Information and Software Technologies

In this paper an implementation of a web-based monitoring system, which introduces the components and principles of this monitoring system, and provides the model of heat consumption prediction is presented. The general architecture of the information system is described.

The data collection subsystem comprises monitoring devices such as digital sensors and a data collection terminal. This allows providing relevant information about the status of the heating supply system for monitoring in real-time. The HeatCAM system (web-based information system for monitoring and prediction of building heat consumption) was implemented to provide analysis of current state of heating in buildings and short-term prediction of the required amount of heat under certain climatic conditions.

This paper describes the features of Smart MicroGrid and explains the of prior building appropriate information model of this system. It was determined information power system evaluation techniques and existing methods that can be applied in information system with simulation tools classification. This paper compares different tools for modeling, which are based on using renewable energy sources. The system has to combine basic points: evaluation energy sources in region, their calculation, gives recommendation for building energy smart grid in micro grid level and modelling her work. Our goal is definition of existing approaches, which can be used in future system.

The considerable attention implementing information systems test should be paid to the development test of the specified requirements. The paper discusses the possibility and the importance of the functional test case generation using artifacts obtained during the analysis of requirements in test process. Based on requirements description formats and test case generation methods of analysis the use case and activity diagrams are suggested to use for this purpose. This paper presents the methodology and practical evaluation of the description of requirements and their use in generating test cases. This decision is relevant for the information system analytics and testers, test managers and others involved in test process.

The article explores a global principle of communication in Smart Grid networks with a focus on specific communication infrastructure aspects. The paper is divided in two main parts. First part focuses on a description of the main concepts and control of Smart Grid network power distribution. Second part of this paper presents specific requirements regarding Smart Grid distribution flows and network elements. The paper proposes a general scheme of Smart Grid network communication infrastructure, which enables complex perspective of the given issue and its effective use. It presents different power grid management requirements in various types of regions in Czech Republic.

Business Models play a pivotal role in organizations, especially in building bridges and enabling dialogue between business and technological worlds. Complementarily, as Use Cases are one of the most popular techniques for eliciting requirements in the design of Information Systems, Business Goals and Business Rules associate with Business Process Use Cases to compose a Business Model base structure. However, methods for relating Business Processes, Goals and Rules (PGR) are scarce, dissonant or poorly grounded. In this sense, we propose the specification of a method, within a SPEM approach, covering the elicitation of Business Goals and Rules from Process-level Use Cases, and their mapping to a Business Model representation. As a result, a tailorable method for the generation of a solution Business Model, by aligning the resulting trios (PGR) with a Business Model Canvas, is presented and demonstrated in a live project.

Enterprises and their architecture (EA) are changing continuously, what leads to changes in enterprise information systems (IS) and its architecture. Ineffective IS change management has a particularly adverse effect on EA because of wrong architectural decisions. These decisions can lead to several problems such as poor IS performance, wrong interfaces, bad data quality, doubled data input and sub-optimal IS support to business processes. It is assumed than an enterprise IS strategy is an important source of information guiding the EA architecting and implementation of the changes. In this paper, a case study on definition of the IS strategy for a Latvian telecommunication company is presented. The goal of the case study is to identify typical practical challenges arising in EA architecting and to examine the role of the enterprise IS strategy. The results of this study will be used in further research on development of the approach for the strategic IS change control.

There is an increasing need and interest for organizations to collaborate with internal and external partners on a global scale for creating software-based products and services. Potential risks and different strategies need to be addressed when setting up such collaborations. Aspects such as cultural and social features, coordination, infrastructure, organizational change processes, or communication issues need to be considered. Although there are already experiences available with respect to setting up global collaborations, they mainly focus on specific areas. It is difficult for companies to quickly assess if they have considered all relevant aspects. An overall aid that guides companies in systematically setting up global collaborations is widely missing. In this paper we present a study based on the snowballing method as a systematic approach to literature review. Based on this literature review and inputs from industry we investigated what aspects and practices need to be considered when establishing global software development collaborations and how to prioritize them. Based on that we created activity roadmaps that aggregate existing experiences. Reported experiences were structured into nine main aspects each containing extracted successful practices for setting up global software development collaborations. As a result we came up with an initial version of a canvas that is proposed as guidance for companies for setting up global collaborations in the software development domain.

