Human Action Research Articles

An AI-driven framework for modernizing oracle ERP systems in the public sector

Public sector organizations face serious need to upgrade their Enterprise Resource Planning systems because this upgrade helps them to work more efficiently and serve customers effectively. This paper suggests an innovative plan to include Artificial Intelligence into Oracle ERP systems, which helps improve work processes and makes better decisions while handling automatic repetitive tasks. This framework enables easy modifications to ERP systems through AI while also working with less human action to give improved data insights. The research analyzes ERP system challenges before explaining how AI tools help systems to execute processes faster and more securely plus offering better adaptability. The analysis uses actual practice evidence and numerical data to explain how AI supports government organizations when they transform their Oracle ERPs. Research data proves that digital ERP systems that employ Artificial Intelligence technologies assist companies to work better and make smart transformational digital decisions.

The Ancient Egyptian Econometric Model: Multidimensional Osmosis Therapy in Africa

How can potential impact of the optimal policies of externalities trade to uncouple growth and volatility in order to restore Ancient Egypt economic model be explored by the means of numerical econometrics test? An in-depth study of the economic model of Ancient Egypt through a thirty-three-year experiment using therapeutic osmosis reveals a serious rout from the modern era onwards, with balkanization and a vast apostasy of science into domains of approximate knowledge in a world that had hitherto been characterized by adoration and strict obedience to the laws, principles, ordinances and covenants that formed the foundation of all human action. The optimal policies ensured the equilibrium and automatic regulation of the economy and of all life in society. It is clear that this restoration of African identity would not only benefit Africa but could save the whole world from inevitable extinction. Using numerical evidence, through priesthood authority theory experiments, we find that the human organism's multidimensional exchange mechanism, consisting of more or less integral compensation processes for negative and positive externalities, is responsible for the volatility of human growth, the main determinant of life expectancy, analogous to the relationship between the processes of economic growth volatility and sustainable growth.

Visual learning model for behavioral cloning in gaming: Towards human-like ai systems

Behavioral cloning is a transformative paradigm in artificial intelligence, enabling systems to emulate human behaviors in complex domains such as gaming, robotics, and autonomous systems. This whitepaper presents a novel visual learning model designed to learn strategic and dynamic behaviors by analyzing gameplay footage. By employing sequential data processing and advanced temporal modeling, the architecture bridges human actions with actionable artificial intelligence (AI) strategies. The paper delves into the intricacies of model architecture, training methodologies, and evaluation metrics, offering a robust framework for real-time, context-aware decision-making. Key applications span gaming bots, collaborative artificial intelligence (AI) in robotics, and task automation systems. The proposed framework addresses critical challenges in synchronization, resource management, and adaptability, paving the way for generalized AI systems.

The Aesthetics of Place and Displacement in Ushie's Eco-Poetics.

This paper examines the portrayal of environmental exploitation and destruction in Joe Ushe’s "Hill Songs". Focusing on the African context, the poet sheds light on the detrimental effects of leaders exploiting natural resources for personal gain. Through vivid imagery and metaphors, the poems illustrate the relentless and destructive behaviour of the exploiters, symbolized as African mosquitoes and scavengers. The analysis uses ecocritical literary theory to explore the underlying themes of human indifference, the complex relationship between humans and nature, and the consequences of unsustainable practices. In Hill Songs, Ushie employs the metaphor of mosquitoes drilling and sucking the peasant blood (natural resources) to depict the exploitative nature of the well-to-do individuals. The poem highlights the exploiter's consistent and unapologetic actions, disregarding the suffering of the victims and leaving the land empty and depleted. The imagery of a persistent horn sounding in the persona's ear emphasises the exploiter's disregard for human welfare and their insatiable greed. Furthermore, the poem suggests that nature serves as a refuge from human interference, but it also conveys the consequences of human actions on the environment. The persona's cautionary tone warns against the destructive impact of exploitative practices and emphasizes the need to protect the environment. The poems highlight the urgent need to address environmental crises and advocate for the preservation of the natural world. This study underscores the aesthetics employed by Ushie, including vivid imagery, sensory language, metaphors, and irony, to convey the destructive relationship between humans and the environment. The exploration of these themes and literary techniques provides valuable insights into the consequences of environmental exploitation and serves as a compelling call to action to protect and preserve the environment for future generations.

