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1
Cayron, Cyril. "GenOVa: a computer program to generate orientational variants." Journal of Applied Crystallography 40, no. 6 (November 10, 2007): 1179–82. http://dx.doi.org/10.1107/s0021889807048741.
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A computer program calledGenOVa, written in Python, calculates the orientational variants, the operators (special types of misorientations between variants) and the composition table associated with a groupoid structure. The variants can be represented by three-dimensional shapes or by pole figures.
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Ayer, Vidya M., Sheila Miguez, and Brian H. Toby. "Why scientists should learn to program in Python." Powder Diffraction 29, S2 (December 2014): S48—S64. http://dx.doi.org/10.1017/s0885715614000931.
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The importance of software continues to grow for all areas of scientific research, no less for powder diffraction. Knowing how to program a computer is a basic and useful skill for scientists. This paper explains the three approaches for programming languages and why scripting languages are preferred for non-expert programmers. The Python-scripting language is extremely efficient for science and its use by scientists is growing. Python is also one of the easiest languages to learn. The language is introduced, as well as a few of the many add-on packages available that extend its capabilities, for example, for numerical computations, scientific graphics, and graphical user interface programming. Resources for learning Python are also provided.
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Chaput, Ludovic, Valentin Guillaume, Natesh Singh, Benoit Deprez, and Bruno O. Villoutreix. "FastTargetPred: a program enabling the fast prediction of putative protein targets for input chemical databases." Bioinformatics 36, no. 14 (June 27, 2020): 4225–26. http://dx.doi.org/10.1093/bioinformatics/btaa494.
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Abstract Summary Several web-based tools predict the putative targets of a small molecule query compound by similarity to molecules with known bioactivity data using molecular fingerprints. In numerous situations, it would however be valuable to be able to run such computations on a local computer. We present FastTargetPred, a new program for the prediction of protein targets for small molecule queries. Structural similarity computations rely on a large collection of confirmed protein–ligand activities extracted from the curated ChEMBL 25 database. The program allows to annotate an input chemical library of ∼100k compounds within a few hours on a simple personal computer. Availability and implementation FastTargetPred is written in Python 3 (≥3.7) and C languages. Python code depends only on the Python Standard Library. The program can be run on Linux, MacOS and Windows operating systems. Pre-compiled versions are available at https://github.com/ludovicchaput/FastTargetPred. FastTargetPred is licensed under the GNU GPLv3. The program calls some scripts from the free chemistry toolkit MayaChemTools. Contact bruno.villoutreix@inserm.fr Supplementary information Supplementary data are available at Bioinformatics online.
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Reyes Peña, Cecilia, Mireya Tovar Vidal, and Concepción Stephanie Vázquez González. "Creation of a consulting tool and implementation of an ontology for a Master’s Degree Program in Computer Sciences." Revista Colombiana de Computación 19, no. 1 (June 1, 2018): 29–38. http://dx.doi.org/10.29375/25392115.3227.
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In this paper, a manual ontology for a Computer Sciences Master program constructed, that uses some elements from the METHONTOLOGY, Grüninger and Fox, and Bravo’s methodologies, is presented. A series of steps to identify and represent the Master’s Degree program’s knowledge base has been followed. Afterwards, first order logic axioms and competency questions to evaluate the ontology are used. The development of a module written in Python language is used for evaluating the ontology through competency questions defined during design phase. This module is flexible enough to present predefined or defined questions by the user in running time and to obtain results to the queries representing the competency questions. Elements as a hierarchy class diagram and a description of the relations and attributes are used in this ontology’s construction. Keywords: Ontology; Python tool; SPARQL language.
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De Pra, Yuri, and Federico Fontana. "Programming Real-Time Sound in Python." Applied Sciences 10, no. 12 (June 19, 2020): 4214. http://dx.doi.org/10.3390/app10124214.
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For its versatility, Python has become one of the most popular programming languages. In spite of its possibility to straightforwardly link native code with powerful libraries for scientific computing, the use of Python for real-time sound applications development is often neglected in favor of alternative programming languages, which are tailored to the digital music domain. This article introduces Python as a real-time software programming tool to interested readers, including Python developers who are new to the real time or, conversely, sound programmers who have not yet taken this language into consideration. Cython and Numba are proposed as libraries supporting agile development of efficient software running at machine level. Moreover, it is shown that refactoring few critical parts of the program under these libraries can dramatically improve the performances of a sound algorithm. Such improvements can be directly benchmarked within Python, thanks to the existence of appropriate code parsing resources. After introducing a simple sound processing example, two algorithms that are known from the literature are coded to show how Python can be effectively employed to program sound software. Finally, issues of efficiency are mainly discussed in terms of latency of the resulting applications. Overall, such issues suggest that the use of real-time Python should be limited to the prototyping phase, where the benefits of language flexibility prevail on low latency requirements, for instance, needed during computer music live performances.
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Alam, Marzia, Mehreen Saleem Gul, and Tariq Muneer. "Radiation View Factor for Building Applications: Comparison of Computation Environments." Energies 12, no. 20 (October 10, 2019): 3826. http://dx.doi.org/10.3390/en12203826.
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Computation of view factors is required in several building engineering applications where radiative exchange takes place between surfaces such as ground and vertical walls or ground and sloping thermal or photovoltaics collectors. In this paper, view factor computations are performed for bifacial solar photovoltaic (PV) collectors based on the finite element method (FEM) using two programming languages known as Microsoft Excel-Visual Basic for Applications (VBA) and Python. The aim is to determine the computer response time as well as the performance of the two languages in terms of accuracy and convergence of the numerical solution. To run the simulations in Python, an open source just-in-time (JIT) compiler called Numba was used and the same program was also run as a macro in VBA. It was observed that the simulation response time significantly decreased in Python when compared to VBA. This decrease in time was due to the increase in the total number of iterations from 400 million to 250 billion for a given case. Results demonstrated that Python was 71–180 times faster than VBA and, therefore, offers a better programming platform for the view factor analysis and modelling of bifacial solar PV where computation time is a significant modelling challenge.
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Cayron, Cyril. "ARPGE: a computer program to automatically reconstruct the parent grains from electron backscatter diffraction data." Journal of Applied Crystallography 40, no. 6 (November 10, 2007): 1183–88. http://dx.doi.org/10.1107/s0021889807048777.
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A computer program calledARPGEwritten in Python uses the theoretical results generated by the computer programGenOVato automatically reconstruct the parent grains from electron backscatter diffraction data obtained on phase transition materials with or without residual parent phase. The misorientations between daughter grains are identified with operators, the daughter grains are identified with indexed variants, the orientations of the parent grains are determined, and some statistics on the variants and operators are established. Some examples with martensitic transformations in iron and titanium alloys were treated. Variant selection phenomena were revealed.
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Geldiev, Ertan Mustafa, Nayden Valkov Nenkov, and Mariana Mateeva Petrova. "EXERCISE OF MACHINE LEARNING USING SOME PYTHON TOOLS AND TECHNIQUES." CBU International Conference Proceedings 6 (September 25, 2018): 1062–70. http://dx.doi.org/10.12955/cbup.v6.1295.
