Open World Research Articles

Review: Ludified, edited by Marko Ciciliani, Barbara Lüneburg, and Andreas Pirchner

Review: <i>Ludified</i>, edited by Marko Ciciliani, Barbara Lüneburg, and Andreas Pirchner

Active Learning for Domain Adaptation: An Energy-Based Approach

Unsupervised domain adaptation has recently emerged as an effective paradigm for generalizing deep neural networks to new target domains. However, there is still enormous potential to be tapped to reach the fully supervised performance. In this paper, we present a novel active learning strategy to assist knowledge transfer in the target domain, dubbed active domain adaptation. We start from an observation that energy-based models exhibit free energy biases when training (source) and test (target) data come from different distributions. Inspired by this inherent mechanism, we empirically reveal that a simple yet efficient energy-based sampling strategy sheds light on selecting the most valuable target samples than existing approaches requiring particular architectures or computation of the distances. Our algorithm, Energy-based Active Domain Adaptation (EADA), queries groups of target data that incorporate both domain characteristic and instance uncertainty into every selection round. Meanwhile, by aligning the free energy of target data compact around the source domain via a regularization term, domain gap can be implicitly diminished. Through extensive experiments, we show that EADA surpasses state-of-the-art methods on well-known challenging benchmarks with substantial improvements, making it a useful option in the open world. Code is available at https://github.com/BIT-DA/EADA.

Vis-NIR hyperspectral imaging combined with incremental learning for open world maize seed varieties identification

There are many maize seed varieties circulating on the Chinese market, some varieties will be added and eliminated by the government every year, and fake varieties cannot be exhaustively listed. Furthermore, the updating of some varieties requires retraining the entire model, which is time-consuming and laborious. This poses a huge challenge for the authenticity identification of varieties and online model updating. Herein, hyperspectral imaging (HSI) combined with incremental learning (IL) was used to solve this problem. A novel radial basis function-biomimetic pattern recognition (RBF-BPR) model for IL was proposed and compared with one-class support vector machine (OCSVM) and BPR models under two test schemes. Hyperspectral images of five varieties of maize seeds were collected, and convolutional autoencoder (CAE) was used to extract features to remove redundant information and improve the generalization ability of models. A unique hybrid model was designed for each variety respectively, and the IL process was simulated. In two test schemes, the overall correct acceptance rate (CAR) for the known varieties and the overall correct rejection rate (CRR) for the unknown varieties of CAE-RBF-BPR model both reached 100%, which was superior to CAE-OCSVM and CAE-BPR models. Especially after RBF was used to map data, the performance of RBF-BPR model had a qualitative improvement compared with the original BPR model. In summary, the proposed method can realize IL without accessing the old classes data, while meeting the requirements of identifying known varieties and rejecting unknown varieties. In addition, if some varieties are eliminated by the government in the future, the corresponding models can also be removed form the whole system. The combination of such method and HSI has a broad application prospect in the identification of maize seed varieties, thus avoiding the trouble of retraining entire model when some maize seed varieties need to be updated.

The Eutopian City: The Challenge of Urban Conviviality in the Laudato Si’ and Fratelli Tutti Encyclicals

Abstract This article aims to show how the concept of the eutopian city can be used as a key for reading Pope Francis’s latest two encyclicals (Laudato Si’, from 2015 and Fratelli Tutti, from 2020). We highlight the ideal of conviviality in the notion of common home, political love, and social friendship, whose paradigm in contemporary urban life would be the experience of neighbourhood. This involves thinking of the city as a space of conviviality and the construction of a common project of society, overcoming the divisions of a closed world in favour of an open world. The papal texts therefore reveal formulation of a political proposal precisely at the time when politics was dying, fostered by new climate conditions and the renewed culture of walls.

