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The paper describes an up-to-date approach to searching for an optimal blade shape for the airplane propeller while considering geometric and technological restrictions. This approach uses the advanced parametric optimization methods. The paper shows an application of the approach developed to obtain an optimal aerodynamic blade shape for different engine operation modes.

This paper is devoted to the practical application of parallel sorting algorithms and parallel input-output methods for the problem of genome alignment. The paper considers different approaches to the implementation of such algorithms, taking into account the capabilities of high-performance systems. Main purpose of the work is to develop a genome sorting program, the efficiency of which significantly exceeds the efficiency of free software analogues. The genome sorting program is implemented for a supercomputer using the C++ language and the OpenMP and OpenMPI. The developed program demonstrates a significant increase in the speed of operation (up to 10 times) compared to free software analogues due to massive parallel data input and output. Different approaches for data input/output parallelization and data processing considered in the paper can be applied in other subject areas.

The paper relates to the subject field of image recommender systems. The proposed approach of automatic image recommendation addresses the following shortcomings of existing solutions: manual input of metadata by users, the lack of user rating history consideration, significant computational resources. The main idea of the proposed approach is to recognize object classes from images using a convolutional neural network to make recommendations. In the proposed solution users and images are located in the semantic space represented by a graph. Software implementation of the proposed approach and obtained results are considered.

The paper is devoted to optimization of technological processes of a single and small-scale production at the stage of technological preparation of production. Simulation model of a technological process and solution of a multi-criteria optimization problem are proposed to obtain optimal working process of a production site in terms of time and cost based on initial data, conditions and restrictions. Software implementation of the developed approach was tested in simulation of technological preparation of production of a "Pusher" part.

In this paper, the numerical simulation approach for designing the landing gear strut for a light aircraft is presented. The problems of extension and compression of the landing gear, as well as its strength during landing, are considered. The application of the topological optimization method for determining the optimal landing gear strut shape is shown.

The problem of microgeometry profiling of the lubricating layer of an irreversible plain bearing is considered with the assumption of the maximum lift force on the basis of a Rayleigh pocket in order to construct profiles easy to manufacture. To this end the lift force dependence on several selected parameters, which most accurately approximate the considered profile to the profile of the global extremum, is investigated. The formulated problem of parametric optimization is solved using the software packages IOSO and modeFrontier, whereas the pressure field in the bearing is determined by the Navier–Stokes equations using the ANSYS/CFX. The results may be used to construct optimal processable profiles of plain bearings applied in various power engineering and other machines and devices.

Software developers sometimes have to repeat an edit in multiple parts of their codebase in order to maintain or extend their software. To let the user perform a repetitive edit, text editors provide multi-cursor editing, which applies editing commands in multiple locations simultaneously. However, multi-cursor text editing is limited, since each executed command must make the desired change regardless of which cursor executes it. To perform a wider range of repeated edits, some developers write refactoring scripts that work structurally. However, unlike multi-cursor editing, the process of developing a refactoring script is not interactive. We propose Forest, the first editor which specially integrates structural editing commands with multi-cursor editing. Compared to a text editor, Forest offers different editing commands, and therefore supports different multi-cursor edits. Forest allows performing edits similar to those from refactoring scripts, while still being interactive. We attempted to perform edits from 48 real-world refactoring scripts using Forest and found that 11 were possible, while another 17 would be possible with added features. Additionally, we investigated a real-world codebase, finding that ∼15% of commits contained edits with potential for multi-cursor editing.

As usually, there are very many situations when a man is clashing with the necessity to treat/process any statistical data (may be, about reliability of technical system, results of investigations or experiments about weather, temperature, pressure, productivity of labour and so on). In addition to that all academics try to determine the right law of distribution with their help to definite mathematical equations/formulas or with the special ways to find the possibility to solve the problem. Such task isn’t mighty easy in many cases. It is needed to know perfectly well the theory of probability, laws of distribution (they are more 30) and criteria (more than 10) to confirm correctly the common conclusion of calculations [1-8,9,10,11,12]. In this article two ways how really we can get the right finish result without any mistake the researcher can receive and more accurate appreciation of the statistical information is given as well.

