scholarly journals Using Machine Learning to Predict Indoor Acoustic Indicators of Multi-Functional Activity Centers

2021 ◽  
Vol 11 (12) ◽  
pp. 5641
Author(s):  
Chiu-Yu Yeh ◽  
Yaw-Shyan Tsay
Keyword(s):  
Machine Learning ◽  
Functional Activity ◽  
Architectural Design ◽  
Parametric Design ◽  
Simulation Software ◽  
Evaluation Tool ◽  
Accurate Analysis ◽  
Interior Decoration ◽  
Estimation Formula ◽  
Almost All

In Taiwan, activity centers such as school auditoriums and gymnasiums are common multi-functional spaces that are often used for performances, singing, and speeches. However, most cases are designed using only Sabine’s equation for architectural acoustics. Although that estimation formula is simple and fast, the calculation process ignores many details. Furthermore, while more accurate analysis can be obtained through acoustics simulation software, it is more complicated and time-consuming and thus is rarely used in practical design. The purpose of this study is to use machine learning to propose a predictive model of acoustic indicators as a simple evaluation tool for the architectural design and interior decoration of multi-functional activity centers. We generated 800 spaces using parametric design, adopting Odeon to obtain acoustic indicators. The machine learning model was trained with basic information of the space. We found that through GBDT and ANN algorithms, almost all acoustic indicators could be predicted within JND ± 2, and the JND of C50, C80, STI, and the distribution of SPL could reach within ±1. Through machine learning methods, we established a convenient, fast, and accurate prediction model and were able to obtain various acoustic indicators of the space without 3D-modeling or simulation software.

scholarly journals MLGen: Generative Design Framework Based on Machine Learning and Topology Optimization

2021 ◽  
Vol 11 (24) ◽  
pp. 12044
Author(s):  
Nikos Ath. Kallioras ◽  
Nikos D. Lagaros
Keyword(s):  
Machine Learning ◽  
Topology Optimization ◽  
Architectural Design ◽  
Parametric Design ◽  
Optimization Problems ◽  
Design Procedure ◽  
Performance Criteria ◽  
Design Framework ◽  
Generative Design ◽  
New Era

Design and manufacturing processes are entering into a new era as novel methods and techniques are constantly introduced. Currently, 3D printing is already established in the production processes of several industries while more are continuously being added. At the same time, topology optimization has become part of the design procedure of various industries, such as automotive and aeronautical. Parametric design has been gaining ground in the architectural design literature in the past years. Generative design is introduced as the contemporary design process that relies on the utilization of algorithms for creating several forms that respect structural and architectural constraints imposed, among others, by the design codes and/or as defined by the designer. In this study, a novel generative design framework labeled as MLGen is presented. MLGen integrates machine learning into the generative design practice. MLGen is able to generate multiple optimized solutions which vary in shape but are equivalent in terms of performance criteria. The output of the proposed framework is exported in a format that can be handled by 3D printers. The ability of MLGen to efficiently handle different problems is validated via testing on several benchmark topology optimization problems frequently employed in the literature.

scholarly journals Blockchain Disrupting Fintech and the Banking System

Proceedings ◽  
2021 ◽  
Vol 74 (1) ◽  
pp. 24
Author(s):  
Eduard Alexandru Stoica ◽  
Daria Maria Sitea
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Financial Institutions ◽  
New World ◽  
Great Part ◽  
Banking System ◽  
Daily Activities ◽  
Blockchain Technology ◽  
Almost All

Nowadays society is profoundly changed by technology, velocity and productivity. While individuals are not yet prepared for holographic connection with banks or financial institutions, other innovative technologies have been adopted. Lately, a new world has been launched, personalized and adapted to reality. It has emerged and started to govern almost all daily activities due to the five key elements that are foundations of the technology: machine to machine (M2M), internet of things (IoT), big data, machine learning and artificial intelligence (AI). Competitive innovations are now on the market, helping with the connection between investors and borrowers—notably crowdfunding and peer-to-peer lending. Blockchain technology is now enjoying great popularity. Thus, a great part of the focus of this research paper is on Elrond. The outcomes highlight the relevance of technology in digital finance.

