Spelling suggestions: "subject:"[een] ALGORITHMIC"" "subject:"[enn] ALGORITHMIC""
321 |
金融科技與投資產業 : 新商業模式 / Fintech and Investment : New Business Models李齊良, Lee, Chi Liang Unknown Date (has links)
摘要
自2008年金融風暴後,長期的經濟動盪造成顧客喪失對於傳統投資產業之信心。在這樣的環境下,從自動化投資管理、社群交易平台到零售演算法交易的興起,提供低成本與先進的替代方案取代傳統的投資管理產業。這種方式獲得廣大消費者的信賴,並使得顧客擁有更多投資管理之控制權。
本研究欲探討賦權投資者於金融科技的浪潮下,競爭者加入後所面臨之挑戰進行情境分析,了解投資者如何以自動化管理及報告、社群交易平台和零售演算法交易改變投資管理業之發展,並使得傳統以顧問諮詢為主的投資管理興起全自動化或財務顧問協助之新商業模式;再者,透過個案分析,分別探討自動化管理及報告為代表之機器人理財公司以及零售演算法交易平台Quantopian,並建議投資產業應善用金融科技結合兩者,因此,未來顧問所扮演的角色將轉型為從旁協助財務規劃之服務,不僅能夠降低成本,亦可大幅提升理專的效率,為更廣大的客群提供高價值之金融服務。 / Abstract
The 2008 financial crisis was the worst economic disaster since it has caused public losing confidence in traditional investement management industry. As a result, the three key innovation clusters are booming─automated management and advice, retail algorithmic trading and social trading platform─that offer lower-cost and advanced alternatives to replace the traditional investement management industry. Additionally, those innovation clusters gain more trust to the masses and allow customers to control in their own investment portfolio. This study analyzes three scenarios how the empowered investors face the challenges under the new waves of Fintech. In particular, we consider the investment management industry transfer the traditional model to the new business models of fully automation or advisor-assistant. In the case studies, we compare six typical robo-advisor firms and retail algorithmic trading platform like Quantopian. Furthermore, we suggest that the investment industry should make good use of Fintech that combines both advantage of automated management and retail algorithmic trading;therefore, it can not only reduce costs but also improve the efficiency of financial services.
|
322 |
Luteria composicional de algoritmos pós-tonaisSoares, Guilherme Rafael 30 March 2015 (has links)
Submitted by Renata Lopes (renatasil82@gmail.com) on 2015-12-07T16:46:12Z
No. of bitstreams: 1
guilhermerafaelsoares.pdf: 5619162 bytes, checksum: 75fa907e315795bd1f893ed8c941e9bd (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2015-12-07T21:41:38Z (GMT) No. of bitstreams: 1
guilhermerafaelsoares.pdf: 5619162 bytes, checksum: 75fa907e315795bd1f893ed8c941e9bd (MD5) / Made available in DSpace on 2015-12-07T21:41:38Z (GMT). No. of bitstreams: 1
guilhermerafaelsoares.pdf: 5619162 bytes, checksum: 75fa907e315795bd1f893ed8c941e9bd (MD5)
Previous issue date: 2015-03-30 / FAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerais / Esta pesquisa sistematiza um catálogo de experimentos constituído de estudos musicais
e seus algoritmos geradores, organizando procedimentos para composição assistida por
computador orientados por regras derivadas de análises musicais de contexto pós-tonal.
Os procedimentos são inspirados em apontamentos de estudos sobre pós-tonalidade no
compositor Béla Bartók, encontrados nas obras de Lendvai (1971), Antokoletz (1984),
Cohn (1991) e Suchoff (2004). Problematizam-se aqui os conceitos de ciclos intervalares,
eixos de simetria, polimodalismo e peculiaridades de coleções referenciais de classes de
altura - conforme sugestões de Forte (1973), Straus (2004) e Susanni e Antokoletz (2012).
São detalhadas questões computacionais para esta implementação, utilizando como base
as ferramentas OpenMusic e biblioteca Python Music21.
Um legado em código aberto fica disponível para continuidades possíveis deste trabalho. / This research produces a catalog of experiments in musical studies and its related generative
algorithms, organizing procedures for computer aided composition oriented by constraints
extracted from post-tonal musical analyses.
The procedures are inspired by post-tonality studies of Béla Bartók’s music, found in the
works of Lendvai (1971), Antokoletz (1984), Cohn (1991) and Suchoff (2004).
