Relevant bibliographies by topics / GATE, Python

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'GATE, Python'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "GATE, Python"

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Malhotra, Kritika, and Amit Prakash Singh. "Implementation of decision tree algorithm on FPGA devices." IAES International Journal of Artificial Intelligence (IJ-AI) 10, no. 1 (March 1, 2021): 131. http://dx.doi.org/10.11591/ijai.v10.i1.pp131-138.

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<span id="docs-internal-guid-01e673b1-7fff-8dc3-6b99-14ed17cd6b49"><span>Machine learning techniques are rapidly emerging in large number of fields from robotics to computer vision to finance and biology. One important step of machine learning is classification which is the process of finding out to which category a new encountered observation belongs based on predefined categories. There are various existing solutions to classification and one of them is decision tree classification (DTC) which can achieve high accuracy while handling the large datasets. But DTC is computationally intensive algorithm and as the size of the dataset increases its running time also increases which could be from some hours to days even. But thanks to field programmable gate arrays (FPGA) which could be used for large datasets to achieve high performance implementation with low energy consumption. Along with FPGA’s, python is used for accelerating the application development and python is leveraged by using python productivity for zynq (PYNQ), a python development environment for application development. This paper provides the literature review of an implementation of DTC for FPGA devices along with future work that can be done.</span></span>
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Holik, Martin, Tomas Horvath, Vaclav Oujezsky, Petr Munster, Adrian Tomasov, and Sobeslav Valach. "MongoDB Database as Storage for GPON Frames." Sensors 20, no. 21 (October 30, 2020): 6208. http://dx.doi.org/10.3390/s20216208.

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This work is focused on creating an open-source software-based solution for monitoring traffic transmitted through gigabit passive optical network. In this case, the data are captured by the field-programmable gate array (FPGA) card and reassembled using parsing software from a passive optical network built on the International Telecommunication Unit telecommunication section (ITU-T) G.984 gigabit-capable passive optical network GPON recommendation. Then, the captured frames are converted by suitable software into GPON frames, which will be further processed for analysis. Due to the high transfer rate of GPON recommendations, the work describes the issue of writing to the Mongo database system. In order to achieve the best possible results and minimal loss of transmitted frames, a series of tests were performed. The proposed test scenarios are based on different database writing approaches and are implemented in the Python and C# programming languages. Based on our results, it has been shown that the high processing speed is too high for Python processing. Critical operations must be implemented in the C# programming language. Due to rapid application development, Python can only be used for noncritical time-consuming data processing operations.
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Bhat K, Mahesh, and Namita Palecha. "Implementation of a Parallel Fault Simulation System using PODEM in a Hardware Accelerator using Python." Journal of University of Shanghai for Science and Technology 23, no. 06 (June 17, 2021): 530–36. http://dx.doi.org/10.51201/jusst/21/05296.

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VLSI Testing is one of the essential domains in recent times. With the channel length of the transistor decreasing continually, the number of transistors in a chip increases, thus increasing the probability of defects or faults. Automatic Test Pattern Generator is one way to find such input test vectors to the circuit, which will help identify the faults if present. PODEM algorithm is one such algorithm used in this regard. This paper helps in reducing the runtime of this algorithm by the parallelism approach. Different stuck-at faults in the gate level circuit are simulated parallelly.
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Steiger, Damian S., Thomas Häner, and Matthias Troyer. "ProjectQ: an open source software framework for quantum computing." Quantum 2 (January 31, 2018): 49. http://dx.doi.org/10.22331/q-2018-01-31-49.

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We introduce ProjectQ, an open source software effort for quantum computing. The first release features a compiler framework capable of targeting various types of hardware, a high-performance simulator with emulation capabilities, and compiler plug-ins for circuit drawing and resource estimation. We introduce our Python-embedded domain-specific language, present the features, and provide example implementations for quantum algorithms. The framework allows testing of quantum algorithms through simulation and enables running them on actual quantum hardware using a back-end connecting to the IBM Quantum Experience cloud service. Through extension mechanisms, users can provide back-ends to further quantum hardware, and scientists working on quantum compilation can provide plug-ins for additional compilation, optimization, gate synthesis, and layout strategies.
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Sanngoen, Wanayuth, Watcharin Po-Ngaen, Chirot Charitkhuan, and Kitsada Doungjitjaroen. "Development of Parallel Delta Robot System Controller Based on Raspberry Pi and FPGA." Applied Mechanics and Materials 835 (May 2016): 698–704. http://dx.doi.org/10.4028/www.scientific.net/amm.835.698.

