Applied Science and Engineering Journal for Advanced Research
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Exploring Material Selection and Applications for Embedded Carbon Reduction in the Built Environment
Get PDFThe building and construction industry is a significant contributor to global greenhouse gas emissions, with 37% of total emissions attributed to this sector. While efforts have primarily targeted operational carbon emissions, which stem from building operations like heating and cooling, the urgent need to address embodied carbon—associated with the materials used and their life cycle—has gained attention. This paper explores the critical role of material selection and innovative practices in reducing embedded carbon in the built environment. It highlights collaborative models and international cooperation essential for decarbonizing building materials to achieve net-zero emissions by mid-century. The findings underscore that embodied carbon currently represents a growing proportion of a building\u27s overall carbon footprint, necessitating proactive measures in the design and construction phases. By integrating life cycle assessments and prioritizing sustainable material choices, stakeholders can significantly diminish carbon emissions and align with global climate goals. Through case studies and best practices, this research advocates for a comprehensive approach to carbon reduction that encompasses both operational and embodied emissions in the built environment
A Study on Decision Support Systems Concepts and Resources for Understanding and Managing Organization
Get PDFThis study aims to investigate the function of information systems within businesses. First, an explanation of the significance of information systems in modern businesses is given. Then, every one of these methods for evaluating information systems, including TPS, MIS, DSS, ES, WGSS, and the OAS, is assessed from a distinct angle. Each of these approaches has a designated place in the organizational hierarchy. Finding the commonalities and differences between management information systems and decision support systems was a primary goal of this study. The following are the most significant findings: 1. The decision support system operates in real time, while the management information system operates online. 2. While the decision support system can handle enormous volumes of data, the management support system can only handle medium levels of data. 3. While the decision support system makes extensive use of graphics, the management support system makes less use of them. 4-While decision support systems concentrate on both structured and semi-structured data, management information systems solely concentrate on completely organized tasks or routines for decision-making
Spam Detection and Classification Based on DistilBERT Deep Learning Algorithm
Get PDFThis paper discusses the importance of spam classification in the field of information security. With the popularity of the Internet and email, spam has become one of the major issues affecting user experience and information security. The study begins with preprocessing text data in various ways, including converting to lowercase, removing irrelevant content, links, punctuation, etc., and filtering deactivated words and words of length 1. By applying the DistilBERT model to the text classification task, the results show that it achieves 93% accuracy in spam classification, effectively distinguishing between spam and non-spam emails. The confusion matrix showed that 18,500 emails were correctly classified and a small number of spam emails were misclassified as non-spam emails. Overall, the DistilBERT model showed high accuracy in spam classification, but more algorithms are still expected to emerge to improve the prediction accuracy. This study provides a useful reference for improving spam filtering systems in the future, which is expected to further enhance user experience and information security
Effect of Conducting Particle on Spacers in Air Insulated Systems
Get PDFGas Insulated System (GIS) has been known to be reliable for more than 40 years. One of the reasons is because the active components are installed inside sealed-enclosures that reduce the environmental stress. Gas Insulated systems require solid insulating materials to provide mechanical support for conductors. Hence the spacers used in GIS should be precisely designed to realize more or less uniform field distribution along their surfaces. GIS occupy an important position in the power system. Insulating spacers are important parts in GIS. GIS have been used for many years as a means to provide safe and reliable high volt-age electrical systems. Normally, the problems connected with the use of these systems are few, especially when lower voltage levels are considered. However, the presence of metallic contamination can seriously reduce the insulation performance of a GIS. The aim of this work is to investigate the effect of conducting particle on spacers in air insulated system. The spacers used for study are Poly Methyl Metha Acrylate (PMMA) and nylon
Deep Neural Network Enhanced Adaptive Control for a Robotic Manipulator with Actuator Failures
Get PDFThis paper presents a novel control strategy for a robotic manipulator subject to actuator failures. The proposed approach integrates a deep neural network (DNN) with an adaptive control framework to enhance robustness and fault tolerance. The manipulator dynamics are modeled using a rigid-body model, incorporating potential actuator malfunctions such as partial loss of effectiveness and complete failures. A robust adaptive controller is designed to stabilize the manipulator\u27s motion despite these uncertainties. A DNN is then employed to estimate and compensate for the effects of actuator failures in real-time. Lyapunov stability analysis is conducted to guarantee the stability and convergence of the closed-loop system. Simulation results demonstrate the effectiveness of the proposed approach in achieving accurate trajectory tracking and maintaining stability in the presence of various actuator failures
Urban Planning and Green Building Technologies Based on Artificial Intelligence: Principles, Applications, and Global Case Study Analysis
