Richard Cimler

Security Issues of Mobile Application Using Cloud Computing

Security issues of the mobile application using cloud computation services are discussed in this paper. Communication between smart phone as a client on the one side and cloud server on the other is described. Security analyse for proposed solution of the health monitoring application is introduced as well. Data about health of the person are one of the most confidential thus need to be secured against different types of threats. Proposed solution is based on the smartphone as a client gathering data and the cloud servers as a computational platform for data storage and analysing. The sensors embedded in the smart phone measure data about monitored person then are partly processed and sent to the server by the internet connection for the deeper analysis.

Cloud based solution for mobile healthcare application

Design of the Watch Dog health care application is presented in this paper. Solution is based on the client running on the smartphone and the server side running in the cloud. Sensors embedded in the smartphone are used for the measurement of the different information about the monitored person such as position, temperature, breath frequency etc. Basic algorithms evaluating current persons health status run on the smartphone. Measured data are sent to the second part of the application running in the cloud for deeper analysis. Suitability of the cloud solution for this application is discussed in this paper.

Lower Layers of a Cloud Driven Smart Home System

This presented article introduces utilization of a cloud solution as a part of inovative smart home system (HAUSY - Home Automation System). This solution is based on highly modular structure, which ensures a unique solution for individual implementations. In scope of the presented solution, a universal architecture not requiring a specialized hardware for its utilization is suggested. In the first part, the original three-part smart home system architecture and the functionality of individual layers are introduced. The second part of the article introduces a specific solution for functionalities and communication between individual end nods and microcontrollers. The suggested solution is unique for its option of personalizations of user access and priorities, comfortable interface for defining rules of autonomous operations, and the option of connecting external systems via a unified API with the option of using cloud.

Understanding the Iron Age Economy: Sustainability of Agricultural Practices under Stable Population Growth

Some of the most significant settlements of late Iron Age Europe were founded in agriculturally marginal landscapes. The specific locations caused their food production potential to be regarded usually as deficit in terms of sustainability. Such notion, however, can be re-examined with help of new methodological tools. In order to capture the dynamics of the agro-pastoral economy processes in recurrent year-to-year cycles, this chapter exploits the objective advantages and limits of coupled GIS environmental and agent-based social modelling approaches. Three consecutive models are presented—the population dynamics in The Population Model, and the sustainability of the land-use strategies in The Crop Production Model and The Field Allocation Model. Models are firmly based on authentic archaeological and environmental record with the region around long-term investigated oppidum of Stare Hradisko (Czech Republic) used as the case study. Results obtained with the simulation demonstrate limits of the sustainable economy practiced by a constantly growing population under particular environmental settings. The immediate or gradual impact of the success rate in food production and its potential influences on the social processes including the oppida abandonment are also addressed.

Eigenspace structure of a max-prod fuzzy matrix

The eigenvectors of a fuzzy matrix correspond to steady states of a complex discrete-events system, characterized by the given transition matrix and fuzzy state vectors. The descriptions of the eigenspace (the set of all eigenvectors) for matrices in the max-min, max-ukasiewicz or max-drast fuzzy algebra have been presented in previous papers. The eigenspace of a fuzzy matrix in the max-prod algebra is investigated in this paper. First, necessary and sufficient conditions are shown under which the eigenspace restricted to increasing eigenvectors of a given matrix is non-empty, and the structure of the increasing eigenspace is described. Then, using simultaneous row and column permutations of the matrix, the complete characterization of the whole eigenspace structure of a given fuzzy matrix is shown. The details for matrices of order 3 are only presented. The method works analogously for square matrices of higher orders, with rapidly increasing complexity of the formulas.

