Alexandra Cernian

Cloud-based application development platform for secure, intelligent, interlinked and interactive infrastructure

This paper presents a cloud-based secure, intelligent, interlinked and interactive application development platform that is able to collect and transmit information from a variety of data sources across multiple wireless communication systems. The platform is called S4I and it is based on a three layer scalable architecture, facilitating communication interoperability. Web-based applications, hosted on cloud servers, can be developed and customized according to the clients needs and accessed by the end user from anywhere in the world. The S4I platform brings major achievements to the wireless cloud-based communication and interoperability.

Cloud-based mobile asset management solution

This paper presents an application based on the the cloud-based S4I platform [1], which is called Mobile Asset Management System (MAMS). The application is able to monitor and control mobile assets anywhere in the world with a PC and Internet connection. It is integrated in the Application Layer of the S4I platform. MAMS is a mobile asset management solution dedicated to locating and monitoring commercial fleets. The implementation of the MAMS application is a reliable proof of the flexibility and the scalability of the S4I platform, truly creating a unique cloud-based integration system for wireless radio communication.

A semantic Web based scientific news aggregator

Scientists want to stay connected with everything that is new in scientific world, so they constantly read several online scientific magazines and newspapers. However, not all the subjects are of interest to everyone. Consequently, a user is forced to do a lot of browsing to find the articles which are important to him. This paper presents a scientific news aggregator, structured as an online magazine. The content is automatically withdrawn from several online publications, available on the Internet. Instead of using a traditional database, all the information about the items posted on the site is stored in a RDF file, which is automatically updated.

An Architecture for a Semantic Web Management System

The Semantic Web is a project and vision of theWorld Wide Web Consortium to extend the current Web, so that information is given well-defined meaning and structure, enhancing computers and people to work in cooperation.Semantic technologies are being added to enterprise solutions to accommodate new techniques for discovering relationships across different database, business applications and Web services. In this paper, we present an architectural model for a software tool which combines the use of Semantic Web mechanisms with database metadata and data warehousing mechanisms. If the benefits of the Semantic Web concept are combined with a powerful database server, then the information management will be much improved.

Biomedical data correlation and reuse in analyzing the efficiency of rehabilitation treatment

The aim of the project making the subject of this paper was setting up a complex database (medical, imagistic, biomechanical) and developing conceptual models for interpreting the available data, with direct applicability in choosing and evaluating the treatment. The database contains heterogeneous, multidisciplinary data, provided by various investigations. Research based on corroborating clinical data, specific to each specialization involved in the functional rehabilitation process for patients with orthopaedics or neuromuscular pathology, has been successfully associated with motion analysis software, in order to create a complex acquisition and data processing system, with direct applicability in the human motility analysis.

Mood Detector - On Using Machine Learning to Identify Moods and Emotions

This paper presents the design and implementation of the Mood Detector application, which is designed to detect the mood and emotional state of the user by analyzing 3 physical parameters (pulse, skin electro conductivity and temperature) by using a machine learning algorithm which is trained with data from the users. The application has been tested repetitively until the results generated by the learning algorithm have been validated 100%, thus confirming that the machine learning algorithms provides the correct output. The application also integrates a music recommender system, which suggests the user to listen to specific playlists, designed according to his currently detected mood.

The risks in the social networks — An exploratory study

While social networking has gone on almost as long as societies themselves have existed, the unparalleled potential of the Web to facilitate such connections has led to an exponential and ongoing expansion of that phenomenon. In addition to social media platforms, the capacity for social interaction and collaboration is increasingly built into business applications [1]. The risks in the online space and particularly in social networks represent one of the most important and opened issue of our time. The paper is an exploratory study with the focus point related to an original research based on a questionnaire with more that 300 of respondents. Topics about the risks in the social networks such as: the security in the social networks, incidents, viruses, worms, spam, the level of security regarding the applications used on social networks, etc were analysed. The findings of this research provide a basis that is useful to understand the importance of the prevention and treatment of risks in the social networks. Regarding the management perspective of an organization, this paper highlights the necessity of the investments in companies security against cyber risks. The paper also provides useful findings in the field of cyber risks for the online community.

The use of social platforms and personal data protection — An exploratory study

The social networks are used by millions of users. Depending on the social media platform, members may be able to contact any other member. In other cases, members can contact anyone they have a connection to, and subsequently anyone that contact has a connection to, and so on. Some services require members to have a preexisting connection to contact other members [1]. According to [2], the number of unique visitors on some social platforms is: Facebook — 1,500,000,000 — Estimated Unique Monthly Visitors, YouTube — 1,499,000,000 — Estimated Unique Monthly Visitors, Twitter — 400,000,000, Instagram — 275,000,000 Visitors/month, LinkedIn — 250,000,000 Visitors/month. The main scope of a social network is to interconnect persons with common interests. They can also be used in business. The paper is a study about social media and consists of an original research based on a questionnaire with more than 300 of respondents. Some of the investigated issues are: the security in the social networks, the scope of the use of social networks, personal data protection, identity theft, the dependence of the use of social media, etc. The results of the research provide a basis that is useful to understand the importance of the use of social networks and also the personal data protection in such platforms. The paper also provides useful findings for the online community regarding the use of social platforms and the protection of person on such virtual medium.

On Using a Cloud-Based Approach to Develop a Mobile Asset Management Solution

After the 9/11 events, stakeholders around the world have become concerned and looked for solutions to address the safety of the global transportation infrastructure. The Mobile Assets Management System (MAMS) presented in this paper focuses on improving transportation safety related aspects such as vehicle safety, cargo safety, passenger safety and driver safety. MAMS is a mobile asset management solution dedicated to locating and monitoring commercial fleets, offering fleet managers and dispatchers complete monitoring and control capabilities from an Internet-connected computer located anywhere in the world. The system is built on a cloud based secure, intelligent, interlinked and interactive infrastructure, namely the S4I I™ platform developed by SafeMobile. The implementation of the MAMS application is a reliable proof of the flexibility and the scalability of the S4I platform, truly creating a unique cloud-based integration system for wireless radio communication. We present the context and the benefits of the mobile asset management solution, the architecture and the main components of the system and we underline the advantages it provides to the global transportation infrastructure in terms of safety and security, which is a major concern nowadays.

Cloud based Student Transportation Safety System

In the post-9/11 world, fleet managers, government officials, public safety personnel, and other stakeholders have become concerned about the potential for attacks involving trucks, containers, or other elements of the global transportation infrastructure. The current smart city trend focuses on providing an intelligent, interoperable and secure environment for all citizens. The cloud based Student Transportation Safety System presented in this paper is a location aware mobile asset management solution for operators of commercial fleets, having a cloud based platform at its core. The system focuses on improving all aspects related to transportation safety and it is based on a secure, global transportation infrastructure that is intelligent, interlinked and interactive.