Sunday, September 27, 2015

Network Proximity for Content Discovery

Our new paper: I. D. Yousef and D. Namiot, “Network proximity for content discovery,” International Journal of Interactive Mobile Technologies (iJIM), vol. 9, no. 4, pp. 42–48, 2015.

The paper describes our approach for using wireless sensors on mobile phones for delivering new data to mobile subscribers. We propose a new practical approach for social context-aware data retrieval based on mobile phones as a sensor concept. This approach uses Wi-Fi and Bluetooth modules located on mobile phones as sensors for getting proximity information that can open (discover) access to any user-generated content or content published in the social networks. A special mobile service (context-aware browser client for Android) can present that information to mobile subscribers. The potential use-cases for the proposed approach include all projects associated with hyper-local news data. For example, news services in Smart City projects, proximity marketing, indoor data delivery, etc.

Saturday, September 26, 2015

Meta-Data in SDN API

Our new paper: M. Sneps-Sneppe and D. Namiot, “Metadata in sdn api for wsn,” in New Technologies, Mobility and Security (NTMS), 2015 7th International Conference on, pp. 1–5, IEEE Paris, France, 2015.

This paper discusses the system aspects of the development of applied programming interfaces in Software-Defined Networking (SDN). SDN is a prospect software enablement for Wireless Sensor Networks (WSN). So, application layer SDN API will be the main application API for WSN. Almost all existing SDN interfaces use so-called Representational State Transfer (REST) services as a basic model. This model is simple and straightforward for developers, but often does not support the information (metadata) necessary for programming automation. In this article, we cover the issues of representation of metadata in the SDN API.

Friday, September 25, 2015

On events recognition in optical sensing systems

Aleksey Fedorov, Maxim Anufriev, Andrey Zhirnov, Konstantin Stepanov, Evgeniy Nesterov, Dmitry Namiot, Valery Karasik, Alexey Pnev "Gaussian mixture model for events recognition in optical time-domain reflectometry based sensing systems"

The novel approach for recognition of particular classes of non-conventional events in signals from phase-sensitive optical time-domain reflectometry is proposed. The proposed algorithmic solution is based on the adaptive filtering for de-nosing of signals and Gaussian Mixture Model with the feature space formed by the cepstral coefficients for their clustering. We use experimentally measured signals from phase-sensitive optical time-domain reflectometry based sensing systems for evidence of the suggested algorithm. Our results show that two classes of events can be detected and distinguished between two classes with the probability being close to 0.9. Proposed algorithmic solution can be used in real-time distributed fiber optic sensing systems for control of protected areas.

Thursday, September 24, 2015

Twitter as a transport in information systems

Dmitry Namiot "Twitter as a Transport Layer Platform"

Internet messengers and social networks have become an integral part of modern digital life. We have in mind not only the interaction between individual users but also a variety of applications that exist in these applications. Typically, applications for social networks use the universal login system and rely on data from social networks. Also, such applications are likely to get more traction when they are inside of the big social network like Facebook. At the same time, less attention is paid to communication capabilities of social networks. In this paper, we target Twitter as a messaging system at the first hand. We describe the way information systems can use Twitter as a transport layer for own services. Our work introduces a programmable service called 411 for Twitter, which supports user-defined and application-specific commands through tweets.

Sunday, September 20, 2015

To Deep or not to Deep

An interesting discussion: Will deep learning make other Machine Learning algorithms obsolete?

Our own answer - No. Very often, simpler algorithms like logistic regression will work fine. Deep Learning success depends on the data volume. It should be huge and it is not always true.

Tuesday, September 15, 2015

Monday, September 14, 2015

LSTM Networks

A good technical paper: Long Short Term Memory networks – usually just called “LSTMs” – are a special kind of RNN, capable of learning long-term dependencies.

Thursday, August 20, 2015

On JavaScript memory management

Please, vode for our presentation on JavaScript memory management. We will publish it here after the conference.

Introduction to Markov chain

Markov chain is based on a principle of “memorylessness”. In other words the next state of the process only depends on the previous state and not the sequence of states. This simple assumption makes the calculation of conditional probability easy and enables this algorithm to be applied in number of scenarios. In this article, we will restrict ourself to simple Markov chain. - from here

Tuesday, August 04, 2015

INJOIT vol. 3, no. 8

International Journal of Open Information Technologies has just published its latest issue at We invite you to review the Table of Contents here and then visit our web site to review articles and items of interest.

International Journal of Open Information Technologies Vol 3, No 8 (2015)

Table of Contents

Applied mathematics

Intensification of search domain contraction in non-uniform covering method (1-7)

Modern programming issues

The case tool for software structure and metrics visualization in 3D space (8-16)

Telecommunication technologies and computer networks

On Model of Information System Based on push-notifications (17-29)
Control of transport routes via mobile phones (30-39)
On telecom services and the DISN evolution (40-47)

Big data and their applications

On Big Data Stream Processing (48-51)

Sunday, July 26, 2015

Introduction to Monte-Carlo

The idea of Monte Carlo methods is this—generate some random samples for some random variable of interest, then use these samples to compute values you’re interested in.

Friday, July 17, 2015

On Mobile Wireless Tags

Namiot D., Sneps-Sneppe M. On mobile wireless tags // Automatic Control and Computer Sciences. — 2015. — Vol. 49, no. 3. — P. 159–166.

The subject of the article refers to services of mobile networks related to a context. We are examining the questions of the development of mobile services employing wireless tags. In addition to this, a new model of usage (application) of Core Bluetooth devices is offered. In our model Bluetooth devices act as tags and are used for reference (binding) and the subsequent context-dependent determination of data available to mobile users. Mobile phones, as well as already existing devices with Bluetooth support, can be used as such dynamic tags. In this case a single mobile application is sufficient for coverage of all stages of the life cycle of contextual services. The application provides a presentation of a tag (tags) and the binding of informational content to these tags, as well as the viewing of data bound to other tags. The possible application fields are applications for retail and service organizations and context-dependent services for Smart Cities. DOI