25 research outputs found
The 2005 Chios Ancient Shipwreck Survey: New Methods for Underwater Archaeology
No full textIn 2005 a Greek and American interdisciplinary team investigated two shipwrecks off the coast of Chios dating to the 4th-century b.c. and the 2nd/1st century. The project pioneered archaeological methods of precision acoustic, digital image, and chemical survey using an autonomous underwater vehicle (AUV) and in-situ sensors, increasing the speed of data acquisition while decreasing costs. The AUV recorded data revealing the physical dimensions, age, cargo, and preservation of the wrecks. The earlier wreck contained more than 350 amphoras, predominantly of Chian type, while the Hellenistic wreck contained about 40 Dressel 1C amphoras. Molecular biological analysis of two amphoras from the 4th-century wreck revealed ancient DNA of olive, oregano, and possibly mastic, part of a cargo outbound from Chios.
Author(s): Brendan P. Foley 1 | Katerina Dellaporta 2 | Dimitris Sakellariou 3 | Brian S. Bingham 4 | Richard Camilli 5 | Ryan M. Eustice 6 | Dionysis Evagelistis 7 | Vicki Lynn Ferrini 8 | Kostas Katsaros 9 | Dimitris Kourkoumelis 10 | Aggelos Mallios 11 | Paraskevi Micha 12 | David A. Mindell 13 | Christopher Roman 14 | Hanumant Singh 15 | David S. Switzer 16 | Theotokis Theodoulou 17Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86047/1/bfoley-11.pd
XRFast a new software package for processing of MA-XRF datasets using machine learning
No full textX-ray fluorescence (XRF) spectroscopy is a common technique in the field of heritage science. However, data processing and data interpretation remain a challenge as they are time consuming and often require a priori knowledge of the composition of the materials present in the analyzed objects. For this reason, we developed an open-source, unsupervised dictionary learning algorithm reducing the complexity of large datasets containing 10s of thousands of spectra and identifying patterns. The algorithm runs in Julia, a programming language that allows for faster data processing compared to Python and R. This approach quickly reduces the number of variables and creates correlated elemental maps, characteristic for pigments containing various elements or for pigment mixtures. This alternative approach creates an overcomplete dictionary which is learned from the input data itself, therefore reducing the a priori user knowledge. The feasibility of this method was first confirmed by applying it to a mock-up board containing various known pigment mixtures. The algorithm was then applied to a macro XRF (MA-XRF) data set obtained on an 18th century Mexican painting, and positively identified smalt (pigment characterized by the co-occurrence of cobalt, arsenic, bismuth, nickel, and potassium), mixtures of vermilion and lead white, and two complex conservation materials/interventions. Moreover, the algorithm identified correlated elements that were not identified using the traditional elemental maps approach without image processing. This approach proved very useful as it yielded the same conclusions as the traditional elemental maps approach followed by elemental maps comparison but with a much faster data processing time. Furthermore, no image processing or user manipulation was required to understand elemental correlation. This open-source, open-access, and thus freely available code running in a platform allowing faster processing and larger data sets represents a useful resource to understand better the pigments and mixtures used in historical paintings and their possible various conservation campaigns.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Team Matthias Alfel
Musical Track Popularity Mining Dataset
No full textPart 10: Mining Humanistic Data Workshop (MHDW)International audienceMusic Information Research requires access to real musical content in order to test efficiency and effectiveness of its methods as well as to compare developed methodologies on common data. Existing datasets do not address the research direction of musical track popularity that has recently received considerate attention. Existing sources of musical popularity do not provide easily manageable data and no standardised dataset exists. Accordingly, in this paper we present the Track Popularity Dataset (TPD) that provides different sources of popularity definition ranging from 2004 to 2014, a mapping between different track/author/album identification spaces that allows use of all different sources, information on the remaining, non popular, tracks of an album with a popular track, contextual similarity between tracks and ready for MIR use extracted features for both popular and non-popular audio tracks
Trialogical Learning:A New Framework for Learning Through the Creative Relationship Between Emerging Technologies and Multiple Participants
No full textDifferent ways of knowing are acknowledged. What constitutes ‘knowledge’ is open to debate. The authority of the ‘author’ is being questioned, and related to that is the role and purpose of the ‘publisher’ as arbiter of quality. The nature of education is changing as learners take a more active role in the process and help shape what is ‘taught’ and how the curriculum is delivered. Emerging technologies offer possibilities for multi sensory engagement with learning materials and methods. A space now exists in which multiple learners may interact with experienced educators through digital media in a trialogical relationship that encourages the creative construction of new learning content and shared understandings that possibly may challenge and/or alter existing ones. This chapter speculates on such a framework for learning. It draws on extensive experience in creative practice, inquiry through practice and related pedagogy. Although currently only a concept, it is clear how such a framework might be realised
Design and implementation of ambiently powered Internet of Things-That-Think with asynchronous inference
No full textThis work was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) through the “First Call for H.F.R.I. Research Projects to support Faculty Members and Researchers and the Procurement of High-Cost Research Equipment” under Project 2846.
