Abstract: The integration of Artificial Intelligence (AI) into predictive project management has revolutionized the way projects are planned, monitored, and executed. This study explores the application of AI-driven models, including Artificial Neural Networks (ANN), Support Vector Machines (SVM), and Random Forest (RF), to predict project timelines and costs accurately. The models were trained on real-world data, with results showing ANN as the most effective in reducing errors and improving reliability. Key insights reveal that AI enhances decision-making, minimizes deviations, and optimizes resource allocation. Despite these advancements, challenges such as data dependency, unforeseen risks, and ethical considerations remain. This research contributes to developing a predictive framework, a model performance analysis, and practical strategies for AI implementation in project management. Future work should focus on integrating adaptive learning techniques and addressing external risk factors to enhance applicability.

Keywords: Predictive project management, Artificial Intelligence, Artificial Neural Networks, timeline prediction, cost optimization, machine learning models.

Title: Utilizing Artificial Intelligence for Predictive Project Management

Author: Mohammad Abdullah, Md Minhajul Amin, Sakina Yasmin Tisha, Sabera Samin Kafil, Tahsin Kownine Antor

International Journal of Novel Research in Engineering and Science

ISSN 2394-7349

Vol. 11, Issue 2, September 2024 - February 2025

Page No: 36-43

Novelty Journals

Website: www.noveltyjournals.com

Published Date: 07-December-2024

Abstract: In this paper, based on a new multiplication of fractional analytic functions, we study two types of fractional integrals involving fractional trigonometric functions. We can obtain the exact solutions of these two types of fractional integrals by using some techniques. Moreover, our results are generalizations of the results of ordinary calculus.    

Keywords: New multiplication, fractional analytic functions, fractional integrals, fractional trigonometric functions.

Title: A Study on Two Types of Fractional Integrals Involving Fractional Trigonometric Functions

Author: Chii-Huei Yu

International Journal of Novel Research in Engineering and Science

ISSN 2394-7349

Vol. 11, Issue 2, September 2024 - February 2025

Page No: 30-35

Novelty Journals

Website: www.noveltyjournals.com

Published Date: 11-November-2024

Abstract: Obstacle detection is a critical aspect of autonomous vehicle systems, ensuring safe navigation in dynamic environments. This paper presents a novel approach to improving obstacle detection by integrating LIDAR and RADAR data using a robust sensor fusion framework, along with advanced clustering algorithms such as DBSCAN. The proposed method enhances the accuracy and reliability of obstacle identification by reducing noise through advanced preprocessing techniques and optimizing the clustering parameters. Extensive testing in various real-world scenarios demonstrated that the algorithm significantly reduces false positives while improving precision and recall metrics. In addition, the system achieves real-time performance, ensuring immediate responses in challenging driving conditions. Compared to existing methods, the proposed approach provides superior accuracy, adaptability to different environments, and a more comprehensive obstacle detection process. This work contributes to the development of safer and more reliable autonomous vehicles.

Keywords: Autonomous vehicles, Obstacle detection, Sensor fusion, LIDAR, RADAR, Clustering algorithms.

Title: Advance Obstacle Detection for Autonomous Vehicles Using Numerical Data from LIDAR and RADAR Sensor: A Machine Learning Approach

Author: Rabaya Akter, Kaniz Fatema Oyshee, Md Nagib Mahfuz Sunny, PROMANANDA ROY, Faysal Ahammed, Md Faysal Refat

