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1051 articles for “time machine”
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Review on Number Theory, Quantisation in Physics and Nanotechnology to Invent the Time-Machine in Rocket Engineering
Abstract: In this research-paper, the interdisciplinary-nature of science is demonstrated by highlighting the aspects of nanotechnology in other branches of science and engineering. The domain of semiconductor-nanostructures in nanotechnology including Ghatak-investigations is highlighted. The experimental demonstration of microfluidics in fluid mechanics is provided towards the probable establishment of nanofluidics in future. The theoretical demonstration on high electron mobility transistors is provided towards the experimental establishment of Nanoelectronics in future. Application of …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 10, Issue 3, 2020 · pp. 20–34 Read article
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Review on the Inventions in Third Quantisation with the Possibility of Time-Machine to be implemented in the Indian-Space-Programmes under the Department of Space (Government of India)
Abstract: AbstractQuantum theory is the first quantisation, and quantum field theory is the second quantisation. Mukhopadhyay’s concept theory is the third quantisation in theoretical physics. Recently, few discoveries in third quantisation are performed and reported by Mukhopadhyay as author. In this review work, the inventions in third quantisation are summarised and briefly mentioned by Mukhopadhyay. Indian Space Research Organisation (ISRO) under the Department of Space (Government of India) has highly smart …
Published in Trends in Opto-electro & Optical Communication · Vol. 10, Issue 2, 2020 · pp. 26–31 Read article
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Feature Based Time Estimation: A Review
Abstract: Productivity improvement is the need of current market and manufacturing sector globally and machining time plays a very important role in reducing cost and time. In this review paper author aims to study the various factors affecting the NC machining time estimation and also tries to study the available methods used for estimating it. Hence a new prototype feature based model has been developed for NC machine time estimation. This …
Published in Journal of Production Research & Management · Vol. 5, Issue 3, 2015 · pp. 39–44 Read article
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Multi Objective Optimization in Turning Parameters of Al 6463 using Principal Component Analysis
Abstract: AbstractIn multi objective optimization, weight criterion of each objective is important for producing better and accurate solutions. Now a day, due to the growing requirement of the higher precision apparatus for its useful aspect, machining time (MT) and material removal rate (MRR) of a machined part plays a significant role in the modern manufacturing process. This study focuses on optimizing CNC turning parameters on Al 6463 based on principal component …
Published in Journal of Materials & Metallurgical Engineering · Vol. 7, Issue 2, 2017 · pp. 6–15 Read article
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Optimum Selection of Process Parameters of CNC End Milling Using Grey Relational Analysis (GRA)
Abstract: In this competitive world, to build a good quality product and productivity of any manufacturing corporation optimum selection of process parameters is very vital, when it comes to the desired dimension and tolerances in order to fulfill the purpose of the product. This paper explains the utility of grey relational analysis (GRA) for minimizing the machining time and lubrication thickness simultaneously, in vertical CNC end milling of Al-7075 T6. The …
Published in Journal of Production Research & Management · Vol. 8, Issue 3, 2018 · pp. 24–30 Read article
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Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Stock Price Movement Prediction using Machine Learning Algorithms and Time Series Models: A Review
Abstract: The stock market is a very important place for investment in a country. It also serves as the index of the growth for an economy. To determine the behavior of the stock market trends has been the focal point of researchers for very long. The nonlinear structure of the stock market makes it challenging to predict how the stock price will change. But it has been demonstrated that stock market …
Published in Journal of Operating Systems Development & Trends · Vol. 9, Issue 2, 2022 · pp. 7–13 Read article
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Dynamic Approach to Evaluate Costing through Software with Integration of CAD/CAM
Abstract: This paper provides the approach to evaluate costing of a model through the use of CAD/CAM integration with establishing rules and scripting. Costing includes the direct and indirect cost of the product. The earlier process of cost estimation was laborious for engineers and it takes long time to evaluate the cost of a finished product. This methodology provides the knowledge to integrate software technology with production knowledge by establishing the …
Published in Trends in Machine design · Vol. 5, Issue 1, 2018 · pp. 21–32 Read article
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Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
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Analysis and Optimization of End Milling Machining Parameters for Polypropylene composite using Taguchi based GRA
Abstract: This paper offerings the effect of machining parameters on Surface roughness (Ra & Rz) and Machining time during end milling of polypropylene material on CNC milling machine at different levels. In this effort, the machining parameters namely milling speed (MS), feed (Feed) and depth of cut (DOC) were designed using Taguchi L16 experimental design matrix. The impact of all the input parameters on the response parameters (surface roughness and machining …
Published in Trends in Mechanical Engineering & Technology · Vol. 8, Issue 3, 2018 · pp. 91–100 Read article
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Transforming Cancer Care Through AI-Driven Machine Learning: Real-Time Patient Monitoring and Personalized Intervention Strategies
Abstract: Modern healthcare systems are being improved by artificial intelligence (AI) and machine learning (ML), particularly in the treatment of cancer. An AI-driven machine learning system for monitoring cancer patients in real time and offering tailored therapeutic methods is presented in this research. In order to track health issues in real time, the suggested system gathers ongoing health data from wearable sensors and integrates it with patient medical records. This data …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 · pp. 31–38 Read article
