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Dr. Antonios Konstantaras
Department of Electronic Engineering, Hellenic Mediterranean University

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0 Data Mining
0 Ontology
0 Parallel Algorithms
0 Software Engineering
0 Machine and Deep Learning

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Journal article
Published: 21 May 2021 in Energies
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Sewage sludge hydrochars (SSHs), which are produced by hydrothermal carbonization (HTC), offer a high calorific value to be applied as a biofuel. However, HTC is a complex processand the properties of the resulting product depend heavily on the process conditions and feedstock composition. In this work, we have applied artificial neural networks (ANNs) to contribute to the production of tailored SSHs for a specific application and with optimum properties. We collected data from the published literature covering the years 2014–2021, which was then fed into different ANN models where the input data (HTC temperature, process time, and the elemental content of hydrochars) were used to predict output parameters (higher heating value, (HHV) and solid yield (%)). The proposed ANN models were successful in accurately predicting both HHV and contents of C and H. While the model NN1 (based on C, H, O content) exhibited HHV predicting performance with R2 = 0.974, another model, NN2, was also able to predict HHV with R2 = 0.936 using only C and H as input. Moreover, the inverse model of NN3 (based on H, O content, and HHV) could predict C content with an R2 of 0.939.

ACS Style

Theodoros Kapetanakis; Ioannis Vardiambasis; Christos Nikolopoulos; Antonios Konstantaras; Trinh Trang; Duy Khuong; Toshiki Tsubota; Ramazan Keyikoglu; Alireza Khataee; Dimitrios Kalderis. Towards Engineered Hydrochars: Application of Artificial Neural Networks in the Hydrothermal Carbonization of Sewage Sludge. Energies 2021, 14, 3000 .

AMA Style

Theodoros Kapetanakis, Ioannis Vardiambasis, Christos Nikolopoulos, Antonios Konstantaras, Trinh Trang, Duy Khuong, Toshiki Tsubota, Ramazan Keyikoglu, Alireza Khataee, Dimitrios Kalderis. Towards Engineered Hydrochars: Application of Artificial Neural Networks in the Hydrothermal Carbonization of Sewage Sludge. Energies. 2021; 14 (11):3000.

Chicago/Turabian Style

Theodoros Kapetanakis; Ioannis Vardiambasis; Christos Nikolopoulos; Antonios Konstantaras; Trinh Trang; Duy Khuong; Toshiki Tsubota; Ramazan Keyikoglu; Alireza Khataee; Dimitrios Kalderis. 2021. "Towards Engineered Hydrochars: Application of Artificial Neural Networks in the Hydrothermal Carbonization of Sewage Sludge." Energies 14, no. 11: 3000.

Preprint content
Published: 03 March 2021
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This research aims to depict ontological findings related to topical seismic phenomena within the Hellenic-Seismic-Arc via deep-data-mining of the existing big-seismological-dataset, encompassing a deep-learning neural network model for pattern recognition along with heterogeneous parallel processing-enabled interactive big data visualization. Using software that utilizes the R language, seismic data were 3D plotted on a 3D Cartesian plane point cloud viewer for further investigation of the formed three-dimensional morphology. As a means of mining information from seismic big data, a deep neural network was trained and refined for pattern recognition and occurrence manifestation attributes of seismic data of magnitudes greater than Ms 4.0. The deep learning neural network comprises of an input layer with six input neurons for the insertion of year, month, day, latitude, longitude and depth, followed by six hidden layers with a hundred neurons each, and one output layer of the estimated magnitude level. This approach was conceptualised to investigate for topical patterns in time yielding minor, interim and strong seismic activity, such as the one depicted by the deep learning neural network, observed in the past ten years on the region between Syrna and Kandelioussa. This area’s coordinates are around 36,4 degrees in latitude and 26,7 degrees in longitude, with the deep learning neural network achieving low error rates, possibly depicting a pattern in seismic activity.

References

Axaridou A., I. Chrysakis, C. Georgis, M. Theodoridou, M. Doerr, A. Konstantaras, and E. Maravelakis. 3D-SYSTEK: Recording and exploiting the production workflow of 3D-models in cultural heritage. IISA 2014 - 5th International Conference on Information, Intelligence, Systems and Applications, 51-56, 2014.

Konstantaras A. Deep Learning and Parallel Processing Spatio-Temporal Clustering Unveil New Ionian Distinct Seismic Zone. Informatics, 7 (4), 39, 2020.

Konstantaras A.J. Expert knowledge-based algorithm for the dynamic discrimination of interactive natural clusters. Earth Science Informatics. 9 (1), 95-100, 2016.

Konstantaras A.J. Classification of distinct seismic regions and regional temporal modelling of seismicity in the vicinity of the Hellenic seismic arc. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 6 (4), 1857-1863, 2012.

Konstantaras A., F. Vallianatos, M.R. Varley, J.P. Makris. Soft-Computing modelling of seismicity in the southern Hellenic Arc. IEEE Geoscience and Remote Sensing Letters, 5 (3), 323-327, 2008.

Konstantaras A., M.R. Varley, F. Vallianatos, G. Collins and P. Holifield. Recognition of electric earthquake precursors using neuro-fuzzy methods: methodology and simulation results. Proc. IASTED Int. Conf. Signal Processing, Pattern Recognition and Applications (SPPRA 2002), Crete, Greece, 303-308, 2002.

Maravelakis E., Konstantaras A., Kilty J., Karapidakis E. and Katsifarakis E. Automatic building identification and features extraction from aerial images: Application on the historic 1866 square of Chania Greece. 2014 International Symposium on Fundamentals of Electrical Engineering (ISFEE), Bucharest, 1-6, 2014. doi: 10.1109/ISFEE.2014.7050594.

