Detached house, Štěpánkovice

Tématem bakalářské práce je projekt rodinného domu. Dům je navržený jako dvoupodlažní, nepodsklepená dřevostavba se sedlovou střechou, dispoziční uspořádání 6+KK odpovídá návrhu pro 4-6 člennou rodinu. Do domu se vstupuje ze severozápadní strany. Na kryté závětří navazuje zádveří, ze kterého se dostaneme do chodby ze které je přístupná kuchyně s obývacím pokojem, schodišťový prostor, pracovna, ložnice pro rodiče se samostatnou šatnou a koupelnou, technická místnost a WC. Dále je ze zádveří přístupná garáž pro jeden osobní automobil, na kterou navazuje sklad. V druhém podlaží se nachází tři dětské pokoje, koupelna s WC a šatna. Všechny obytné místnosti jsou přístupné z chodby a jsou orientovány převážně na jižní stranu. Jedná se o dřevostavbu z velkoformátových panelů NOVATOP. Objekt je zastřešený sedlovou střechou z G-N vazníků.The Bachelor thesis topic is a project of a detached house. The house design is a two-story wooden building with a pitched roof and no basement. The wooden building is constructed of large panels and the roof is supported by G-N timber trusses. The entrance is situated in the northwest part of the house. Containing six bedrooms, the building layout fullfills the design for 4-6 family members. On the sheltered lee builds vestibule from which we get into the hall. The main hall opens to the kitchen and living room, stairs, and study room. As well, the main haill leads to the master bedroom which has a separate dressing room, bathroom, wash room, and utility room.There is access to the main hallway from the garage and side door. The second floor has three children's bedrooms, bathroom, and wash and dressing rooms. All of the bedrooms are accessible form the second-floor hallway.All of the bedrooms are enterable form the hall and are situated on south side. It is a wooden building of large-size panels. The roof is supported by G-N timber trusses.

Analysis and risk assessment of construction technologies of structures in an integrated management system

Diplomová práce se zabývá analýzou a hodnocením kvalitativních, environmentálních a bezpečnostních rizik a aplikací vhodné metodiky na konkrétní stavební dílo. Pro aplikaci jsou zvoleny klíčové stavební technologie, jež jsou zařazeny podle třídníku stavebních konstrukcí a prací (TSKP) do kapitoly hlavní stavební výroba (HSV). Z ČSN EN 31010 Management rizik -Techniky posuzování rizik jsou pro práci vybrány nástroje - analýza příčin a důsledků, analýza způsobů a důsledků poruch (FMEA), Paretův diagram a analýza typu motýlek. Cílem diplomové práce je analyzovat a posoudit kvalitativní, environmentální a bezpečnostní rizika vybraných stavebních technologií a v podmínkách zavedeného integrovaného systému řízení zpracovat jednoduché nástroje pro jejich řízení a eliminaci.This thesis deals with the analysis and evaluation of quality, environmental and safety risks and the application of appropriate methodologies to concrete construction work. For application are selected key construction technologies, which are classified according to the Classification of building structures and works (TSKP) in Chapter main building production (HSV). From ČSN EN 31010 Risk management – Risk assessment techniques were selected for work tools - Causes and effect analysis, Failure Modes and Effects Analysis (FMEA), Pareto diagram, Bow tie analysis. The aim of this thesis is to analyze and assess the quality, environmental and safety risks of selected construction technologies and conditions established an integrated management system to handle simple tools for the management andelimination.

Community Based Platform for Vulnerability Categorization

Many approaches, such as attack graphs, require knowledge of vulnerability's properties such as impact, prerequisities, and exploitability. Currently, those properties are either categorized manually or too roughly. We present a program for granular, automated categorization of vulnerability. Further, we present a platform supporting researchers by gathering and sharing raw data about vulnerabilities and community labeled datasets. The source code of our categorization program is available on GitHub

Projekt Etymologického slovníku české a slovenské vinohradnické a vinařské terminologie

V prispevku je predstavljen raziskovalni projekt Jezik tradicionalnega vinogradništva in vinarstva v srednjeevropskem prostoru: etimologija in arealno jezikoslovje ter njegov temeljni rezultat, tj. elektronski Etimološki slovar češke in slovaške vinogradniške ter vinarske terminologije. Gre za slovar manjšega obsega, v katerem je predstavljena etimologija in zgodovinski razvoj zbranih čeških (in primerjalno tudi slovaških) vinogradniških ter vinarskih terminov. Analiza čeških in slovaških besed je vključena v širši geografski okvir t. i. srednjeevropskega vinarskega prostora, zato so zajeti tudi ustrezni terminološki sistemi v nemščini (ali avstrijski nemščini), madžarščini, slovenščini, hrvaščini in poljščini. This paper presents the research project The language of traditional viticulture and viniculture in the Central European area: etymology and areal linguistics as well as its main result – the electronic Etymological dictionary of the Czech and Slovak viticultural and vinicultural terminology. This is a small-scale dictionary, in which the collected Czech (and comparatively also Slovak) terms are etymologized and their development is described. The analysis of the Czech and Slovak words is implemented in a broader geographic context – the so-called Central European wine-growing area. The equivalent terminological systems of the neighbouring languages are researched – the German (respectively Austrian), Hungarian, Slovenian, Croatian and Polish

