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in Architecture & Planning
Periodicals

Addressing Function Approximation Error in Actor-Critic Methods

In value-based reinforcement learning methods such as deep Q-learning, function approximation errors are known to lead to overestimated value estimates and suboptimal policies. We show that this problem persists in an actor-critic setting and propose novel mechanisms to minimize its effects on both the actor and the critic. Our algorithm builds on Double Q-learning, by taking the minimum value between a pair of critics to limit overestimation. We draw the connection between target networks and overestimation bias, and suggest delaying policy updates to reduce per-update error and further improve performance. We evaluate our method on the suite of OpenAI gym tasks, outperforming the state of the art in every environment tested.

Architecture & Planning• 2018• University of Amsterdam
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Agricultural Value Chains in Developing Countries A Framework for Analysis

The paper presents a framework for developing country value chain analysis made up of three components. The first consists of identifying major constraints for value chain upgrading: market access restrictions, weak infrastructures, lacking resources and institutional voids. In the second component three elements of a value chain are defined: value addition, horizontal and vertical chain-network structure and value chain governance mechanisms. Finally, upgrading options are defined in the area of value addition, including the search for markets, the value chain- network structure and the governance form of the chain. Part of this component is the identification of the most suitable partnerships for upgrading the value chain. The three components of the framework are derived from major theoretical streams on inter-company relationships and from the literature on developing country value chains. The framework is applied in a case example of a developing country value chain.

Architecture & Planning• 2011• University of Minnesota Rochester
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A Survey on OFDM-Based Elastic Core Optical Networking

Orthogonal frequency-division multiplexing (OFDM) is a modulation technology that has been widely adopted in many new and emerging broadband wireless and wireline communication systems. Due to its capability to transmit a high-speed data stream using multiple spectral-overlapped lower-speed subcarriers, OFDM technology offers superior advantages of high spectrum efficiency, robustness against inter-carrier and inter-symbol interference, adaptability to server channel conditions, etc. In recent years, there have been intensive studies on optical OFDM (O-OFDM) transmission technologies, and it is considered a promising technology for future ultra-high-speed optical transmission. Based on O-OFDM technology, a novel elastic optical network architecture with immense flexibility and scalability in spectrum allocation and data rate accommodation could be built to support diverse services and the rapid growth of Internet traffic in the future. In this paper, we present a comprehensive survey on OFDM-based elastic optical network technologies, including basic principles of OFDM, O-OFDM technologies, the architectures of OFDM-based elastic core optical networks, and related key enabling technologies. The main advantages and issues of OFDM-based elastic core optical networks that are under research are also discussed.

Architecture & Planning• 2012• Institute of Electrical and Electronics Engineers
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Periodicals

Crip Technoscience Manifesto

As disabled people engaged in disability community, activism, and scholarship, our collective experiences and histories have taught us that we are effective agents of world building and dismantling toward more socially just relations.The grounds for social justice and world remaking, however, are frictioned;technologies, architectures, and infrastructures are often designed and implemented without committing to disability as a difference that matters. This manifesto calls attention to the powerful, messy, non-innocent, contradictory, and nevertheless crucial work of what we name as “crip technoscience,” practices of critique, alteration, and reinvention of our material-discursive world. Disabled people are experts and designers of everyday life. But we also harness technoscience for political action, refusing to comply with demands to cure, fix, or eliminate disability. Attentive to the intersectional workings of power and privilege, we agitate against independence and productivity as requirements for existence. Instead, we center technoscientific activism and critical design practices that foster disability justice.

Architecture & Planning• 2019
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Periodicals

Bioprinting three-dimensional cell-laden tissue constructs with controllable degradation

Alginate hydrogel is a popular biologically inert material that is widely used in 3D bioprinting, especially in extrusion-based printing. However, the printed cells in this hydrogel could not degrade the surrounding alginate gel matrix, causing them to remain in a poorly proliferating and non-differentiating state. Here, we report a novel study of the 3D printing of human corneal epithelial cells (HCECs)/collagen/gelatin/alginate hydrogel incubated with a medium containing sodium citrate to obtain degradation-controllable cell-laden tissue constructs. The 3D-printed hydrogel network with interconnected channels and a macroporous structure was stable and achieved high cell viability (over 90%). By altering the mole ratio of sodium citrate/sodium alginate, the degradation time of the bioprinting constructs can be controlled. Cell proliferation and specific marker protein expression results also revealed that with the help of sodium citrate degradation, the printed HCECs showed a higher proliferation rate and greater cytokeratin 3(CK3) expression, indicating that this newly developed method may help to improve the alginate bioink system for the application of 3D bioprinting in tissue engineering.

