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This study aims to analyze a conspicuous corpus of literature related to the field of technology-based intensive care research and to develop an architecture model of the future smart intensive care unit (ICU).

Papers related to the topics of electronic health record (EHR), big data, data flow and clinical decision support in ICUs were investigated. These concepts have been analyzed in combination with secondary use of data, prediction models, data standardization and interoperability challenges. Based on the findings, an architecture model evaluated using MIMIC III is proposed.

Research identified issues regarding implementation of systems, data sources, interoperability, management of big data and free text produced in ICUs and lack of accuracy of prediction models. ICU should be treated as part of a greater system, able to intercommunicate with other entities.

The research examines the current needs of ICUs in interoperability and data management. As environment changes dynamically, continuous assessment and evaluation of the model with other ICU databases is required.

The proposed model improves ICUs interoperability in national health system, ICU staff intercommunication, remote access and decision support. Its modular approach ensures that ICUs can have their own particularities and specialisms while ICU functions provide ongoing expertise and training to upgrade its staff.

The purpose of this paper is to introduce an interactive system that relies on the educational data generated from the online Universities services to assess, correct and ameliorate the learning process for both students and faculty.

In the presented research, data from the online services, provided by a Greek University, prior, during and after the COVID-19 outbreak, are analyzed and utilized in order to ameliorate the offered learning process and provide better quality services to the students. Moreover, according to the learning paths, their presence online and their participation in the services of the University, insights can be derived for their performance, so as to better support and assist them.

The system can deduce the future learning progression of each student, according to the past and the current performance. As a direct consequence, the exploitation of the data can provide a road map for the strategic planning of universities, can indicate how the learning process can be updated and amended, both online and in person, as well as make the learning experience more essential, effective and efficient for the students and aiding the professors to provide a more meaningful and to-the-point learning experience.

Nowadays, educational activities in academia are strongly supported by online services, information systems and online educational materials. The learning design in the academic setting is primarily facilitated in the University premises. However, the exploitation of the contemporary technologies and supporting materials that are available online can enrich and transform the educational process and its results.

The purpose of this paper is to propose a distributed smartphone sensing-enabled system, which assumes an intelligent transport signaling (ITS) infrastructure that operates traffic lights in a smart city (SC). The system is able to handle priorities between groups of cyclists (crowd-cycling) and traffic when approaching traffic lights at road junctions.

The system takes into consideration normal probability density function (PDF) and analytics computed for a certain group of cyclists (i.e. crowd-cycling). An inference model is built based on real-time spatiotemporal data of the cyclists. As the system is highly distributed – both physically (i.e. location of the cyclists) and logically (i.e. different threads), the problem is treated under the umbrella of multi-agent systems (MAS) modeling. The proposed model is experimentally evaluated by incorporating a real GPS trace data set from the SC of Melbourne, Australia. The MAS model is applied to the data set according to the quantitative and qualitative criteria adopted. Cyclists’ satisfaction (CS) is defined as a function, which measures the satisfaction of the cyclists. This is the case where the cyclists wait the least amount of time at traffic lights and move as fast as they can toward their destination. ITS system satisfaction (SS) is defined as a function that measures the satisfaction of the ITS system. This is the case where the system serves the maximum number of cyclists with the fewest transitions between the lights. Smart city satisfaction (SCS) is defined as a function that measures the overall satisfaction of the cyclists and the ITS system in the SC based on CS and SS. SCS defines three SC policies (SCP), namely, CS is maximum and SS is minimum then the SC is cyclist-friendly (SCP1), CS is average and SS is average then the SC is equally cyclist and ITS system friendly (SCP2) and CS is minimum and SS is maximum then the SC is ITS system friendly (SCP3).

Results are promising toward the integration of the proposed system with contemporary SCs, as the stakeholders are able to choose between the proposed SCPs according to the SC infrastructure. More specifically, cyclist-friendly SCs can adopt SCP1, SCs that treat cyclists and ITS equally can adopt SCP2 and ITS friendly SCs can adopt SCP3.