Maravelakis E., A. Konstantaras, K. Kabassi, I. Chrysakis, C. Georgis and A. Axaridou. 3DSYSTEK web-based point cloud viewer. IISA 2014 - 5th International Conference on Information, Intelligence, Systems and Applications, 262-266, 2014.

Maravelakis E., Bilalis N., Mantzorou I., Konstantaras A. and Antoniadis A. 3D modelling of the oldest olive tree of the world. International Journal Of Computational Engineering Research. 2 (2), 340-347, 2012.

ACS Style

Antonios Konstantaras; Theofanis Frantzeskakis; Emmanouel Maravelakis; Alexandra Moshou; Panagiotis Argyrakis. Heterogeneous Parallel Processing Enabled Deep Learning Pattern Recognition of Seismic Big Data in Syrna and Kandelioussa. 2021, 1 .

AMA Style

Antonios Konstantaras, Theofanis Frantzeskakis, Emmanouel Maravelakis, Alexandra Moshou, Panagiotis Argyrakis. Heterogeneous Parallel Processing Enabled Deep Learning Pattern Recognition of Seismic Big Data in Syrna and Kandelioussa. . 2021; ():1.

Chicago/Turabian Style

Antonios Konstantaras; Theofanis Frantzeskakis; Emmanouel Maravelakis; Alexandra Moshou; Panagiotis Argyrakis. 2021. "Heterogeneous Parallel Processing Enabled Deep Learning Pattern Recognition of Seismic Big Data in Syrna and Kandelioussa." , no. : 1.

Preprint content
Published: 03 March 2021
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On 30th October 2020, at 11.51 (UTC), a very strong earthquake of magnitude Mw = 7.0 struck north of the Greek island of Samos in the Aegean coast of Turkey, south of Izmir. The epicentre was determined 17km north of Samos, in the Gulf of Ephesus and was felt in many parts of Greece and western Turkey. The geographical coordinates as calculated of the manual analysis of the National Observatory of Athens (http://bbnet.gein.noa.gr/Events/2020/10/noa2020vipzs_info.html) was determined as  φ= 37.9001⁰N, λ=26.8167⁰E at a focal depth at 11.8km. The earthquake triggered a tsunami that flooded the coastal district of Seferihisar (Turkey), Cesme, Izmir and the port of Samos (Greece). In the next 8 minutes after the detection of the earthquake, tsunami bulletins were issued to national focal points by the Tsunami Service Providers accredited by UNESCO’s IOC Intergovernmental Coordination Group for the Tsunami Early Warning and Mitigation System in the North-eastern Atlantic, the Mediterranean and connected seas (ICG/NEAMTWS). Greece and Turkey were put on Tsunami Watch (highest level of alert). In Seferishar the tsunami swept away many boats in the marina and the water level reached 1.5 meters causing damage to shops.

Three hours later, 15:14 (UTC) a second strong event (Mw = 5.3) occurred in the same region some kilometres south of the main earthquake (φ=37.8223⁰N,λ=26.8652⁰E, http://bbnet.gein.noa.gr/Events/2020/10/noa2020viwsi_info.html). By the end of the same day that the earthquake took place, there were 65 aftershocks while a total of 576 aftershocks up to 31/12 with magnitude greater than 1.0. For the aftershocks with 3.7L<7.0 we applied the moment tensor inversion to determine the focal mechanism, the Seismic Moment (M0) and the Moment Magnitude (Mw). For this purpose, 3–component broadband seismological data from the Hellenic Unified Seismological Network (HUSN) at epicentral distances less than 3˚ were selected and analysed. The preparation of the data, includes the deconvolution of instrument response, following the velocity was integrated to displacement and finally the horizontal components rotated to radial and transverse. Finally, an extensive kinematic analysis from data provided by two private sector companies networks was done.

References:

Athanassios Ganas, Penelope Kourkouli, Pierre Briole, Alexandra Moshou, Panagiotis Elias and Isaak Parcharidis. Coseismic Displacements from Moderate-Size Earthquakes Mapped by Sentinel-1 Differential Interferometry: The Case of February 2017 Gulpinar Earthquake Sequence (Biga Peninsula, Turkey), Remote Sensing, 2018, pp. 237 – 248

Athanassios Ganas, Zafeiria Roumelioti, Vassilios Karastathis, Konstantinos Chousianitis, Alexandra Moshou, Evangelos Mouzakiotis. The Lemnos 8 January 2013 (Mw=5.7) earthquake: fault slip, aftershock properties and static stress transfer modeling in the north Aegean Sea J Seismol (2014) 18:433–455 DOI 10.1007/s10950-014-9418-3

Konstantaras A. Deep Learning and Parallel Processing Spatio-Temporal Clustering Unveil New Ionian Distinct Seismic Zone. Informatics, 7(4), 39, 2020

KONSTANTARAS, A. Expert knowledge-based algorithm for the dynamic discrimination of interactive natural clusters. Earth Science Informatics 9, (2016), 95-100

ACS Style

Alexandra Moshou; Antonios Konstantaras; Panagiotis Argyrakis. The major (Mw=7.0) earthquake of 30th October 2020 north Samos Island, Greece: Analysis of seismological and geodetic data . 2021, 1 .

AMA Style

Alexandra Moshou, Antonios Konstantaras, Panagiotis Argyrakis. The major (Mw=7.0) earthquake of 30th October 2020 north Samos Island, Greece: Analysis of seismological and geodetic data . . 2021; ():1.