Main focus on problematization of interval cycles, symmetry axis, polymodalism and
peculiarity of referencial collections from pitch-class set theory - as sugested by Forte
(1973), Straus (2004) and Susanni e Antokoletz (2012).
Details of computational issues for the implementation, using the open source tools
OpenMusic and Music21 (python library) as base.
|
323 |
Systèmes d’intelligence artificielle et santé : les enjeux d’une innovation responsable.Voarino, Nathalie 09 1900 (has links)
L’avènement de l’utilisation de systèmes d’intelligence artificielle (IA) en santé s’inscrit dans le cadre d’une nouvelle médecine « haute définition » qui se veut prédictive, préventive et personnalisée en tirant partie d’une quantité inédite de données aujourd’hui disponibles. Au cœur de l’innovation numérique en santé, le développement de systèmes d’IA est à la base d’un système de santé interconnecté et auto-apprenant qui permettrait, entre autres, de redéfinir la classification des maladies, de générer de nouvelles connaissances médicales, ou de prédire les trajectoires de santé des individus en vue d’une meilleure prévention. Différentes applications en santé de la recherche en IA sont envisagées, allant de l’aide à la décision médicale par des systèmes experts à la médecine de précision (ex. ciblage pharmacologique), en passant par la prévention individualisée grâce à des trajectoires de santé élaborées sur la base de marqueurs biologiques.
Des préoccupations éthiques pressantes relatives à l’impact de l’IA sur nos sociétés émergent avec le recours grandissant aux algorithmes pour analyser un nombre croissant de données relatives à la santé (souvent personnelles, sinon sensibles) ainsi que la réduction de la supervision humaine de nombreux processus automatisés. Les limites de l’analyse des données massives, la nécessité de partage et l’opacité des décisions algorithmiques sont à la source de différentes préoccupations éthiques relatives à la protection de la vie privée et de l’intimité, au consentement libre et éclairé, à la justice sociale, à la déshumanisation des soins et du patient, ou encore à la sécurité. Pour répondre à ces enjeux, de nombreuses initiatives se sont penchées sur la définition et l’application de principes directeurs en vue d’une gouvernance éthique de l’IA. L’opérationnalisation de ces principes s’accompagne cependant de différentes difficultés de l’éthique appliquée, tant relatives à la portée (universelle ou plurielle) desdits principes qu’à la façon de les mettre en pratique (des méthodes inductives ou déductives).
S’il semble que ces difficultés trouvent des réponses dans la démarche éthique (soit une approche sensible aux contextes d’application), cette manière de faire se heurte à différents défis. L’analyse des craintes et des attentes citoyennes qui émanent des discussions ayant eu lieu lors de la coconstruction de la Déclaration de Montréal relativement au développement responsable de l’IA permet d’en dessiner les contours. Cette analyse a permis de mettre en évidence trois principaux défis relatifs à l’exercice de la responsabilité qui pourrait nuire à la mise en place d’une gouvernance éthique de l’IA en santé : l’incapacitation des professionnels de santé et des patients, le problème des mains multiples et l’agentivité artificielle. Ces défis demandent de se pencher sur la création de systèmes d’IA capacitants et de préserver l’agentivité humaine afin de favoriser le développement d’une responsabilité (pragmatique) partagée entre les différentes parties prenantes du développement des systèmes d’IA en santé. Répondre à ces différents défis est essentiel afin d’adapter les mécanismes de gouvernance existants et de permettre le développement d’une innovation numérique en santé responsable, qui doit garder l’humain au centre de ses développements. / The use of artificial intelligence (AI) systems in health is part of the advent of a new "high definition" medicine that is predictive, preventive and personalized, benefiting from the unprecedented amount of data that is today available. At the heart of digital health innovation, the development of AI systems promises to lead to an interconnected and self-learning healthcare system. AI systems could thus help to redefine the classification of diseases, generate new medical knowledge, or predict the health trajectories of individuals for prevention purposes. Today, various applications in healthcare are being considered, ranging from assistance to medical decision-making through expert systems to precision medicine (e.g. pharmacological targeting), as well as individualized prevention through health trajectories developed on the basis of biological markers.
