Faculty of Design

Abstract The global fashion industry is changing with the integration of digital technologies. Designers now employ digital design software, tools and technology to develop innovative designs, purchase fabrics and materials and market their new designs. Digital media and technology have also contributed to the growth of influencers and personal stylists who use social media and apps to offer reviews and advice, including personal devices that leverage machine learning and algorithmic recommendation systems. This article brings together design anthropology and digital anthropology to understand the ways in which algorithms are increasingly entangled with notions of aesthetics and style. Comparing the ways in which style is created through ‘feeding’ and ‘reading’ the algorithm, the article draws upon Seaver’s notion of algorithmic cultures to explore two examples of the ways algorithms are made meaningful in people’s lives. The first example was carried out with professional women who experimented with a commercially available personal stylist device that provides algorithm‐based style recommendations. The second case study turns to the ways different fashion designers use and interpret social media algorithms to develop brands locally in Fiji and globally. By exploring the ways in which fashion and style‐oriented algorithms are used by different individuals and communities across the fashion value chain, the article examines how algorithmic technologies become enlivened as different people act, engage and interact with them and change over time.

Purpose This study explains how the informal sector impacts deal completion and the contingent roles of formal institutions, infrastructure and major restructuring. Using institutional complexity theory, this study aims to propose a new link between the informal sector and deal completion that emerges through the decreasing transaction cost of emerging markets. Design/methodology/approach The authors acquire deal-level data from the China Stock Market and Accounting Research Database (CSMAR) and national-level data from the World Bank Enterprise Survey (WBES). CSMAR includes full information on listed Chinese firms and is one of the most frequently used databases for research in the Belt and Road Initiative context. WBES provides data on the informal sector, formal institutions and infrastructure in 154 countries by administering a series of surveys to enterprises, and these data have been used in a few IB studies. Findings Data from a longitudinal sample reveal the positive effects of the informal sector on deal completion. The findings also show that formal institutions, infrastructure and major restructuring weaken this positive relationship. Practical implications This research has several implications for CEOs, top management teams (TMTs) and managers of emerging firms. First, the findings may reshape CEO entry strategies in emerging markets. Second, the findings indicate that the strategic collaboration of the TMT could maximize the advantages of the informal sector. Third, the strategic collaboration between the CEO and the TMT is based on managers whose work includes communication with the informal sector. Originality/value This investigation seeks to advance the understanding of sector-level informality and its impact on cooperative organizational response. This study deepens the understanding of institutional complexity in the interaction between the informal sector and formal institutions.

ROSUS 2026 – Računalniška obdelava slik in njena uporaba v Sloveniji 2026 je strokovna računalniška konferenca, ki jo od leta 2006 naprej vsako leto organizira Inštitut za računalništvo, Fakulteta za elektrotehniko, računalništvo in informatiko, Univerze v Mariboru. Konferenca povezuje strokovnjake in raziskovalce s področij digitalne obdelave slik in strojnega vida z uporabniki tega znanja, pri čemer uporabniki prihajajo iz raznovrstnih industrijskih okolij, biomedicine, športa, zabavništva in sorodnih področij. Zbornik konference ROSUS 2026 združuje strokovne prispevke več avtorjev, od tega dve vabljeni predavanji ter več demonstracijskih prispevkov. Prispevki podajajo najnovejše dosežke slovenskih strokovnjakov s področij digitalne obdelave slik in strojnega vida, osvetljujejo pa tudi trende in novosti na omenjenih strokovnih področjih. Velik poudarek prispevkov je na promoviranju ekonomske koristnosti aplikacij računalniške obdelave slik in vida v slovenskem prostoru. Takšne računalniške aplikacije zaradi visoke natančnosti, robustnosti in izjemnih hitrosti pri obdelovanju informacij nudijo namreč nove priložnosti za uveljavitev na trgu visokih tehnologij.

There are still not many academic reports on cases where privately owned postwar modern architecture that are not registered as cultural properties and have been completely renovated. In order to preserve and maintain more modern architecture in the future, it is essential not only to discuss methodologies, but also to accumulate reports of similar cases that can be referred to. This paper reports the overview of the Office and Hall of All Japan Seamen’s Union designed by Masato Otaka and completed in 1964, and its process toward the decision making of the renovation project.