Predictions of Network Attacks in Collaborative Environment

This paper is a digest of the thesis on predicting cyber attacks in a collaborative environment. While previous works mostly focused on predicting attacks as seen from a single observation point, we proposed taking advantage of collaboration and exchange of intrusion detection alerts among organizations and networks. Thus, we can observe the cyber attack on a large scale and predict the next action of an adversary and its target. The thesis follows the three levels of cyber situational awareness: perception, comprehension, and projection. In the perception phase, we discuss the improvements of intrusion detection systems that allow for sharing intrusion detection alerts and their correlation. In the comprehension phase, we employed data mining to discover frequent attack patterns. In the projection phase, we present the analytical framework for the predictive analysis of the alerts backed by data mining and contemporary data processing approaches. The results are shown from experimental evaluation in the security alert sharing platform SABU, where real-world alerts from Czech academic and commercial networks are shared. The thesis is accompanied by the implementation of the analytical framework and a dataset that provides a baseline for future work

Survey of Attack Projection, Prediction, and Forecasting in Cyber Security

This paper provides a survey of prediction, and forecasting methods used in cyber security. Four main tasks are discussed first, attack projection and intention recognition, in which there is a need to predict the next move or the intentions of the attacker, intrusion prediction, in which there is a need to predict upcoming cyber attacks, and network security situation forecasting, in which we project cybersecurity situation in the whole network. Methods and approaches for addressing these tasks often share the theoretical background and are often complementary. In this survey, both methods based on discrete models, such as attack graphs, Bayesian networks, and Markov models, and continuous models, such as time series and grey models, are surveyed, compared, and contrasted. We further discuss machine learning and data mining approaches, that have gained a lot of attention recently and appears promising for such a constantly changing environment, which is cyber security. The survey also focuses on the practical usability of the methods and problems related to their evaluation

Machine Learning Fingerprinting Methods in Cyber Security Domain: Which one to Use?

Identification of a communicating device operating system is a fundamental part of network situational awareness. However, current networks are large and change often which implies the need for a system that will be able to continuously monitor the network and handle changes in identified operating systems. The aim of this paper is to compare machine learning methods performance for OS fingerprinting on real-world data in the terms of processing time, memory requirements, and performance measures of accuracy, precision, and recall.Identification of a communicating device operating system is a fundamental part of network situational awareness. However, current networks are large and change often which implies the need for a system that will be able to continuously monitor the network and handle changes in identified operating systems. The aim of this paper is to compare machine learning methods performance for OS fingerprinting on real-world data in the terms of processing time, memory requirements, and performance measures of accuracy, precision, and recall

Decision Support for Mission-Centric Cyber Defence

In this paper, we propose a novel approach to enterprise mission modeling and mission-centric decision support for cybersecurity operations. The goal of the decision support analytical process is to suggest an effective response for an ongoing attack endangering established mission security requirements. First, we propose an enterprise mission decomposition model to represent the requirements of the missions' processes and components on their confidentiality, integrity, availability. The model is illustrated in a real-world scenario of a medical information system. Second, we propose an analytical process that calculates mission resilience metrics using the attack graphs and Bayesian network reasoning. The process is designed to help cybersecurity operations teams in understanding the complexity of a situation and decision making concerning requirements on enterprise missions

CRUSOE: A Toolset for Cyber Situational Awareness and Decision Support in Incident Handling

The growing size and complexity of today’s computer network make it hard to achieve and maintain so-called cyber situational awareness, i.e., the ability to perceive and comprehend the cyber environment and be able to project the situation in the near future. Namely, the personnel of cybersecurity incident response teams or security operation centers should be aware of the security situation in the network to effectively prevent or mitigate cyber attacks and avoid mistakes in the process. In this paper, we present a toolset for achieving cyber situational awareness in a large and heterogeneous environment. Our goal is to support cybersecurity teams in iterating through the OODA loop (Observe, Orient, Decide, Act). We designed tools to help the operator make informed decisions in incident handling and response for each phase of the cycle. The Observe phase builds on common tools for active and passive network monitoring and vulnerability assessment. In the Orient phase, the data on the network are structured and presented in a comprehensible and visually appealing manner. The Decide phase opens opportunities for decision-support systems, in our case, a recommender system that suggests the most resilient configuration of the critical infrastructure. Finally, the Act phase is supported by a service that orchestrates network security tools and allows for prompt mitigation actions. Finally, we present lessons learned from the deployment of the toolset in the campus network and the results of a user evaluation study