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A generative design-based optimization model for multi-objective construction site layout planning

ENGINEERING CONSTRUCTION AND ARCHITECTURAL MANAGEMENT 2024年

作者： Wefki, Hossam Salah, Mona Elbeltagi, Emad Elsheikh, Asser Khallaf, Rana Port Said Univ Fac Engn Dept Civil Engn Port Said Egypt Mansoura Univ Dept Struct Engn Mansoura Egypt Horus Univ Dept Civil Engn New Damietta Egypt Qassim Univ Coll Engn Dept Civil Engn Buraydah Saudi Arabia RUDN Univ Peoples Friendship Univ Russia Dept Construct Technol & Struct Mat Moscow Russia Future Univ Egypt Struct Engn & Construct Management Dept Cairo Egypt

PurposeGiven the growing interest in modern construction techniques and the emergence of innovative technologies, construction site layout planning research has progressively been investigating approaches to adopt innovative concepts and incorporate renewed approaches to improve widespread efficiency. This research develops a decision-making tool that optimizes construction site layout plans. The developed model targets two main objectives: minimizing material transportation costs and maximizing safety by optimally placing facilities on construction ***/methodology/approachA novel approach is devised based on the integration of Building Information Modeling and Generative Design (BIM-GD). This engine is used to optimize the multi-objective site layout problems to identify layout alternatives in the early project stages. Parametric modeling uses Dynamo to construct the model and explore constraints initially. Finally, the GD environment is utilized to create different design alternatives, and then the decision-making procedure selects the most appropriate design alternative. Additionally, a case study is applied to validate the effectiveness of the developed *** results indicate the effectiveness of the proposed GD tool and its potential for more complex applications. The GD engine examined optimal layout plans, balancing different objectives and adhering to appointed geometric constraints. A case study was conducted to assess the model's effectiveness and showcase its suitability. Construction Site Layout Planning (CSLP) is an essential step in design that can influence considerable aspects, such as material transportation expenses and different safety standards on the site. Employing visual programming for parametric modeling within Dynamo-Revit creates an expedient and user-friendly platform for planning engineers who may require more programming expertise to create and program algorithmic models visually. Utilizing GD in CSLP has proven to

关键词： Construction sites Layout planning Safety Optimization Generative design Transportation cost visual programming Parametric modeling

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Geospatial Analytics Extension for KNIME

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SOFTWAREX 2024年 25卷

作者： Liu, Lingbo Fu, Xiaokang Koetter, Tobias Sturm, Kevin Haubold, Carsten Guan, Weihe Wendy Bao, Shuming Wang, Fahui Harvard Univ Ctr Geog Anal Cambridge MA 02138 USA KNIME GmbH Kortestr 10 D-10967 Berlin Germany China Data Inst Ann Arbor MI 48108 USA Louisiana State Univ Dept Geog & Anthropol Baton Rouge LA 70803 USA

The Geospatial Analytics Extension for KNIME (GAEK) is an innovative tool designed to integrate visual programming with geospatial analytics, streamlining GIS education and research in social sciences. GAEK simplifies access for users with an intuitive, visual interface for complex spatial analysis tasks and contributes to the organization of the GIS Knowledge Tree through its geospatial analytics nodes. This paper discusses GAEK's architecture, functionalities, and its transformative impact on GIS applications. While GAEK significantly enhances user experience and research reproducibility, future updates aim to expand its functionality and optimize its bundled environment.

关键词： Geospatial analytics KNIME analytics platform GIS visual programming Replicability and reproducibility

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OneLabeler: A Flexible System for Building Data Labeling Tools 22

OneLabeler: A Flexible System for Building Data Labeling Too...

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CHI Conference on Human Factors in Computing Systems (CHI)

作者： Zhang, Yu Wang, Yun Zhang, Haidong Zhu, Bin Chen, Siming Zhang, Dongmei Univ Oxford Oxford England Microsoft Res Asia Beijing Peoples R China Fudan Univ Shanghai Peoples R China

ISBN: (纸本)9781450391573

Labeled datasets are essential for supervised machine learning. Various data labeling tools have been built to collect labels in different usage scenarios. However, developing labeling tools is timeconsuming, costly, and expertise-demanding on software development. In this paper, we propose a conceptual framework for data labeling and OneLabeler based on the conceptual framework to support easy building of labeling tools for diverse usage scenarios. The framework consists of common modules and states in labeling tools summarized through coding of existing tools. OneLabeler supports confguration and composition of common software modules through visual programming to build data labeling tools. A module can be a human, machine, or mixed computation procedure in data labeling. We demonstrate the expressiveness and utility of the system through ten example labeling tools built with OneLabeler. A user study with developers provides evidence that OneLabeler supports efcient building of diverse data labeling tools.