Introduction: Huge amount of the mechanical systems (mechanisms, devices, test benches, machines, vehicles and so on) have very many mobile pairs of friction in their design. During the operation these parts begin to deteriorate with the different rate. The main factor to appear the limit term of normal operation is the permissible wear for each pair of friction. It is not good if each part will stop its normal operation in a different time/period of operation. Consequently, there is very important problem connected with the cycle of manufacture to get the situation when practically all pairs of friction will their technical resource the same/identical. Obviously, the analogous situation takes place to the parts if we make the analysis about their resistance to shock, to bending strength and so forth. If the rate of the appearance of the destructions is quite different for many parts, therefore there is no possibility to put/appoint the united term of the limit operation for the mechanical system to have the highest reliability. In this article there are one method and recommendations with examples how to overcome this negative situation in practice.

The paper presents an analysis of existing algorithms for single-pitch estimation and proposes a new neural network based algorithm for musical chords recognition. To analyze the algorithms their software implementation was performed and used for the recognition of notes in melodies containing noise echoes and overtones, as well as specific playing techniques characteristic of certain musical instruments. Based on the obtained results a comparative analysis of the existing algorithms is performed specifying their limitations and disadvantages which impede their efficient application for chord recognition. The implemented algorithm based on a fully connected three-layer neural network for chord recognition is described. Assessment of its accuracy and efficiency is shown.

The results of the approach to predicting RTS index futures based on linear and polynomial regression are presented. Two modifications of the proposed algorithm are described. Based on the analysis of the obtained results some recommendations and conclusions are made on using of the developed approach. Also presented in the paper is an overview of the most popular stock market prediction methods based on machine learning as well as the results of their usage.

Teaching is the constant process in our life. It makes our parents, teachers/pedagogues at school or in the universities, mentors, experts, coaches, well-known academic, preachers and so on. The additional such factor maybe (and do indeed) Internat. Moreover, the common link among people is essentially exchanged as well. Many persons prefer have short conversation using SMS-communications, and it isn’t face-to-face unfortunately. In any transport (metro, bus, trolleybus) a man seeks interesting or useful information but has not noticed persons’ associates. It’s not good. We can see the next negative situation at home in a family. For example: let’s suppose that one student arrived home. Members of his family ask him about his routine business. And they usually here that everything is OK. Even during his eating, he tries to read the information which he sees in his mobile telephone or in the planetable. Besides, he sends different short communications and gives answers. There are not any friendly dialogs with his family (father, mother, grandfather, grandmother, brother or sister). That’s why in this article you can understand the new way how to exchange such negative situation in full.

In this paper we describe many important aspects connected with the problems which the railway transport creates for us, namely: harmful gases (especially from diesel locomotives), noise, dust, vibration, products from the wear and tear, leakage of oil and bad evaporations, the definite probability connected with the casual damages, there is negative influence for the ecology and so forth. How can we diminish such negative aspects which influence badly not only for people but for the nature as well? Some examples will be depicted in here which show the perspective ways to realize them in practice during both the operation and in the period of the maintenance. In particular, the new gasket will be demonstrated which hinders effectively against any leakages (gases, oils, aggressive liquids) and the original way to catch different harmful evaporations. Some of this information is defended as the official registered patents including the protection electrical wires against the break under the strong wind. In a capacity of the conformation there are two physical models which are represented also below.

