The rapid digitalization of financial processes, coupled with increasing regulatory complexity, cyber risks, and economic volatility, has exposed the limitations of traditional accounting automation systems that rely on static rules and retrospective analysis. In response, this paper proposes an interdisciplinary framework for the development of intelligent accounting automation systems that integrate predictive risk analytics (PRA) and dynamic internal control mechanisms (DICM). Drawing on advances in artificial intelligence, machine learning, data analytics, and governance theory, the study synthesizes existing literature to illustrate how accounting systems can transition from reactive compliance tools to proactive, adaptive decision-support infrastructures. The framework emphasizes real-time risk prediction, continuous learning, automated control adaptation, and ethical governance as core design principles. Through sectoral illustrations from finance, healthcare, and technology-driven supply chains, the paper demonstrates how intelligent accounting systems enhance fraud detection, regulatory compliance, and operational resilience in high-risk economic environments. The study contributes to accounting and information systems research by providing a structured conceptual foundation for next-generation accounting automation and highlighting practical integration strategies that align technological innovation with transparency, accountability, and sustainable value creation.
This review of Graphic Refuge: Visuality and Mobility in Refugee Comics, co-written by Dominic Davies and Candida Rifkind, with a preface by Vinh Nguyen (2025), places the book in the wider political and social context of recent policies against immigrants and refugees in the United States and Europe, and in the broader context of scholarly work on memory studies, visual studies, and critical refugee studies. The author provides an overview of the main themes, critical concepts, and primary sources approached by Davies and Rifkind, and argues that the book successfully engages with previous scholarship to foster new perspectives on refugeetude.
Drawing. Design. Illustration, Literature (General)
Markets are shaped by innovation and choice. Drawing upon advances in the scientific study of awe, in this article I present a model that details how experiences of this emotion shape innovation and choice. I first detail the latest science on awe, which finds it to be distinct from closely related states, like beauty, interest, admiration, and fear, and that orients individuals to rigorous, systems‐based, meaning‐making thought, and actions that enhance social integration. I then summarize how awe leads to a mental state of wonder and curiosity, a fertile ground for the creation of cultural forms through acts of innovation. As illustrations, I consider how awe leads to creative representation, symbolic expression, ritualization, and object design. To the extent that these cultural creations are touched by awe, I then reason, they will fare well in terms of choice, a process whose discussion is the concern in the last section of this article.
Background/Objectives: Artificial intelligence (AI) has attracted great interest due to its applicability in many fields. The adoption of visual illustration techniques produced by AI in the field of graphic design has further expanded the field of use of this technology. This study focuses on foot anatomy illustrations generated by Adobe Firefly and Microsoft Designer Image Creator applications, evaluating them based on detail, clarity, anatomical realism, accuracy, and aesthetic appeal. Methods: The illustrations were created using text-based scripts, and five anatomists compared them to traditional illustrations from the Sobotta Atlas of Human Anatomy. Results: Fleiss’ Kappa statistic was used to analyze consistency among expert evaluations. For the four figures generated by both AI applications, Fleiss’ Kappa agreement was high. Adobe Firefly performed slightly better in illustrating phalanx and ankle bones, but its anatomical accuracy was lower for tarsal and metatarsal bones. Microsoft Designer Image Creator excelled in illustrating metatarsal bones, while its tarsal and phalanx illustrations were less anatomically accurate than Adobe Firefly and the atlas drawings. Both programs showed average realism in ankle structures, while the tarsal bones had low realism. Conclusions: Artificial intelligence applications within the scope of the study showed fast performance. Aesthetic appeal is dominant at first glance in the resulting drawings. In general, both applications have struggled to reflect anatomical reality.
This article examines the evolving legal framework of cross-border transactions against the backdrop of shifting international regulations and diminishing traditional notions of state sovereignty. Drawing upon doctrinal analysis and a comparative perspective, it explores how emerging global governance structures, regional integration mechanisms, and soft-law instruments influence the design and implementation of transnational deals. Key areas of focus include the choice of corporate structures (holdings, SPVs, joint ventures), compliance with anti-corruption and tax regulations, and the strategic use of dispute resolution clauses, particularly in a context where national, supranational, and private regulatory regimes increasingly overlap. Empirical illustrations from Europe, North America, and Asia underscore the growing role of borderland cooperation and subnational initiatives in shaping cross-border transactions. The analysis highlights the need for practitioners to adapt contractual mechanisms in light of complex global norms and offers a multi-level approach to legal and regulatory compliance. Ultimately, the article argues that success in cross-border endeavors depends on integrating national law with transnational standards, leveraging innovative dispute resolution processes, and proactively engaging with local/regional stakeholders to foster legal certainty and minimize risk.