Response to “Comment on ‘A planning quality evaluation tool for prostate adaptive IMRT based on machine learning’ ” [Med. Phys. 38, 719 (2011)]

2011 ◽  
Vol 38 (5) ◽  
pp. 2821-2821 ◽  
Author(s):  
Xiaofeng Zhu ◽  
Taoran Li ◽  
Fang-Fang Yin ◽  
Q Jackie Wu ◽  
Yaorong Ge
Keyword(s):  
Machine Learning ◽  
Quality Evaluation ◽  
Evaluation Tool

The Role of Nursing Homes Architectural Design in Mitigating the Risk of COVID-19 Pandemics: The Case of Slovenia

2022 ◽  
Vol 8 (1) ◽  
pp. 51-66
Author(s):  
Vesna Žegarac Leskovar ◽  
Vanja Skalicky Klemenčič
Keyword(s):  
Nursing Home ◽  
Nursing Homes ◽  
Older People ◽  
Architectural Design ◽  
Nursing Home Residents ◽  
The Elderly ◽  
Evaluation Tool ◽  
Negative Effect ◽  
Disproportionate Number ◽  
Role Of Nursing

Currently, many older people live in institutions for various social and health reasons. In Slovenia, this proportion is almost 5% of the population aged 65 and over. In the COVID-19 pandemic, the elderly proved to be the most vulnerable social group, as they are exposed to a number of comorbidities that increase the risk of mortality. At that time, nursing homes represented one of the most critical types of housing, as seen from a disproportionate number of infections and deaths among nursing home residents worldwide, including Slovenia. During the emergency, a number of safety protocols had to be followed to prevent the spread of infection. Unfortunately, it turned out that while the safety measures protected the nursing home residents, they also had a negative effect on their mental health, mainly due to isolation and social distancing. It follows that especially in times of epidemics of infectious respiratory diseases, the quality of life in nursing homes requires special attention. In this context, it is also necessary to consider whether and how an appropriate architectural design can help mitigating the spread of infections, while at the same time enable older people to live in dignity and with a minimum of social exclusion. To this end, the present study examined 97 nursing homes in Slovenia, analysing the number of infections in nursing homes and their correlation with the degree of infection in the corresponding region in Slovenia. Additionally, 2 nursing homes were studied in more detail with the use of newly developed “Safe and Connected” evaluation tool, analysing the architectural features of each building. The advantages identified so far include living in smaller units, single rooms with balconies, the possibility of using green open spaces and the use of an adequate ventilation. Conclusions of this study are useful for further consideration of design of new nursing homes and the refurbishment of existing ones.

scholarly journals A Review on Linear Regression Comprehensive in Machine Learning

2020 ◽  
Vol 1 (4) ◽  
pp. 140-147
Author(s):  
Dastan Maulud ◽  
Adnan M. Abdulazeez
Keyword(s):  
Machine Learning ◽  
Linear Regression ◽  
Linear Relationship ◽  
Multiple Regression ◽  
Polynomial Regression ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Explanatory Variables ◽  
Almost All ◽  
Simple Regression

Perhaps one of the most common and comprehensive statistical and machine learning algorithms are linear regression. Linear regression is used to find a linear relationship between one or more predictors. The linear regression has two types: simple regression and multiple regression (MLR). This paper discusses various works by different researchers on linear regression and polynomial regression and compares their performance using the best approach to optimize prediction and precision. Almost all of the articles analyzed in this review is focused on datasets; in order to determine a model's efficiency, it must be correlated with the actual values obtained for the explanatory variables.