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One of the goals of predictive analytics training using Python tools is to create a "Model" from classified examples that classifies new examples from a Dataset. The purpose of different strategies and experiments is to create a more accurate prediction model. The goals we set out in the study are to achieve successive steps to find an accurate model for a dataset and preserving it for its subsequent use using the python instruments. Once we have found the right model, we save it and load it later, to classify if we have "phishing" in our case. In the case that the path we reach to the discovery of the search model, we can ask ourselves how much we can automate everything and whether a computer program can be written to automatically go through the unified steps and to find the right model? Due to the fact that the steps for finding the exact model are often unified and repetitive for different types of data, we have offered a hypothetical algorithm that could write a complex computer program searching for a model, for example when we have a classification task. This algorithm is rather directional and does not claim to be all-encompassing. The research explores some features of Python Scientific Python Packages like Numpy, Pandas, Matplotlib, Scipy and scycit-learn to create a more accurate model. The Dataset used for the research was downloaded free from the UCI Machine Learning Repository (UCI Machine Learning Repository, 2017).
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Gunawan, Alexander A. S., and Jimmy Linggarjati. "Pengembangan Program Aplikasi Enhanced Machine Control dengan Python untuk Metode Interpolasi Newton." ComTech: Computer, Mathematics and Engineering Applications 3, no. 1 (June 1, 2012): 154. http://dx.doi.org/10.21512/comtech.v3i1.2396.
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Nowadays, one of industrial main problems is the flexibility of machines to be customized since they are designed based on certain standard. This research develops software for CNC (Computer Numerically Controlled) machine in order to execute the Newton Interpolation using Python. The platform used in the CNC machine is EMC (Enhanced Machine Control) and GUI (Graphical User Interface) AXIS on the operating system Linux Ubuntu. The Newton interpolation is used to create a curve based on several point determined by user. By converting this curve into G-Code, which could be read by CNC machine, the machine can move according to curve designed by user. This research is an initial study to customize the CNC machine and will continue to fulfill the user needs. This research obtained a program that is able to run well up to 4 input pairs. The higher number inputs will cause the oscillation in the interpolation curve.
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Tarzhanov, Timofey, Vadim Kudryashov, and Diana Makarova. "DELETRIOUS SOFTWARE AND METHODS FOR COMBATING IT." Interexpo GEO-Siberia 9 (2019): 15–18. http://dx.doi.org/10.33764/2618-981x-2019-9-15-18.
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The article discusses existing malware. To study the features of building deletrious software, the most common computer viruses were analyzed. A program for capturing keystrokes by means of the Python 3.7 language was developed, and a function for sending captured data to mail was implemented.
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Madlazim, M., and Bagus Jaya Santosa. "Computational physics Using Python: Implementing Maxwell Equation for Circle Polarization." Jurnal Penelitian Fisika dan Aplikasinya (JPFA) 1, no. 1 (June 14, 2011): 1. http://dx.doi.org/10.26740/jpfa.v1n1.p1-7.
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Python is a relatively new computing language, created by Guido van Rossum [A.S. Tanenbaum, R. van Renesse, H. van Staveren, G.J. Sharp, S.J. Mullender, A.J. Jansen, G. van Rossum, Experiences with the Amoeba distributed operating system, Communications of the ACM 33 (1990) 46–63; also on-line at http://www.cs.vu.nl/pub/amoeba/, which is particularly suitable for teaching a course in computational physics. There are two questions to be considered: (i) For whom is the course intended? (ii) What are the criteria for a suitable language, and why choose Python? The criteria include the nature of the application. High performance computing requires a compiled language, e.g., FORTRAN. For some applications a computer algebra, e.g., Maple, is appropriate. For teaching, and for program development, an interpreted language has considerable advantages: Python appears particularly suitable. Python‟s attractions include (i) its system of modules which makes it easy to extend, (ii) its excellent graphics (VPython module), (iii) its excellent on line documentation, (iv) it is free and can be downloaded from the web. Python and VPython will be described briefly, and some programs demonstrated numerical and animation of some phenomenal physics. In this article, we gave solution of circle polarization by solving Maxwell equation.
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McCoid, Scott, Jason Freeman, Brian Magerko, Christopher Michaud, Tom Jenkins, Tom Mcklin, and Hera Kan. "EarSketch: An integrated approach to teaching introductory computer music." Organised Sound 18, no. 2 (July 11, 2013): 146–60. http://dx.doi.org/10.1017/s135577181300006x.
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EarSketch is an all-in-one approach to supporting a holistic introductory course to computer music as an artistic pursuit and a research practice. Targeted to the high school and undergraduate levels, EarSketch enables students to acquire a strong foundation in electroacoustic composition, computer music research and computer science. It integrates a Python programming environment with a commercial digital audio workstation program (Cockos’ Reaper) to provide a unified environment within which students can use programmatic techniques in tandem with more traditional music production strategies to compose music. In this paper we discuss the context and goals of EarSketch, its design and implementation, and its use in a pilot summer camp for high school students.
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Papakonstantinou, Eleni, Vasileios Megalooikonomou, and Dimitrios Vlachakis. "Dark Suite; a comprehensive toolbox for computer-aided drug design." EMBnet.journal 25 (March 13, 2020): e928. http://dx.doi.org/10.14806/ej.25.0.928.
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Dark Suite is a complete interactive software pipeline aiming to exploit the advantages of free software and modern programming. Besides two commands (installation and opening) on the command line, the handling and the program operation is done through a user’s friendly interface. This platform has a central graphical interface which allows the user to choose in what computational tool to work. Each computational tool has an interface. Dark Suite combines the functions of other programmes to create a pipeline for high-quality secondary effects through a friendly user interface. It is made to run on GNU/Linux distributions and its interface was built using JAVA to seamlessly integrate scientific tools written in Perl, Java, R and Python.
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Keller, Lisa, and Isabel John. "Motivating Female Students for Computer Science by Means of Robot Workshops." International Journal of Engineering Pedagogy (iJEP) 10, no. 1 (January 27, 2020): 94. http://dx.doi.org/10.3991/ijep.v10i1.11661.
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As women belong to a minority in computer science, this work aims to provide possible STEM education initiatives for middle to high school students. These initiatives are designed for institutions to contribute to increasing the proportion of women in computer science by using robots. Through applying these initiatives, institutions such as computer science faculties can help to reduce the gender imbalance, increase diversity and the amount of computer science specialists, who are requested immensely. Based on the results of conducted requirements elicitation a concept for programming an application with the NAO robot which trains vocabularies, as well as a concept with the Cozmo robot which piles up cubes, were developed. First tests were performed with female and male high school students. Either concept consists of an introduction of possible robotics application fields, a presentation explaining the Python program code of the concept as well as corresponding exercises with the robot and Python. Evaluation of the workshop concepts through questionnaires showed that both concepts have the potential to increase the proportion of women and to motivate female as well as male students for computer science. Moreover, recommendations for further robotics projects with respect to motivating young women for STEM can be made based on the insights of the requirements elicitation and the evaluation of the concepts. Nevertheless, further refinement and validation has to be undertaken. Long-term as well as short-term initiatives are feasible with the developed concepts. All participating schools showed high interest in both types of initiatives and further cooperation.
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Zahariev, Federico, Nuwan De Silva, Mark S. Gordon, Theresa L. Windus, and Marilu Dick-Perez. "ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data." Journal of Chemical Information and Modeling 57, no. 3 (February 23, 2017): 391–96. http://dx.doi.org/10.1021/acs.jcim.6b00654.
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Murdiya, Fri, and Rofi Hariadi. "Analysis of Lightning Performance on 345 kV Transmission Lines Using Python Programming." International Journal of Electrical, Energy and Power System Engineering 3, no. 3 (October 12, 2020): 65–76. http://dx.doi.org/10.31258/ijeepse.3.3.65-76.