This paper proposes a new approach to the 3D structures automating the assembly process. The approach that is designed allows you to verify assembly procedures by using formal predicate models. This uses Prolog’s logical output language, which can be self-deposed during execution. The proposed approach consists of four stages: processing the source data and building an ontological model, building a connection diagram and building a formal predicate model, converting the model into the Prolog program, and translating the program into a function block. The technologist, developing the assembly process technological map, forms the raw data. This data is converted into a connection scheme. The connection scheme is described in the Prolog as a fact set. Prolog also develops rules that allow you to verify and upgrade the 3D structures assembly. The facts resulting set is converted into function blocks that are embedded in the assembly management system. The proposed approach is tested using the LEGO assembly process example. #CSOC1120

© 2020 Elsevier Ltd Serious games and gamification are useful tools for learning and sustaining long-term engagement in the activities that are not meant to be entertaining. However, the application of game design in the participatory modeling context remains fragmented and mostly limited to user-friendly interfaces, storytelling, and visualization for better representation of the simulation models. This paper suggests possible extensions of game design use for each stage of the participatory modeling process, aiming at better learning, communication among stakeholders, and overall engagement. The proposed extensions are based on the effects that different types of game-like applications bring to the aspects of social learning and the contribution of gamification to engagement, motivation, and enjoyment of some activities. We conclude that serious games and gamification have a high potential for improving the quality of the participatory modeling process, while also highlighting additional research that is needed for designing particular practical gamified applications in this context.

System-of-systems approaches for integrated assessments have become prevalent in recent years. Such approaches integrate a variety of models from different disciplines and modeling paradigms to represent a socio-environmental (or social-ecological) system aiming to holistically inform policy and decision-making processes. Central to the system-of-systems approaches is the representation of systems in a multi-tier framework with nested scales. Current modeling paradigms, however, have disciplinary-specific lineage, leading to inconsistencies in the conceptualization and integration of socio-environmental systems. In this paper, a multidisciplinary team of researchers, from engineering, natural and social sciences, have come together to detail socio-technical practices and challenges that arise in the consideration of scale throughout the socio-environmental modeling process. We identify key paths forward, focused on explicit consideration of scale and uncertainty, strengthening interdisciplinary communication, and improvement of the documentation process. We call for a grand vision (and commensurate funding) for holistic system-of-systems research that engages researchers, stakeholders, and policy makers in a multi-tiered process for the co-creation of knowledge and solutions to major socio-environmental problems., Highlights • Scale incompatibilities among system representations are a key challenge in socio-environmental systems modeling. • Issues of scale arise from the complexity, size and heterogeneity of the constituent systems and their interactions. • A more holistic systems-of-systems modeling framework is needed within which to integrate current approaches and tools. • Socio-technical considerations for system-of-systems modeling is presented from a range of disciplinary perspectives.

Integrated geographic modelling and simulation is a computational means to improve understanding of the environment. With the development of Service Oriented Architecture (SOA) and web technologies, it is possible to conduct open, extensible integrated geographic modelling across a network in which resources can be accessed and integrated, and further distributed geographic simulations can be performed. This open web-distributed modelling and simulation approach is likely to enhance the use of existing resources and can attract diverse participants. With this approach, participants from different physical locations or domains of expertise can perform comprehensive modelling and simulation tasks collaboratively. This paper reviews past integrated modelling and simulation systems, highlighting the associated development challenges when moving to an open web-distributed system. A conceptual framework is proposed to introduce a roadmap from a system design perspective, with potential use cases provided. The four components of this conceptual framework - a set of standards, a resource sharing environment, a collaborative integrated modelling environment, and a distributed simulation environment - are also discussed in detail with the goal of advancing this emerging field.

Synthetic Aperture Radar (SAR) and medium (MR) and very high (VHR) resolution optical satellite images are valuable sources of information for maritime situational awareness. This paper presents the Earth Observation Maritime Surveillance System (EO-MARISS), an integrated processing framework of remote sensing satellite data developed at DLR’s Maritime Safety and Security Lab Neustrelitz to support sea monitoring tasks. The system is currently developed for operational use at DLR’s Ground Station Neustrelitz to support service provider like AIRBUS or EUSI and processes image data from different satellite missions received directly at the ground station or provided by a network of ground stations and service providers.

