Improvements in both software and curricula have helped introductory computer science courses attract and retain more students. Pythy is one such online learning environment that aims to reduce software setup related barriers to learning Python while providing facilities like course management and grading to instructors. To further enable its goals of being beginner-centric, we want to integrate full support for media-computation-style programming activities. The media computation curriculum teaches fundamental computer science concepts through the activities of manipulating images, sounds and videos, and has been shown to be successful in retaining students and helping them gain transferable knowledge. In this work we tackle the first two installments of the problem namely, supporting image and sound-based media computation programs in Pythy. This involves not only client-side support that enables students to run media-computation exercises in the browser, but also server-side support to leverage Pythy's auto-grading facilities. We evaluated our implementation by systematically going through all 82 programs in the textbook that deal with image and sound manipulation and verifying if they worked in Pythy as-is, while complementing this with unit-tests for full test coverage. As a result, Pythy now supports 65 out of the 66 media-computation methods required for image and sound manipulation on both the client and the server-side, and 81 out of the 82 programs in the media-computation textbook can be executed as-is in Pythy. / Master of Science

Titre de l'écran-titre (visionné le 29 novembre 2023) / L'apprentissage automatique a considérablement progressé dans le domaine de la recherche en neurosciences, mais son application pose des défis en raison des différences entre les principes biologiques du cerveau et les méthodes traditionnelles d'apprentissage automatique. Dans ce contexte, le projet présenté propose NeuroTorch, un pipeline convivial d'apprentissage automatique spécialement conçu pour les neuroscientifiques, afin de relever ces défis. Les objectifs clés de ce projet sont de fournir une librairie d'apprentissage profond adaptée aux neurosciences computationnelles, d'implémenter l'algorithme eligibility trace forward propagation (e-prop) pour sa plausibilité biologique, de comparer les réseaux de neurones continus et à impulsions en termes de résilience, et d'intégrer un pipeline d'apprentissage par renforcement. Le projet se divise en plusieurs parties. Tout d'abord, la théorie des dynamiques neuronales, des algorithmes d'optimisation et des fonctions de transformation d'espaces sera développée. Ensuite, l'attention sera portée sur la conception du pipeline NeuroTorch, incluant l'implémentation de l'algorithme e-prop. Les résultats de la prédiction de séries temporelles d'activité neuronale chez le poisson-zèbre seront présentés, ainsi que des observations sur la résilience à l'ablation des réseaux obtenus. Enfin, une section sera consacrée à l'exploration du pipeline d'apprentissage par renforcement de NeuroTorch et à la validation de son architecture dans l'environnement LunarLander de Gym. En résumé, les modèles à impulsions de NeuroTorch ont atteint des précisions de 96,37%, 85,58% et 74,16% respectivement sur les ensembles de validation MNIST, Fashion-MNIST et Heidelberg. De plus, les dynamiques leaky-integrate-and-fire with explicit synaptic current - low pass filter (SpyLIF-LPF) et Wilson-Cowan ont été entraînées avec succès à l'aide de l'algorithme e-prop sur des données neuronales expérimentales du ventral habenula du poisson-zèbre, obtenant respectivement des valeurs de pVar de 0,97 et 0,96. Les résultats concernant la résilience indiquent que l'application de la loi de Dale améliore la robustesse des modèles en termes d'ablation hiérarchique. Enfin, grâce au pipeline d'apprentissage par renforcement de NeuroTorch, différents types d'agents inspirés des neurosciences ont atteint le critère de réussite dans l'environnement LunarLander de Gym. Ces résultats soulignent la pertinence et l'efficacité de NeuroTorch pour les applications en neurosciences computationnelles. / Machine learning has made significant advancements in neuroscience research, but its application presents challenges due to the differences between the biological principles of the brain and traditional machine learning methods. In this context, the presented project proposes NeuroTorch, a comprehensive machine learning pipeline specifically designed for neuroscientists to address these challenges. The key objectives of this project are to provide a deep learning library tailored to computational neuroscience, implement the eligibility trace forward propagation (e-prop) algorithm for biological plausibility, compare continuous and spiking neural networks in terms of resilience, and integrate a reinforcement learning pipeline. The project is divided into several parts. Firstly, the theory of neural dynamics, optimization algorithms, and space transformation functions will be developed. Next focus will be on the