Techno-Social Systems in the Internet as a Tool for Social Adaptation of the Visually Impaired

The chapter deals with issues related to social adaptation of the visually impaired in techno-social systems of the internet. The current legislation providing access for visually impaired people to such techno-social systems is analyzed, as well as the way the legislation is implemented. Traditions and innovations in the field of accessibility of techno-social systems for visually impaired people in Russia are discussed. The opportunities of the electronic banking system of the European Union and Great Britain for the visually impaired are analyzed.

Enabling Small-Scale Actors to Operate on Markets of Energy and Ancillary Services

Widespread renewable energy alters infrastructures and business by changing a way to balance between the demand and the offer. In customer-centered model, flexible economic behavior of small-scaled energy actors mitigates variability and uncertainty in flows of power and energy. Flexible cooperative behavior of many intraday market participants has a potential to reduce uncertainty in renewable energy flows. However, owners of small-scale renewable energy plants play limited market role. This chapter presents changed socio-economic and technology contexts and attracts attention to new challenges. New ICT enabler activates role of small-scale renewable energy actors by complementing their physical energy by structured information about the capacity and flexibility. In new market scenario, unpredictability of renewable energy is reduced by adding knowledge and exploiting better flexible behavior. Main conclusion is about using the information about flexibility to activate small-scale actors on real-time markets while improving ecological sustainability.

Mathematical Modeling of Information Warfare in Techno-Social Environments

The chapter discusses a number of mathematical models of information battle in techno-social environments. Some models take into account such battle factors as the mass information media's incomplete coverage of the society, the individuals' acquisition of the information only after receiving it twice, the individuals' forgetting the information, a priori bias to support a party to the battle, and polarization of the society. For simpler models, the results are described in brief. For more complicated ones, mathematical research has been conducted with the sociological interpretation of the results.

Local Forum as a Knowledge Source

An internet forum can be used as a crowdsourcing tool for searching for new knowledge and the latest non-standard ideas being a result of forum members' joint creative work. On the basis of these regularities, criteria of the forum maturity in processes of its formation and advance are elaborated. Basing on these results on a 2015 analysis of the forum, formed on the ground of the Universidad Tecnologica de la Mixteca (UTM), the State of Oaxaca, Mexico, a moment when the forum reaches its maturity was revealed. These conceptions are suitable for forming a thesaurus and taxonomy prototype of socio-cultural, environmental, and economic problems in Mixteca region. In its turn, a forum thesaurus gives opportunities for the regional community to understand a degree of its involvement into revealing and discussing the most actual regional problems on the internet.

A Framework for Analyzing the Impact of Data Analytics and the Internet of Things on Digital Marketing

The proliferation of the internet of things will open up new opportunities for implementing the digital transformation of businesses. Available data is expected to rise in unprecedented levels of quantity with the IoT playing an important role towards that end. Data analytics techniques will provide businesses with refined pieces of information in almost all aspects in both B2C and B2B context, thus refining services design and customization with more flexibility and options that focus right at the heart of consumers' needs. Digital marketing depends on these developments. This chapter aims at proposing a framework for analyzing the implications of data analytics and IoT on digital marketing.

Vector Distribution of Limited Resources in Complex Systems

The problem of distribution of the given global resource of the system under the constraints imposed on individual resources is considered. It is shown that the problem lies in constructing an adequate objective function for optimization of the resources distribution under their limitations. For solving the considered problem, the multicriteria optimization approach is undertaken with the nonlinear trade-off scheme. The proposed nonlinear compromise scheme has the property to adapt to the situation of multicriteria decision-making. The adaptation to the situation of a nonlinear scheme is carried out continuously, while the traditional selection of compromise schemes is done discretely that adds to subjective errors the errors, associated with the quantization compromise schemes. Model examples are given.

Multicriteria Synthesis of Neural Network Architecture

Statement of a problem and procedure of vector optimization of the neural-network classifier architecture is considered. As a criterion function, the scalar convolution of criteria under the nonlinear scheme of compromises is offered. Search methods of optimization with discrete arguments are used. The example, neural-network classifier of texts, is given.

Using Online Data in Predicting Stock Price Movements

A lot of research has been focusing on incorporating online data into models of various phenomena. The chapter focuses on one specific problem coming from the domain of capital markets where the information contained in online environments is quite topical. The presented experiments were designed to reveal the association between online texts (from Yahoo! Finance, Facebook, and Twitter) and changes in stock prices of the corresponding companies. As the method for quantifying the association, machine learning-based classification was chosen. The experiments showed that the data preparation procedure had a substantial impact on the results. Thus, different stock price smoothing, the lags between the release of documents and related stock price changes, levels of a minimal stock price change, different weighting schemes for structured document representation, and classifiers were studied. The chapter also shows how to use currently available open source technologies to implement a system for accomplishing the task.

Set Classification

The classification problem where each object is given by a set of multidimensional measurements that is associated with an unknown dependence is considered. Intersection of sets that define objects from different classes is allowed. In this case, it is natural to found classification algorithms based on the difference between dependencies for the objects belonging to different classes. Two algorithms to convert the set classification problem solution from the initial feature space into (1) the parameters space of the common model structure for all the objects and (2) the parameters spaces of the best structures for each class are proposed, along with a classification algorithm based on the accuracy of object representation by the models based on the structures found for each class. If the objects are described with big data, the approach can be used to transform data into a compact form (model parameters) that preserves the characteristics that are necessary to separate the classes. An approach to solve a problem of clustering sets is proposed. Some examples are given.

Studying the Big Data Paradigm in Dynamics of Its Advance

The study of the big data subject matter in its advance already has its own history. Assuming as a basis the content analysis of article abstracts on big data, using e-library stocks of Association for Computing Machinery (ACM) and Institute of Electrical and Electronics Engineers (IEEE), one succeeds to monitor the life cycle phases of the big data paradigm and distinguish the stages of developing programs and algorithms from the technology update, including applications and their advanced renewals. In order to carry out the analysis, it is proposed to approximate the curves of cumulative frequencies of words, obtained from the corpus of texts by means of cubic parabolas, their parameters being in good concordance with ones of logistic curves.