关键词： data labeling framework toolkit interactive machine learning visual programming

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Ascending the Ladder to Self-Sustainability Achieving Open Evolution in an Interactive Graphical System

Ascending the Ladder to Self-Sustainability Achieving Open E...

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ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on programming and Software (Onward!)

作者： Jakubovic, Joel Petricek, Tomas Univ Kent Canterbury Kent England Charles Univ Prague Prague Czech Republic

ISBN: (纸本)9781450399098

programming is usually based on an inconvenient separation between an implementation level and a user level. Self-sustaining systems expose their implementation at their user level so that they can be modified and improved from within. However, the few examples that exist are tightly linked to textual language-based accounts of compiler bootstrapping. If we want systems to be truly open for modification, we need to step beyond programming languages and support more structured, visual ways of programming as well. How the bootstrapping process can work in such an interactive context is important yet unexplored territory. This essay is a critical report on our first-hand experience of building one such system named BootstrapLab. We trace and reconstruct the steps for achieving self-sustainability in an interactive, structured, graphical context: choose the platform;design the substrate;implement temporary infrastructure;implement a high-level language;pay off outstanding substrate debt;provide for domain-specific notations. Throughout, we discuss the challenges involved, identifying design forces that shaped the decisions and capturing heuristics that resolved these forces in our case. Both positive and negative results are featured, including the efficacy of the heuristics. We close by suggesting how to generalise what worked in our particular case to alternative paths and starting points. The enterprise as a whole takes us a further step towards achieving open and malleable programming systems for everyone.

关键词： self-sustaining self-sustainable interactive bootstrapping visual programming context-specific domain-specific

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LevelUp - Automatic Assessment of Block-Based Machine Learning Projects for AI Education

LevelUp - Automatic Assessment of Block-Based Machine Learni...

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2022 IEEE Symposium on visual Languages and Human-Centric Computing

作者： Reddy, Tejal Williams, Randi Breazeal, Cynthia MIT EECS Cambridge MA 02139 USA MIT Media Lab Cambridge MA USA

ISBN: (数字)9781665442145

ISBN: (纸本)9781665442152;9781665442145

Although artificial intelligence (AI) is increasingly involved in everyday technologies, AI literacy amongst the general public remains low. Thus many AI education curricula for people without prior AI experience have emerged, often utilizing graphical programming languages for hands-on projects. However, there are no tools that assist educators in evaluating learners' AI projects or provide learners with contemporaneous feedback on their work. We developed LevelUp, an automatic code analysis tool to support these educators and learners. LevelUp is built into a block-based programming platform and gives users continuous feedback on their text classification projects. We evaluated the tool with a crossover user study where participants completed two text classification projects, once where they could access LevelUp and once when they could not. To measure the tool's impact on participants' understanding of text classification, we used pre-post assessments and graded both of their projects against LevelUp's rubric. We saw a significant improvement in the quality of participants' projects after they used the tool. We also used questionnaires to solicit participants' feedback. Overall, participants said that LevelUp was useful and intuitive. Our investigation of this novel automatic assessment tool can inform the design of future code analysis tools for AI education.

关键词： Computer science education machine learning automatic assessment tools visual programming

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ML Blocks: A Block-Based, Graphical User Interface for Creating TinyML Models

ML Blocks: A Block-Based, Graphical User Interface for Creat...

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2022 IEEE Symposium on visual Languages and Human-Centric Computing

作者： Williams, Randi Moskal, Michal de Halleux, Peli MIT Media Lab Cambridge MA 02139 USA Microsoft Res Seattle WA USA

ISBN: (纸本)9781665442152;9781665442145

This paper describes ML Blocks, https://***/ml-blocks, a novel interface for training, evaluating, and deploying Tiny Machine Learning (TinyML) models. TinyML is a fast-growing field that incorporates powerful machine learning algorithms into everyday technologies such as activity trackers and Internet of Things devices. Although TinyML-capable microcontrollers are popular in computer science education, few students have had the opportunity to learn about the field because of a lack of novice-friendly ML interfaces. With ML Blocks, users assemble data sets, define, and train neural network classifiers, within one unified block interface. Users can quickly evaluate their classifiers using built-in visualization tools and then export them for use in microcontroller projects. ML Blocks makes the end-to-end development of TinyML models easier for physical computing students and tinkerers at all levels.

关键词： Machine learning visual programming microprocessors and microcomputers

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Domain-Specific visual Language for Data Engineering Quality 1

Domain-Specific Visual Language for Data Engineering Quality

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1st International Workshop on programming Abstractions and Interactive Notations, Tools, and Environments (PAINT)

作者： De Meo, Alexis Homer, Michael Trove Wellington New Zealand Victoria Univ Wellington Sch Engn & Comp Sci Wellington New Zealand

ISBN: (纸本)9781450399104

Data engineering pipelines process large amounts of information, and ensuring that the quality and integrity of the data is maintained throughout is critical for technical, business, and social reasons. Conventional data quality assurance approaches require a large amount of fine-grained testing code, which is laborious, easy to get out of sync, and inscrutable to non-technical stakeholders. An executable higher-level visual approach to expressing quality requirements can serve as a shared representation of these constraints and their implications for all parties, eliminating repetition while increasing accessibility and maintainability. We present a visual programming language for expressing data quality requirements within a pipeline declaratively, structured as a diagram of compositional data flow, transformation, and validation steps.

