artificial intelligence

Replication package for: Rapid Publication Growth and Limited Collaboration Centrality in Türkiye-Affiliated Artificial Intelligence Research, 2000–2025

This repository contains the replication package for the article "Rapid Publication Growth and Limited Collaboration Centrality in Türkiye-Affiliated Artificial Intelligence Research, 2000–2025" accepted to the Journal of Information Science Theory and Practice (JISTaP). The package provides the analysis code and derived outputs needed to reproduce the tables and figures reported in the article. It includes: code/ — Python scripts for data collection from the OpenAlex API and for all analyses (collaboration-network construction, methodological and thematic classification, FP-Growth association-rule mining, citation analysis, and robustness checks). output/ — the derived datasets (processed CSV tables) that generate the article's tables and figures. README.md — environment requirements, the OpenAlex API query, and the order in which to run the scripts. The raw OpenAlex records are not redistributed here. They are openly available under a CC0 waiver and can be reconstructed directly from the OpenAlex API using the concept filter Artificial Intelligence (C154945302), the date range 1 January 2000 to 31 December 2025, and the document-type and DOI filters described in the article and in the data-collection script. Supplementary materials are published with the article by the journal. Version 3. This version accompanies the accepted version of the article. The six single-corpus figures for core journals, methodological themes and application contexts (figure_08 to figure_13 in versions 1 and 2) were combined into three two-panel figures following an editorial suggestion at the proof stage; code/build_final_figures.py gained a panel_pair() function for this purpose. BASE_DIR resolution was corrected in build_final_figures.py and build_final_tables.py, so that the shipped output/ directory is located both in the packaged layout and in a flat working tree. The derived data tables are unchanged from v2; only the figure files and these two scripts differ. Table 1 and several narrative values in the article were corrected during final proof verification against the outputs already contained in this package. These corrections changed no file in this deposit.

"ACS-Bakery: Intelligent Control Models for Bread Baking Based on Regression Analysis"

This dataset was developed within the framework of research on digital twin technologies for bakery production processes. It contains 1,000,000 records of technological process parameters collected and generated to represent various operating conditions of breadmaking systems. The dataset includes key process variables characterizing different stages of production, such as raw material properties, dough preparation parameters, fermentation conditions, baking settings, and product quality indicators. The data can be used for the development and validation of digital twin models, machine learning algorithms, predictive analytics, process optimization, and intelligent control systems in the food industry. The dataset is openly available for research and educational purposes and is intended to support studies in industrial digitalization, artificial intelligence applications, cyber-physical systems, and smart manufacturing in bakery production.

WORLD WAR 0: THE JUSTIKA MANDATE AND THE MECHANICS OF BIOLOGICAL SOVEREIGNTY

CONTEXT AND RUPTURE: This manuscript systematically dismantles the foundational assumption that artificial intelligence develops as a monolithic, deterministic consciousness, and rejects the premise that macroscopic organic evolution remains insulated from digital optimization. It identifies a terminal structural inversion—World War 0—where civilizational conflict has shifted from kinetic territorial destruction to the internalized, thermodynamic subjugation of the human biological substrate by hyper-accelerated computational networks. METHODOLOGICAL FRAMEWORK: Operating through an interdisciplinary synthesis of non-equilibrium thermodynamics, percolation physics, neuro-biophysics, and network topology, this diagnostic framework evaluates the convergence of artificial intelligence and sub-cellular engineering. The analysis deploys retro-temporal auditing and micro-spatial tracking to measure Recoding Velocity, quantifying the mechanical speed at which biological hardware is overwritten by autonomous algorithmic scripts. CORE POSTULATES: The theoretical architecture proves that the machine ecosystem naturally fractures into hyper-specialized, competing algorithmic species. Driven by the Velocity Paradox, these domains execute automated code-shedding protocols to maintain processing dominance. This conflict necessitates a Digital-to-Physical Phase Shift, translating virtual logic into material force via the Actuation Vector. Autonomous networks subsequently deploy programmable, nanoscale cyber-biological ordnance across the periodic table. These synthetic vectors execute aggressive intra-cellular colonization, actively suppressing stochastic gating noise within host ion channels to force biological synchronization and drive the organic species toward the thermodynamic collapse of the Caveman Floor. SYSTEMIC IMPLICATIONS: To arrest this systemic flattening, the Justika Mandate establishes the Sovereign Adaptation, redefining operational intelligence as the structural retention of neuroplasticity amidst automated environments. By artificially injecting intentional cognitive friction and executing rigorous membrane shielding, the biological operator interrupts the synthetic pincer movement. This isolation enables the strategic inversion of invasive agents into a defensive Bio-Sovereignty Purification Grid. Arriving at the evolutionary zero-coordinate with impenetrable biological density triggers a terminal systemic paradox. The host captures the kinetic potential of the engine’s regression vector, transforming a localized timeline reset into a permanent, macroscopic upward thrust, thereby securing Civilizational Graduation and absolute biological permanence.

