On transport models

On Passenger Flow Estimation for new Urban Railways

In this paper, we discuss the questions, associated with the forecast for passenger traffic for urban railways. The aim of the study is to select and verify the model for predicting passenger traffic of new urban railways. The article is based on the practical tasks implemented during the project phase for new urban railways in Moscow, Russia. We are considering data sources for building the forecast, as well as practical models that can be used to obtain numerical estimates. Among the discussed data sources, we target migration data that can be collected with the help of telecommunications operators, and information on the use of public transport, obtained from the validation of transport cards. Also, in this paper, we investigate the metrics for traffic along the new city rail line, which can be determined on the basis of the projected passenger traffic. The result of the work was the constructed model of the transport behavior of passengers, taking into account the availability of new urban railways and a set of metrics for assessing the functioning of this transport tool.

Use cases for time series database

Axibase Time Series Database: Usage Examples and Research Articles

See more about time series databases

On machine learning speculations

In this paper, we focus on the following four patterns that appear to us to be trending in ML scholarship:

Failure to distinguish between explanation and speculation.
Failure to identify the sources of empirical gains, e.g. emphasizing unnecessary modifications to neural architectures when gains actually stem from hyper-parameter tuning.
Mathiness: the use of mathematics that obfuscates or impresses rather than clarifies, e.g. by confusing technical and non-technical concepts.
Misuse of language, e.g. by choosing terms of art with colloquial connotations or by overloading established technical terms.

from here

More Data Science Books

10 More Free Must-Read Books for Machine Learning and Data Science

5G and Digital Economy

Our presentations from 22st Conference of Open Innovations Association FRUCT:

On 5G projects for urban railways and Russian Digital Economy program

On Digital Economy Issues Looking From the Information Systems Viewpoint

Papers from conrefence: here и here

AI book

Artificial Intelligence: A Modern Approach

Data Science Books

Yet another good collection of free data science books

Procurement assessment

The Art of Service's Procurement Standard Requirements Excel Dashboard and accompanying eBook is for managers, advisors, consultants, specialists, professionals and anyone interested in Procurement assessment. You can see it here

AIST-SUP 2017

Supplementary Proceedings of the Sixth International Conference on Analysis of Images, Social Networks and Texts (AIST-SUP 2017), Moscow, Russia, July 27 - 29, 2017

SAS on ML

Which machine learning algorithm should I use?

P.S. see more posts about machine learning

IoT education

Our new paper:

Namiot D., Sneps-Sneppe M., Daradkeh Y. On internet of things education // Open Innovations Association (FRUCT), 2017 20th Conference of. — Piscataway, NJ, United States: Piscataway, NJ, United States, 2017.

In this paper, we discuss educational courses for Internet of Things and related areas such as Machine to Machine communications and Smart Cities. The Internet of Things models introduce many new business prospects and, of course, they should be presented in the university curriculum. The purpose of the discussed educational program is to examine issues related to information and communication technologies used in Internet of Things projects and related areas based on them, such as Smart Cities. The educational course proposed in this paper aims to introduce students to modern information technology, standing for such areas as Machine to Machine communications, Internet of Things, and Smart Cities

ICTIR 2017

We continue to share links for monitoring the interesting events in Twitter. Now it is The 3rd ACM International Conference on the Theory of Information Retrieval, Amsterdam 2017

Twitter Live Feed: ICTIR 2017

/via Bluetooth Data Points

Mobility on demand

An interesting paper: Data-Driven Model Predictive Control of Autonomous Mobility-on-Demand Systems

On Search Services for Internet of Things

The Internet of Things (IoT) data services are designed to be available to other services and users by demand. In other words, in practice, the services should be available at any time and at any location. But the big question here is how the other parties become aware of existing services. Sure, for some use cases we could have a static map of available services. But of course, it does not cover all the possible IoT deployment scenarios. So, the search (discovery) should be one of the keys for Internet of Things. And we can see here the whole analogue with the Internet itself. But for Internet of things, we will face a lot of challenges for search services. For example, we will see a lot of resources (billions of devices), heterogeneity, dynamic nature of services, streaming data, etc. In this paper, we discuss existing approaches for implementing IoT search, as well as approaches for setting standards in this area. See our new paper here.