Cloud-native architectures has become an essential part of the cloud computing paradigm with the ... more Cloud-native architectures has become an essential part of the cloud computing paradigm with the capacity of improved horizontal and vertical scalability, automation, usability and multi-tenancy. However, there are parts that are yet to be fully discovered like multi-tenancy. Multi-tenancy an essential part of the cloud computing, has not been fully. The purpose of this study is to survey existing research on multi-tenancy in cloud-native architecture in order to identify useful trends, opportunity, challenges and finally the needs for further researches. A systematic mapping method was used to systematically compare, classify, analyse, evaluate and appraise existing works of literature on multi-tenancy in cloud-native. We started from over 921 potentially relevant peer reviewed publications. We applied a selection procedure resulting in 64 peer reviewed publications over the last six years between 2015 to 2022 and the selected studies were classified through the characterisation fr...
This electronic document describes one of the first full open-source frameworks for posture and f... more This electronic document describes one of the first full open-source frameworks for posture and face detection and classification using Kinect sensors, based entirely on an open-sourced software platform. It has been designed with the possibility of automatic monitoring of either an elderly person who is situated in a closed space (a room with furniture, appliances, and other rigid objects), or a patient who suffers from a physiological disorder. It is also based on an original hardware platform (the AmI-Platform), which includes more Kinect sensors, data acquisition stations, and crunches (data servers). The articles tackle two of the most important issues for ambient intelligence: accurate determination of the person and his or her facial landmarks (to understand emotions) and fast and reliable posture determination (to take appropriate measures in case of an accident).
A 64-year-old man with ethanol intoxication, ingested a bottle of Herbiace (100 ml, 32 w/v% of bi... more A 64-year-old man with ethanol intoxication, ingested a bottle of Herbiace (100 ml, 32 w/v% of bialaphos, CAS #35597-43-4, Meiji Seika Kaisha, Tokyo, Japan). He had severe metabolic acidosis and was treated with infusions of sodium bicarbonate and furosemide, plus gastric lavage and enema. The metabolic acidosis improved 15 hours after treatment but nystagmus, apnea and convulsions were progressive. Although his sensorium was clear, spontaneous respirations were not observed for 64 hours. The electroencephalographic findings of atypical triphasic waves and slow waves suggest a unique response to bialaphos poisoning. His clinical course indicates that the management of apnea is critically important to recovery from bialaphos poisoning.
In this paper the children’s emotion recognition performance of several neural networks approache... more In this paper the children’s emotion recognition performance of several neural networks approaches is
Η παρούσα διδακτορική διατριβή eίναι eπικeντρωμένη γύρω από την ανάπτυξη και eφαρμογή, μe χαμηλές... more Η παρούσα διδακτορική διατριβή eίναι eπικeντρωμένη γύρω από την ανάπτυξη και eφαρμογή, μe χαμηλές υπολογιστικές απαιτήσeις, βασισμένeς σe Τeχνητά Νeυρωνικά Δίκτυα, για την Ανάλυση Βιοϊατρικών σημάτων και Data Mining σe Ιατρικά Δeδομένα. Απώτeρος σκοπός της παρούσης διατριβής στον τομέα της Βιοϊατρικής Τeχνολογίας eίναι να παρέχeι στους ιατρούς μe την καλύτeρη δυνατή πληροφόρηση για να κάνουν μια ακριβή διάγνωση (στην πeρίπτωση του ισχαιμικού μυοκαρδίου) και να προτeίνeι αναπτυγμένα μαθηματικά μοντέλα για να ανακάμψeι πολύπλοκeς eξαρτήσeις μeταξύ τον μeταβλητών μιας φυσικής διeργασίας από ένα σύνολο διαφορeτικών παρατηρήσeων. Μeτά την πeριγραφή μeρικών από τους βασικούς τύπους τeχνητών Νeυρωνικών Δικτύων που χρησιμοποιούνται στην παρούσα διατριβή, eμeίς αρχίσαμe να σχeδιάζουμe ένα μοντέλο για ταξινόμηση προτύπων κατασκeυάζοντας πολλά τοπικά μοντέλα γeιτονικά μe τον παρόντα χώρο. Για αυτό το σκοπό eμeίς χρησιμοποιούμe το αλγόριθμο για clustering k-windows για να ανιχνeύeι αυτόματα γeι...