© 2013 IEEE. The Centre on Persuasive Systems for Wise Adaptive Living (PERSWADE) aims at developing and applying persuasive technologies and system science for social innovation that can help humanity to move toward sustainable, wise, adaptive living. The PERSWADE collaborative knowledge base needs to be designed with the intent to bring together, enrich and logically relate heterogeneous content, such as datasets, scientific literature and any kind of multimedia and social content, to support a participatory approach and help to translate science into action. PERSWADE-CORE, the foundation ontology described in this paper, plays a critical role in this by providing the backbone semantic infrastructure to enable collaboration through efficient data and knowledge integration, sharing and reuse. It also serves the purpose of clarifying and explaining the goals, functions and operations of the Centre. Because of its purpose, PERSWADE-CORE has been designed to be easy-to-use and easy-to-adapt by allowing generic, as well as more specific, relationships among concepts. The PERSWADE approach prioritizes interoperability and relies on the Semantic Web infrastructure. Furthermore, its design is intrinsically aimed at collaborative environments in which ontologies are expected to evolve as a response to users' activity.

Described in the paper is an approach to symbolic test scenarios concretization in the scope of automated software verification and testing technology. Tools for automated concretization process based on user defied settings are presented.

International audience; In this article, an approach of detailing verified test scenarios for developed software system without losing the model's semantics is proposed. Existing problem of generating test cases for real software systems is solved by using multi-level paradigm to obtain the real system signals, transactions and states. Because of this, the process is divided into several steps. Initial abstract traces (test cases) with symbolic values are generated from the verified behavioral model of software product. On the next step, called concretization, these values in test scenarios are replaced with concrete ones. Resulting concrete traces are then used as input for the next step, data structures conversion. This step is needed because concrete traces do not contain all the information for communicating with developed software and presented in another way with different data structures. After concrete test scenarios are detailed, they can be used for generation of executable test cases for informational and control systems. In this paper, a software tool is suggested for detailing test scenarios. It consists of several modules: a Lowering editor that allows user to create rules of detailing a signal, a Signals editor used to define complex data structures inside the signal and a Templates editor that eases work with similar signals. Process of translating abstract data structures into detailed data structures used in system implementation is presented with examples.

© 2017 Informa UK Limited, trading as Taylor & Francis Group. Modeling and simulation are recognized as effective tools for management and decision support across various disciplines; however, poor communication of results to the end users is a major obstacle for properly using and understanding model output. Visualizations can play an essential role in making modeling results accessible for management and decision-making. Virtual reality (VR) and virtual geographic environments (VGEs) are popular and potentially very rewarding ways to visualize socio-environmental models. However, there is a fundamental conflict between abstraction and realism: models are goal-driven, and created to simplify reality and to focus on certain crucial aspects of the system; VR, in the meanwhile, by definition, attempts to replicate reality as closely as possible. This elevated realism may add to the complexity curse in modeling, and the message might be diluted by too many (background) details. This is also connected to information overload and cognitive load. Moreover, modeling is always associated with the treatment of uncertainty–something difficult to present in VR. In this paper, we examine the use of VR and, specifically, VGEs in socio-environmental modeling, and discuss how VGEs and simulation modeling can be married in a mutually beneficial way that makes VGEs more effective for users, while enhancing simulation models.

This paper considers a method for verification and subsequent modification of the Smart Grid during design stage. For automated use, it is required to create a network template, the elements of which would be present in any particular case of implementation. This role in our method is performed by the Smart Grid ontology. Verification for the network created by designer is carried out through comparison with abstract ontology model. When differences are found (e.g., lack of desired control system), the solution search occurs among the rules in Prolog language for this situation, and the Smart Grid model created by designer is translated into Prolog description. If rules are found, then they are applied, modifying the model created by designer. If not – return the model to designer for improvement. The last stage is the processed ontology model translation back to initial description. This method is considered on the example of abstract network model.