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This paper presents a system control design on 2 axes “Delta Industrial Robot”. The control system utilizes both the embedded technology and the “Raspberry Pi" which is a low power consumption PC with open source operating system. The user can communicate with the PC and FPGA (Field Programmable Gate Array) via the system GUI interface. The FPGA acts as dedicated hardware to provide both the efficiency and flexibility for the closed-loop servo control system.To calculate all related kinematics equations for the robot, look up table approach has been implemented to reduce the calculation complexity. Python programs are also implemented to create and search the look up tables. The inverse kinematics is the key to find the position of the robot. A test load of 0.2 kg at the velocity of 2.618 m/s, the S.D. of the end effector’s position of the test result is within 0.06 mm.
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Bocci, Andrea, David Dagenhart, Vincenzo Innocente, Christopher Jones, Matti Kortelainen, Felice Pantaleo, and Marco Rovere. "Bringing heterogeneity to the CMS software framework." EPJ Web of Conferences 245 (2020): 05009. http://dx.doi.org/10.1051/epjconf/202024505009.

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The advent of computing resources with co-processors, for example Graphics Processing Units (GPU) or Field-Programmable Gate Arrays (FPGA), for use cases like the CMS High-Level Trigger (HLT) or data processing at leadership-class supercomputers imposes challenges for the current data processing frameworks. These challenges include developing a model for algorithms to offload their computations on the co-processors as well as keeping the traditional CPU busy doing other work. The CMS data processing framework, CMSSW, implements multithreading using the Intel Threading Building Blocks (TBB) library, that utilizes tasks as concurrent units of work. In this paper we will discuss a generic mechanism to interact effectively with non-CPU resources that has been implemented in CMSSW. In addition, configuring such a heterogeneous system is challenging. In CMSSW an application is configured with a configuration file written in the Python language. The algorithm types are part of the configuration. The challenge therefore is to unify the CPU and co-processor settings while allowing their implementations to be separate. We will explain how we solved these challenges while minimizing the necessary changes to the CMSSW framework. We will also discuss on a concrete example how algorithms would offload work to NVIDIA GPUs using directly the CUDA API.
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Shinde, Piyush N. "Pygame: Develop Games using Python." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 30, 2021): 4442–47. http://dx.doi.org/10.22214/ijraset.2021.35735.

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In this paper, we will present the process of creating a simple game(Dracula) made in Python. For the purposes of this work, we created the game Dracula using the Pygame package. The aim of this paper is to show the process of creating a game, i.e the gradual construction of each element of the game. The game was created in several phases, and we will describe and explain each in detail. We will start from the construction of the basic skeleton of the game, that is. a graphical representation of the background image window. We will gradually introduce and add new elements (heroes, enemies, bullets, levels ...) all the way to a fully built and functional game. We will point out the possibilities and limitations that arise when programming the dracula game.
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Glynatsi, Nikoleta, and Vincent Knight. "Game Theory and Python: An educational tutorial to game theory and repeated games using Python." Journal of Open Source Education 4, no. 39 (May 24, 2021): 78. http://dx.doi.org/10.21105/jose.00078.

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Bandura, K., A. N. Bender, J. F. Cliche, T. de Haan, M. A. Dobbs, A. J. Gilbert, S. Griffin, et al. "ICE: A Scalable, Low-Cost FPGA-Based Telescope Signal Processing and Networking System." Journal of Astronomical Instrumentation 05, no. 04 (December 2016): 1641005. http://dx.doi.org/10.1142/s2251171716410051.

