Hasil untuk "The performing arts. Show business"

Yesica Pamela Muszczynski

El propósito del presente trabajo de investigación será adentrarse en la mirada que se ha construido en torno a la figura de Alfonsina Storni y su poesía en relación a la maternidad, el suicidio y el vínculo con los hombres. Abordaremos el modo en que desde los diversos universos escénicos se elaboró su figura a partir de varios elementos descriptivos que se hacen presentes en sus trabajos poéticos, y que de alguna forma dichos elementos han condicionado el modo de investigarla, ya no como objeto de estudio sino en tanto mujer, no ya como una Mujer escritora en un contexto histórico donde la poesía era enteramente varonil. El punto central al que haremos foco será indagar desde qué miradas teatrales se puede concebir una Alfonsina por fuera del mar y de la blancura como motes que de alguna forma reprimen quién fue, digo además de la poeta del mar, o de la madre soltera, o de la niña que ya en su infancia escribía versos. A partir de la obra Alfonsina y los hombres de Mariano Moro (2012-2019) se nos revela como interrogante ¿Cómo ha sido concebida la figura de Alfonsina en diversas puestas de escena en general y en la obra antes mencionada en particular? y ¿de qué modo- aún en la intención de visibilizar su figura-, sigue operando un dispositivo patriarcal dentro de los textos teatrales? y ¿cómo aquello ha legitimado el modo en que nos apropiamos de una figura que aún en el conocimiento biográfico que tengamos sobre ella, se nos diluye.

Meng Wang, Philipp Görz, Joschua Schilling et al.

Detecting business logic vulnerabilities is a critical challenge in software security. These flaws come from mistakes in an application's design or implementation and allow attackers to trigger unintended application behavior. Traditional fuzzing sanitizers for dynamic analysis excel at finding vulnerabilities related to memory safety violations but largely fail to detect business logic vulnerabilities, as these flaws require understanding application-specific semantic context. Recent attempts to infer this context, due to their reliance on heuristics and non-portable language features, are inherently brittle and incomplete. As business logic vulnerabilities constitute a majority (27/40) of the most dangerous software weaknesses in practice, this is a worrying blind spot of existing tools. In this paper, we tackle this challenge with ANOTA, a novel human-in-the-loop sanitizer framework. ANOTA introduces a lightweight, user-friendly annotation system that enables users to directly encode their domain-specific knowledge as lightweight annotations that define an application's intended behavior. A runtime execution monitor then observes program behavior, comparing it against the policies defined by the annotations, thereby identifying deviations that indicate vulnerabilities. To evaluate the effectiveness of ANOTA, we combine ANOTA with a state-of-the-art fuzzer and compare it against other popular bug finding methods compatible with the same targets. The results show that ANOTA+FUZZER outperforms them in terms of effectiveness. More specifically, ANOTA+FUZZER can successfully reproduce 43 known vulnerabilities, and discovered 22 previously unknown vulnerabilities (17 CVEs assigned) during the evaluation. These results demonstrate that ANOTA provides a practical and effective approach for uncovering complex business logic flaws often missed by traditional security testing techniques.

Ali Nour Eldin, Benjamin Dalmas, Walid Gaaloul

In recent years, there has been a growing interest in the verification of business process models. Despite their lack of formal characterization, these models are widely adopted in both industry and academia. To address this issue, formalizing the execution semantics of business process modeling languages is essential. Since data and process are two facets of the same coin, and data are critical elements in the execution of process models, this work introduces Proving an eXecutable BPMN injected with data, BPMN-ProX. BPMN-ProX is a low-code testing framework that significantly enhances the verification of data-aware BPMN. This low-code platform helps bridge the gap between non-technical experts and professionals by proposing a tool that integrates advanced data handling and employs a robust verification mechanism through state-of-the-art model checkers. This innovative approach combines theoretical verification with practical modeling, fostering more agile, reliable, and user-centric business process management.

Бекеев Н.М.