The paper describes architecture of a distributed OAIS-based digital preservation system which uses HDFS as a file storage system and supports wide distribution on a number of cluster's nodes. It is based on Apache Hadoop framework — a reliable open source solution with well horizontally scalable distributed architecture. Novelty of the proposed system is defined by the fact that none of existing OAIS digital preservation systems use HDFS storage for both structured and unstructured data archiving. Implementation of the system's prototype and results of its testing are also shown.

Optimized technological routes at production sites provide more balanced and effective organization of the whole manufacturing process. The approach described in this paper is based on digital modeling and allows to automatically obtain correct and verified technological routes. It includes formalization based on modular technology, optimization, simulation of a product implementation and analysis of simulation results.

The theory of complex-valued econometrics makes it possible to generate qualitatively new features that can be used in machine learning algorithms. Our study reveals the task of determining the long-term dependence of future companies’ stock prices from a time-generated feature, i.e., a calculated tonality coefficient gained by methods of semantic analysis of texts from social networks. Data was gathered from the Twitter platform with the use of Big Data ETL-scenarios. The resulting data sets were used to train machine learning algorithms designed to work with Big Data technologies. A semantic coefficient was calculated on the basis of aggregated estimates for each day, with the further application of the methods of complex-valued econometrics. To demonstrate the new approach of feature generation, a complex-valued linear regression model based on the semantic coefficients and stock markets data was constructed. The outcome obtained by the new approach was compared with existing solutions in terms of accuracy. Finally, we demonstrate a possible route for impacting improvements of the existing algorithms for trading strategies using the complex-valued regression.

One of the core components of remote sensing based maritime surveillance applications is vessel detection. It helps to prevent and investigate different unlawful actions as well as environmental hazards present at sea. Growing constellation of very high resolution (VHR) optical satellite sensors are able to frequently cover large areas with spatial resolution of up to 0.3m per pixel, which is sufficient to detect and distinguish different types of vessels. This paper presents a novel method for automatic multiclass vessel detection with use of deep convolutional neural networks (DCNN) and principle component analysis (PCA). The described approach provides reasonable performance and therefore is potentially suitable for near real time (NRT) applications.

The paper is devoted to research in the field of software maintenance automation. An approach to solving customer requests based on the use of the Doc2Vec algorithm is proposed. It consists of finding semantically related resolved requests, as well as identifying qualified software engineers in the Jira bug tracking system. The developed software tool implements the proposed approach and provides reports which help software engineers in solving unresolved customer requests. The experiment compares the automated approach to resolving customer requests with the manual one. The results show advantages of using the software tool in the maintenance process.

The use of simulation models is essential when exploring transitions to low-carbon futures and climate change mitigation and adaptation policies. There are many models developed to understand socio-environmental processes and interactions, and analyze alternative scenarios, but hardly one single model can serve all the needs. There is much expectation in climate-energy research that constructing new purposeful models out of existing models used as building blocks can meet particular needs of research and policy analysis. Integration of existing models, however, implies sophisticated coordination of inputs and outputs across different scales, definitions, data and software. This paper presents an online integration platform which links various independent models to enhance their scope and functionality. We illustrate the functionality of this web platform using several simulation models developed as standalone tools for analyzing energy, climate and economy dynamics. The models differ in levels of complexity, assumptions, modeling paradigms and programming languages, and operate at different temporal and spatial scales, from individual to global. To illustrate the integration process and the internal details of our integration framework we link an Integrated Assessment Model (GCAM), a Computable General Equilibrium model (EXIOMOD), and an Agent Based Model (BENCH). This toolkit is generic for similar integrated modeling studies. It still requires extensive pre-integration assessment to identify the appropriate models and links between them. After that, using the web service approach we can streamline module coupling, enabling interoperability between different systems and providing open access to information for a wider community of users. © 2019 by the authors. This research was funded by COMPLEX—Knowledge Based Climate Mitigation Systems for a Low Carbon Economy Project, EU-FP7-308601. I.A. was supported by the Spanish Government through María de Maeztu excellence accreditation MDM-2017-0714 and the grant RTI2018-099858-A-100, and the Czech Science Foundation under the project VEENEX GA Cˇ R 16-17978S.

