Substitution of hazardous chemical substances using Deep Learning and t-SNE

Manufacturing companies in the European Union are obliged to regularly analyze their recipes to find safer alternatives for hazardous substances. Unfortunately, available substance information is dispersed, heterogeneous and stored in databases of many private and public entities. In addition, the number of existing chemical substances already surpassed 85,000 with over 200 attributes describing substance characteristics, which makes it impossible for experts to collect and manually review this data. We tackle these issues by introducing a novel machine learning approach for alternative assessment. After developing a central database, we design an approach that performs nearest neighbor search in latent space obtained by deep autoencoders. Furthermore, we implement a post-hoc explanation technique, t-SNE, to visualize deep embeddings that enables to justify model outcomes. The application in a real-world project with a manufacturer shows that this approach can help process experts to identify possible replacement candidates more quickly and fosters comprehensibility through visualization

Developing a system for health and safety enhancement and automation in construction sites

The construction industry forms an important element within the economic activities and is known to be challenging and dangerous. Erroneously construction site accidents were accepted as unavoidable. The existing work health and safety protocols goals were not to cut risk but to provide risk assessment by understanding the types of risks associated with various activities and setting out rules and procedures to manage them and cut their impact. This study attempts a proactive approach to construction site health and safety by anticipating the hazards associated with a planned daily work activity and providing on site the relevant training and safety instructions. This was achieved by integrating the project’s digital design with site images processing and analysis. Digital image processing applies signal processing algorithms to images and videos resulting in extracting useful information from them. An essential and critical issue in the field of computer vision is the object’s recognition methods which should be capable of finding the partial occlusion of objects. Knowledge management systems archive and locate the required information and make it available to the relevant destination quickly and efficiently. It can also provide access to information in other construction sites and to the design team. This management system helps to save the gained experience and make it available to the project or other similar projects. The Building Information System was introduced as a system in which the objectives of this study can be incorporated leaving the door open to incorporate other project management activities. The possible solutions for the identified health and safety business problem were analysed in order to arrive at the best solution suitable to the objectives of the study. The end users ‘needs obtained from the distributed questionnaire and the project’s functional requirements were considered in order to create a model that will achieve their goals in an efficient manner. An activity diagram and a user case diagram based on the UML language were generated. Based on them a computerized model (CONSTRUCTION AUTOMATA) was developed to identify risks associated with specific work activities and provide the relevant safety instructions and training to mitigate them. The model automatically produces safety reports to record and serve as a knowledge management base for future reference thus eliminating possible human errors. The computer program was tested with available site images from an existing project and it proved to deliver its outputs according to its design. The developed model was then demonstrated to a selected group of relevant professionals and was seen to score well with ease of use mark of (6.17) and effectiveness as a health and safety tool mark of (6.37) out of a total mark of (10)

The Calumet Area Hazardous Substance Data Base : A User's Guide with Documentation

HWRIC Project 88/89-055NTIS PB90-25193

A Semantic Information Management Approach for Improving Bridge Maintenance based on Advanced Constraint Management

Bridge rehabilitation projects are important for transportation infrastructures. This research proposes a novel information management approach based on state-of-the-art deep learning models and ontologies. The approach can automatically extract, integrate, complete, and search for project knowledge buried in unstructured text documents. The approach on the one hand facilitates implementation of modern management approaches, i.e., advanced working packaging to delivery success bridge rehabilitation projects, on the other hand improves information management practices in the construction industry

English for Study and Work: Coursebook in 4 books. Book 2 Obtaining and Processing Information for Specific Purposes

Подано всі види діяльності студентів з вивчення англійської мови, спрямовані на розвиток мовної поведінки, необхідної для ефективного спілкування в академічному та професійному середовищах. Містить завдання і вправи, типові для різноманітних академічних та професійних сфер і ситуацій. Структура організації змісту – модульна, охоплює мовні знання і мовленнєві вміння залежно від мовної поведінки. Даний модуль має на меті розвиток у студентів стратегій, умінь, навичок читання, пошуку та вилучення професійно-орієнтованої інформації, необхідної для ефективної професійної діяльності і навчання. Містить завдання і вправи, типові для академічних та професійних сфер, пов’язаних з гірництвом і розробкою родовищ корисних копалин. Зразки текстів – автентичні, різножанрові, взяті з реального життя, містять цікаву й актуальну інформацію про особливості видобутку мінеральних ресурсів в провідних країнах світу, сучасний підхід до розробки родовищ тощо. Ресурси для самостійної роботи (Частина ІІ) містять завдання та вправи для розширення словникового запасу та розвитку знань найуживанішої термінології з гірництва, що спрямовано на організацію самостійної роботи з розвитку мовленнєвих умінь, знань про корисні копалини, методи їх видобутку. За допомогою засобів діагностики студенти можуть самостійно перевірити засвоєння навчального матеріалу й оцінити свої досягнення. Призначений для студентів вищих навчальних закладів, зокрема технічних університетів. Може використовуватися для самостійного вивчення англійської мови викладачами, фахівцями і науковцями різних галузей

EG-ICE 2021 Workshop on Intelligent Computing in Engineering

The 28th EG-ICE International Workshop 2021 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways