Notice Board :

Call for Paper
Vol. 5 Issue 11

Submission Start Date:
Nov 01, 2024

Acceptence Notification Start:
Nov 10, 2024

Submission End:
Nov 25, 2024

Final MenuScript Due:
Nov 30, 2024

Publication Date:
Nov 30, 2024
                         Notice Board: Call for PaperVol. 5 Issue 11      Submission Start Date: Nov 01, 2024      Acceptence Notification Start: Nov 10, 2024      Submission End: Nov 25, 2024      Final MenuScript Due: Nov 30, 2024      Publication Date: Nov 30, 2024




Volume V Issue IX

Author Name
Rinku Sarkar
Year Of Publication
2024
Volume and Issue
Volume 5 Issue 9
Abstract
sanskrutasahityam vedadarabhya loukikam yavat jagatah sakalakalyanam prati abhiprerayati. sahityam na kevalam manoranjanay bhavati apitu manavamanasah antaschetnamuöaavayitum nitaram apurvaam bhumikamavahati. adikaladev darshanikam chintanam upnishöootam aasit.
PaperID
2024/IJEASM/5/2024/2175

Author Name
Payal Maida, Yogesh Patidar
Year Of Publication
2024
Volume and Issue
Volume 5 Issue 9
Abstract
Integrated circuits (ICs) are fundamental to modern technology, underpinning advancements across diverse fields such as computing, medicine, and industrial applications. As IC technology progresses, it significantly influences the development of artificial intelligence (AI), creating a mutually reinforcing relationship between the two. ICs provide the essential hardware infrastructure required for AI’s complex data processing tasks, while AI contributes to the enhancement of IC design, analysis, and optimization. This dynamic interplay has led to several key innovations, including the creation of specialized AI chips, which offer substantial improvements in performance, efficiency, and power consumption. Additionally, AI has revolutionized fault diagnosis methods, enabling more accurate and efficient identification of circuit faults, and has streamlined circuit design processes through machine learning-based optimization techniques. The ongoing synergy between AI and ICs is driving the
PaperID
2024/IJEASM/5/2024/2176

Author Name
Pooja Kumari Singh, Leena Shrivastava
Year Of Publication
2024
Volume and Issue
Volume 5 Issue 9
Abstract
This study compares the effectiveness of three optimization algorithms—Grey Wolf Optimizer (GWO), Flower Pollination Algorithm (FPA), and Particle Swarm Optimization (PSO)—for task scheduling in a cloud computing environment. The simulation results reveal that GWO consistently outperforms both FPA and PSO in terms of execution time and cost efficiency. Specifically, GWO delivers the fastest execution times, starting from 122.2 milliseconds for 200 tasks and increasing to 162.6 milliseconds for 1000 tasks. It also demonstrates superior cost efficiency, with costs beginning at Rs 123.2 for 200 tasks and rising to Rs 152.6 for 1000 tasks. In comparison, FPA and PSO show higher execution times and costs, particularly for larger task sizes. These results highlight GWO’s effectiveness in managing task scheduling efficiently and economically, making it a preferable choice for large-scale and cost-sensitive cloud computing applications.
PaperID
2024/IJEASM/5/2024/2177

Author Name
Md. Aquib Iqbal, Rahul Sharma
Year Of Publication
2024
Volume and Issue
Volume 5 Issue 9
Abstract
Self Compacting Concrete's rise to prominence in constructional represents a watershed moment in the industry's history. It has a number of advantages over traditional concrete, including increased productivity, lower labour and overall costs, and a high-quality end product with good mechanical reaction and durability. Fibres addition improves SCC characters, particularly those related to post-crack behaviour. As a result, the purpose behind this to compare mechanical properties of self-consolidating concrete reinforced with various types of fibres. Type and varied percentages of fibres in the study. The mechanical characteristics, toughness, fracture energy, and sorptivity of fresh SCC were investigated. The bond and hydrated structure formation of fibre with mixed are studied using a SEM to examine the microstructure of various mixes. carbon fibre, basalt fibre and 12 mm glass fibre were employed in the investigation. 0.0 percent, 0.1 percent, 0.15 percent, 0.2 percent, 0.25 percent,
PaperID
2024/IJEASM/5/2024/2178