Efficient application of model-based software design methodologies in industrial automation requires methods and tools for automatic code generation. Formal models can be especially useful to avoid ambiguity, to verify and evaluate performance, which ultimately will improve the quality and reliability of the project and lead to lower design costs. This paper proposes methods for implementing state-transition formal models, such as finite state and pushdown automata, as well as extended Petri nets (A-nets) by means of IEC 61499 function blocks. These implementation approaches can be used in the design of industrial cyber-physical systems for monitoring, diagnostics, conformance checking, detection and selection of specified sequences of events and parameterized objects from an input stream. One of the proposed applications is illustrated using an example of an assembly process with LEGO blocks.

The article describes architecture of a big data processing system based on Apache Hadoop, Apache Flume and Apache Spark toolset. Application of the developed system is shown for storage and analysis of dataset containing generated events within GitHub repository - the world’s largest web-service for version control using Git. System performance results are evaluated using chosen metrics.

© 2018 IEEE. The management of coupled human-natural (CHN) systems, including natural resource and environmental systems, would benefit from recognition of the need to integrate, and bring critical thinking, transparency, and accountability to science and policy development. It would benefit also from: (1) stakeholder engagement and participatory processes, (2) societal and institutional continuity in science and decisions evaluation and follow-through, and (3) recognition and understanding of the role of biases, beliefs, heuristics, and values (BBHV) in decision-making.We suggest that creating multi-media, efficiently accessible, »Records of Engagement» (RoE) could support meeting the above needs. RoE would offer: (1) a reward system to support and foster stakeholder engagement; (2) a record structure for evaluating processes and outcomes and for learning and knowledge transfer, and (3) an opportunity to systematize, facilitate, create efficiencies, and improve the engagement of experts and stakeholders in participatory modeling, planning and policy development. RoE, in our view, should also not only describe scientific evidence and lines of argumentation but also BBHV and emotions expressed, a first step in understanding their impacts on decision making and management of CHN systems.We seek to engage readers to help us determine how to create RoE, including what they might contain to be most useful. Preliminary thoughts are offered on RoE framework design and content, and on a Decision Tracking System and methodologies that could be used to support creation and use of RoE. Some existing stakeholder engagement records are discussed in reference to the ideal RoE that we envision.

In participatory modeling (PM), a conceptual model emerges from an exchange of information and opinions among stakeholders. This usually happens in a series of in-person workshops restricted to a certain number of attendees during designated time intervals. Our goal is to open up the PM workshop process to engage an unlimited number of participants at various locations, while supporting them with the functionality that the modeling context can offer. We develop a real-time, moderated steering environment, named Discussoo, to facilitate online PM. Users express their opinions about a topic by providing their comments in online discussions. As the discussion evolves, an ensemble of artificial intelligence algorithms in the background automatically produces a dynamic conceptual model to visualize the on-going exchange of opinions. Moderators can use this model to provide feedback to users and guide the discussion. Policymakers and managers can use Discussoo to support more transparent and meaningful engagement of stakeholders.

© 2019 Society for Modeling & Simulation International (SCS). Artificial societies used to guide and evaluate policies should be built by following “best practices”. However, this goal may be challenged by the complexity of artificial societies and the interdependence of their sub-systems (e.g., built environment, social norms). We created a list of seven practices based on simulation methods, specific aspects of quantitative individual models, and data-driven modeling. By evaluating published models for public health with respect to these ideal practices, we noted significant gaps between current and ideal practices on key items such as replicability and uncertainty. We outlined opportunities to address such gaps, such as integrative models and advances in the computational machinery used to build simulations.

In the modular approach we do not intend to design a unique general model. Instead, the goal is to offer a framework that can be easily extended and is flexible to be modified. A module that performs best in one case may not be sufficient in another. The goals and scale of a particular study may require a completely different set of modules that will be invoked and further translated into a working model. There is a certain disparity between the software developer and the researcher views upon models and modules. For a software developer, a module is an entity, a black box, which should be as independent as possible, and should be as easy as possible to combine with other modules. This is especially true for the federation approach to modular modeling and is well demonstrated by the web-based modeling systems. The utility of such applications may be marginal from the research viewpoint.