Enhancing Surveillance Vision-Based Human Action Recognition Using Skeleton Joint Swing and Angle Feature and Modified AlexNet-LSTM

Enhancing Surveillance Vision-Based Human Action Recognition Using Skeleton Joint Swing and Angle Feature and Modified AlexNet-LSTM

Theater Scene Description for Human-Scene Interaction

Entertainment venues like theaters are key to social engagement, but the lack of assistive technologies for people with visual impairments limits their participation. Our research aims to enhance theater accessibility using computer vision techniques to detect visual information about objects and actor gestures and convey them to blind audiences through non-visual modalities. In this work, we focus on providing a novel dataset, TS-RGBD, containing theater scenes to guide the development of computer-vision-based systems for theater scene description. It includes RGB, depth, and skeleton sequences captured by Microsoft Kinect in a theatrical setting. The dataset features untrimmed theater scenes as well as trimmed sequences consisting of individual gestures for actor gesture recognition. We test state-of-the-art image captioning models on untrimmed scenes, revealing that dense captioning models generate redundant captions with fixed numbers, leading to imprecise descriptions and a lack of context. These challenges hinder visually impaired individuals from comprehending theater scenes descriptions effectively. Additionally, we assess the performance of skeleton-based graph convolution networks for human action recognition in a theater environment using trimmed skeleton sequences. The results highlight limitations in recognizing human actions in this setting. Based on these findings, we propose solutions for overcoming these challenges, paving the way for future improvements in making theater performances more accessible to individuals with visual impairments.

The Interwar Period That Wasn’t: Alternative Histories of the Twentieth Century in the Prose of Jacek Dukaj

The article analyzes the creation of alternative histories using the examples of Xavras Wyżryn [Xavras Wyżryn] and Lód [Ice]. The focus of the interpretations will be on the question of why this particular period was subjected to counterfactual processes. In Xavras, the first half of the twentieth century is presented as a sequence of events resulting from the still ongoing war of 1920, that is, as an effect of human actions; in Ice, on the other hand, the events are caused by a meteorite impact, that is, they result from natural factors. In both works, 1918–1939 is not a period marked by war and is not decisive for the development of the Polish state. In this article, I will discuss the methods of constructing fictional worlds and answer the fundamental questions about the relationship between chance and the supreme law built into history, especially the juxtaposition of ideas of modernity and the growing totalitarianism. First, however, I will focus on the new ways of interpreting culturally mythologized spaces, logical and philosophical theories, and interpersonal relations through fictional alternative worlds.

The Person Holding the Phone

In this paper, I present a personal case study centered on my experience of attending my grandfather's funeral virtually in 2023. This event serves as a lens to explore broader themes of mediated grief work and the integration of digital media into experiences of death and mourning. Drawing on Bruno Latour's actor-network theory, I analyze the formation of temporary digital mourning assemblages, examining the ties that connect participants both on the ground and online. A key focus is the role and impact of the human actor within technological and media interfaces. The person operating the phone, capturing images, and managing the technical aspects of a Zoom call is often overshadowed by discussions that prioritize the technology itself.

The impact of governance and economic factors on Biocracy in the committed countries in COP28

<p>Biocracy refers to a system of governance and decision-making that prioritizes the well-being and health of living systems, including ecosystems, species, and human communities. Biocracy promotes holistic, participatory, and adaptive management, integrating science, traditional knowledge, and collective decision-making. The goal is to cultivate a mutually enriching relationship between humans and the natural world. As a result, all human actions have an impact on Biocracy. This study covers annual data from 2010 to 2022 for a group of member countries of the COP28 with the percentage of emissions reduction needed to meet the 1.5-degree Celsius target by 2030 among current top emitters and employs the tobit panel model with a limited dependent variable (LDV). The primary economic variables that substantially influence Biocracy are GDP growth, foreign investment, inflation rate, employment, trade-related variables (exports and imports), and governance. The results indicate that the governance index and imports variable have the most significant positive effect on Biocracy, and the elasticity of governance has the largest impact on Biocracy among all the variables studied. The study’s objective is to identify strategies to enhance Biocracy without hindering economic growth, with an emphasis on the role of good governance.</p>

Humanity and AI: Collaborating for a Flourishing Planet Through Wise Decision-Making

