Friday, December 20, 2019

OD matrices in transport tasks

The paper considers the analysis of data in so-called origin-destination matrices. Also in relation to them often use the term matrix of correspondence. As practical examples, we are using data from Moscow metro and Moscow suburb railways. The correspondence matrix shows the number of trips between two points (stations) for a selected time interval. Theoretically, such data being calculated for the given time intervals describe all the characteristics of the passenger load. But practically, it depends on the existing models for traffic. Currently, such data used, mostly, just to calculate simple statistics. But such a simplified approach completely ignores the temporal characteristics of the traffic. In this paper, we discuss data mining models and approaches for origin-destination matrices analysis. Also, we describe the results of applying such approaches to analyzing data from the Moscow region.

from our new paper: On Processing of Correspondence Matrices in Transport Systems

Thursday, December 19, 2019

On Physical Web for Social Networks

The article discusses the use of Physical Web approaches for the expansion of social networks. This implies the presentation of data from social networks in a real (physical) context, as well as the inverse task of using information about a real physical context in querying and analyzing data from social networks. First of all, mobile phones of social network users are considered as real objects that will be used both in data dissemination and in gathering information about the context. In this case, the purpose of consideration is to build a “natural” extension, when the implementation does not require the creation of a special type of social network entries. The general scheme or model of implementation is based on the minimization (or even complete absence) of requesting additional rights to access the social network, the absence of marks in the social network, and the use of basic functionality and standard protocols for mobile devices.

From our new paper: Namiot D., Sneps-Sneppe M. (2019) On Physical Web for Social Networks. In: Vishnevskiy V., Samouylov K., Kozyrev D. (eds) Distributed Computer and Communication Networks. DCCN 2019. Communications in Computer and Information Science, vol 1141. Springer, Cham

Tuesday, December 10, 2019

On mobility patterns in Smart City

The article is devoted to the analysis of transport data in the Moscow region, which was used in the design of new urban rail lines. Mobility (smart mobility) is one of the main characteristics of a smart city. Understanding how residents in a city actually move is necessary for the reliable provision of transport services, the construction of new transport lines, etc. Understanding patterns of displacement allows you to identify anomalies in urban displacements, which are evidence of some changes in the urban environment. The basis for the analysis is the data of mobile operators and information on the use of travel documents. - from our new paper

Thursday, October 31, 2019

On Enterprise Information Systems and Cyber Threats

The main goal of the paper is to look for new university courses regard Russian digital economy program, which is oriented to the end-to-end digital technologies, including: Big Data; neuro-technologies and artificial intelligence; quantum technologies; industrial internet; robotics and sensory; wireless communication; technologies of the virtual and complemented realities. According to the newer Pentagon activities, the key attention in the field of Information Systems has turned to Cloud Strategy and Artificial intelligence. This Pentagon's new strategy was developed after the serious critics of the current state, namely, the shortcomings with Joint Information Environment and its key cyber-security equipment - Joint Regional Security Stacks. Two-side difficulties for DoD modernization are discussed: from one side, the vendors' pressure introduce the latest achievements, namely, Software Defined Network and Network Function Virtualization, and from another, it is difficult to abandon the old technology, as time-division multiplexing, asynchronous transfer mode equipment, signaling protocol SS7 and Advanced Intelligent Network - our presentation from ICUMT 2019

Tuesday, October 08, 2019

The curse of software

For shifting from circuit switching to packet switching in telecommunications, the main obstacle is excessive software. Our presentation "The curse of software: Pentagon telecommunications case"

Saturday, September 14, 2019

Channel Switching Protocols Hinder the Transition to IP World

In this paper, we target the strategy for telecommunications architectures during the transition to the IP-only models. The paper discusses the shifting from circuit switching to packet switching in telecommunications. Particularly, we analyze the coexistence of circuit switching and packet switching technologies in American military communications where each warfare object should have own IP address. The paper discusses the role of multifunction Soft Switches (MFSS). This Soft Switch plays the role of a media gateway between TDM channels and IP channels. As a case, we are passing through the transformation from SS7 signaling to internet protocol, ISDN-based government Defense Red Switch Network and, finally, the extremely ambitious cybersecurity issues and the cyber vulnerabilities of weapons found by Government Accountability Office. We conclude the growing cyber threats will provide a long-term channel-packet coexistence.

from our new paper

Thursday, May 23, 2019

On proximity information systems

The paper discusses the replacement of well-known conception of geo-information systems with a new model based on proximity. Geo-information systems have attracted great attention and have received great development in recent times. The reasons for this are fairly obvious. On the one hand, services are required by users, primarily at their location, and on the other hand, location determination has become easy, especially in connection with the proliferation of smartphones. But at the same time, the actual geographic coordinates are not needed by the majority of such services. Coordinates are used only for searching and organizing data. While the actual assignment of most services is a search for data (services) bound by these coordinates to a spe cific area. In other words, in most cases, service is meant data near the current location. Hence the idea to build services directly on the assessment of proximity, completely bypassing the work with coordinates. It also makes possible completely new services, especially in the technical field (for example, in transport, agriculture, etc.).

