ATD: a multiplatform for semiautomatic 3-D detection of kidneys and their pathology in real time

This research presents a novel multi-functional system for medical Imaging-enabled Assistive Diagnosis (IAD). Although the IAD demonstrator has focused on abdominal images and supports the clinical diagnosis of kidneys using CT/MRI imaging, it can be adapted to work on image delineation, annotation and 3D real-size volumetric modelling of other organ structures such as the brain, spine, etc. The IAD provides advanced real-time 3D visualisation and measurements with fully automated functionalities as developed in two stages. In the first stage, via the clinically driven user interface, specialist clinicians use CT/MRI imaging datasets to accurately delineate and annotate the kidneys and their possible abnormalities, thus creating “3D Golden Standard Models”. Based on these models, in the second stage, clinical support staff i.e. medical technicians interactively define model-based rules and parameters for the integrated “Automatic Recognition Framework” to achieve results which are closest to that of the clinicians. These specific rules and parameters are stored in “Templates” and can later be used by any clinician to automatically identify organ structures i.e. kidneys and their possible abnormalities. The system also supports the transmission of these “Templates” to another expert for a second opinion. A 3D model of the body, the organs and their possible pathology with real metrics is also integrated. The automatic functionality was tested on eleven MRI datasets (comprising of 286 images) and the 3D models were validated by comparing them with the metrics from the corresponding “3D Golden Standard Models”. The system provides metrics for the evaluation of the results, in terms of Accuracy, Precision, Sensitivity, Specificity and Dice Similarity Coefficient (DSC) so as to enable benchmarking of its performance. The first IAD prototype has produced promising results as its performance accuracy based on the most widely deployed evaluation metric, DSC, yields 97% for the recognition of kidneys and 96% for their abnormalities; whilst across all the above evaluation metrics its performance ranges between 96% and 100%. Further development of the IAD system is in progress to extend and evaluate its clinical diagnostic support capability through development and integration of additional algorithms to offer fully computer-aided identification of other organs and their abnormalities based on CT/MRI/Ultra-sound Imaging

Characteristics of Recent Aftershocks Sequences (2014, 2015, 2018) Derived from New Seismological and Geodetic Data on the Ionian Islands, Greece

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

Edge Computing for Vision-Based, Urban-Insects Traps in the Context of Smart Cities

Our aim is to promote the widespread use of electronic insect traps that report captured pests to a human-controlled agency. This work reports on edge-computing as applied to camera-based insect traps. We present a low-cost device with high power autonomy and an adequate picture quality that reports an internal image of the trap to a server and counts the insects it contains based on quantized and embedded deep-learning models. The paper compares different aspects of performance of three different edge devices, namely ESP32, Raspberry Pi Model 4 (RPi), and Google Coral, running a deep learning framework (TensorFlow Lite). All edge devices were able to process images and report accuracy in counting exceeding 95%, but at different rates and power consumption. Our findings suggest that ESP32 appears to be the best choice in the context of this application according to our policy for low-cost devices

Characteristics of Recent Aftershocks Sequences (2014, 2015, 2018) Derived from New Seismological and Geodetic Data on the Ionian Islands, Greece

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

Data Management and Processing in Seismology: An Application of Big Data Analysis for the Doublet Earthquake of 2021, 03 March, Elassona, Central Greece

On 3 March 2021 (10:16, UTC), a strong earthquake, Mw 6.3, occurred in Elassona, Central Greece. The epicenter was reported 10 km west of Tyrnavos. Another major earthquake followed this event on the same day at Mw 5.8 (3 March 2021, 11:45, UTC). The next day, 4 March 2021 (18:38, UTC), there was a second event with a similar magnitude as the first, Mw 6.2. Both events were 8.5 km apart. The following analysis shows that the previous events and the most significant aftershocks were superficial. However, historical and modern seismicity has been sparse in this area. Spatially, the region represents a transitional zone between different tectonic domains; the right-lateral slip along the western end of the North Anatolian Fault Zone (NAFZ) in the north Aegean Sea plate-boundary structure ends, and crustal extension prevails in mainland Greece. These earthquakes were followed by rich seismic activity recorded by peripheral seismographs and accelerometers. The installation of a dense, portable network from the Aristotle University of Thessaloniki team also helped this effort, installed three days after the seismic excitation, as seismological stations did not azimuthally enclose the area. In the present work, a detailed analysis was performed using seismological data. A seismological catalogue of 3.787 events was used, which was processed with modern methods to calculate 34 focal mechanisms (Mw > 4.0) and to recalculate the parameters of the largest earthquakes that occurred in the first two days

Data Management and Processing in Seismology: An Application of Big Data Analysis for the Doublet Earthquake of 2021, 03 March, Elassona, Central Greece

On 3 March 2021 (10:16, UTC), a strong earthquake, Mw 6.3, occurred in Elassona, Central Greece. The epicenter was reported 10 km west of Tyrnavos. Another major earthquake followed this event on the same day at Mw 5.8 (3 March 2021, 11:45, UTC). The next day, 4 March 2021 (18:38, UTC), there was a second event with a similar magnitude as the first, Mw 6.2. Both events were 8.5 km apart. The following analysis shows that the previous events and the most significant aftershocks were superficial. However, historical and modern seismicity has been sparse in this area. Spatially, the region represents a transitional zone between different tectonic domains; the right-lateral slip along the western end of the North Anatolian Fault Zone (NAFZ) in the north Aegean Sea plate-boundary structure ends, and crustal extension prevails in mainland Greece. These earthquakes were followed by rich seismic activity recorded by peripheral seismographs and accelerometers. The installation of a dense, portable network from the Aristotle University of Thessaloniki team also helped this effort, installed three days after the seismic excitation, as seismological stations did not azimuthally enclose the area. In the present work, a detailed analysis was performed using seismological data. A seismological catalogue of 3.787 events was used, which was processed with modern methods to calculate 34 focal mechanisms (Mw > 4.0) and to recalculate the parameters of the largest earthquakes that occurred in the first two days

Assessment of Radiofrequency Exposure in the Vicinity of School Environments in Crete Island, South Greece

This study aimed to estimate the radiofrequency exposure levels in the vicinity of nursery and primary schools at the northwest part of Crete island in Greece. Moreover, the compliance with the exposure limits, according to Greek legislation, was investigated. A total of 396 in situ frequency-selective and broadband measurements were conducted around 69 schools, classified in urban and suburban environments, in the range of 27–3000 MHz (subdivided in seven frequency bands). The measured value of the electric field strength (V/m) was recorded and, subsequently, the exposure ratio was calculated. Statistical analysis was performed in order to analyze and evaluate the data. In addition, a worst-case scenario was examined by considering the highest measured exposure level around each school. The statistical tests indicated that the mean and median values of the exposure ratio, even in the worst-case scenario, were found well below 1 for all frequency bands. The calculated distributions of the electric field measurements demonstrated that almost 90% of the latter were below 1 V/m, with the majority of values lying in the range of 0.5–1 V/m. The main contributors to the total exposure were the mobile communication frequencies and broadcasting, while the exposure was greater in urban than in suburban environments

Towards Engineered Hydrochars: Application of Artificial Neural Networks in the Hydrothermal Carbonization of Sewage Sludge

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