, no. 2, pp. 291–311, Jan. 2000.

8. H. Tuo and M. Wenping, “An effective fuzzy keyword search scheme in cloud computing,” in International Conference on Intelligent Networking and Collaborative Systems, 2013, pp. 786–789.

9. M. Zheng and H. Zhou, “An efficient attack on a fuzzy keyword search scheme over encrypted data,” in International Conference on High Performance Computing and Communications and Embedded and Ubiquitous Computing, 2013, pp. 1647 1651.

10. S. Zittrower and C. C. Zou, “Encrypted phrase searching in the cloud,” in IEEE Global Communications Conference, 2012, pp. 764– 770.

11. Y. Tang, D. Gu, N. Ding, and H. Lu, “Phrase search over encrypted data with symmetric encryption scheme,” in International Conference on Distributed Computing SystemsWorkshops, 2012, pp. 471–480.

12. H. Poon and A. Miri, “An efficient conjunctive keyword and phrase search scheme for encrypted cloud storage systems,” in IEEE International Conference on Cloud Computing, 2015.

13. “A low storage phrase search scheme based on bloom filters for encrypted cloud services,” to appear in IEEE International Conference on Cyber Security and Cloud Computing, 2015.

14. H. S. Rhee, I. R. Jeong, J. W. Byun, and D. H. Lee, “Difference set attacks on conjunctive keyword search schemes,” in Proceedings of the Third VLDB International Conference on Secure Data Management, 2006, pp. 64–74.

15. K. Cai, C. Hong, M. Zhang, D. Feng, and Z. Lv, “A secure conjunctive keywords search over encrypted cloud data against inclusion-relation attack,” in IEEE International Conference on Cloud Computing Technology and Science, 2013, pp. 339–346.

16. Y. Yang, H. Lu, and J. Weng, “Multi-user private keyword search for cloud computing,” in IEEE Third International Conference on

17. Cloud Computing Technology and Science, 2011, pp. 264–271. 18. C. Wang, N. Cao, J. Li, K. Ren, and W. Lou, “Secure ranked keyword search over encrypted cloud data,” in International

Conference on Distributed Computing Systems, 2010, pp. 253–262.

19. M. T. Goodrich, M. Mitzenmacher, O. Ohrimenko, and R. Tamassia, “Practical oblivious storage,” in Proceedings of the Second ACM Conference on Data and Application Security and Privacy, 2012, pp. 13–24.

20. B. Chor, O. Goldreich, E. Kushilevitz, and M. Sudan, “Private information retrieval,” in Proceedings of the 36th Annual Symposium on Foundations of Computer Science, 1995, pp. 41–50.

21. S. Ruj, M. Stojmenovic, and A. Nayak, “Privacy preserving access control with authentication for securing data in clouds,” in Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, 2012, pp. 556 563.

1-6

2.

Authors: Ajay Singh Yadav, Kapil Kumar Bansal, Jitendra Kumar, Sachin Kumar

Paper Title: Supply Chain Inventory model for deteriorating item with warehouse & Distribution centres under

Inflation

Abstract: Inventory of Chemical Industry model is a method of balancing investment to achieve the service-level goal. Here consider Warehouse of Chemical Industry and Distribution centres of Inventory of Chemical

Industry models. One is of finite capacity treated as Distribution centres of Chemical Industry which is at market

place and other warehouse is of infinite capacity treated as Warehouse which is at some other place from the

market PSO Algorithm and SA. Here the objective is to minimize the total cost .In this work Particle swarm

optimization Algorithm and Simulated Annealing is used to optimize or to minimize the cost. The results

produced from the Particle swarm optimization Algorithm and Simulated Annealing are compared with

mathematical model and genetic algorithm. Results show that the PSO Algorithm and SA optimized the results

7-13

more than traditional mathematical model and PSO Algorithm and SA.

Keywords: Inventory of Chemical Industry, Warehouse of Chemical Industry, Distribution centres of Chemical Industry, PSO Algorithm and SA

References: 1. Yadav, A.S. and Swami, A. (2018) Integrated Supply Chain Model For Deteriorating Items With Linear Stock Dependent

Demand Under Imprecise And Inflationary Environment. International Journal Procurement Management, Volume 11 No 6.

2. Yadav, A.S. and Swami, A. (2018) A partial backlogging production-inventory lot-size model with time-varying holding cost and weibull deterioration International Journal Procurement Management, Volume 11, No. 5.

3. Yadav, A.S., Swami, A. and Kumar, S. (2018) A supply chain Inventory Model for decaying Items with Two Ware-House and Partial ordering under Inflation. International Journal of Pure and Applied Mathematics, Volume 120 No 6.

4. Yadav, A.S., Swami, A. and Kumar, S. (2018) An Inventory Model for Deteriorating Items with Two warehouses and variable holding Cost International Journal of Pure and Applied Mathematics, Volume 120 No 6.

5. Yadav, A.S., Swami, A. and Kumar, S. (2018) Inventory of Electronic components model for deteriorating items with warehousing using Genetic Algorithm. International Journal of Pure and Applied Mathematics, Volume 119 No. 16.

6. Yadav, A.S., Johri, M., Singh, J. and Uppal, S. (2018) Analysis of Green Supply Chain Inventory Management for Warehouse With Environmental Collaboration and Sustainability Performance Using Genetic Algorithm. International Journal of Pure and

Applied Mathematics, Volume 118 No. 20. 7. Yadav, A.S., and Kumar, S. (2017) Electronic Components Supply Chain Management for Warehouse with Environmental

Collaboration & Neural Networks. International Journal of Pure and Applied Mathematics, Volume 117 No. 17.

8. Yadav, A.S., Taygi, B., Sharma, S. and Swami, A. (2017) Effect of inflation on a two-warehouse inventory model for deteriorating items with time varying demand and shortages International Journal Procurement Management, Volume 10, No. 6.

9. Yadav, A.S., Mahapatra, R.P., Sharma, S. and Swami, A. (2017) An Inflationary Inventory Model for Deteriorating items under Two Storage Systems International Journal of Economic Research, Volume 14 No.9.

10. Yadav, A.S., Sharma, S. and Swami, A. (2017) A Fuzzy Based Two-Warehouse Inventory Model For Non instantaneous Deteriorating Items With Conditionally Permissible Delay In Payment, International Journal of Control Theory And

Applications, Volume 10 No.11. 11. Yadav, A.S., (2017) Analysis Of Supply Chain Management In Inventory Optimization For Warehouse With Logistics Using

Genetic Algorithm International Journal of Control Theory And Applications, Volume 10 No.10.

12. Yadav, A.S., Swami, A., Kher, G. and Sachin Kumar (2017) Supply Chain Inventory Model for Two Warehouses with Soft Computing Optimization International Journal of Applied Business and Economic Research Volume 15 No 4.

13. Yadav, A.S., Mishra, R., Kumar, S. and Yadav, S. (2016) Multi Objective Optimization for Electronic Component Inventory Model & Deteriorating Items with Two-warehouse using Genetic Algorithm International Journal of Control Theory and applications, Volume 9 No.2.

14. Yadav, A.S., (2017) Modeling and Analysis of Supply Chain Inventory Model with two-warehouses and Economic Load Dispatch Problem Using Genetic Algorithm International Journal of Engineering and Technology (IJET) Volume 9 No 1.

15. Yadav, A.S., Swami, A. and Kher, G. (2018) Particle Swarm optimization of inventory model with two-warehouses Asian Journal of Mathematics and Computer Research Volume 23 No.1.

16. Yadav, A.S., Maheshwari, P., Swami, A. and Pandey, G. (2018) A supply chain management of chemical industry for deteriorating items with warehouse using genetic algorithm Selforganizology, Volume 5 No.1-2.

17. Yadav, A.S., (2017) Analysis Of Seven Stages Supply Chain Management In Electronic Component Inventory Optimization For Warehouse With Economic Load Dispatch Using GA And PSO Asian Journal Of Mathematics And Computer Research volume

16 No.4 2017.

18. Yadav, A.S., Garg, A., Gupta, K. and Swami, A. (2017) Multi-objective Genetic algorithm optimization in Inventory model for deteriorating items with shortages using Supply Chain management IPASJ International journal of computer science (IIJCS)

Volume 5, Issue 6.

19. Yadav, A.S., Garg, A., Swami, A. and Kher, G. (2017) A Supply Chain management in Inventory Optimization for deteriorating items with Genetic algorithm International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) Volume

6, Issue 3.

20. Yadav, A.S., Maheshwari, P., Garg, A., Swami, A. and Kher, G. (2017) Modeling & Analysis of Supply Chain management in Inventory Optimization for deteriorating items with Genetic algorithm and Particle Swarm optimization International Journal of

Application or Innovation in Engineering & Management (IJAIEM) Volume 6, Issue 6.

21. Yadav, A.S., Garg, A., Gupta, K. and Swami, A. (2017) Multi-objective Particle Swarm optimization and Genetic algorithm in Inventory model for deteriorating items with shortages using Supply Chain management International Journal of Application or

Innovation in Engineering & Management (IJAIEM) Volume 6, Issue 6.

22. Yadav, A.S., Maheshwari, P., Swami, A. and Kher, G. (2017) Soft Computing Optimization of Two Warehouse Inventory Model With Genetic Algorithm. Asian Journal of Mathematics and Computer Research volume 19 No.4.

23. Yadav, A.S., Swami, A. and Kher, G. (2017) Multi-Objective Genetic Algorithm Involving Green Supply Chain Management International Journal for Science and Advance Research In Technology (IJSART) Volume 3 Issue 9.

