scholarly journals Design guidelines for automated floor plan generation applications – target group survey, results and reflections

2020 ◽  
Vol 15 (1) ◽  
pp. 73-89
Author(s):  
Maciej Nisztuk ◽  
Jacek Kościuk ◽  
Paweł Myszkowski
Keyword(s):  
Data Mining ◽  
Architectural Design ◽  
Design Guidelines ◽  
Target Group ◽  
Floor Plan ◽  
Plan Generation ◽  
Use Of Data ◽  
Survey Results ◽  
Analytical Tools

This article presents the results of a survey regarding architects’ expectations towards software for automated floor plan generation (AFPG) and optimisation processes in architectural design. More than 150 practising architects from Poland and abroad took part in the survey. Survey results were then extracted, ordered and interpreted with the use of data mining. The survey structure, methodology and analytical tools used are described in the paper.

Hybrid Evolutionary Algorithm applied to Automated Floor Plan Generation

2019 ◽  
Vol 17 (3) ◽  
pp. 260-283 ◽  
Author(s):  
Maciej Nisztuk ◽  
Paweł B. Myszkowski
Keyword(s):  
Evolutionary Algorithm ◽  
Real World ◽  
Architectural Design ◽  
Fitness Function ◽  
Design Guidelines ◽  
Domain Model ◽  
Future Research ◽  
Floor Plan ◽  
Hybrid Evolutionary Algorithm ◽  
Plan Generation

The article presents the application of Hybrid Evolutionary and Greedy-based algorithms to the problem of Automated Floor Plan Generation. The described optimization issue is part of a wider domain of Computer-Aided Architectural Design. The article covers the extensive description of the representation domain model (architectural canonical guidelines, user design requirements and constraints) and the explanation of proposed approach: problem representation, genetic algorithm operators, and fitness function definition. The research experimental procedures are based on real-world data: the architectural design guidelines being the design constraints and five real-world functional programs introduced and proposed as benchmarks. The article summarizes the implementation of the proposed approach, compares the Hybrid Evolutionary Algorithm experimental results with the Greedy-based algorithm, and suggests possible extensions and future research directions.

Usability of contemporary tools for the computational design of architectural objects: Review, features evaluation and reflection

2017 ◽  
Vol 16 (1) ◽  
pp. 58-84 ◽  
Author(s):  
Maciej Nisztuk ◽  
Paweł B Myszkowski
Keyword(s):  
Computer Aided Design ◽  
Architectural Design ◽  
Computational Design ◽  
Point Of View ◽  
Floor Plan ◽  
Plan Generation ◽  
Current State ◽  
Floor Plans ◽  
Aided Design ◽  
Architectural Perspective

This article is an overview focused on functionality and usability of selected contemporary approaches for the computational floor plan generation of architectural objects. This article describes current solutions for generative architectural design and focuses on their usability from the point of view of architectural design practice. Recent research papers and prototypes, as well as the most important tools (selected computer-aided design and BIM software) for generative design from the architectural perspective, are described. The functionalities and level of usability of present-day software and prototypes are described. In addition, the descriptive review of the research prototypes architectural design outcomes is present. Furthermore, the survey among active architects regarding the usage of computational tools in the professional practice and possible guidelines for the development of such tools are present. This article summarises with the conclusion about the current state of generative floor plan design tools, the lack of fully functional and developed commercial tools of this type on the market and future directions for the development of generative floor plans tools.

scholarly journals Data Mining Usage in Corporate Information Security: Intrusion Detection Applications

2017 ◽  
Vol 8 (1) ◽  
pp. 51-59 ◽  
Author(s):  
Masoud Al Quhtani
Keyword(s):  
Data Mining ◽  
Information Security ◽  
Intrusion Detection ◽  
Mining System ◽  
Systematic Analysis ◽  
New Methods ◽  
Use Of Data ◽  
Efficient Data ◽  
Abuse Risk ◽  
Corporate Information