Our world now faces significant challenges including complex issues arising from human–machine interaction. This paper explores how we could address these challenges using a new approach called Cybernetics 3.0. This approach highlights human agency and the co-evolution of humans and machines, particularly regarding how we make decisions. Rather than viewing machines as separate from people, Cybernetics 3.0 views machines as extensions of human action, which is vital in our complex world. This paper argues that when this approach is combined with advanced Web 3.0 technologies, we can create better decision-making systems that integrate both human values and machine capabilities. This paper uses diagrams to illustrate how human and machine decision-making are interconnected and provides a healthcare example to demonstrate the practical value of this framework. Through a holistic and systems thinking approach, we can foster sustainable and wise decisions that will promote human flourishing and planetary health. The discipline of cybernetics is a promising way to better understand the interaction between humans and technology via its focus on systems of control, human–AI learning and communication, feedback loops, self-regulating systems, and knowledge enhancement in humans and machines. Ultimately this approach could help us to address critical issues such as inequality, climate change, and other complex threats to our planet and society.

Peran Manusia Terhadap Lingkungan Hidup Dalam Al-Qur’an Perspektif M.Quraish Shihab (Studi Tematik Tafsir Al-Misbah)

The role of humans in the environment is one of the important themes in Islamic teachings. The Qur’an, as the holy book of Muslims, provides clear guidance on the relationship between humans and the environment. M. Quraish Shihab, through his monumental work, Tafsir Al-Misbah, provides a comprehensive and in-depth explanation of this concept. This study aims to examine the role of humans in the environment according to M. Quraish Shihab’s perspective, as outlined in Tafsir Al-Misbah. The method used in this study is a thematic study, which focuses on the verses of the Qur’an that discuss the environment and how M. Quraish Shihab interprets them. The results of the study show that M. Quraish Shihab emphasizes the importance of the role of humans as caliphs on earth, who have a great responsibility to protect and preserve the environment. The concept of the caliphate includes the obligation not to be excessive in using natural resources, maintaining the balance of the ecosystem, and acting fairly and wisely in managing the environment. In addition, M. Quraish Shihab also highlighted the importance of ecological awareness in every human action. He emphasized that environmental damage is the result of irresponsible human behavior, and that improvement can only be achieved through behavioral changes in accordance with Islamic teachings. This study is expected to contribute to efforts to understand and apply the values ​​of the Qur'an in the context of environmental protection, as well as inspire Muslims to be more concerned and responsible for the environment.

Automated Human Action Recognition with Improved Graph Convolutional Network-based Pose Estimation

The process of utilizing Artificial Intelligence (AI) to identify and label human behaviors from unprocessed activity data gathered from various sources is known as Human Activity Recognition (HAR). Because of its potential applications across multiple areas, computer vision faces a significant challenge in recognizing human actions and the accompanying interactions with objects and the environment. Investigating the temporal and geographical characteristics of the skeleton sequence is essential for this endeavor, according to recent studies. However, efficiently extracting discriminative temporal and spatial information remains a difficult task. This work proposes a novel Human Action Recognition Model exploiting improved Graph Convolutional Network (GCN)-based pose estimation with a Hybrid Classifier (IGCN-HC). The phases carried out in this model are pre-processing, pose estimation, feature extraction, and activity recognition. Initially, the input video will be pre-processed and a frame from the input video stream will be generated. Subsequently, human pose estimation exploiting improved GCN will be accomplished. Further, human skeletal joints’ coordinates in two- or three-dimensional spaces are determined via human pose estimation. Then, Shape Local Binary Texture (SLBT) and an improved hierarchy of skeleton features have been used to detect the variance in different activities. In the last phase, a hybrid classification model with the combination of Deep Maxout and customized CNN has been proposed for the recognition phase. The model utilizes two inputs pose estimation results (skeleton) and the extracted features for training purposes. Finally, the proposed trained model is evaluated for recognition on different test inputs and contrasted with the existing techniques.

Exploring Changes in Lin Yutang’s Translation Habitus

As the core of Bourdieu’s sociological notions, habitus is initiative, generative and accumulative, constantly restructuring itself in accordance with external changes. The notion is frequently used to explain human action. Within the context of Translation Studies, the translator’s habitus can be an analytical tool to analyze a translator’s translation practice and to determine the hidden factors influencing translation behaviors. Lin Yutang is a well-known Chinese translator, and numerous studies have been carried out focusing on him as a translator and his translations from various perspectives. This study attempts to complement these previous studies by employing the concept of habitus. In other words, this study tries to investigate Lin Yutang’s translation habitus in order to more comprehensively understand him as a translator and further understand the restructuring characteristics of habitus. Within the framework of Bourdieu’s Theory of Social Practice, this paper diachronically examines Lin Yutang’s translation habitus through a comparison of his two translations of Six Chapters of a Floating Life which were translated in different times. The findings show that with the change of literary fields and the increase of his symbolic capital, Lin Yutang adjusted his translation habitus accordingly by turning from an “academic translation model” to a “business translation model”, and from adopting a foreignizing strategy to a domesticating strategy.