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One of main causes of interruption of electrical power supply is the lightning strike on overhead power transmission lines. The lightning performance of transmission line can be determined by value of shielding failure flashover rate (SFFOR) and back flashover rate (BFOR). The object of this study is to create a computer application to compute lightning performance on the transmission lines using Python programming. Pythons package tkinter used for program interface window. Application programming is done by using the concept of object-oriented programming (OOP) using Pythons keyword class. Validation shows that the application has applied the method correctly with a percentage error 0 % for SFFOR and 3.14 % for BFOR. The application can do analysis on the factors that affecting SFFOR and BFOR such as the effect of thunder day, tower foot resistance, and number of isolator disk. The results obtained in this study is computer application that can perform lightning performance analysis and analysis of factors that can affect it, such as thunder day, tower foot resistance and the number of isolator disk.
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Pontes, Thiago, Guilhermina Miranda, and Gabriela Celani. "Algorithm-Aided Design with Python: Analysis of Technological Competence of Subjects." Education Sciences 8, no. 4 (November 15, 2018): 200. http://dx.doi.org/10.3390/educsci8040200.
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Difficulties in learning computer programming for novices is a subject of abundant scientific literature. These difficulties seem to be accentuated in students whose academic choice is not computation, like architecture students. However, they need to study programming, since it is part of the new academic curricula. The results presented here are part of a PhD research, which investigates the achievement motivation and the acquisition and transfer of programming knowledge from an online environment designed on the basis of the 4C-ID instructional design model. These results are a sociodemographic analysis, and the technological competence of these subjects. We concluded that most of the students of our sample do not know how to auto assess their ICT expertise level, because they believed that they had sufficient computational knowledge for their needs. However, most of them told that they had difficulties creating codes. However, they recognized the importance of learning to program, thought it was valuable for architectural students, and felt motivated to acquire this new skill.
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Eaton, Deren A. R., and Isaac Overcast. "ipyrad: Interactive assembly and analysis of RADseq datasets." Bioinformatics 36, no. 8 (January 6, 2020): 2592–94. http://dx.doi.org/10.1093/bioinformatics/btz966.
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Abstract Summary ipyrad is a free and open source tool for assembling and analyzing restriction site-associated DNA sequence datasets using de novo and/or reference-based approaches. It is designed to be massively scalable to hundreds of taxa and thousands of samples, and can be efficiently parallelized on high performance computing clusters. It is available both as a command line interface and as a Python package with an application programming interface, the latter of which can be used interactively to write complex, reproducible scripts and implement a suite of downstream analysis tools. Availability and implementation ipyrad is a free and open source program written in Python. Source code is available from the GitHub repository (https://github.com/dereneaton/ipyrad/), and Linux and MacOS installs are distributed through the conda package manager. Complete documentation, including numerous tutorials, and Jupyter notebooks demonstrating example assemblies and applications of downstream analysis tools are available online: https://ipyrad.readthedocs.io/.
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Förster, Anna, Jens Dede, Asanga Udugama, Alexander Förster, Daniel Helms, Louis Kniefs, Julia Müller, Lars Gerken, Franziska Richter, and Jan Kulmann. "A Blended Learning Approach for an Introductory Computer Science Course." Education Sciences 11, no. 8 (July 22, 2021): 372. http://dx.doi.org/10.3390/educsci11080372.
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In this paper, we present our experience with redesigning an introductory computer science course for (electrical) engineers with blended learning concepts. It is a large mandatory course with eight credit points over the course of two semesters, where first year electrical engineers learn how to program with Arduino, C and Python. Additionally, they need to cover basic computer science concepts such as binary numbers, Boolean algebra, encodings, finite state machines and object-oriented programming. We designed the course to cover the fields that are most relevant to our students’ future careers. With the new format, students declare they are much more engaged with the course, they drop the course less often and they actually achieve better exam results. We completely re-structured the course, introduced inverted classroom elements and hackathons and we continuously optimized and adapted the course. The main focus is on hands-on-experience and teamwork, which we mostly achieve by the use of hackathons. In this paper, we described the contents and teaching concepts of the course and we discussed the achieved results.
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Lazarus, David B., Johan Renaudie, Dorina Lenz, Patrick Diver, and Jens Klump. "Raritas: a program for counting high diversity categorical data with highly unequal abundances." PeerJ 6 (October 9, 2018): e5453. http://dx.doi.org/10.7717/peerj.5453.
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Acquiring data on the occurrences of many types of difficult to identify objects are often still made by human observation, for example, in biodiversity and paleontologic research. Existing computer counting programs used to record such data have various limitations, including inflexibility and cost. We describe a new open-source program for this purpose—Raritas. Raritas is written in Python and can be run as a standalone app for recent versions of either MacOS or Windows, or from the command line as easily customized source code. The program explicitly supports a rare category count mode which makes it easier to collect quantitative data on rare categories, for example, rare species which are important in biodiversity surveys. Lastly, we describe the file format used by Raritas and propose it as a standard for storing geologic biodiversity data. ‘Stratigraphic occurrence data’ file format combines extensive sample metadata and a flexible structure for recording occurrence data of species or other categories in a series of samples.
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Kurilin, Sergey P., Andrey M. Sokolov, and Nikolai N. Prokimnov. "A computer program for electromechanical system operational diagnostics based on the topological approach." Journal Of Applied Informatics 16, no. 4 (August 31, 2021): 62–73. http://dx.doi.org/10.37791/2687-0649-2021-16-4-62-73.
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The paper presents a method, a mathematical model, and a computer program for the operational diagnostics of an electromechanical system (EMS). During EMS operation, service aging changes the properties of the parametric matrices of the windings and, as a consequence, the characteristics of the EMS vector space. Periodic testing of the vector space offers relevant and reliable data on the current health of the EMS, its changes during operation, and the risk of loss of function. The object of the study is an asynchronous electric motor (AEM). It is urgent to automate the process of assessing the current health of an AEM and to organize the storage of information on its states at different stages of its life cycle. To solve the problem, software (SW) for accumulation of information on AEM operation and for evaluation of its basic performance metrics has been developed in the Python programming language. The SW is based on the topological approach to diagnostics, which implies the analysis of the current responses of motor rotor windings to phase voltage pulses. The SW enables one to determine the rate of the service aging of an item, the probability of its survival and residual life, to obtain access to the history of previous diagnostics, and to visualize the in-service history of the above-mentioned performance metrics. The developed SW can be used to increase the AEM operation efficiency and to plan engineering or repair work; it can also be used as an information source for re- engineering and modification of existing AEMs. The described SW can be extended to perform operational diagnostics based on the topological approach of devices of various types. Also, this SW can be considered as a separate information component of the digital twin of a complex EMS, which will allow us to study the main indicators of its reliability, fault tolerance and operational efficiency at all stages of the life cycle.
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Mihaljević, Josip. "Analys is and Creation of Free Sentiment Analysis Programs." Medijska istraživanja 25, no. 1 (July 12, 2019): 83–105. http://dx.doi.org/10.22572/mi.25.1.4.
