15 research outputs found
SMILE: Search for MIlli-LEnses
ABSTRACTDark matter (DM) haloes with masses below ∼108 M⊙, which would help to discriminate between DM models, may be detected through their gravitational effect on distant sources. The same applies to primordial black holes, considered as an alternative scenario to DM particle models. However, there is still no evidence for the existence of such objects. With the aim of finding compact objects in the mass range of ∼106–109 M⊙, we search for strong gravitational lenses on milliarcsec scales (</p
Programming and control of an industrial robotic system
The importance of robotic systems in the automation of industrial units is well known. In this paper is described the logic programming and computer control system of a robotic manipulator (IBM Scara robot) utilized in specific palletizing and assembling tasks in a machines constructions company. At low level of communication control is achieved through AML assembly routines in conjunction with C programming modules, while at user interface Prolog predicates are used for interactive and comprehensive communication. The system incorporates visual data (through a grip camera) for specific objects identification and definition of their location. Effective machine vision processing algorithms intend to strengthen the reliability of system's control and operation in real-time. Although high-level control and task planning in robotics remain a particular difficult problem, this combined approach of low and high level control and image processing algorithms, seems to ease the operator's work and ensures higher quality of operation. After long-lasting tests and measurements of control system's implementation the outcomes and the production results achieved (e.g. reduced errors, time and cost), have reconfirmed its effectiveness compared to previous solutions
Social Relevance Feedback Based on Multimedia Content Power
This paper proposes a novel social media relevance feedback algorithm, based on multimedia content power (MCP). The algorithm estimates in a recursive manner, the similarity measure. This is accomplished by using a set of relevant/irrelevant samples, which are provided by the user, in order to adjust the system's response. In particular, the similarity measure is expressed in a parametric form of functional components. Another innovative point has to do with the estimation of MCP, which measures the influence of files over social media users. Toward this direction, user interactions (e.g., comments, likes, and shares) indicate that the file is influencing to them. The algorithm takes into consideration both the visual characteristics of multimedia files and their influence to retrieve information. The experimental results show that the proposed scheme offers several merits and future work is also discussed. © 2014 IEEE
Energy Retrofit Assessment Through Automated Valuation Models: an Italian Case Study
With reference to the current issue of energy efficiency of residential buildings, the aim of this research is to analyze the possible influence of the energy performance component on the property prices formation. The study sample consists of two hundred residential units recently sold and located in the city of Bari (Italy). The implemented methodology is represented by a data-driven technique that employs a genetic algorithm to identify the functional expressions. The elaborations carried out have allowed the identification of a statistically reliable and easily interpretable model, which denotes an appreciable contribution of the energy component on housing prices
Fine needle aspiration cytology of nodular thyroid lesions: a 2-year experience of the Bethesda system for reporting thyroid cytopathology in a large regional and a university hospital, with histological correlation
ObjectiveThyroid fine needle aspiration (FNA) contributes to the
appropriate management of nodular thyroid lesions. The introduced
categories in the Bethesda system for reporting thyroid cytopathology
(TBSRTC) are associated with an implied cancer risk, providing a
clinical management guideline. This study aims to evaluate the
reproducibility of this implied risk and to compare the results from two
different cytopathology departments.
MethodsFive hundred histologically confirmed FNAs, studied since the
introduction of TBSRTC, were obtained from 4208 and 3587 FNAs performed
in a large regional hospital in Herakleion, Crete (group A) and a
university hospital in Athens (group B), respectively. Reports were
issued according to TBSRTC. Aspirates were prepared with ThinPrep((R))
and evaluated by two experienced cytopathologists. The reproducibility
and accuracy were evaluated.
ResultsThe proportion test for suspicious for malignancy (SFM) and
malignant (M) cytology reports (P<0.0001), and the number of
malignancies on histology (P<0.0001), were significantly higher in group
A than in group B, consistent with a higher incidence of thyroid
carcinomas in southern Greece. Although the malignancy rates were higher
in group A than in group B for all categories, except M (A, 99.3%; B,
100%), the difference was only significant for benign aspirates
(P=0.0303). Malignancy rates for all categories in group A were above
the TBSRTC recommended range, but were consistent with an increased
prevalence of malignancy in that centre, differences in reporting
practice and the variable ranges reported in the literature. There was
lower sensitivity (P=0.019) and overall accuracy (P=0.003) in group A
relative to group B, but no difference in specificity.
ConclusionsTBSRTC provides valuable information for the appropriate
management of nodular thyroid lesions, both in a university and a large
regional hospital
Radial basis function artificial neural network for the investigation of thyroid cytological lesions
Objective. This study investigates the potential of an artificial intelligence (AI) methodology, the radial basis function (RBF) artificial neural network (ANN), in the evaluation of thyroid lesions. Study Design. The study was performed on 447 patients who had both cytological and histological evaluation in agreement. Cytological specimens were prepared using liquid-based cytology, and the histological result was based on subsequent surgical samples. Each specimen was digitized; on these images, nuclear morphology features were measured by the use of an image analysis system. The extracted measurements (41,324 nuclei) were separated into two sets: the training set that was used to create the RBF ANN and the test set that was used to evaluate the RBF performance. The system aimed to predict the histological status as benign or malignant. Results. The RBF ANN obtained in the training set has sensitivity 82.5%, specificity 94.6%, and overall accuracy 90.3%, while in the test set, these indices were 81.4%, 90.0%, and 86.9%, respectively. Algorithm was used to classify patients on the basis of the RBF ANN, the overall sensitivity was 95.0%, the specificity was 95.5%, and no statistically significant difference was observed. Conclusion. AI techniques and especially ANNs, only in the recent years, have been studied extensively. The proposed approach is promising to avoid misdiagnoses and assists the everyday practice of the cytopathology. The major drawback in this approach is the automation of a procedure to accurately detect and measure cell nuclei from the digitized images. © 2020 Christos Fragopoulos et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
SMILE
Publisher Copyright: © 2021 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.Dark matter (DM) haloes with masses below ∼108 M·, which would help to discriminate between DM models, may be detected through their gravitational effect on distant sources. The same applies to primordial black holes, considered as an alternative scenario to DM particle models. However, there is still no evidence for the existence of such objects. With the aim of finding compact objects in the mass range of ∼106-109 M·, we search for strong gravitational lenses on milliarcsec scales (<150 mas). For our search, we used the Astrogeo very long baseline interferometry (VLBI) fits image data base - the largest publicly available data base, containing multifrequency VLBI data of 13 828 individual sources. We used the citizen science approach to visually inspect all sources in all available frequencies in search for images with multiple compact components on mas scales. At the final stage, sources were excluded based on the surface brightness preservation criterion. We obtained a sample of 40 sources that passed allsteps and therefore are judged to be mas lens candidates. These sources are currently followed up with ongoing European VLBI network observations at 5 and 22 GHz. Based on spectral index measurements, we suggest that two of our candidates have a higher probability to be associated with gravitational lenses.Peer reviewe