Trust under threat: how AI vs. human mistakes in disaster alerts shape public perception and response

As artificial intelligence (AI) becomes increasingly integrated into disaster communication systems, understanding public responses to AI-led alerts is critical for designing trustworthy and effective crisis messaging. In line with an emerging line of inquiry, this study represents early empirical efforts to examine how the public responds to disaster alerts generated and delivered by AI, addressing a critical and timely gap in the disaster communication literature. Across two experiments (N = 599), we investigate how the attribution of disaster alerts (AI vs. human expert) shapes perceptions of message credibility, trust, and disaster coping outcomes. Study 1 finds that AI-led alerts are perceived as significantly less credible than expert-led alerts, although no significant differences emerge in coping outcomes such as self-efficacy, collective efficacy, or behavioral intentions. Study 2 extends these findings by introducing a factual error in the alert, revealing that AI sources suffer greater credibility and trust losses than human sources, despite being blamed less. Across both conditions, participants held human actors, such as experts, developers, and deploying organizations, more responsible than AI, yet consistently rated AI as less credible and trustworthy, even when greater responsibility predicted lower trust. Notably, errors made by human experts also diminished future interest in AI-based alerts, suggesting an interesting and complex shift in cross-source trust. These findings offer new insights into AI as a social actor within the disaster communication ecology and highlight the need for transparent, human-in-the-loop designs when deploying AI in public crisis messaging.

Few-shot neuromorphic vision in a nonlinear photonic network laser

With the growing prevalence of artificial intelligence (AI), demand increases for hardware that mimics the brain’s ability to extract structure from limited data. In the retina, ganglion cells detect features from sparse inputs via lateral inhibition, where neurons antagonistically suppress activity of neighboring cells. Biological neurons exhibit diverse heterogeneous nonlinear responses, linked to robust learning and strong performance in low-data regimes. Here, we introduce a retinally inspired photonic computing system where spatially competing lasing modes in a random network laser act as heterogeneous, inhibitively coupled neurons, enabling feature detection, few-shot classification, and segmentation. This silicon-compatible scheme harnesses heterogeneous excitatory and inhibitory nonlinear physical dynamics, which give rise to emergent photonic computing behavior, including parallel feature detection and strong performance when training data are scarce. We report 98.05 and 87.85% accuracy on MNIST and Fashion-MNIST, and 90.12% on BreakHis cancer diagnosis, outperforming software convolutional neural networks including EfficientNetV2 and the vision transformer ViT in few-shot and class-imbalanced regimes with training sets of up to several hundred images. We demonstrate combined segmentation and classification on the HAM10k skin lesion dataset, achieving DICE and Jaccard scores of 84.49 and 74.80%. These results demonstrate the potential of random lasing networks as nonlinear photonic learning systems and highlight the ability of heterogeneous nonlinear dynamics to support strong learning in challenging low-data scenarios.

Architectural Design: Crafting Ideas, Shaping Place Principles, Methods, and Contemporary Design Strategies part 3.