Spatial and Temporal Scales of Variability of Mollusks in a Strongly Threatened Mediterranean Coastal Lagoon (Mar Menor, Murcia, Spain)

Coastal lagoons are dynamic and highly productive systems that offer a remarkable number of ecological services and benefits for humans. However, our understanding of them is still far from adequate. The Mar Menor lagoon is an ecosystem subject to anthropogenic pressures that have worsened in recent years. These pressures include coastal works, such as dredging and sand dumping, as well as changes in agricultural regimes that have induced a process of eutrophication that set off alarms after the eutrophic crisis that occurred in 2016. Benthic organisms, and in particular mollusks, are very sensitive to environmental variations, often serving as indicators of these changes. This work analyzes the malacofauna of the Mar Menor from 1981 to 2019 in the context of the environmental changes that have occurred in it during these years. Eighty-six species have been recorded throughout our study period, and species richness, abundances, local assemblage structures, along with changes in the main environmental parameters of the water column (salinity, temperature, and chlorophyll a concentration) have been used to explain the composition of the communities of the main lagoon habitats and to detect their spatial and temporal variations. With the information provided, the complete inventory of mollusks reported in the lagoon has been updated to 126 species. The results indicate that, during these almost 40 years, the total number of species has remained relatively constant, but with a high percentage of occasional and very rare species, along with a high rate of change from one species to another over time, accompanied by variations in the abundance and dominance of some species compared to others depending on the environmental conditions and pressures that the lagoon has undergone. The high spatial and temporal heterogeneity detected is determined by the restricted connectivity with the open sea, the diversity of environments and habitats, and the changes in environmental conditions due to human actions.

Agent-Based Analysis of Financial Crisis Management Strategies to Enhance the Energy Transition in Germany

Crises appear to be occurring with increased frequency, whether provoked directly by human actions or through indirect causes such as resource scarcity or natural disasters. Crisis management strategies are frequently implemented with the aim of mitigating the immediate impacts of these crises. Nevertheless, it is critical to also consider the long-term consequences of such strategies. This study investigates both the short- and long-term effects of various crisis management strategies during a financial crisis in relation to the energy transition. An agent-based model of the German electricity sector is developed to analyze the effects of different strategies. The findings suggest that a reduction in electricity demand by 10% achieves the most favorable outcomes, decreasing short-term electricity costs by 11% and long-term carbon dioxide emissions by 9%.

V's Virtual Afterlife

Nonhuman Online Personas (NHOPs) are coherent digital assemblages not directly associated with the identities of individual humans. NHOPs encompass entities like brands, places, artificial intelligences, and, as we explore in this study, video game characters. This article examines the NHOP of V, the customisable protagonist from the video game Cyberpunk 2077, to consider how such characters attain a virtual afterlife beyond the original text through collective fan engagement. We propose ‘persona analysis’ as a novel qualitative case study methodology for researching NHOPs. Our approach integrates netnography, analytic autoethnography and textual analysis, enabling a comprehensive examination of the emergent, unpredictable, and collective natures of online personas. Building on existing persona studies frameworks, we focus on the collective dimension of persona as the sets of negotiations between human and nonhuman actors through which the NHOP is constructed. Using V as a case study, we apply the five dimensions of persona—mediatisation, publicness, performance, collective, and value—to analyse the NHOP. Data was collected from online platforms where fan productions occur, including fan fiction, game mods, virtual photography, conversation, and discussion. This multi-platform approach allowed us to observe the extensive participatory practices of fans' co-construction of V’s NHOP with its developers. Our analysis reveals that V’s NHOP is a complex, rhizomatic assemblage resulting from the participatory interplay between in-game characters, fans, games designers, developers, the storyworld’s creators, and intellectual property owners. By extending persona studies to encompass NHOPs, this research contributes to a deeper understanding of how online personas are collectively constructed. This, in turn, challenges established notions of online identity grounded in selfhood and opens new possibilities for examining the co-creation of online personas across all media types.