24. Yadav, A.S., Swami, A. and Kher, G. (2017) Multi-Objective Particle Swarm Optimization Algorithm Involving Green Supply Chain Inventory Management International Journal for Science and Advance Research In Technology (IJSART) Volume 3 Issue

9. 25. Yadav, A.S., Swami, A. and Pandey, G. (2017) Green Supply Chain Management for Warehouse with Particle Swarm

Optimization Algorithm International Journal for Science and Advance Research In Technology (IJSART) Volume 3 Issue 10.

26. Yadav, A.S., Swami, A., Kher, G. and Garg, A. (2017) Analysis of seven stages supply chain management in electronic component inventory optimization for warehouse with economic load dispatch using genetic algorithm Selforganizology, Volume

4 No.2.

27. Yadav, A.S., Maheshwari, P., Swami, A. and Garg, A. (2017) Analysis of Six Stages Supply Chain management in Inventory Optimization for warehouse with Artificial bee colony algorithm using Genetic Algorithm Selforganizology, Volume 4 No.3.

28. Yadav, A.S., Swami, A., C. B. Gupta, and Garg, A. (2016) Analysis of Electronic component inventory Optimization in Six Stages Supply Chain management for warehouse with ABC using genetic algorithm and PSO Selforganizology, Volume 4 No.4.

29. Yadav, A.S., Swami, A., Kumar, S. and Singh, R.K. (2016) Two-Warehouse Inventory Model for Deteriorating Items with Variable Holding Cost, Time-Dependent Demand and Shortages IOSR Journal of Mathematics (IOSR-JM) Volume 12, Issue 2

Ver. IV. 30. Yadav, A.S., Sharam, S. and Swami, A. (2016) Two Warehouse Inventory Model with Ramp Type Demand and Partial

Backordering for Weibull Distribution Deterioration International Journal of Computer Applications Volume 140 –No.4.

31. Yadav, A.S., Swami, A. and Singh, R.K. (2016) A two-storage model for deteriorating items with holding cost under inflation and Genetic Algorithms International Journal of Advanced Engineering, Management and Science (IJAEMS) Volume -2, Issue-4.

32. Singh, R.K., Yadav, A.S. and Swami, A. (2016) A Two-Warehouse Model for Deteriorating Items with Holding Cost under Particle Swarm Optimization International Journal of Advanced Engineering, Management and Science (IJAEMS) Volume -2, Issue-6.

33. Singh, R.K., Yadav, A.S. and Swami, A. (2016) A Two-Warehouse Model for Deteriorating Items with Holding Cost under

Inflation and Soft Computing Techniques International Journal of Advanced Engineering, Management and Science (IJAEMS) Volume -2, Issue-6.

34. Sharma, S., Yadav, A.S. and Swami, A. (2016) An Optimal Ordering Policy For Non-Instantaneous Deteriorating Items With Conditionally Permissible Delay In Payment Under Two Storage Management International Journal of Computer Applications Volume 147 –No.1.

Yadav, A.S., Maheshwari, P. and Swami, A. (2016) Analysis of Genetic Algorithm and Particle Swarm Optimization for

warehouse with Supply Chain management in Inventory control International Journal of Computer Applications Volume 145 –No.5.

35. Swami, A., Singh, S. R., Pareek, S. and Yadav, A.S. (2015) Inventory policies for deteriorating item with stock dependent demand and variable holding costs under permissible delay in payment International Journal of Application or Innovation in Engineering & Management (IJAIEM) Volume 4, Issue 2.

36. Swami, A., Pareek, S. , , S. R. Singh and Yadav, A.S. (2015) An Inventory Model With Price Sensitive Demand, Variable Holding Cost And Trade-Credit Under Inflation International Journal of Current Research Volume 7, Issue, 06.

37. Gupta, K., Yadav, A.S., Garg, A. and Swami, A. (2015) A Binary Multi-Objective Genetic Algorithm &PSO involving Supply Chain Inventory Optimization with Shortages, inflation International Journal of Application or Innovation in Engineering &

Management (IJAIEM) Volume 4, Issue 8. 38. Yadav, A.S., Gupta, K., Garg, A. and Swami, A. (2015) A Soft computing Optimization based Two Ware-House Inventory

Model for Deteriorating Items with shortages using Genetic Algorithm International Journal of Computer Applications Volume

126 – No.13. 39. Gupta, K., Yadav, A.S. and Garg, A. (2015) Fuzzy-Genetic Algorithm based inventory model for shortages and inflation under

hybrid & PSO IOSR Journal of Computer Engineering (IOSR-JCE) Volume 17, Issue 5, Ver. I.

40. Yadav, A.S., Gupta, K., Garg, A. and Swami, A. (2015) A Two Warehouse Inventory Model for Deteriorating Items with Shortages under Genetic Algorithm and PSO International Journal of Emerging Trends & Technology in Computer Science

(IJETTCS) Volume 4, Issue 5(2).

41. Taygi, B., Yadav, A.S., Sharma, S. and Swami, A. (2015) An Inventory Model with Partial Backordering, Weibull Distribution Deterioration under Two Level of Storage International Journal of Computer Applications.

42. Yadav, A.S. and Swami, A. (2014) Two-Warehouse Inventory Model for Deteriorating Items with Ramp-Type Demand Rate and Inflation. American Journal of Mathematics and Sciences Volume 3 No-1.

43. Yadav, A.S. and Swami, A. (2013) Effect of Permissible Delay on Two-Warehouse Inventory Model for Deteriorating items with Shortages. International Journal of Application or Innovation in Engineering & Management (IJAIEM) Volume 2, Issue 3.

44. Yadav, A.S., Swami, A. (2013) A Two-Warehouse Inventory Model for Decaying Items with Exponential Demand and Variable Holding Cost. International of Inventive Engineering and Sciences (IJIES) Volume-1, Issue-5.

3.

Authors: Ajay Singh Yadav, Jitendra Kumar, Medhavi Malik, Tripti Pandey

Paper Title: Supply Chain of Chemical industry for Warehouse with distribution centres using Artificial bee

colony algorithm

Abstract: Chemical industry supply chain management for chemical industry warehouses with environmental concerns A technique based on artificial bee colony algorithm to optimize inventory throughout the supply

chain. We focus on determining the dynamics of the overstock and bottleneck levels required to optimize

inventory in the supply chain, minimizing the overall supply chain management of the chemical industry in the

warehouse. The chemical industry with environmental concerns. The complexity of the problem increases as

more and more products and many retailers participate in the management of the chemical industry's supply

chain for the chemical industry's warehouse, which resolves the environmental problems posed by this work.

Here we propose an optimization method using the Artificial Bee Colony algorithm, one of the best optimization

algorithms, to help you overcome the current impasse in order to maintain optimal inventory levels for each

member of the chain. supply of the chemical industry. Environmental concerns. We apply our method to four

members of the chemical industry supply chain for the optimization model studied by the chemical storage

industry.

Keywords: Supply Chain, Warehouse of Chemical industry, Two- distribution centres, Two-Retailers, environmental collaboration and Artificial bee colony algorithm .

References: 1. Yadav, A.S. and Swami, A. (2018) Integrated Supply Chain Model For Deteriorating Items With Linear Stock Dependent

Demand Under Imprecise And Inflationary Environment. International Journal Procurement Management, Volume 11 No 6.

2. Yadav, A.S. and Swami, A. (2018) A partial backlogging production-inventory lot-size model with time-varying holding cost and weibull deterioration International Journal Procurement Management, Volume 11, No. 5.

3. Yadav, A.S., Swami, A. and Kumar, S. (2018) A supply chain Inventory Model for decaying Items with Two Ware-House and Partial ordering under Inflation. International Journal of Pure and Applied Mathematics, Volume 120 No 6.

4. Yadav, A.S., Swami, A. and Kumar, S. (2018) An Inventory Model for Deteriorating Items with Two warehouses and variable holding Cost International Journal of Pure and Applied Mathematics, Volume 120 No 6.

5. Yadav, A.S., Swami, A. and Kumar, S. (2018) Inventory of Electronic components model for deteriorating items with warehousing using Genetic Algorithm. International Journal of Pure and Applied Mathematics, Volume 119 No. 16.

6. Yadav, A.S., Johri, M., Singh, J. and Uppal, S. (2018) Analysis of Green Supply Chain Inventory Management for Warehouse With Environmental Collaboration and Sustainability Performance Using Genetic Algorithm. International Journal of Pure and Applied Mathematics, Volume 118 No. 20.

7. Yadav, A.S., and Kumar, S. (2017) Electronic Components Supply Chain Management for Warehouse with Environmental Collaboration & Neural Networks. International Journal of Pure and Applied Mathematics, Volume 117 No. 17.

8. Yadav, A.S., Taygi, B., Sharma, S. and Swami, A. (2017) Effect of inflation on a two-warehouse inventory model for deteriorating items with time varying demand and shortages International Journal Procurement Management, Volume 10, No. 6.

9. Yadav, A.S., Mahapatra, R.P., Sharma, S. and Swami, A. (2017) An Inflationary Inventory Model for Deteriorating items under Two Storage Systems International Journal of Economic Research, Volume 14 No.9.

10. Yadav, A.S., Sharma, S. and Swami, A. (2017) A Fuzzy Based Two-Warehouse Inventory Model For Non instantaneous Deteriorating Items With Conditionally Permissible Delay In Payment, International Journal of Control Theory And Applications, Volume 10 No.11.

11. Yadav, A.S., (2017) Analysis Of Supply Chain Management In Inventory Optimization For Warehouse With Logistics Using Genetic Algorithm International Journal of Control Theory And Applications, Volume 10 No.10.

12. Yadav, A.S., Swami, A., Kher, G. and Sachin Kumar (2017) Supply Chain Inventory Model for Two Warehouses with Soft Computing Optimization International Journal of Applied Business and Economic Research Volume 15 No 4.

