Christos Skourlas

Providing advanced remote medical treatment services through pervasive environments

Advances on sensor technology, wireless environments and data mining introduce new possibilities in the healthcare sector, realizing the anytime-anywhere access to medical information. Towards this direction, integration of packet-switched networks and sensor devices can be effective in deploying assistive environments, such as home monitoring for elderly or patients. In this paper we describe a policy-based architecture that utilizes wireless sensor devices, advanced network topologies and software agents to enable remote monitoring of patients and elderly people; through the aforementioned technologies we achieve continuous monitoring of a patient’s condition and we can proceed when necessary with proper actions. We also present a software framework and network architecture that realizes the provision of remote medical services, in compliance with the imposed security and privacy requirements. A proof of concept prototype is also deployed, along with an evaluation of the overall architecture’s performance.

PNS: A Personalized News Aggregator on the Web

Summary. This paper presents a system that aggregates news from various electronic news publishers and distributors. The system collects news from HTML and RSS Web documents by using source-specific information extraction programs (wrappers) and parsers, organizes them according to pre-defined news categories and constructs personalized views via a Web-based interface. Adaptive personalization is performed, based on the individual user interaction, user similarities and statistical analysis of aggregate usage data by machine learning algorithms. In addition to the presentation of the basic system, we present here the results of a user study, indicating the merits of the system, as well as ways to improve it further.

A parametric methodology for text classification

Finding the correct category (class) a new unclassified document belongs to is an interesting and difficult problem, with a wide range of applications. Our methodology for narrative text classification is based on two techniques: we calculate the distance (similarity) between the new unclassified document and all the pre-classified documents of each class and also calculate the similarity of the new document to the ‘average class document’ of each class. In both cases we use key phrases (text phrases or key terms) as the distinctive features of our text classification methodology and eventually the proposed text classification method is based on the automatic extraction of an authority list of key phrases that is appropriate for discriminating between different classes. In this paper, we apply this methodology in handling Greek text and we present the key concepts, the algorithms, and some critical decisions. A number of parameters of the mining algorithm are also fine tuned. The actual text classification system, the adopted (embedded) ideas and the alternative values of parameters are evaluated using two training sets (test collections).

A pervasive architectural framework for providing remote medical treatment

The proliferation of mobile devices has led to their integration into a huge number of assistive environments where they perform a key role. Pervasive environments, built over wireless infrastructures, introduce new possibilities in the healthcare sector realizing the anytime-anywhere access to medical information paradigm. Towards this direction pervasive technology can be deployed in assistive environments, such as home monitoring for elderly or patients. In this paper we describe a policy based architecture that utilizes software agents and wireless sensor technologies to enable remote monitoring of patients and elderly people. We also discuss the technical challenges which directed the decisions with respect to the design of our software prototype architecture. These decisions mainly focus on providing continuous feedback of the patients condition, while transferring encrypted versions of the necessary medical information in accordance with the increased security and privacy requirements. The presented prototype implementation utilizes advanced network management technologies and software agent engineering in order to operate effectively, to achieve interoperability through the different modules and in order to comply with the imposed (by the legislative framework) increased security and privacy requirements.

Computer assisted information resources navigation

In this paper, the design and development of Computer Assisted Information Resources Navigation (CAIRN) is discussed. CAIRN system is a medical information retrieval system that allows physicians and students to store full text medical information from any resource, organize and retrieve it. The most important feature of CAIRN is its capability to assist the user, physician, student etc. in selecting documents against a submitted query in Natural Language. The retrieved documents are presented in decreasing order according to their similarity to the submitted query. The nearest neighbour method is used. An alternative similarity measure based on a new calculation of the length of documents is proposed and some experimentation with it is discussed.

Human factor and information security in higher education

– 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.

Secure and distributed knowledge management in pervasive environments

Pervasive environments are mostly based on the ad hoc networking paradigm and are characterized by ubiquity in both users and devices and artefacts. In these inherently unstable conditions and bearing in mind the resources limitations that are attributed to participating devices, the deployment of knowledge management techniques is considered complicated due to the particular requirements. This paper addresses the issue of secure and distributed knowledge management applications in pervasive environments. We present a prototype implementation after having presented 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.

Deploying pervasive secure knowledge management infrastructures

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).

A wireless distributed framework for supporting assistive learning environments

There is a lot of interest in developing environments utilizing various types of assistive technologies lately. Among else, people with specific difficulties may benefit from specially designed devices and software that aim in overcoming the disabilities of various groups. We describe a framework that aims in the provision of advanced services towards the facilitation of access to information for specific groups of people. Among else, our approach uses various tools and techniques. With wireless devices access to information is achieved independently of location, while with personalized services there is a capability to adjust the services and interfaces to various demands. Finally with a specific methodology that has been developed and tested as a result of international projects, the content and interfaces are adjusted to various needs of the participating user-groups.

Naive Rule Induction For Text ClassificationBased On Key-phrases

In this paper, we focus on the induction of naive rules for classifying text documents. An algorithm is briefly described for the creation of key-phrases from a given set of documents and these key-phrases are organized and used as features for the automatic classification of new documents. An Authority list of key-phrases is specified by the algorithm containing key-phrases that are frequent within the documents of only one or few classes in the training set. In this framework, this last property permitted us the creation of naive rules that measure the similarity of new documents with the existing classes.