Agency theory provides a critical framework for analysing the contractual relationship between principals, such as shareholders, and agents, including managers and executives. While agents are entrusted to act in the best interests of principals, conflicts frequently arise due to divergent objectives, information asymmetry, and differing risk appetites. These agency conflicts generate monitoring costs, reduce accountability, and threaten organisational performance. This paper adopts a conceptual research design, drawing on secondary sources including academic literature, regulatory frameworks, professional standards, and case studies from global and Nigerian contexts. Through a thematic analysis, it explores the evolution of agency theory, examines mechanisms traditionally used to mitigate principal–agent conflicts, and emphasises the unique role of internal audit as a governance safeguard. The findings highlight that internal audit reduces information asymmetry, lowers monitoring costs, and enhances transparency and accountability, thereby aligning managerial actions with shareholder interests. Case illustrations, such as Enron, WorldCom, and Cadbury Nigeria, demonstrate how weak internal audit functions exacerbate agency problems. The paper contributes by integrating internal audit directly into the agency theory framework and concludes with recommendations for strengthening audit independence, embedding risk management practices, and adapting audit functions to emerging governance challenges.
“Could it be that theory in and of architecture could take up residence in territories that are perforce ill-defined and indeterminate?” David Leatherbarrow, “Foreword,” in The Contested Territory of Architectural Theory, edited by Elie G. Haddad (Routledge, 2023), xxii. This essay charts the implementation of an affective drawing practice, with the aim of registering and gaining greater insight into the premise that a dialogue, or ‘correspondence’, exists between building and occupant. Working within the domains of intuition, unknowing and affect these works employ analogue and digital strategies – drawings-on-glass, writing, scanning, projecting, and filmic sketches – to determine the ineffable, abstract qualities and traces of previous occupancies that could be crucial to the locus of a specific place. Through these studies, we begin to re-witness echoes of actions and habitual patterns of movement around and through a former joinery workshop. The act of casually cleaning a paintbrush is revealed by paint on the timber-lapped walls, a gentle curve deeply worn into a stone threshold sculpted over time shows where so many feet have passed. The transient daylight, and the enfolding darkness of night, are subtlety registered and find potential in the abstract marks of architectural representations. Speculative enquiries begin to unfold, and in so doing they reveal unchartered territories and unforeseen possibilities, proposing new perceptions of being and meaning within this utilitarian and modest space. Read the full article online at: https://drawingon.org/Issue-04-01-Affective-Drawing
Ferdinand Wöhr, Simon Königs, Max Stanglmeier
et al.
Analysing hierarchical design processes is difficult due to the technical and organizational dependencies spanning over multiple levels. The V-Model of Systems Engineering considers multiple levels. It is, however, not quantitative. We propose a model for simulating hierarchical product design processes based on the V-Model. It includes, first, a product model which structures physical product properties in a hierarchical dependency graph; second, an organizational model which formalizes the assignment of stakeholder responsibility; third, a process model which describes the top-down and bottom-up flow of design information; fourth, an actor model which simulates the combination of product, organization and process by using computational agents. The quantitative model is applied to a simple design problem with three stakeholders and three separate areas of responsibility. The results show the following phenomena observed in real-world product design: design iterations occur naturally as a consequence of the designers’ individual behaviour; inconsistencies in designs emerge and are resolved. The simple design problem is used to compare point-based and interval-based requirement decomposition quantitatively. It is shown that development time can be reduced significantly by using interval-based requirements if requirements are always broken down immediately.
Publishing in premier journals is a multifaceted challenge that requires not only conducting impactful research but also mastering the art of scholarly writing. This article offers a comprehensive guide, specifically tailored for quantitative research, a dominant methodology in premier journals. The guide systematically navigates through each section of a quantitative research paper—title, abstract, keywords, introduction, literature review, methodology, results, discussion, conclusion, and references—providing clear, actionable advice. Drawing from a research publication in a Q1‐ranked journal as an illustration, this guide elucidates the nuances of constructing an engaging and rigorous quantitative research paper. The guide also delves into the expectations of editors and reviewers, offering innovative strategies and insights to enhance the clarity, coherence, and persuasiveness of submissions. Designed to resonate deeply with quantitative scholars, this guide empowers researchers to craft research papers that not only align but surpass the expectations of premier journals.