FinTech Adoption in China

2021 ◽  
pp. 166-173
Author(s):  
Gagan Kukreja
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Financial Services ◽  
New Technologies ◽  
Large Population ◽  
Financial Inclusion ◽  
High Penetration ◽  
Digital Payments ◽  
Almost All

Almost all financial services (especially digital payments) in China are affected by new innovations and technologies. New technologies such as blockchain, artificial intelligence, machine learning, deep learning, and data analytics have immensely influenced all most all aspects of financial services such as deposits, transactions, billings, remittances, credits (B2B and P2P), underwriting, insurance, and so on. Fintech companies are enabling larger financial inclusion, changing in lifestyle and expenditure behavior, better and fast financial services, and lots more. This chapter covers the development, opportunities, and challenges of financial sectors because of new technologies in China. This chapter throws the light on opportunities that emerged because of the large population of 1.4 billion people, high penetration, and access to the latest and affordable technology, affordable cost of smartphones, and government policies and regulations. Lastly, this chapter portrays the untapped potentials of Fintech in China.

Impact of Deep Learning on Semantic Sentiment Analysis

2021 ◽  
pp. 97-117
Author(s):  
Neha Gupta ◽  
Rashmi Agrawal
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Deep Learning ◽  
Sentiment Analysis ◽  
Semantic Technologies ◽  
Sources Of Information ◽  
Accurate Analysis ◽  
Online Social Media ◽  
Semantic Orientation ◽  
Semantically Enhanced

Online social media (forums, blogs, and social networks) are increasing explosively, and utilization of these new sources of information has become important. Semantics plays a significant role in accurate analysis of an emotion speech context. Adding to this area, the already advanced semantic technologies have proven to increase the precision of the tests. Deep learning has emerged as a prominent machine learning technique that learns multiple layers or data characteristics and delivers state-of-the-art output. Throughout recent years, deep learning has been widely used in the study of sentiments, along with the growth of deep learning in many other fields of use. This chapter will offer a description of deep learning and its application in the analysis of sentiments. This chapter will focus on the semantic orientation-based approaches for sentiment analysis. In this work, a semantically enhanced methodology for the annotation of sentiment polarity in Twitter/ Facebook data will be presented.

The Roles of Professionals

2021 ◽  
pp. 181-200
Author(s):  
Patrick Hennessey ◽  
Philippe Kuhn
Keyword(s):  
Architectural Design ◽  
Project Managers ◽  
Construction Operations ◽  
Interior Decoration ◽  
Building Engineering

This chapter discusses professions that are traditionally concerned with building and engineering works, such as architects, engineers, and quantity surveyors. It analyses how project managers are being added to the group of construction professionals engaged by employers. It also probes the work of construction professionals in England, Wales, and Scotland that is subject to the Housing Grants, Construction and Regeneration Act 1996 (HGCRA). This chapter cites a construction contract in the HGCRA as an agreement to do architectural, design, or surveying work or provide advice on building, engineering, interior decoration, or exterior decoration to construction operations. It looks at traditional forms of contract that is responsible for the design of the works and the contractor for the construction.

scholarly journals A Design Methodology Using Prototyping Based on the Digital-Physical Models in the Architectural Design Process

2019 ◽  
Vol 11 (16) ◽  
pp. 4416 ◽  
Author(s):  
Do Young Kim
Keyword(s):  
Science Fiction ◽  
Design Process ◽  
Smart Materials ◽  
Architectural Design ◽  
Design Methodology ◽  
Parametric Design ◽  
Design Method ◽  
Physical Models ◽  
Digital Models ◽  
Education Environment

In this study, a design methodology based on prototyping is proposed. This design methodology is intended to enhance the functionality of the test, differentiating it from the prototyping that is being conducted in conventional architectural design projects. The objective of this study is to explore reference cases that enable designers to maximize the utilization of both digital models and physical models that have been currently used in architectural designs. Also, it is to explore the complementary roles and effects of digital models and physical models. Smart Building Envelopes (SBEs) are one of challenging topics in architectural design and requires innovative design process included tests and risk management. A conceptual prototyping-based model considering the topic is applied to the design studio (education environment in university). Designing SBEs is not difficult to conceive ideas, but it is impossible to “implement” using the conventional design method. Implementing SBEs requires to strengthen validities and improve responsibilities of ideas in the stages of architectural designs, with cutting-edge technologies and smart materials. The design methodology enables designers (represented by students) to apply materials and manufacturing methods using digital models (parametric design, simulation, BIM) and physical models, rather than representing vanity images that are considered simple science fiction.

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