However, urgent ethical concerns emerge with the increasing use of algorithms to analyze a growing number of data related to health (often personal and sensitive) as well as the reduction of human intervention in many automated processes. From the limitations of big data analysis, the need for data sharing and the algorithmic decision ‘opacity’ stems various ethical concerns relating to the protection of privacy and intimacy, free and informed consent, social justice, dehumanization of care and patients, and/or security. To address these challenges, many initiatives have focused on defining and applying principles for an ethical governance of AI. However, the operationalization of these principles faces various difficulties inherent to applied ethics, which originate either from the scope (universal or plural) of these principles or the way these principles are put into practice (inductive or deductive methods).
These issues can be addressed with context-specific or bottom-up approaches of applied ethics. However, people who embrace these approaches still face several challenges. From an analysis of citizens' fears and expectations emerging from the discussions that took place during the coconstruction of the Montreal Declaration for a Responsible Development of AI, it is possible to get a sense of what these difficulties look like. From this analysis, three main challenges emerge: the incapacitation of health professionals and patients, the many hands problem, and artificial agency. These challenges call for AI systems that empower people and that allow to maintain human agency, in order to foster the development of (pragmatic) shared responsibility among the various stakeholders involved in the development of healthcare AI systems. Meeting these challenges is essential in order to adapt existing governance mechanisms and enable the development of a responsible digital innovation in healthcare and research that allows human beings to remain at the center of its development.
|
324 |
Problèmes numériques en mathématiques financières et en stratégies de trading / Numerical problems in financial mathematics and trading strategiesBaptiste, Julien 21 June 2018 (has links)
Le but de cette thèse CIFRE est de construire un portefeuille de stratégies de trading algorithmique intraday. Au lieu de considérer les prix comme une fonction du temps et d'un aléa généralement modélisé par un mouvement brownien, notre approche consiste à identifier les principaux signaux auxquels sont sensibles les donneurs d'ordres dans leurs prises de décision puis alors de proposer un modèle de prix afin de construire des stratégies dynamiques d'allocation de portefeuille. Dans une seconde partie plus académique, nous présentons des travaux de pricing d'options européennes et asiatiques. / The aim of this CIFRE thesis is to build a portfolio of intraday algorithmic trading strategies. Instead of considering stock prices as a function of time and a brownian motion, our approach is to identify the main signals affecting market participants when they operate on the market so we can set up a prices model and then build dynamical strategies for portfolio allocation. In a second part, we introduce several works dealing with asian and european option pricing.
|
325 |
Une étude des effets du travail documentaire et collectif sur le développement professionnel des enseignants de mathématiques : apport des concepts d'expérience et de trajectoire documentaires / A study on the effects of documentation work and collective work on the professional development of mathematics : contribution of the concepts of documentational experience and trajectoryDe Moraes Rocha, Katiane 25 June 2019 (has links)
La thèse traite de la construction d’expérience, en France, par les professeurs de mathématiques quand ils interagissent avec les ressources de leur enseignement tout au long de leur carrière. Elle s’intéresse plus particulièrement à l’impact de l’introduction de l’enseignement de l’algorithmique et de la programmation au collège -proposée par la réforme de 2016- sur leur travail documentaire. Pour cette étude, nous proposons un cadre théorique qui s’appuie sur l’approche documentaire du didactique et sur la didactique professionnelle. Nous nous intéressons aux événements (liés au travail individuel et/ou collectif) qui sont porteurs de transformation sur le travail documentaire des enseignants au cours du temps, en introduisant les concepts de trajectoire et d’expérience documentaires. Nous avons développé un cadre méthodologique inspiré des principes de l’investigation réflexive. Nous avons ainsi suivi deux enseignantes (à mi-carrière) au collège :Anna et Viviane. Les deux enseignantes ont été choisies pour leurs profils contrastés par rapport au travail collectif. L’étude met en évidence que les enseignantes interagissent de façon très différente avec les ressources et leurs trajectoires documentaires aident à comprendre ce qui est sous-jacent à ces différences. Enfin, elle met en évidence le potentiel du travail collectif pour le développement professionnel des enseignants, en particulier pour faire face aux changements curriculaires. / The thesis deals