Architecture & Planning• 2016• Nature Portfolio
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Limited Data Rolling Bearing Fault Diagnosis With Few-Shot Learning

This paper focuses on bearing fault diagnosis with limited training data. A major challenge in fault diagnosis is the infeasibility of obtaining sufficient training samples for every fault type under all working conditions. Recently deep learning based fault diagnosis methods have achieved promising results. However, most of these methods require large amount of training data. In this study, we propose a deep neural network based few-shot learning approach for rolling bearing fault diagnosis with limited data. Our model is based on the siamese neural network, which learns by exploiting sample pairs of the same or different categories. Experimental results over the standard Case Western Reserve University (CWRU) bearing fault diagnosis benchmark dataset showed that our few-shot learning approach is more effective in fault diagnosis with limited data availability. When tested over different noise environments with minimal amount of training data, the performance of our few-shot learning model surpasses the one of the baseline with reasonable noise level. When evaluated over test sets with new fault types or new working conditions, few-shot models work better than the baseline trained with all fault types. All our models and datasets in this study are open sourced and can be downloaded from https://mekhub.cn/as/fault_diagnosis_with_few-shot_learning/.

Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
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Sustainable Business Models: A Review

During the past two decades of e-commerce growth, the concept of a business model has become increasingly popular. More recently, the research on this realm has grown rapidly, with diverse research activity covering a wide range of application areas. Considering the sustainable development goals, the innovative business models have brought a competitive advantage to improve the sustainability performance of organizations. The concept of the sustainable business model describes the rationale of how an organization creates, delivers, and captures value, in economic, social, cultural, or other contexts, in a sustainable way. The process of sustainable business model construction forms an innovative part of a business strategy. Different industries and businesses have utilized sustainable business models’ concept to satisfy their economic, environmental, and social goals simultaneously. However, the success, popularity, and progress of sustainable business models in different application domains are not clear. To explore this issue, this research provides a comprehensive review of sustainable business models literature in various application areas. Notable sustainable business models are identified and further classified in fourteen unique categories, and in every category, the progress -either failure or success- has been reviewed, and the research gaps are discussed. Taxonomy of the applications includes innovation, management and marketing, entrepreneurship, energy, fashion, healthcare, agri-food, supply chain management, circular economy, developing countries, engineering, construction and real estate, mobility and transportation, and hospitality. The key contribution of this study is that it provides an insight into the state of the art of sustainable business models in various application areas and future research directions. This paper concludes that popularity and the success rate of sustainable business models in all application domains have been increased along with the increasing use of advanced technologies.

Architecture & Planning• 2019• Multidisciplinary Digital Publishing Institute
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What Are You Feeling? Using Functional Magnetic Resonance Imaging to Assess the Modulation of Sensory and Affective Responses during Empathy for Pain

BACKGROUND: Recent neuroscientific evidence suggests that empathy for pain activates similar neural representations as the first-hand experience of pain. However, empathy is not an all-or-none phenomenon but it is strongly malleable by interpersonal, intrapersonal and situational factors. This study investigated how two different top-down mechanisms - attention and cognitive appraisal - affect the perception of pain in others and its neural underpinnings. METHODOLOGY/PRINCIPAL FINDINGS: We performed one behavioral (N = 23) and two functional magnetic resonance imaging (fMRI) experiments (N = 18). In the first fMRI experiment, participants watched photographs displaying painful needle injections, and were asked to evaluate either the sensory or the affective consequences of these injections. The role of cognitive appraisal was examined in a second fMRI experiment in which participants watched injections that only appeared to be painful as they were performed on an anesthetized hand. Perceiving pain in others activated the affective-motivational and sensory-discriminative aspects of the pain matrix. Activity in the somatosensory areas was specifically enhanced when participants evaluated the sensory consequences of pain. Perceiving non-painful injections into the anesthetized hand also led to signal increase in large parts of the pain matrix, suggesting an automatic affective response to the putatively harmful stimulus. This automatic response was modulated by areas involved in self/other distinction and valence attribution - including the temporo-parietal junction and medial orbitofrontal cortex. CONCLUSIONS/SIGNIFICANCE: Our findings elucidate how top-down control mechanisms and automatic bottom-up processes interact to generate and modulate other-oriented responses. They stress the role of cognitive processing in empathy, and shed light on how emotional and bodily awareness enable us to evaluate the sensory and affective states of others.