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Response Surface Approach of Optimization to study the Effects of Drilling Parameters in AISI-304 Stainless Steel
Abstract: The effect of cutting parameters specifically cutting speed, feed rate, drill depth and drill diameter during drilling of AISI-304 stainless steel material on automatic radial drilling machine (RM-62) at different level presents in this work. All the cutting parameters are modeled using response surface methodology (RSM). The impact of cutting speed, feed rate, drill depth and drill diameter on the machining time, average roughness and peak roughness is examined. Finally, …
Published in Journal of Mechatronics and Automation · Vol. 4, Issue 2, 2017 · pp. 21–32 Read article
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Time Series Sales Forecasting Using ARIMA Model
Abstract: Sales forecasting is a critical application in various industries and presents one of the most challenging problems worldwide. One method of prediction involves identifying patterns in historical data, where the outcome is known in advance and can be validated using more recent data. If a pattern consistently leads to the same outcome, it can be considered a genuine relationship. This method is highly flexible and can be utilized with diverse …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 17–27 Read article
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Stock Market Prediction Using Machine Learning: Techniques, Challenges, and Future Directions
Abstract: The continuous advancement of machine learning (ML) technologies has significantly transformed the field of financial forecasting, particularly in the area of stock market prediction. The ability to accurately forecast stock price movements and market trends plays a crucial role in supporting informed investment strategies and effective risk management. This paper provides a comprehensive review of recent developments in the application of ML techniques for predicting stock market behavior. It classifies …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 10–16 Read article
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Optimization of Machining Process Parameters in Hard Turning of AISI D3 Tool Steel
Abstract: Machining operation is still irrefutably vital process in manufacturing, that involves complex relation of input parameters (like cutting speed, feed rate, depth of cut, nature of cooling, etc.) to output parameters (like surface finish, tool life, tool wear, machining time, machining cost, etc.). Numerous efforts were noticed in literature, to relate these parameters with each other so as to implement cost effective machining with least efforts. This paper presents one …
Published in Journal of Mechatronics and Automation · Vol. 4, Issue 1, 2017 · pp. 23–30 Read article
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Machine Vision Robot with Real Time Sensing
Abstract: Till now by giving the commands through voice we were able to control the robot but we can’t be there every where all the time so to give command through the voice some time we may face difficulty. So in our paper we are giving the commands through the text images. The robot captures it, after processing the image it react to the command which is in the text image. …
Published in Journal of Advancements in Robotics · Vol. 1, Issue 3, 2014 · pp. 30–34 Read article
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Real-time Malicious URL Detection Using Machine Learning
Abstract: In malicious URLs (universal resource locators)discovery, antiquated classifiers are tested because of the information volume is enormous, designs are dynamical over the long haul, and furthermore the relationships among choices are modern. Feature engineering plays a crucial role in addressing these issues. To raised representation, the underlying the drawback and improve the performances of classifiers in characteristic malicious URLs.This paper proposes a mixture of linear and non-linear house transformation strategies. …
Published in Journal of Web Engineering & Technology · Vol. 8, Issue 1, 2021 · pp. 8–13 Read article
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Efficient Machine Defect Detection with Sugeno Fuzzy Membership and GRU Networks for Robust Industrial Automation
Abstract: Machine fault detection is of immense significance in industrial automation to achieve efficient operations, reduced downtime, and reduced economic losses. Sugeno fuzzy logic and Gated Recurrent Unit (GRU) networks are used in this research to provide a new hybrid solution that addresses problems such as noisy data, evolving defect patterns, and real-time detection. To improve readability and reliability, the Sugeno fuzzy logic unit preprocesses fuzzy and uncertain input data into …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 17–26 Read article
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Real-time DDoS Attack Prediction in SDN Environments Using Machine Learning
Abstract: The ever-growing reliance on sdn-based services necessitates robust security measures against Distributed Denial-of-Service (DDoS) attacks that threaten service availability. This project investigates the development of a real-time prediction system for DDoS attacks in sdn environments, leveraging the power of machine learning. The proposed system employs a Decision Tree classification algorithm implemented in Python. To ensure accurate attack identification, the system meticulously addresses data preprocessing challenges inherent in network traffic datasets. …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 16–27 Read article
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Design of Tool Allocation Positions on Magazines Using Optimization Algorithm
Abstract: In today’s manufacturing environment, several industries are accomplishing flexible manufacturing systems (FMS) of group technology in cellular manufacturing to meet the competitive market requirements.CNC machines are widely used in FMS due to their high flexibility in processing. Generation of optimal index positions of cutting tools index position is an important task to overcome then on-machining time of CNC machines and for achievement of optimal plans.The present work proposes an application …
Published in Trends in Machine design · Vol. 2, Issue 3, 2015 · pp. 20–29 Read article