from our new paper

Thursday, May 16, 2019

On Content Models for Proximity Services

First time introduced in Release 12 of the 3GPP specifications, Proximity Services (ProSe in the above-mentioned specification) is a Device-to-Device (D2D) technology that allows two devices to detect each other and to communicate directly without traversing the Base Station or core network. In other words, it is a technology that is oriented (ultimately) on the direct connection of two devices. In this article, we are promoting the idea that proximity services are more than just support for a direct connection (in fact, search for candidates for a direct connection). The paper discusses content models (that is, information dissemination models) based on proximity data. In this case, a direct connection is simply one of the possible options for disseminating information.

Our new paper from FRUCT conference

Wednesday, April 17, 2019

Bikes in Smart Cities

Our new paper: On Bikes in Smart Cities

In this paper, we discuss data models and data mining for bicycles in Smart Cities. Mobilityissues (or Smart Mobility) are one of the main components of Smart Cities. Bicycles, as a transportcomponent in the cities, are on the rise all over the world. At least, it is true for all areas where the cli-mate even minimally allows it. The reasons are quite obvious. This is democratic and accessible thistype of transport, it is cheap and environmental friendliness. Of course, the promotion of a healthylifestyle also plays its role. The development of this type of transport (like any other) has many differentaspects. In this paper, we dwell on the issues of tracking the movement of cyclists and planning bike-sharing systems. All this information will serve as a set of metrics for any design in Smart Cities.

Read it here

Tuesday, March 12, 2019

Time series on railways

The article analyzes the patterns of use of railway stations in the Moscow region. The basis for the analysis is the data of smart cards on the entrances and exits of passengers. The technical tool is time series similarity analysis. As a result, the work identifies the main patterns of user behavior on the use of railway stations (railway transport). The results of the work were used in the design of new lines of urban railways. Obviously, the use patterns reflect the current state of the transport system and the urban environment. Accordingly, the recorded changes in usage patterns can serve as indicators and metrics for changes in the urban environment. Our paper in Arxiv

Wednesday, January 16, 2019

Open PhD positions

Announcement: 15 PhD positions fully funded for 3 years within A-WEAR Joint Doctorate Network

Target audience: fresh MSc graduates in various engineering fields (who have completed their first master no earlier than Fall 2015 or who will soon complete their MSc) and who are passionate about pursuing a PhD in a research field of high relevance to today’s society (wearable computing & IoT).

Job description: fully funded 36 months PhD positions towards double/joint PhD programs in 5 top European technical universities in Finland, Italy, Spain, Czech republic, and Romania
Gross salary (approx. in EUR/month): 3600 (FI), 2800 (ES), 2000 (RO), 2400 (CZ), 2900 (IT)
Application deadline: 28th of February 2019

Starting time of the PhD: Fall 2019

Selection criteria: Study records Bsc + Msc (20%); Work & research experience (15%); Motivation (20%); Clarity, relevance, innovativeness, and technical soundness of the ’Dissertation Essay’ (25%); Letters of recommendation (10%); Positive attitude, previous mobility experience, good communication skills (10%); English proficiency: fail/pass criterion.

We strive to improve the gender balance in our research groups and encourage female candidates to apply. At the end of the evaluation process, the recruitment committee will decide which candidates to select for each project, taking into account the candidates’ preferences and potential. In case of equal qualifications between a male and a female candidate for the final position, the balance at network level may affect the decision.

More information and link to the application page: www.a-wear.eu/recruitment or https://euraxess.ec.europa.eu/jobs/364125

Tuesday, January 08, 2019

Machine learning in software development

The subject of the article is the “coding style” concept and the main approaches to detecting the individual style of a programmer. The entire process of creating a software product from this point of view and the main features of programming style are analyzed. It emphasizes the relevance and commercial significance of the problem in terms of product support, plagiarism, work of a large developer’s community in a single repository, an evolution of developer skills. Computational stylometry issues, a possibility of using programming paradigms as an additional factor of style identification are considered. It offers the idea of creating a software tool that allows to identify the style of the author who wrote a particular program fragment and allows less experienced developers to follow the rules accepted in the major part of the repository and determined by coding style of "experts", which leads the code to a uniform format that is easier to maintain and make adjustments. Globally, this stage of analyzing the original (and then the modified code) allows improving the existing algorithms for automatic synthesis of programs.

Our new paper: Using Machine Learning Methods to Establish Program Authorship