Актуальность исследования заключается в постановке проблемы эффективности арт-менеджмента как основного условия успешного продвижения современной кинематографии, поскольку арт-менеджмент играет ключевую роль в создании уникального визуального образа и эмоциональной привлекательности кинопродукции. Основные методы исследования включают наблюдение, интервью и анализ литературы. Автор статьи обосновывает, что арт-менеджмент способствует выделению фильма в конкурентной среде за счет создания уникального брендирования и маркетинговых технологий. Визуальные решения, такие как постеры, трейлеры и интерактивные медиа, создают особую атмосферу вокруг фильма, позволяя ему стать частью современной культурной жизни. Технологические инновации (виртуальная реальность, например) открывают новые горизонты для продвижения фильма. Примеры успешного арт-менеджмента автор предлагает видеть в менеджмент-, PR и маркетинг-компаниях фильмов «Париж, я люблю тебя» и «Марсианин», при работе с которыми креативная команда взаимодействовала с аудиторией через социальные сети. В статье приводятся и иные примеры того, как цифровые медиа-платформы дают хорошую возможность поднять роль кинематографа и отдельных произведений в культуре страны.

Tracy Tam, Asha Rao, Joanne Hall

Small businesses are increasingly adopting IT, and consequently becoming more vulnerable to cyber-incidents. Whilst small businesses are aware of the cyber-security risks, many struggle with implementing mitigations. Some of these can be traced to fundamental differences in the characteristics of small business versus large enterprises where modern cyber-security solutions are widely deployed. Small business specific cyber-security tools are needed. Currently available cyber-security tools and standards assume technical expertise and time resources often not practical for small businesses. Cyber-security competes with other roles that small business owners take on, e.g. cleaning, sales etc. A small business model, salient and implementable at-scale, with simplified non-specialist terminologies and presentation is needed to encourage sustained participation of all stakeholders, not just technical ones. We propose a new UML class (Small IT Data (SITD)) model to support the often chaotic information-gathering phase of a small business' first foray into cyber-security. The SITD model is designed in the UML format to help small business implement technical solutions. The SITD model structure stays relevant by using generic classes and structures that evolve with technology and environmental changes. The SITD model keeps security decisions proportionate to the business by highlighting relationships between business strategy tasks and IT infrastructure. We construct a set of design principles to address small business cyber-security needs. Model components are designed in response to these needs. The uses of the SITD model are then demonstrated and design principles validated by examining a case study of a real small business operational and IT information. The SITD model's ability to illustrate breach information is also demonstrated using the NotPetya incident.

Haiyan Hao, Yan Wang

Existing Spatial Interaction Models (SIMs) are limited in capturing the complex and context-aware interactions between business clusters and trade areas. To address the limitation, we propose a SIM-GAT model to predict spatiotemporal visitation flows between community business clusters and their trade areas. The model innovatively represents the integrated system of business clusters, trade areas, and transportation infrastructure within an urban region using a connected graph. Then, a graph-based deep learning model, i.e., Graph AttenTion network (GAT), is used to capture the complexity and interdependencies of business clusters. We developed this model with data collected from the Miami metropolitan area in Florida. We then demonstrated its effectiveness in capturing varying attractiveness of business clusters to different residential neighborhoods and across scenarios with an eXplainable AI approach. We contribute a novel method supplementing conventional SIMs to predict and analyze the dynamics of inter-connected community business clusters. The analysis results can inform data-evidenced and place-specific planning strategies helping community business clusters better accommodate their customers across scenarios, and hence improve the resilience of community businesses.

Frank Schweitzer, Giona Casiraghi

We explore the nonlinear dynamics of a macroeconomic model with resource constraints. The dynamics is derived from a production function that considers capital and a generalized form of energy as inputs. Energy, the new variable, is depleted during the production process and has to be renewed, whereas capital grows with production and decreases from depreciation. Dependent on time scales and energy related control parameters, we obtain steady states of high or low production, but also sustained oscillations that show properties of business cycles. We also find conditions for the coexistence of stable fixed points and limit cycles. Our model allows to specify investment and saving functions for Kaldor's model of business cycles. We provide evidence for an endogenous origin of business cycles if depleting resources are taken into account.