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This paper analyzes free online programs for sentiment analysis which can, on the bases of their algorithm, give a positive, negative or neutral opinion of a text. At the beginning of the paper sentiment analysis programs and techniques they use such as Naive Bayes and Recurrent Neural Networks are presented. The programs are divided into two categories for analysis. The fi rst category consists of sentiment analysis programs which analyze texts written or copied inside the user interface. The second category consists of programs for analyzing opinions posted on social networks, blogs, and other media sites. Programs from both categories were chosen for this research on the bases of positive reviews on computer science portals and their popularity on web search engin es such as Google and Bing. The accuracy of the programs from the fi rst category was checked by inserting the same sentence from movie reviews and comparing the results. Their additional options have also been analyzed. For the second category of programs, it was determined which social networks, blogs, and other social media they cover on the internet. The purpose of this analysis was to check the overall quality and options that free sentiment analysis programs provide. An example of how to create one’s own custom sentiment analyzer by using the available Python code and libraries found online is also given. Two simple programs were created using Python. The fi rst program belongs to the fi rst category of programs for analyzing an input text. This program serves as a pilot program for Croatian which gives only the basic analysis of sentences. The second program collects recent tweets from Twitter containing certain words and creates a pie chart based on the analysis of the results.
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Zhang, Henry B., Minji Kim, Jeffrey H. Chuang, and Yijun Ruan. "pyBedGraph: a python package for fast operations on 1D genomic signal tracks." Bioinformatics 36, no. 10 (February 11, 2020): 3234–35. http://dx.doi.org/10.1093/bioinformatics/btaa061.
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Abstract Motivation Modern genomic research is driven by next-generation sequencing experiments such as ChIP-seq and ChIA-PET that generate coverage files for transcription factor binding, as well as DHS and ATAC-seq that yield coverage files for chromatin accessibility. Such files are in a bedGraph text format or a bigWig binary format. Obtaining summary statistics in a given region is a fundamental task in analyzing protein binding intensity or chromatin accessibility. However, the existing Python package for operating on coverage files is not optimized for speed. Results We developed pyBedGraph, a Python package to quickly obtain summary statistics for a given interval in a bedGraph or a bigWig file. When tested on 12 ChIP-seq, ATAC-seq, RNA-seq and ChIA-PET datasets, pyBedGraph is on average 260 times faster than the existing program pyBigWig. On average, pyBedGraph can look up the exact mean signal of 1 million regions in ∼0.26 s and can compute their approximate means in <0.12 s on a conventional laptop. Availability and implementation pyBedGraph is publicly available at https://github.com/TheJacksonLaboratory/pyBedGraph under the MIT license. Supplementary information Supplementary data are available at Bioinformatics online.
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Zhu, Lihua. "Implementation of Web Log Mining Device Under Apriori Algorithm Improvement and Confidence Formula Optimization." International Journal of Information Technology and Web Engineering 15, no. 4 (October 2020): 53–71. http://dx.doi.org/10.4018/ijitwe.2020100104.
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With the increasing number of internet users, a large number of network alarm information increases, resulting in the increasing pressure of SMS gateway and frequent alarm delay. Therefore, in order to effectively improve the above problems, the article is based on the improved Apriori algorithm and confidence formula, points and grabbing module, model training module and the test evaluation module device, three steps to realize the web log mining and mining system design for the data acquisition module, data preprocessing module, mining model building blocks, mining model checking module and mining model analysis and evaluation module five modules. Finally, the Python program was used to verify the test data of about two million pieces of original alarm data in a company's network management database for a consecutive month. The verification results show that the design of this paper has greatly reduced the number of original alarms and completed the merging of related rules.
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McCubbine, Jack, Fabio Caratori Tontini, Vaughan Stagpoole, Euan Smith, and Grant O’Brien. "Gsolve, a Python computer program with a graphical user interface to transform relative gravity survey measurements to absolute gravity values and gravity anomalies." SoftwareX 7 (January 2018): 129–37. http://dx.doi.org/10.1016/j.softx.2018.04.003.
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Michalík, Roman, Aleš Janota, Michal Gregor, and Marián Hruboš. "Human-Robot Motion Control Application with Artificial Intelligence for a Cooperating YuMi Robot." Electronics 10, no. 16 (August 17, 2021): 1976. http://dx.doi.org/10.3390/electronics10161976.
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This paper deals with the application focused on motion control for a cooperating YuMi robot. The use of sensors on gloves or other controls to control robots may restrict both operation of the robot and the operator’s activities. Therefore, research focusing on camera-based monitoring of body parts or hand gestures is becoming increasingly popular. The presented approach is based on using a camera to recognize hand gestures and implementing artificial intelligence to control a YuMi robot with Python using a TCP/IP connection. The program can be expanded by integrating other IoT devices to help control the robot and collect data useful for a needed application.
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Kim, Yewon, and Yongjin Yeom. "Accelerated implementation for testing IID assumption of NIST SP 800-90B using GPU." PeerJ Computer Science 7 (March 8, 2021): e404. http://dx.doi.org/10.7717/peerj-cs.404.
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In cryptosystems and cryptographic modules, insufficient entropy of the noise sources that serve as the input into random number generator (RNG) may cause serious damage, such as compromising private keys. Therefore, it is necessary to estimate the entropy of the noise source as precisely as possible. The National Institute of Standards and Technology (NIST) published a standard document known as Special Publication (SP) 800-90B, which describes the method for estimating the entropy of the noise source that is the input into an RNG. The NIST offers two programs for running the entropy estimation process of SP 800-90B, which are written in Python and C++. The running time for estimating the entropy is more than one hour for each noise source. An RNG tends to use several noise sources in each operating system supported, and the noise sources are affected by the environment. Therefore, the NIST program should be run several times to analyze the security of RNG. The NIST estimation runtimes are a burden for developers as well as evaluators working for the Cryptographic Module Validation Program. In this study, we propose a GPU-based parallel implementation of the most time-consuming part of the entropy estimation, namely the independent and identically distributed (IID) assumption testing process. To achieve maximal GPU performance, we propose a scalable method that adjusts the optimal size of the global memory allocations depending on GPU capability and balances the workload between streaming multiprocessors. Our GPU-based implementation excluded one statistical test, which is not suitable for GPU implementation. We propose a hybrid CPU/GPU implementation that consists of our GPU-based program and the excluded statistical test that runs using OpenMP. The experimental results demonstrate that our method is about 3 to 25 times faster than that of the NIST package.
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Durrant, Jacob D. "BlendMol: advanced macromolecular visualization in Blender." Bioinformatics 35, no. 13 (November 27, 2018): 2323–25. http://dx.doi.org/10.1093/bioinformatics/bty968.
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Abstract Summary Programs such as VMD and PyMOL are excellent tools for analyzing macromolecular structures, but they do not implement many of the advanced rendering techniques common in the film and video-game industries. In contrast, the open-source program Blender is a general-purpose tool for industry-standard rendering/visualization, but its user interface is poorly suited for rigorous scientific analysis. We present BlendMol, a Blender plugin that imports VMD or PyMOL scenes into Blender. BlendMol-generated images are well suited for use in manuscripts, outreach programs, websites and classes. Availability and implementation BlendMol is available free of charge from http://durrantlab.com/blendmol/. It is written in Python. Supplementary information Supplementary data are available at Bioinformatics online.
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Hayes, John A., Eirini Papagiakoumou, Pierre-Louis Ruffault, Valentina Emiliani, and Gilles Fortin. "Computer-aided neurophysiology and imaging with open-source PhysImage." Journal of Neurophysiology 120, no. 1 (July 1, 2018): 23–36. http://dx.doi.org/10.1152/jn.00048.2017.