AbstractBackground: The globalization era has brought with it the development of high technology, and therefore new methods of preserving and storing data. New data storing techniques ensure data are stored for longer periods of time, more efficiently and with a higher quality, but also with a higher data abuse risk. Objective: The goal of the paper is to provide a review of the data mining applications for the purpose of corporate information security, and intrusion detection in particular. Methods/approach: The review was conducted using the systematic analysis of the previously published papers on the usage of data mining in the field of corporate information security. Results: This paper demonstrates that the use of data mining applications is extremely useful and has a great importance for establishing corporate information security. Data mining applications are directly related to issues of intrusion detection and privacy protection. Conclusions: The most important fact that can be specified based on this study is that corporations can establish a sustainable and efficient data mining system that will ensure privacy and successful protection against unwanted intrusions.

Fault Diagnosis of Automobile ECUs with Data Mining Technologies

2010 ◽  
Vol 40-41 ◽  
pp. 156-161 ◽  
Author(s):  
Yang Li ◽  
Yan Qiang Li ◽  
Zhi Xue Wang
Keyword(s):  
Data Mining ◽  
Fault Diagnosis ◽  
Decision Tree ◽  
Data Stream ◽  
Electronic Control Unit ◽  
Rapid Development ◽  
Reliability And Validity ◽  
Control Unit ◽  
Use Of Data ◽  
The Cost

With the rapid development of automotive ECUs(Electronic Control Unit), the fault diagnosis becomes increasingly complicated. And the link between fault and symptom becomes less obvious. In order to improve the maintenance quality and efficiency, the paper proposes a fault diagnosis approach based on data mining technologies. By making full use of data stream, we firstly extract fault symptom vectors by processing data stream, and then establish a diagnosis decision tree through the ID3 decision tree algorithm, and finally store the link rules between faults and the related symptoms into historical fault database as a foundation for the fault diagnosis. The database provides the basis of trend judgments for a future fault. To verify this approach, an example of diagnosing faults of entertainment ECU is showed. The test result testifies the reliability and validity of this diagnostic method and reduces the cost of ECU diagnosis.

Predicting effects of selected impregnation processes on the observed bending strength of wood, with use of data mining models

BioResources ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. 4891-4904
Author(s):  
Selahattin Bardak ◽  
Timucin Bardak ◽  
Hüseyin Peker ◽  
Eser Sözen ◽  
Yildiz Çabuk
Keyword(s):  
Data Mining ◽  
Goodness Of Fit ◽  
Bending Strength ◽  
Wood Preservation ◽  
Ambient Conditions ◽  
Data Mining Algorithms ◽  
Use Of Data ◽  
The Cost ◽  
Mining Algorithms ◽  
The Relationship

Wood materials have been used in many products such as furniture, stairs, windows, and doors for centuries. There are differences in methods used to adapt wood to ambient conditions. Impregnation is a widely used method of wood preservation. In terms of efficiency, it is critical to optimize the parameters for impregnation. Data mining techniques reduce most of the cost and operational challenges with accurate prediction in the wood industry. In this study, three data-mining algorithms were applied to predict bending strength in impregnated wood materials (Pinus sylvestris L. and Millettia laurentii). Models were created from real experimental data to examine the relationship between bending strength, diffusion time, vacuum duration, and wood type, based on decision trees (DT), random forest (RF), and Gaussian process (GP) algorithms. The highest bending strength was achieved with wenge (Millettia laurentii) wood in 10 bar vacuum and the diffusion condition during 25 min. The results showed that all algorithms are suitable for predicting bending strength. The goodness of fit for the testing phase was determined as 0.994, 0.986, and 0.989 in the DT, RF, and GP algorithms, respectively. Moreover, the importance of attributes was determined in the algorithms.