El presente artículo explora el fenómeno del consumo identitario y la importancia de considerar, en el diseño de producto, las distintas posibilidades de inclusión de valores de distinta índole. Se aleja de una visión exclusiva del diseño como una disciplina configuradora con base en el binomio forma-función. Este trabajo expone la relevancia de dotar de identidad a los productos y, con ello, la posibilidad de creación de significados, al profundizar en la clasificación de valores de consumo- culturales, experienciales y racionales-. Esto se hace a través de ejemplos y casos prácticos que demuestran la importancia de emplear la identidad como un activo importante de consumo.
Design practice traditionally focused on human concerns, either overseeing the various effects of climate issues on nonhuman stakeholders or considering them as resources to address these problems. The climate crisis's urgency demands a design shift towards sustainability and inclusivity. This shift was happening through an emerging theme in design, More-Than-Human (MTH), which expands the notion of the user to animals, things, nature, and microbes. Such an expansion creates a requirement for designers to consider nonhuman perspectives during the design process. This paper investigates the methods used in MTH Design studies to explore and synthesize the perspectives of nonhuman users. Reviewing 30 papers, it highlights a predominant focus on animals and things over plants and microbes in MTH studies, along with a scarcity of synthesis methods. It identifies the necessity of tools that represent nonhumans with their relationships within larger ecosystems, and calls for increased attention to plants and microbes, emphasizing their vital role in sustainable environments and urging researchers to develop methods for understanding these species. By highlighting method strengths and weaknesses, it aims to guide designers and design researchers who plan to work with nonhuman users in selecting appropriate methods.
The field of quickest change detection (QCD) concerns design and analysis of algorithms to estimate in real time the time at which an important event takes place, and identify properties of the post-change behavior. It is shown in this paper that approaches based on reinforcement learning (RL) can be adapted based on any "surrogate information state" that is adapted to the observations. Hence we are left to choose both the surrogate information state process and the algorithm. For the former, it is argued that there are many choices available, based on a rich theory of asymptotic statistics for QCD. Two approaches to RL design are considered: (i) Stochastic gradient descent based on an actor-critic formulation. Theory is largely complete for this approach: the algorithm is unbiased, and will converge to a local minimum. However, it is shown that variance of stochastic gradients can be very large, necessitating the need for commensurately long run times; (ii) Q-learning algorithms based on a version of the projected Bellman equation. It is shown that the algorithm is stable, in the sense of bounded sample paths, and that a solution to the projected Bellman equation exists under mild conditions. Numerical experiments illustrate these findings, and provide a roadmap for algorithm design in more general settings.
Complexity, cost, and power requirements for the actuation of individual robots can play a large factor in limiting the size of robotic swarms. Here we present PCBot, a minimalist robot that can precisely move on an orbital shake table using a bi-stable solenoid actuator built directly into its PCB. This allows the actuator to be built as part of the automated PCB manufacturing process, greatly reducing the impact it has on manual assembly. Thanks to this novel actuator design, PCBot has merely five major components and can be assembled in under 20 seconds, potentially enabling them to be easily mass-manufactured. Here we present the electro-magnetic and mechanical design of PCBot. Additionally, a prototype robot is used to demonstrate its ability to move in a straight line as well as follow given paths.
The objective of this paper is to reflect on the role of creative writing in the university. Our proposal is based on cognitive studies of creativity and current development on creative teaching. We present four experiences, in our opinion, of creative writing at the university: travel notebooks, paths of life, a class in a word and tips to become a creative scientist. Finally, we try to articulate creative writing, teaching, research and university connection. In the writing we take some licenses, we include images of the experiences and some brief stories. The text intends to challenge from questions and not answers or certainties. We seek, at least in part, to tell our experiences by appealing to different formats and modalities. We invite readers to generate creative spaces in the university where spaces are enabled for indiscipline, border writing and divergent actions.