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Improved integration between imaging and electrophysiological data has become increasingly critical for rapid interpretation and intervention as approaches have advanced in recent years. Here, we present PhysImage, a fork of the popular public-domain ImageJ that provides a platform for working with these disparate sources of data, and we illustrate its utility using in vitro preparations from murine embryonic and neonatal tissue. PhysImage expands ImageJ’s core features beyond an imaging program by facilitating integration, analyses, and display of 2D waveform data, among other new features. Together, with the Micro-Manager plugin for image acquisition, PhysImage substantially improves on closed-source or blended approaches to analyses and interpretation, and it furthermore aids post hoc automated analysis of physiological data when needed as we demonstrate here. Developing a high-throughput approach to neurophysiological analyses has been a major challenge for neurophysiology as a whole despite data analytics methods advancing rapidly in other areas of neuroscience, biology, and especially genomics. NEW & NOTEWORTHY High-throughput analyses of both concurrent electrophysiological and imaging recordings has been a major challenge in neurophysiology. We submit an open-source solution that may be able to alleviate, or at least reduce, many of these concerns by providing an institutionally proven mechanism (i.e., ImageJ) with the added benefits of open-source Python scripting of PhysImage data that eases the workmanship of 2D trace data, which includes electrophysiological data. Together, with the ability to autogenerate prototypical figures shows this technology is a noteworthy advance.
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Javidi, Giti, and Ehsan Sheybani. "Application of Digital Signal Processing in USRP Satellite Signal Detection." International Journal of Interdisciplinary Telecommunications and Networking 9, no. 2 (April 2017): 16–25. http://dx.doi.org/10.4018/ijitn.2017040102.
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The Universal Software Radio Peripheral development technique is designing and implementing radio frequency based systems. The distinctiveness originates from the interchangeable daughterboard within the USRP. The system is designed around the Xilinx Vertex 3 FPGA chip. This means C++, Python, and VHDL can be used to program this device. The project consists of creating a receiver. The objective of the project is to research and comprehend the hardware functionalities of the USRP. The purpose is to create codes in C++ and Python to implement receiving capabilities of the device. The goal of this project was to design a GPS receiver that is capable of recording the L1 signal from a DirecTV satellite. The USRP is used a lot for research. This project consisted of more than just one method. We used GNU Radio Companion and Matlab/Simulink. GNU Radio is open source for building software defined radios. It is also known as GRC. While using GRC the USRP1 was the device used. This software has rapid development. It runs in Ubuntu, a Linux operating system. Within this software there are logic blocks. Each block consists of information to create a flow graph. The flow graph builds and generates the program. Simulink can be compared to GRC. They both have logic blocks that have to be connected to run. Simulink can be used to create a transmitter or a receiver for software radio development and signal processing. Software-defined radio can only be defined if its baseband operations can be completely defined by software. A SDR converts digital to analog signals. The USRP can also convert digital signals from a computer to Radio Frequency Signals (RF). This software is one way to communicate between hardware and software.
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Lehmann, Jannis, Christian Tzschaschel, Manfred Fiebig, and Thomas Weber. "Microdisplays as a versatile tool for the optical simulation of crystal diffraction in the classroom." Journal of Applied Crystallography 52, no. 2 (March 26, 2019): 457–62. http://dx.doi.org/10.1107/s1600576719001948.
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Presented here is a flexible and low-cost setup for demonstrating X-ray, electron or neutron diffraction methods in the classroom. Using programmable spatial light modulators extracted from a commercial video projector, physical diffraction patterns are generated, in real time, of any two-dimensional structure which can be displayed on a computer screen. This concept enables hands-on experience beyond simplest-case scenarios of scattering phenomena, and for the students, the transfer to the regime of visible light greatly enhances intuitive understanding of diffraction in real and reciprocal space. The idea and working principle of the modified video projector are explained, technical advice is given for its choice and successful modification, and a Python-based open-source program code is provided. Program features include the design and interactive manipulation of two-dimensional crystal structures to allow a straightforward demonstration of concepts such as reciprocal space, structure factors, selection rules, symmetry and symmetry violation, as well as structural disorder. This approach has already proved helpful in teaching crystal diffraction to undergraduate students in materials science.
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Semeniuta, Oleksandr, and Petter Falkman. "Event-driven industrial robot control architecture for the Adept V+ platform." PeerJ Computer Science 5 (July 29, 2019): e207. http://dx.doi.org/10.7717/peerj-cs.207.
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Modern industrial robotic systems are highly interconnected. They operate in a distributed environment and communicate with sensors, computer vision systems, mechatronic devices, and computational components. On the fundamental level, communication and coordination between all parties in such distributed system are characterized by discrete event behavior. The latter is largely attributed to the specifics of communication over the network, which, in terms, facilitates asynchronous programming and explicit event handling. In addition, on the conceptual level, events are an important building block for realizing reactivity and coordination. Event-driven architecture has manifested its effectiveness for building loosely-coupled systems based on publish-subscribe middleware, either general-purpose or robotic-oriented. Despite all the advances in middleware, industrial robots remain difficult to program in context of distributed systems, to a large extent due to the limitation of the native robot platforms. This paper proposes an architecture for flexible event-based control of industrial robots based on the Adept V+ platform. The architecture is based on the robot controller providing a TCP/IP server and a collection of robot skills, and a high-level control module deployed to a dedicated computing device. The control module possesses bidirectional communication with the robot controller and publish/subscribe messaging with external systems. It is programmed in asynchronous style using pyadept, a Python library based on Python coroutines, AsyncIO event loop and ZeroMQ middleware. The proposed solution facilitates integration of Adept robots into distributed environments and building more flexible robotic solutions with event-based logic.
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Marotta, Gianluca, Paola Sansoni, Franco Francini, David Jafrancesco, Maurizio De Lucia, and Daniela Fontani. "Structured Light Profilometry on m-PTC." Energies 13, no. 21 (October 29, 2020): 5671. http://dx.doi.org/10.3390/en13215671.
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In concentrating solar systems, it is essential to study the optical losses of the collectors. A fundamental parameter is the intercept factor, namely, the fraction of sunrays reflected by the concentrator that reaches the receiver. Optical profilometry studies the relationship between the collector profile and the intercept factor, which influences the collection efficiency. Profilometric analyses were performed on a micro-parabolic trough collector (m-PTC), with reduced sizes and greater mirror curvature than a usual PTC. The proposed technique projects a luminous pattern (structured light) both on the collector with an opaque covering and on a flat reference plane. Measurement set-up and calibration technique were developed for m-PTC. A program coded in Python analyzed the images and reconstructs the mirror profile. The tilted reference plane was reconstructed using an original geometric model and a calibration procedure. The focal length of each parabolic section was calculated, providing information on surface defects in the mirror. An important parameter obtained was the displacement of the focus of the parabola with respect to the ideal position. Using this value, the intercept factor was estimated to be 0.89. The proposed technique was validated by comparing the results with an independent profilometric study applied to the same m-PTC.
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van der Heijde, Annelies Vandermeulen, Salenbien, and Helsen. "Integrated Optimal Design and Control of Fourth Generation District Heating Networks with Thermal Energy Storage." Energies 12, no. 14 (July 18, 2019): 2766. http://dx.doi.org/10.3390/en12142766.
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In the quest to increase the share of renewable and residual energy sources in our energy system, and to reduce its greenhouse gas emissions, district heating networks and seasonal thermal energy storage have the potential to play a key role. Different studies prove the techno-economic potential of these technologies but, due to the added complexity, it is challenging to design and control such systems. This paper describes an integrated optimal design and control algorithm, which is applied to the design of a district heating network with solar thermal collectors, seasonal thermal energy storage and excess heat injection. The focus is mostly on the choice of the size and location of these technologies and less on the network layout optimisation. The algorithm uses a two-layer program, namely with a design optimisation layer implemented as a genetic algorithm and an optimal control evaluation layer implemented using the Python optimal control problem toolbox called modesto. This optimisation strategy is applied to the fictional district energy system case of the city of Genk in Belgium. We show that this algorithm can find optimal designs with respect to multiple objective functions and that even in the cheaper, less renewable solutions, seasonal thermal energy storage systems are installed in large quantities.