Jiale Liu, Yifan Zeng, Malte Højmark-Bertelsen et al.

Traditional enterprises face significant challenges in processing business documents, where tasks like extracting transport references from invoices remain largely manual despite their crucial role in logistics operations. While Large Language Models offer potential automation, their direct application to specialized business domains often yields unsatisfactory results. We introduce Matrix (Memory-Augmented agent Training through Reasoning and Iterative eXploration), a novel paradigm that enables LLM agents to progressively build domain expertise through experience-driven memory refinement and iterative learning. To validate this approach, we collaborate with one of the world's largest logistics companies to create a dataset of Universal Business Language format invoice documents, focusing on the task of transport reference extraction. Experiments demonstrate that Matrix outperforms prompting a single LLM by 30.3%, vanilla LLM agent by 35.2%. We further analyze the metrics of the optimized systems and observe that the agent system requires less API calls, fewer costs and can analyze longer documents on average. Our methods establish a new approach to transform general-purpose LLMs into specialized business tools through systematic memory enhancement in document processing tasks.

Diederik Aerts, Jonito Aerts Arguēlles, Lester Beltran et al.

Identical systems, or entities, are indistinguishable in quantum mechanics (QM), and the symmetrization postulate rules the possible statistical distributions of a large number of identical quantum entities. However, a thorough analysis on the historical development of QM attributes the origin of quantum statistics, in particular, Bose-Einstein statistics, to a lack of statistical independence of the micro-states of identical quantum entities. We have recently identified Bose-Einstein statistics in the combination of words in large texts, as a consequence of the entanglement created by the meaning carried by words when they combine in human language. Relying on this investigation, we put forward the hypothesis that entanglement, hence the lack of statistical independence, is due to a mechanism of contextual updating, which provides deeper reasons for the appearance of Bose-Einstein statistics in human language. However, this investigation also contributes to a better understanding of the origin of quantum mechanical statistics in physics. Finally, we provide new insights into the intrinsically random behaviour of microscopic entities that is generally assumed within classical statistical mechanics.

Francisco Gutiérrez

En el presente artículo analizaremos la obra Donde se descomponen las colas de los burros de la dramaturga Carolina Vivas, la que puede ser leída como una recepción de la tragedia Antígona. En este sentido, nos interesa presentar la transformación del personaje y su argumento en el contexto latinoamericano, para visualizar cómo la apropiación previa del texto clásico en el continente influye en la obra de la autora colombiana y, a su vez, para destacar los elementos de la tragedia que ella rescata y modifica. Para esto presentaremos un recorrido por diversas las lecturas y recepciones de Antígona, enfatizando las realizadas en Latinoamérica. Estudiaremos todo lo anterior para circunscribir el lugar desde donde se sitúa la reescritura de Carolina Vivas y pensarla como una pieza que, debido a la particular forma en que reescribe el argumento y la figura de Antígona, se configura como un hito en la ya extensa tradición de recepciones de la tragedia de Sófocles en nuestro continente.

Zander Porter

This writing (thinking-feeling) unfolds (an articulation of) contemporary (dis)embodiment through specified glances at the "(post-)internet,” schizoid relationality, and network/device/identity matrices. Technogenetic (and hormonal) play and transductions for transindividuality on the transparency-obfuscation (or personality/anonymity) binaries arrive as psychotherapeutics for symphonic moving-sensing-feeling-thinking-communicating in a potentiated post-neoliberal matrix (networking). Generated is a set of direction-possibilities for a post-internet-bodied world consumed by a hegemony of individualizations and self-captures, desiring instead towards queerer ceremonies and telepathic forms of (care-)presence/therapy for being-together-alone (individuation). The concurrent/included choreographic and research-artistic work 3M0T1NG{n3tw0rk1ng} peeks into a technogenetic xeno-spacetime containing relating (meta-)selves.