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We present an overview of the ‘ICE’ hardware and software framework that implements large arrays of interconnected field-programmable gate array (FPGA)-based data acquisition, signal processing and networking nodes economically. The system was conceived for application to radio, millimeter and sub-millimeter telescope readout systems that have requirements beyond typical off-the-shelf processing systems, such as careful control of interference signals produced by the digital electronics, and clocking of all elements in the system from a single precise observatory-derived oscillator. A new generation of telescopes operating at these frequency bands and designed with a vastly increased emphasis on digital signal processing to support their detector multiplexing technology or high-bandwidth correlators — data rates exceeding a terabyte per second — are becoming common. The ICE system is built around a custom FPGA motherboard that makes use of an Xilinx Kintex-7 FPGA and ARM-based co-processor. The system is specialized for specific applications through software, firmware and custom mezzanine daughter boards that interface to the FPGA through the industry-standard FPGA mezzanine card (FMC) specifications. For high density applications, the motherboards are packaged in 16-slot crates with ICE backplanes that implement a low-cost passive full-mesh network between the motherboards in a crate, allow high bandwidth interconnection between crates and enable data offload to a computer cluster. A Python-based control software library automatically detects and operates the hardware in the array. Examples of specific telescope applications of the ICE framework are presented, namely the frequency-multiplexed bolometer readout systems used for the South Pole Telescope (SPT) and Simons Array and the digitizer, F-engine, and networking engine for the Canadian Hydrogen Intensity Mapping Experiment (CHIME) and Hydrogen Intensity and Real-time Analysis eXperiment (HIRAX) radio interferometers.
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ABBAS, Yasir M. O., and Kenichi Asami. "Design of Software-Defined Radio-Based Adaptable Packet Communication System for Small Satellites." Aerospace 8, no. 6 (June 4, 2021): 159. http://dx.doi.org/10.3390/aerospace8060159.

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Software-defined radio (SDR) devices have made a massive contribution to communication systems by reducing the cost and development time for radio frequency (RF) designs. SDRs opened the gate to programmers and enabled them to increase the capabilities of these easily manipulated systems. The next step is to upgrade the reconfigurability into adaptability, which is the focus of this paper. This research contributes to improving SDR-based systems by designing an adaptable packet communication transmitter and receiver that can utilize the communication window of CubeSats and small satellites. According to the feedback from the receiver, the transmitter modifies the characteristics of the signal. Theoretically, the system can adopt many modes, but for simplicity and to prove the concept, here, the changes are limited to three data rates of the Gaussian minimum shift keying (GMSK) modulation scheme, i.e., 2400 bps GMSK, 4800 bps GMSK and 9600 bps GMSK, which are the most popular in amateur small satellites. The system program was developed using GNU Radio Companion (GRC) software and Python scripts. With the help of GRC software, the design was simulated and its behavior in simulated conditions observed. The transmitter packetizes the data into AX.25 packets and transmits them in patches. Between these patches, it sends signaling packets. The patch size is preselected. Alternatively, the receiver extracts the data and saves it in a dedicated file. It directly replies with a feedback message whenever it gets the signaling packets. Based on the content of the feedback message, the characteristics of the transmitted signal are altered. The packet rate and the actual useful data rate are measured and compared with the selected data rate, and the packet success rate of the system operating at a fixed data rate is also measured while simulating channel noise to achieve the desired Signal-to-Noise Ratio (SNR).
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Dissertations / Theses on the topic "GATE, Python"

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Vieira, Igor Fagner. "Desenvolvimento de um software para modelagem de tomógrafos por emissão de pósitrons." Universidade Federal de Pernambuco, 2013. https://repositorio.ufpe.br/handle/123456789/10121.

