Locating experts and carving out the state of the art: A systematic review on Industry 4.0 and energy system analysis

2019 ◽  
Vol 43 (9) ◽  
pp. 3981-4002 ◽  
Author(s):  
Lars Nolting ◽  
Alexander Kies ◽  
Marius Schönegge ◽  
Martin Robinius ◽  
Aaron Praktiknjo
Keyword(s):  
Systematic Review ◽  
Industry 4.0 ◽  
System Analysis ◽  
State Of The Art ◽  
Energy System ◽  
The State ◽  
Energy System Analysis

Proteomics of Pancreatic Neuroendocrine Tumors: A Systematic Review

2020 ◽  
Vol 27 (12) ◽  
pp. 1276-1287
Author(s):  
Brigida Anna Maiorano ◽  
Giovanni Schinzari ◽  
Sabrina Chiloiro ◽  
Felicia Visconti ◽  
Domenico Milardi ◽  
...  
Keyword(s):  
Systematic Review ◽  
Neuroendocrine Tumors ◽  
Prognostic Markers ◽  
State Of The Art ◽  
Therapeutic Targets ◽  
The State ◽  
Pancreatic Neuroendocrine Tumors ◽  
Rare Tumors ◽  
Personalized Approach ◽  
Future Management

Pancreatic neuroendocrine tumors (PanNETs) are rare tumors having usually an indolent behavior, but sometimes with unpredictable aggressiveness. PanNETs are more often non-functioning (NF), unable to produce functioning hormones, while 10-30% present as functioning (F) - PanNETs, such as insulinomas , gastrinomas , and other rare tumors. Diagnostic and prognostic markers, but also new therapeutic targets, are still lacking. Proteomics techniques represent therefore promising approaches for the future management of PanNETs. We conducted a systematic review to summarize the state of the art of proteomics in PanNETs. A total of 9 studies were included, focusing both on NF- and F-PanNETs. Indeed, proteomics is useful for the diagnosis, the prognosis and the detection of therapeutic targets. However, further studies are required. It is also warranted to standardize the analysis methods and the collection techniques, in order to validate proteins with a relevance in the personalized approach to PanNETs management.

scholarly journals Towards Scalable Economic Photovoltaic Potential Analysis Using Aerial Images and Deep Learning

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3800
Author(s):  
Sebastian Krapf ◽  
Nils Kemmerzell ◽  
Syed Khawaja Haseeb Khawaja Haseeb Uddin ◽  
Manuel Hack Hack Vázquez ◽  
Fabian Netzler ◽  
...  
Keyword(s):  
Deep Learning ◽  
System Analysis ◽  
State Of The Art ◽  
Critical Role ◽  
Semantic Segmentation ◽  
Energy System ◽  
Aerial Images ◽  
Potential Analysis ◽  
3D Data ◽  
Challenges And Opportunities

Roof-mounted photovoltaic systems play a critical role in the global transition to renewable energy generation. An analysis of roof photovoltaic potential is an important tool for supporting decision-making and for accelerating new installations. State of the art uses 3D data to conduct potential analyses with high spatial resolution, limiting the study area to places with available 3D data. Recent advances in deep learning allow the required roof information from aerial images to be extracted. Furthermore, most publications consider the technical photovoltaic potential, and only a few publications determine the photovoltaic economic potential. Therefore, this paper extends state of the art by proposing and applying a methodology for scalable economic photovoltaic potential analysis using aerial images and deep learning. Two convolutional neural networks are trained for semantic segmentation of roof segments and superstructures and achieve an Intersection over Union values of 0.84 and 0.64, respectively. We calculated the internal rate of return of each roof segment for 71 buildings in a small study area. A comparison of this paper’s methodology with a 3D-based analysis discusses its benefits and disadvantages. The proposed methodology uses only publicly available data and is potentially scalable to the global level. However, this poses a variety of research challenges and opportunities, which are summarized with a focus on the application of deep learning, economic photovoltaic potential analysis, and energy system analysis.

scholarly journals A Systematic Review of Recommender Systems and Their Applications in Cybersecurity

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5248
Author(s):  
Aleksandra Pawlicka ◽  
Marek Pawlicki ◽  
Rafał Kozik ◽  
Ryszard S. Choraś
Keyword(s):  
Systematic Review ◽  
Recommender Systems ◽  
Recommender System ◽  
State Of The Art ◽  
The State ◽  
Advantages And Disadvantages ◽  
Comprehensive Survey ◽  
Security Concerns ◽  
Valuable Role

This paper discusses the valuable role recommender systems may play in cybersecurity. First, a comprehensive presentation of recommender system types is presented, as well as their advantages and disadvantages, possible applications and security concerns. Then, the paper collects and presents the state of the art concerning the use of recommender systems in cybersecurity; both the existing solutions and future ideas are presented. The contribution of this paper is two-fold: to date, to the best of our knowledge, there has been no work collecting the applications of recommenders for cybersecurity. Moreover, this paper attempts to complete a comprehensive survey of recommender types, after noticing that other works usually mention two–three types at once and neglect the others.