Symbolic model checking is a technique for verifying finite-state concurrent systems that has been extended to handle real-time systems. Timed automata are widely used to model such systems behavior. In this paper we are concerned by durational actions timed automata (daTA) which is a timed automata handling action durations and true concurrency. Our aim is to compute efficiently the state space of (daTA) in order to verify quantitative timing requirements and preserve the true concurrency property.

We present a novel approach to compute quantitative information about the system and exploring the state space of daTA based on maximality semantics.

We have designed a new zone graph under the maximality semantics, named Maximality-based Zone Graph (MZG), for describing symbolic execution of daTA. In the implemented tool TaMaZG, daTA description is compiled into a MZG and represented symbolically using the Difference Bounded Matrices data structure (DBM).

The goal of this paper is to introduce test patterns for checking inconsistencies in the hierarchical structure of wordnets. Every test pattern (displayed as a substructure) points out the cases of multiple inheritance and two of them are studied in depth by expert linguists, or lexicographers. Furthermore, this research associates test patterns with the inconsistencies they help to detect in wordnets, and presents instances of the test patterns. All examples use the Estonian Wordnet (Versions 66 or 67), some results we are shown for the Princeton WordNet (Version 3.1).

Due to the enormous amount of data stored in spatial multidimensional databases (also called spatial datacubes) and the complexity of multidimensional structures, extracting interesting information by exploiting spatial data cubes becomes more and more difficult. Users might overlook what part of the cube contains the relevant information and what the next query should be. This could affect their exploitation of spatial datacubes.

In order to help users to better exploit their spatial datacubes, we propose to use a collaborative filtering recommendation approach. The approach is based on computing the similarity between the user’s behaviors in term of their spatial MDX queries launched on the system.

This paper introduces a new similarity measure for comparing spatial MDX queries. The proposed measure could directly support the development of spatial personalization and recommendation approaches. The presented measure takes into account both the semantic similarity as well as the basic components of spatial similarity assessment models: the topology, the direction and the distance.

Managing the decisions in organizations raises substantial challenges in regards of the associated processes. In software project management decision making has the critical role in this scenario since it defines the manager’s responsibilities and stems from the various sources linked to the process. The decision making constructs the essential foundation and thereby it needs a reliable framework for modeling of the decision structure. In this paper a conceptual multi-method simulation based framework will be introduced in a modality to cover multiple levels of the decision structure over software project management process. The framework is base on a model in which is inspired by a semi-supervised learning technique known as partially observable Markov decision process (POMDP). The methods used are integrated towards a multi-method simulation model whereas each of these methods exclusively realizes distinct aspect of software project management. The framework evolves the manner of decision making by a paradigm which establishes the foundation for a tactical level understanding and decision support for practitioners. At the results section an optimal decision policy for the framework will be presented.

The difference between smart home (or smart agent) and intellectual- ized smart home (or intellectual smart agent) is delivered, and the framework for their modelling is described. Question of a sophisticated adequacy evalua- tion is raised to compare the reality and its model. The proposed approach was used to evaluate four different decision making technologies implemented in the models of the intellectualized smart home environment, and the comparison of those experimental technologies prepared by expert is presented.

Paper presents a technique for fuzzy rule extraction. It applies a division of a feature space into fuzzy grids and a selection of discrete values as inputs for neural network. A neural network generates fuzzy rules that are simplified using a decision table analysis tool Prologa. The tool detects and fixes cases of redundancy and ambivalence in a fuzzy rule base. A case study contains an illustration of the proposed technique and a comparison of the results to other sources. A comparative analysis of a productivity of traffic light controllers developed using an expert rule base and a rule base formed using our technique is given. Iris classification problem is considered too. Comparison results prove better accuracy of the technique suggested.