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Submitted by Amanda Silva (amanda.osilva2@ufpe.br) on 2015-03-03T13:37:46Z No. of bitstreams: 2 Dissertacao Igor Fagner Vieira.pdf: 11971580 bytes, checksum: 9b20669e6b9542d3990f183c304ff233 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5)
Made available in DSpace on 2015-03-03T13:37:46Z (GMT). No. of bitstreams: 2 Dissertacao Igor Fagner Vieira.pdf: 11971580 bytes, checksum: 9b20669e6b9542d3990f183c304ff233 (MD5) license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Previous issue date: 2013
CRCN-NE,CNEN e FACEPE
Há uma tendência cada vez mais crescente na comunidade cientifica, ou mesmo dentro das grandes empresas da área médica, de utilizar códigos de transporte das radiações para validar resultados experimentais ou mesmo para projetar novos experimentos e/ou equipamentos. Neste trabalho, um método para modelagem de tomógrafo por emissão de pósitrons utilizando o GATE (Geant4 Application for Tomographic Emission) foi proposto e inicialmente validado. O GATE é uma plataforma internacionalmente reconhecida e utilizada para desenvolvimento de Modelos Computacionais de Exposição (MCE) no contexto da Medicina Nuclear, embora atualmente hajam módulos dedicados para aplicações em Radioterapia e Tomografia Computadorizada (TC). O GATE usa métodos Monte Carlo (MC) e tem uma linguagem de script própria. A escrita dos scripts para simulação de um PET scanner no GATE envolve um conjunto de passos interligados, sendo a acurácia da simulação dependente do arranjo correto das geometrias envolvidas, já que os processos físicos dependem destas, bem como da modelagem da eletrônica dos detectores no módulo Digitizer, por exemplo. A realização manual desse setup pode ser fonte de erros, sobretudo para usuários que não tenham experiência alguma no campo das simulações ou familiaridade prévia com uma linguagem de programação, considerando também o fato de todo este processo de modelagem no GATE ainda permanecer vinculado ao terminal do LINUX/UNIX, um ambiente familiar apenas para poucos. Isso se torna um obstáculo para iniciantes e inviabiliza o uso do GATE por uma gama maior de usuários, interessados em otimizar seus experimentos e/ou protocolos clínicos por meio de um modo mais acessível, rápido e amigável. O objetivo deste trabalho consiste, portanto, em desenvolver um software amigável para modelagens de Tomógrafos por Emissão de Pósitrons, chamado GUIGATE (Graphical User Interface for GATE), com módulos específicos e dedicados a controle de qualidade em PET scanners. Os resultados obtidos exibem os recursos disponíveis no GUIGATE, presentes em um conjunto de janelas que permitem ao usuário criar seus arquivos de entrada (os inputs), executar e visualizar em tempo real o seu modelo, bem como analisar seus arquivo de saída (os outputs) em um único ambiente, viabilizando assim de modo intuitivo o acesso a toda a arquitetura de simulação do GATE e ao analisador de dados do CERN, o ROOT.
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Johnsen, Andreas Lyngstad, and Georgy Ushakov. "[Lecture Games] Python programming game." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-13582.

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Pythia is a programming game that allows the player to change pieces of theirenvironment through use of the programming language Python. The idea is that thegame could be used as a part of teaching simple programming to &#64257;rst year universitystudents. The game should be fun enough for the students to keep playing, teachenough for it to earn a place as a teaching tool, and it should be usable by allstudents. It should also be possible for a teacher to create their own content for thegame.Pythia was implemented by extending the Python-interpreter Jython and building a game around it. The game was rendered using a simple hardware accelerationlibrary. A simple story was invented and there was some research on learning andprogramming in games.A set of levels was made, matching the story and introducing puzzles related tosimple programming. These levels were used in testing to collect data on usability,entertainment, and learning. There were also tests of the performance of the gameon several systems, and an evaluation was made on creating content for the game.The game has potential for being used to teach programming to &#64257;rst yearstudents, as testers found it to be both fun and educational. We do not know if itwould be possible to use it, as it does not currently run on thin clients. If studentscan run it, we feel that it should be possible for teachers to create puzzles thatemulate the teaching goal.
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Laskemoen, Kristian. "Pyception : Teaching Python with a Serious Game." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for datateknikk og informasjonsvitenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-23906.

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This thesis set out to study how an online serious game could affect users? motivation on learning Python. One of the projects core goals is to find out whether learning Python is more motivating when having an effortless start through a web based game. A second goal is to find out if Python as a programming language are well suited for a serious game.After the development and implementation of the game, it was performed a user experiment in order to receive feedback. Data from this user experiment were collected in a questionnaire and the results regarding usability were collected in a System Usability Scale. The results were positive, and indicates that most users were satisfied with the game. Feedback from users indicate that the game was both fun and educational, and more motivating than traditional task solving. However, some changes need to be applied in order to publish this serious game.
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Pelini, Nicholas Michael. "Netlist Security Algorithm Acceleration Using OpenCL on FPGAs." University of Dayton / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1501861339318045.