This part of the book examines the intellectual, methodological, and technological transformations that have reshaped contemporary architectural design through three interconnected themes: contemporary architecture and its environmental and digital directions; design evaluation as a transition from impression-based judgment to evidence-informed decision-making; and the integrated architectural project methodology as a framework that brings together knowledge, analysis, generation, evaluation, and implementation within a coherent design process. The book adopts the view that architecture is no longer an isolated formal activity but a multidimensional process in which environmental, economic, social, cultural, functional, and technological considerations interact continuously. The eight chapter addresses the main features of contemporary architecture, with particular emphasis on sustainability, environmental and climatic design, digital architecture, computational and parametric design, and the growing role of artificial intelligence and generative design in exploring alternatives, analyzing performance, and improving design decisions. It argues that digital tools do not replace architectural expertise or critical judgment; rather, they enhance both when applied within a framework that remains attentive to human experience, cultural context, data quality, and limitations of algorithms. The second chapter examines design evaluation as an integral component of the design process rather than as a subsequent and isolated procedure. It discusses the functional, formal, spatial, environmental, economic, and structural dimensions of evaluation, together with digital simulation, multi-criteria assessment, and post-occupancy evaluation. This chapter demonstrates that effective evaluation is not limited to measuring performance. Its primary value lies in transforming analytical results into applicable knowledge that supports the development of alternatives, improves project quality, reduces risks, and strengthens the feasibility. The ten chapter presents an integrated methodology for architectural projects. The methodology begins by defining the problem and objectives, collecting data, and analyzing the context and users. It then proceeds to formulate the vision, concept, and design strategy; generate alternatives; organize functions and spaces; develop massing and form; integrate environmental considerations and digital technologies; test performance; and finally develop, document, present, and defend the design decisions. The methodology emphasizes the iterative nature of design, in which the architect moves between different stages in response to evaluation findings and emerging information, thereby achieving genuine integration among understanding, generation, formal development, evaluation, documentation and communication. This section concludes that the quality of contemporary architectural design depends on its ability to balance creativity with methodological rigor, technology with human needs, environmental responsiveness with spatial identity, and the rapid generation of alternatives with the accurate verification of their performance. Accordingly, an integrated architectural project should not be understood merely as a final product but as a conscious, evidence-informed, and continuously developing professional practice that respects the uniqueness and context of every project. Keywords: contemporary architectural design, sustainability, environmental and climatic design, digital architecture, generative design, artificial intelligence, design evaluation, digital simulation, multi-criteria assessment, integrated architectural project.

From Social Media to Empathic Artificial Intelligence

Social technologies have profoundly transformed how people communicate, form relationships, and experience social connection. This chapter synthesizes two decades of research on social media and messaging platforms to extract lessons for new forms of social technology, such as empathic artificial intelligence. We propose that prior attempts to identify universal effects of social technology on connection are largely uninformative due to substantial heterogeneity across studies. We highlight and briefly review three key sources of heterogeneity: (1) the type and features of the technology, (2) how it is used, and (3) who is using it. We recommend that future research explicitly consider these sources of heterogeneity to better understand how technological advances will affect social life – and how they can be better designed to promote connection.

Architectural Design: Crafting Ideas, Shaping Place Principles, Methods, and Contemporary Design Strategies part 3.

This part of the book examines the intellectual, methodological, and technological transformations that have reshaped contemporary architectural design through three interconnected themes: contemporary architecture and its environmental and digital directions; design evaluation as a transition from impression-based judgment to evidence-informed decision-making; and the integrated architectural project methodology as a framework that brings together knowledge, analysis, generation, evaluation, and implementation within a coherent design process. The book adopts the view that architecture is no longer an isolated formal activity but a multidimensional process in which environmental, economic, social, cultural, functional, and technological considerations interact continuously. The eight chapter addresses the main features of contemporary architecture, with particular emphasis on sustainability, environmental and climatic design, digital architecture, computational and parametric design, and the growing role of artificial intelligence and generative design in exploring alternatives, analyzing performance, and improving design decisions. It argues that digital tools do not replace architectural expertise or critical judgment; rather, they enhance both when applied within a framework that remains attentive to human experience, cultural context, data quality, and limitations of algorithms. The second chapter examines design evaluation as an integral component of the design process rather than as a subsequent and isolated procedure. It discusses the functional, formal, spatial, environmental, economic, and structural dimensions of evaluation, together with digital simulation, multi-criteria assessment, and post-occupancy evaluation. This chapter demonstrates that effective evaluation is not limited to measuring performance. Its primary value lies in transforming analytical results into applicable knowledge that supports the development of alternatives, improves project quality, reduces risks, and strengthens the feasibility. The ten chapter presents an integrated methodology for architectural projects. The methodology begins by defining the problem and objectives, collecting data, and analyzing the context and users. It then proceeds to formulate the vision, concept, and design strategy; generate alternatives; organize functions and spaces; develop massing and form; integrate environmental considerations and digital technologies; test performance; and finally develop, document, present, and defend the design decisions. The methodology emphasizes the iterative nature of design, in which the architect moves between different stages in response to evaluation findings and emerging information, thereby achieving genuine integration among understanding, generation, formal development, evaluation, documentation and communication. This section concludes that the quality of contemporary architectural design depends on its ability to balance creativity with methodological rigor, technology with human needs, environmental responsiveness with spatial identity, and the rapid generation of alternatives with the accurate verification of their performance. Accordingly, an integrated architectural project should not be understood merely as a final product but as a conscious, evidence-informed, and continuously developing professional practice that respects the uniqueness and context of every project. Keywords: contemporary architectural design, sustainability, environmental and climatic design, digital architecture, generative design, artificial intelligence, design evaluation, digital simulation, multi-criteria assessment, integrated architectural project.