Architecture & Planning• 2007• Public Library of Science
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Competitive Coevolution through Evolutionary Complexification

Two major goals in machine learning are the discovery and improvement of solutions to complex problems. In this paper, we argue that complexification, i.e. the incremental elaboration of solutions through adding new structure, achieves both these goals. We demonstrate the power of complexification through the NeuroEvolution of Augmenting Topologies (NEAT) method, which evolves increasingly complex neural network architectures. NEAT is applied to an open-ended coevolutionary robot duel domain where robot controllers compete head to head. Because the robot duel domain supports a wide range of strategies, and because coevolution benefits from an escalating arms race, it serves as a suitable testbed for studying complexification. When compared to the evolution of networks with fixed structure, complexifying evolution discovers significantly more sophisticated strategies. The results suggest that in order to discover and improve complex solutions, evolution, and search in general, should be allowed to complexify as well as optimize.

Architecture & Planning• 2004• AI Access Foundation
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Periodicals

Intersubjectivity: Towards a Dialogical Analysis

Intersubjectivity refers to the variety of possible relations between perspectives. It is indispensable for understanding human social behaviour. While theoretical work on intersubjectivity is relatively sophisticated, methodological approaches to studying intersubjectivity lag behind. Most methodologies assume that individuals are the unit of analysis. In order to research intersubjectivity, however, methodologies are needed that take relationships as the unit of analysis. The first aim of this article is to review existing methodologies for studying intersubjectivity. Four methodological approaches are reviewed: comparative self‐report, observing behaviour, analysing talk and ethnographic engagement. The second aim of the article is to introduce and contribute to the development of a dialogical method of analysis. The dialogical approach enables the study of intersubjectivity at different levels, as both implicit and explicit, and both within and between individuals and groups. The article concludes with suggestions for using the proposed method for researching intersubjectivity both within individuals and between individuals and groups.

Architecture & Planning• 2009• Wiley
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Deep Learning for Change Detection in Remote Sensing Images: Comprehensive Review and Meta-Analysis

Deep learning (DL) algorithms are considered as a methodology of choice for remote-sensing image analysis over the past few years. Due to its effective applications, deep learning has also been introduced for automatic change detection and achieved great success. The present study attempts to provide a comprehensive review and a meta-analysis of the recent progress in this subfield. Specifically, we first introduce the fundamentals of deep learning methods which are frequently adopted for change detection. Secondly, we present the details of the meta-analysis conducted to examine the status of change detection DL studies. Then, we focus on deep learning-based change detection methodologies for remote sensing images by giving a general overview of the existing methods. Specifically, these deep learning-based methods were classified into three groups; fully supervised learning-based methods, fully unsupervised learning-based methods and transfer learning-based techniques. As a result of these investigations, promising new directions were identified for future research. This study will contribute in several ways to our understanding of deep learning for change detection and will provide a basis for further research. Some source codes of the methods discussed in this paper are available from: https://github.com/lazharkhelifi/deeplearning_changedetection_remotesensing_review.

Architecture & Planning• 2020• Institute of Electrical and Electronics Engineers
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Machine Learning for 5G/B5G Mobile and Wireless Communications: Potential, Limitations, and Future Directions

Driven by the demand to accommodate today's growing mobile traffic, 5G is designed to be a key enabler and a leading infrastructure provider in the information and communication technology industry by supporting a variety of forthcoming services with diverse requirements. Considering the ever-increasing complexity of the network, and the emergence of novel use cases such as autonomous cars, industrial automation, virtual reality, e-health, and several intelligent applications, machine learning (ML) is expected to be essential to assist in making the 5G vision conceivable. This paper focuses on the potential solutions for 5G from an ML-perspective. First, we establish the fundamental concepts of supervised, unsupervised, and reinforcement learning, taking a look at what has been done so far in the adoption of ML in the context of mobile and wireless communication, organizing the literature in terms of the types of learning. We then discuss the promising approaches for how ML can contribute to supporting each target 5G network requirement, emphasizing its specific use cases and evaluating the impact and limitations they have on the operation of the network. Lastly, this paper investigates the potential features of Beyond 5G (B5G), providing future research directions for how ML can contribute to realizing B5G. This article is intended to stimulate discussion on the role that ML can play to overcome the limitations for a wide deployment of autonomous 5G/B5G mobile and wireless communications.

Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
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The Lid Domain in Lipases: Structural and Functional Determinant of Enzymatic Properties

Lipases are important industrial enzymes. Most of the lipases operate at lipid-water interfaces enabled by a mobile lid domain located over the active site. Lid protects the active site and hence responsible for catalytic activity. In pure aqueous media, the lid is predominantly closed, whereas in the presence of a hydrophobic layer, it is partially opened. Hence, the lid controls the enzyme activity. In the present review, we have classified lipases into different groups based on the structure of lid domains. It has been observed that thermostable lipases contain larger lid domains with two or more helices, whereas mesophilic lipases tend to have smaller lids in the form of a loop or a helix. Recent developments in lipase engineering addressing the lid regions are critically reviewed here. After on, the dramatic changes in substrate selectivity, activity, and thermostability have been reported. Furthermore, improved computational models can now rationalize these observations by relating it to the mobility of the lid domain. In this contribution, we summarized and critically evaluated the most recent developments in experimental and computational research on lipase lids.

Architecture & Planning• 2017• Frontiers Media
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Immune System Dysregulation During Spaceflight: Potential Countermeasures for Deep Space Exploration Missions

Recent studies have established that dysregulation of the human immune system and the reactivation of latent herpesviruses persists for the duration of a 6-month orbital spaceflight. It appears certain aspects of adaptive immunity are dysregulated during flight, yet some aspects of innate immunity are heightened. Interaction between adaptive and innate immunity also seems to be altered. Some crews experience persistent hypersensitivity reactions during flight. This phenomenon may, in synergy with extended duration and galactic radiation exposure, increase specific crew clinical risks during deep space exploration missions. The clinical challenge is based upon both the frequency of these phenomena in multiple crewmembers during low earth orbit missions and the inability to predict which specific individual crewmembers will experience these changes. Thus, a general countermeasure approach that offers the broadest possible coverage is needed. The vehicles, architecture, and mission profiles to enable such voyages are now under development. These include deployment and use of a cis-Lunar station (mid 2020s) with possible Moon surface operations, to be followed by multiple Mars flyby missions, and eventual human Mars surface exploration. Current ISS studies will continue to characterize physiological dysregulation associated with prolonged orbital spaceflight. However, sufficient information exists to begin consideration of both the need for, and nature of, specific immune countermeasures to ensure astronaut health. This article will review relevant in-place operational countermeasures onboard ISS and discuss a myriad of potential immune countermeasures for exploration missions. Discussion points include nutritional supplementation and functional foods, exercise and immunity, pharmacological options, the relationship between bone and immune countermeasures, and vaccination to mitigate herpes (and possibly other) virus risks. As the immune system has sentinel connectivity within every other physiological system, translational effects must be considered for all potential immune countermeasures. Finally, we shall discuss immune countermeasures in the context of their individualized implementation or precision medicine, based on crewmember specific immunological biases.

Architecture & Planning• 2018• Frontiers Media
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Periodicals

A boost and bounce theory of temporal attention.

What is the time course of visual attention? Attentional blink studies have found that the 2nd of 2 targets is often missed when presented within about 500 ms from the 1st target, resulting in theories about relatively long-lasting capacity limitations or bottlenecks. Earlier studies, however, reported quite the opposite finding: Attention is transiently enhanced, rather than reduced, for several hundreds of milliseconds after a relevant event. The authors present a general theory, as well as a working computational model, that integrate these findings. There is no central role for capacity limitations or bottlenecks. Central is a rapidly responding gating system (or attentional filter) that seeks to enhance relevant and suppress irrelevant information. When items sufficiently match the target description, they elicit transient excitatory feedback activity (a "boost" function), meant to provide access to working memory. However, in the attentional blink task, the distractor after the target is accidentally boosted, resulting in subsequent strong inhibitory feedback response (a "bounce"), which, in effect, closes the gate to working memory. The theory explains many findings that are problematic for limited-capacity accounts, including a new experiment showing that the attentional blink can be postponed.

Architecture & Planning• 2008• American Psychological Association
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Dynamic interactions between forest structure and fire behavior in boreal ecosystems

<ja:p>This paper reviews and synthesizes literature on fire as a disturbance factor in boreal forests. Spatial and temporal variation in the biophysical environment, specifically, vegetative structure, terrain, and weather lead to variations in fire behavior. Changes in slope, aspect, elevation, and soil affect site energy and water budgets and the potential plant community. These terrain features also have a major influence on fire-caused disturbance through their role in determining moisture conditions and flammability of fuels on hourly, seasonal, and successional time-scales. On fine time scales (minutes to hours), changes in weather, specifically wind and relative humidity, significantly affect a fire’s intensity and aboveground effects. Normal seasonal changes in dryness and periodic drought influence fire intensity and severity principally by affecting the depth of burn and belowground effects. On decades-long time scales changes in vegetative structure affect the mass of fuel available for burning and therefore the potential energy that can be released during a fire. The severity of fire varies in time and space depending not only on the biophysical environment, but also on the location on the fire’s perimeter (head vs. flank vs. rear). Spatial and temporal variation in severity within a fire can have long-lasting impacts on the structure and species composition of post-fire communities and the potential for future disturbances. Characteristic temperature histories of ground, surface, and crown fires are used to illustrate variations in fire severity. A soil-heating model is used to illustrate the impact of varying depth of burn on the depth at which various fire effects occur in the soil profile. A conceptual model is presented for the effects of fire severity on fire-plant regeneration interactions. The conceptual model can be used by restoration ecologists to evaluate the differential effects of controlled or prescribed fires and wildfires and to plan and implement fire treatments to conserve biodiversity.</ja:p>