关键词： data engineering visual programming dataflow programming

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Matters of Neural Network Repository Designing for Analyzing and Predicting of Spatial Processes

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2021年第5期12卷 17-22页

作者： Yamashkin, Stanislav A. Yamashkin, Anatoliy A. Yamashkina, Ekaterina O. Kamaeva, Anastasiya A. Natl Res Mordovia State Univ Inst Inst Elect & Lighting Engn Saransk Russia Natl Res Mordovia State Univ Geog Fac Saransk Russia MIREA Russian Technol Univ Inst Informat Technol Moscow Russia

The article is devoted to solving the scientific problem of accumulating and systematizing models and machine learning algorithms by developing a repository of deep neural network models for analyzing and predicting of spatial processes in order to support the process of making managerial decisions in the field of ensuring conditions for sustainable development of regions. The issues of architecture development and software implementation of a repository of deep neural network models for spatial data analysis are considered, based on a new ontological model, which makes it possible to systematize models in terms of their application for solving design problems. An ontological model of a deep neural network repository for spatial data analysis is decomposed into the domain of deep machine learning models, problems being solved and data. Special attention is paid to the problems of storing data in the repository and the development of a subsystem for visualizing neural networks using a graph model. The authors have shown that for organizing a repository of deep neural network models, it is advisable to use a scientifically grounded set of database management systems integrated into a multi-model storage, characterizing the domains of using relational and NoSQL storages.

关键词： Repository deep learning artificial neural network spatial data visual programming

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A Study of Free-Form Shape Rationalization Using Biomimicry as Inspiration

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POLYMERS 2023年第11期15卷 2466页

作者： Dutta, Gaurab Sundar Meiners, Dieter Merkert, Nina Tech Univ Clausthal Inst Polymer Mat & Plast Technol Agricolastr 6 D-38678 Clausthal Zellerfeld Germany Tech Univ Clausthal Inst Appl Mech Arnold-Sommerfeld-Str 6Room 310 D-38678 Clausthal Zellerfeld Germany

Bridging the gap between the material and geometrical aspects of a structure is critical in lightweight construction. Throughout the history of structural development, shape rationalization has been of prime focus for designers and architects, with biological forms being a major source of inspiration. In this work, an attempt is made to integrate different phases of design, construction, and fabrication under a single framework of parametric modeling with the help of visual programming. The idea is to offer a novel free-form shape rationalization process that can be realized with unidirectional materials. Taking inspiration from the growth of a plant, we established a relationship between form and force, which can be translated into different shapes using mathematical operators. Different prototypes of generated shapes were constructed using a combination of existing manufacturing processes to test the validity of the concept in both isotropic and anisotropic material domains. Moreover, for each material/manufacturing combination, generated geometrical shapes were compared with other equivalent and more conventional geometrical constructions, with compressive load-test results being the qualitative measure for each use case. Eventually, a 6-axis robot emulator was integrated with the setup, and corresponding adjustments were made such that a true free-form geometry could be visualized in a 3D space, thus closing the loop of digital fabrication.

关键词： shape rationalization biological forms free-form geometry visual programming parametric modelling fiber composite digital fabrication

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RoboTIC: A serious game based on augmented reality for learning programming

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MULTIMEDIA TOOLS AND APPLICATIONS 2020年第45-46期79卷 34079-34099页

作者： Schez-Sobrino, Santiago Vallejo, David Glez-Morcillo, Carlos Redondo, Miguel A. Jesus Castro-Schez, Jose Univ Castilla La Mancha Paseo Univ 4 Ciudad Real 13071 Spain

Coding skills are becoming more and more important in today's world, especially within the context of the fourth industrial revolution. They also help practice other 21 century skills such as computational thinking, problem solving and teamwork. Unfortunately, learning how to program is tough and can be also frustrating for beginner students. In this work we introduce RoboTIC, a serious game based on gamification and Augmented Reality that facilitates the learning of programming to students in lower levels of the education system by using a novel set of visual metaphors derived from a notation of roads and traffic signs. The architecture that supports RoboTIC has been designed to allow the integration of multimedia components when new programming concepts and techniques must be addressed and to add game levels that enable students to learn incrementally. Experiments have been conducted in a youth center with children who do not have coding skills at all to demonstrate the feasibility of the proposal. The results show promising conclusions in terms of children's motivation and interest in programming.

关键词： Learning programming Serious games visual programming Augmented reality

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