13. Yadav, A.S., Mishra, R., Kumar, S. and Yadav, S. (2016) Multi Objective Optimization for Electronic Component Inventory

14-19

Model & Deteriorating Items with Two-warehouse using Genetic Algorithm International Journal of Control Theory and applications, Volume 9 No.2.

14. Yadav, A.S., (2017) Modeling and Analysis of Supply Chain Inventory Model with two-warehouses and Economic Load Dispatch Problem Using Genetic Algorithm International Journal of Engineering and Technology (IJET) Volume 9 No 1.

15. Yadav, A.S., Swami, A. and Kher, G. (2018) Particle Swarm optimization of inventory model with two-warehouses Asian Journal of Mathematics and Computer Research Volume 23 No.1.

16. Yadav, A.S., Maheshwari, P., Swami, A. and Pandey, G. (2018) A supply chain management of chemical industry for deteriorating items with warehouse using genetic algorithm Selforganizology, Volume 5 No.1-2.

17. Yadav, A.S., (2017) Analysis Of Seven Stages Supply Chain Management In Electronic Component Inventory Optimization For Warehouse With Economic Load Dispatch Using GA And PSO Asian Journal Of Mathematics And Computer Research volume 16 No.4 2017.

18. Yadav, A.S., Garg, A., Gupta, K. and Swami, A. (2017) Multi-objective Genetic algorithm optimization in Inventory model for deteriorating items with shortages using Supply Chain management IPASJ International journal of computer science (IIJCS) Volume 5, Issue 6.

19. Yadav, A.S., Garg, A., Swami, A. and Kher, G. (2017) A Supply Chain management in Inventory Optimization for deteriorating items with Genetic algorithm International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) Volume 6, Issue 3.

20. Yadav, A.S., Maheshwari, P., Garg, A., Swami, A. and Kher, G. (2017) Modeling & Analysis of Supply Chain management in Inventory Optimization for deteriorating items with Genetic algorithm and Particle Swarm optimization International Journal of Application or Innovation in Engineering & Management (IJAIEM) Volume 6, Issue 6.

21. Yadav, A.S., Garg, A., Gupta, K. and Swami, A. (2017) Multi-objective Particle Swarm optimization and Genetic algorithm in Inventory model for deteriorating items with shortages using Supply Chain management International Journal of Application or Innovation in Engineering & Management (IJAIEM) Volume 6, Issue 6.

22. Yadav, A.S., Maheshwari, P., Swami, A. and Kher, G. (2017) Soft Computing Optimization of Two Warehouse Inventory Model With Genetic Algorithm. Asian Journal of Mathematics and Computer Research volume 19 No.4.

23. Yadav, A.S., Swami, A. and Kher, G. (2017) Multi-Objective Genetic Algorithm Involving Green Supply Chain Management International Journal for Science and Advance Research In Technology (IJSART) Volume 3 Issue 9.

24. Yadav, A.S., Swami, A. and Kher, G. (2017) Multi-Objective Particle Swarm Optimization Algorithm Involving Green Supply Chain Inventory Management International Journal for Science and Advance Research In Technology (IJSART) Volume 3 Issue

9.

25. Yadav, A.S., Swami, A. and Pandey, G. (2017) Green Supply Chain Management for Warehouse with Particle Swarm Optimization Algorithm International Journal for Science and Advance Research In Technology (IJSART) Volume 3 Issue 10.

26. Yadav, A.S., Swami, A., Kher, G. and Garg, A. (2017) Analysis of seven stages supply chain management in electronic component inventory optimization for warehouse with economic load dispatch using genetic algorithm Selforganizology, Volume 4 No.2.

27. Yadav, A.S., Maheshwari, P., Swami, A. and Garg, A. (2017) Analysis of Six Stages Supply Chain management in Inventory Optimization for warehouse with Artificial bee colony algorithm using Genetic Algorithm Selforganizology, Volume 4 No.3.

28. Yadav, A.S., Swami, A., C. B. Gupta, and Garg, A. (2016) Analysis of Electronic component inventory Optimization in Six Stages Supply Chain management for warehouse with ABC using genetic algorithm and PSO Selforganizology, Volume 4 No.4.

29. Yadav, A.S., Swami, A., Kumar, S. and Singh, R.K. (2016) Two-Warehouse Inventory Model for Deteriorating Items with Variable Holding Cost, Time-Dependent Demand and Shortages IOSR Journal of Mathematics (IOSR-JM) Volume 12, Issue 2

Ver. IV. 30. Yadav, A.S., Sharam, S. and Swami, A. (2016) Two Warehouse Inventory Model with Ramp Type Demand and Partial

Backordering for Weibull Distribution Deterioration International Journal of Computer Applications Volume 140 –No.4.

31. Yadav, A.S., Swami, A. and Singh, R.K. (2016) A two-storage model for deteriorating items with holding cost under inflation and Genetic Algorithms International Journal of Advanced Engineering, Management and Science (IJAEMS) Volume -2, Issue-4.

32. Singh, R.K., Yadav, A.S. and Swami, A. (2016) A Two-Warehouse Model for Deteriorating Items with Holding Cost under Particle Swarm Optimization International Journal of Advanced Engineering, Management and Science (IJAEMS) Volume -2, Issue-6.

33. Singh, R.K., Yadav, A.S. and Swami, A. (2016) A Two-Warehouse Model for Deteriorating Items with Holding Cost under Inflation and Soft Computing Techniques International Journal of Advanced Engineering, Management and Science (IJAEMS) Volume -2, Issue-6.

34. Sharma, S., Yadav, A.S. and Swami, A. (2016) An Optimal Ordering Policy For Non-Instantaneous Deteriorating Items With Conditionally Permissible Delay In Payment Under Two Storage Management International Journal of Computer Applications Volume 147 –No.1.

35. Yadav, A.S., Maheshwari, P. and Swami, A. (2016) Analysis of Genetic Algorithm and Particle Swarm Optimization for warehouse with Supply Chain management in Inventory control International Journal of Computer Applications Volume 145 –No.5.

36. Swami, A., Singh, S. R., Pareek, S. and Yadav, A.S. (2015) Inventory policies for deteriorating item with stock dependent demand and variable holding costs under permissible delay in payment International Journal of Application or Innovation in Engineering & Management (IJAIEM) Volume 4, Issue 2.

37. Swami, A., Pareek, S. , , S. R. Singh and Yadav, A.S. (2015) An Inventory Model With Price Sensitive Demand, Variable Holding Cost And Trade-Credit Under Inflation International Journal of Current Research Volume 7, Issue, 06.

38. Gupta, K., Yadav, A.S., Garg, A. and Swami, A. (2015) A Binary Multi-Objective Genetic Algorithm &PSO involving Supply Chain Inventory Optimization with Shortages, inflation International Journal of Application or Innovation in Engineering &

Management (IJAIEM) Volume 4, Issue 8. 39. Yadav, A.S., Gupta, K., Garg, A. and Swami, A. (2015) A Soft computing Optimization based Two Ware-House Inventory

Model for Deteriorating Items with shortages using Genetic Algorithm International Journal of Computer Applications Volume

126 – No.13. 40. Gupta, K., Yadav, A.S. and Garg, A. (2015) Fuzzy-Genetic Algorithm based inventory model for shortages and inflation under

hybrid & PSO IOSR Journal of Computer Engineering (IOSR-JCE) Volume 17, Issue 5, Ver. I.

41. Yadav, A.S., Gupta, K., Garg, A. and Swami, A. (2015) A Two Warehouse Inventory Model for Deteriorating Items with Shortages under Genetic Algorithm and PSO International Journal of Emerging Trends & Technology in Computer Science

(IJETTCS) Volume 4, Issue 5(2).

42. Taygi, B., Yadav, A.S., Sharma, S. and Swami, A. (2015) An Inventory Model with Partial Backordering, Weibull Distribution Deterioration under Two Level of Storage International Journal of Computer Applications.

43. Yadav, A.S. and Swami, A. (2014) Two-Warehouse Inventory Model for Deteriorating Items with Ramp-Type Demand Rate and Inflation. American Journal of Mathematics and Sciences Volume 3 No-1.

44. Yadav, A.S. and Swami, A. (2013) Effect of Permissible Delay on Two-Warehouse Inventory Model for Deteriorating items with Shortages. International Journal of Application or Innovation in Engineering & Management (IJAIEM) Volume 2, Issue 3.

45. Yadav, A.S., Swami, A. (2013) A Two-Warehouse Inventory Model for Decaying Items with Exponential Demand and Variable Holding Cost. International of Inventive Engineering and Sciences (IJIES) Volume-1, Issue-5.

4. Authors: HemanthBabu N, Sujata Shivashimpiger, N. Samanvita, V M Parthasarathy

Paper Title: Performance Ratio and Loss Analysis for 20MW Grid Connected Solar PV System - Case Study

Abstract: Solar Energy is fast developing source of energy in all over the world .The total installed capacity of Solar photovoltaic plant is 20 GW in India till February 2018. Knowledge about the performance of solar PV

plant will result in correct investment decision and better regulatory framework, technical enhancement of solar

photovoltaic technology. The study reports the various performance parameters such as Performance Ratio (PR),

loss parameters and actors contributing to the performance of solar power plants. i.e., radiation, temperature, and

other climate conditions and design parameters.PR is very essential at the starting stage of plant construction to

get generation yield, good performance and results of Solar Photo Voltaic (SPV) System in twenty five years of

time span. Solar PV plant performance is calculated on the basis of PR for particular time span of energy

generation through solar PV at any location. In this paper 20 MW Solar PV plant is considered for the case study

which is located in Kolar dist Karnataka. For this analysis the performance of Solar PV plant based on the site

survey and one year practical performance data is compared with simulated performance data and loss analysis

through PVSYST software.

Keywords: PhotoVoltaic(PV)System, Losses, PVSYST Software and Performance Ratio(PR), Efficiency.