The usage of probabilistic models in business process mining enables analysis of business processes in a more efficient manner. Although, the Bayesian belief network is one of the most common probabilistic models, possibilities to use it in business process mining are still not widely researched. Existing process mining approaches are incapable to extract directed acyclic graphs for representing Bayesian networks. This paper presents an approach for extraction of directed acyclic graph from event logs. The results obtained during the experiment show that the proposed approach is feasible and may be applied in practice.

The purpose of this paper is to compare the efficiency of three different evolutionary programming techniques – Genetic Programming, Grammatical Evolution and Gene Expression Programming. These algorithms were applied to different type test problems with the same set of parameters. The results of the experiments and some insights on similar experiments of the other authors are provided.

Organizational alignment is an important issue in various interest areas such as Strategy, Business Process Management, Requirements Engineering, and Enterprise Architecture. From IT perspective the most holistic approach on alignment and control is Enterprise Architecture. Enterprise Architecture’s eminent standard framework is TOGAF with companion architecture modeling language ArchiMate. Although ArchiMate proposes Motivation Extension to facilitate strategic alignment, this extension does not offer any facility to verify and/or validate the architecture model. Moreover, the Motivation Extension proposes its model elements to be linked to the core elements only through the

stakeholder

element. This paper proposes an ArchiMate Profile for

GoalDAG

. GoalDAG is a simple goal model that can be linked to the different model elements seamlessly and enables to validate the existing model. To represent GoalDAG integration with Enterprise Architecture, ArchiMate - GoalDAG profile is developed and exemplified through TOGAF’s ArchiSurance fictitious case study.

This paper proposes a formal environment, named FMEBP, for modeling business processes. This environment is based on a transformation approach that translates Web services, described in BPEL language, to abstract specifications, written in a high-level real-time language called D-LOTOS. The interest of D-LOTOS language is provided from the fact that it is based on true-concurrency semantics and supports both timing constraints and actions durations. For assessing the proposed environment we study a specification of a Web services application.

Customer Flow Management (CFM) systems are used to manage queues and support customer service business processes at various companies. The customer experience could be improved and waiting time reduced, if the service provisioning adapts to the context. To solve this problem, an approach for design and implementation of CFM systems on the basis of adaptive workflows is proposed. The adaptive workflows are modeled using BPMN and implemented using the object-oriented approach. To support model-driven implementation of adaptive workflows, the BPMN meta-model is extended to represent adaptive features and to support reuse of workflow activities across multiple alternative implementations of workflow execution variants. To illustrate the approach, a prototype of the dynamic luggage registration and online ticket re-registration in case of flight cancellation CFM system is developed.

Mobile UML (M-UML) has been proposed as an extension of UML to model mobile agent-based software systems. As UML, M-UML suffers from lack of semantics due to its semi-formal structure. Formal methods have been used largely in order to deal with such problems.

π

-calculus is one of these formal methods that deal with mobile computation. In this paper, we propose a formalization of M-UML statechart diagrams using

π

-calculus in order to provide a formal semantics for such diagrams. The generated

π

-calculus specifications are then used to analyze and check systems using

π

-calculus analytical tools (e.g. MWB tool). We illustrate our approach by an example.

Completeness of requirements has persisted as a challenge in software development projects. Particularly, in an iterative and incremental development process, only a small portion of requirements are specified before iterations start. Initial versions of the models may be developed in parallel whilst requirements elicitation is still ongoing. In this paper, we propose a metamodel approach for automating the detection of incompleteness in requirements during the conceptual modeling process. Our approach utilizes the metamodel information to allow the modeler to record explicitly each of the model’s "known-unknowns", i.e. items of information which are needed to make the model complete, yet which cannot be inferred from the available requirements.