Keno K. Bressem, Jens-Michalis Papaioannou, Paul Grundmann et al.

This paper presents medBERTde, a pre-trained German BERT model specifically designed for the German medical domain. The model has been trained on a large corpus of 4.7 Million German medical documents and has been shown to achieve new state-of-the-art performance on eight different medical benchmarks covering a wide range of disciplines and medical document types. In addition to evaluating the overall performance of the model, this paper also conducts a more in-depth analysis of its capabilities. We investigate the impact of data deduplication on the model's performance, as well as the potential benefits of using more efficient tokenization methods. Our results indicate that domain-specific models such as medBERTde are particularly useful for longer texts, and that deduplication of training data does not necessarily lead to improved performance. Furthermore, we found that efficient tokenization plays only a minor role in improving model performance, and attribute most of the improved performance to the large amount of training data. To encourage further research, the pre-trained model weights and new benchmarks based on radiological data are made publicly available for use by the scientific community.

Sonja Blum

Flicker is a coordinated beat which can be superimposed on the brain’s alpha rhythm, through a flickering light source, and is associated with hallucinatory or visionary states of mind. In this experimental piece, I weave ideas and performance into a poetic image and text piece proposing some hypotheses and questions surrounding the relationship of moving bodies, the sun, and eureka moments of visions and dreams of new worlds.

Paula Rojas

Este artículo tiene como objetivo analizar la investigación-creación que cuestiona la problemática de la adaptación de un texto narrativo al teatro al integrar las posibilidades dramatúrgicas que la presencia de las tecnologías digitales ofrece a la escena. Este proceso nos aleja de una adaptación tradicional, adoptando en su lugar una perspectiva intermedial y con ella la idea de la adaptación como conexión. Esta visión acentúa la dinámica, la relación y la reciprocidad entre las obras que dialogan entre sí, en oposición a una visión unidireccional (obra de partida-obra de llegada).  Como parte del trabajo metodológico, se llevan a cabo una serie de laboratorios de investigación escénica en los cuales se crean dispositivos escénicos videográficos, sonoros y espaciales, que son integrados y dan forma al guión dramatúrgico El mundo no se detiene concebido como una escritura intermedial.

Marco Pegoraro, Merih Seran Uysal, David Benedikt Georgi et al.

The real-time prediction of business processes using historical event data is an important capability of modern business process monitoring systems. Existing process prediction methods are able to also exploit the data perspective of recorded events, in addition to the control-flow perspective. However, while well-structured numerical or categorical attributes are considered in many prediction techniques, almost no technique is able to utilize text documents written in natural language, which can hold information critical to the prediction task. In this paper, we illustrate the design, implementation, and evaluation of a novel text-aware process prediction model based on Long Short-Term Memory (LSTM) neural networks and natural language models. The proposed model can take categorical, numerical and textual attributes in event data into account to predict the activity and timestamp of the next event, the outcome, and the cycle time of a running process instance. Experiments show that the text-aware model is able to outperform state-of-the-art process prediction methods on simulated and real-world event logs containing textual data.

Rim Krouk, Fernando Almeida

Society is undergoing many transformations and faces economic crises, environmental, social, and public health issues. At the same time, the Internet, mobile communications, cloud technologies, and social networks are growing rapidly and fostering the digitalization processes of business and society. It is in this context that the shared economy has assumed itself as a new social and economic system based on the sharing of resources and has allowed the emergence of innovative businesses like Airbnb. However, COVID-19 has challenged this business model in the face of restrictions imposed in the tourism sector. Its consequences are not exclusively short-term and may also call into question the sustainability of Airbnb. In this sense, this study aims to explore the sustainability of the Airbnb business model considering two theories which advocate that hosts can cover the short-term financial effects, while another defends a paradigm shift in the demand for long-term accommodations to ensure greater stability for hosts.