References: 1. Julie A Rodiek, Steve R Best, “Comparison of photovoltaic modeling analysis and actual performance data of Lee County Justice

Center solar power installation project”, 8th annual International energy conversion engineering conference.

2. Indian standard “Photovoltaic system performance monitoring-guideline for measurement, data exchange and analysis” IS/EN 61724.

3. Dinesh Kumar Sharma1, Varsha Verma2, Shailendra Sharma2Performance Ratio and Losses Analysis of 1MW Grid-Connected Photovoltaic System

4. Parvathy Suresh Performance analysis of a stand alone system using PVSYST. 5. Sami Ekici Investigation of PV system cable losses 6. B. Mondoc 3RD International Conference on Modern Power Systems MPS 2010, Factors Influence the performance of

photovoltaic plant.

7. Bharat Kumar M Performance Evaluation of 5MW Grid Connected Solar Photovoltaic power plant established in karnataka 8. K. Padmavathi , S. Arjun Daniel Performance analysis of a 3MW grid connected solar photovoltaic power plant in India. 9. http://www. pvsyst.com 10. http://www. pveducation.org

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5.

Authors: Ompal Singh, Kapil Kumar Bansal, Satish Kumar

Paper Title: Algorithm of Model on Zoning Process

Abstract: This paper represent is the process by which a network is partitioned into smaller network each of which is delegated with a smaller network each of which is delegated with a certain degree of autonomy in terms

of resource allocation and operation. The term “Autonomy” implies that once the guiding policy is articulated

and the resource allocation is decided upon, local management may enjoy some freedom in local, short-term

decisions such as dispatching repositioning, budget planning and manning. The implications of zoning prevail

over a long period. Once a wide network is partitioned into sub network, each sub network will likely be treated

as almost an independent network in terms of its “rights” to possess and to operate resources.

Keywords: Resources, Partition, Autonomy, Delegated, Network

References: 1. Ayeni, MAD, “A Predictive Model of urban Stock and Activity” Empirical Development Environment and planning A, PP 59-77,

1976.

2. Beckman and M.J., “Continuous Model of transportation and location” Sistemi Urbani,International Journal of Network system, 4(5), PP 619-630, 1981.

3. Berman, O., and A.R.Odoni, “locating Mobile Servers on a Network with Markovian properties” Network 12, PP 73-86, 1982.

4. Conway, R.W., W.O. Maxwen and L.W. Miller, “Theory of scheduling” International Journal of Network system, 4(5), PP 312-325, 1996.

5. Eilon,S.,C.D.T.,Watson-Gandy and N.Christofides, “Distribution Management: Mathematical Sodeling and Practical analysis” Grifin Landon, P 125-135, 1971.

6. EI-Shaieb, A.M., “A New Algorithm for Locating Sources among destinations” Management Science 20, P 221-231, 1973. 7. Garfinkel, R.S., and G.L.Nemhauser, “Optimal Political districting by Implicit Enumeration Techniques” Management Science

16(8), P 495- 508, 1970.

8. Goldman, A. J., “Optimal Centre Location in simple Networks” Transportation science 5, P 212-221, 1971. 9. Hall and R.W., “Direct versus Terminal Freight routing on a network with concave costs” International Journal of Network

system 4(5), 287- 298, 2009.

10. Hallpern, J and O.Maimon, “Algorithms for the m-centre problems a survey” European Journal of operation research 10(3), PP 195-203, 2011.

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6.

Authors: Himanshu Sirohia, Koushik Chakraborty, Neha Mathur

Paper Title: Enhancement of Op-Amp Characteristics by improving Common mode Rejection Ratio

Abstract: The present invention relates to the “CMRR of Op-Amp” developed for Characteristics Improvement

of Operational-Amplifier. CMMR is an acronym for Common Mode Rejection Ratio which is a measure of the

capability of an op-amp to reject a signal that is common to both inputs [2,15]. Ideally, CMRR is infinite: if both

inputs fluctuate by the same amount, then it will not affect the output. But practically its value depends on the

circuit used and the value of its components [1, 11]. Practical value of CMRR is 90db, but this invention will

improve its conventional value. In order to improve the performance of an Op-Amp, a method has been

proposed, measurement setup has been improved to characterize CMRR more accurately according to its ideal

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value over wider frequency range. Practically op-amps have high CMRRs, the ubiquitous 741 has approximately

90 dB, and almost 3,000 devices are using this in terms of a ratio [3, 5]. CMRR can be enhanced up to 90 to 100

dB using the proposed method.

Keywords: Op-Amp, CMRR, dB .

References: 1. P. Pandey, J. Silva-Martinez, and A. Liu Xuemei, “CMOS 140-mW fourth-order continuous-time low-pass filter stabilized with a

class AB common-mode feedback operating at 550 MHz”,IEEE Tran. Circ. Syst. I: Reg. Papers 56, 811–820(2006).

2. V. Saari, M. Kaltiokallio, S. Lindfors, J. Ryynanen, and K.A.I. Halonen, “A 240-MHz low-pass filter with variable gain in 65-nm CMOS for a UWB radio receiver”, Tran. Circ. Syst. I: Reg. Papers 56, 1488–1499 (2009).

3. Afzali-Kusha, M. Nagata, N.K. Verghese, and D.J. Allstot, “Substrate noise coupling in SoC design: modeling, Avoidance, and validation”, Proc. IEEE94, 2109–2138 (2006).

4. E. Charbon, R. Gharpurey, P. Miliozzi, R.G. Meyer, and A. Sangiovanni-Vincentelli, “Substrate Noise: Analysis and Optimization for IC Design” , KAP, Boston, 2003.

5. P.E. Allen and D.R. Holberg, “CMOS Analog Circuit Design”, Oxford University Press, Oxford, 2002. 6. G. Giustolisi, G. Palmisano, and G. Palumbo, “CMRR frequency response of CMOS operational transconductance amplifiers”,

IEEE Tran. Instrument. Measurement 49, 137 143(2000).

7. C. Sripaipa and W.H. Holmes, “Achieving wide-band common-mode rejection in differential amplifiers”, Proc. IEEE 58, 600–602 (1970).

8. A. Ciubotaru, “Technique for improving high-frequency CMRR of emitter-coupled differential pairs”, IET Electronics Letters 38, 943–944 (2002).

9. F. You, S.H.K. Embabi, and E. Sanchez-Sinencio, “On the common mode rejection ratio in low voltage operational amplifiers with complementary N-P input pairs”, IEEE Tran. Circ.Syst. II: Analog Digital Signal Proc.44, 678–683 (1997).

10. P.S. Crovetti and F. Friori, “Finite Common-mode rejection in fully differential operational amplifiers”, IET Electronics Letters 42, 615–617 (2006).

11. S. Szczepanski, J. Jakusz, and R. Schaumann, “A linear fully balanced CMOS OTA for VHF filtering applications”, IEEE Tran. Circ. Syst. Part II: Analog Digital Signal Proc. 44, 174– 187 (1997).

12. S. Koziel and S. Szczepanski, “Dynamic range comparison of voltage-mode and current-mode state-space Gm-C biquad filters in reciprocal structures”, IEEE Tran. Circ. Syst. I: Regular Papers50, 1245–1255 (2003).

13. J.F. Fernandez-Bootello, M. Delgado-Restituto, and A. Ro-drıguez-Vazquez, “IC-constrained optimization of continuous-time Gm-C filters”,Int. J. Circ. Theory Applic.40, 127–143(2012)

14. P. Pandey, J. Silva-Martinez, and A. Liu Xuemei, “CMOS 140-mW fourth-order continuous-time low-pass filter stabilized with a class AB common-mode feedback operating at 550 MHz”, IEEE Tran. Circ. Syst. I: Reg. Papers 56, 811–820 (2006).

15. G. Giustolisi, G. Palmisano, and G. Palumbo, “CMRR frequency response of CMOS operational transconductance appliers”, IEEE Tran. Instrument. Measurement 49, 137–143 (2000).

16. C. Sripaipa and W.H. Holmes, “Achieving wide-band common mode rejection in deferential amplifiers”, Proc. IEEE 58, 600– 602 (1970).

17. A. Ciubotaru, “Technique for improving high-frequency CMRR of emitter-coupled differential pairs”, IET Electronics Letters 38, 943–944 (2002).

7.

Authors: Surender Kaur

Paper Title: Biodiversity of River Ganga at Sapt Rishi Ashram, Hardwar, Uttaranchal

Abstract: Ganga is one of the oldest rivers which are recognized as major natural resources not only as sources

of domestic, industrial , agricultural water and hydroelectric power but also for the food production and to have

supported human settlements. The river has been the place of development of human civilization to a great

extent. However, the occupancy over the year and industrialization is now having its ill effects on the river

slowly but surely destroying the river in time and space. Ganga river is facing grave danger. The quality and

biodiversity of Ganga River is getting degraded more severe every day. The concern over deterioration of

quality and its biodiversity has stimulated research into the basic dynamics of river environment and its biotic

communities so that the biodiversity of river could be conserved. Keeping this view in mind a study was

conducted on biodiversity of River Ganga at Saptrishi Ashram during the year 2016-17. This paper reports the

finding of a survey carried out at Saptrishi ashram region of Uttaranchal on the basis of season. The work was

carried out to generate information on the freshwater aquatic system to help to manage the freshwater system

using the ecosystem approach. Hardwar lies between approximately between approximately latitude 29º58'

North and longitude at 78º13’ East. Physico- chemical and biological parameters were observed in the first and

third week of each month at study area. It was recorded that phytoplankton dominated over zooplankton. . It was

recorded that plankton were maximum in winters and minimum in monsoon period, there is a direct interrelation

between physico -chemical parameter sand biological parameters. The fluctuation of planktonic communities

can be affected by the variation of the physico - chemical parameters.

