Nonparametric algorithm of electronic components test data pattern recognition

The paper discusses the quality diagnostics of electrical radio components based on the results of non-destructive testing. A proposed clustering algorithm does not require preliminary information on the number of classes and the training sample. The algorithm allows to automatically determine the number of classes. The division into classes is due to the different characteristics of the measured variables, which correspond to different product quality ranges

The CLAS12 Software Framework and Event Reconstruction

We describe offline event reconstruction for the CEBAF Large Acceptance Spectrometer at 12 GeV (CLAS12), including an overview of the offline reconstruction framework and software tools, a description of the algorithms developed for the individual detector subsystems, and the overall approach for charged and neutral particle identification. We also present the scheme for data processing and the code management procedures

The CLAS12 software framework and event reconstruction

We describe offline event reconstruction for the CEBAF Large Acceptance Spectrometer at 12 GeV (CLAS12), including an overview of the offline reconstruction framework and software tools, a description of the algorithms developed for the individual detector subsystems, and the overall approach for charged and neutral particle identification. We also present the scheme for data processing and the code management procedures

Robust indoor speaker recognition in a network of audio and video sensors

AbstractSituational awareness is achieved naturally by the human senses of sight and hearing in combination. Automatic scene understanding aims at replicating this human ability using microphones and cameras in cooperation. In this paper, audio and video signals are fused and integrated at different levels of semantic abstractions. We detect and track a speaker who is relatively unconstrained, i.e., free to move indoors within an area larger than the comparable reported work, which is usually limited to round table meetings. The system is relatively simple: consisting of just 4 microphone pairs and a single camera. Results show that the overall multimodal tracker is more reliable than single modality systems, tolerating large occlusions and cross-talk. System evaluation is performed on both single and multi-modality tracking. The performance improvement given by the audio–video integration and fusion is quantified in terms of tracking precision and accuracy as well as speaker diarisation error rate and precision–recall (recognition). Improvements vs. the closest works are evaluated: 56% sound source localisation computational cost over an audio only system, 8% speaker diarisation error rate over an audio only speaker recognition unit and 36% on the precision–recall metric over an audio–video dominant speaker recognition method

Flow pattern analysis for magnetic resonance velocity imaging

Blood flow in the heart is highly complex. Although blood flow patterns have been investigated by both computational modelling and invasive/non-invasive imaging techniques, their evolution and intrinsic connection with cardiovascular disease has yet to be explored. Magnetic resonance (MR) velocity imaging provides a comprehensive distribution of multi-directional in vivo flow distribution so that detailed quantitative analysis of flow patterns is now possible. However, direct visualisation or quantification of vector fields is of little clinical use, especially for inter-subject or serial comparison of changes in flow patterns due to the progression of the disease or in response to therapeutic measures. In order to achieve a comprehensive and integrated description of flow in health and disease, it is necessary to characterise and model both normal and abnormal flows and their effects. To accommodate the diversity of flow patterns in relation to morphological and functional changes, we have described in this thesis an approach of detecting salient topological features prior to analytical assessment of dynamical indices of the flow patterns. To improve the accuracy of quantitative analysis of the evolution of topological flow features, it is essential to restore the original flow fields so that critical points associated with salient flow features can be more reliably detected. We propose a novel framework for the restoration, abstraction, extraction and tracking of flow features such that their dynamic indices can be accurately tracked and quantified. The restoration method is formulated as a constrained optimisation problem to remove the effects of noise and to improve the consistency of the MR velocity data. A computational scheme is derived from the First Order Lagrangian Method for solving the optimisation problem. After restoration, flow abstraction is applied to partition the entire flow field into clusters, each of which is represented by a local linear expansion of its velocity components. This process not only greatly reduces the amount of data required to encode the velocity distribution but also permits an analytical representation of the flow field from which critical points associated with salient flow features can be accurately extracted. After the critical points are extracted, phase portrait theory can be applied to separate them into attracting/repelling focuses, attracting/repelling nodes, planar vortex, or saddle. In this thesis, we have focused on vortical flow features formed in diastole. To track the movement of the vortices within a cardiac cycle, a tracking algorithm based on relaxation labelling is employed. The constraints and parameters used in the tracking algorithm are designed using the characteristics of the vortices. The proposed framework is validated with both simulated and in vivo data acquired from patients with sequential MR examination following myocardial infarction. The main contribution of the thesis is in the new vector field restoration and flow feature abstraction method proposed. They allow the accurate tracking and quantification of dynamic indices associated with salient features so that inter- and intra-subject comparisons can be more easily made. This provides further insight into the evolution of blood flow patterns and permits the establishment of links between blood flow patterns and localised genesis and progression of cardiovascular disease.Open acces