Although the teaching of handwriting is not compulsory in all countries, it is widely accepted th... more Although the teaching of handwriting is not compulsory in all countries, it is widely accepted that this activity highly improves young children’s personality, basic coordination abilities and communication skills. In this context, we present an intelligent tutor that evaluates not only the quality of the written symbol, but also the child’s personality and emotional state in order to adapt its teaching strategy. In the first part of the paper, we propose a tool designed for automatic quality evaluation of handwritten symbols. We acquire the letters using a digital pen that transmits the space and time coordinates. We transform these coordinates in a binary image representation of the letter which is compared with the prototype letter. The evaluation module computes several parameters related to the legibility, size and space. An overall quality evaluation of the handwritten symbol is made. Human communication is a combination of verbal and non-verbal interactions. Our intelligent t...
The recognition of humans and their activities from video sequences is currently a very active ar... more The recognition of humans and their activities from video sequences is currently a very active area of research because of its many applications in video surveillance, multimedia communications, medical diagnosis, forensic research and sign language recognition. Our system is designed with the aim to precisely identify human gestures for Irish Sign Language (ISL) recognition. The system is to be developed and implemented on a standard personal computer (PC) connected to a colour video camera. The present paper tackles the problem of shape recognition for deformable objects like human hands using modern classification techniques derived from artificial intelligence.
The recognition of human activities from video sequences is currently one of the most active area... more The recognition of human activities from video sequences is currently one of the most active areas of research because of its many applications in video surveillance, multimedia communications, medical diagnosis, forensic research and sign language recognition. The work described in this paper describes a new method designed to precisely identify human gestures for Sign Language recognition. The system is to be developed and implemented on a standard personal computer (PC) connected to a colour video camera. The present paper tackles the problem of shape recognition for deformable objects like human hands using modern classification techniques derived from artificial intelligence.
ABSTRACT In this paper the children's emotion recognition performance of several neural n... more ABSTRACT In this paper the children's emotion recognition performance of several neural networks approaches is described. The Radial Basis Function (RBF), Probabilistic Neural Networks (PNN), Extreme Learning Machines (ELM) and Support Vector Machines (SVM) variants were tested on recorded speech signals and face detected images. For the speech signal the Mel Frequency Cepstral Coefficients (MFCC) and other parameters were computed together with their mean and standard deviation in order to obtain the feature vector for the neural network input. For images, input parameters for emotion detection consisted in several distances computed between certain facial features using space coordinates for eyes, eyebrows and lips. In case of RBF networks and speech signals we investigated the influence of the number of centres chosen by the k-means algorithm on the recognition performance on both training and test databases. The FAU Aibo Emotion corpus database was used because it has recordings from 51 children aged 10 to 13 years while interacting with a Sony Aibo robot. It is shown that there is a limitation of performance over a certain number of centers for the chosen identified emotions. Another promising technique for classification of speech feature vectors is the use of ELM. They are Single-hidden Layer Feedforward Neural (SFLN) networks. In this case, random values are allocated to the weights of the hidden layer and the output weights are found by matrix operations. Our simulations have shown a similar behavior of ELM networks with the RBF networks. There is a limitation of ELM performance after an increase of the number of hidden neurons over a specific number. Also, it is shown that the variant called Online Sequential ELM (OS-ELM) obtains very close classification performance to that of ELM. For facial emotion recognition a subset of 20 subjects ages 6 to 9 (10 boys and 10 girls) from The Dartmouth Database of Children's Faces was used. Different types of RBF networks (Classic RBF, Multi-Stage RBF, and Probabilistic Neural Networks) with variable number of hidden neurons were trained and tested. SVMs are a new type of supervised nonlinear learning paradigms which were used in the last decades both for classification and regression analysis. They have shown similar performance to RBF networks in our emotion detection simulations. The results prove the effectiveness of several neural networks techniques in estimating the children affective state that can have important implications on technology-enhanced learning and intelligent software applications for children. It is shown that child affective modeling it is as important as their cognitive modeling when it comes to deciding the next tutoring step and how it should be delivered.
Proceedings of the 9th Wseas International Conference on Simulation Modelling and Optimization, 2009
The recognition of humans and their activities from video sequences is currently a very active ar... more The recognition of humans and their activities from video sequences is currently a very active area of research because of its many applications in video surveillance, multimedia communications, medical diagnosis, forensic research and sign language recognition. ...