The proposed approach uses internet connectivity available in modern smartphones, which provide users control over the data they provide to us, to obviate the installation of additional sensing infrastructure. It extends related study by assuming an ITS system, which turns traffic lights green by considering the normal PDF and the analytics computed for a certain group of cyclists. The inference model is built based on the real-time spatiotemporal data of the cyclists. As the system is highly distributed – both physically (i.e. location of the cyclists) and logically (i.e. different threads), the system is treated under the umbrella of MAS. MAS has been used in the literature to model complex systems by incorporating intelligent agents. In this study, the authors treat agents as proxy threads running in the cloud, as they require high computation power not available to smartphones.

Institutional repositories (IR) are usually used to archive and manage digital collections including research results, educational material, etc. Learning management systems (LMS) form a popular basis for e-learning and blended learning. This paper aims to study how to integrate IR and LMS to support accessibility of disabled students and students with learning difficulties (dyslexic students) in higher education. Customised ontologies focusing on disabled students can be used to facilitate indexing, and access of items in the repository.

The authors propose a simple methodological approach to establish an integrating system for supporting accessibility. First, the authors review research works related to adaptive learning environments (ALEs) and blended learning, and discuss issues of the interoperability of IR and LMS. Then, based on the review, the authors discuss the use of an integrated ALE for supporting disabled students in the domain of higher technological education. The integrated system is based on IR, LMS and assistive and adaptive technology. The open source software platform DSpace is used to build up the repository applications Use of the web ontology language (OWL) ontologies is also proposed for indexing and accessing the various, heterogeneous items stored in the repository. Various open source LMS (e.g. openeclass) could be used to build up the integrated system. Finally, the authors describe experimentation with a prototype implemented to provide the mentioned capabilities.

The technology is mature enough for building up integrated systems, combining capabilities of IR and LMS, for supporting disabled students. The use of ontologies focused on disabled students could facilitate the use of such integrated systems. Customisation and operation of a platform, for the selection and use of portions of OWL ontologies, could be based on the open source software Protégé. Such a platform forms a basis to create an appropriate ontology suitable for specific domains, e.g. the domain of technological education. Finally, the authors argue that the combined use of the OWL platform and the DSpace repository with open source LMS platforms could support domain experts for creating customised ontologies and facilitating searching.

A new perception of the term integrated system for supporting disabled students in the higher education context is presented. This perception tries to combine the IR technology that supports the self-archiving approach of information, open LMS technology and the user-centred approach to support students and manage the “life of information”.

Pervasive environments are mostly based on the ad hoc networking paradigm and are characterized by ubiquity in both users and devices and artifacts. In these inherently unstable conditions and bearing in mind the resource’s limitations that are attributed to participating devices, the deployment of Knowledge Management techniques is considered complicated due to the particular requirements. Security considerations are also very important since the distribution of knowledge information to multiple locations over a network, poses inherent problems and calls for advanced methods in order to mitigate node misbehaviour and in order to enforce authorized and authenticated access to this information. This paper addresses the issue of secure and distributed knowledge management applications in pervasive environments. We present a prototype implementation after having discussed detailed design principles as far as the communications and the application itself is regarded. Robustness and lightweight implementation are the cornerstones of the proposed solution. The approach we have undertaken makes use of overlay networks to achieve efficiency and performance optimization, exploiting ontologies. The work presented in this paper extends our initial work to tackle this problem, as this was described in (28).

The purpose of this paper is to understand the emotional state of a human being by capturing the speech utterances that are used during common conversation. Human beings except of thinking creatures are also sentimental and emotional organisms. There are six universal basic emotions plus a neutral emotion: happiness, surprise, fear, sadness, anger, disgust and neutral.

It is proved that, given enough acoustic evidence, the emotional state of a person can be classified by an ensemble majority voting classifier. The proposed ensemble classifier is constructed over three base classifiers: k nearest neighbors, C4.5 and support vector machine (SVM) polynomial kernel.