Chicago/Turabian Style

Alexandra Moshou; Antonios Konstantaras; Panagiotis Argyrakis. 2021. "The major (Mw=7.0) earthquake of 30th October 2020 north Samos Island, Greece: Analysis of seismological and geodetic data ." , no. : 1.

Journal article
Published: 20 January 2021 in Data
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In 2014–2018, four strong earthquakes occurred in the Ionian Sea, Greece. After these events, a rich aftershock sequence followed. More analytically, according to the manual solutions of the National Observatory of Athens, the first event occurred on 26 January 2014 in Cephalonia Island with magnitude ML = 5.8, followed by another in the same region on 3 February 2014 with magnitude ML = 5.7. The third event occurred on 17 November 2015, ML = 6.0 in Lefkas Island and the last on 25 October 2018, ML = 6.6 in Zakynthos Island. The first three of these earthquakes caused moderate structural damages, mainly in houses and produced particular unrest to the local population. This work determines a seismic moment tensor for both large and intermediate magnitude earthquakes (M > 4.0). Geodetic data from permanent GPS stations were analyzed to investigate the displacement due to the earthquakes.

ACS Style

Alexandra Moshou; Panagiotis Argyrakis; Antonios Konstantaras; Anna-Christina Daverona; Nikos C. Sagias. Characteristics of Recent Aftershocks Sequences (2014, 2015, 2018) Derived from New Seismological and Geodetic Data on the Ionian Islands, Greece. Data 2021, 6, 8 .

AMA Style

Alexandra Moshou, Panagiotis Argyrakis, Antonios Konstantaras, Anna-Christina Daverona, Nikos C. Sagias. Characteristics of Recent Aftershocks Sequences (2014, 2015, 2018) Derived from New Seismological and Geodetic Data on the Ionian Islands, Greece. Data. 2021; 6 (2):8.

Chicago/Turabian Style

Alexandra Moshou; Panagiotis Argyrakis; Antonios Konstantaras; Anna-Christina Daverona; Nikos C. Sagias. 2021. "Characteristics of Recent Aftershocks Sequences (2014, 2015, 2018) Derived from New Seismological and Geodetic Data on the Ionian Islands, Greece." Data 6, no. 2: 8.

Journal article
Published: 29 September 2020 in Informatics
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This research work employs theoretical and empirical expert knowledge in constructing an agglomerative parallel processing algorithm that performs spatio-temporal clustering upon seismic data. This is made possible by exploiting the spatial and temporal sphere of influence of the main earthquakes solely, clustering seismic events into a number of fuzzy bordered, interactive and yet potentially distinct seismic zones. To evaluate whether the unveiled clusters indeed depict a distinct seismic zone, deep learning neural networks are deployed to map seismic energy release rates with time intervals between consecutive large earthquakes. Such a correlation fails should there be influence by neighboring seismic areas, hence casting the seismic region as non-distinct, or if the extent of the seismic zone has not been captured fully. For the deep learning neural network to depict such a correlation requires a steady seismic energy input flow. To address that the western area of the Hellenic seismic arc has been selected as a test case due to the nearly constant motion of the African plate that sinks beneath the Eurasian plate at a steady yearly rate. This causes a steady flow of strain energy stored in tectonic underground faults, i.e., the seismic energy storage elements; a partial release of which, when propagated all the way to the surface, casts as an earthquake. The results are complementary two-fold with the correlation between the energy release rates and the time interval amongst large earthquakes supporting the presence of a potential distinct seismic zone in the Ionian Sea and vice versa.

ACS Style

Antonios Konstantaras. Deep Learning and Parallel Processing Spatio-Temporal Clustering Unveil New Ionian Distinct Seismic Zone. Informatics 2020, 7, 39 .

AMA Style

Antonios Konstantaras. Deep Learning and Parallel Processing Spatio-Temporal Clustering Unveil New Ionian Distinct Seismic Zone. Informatics. 2020; 7 (4):39.

Chicago/Turabian Style

Antonios Konstantaras. 2020. "Deep Learning and Parallel Processing Spatio-Temporal Clustering Unveil New Ionian Distinct Seismic Zone." Informatics 7, no. 4: 39.

Preprint
Published: 04 September 2020
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During the period January 2014 – October 2018, four strong earthquakes occurred in the Ionian Sea, Greece. A rich aftershock sequence followed each event of them. More analytically, according to the manual solutions of National Observatory of Athens, the first event (K1), occurred on 26 January 2014 in Kefallinia Island with magnitude ML = 5.8, which was followed by another in the same region (K2) on 3 February 2014 with magnitude ML = 5.7. The third event occurred on 17 November 2015, ML = 6.0 in Lefkas Island (L1) and the last on 25 October 2018, ML = 6.6 in Zande Island (Z1). The first three of these earthquakes caused moderate structural damages mainly in houses and produced particular unrest to the local population. This work presents first the calculation of the source parameters of the strong events as well as for all earthquakes with magnitude ML > 4.0, using the methodology of the Moment tensor inversion and secondary data from permanent GPS stations were analyzed to confirm the findings from seismological data and to investigate the displacement due to the earthquakes.

ACS Style

Alexandra Moshou; George Drakatos; Vassilios Moussas; Panagiotis Argyrakis; Antonios Konstantaras; Anna Christina Daverona; Dimos Pantazis; Nikos C. Sagias. Spatio – Temporal Characteristics of the Aftershocks Sequences that followed the Strong Earthquakes in Ionian Islands, Greece. 2020, 1 .