Development of a dynamic European residential building stock typology for energy system analysis

2021 ◽  
Author(s):  
Max Kleinebrahm ◽  
Elias Naber ◽  
Jann Weinand ◽  
Russell McKenna ◽  
Armin Ardone
Keyword(s):  
System Analysis ◽  
Residential Building ◽  
Weather Conditions ◽  
Energy System ◽  
Data Sets ◽  
European Level ◽  
Residential Energy ◽  
Building Stock ◽  
Energy System Analysis ◽  
Framework Conditions

<p>In recent years, different approaches have been developed with the aim of defining representative buildings that can be used as a basis for residential building energy system analyses. Due to the coupling of different sectors at the household level, the analysis of future residential energy systems is becoming increasingly complex. On the European level a large amount of data has been published over the last years. This study combines multiple different data sets relevant for energy system analysis at the building level and presents a dynamic methodology for the derivation of representative building/household combinations, which can be used as a basis for residential energy system analyses on a European level. The approach enables representative buildings to be generated dynamically taking into account the parameters relevant to the respective research question. In a first step, various data sets are combined to describe local building properties, weather conditions, economic and ecological framework conditions as well as socio-demographic parameters on NUTS3 level. Based on the developed database, a two-step procedure for the derivation of building household combinations is presented. In the first step, a synthetic European population is generated by using iterative proportional fitting. In the second step different cluster approaches are compared for the derivation of case specific archetype buildings. Finally, the developed methodology is used in an exemplary way for the analysis of the potential of energy self-sufficient single-family buildings in the future European building stock by using a mixed integer linear programming optimization model for the optimal energy system design and dispatch of residential buildings, taking into account relevant framework conditions such as weather conditions, regulatory framework conditions and site-specific building properties.</p>

Current practices of management of congenital Cytomegalovirus infection during pregnancy and childhood: systematic review protocol

2020 ◽  
Author(s):  
Claire Perillaud Dubois ◽  
Drifa Belhadi ◽  
Cédric Laouénan ◽  
Laurent Mandelbrot ◽  
Christelle Vauloup-Fellous ◽  
...  
Keyword(s):  
Systematic Review ◽  
Pregnant Women ◽  
State Of The Art ◽  
Grey Literature ◽  
The State ◽  
Cochrane Library ◽  
Cmv Infection ◽  
Congenital Cmv Infection ◽  
Congenital Cmv ◽  
Current Practices

Abstract Background: Congenital CMV infection is the first worldwide cause of congenital viral infection and a major cause of sensorineural hearing loss and mental retardation. As systematic screening of pregnant women and newborns is still debated in many countries, this systematic review aims to provide the state of the art on current practices concerning management of congenital CMV infection.Methods: We will perform electronically searches on MEDLINE, EMBASE, Cochrane Library (CENTRAL), ClinicalTrials.gov, Web of Science and hand searches in grey literature. Interventions regarding biological, imaging, and therapeutic management of infected pregnant women, fetuses and neonates/children (from birth to 6 years old) will be studied in this systematic review. Study screening will be performed in duplicate by two independent reviewers and risk of bias will be evaluated with the ROBINS-I tool. Discussion: This review will provide the state of the art of current management of congenital CMV infection in pregnant women, fetuses, neonates and children until 6 years old, in order to have an overview of current practices of congenital CMV infection.Systematic review registration: PROSPERO CRD42019124342

Semantic Web of Things for Industry 4.0

Semantic Web ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 885-886
Author(s):  
Dhavalkumar Thakker ◽  
Pankesh Patel ◽  
Muhammad Intizar Ali ◽  
Tejal Shah
Keyword(s):  
Semantic Web ◽  
Industry 4.0 ◽  
State Of The Art ◽  
The State ◽  
Special Issue ◽  
Semantic Web Technologies ◽  
Web Of Things ◽  
Web Technologies

Welcome to this special issue of the Semantic Web (SWJ) journal. The special issue compiles four technical contributions that significantly advance the state-of-the-art in Semantic Web of Things for Industry 4.0 including the use of Semantic Web technologies and techniques in Industry 4.0 solutions.

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