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Shepherd, Jack W., Ed J. Higgins, Adam J. M. Wollman, and Mark C. Leake. "PySTACHIO: Python Single-molecule TrAcking stoiCHiometry Intensity and simulatiOn, a flexible, extensible, beginner-friendly and optimized program for analysis of single-molecule microscopy data." Computational and Structural Biotechnology Journal 19 (2021): 4049–58. http://dx.doi.org/10.1016/j.csbj.2021.07.004.
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Kuziv, Yaroslav Yu. "Software for the numerical solution of first-order partial differential equations." Discrete and Continuous Models and Applied Computational Science 27, no. 1 (December 15, 2019): 42–48. http://dx.doi.org/10.22363/2658-4670-2019-27-1-42-48.
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Partial differential equations of the first order, arising in applied problems of optics and optoelectronics, often contain coefficients that are not defined by a single analytical expression in the entire considered domain. For example, the eikonal equation contains the refractive index, which is described by various expressions depending on the optical properties of the media that fill the domain under consideration. This type of equations cannot be analysed by standard tools built into modern computer algebra systems, including Maple.The paper deals with the adaptation of the classical Cauchy method of integrating partial differential equations of the first order to the case when the coefficients of the equation are given by various analytical expressions in the subdomains G1, . . . , Gk , into which the considered domain is divided. In this case, it is assumed that these subdomains are specified by inequalities. This integration method is implemented as a Python program using the SymPy library. The characteristics are calculatednumerically using the Runge-Kutta method, but taking into account the change in the expressions for the coefficients of the equation when passing from one subdomain to another. The main functions of the program are described, including those that can be used to illustrate the Cauchy method. The verification was carried out by comparison with the results obtained in the Maple computer algebra system.
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Winarno, Agustinus, Sus Lasiyah, Benidiktus Tulung Prayoga, Ignatius Aris Hendaryanto, and Fransiskus Xaverius Sukidjo. "Development of Accuracy Evaluation Method for Open Loop Educational CNC Milling Machine." Jurnal Rekayasa Mesin 12, no. 1 (May 31, 2021): 217. http://dx.doi.org/10.21776/ub.jrm.2021.012.01.23.
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<p>The open-loop educational computer numerical control (CNC) milling machine requires accuracy verification in order to ensure its accuracy and functionality. In this paper, the new verification method is proposed based on the length measurement using the fringe counting of He-Ne laser interferometry. The ideal translation length is defined by the number of electric pulses generated by the micro-stepping driver, while the actual length is measured using He-Ne laser interferometry. In the experimental process, the data of the fringe pattern of the He-Ne laser and the number of electric pulses which drive the stepper motors were simultaneously acquired using an oscilloscope. Hence, the data has been analyzed to obtain the ideal and actual lengths by using an in-house program developed in Python. By comparing the actual translation and ideal length, the accuracy of the educational CNC milling machine has been evaluated to be 50 µm for the length up to 200 mm.</p>
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Sulistyo, Meiyanto Eko, Stephanus Hanurjaya, and Muhammad Danang Prastowo. "Monitoring Print Engine Output Using Arduino and Raspberry Pi." Journal of Electrical, Electronic, Information, and Communication Technology 3, no. 1 (April 30, 2021): 6. http://dx.doi.org/10.20961/jeeict.3.1.49771.
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In the printing industry process, monitoring is necessary for quality control of the product. The making of the tool on this project serves to monitor the output of the production machine. This monitoring is done by detecting the product output from the production machine using Sensor E18 D80NK. When the sensor detects the output, the sensor sends a signal to the Arduino UNO R3 which will calculate the amount of output from the product. Arduino will send information of the number of outputs via a USB connection to a central computer that is a Raspberry Pi 3 model B. The Python program on Raspberry Pi will read input from each Arduino address and display the data in realtime. At the same time, the data will be stored as a text file. This text file contains the number of product output and the time of the output. The prototype of this tool has been successfully created and there is still much development to do.
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GRIMSHAW, ANDREW, MARK MORGAN, and AVINASH KALYANARAMAN. "GFFS — THE XSEDE GLOBAL FEDERATED FILE SYSTEM." Parallel Processing Letters 23, no. 02 (June 2013): 1340005. http://dx.doi.org/10.1142/s0129626413400057.
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Federated, secure, standardized, scalable, and transparent mechanism to access and share resources, particularly data resources, across organizational boundaries that does not require application modification and does not disrupt existing data access patterns has been needed for some time in the computational science community. The Global Federated File System (GFFS) addresses this need and is a foundational component of the NSF-funded eXtreme Science and Engineering Discovery Environment (XSEDE) program. The GFFS allows user applications to access (create, read, update, delete) remote resources in a location-transparent fashion. Existing applications, whether they are statically linked binaries, dynamically linked binaries, or scripts (shell, PERL, Python), can access resources anywhere in the GFFS without modification (subject to access control). In this paper we present an overview of the GFFS and its most common use cases: accessing data at an NSF center from a home or campus, accessing data on a campus machine from an NSF center, directly sharing data with a collaborator at another institution, accessing remote computing resources, and interacting with remote running jobs. We present these uses cases and how they are realized using the GFFS.
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Barreto Bezerra, Alysson Aldrin, Luanda Maria Sousa da Silva, and Antônio Wagner de Lima. "Desenvolvimento de um programa computacional para análise de vigas Euler-Bernoulli utilizando a linguagem Pytho." Revista Principia - Divulgação Científica e Tecnológica do IFPB 1, no. 38 (February 15, 2018): 54. http://dx.doi.org/10.18265/1517-03062015v1n38p54-60.
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Among the many areas of Civil Engineering, there is one known as Structures. In view of the growing sophistication of the constructions, and consequently an increase in the complexity of the calculations involved, auxiliary computational software has been revolutionizing this area. Already present in the professional work of the engineer, this technological support has a direct effect on the teaching and learning process, since many computer programs, some of them difficult to understand by students, are study tools of the disciplines of the Structures area. Among the contents in which the students present more difficulty, there is Finite Element Analysis, a discipline offered on graduation and that had its practical development linked to the advent of computation. By being the method most used as a computational tool in the field of engineering these days, this knowledge is indispensable to the students of this course. The objective of this work is to construct a computational code in order to facilitate the study of linear-elastic behavior of Euler-Bernoulli beams with punctual loads using the Finite Element Analysis. For this, a numerical example was analyzed, with the aid of a program implemented with the Python® language, to reinforce the effectiveness of the program and, consequently, to promote the improvement of student learning.
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Hewelt, Blake, Haiqing Li, Mohit Kumar Jolly, Prakash Kulkarni, Isa Mambetsariev, and Ravi Salgia. "The DNA walk and its demonstration of deterministic chaos—relevance to genomic alterations in lung cancer." Bioinformatics 35, no. 16 (January 7, 2019): 2738–48. http://dx.doi.org/10.1093/bioinformatics/bty1021.