AMA Style

Alexandra Moshou, George Drakatos, Vassilios Moussas, Panagiotis Argyrakis, Antonios Konstantaras, Anna Christina Daverona, Dimos Pantazis, Nikos C. Sagias. Spatio – Temporal Characteristics of the Aftershocks Sequences that followed the Strong Earthquakes in Ionian Islands, Greece. . 2020; ():1.

Chicago/Turabian Style

Alexandra Moshou; George Drakatos; Vassilios Moussas; Panagiotis Argyrakis; Antonios Konstantaras; Anna Christina Daverona; Dimos Pantazis; Nikos C. Sagias. 2020. "Spatio – Temporal Characteristics of the Aftershocks Sequences that followed the Strong Earthquakes in Ionian Islands, Greece." , no. : 1.

Preprint content
Published: 23 March 2020
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The identification of distinct seismic regions and the extraction of features of theirs in relation to known underground fault mappings could provide most valuable information towards understanding the seismic clustering phenomenon, i.e. whether an earthquake occurring in a particular area can trigger another earthquake in the vicinity. This research paper works towards that direction and unveils the potential presence and extent of distinct seismic regions in the area of the Southern Hellenic Seismic Arc. To achieve that, a spatio-temporal clustering algorithm has been developed based on expert knowledge regarding the spatial and timely influence of an earthquake  in its nearby vicinity using seismic data provided by the Geodynamics Institute of Athens, and is further supported by geological observations of underground faults’ mappings beneath the addressed potentially distinct seismic regions. This is made possible thanks to advances in deep learning and graphics processing units’ 3D technology that encompass parallel processing architectures, which comprise of blocks of multiple cores with parallel threads providing the necessary foundation in terms of hardware for accelerated processing for parallel seismic big data analysis. Seismic data are normally stored in massive continuously expanding matrices, as wide areas seismic covering is thickening, due to the establishment of denser recording networks, and decades of data are being stacked together. This research work embodies that technology for the development and implementation of a Cuda parallel processing agglomerative spatio-temporal clustering algorithm that enables the import of expert knowledge for the investigation of the potential presence of distinct seismic regions in the vicinity under investigation. The overall spatio temporal clustering results are also in accordance with empirical observations reported in the literature throughout the vicinity of the Hellenic Seismic Arc.

Indexing terms: parallel processing, heterogeneous parallel programming, Cuda, distinct seismic regions, seismic clustering, spatio-temporal clustering

References

Axaridou A., I. Chrysakis, C. Georgis, M. Theodoridou, M. Doerr, A. Konstantaras, and E. Maravelakis. 3D-SYSTEK: Recording and exploiting the production workflow of 3D-models in cultural heritage. IISA 2014 - 5th International Conference on Information, Intelligence, Systems and Applications, 51-56, 2014.

Drakatos G. and J. Latoussakis. A catalog of aftershock sequences in Greece (1971–1997): Their spatial and temporal characteristics. Journal of Seismology. 5, 137–145, 2001.

Konstantaras A.J. Classification of distinct seismic regions and regional temporal modelling of seismicity in the vicinity of the Hellenic seismic arc. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 6 (4), 1857-1863, 2012.

Konstantaras A.J., E. Katsifarakis, E. Maravelakis, E. Skounakis, E. Kokkinos and E. Karapidakis. Intelligent spatial-clustering of seismicity in the vicinity of the Hellenic Seismic Arc. Earth Science Research 1 (2), 1-10, 2012.

Maravelakis E., A. Konstantaras, K. Kabassi, I. Chrysakis, C. Georgis and A. Axaridou. 3DSYSTEK web-based point cloud viewer. IISA 2014 - 5th International Conference on Information, Intelligence, Systems and Applications, 262-266, 2014.

Moshou Alexandra, Eleftheria Papadimitriou, George Drakatos, Christos Evangelidis Vasilios Karakostas, Filippos Vallianatos, and Konstantinos Makropoulos Focal Mechanisms at the convergent plate boundary in Southern Aegean, Greece, Geophysical Research Abstracts, Vol. 16, EGU2014-12185, 2014, EGU General Assembly 2014

ACS Style

Alexandra Moshou; Antonios Konstantaras; Emmanouil Markoulakis; Panagiotis Argyrakis; Emmanouil Maravelakis. A Deep-Learning Parallel Processing Agglomerative Algorithm for the Identification of Distinct Seismic Regions in the Southern Hellenic Seismic Arc. 2020, 1 .

AMA Style

Alexandra Moshou, Antonios Konstantaras, Emmanouil Markoulakis, Panagiotis Argyrakis, Emmanouil Maravelakis. A Deep-Learning Parallel Processing Agglomerative Algorithm for the Identification of Distinct Seismic Regions in the Southern Hellenic Seismic Arc. . 2020; ():1.

Chicago/Turabian Style

Alexandra Moshou; Antonios Konstantaras; Emmanouil Markoulakis; Panagiotis Argyrakis; Emmanouil Maravelakis. 2020. "A Deep-Learning Parallel Processing Agglomerative Algorithm for the Identification of Distinct Seismic Regions in the Southern Hellenic Seismic Arc." , no. : 1.