Keywords: aquatic system, Hardwar region, phytoplankton, zooplankton

References: 1. Bhowmick, B.N. and Singh, A.K. (1985); Phytoplankton population in relation to physic-chemical factors of river Ganga at

Patna. Indian Journal of Ecology.12(2): 360-367

2. Joshi, B.D. and Bisht, R.C.S. and Joshi,N. (1996); Planktonic population in relation to certain physic chemical factors of Ganga canal at Jwalapur, Hardwar. Himalayan Journal of Environment and Zoology.10(2): 75-77.

3. Joshi,B.D.,Dishi. and Joshi,K.(2001); Seasonal variation in some physical characteristics of three hill streams, between Byasi and Rishikesh, in Uttranchal Himalaya.Himalayan Journal of Environment and Zoology.15 2): 167-172.

4. Joshi,B.D. and Singh,R.(1999);On some physic- chemical values of River Ganga between Devprayag and Rishikesh. Himalayan Journal of Environment and Zoology.113( 2): 83-92.

5. Khanna, D.R.(1993); In: Ecology and pollution of Ganga river,Ashish publisher,New Delhi. 6. Khanna,D.R.,Badola,S.P. and Rawat, H.S.(1992); In: Limnology of Dhella river,Kashipur. Ashish Publishing House, New

Delhi.95-99

7. Sabata ,B.C. and Nayay,M.P.(1995); In: River Pollution in India,A.P.H. Publisher,New Delhi. 8.

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9. Seth,T.R., Khanna, D.R.,Gautam,A.,Chug, T. and Sarkar,P. (2000); Temporal trends of phytoplanktonic diversity in the river Ganga at Haridwar. Himalayan Journal of Environment and Zoology. 14(2):129-134

10. Sharma,A.P.,Deorari,B.P.and Singh,C.S.(1991);In: Observation on ecology and fisheries of Tarai reservoir of Kumaon,Ashish Publishing House,Punjabi Bagh,New Delhi.

8.

Authors: R. Devakunchari, Rishabh Agarwal, Eshita Agarwal

Paper Title: A Survey of Chatbot Design Techniques

Abstract: Chatbots gives us a fresh way to converse with computers. To get answers to our questions by a computer we either use a search engine, or fill out form, whereas a chatbot allows us to simply ask questions in

the same manner that we would ask a human i.e., a chatbot is a program that mimics human conversation using

Artificial Intelligence (AI). A chatbot is devised to be the ideal virtual assistant, helping one to complete

different tasks such as answering questions, getting driving directions, turning up the thermostat in smart homes,

to playing one’s favourite tunes etc. Chatbots recently have gained a lot of popularity in the field of human-

computer interaction. They are being used extensively in all sorts of applications like customer support, personal

assistant, advising, sales, marketing etc. The technologies at the core of the rise of the chatbot are Machine

Learning (ML) and Natural Language Processing (NLP). However, these chatbots lack one or more

functionalities such as not being able to maintain a persona, unable to give personalized responses depending on

the user or preventing faulty responses to unknown questions. The relevance of this paper is to review the

various existing chatbot design techniques, discuss their strengths and evaluate them based on their uses.

Keywords: Chatbot, AIML, LSA, Patten Matching, ChatScript, Parsing, Language Tricks

References: 1. Liu, B., Xu, Z., Sun, C., Wang, B., Wang, X., Wong, D. F., ... & Wang, B. “Content Oriented User Modeling for Personalized

Response Ranking in Chatbots”, IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), Vol. 26, Issue

1, pp. 122-133, 2018. 2. Setiaji, B., & Wibowo, F. W. “Chatbot using a knowledge in database”. In proceedings of 7th International Conference on

Intelligent Systems, Modelling and Simulation, IEEE, Bangkok, pp. 72-77, 25-27th Jan 2016.

3. Ranoliya, B. R., Raghuwanshi, N., & Singh, S. “Chatbot for university related FAQs”. In proceedings of Advances in Computing, Communications and Informatics (ICACCI), International Conference on (pp. 1525-1530). IEEE, 2017.

4. Ahmad, N. A., Che, M. H., Zainal, A., Rauf, M. F. A., & Adnan, Z. “Review of Chatbots Design Techniques”. In International Journal of Computer Applications, Vol. 181, Issue 8, pp. 7-10, 2018.

5. Bradeško, L., & Mladenić, D. “A survey of chatbot systems through a loebner prize competition”. In proceedings of Slovenian Language Technologies Society Eighth Conference of Language Technologies pp. 34-37, 2012.

6. Weizenbaum, J. “ELIZA—a computer program for the study of natural language communication between man and machine”. Communications of the ACM, Vol. 9, Issue 1, 36-45, 1966.

7. Hutchens, J. L. “How to pass the Turing test by cheating”. School of Electrical, Electronic and Computer Engineering research report. Perth: University of Western Australia, 1997.

8. Winograd, T. “Understanding natural language”. Cognitive psychology, Vol. 3 Issue 1, pp. 1-191, 1972. 9. Seneff, S., Hirschman, L., & Zue, V. W. “Interactive problem solving and dialogue in the ATIS domain”. In Speech and Natural

Language: Proceedings of a Workshop Held at Pacific Grove, California, February 19-22, 1991. 10. Weintraub, J. “History of the PC Therapist”. Online at http://www.loebner.net/Prizef/weintraub-bio.html, 1986. 11. Wallace, R. “The elements of AIML style”. Alice AI Foundation, 2003. 12. Marietto, M. D. G. B., de Aguiar, R. V., Barbosa, G. D. O., Botelho, W. T., Pimentel, E., França, R. D. S., & da Silva, V. L.

“Artificial intelligence markup language: a brief tutorial”. arXiv preprint arXiv:1307.3091, 2013.

13. Abdul-Kader, S. A., & Woods, J. C. “Survey on chatbot design techniques in speech conversation systems”. International Journal of Advanced Computer Science and Applications, Vol. 6, Issue 7, 2015.

14. Colby K. M., “Artificial Paranoia: A computer program for the study of natural language communication between man and machine”, Communications of the ACM, Vol. 9, pp. 36-45, 1975.

15. Comendador, B. E. V., Francisco, B. M. B., Medenilla, J. S., & Mae, S. “Pharmabot: a pediatric generic medicine consultant chatbot”. Journal of Automation and Control Engineering Vol, 3, Issue 2, pp. 137-140, 2015.

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9.

Authors: Ajit Solanki, Mehul P. Barot

Paper Title: Study of Heart Disease Diagnosis by Comparing Various Classification Algorithms

Abstract: In the survey paper, different techniques of mining for forecasting of heart risk are discussed. Heart disease cause millions of death every year, It’s rapidly increasing. Mining methods are too much helpful detect

and diagnose heart risk. Data mining in medical domain has great potential to uncover the pattern which are

hidden in the medical dataset [2]. For this reason, different mining methods can be used to abstract knowledge

for forecasting heart disease [4]. In this paper, survey is carried on various single data mining techniques and

hybrid mining techniques to identify the best suited technique to achieve high accuracy in prediction of heart

disease [5]. Here, Potential of many classification techniques was evaluated, namely Naïve Bayes, SVM,

Decision tree, K-nearest neighbour, and even hybrid approach of classifiers. Analysis on various methods

proved that techniques based on classification obtain high accuracy compared to previous methods [14].

Keywords: Data mining, Classification, Disease Diagnosis, prediction, Accuracy .

References: 1. Sushmita Manikandan, “Heart Attack Prediction System” International conferenceon Energy, communication, Data Analytics and

Soft Computing. (ICECDS-2017)

2. Sarath Babu, Vivek EM, Famina KP, Fida K, Aswathi P, Shanid M, Hena M, “Heart Disease Diagnosis Using Data Mining Technique”, International Conference on Electronics, Communication and Aerospace Technology ICECA 2017

3. Ankita Dewan, Meghna Sharma, “Prediction of Heart Disease Using a Hybrid Technique in Data Mining Classification”, 978-9-3805-441 6-8/15/$31.00 c 2015 IEEE

4. Monika Gandhi, Dr Shailendra Narayan sinh, “Predictions in Heart Disease Using Techniques of Data Mining”, 2015 1st

40-42

International Conference on Futuristic trend in Computational Analysis and Knowledge Management (ABLAZE-2015) 5. Gnaneswar B., Ebenezar Zebarani M.R., “A review on prediction and diagnosis of heart failure”, 2017 (ICIIECS) 6. M.A.Jabbar, Shirina samreen, “Heart Disease prediction System based on Hidden Naïve Bayes Classifier” 7. B. Jin*, Senior Member, IEEE , C. Che*, Z. Liu, Shulong Zhang, Xiaomeng Yin and X.P. Wei, “Predicting the risk of Heart

Failure with HER sequential data modelling”, DOI 10.1109/ACCESS.2017.2789324, IEEE Access

8. Kanika Pahwa, Ravinder Kumar. ”Prediction of Heart Disease using Hybrid Technique for selecting Features” 2017 4th IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (UPCON) GLA University, Mathura, Oct 26-28, 2017

9. Purushottam, Prof. (Dr.) Kanak Saxena,Richa Sharma, “Efficient Heart Disease Prediction system using Decision Tree” International Conference on Computing, Communication and Automation (ICCCA2015)

10. Rashmi G Saboji, Prem Kumar Ramesh, “ A Scalable Solution for Heart Disease Prediction using Classification Mining Techniques” International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS-2017)

11. Meenal Saini, Niyati Baliyan, Vineeta Bassi,,”Prediction of Heart Disease Severity with Hybrid Data Mining.” 2017 2nd International Conference on Telecommunication and Networks (TEL-NET 2017)

12. Jayshril S. Sonawane, D.R. Patil, “Prediction of Heart Disease using Multilayer Layer Perceptron Neural Network”, ICICES2014 - S.A.Engineering College, Chennai, Tamil Nadu, India

13. Theresa Princy R., J. Thomas, “Human Heart Disease Prediction System Using Data Mining Techniques”, 2016 International Conference on Circuit, Power and Computing Technologies [ICCPCT]

14. C. Sowmiya, Dr. P.Sumitra, “Analytical Study of Heart Disease Diagnosis using Classification Techniques”, 2017 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT TECHNIQUES IN CONTROL,OPTIMIZATION AND SIGNAL

PROCESSING

10.