The proposed ensemble classifier achieves better performance than each base classifier. It is compared with two other ensemble classifiers: one-against-all (OAA) multiclass SVM with radial basis function kernels and OAA multiclass SVM with hybrid kernels. The proposed ensemble classifier achieves better performance than the other two ensemble classifiers.

The current paper performs emotion classification with an ensemble majority voting classifier that combines three certain types of base classifiers which are of low computational complexity. The base classifiers stem from different theoretical background to avoid bias and redundancy. It gives to the proposed ensemble classifier the ability to be generalized in the emotion domain space.

The purpose of this paper is to examine personal digital libraries (PDL) as a self-archiving approach, mainly based on individuals’ activities. Literature presents a wide range of perceptions of the term PDL. The rationale of using PDL and the capabilities that PDL should offer are also discussed. The key questions we focus on are: “What are the critical features of PDL?” and “Are there technologies that enable the implementation/incorporation of such capabilities in a low cost software product?”

We focus on “a user centred view of information process”, and examine how PDL could assist individuals to “create, seek, share and manage the life of information” (Foster et al., 2010). The capabilities that PDL should support, and the related technologies, are also discussed. Then, we describe experimentation with a prototype implemented to support/provide the mentioned capabilities. It is used to clarify our view for the creation of PDL. Finally, further discussion and conclusions are presented.

The technology is mature enough for building up PDLs with the specified features/capabilities.

A new perception of the term PDLs is presented. This perception tries to combine the self-archiving approach of information, based on a low-cost tool, and the user-centred approach to manage the “life of information”. This type of library is mainly used to cover personal needs. Users benefit from this type of PDL by personalised handling of information, reduced time to search and seek specific documents in their personal collections and less possibility for broken links or unavailable documents. We must also mention that new opportunities seem to appear for offering PDL as a service in the cloud.

The purpose of this paper is to investigate the association of lack of awareness and human factors and the association of lack of awareness and significant attacks that threat computer security in higher education.

Five human factors and nine attacks are considered to investigate their relationship. A field research is conducted on Greek employees in higher education to identify the human factors that affect information security. The sample is consisted of 103 employees that use computers at work. Pearson correlation analysis between lack of awareness and nine (9) computer security risks is performed.

Examining the association of lack of awareness with these attacks that threat the security of computers, all nine factors of important attacks exert significant and positive effect, apart from phishing. Considering the relationship of lack of awareness to human factors, all five human factors used are significantly and positively correlated with lack of awareness. Moreover, all nine important attacks, apart from one, exert a significant and positive effect.

The paper extends understanding of the relationship of the human factors, the lack of awareness and information security. The study has focused on employees of the Technological Educational Institute (TEI) of Athens, namely, teachers, administrators and working post-graduate students.

The paper has used weighted factors based on data collection in higher education to calculate a global index for lack of awareness, as the result of the weighted aggregation of nine (9) risks, and extends the analysis performed in the literature to evaluate the effectiveness of security awareness in computer risk management.

The purpose of this paper is to investigate risk reduction strategies in online shopping through the perspective of buyer’s trust.

An explanatory research approach is adopted to identify cause-and-effect relationships between e-quality and customers’ loyalty, satisfaction and trust. This approach is accomplished through field research, which is based on a structured questionnaire that utilizes the E-S-QUAL tool, which is a multiple-item general scale for measuring electronic service quality. The sample is consisted of 92 e-buyers (consumers).

The field research revealed that three e-quality dimensions, namely, ease of use, customization and assurance, e-scape and responsiveness, have significant positive effects on e-loyalty and e-satisfaction. Regarding e-trust, only customization and assurance exerts a significant positive effect.

The field research provides in-depth understanding of relationships among e-loyalty, e-satisfaction and e-trust. The majority of the respondents are young people living in Athens, Greece, highly educated, with a relative low monthly income.

This study investigates how trust is affecting the consumers’ engagement to e-commerce, suggesting the appropriate security that should be taken to mitigate perceived risks. Reviewing security measures can help reduce risks of an e-company and simultaneously enforce the level of trust and customers' intentions to buy.