Mimarlık ve şehircilikte, mevcut yapı stoğu ve doğal peyzaj dahil olmak üzere tüm kaynak ve malzemeleri kapsayan, döngüsellik ve uyarlanabilirlik eksenli bir tasarım kültürüne yönelim artmaktadır. Yıkım eylemi sorgulanmakta, mevcut yapılarda ve kentsel mekanlarda, onarım, bakım ve yeniden işlevlendirmeyi önceleyen müdahale ve dönüşümler daha fazla tercih edilmektedir. Bu makale, yeniden işlevlendirmeye ilişkin el kitapları ve atlaslarda baskın olan örnek temelli ve pratik odaklı yaklaşımlardan farklılaşarak, yapılı çevrenin birikmiş bilgisinden ve deneysel çeşitliliğinden öğrenmenin önemini vurgulamaktadır. Yeniden işlevlendirilmiş yapıları tekil olarak değil, kolektif olarak bağlamlarıyla bütünleşik olarak incelemenin, mevcut yapılı çevreye eleştirel bir bakış açısı getirdiğini ve özen temelli bir yaklaşımı teşvik ettiğini savunmaktadır. Makale, Ankara’ya odaklanan ve kenti yeniden işlevlendirmenin deneysel bir arşivi olarak inceleyen lisansüstü düzeyde bir ders kapsamında yürütülen araştırma projesine dayanmaktadır. Araştırma kapsamında öğrenciler, kentteki yeniden işlevlendirilmiş yapıların iz sürme, haritalama ve dizinleme yoluyla bir arşivini oluştururken aynı zamanda dönüştürülmüş yapılı çevreleri yorumlamanın yaratıcı ve eleştirel yollarını aramışlardır. Öğrencilerin ikamet ettiği şehirde yer alan bu araştırma, mevcut yapıları geçirdikleri dönüşümler sonrası deneyimleme fırsatı sunarak, yeniden işlevlendirmenin yalnızca bir tasarım müdahalesi olarak değil, bir süreç olarak anlaşılmasını hedeflemektedir. Bu araştırma, mimarlık eğitimini, mimarlık pratiğinin giderek daha fazla dönüşüm ve yeniden işlevlendirmeye odaklanan süreçleriyle bütünleştirmek için yerleşik ve araştırma temelli bir öğrenme modeli önermekte; kenti bir arşiv olarak incelemenin kavramsal ve stratejik araçlarını tartışmaktadır.

This study investigates the distinct mechanisms of human versus Large Language Model (LLM) creativity. Employing a two-stage experimental design, we systematically compared Human-Only, LLM-Only, and LLM-Assisted performance across propositional and creative writing tasks. Results revealed a critical asymmetry contingent upon the research context: human authors exhibited higher originality in high-demand creative tasks, whereas LLMs governed execution quality, maintaining superior effectiveness across different tasks and cohorts. This pattern is characterized by four exploratory writing creativity profiles: Ideal, Safe, Moderate, and Plain. The distribution of human and LLM writings across these profiles was strikingly different. Hierarchical Moderated Regression analysis uncovered divergent linguistic pathways: human originality is predicted by markers of subjective cognitive investment, while LLM effectiveness is mechanistically driven by optimized structural coherence. Furthermore, the study identified a "Collaboration Trap" during collaboration with a suboptimal LLM. This partnership failed to improve human performance relative to LLM-Only benchmarks and induced cognitive anchoring, leading humans to mimic AI complexity without quality gains. These insights offer critical implications for preserving human agency and avoiding homogenization in future human-AI collaborative writing pedagogies.

The transition to renewable fuels necessitates reliablediagnostictools for monitoring engine health and lubricant stability. This studyintroduces an integrated methodology that combines vibration signatureanalysis with oil degradation indices to evaluate the long-term performanceof a single-cylinder diesel engine operated with Jatropha-based biodieselblends (10%, 20%, and 30% v/v). Over 100 h (h) of operation, vibrationdata were recorded using fast Fourier transform analysis, while oilcondition was monitored through viscosity, density, and infrared spectroscopyto quantify soot, oxidation, nitration, sulfation, and additive depletion.Statistical evaluation, including Pearson correlation, revealed stronginterdependencies between vibration amplitude and chemical degradationmarkers, confirming a direct mechanical–chemical linkage. Amongall blends, the 20% biodiesel blend exhibited the most favorable performance,showing the lowest vibration amplitude, minimal additive depletion,and stable physicochemical oil properties, thereby aligning closelywith baseline diesel. These findings establish a novel dual-parameterdiagnostic framework for predictive maintenance, offering significantpotential for extending the lubricant life, reducing downtime, andsupporting the adoption of sustainable biodiesel in compression ignitionengines. To the best of our knowledge, this is the first study todirectly correlate vibration signatures with FTIR-based oil degradationindices to establish a dual-parameter predictive diagnostic frameworkfor biodiesel-fueled engines. The study also develops a regression-basedpredictive model (R2 = 0.81, p < 0.05) linking vibration amplitude with oxidation and viscosityindices, establishing a foundation for real-time predictive maintenanceapplications.