Authors: Renu, Sanjeev Sharma

Paper Title: An Energy efficient integrated Framework for secure Routing and key management in Mobile Ad-

hoc Networks

Abstract: (MANETs) are being very trendy these days and used in a number of applications where security is challange like military operations or other sensitive projects, whereby if the network is compromised then the

outcomes can be terrible. It would not be easy task to apply energy efficient and reliable routing in MANETs,

because it will not be possible to recharge / replace a battery of mobile node. To take full benefit of the lifetime

of nodes, traffic should be routed in a way that energy usage also should be minimized. A lot of security

proposal have came which address different protocol stack but no scheme is fully integrated with respect of

energy and security. The proposed integrated approach based on Identity cryptography which belongs to the

class of pair wise cryptography, addresses all the concerns like secure routing and key management as well as

energy.It is a general method for providing routing security and can be applied to any routing protocols.

Keywords: Cryptography, MANET, communication, routing

References: 1. L Junhai, X Liu, Y Danxia, Research on Mul-ticast Routing Protocols for Mobile Ad-Hoc Net-worksComputer Networks –

Elsevier, 2008.

2. Kapil, A, etc "Identity-Based Key Manage-ment in MANETs using Public Key Cryptog-raphy."International Journal of Security (IJS) 3.1(2009): 1-26

3. V. N. Talooki, H. Marques, and J. Rodriguez, \Energy efficient dynamic manet on-demand routing protocol," Symposium and Workshops on a World of Wireless, Mobile and Multimedia Net-works 2013.

4. M. Maleki, K. Dantu and M. Pedram, Power-Aware On-Demand Routing Protocols for Mobile AdHoc Networks, International Symposium on Low Power Electronics and Design,pp. 72-75, 2002.

5. Q. Li, J. Aslam, D. Rus, Online Power Aware Routing, Proceedings of International Conference on Mobile Computing and Networking (Mo-biCom’2001), 2001.

6. I. Stojmenovic and X. Lin, Power Aware Lo-calized Routing in Wireless Networks, IEEE Transactions on Parallel and Distributed Systems, vol. 12, no. 11, pp. 1122-1133, November 2001.

7. R. A. Shaikh, S. Lee, M. A. U. Khan, and Y. J. Song, “LSec:lightweight security protocol for distributed wireless sensor net-work”, Lecture Notes in Computer Science, vol. 4217, 2006.

8. A. Shamir, “Identity-Based Cryptosystems and Signature Schemes,” in Advances in Cryptology, Berlin, Germany: Springer Berlin Heidelberg, 1985, pp. 47–53.

9. A. Shamir, “How to Share a Secret,” Commun. ACM, vol. 22, no.11, Nov. 1979, pp. 612–613 10. B. Lee et al., “Secure Key Issuing in ID-Based Cryptography,” inProc. Workshop Aus-tralasian Inf. Security, Data Mining

WebIntell., Softw. Int., vol. 32, Australia: Australian Com-puter SocietyInc., 2004, 11. B. A. Mahmood and D. Manivannan, \Position based and hybrid routing protocols for mobile ad hoc networks: a survey,"

Wireless Per-sonal Communications,vol. 832015.

12. Renu M.,Dr. Sanjeev S.,Inderpreet K.“Secret Sharing for Key Management Scheme in Ad-hoc Networks” Proc. IEEE International Conference on advanced computing & communication tech-nologies

13. Y. Ren et al., “Identity-Based Key Issuing Protocol for Ad Hoc Networks,” IEEE Int. Conf. Comput. Intell. Security, Harbin,China, Dec. 15–19, 2007, pp. 917–921.

14. Renu Mishra, Inderpreet Kaur & Sanjeev Sharma” New Trust based security method for mobile ad-hoc networks” International Journal of Computer Science and Security (IJCSS), Volume (4), Issue: (3) 346 -3512 June -July010

15. H. Deng and D.P. Agrawal, “TIDS: Thresh-old and Identity-Based Security Scheme for Wireless Ad Hoc Networks,” Ad Hoc Netw.,vol. 2, no. 3, July 2004, pp. 291–307.

16. Sandeep Saxena, Goutam Sanyal and Shashank Srivastava”Mutual Authentication Pro-tocol Using IdentityBased Shared Secret Key in Cloud Environments”IEEE International Confer-ence (ICRAIE-2014),

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11.

Authors: Medhavi Malik, Bersha Kumari, Madhuri Sharma

Paper Title: Steps: To Make NLP More Enhance by New Techniques

Abstract: Natural language processing (NLP) is the investigation of scientific and computational displaying of different parts of language and the advancement of a wide scope of frameworks. Each millisecond our life is

recorded, each laughter, each tear all that we have seen, heard and felt is held inside this enormous database

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inside our mind. But then also sometimes we are not able to remember where we have lost our things which

must be so, important. So NLP (neuro linguistics programming) tools is practicing on worldwide directly and

indirectly professionally because this is the science in which we identify or analyses our thoughts with the help

of 5 senses to interact or find the appropriate result. In this paper all the issues o NLP its processing how does it

works and some of the solutions of the current issues is given.

Keywords: Natural language processing, neural network

References: 1. L. R. Bahl, P. F. Brown, P. V. de Souza, and R. L. Mercer, “A tree based statistical language model for natural language speech

recognition,” in Acoustics, Speech and Signal Processing, IEEE Transactions on, vol. 37, Issue 7, (Yorktown Heights, NY,USA), pp. 1001–1008, July 1989.`rt

2. P . Clarkson and R. Rosenfeld, “Statistical language modeling using the cmu-cambridge toolkit,” in Proceedings EUROSPEECH (N. F.G. Kokkinakis and E. Dermatas, eds.), vol. 1, (Rhodes, Greece), pp. 2707–2710, September 1997.

3. J. Tejedor, R. Garca, M. Fernndez, F. J. LpezColino, F. Perdrix, J. A. Macas, R. M. Gil, M. Oliva, D. Moya, J. Cols, , and P. Castells, “Ontology-based retrieval of human speech,” in Database and Expert Systems Applications, 2007. DEXA ’07. 18th

International Conference on, (Regensburg, Germany), pp. 485– 489, September 2007. 4. J. R. Bellegarda, “Statistical language model adaptation: Review and perspectives,” vol. 42, no. 1, pp. 93–108, 2004. 5. Y.-Y. Wang, M. Mahajan, and X. Huang, “A unified context-free grammar and n-gram model for spoken language processing,”

in IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. III, (Istanbul, Turkey), pp. 1639–1642, Institute of Electrical and Electronics Engineers, Inc., 2000

6. L. Zhou and D. Zhang, “NLPIR: a theoretical framework for applying natural language processing to information retrieval,” J. Am. Soc. Inf. Sci. Technol., vol. 54, no. 2, pp. 115–123, 2003

7. L. Zhou and D. Zhang, “NLPIR: a theoretical framework for applying natural language processing to information retrieval,” J. Am. Soc. Inf. Sci. Technol., vol. 54, no. 2, pp. 115–123, 2003.

8. Guerra, A. “T. Rowe Price to hone in on voice systems,” Wall Street and Technology, Vol. 19, No. 3, 2000. 9. Y.-Y. Wang, M. Mahajan, and X. Huang, “A unified context-free grammar and n-gram model for spoken language processing,”

in IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. III, (Istanbul, Turkey), pp. 1639–1642,

Institute of Electrical and Electronics Engineers, Inc., 2000 10. L. Zhou and D. Zhang, “NLPIR: a theoretical framework for applying natural language processing to information retrieval,” J.

Am. Soc. Inf. Sci. Technol., vol. 54, no. 2, pp. 115–123, 2003

11. L. Zhou and D. Zhang, “NLPIR: a theoretical framework for applying natural language processing to information retrieval,” J. Am. Soc. Inf. Sci. Technol., vol. 54, no. 2, pp. 115–123, 2003.

12. Wohleb, R. “Natural Language Processing: Understanding Its Future,” PC/AI, November/December, 2001. 13. Guerra, A. “T. Rowe Price to hone in on voice systems,” Wall Street and Technology, Vol. 19, No. 3, 2000.

12.

Authors: R.Manjula Sri, J.Jyothirmai, D.Swetha

Paper Title: Analysis of Retinal Blood Vessel Segmentation in different types of Diabetic Retinopathy

Abstract: The extraction of retinal blood vessels from a fundus image is one of the solutions to detect number

of diseases such as diabetes, hypertension and arteriosclerosis. Dimensions of the vessels is significant for

detection of retinal diseases. Blood vessel thickness(diameter) in Different types (stages) of Diabetic

Retinopathy (DR) are analyzed in this work. In Normal and Proliferative DR thick vessels are affected and in

Hypertensive and Non-Proliferative DR the thin vessels are affected. The objective of this paper is to employ

image processing techniques to enhance and measure the dimensions of the retinal blood vessels. Segmentation

is implemented through three techniques namely Gaussian method, mathematical morphology method and

multi-scale analysis method. Gaussian method uses a Gaussian resolution hierarchy to detect thin as well as

thick vessels. It is a faster technique but presents noise, hence suitable only for detecting thick vessels.

