iosr-JCE   Volume-26 ~ Issue-4 ~ Jul. - Aug. 2024

Abstract: Neural Machine Translation (NMT) is a state of the art of machine translations that uses neural network models to translate text from one language to another. Unlike traditional machine translation methods, which rely on statistical models and rule-based systems, NMT leverages the power of deep learning, specifically using techniques such as recurrent neural networks (RNNs), long short-term memory networks (LSTMs), or more recently, transformers. Neural Machine Translation represents a significant dive forward in the field of automatic translation, leveraging the latest advancements in deep learning to deliver more accurate and natural translations. The progress.....

Keywords- Machine translation, Neural network, Architectures of neural network, Data set, BLEU score

[1] Jordi Armengol‐Estapé, Marta R. Costa‐Jussà (2021), Semantic And Syntactic Information For Neural Machine Translation - Injecting Features To The Transformer. Https://Doi.Org/10.1007/S10590-021-09264-2
[2] Zhixing Tan, Shuo Wang, Et Al. (2020). Neural Machine Translation: A Review Of Methods, Resources, And Tools. Www.Keaipublishing.Com/En/Journals/Ai-Open
[3] Philipp Koehn (2017). Neural Machine Translation. Arxiv:1709.07809v1
[4] Brown, T. B., Mann, B., Ryder, N., Et Al. (2020). Language Models Are Few-Shot Learners. *Arxiv Preprint Arxiv:2005.14165*.
[5] Vaswani, A., Shazeer, N., Parmar, N., Et Al. (2017). Attention Is All You Need. *Advances In Neural Information Processing Systems*, 5998-6008

Abstract: Beyond spy movies, lip-reading technology whispers the promise of a quieter world. From assisting the hearing-impaired to navigating noisy environments and silent settings, it unlocks communication avenues like lip into text translation and biometrics. But challenges murmur concerns: limited data, visual ambiguity, and complex models. Researchers, however, shout back with diverse approaches, from feature-based analysis to powerful deep learning. Datasets like MIRACL.....

Key Word: Speech recognition, Lip movement, CNN, LSTM, Feature Extraction.

[1]. H. Laux, A. Hallawa, J. C. S. Assis, A. Schmeink, L. Martin And A. Peine, "Two-Stage Visual Speech Recognition For Intensive Care Patients", Scientific Reports, 13(1), 928, January 2023. Available: Https://Www.Nature.Com/Articles/S41598-022-26155-5.
[2]. A. Garg, J. Noyola And S. Bagadia, "Lip Reading Using Cnn And Lstm", Technical Report, Stanford University, Cs231 N Project Report, 2016. Available: Http://Vision.Stanford.Edu/Teaching/Cs231n/Reports/2016/Pdfs/217_Report.Pdf.
[3]. J. U. Swami And J. S. R., "Lip Reading Recognition", Jetir, Volume 8, Issue 5, May 2021. Available:
Https://Www.Jetir.Org/Papers/Jetir2105723.Pdf.
[4]. A. S. Nambeesan, C. Payyappilly, E. J. C., J. John P, S. Alex, "Lip Reading Using Facial Feature Extraction And Deep Learning", International Journal Of Innovative Science And Research Technology, Volume 6, Issue 7, July – 2021. Available:
Https://Ijisrt.Com/Assets/Upload/Files/Ijisrt21jul035.Pdf.
[5]. G. Schwiebert, C. Weber, L. Qu, H. Siqueira And S. Wermter, "A Multimodal German Dataset For Automatic Lip Reading Systems And Transfer Learning", Arxiv Preprint Arxiv:2202.13403, May 2022. Available: Https://Arxiv.Org/Abs/2202.13403

Abstract: This paper investigates the performance of different distributed query optimization algorithms and presents the outcome of this study to suggest efficient query processing techniques for performance improvement in distributed query processing. In query processing, each query is converted to a series of data manipulation operations. We have analyzed a query in different strategies and showed that efficient technique can be chosen to reduce communication.......