Analyzing education based on metaverse technology

The Metaverse is a post-reality universe, a perpetual multi-user environment that combines physical reality and digital virtuality. It is based on the convergence of technologies that enable multisensory interactions with virtual environments, digital objects, and people, such as virtual reality (VR) and augmented reality (AR). As a result, Metaverse is a web of social, networked immersive environments on persistent multi-user platforms. It allows for real-time, embodied user communication and dynamic interactions with digital artifacts. Its first incarnation was a web of virtual worlds between which avatars could teleport. The modern Metaverse includes social, immersive VR platforms that are compatible with massive multiplayer online video games, open game worlds, and AR collaborative spaces.&#x0D; The aim of the research is to thoroughly examine the perceptions and educational requirements of Metaverse-based education and to investigate its educational applicability. Using a mixed research method, the study investigated instructors' and students' perceptions of the use of the Metaverse in education, as well as the support system for classes that use the Metaverse. And determining the implications for action. plans and directions for its application in education.

EDUCATION OF ARCHITECTURAL ENGINEERS IN SERBIA FOR THE SUSTAINABLE DEVELOPMENT MODEL

Understanding the developmental needs of society, engineers have always enabled the development of civilization. Due to the challenges they faced and the tasks that await engineers in the future, there is a need for their new knowledge and skills, necessary to solve problems related to the paradigm of sustainable development. This paper analyzes the requirements of the sustainable development model and the role of architectural engineers in creating solutions within this model. The basic potential for sustainable development consists of educated and professional people in general, education and training of architectural engineers for efficient performance, in modern conditions imposed by globalization with strong competition in the open world market and knowledge society.

Використання супутникових продуктів для аналізу змін територій природно-заповідного фонду України

Дана робота присвячена дослідженню тимчасових змін типів земногопокриву в межах природно-заповідного фонду України. Перш за все, цеаналіз зміни лісового покриву (вирубка чи лісовідновлення) за відкритимиданими Global Forest Change 2000–2020 з просторовою роздільноюздатністю 30 м з визначенням найбільш проблемних типів заповідників, девідбувалась вирубка лісів у 2000–2020 рр. Іншим аспектом дослідженняє моніторинг використання земель природно-заповідного фонду длясільського господарства, зміни площ сільськогосподарських полів у часі таїх порівняння. Це дослідження проведено на основі власних карт земногопокриву з просторовою роздільною здатністю 10 м за 2016–2020 рр., а такожу порівнянні з відкритим набором даних World Cover Map для Україниза 2020 р. Для створення власних карт земного покриву для всієї Українивикористані оптичні супутникові (Sentinel–2) та радарні дані (Sentinel–1).У роботі описана технологія побудови карт класифікації земного покривудля великих територій на основі супутникових даних. Розглянуто основніетапи попередньої обробки супутникових даних, методологія злиттяданих різної та однорідної природи за різні часові дати. За допомогоюнаборів геопросторових продуктів досліджено динаміку змін площі лісу тапосівних угідь за різними видами природно-заповідного фонду України за2000–2020 рр. Найбільшу частку ліси займають в заповідних урочищах,парках-пам’ятках садово-паркового мистецтва та дендрологічних парках(більше 73 % лісів), з яких найбільші зміни відбулися в заповідних урочищах на 1,81 % площ (1,7 тис. га) та дендрологічних парках — на 1,02 %площ (17 га). Дослідження та результати показали, що в цілому на національному рівні зміни з часом не суттєві (до 3 % для лісів і до 2 % длясільськогосподарських площ), однак вони мають велике значення,оскільки природні ресурси обмежені, а якість життя людства залежитьнасамперед від природи, екології та якості навколишнього середовища.

Wither the Trade Regime?

Abstract Democratic governance, liberal values, and the open trading regime are facing interconnected existential challenges. For most of the post-WWII period, they were “legs to the same stool.” Today, the connections among the three have frayed, and this has implications for the future of the liberal international economic order. While the trade regime successfully incorporated smaller autocratic states, the rise of China and increasing tension among signatories to the WTO has challenged the rule-based trading system. This essay argues that even with these divisions among the memberships, all trading nations, including China, need the General Agreement on Tariffs and Trade (GATT)/WTO. Trade requires market predictability; exporters and their home governments require some means to adjudicate conflict. The GATT/WTO remains the best, and perhaps the only, organization that can facilitate such coordination and finesse the changing nature of the international system to assure an open world economy.

