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Introduction
Published in Nebojša Kukurić, Development of a Decision Support System for Groundwater Pollution Assessment, 2020
In general terms, groundwater Vulnerability Assessment (VA) can be described as a procedure for the quick assessment of groundwater pollution potential. It is based on intrinsic aquifer characteristics, though contaminant characteristics and management practice can also be taken into account. In the context of investigations of groundwater pollution potential (at a local scale), VA is seen as a step that follows characterisation of the investigated site. Accordingly, VA uses the results of the site characterisation, yielding a first assessment of the pollution potential. The results of VA provide a basis for further investigations and/or assessment, and a means for comparison of pollution potentials. A new ranking-based VA methodology has been developed and encapsulated in the VAM-Vulnerability Assessment Module (Chapter 5). The VAM has been developed in object-orientated Borland Delphi Developer, a tool based on Object Pascal as a programming language. Integration of the VAM into the DSS involved (inter alia) DSS kernel, the SCM and a Chemical Database (CDB). The module was presented at the international conference ‘Hydrology in a Changing Environment’ (Exeter, United Kingdom) and the paper was published in the conference proceedings (Kukurić et al, 1998b).
Simulation Models and Other Computer Programs
Published in Donald E. Struble, John D. Struble, Automotive Accident Reconstruction, 2020
Donald E. Struble, John D. Struble
In the mid-1990s, NHTSA rewrote the Crash3 program in the Delphi programming language in the Microsoft Windows environment, making several enhancements to it and integrating it with the NASS/CDS data entry system.5 Enhancements included (1) a reformulated damage algorithm, (2) updated stiffness coefficients, (3) input fields for overwriting default stiffness coefficients, (4) a new algorithm for reconstructions with a missing vehicle, and (5) estimation of Barrier Equivalent Speed. The last item is defined as “the speed with a vehicle would have to collide with a fixed barrier in order to absorb the same amount of energy or produce the same amount of crush to the vehicle as in the crash.” WinSMASH retains all the simplifying assumptions of Crash3, including no restitution. The trajectory analysis used in both programs is identical.
Assessment of Productivity of the Image Processing and Recognition Systems Based on FAI Analysis
Published in Stepan Bilan, Sergey Yuzhakov, Image Processing and Pattern Recognition, 2018
Determination of the speed of information processing for image recognition system based on the analysis of the functions of the area of intersection is not possible. At the time of writing, the hardware that constitutes such a system had not been built. The software modelling was performed using the Delphi 7 programming language. In the programming model of image recognition system a working field has a size 500 × 500 pixels. Its square shape is necessary for implementation of the process of rotation of the object in the learning phase. In this case, on the formation of a single FAI at an average of one second is spent. Functions of the area of the intersection of real image are determined for two of the orthogonal directions; also, the time spent directly in comparison of the FAI and integral coefficients of the real image with the image patterns. Obviously, for hardware implementation due to parallel processes the time that is necessary for processing of objects will be less by two orders.
Reinforcement learning applied to production planning and control
Published in International Journal of Production Research, 2023
Ana Esteso, David Peidro, Josefa Mula, Manuel Díaz-Madroñero
Finally, the third dimension comprises four elements related to the software used to solve the RL algorithm: Number of agents: it identifies if the RL approach is developed for a single-agent or a multi-agent environment, understood as a system composed of multiple distributed entities that autonomously make decisions and interact in a shared environment (Weiss 1999)SW tool: it identifies whether RL has been implemented into high-level programming language (Python, Java, C++, Delphi C# or Visual Basic. NET, among others) or has been extracted from an existing library. It also identifies the rest of the software involved in solving RL: ML platforms (Tensorflow, Pythorch, DL4J); ML APIs (Keras, Google, Microsoft, Amazon); RL frameworks (TensorForce, Keras-RL, RLlib, Stable Baselines); and other tools and platforms or simulation software, such as Simpy, ARENA, MATLAB, CSIM, Weka, Minitab, GAMBIT, and multi-agent platforms like JADE and MADKitApplication: it defines whether the proposed RL algorithms are applied to a numerical study, a benchmark, a case study or a real-world problemProblem size: it identifies the number of each element considered in the problem addressed by the proposed RL models during experimentation
Concurrent manual-order-picking warehouse design: a simulation-based design of experiments approach
Published in International Journal of Production Research, 2018
Safwan A. Altarazi, Maysa M. Ammouri
Simulation modelling can be implemented through formal modelling such as PN (Basile, Pasquale, and Domenico 2012), CPN (Buil and Miguel 2008), matrix-based framework (Giordano et al. 2008); commercial simulation tools such as ARENA (Altarazi and Ammouri 2010; Ekren et al. 2010; Chan and Hing 2011; Emami, Arabzad, and Sajjadi 2014; Peixoto et al. 2016), ProModel (Dukic, Vedran, and Opetuk 2010), AutoMod (Hwang and Gyu 2006), Enterprise Dynamic (Chackelson et al. 2013), NetLogo (Shqair, Altarazi, and Al-Shihabi 2014); or appropriate programming language such as visual basic (Roodbergen, Vis, and Taylor 2015) and Delphi (Basile, Pasquale, and Domenico 2012). PN is one of the most resourceful modelling tool for discrete-event systems (Mueller 2007), its’ models are usually modular and scalable (Basile, Pasquale, and Domenico 2012), and suits large systems with many subsystems (Zhou and Venkatesh 1999). However, researchers on warehouse design via simulation usually prefer to implement commercial simulation tools; implementation of formal modelling approaches, in warehouse design, has been mainly associated with operational control issues. This can be attributed to the higher complexity of the formal model in comparison with the friendly-use of commercial simulation packages. According to Baker and Canessa (2009), more than half of warehouse designers use simulation software during the warehouse design process. ARENA 15.0 software was used in this research. During the last years, ARENA had established a proven track record of enabling companies to model and evaluate supply chains and warehouses (ARENA 2017). Several ARENA-adopted case studies covering supply chain, logistics and retail case studies can be found in (ARENA 2017).
Automated detection, 3D position of facial skin lesions using genetic algorithm and Kinect camera
Published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 2022
Negarin Javadi, Hadi Soltanizadeh
In the proposed method, by using image processing techniques and Delphi programming language, features were extracted, and classified. Afterwards, by using data, the location and position of the scars and acne were determined in the facial images.