In my thesis I focused on the level of public knowledge in the field of protection of general population, because I wanted to identify the current state and to find out if cancellation of teaching this subject matter affected the public´s knowledge on this issue. The subject matter education was ended up after the change of the political system in the Czech Republic and the fall of communist regimes in Central Europe, where the population in the response to changes in domestic and global politics, that eliminated a military assault of the Czech Republic, lost interest in the issue. However, people do not realize that although the danger of war is eliminated, there are other dangers of human inventions such as industrial production, transport of chemicals, or energy production and other activities, and other dangers on the part of nature, such as excessive rainfall, strong winds and other natural calamities. In the introductory section of the thesis information on history of the public warning system and the current state of warning, evacuation and protection of population is given. Data was gathered through questionnaires, where respondents had to indicate the type of a recorded sound of a siren and the subsequent response to the sound of the siren. Other questions in the questionnaire were focused on evacuation of population and improvised protection from hazardous substances. The introductory section is followed by the description of the obtained data evaluation. The hypothesis assuming that the current population has little knowledge in the field of protection of population and that a part of the population who have undergone lessons in the subject called national defence education have greater knowledge than those who did not have this education, was confirmed after evaluation of the questionnaires. Only one quarter of respondents identified the recorded sound of a siren, which is a warning value. For other questions higher values were obtained. Another part of the population, which had not undergone lessons in national defence education, reached a lower percentage of correct answers. In the final section of the thesis evaluation of individual questions is mentioned. The situation is reviewed and measures proposed to improve the level of knowledge of the Czech Republic population in the response to warning signals.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Intrusion Detection Systems (IDS) are designed to monitor the computer network infrastructure against possible attacks by generating security alerts. With the increase of components connected to computer networks, traditional IDS are not capable of effectively detecting malicious attacks. This occurs either by the distributed amount of data that traverses the network or the complexity of the attacks launched against the network. Therefore, the design of Internet Early Warning Systems (IEWS) enables the early detection of threats in the network, possibly avoiding eventual damages to the network resources. The IEWS works as a sink that collects alerts from different sources (for example, from different IDS), centralizing and correlating information in order to provide a holistic view of the network. This way, the current dissertation describes an IEWS architecture for correlating alerts from (geographically) spread out IDS using the Case-Based Reasoning (CBR) technique together with IP Georeferencing. The results obtained during experiments, which were executed over the implementation of the developed technique, showed the viability of the technique in reducing false-positives. This demonstrates the applicability of the proposal as the basis for developing advanced techniques inside the extended IEWS architecture. / Sistemas de Detecção de Instrução (Intrusion Detection Systems IDS) são projetados para monitorar possíveis ataques à infraestruturas da rede através da geração de alertas. Com a crescente quantidade de componentes conectados na rede, os IDS tradicionais não estão sendo suficientes para a efetiva detecção de ataques maliciosos, tanto pelo volume de dados como pela crescente complexidade de novos ataques. Nesse sentido, a construção de uma arquitetura Internet Early Warning Systems (IEWS) possibilita detectar precocemente as ameaças, antes de causar algum perigo para os recursos da rede. O IEWS funciona como um coletor de diferentes geradores de alertas, possivelmente IDS, centralizando e correlacionado informações afim de gerar uma visão holística da rede. Sendo assim, o trabalho tem como objetivo descrever uma arquitetura IEWS para a correlação de alertas gerados por IDS dispersos geograficamente utilizando a técnica Case-Based Reasoning (CBR) em conjunto com Georreferenciamento de endereços IP. Os resultados obtidos nos experimentos, realizados sobre a implementação da técnica desenvolvida, mostraram a viabilidade da técnica na redução de alertas classificados como falsos-positivos. Isso demonstra a aplicabilidade da proposta como base para o desenvolvimento de técnicas mais apuradas de detecção dentro da arquitetura de IEWS estendida.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The popularization of the Internet has provided an increase in the number of web applications that work with critical information. Parallel to this, attacks that exploit the vulnerabilities of these applications has also grown. This scenario has stimulated companies to invest in tools to monitor their network infrastructure in order to detect malicious activity. One of the main tools used by companies to monitor their network infrastructures and identifying attacks are Intrusion Detection Systems. However, due to expansion of the volume of data in computer networks, these systems are becoming limited. In contrast, researchers have explored the construction of Internet Early Warning Systems to monitor malicious activities on the Internet. This work proposes a data model of a knowledge base for Internet EarlyWarning Systems. The model represents the data of different aspects of the network with a focus on events related to intrusion detection, such as data of alerts generated by intrusion detection systems, information on response measures, traffic statistics and signatures of known attacks. A case study on a real network infrastructure demonstrates the applicability of the data model of knowledge base and identifies the advantages of its use. Furthermore, the data stored in the knowledge base potentializes the construction of situational awareness of monitored environment, directing the activities of the security team and helping in the decision process responses to potential attacks. / A popularização da Internet tem proporcionado um aumento no número de aplicações web que trabalham com informações críticas. Em paralelo a isso, os ataques que exploram as vulnerabilidades dessas aplicações também tem crescido. Esse cenário tem estimulado as empresas a investir em ferramentas para monitorar sua infraestrutura de rede, visando a detecção de atividades mal-intencionadas. Uma das principais ferramentas utilizadas pelas empresas para o monitoramento de suas infraestruturas de redes e identificação de ataques são os Sistemas de Detecção de Intrusão. No entanto, devido a expansão do volume de dados que trafegam nas redes de computadores, estes sistemas estão tornando-se limitados. Em contrapartida, pesquisadores têm explorado a construção de Internet Early Warning Systems para o monitoramento de atividades maliciosas na Internet. Este trabalho propõe a modelagem de dados de uma base de conhecimento para Internet Early Warning Systems. O modelo representa os dados de diferentes aspectos da rede com foco em eventos relacionados a detecção de intrusão, tais como: dados de alertas gerados por sistemas de detecção de intrusão, informações sobre medidas de respostas, estatísticas do tráfego e assinaturas de ataques já conhecidos. Um estudo de caso em uma infraestrutura de rede real demonstra a aplicabilidade do modelo de dados da base de conhecimento e permite identificar as vantagens de sua utilização. Além disso, os dados armazenados na base de conhecimento potencializam a construção de uma consciência situacional do ambiente monitorado, direcionando as atividades da equipe de segurança e auxiliando no processo de decisão de respostas a ataques em potencial.