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Kovařík, Viktor. "IoT systém pro domácnost." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-417285.

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The aim of this thesis was to learn and summarize basic information about IoT systems, which protocols are used and introduction of Google Home system. The first part of the thesis describes the individual parts of the system --- microcontrollers, sensors, light elements and possible systems for backend. In the implementation part of the thesis was designed a solution for smart home controling using Google Home technology. Based on data from the weather station, the system controls and adjusts the intensity of outdoor lighting and controls the blinds. Furthermore, a control module for gate and garage door control is implemented. The system also takes care of vacuum cleaning in the house using iRobot Roomba vacuum cleaners with custom Wi-Fi module. The final part of the thesis summarizes the achieved results.
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Gardini, Lorenzo. "Studio e Sperimentazione di Algoritmi di Reinforcement Learning Applicati a Video Game." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21847/.

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Nella prima parte del mio lavoro viene presentato uno studio di una prima soluzione "from scratch" sviluppata da Andrew Karpathy. Seguono due miei miglioramenti: il primo modificando direttamente il codice della precedente soluzione e introducendo, come obbiettivo aggiuntivo per la rete nelle prime fasi di gioco, l'intercettazione della pallina da parte della racchetta, migliorando l'addestramento iniziale; il secondo é una mia personale implementazione utilizzando algoritmi più complessi, che sono allo stato dell'arte su giochi dell'Atari, e che portano un addestramento molto più veloce della rete.
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Veselá, Cindy. "Terapeutická hra pro měření reakční doby s využitím platformy BITalino." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2020. http://www.nusl.cz/ntk/nusl-413174.

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This master’s thesis focuses on real-time detection of activity in electromyographic signal for reaction time measurement. For patients motivation there was designed and implemented therapeutic car game controlled throught the muscle activity. In this thesis were used three different algorithms for muscles activity detection in EMG signal. The best accuracy of this three methods has designed artificial network with U-Net hierarchy, which is used to segment samples into two categories - samples of signal with activity and samples representing calm. Accuracy of this method is 97 %. Later there were examined differences between groups of probands, different stimulus and the changes of reaction time over time.
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Orazi, Gabriele. "Progettazione e sviluppo di un bot automatico per giochi di strategia su device mobili." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15430/.

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In questa tesi viene discussa l'implementazione di un bot automatico in grado di interfacciarsi ad un device mobile, al fine di controllare autonomamente le fasi di battaglia di un gioco strategico. Il dispositivo in questione viene interamente controllato da un calcolatore esterno tramite l'invio di segnali atti ad emulare in tutto e per tutto quelli di un giocatore reale che sfiora lo schermo touchscreen del device. Inoltre è stata progettata una prima rete neurale con l'intento di riuscire ad ottimizzare le strategie di attacco del bot.
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Jileček, Jan. "Analýza a klasifikace dat ze snímače mozkové aktivity." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403817.

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This thesis aims to implement methods for recording EEG data obtained with the neural activity sensor OpenBCI Ultracortex IV headset. It also describes neurofeedback, methods of obtaining data from the motor cortex for further analysis and takes a look at the machine learning algorithms best suited for the presented problem. Multiple training and testing datasets are created, as well as a tool for recording the brain activity of a headset-wearing test subject, which is being visually presented with cognitive challenges on the screen in front of him. A neurofeedback demo app has been developed, presented and later used for calibration of new test subjects. Next part is data analysis, which aims to discriminate the left and right hand movement intention signatures in the brain motor cortex. Multiple classification methods are used and their utility reviewed.
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Talevi, Luca, and Luca Talevi. "“Decodifica di intenzioni di movimento dalla corteccia parietale posteriore di macaco attraverso il paradigma Deep Learning”." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/17846/.