One of the main features of Model Driven Architecture is a model-to-model (M2M) transformations, which improve the overall model-driven systems development process by speeding up the development process itself and also enabling the reusability of the existing models within a single or even multiple projects. However, CASE tool-supported M2M transformations quite often lack so needed flexibility and customization options. The main goal of this paper is to present a practical model-driven approach to improve the usability of partial model-to-model transformations in a CASE tool environment. The approach is currently implemented in the CASE tool MagicDraw; however, it can be adopted by any other CASE tool that meets certain capability requirements.

Electronic business uses ICT to support its activities. This has positively impacted business performance. Recognizing the successful implementation of e-business, governments have decided to use ICT in public services in order to improve the performance of government organizations in providing best possible information and services to citizens, businesses and other public departments. Computing technologies have grown by leaps and bounds, and governments of all nations plan to make optimum use of such advanced technologies across public service organizations. However, due to financial crises, governments have resorted to cost-cutting, which in turn has resulted in a cap on their ICT budget. As a large-scale facility, e-government requires large monetary investment from the government. Some new inventions in the field of computing technologies have made cost reduction possible, while also increasing the efficiency and flexibility of government sectors. One such invention is cloud computing, which provides information and computing services as utilities. Cloud-based e-government provides the best possible services to its citizens and businesses at an affordable cost. This is because governments do not need to purchase and install ICT equipment on their premises. In this paper we analyse cloud computing and its applications in the context of e-government.

The paper introduces the stage-based specialization of the initial reusable GLOs treated as meta-programs. The aim is to support pre-programmed user-guided adaptation of the Computer Science (CS) teaching content within the educational robot environment. Specialization of GLOs by staging enables to flexibly (automatically) prepare the content at a higher level for the different contexts of use. We describe the approach along with the case study from the user’s perspective taking into account the specializer tool we have developed. The contribution of the paper is the staged specialization for the pre-programmed adaptation of the learning content.

This work presents a performance evaluation of the state-of-the-art computer vision algorithms for object detection and pose estimation. Depth information from Kinect sensor is used in this work for the estimation task. It is shown, that Kinect depth sensor is more superior for orientation estimation than a regular stereo camera setup. Accuracy and performance of a point cloud alignment ICP method is analyzed and tested. Furthermore, multiple object detectors accuracy and runtime performance is evaluated. Simple but effective techniques are provided for the comparison. Conducted experiments show a maximum object detection accuracy of 90% and speed of 15 fps for standard size VGA images, while ICP alignment performance of 2 fps is achieved. Additional optimizations would be necessary to attain better real-time object detection and pose extraction performance.

In this paper we discuss the idea to apply evolutionary computation method, in particular firefly algorithm, to search for key-points in 2D images. In the research, classic firefly algorithm is used to search for special areas in test images. Research results are presented and discussed to show potential efficiency of applied method.

Mobile devices are currently the most popular way of delivering ubiquitous augmented reality experiences. Traditionally, content sources for mobile augmented reality applications can be seen as isolated silos of information, being designed specifically for the intended purpose of the application. Recently, due to the raising in popularity and usage of the Semantic Web technologies and the Linked Data, some efforts have been made to overcome current augmented reality content sources limitations by integrating Linked Data principles and taking advantage of the significant increase in size and quality of the Linked Open Data cloud. This paper presents a literature review of the previous efforts in this respect, while highlighting in detail the limitations of current approaches, the advantages of integrating Linked Data principles in mobile augmented reality applications and up-to-date challenges in regarding this still novel approach. The authors conclude by suggesting some future research directions in this area.

Mobile augmented reality applications have seen tremendous growth in recent years and tourism is one of the fields in which this set of technologies has been proved to be a natural fit. Augmented reality has the potential of enhancing the surroundings of the tourist in a meaningful way. In order to provide personalized and rich content for the augmented reality application, researchers have explored the use of Semantic Web and especially Linked Data principles and technologies. In this paper we review existing projects at the intersection of these technologies and current aspects, not necessarily specific, but highly relevant to the integration of Linked Open Data in mobile augmented reality applications for tourism. In this respect, we discuss approaches in the area of geodata integration, quality of the open data, provenance information and trust. We conclude with recommendations regarding future research in this area.