Avoiding Negative Side Effects of Autonomous Systems in the Open World

Autonomous systems that operate in the open world often use incomplete models of their environment. Model incompleteness is inevitable due to the practical limitations in precise model specification and data collection about open-world environments. Due to the limited fidelity of the model, agent actions may produce negative side effects (NSEs) when deployed. Negative side effects are undesirable, unmodeled effects of agent actions on the environment. NSEs are inherently challenging to identify at design time and may affect the reliability, usability and safety of the system. We present two complementary approaches to mitigate the NSE via: (1) learning from feedback, and (2) environment shaping. The solution approaches target settings with different assumptions and agent responsibilities. In learning from feedback, the agent learns a penalty function associated with a NSE. We investigate the efficiency of different feedback mechanisms, including human feedback and autonomous exploration. The problem is formulated as a multi-objective Markov decision process such that optimizing the agent’s assigned task is prioritized over mitigating NSE. A slack parameter denotes the maximum allowed deviation from the optimal expected reward for the agent’s task in order to mitigate NSE. In environment shaping, we examine how a human can assist an agent, beyond providing feedback, and utilize their broader scope of knowledge to mitigate the impacts of NSE. We formulate the problem as a human-agent collaboration with decoupled objectives. The agent optimizes its assigned task and may produce NSE during its operation. The human assists the agent by performing modest reconfigurations of the environment so as to mitigate the impacts of NSE, without affecting the agent’s ability to complete its assigned task. We present an algorithm for shaping and analyze its properties. Empirical evaluations demonstrate the trade-offs in the performance of different approaches in mitigating NSE in different settings.

Are libraries sustainable in the new open science world?

Are libraries sustainable in the new open science world?

On Trade Agreements and a Social Reproduction Approach to GVCs: A Reply to Donatella Alessandrini

Abstract The 15 years following the 2008–2009 global financial crisis witnessed increasing questioning in the global North of the distribution of the gains and costs of an open world economy and the multilateral rules-based trade order. Difficulties in (re-)negotiating trade agreements in the World Trade Organization led states to shift even more of their focus to reciprocal and bilateral trade agreements as these internalize benefits among partners by continuing to maintain trade barriers against non-signatories (mostly emerging economies). There is a vigorous debate across academic disciplines whether such agreements help to increase participation in global value chains (GVCs) by signatory nations and the magnitude and incidence of the associated economic, social and environmental impacts – positive or negative. These are questions calling for rigorous empirical research that assesses impacts against appropriate baselines and counterfactuals and investment in data collection, monitoring and evaluation by participating governments. Mischaracterizing both the extent to which trade agreements constrain the ability of states to regulate and reports published by international organizations on GVCs and trade agreements detracts from where the focus arguably should be: providing compelling empirical evidence that GVCs and trade agreements detrimentally affect social reproduction and specific suggestions on how the design of trade agreements should be changed to improve outcomes.

The Transdisciplinary Encounter of Narratology and Visual Art in MMORPGs

The aim of this paper is to present and analyze visual elements of MMORPG (Massively Multiplayer Online Role-playing Game) storyworlds as important aspects of both world-building and the immersion capacity of virtual worlds. MMORPGs are characterized by multi-user environments called ‘open worlds’, in which maps and geography of space play an important role. Geography and maps that represent these geographical forms in the game play a significant role in creating the worldness of virtual space and the narratives located in them. The same goes for the features of architecture, natural or outer space expanses. Visual elements contribute to the narrative in numerous ways, which is analyzed in detail using a transdisciplinary approach – the narratological apparatus and especially the shift towards postclassical narratology. Another, but not less important visual aspect that will be presented in the paper is the importance of character appearance, as well as clothing (armors) and equipment in the context of building character identity for themself (the player) and the way they present themselves to other players. All of these aspects indicate that visual space (geographical and architectural) as well as visual characteristics of the characters have an important role in storytelling, supporting the transmedial praxis of contemporary narrative forms. Article received: December 23, 2021; Article accepted: February 1, 2022; Published online: April 15, 2022; Original scholarly article

Using GIS to Understand Healthcare Access Variations in Flood Situation in Surabaya