Journal article
Published: 08 November 2019 in Results in Physics
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The magnetic dipole field geometry of subatomic elementary particles like the electron differs from the classical macroscopic field imprint of a bar magnet. It resembles more like an eight figure or else joint double quantum-dots instead of the classical, spherical more uniform field of a bar magnet. This actual subatomic quantum magnetic field of an electron at rest, is called Quantum Magnet or else a Magneton. It is today verified experimentally by quantum magnetic field imaging methods and sensors like SQUID scanning magnetic microscopy of ferromangets and also seen in Bose-Einstein Condensates (BEC) quantum ferrrofluids experiments. Normally, a macroscale bar magnet should behave like a relative giant Quantum Magnet with identical magnetic dipole field imprint since all of its individual magnetons collectively inside the material, dipole moments are uniformly aligned forming the total net field of the magnet. However due to Quantum Decoherence (QDE) phenomenon at the macroscale and macroscopic magnetic field imaging sensors limitations which cannot pickup these rapid quantum magnetization fluctuations, this field is masked and not visible at the macroscale. By using the relative inexpensive submicron resolution Ferrolens quantum magnetic optical superparamagnetic thin film sensor for field real time imaging and method we have researched in our previous publications, we can actually make this net magneton field visible on macroscale magnets. We call this net total field herein, Quantum Field of Magnet (QFM) differentiating it therefore from the field of the single subatomic magneton thus quantum magnet. Additionally, the unique potential of the Ferrolens device to display also the magnetic flux lines of this macroscopically projected giant Magenton gives us the opportunity for the first time to study the individual magnetic flux lines geometrical pattern that of a single subatomic magneton. We describe this particular magnetic flux of the magneton observed, quantum magnetic flux. Therefore an astonishing novel observation has been made that the Quantum Magnetic Field of the Magnet-Magneton (QFM) consists of a dipole vortex shaped magnetic flux geometrical pattern responsible for creating the classical macroscopic N-S field of magnetism as a tension field between the two polar quantum flux vortices North and South poles. A physical interpretation of this quantum decoherence mechanism observed is analyzed and presented and conclusions made showing physical evidence of the quantum origin irrotational and therefore conservative property of magnetism and also demonstrating that ultimately magnetism at the quantum level is an energy dipole vortex phenomenon.

ACS Style

Emmanouil Markoulakis; Antonios Konstantaras; John Chatzakis; Rajan Iyer; Emmanuel Antonidakis. Real time observation of a stationary magneton. Results in Physics 2019, 15, 102793 .

AMA Style

Emmanouil Markoulakis, Antonios Konstantaras, John Chatzakis, Rajan Iyer, Emmanuel Antonidakis. Real time observation of a stationary magneton. Results in Physics. 2019; 15 ():102793.

Chicago/Turabian Style

Emmanouil Markoulakis; Antonios Konstantaras; John Chatzakis; Rajan Iyer; Emmanuel Antonidakis. 2019. "Real time observation of a stationary magneton." Results in Physics 15, no. : 102793.

Journal article
Published: 07 July 2018 in Journal of Magnetism and Magnetic Materials
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It has been more than two hundred years since the first iron filings experiment, showing us the 2D macroscopic magnetic imprint of the field of a permanent magnet. However, latest developments in modern nanomagnetic passive direct observation devices reveal in real-time and color a more intriguing 3D dynamic and detailed image of the field of a magnet, with surprising new findings, that can change our perspective for dipole magnetism forever and lead to new research. This research is a continuation of our previous work, “Markoulakis, E., Rigakis, I., Chatzakis, J., Konstantaras, A., Antonidakis, E. Real time visualization of dynamic magnetic fields with a nanomagnetic ferrolens(2018) Journal of Magnetism and Magnetic Materials, 451, pp. 741-748.DOI: 10.1016/j.jmmm.2017.12.023” that is using a ferrolens apparatus for showing the dynamic magnetic field on a transmitting radio antenna, while this time the magnetostatic fields were under our scope and examined with the aid of the ferrolens. We are presenting experimental and photographical evidence, demonstrating the true complex 3D Euclidian geometry of the quantum field of permanent magnets that have never been seen before and the classic iron filings experiment, apart of its 2D limitations, fails to depict. An analysis of why and what these iron filings inherent limitations are, giving us an incomplete and also in some degree misguiding image of the magnetic field of a magnet is carried out, whereas, as we prove the ferrolens is free of these limitations and its far more advanced visualization capabilities is allowing it to show the quantum image with depth of field information, of the dipole field of a permanent magnet. For the first time the domain wall (i.e. Bloch or Neel wall) region of the field of a magnet is clearly made visible by the ferrolens along with what phenomenon is actually taking place there, leading to the inescapable conclusion, novel observation and experimental evidence that the field of any dipole magnet actually consists of two distinct and separate toroidal shaped 3D magnetic bubbles, each located at either side of the dipole around the exact spatial regions where the two poles of the magnet reside.

ACS Style

Emmanouil Markoulakis; Antonios Konstantaras; Emmanuel Antonidakis. The quantum field of a magnet shown by a nanomagnetic ferrolens. Journal of Magnetism and Magnetic Materials 2018, 466, 252 -259.

AMA Style

Emmanouil Markoulakis, Antonios Konstantaras, Emmanuel Antonidakis. The quantum field of a magnet shown by a nanomagnetic ferrolens. Journal of Magnetism and Magnetic Materials. 2018; 466 ():252-259.

Chicago/Turabian Style

Emmanouil Markoulakis; Antonios Konstantaras; Emmanuel Antonidakis. 2018. "The quantum field of a magnet shown by a nanomagnetic ferrolens." Journal of Magnetism and Magnetic Materials 466, no. : 252-259.

Journal article
Published: 01 April 2018 in Journal of Magnetism and Magnetic Materials
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ACS Style

Emmanouil Markoulakis; Iraklis Rigakis; John Chatzakis; Antonios Konstantaras; Emmanuel Antonidakis. Real time visualization of dynamic magnetic fields with a nanomagnetic ferrolens. Journal of Magnetism and Magnetic Materials 2018, 451, 741 -748.