Itzel Ibargoyen, Sofía Lans, Matias Arismendi et al.

O texto que apresentamos medita, desde o Uruguay, sobre a práctica do Choque como dispositivo relacional e performático para instalalo na via pública. O Choque e uma práctica corporal híbrida, onde confluim diferentes ritmos que podemos identificar como de raiz africana e que nos permite pensar e acionar ao redor dos mandatos de masculinidade, os corpos normados, a captura do prazer e a festa como potencia coletiva. O texto encara algunas ideias iniciais sobre estes asuntos do ponto de vista de um corpo que soa, grita e se manifesta com palabras. Com a certeza de que é necesario una pesquisa da potencia do común e a relevancia que a danza pode ter nos processos de germinação de otras corporalidades.

Dalmir Rogério Pereira

This article approaches the performance design from a case study of the exhibition project This Building Talks Truly directed by the Republic of North Macedonia and awarded with a Golden Trout of the best project at the Exhibition of Countries and Regions of the 14th edition of the Quadrennial of Prague of Performance Design and Space. The study proposes the problematization of the “public quality of the work” (CORNAGO, 2019) conceived in the form of a situation and / or device in which the strategies for activating space through performance will be analyzed. Specifically in the condition of activity and symbolic gesture inserted in the community social sphere and its displacement to the exhibition space. For the analysis, the concept of theatricality will be used as a reading operator based on the notion of “testimonial theatricality” (CABALLERO, 2016) defined by the author as a strategy capable of making visible and warning processes of deterioration and annihilation of communities in the relationship between subject and space. In this sense, theatricality acts as an expanded device capable of influencing the disposition of behaviors and events located in the context of scenic practices such as social discourse and cultural intervention. Condition that authorizes the theoretical and practical displacement of the perspective of the scene design while aimed at the productions of supposed daily aesthetics, beyond the theater and the arts. The Expository Project acts as a mosaic of overlaps, displacements of languages and situations with the gravitational center as the synthesis event - a long-term community relational program - developed in the occupied Railway Building. In this sense, it is assumed that regardless of cultural, economic and geographical reality, testimonial theatricality as a device, acts as a mechanism that generates liminal spaces capable of suspending, transiting and reorganizing languages and realities in experimental models of “anti-structure” (TURNER, 2013).

Tom Pape

The popularity of business intelligence (BI) systems to support business analytics has tremendously increased in the last decade. The determination of data items that should be stored in the BI system is vital to ensure the success of an organisation's business analytic strategy. Expanding conventional BI systems often leads to high costs of internally generating, cleansing and maintaining new data items whilst the additional data storage costs are in many cases of minor concern -- what is a conceptual difference to big data systems. Thus, potential additional insights resulting from a new data item in the BI system need to be balanced with the often high costs of data creation. While the literature acknowledges this decision problem, no model-based approach to inform this decision has hitherto been proposed. The present research describes a prescriptive framework to prioritise data items for business analytics and applies it to human resources. To achieve this goal, the proposed framework captures core business activities in a comprehensive process map and assesses their relative importance and possible data support with multi-criteria decision analysis.

Partha Konar, Ananya Mukherjee, Abhijit Kumar Saha et al.

We examine simple extension of the standard model with a pair of fermions, one singlet and a doublet, in a common thread linking the dark matter problem with the smallness of neutrino masses associated with several exciting features. In the presence of a small bare Majorana mass term, the singlet fermion brings in a pseudo-Dirac dark matter capable of evading the strong spin-independent direct detection bound by suppressing the dark matter annihilation processes mediated by the neutral current. In consequence, the allowed range of mixing angle between the doublet and the singlet fermions gets enhanced substantially. Presence of the same mass term in association of singlet scalars also elevates tiny but nonzero masses radiatively for light Majorana neutrino satisfying observed oscillation data.