We present a vision of using educational robots as smart mobile components (“things”) of Internet-of-Things. Such robots, beside their primary mission to facilitate learning, are able to communicate; have computing capabilities; as well as have sensors and actuators to sense and change their physical context. The robot serves both as the educational service that allows to visualize knowledge through explicit actions and behaviour as well as the enabler of learning and providing student engagement through immersion and instant feedback. The vision is based on the principles of contextualization, physicality and immersion. The pedagogical background is the proposed Internet-of-Things Supported Collaborative Learning (IoTSCL) paradigm based on constructivism, which provides a highly motivating learning environment in university, promoting collaboration among students, and achieving the creation of new knowledge in a reflexive process directed by the teacher. We demonstrate the implementation of the paradigm in the project-based setting at the university course and evaluate it using the Four-Phased Model of Interest Development.

Educational systems are complex adaptive systems with basic properties of openness, nonlinearity, feedback and adaptivity.Modelling and assessment of a teaching/learning process is a difficult task that involves many factors at multiple dimensions (pedagogical, technological, organizational, social, etc.). Common methods used for evaluation of teaching/learning effectiveness such as surveys, questionnaires and tests are subjective and lack of statistical control and standards for comparison. In this paper, we propose an empirical knowledge transfer model for closed teacher-learner systems and its extension for open teacher-learner systems. The model is based on the theory of communication in noisy channels with additive white Gaussian noise. We describe the pedagogical interpretation of the model’s parameters and describe its application in modelling the transfer of knowledge in the teaching/learning process.

Phylogenetic algorithms are a tool that is frequently used in biology and linguistics for reconstruction of the evolution trees for species or languages. However, there is no a definitely superior algorithm: various algorithms have shown the best results in various studies. In this paper we test four most popular algorithms. We make recommendations which algorithm is better to choose in different cases. In particular, the influence of the feasibility of the lexical clock hypothesis is shown. It is shown that the results are also affected by the choice of metric, and that the results can be improved by using the

λ

-measure instead of the Hamming’s measure. The results of the paper are obtained using both the simulation method and real data.

Online social networks are largely failing to engage people in relevant interactions with people, contents or resources in their physical environment. We motivate the potential of automatically establishing sporadic social networks among people (acquaintances or strangers) who happen to be physically close to one another at a certain moment. We present the design of one platform intended to provide solutions from the lowest level of establishing ad-hoc connections among nearby mobile devices, up to the highest level of automatically identifying the most relevant pieces of information to deliver at any time. A number of application scenarios are presented, along with conclusions from redesigning a former system that delivered immersive learning experiences in museums according to the constructs of the sporadic social networks.

Fiducial markers are widely used in many Augmented Reality (AR) applications such as to manipulate AR objects, robot navigation, education and AR based games. ARToolKit is an open source, easy to configure and well-documented tracking system which is widely used for designing marker based AR applications. The quality of ARToolKit markers plays a vital role in the performance of these AR applications, but currently there is neither algorithm nor quantitative measure to guide users for designing high quality markers in order to achieve their reliable tracking. In this paper we studied the effect of edge sharpness, noise and markers distinction on markers reliability. We also developed the specialized algorithms for designing Sharp-edged, De-noised and Distinct (SDD) markers, which have low inter-marker confusion and are highly reliable.

Failure simulation for the flat structure assembled of the degenerated shell elements and referred as unidirectional composite is considered in this paper. Master-Slave and penalty methods are implemented in order to describe connections between elements. The results are compared for 2D simulation by both methods if structure is loaded in longitudinal and transverse directions.

The Internet of Things is a rapidly evolving technology, which creates new challenges to security and energy consumption of devices at the various environmental conditions. Wireless communication technologies are one of the bases of IoT. In this paper, we proposed the security requirements of IoT applications to relate with the operating modes of wireless protocols. In addition, we presented the measurement and analysis of energy consumption and data transfer rates of Wi-Fi and Bluetooth protocols, depending on the security requirements of applications and conditions of environment.