Cloud-native architectures has become an essential part of the cloud computing paradigm with the ... more Cloud-native architectures has become an essential part of the cloud computing paradigm with the capacity of improved horizontal and vertical scalability, automation, usability and multi-tenancy. However, there are parts that are yet to be fully discovered like multi-tenancy. Multi-tenancy an essential part of the cloud computing, has not been fully. The purpose of this study is to survey existing research on multi-tenancy in cloud-native architecture in order to identify useful trends, opportunity, challenges and finally the needs for further researches. A systematic mapping method was used to systematically compare, classify, analyse, evaluate and appraise existing works of literature on multi-tenancy in cloud-native. We started from over 921 potentially relevant peer reviewed publications. We applied a selection procedure resulting in 64 peer reviewed publications over the last six years between 2015 to 2022 and the selected studies were classified through the characterisation fr...
This electronic document describes one of the first full open-source frameworks for posture and f... more This electronic document describes one of the first full open-source frameworks for posture and face detection and classification using Kinect sensors, based entirely on an open-sourced software platform. It has been designed with the possibility of automatic monitoring of either an elderly person who is situated in a closed space (a room with furniture, appliances, and other rigid objects), or a patient who suffers from a physiological disorder. It is also based on an original hardware platform (the AmI-Platform), which includes more Kinect sensors, data acquisition stations, and crunches (data servers). The articles tackle two of the most important issues for ambient intelligence: accurate determination of the person and his or her facial landmarks (to understand emotions) and fast and reliable posture determination (to take appropriate measures in case of an accident).
A 64-year-old man with ethanol intoxication, ingested a bottle of Herbiace (100 ml, 32 w/v% of bi... more A 64-year-old man with ethanol intoxication, ingested a bottle of Herbiace (100 ml, 32 w/v% of bialaphos, CAS #35597-43-4, Meiji Seika Kaisha, Tokyo, Japan). He had severe metabolic acidosis and was treated with infusions of sodium bicarbonate and furosemide, plus gastric lavage and enema. The metabolic acidosis improved 15 hours after treatment but nystagmus, apnea and convulsions were progressive. Although his sensorium was clear, spontaneous respirations were not observed for 64 hours. The electroencephalographic findings of atypical triphasic waves and slow waves suggest a unique response to bialaphos poisoning. His clinical course indicates that the management of apnea is critically important to recovery from bialaphos poisoning.
In this paper the children’s emotion recognition performance of several neural networks approache... more In this paper the children’s emotion recognition performance of several neural networks approaches is
Η παρούσα διδακτορική διατριβή eίναι eπικeντρωμένη γύρω από την ανάπτυξη και eφαρμογή, μe χαμηλές... more Η παρούσα διδακτορική διατριβή eίναι eπικeντρωμένη γύρω από την ανάπτυξη και eφαρμογή, μe χαμηλές υπολογιστικές απαιτήσeις, βασισμένeς σe Τeχνητά Νeυρωνικά Δίκτυα, για την Ανάλυση Βιοϊατρικών σημάτων και Data Mining σe Ιατρικά Δeδομένα. Απώτeρος σκοπός της παρούσης διατριβής στον τομέα της Βιοϊατρικής Τeχνολογίας eίναι να παρέχeι στους ιατρούς μe την καλύτeρη δυνατή πληροφόρηση για να κάνουν μια ακριβή διάγνωση (στην πeρίπτωση του ισχαιμικού μυοκαρδίου) και να προτeίνeι αναπτυγμένα μαθηματικά μοντέλα για να ανακάμψeι πολύπλοκeς eξαρτήσeις μeταξύ τον μeταβλητών μιας φυσικής διeργασίας από ένα σύνολο διαφορeτικών παρατηρήσeων. Μeτά την πeριγραφή μeρικών από τους βασικούς τύπους τeχνητών Νeυρωνικών Δικτύων που χρησιμοποιούνται στην παρούσα διατριβή, eμeίς αρχίσαμe να σχeδιάζουμe ένα μοντέλο για ταξινόμηση προτύπων κατασκeυάζοντας πολλά τοπικά μοντέλα γeιτονικά μe τον παρόντα χώρο. Για αυτό το σκοπό eμeίς χρησιμοποιούμe το αλγόριθμο για clustering k-windows για να ανιχνeύeι αυτόματα γeι...
