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In this paper, we study a class of nonlocal functional evolution inclusions in the form of multivalued perturbations of m–dissipative operators. We prove some new existence results in case of dissipative type conditions on the right-hand side. Illustrative example is provided. [ABSTRACT FROM AUTHOR]

The stability in terms of two different measures for differential equations with supremum and non-instantaneous impulses is studied using Lyapunov like functions and Razumikhin technique. In these differential equation we have impulses, which start abruptly at some points and their action continue on given finite intervals. An example is given to illustrate the results. [ABSTRACT FROM AUTHOR]

Practical stability for nonlinear differential equations with non-instantaneous impulses and supremum is studied. The impulses start abruptly at some points and their actions continue on given finite intervals. Some sufficient conditions for practical stability and strong practical stability are obtained. An example is given to illustrate some of the results. [ABSTRACT FROM AUTHOR]

In this paper we have analyzed the IoT security issues in the context of security intelligence and IoT analytics. Furthermore, the potential and benefits of applying Big data technologies have been revealed for building up intelligent security solutions for the IoT ecosystem. We have suggested design approach for building up parallel differentiated diagnostic analytic workflows for the case study of intrusion detection. The conceptual software architecture of intelligent intrusion detection system has been proposed comprising machine learning and operational sections. The functionality of the intelligent system involves detection of unknown attacks based on models and identification of known attacks based on sets of rules. The functionality of the proposed intelligent system has been verified experimentally for the case study of diagnostics. [ABSTRACT FROM AUTHOR]

Digitalizing the healthcare systems and processes is essential for increasing patient safety and decreasing medical errors. Healthcare complex logic and zero tolerance for errors re-quire special processes for creating medical software. The purpose of this paper is to high-light and elaborate on key differences among all significant and widely used software development methodologies as they all have their beneficial properties and drawbacks in different situations. In this paper the general usability of the methodologies will be discussed, including a description of how culture, continuous integration and delivery are achieved with each one of them. [ABSTRACT FROM AUTHOR]

This paper aims to suggest a conceptual framework of the interaction between Management Control Systems (MCS) and Big Data Analytics (BDA), since MCS can be considered as the formal, information-based routines and procedures managers use to maintain or alter patterns in organizational activities. Developed as a theoretical framework, it could contribute to understanding of how BDA capabilities, which are one of the most important factors for successful strategy implementation, could influence MCS in order to achieve the strategic goals of the company. For the purposes of the conceptual framework development the Simons' Levers of Control framework is used. It is considered as appropriate since it combines a focus on the achievement of the strategic goals of the organization with the broader perception of the control mechanisms that can be used for effective and efficient implementation of the strategy. The proposed framework can be considered as a contribution to the effective strategy implementation due to the fact that it provides the opportunity to define how BDA interacts and affects the fourth Levers of Control. Thus, by integrating BDA capabilities in the above mentioned levers, better control on effective business strategy implementation and performance can be achieved. [ABSTRACT FROM AUTHOR]

The paper presents an overview and analysis of the workflow platforms used for solving problems in bioinformatics, biology, medicine. In the paper seven workflow frameworks are categorized in three groups: stand-alone platforms, web-based workflow systems, cloud-based workflow solutions. Chipster, Apache Taverna, Mobyle, Galaxy, NVIDIA Clara, Trident and Apache Spark are discussed in details and recommendations for their application are added. [ABSTRACT FROM AUTHOR]

The paper below presents an overview of big data integration techniques, methods and approaches. The report describes the data integration architecture and its components. Also, an overview of five big data integrators is included. Integrator.io, Oracle Data Integrator, Apache Spark, SQL Server Integration Service, Zapier are discussed in details. In addition, recommendations for their application are presented. [ABSTRACT FROM AUTHOR]

In this paper we have proposed a conceptual model of differential analytical scientific workflow for imaging diagnostics of abnormal pneumonias. The model is based on the method of deep convolutional neural networks (CNN) and the approach of Gradient-weighted Class Activation Mapping (Grad-CAM), which uses specific for the class information from the gradient, incoming in the last convolutional layer of CNN, in order to create rough map of localization of important region within the medical image. The proposed conceptual model is implement in Python with Google's open source framework Tensorflow and Keras. In the development process, we have used customized Jupiter Notebook – Colab. For the creation and visualization plots we used Matplotlib. Neural Networks are pre-trained with ImageNet dataset, which consist of large amount of non-medical images. The experimental results for the 5 types of convolutional neural networks show accuracy more than 95%. The models for image diagnostics are integrated within the machine learning section of the intelligent platform for big biomedical data analytics InSilicoKDD. [ABSTRACT FROM AUTHOR]

While youth transitions to adulthood have been subject to various social studies, it is often the case that statistical tools of choice are limited in terms of sophistication and flexibility. Our study uses information collected as part of the SAHWA project [1] with the primary goal being to verify if machine learning can help rule out inappropriate assumptions and improve transition to adulthood analysis by outlining youth groups, their common characteristics and outlier cases (as well as if they are significant). As data includes numeric, as well as categorical and nominal variables use of common algorithms like K-Means clustering is not possible. It's also not reasonable to build on Eucledian distances in this mixed space, ruling out other classification methods that rely on it. We split the clustering algorithm selection into: (1) selection of distance calculation function, (2) algorithm and (3) decision on number of groups. A valuable information about transition to adulthood is obtained without imposing restrictive theoretical framework. [ABSTRACT FROM AUTHOR]

Real estate has always been an important investment opportunity. With a diverse set of financial instruments linked to real estate assets, it is significant for both investors and intermediaries. In this paper we assess how artificial intelligence can be used to improve our understanding for the real estate market changes. We suggest and test a three-stage model in support for real estate valuation and market forecasting, that is able to account for global economic factors as well as for individual characteristics influencing property prices. Every stage provides for using different artificial intelligence and machine learning methods in order to automate processing of market data and assess how qualitative factors affect valuation. We conduct a survey on the accuracy of the model NAREIT and BGREIT index data. [ABSTRACT FROM AUTHOR]

The quality of medical images is very important in clinical use, such as clinical diagnosis, pathology analysis, etc. This paper presents a brief survey of the advantages and trends of medical image processing techniques based on multidimensional wavelet transforms as well as their combinations with other methods, which model each coefficient set as a tensor. Unlike the classical wavelet decompositions wavelet tensor modifications has only one parameter to be tuned, which makes the computing easier to use in various medical processing methods such as noise reduction, compression, segmentation, classification, medical image fusion. These methods can be very useful for multidimensional images such as MRI and CT data or for integration and analysis of many types of medical image data. [ABSTRACT FROM AUTHOR]

An approach to creating a payoff matrix for modeling using the game theory to find the optimal strategies of the seller and the buyer is proposed. The index of customer loyalty can be used as input data. The result is a payoff matrix consisting of forecasted average profits. [ABSTRACT FROM AUTHOR]