Introduction: Vital waste, or, the body extended

This special issue, Vital Waste, tackles the trajectories and perceptions of substances originating from human and animal bodies that were excreted, expelled, cut, removed, and/or used, in a period and contexts ranging from Medieval Iran to contemporary South India. We approach the substances in question through the lenses of history of science and technology in addition to anthropology, re-examining the conceptual frameworks of “afterlives,” and “signs of life,” and analyzing the meaning of life in bodily substances. Five articles demonstrate how different communities created, explored, and evaluated materials as both related to the “body integral” and disintegrated from it. Such ex-corporated substances, they show, are potent and stay active enough to mobilize human and nonhuman actors to act, often with a tendency to reduce proximity and move them away. This approach offers a new understanding of bodily waste as a vital material which preserves traces of life and whose connections with the body of origin either disturb or are highly desirable. This vitality contained within bodily materials is our focus. Traces or signs of life constitute potencies, both material and emotional, which are life-lasting and have to be framed as a value or a threat. Ultimately, the contributions that make up this special issue complicate our understanding of both waste and bodily boundaries.

An action decoding framework combined with deep neural network for predicting the semantics of human actions in videos from evoked brain activities.

Recently, numerous studies have focused on the semantic decoding of perceived images based on functional magnetic resonance imaging (fMRI) activities. However, it remains unclear whether it is possible to establish relationships between brain activities and semantic features of human actions in video stimuli. Here we construct a framework for decoding action semantics by establishing relationships between brain activities and semantic features of human actions. To effectively use a small amount of available brain activity data, our proposed method employs a pre-trained image action recognition network model based on an expanding three-dimensional (X3D) deep neural network framework (DNN). To apply brain activities to the image action recognition network, we train regression models that learn the relationship between brain activities and deep-layer image features. To improve decoding accuracy, we join by adding the nonlocal-attention mechanism module to the X3D model to capture long-range temporal and spatial dependence, proposing a multilayer perceptron (MLP) module of multi-task loss constraint to build a more accurate regression mapping approach and performing data enhancement through linear interpolation to expand the amount of data to reduce the impact of a small sample. Our findings indicate that the features in the X3D-DNN are biologically relevant, and capture information useful for perception. The proposed method enriches the semantic decoding model. We have also conducted several experiments with data from different subsets of brain regions known to process visual stimuli. The results suggest that semantic information for human actions is widespread across the entire visual cortex.

Multiple translatorship in the digital age: Interactive dynamics in the production of online literary translation

This article examines one of the first Chinese online literary translations from the early 2000s, Xiao Mao’s translations of two classic children’s novels by E. B. White. It uses the concepts of multiple translatorship and (con)textual voices to explain the translator’s involvement with different actors during his problem-solving process. The datasets include the paratexts of the translations, the mailing-list archives, and my interviews with the translator. A qualitative data analysis reveals a collective problem-solving process between Xiao and members of the New Threads online community. Most voices of these members are audible in peritexts thanks to the translator’s open credit, although there are some uncredited or miscredited voices. This interactive translation process demonstrates the translator’s relational identity with a posthuman approach, which means that he is part of an assemblage of various (non-)human actors. This article also suggests the democratizing potential of the shift from professional to non-professional translation.

World and Human Action Models towards gameplay ideation

Generative artificial intelligence (AI) has the potential to transform creative industries through supporting human creative ideation—the generation of new ideas1, 2, 3, 4–5. However, limitations in model capabilities raise key challenges in integrating these technologies more fully into creative practices. Iterative tweaking and divergent thinking remain key to enabling creativity support using technology6,7, yet these practices are insufficiently supported by state-of-the-art generative AI models. Using game development as a lens, we demonstrate that we can make use of an understanding of user needs to drive the development and evaluation of generative AI models in a way that aligns with these creative practices. Concretely, we introduce a state-of-the-art generative model, the World and Human Action Model (WHAM), and show that it can generate consistent and diverse gameplay sequences and persist user modifications—three capabilities that we identify as being critical for this alignment. In contrast to previous approaches to creativity support tools that required manually defining or extracting structure for relatively narrow domains, generative AI models can learn relevant structure from available data, opening the potential for a much broader range of applications.