design of the NeuroTorch pipeline, including the implementation of the e-prop algorithm. Results of predicting a time series of neuronal activity in zebrafish will be presented, along with observations on the resilience to network ablations obtained. Finally, a section will be dedicated to exploring the NeuroTorch reinforcement learning pipeline and validating its architecture in the LunarLander environment of Gym. In summary, NeuroTorch spiking models achieved accuracies of 96.37%, 85.58%, and 74.16% on the MNIST, Fashion-MNIST, and Heidelberg validation sets, respectively. Furthermore, the leaky-integrate-and-fire with explicit synaptic current - low pass filter (SpyLIF-LPF) and Wilson-Cowan dynamics were successfully trained using the e-prop algorithm on experimental neuronal data from the ventral habenula of zebrafish, achieving pVar values of 0.97 and 0.96, respectively. Results regarding resilience indicate that the application of the Dale law improves the robustness of models in terms of hierarchical ablation. Lastly, through the NeuroTorch reinforcement learning pipeline, different types of neuroscience-inspired agents successfully met the success criterion in the Gym's LunarLander environment. These results highlight the relevance and effectiveness of NeuroTorch for applications in computational neuroscience.

SQL injection attacks have been a problem since the early 2000s. Even though the issue is well known today, SQL injection vulnerabilities remain to be one of the most common security flaws. Our study looks at open source-projects written in Java and Python to examine the current state of SQL injection vulnerabilities. We take a deeper look into the vulnerabilities' code patterns and discuss suitable prevention methods.The open-source projects were mined from Github. The projects that contained a connection to a relational database were further analyzed with static analysis to find vulnerabilities. A subset of projects was picked out for deeper analysis of the source code. Among 167,644 Java projects that met the selection criteria, 24,416 were identified to have a connection to a relational database. The corresponding figures for Python were 294,637 and 20,994. Notably, concatenation is more prevalent in Java, whereas prepared statements are favored in Python. Additionally, the analysis revealed that the Python projects tended to have more recent updates and a higher number of contributors compared to the Java projects. Moreover, projects employing both prepared statements and concatenation were observed to be larger in size compared to those using only one of these methods or relying on hardcoded queries. With legacy projects and concatenation being more common in Java, it is suggested that Python projects better follow best practices when it comes to SQL injection. Although indications were found that the overall knowledge of SQL injection has increased since 2019, the use of identifier concatenation still is prevalent.

Existem várias linguagens e plataformas que permitem a programação baseada no modelo de atores, uma solução elegante para a programação concorrente proposta há algumas décadas. Segundo esse modelo, implementa-se o programa na forma de uma série de agentes que são executados em paralelo e se comunicam entre si somente por meio da troca de mensagens, sem a necessidade de memória compartilhada ou estruturas tradicionais de sincronização como semáforos e mutexes. Uma das áreas nas quais esse modelo seria particularmente adequado é a programação de aplicações web, isto é, aplicações cujas lógicas de negócios e de dados residem num servidor e que são acessadas pelo usuário por intermédio de um navegador. Porém, existem muitos obstáculos ao desenvolvimento de aplicações desse tipo, entre eles a falta de linguagens e ferramentas que permitam integrar tanto o servidor quanto o cliente (navegador) no modelo de atores, as dificuldades de conversões de dados que se fazem necessárias quando o servidor e o cliente são desenvolvidos em linguagens diferentes, e a necessidade de contornar as dificuldades inerentes aos detalhes do protocolo de comunicação (HTTP). O PAWEB é uma proposta de uma plataforma para o desenvolvimento e execução de aplicações web que fornece a infraestrutura necessária para que tanto o lado cliente quanto o lado servidor do aplicativo hospedado possam ser escritos numa mesma linguagem (Python), e possam criar e gerenciar atores que trocam mensagens entre si,tanto local quanto remotamente, de maneira transparente e sem a necessidade de implementar conversões de dados ou outros detalhes de baixo nível. / There are several programming languages and platforms that allow the development of systems based on the actor model, an elegant solution for concurrent programming proposed a few decades ago. According to this model, the program is implemented in the form of several agents that run concurrently and only communicate amongst themselves through the exchange of messages, without the need for shared memory or traditional synchronization structures such as