Mathematical morphology method is suitable to detect the fine details of thin vessels more precisely. The third

technique detects the thick and thin vessels without noise and is preferable for its invariant analysis with

transformation of images. To employ image processing techniques and measure the vessel diameter LabVIEW

software is used. A comparative study on these three techniques has been carried out on different retinal images

with vessel related eye diseases. The work was carried out under the guidance of senior eye care doctors.

Keywords: Gaussian method, Mathematical morphology, Multi-scale Representation, Vessel enhancement.

References: 1. Sonam Dilip Solkar , Lekha Das - Survey on Retinal Blood Vessels Segmentation Techniques for Detection of Diabetic

Retinopathy- International Journal of Electronics, Electrical and Computational System IJEECS, ISSN 2348-117X Volume 6, Issue 6 June 2017

2. D.Siva Sundhara Raja and S. Vasuki-Automatic Detection of Blood Vessels in Retinal Images for Diabetic Retinopathy Diagnosis- Computational and Mathematical Methods in Medicine- Volume 2015

3. Marc Saeza,, Sonia González-Vázquec, Manuel González-Penedoc, Maria Antònia Barcelo, Marta Pena-Seijo, Gabriel Coll de Tuero, Antonio Pose-Reinod : Development of an automated system to classify retinal vessels into arteries and veins. Computer

methods and programs in biomedicine.2012 4. K.M.M.Rao, Dr. G.Chandra Shekar, Dr. Lalith Dandona, S. Rajendra Kumar, R.N.Anjani, :Plannimetric Analysis of Optic Disc

and Cup, Reradings in Remote Sensing,NRSC,ISRO,2001 p 54-58.

5. M.M. Fraz, P. Remagnino, A. Hoppe, B. Uyyanonvara, A.R. Rudnicka, C.G. Owen, S.A. Barmana:Blood vessel segmentation methodologies in retinal images – A survey - Computer methods and programs in biomedicine.2012

6. D.J.J.Farnel , F.N.Hatfield , P.Knox , M.Reakes , S.Spencer , D.Parry , S.P.Harding.: Enhancement of blood vessels in digital fundus photographs via the application of multiscale line operators volume 345,Issue-715 ,2008

7. Peng Feng, Yingjun Pan , Biao Wei, Wei Jin , Deling Mi: Enhancing retinal image by the Contourlet transform- Pattern Recognition Letters 28 (2007) 516–522

8. Qin Li, Jane You, David Zhang:Vessel segmentation and width estimation in retinal images using multiscale production of matched filter responses-Expert Systems with Applications (2012) 7600–7610

9. Praveen Kumar Reddy Yelampalli, Jagadish Nayak, and Vilas H Gaidhane-Blood Vessel Segmentation and Classification of Diabetic Retinopathy Images using Gradient Operator and Statistical Analysis- Proceedings of the World Congress on Engineering and Computer Science 2017 Vol II WCECS 2017, October 25-27, 2017, San Francisco, USA

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10. M. E. Martinez-Perez, A. D. Hughes, S. A. Thom, A. A. Bharath and K. H. Parker: Segmentation of Blood Vessels from Red-free and Fluorescein Retinal Images. Medical Image Analysis. 11 (1): 47-61, 2007.

11. QIN LI, JANE YOU , AND LEI ZHANG , PRABIR BHATTACHARYA: AUTOMATED RETINAL VESSEL SEGMENTATION USING MULTISCALE ANALYSIS AND ADAPTIVE THRESHOLDING - IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, 2006.

13.

Authors: K. RAJASEKHAR, B. JAYACHANDRAIAH, S.NISHANTHI

Paper Title: Experimental Evaluation of Injection Pressure and Injection Timing on Diesel Engine

Abstract: An attempt is made in this paper to conduct experiments to study the effect of different injection pressure with different injection timing of a Diesel Engine and evaluate performance and emission

characteristics.

The experiments are conducted at different Load conditions of 0%,,25% ,50%,& 75% and Full Load by varying

injection pressures of 200 and 220 Bar with different injection timings at19°, 23° and 27° bTDC. Output results

shows that engine operating at 220 bar pressure gives nearly 1% more brake thermal efficiency than lower

pressure irrespective of the injection timing whereas brake specific fuel consumption is found to have significant

changes at the initial conditions. It is also shows that the CO emissions decrease with increase in injection

pressure and advancement in injection timings at 220 bar and 27º bTDC but also those conditions yield the

lowest CO emission because of the NOx emissions increase with increase in injection pressure.

Keywords: Single cylinder, Brake Power, Performance Characteristics

References: 1. P. Bridjesh, G. Arun Kumar, 2015. Study on the effects of variation of fuel injection pressure on single cylinder diesel engine,

ARPN 1819-6608.

2. K.S. Rostami, B.Ghobadian and M.Kiani Deh Kiani, 2014. Effect of the injection timing on the performance of a diesel engine using diesel-biodiesel blends, IJAME 2180-1606.

3. Hani chotai, 2014. Review on effect of varying injection pressure and injection timing on performance and emissions of diesel engine operating on diesel/biodiesel, IJRSI 2321-2705.

4. M.L.S Deva Kumar, S. Drakshayani, K.Vijaya Kumar Reddy, 2012. Effect of fuel injection pressure on performance of single cylinder diesel engine at different intake manifold inclinations, IJEIT 2277-3754.

5. G.Rajendra Prasad, 2014. Experimental investigation for optimum fuel injection pressure on diesel engine, IJARSET, 2350- 0328.

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14.

Authors: Gunduru Swathi Lakshmi, Neelima K, C. Subhas

Paper Title: Error Detection and Correction Methods for Memories used in System-on-Chip Designs

Abstract: Memory is the basic necessity in any SoC design. Memories are classified into single port memory and multiport memory. Multiport memory has ability to source more efficient execution of operation

and high speed performance when compared to single port. Testing of semiconductor memories is increasing

because of high density of current in the chips. Due to increase in embedded on chip memory and memory

density, the number of faults grow exponentially. Error detection works on concept of redundancy where extra

bits are added for original data to detect the error bits. Error correction is done in two forms: one is receiver itself

corrects the data and other is receiver sends the error bits to sender through feedback. Error detection and

correction can be done in two ways. One is Single bit and other is multiple bit. Single bit error detection and

correction is categorized into two as Classical Algorithm and March Algorithm. Multiple bits error detection and

correction is categorized into Adjacent codes and Random codes. Different methods are applicable for different

types of faults that manifest as errors.

Keywords: Faults and its types, Error Detection and Correction, Single error detection and correction, Multiple Error detection and correction.

References: 1. Balwinderr Singh Lakha, Sukhleen Bindra Narang and Arun Khosla, “Modeling and Simulation of Efficient March Algorithm for

Memory Testing”, Contemporary Computing - Third International Conference, pp.96-107, August 2010.

2. Joseph, P Elsa and P Rony Antomy, “VLSI Design and Comparative Analysis of Memory BIST controllers”, First International Conference on computational Systems and Communications (ICCSC), pp.272-276, December 2014.

3. Manoj S, C Babu, “Improved Error Detection and Correction for Memory Reliability against Multiple Cell Upsets using DMC &PMC”, IEEE, 2016.

4. Kavya B S, “Survey on Error Correction and Detection Schemes for Memory Applications”, International Journal of Scientific & Engineering Research, Vol. 6, February 2015.

5. J Manikandan and DR. M.Manikandan, “Design of Single Error Correction – Double Adjacent Error Detection – Triple Adjacent Error Detection – Tetra Adjacent Error Detection (SEC – DAED –TAED – Tetra AED) Codes”, International Journal of Applied

EngineeringReasearch, Vol. 11, pp. 4440-4444, November 2016. 6. Harutunyan G.,Vardanian V. A., Zorian Y., “Minimal March Tests for Unliked Static Faults in Random Access Memories”, in

proceeding of VLSI Test Symposium, pp. 53-59, 2005.

7. Er. Manoj Arora, Er. Shipra Tripathi, “Comparative Simulaton of MBIST using March Test Algorithms”, International Journal of

Scientific & Engineering Research, Vol. 2, December2011.

8. R. Naseer and J. Draper, “Dec ECC Design to Improve Memory Reliability in sub-100nm Technologies”, IEEE, ICECS, pp. 586-589.

9. Pedro Revirigeo, Salvatore Pontarelli, Adrian Evans, and Juan Antonio Maestro, “A Class of SEC – DEC - DAEC Codes Derived From orthogonal Latin Square Codes”, IEEE Transactionon Very Large Scale Integration (VLSI) Systems, 2014.

10. Shanshan Liu, Pedro Reviriego, Liyi Xiao and Juan Antonio Maestro, “Reducing the Cost of Triple Adjacent Error Correction in Double Error Correction Orthogonal Latin Square Codes”, IEEE Transactions on Device and Materials Reliablity, Volume :16,

June 2016. 11. Hamming R. W. M., “ Error Detecting and Error Correcting Codes”, Bell System Tech.Jour., 29 (1950), pp. 147-160.

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12. Hamming SEC - DAED and Extended Hamming SEC – DEC - TAED codes through Selective Shortening and Bit Placement”, IEEE Transactions on Device and Materials Reliability, Volume 14, pp.574-576, March 2014.

13. J. Chen, P. Owsley, “A Brust Error Correcting Algorithm for Reed Solomon codes”, IEEE Transaction, vol. 64, pp. 1497-1500, May 2015.

14. Mohammed Hasan Alwan, Mandeep Singh, Hussain Falih Mahdi, “Performace Comparsion of Turbo Codes with LDPC Codes and with BCH Codes for Forward Error Correcting Codes”, IEEE Student Conference on Research and Development (SCOReD),

December 2015. 15. E. Mytsko, A. Malchukov, I. Novogilov and V. Kim, “Fast decoder of BCH code with cyclic decoding method”, International

Siberian Conference Control and Communication (SIBCON), IEEE Conferences, 2016.