This thesis is based on the work carried out in the field of safety systems for Autonomous Guided Vehicles(AGV). With autonomous vehicles being more prominent today, safe traversing of these is a major concern. The same is true for AGVs working in industry environment like forklift trucks etc. Our work applies to industrial robots. The method described here is developed by closely following an algorithm developed for safe traversing of a robot using a warning field. The report describes the literature review with work related to the safe traversing, path planning and collision avoidance in robots. The next part is dedicated to describing the methodology of implementation of the Adaptive Warning Field Method and the Dynamic Window Approach. The evaluation of the Adaptive Warning Method with the previous developed Warning Field Methods is done and test cases are designed to test the working of the designed method. Vrep simulation environment and Industrial data is used to run a simulation of the robot using the method developed in this work. We find that the method performs better compared to the previous methods in the designed scenarios. Lastly we conclude the report with the future work that can be carried out to improve and extend the algorithm.

Magister Artium - MA / This dissertation explores the potential contributions of the mechanisms for early warning and intelligence sharing to regional security in Africa. The Continental Early Warning System (CEWS) and the Committee on Intelligence and Security Services of Africa (CISSA) are centrally concerned with the dissemination of information to enable decision-making on continental security. The main focus of the dissertation is on the manner in which the information generated by the CEWS and CISSA can contribute to regional security. In order to analyse the potential contribution of the CEWS and CISSA to regional security, a sound theoretical framework is proposed so as to explore how and why states choose to cooperate, as well as addressing multifaceted cooperation and integration at inter-state, government department and nonstate levels. Constructivist interpretations of international cooperation are utilised to explore the role of ideas, meanings and understandings in shaping behaviour. The focus is placed on the manner in which interaction as provided for by the CEWS and CISSA can shape understandings of reality and potentially impact on the definition of actors' interests. This is based on the assumption drawn from security community and epistemic community theory that, enabling the creation of shared meanings and shared knowledge there is the potential for both the CEWS and CISSA to have a positive influence on the choices that stakeholders take in favour of peaceful change. / South Africa