semaphores and mutexes. One of the areas where this model would be particularly appropriate would be the development of web applications, that is, applications whose business and database logic reside on the server and are accessed by the user by means of a web browser. However, there are several obstacles to the development of this type of application, amongst them the lack of languages and tools that allow for the integration of both the server and the client (browser) into the actor model, data conversion difficulties arising from using different programming languages on the server and the client, and the need to circumvent the inherent difficulties posed by the details of the communications protocol (HTTP). PAWEB is a proposal for an application development and execution platform that supplies the infrastructure needed so that both the server and client sides of the hosted application can be written in the same language (Python) and so that they may create and manage actors that exchange messages with one another, both locally and remotely, in a transparent manner and without the need to implement data conversions or other low-level mechanisms.

A presente pesquisa tem por objetivo desenvolver um sistema automático de detecção de eixos de caminhões a partir de imagens. Para isso, são apresentados dois sistemas automáticos: o primeiro para extração de imagens de caminhões a partir de filmagens de tráfego rodoviário feitas em seis locais de uma mesma rodovia situada no Estado de São Paulo, e o segundo, para detecção dos eixos dos caminhões nas imagens. Ambos os sistemas foram fundamentados em conceitos de Processamento de Imagens e Visão Computacional e o desenvolvimento foi feito utilizando programação em linguagem Python e as bibliotecas OpenCV e SciKit. O salvamento automático das imagens de caminhões foi necessário para a construção do banco de imagens utilizado no outro método: a detecção dos eixos dos veículos identificados. Neste estágio foram realizadas a segmentação da imagem do caminhão, a detecção propriamente dita e a classificação dos eixos. Na segmentação dos veículos, utilizou-se as técnicas de limiarização adaptativa seguida de morfologia matemática e em outra ocasião, o descritor de texturas LBP; enquanto na detecção, a Transformada de Hough. Da análise de desempenho desses métodos, a taxa de salvamento das imagens foi 69,2% considerando todos os caminhões que se enquadraram nos frames. Com relação às detecções, a segmentação das imagens dos caminhões feita utilizando limiarização adaptativa com morfologia matemática ofereceu resultados de 57,7% da detecção do total de eixos dos caminhões e 65,6% de falsas detecções. A técnica LBP forneceu, para os mesmos casos, respectivamente, 68,3% e 84,2%. O excesso de detecção foi um ponto negativo dos resultados e pode ser relacionado aos problemas do ambiente externo, geralmente intrínsecos às cenas de tráfego de veículos. Dois fatores que interferiram de maneira significativa foram a iluminação e a movimentação das folhas e galhos das árvores devido ao vento. Desconsiderando esse inconveniente, derivado dos fatores recém citados, as taxas de acerto dos dois tipos de segmentação aumentariam para 90,4% e 93,5%, respectivamente, e as falsas detecções mudariam para 66,5% e 54,7%. Desse modo, os dois sistemas propostos podem ser considerados promissores para o objetivo proposto. / This research aims to develop an automatic truck axle detection system using images. Two automatic systems are presented: one for the extraction of truck images from road videos recorded in a São Paulo state highway and one for the axle detection on images. Both systems are based on Image Processing and Computational Vision techniques, with using programming in Python and OpenCV and SciKit libraries. The truck image extraction system was necessary for the creation of image base, to be used on the axle detection system. Thereunto, image segmentation, axle detection and classification on images were made. In segmentation was used adaptive threshold technique, followed by mathematical morphology and on another time, LBP texture descriptors; for detection, was used Hough Transform. Performance analysis on these methods wielded 69.2% on image save rate, on trucks entirely framed on the image. About axle detection, the truck image segmentation using a combination of adaptive threshold and mathematical morphology wielded 57.7% on axle detection, whilst achieving 65.6% of false detection. Using LBP wielded, on the same images, 68.3% on axle detection and 84.2% of false detection. These excesses was a negative result and can be related to intrinsic issues on the external road traffic environment. Two main factors affected the result: lighting condition changes and the movement of tree leaves and branches. Disregarding these two factors, the proposed system had 90.4% axle truck detection rate using adaptive threshold and mathematical morphology and 93.5% using LBP, and the false detection, changed for 66.5% e 54.7%. Thus, both proposed systems are considered promising.

