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Institution

Aalto University

EducationEspoo, Finland
About: Aalto University is a education organization based out in Espoo, Finland. It is known for research contribution in the topics: Population & Carbon nanotube. The organization has 9969 authors who have published 32648 publications receiving 829626 citations. The organization is also known as: TKK & Aalto-korkeakoulu.


Papers
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Journal ArticleDOI
TL;DR: The implementation of the time-dependent density-functional theory both in linear-response and in time-propagation formalisms using the projector augmented-wave method in real-space grids is presented.
Abstract: We present the implementation of the time-dependent density-functional theory both in linear-response and in time-propagation formalisms using the projector augmented-wave method in real-space grids. The two technically very different methods are compared in the linear-response regime where we found perfect agreement in the calculated photoabsorption spectra. We discuss the strengths and weaknesses of the two methods as well as their convergence properties. We demonstrate different applications of the methods by calculating excitation energies and excited state Born–Oppenheimer potential surfaces for a set of atoms and molecules with the linear-response method and by calculating nonlinear emission spectra using the time-propagation method.

188 citations

Journal ArticleDOI
Minna Halme1
TL;DR: In this paper, the authors investigated learning toward sustainable development in multi-stakeholder public-private networks and found that the process of cooperation appears more important vis-a-vis achievements regarding sustainable tourism than the structure of networks.
Abstract: The present study investigates learning toward sustainable development in multi-stakeholder public–private networks. The evidence is grounded in the data from six tourism networks in four European countries. The process of cooperation appears more important vis-a-vis achievements regarding sustainable tourism than the structure of networks. This process will determine the network's ability to become adept at explicating tacit knowledge among its actors, and to develop the network so it can facilitate the creation of sustainability outcomes. A leading public actor may assume a ‘teacher's’ role in the network. In these instances, the network runs a risk of becoming merely an information dissemination tool. This involves a trap of one-way communication and under-used knowledge utilization opportunities. Receptivity of the teacher actor is low and the partners do not really collaborate. The teacher actor should make a special effort to create feedback loops leading to two-way communication, so that a learning strategy of collaboration can take place. The findings also imply that in some networks with a public leader there is an overly high belief in the ability of information dissemination and classroom education to promote learning about sustainable development although learning about sustainability in the practical level requires concrete results and joint action. Copyright © 2001 John Wiley & Sons, Ltd and ERP Environment

188 citations

Journal ArticleDOI
TL;DR: In this paper, the authors provide a holistic overview on the exploitation of MEC technology for the realization of IoT applications and their synergies, and discuss the technical aspects of enabling MEC in IoT and provide some insight into various other integration technologies therein.
Abstract: The Internet of Things (IoT) has recently advanced from an experimental technology to what will become the backbone of future customer value for both product and service sector businesses. This underscores the cardinal role of IoT on the journey towards the fifth generation (5G) of wireless communication systems. IoT technologies augmented with intelligent and big data analytics are expected to rapidly change the landscape of myriads of application domains ranging from health care to smart cities and industrial automations. The emergence of Multi-Access Edge Computing (MEC) technology aims at extending cloud computing capabilities to the edge of the radio access network, hence providing real-time, high-bandwidth, low-latency access to radio network resources. IoT is identified as a key use case of MEC, given MEC's ability to provide cloud platform and gateway services at the network edge. MEC will inspire the development of myriads of applications and services with demand for ultra low latency and high Quality of Service (QoS) due to its dense geographical distribution and wide support for mobility. MEC is therefore an important enabler of IoT applications and services which require real-time operations. In this survey, we provide a holistic overview on the exploitation of MEC technology for the realization of IoT applications and their synergies. We further discuss the technical aspects of enabling MEC in IoT and provide some insight into various other integration technologies therein.

188 citations

Posted Content
TL;DR: In this paper, a 3D articulated Gaussian mixture alignment strategy is proposed for real-time simultaneous tracking of hands manipulating and interacting with external objects using a single commodity RGB-D camera.
Abstract: Real-time simultaneous tracking of hands manipulating and interacting with external objects has many potential applications in augmented reality, tangible computing, and wearable computing. However, due to difficult occlusions, fast motions, and uniform hand appearance, jointly tracking hand and object pose is more challenging than tracking either of the two separately. Many previous approaches resort to complex multi-camera setups to remedy the occlusion problem and often employ expensive segmentation and optimization steps which makes real-time tracking impossible. In this paper, we propose a real-time solution that uses a single commodity RGB-D camera. The core of our approach is a 3D articulated Gaussian mixture alignment strategy tailored to hand-object tracking that allows fast pose optimization. The alignment energy uses novel regularizers to address occlusions and hand-object contacts. For added robustness, we guide the optimization with discriminative part classification of the hand and segmentation of the object. We conducted extensive experiments on several existing datasets and introduce a new annotated hand-object dataset. Quantitative and qualitative results show the key advantages of our method: speed, accuracy, and robustness.

188 citations

Journal ArticleDOI
TL;DR: The Roadmap on Magnonics as mentioned in this paper is a collection of 22 sections written by leading experts in this field who review and discuss the current status but also present their vision of future perspectives.
Abstract: Magnonics is a rather young physics research field in nanomagnetism and nanoscience that addresses the use of spin waves (magnons) to transmit, store, and process information. After several papers and review articles published in the last decade, with a steadily increase in the number of citations, we are presenting the first Roadmap on Magnonics. This a collection of 22 sections written by leading experts in this field who review and discuss the current status but also present their vision of future perspectives. Today, the principal challenges in applied magnonics are the excitation of sub-100 nm wavelength magnons, their manipulation on the nanoscale and the creation of sub-micrometre devices using low-Gilbert damping magnetic materials and the interconnections to standard electronics. In this respect, magnonics offers lower energy consumption, easier integrability and compatibility with CMOS structure, reprogrammability, shorter wavelength, smaller device features, anisotropic properties, negative group velocity, non-reciprocity and efficient tunability by various external stimuli to name a few. Hence, despite being a young research field, magnonics has come a long way since its early inception. This Roadmap represents a milestone for future emerging research directions in magnonics and hopefully it will be followed by a series of articles on the same topic.

188 citations


Authors

Showing all 10135 results

NameH-indexPapersCitations
John B. Goodenough1511064113741
Ashok Kumar1515654164086
Anne Lähteenmäki11648581977
Kalyanmoy Deb112713122802
Riitta Hari11149143873
Robin I. M. Dunbar11158647498
Andreas Richter11076948262
Mika Sillanpää96101944260
Muhammad Farooq92134137533
Ivo Babuška9037641465
Merja Penttilä8730322351
Andries Meijerink8742629335
T. Poutanen8612033158
Sajal K. Das85112429785
Kalle Lyytinen8442627708
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023101
2022342
20212,842
20203,030
20192,749
20182,719