Drawing. Design. Illustration, Communication. Mass media
An orthogonal drawing is an embedding of a plane graph into a grid. In a seminal work of Tamassia (SIAM Journal on Computing 1987), a simple combinatorial characterization of angle assignments that can be realized as bend-free orthogonal drawings was established, thereby allowing an orthogonal drawing to be described combinatorially by listing the angles of all corners. The characterization reduces the need to consider certain geometric aspects, such as edge lengths and vertex coordinates, and simplifies the task of graph drawing algorithm design. Barth, Niedermann, Rutter, and Wolf (SoCG 2017) established an analogous combinatorial characterization for ortho-radial drawings, which are a generalization of orthogonal drawings to cylindrical grids. The proof of the characterization is existential and does not result in an efficient algorithm. Niedermann, Rutter, and Wolf (SoCG 2019) later addressed this issue by developing quadratic-time algorithms for both testing the realizability of a given angle assignment as an ortho-radial drawing without bends and constructing such a drawing. In this paper, we further improve the time complexity of these tasks to near-linear time. We establish a new characterization for ortho-radial drawings based on the concept of a good sequence. Using the new characterization, we design a simple greedy algorithm for constructing ortho-radial drawings.
I study a repeated auction in which payments are made with a blockchain token created and initially owned by the auction designer. Unlike the ``virtual money'' previously examined in mechanism design, such tokens can be saved and traded outside the mechanism. I show that the present-discounted value of expected revenues equals that of a conventional dollar auction, but revenues accrue earlier and are less volatile. The optimal monetary policy burns the tokens used for payment, a practice common in blockchain-based protocols. I also show that the same outcome can be reproduced in a dollar auction if the auctioneer issues a suitable dollar-denominated security. This equivalence breaks down with moral hazard and contracting frictions: with severe contracting frictions the token auction dominates, whereas with mild contracting frictions the dollar auction combined with a dollar-denominated financial instrument is preferred.
Graphic design, which has been evolving since the 15th century, plays a crucial role in advertising. The creation of high-quality designs demands design-oriented planning, reasoning, and layer-wise generation. Unlike the recent CanvaGPT, which integrates GPT-4 with existing design templates to build a custom GPT, this paper introduces the COLE system - a hierarchical generation framework designed to comprehensively address these challenges. This COLE system can transform a vague intention prompt into a high-quality multi-layered graphic design, while also supporting flexible editing based on user input. Examples of such input might include directives like ``design a poster for Hisaishi's concert.'' The key insight is to dissect the complex task of text-to-design generation into a hierarchy of simpler sub-tasks, each addressed by specialized models working collaboratively. The results from these models are then consolidated to produce a cohesive final output. Our hierarchical task decomposition can streamline the complex process and significantly enhance generation reliability. Our COLE system comprises multiple fine-tuned Large Language Models (LLMs), Large Multimodal Models (LMMs), and Diffusion Models (DMs), each specifically tailored for design-aware layer-wise captioning, layout planning, reasoning, and the task of generating images and text. Furthermore, we construct the DESIGNINTENTION benchmark to demonstrate the superiority of our COLE system over existing methods in generating high-quality graphic designs from user intent. Last, we present a Canva-like multi-layered image editing tool to support flexible editing of the generated multi-layered graphic design images. We perceive our COLE system as an important step towards addressing more complex and multi-layered graphic design generation tasks in the future.
The complexity of modern hardware designs necessitates advanced methodologies for optimizing and analyzing modern digital systems. In recent times, machine learning (ML) methodologies have emerged as potent instruments for assessing design quality-of-results at the Register-Transfer Level (RTL) or Boolean level, aiming to expedite design exploration of advanced RTL configurations. In this presentation, we introduce an innovative open-source framework that translates RTL designs into graph representation foundations, which can be seamlessly integrated with the PyTorch Geometric graph learning platform. Furthermore, the Verilog-to-PyG (V2PYG) framework is compatible with the open-source Electronic Design Automation (EDA) toolchain OpenROAD, facilitating the collection of labeled datasets in an utterly open-source manner. Additionally, we will present novel RTL data augmentation methods (incorporated in our framework) that enable functional equivalent design augmentation for the construction of an extensive graph-based RTL design database. Lastly, we will showcase several using cases of V2PYG with detailed scripting examples. V2PYG can be found at \url{https://yu-maryland.github.io/Verilog-to-PyG/}.
Subtain Malik, Muhammad Tariq Saeed, Marya Jabeen Zia
et al.
In this paper, we present a review of the recent work in deep learning methods for user interface design. The survey encompasses well known deep learning techniques (deep neural networks, convolutional neural networks, recurrent neural networks, autoencoders, and generative adversarial networks) and datasets widely used to design user interface applications. We highlight important problems and emerging research frontiers in this field. We believe that the use of deep learning for user interface design automation tasks could be one of the high potential fields for the advancement of the software development industry.