O Presente trabalho é o estudo das funcionalidades de um descritor e sua aplicabilidade em análise musical tendo como ponto de partida a obra a Ladainha de Nossa Senhora de Faustino Xavier do Prado. Utilizaremos os intervalos melódicos existentes na Ladainha como padrões para verificar similaridades nos contextos; Brasil, Itália e Portugal. Utilizaremos como ferramenta de busca de padrões o software MelodicMatch e desenvolveremos um software para tratar os resultados obtidos organizando-os em uma proposta metodológica que estará descrita na própria aplicação. / The present work is the study of the features of a descriptor and its use in musical analysis taking as its starting point the work of the Ladainha de Nossa Senhora - Faustino Xavier del Prado. We will use existing melodic intervals in the Ladainha as standards for checking similarities in the contexts; Brazil, Italy and Portugal. We will use as standards search tool MelodicMatch the software and develop software to handle the results organizing them into a methodology that will be described in the application itself.

No ciclo hidrológico, o processo de evapotranspiração (ET) representa a maior percentagem do total de precipitação. As maiores percentagens de ET são encontradas nas zonas ripárias visto a alta disponibilidade hídrica. Embora existam métodos acessíveis para estimativa da ET em zona ripária, como os baseados na flutuação diária do nível piezométrico, poucos estudos têm sido desenvolvidos devido à complexidade teórica da variável, ao elevado custo de equipamentos, e à reduzida largura dessas áreas. Desta forma, o objetivo deste trabalho foi avaliar 10 métodos baseados na flutuação diária do nível piezométrico usando o método de balanço de energia &#8211; Razão de Bowen. Para tal fim, foram construídos cinco poços e uma torre de monitoramento em uma área de zona ripária da bacia hidrográfica do Ribeirão da Onça (Brotas, São Paulo). Os dados dos poços e da torre de monitoramento foram coletados, a cada 15 minutos, no período de, respectivamente, abril de 2018 e junho de 2018, a janeiro de 2019. Para o processamento dos dados, foi feito um programa em linguagem Python. Nos dados do método de balanço de energia Razão de Bowen foram utilizados o critério de propagação de erros para a rejeição de estimativas, e o método de amostragem direta para a posterior reconstrução da série temporal. No período seco e chuvoso, as taxas médias de ET obtidas pelo método de balanço de energia &#8211; Razão de Bowen foram, respectivamente, de 3,62 &#177; 0,93 mm/dia e 5,09 &#177; 2,34 mm/dia. Entre os métodos baseados na flutuação diária do nível piezométrico, o método de Gribovski apresentou as melhores métricas na avaliação (<font style=\"text-decoration: overline;\"> &#961; = 0.69, <font style=\"text-decoration: overline;\"> &#964;s = 0.55, <font style=\"text-decoration: overline;\"> MAE = 1.77 mm/dia, <font style=\"text-decoration: overline;\"> RMSE = 2.07 mm/dia e <font style=\"text-decoration: overline;\"> MBE = 1.63 mm/dia), o qual mostra o potencial desse tipo de métodos para estimar a ET em zonas ripárias. / Evapotranspiration rate (ET) represents a significant percentage of precipitation in the water balance. At the riparian zones, ET slightly increases due to high water availability. Although there are available methods to ET estimation, such as the based on groundwater level variation, few studies have developed because of theorical complexity, high equipment cost and narrow band of the riparian zones. Thus, this work aims to evaluate 10 groundwater level variation methods using the energy balance &#8211; Bowen ratio method. For that, five wells and one monitoring tower were installed in a riparian zone of the Onça Creek basin (Brotas, São Paulo, Brazil). Data from wells and monitoring tower were collected at each 15 minutes from, respectively, April/2018 and June/2018 to January/2019. For data processing, a Python languague programme was developed. Error propagation method was applied to reject unreliable estimation of ET. Also, direct sampling was