The aim of this paper is to provide an approach to planning and optimization of small-scale net-centric manufacturing. Automation of small-scale net-centric manufacturing in machinery requires solution of many tasks such as automated formalization of technological processes (implying conversion of existing and new production documentation into technological paths of automated manufacturing), distribution of workshop equipment, materials and tools between technological paths, monitoring of concurrent processes of supply and execution, analysis, network planning and manufacturing optimization considering miscellaneous criteria distributed among three levels of industrial network.

Vessel detection and type recognition is crucial in any maritime surveillance application. This component aims at preventing or investigating unlawful actions present at sea. Modern very high resolution (VHR) optical satellite sensors are able to capture images with spatial resolution up to 0.3m per pixel, which is sufficient to distinguish ship features such as bridge position, cranes, landing pads and many others and thus possible to differentiate ship types. This paper presents a new method for automatic vessel detection and type recognition based on fusion of deep convolutional neural network architectures (CNN), which has potential for near-real time (NRT) applications.

© 2018 Elsevier Ltd Various tools and methods are used in participatory modelling, at different stages of the process and for different purposes. The diversity of tools and methods can create challenges for stakeholders and modelers when selecting the ones most appropriate for their projects. We offer a systematic overview, assessment, and categorization of methods to assist modelers and stakeholders with their choices and decisions. Most available literature provides little justification or information on the reasons for the use of particular methods or tools in a given study. In most of the cases, it seems that the prior experience and skills of the modelers had a dominant effect on the selection of the methods used. While we have not found any real evidence of this approach being wrong, we do think that putting more thought into the method selection process and choosing the most appropriate method for the project can produce better results. Based on expert opinion and a survey of modelers engaged in participatory processes, we offer practical guidelines to improve decisions about method selection at different stages of the participatory modeling process.

The methods and Web application with automatic code generation for the mathematical and 3D-modeling of industrial robots are provided. The code ensures the execution of the program movements of the working tool (the gripper) or the controlled angular and linear coordinates. 3D modeling is made with the extensible 3D vector graphics markup language (X3D). The SYSTEL software is used for mathematical modeling. The article describes two examples of modeling with the control code generation for FAULHABER drives with a rotary and linear electric motor. The first example is an electromechanical manipulator with a polar coordinate system; the pen is used as the manipulator working element for drawing the second-order graphs of target curves in the horizontal plane. The second example considers a mechatronic device with two translational and three rotational kinematic pairs, forming one cycle. Both devices are made at the Electric Engineering Faculty of the South Ural State University Branch in Miass. They use rotary and linear FAULHABER drives. They are used for verifying the results of modeling, forming program movements and the control code generation.

This article covers the architecture, functional specifications and structure of the control system and operating modes of a 6-degree-of-freedom radiation-proof manipulators designed for the replacement of an outdated human-driven copying-type manipulator. The proposed robotic systems provide manual, semi-automatic and automatic modes, including the definition of workspace, collision avoidance, and automatic grasping of tare and materials.

Nowadays, maritime security faces many kinds of problems – environmental hazards, unlawful actions such like piracy, cargo theft, illegal border crossing etc. These challenges bring the situational awareness of this domain to a high level of importance. Optical satellite images, captured during cloudless weather conditions, are valuable source of information about situation at sea. On the one hand, modern very high resolution (VHR) optical sensors (e.g. WorldView family) taking images with spatial resolution higher than 0.5 m per pixel, enabling to perform object (ship) detection tasks. On the other hand, high resolution (HR) sensors like Landsat-8 and Sentinel-2A(B) are able to cover relatively large areas and are suitable for environment monitoring tasks. Developed at the German Remote Sensing Data Center (DFD), part of the German Aerospace Center (DLR), Maritime Security Lab Processing Framework is intended to support the operational maritime surveillance near real time (NRT) services based HR and VHR optical satellite data. The Framework supports automated request driven processing from different satellite missions provided by a network of different ground stations and service providers. Actionable information products are created in an automatic processing chain including image pre-processing, data transcription and GUI based interactive value adding and validation. The paper will focus on the overall architecture of the framework including workflow of data handling, the interfaces and components, needed to enable fast data access for operator analysis and supervision.

