To Uncertainty and Beyond: Identifying the Capabilities Needed by Hospitals to Function in Dynamic Environments

Hospitals operate in increasingly complex and dynamically uncertain environments. To understand how hospital organizations can cope with such profound uncertainty, this article presents a multiple case study of five hospitals during the COVID-19 crisis in a heavily hit region of the Netherlands. We find that hospitals make adaptations in five key categories, namely: reorganization, decision-making, human resources, material resources, and planning. These adaptations offer insights into the core capabilities needed by hospitals to cope with dynamic uncertainty. Our findings highlight the need for hospitals to become more flexible without sacrificing efficiency. Organizations can accomplish this by building in more sensing and seizing capabilities to be better prepared for and respond to environmental change. Furthermore, transforming capabilities allow organizations to be more resilient and responsive in the face of ongoing uncertainty. We make recommendations on how hospitals can build these capabilities and address the core challenges they face in this pursuit.

Optimal adaptive computed torque control for haptic-teleoperation system with uncertain dynamics

This study aimed to eliminate dynamic uncertainty, one of the main problems of haptic teleoperation robotic systems. The optimal adaptive computed torque control method was used to overcome this problem. As is known, excellent stability and transparency are required in teleoperation systems. However, dynamic uncertainty that causes stability problems in the control of these systems also causes poor performance. In conventional adaptive computed torque control methods, updating the parameters of the system is generally discussed, but updating the control coefficients of vital importance in the control of the system is not considered. In the proposed method, an adaptation rule has been created to update uncertain parameters. In addition, the gray wolf optimization algorithm, one of the current optimization algorithms, has been proposed and applied to obtain the control coefficients of the system. The position tracking stability of the system was examined by using Lyapunov stability analysis method. As a result, both simulation and real-time optimal adaptive computational torque control method were used and bilateral position and force control was performed and the performance results of the system are obtained graphically and examined. Optimal adaptive computed torque control method obtained using the gray wolf optimization algorithm was used first in the literature search and success results have been obtained. In this regard, the authors have the idea that this work is an innovative aspect of both simulation and real time with the optimal adaptive computed torque control method.

Mature field Development to Periphery Area: Tambora West Flank development

Tambora gas field, discovered in 1974 is located in a swamp area at the apex of Mahakam Delta, and it is adjacent to Nilam field, which is operated by another operator. Geologically, the Tambora and Nilam Fields have the same anticline structure that originates from the sediment provenance west of Kalimantan as reflected in present day Mahakam Delta. Therefore, this study aims to analyze the challenges to unlock the potential of the west flank area of Tambora Fields. The geological synthesis of both Tambora and Nilam fields shows similar net sand and pay distribution in lateral and vertical proportions. Most developments in the Tambora Anticline area are in the crest and the distances between wells are ~100-200m. Challenges to unlock potential in flank areas are derived from the limitation of wells and seismic data. Based on data and knowledge of the flank areas in both fields, the west flank has better productivity compared to the east. Therefore, geological synthesis is conducted in the west flank area to define hydrocarbon and reservoir properties. Furthermore, channel models were made from 2D seismic scouring, controlled by the continuation of well log channel facies in the anticline crest area. Based on the preliminary approach, 3 wells were proposed to unlock west flank Tambora potential and were integrated into the plan of development. Primarily, dynamic uncertainty affects the potential of the west flank since production in the anticline crest area is enormous, and the uncertainty was analyzed by drilling one recent well. The result shows that hydrocarbon in the flank is not fully connected with the anticline crest area and has proven the sidebar heterogeneity concept. These gave more confidence to seek further positive results and develop west flank Tambora to sustain Mahakam production in the future.

Artificial Intelligence for Sustainable Complex Socio-Technical-Economic-Ecosystems.

The strong couplings among ecological, economic, social and technological processes explains the complexification of human-made systems, and phenomena such as globalization, climate change, the increased urbanization and inequality of human societies, the power of information, and the COVID-19 syndemics. Among complexification’s essential features are non-decomposability, asynchronous behavior, components with many degrees of freedom, increased likelihood of catastrophic events, irreversibility, nonlinear phase spaces with immense combinatorial sizes, and the impossibility of long-term, detailed prediction. Sustainability for complex systems implies enough efficiency to explore and exploit their dynamic phase spaces and enough flexibility to coevolve with their environments. This in turn means solving intractable nonlinear semi-structured dynamic multi-objective optimization problems, with conflicting, incommensurable, non-cooperative objectives and purposes, under dynamic uncertainty, restricted access to materials, energy and information, and a given time horizon, aiming at enhancing the co-evolutionary power of the Biosphere and its human subsystems. Giving the high-stakes, the need for effective, efficient, diverse solutions, their local-global, present-future effects, and their unforeseen short, medium and long-term impacts, achieving sustainable complex systems implies the need for Sustainability-designed Universal Intelligent Agents, harnessing the strong functional coupling between human, artificial and nonhuman biological intelligence in a no-zero-sum game to achieve sustainability.

Iterative learning NARMA-L2 control for turbofan engine with dynamic uncertainty in flight envelope

Nonlinear control of turbofan engines in the flight envelope has attracted much attention in consideration of the inherent nonlinearity of the engine dynamics. Most nonlinear control design techniques rely on the correction theory of reference model parameter to extend the typical flight operations from ground operation. However, dynamic uncertainties in flight envelope lead to the deviation of operating state, and it is negative to control performance. This article is to develop online correction neural network–based speed control approaches for the turbofan engine with dynamic uncertainty in the flight envelope. Two improved online correction nonlinear ways combined with nonlinear autoregressive moving average (NARMA) are proposed, such as gradient search nonlinear autoregressive moving average with feedback linearization (NARMA-L2) control and iterative learning NARMA-L2 control. The contribution of this article is to provide better control quality of fast regulation and less steady errors of engine speed by the proposed methodology in comparison to the conventional NARMA-L2 control. Some important results are reached on both turbofan engine controller design and dynamic uncertainty tolerance at the typical flight operations, and the numerical examples demonstrate the superiority of the proposed control in the flight envelope.

The Genesis of Socio-Philosophical Understanding of the Peace and War Relationship in the Social World Development

The article is devoted to research the genesis of the relationship between peace and war in the development of the social world was determined. It was found that the social world in concrete historical manifestations was considered by philosophers through the functioning of state-building processes of government and self-organization, and the absolutization of one of them led to war, and harmonization – to peace. The stages of formation of the problem were traced and the traditions of understanding the social world were determined. The first stage was characterized by the study of the world as a cosmic phenomenon – in the natural philosophical, mythological and cosmogonic traditions – and social – in the socio-organic, polis, paternalistic-subject traditions. The second stage – the dominance of the theocentric position – was characterized by the distinction between Heaven and Earth. The third stage – modernism – was marked by the dominance of the objectified world in connection with the invention of printing, the development of the institute of education, institutionalization of science. The fourth – stage of industrial institutionalization and world institutions, which was characterized by the consideration of peace and war as a world phenomenon, marked by ideological, idealistic, materialistic, managerial, psychological and peacekeeping traditions. In the fifth – the stage of information and virtual worlds formation, which took place in the integrity of the relationship “society – technology”, it was highlighted the system-holistic tradition. The sixth is the modern stage of the synergetic world, defined by the phenomena of hybrid and network war and peace and connected with the hybrid, network and synergetic traditions. Here the problem of the world as a whole in the dynamic uncertainty and technological aspect of the subjects’ activity is actualized.