with the construction of experience, in France, by mathematics teachers when they interact with the resources of their teaching throughout their career. It is particularly interested in the impact of the introduction of algorithmics and programming -proposed by the 2016 reform -on their documentational work. For this study, we propose a theoretical framework based on the documentational approach to didactics and on the professional didactics. We are interested in events (related to individual and / or collective work) that have the potential to transform teachers’ documentational work over time, introducing the concepts of documentational trajectory and experience. We have developed a methodological framework inspired by the principles of reflective investigation. We followed then two middle schools mid-career teachers: Anna and Viviane. The two teachers were chosen for their contrasted profiles in relation to the collective work. The study highlights that teachers interact in a very different way with resources and their documentational trajectories help to understand what is behind these differences. Finally, it highlights the potential of collective work for the professional development of teachers, in particular to cope with curriculum changes. / A tese trata da construção da experiência por professores de matemática, na França, quando eles interagem com os recursos para preparar o seu ensino durante toda carreira profissional. Ela se interessa particularmente pelo impacto da introdução do ensino de algoritmo e da programação no ensino fundamental -proposta pela reforma de 2016- sobre o trabalho documental dos professores. Para este estudo, propomos um referencial teórico baseado na abordagem documental do didático e da didática profissional. Estamos interessados em eventos (relacionados ao trabalho individual e/ou coletivo) que transformam o trabalho documental dos professores 8 ao longo do tempo, introduzindo para isso os conceitos de trajetória e experiência documentais. Desenvolvemos um quadro metodológico inspirado nos princípios da investigação reflexiva. Nós seguimos assim duas professoras (em meio de carreira) do ensino fundamental: Anna e Viviane. As duas professoras foram escolhidas por seus perfis diferentes em relação ao trabalho coletivo. O estudo mostra que as professoras interagem de forma diferente com os recursos e que suas trajetórias documentais ajudam a entender o que está por trás dessas diferenças. Finalmente, a tese destaca o potencial do trabalho coletivo para o desenvolvimento profissional dos professores, em particular para lidar com as mudanças curriculares
|
326 |
Jaroslavice – sídlo v krajině / Jaroslavice – place in the landscapeŠmejkal, Jiří January 2018 (has links)
The theme of this diploma thesis is the architectural study of the complex of the Farm of 3D Printers in Jaroslavice. The technology of 3D printing at its speed of development has far outweighed the response to its needs. It lacks a new systematically planned building typology corresponding to the requirements of farms. Farms adapt to the spaces. The main aim of the work is to introduce the possibility of turning the situation and adapting the premises to the farms. The thesis follows the urban design of the restructuring of the Jaroslavice landscape elaborated in the previous semester. The project respects established principles at microregion level in the form of emphasis on self-sufficiency, population integrity or the use of current technologies. The land is located on the southern part of Jaroslavice. There are 3 agricultural buildings located on the property, which until 2010, when a photovoltaic power plant was built, operated in conjunction with a neighboring agricultural court. After the power plant was built, the bonds were irreversibly broken. Buildings are in a very poor condition and mutual cooperation no longer works. The existing solution replaces and shows the possibility of using solar energy in a different way. Thus, the construction cartridge works with a hybrid typology where the 3D production area is combined with the maximum solar gains of the photovoltaic panels. Generative methods have been used to design dominantly either for finding a form in terms of achieving maximum solar gains or after verifying the efficiency of the structure. The proposal has several scenarios of possible development. There are four different stages of growth and the linkage of production areas. Printers are able to replicate themselves at such a rate that they can expect rapid growth. The proposal uses controlled growth methods to simulate complex development under the conditions of maximum solar radiation. Visual distraction and overheating are also solved by atypical sunsets on the exterior façade. Thin-film photovoltaic panels are used on the sun, so it is able to produce electricity besides the shield. The energy-efficient shape along with the great advantage of the layout solution, instead of the corridor disposition, is a basic cell on the central plan view. This makes it possible to control and operate more of the machines more efficiently. The production site forwards counts full robot automation.
