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2D Planning

Engineering

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It is a new concept in town planning, and it may have a highly positive impact on cities and communities. It not only promotes sustainability but also helps increase the health of people and boost the economy. Although it has a lot of advantages, critics argue that this concept is not for all cities and describe its effects as well. New cities should follow this pattern to build and develop their cities

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We investigated the applicability and efficiency of the MLMC approach to the Henry-like problem with uncertain porosity, permeability and recharge. These uncertain parameters were modelled by random fields with three independent random variables. Permeability is a function of porosity. Both functions are time-dependent, have multi-scale behaviour and are defined for two layers. The numerical solution for each random realisation was obtained using the well-known ug4 parallel multigrid solver. The number of random samples required at each level was estimated by calculating the decay of the variances and the computational cost for each level. The MLMC method was used to compute the expected value and variance of several QoIs, such as the solution at a few preselected points $(t,\bx)$, the solution integrated over a small subdomain, and the time evolution of the freshwater integral. We have found that some QoIs require only 2-3 mesh levels and samples from finer meshes would not significantly improve the result. Other QoIs require more grid levels.

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Exploring AI's Impact: Key Features in Due Diligence In the realm of due diligence, AI emerges as a game-changer, revolutionizing traditional methods with its advanced features. AI-powered algorithms excel in data analysis, swiftly sifting through vast amounts of information for crucial insights. Automation streamlines document review processes, ensuring accuracy and efficiency. Moreover, AI enables predictive analytics, forecasting potential risks and opportunities with precision. With machine learning capabilities, AI continuously improves its performance, adapting to evolving trends and patterns. By integrating AI into due diligence practices, businesses gain a competitive edge, maximizing efficiency and making informed decisions swiftly. AI in due diligence is not just a tool; it's a transformational force driving businesses into the future. https://www.leewayhertz.com/ai-in-due-diligence/

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This simple Python software is designed to assist Civil and Geotechnical Engineers in performing site-specific seismic hazard assessments. The program calculates the seismic response spectrum based on user-provided geotechnical and seismic parameters, generating a comprehensive technical report that includes the response spectrum data and figures. The analysis adheres to Eurocode 8 and the Greek Annex, ensuring compliance with international standards for earthquake-resistant design.

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Welcome to my portfolio! I'm Maher Othman, an accomplished Interior Design Director with a passion for creating captivating spaces that blend functionality with aesthetics. With eighteen years of experience in the industry, I've had the privilege of leading diverse projects across residential, commercial, and hospitality sectors. At the heart of my approach lies a commitment to understanding the unique needs and aspirations of my clients. I believe that every space has a story to tell, and it's my mission to translate those narratives into immersive environments that resonate with both occupants and visitors alike. With a keen eye for detail and a flair for innovation, I strive to push the boundaries of design while adhering to practical considerations and budgetary constraints. Whether it's revitalizing outdated interiors, conceptualizing cutting-edge office spaces, or curating luxurious residential retreats, I approach each project with enthusiasm and dedication. Throughout my career, I've cultivated a collaborative mindset, working closely with clients, architects, contractors, and artisans to bring visions to life. From initial concept development to final implementation, I prioritize clear communication, meticulous planning, and seamless execution to ensure the success of every endeavor. In this portfolio, I invite you to explore a curated selection of my most notable projects, each offering a glimpse into my design philosophy, creative process, and commitment to excellence. From striking visual transformations to thoughtful spatial arrangements, I hope these examples inspire and resonate with you. Thank you for considering my work. I look forward to the opportunity to collaborate on your next design venture and bring your vision to fruition. Warm regards, Maher Othman Interior Design Director

Maher Othman Interior Design Portfolio..

MaherOthman7

A Coordinate Measuring Machine (CMM) is a precision measuring metrology machine used in manufacturing and quality control processes to precisely measure the geometric characteristics of objects. It operates on the principle of coordinate geometry, employing a probe to collect data points from the surface of an object to determine the dimensions, shapes, and positions of features, such as holes, slots, and surfaces. CMMs are essential tools for ensuring that manufactured parts meet design specifications and quality standards.

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This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.

Developing a smart system for infant incubators using the internet of things ...

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