used to temporal serie rebuilding. The ET estimations from Bowen ration method range from 3,62 &#177; 0,93 mm/day and 5,09 &#177; 2,34 mm/day (dry and wet period, respectively). Among the groundwater level variation methods, the Gribovski method reached the smallest error (<font style=\"text-decoration: overline;\"> &#961; = 0.69, <font style=\"text-decoration: overline;\"> &#964; s = 0.55, <font style=\"text-decoration: overline;\"> MAE = 1.77 mm/day, <font style=\"text-decoration: overline;\"> RMSE = 2.07 mm/day e <font style=\"text-decoration: overline;\"> MBE = 1.63 mm/day). Then, the Griboski method may be used to ET estimation in riparian zones.

A técnica de análise por ativação com nêutrons instrumental tem sido amplamente utilizada pelo Laboratório de Ativação Neutrônica (LAN) do IPEN, com emprego do método comparativo, utilizando-se como fonte de nêutrons o reator de pesquisa do tipo piscina IEA-R1, do Instituto de Pesquisas Energéticas e Nucleares (IPEN). Neste método uma amostra é irradiada, simultaneamente, com um padrão do elemento a ser determinado. Para contornar a dificuldade de uma análise multielementar, por ser necessário preparar vários padrões, foi desenvolvido o método k0 de ativação neutrônica. No método k0 a concentração dos elementos de interesse da amostra é calculada em relação a um elemento comparador, geralmente o ouro. Todavia, esse método requer, com precisão, a eficiência de detecção no intervalo de energia de interesse e na geometria do arranjo experimental. Para contornar o tratamento manual dos dados em planilhas eletrônicas, passíveis de incidência de erros, foi desenvolvido, então, um software web, com acesso de qualquer dispositivo com Internet, livre, para calibração da eficiência absoluta de detectores do tipo HPGe. Utilizou-se a linguagem de programação Python, livre, de baixa curva de aprendizagem e padronizada no projeto eScience, a qual o referido software faz parte, e o framework web Django. No sistema é possível realizar todos os cadastros das informações utilizadas no cálculo da eficiência. Além de calcular a eficiência, o sistema plota o gráfico com os pontos da eficiência, linha de regressão, com possibilidade de ajustes, e barra de erro representando as incertezas. Como parte integrante do projeto e-science, o software emite relatórios referentes aos dados dos espectros e da eficiência, permitindo seu compartilhamento. / The technique of instrumental neutron activation analysis has been widely used by IPEN\'s Neutron Activation Laboratory (LAN), using the comparative method, using the IEA-R1 pool-type research reactor as the neutron source Energy and Nuclear Research (IPEN). In this method a sample is simultaneously irradiated with a pattern of the element to be determined. In order to overcome the difficulty of a multielementary analysis, because it isnecessary to prepare several standards, the k0 method of neutron activation was developed. In method k0 the concentration of the elements of interest of the sample is calculated in relation to a comparator element, generally gold. However, this method accurately requires the detection efficiency in the energy range of interest and the geometry of the experimental arrangement. In order to circumvent the manual processing of the data in electronic spreadsheets, which could lead to errors, a web software was developed with access from any free Internet device for calibration of the absolute efficiency of HPGe type detectors. It was used the free and low learning curve, Python programming language, standardized in the eScience project, to which the software is part, and the Django web framework. In the softwareit is possible to carry out all the registers of the information used in the calculation of the efficiency. In addition to calculating efficiency, the software plots the graph with the efficiency points, regression line, with possibility of adjustments, and error bar representing the uncertainties. As part of the e-science project, the software issues reports on spectra and efficiency data, allowing it to share.