This paper proposes to identify the variation of accessibility to healthcare facilities based on vulnerability assessments of floods by using open source data. The open source data comprises Open Street Map (OSM), world population, and statistical data. The accessibility analysis is more focused on vulnerable populations that might be affected by floods. Therefore, a vulnerability assessment is conducted beforehand to identify the location where the vulnerable population is located. A before and after scenario of floods is applied to evaluate the changes of healthcare accessibility. A GIS Network Analyst is chosen as the accessibility analysis tool. The results indicate that the most vulnerable population lives in the Asemrowo district. The service area analysis showed that 94% of the West of Surabaya was well-serviced in the before scenario. Otherwise, the decrement of service area occurs at the city center in the after scenario. Thus, the disaster manager can understand which vulnerable area is to be more prioritized in the evacuation process.

Open World Active Learning for Echocardiography View Classification.

Existing works for automated echocardiography view classification are designed under the assumption that the views in the testing set must belong to a limited number of views that have appeared in the training set. Such a design is called closed world classification. This assumption may be too strict for real-world environments that are open and often have unseen examples, drastically weakening the robustness of the classical view classification approaches. In this work, we developed an open world active learning approach for echocardiography view classification, where the network classifies images of known views into their respective classes and identifies images of unknown views. Then, a clustering approach is used to cluster the unknown views into various groups to be labeled by echocardiologists. Finally, the new labeled samples are added to the initial set of known views and used to update the classification network. This process of actively labeling unknown clusters and integrating them into the classification model significantly increases the efficiency of data labeling and the robustness of the classifier. Our results using an echocardiography dataset containing known and unknown views showed the superiority of the proposed approach as compared to the closed world view classification approaches.

Knowledge guided learning: Open world egocentric action recognition with zero supervision

• Current approaches are driven by data-hungry deep learning algorithms which require large amounts of annotated training data. • Deep learning models are inductive learners where the vocabulary is fixed and do not generalize beyond their training domain. • We address the problem of open world action recognition (i.e., unknown vocabulary) with Pattern Theory and Concept-Net. • Extensive experiments show our competitive performance for open world egocentric action recognition and object detection. Advances in deep learning have enabled the development of models that have exhibited a remarkable tendency to recognize and even localize actions in videos. However, they tend to experience errors when faced with scenes or examples beyond their initial training environment. Hence, they fail to adapt to new domains without significant retraining with large amounts of annotated data. In this paper, we propose to overcome these limitations by moving to an open-world setting by decoupling the ideas of recognition and reasoning. Building upon the compositional representation offered by Grenander’s Pattern Theory formalism, we show that attention and commonsense knowledge can be used to enable the self-supervised discovery of novel actions in egocentric videos in an open-world setting, where data from the observed environment (the target domain) is open i.e., the vocabulary is partially known and training examples (both labeled and unlabeled) are not available. We show that our approach can infer and learn novel classes for open vocabulary classification in egocentric videos and novel object detection with zero supervision . Extensive experiments show its competitive performance on two publicly available egocentric action recognition datasets (GTEA Gaze and GTEA Gaze+) under open-world conditions.

Learning Open-World Object Proposals Without Learning to Classify

Object proposals have become an integral pre-processing step of many vision pipelines including object detection, weakly supervised detection, object discovery, tracking, etc. Compared to the learning-free methods, learning-based proposals have become popular recently due to the growing interest in object detection. The common paradigm is to learn object proposals from data labeled with a set of object regions and their corresponding categories. However, this approach often struggles with novel objects in the open world that are absent in the training set. In this letter, we identify that the problem is that the binary classifiers in existing proposal methods tend to overfit to the training categories. Therefore, we propose a <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">classification-free</b> Object Localization Network (OLN) which estimates the objectness of each region purely by how well the location and shape of a region overlap with any ground-truth object (e.g., centerness and IoU). This strategy learns generalizable objectness and outperforms existing proposals on cross-category generalization on COCO. We further explore more challenging cross-dataset generalization onto RoboNet and EpicKitchens dataset, and long-tail detection on LVIS dataset. We demonstrate clear improvement over the state-of-the-art object detectors and object proposers. The code is publicly available at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/mcahny/object_localization_network</uri> .