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Le Brain Computer Interfaces (BCI) invasive permettono di restituire la mobilità a pazienti che hanno perso il controllo degli arti: ciò avviene attraverso la decodifica di segnali bioelettrici prelevati da aree corticali di interesse al fine di guidare un arto prostetico. La decodifica dei segnali neurali è quindi un punto critico nelle BCI, richiedendo lo sviluppo di algoritmi performanti, affidabili e robusti. Tali requisiti sono soddisfatti in numerosi campi dalle Deep Neural Networks, algoritmi adattivi le cui performance scalano con la quantità di dati forniti, allineandosi con il crescente numero di elettrodi degli impianti. Impiegando segnali pre-registrati dalla corteccia di due macachi durante movimenti di reach-to-grasp verso 5 oggetti differenti, ho testato tre basilari esempi notevoli di DNN – una rete densa multistrato, una Convolutional Neural Network (CNN) ed una Recurrent NN (RNN) – nel compito di discriminare in maniera continua e real-time l’intenzione di movimento verso ciascun oggetto. In particolare, è stata testata la capacità di ciascun modello di decodificare una generica intenzione (single-class), la performance della migliore rete risultante nel discriminarle (multi-class) con o senza metodi di ensemble learning e la sua risposta ad un degrado del segnale in ingresso. Per agevolarne il confronto, ciascuna rete è stata costruita e sottoposta a ricerca iperparametrica seguendo criteri comuni. L’architettura CNN ha ottenuto risultati particolarmente interessanti, ottenendo F-Score superiori a 0.6 ed AUC superiori a 0.9 nel caso single-class con metà dei parametri delle altre reti e tuttavia maggior robustezza. Ha inoltre mostrato una relazione quasi-lineare con il degrado del segnale, priva di crolli prestazionali imprevedibili. Le DNN impiegate si sono rivelate performanti e robuste malgrado la semplicità, rendendo eventuali architetture progettate ad-hoc promettenti nello stabilire un nuovo stato dell’arte nel controllo neuroprotesico.
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Books on the topic "GATE, Python"

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Kelly, Sloan. Python, PyGame and Raspberry Pi Game Development. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2517-2.

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Kelly, Sloan. Python, PyGame, and Raspberry Pi Game Development. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4533-0.

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Koivunen-Niemi, Laura. Learn to Create a Waterfall Chart Using Python With Data From Bill and Melinda Gates Foundation (2020). 1 Oliver’s Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications, Ltd., 2021. http://dx.doi.org/10.4135/9781529777680.

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Ahlquist, John. Game development essentials: Game artificial intelligence. Clifton Park, NY: Thomson/Delmar Learning, 2008.

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Game Development Using Python. Mercury Learning & Information, 2019.

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Riley, Sean. Game Programming With Python (Game Development Series). Charles River Media, 2003.

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Game Programming with Python, Lua, and Ruby (Game Development). Course Technology PTR, 2003.

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Kelly, Sloan. Python, PyGame and Raspberry Pi Game Development. Apress, 2016.

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Kelly, Sloan. Python, PyGame, and Raspberry Pi Game Development. Apress, 2019.

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Beginning Game Development with Python and Pygame. Berkeley, CA: Apress, 2007. http://dx.doi.org/10.1007/978-1-4302-0325-4.

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Book chapters on the topic "GATE, Python"

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Kelly, Sloan. "Introducing Python." In Python, PyGame and Raspberry Pi Game Development, 7–21. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2517-2_3.

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Kelly, Sloan. "Introducing Python." In Python, PyGame, and Raspberry Pi Game Development, 11–31. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4533-0_3.

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Kelly, Sloan. "What Is Python?" In Python, PyGame and Raspberry Pi Game Development, 3–5. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-2517-2_2.

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Kelly, Sloan. "What Is Python?" In Python, PyGame, and Raspberry Pi Game Development, 5–9. Berkeley, CA: Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4533-0_2.

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Watkiss, Stewart. "Getting Started with Python." In Beginning Game Programming with Pygame Zero, 11–49. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5650-3_2.

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Hetland, Magnus Lie. "Project 10: Do-It-Yourself Arcade Game." In Beginning Python, 547–67. Berkeley, CA: Apress, 2008. http://dx.doi.org/10.1007/978-1-4302-0634-7_29.

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Hetland, Magnus Lie. "Project 10: Do-It-Yourself Arcade Game." In Beginning Python, 475–93. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-0028-5_29.

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Kinsley, Harrison, and Will McGugan. "Game Object Reference." In Beginning Python Games Development, 265–71. Berkeley, CA: Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-0970-7_13.