This article was presented in part at 5th IEEE International Workshop on Wireless Communications and Networking in Extreme Environments (WCNEE), International Conference on Distributed Computing in Sensor Systems (DCOSS), Pafos, Cyprus, July 2021, pp. 458–465 [DOI: 10.1109/DCOSS52077.2021.00077]. (Vasileios Papageorgiou, Athanasios Nichoritis, and Panagiotis Vasilakopoulos contributed equally to this work.) (Corresponding author: Aggelos Bletsas.)Summarization: This work offers design and implementation of in-network inference, using message passing among ambiently powered wireless sensor network (WSN) terminals. The stochastic nature of ambient energy harvesting dictates intermittent operation of each WSN terminal and as such, the message passing inference algorithms should be robust to asynchronous operation. It is shown, perhaps for the first time in the literature (to the best of our knowledge), a proof of concept, where a WSN harvests energy from the environment and processes itself the collected information in a distributed manner, by converting the (network) inference task to a probabilistic, in-network message passing problem, often at the expense of increased total delay. Examples from Gaussian belief propagation and average consensus (AC) are provided, along with the derivation of a statistical convergence metric for the latter case. A k-means method is offered that maps the elements of the calculated vector to the different WSN terminals and overall execution delay (in number of iterations) is quantified. Interestingly, it is shown that there are divergent instances of the in-network message passing algorithms that become convergent, under asynchronous operation. Ambient solar energy harvesting availability is also studied, controlling the probability of successful (or not) message passing. Hopefully, this work will spark further interest for asynchronous message passing algorithms and technologies that enable in-network inference, toward ambiently powered, batteryless Internet of Things-That-Think.Presented on: IEEE Internet of Things Journa
In silico estimation of annealing specificity of query searches in DNA databases
No full textWe consider DNA implementations of databases for digital signals with retrieval and mining capabilities. Digital signals are encoded in DNA sequences and retrieved through annealing between query DNA primers and data carrying DNA target sequences. The hybridization between query and target can be non-specific containing multiple mismatches thus implementing similarity-based searches. In this paper we examine theoretically and by simulation the efficiency of such a system by estimating the concentrations of query-target duplex formations at equilibrium. A coupled kinetic model is used to estimate the concentrations. We offer a derivation that results in an equation that is guaranteed to have a solution and can be easily and accurately solved computationally with bi-section root-finding methods. Finally, we also provide an approximate solution at dilute query concentrations that results in a closed form expression. This expression is used to improve the speed of the bi-section algorithm and also to find a closed form expression for the specificity ratios
A Type-and-Effect System for Object Initialization
No full textEvery newly created object goes through several initialization states: starting from a state where all fields are uninitialized until all of them are assigned. Any operation on the object during its initialization process, which usually happens in the constructor via \emph{this}, has to observe the initialization states of the object for correctness, i.e.~only initialized fields may be used. Checking safe usage of \emph{this} statically, without manual annotation of initialization states in source code, is a challenge, due to aliasing and virtual method calls on \emph{this}. Mainstream languages either do not check initialization errors, like Java, C++, Scala, or they defend against them by not supporting useful initialization patterns, such as Swift. In parallel, past research has shown that safe initialization can be achieved for varying degrees of expressiveness but by sacrificing syntactic simplicity. We approach the problem by upholding \emph{local reasoning} of initialization which avoids whole-program analysis, and we achieve \emph{typestate polymorphism} via subtyping. On this basis, we put forward a novel type-and-effect system that can effectively ensure initialization safety while allowing flexible initialization patterns with almost zero annotation burden.LAMP
The effect of socio-economic status on children's dental health
No full textThe aim of the present study was to record the oral health status of children from different socioeconomic backgrounds and correlate these findings with parent-associated factors. It comprised a cross-sectional study of healthy children, aged 6–12 years, attending either the Reception and Solidarity Center of the Municipality of Athens or the Postgraduate Paediatric Dentistry Department (NKUA) for dental care. Data regarding the demographics of both parents-guardians, as well as the children, and oral hygiene and dietary habits were collected through a structured questionnaire. This was followed by a thorough clinical examination evaluating oral hygiene status, gingival inflammation and caries experience. Analysis was based on the socioeconomic status (SES) of the parents which was according to the family income. Families with a monthly income of <1400 euros were considered as being of a low SES and families with incomes of >1400 euros as medium. Data were presented in frequency tables and significance of calculated differences was tested using chi-square and Fisher’s exact tests. Multivariate regression analysis was used to detect possible risk factors for development of poor dental health. The sample consisted of 216 children (146 from a low and 70 from a medium SES) with a mean chronological age of 9.19 years. Parents from low SES were younger, of lower education, had lived abroad most of their lives and were unemployed or worked in the private sector. Children from low SES backgrounds reported infrequent dental visits, consumed more meals and had more sugary snacks. This was reflected in their worse dental health with significantly higher values for oral hygiene and caries indices. Despite the above differences, none of the parent-associated factors were significantly correlated to worse dental health. In conclusion, SES of parents is reflected in the oral health of children, although it is not a significant predictor of dental health. © 2024 The Author(s)
How can DNA computing be applied to digital signal processing?
No full textAlthough digital signals have been used as inputs in some DNA computing applications, there has been a small research regarding the application of DNA computing principles in solving DSP problems. This article offers a first step towards filling this gap and thus strengthening the ties between biology and signal processing. By focusing the attention of the article to a specific domain, the author believes that many new exciting applications of DNA computation can be discovered. A short overview of molecular biology and tools commonly used in DNA computing is also provided for presentation purposes. This article offers the signal processing community some future directions regarding the unexplored area of research in biocomputing technology