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AbstractMotivationAdvancements in cancer genetics have facilitated the development of therapies with actionable mutations. Although mutated genes have been studied extensively, their chaotic behavior has not been appreciated. Thus, in contrast to naïve DNA, mutated DNA sequences can display characteristics of unpredictability and sensitivity to the initial conditions that may be dictated by the environment, expression patterns and presence of other genomic alterations. Employing a DNA walk as a form of 2D analysis of the nucleotide sequence, we demonstrate that chaotic behavior in the sequence of a mutated gene can be predicted.ResultsUsing fractal analysis for these DNA walks, we have determined the complexity and nucleotide variance of commonly observed mutated genes in non-small cell lung cancer, and their wild-type counterparts. DNA walks for wild-type genes demonstrate varying levels of chaos, with BRAF, NTRK1 and MET exhibiting greater levels of chaos than KRAS, paxillin and EGFR. Analyzing changes in chaotic properties, such as changes in periodicity and linearity, reveal that while deletion mutations indicate a notable disruption in fractal ‘self-similarity’, fusion mutations demonstrate bifurcations between the two genes. Our results suggest that the fractals generated by DNA walks can yield important insights into potential consequences of these mutated genes.Availability and implementationIntroduction to Turtle graphics in Python is an open source article on learning to develop a script for Turtle graphics in Python, freely available on the web at https://docs.python.org/2/library/turtle.html. cDNA sequences were obtained through NCBI RefSeq database, an open source database that contains information on a large array of genes, such as their nucleotide and amino acid sequences, freely available at https://www.ncbi.nlm.nih.gov/refseq/. FracLac plugin for Fractal analysis in ImageJ is an open source plugin for the ImageJ program to perform fractal analysis, free to download at https://imagej.nih.gov/ij/plugins/fraclac/FLHelp/Introduction.html.Supplementary informationSupplementary data are available at Bioinformatics online.
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Suherly, Tomy, and Minarni Shiddiq. "Estimasi Volume Buah Kiwi Menggunakan Metode Pencitraan dan Aturan Simpson." JURNAL MEDIA INFORMATIKA BUDIDARMA 4, no. 3 (July 20, 2020): 535. http://dx.doi.org/10.30865/mib.v4i3.2144.
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Volume is one of important quantities that have been applied to fruit sorting based on size. Imaging method or computer vision is a simple non destructive method that has been proposed to measure fruits volume. This study was aimed to estimate the volumes of kiwi fruits using Computer Vision imaging method and compared to a water displacement method. The samples were 20 green kiwi fruits (Actinidia deliciosa). A smartphone camera was used to record the kiwifruit images and Python based program to drive the camera and process the images. Images resulted in Computer Vision are two dimensions (2D) images. The 1/3 rd Simpson rule was employed to determine the volume of kiwi fruits based on the volume integration of a spinning object where surface image of kiwi was divided into 8 parts and then summed. The results show that the 2D imaging method assisted by the Simpson rule was successfully able to determine the kiwi fruit volumes with 4.57 % average difference percentage compared to the water displacement method. This was about 4.97 cm3 of average volume difference of 20 samples. The sample volumes measured using this method ranges from 82,48 cm3 - 126,85 cm3. These results will be one of steps toward the development of machine vision for fruit sorter based on volume
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Yu, Guoli, Jinge Sang, and Yafei Sun. "Thermal energy diagnosis of boiler plant by computer image processing and neural network technology." Thermal Science 24, no. 5 Part B (2020): 3367–74. http://dx.doi.org/10.2298/tsci191218128y.
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The paper aims to study the identification and diagnosis of infrared thermal fault of airborne circuit board of equipment, expand the application of intelligent algorithm in infrared thermal fault diagnosis, and promote the development of computer image processing technology and neural network technology in the field of thermal diagnosis. Taking the airborne circuit board in the boiler plant as the research object, first, the sequential analysis method was selected to collect the temperature changes during the operation of the circuit board. Second, on the basis of convolutional neural network, the program was written in Python, and the Relu function was used as the activation function establish the thermal fault diagnosis method of the on-board circuit board of the boiler plant equipment based on the convolutional neural network model. Third, based on the support vector machine intelligent algorithm, genetic algorithm was used to optimize the parameters, and combined with the grey prediction model, the infrared thermal fault diagnosis scheme of the circuit board of the multistage support vector machine boiler plant equipment was constructed. The results showed that the accuracy of the model after 6000 iterations was stable between 0.92-0.96, and the loss function value was stable at about 0.17. After the optimization of genetic algorithm, the accuracy of thermal fault diagnosis based on support vector machine model was optimized. Compared with grey prediction model, the accuracy of support vector machine model for fault diagnosis was higher, mean square error value was 0.0258, and the correlation coefficient was 91.55%. To sum up, the support vector machin model shows higher accuracy than grey prediction model, which can be used for thermal fault diagnosis.
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Nekrasova, Irina Ivanovna, Konstantin Vladimirovich Rozov, and Boris Aleksandrovich Schreiner. "Prospects For the Introduction of Artificial Intelligence Technologies in Higher and General Education." Siberian Pedagogical Journal, no. 3 (July 7, 2021): 20–27. http://dx.doi.org/10.15293/1813-4718.2103.02.
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At present, comprehensive research on the implementation of artificial intelligence technologies is of particular relevance. The article is devoted to the implementation of artificial intelligence technologies in the field of education. The perspective directions of using artificial intelligence in the sphere of higher and general education are considered and analyzed. The article actualizes the problem of implementing artificial intelligence technologies in teaching students and schoolchildren. The purpose of the article is to reveal the specifics of the use of artificial intelligence technologies in the field of education. The study is theoretical in nature and includes an analysis of the possibilities of using artificial intelligence technologies at different levels of education. The program of the discipline “Artificial Intelligence Technologies”, developed in the areas of Teacher education training at the Novosibirsk State Pedagogical University, is presented. The possibilities of studying artificial intelligence technologies using the Python language in a school computer science course are considered, which will allow you to move to a new level of learning programming both in schools and in higher education.
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Tseng, Yuan-Wei, Tsung-Wui Hung, Chung-Long Pan, and Rong-Ching Wu. "Motion Control System of Unmanned Railcars Based on Image Recognition." Applied System Innovation 2, no. 1 (March 5, 2019): 9. http://dx.doi.org/10.3390/asi2010009.
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The main purpose of this paper is to construct an autopilot system for unmanned railcars based on computer vision technology in a fixed luminous environment. Four graphic predefined signs of different colors and shapes serve as motion commands of acceleration, deceleration, reverse and stop for the motion control system of railcars based on image recognition. The predefined signs’ strong classifiers were trained based on Haar-like feature training and AdaBoosting from Open Source Computer Vision Library (OpenCV). Comprehensive system integrations such as hardware, device drives, protocols, an application program in Python and man machine interface have been properly done. The objectives of this research include: (1) Verifying the feasibility of graphic predefined signs serving as commands of a motion control system of railcars with computer vision through experiments; (2) Providing reliable solutions for motion control of unmanned railcars, based on image recognition at affordable cost. The experiment results successfully verify the proposed methodology and integrated system. In the main program, every predefined sign must be detected at least three times in consecutive images within 0.2 s before the system confirms the detection. This digital filter like feature can filter out false detections and make the correct rate of detections close to 100%. After detecting a predefined sign, it was observed that the system could generate new motion commands to drive the railcars within 0.3 s. Therefore, both real time performance and the precision of the system are good. Since the sensing and control devices of the proposed system consist of computer, camera and predefined signs only, both the implementation and maintenance costs are very low. In addition, the proposed system is immune to electromagnetic interference, so it is ideal to merge into popular radio Communication Based Train Control (CBTC) systems in railways to improve the safety of operations.