Keyword: Distributed Database, Distributed Query Optimization, Communication Costs, Data Manipulation Operations, Dynamic Programming, Response Time, Query Execution Plan, Optimization Algorithms, Query Processing Strategies.

[1] S. Padia, S. Khulge, A. Gupta, P. Khadilikar. Query Optimization Strategies In Distributed Databases. International Journal Of Computer Science And Information Technologies. Vol 6(5), 2015.
[2] B. Johnsirani And M. Natarajan. An Overview Of Distributed Database Management System. International Journal Of Trend In Research And Development. Vol 2(5), Sep-Oct 2015.
[3] D. Sukheja And U. K. Singh. Novel Distributed Query Optimization Model And Hybrid Query Optimization Algorithm. International Journal Of Computer Applications, Vol. 75(17), 2013.
[4] M. Tamer Ozsu And Patrick Valduriez, Principles Of Distributed Database Systems, Prentice Hall, 3rd Edition, 2011.
[5] William T. Bealor. Semi-Join Strategies For Total Cost Minimization In Distributed Query Processing. M.Sc. Thesis, University Of Windsor, 1995.

Abstract: The integration of Python into civil engineering processes has revolutionized structural engineering by enhancing analytical capabilities, automating repetitive tasks, and improving design efficiency. Python, a high-level programming language known for its simplicity and versatility, has emerged as a powerful tool in civil engineering. This paper explores the diverse applications of Python in the field of civil engineering, highlighting its role in design automation, structural analysis, data management, and project management. Through practical examples and case studies, this paper demonstrates how Python enhances efficiency, accuracy, and innovation in civil engineering practices

Keyword: Python, Design automation, Structural analysis, Data management, Project management and Python in Civil Engineering.

[1] Is1893:2002(Part I) Criteria For Earthquake Resistant Design Of Structures, Bureau Of Indian Standard, New Delhi. Is: 875(Part-I, Ii, Iii)-1987, Code Of Practice For Design Loads (Other Than Earthquake) For Buildings And Structures, Bureau Of Indian Standards, New Delhi.
[2] Model On Equilibrium Of Connected Bodies: Inventors N.K. Dhapekar, Publication Date 2012/1, Patent Office In, Patent Number 363, Application Number 81/Mum/2012.
[3] Data Structures And Algorithms Using Python By Rance D Necaise.
[4] Shashank Bisen, Adoption Of Programming Codes In The Design Of Earth Retaining Wall In Different Backfill Conditions, The International Journal Of Engineering And Science (Ijes),Issn (E): 2319 – 1813.
[6] Mcgrath M. (2018), Python In Easy Steps, 2013 Edition, Ninth Reprint, Mcgraw Hill Education Pvt. Ltd, Chennai..

Abstract: The implementation of smart city concepts is essential to improve the quality and efficiency of city's infrastructures. This research paper seeks to examine the application of data pipelines' integration in the management of cities. Introduction and Importance: Smart city management using IoT, big data analytics, and AI can enhance services in transportation, energy, water sector, and public safety to a large extent. Methodology: These strategies are; utilization of IoT sensors for data acquisition, data lakes for storing, and machine learning for data analysis and modeling. Real-time data processing frameworks such as Apache Kafka and real-time dashboards using Tableau are also used to support decision making on time.........

Keyword: Smart City Infrastructure, Data Integration Frameworks, IoT for Smart Cities, Big Data & Analytics, Real Time Data Acquisition, Machine Learning for Smart Cities, Predictive Modeling, Sustainability of Smart Cities.