15.

Authors: Sama Sanghamitra, Sandip S. Deshmukh

Paper Title: Prominence of Bio-Fuels as an Alternate Fuel in CI Engines

Abstract: CI engine have always been the primary choice for on-road, agriculture and industrial applications.

On-road operations are dominated by CI engines because of their better efficiency, fuel availability and fuel

economy. Worldwide, nearly 14% of greenhouse gas emissions are releasing from the world’s highest energy

demanding sector, transportation. The day-by-day increase in diesel engine’s use associated with the aspiration

of underdeveloped or developing countries to improve their economic status has led to increase the demand for

diesel fuel supply, which is causing running out of fossil fuel very shortly. The increasing fuel usage will

increase the level of air pollutants in the atmosphere, which are threatening the environment and human health.

Fossil fuel depletion and harmful exhaust gas emissions has created an intensive interest for the development of

renewable alternative fuel. Since last three decades, researchers are showing interest to develop an alternative

fuel from biomass-based feed stock. Fuels developed from biomass-based feed stock are referred as biofuels.

These biofuels can be categorized into bio-alcohols and biodiesel, which are more suitable to use as an alternate

fuel for SI and CI engines because of their high octane and cetane numbers respectively. This paper presents the

exhaustive review of literature on testing of different renewable alternative biofuels under different testing

conditions in CI engine to replace petroleum diesel and to have effective control over the harmful exhaust

emissions. This paper also gives insight of recent trends in development of fourth generation biofuels based on

photobiological solar fuels and electro fuels, which can be a more promising alternate fuel in the field of

biofuels.

Keywords: CI Engine, Biofuel, Engine Performance, Engine Emissions.

References: 1. E. S. Shuba and D. Kifle, “Microalgae to biofuels: ‘Promising’ alternative and renewable energy, review,” Renew. Sustain.

Energy Rev., vol. 81, no. August 2017, pp. 743–755, 2018. 2. K. Schindler and V. Ag, “Why Do We Need the Diesel ?,” Technology, no. 412, 1997. 3. H. Yerrennagoudaru, K. Manjunatha, K. R. Vijaya Kumar, and M. Dodda Basavanagouda, “‘investigation and assessment of

performance and emissions of an IC engine fuelled with diesel and different bio-fuels blended with Ethanol,’” Mater. Today Proc., vol. 5, no. 2, pp. 6238–6246, 2018.

4. M. Mofijur, M. G. Rasul, J. Hyde, and M. M. K. Bhuyia, “Role of Biofuels on IC Engines Emission Reduction,” Energy Procedia, vol. 75, pp. 886–892, 2015.

5. S. Shinde, D. D. Palande, and H. P. Engg, “Performance and Emission Analysis of Diesel-Ethanol-Biodiesel Blend on CI Engine-A Review,” pp. 3085–3088, 2016.

6. F. Saladini, N. Patrizi, F. M. Pulselli, N. Marchettini, and S. Bastianoni, “Guidelines for emergy evaluation of first, second and third generation biofuels,” Renew. Sustain. Energy Rev., vol. 66, no. September 2015, pp. 221–227, 2016.

7. W. Hamilton, “Report on Lieut. Stelwagon’s coast survey sounding apparatus,” J. Franklin Inst., vol. 45, no. 5, p. 392, 1848. 8. L. C. Meher, C. P. Churamani, M. Arif, Z. Ahmed, and S. N. Naik, “Jatropha curcas as a renewable source for bio-fuels - A

review,” Renew. Sustain. Energy Rev., vol. 26, pp. 397–407, 2013.

9. R. O. Idem, S. P. R. Katikaneni, and N. N. Bakhshi, “Catalytic conversion of canola oil to fuels and chemicals: Roles of catalyst acidity, basicity and shape selectivity on product distribution,” Fuel Process. Technol., vol. 51, no. 1–2, pp. 101–125, 1997.

10. C. Alberola, E. Lichtfouse, M. Navarrete, P. Debaeke, and V. Souchère, Agronomy for sustainable development, vol. 3, no. 3. 2008.

11. M. Siaut et al., “Oil accumulation in the model green alga Chlamydomonas reinhardtii: Characterization, variability between common laboratory strains and relationship with starch reserves,” BMC Biotechnol., vol. 11, 2011.

12. F. M. Hossain, T. J. Rainey, Z. Ristovski, and R. J. Brown, “Performance and exhaust emissions of diesel engines using microalgae FAME and the prospects for microalgae HTL biocrude,” Renew. Sustain. Energy Rev., vol. 82, no. March 2018, pp.

4269–4278, 2018.

13. F. Delrue et al., “An economic, sustainability, and energetic model of biodiesel production from microalgae,” Bioresour. Technol., vol. 111, pp. 191–200, 2012.

14. E. M. Trentacoste et al., “Metabolic engineering of lipid catabolism increases microalgal lipid accumulation without compromising growth,” Proc. Natl. Acad. Sci., vol. 110, no. 49, pp. 19748–19753, 2013.

15. E. M. Aro, “From first generation biofuels to advanced solar biofuels,” Ambio, vol. 45, no. 1, pp. 24–31, 2016. 16. W. J. Pitz and C. J. Mueller, “Recent progress in the development of diesel surrogate fuels,” Prog. Energy Combust. Sci., vol. 37,

no. 3, pp. 330–350, 2011. 17. A. M. Liaquat et al., “Effect of coconut biodiesel blended fuels on engine performance and emission characteristics,” Procedia

Eng., vol. 56, pp. 583–590, 2013.

18. B. Q. He, S. J. Shuai, J. X. Wang, and H. He, “The effect of ethanol blended diesel fuels on emissions from a diesel engine,” Atmos. Environ., vol. 37, no. 35, pp. 4965–4971, 2003.

19. D. T. Guide, “The Case for the Diesel Engine What Is the Diesel Engine ?,” pp. 1–21, 2007. 20. S. Thapa, N. Indrawan, and P. R. Bhoi, “An overview on fuel properties and prospects of Jatropha biodiesel as fuel for engines,”

Environ. Technol. Innov., vol. 9, pp. 210–219, 2018.

21. S. Karthikeyan, K. Kalaimurugan, and A. Prathima, “Investigation on the emission quality characteristics of a diesel engine fueled with algae biofuel with nano additives,” Energy Sources, Part A Recover. Util. Environ. Eff., vol. 39, no. 21, pp. 2046–2052, 2017.

22. E. Sadeghinezhad et al., “A comprehensive literature review of bio-fuel performance in internal combustion engine and relevant costs involvement,” Renew. Sustain. Energy Rev., vol. 30, pp. 29–44, 2014.

23. Sangeeta et al., “Alternative fuels: An overview of current trends and scope for future,” Renew. Sustain. Energy Rev., vol. 32, pp. 697–712, 2014.

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24. X. Shan, Y. Qian, L. Zhu, and X. Lu, “Effects of EGR rate and hydrogen / carbon monoxide ratio on combustion and emission characteristics of biogas / diesel dual fuel combustion engine,” Fuel, 2016.

25. E. Rajasekar, A. Murugesan, R. Subramanian, and N. Nedunchezhian, “Review of NO x reduction technologies in CI engines fuelled with oxygenated biomass fuels,” Renew. Sustain. Energy Rev., vol. 14, no. 7, pp. 2113–2121, 2010.

26. B. V. V. S. U. Prasad, C. S. Sharma, T. N. C. Anand, and R. V Ravikrishna, “High swirl-inducing piston bowls in small diesel engines for emission reduction,” Appl. Energy, vol. 88, no. 7, pp. 2355–2367, 2011.

27. B. Karmakar and G. Halder, “Progress and future of biodiesel synthesis : Advancements in oil extraction and conversion technologies,” vol. 182, no. December 2018, pp. 307–339, 2019.

28. C. Bae and J. Kim, “Alternative fuels for internal combustion engines,” Proc. Combust. Inst., vol. 36, no. 3, pp. 3389–3413, 2017.

16.

Authors: CH. Bala Rama Krishna, P. Jagadeesh

Paper Title: Durability studies on SCC Replacing Sand Partially with HIPS Granules

Abstract: This investigation is carried out on Self-Compacting Concrete (SCC) replacing sand partially with plastic waste granules of High impact polystyrene (HIPS). Fly ash content of 30% is replaced for cement in the

binder content of 497 kg/m3 and HIPS granules with varying percentages from 0-40% are replaced for sand in

SCC. Water-to-cementitious content ratio of 0.36 is used in all SCC mixtures. Durability analysis on SCC

specimens is conducted by water absorption and sorptivity tests at 28 and 90 days curing age. Fly ash fills the

pores at interfacial transition zone and sufficient compaction reduced. So, low volume HIPS replacement up to

30% in SCC has lower porosity. Values are linearly declined up to 30% in the both tests at all curing ages. The

smooth surface and spherical shape of HIPS granules leads to weak bonding at cement paste and aggregate

interface. Thus porosity increases at high volume replacement starting from 40% due to the less packing density

in the concrete matrix. Both water absorption and sorptivity values are higher at 40% replacement compared to

SCC mixes contained 0-30% HIPS. E-waste HIPS can be incorporated in concrete to solve issues related to

environmental pollution and SCC designed with HIPS up to 30% is more durable.

Keywords: Durable, electronic plastic waste, Self-Compacting Concrete, Sorptivity, Water absorption.

References: 1. ASTM C642-13, Standard Test Method for Density, Absorption, and Voids in Hardened Concrete, ASTM International, West

Conshohocken, PA, 2013, www.astm.org

2. ASTM C1585-13, Standard Test Method for Measurement of Rate of Absorption of Water by Hydraulic—Cement Concretes, ASTM International, West Conshohocken,