International Journal of Novel Research in Engineering and Science

ISSN 2394-7349

Vol. 11, Issue 2, September 2024 - February 2025

Page No: 20-29

Novelty Journals

Website: www.noveltyjournals.com

Published Date: 19-October-2024

Abstract: Thermodynamic HIV infectivity expressed model was incorporated in an adopted basic viral dynamics model. The ensued thermodynamic HIV dynamic model, an Ordinary Differential Equation (ODE) was solved using the numerical integration that utilized explicit Runge-Kutta method in MATLAB^TM function ode 23 for the infection time course of a HIV discordant couple. The infection dynamics representing the solution of the ensued model was allowed to progress from day zero to day one hundred and ninety nine in two series, the green series with ɛ=0  representing infection dynamics of the HIV negative wife while the black series with ɛ=0.003 , represent the HIV positive husband with daily introduction of infected cells to the green series (woman) with introduction of infected cell count y1-199=10-1(cellsμL-1)  representing sex with the HIV positive man in black series. In the second instance some measure of control was introduced in the black series representing the man at day 200 to actually showcase that the dynamics can actually be influenced by drug intervention. Dynamics of the green series, the HIV negative wife remained uninfected despite introduction of infected cells y1-199=10-1(cellsμL-1)  representing sex with the HIV positive man in black series. The infectivity value at ɛ=0  was obtained as 0mLcopies.d . This ensured that the green series being HIV negative woman did not get infected despite being the higher mass recipient during sex. The infection time course of the two series represented in principle what is expected in reality. This goes a long way to demystify the mystery of existence of HIV discordant couples. Means of characterizing the genetic factor in HIV infectivity should be sought in further studies to give it a physical meaning as its use can actually hinder continued HIV infection.

Keywords: Human immunodeficiency virus, Interfacial energetics, Infectivity, Genetics.

Title: DYNAMICS OF INTERFACIAL ENERGETICS AND FUNCTIONAL GENETICS IN HIV DISCORDANT COUPLES

Author: Ilo, C. P., Atama, N. D., Dim, E. C.

International Journal of Novel Research in Engineering and Science

ISSN 2394-7349

Vol. 11, Issue 2, September 2024 - February 2025

Page No: 14-19

Novelty Journals

Website: www.noveltyjournals.com

Published Date: 28-September-2024

Abstract: Engineering projects are by nature complicated and frequently exposed to a range of risks that may affect their outcome. In order to make educated decisions and guarantee that project objectives are fulfilled, project stakeholders must effectively manage these risks. The importance of visualizing risk factors in engineering project management is examined in this work, which also provides a thorough analysis using visualizations based on MATLAB. The study represents and analyzes many aspects of project risks using a variety of visualization techniques, such as risk matrices, spider charts, and Monte Carlo simulations. We are able to recognize patterns, rank hazards, and offer insights into how risks change over time thanks to these visual aids. The results deepen our understanding of how risk factors interact in engineering projects and provide practitioners and decision-makers with useful instruments for proactive risk management. The purpose of this study is to close current gaps in the literature about risk factor visualization and to promote the use of visual analytics into conventional project management procedures.

Keywords: Engineering projects, Risk factors, Project management, Risk visualization, Decision-making, Pro, Visual analytics, MATLAB.

Title: Strategic Risk Visualization for Proactive Engineering Project Management

Author: Shabuj Mia, Md Rahat Hossain, Md Saikat Ahmed, Syeda Fatema Jannat, Shahab Anas Rajput

International Journal of Novel Research in Engineering and Science

ISSN 2394-7349

Vol. 11, Issue 2, September 2024 - February 2025

Page No: 8-13

Novelty Journals

Website: www.noveltyjournals.com

Published Date: 19-September-2024

Abstract: Through the identification, assessment, and mitigation of potential environmental impacts, environmental impact assessment (EIA) is a crucial component of sustainable engineering projects. This study looks at creative ways to illustrate the environmental impact assessment (EIA) process with the goal of improving understanding, communication, and decision making. For efficient visualization, a variety of figures are suggested, including flowcharts, impact matrices, geographical maps, timeline charts, and others. The spatial map gives a geographical picture of potential consequences, while the timeline chart shows how the project progressed through important EIA stages. Applying these visualizations promotes informed decision-making and increases stakeholder engagement. In the end, the study fosters environmentally conscious and sustainable behaviors by providing insightful information about the practical integration of visual tools to manage and communicate environmental factors in engineering projects.

Keywords: Environmental Impact Assessment, Engineering Projects, Visualization, Sustainable Development, Stakeholder Engagement.

Title: Innovative Approaches to Environmental Impact Assessment: A Visual Strategy for Engineering Project Management

Author: Md Rahat Hossain, Md Iqbal Hossain, Md Saikat Ahmed, Syeda Fatema Jannat, Shahab Anas Rajput

International Journal of Novel Research in Engineering and Science

ISSN 2394-7349

Vol. 11, Issue 2, September 2024 - February 2025

Page No: 1-7

Novelty Journals

Website: www.noveltyjournals.com

Published Date: 14-September-2024