|
327 |
Gradient-Based Wind Farm Layout OptimizationThomas, Jared Joseph 07 April 2022 (has links) (PDF)
As wind energy technology continues to mature, farm sizes grow and wind farm layout design becomes more difficult, in part due to the number of design variables and constraints. Wind farm layout optimization is typically approached using gradient-free methods because of the highly multi-modal shape of the wind farm layout design space. Gradient-free method performance generally degrades with increasing problem size, making it difficult to find optimal layouts for larger wind farms. However, gradient-based optimization methods can effectively and efficiently solve large-scale problems with many variables and constraints. To pave the way for effective and efficient wind farm layout optimization for large-scale wind farms, we have worked to overcome the primary barriers to applying gradient-based optimization to wind farm layout optimization. To improve model/algorithm compatibility, we adjusted wake and wind farm models, adding more realistic curvature and smoothness to enable optimization algorithms to travel through areas in the design space where they had previously gotten stuck. We reduced the number of function calls required for gradient-based wind farm layout optimization by over three orders of magnitude for large farms by using algorithmic differentiation to compute derivatives. We reduced the multi-modality of the wind farm layout design space using wake expansion continuation (WEC). We developed WEC to work with existing optimization algorithms, enabling them to get out of local optima while remaining fully gradient-based. Across four case studies, WEC found results with lower wake loss, on average, than the other methods we tested. To resolve concerns about optimization algorithms exploiting model inaccuracies, we compared the initial and optimized layouts to large-eddy simulation (LES) results. The simple models predicted an AEP improvement of 7.7% for a low-TI case, and LES predicted 9.3%. For a high-TI case, the simple models predicted a 10.0% improvement in AEP and LES predicted 10.7%. To resolve uncertainty regarding relative solution quality for gradient-based and gradient-free methods, we collaborated with seven organizations to compare eight optimization methods. Each method was managed by researchers experienced with them. All methods found solutions of similar quality, with optimized wake loss between 15.48 % and 15.70 %. WEC with SNOPT was the only purely gradient-based method included and found the third-to-best solution.
|
328 |
Uncontrolled intersection coordination of the autonomous vehicle based on multi-agent reinforcement learning.McSey, Isaac Arnold January 2023 (has links)
This study explores the application of multi-agent reinforcement learning (MARL) to enhance the decision-making, safety, and passenger comfort of Autonomous Vehicles (AVs)at uncontrolled intersections. The research aims to assess the potential of MARL in modeling multiple agents interacting within a shared environment, reflecting real-world situations where AVs interact with multiple actors. The findings suggest that AVs trained using aMARL approach with global experiences can better navigate intersection scenarios than AVs trained on local (individual) experiences. This capability is a critical precursor to achieving Level 5 autonomy, where vehicles are expected to manage all aspects of the driving task under all conditions. The research contributes to the ongoing discourse on enhancing autonomous vehicle technology through multi-agent reinforcement learning and informs the development of sophisticated training methodologies for autonomous driving.
|
329 |
MahlerNet : Unbounded Orchestral Music with Neural Networks / Orkestermusik utan begränsning med neurala nätverkLousseief, Elias January 2019 (has links)
Modelling music with mathematical and statistical methods in general, and with neural networks in particular, has a long history and has been well explored in the last decades. Exactly when the first attempt at strictly systematic music took place is hard to say; some would say in the days of Mozart, others would say even earlier, but it is safe to say that the field of algorithmic composition has a long history. Even though composers have always had structure and rules as part of the writing process, implicitly or explicitly, following rules at a stricter level was well investigated in the middle of the 20th century at which point also the first music writing computer program based on mathematics was implemented. This work in computer science focuses on the history of musical composition with computers, also known as algorithmic composition, using machine learning and neural networks and consists of two parts: a literature survey covering in-depth the last decades in the field from which is drawn inspiration and experience to construct MahlerNet, a neural network based on the previous architectures MusicVAE, BALSTM, PerformanceRNN and BachProp, capable of modelling polyphonic symbolic music with up to 23 instruments. MahlerNet is a new architecture that uses a custom preprocessor with musical heuristics to normalize and filter the input and output files in MIDI format into a data representation that it uses for processing. MahlerNet, and its preprocessor, was written altogether for this project and produces music that clearly shows musical characteristics reminiscent of the data it was trained on, with some long-term structure, albeit not in the form of motives and themes. / Matematik och statistik i allmänhet, och maskininlärning och neurala nätverk i synnerhet, har sedan långt tillbaka använts för att modellera musik med en utveckling som kulminerat under de senaste decennierna. Exakt vid vilken historisk tidpunkt som musikalisk komposition för första gången tillämpades med strikt systematiska regler är svårt att säga; vissa skulle hävda att det skedde under Mozarts dagar, andra att det skedde redan långt tidigare. Oavsett vilket, innebär det att systematisk komposition är en företeelse med lång historia. Även om kompositörer i alla tider följt strukturer och regler, medvetet eller ej, som en del av kompositionsprocessen började man under 1900-talets mitt att göra detta i högre utsträckning och det var också då som de första programmen för musikalisk komposition, baserade på matematik, kom till. Den här uppsatsen i datateknik behandlar hur musik historiskt har komponerats med hjälp av datorer, ett område som också är känt som algoritmisk komposition. Uppsatsens fokus ligger på användning av maskininlärning och neurala nätverk och består av två delar: en litteraturstudie som i hög detalj behandlar utvecklingen under de senaste decennierna från vilken tas inspiration och erfarenheter för att konstruera MahlerNet, ett neuralt nätverk baserat på de tidigare modellerna MusicVAE, BALSTM, PerformanceRNN och BachProp. MahlerNet kan modellera polyfon musik med upp till 23 instrument och är en ny arkitektur som kommer tillsammans med en egen preprocessor som använder heuristiker från musikteori för att normalisera och filtrera data i MIDI-format till en intern representation. MahlerNet, och dess preprocessor, är helt och hållet implementerade för detta arbete och kan komponera musik som tydligt uppvisar egenskaper från den musik som nätverket tränats på. En viss kontinuitet finns i den skapade musiken även om det inte är i form av konkreta teman och motiv.