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Sabri, Zaid Saeb, and Zhiyong Li. "Low-cost intelligent surveillance system based on fast CNN." PeerJ Computer Science 7 (February 25, 2021): e402. http://dx.doi.org/10.7717/peerj-cs.402.
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Smart surveillance systems are used to monitor specific areas, such as homes, buildings, and borders, and these systems can effectively detect any threats. In this work, we investigate the design of low-cost multiunit surveillance systems that can control numerous surveillance cameras to track multiple objects (i.e., people, cars, and guns) and promptly detect human activity in real time using low computational systems, such as compact or single board computers. Deep learning techniques are employed to detect certain objects to surveil homes/buildings and recognize suspicious and vital events to ensure that the system can alarm officers of relevant events, such as stranger intrusions, the presence of guns, suspicious movements, and identified fugitives. The proposed model is tested on two computational systems, specifically, a single board computer (Raspberry Pi) with the Raspbian OS and a compact computer (Intel NUC) with the Windows OS. In both systems, we employ components, such as a camera to stream real-time video and an ultrasonic sensor to alarm personnel of threats when movement is detected in restricted areas or near walls. The system program is coded in Python, and a convolutional neural network (CNN) is used to perform recognition. The program is optimized by using a foreground object detection algorithm to improve recognition in terms of both accuracy and speed. The saliency algorithm is used to slice certain required objects from scenes, such as humans, cars, and airplanes. In this regard, two saliency algorithms, based on local and global patch saliency detection are considered. We develop a system that combines two saliency approaches and recognizes the features extracted using these saliency techniques with a conventional neural network. The field results demonstrate a significant improvement in detection, ranging between 34% and 99.9% for different situations. The low percentage is related to the presence of unclear objects or activities that are different from those involving humans. However, even in the case of low accuracy, recognition and threat identification are performed with an accuracy of 100% in approximately 0.7 s, even when using computer systems with relatively weak hardware specifications, such as a single board computer (Raspberry Pi). These results prove that the proposed system can be practically used to design a low-cost and intelligent security and tracking system.
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Nasibullayev, I. Sh. "Application of free software FreeFem++/Gmsh and FreeCAD/CalculiX for simulation of static elasticity problems." Multiphase Systems 15, no. 3-4 (2020): 183–200. http://dx.doi.org/10.21662/mfs2020.3.129.
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The paper discusses the stages of computer numerical simulation of engineering problems and ways to improve the accuracy of simulation; provides a brief overview of free software for simulation elasticity problems by the finite element method, as well as trends in the development of free CAD and CAE software. For a successful engineering study, it is necessary to choose a convenient tool that takes into account all the features of the problem being solved. Based on the solution of a test static problem of linear elasticity, two approaches to engineering modeling were demonstrated. The first approach requires programming skills - the full modeling cycle was written in the programming language of the FreeFem++ software. Additionally, the method mesh generating in the Gmsh program with subsequent use in the FreeFem++ program is shown. In the second approach, the full cycle of modeling is carried out through the interface of the FreeCAD program with the built-in CalculiX solver, which does not require programming skills. A way to parameterize the task using the Python interpreter built into FreeCAD is also proposed. The simulation results obtained using both approaches are compared for an object to which an external action is applied, determined by the Dirichlet or Neumann boundary conditions, and two types of object fastening are analyzed: rigid embedding and limitation by a plane with zero friction. The analysis of the use of computing resources by various direct and iterative methods is carried out. Within the framework of the considered test problem of static linear elasticity, the most optimal method in FreeFem++ is the iterative method of conjugate gradients CG both in terms of computation time and in terms of the memory used. The highest speed of calculations is provided by the Cholesky iterative method with conditioning by the incomplete Cholesky expansion in the CalculiX program.
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Chiriac, Andreea Ioana. "Combining Regression and Clustering for Financial Analysis." Proceedings of the International Conference on Applied Statistics 2, no. 1 (December 1, 2020): 109–18. http://dx.doi.org/10.2478/icas-2021-0010.
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Abstract Artificial Intelligence is used in business through machine learning algorithms. Machine learning is a part of computer science focused on computer systems learning to perform a specific task without using explicit instructions, relying on patterns and inference instead. Though it might seem like we’ve come a long way in the last ten years, which is true from a research perspective, the adoption of AI among corporations is still relatively low. Over time it became possible to automate more tasks and business processes than ever before. The benefit of using artificial intelligence is that does not require to program every step of the process, predicting at each step what could happen and how to resolve it. The algorithms decide for themselves in each case how the problems should be solved, based on the data that is used. I apply Python language to create a synthetic feature vector that allows visualizations in two dimensions for EDIBTA financial ratio. I use Mean-Square Error in order to evaluate the success, having the optimal parameters. In this section, I also mentioned about the purpose, goals, and applications of cluster analysis. I indicated about the basics of cluster analysis and how to do it and also did a demonstration on how to use K-Means.
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Tomski, Andrzej, Marcin Piechota, and Ryszard Przewłocki. "AnnoGene: RESTful Web Service For Annotating Genomic Features." Journal of Applied Computer Science Methods 6, no. 2 (December 1, 2014): 101–10. http://dx.doi.org/10.1515/jacsm-2015-0002.
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Abstract Modern high-throughput sequencing techniques generate a constantly increasing amount of genomic data from eukaryotes. The main problem is quickly identifying the data that may provide information about the nature of intracellular processes, such as the targeting of transcription factor-binding sites. Typically, thousands of peaks or signals are found across the genome and the nearby genes must be annotated. We introduce AnnoGene - a web service for annotating genomic features. AnnoGene was implemented in a representational state transfer (REST) architectural style. The program searches for the gene nearest to the center of a genomic position. Subsequently, the location and annotationsof the gene are shown. The tool can be downloaded and run on a local computer, but it was designed to be a web service. AnnoGene is freely available through a web browser. Moreover, our paper covers examples of the REST clients written in the Python, R and Java programming languages. AnnoGene only requires genomic positions from the user. Even when annotating several thousand positions, the output is typically ready in a few seconds. Moreover, this tool supports Seqinspector – a web tool for finding regulators of the genes.
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Yun, Heuijee, and Daejin Park. "Virtualization of Self-Driving Algorithms by Interoperating Embedded Controllers on a Game Engine for a Digital Twining Autonomous Vehicle." Electronics 10, no. 17 (August 30, 2021): 2102. http://dx.doi.org/10.3390/electronics10172102.
Full textAbstract:
Computer simulation based on digital twin is an essential process when designing self-driving cars. However, designing a simulation program that is exactly equivalent to real phenomena can be arduous and cost-ineffective because too many things must be implemented. In this paper, we propose the method using the online game GTA5 (Grand Theft Auto5), as a groundwork for autonomous vehicle simulation. As GTA5 has a variety of well-implemented objects, people, and roads, it can be considered a suitable tool for simulation. By using OpenCV (Open source computer vision) to capture the GTA5 game screen and analyzing images with YOLO (You Only Look Once) and TensorFlow based on Python, we can build a quite accurate object recognition system. This can lead to writing of algorithms for object avoidance and lane recognition. Once these algorithms have been completed, vehicles in GTA5 can be controlled through codes composed of the basic functions of autonomous driving, such as collision avoidance and lane-departure prevention. In addition, the algorithm tested with GTA5 has been implemented with a programmable RC car (Radio control car), DonkeyCar, to increase reliability. By testing those algorithms, we can ensure that the algorithms can be conducted in real time and they cost low power and low memory size. Therefore, we have found a way to approach digital twin technology one step more easily.