Structured Action Prediction for Teleoperation in Open Worlds

Shared control can assist a human tele-operator in performing tasks on a remote robot, but also adds complexity in the user interface to allow the user to select the mode of assistance. This letter presents an expert action recommender framework that learns what actions are helpful to accomplish a task, and generates a minimal set of recommendations for display in the user interface. We address the learning problem in an open world context where the action choice depends on an unknown number of objects, i.e., the output domain of the prediction problem changes dynamically. Using structured prediction, we can simultaneously learn what actions to suggest and what objects those actions should act on. In experiments on three tasks in cluttered table-top environments, this method achieves over 90% accuracy in producing the correct suggestion in the top 5 predictions, and also generalizes well to novel tasks with limited training data.

The moon, the play and the end of history: A study of lunar temporality in Cyberpunk 2077

This article aims to analyse the representation of the moon in the open-world action RPG Cyberpunk 2077, released by CD Projekt Red in 2020, and its influence on a experience of time during the play. A close reading of CD Projekt’s title suggests a non-mimetic, cinematic and subjective approach to time in the game. Additionally, in Night City, the moon does not change its appearance and remains in its full phase almost until the end of the game. It serves as a bridge between the pre-designed narrative and the ludic interactions with the open world, creating an experience unique to the medium of video games. It signalizes that the player and their avatar V have entered the diachronic, atemporal space. At the same time, the lunar temporality can be read as an emanation of cyberpunk’s frozenness-in-time and its embrace of the neo-liberal version of the end of history.

After agency: The queer posthumanism of video games that cannot be played

This article offers a queer reading of Brent Watanabe’s 2016 video game–based art piece San Andreas Deer Cam, a mod of Grand Theft Auto V in which a computer-controlled deer wanders the game’s extensive open world. During the time that San Andreas Deer Cam was streamed live on Twitch, it became something of an internet sensation, drawing attention for its comedic elements and the deer’s seeming invisibility. I argue here that Watanabe’s piece can read in an alternative way: as a work of queer posthumanism. Drawing from game studies scholars whose research explores the non-human (such as Alenda Chang and Paolo Ruffino), as well as queer studies scholars who have theorized how posthumanism challenges norms of gender, sexuality, and intimacy (such as Dana Luciano and Mel Chen), I analyze video recordings of San Andreas Deer Cam. Through these videos, I articulate the piece’s posthumanist elements, with a focus on the implications of Watanabe’s choice to make the game unplayable and the powerful yet ambivalent picture the piece offers of queerness ‘beyond the human’. In San Andreas Deer Cam, queerness manifests in many forms, all of them wrapped up with the messy divide between peoples, animals, and machines: the visual erotics of the deer sensuously rendered backside, moments of sexual misrecognition as non-player characters appear to catcall the deer, even a prolonged scene in which the deer becomes the object of homophobic violence. Ultimately, I conclude, San Andreas Deer Cam offers a model for how video games themselves can be used to rethink the centrality of human agency, which has long been considered the defining feature of the medium. Watanabe’s piece serves as a provocation to consider the queer potential of games that are unplayable and of refusing – rather than doggedly pursuing – the supposed capacity of video games to place human players in control.

Globalization and climate change: State of knowledge, emerging issues, and policy implications

AbstractIn an integrated global economy, trade policy and climate policy are closely intertwined. This paper adopts an interdisciplinary approach to provide an overview of the key debates in economics, political science, and legal studies related to globalization and climate change. We identify a number of emerging issues that deserve increased attention in future research in this direction. These include international financial flows, migration, telecommunication, and digitization as well as changing lifestyles and consumption patterns across the globe. We also present potential research question regarding the diversification of import and export portfolios in the face of growing climate impacts and the decarbonization of industry, aviation, and shipping. Finally, we discuss how these recent developments could shape trade and climate policy formulation. We conclude that ambitious climate policies seem more likely to flourish in an open world trading system which provides sufficient flexibility for individual countries to adopt nationally appropriate climate policies.This article is categorized under: Climate Economics &gt; Economics and Climate Change