Current state-of-the-art of the research conducted in mapping protein cavities – binding sites of bioactive compounds, peptides or other proteins

Ο σκοπός της διπλωματικής εργασίας είναι η διερεύνηση και αποτύπωση των ερευνητικών μελετών που αφορούν στον χαρακτηρισμό μιας πρωτεϊνικής κοιλότητας – κέντρου πρόσδεσης βιοδραστικών ενώσεων, πεπτιδίων ή άλλων πρωτεϊνών. Στην παρούσα εργασία χρησιμοποιήθηκε η μέθοδος της βιβλιογραφικής επισκόπησης. Παρουσιάζονται τα κυριότερα ευρήματα προηγούμενων ερευνών που σχετίζονται με τη διαδικασία σχεδιασμού φαρμάκων και τον εντοπισμό φαρμακοφόρων με βάση ένα σύνολο προσδετών. Στη συνέχεια συγκρίνονται διαδικασίες επεξεργασίας και ανάλυσης της πρωτεϊνικής κοιλότητας προγενέστερων ερευνών με τη προσέγγιση που προτάθηκε από τους Παπαθανασίου και Φωτόπουλου το 2015. Αναδεικνύονται βασικά πλεονεκτήματα της προσέγγισης αυτής, όπως η εφαρμογή του αλγορίθμου πολυδιάστατη k-means ομαδοποίηση (multidimensional k-means clustering). Η εύρεση βιβλιογραφίας βασίστηκε σε αναζήτηση επιστημονικών άρθρων σε ξενόγλωσσα επιστημονικά περιοδικά, σε κεφάλαια βιβλίων και σε διάφορα άρθρα σε ηλεκτρονικούς ιστότοπους σχετικά με τον σχεδιασμό φαρμάκων και τις κοιλότητες που απαντώνται στις πρωτεΐνες. Στην παρούσα εργασία παρουσιάζονται εν συντομία εργαλεία που εντοπίστηκαν χρησιμοποιώντας λέξεις κλειδιά όπως για παράδειγμα δυναμική πρωτεϊνικής κοιλότητας, καταλυτικό κέντρο ενός ενζύμου, πρόσδεση, πρωτεϊνική θήκη κλπ. Στη συνέχεια συγκροτήθηκε κατάλογος με τα εργαλεία βιοπληροφορικής ανάλυσης που βρέθηκαν και ακολούθησε εκτενής αναφορά επιλεκτικά σε κάποια από αυτά. Κριτήριο επιλογής αυτών των εργαλείων αποτέλεσε η ημερομηνία δημοσίευσής τους, οι αλγόριθμοι και η μεθοδολογία που χρησιμοποιούν. Τα εργαλεία αυτά κατηγοριοποιήθηκαν με βάση τις λέξεις κλειδιά που χρησιμοποιήθηκαν για την εξόρυξη των δεδομένων από την βιβλιογραφία. Τέλος πραγματοποιήθηκε συγκριτική μελέτη αυτών αναδεικνύοντας τα πλεονεκτήματα και εστιάζοντας στην περαιτέρω αξιοποίησή τους.The aim of this thesis was to report on the current state-of-the-art of the research conducted concerning mapping of protein cavities with a potential function role as binding sites of bioactive compounds, peptides or other proteins. A literature review was performed with emphasis on the relevant tools developed during the last decade. In addition, the main research findings regarding drug design and druggable targets based on binding sites are presented. Processes performed in protein cavity detection and analysis, of previous research articles, are compared with the approach described by Anaxagoras Fotopoulos and Athanasios Papathanasiou (2015). The results showed that a competitive advantage of their approach is the multidimensional k-means algorithm for clustering. For the bibliographic review the scientific knowledgebase has been used, which includes international articles and journals, book chapters, as well as online articles regarding drug design and protein cavity. Search keywords such as protein cavity dynamics, catalytic sites of enzymes, protein pocket etc. were used to identify bioinformatics tools with text mining. A catalogue of the most recently developed tools is presented followed by a brief description of selected tools. The selection criteria imposed for preparing the catalogue and the detailed description included the publication date, as well as the algorithms and the methods they use. The tools were then classified according to the search keywords. The findings of this research are discussed, and the algorithms and methods they use are compared, highlighting the advantages of protein cavity detection