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The purpose of this paper is to determine the electric field and specific absorption rate (SAR) distribution within biological tissues in the vicinity of dental implants, exposed to the mobile phone radiation.

This research was performed for the frequency of 2.6 GHz, which corresponds to 4G mobile network. The adequate 3D realistic numerical models of the mobile phone user’s head, dental implants and actual smartphone model are created using packages based on the finite integral technique numerical method.

The obtained results yield to a conclusion that the presence of dental implants affects the increase in electric field intensity and SAR values within biological tissues in its vicinity.

The presented procedure is limited to the 4G mobile network frequency of 2.6 MHz. The study should be extended to other mobile network frequencies to be more general.

The criteria for selection of the materials used for dental implants production should be extended with the recommended material characteristics related to their influence on the electric field and SAR distribution, to keep their values in the limits prescribed by standards.

The obtained results provide the foundation for future research in mobile devices’ electromagnetic fields’ influence on human health.

The accurate determination of the electric field and SAR values within different biological tissues and organs in the vicinity of dental implants exposed to mobile phone electromagnetic radiation, demands highly realistic model of observed biological structures. For purposes of the current study, the procedure for modeling of highly nonhomogeneous structure with finite number of homogenous domains having known electromagnetic parameters is described in the paper. As a result, the 3D complex users’ head model formed of 16 homogeneous domains of different electromagnetic parameters is created.

The purpose of this paper is to determine the impact of human age on the distribution of electric field and absorbed energy that originates from a mobile phone.

This research was performed for frequencies of 900, 1800 and 2100 MHz, which are used in a mobile communication system. To obtain the most accurate results, 3 D realistic model of the child’s head has been created whereby the dimensions of this model correspond to the dimensions of a seven-year-old child. Distribution of the electric field and specific absorption rate (SAR) through the child’s head was obtained by numerical analysis based on the finite integration technique.

The results discover that amount of absorbed energy is greater in the surface layers of the child’s head model when the electromagnetic (EM) characteristics of tissues are adjusted for the child. This deviation corresponds to different EM characteristics of biological tissues and organs of an adult person compared to a child.

The study deals with penetrated electrical field and absorbed EM field energy. There is space for further studies of other EM field effects (e.g. thermal effects).

The analysis of obtained results leads to idea that mobile phones and devices aimed for children using should be modified to provide SAR values inside prescribed standards.

The obtained results are foundation for future research on influence of EM fields of mobile devices on human health.

The proposed procedure offers the model for accurate estimation and quality analysis of SAR and EM field distribution inside child head tissue.

This paper aims to present a methodology by which future knowledge flow can be predicted by predicting co-citations of patents within a technology domain using a link prediction algorithm applied to a co-citation network.

Several methods and approaches are used: a dynamic analysis of a patent citation network to identify technology life cycle phases, patent co-citation network mapping from the patent citation network and the application of link prediction algorithms to the patent co-citation network.

The results of the presented study indicate that future knowledge flow within a technology domain can be predicted by predicting patent co-citations using the preferential attachment link prediction algorithm. Furthermore, they indicate that the patent – co-citations occurring between the end of the growth life cycle phase and the start of the maturation life cycle phase contribute the most to the precision of the knowledge flow prediction. Finally, it is demonstrated that most of the predicted knowledge flow occurs in a time period closely following the application of the link – prediction algorithm.

By having insight into future potential co-citations of patents, a firm can leverage its existing patent portfolio or asses the acquisition value of patents or the companies owning them.

It is demonstrated that the flow of knowledge in patent co-citation networks follows a rich get richer intuition. Moreover, it is show that the knowledge contained in younger patents has a greater chance of being cited again. Finally, it is demonstrated that these co-citations can be predicted in the short term when the preferential attachment algorithm is applied to a patent co-citation network.

This paper aims to describe the structure of an aligned Serbian-German literary corpus (SrpNemKor) contained in a digital library Bibliša. The goal of the research was to create a benchmark Serbian-German annotated corpus searchable with various query expansions.

The presented research is particularly focused on the enhancement of bilingual search queries in a full-text search of aligned SrpNemKor collection. The enhancement is based on using existing lexical resources such as Serbian morphological electronic dictionaries and the bilingual lexical database Termi.

For the purpose of this research, the lexical database Termi is enriched with a bilingual list of German-Serbian translated pairs of lexical units. The list of correct translation pairs was extracted from SrpNemKor, evaluated and integrated into Termi. Also, Serbian morphological e-dictionaries are updated with new entries extracted from the Serbian part of the corpus.

A bilingual search of SrpNemKor in Bibliša is available within the user-friendly platform. The enriched database Termi enables semantic enhancement and refinement of user’s search query based on synonyms both in Serbian and German at a very high level. Serbian morphological e-dictionaries facilitate the morphological expansion of search queries in Serbian, thereby enabling the analysis of concepts and concept structures by identifying terms assigned to the concept, and by establishing relations between terms in Serbian and German which makes Bibliša a valuable Web tool that can support research and analysis of SrpNemKor.

The purpose of this study is to analyze how embedding of self-powered wireless sensors into cloud computing further enables such a system to become a sustainable part of work environment.

This is exemplified by an application scenario in healthcare that was developed in the context of the OpSIT project in Germany. A clearly outlined three-layer architecture, in the sense of Internet of Things, is presented. It provides the basis for integrating a broad range of sensors into smart healthcare infrastructure. More specifically, by making use of short-range communication sensors (sensing layer), gateways which implement data transmission and low-level computation (fog layer) and cloud computing for processing the data (application layer).

A technical in-depth analysis of the first two layers of the infrastructure is given to prove reliability and to determine the communication quality and availability in real-world scenarios. Furthermore, two example use-cases that directly apply to a healthcare environment are examined, concluding with the feasibility of the presented approach.

Finally, the next research steps, oriented towards the semantic tagging and classification of data received from sensors, and the usage of advanced artificial intelligence-based algorithms on this information to produce useful knowledge, are described together with the derived social benefits.

The work presents an innovative, extensible and scalable system, proven to be useful in healthcare environments.

The short lifespan of digital signatures presents a challenge to the long-term preservation of digitally signed records. It can undermine attempts to presume, verify or assess their authenticity. This paper aims to investigate the challenges of the expiration of digital signatures in the context of digital archiving.

The paper identifies requirements for the long-term preservation of digitally signed records and compares them with the existing approaches. The characteristics, operational procedures and requirements of the technologies used for digital signatures are combined with the archival requirements to design a new model.

The paper proposes a new model of a blockchain-based system, which can be combined with any digital archive to assist the process of long-term preservation of digitally signed records.

The proposed model offers a new alternative to the current practice in the long-term preservation of digitally signed records, such as periodic resigning procedures or periodic wrapping of digitally signed records with archival timestamps.

The proposed TrustChain 2.0 model is based on previous research conducted as part of the InterPARES Trust project. It builds on TrustChain 1.0 by including digital signature certificate chain validity information in a blockchain thus avoiding the issues concerning records confidentiality and privacy information disclosure. The paper contributes not only to the development of archival science but also shows archival institutions on how to approach long-term preservation of digitally signed records.