AMA Style

Emmanouil Markoulakis, Iraklis Rigakis, John Chatzakis, Antonios Konstantaras, Emmanuel Antonidakis. Real time visualization of dynamic magnetic fields with a nanomagnetic ferrolens. Journal of Magnetism and Magnetic Materials. 2018; 451 ():741-748.

Chicago/Turabian Style

Emmanouil Markoulakis; Iraklis Rigakis; John Chatzakis; Antonios Konstantaras; Emmanuel Antonidakis. 2018. "Real time visualization of dynamic magnetic fields with a nanomagnetic ferrolens." Journal of Magnetism and Magnetic Materials 451, no. : 741-748.

Journal article
Published: 01 January 2018 in The International Journal of the Inclusive Museum
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ACS Style

Katerina Kabassi; Emmanuel Maravelakis; Antonios Konstantaras. Heuristics and Fuzzy Multi-Criteria Decision Making for Evaluating Museum Virtual Tours. The International Journal of the Inclusive Museum 2018, 11, 1 .

AMA Style

Katerina Kabassi, Emmanuel Maravelakis, Antonios Konstantaras. Heuristics and Fuzzy Multi-Criteria Decision Making for Evaluating Museum Virtual Tours. The International Journal of the Inclusive Museum. 2018; 11 (3):1.

Chicago/Turabian Style

Katerina Kabassi; Emmanuel Maravelakis; Antonios Konstantaras. 2018. "Heuristics and Fuzzy Multi-Criteria Decision Making for Evaluating Museum Virtual Tours." The International Journal of the Inclusive Museum 11, no. 3: 1.

Journal article
Published: 18 August 2015 in Earth Science Informatics
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The identification of distinct seismic regions and features’ extraction of theirs could provide valuable information towards the better understanding of the underlying physics, the generation mechanism and the behavior of the seismic phenomenon. This research paper works towards that direction and unveils the potential presence of a distinct seismic region located in between the Ionean sea and the Cretan see, extending south-east of Peloponnesus, Greece. This observation has emerged as a result of the development and application of a spatio temporal clustering algorithm based on expert knowledge upon seismic data provided by the Geodynamics Institute of Athens, and is further supported by geological observations, which have unveiled the presence of two parallel groups of underground faults beneath the newly discovered potential distinct seismic region. The overall spatio temporal clustering results throughout the Greek vicinity are also in accordance with empirical observations reported in the literature and coincide with cartographic groups of underground faults of Greece.

ACS Style

Antonios Konstantaras. Expert knowledge-based algorithm for the dynamic discrimination of interactive natural clusters. Earth Science Informatics 2015, 9, 95 -100.

AMA Style

Antonios Konstantaras. Expert knowledge-based algorithm for the dynamic discrimination of interactive natural clusters. Earth Science Informatics. 2015; 9 (1):95-100.

Chicago/Turabian Style

Antonios Konstantaras. 2015. "Expert knowledge-based algorithm for the dynamic discrimination of interactive natural clusters." Earth Science Informatics 9, no. 1: 95-100.

Conference paper
Published: 01 July 2015 in 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA)
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Recent advances in aerial photography enabled cadastrates of several countries to proceed to the cartography of rural areas and record existing forestry, farming yards, plane fields and registered land ownerships. Efforts are being made to expand this project to urban areas as well, where the main object of interest apart from land itself are the buildings themselves. The main difficulty with buildings is that they are 3D objects and additional to their planar expansion there is also their height that is of significance as well. This paper aims to comprise planar information obtained through features' extraction from ortho-open aerophotographs with vertical information obtained using terrestrial laser scanning to produce three dimensional models of multiple neighboring building blocks in an urban area. Results from the application of the proposed approach to the historic 1866 square in Chania, Greece, demonstrate both the capabilities and difficulties associated with such an attempt and derive useful conclusions for future advancements that can lead to valuable topographical urban three dimensional mappings.

ACS Style

Antonios Konstantaras; J. A. Kilty; Emmanuel Maravelakis. Coalescing terrestrial laser scanning and aerial orthophotography for urban 3D modelling. 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA) 2015, 1 -5.

AMA Style

Antonios Konstantaras, J. A. Kilty, Emmanuel Maravelakis. Coalescing terrestrial laser scanning and aerial orthophotography for urban 3D modelling. 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA). 2015; ():1-5.

Chicago/Turabian Style

Antonios Konstantaras; J. A. Kilty; Emmanuel Maravelakis. 2015. "Coalescing terrestrial laser scanning and aerial orthophotography for urban 3D modelling." 2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA) , no. : 1-5.

Proceedings article
Published: 01 November 2014 in 2014 International Symposium on Fundamentals of Electrical Engineering (ISFEE)
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During the last decade significant efforts have been made to monitor cities and record their current situation and growth through time. Advances in aerial photography and the implementation of ortho-images enabled the cartography of large scale areas leading to numerous applications in data recording in both rural and urban regions. Features extraction from such images poses a challenging goal especially in areas exhibiting little chromatic variations, such as multiple detached cement buildings surrounded by cement pavements and tar roads, and dynamic noise conditions due to large building shades and moving vehicles. This paper presents a fully automated software solution for the identification of compact buildings-blocks from aerial ortho-photographs. The aim is to identify and record compact building-blocks' perimeters ignoring any lesser features displayed by them in order to produce a set of planar coordinates for every building-block. This information is most valuable for topographical city mapping applications and can be further exploited towards city-modeling either by stereo-photography or laser scanning technology, and necessary scaling and alignment techniques to import the height information in an expanded spatial set of coordinates.