|
330 |
Poésie de l'ADN : portraits audiovisuels poétiques de l'identité biologique et ésotérique de l’être humainFinck-Beccafico, Barbara 08 1900 (has links)
Le projet artistique Poésie de l’ADN prend source dans une démarche interdisciplinaire, en associant la programmation, la biotechnologie, la création sonore et visuelle, l’ésotérisme ainsi que l’art participatif et performatif. Ce mémoire passe en revue les différentes étapes de réflexion et création autour de ce projet, tout d’abord en le replaçant dans son contexte historique et artistique, à la fois au niveau du courant bioart, puis plus précisément dans l’utilisation de l’acide désoxyribonucléique1 (ADN) en arts. Nous verrons comment s’inscrit Poésie de l’ADN aux côtés des oeuvres d’art génétiques visuelles et sonores, ainsi que de portraiture, tout en présentant les influences artistiques et esthétiques qui inspirent mon travail. Ensuite, ce mémoire aborde trois questionnements qui sont au coeur du développement conceptuel de ce projet : 1) les tensions entre l’aléatoire et la subjectivité, c’est-à-dire la constante négociation entre le contrôle de l’artiste et l’autonomie de la machine; 2) l’interprétation des données afin d’établir la signification que l’on reçoit et apporte à la matière; 3) ainsi que les considérations bioéthiques que soulève ce projet. Puis, le mémoire détaille le processus technique et les outils utilisés, ainsi que le processus créatif au sein duquel l’approche ésotérique est fondamentale. Enfin, nous verrons l’impact des critères ADN sur les oeuvres, ainsi que les portraits qui en découlent. Poésie de l’ADN est un projet artistique qui réunit à la fois le développement d’une application dont l’algorithme et les paramétrages permettent de générer des matières audio-visuelles à partir de données ADN, ainsi que la composition de portraits, à travers l’interprétation artistique, ésotérique et humaine de cette matière, pour créer des vidéomusiques individuelles. / DNA Poetry is an artistic project rooted in an interdisciplinary approach, combining programming, biotechnology, sound and visual creation, esotericism as well as participatory and performative art. This thesis reviews the different stages of reflection and creation around this project, first of all by placing it in its historical and artistic context, first off within the bioart artistic movement, then more precisely within the use of deoxyribonucleic acid (DNA) in the arts. We'll see how DNA Poetry fits alongside visual and audio genetic artworks, as well as portraiture, while showcasing the artistic and aesthetic influences that inspire my work. Then, this thesis addresses three questions which are at the heart of the conceptual development of this project: 1) the tensions between algorithm and subjectivity, that is to say the constant negotiation between the artist's control and autonomy of the machine; 2) data interpretation, in order to establish meaning in what is received and brought to the material; 3) and finally the bioethical considerations raised by this project. Then, the thesis details the technical process and the tools used, as well as the creative process in which the esoteric approach is fundamental. Finally, we will see the impact of DNA data on the audio and visual outcome, as well as the portraits that result from them. DNA Poetry is an artistic project that brings together both the development of an application whose algorithm and mappings make it possible to generate audiovisual material from DNA data, as well as the composition of portraits, through the human, esoteric and artistic interpretation of this material, in order to create individual videomusic art pieces.
|
Page generated in 0.0366 seconds