Architecture & Planning• 2002• Finnish Society of Forest Science
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Cloud Quantum Computing of an Atomic Nucleus

We report a quantum simulation of the deuteron binding energy on quantum processors accessed via cloud servers. We use a Hamiltonian from pionless effective field theory at leading order. We design a low-depth version of the unitary coupled-cluster ansatz, use the variational quantum eigensolver algorithm, and compute the binding energy to within a few percent. Our work is the first step towards scalable nuclear structure computations on a quantum processor via the cloud, and it sheds light on how to map scientific computing applications onto nascent quantum devices.

Architecture & Planning• 2018• American Physical Society
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Toward Social Internet of Vehicles: Concept, Architecture, and Applications

The main vision of the Internet of Things (IoT) is to equip real-life physical objects with computing and communication power so that they can interact with each other for the social good. As one of the key members of IoT, Internet of Vehicles (IoV) has seen steep advancement in communication technologies. Now, vehicles can easily exchange safety, efficiency, infotainment, and comfort-related information with other vehicles and infrastructures using vehicular ad hoc networks (VANETs). We leverage on the cloud-based VANETs theme to propose cyber-physical architecture for the Social IoV (SIoV). SIoV is a vehicular instance of the Social IoT (SIoT), where vehicles are the key social entities in the machine-to-machine vehicular social networks. We have identified the social structures of SIoV components, their relationships, and the interaction types. We have mapped VANETs components into IoT-A architecture reference model to offer better integration of SIoV with other IoT domains. We also present a communication message structure based on automotive ontologies, the SAE J2735 message set, and the advanced traveler information system events schema that corresponds to the social graph. Finally, we provide the implementation details and the experimental analysis to demonstrate the efficacy of the proposed system as well as include different application scenarios for various user groups.

Architecture & Planning• 2015• Institute of Electrical and Electronics Engineers
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Measuring Large-Scale Social Networks with High Resolution

This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years-the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection.

Architecture & Planning• 2014• Public Library of Science
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Solid-state batteries: The critical role of mechanics

Solid-state batteries with lithium metal anodes have the potential for higher energy density, longer lifetime, wider operating temperature, and increased safety. Although the bulk of the research has focused on improving transport kinetics and electrochemical stability of the materials and interfaces, there are also critical challenges that require investigation of the mechanics of materials. In batteries with solid-solid interfaces, mechanical contacts, and the development of stresses during operation of the solid-state batteries, become as critical as the electrochemical stability to keep steady charge transfer at these interfaces. This review will focus on stress and strain that result from normal and extended battery cycling and the associated mechanisms for stress relief, some of which lead to failure of these batteries.

Architecture & Planning• 2023• American Association for the Advancement of Science
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Privacy-Preserving Solutions for Blockchain: Review and Challenges

Blockchains offer a decentralized, immutable and verifiable ledger that can record transactions of digital assets, provoking a radical change in several innovative scenarios, such as smart cities, eHealth or eGovernment. However, blockchains are subject to different scalability, security and potential privacy issues, such as transaction linkability, crypto-keys management (e.g. recovery), on-chain data privacy, or compliance with privacy regulations (e.g. GDPR). To deal with these challenges, novel privacy-preserving solutions for blockchain based on crypto-privacy techniques are emerging to empower users with mechanisms to become anonymous and take control of their personal data during their digital transactions of any kind in the ledger, following a Self-Sovereign Identity (SSI) model. In this sense, this paper performs a systematic review of the current state of the art on privacy-preserving research solutions and mechanisms in blockchain, as well as the main associated privacy challenges in this promising and disrupting technology. The survey covers privacy techniques in public and permissionless blockchains, e.g. Bitcoin and Ethereum, as well as privacy-preserving research proposals and solutions in permissioned and private blockchains. Diverse blockchain scenarios are analyzed, encompassing, eGovernment, eHealth, cryptocurrencies, Smart cities, and Cooperative ITS.

Architecture & Planning• 2019• Institute of Electrical and Electronics Engineers
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