ACS Style

Emmanuel Maravelakis; Antonios Konstantaras; J. Kilty; E. Karapidakis; E. Katsifarakis; Maravelakis E.. Automatic building identification and features extraction from aerial images: Application on the historic 1866 square of Chania Greece. 2014 International Symposium on Fundamentals of Electrical Engineering (ISFEE) 2014, 1 -6.

AMA Style

Emmanuel Maravelakis, Antonios Konstantaras, J. Kilty, E. Karapidakis, E. Katsifarakis, Maravelakis E.. Automatic building identification and features extraction from aerial images: Application on the historic 1866 square of Chania Greece. 2014 International Symposium on Fundamentals of Electrical Engineering (ISFEE). 2014; ():1-6.

Chicago/Turabian Style

Emmanuel Maravelakis; Antonios Konstantaras; J. Kilty; E. Karapidakis; E. Katsifarakis; Maravelakis E.. 2014. "Automatic building identification and features extraction from aerial images: Application on the historic 1866 square of Chania Greece." 2014 International Symposium on Fundamentals of Electrical Engineering (ISFEE) , no. : 1-6.

Journal article
Published: 01 October 2014 in Sustainable Cities and Society
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K. Maragkogiannis; D. Kolokotsa; E. Maravelakis; A. Konstantaras. Combining terrestrial laser scanning and computational fluid dynamics for the study of the urban thermal environment. Sustainable Cities and Society 2014, 13, 207 -216.

AMA Style

K. Maragkogiannis, D. Kolokotsa, E. Maravelakis, A. Konstantaras. Combining terrestrial laser scanning and computational fluid dynamics for the study of the urban thermal environment. Sustainable Cities and Society. 2014; 13 ():207-216.

Chicago/Turabian Style

K. Maragkogiannis; D. Kolokotsa; E. Maravelakis; A. Konstantaras. 2014. "Combining terrestrial laser scanning and computational fluid dynamics for the study of the urban thermal environment." Sustainable Cities and Society 13, no. : 207-216.

Conference paper
Published: 01 July 2014 in IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications
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This paper presents the development of a new Web based LiDAR (Light Detection And Ranging) 3D point cloud viewer addressing mobility and portability issues arising from remote field applications by numerous multidisciplinary collaborative scientists. This new Web Browser-based 3D point cloud viewer, hereafter called 3DSYSTEK viewer, was developed and implemented in the framework of the3DSYSTEK research programme that aimed to develop tools to bring together all disciplines working to promote our cultural heritage through laser scanning, 3D modeling, 3D visualization, documentation, and exploitation of 3D data. 3D point cloud viewers' native implementations although they support multiple applications they are very expensive and their features vary from one software to another with considerable problems arising due to the introduction of personalized file formats by each individual native software. The presented 3DSYSTEK viewer is based on open-software, enables personalized expandability to address specific needs by individual users and allows the online remote collaboration amongst scientists at different locations as well as the widespread usage of the TLS surveying technology and 3D modeling of large monuments.

ACS Style

Emmanuel Maravelakis; Antonios Konstantaras; K. Kabassi; Ioannis Chrysakis; C. Georgis; A. Axaridou; Maravelakis E.; Kabassi K.. 3DSYSTEK web-based point cloud viewer. IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications 2014, 262 -266.

AMA Style

Emmanuel Maravelakis, Antonios Konstantaras, K. Kabassi, Ioannis Chrysakis, C. Georgis, A. Axaridou, Maravelakis E., Kabassi K.. 3DSYSTEK web-based point cloud viewer. IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications. 2014; ():262-266.

Chicago/Turabian Style

Emmanuel Maravelakis; Antonios Konstantaras; K. Kabassi; Ioannis Chrysakis; C. Georgis; A. Axaridou; Maravelakis E.; Kabassi K.. 2014. "3DSYSTEK web-based point cloud viewer." IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications , no. : 262-266.

Conference paper
Published: 01 July 2014 in IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications
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The diversity of contemporary technology on 3D-model digitizing and processing procedures necessitates the systematic documentation of all the involved activities. In this paper we present essential concepts and the infrastructure of 3D-SYSTEK (3DS), a system that supports the 3D-modelling provenance preservation in the Cultural Heritage (CH) domain. The proposed system provides an efficient repository and special tools for ingesting and browsing data, supporting the detailed and effective documentation. Specialists working on 3D-model production are able to record the production steps, keep track of their work and recall conditions and processing methods for reproduction. Additionally, CH scientists and researchers are able to browse, retrieve and annotate related CH data. Hence 3D-SYSTEK becomes a powerful tool in the area of 3D-model production, archiving and dissemination.

ACS Style

Anastasia Axaridou; Ioannis Chrysakis; Christos Georgis; Maria Theodoridou; Martin Doerr; Antonios Konstantaras; Emmanuel Maravelakis. 3D-SYSTEK: Recording and exploiting the production workflow of 3D-models in Cultural Heritage. IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications 2014, 51 -56.

AMA Style

Anastasia Axaridou, Ioannis Chrysakis, Christos Georgis, Maria Theodoridou, Martin Doerr, Antonios Konstantaras, Emmanuel Maravelakis. 3D-SYSTEK: Recording and exploiting the production workflow of 3D-models in Cultural Heritage. IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications. 2014; ():51-56.