Get PDFThe application of AI technology in urban planning covers multiple levels, such as data analysis, decision support, and automated planning. Urban research relies on AI technology to understand and summarize the law of urban growth and improve the analysis of the evolution trend of urban space. Planning and design use AI technology to explore the relevant factors affecting urban development and their weights and discuss the critical role of green building technology in the sustainable development of the construction industry. With the increase in global energy consumption and carbon emissions, traditional building methods can no longer meet environmental protection requirements and efficient use of resources. As a sustainable development solution, green building technology has been paid more and more attention to and adopted by people. These technologies focus not only on the energy efficiency and environmental impact of buildings but also on the resource utilization and environmental load of green buildings over their entire life cycle driven by machine learning. This paper details the basic principles and applications of green building technologies, including AI-driven reduction of negative environmental impacts, improvement of occupant health, efficient use of resources, and optimization of indoor environmental quality. This paper focuses on the critical role of the LEED assessment system developed by the U.S. Green Building Council in advancing green building practices. In addition, the paper analyzes vital points such as water use in green building design, machine learning-driven wind environment optimization, solar technology application, and practical application cases of these technologies on a global scale
LLM for Sentiment Analysis in E-commerce: A Deep Dive into Customer Feedback
Get PDFWith the rise of online shopping becoming an integral part of daily life, it has brought unparalleled convenience, allowing us to purchase anything from daily necessities to luxury items with ease. On platforms like Amazon[1], customer feedback mechanisms play a crucial role in shaping user behavior and business practices. These mechanisms include the Star Rate (1-5) and detailed reviews. The star rating provides a quick and intuitive way for customers to score a product, while reviews offer comprehensive descriptions and shopping experiences. These feedback systems influence other customers\u27 purchasing decisions and provide valuable insights for businesses to improve their products.
In our study, we explore the impact of time on user behavior by combining three datasets for analysis. We observe a macro trend of increasing online shopping activity and customer satisfaction over time, with a growing tendency for customers to leave feedback. From a micro perspective, we conduct time series analysis and establish that customer star ratings vary over time, forming a column relationship, which we model using the ARIMA[2] technique to predict future trends.
Furthermore, we investigate the influence of reviews on customer responses, finding that negative reviews spread rapidly and widely through social networks, akin to a viral phenomenon. Utilizing the SIR virus model as a text-based network propagation model, we demonstrate the significant impact of negative reviews on consumption patterns.[3]
Lastly, we employ advanced deep learning models such as BERT, LLM, and GPT for natural language processing (NLP) to analyze the sentiment in customer reviews. By leveraging word vectors through classification functions, we distinguish between pessimistic and optimistic emotions. Our findings reveal a higher-order functional relationship[4] between star ratings and these emotions, providing deeper insights into customer sentiment and product perception
Smart D.O.L Starter
Get PDFThe objective of the project is to control the starter from the application and to provide a start motor The starter is turned on/off from the application itself through a Wi-Fi module The webpage is created through which the starter on/off status can be identified and the motor can be turned on/off. Arduino software is used which receives the Wi-Fi module signal from the webpage. The signal from the Arduino in turn controls the starter action through the relay driver circuit. Additionally, the voltage sensor are given as feedback to the Node MCU to protect the motor from overvoltage and overcurrent. Thus the starter can be controlled from the application through the internet
Optimizing Methods and Analysis of Multicast Routing with using Deep Learning
Get PDFThe machine learning technology has received increased attention in recent years in several vision tasks such as image classification, image detection, and image recognition. In particular, recent advances of machine learning techniques bring encouragement to image classification with convolutional neural networks. CNN has been established as a powerful class of models for image recognition problems and even in some cases they outperform humans. The main purpose of the work presented in this paper is the rise and development of machine learning, deep learning, CNN and to give an overview on using machine learning for image classification. At the end the comparison of CNN with traditional method is discussed
Future-proofing for Climate Change and the Environment
Get PDFThe industrialised countries\u27 disproportionately high cumulative emissions of greenhouse gases (GHGs), as well as their high yearly per capita emissions of GHGs, are mostly to blame for climate change. Although contributing only 4% of the total worldwide emissions (from 1850 to 2019) and maintaining significantly lower per capita emissions than the global average, India is one of the most vulnerable regions due to the problem\u27s global nature. Even though India isn\u27t as much to blame for the huge stock of emissions, it has shown that it is a leader in the world by taking many steps and committing to a growth path with low emissions and a goal of net-zero emissions by 2070.
India has combined its ambitious climate action goals with its development objectives, whether it be through increased solar power capacity (installed), higher energy saving targets announced in PAT cycle-VII, or improved green cover made possible by the Green India Mission, among other focused government initiatives. India presently has 75 Ramsar sites for wetlands as part of its commitment to preserving ecosystems, in addition to several legal and promotional initiatives to save and conserve mangroves. With Namami Gange and the National River Conservation Plan (NRCP), people are working all the time to protect rivers and bring them back to life