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Kinsley, Harrison, and Will McGugan. "Packaging Your Game." In Beginning Python Games Development, 273–75. Berkeley, CA: Apress, 2015. http://dx.doi.org/10.1007/978-1-4842-0970-7_14.

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Elumalai, Aarthi. "Project: Snake Game with Turtle." In Introduction to Python for Kids, 413–44. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6812-4_19.

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Conference papers on the topic "GATE, Python"

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Huang, Sitao, Kun Wu, Hyunmin Jeong, Chengyue Wang, Deming Chen, and Wen-mei Hwu. "PyLog: An Algorithm-Centric Python-Based FPGA Programming and Synthesis Flow." In FPGA '21: The 2021 ACM/SIGDA International Symposium on Field Programmable Gate Arrays. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3431920.3439478.

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Giounanlis, Panagiotis, Elena Blokhina, Imran Bashir, Dirk Leipold, Mike Asker, and Robert Bogdan Staszewski. "A Python-Verilog Toolbox for Modeling of a Hadamard Gate Based on Position-Based CMOS Qubits." In 2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS). IEEE, 2019. http://dx.doi.org/10.1109/icecs46596.2019.8965149.

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Wang, Hong, and Sio-Iong Ao. "Teaching CS1 with Python GUI Game Programming." In IAENG TRANSACTIONS ON ENGINEERING TECHNOLOGIES: Volume 4: Special Edition of the World Congress on Engineering and Computer Science-2009. AIP, 2010. http://dx.doi.org/10.1063/1.3460234.

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Huang, Li-Wen, Li-Wei Chen, and Po-Hsun Cheng. "Board Game Design for Python Programming Education." In 2019 IEEE International Conference on Engineering, Technology and Education (TALE). IEEE, 2019. http://dx.doi.org/10.1109/tale48000.2019.9225988.

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Huang, Li-Wen, Po-Hsun Cheng, and Li-Wei Chen. "Web-based Board Game for Learning Python." In 2021 IEEE World Conference on Engineering Education (EDUNINE). IEEE, 2021. http://dx.doi.org/10.1109/edunine51952.2021.9429144.

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Augusto Ueno Otto, Vítor, Alisson Reinaldo Flores, Manuela Helena Weidmann, Kauan Claudio Elias, Ricardo De la Rocha Ladeira, Aldelir Fernando Luiz, and Adriano Pessini. "Apresentação das Mecânicas de um Jogo Desenvolvido com Arcade." In Computer on the Beach. Itajaí: Universidade do Vale do Itajaí, 2020. http://dx.doi.org/10.14210/cotb.v11n1.p600-603.

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Abstract:
The purpose of this paper is to describe the mechanics and logic ofBombanimal’s creation, a game inspired by the classic Bombermanand created using the Python programming language combinedwith the 2D game development library Arcade. The game has uniquefeatures such as the skills of the characters and its visual theme.As such, the paper discusses how the game was implemented andwhat Arcade classes, methods, and features were used, in order toencourage other programmers to use Arcade on their own games.
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Madrid S., A. "Implementation of quantum game theory simulations using Python." In SPIE Defense, Security, and Sensing, edited by Eric Donkor, Andrew R. Pirich, and Howard E. Brandt. SPIE, 2013. http://dx.doi.org/10.1117/12.2015266.

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Aycock, John, Etienne Pitout, and Sarah Storteboom. "A Game Engine in Pure Python for CS1." In ITICSE '15: Innovation and Technology in Computer Science Education Conference 2015. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2729094.2742590.

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Theethum, Thirada, Attawut Arpornrat, and Sirion Vittayakorn. "Thinkercise: An educational VR game for Python programming." In 2021 18th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON). IEEE, 2021. http://dx.doi.org/10.1109/ecti-con51831.2021.9454730.

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D. Yang, Cheer-Sun, and Jonathan W. Yu. "Using Incremental Worked Examples for Teaching Python and Game Programming Teaching Python with Tkinter and Pygame Modules." In Annual International Conferences on Computer Science Education: Innovation and Technology. Global Science & Technology Forum (GSTF), 2011. http://dx.doi.org/10.5176/2251-2195_cseit11.

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