Although the teaching of handwriting is not compulsory in all countries, it is widely accepted th... more Although the teaching of handwriting is not compulsory in all countries, it is widely accepted that this activity highly improves young children’s personality, basic coordination abilities and communication skills. In this context, we present an intelligent tutor that evaluates not only the quality of the written symbol, but also the child’s personality and emotional state in order to adapt its teaching strategy. In the first part of the paper, we propose a tool designed for automatic quality evaluation of handwritten symbols. We acquire the letters using a digital pen that transmits the space and time coordinates. We transform these coordinates in a binary image representation of the letter which is compared with the prototype letter. The evaluation module computes several parameters related to the legibility, size and space. An overall quality evaluation of the handwritten symbol is made. Human communication is a combination of verbal and non-verbal interactions. Our intelligent t...
The recognition of humans and their activities from video sequences is currently a very active ar... more The recognition of humans and their activities from video sequences is currently a very active area of research because of its many applications in video surveillance, multimedia communications, medical diagnosis, forensic research and sign language recognition. Our system is designed with the aim to precisely identify human gestures for Irish Sign Language (ISL) recognition. The system is to be developed and implemented on a standard personal computer (PC) connected to a colour video camera. The present paper tackles the problem of shape recognition for deformable objects like human hands using modern classification techniques derived from artificial intelligence.
The recognition of human activities from video sequences is currently one of the most active area... more The recognition of human activities from video sequences is currently one of the most active areas of research because of its many applications in video surveillance, multimedia communications, medical diagnosis, forensic research and sign language recognition. The work described in this paper describes a new method designed to precisely identify human gestures for Sign Language recognition. The system is to be developed and implemented on a standard personal computer (PC) connected to a colour video camera. The present paper tackles the problem of shape recognition for deformable objects like human hands using modern classification techniques derived from artificial intelligence.
ABSTRACT In this paper the children's emotion recognition performance of several neural n... more ABSTRACT In this paper the children's emotion recognition performance of several neural networks approaches is described. The Radial Basis Function (RBF), Probabilistic Neural Networks (PNN), Extreme Learning Machines (ELM) and Support Vector Machines (SVM) variants were tested on recorded speech signals and face detected images. For the speech signal the Mel Frequency Cepstral Coefficients (MFCC) and other parameters were computed together with their mean and standard deviation in order to obtain the feature vector for the neural network input. For images, input parameters for emotion detection consisted in several distances computed between certain facial features using space coordinates for eyes, eyebrows and lips. In case of RBF networks and speech signals we investigated the influence of the number of centres chosen by the k-means algorithm on the recognition performance on both training and test databases. The FAU Aibo Emotion corpus database was used because it has recordings from 51 children aged 10 to 13 years while interacting with a Sony Aibo robot. It is shown that there is a limitation of performance over a certain number of centers for the chosen identified emotions. Another promising technique for classification of speech feature vectors is the use of ELM. They are Single-hidden Layer Feedforward Neural (SFLN) networks. In this case, random values are allocated to the weights of the hidden layer and the output weights are found by matrix operations. Our simulations have shown a similar behavior of ELM networks with the RBF networks. There is a limitation of ELM performance after an increase of the number of hidden neurons over a specific number. Also, it is shown that the variant called Online Sequential ELM (OS-ELM) obtains very close classification performance to that of ELM. For facial emotion recognition a subset of 20 subjects ages 6 to 9 (10 boys and 10 girls) from The Dartmouth Database of Children's Faces was used. Different types of RBF networks (Classic RBF, Multi-Stage RBF, and Probabilistic Neural Networks) with variable number of hidden neurons were trained and tested. SVMs are a new type of supervised nonlinear learning paradigms which were used in the last decades both for classification and regression analysis. They have shown similar performance to RBF networks in our emotion detection simulations. The results prove the effectiveness of several neural networks techniques in estimating the children affective state that can have important implications on technology-enhanced learning and intelligent software applications for children. It is shown that child affective modeling it is as important as their cognitive modeling when it comes to deciding the next tutoring step and how it should be delivered.
Proceedings of the 9th Wseas International Conference on Simulation Modelling and Optimization, 2009
The recognition of humans and their activities from video sequences is currently a very active ar... more The recognition of humans and their activities from video sequences is currently a very active area of research because of its many applications in video surveillance, multimedia communications, medical diagnosis, forensic research and sign language recognition. ...
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