In the context of the project real-time services for maritime security (Echtzeitdienste fur die Maritime Sicherheit—security), an experimental research platform for validation of maritime products derived from remote sensing data, was developed. This article describes the work carried out to derive ship-, wind-, and wave detection products out of Sentinel-1 remote-sensing data by DLR’s Maritime Safety and Security Lab in Neustrelitz, part of the German Remote Data Center DFD. The activity aims to the fulfilment of project requirements, primarily to support the need for near real-time performance up to 15 min, as those in maritime situational awareness. The development and implementation cover the task of level 0 processing, based on DLR’s front end processor, the implementation of the framework for real-time processing up to level 2 (value adding), as well as the development of a hardware-independent virtual-processing platform.

Network operators are architecting fifth generation (SG) mobile communication networks with the promises of delivering faster, safer, and smarter wireless services. 5G network architectures embrace current trends in virtualization and software-defined infrastructure (SDI). The 5G Public Private Partnership (5GPPP) proposed a multi-domain architecture for end-to-end service orchestration in multi-operator environments, however, cellular network operators are a natural competitors. Although the scientific community has demonstrated that multi-operator federated systems are possible in practice, the adoption of this type of architecture for cellular network operators will be slower. In this paper we propose Cell-Orch, an architecture for end-to-end service orchestration in multi-operator environments that leverages SDI and allows stakeholders to verify whether their configurations have been effectively provisioned. We discuss how SDI will promote agile programmability of cellular networks, general transparency, and transparency of inter-domain transactions all while enabling end-to-end configuration verification. Furthermore, Cell-Orch provides additional functionalities to allow cellular network operators to build more resilient infrastructures in the same way the Cloud provided analogous capabilities to enterprise IT.

Accumulation technologies of electric energy in electric power supply are an effective tool for increasing energy efficiency and energy saving. This paper is devoted to the development of electromechanic energy storage. Theoretical and experimental results of the development of electrokinetic energy storage are presented; they are intended for the wide application in local electrical networks. The design of the electrokinetic energy store based on the magnetic levitation of the rotor-flywheel with the use of superconducting elements is described; the mathematical modeling of the stiffness of the contactless suspension of the rotor-flywheel is performed. The technical characteristics of electromechanic energy storage and its scope of application are given.

The article describes a compressor problem. The authors used a mathematical way to analyze a compressor and find its weakness. A practical way to increase the reliability for the investigated design has been recommended.

Predictions for Service Oriented Architectures (SOA) to deliver transformational results to the role and capabilities of IT for businesses have fallen short. Unforeseen challenges have often emerged in SOA adoption. They fall into two categories: technical issues stemming from service components reuse difficulties and organizational issues stemming from inadequate support or understanding of what is required from the executive management in an organization to facilitate the technical rollout. This paper first explores and analyses the hindrances to the full exploitation of SOA. It then proposes an alternative service delivery approach that is based on even a higher degree of loose coupling than SOA. The approach promotes knowledge services and agent-based support for integration and identification of services. To support the arguments, this chapter sketches as a proof of concept the operationalization of such a service delivery system in disaster management.

An approach is proposed for the implementation of distributed semaphores in the IEC 61499 architecture on the basis of protocols for solving consensus in a network of unreliable processes that allows developing function blockbased control applications with complex types of interactions using the resources sharing. The models of distributed semaphores (in the form of coloured Petri nets) based on Paxos and Raft protocols for solving consensus are developed, simulation experiments are performed in the CPN Tools, comparative analysis and recommendations are given.