Use of Data Mining in the prediction of risk factors of Type 2 diabetes mellitus in Gulf countries

2021 ◽  
Vol 8 (4) ◽  
pp. 638-645
Author(s):  
W. Boutayeb ◽  
◽  
M. Badaoui ◽  
H. Al Ali ◽  
A. Boutayeb ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Data Mining ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Gulf Coast ◽  
Use Of Data ◽  
Gulf Countries ◽  
Unhealthy Diet

Prevalence of diabetes in Gulf countries is knowing a significant increase because of various risk factors, such as: obesity, unhealthy diet, physical inactivity and smoking. The aim of our proposed study is to use Data Mining and Data Analysis tools in order to determine different risk factors of the development of Type~2 diabetes mellitus (T2DM) in Gulf countries, from Gulf COAST dataset.

An interdisciplinary sound classification framework for environmental sound design

2021 ◽  
Vol 263 (5) ◽  
pp. 1130-1141
Author(s):  
Kivanc Kitapci ◽  
Dogukan Ozdemir
Keyword(s):  
Video Game ◽  
Creative Thinking ◽  
Architectural Design ◽  
Design Guidelines ◽  
Design Framework ◽  
Sound Design ◽  
Environmental Sound ◽  
Sound Classification ◽  
Sensory Interactions ◽  
Auditory Analysis

One of the objectives of architectural design is to create multi-sensory environments. The users are under the influence of a wide variety and intense perceptual data flow when users experience a designed space. Architects and environmental designers should not ignore the sense of hearing, one of the most important of the five primitive senses that allow us to experience the physical environment within the framework of creative thinking from the first stage of the design process. Today, auditory analysis of spaces has been studied under architectural acoustics, soundscapes, multi-sensory interactions, and sense of place. However, the current sound design methods implemented in the film and video game industries and industrial design have not been used in architectural design practices. Sound design is the art and application of making soundtracks in various disciplines and it involves recognizing, acquiring, or developing of auditory components. This research aims to establish a holistic architectural sound design framework based on the previous sound classification and taxonomic models found in the literature. The proposed sound design framework will help the architects and environmental designers classify the sound elements in the built environment and provide holistic environmental sound design guidelines depending on the spaces' functions and context.

The use of data mining to classify Carménère and Merlot wines from Chile

2018 ◽  
Vol 36 (2) ◽  
pp. e12361
Author(s):  
Nattane Luíza Costa ◽  
Laura Andrea García Llobodanin ◽  
Inar Alves Castro ◽  
Rommel Barbosa
Keyword(s):  
Data Mining ◽  
Use Of Data

scholarly journals Use of data mining and spectral profiles to differentiate condition after harvest of coffee plants

2012 ◽  
Vol 32 (1) ◽  
pp. 184-196 ◽  
Author(s):  
Rubens A. C. Lamparelli ◽  
Jerry A. Johann ◽  
Éder R. dos Santos ◽  
Julio C. D. M. Esquerdo ◽  
Jansle V. Rocha
Keyword(s):  
Data Mining ◽  
Expectation Maximization ◽  
Spectral Behavior ◽  
Use Of Data ◽  
Spectral Profiles ◽  
Coffee Plants ◽  
Using Data ◽  
Hyperion Image ◽  
Noise Fraction ◽  
Behavior Profiles

This study aimed at identifying different conditions of coffee plants after harvesting period, using data mining and spectral behavior profiles from Hyperion/EO1 sensor. The Hyperion image, with spatial resolution of 30 m, was acquired in August 28th, 2008, at the end of the coffee harvest season in the studied area. For pre-processing imaging, atmospheric and signal/noise effect corrections were carried out using Flaash and MNF (Minimum Noise Fraction Transform) algorithms, respectively. Spectral behavior profiles (38) of different coffee varieties were generated from 150 Hyperion bands. The spectral behavior profiles were analyzed by Expectation-Maximization (EM) algorithm considering 2; 3; 4 and 5 clusters. T-test with 5% of significance was used to verify the similarity among the wavelength cluster means. The results demonstrated that it is possible to separate five different clusters, which were comprised by different coffee crop conditions making possible to improve future intervention actions.

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