[1] E. B. Priyanka, S. Thangavel, V. Madhuvishal, S. Tharun, K. V. Raagul, And C. S. Shiv Krishnan, "Application Of Integrated Iot Framework To Water Pipeline Transportation System In Smart Cities," In In: Peter, J., Fernandes, S., Alavi, A. (Eds) Intelligence In Big Data Technologies—Beyond The Hype. Advances In Intelligent Systems And Computing, Vol 1167. Springer, Singapore. Https://Doi.Org/10.1007/978-981-15-5285-4_57.
[2] S. Silvestri, G. Tricomi, S. R. Bassolillo, R. De Benedictis, And M. Ciampi, "An Urban Intelligence Architecture For Heterogeneous Data And Application Integration, Deployment And Orchestration," In Sensors 24, No. 7: 2376. Https://Doi.Org/10.3390/S24072376.
[3] P. Elandheraiyan, "Smart City Infrastructure For Sustainable Urban Logistics," In International Journal Of Production Research 59 (7): 2079–89. Doi:10.1080/00207543.2021.1893970.
[4] M. Mohamed And K. Alosman, "An Iot-Enabled Framework For Smart City Infrastructure Management," In Techrxiv. February 27, 2024. Doi: 10.36227/Techrxiv.170906134.46169506/V1
[5] D. Lakshmi, J. Jeyarani, R. Suguna, P. Muneeshwari, G. M. Valantina, And S. Jayaraman, "Impact Of Iot Data Integration On Real-Time Analytics For Smart City Management," Presented At The 10th International Conference On Communication And Signal Processing (Iccsp), Melmaruvathur, India, 2024, Pp. 772-777, Doi: 10.1109/Iccsp60870.2024.10543926.

Abstract: Enhancing road safety and reducing accidents to save lives remains an essential goal for Advanced Driver Assistance Systems (ADAS). A foremost challenge self-driving vehicles face involves robustly detecting lane paths and road boundaries amidst dynamic driving conditions. At its core, this operation relies on lane detection protocols that pinpoint the roadway, discern the vehicle's position within it, and analyze the current direction. Leading techniques apply computer vision to reliably extract lanes from feed from on-board cameras. However, performance consistency eludes existing vision-based detectors when illuminated scenes transition to shadows or indirect lighting..........

Keyword: Hough Line Detection, Raspberry Pi, Lane Boundary Detection, Edge Detection.

[1]. Mr. Mustafa Surti, Dr. Bharati Chourasia, "Real Time Lane Detection System Using Python And Opencv On Raspberry Pi", Ijream Vol-05, Issue-06, Sep 2019.
[2]. Kitae Hwang, In Hwan Jung, Jae Moon Lee, "Implementation Of Autonomous Driving On Rc-Car With Raspberry Pi And Ai Server", Webology, Volume 19, Number 1, January, 2022.
[3]. Michael G. Bechtel, Elise Mcellhiney, Minje Kim, Heechul Yun, "Deeppicar: A Low-Cost Deep Neural Network-Based Autonomous Car", University Of Kansas, Usa, Indiana University, Usa 30 Jul 2018.
[4]. Ketan Bodhe, Himanshu Taiwade, Janhvi Ingle, Juhi Patre, Kajal Singh, Sakshi Polkamwar, Shreeya Bajirao, "Image Processing & M.L Based Driverless Car With Image Detection System", Priyadarshini Institute Of Engineering And Technology, Nagpur, Maharashtra, India. Vol-7 Issue-3 2021.
[5]. Mr. Nihal A Shetty, Mr. Mohan K, Mr. Kaushik K, "Autonomous Self-Driving Car Using Raspberry Pi Model", International Journal Of Engineering Research & Technology (Ijert), Special Issue – 2019.

Abstract: This web-based expert system for the diagnosis and treatment of bacteria diseases will help to provide a prescription and management of syphilis, tuberculosis and tetanus which are classes of bacterial diseases that are difficult to diagnose and the appropriate drugs for its cure are scarce. This will be achieved by storing human expert domain on bacteria treatment like syphilis, tuberculosis and tetanus which can be used by non-medical doctor for quick treatment of these chronic diseases with the aid of expert level knowledge on the diagnosis of these diseases so....

Keywords: Expert System, Diagnosis and Treatment, Tetanus, Syphilis, Tuberculosis, Bacteria Infectious Diseases.

[1]Kattan M. W. (2001): Expert system in Medicine, International Encyclopedia of the social and behavioral Science
[2]Auora Saibene and Marta Giltri (2021): Expert System: Definitions, Advantages and Issues in Medical Application. Expert System with Application