The Applications of the New Technologies “E-Sensing” in Hospitals

Cannistraro, Mauro; Lorenzini, Enrico

doi:10.18280/ijht.340401

Cited by 20 publications

(17 citation statements)

References 20 publications

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“…Next, the CNN classification algorithm was contrasted with the support vector machine (SVM) classification algorithm (Cannistraro et al, 2016). The experimental groups are given in Table 2.…”

Section: Experimental Designmentioning

confidence: 99%

Hyperspectral Image Recognition Based on Artificial Neural Network

Liang¹,

Liu²,

Wang³

et al. 2018

Neuroquantology

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This paper aims to reduce the dimensions of the data in remote sensing hyperspectral image (HIS), and solve the information redundancy caused by the numerous bands in the image. To this end, the neural network sensitivity analysis (NNSA) was introduced to simplify the dimensionality reduction process. Meanwhile, the convolutional neural network (CNN) was adopted as the classification algorithm for the HIS, seeking to prevent the complex data reconstruction of feature extraction and classification. Then, the proposed method was contrasted with several other classification methods in several experiments. The results show that the proposed method outperformed the contrast plans in classification accuracy. Thus, the artificial neural network (ANN) is good at reducing the dimensions of remote sensing HSI and the CNN is a reliable classification tool. The research findings shed new light on remote sensing image processing and other related operations.

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Section: Experimental Designmentioning

confidence: 99%

Hyperspectral Image Recognition Based on Artificial Neural Network

Liang¹,

Liu²,

Wang³

et al. 2018

Neuroquantology

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“…This aimed at complying with legal mandates and least-cost service obligations, in which utilities must help their customers save energy. Particular attention was devoted to exploring techniques that incorporate psychology, design, and behavioral economics insights into the utility of energy-efficient programs, that could use "e-sensing" technologies [36].…”

Section: Energy Consumption and Behavioral Economicsmentioning

confidence: 99%

A Behavioral Economics Approach to Residential Electricity Consumption

et al. 2017

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Consumer behavior is complex and is difficult to represent in traditional economic theories of decision-making. This paper focuses on the development of an agent-based approach to analyze people's behavior in consuming electricity using a behavioral economics framework, where the consumer is the main agent of power systems. This approach may bring useful insights for distribution companies and regulatory agencies, helping to shift thinking to a more user-centric approach. The emergent properties of electricity consumption are modeled by the means of consumer's heuristics, taking into account the electricity price, consumer's satisfaction level, willingness to invest in new technologies, social interactions, and marketing strategies by the power utility. Analysis on the emergent behavior of this approach through simulation studies showed that it is indeed valuable, as does not require in-depth data of all details on human behavior. However, it contributes to the understanding of relations among various objects involved in electricity consumption.

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“…The use of smart technologies "e-sensors" in the field of environmental monitoring, in residential buildings [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29], hospitals and in the field of the historical buildings under protection and safeguard, will make achieve significant developments in the "smart city" and "smart islands", encouraging the growth of tourism and quality of life. The use of renewable energy in the new technologies and plant systems [30][31][32][33][34][35], will make a significant contribution to the sustainable development of Smarts Islands.…”

Section: S91mentioning

confidence: 99%

Islands "Smart Energy" for eco-sustainable energy a case study "Favignana Island"

Cannistraro¹,

Cannistraro²,

Trovato³

2017

IJHT

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The term "Smart" in the last decade has often flanked other words to express a new and intelligent way of living in a modern society where you cannot separate the two synergic aspects: Energy and Sustainability. These latter two aspects flow into the new way of managing an isolated territory that often presents difficulties because of no interactions with the surrounding area; to remedy these difficulties has been developed in recent years the "Smart-Island" project, which involves many European countries and several sponsors. The concept of "SmartIsland" defines a way of life in an isolated environment, such as that of these islands, can solve independently, with the use of renewable and sustainable sources the energy needs of the island, with some projects that take into account the preservation and the wealth of the territory. In this paper, after a brief review of what has been proposed in some islands of the world, it will develop a case study, represented by the island of Favignana, which has particular characteristics in relation to its energy dependence.

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The Applications of the New Technologies “E-Sensing” in Hospitals

Cited by 20 publications

References 20 publications

Hyperspectral Image Recognition Based on Artificial Neural Network

Hyperspectral Image Recognition Based on Artificial Neural Network

A Behavioral Economics Approach to Residential Electricity Consumption

Islands "Smart Energy" for eco-sustainable energy a case study "Favignana Island"

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