pyAXL ist eine Programmierschnittstelle (API) zur Steuerung des "Cisco Call Manager", eine enterprise-VoIP-Verwaltung. Der Vortrag zeigt, wie pyAXL aufgebaut ist. An ein paar Beispielen wird die Verwendung von pyAXL demonstriert.

This report discusses network automation primarily with Ansible. Ansible is a software from Red Hat that can be used for network automation. The report also goes through YAML which is a standardized way of exchanging data, Jinja2 that is a templating language, Python as well as the security with Ansible. The report also goes through why network automation is needed as well as how much time might be saved with Ansible. Ansible ships with modules for Cisco IOS such as ios_config and ios_command and for Cisco ASA asa_config, asa_command and asa_acl as well as many other modules for Arista, Juniper and for other vendors. Ansible can use new APIs by creating new modules for handling that particular API, which means that the only change needed in the playbooks is to change the module name. Ansible can handle NETCONF API using the netconf_config module or various Juniper modules. Ansible is used in this report to perform certain tasks such as to adding VLAN's, close ports on ASA's, audit network devices configuration as well as to create network diagram using the information from CDP. Ansible can be made as secure as manually doing the tasks except that Ansible can do it faster and more consistently.  For connecting to normal Linux servers Ansible uses OpenSSH which is a default SSH client on most Linux systems and for connecting to network devices it uses Paramiko. The security in Ansible depends on SSH and may or may not have passwords stored locally, Ansible can be as secure as the administrator wants it to be such as using RSA key-pair to authenticate, using vault encrypted credentials or asking the administrator about which username and password to use. Using Ansible network automation can save time, the amount saved depends on what is being done, how many devices it is doing it on as well as how the playbook is written. / Rapporten behandlar nätverksautomation primärt i Ansible. Ansible är en mjukvara från Red Hat som kan användas för nätverksautomering. Rapporten går igenom YAML som är ett sätt att standardisera överförning av data, Jinja2 som är ett mallspråk, Python samt säkerheten i Ansible. Rapporten går dessutom igenom varför vi ens vill ha nätverksautomation och hur mycket tid som möjligtvis kan sparas. Ansible kommer med moduler för Cisco IOS som exempelvis ios_config och ios_command och för Cisco ASA finns moduler så som asa_config, asa_command och asa_acl. För andra tillverkare så finns det moduler för Arista, Juniper och för andra leverantörer. Om en ny API kommer ut för en ny enhet så kan en ny Ansible modul skapas som använder denna, vilket betyder att Ansible playbooks kan då använda sig av de nya modulerna med samma struktur som tidigare. Ansible kan hantera NETCONF API med hjälp av netconf_config modulen och av flertalet Juniper moduler. Ansible kan användas på ett lika säkert sätt som manuellt arbete, med undantag på att Ansible gör det snabbare och mer konsekvent. För uppkoppling till vanliga Linux-servrar så använder Ansible OpenSSH klienten som standard och mot nätverksenheter utan Python installerat så används Python biblioteket Paramiko. Ansible använder sig av SSH och kan ha lösenord sparat i playbooken, utanför i annan fil, i ett krypterat vault, fråga användaren som användarnamn och lösenord samt autentisering med hjälp av RSA nycklar. Ansible används för att skapa olika VLAN, stänga portar på en ASA, granska nätverksenhetens konfiguration gentemot vad den borde ha för konfiguration samt för att skapa nätverksdiagram baserat på informationen från CDP. Genom att använda sig av Ansible nätverksautomation så kan tid sparas, hur mycket beror helt på vad som ska göras, hur många enheter det ska göras på samt hur playbooken faktiskt är skapad.