Prediction of population with Alzheimer's disease in the European Union using a system dynamics model

Introduction Alzheimer’s disease (AD) is a slowly progressing neurodegenerative brain disease with irreversible brain effects; it is the most common cause of dementia. With increasing age, the probability of suffering from AD increases. In this research, population growth of the European Union (EU) until the year 2080 and the number of patients with AD are modeled. Aim The aim of this research is to predict the spread of AD in the EU population until year 2080 using a computer simulation. Methods For the simulation of the EU population and the occurrence of AD in this population, a system dynamics modeling approach has been used. System dynamics is a useful and effective method for the investigation of complex social systems. Over the past decades, its applicability has been demonstrated in a wide variety of applications. In this research, this method has been used to investigate the growth of the EU population and predict the number of patients with AD. The model has been calibrated on the population prediction data created by Eurostat. Results Based on data from Eurostat, the EU population until year 2080 has been modeled. In 2013, the population of the EU was 508 million and the number of patients with AD was 7.5 million. Based on the prediction, in 2040, the population of the EU will be 524 million and the number of patients with AD will be 13.1 million. By the year 2080, the EU population will be 520 million and the number of patients with AD will be 13.7 million. Conclusion System dynamics modeling approach has been used for the prediction of the number of patients with AD in the EU population till the year 2080. These results can be used to determine the economic burden of the treatment of these patients. With different input data, the simulation can be used also for the different regions as well as for different noncontagious disease predictions.

Agent-Based Model of Celtic Population Growth: NetLogo and Python

The agent-based model of Celtic population growth was developed using specific domain knowledge and general demographic assumptions about birth-rates and mortality. The model allows archaeologists to simulate the time series of available workforce and actual consumption of the population living in the given settlement agglomeration. Parameters of the NetLogo model were refined experimentally. The implementation in Python was created for validation and reporting. The simulated population is stable, with appropriate age distribution and growth rate. The model is used for further simulations of the settlement population dynamics and for testing hypotheses about the agricultural practices, trade and exchange etc. The final objective of our research project is to better understand the collapse of the Celtic society in Europe in the Late Iron Age.

Interactive evolutionary optimization of fuzzy cognitive maps

Abstract Modeling dynamic systems with Fuzzy Cognitive Maps (FCMs) is characterized by the simplicity of the model representation and its execution. Furthermore, FCMs can easily incorporate human knowledge from the given domain. Despite the many advantages of FCMs, there are some drawbacks, too. The quality of knowledge obtained from the domain experts, and any differences and uncertainties in their opinions, has to be improved by different methods. We propose a new approach for handling incompleteness and natural uncertainty in expert evaluation of the connection matrix of a particular FCM. It is based on partial expert estimations and evolutionary algorithms in the role of an expert-driven optimization and outside of the FCM optimization (adaptation) research area known as Interactive Evolutionary Computing (IEC). In the present paper, a modification of IEC for the purposes of FCM optimization is presented, referred to as the IEO-FCM method, i.e., the Interactive Evolutionary Optimization of Fuzzy Cognitive Maps. Experimental results on two control problems suggest that the IEO-FCM method can improve the quality of an FCM even in situations without any measured data necessary for other known learning algorithms.

Lightweight Protocol for M2M Communication

Increasing popularity of Internet of Things and Smart home system raises new requirements for micro-controllers. There is a need for affordable solutions with low power consumption and reasonably fast communication transmission rate. This article deals with the communication protocols and introduces own protocol designed for machine to machine communication. Different ways of data transfer between various hardware layers are shown and compared. Every approach is discussed with its benefits and downfalls. Benchmark of three selected types of communication using proposed protocol is performed and results are shown.

Exploration of Autoimmune Diseases Using Multi-agent Systems

Autoimmune disease is a group of pathological events identified by abnormal reactions of the immune system against self-structures of the organism. Pathogenesis of autoimmune diseases is multi-factorial. Genetics, infections, and environmental factors can support the progress of the autoimmunity. We investigated this mechanism using in vivo or in vitro approaches. Main aim of this manuscript is to explore the autoimmunity with in-silico approach - multi-agent systems. The preliminary research finds out which results can be acquired using factual data applied for building the multi-agent-based model. Preliminary computational model integrates one of the common aspects of autoimmune diseases - abnormal behaviour of B-cells during their organogenesis.