Chicago/Turabian Style

Anastasia Axaridou; Ioannis Chrysakis; Christos Georgis; Maria Theodoridou; Martin Doerr; Antonios Konstantaras; Emmanuel Maravelakis. 2014. "3D-SYSTEK: Recording and exploiting the production workflow of 3D-models in Cultural Heritage." IISA 2014, The 5th International Conference on Information, Intelligence, Systems and Applications , no. : 51-56.

Journal article
Published: 25 November 2013 in IEEE Transactions on Human-Machine Systems
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This research presents a novel multifunctional platform focusing on the clinical diagnosis of kidneys and their pathology (tumors, stones and cysts), using a “templates”-based technique. As a first step, specialist clinicians train the system by accurately annotating the kidneys and their abnormalities creating “3-D golden standard models.” Then, medical technicians experimentally adjust rules and parameters (stored as “templates”) for the integrated “automatic recognition framework” to achieve results which are closest to those of the clinicians. These parameters can later be used by nonexperts to achieve increased automation in the identification process. The system's functionality was tested on 20 MRI datasets (552 images), while the “automatic 3-D models” created were validated against the “3-D golden standard models.” Results are promising as they yield an average accuracy of 97.2% in successfully identifying kidneys and 96.1% of their abnormalities thus outperforming existing methods both in accuracy and in processing time needed.

ACS Style

Emmanouil Skounakis; Konstantinos Banitsas; Atta Badii; Stavros Tzoulakis; Emmanuel Maravelakis; Antonios Konstantaras. ATD: A Multiplatform for Semiautomatic 3-D Detection of Kidneys and Their Pathology in Real Time. IEEE Transactions on Human-Machine Systems 2013, 44, 146 -153.

AMA Style

Emmanouil Skounakis, Konstantinos Banitsas, Atta Badii, Stavros Tzoulakis, Emmanuel Maravelakis, Antonios Konstantaras. ATD: A Multiplatform for Semiautomatic 3-D Detection of Kidneys and Their Pathology in Real Time. IEEE Transactions on Human-Machine Systems. 2013; 44 (1):146-153.

Chicago/Turabian Style

Emmanouil Skounakis; Konstantinos Banitsas; Atta Badii; Stavros Tzoulakis; Emmanuel Maravelakis; Antonios Konstantaras. 2013. "ATD: A Multiplatform for Semiautomatic 3-D Detection of Kidneys and Their Pathology in Real Time." IEEE Transactions on Human-Machine Systems 44, no. 1: 146-153.

Journal article
Published: 01 August 2013 in Expert Systems with Applications
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G. Georgoulas; Antonios Konstantaras; E. Katsifarakis; C.D. Stylios; Emmanuel Maravelakis; G.J. Vachtsevanos. “Seismic-mass” density-based algorithm for spatio-temporal clustering. Expert Systems with Applications 2013, 40, 4183 -4189.

AMA Style

G. Georgoulas, Antonios Konstantaras, E. Katsifarakis, C.D. Stylios, Emmanuel Maravelakis, G.J. Vachtsevanos. “Seismic-mass” density-based algorithm for spatio-temporal clustering. Expert Systems with Applications. 2013; 40 (10):4183-4189.

Chicago/Turabian Style

G. Georgoulas; Antonios Konstantaras; E. Katsifarakis; C.D. Stylios; Emmanuel Maravelakis; G.J. Vachtsevanos. 2013. "“Seismic-mass” density-based algorithm for spatio-temporal clustering." Expert Systems with Applications 40, no. 10: 4183-4189.

Conference paper
Published: 01 January 2013 in Transactions on Petri Nets and Other Models of Concurrency XV
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This research paper aims to address the problem of lack of a unified system for 3D documentation, promotion and exploitation of cultural heritage monuments via complete 3D data acquisition, 3D modeling and metadata recording using terrestrial laser scanners. Terrestrial laser scanning is a new fast developing technology that allows for the mapping and exact replication of the entire 3D shape of physical objects through the extraction of a very large number of points in space (point cloud) in short time periods, with great density and precision, and with no actual physical contact with the object of interest. The problem lies on the various types of hardware equipment and software systems used in the whole workflow of the 3D scanning process, including for the extraction of point clouds and the building process of the computerized 3D model development and the final products presentation. These often results in a large volume of interim and final products with little if no standardization, multiple different metadata, various user-dependent annotation requirements and vague documentation which often casts repeating a certain process impossible. This paper presents a user requirement analysis for a complete metadata recording during the whole lifecycle of a 3D product, aiming at supporting workflow history and provenance of 3D products of cultural heritage monuments.

ACS Style

Emmanuel Maravelakis; Antonios Konstantaras; A. Kritsotaki; D. Angelakis; M. Xinogalos. Analysing User Needs for a Unified 3D Metadata Recording and Exploitation of Cultural Heritage Monuments System. Transactions on Petri Nets and Other Models of Concurrency XV 2013, 8034, 138 -147.

AMA Style

Emmanuel Maravelakis, Antonios Konstantaras, A. Kritsotaki, D. Angelakis, M. Xinogalos. Analysing User Needs for a Unified 3D Metadata Recording and Exploitation of Cultural Heritage Monuments System. Transactions on Petri Nets and Other Models of Concurrency XV. 2013; 8034 ():138-147.

Chicago/Turabian Style

Emmanuel Maravelakis; Antonios Konstantaras; A. Kritsotaki; D. Angelakis; M. Xinogalos. 2013. "Analysing User Needs for a Unified 3D Metadata Recording and Exploitation of Cultural Heritage Monuments System." Transactions on Petri Nets and Other Models of Concurrency XV 8034, no. : 138-147.