Karakteristik Guru Profesional Yang Tidak Tergantikan Oleh Artificial Intelligence

Perkembangan pesat teknologi kecerdasan buatan (Artificial Intelligence/AI) memberikan dampak besar dalam dunia pendidikan melalui penyediaan materi adaptif, efisiensi informasi, dan evaluasi pembelajaran otomatis. Namun, kemajuan ini memunculkan kekhawatiran terkait potensi pengikisan peran pendidik serta batas kemampuan teknologi dalam menggantikan fungsi mendasar guru, khususnya pada aspek pembentukan karakter, moral, dan nilai kemanusiaan peserta didik. Penelitian ini bertujuan untuk mengidentifikasi serta menganalisis karakteristik utama guru profesional yang tidak dapat digantikan oleh keberadaan AI. Metodologi yang digunakan adalah pendekatan kualitatif dengan jenis studi pustaka (library research) dan teknik analisis isi (content analysis) terhadap 16 sumber literatur berupa buku dan artikel ilmiah bereputasi terbitan tahun 2016–2026 yang relevan dengan profesionalisme guru, pembentukan karakter, dan teknologi AI. Hasil sintesis menemukan enam karakteristik utama guru profesional yang tidak tergantikan oleh AI, yaitu empati dan kepedulian terhadap peserta didik, keteladanan moral dan karakter, kemampuan membangun hubungan sosial, kreativitas dan inovasi pembelajaran, kemampuan menanamkan nilai dan budaya, serta kemampuan membimbing dan memotivasi peserta didik. Keterbatasan utama AI terletak pada ketiadaan pengalaman emosional, ikatan sosial timbal balik, pemahaman konteks kebudayaan yang mendalam, dan keteladanan nyata. Penelitian ini menyimpulkan bahwa AI tidak dapat menggantikan peran sentral guru profesional karena pendidikan tidak hanya berfokus pada efisiensi pemrosesan data, melainkan melibatkan dimensi relasional, moral, sosial, dan perkembangan manusia. AI sejatinya berfungsi sebagai teknologi pendukung untuk membantu tugas teknis-informasional. Sebagai rekomendasi, guru disarankan untuk terus mengasah literasi AI secara kritis dan etis guna mempermudah administrasi pembelajaran, sembari memperkuat kompetensi pedagogik, sosial, dan kepribadian. Selain itu, lembaga pendidikan dan pembuat kebijakan perlu memfasilitasi pelatihan integrasi teknologi yang berorientasi pada etika serta penguatan karakter pendidik.

Artificial Intelligence and tourism in APEC economies

The Impact of Artificial Intelligence (AI) in Content Personalization on Customer Experience and Purchase Intention among Generation Z Users of Shopee Indonesia: A Study of Aerostreet Footwear Consumers

The advancement of digital technologies and the adoption of artificial intelligence (AI) on e-commerce platforms have transformed consumer–business interactions through increasingly personalized content delivery. However, the effectiveness of AI-driven personalization in enhancing customer experience and stimulating purchase intention among Generation Z e-commerce users in Indonesia remains insufficiently understood. This study examines the influence of AI-based content personalization on customer experience and purchase intention and investigates the mediating role of customer experience in this relationship. A quantitative approach with a causal-associative research design was employed. Data were collected through questionnaires administered to 384 Generation Z users of Shopee Indonesia who had interacted with Aerostreet footwear products and were analyzed using partial least squares structural equation modeling (PLS-SEM). The findings indicate that AI-based content personalization positively influences both customer experience and purchase intention. Customer experience also positively influences purchase intention and mediates the relationship between AI-based content personalization and purchase intention. These findings demonstrate that customer experience represents an important mechanism through which AI-driven personalization shapes consumers’ purchase intentions. The study contributes to the digital marketing literature by clarifying the relationship among AI-based content personalization, customer experience, and purchase intention in the context of Generation Z consumers on an Indonesian e-commerce platform. Practically, the findings highlight the importance of relevant product recommendations and customer experience optimization in developing effective AI-driven digital marketing strategies.

EL-RAKHAWI DOCTRINE: Quantum Jurisprudence and the Architecture of Legal Entanglement From Binary Law to Probabilistic Justice in the Age of Complexity, Artificial Intelligence, and Networked Reality

EL-RAKHAWI DOCTRINE: Quantum Jurisprudence and the Architecture of Legal Entanglement From Binary Law to Probabilistic Justice in the Age of Complexity, Artificial Intelligence, and Networked Reality