Digital substations, based on technologies like IEC 61850, are at the forefront of modern power grid advancements, offering enhanced automation, communication, and control capabilities. Mongolia's Ministry of Ener...
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this study explores the use of chaos engineering in evaluating the performance and resilience of serverless applications, which are built as complex distributed systems subject to different types of failures and error...
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the wave of maturing technology in the energy field on a global level, which includes both advanced energy production systems, storage devices, transport systems, as well as new metering methods from the consumer, bri...
the wave of maturing technology in the energy field on a global level, which includes both advanced energy production systems, storage devices, transport systems, as well as new metering methods from the consumer, bring to the fore a new concept of remodeled entire energy system with a future-oriented climate policy, more sustainable and more decarbonized. the present work proposes a new architectural paradigm for Smart Grids based on fractality, that represent an emerging structure of a medium voltage (MV) generation system consisting of several active low voltage (LV) networks. the control of the microgrid can be achieved in various ways, but in the work we pursued the realization of a structure arranged on several levels, ranked according to the fractal principles of organization. the optimization of the power dispatching of the multi-microgrid is presented in the improved form of a Cuckoo Search (CS) algorithm, which will bring benefits of power systems operation in accordance withthe cost condition of the market.
Nowadays, neurological diseases represent a medical emergency for which new prevention, monitoring and adequate treatment solutions are needed. ALAMEDA project proposes a monitoring solution for patients with Parkinso...
Nowadays, neurological diseases represent a medical emergency for which new prevention, monitoring and adequate treatment solutions are needed. ALAMEDA project proposes a monitoring solution for patients with Parkinson’s disease, Multiple Sclerosis, and Stroke, using multiple sensors and specific applications to collect information on the condition of health and aspects of lifestyle, activity level, sociability and mood. the paper describes the ALAMEDA infrastructure architecture and all processes to support the dedicated AI toolkit, along with all relevant concepts, components and interactions. Data collection methods are central to the objectives of the ALAMEDA project, as they are responsible for the acquisition of all data necessary for patient monitoring and evaluation during the pilot period. In this sense, the data flow for the data collection service for smart bracelets and smart insoles is presented, as well as how users interact withthese devices.
Artificial neural networks (ANN) closest to natural neural networks are a class of Deep Neural Networks (DNN) called Spiking Neural Networks (SNN). they are considered the 3rd (and next) generation of neural networks ...
Artificial neural networks (ANN) closest to natural neural networks are a class of Deep Neural Networks (DNN) called Spiking Neural Networks (SNN). they are considered the 3rd (and next) generation of neural networks and have promising behavior for reducing the gap between neuroscience inspired technologies and machine learning technologies, using models of neuron networks for computation. An SNN operates using spikes as time-stamped events for both input and output information. A spike occurrence is modeled by equations that represent a neuron membrane potential, which fires information when it reaches a certain potential (or threshold). the purpose of this paper is to analyze the current solutions for training SNNs, the current solutions for neuromorphic hardware, and to demonstrate there is potentiality in combining them.
the data security in e-Health applications is a big challenge, given the high sensitivity of the medical data and the requirements for a proper complexity vs. performance trade-off. In this case study the authenticati...
the data security in e-Health applications is a big challenge, given the high sensitivity of the medical data and the requirements for a proper complexity vs. performance trade-off. In this case study the authentication of the authorized users for medical databases is approached with biometrics. the paper presents an architectural and functional model for the biometric authentication with design for use-cases belonging to e-Health. the purpose is to enhance the security in e-Health applications requiring the remote access of the authorized users to medical data. the multimodal biometric system is presented with its architecture and data processing, in which a pre-classification fusion rule is specified. Different security levels according to the user’s roles are considered for the biometric data classifier.
For modeling cyber-physical systems (CPS) there is a multitude of languages to choose from, and often one needs more than one of the existing languages to cover all concerns to be considered. the design of CPS needs t...
For modeling cyber-physical systems (CPS) there is a multitude of languages to choose from, and often one needs more than one of the existing languages to cover all concerns to be considered. the design of CPS needs to go across languages, pertaining to different paradigms, and creating overlapping and combined challenges for reaching coherence. An appropriate selection of languages for creating a new CPS requires an in-depth analysis of the architecture viewpoints relevant to all the stake-holders’ concerns. this paper identifies and analyzes a set of viewpoints and their corresponding model kinds for UML and two of its profiles, SysML and MARTE, well-known for their applicability to cyber-physical systems. We discuss how the viewpoint coverage and the relationships between them can lead towards a recommendation system for choosing the right combination of languages, to be used by educators and software architects.
this paper addresses a kernel-based learning problem for a network of agents locally observing a latent multidimensional, nonlinear phenomenon in a noisy environment. We propose a learning algorithm that requires only...
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ISBN:
(纸本)9783031637582;9783031637599
this paper addresses a kernel-based learning problem for a network of agents locally observing a latent multidimensional, nonlinear phenomenon in a noisy environment. We propose a learning algorithm that requires only mild a priori knowledge about the phenomenon under investigation and delivers a model with corresponding non-asymptotic high probability error bounds. Both non-asymptotic analysis of the method and numerical simulation results are presented and discussed in the paper.
Psychomotor learning is an emerging research direction in the AIED (Artificial Intelligence in Education) field. this topic was introduced in the AIED research agenda back in 2016 in a contribution at the Internationa...
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ISBN:
(数字)9783031363368
ISBN:
(纸本)9783031363351;9783031363368
Psychomotor learning is an emerging research direction in the AIED (Artificial Intelligence in Education) field. this topic was introduced in the AIED research agenda back in 2016 in a contribution at the international Journal of AIED, where the SMDD (Sensing-Modelling-Designing-Delivering) process model to develop AIED psychomotor systems was introduced. Recently, a systematic review of the state of the art on this topic has also been published in the novel Handbook of AIED. In this context, the aim of the IPAIEDS tutorial is to motivate the AIED community to research on intelligent psychomotor systems and give tools to design, build and evaluate this kind of systems.
Micro-timing is an essential part of human music-making, yet it is absent from most computer music systems. Partly to address this gap, we present a novel system for generating music with style-specific micro-timing w...
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