By means of car2x communication technologies (car2x) driver warnings can be presented to drivers quite early. However, due to their early timing they could be misunderstood by drivers, distract or even disturb them. These problems arise if, at the moment of the warning, the safety–critical situation is not yet perceivable or critical. In order to examine, when drivers want to receive early warnings as a function of the situation criticality, a driving simulator study was conducted using the two early warning stages of a multi stage collision warning system (first stage: informing the driver; second stage: prewarning the driver). The optimum timing to activate these two early warning stages was derived by examining the drivers’ evaluation of these timings concerning their appropriateness and usefulness. As situational variation, drivers traveling at about 100 km/h were confronted with slow moving traffic either driving at 25 km/h or 50 km/h at the end of a rural road. In total, 24 participants were tested in a within-subjects design (12 female, 12 male; M = 26.6 years, SD = 7.2 years). For both stages, drivers preferred an earlier timing when approaching slow moving traffic traveling at 25 km/h (first stage: 447 m, second stage: 249 m ahead of the lead vehicle) compared to 50 km/h (first stage: 338 m, second stage: 186 m ahead of the lead vehicle). The drivers’ usefulness rating also varied with the timing, spanning a range of 8 s for driver-accepted timing variations and showed correspondence to the drivers’ appropriateness ratings. Based on these results and those of a previous study, a timing function for each of the two early warning stages depending on the speed difference between the safety–critical object and the host vehicle is presented. Indirectly, similar adaptations are already implemented in current collision warning systems, which use the time-to-collision to give drivers acute warnings in a later stage, when an immediate reaction of the driver may still prevent a collision. However, this study showed that drivers also favor this kind of adaptation for earlier warning stages (information and prewarning). Thus, adapting the timing according to the drivers’ preferences will contribute to a better acceptance of these collision warning systems.

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Yes / In English hospitals, the patient’s vital signs are monitored and summarised into a National Early Warning Score (NEWS). NEWS is more accurate than the quick sepsis related organ failure assessment (qSOFA) score at identifying patients with sepsis. We investigate the extent to which the accuracy of the NEWS is enhanced by developing computer-aided NEWS (cNEWS) models. We compared three cNEWS models (M0=NEWS alone; M1=M0 + age + sex; M2=M1 + subcomponents of NEWS + diastolic blood pressure) to predict the risk of sepsis. Methods: All adult emergency medical admissions discharged over 24-months from two acute hospitals (YH–York Hospital for model development; NH–Northern Lincolnshire and Goole Hospital for external model validation). We used a validated Canadian method for defining sepsis from administrative hospital data. Findings: The prevalence of sepsis was lower in YH (4.5%=1596/35807) than NH (8.5%=2983/35161). The c-statistic increased across models (YH: M0: 0.705, M1:0.763, M2:0.777; NH:M0: 0.708, M1:0.777, M2:0.791). At NEWS 5+, sensitivity increased (YH: 47.24% vs 50.56% vs 52.69%; NH: 37.91% vs 43.35% vs 48.07%)., the positive likelihood ratio increased (YH: 2.77 vs 2.99 vs 3.06; NH: 3.18 vs 3.32 vs 3.45) and the positive predictive value increased (YH: 11.44% vs 12.24% vs 12.49%; NH: 22.75% vs 23.55% vs 24.21%). Interpretation: From the three cNEWS models, Model M2 is the most accurate. Since it places no additional data collection burden on clinicians and can be automated, it may now be carefully introduced and evaluated in hospitals with sufficient informatics infrastructure. / The Health Foundation, National Institute for Health Research (NIHR) Yorkshire and Humberside Patient Safety Translational Research Centre / Research Development Fund Publication Prize Award winner, April 2019.

Published Article / Early indication of possible drought can help in developing suitable drought mitigation strategies and measures in advance. Therefore, drought forecasting plays an important role in the planning and management of water resource in such circumstances. In this study, a non-linear streamflow forecasting model was developed using Artificial Neural Network (ANN) modeling technique at the Melka Sedi stream gauging station, Ethiopia, with adequate lead times. The available data was divided into two independent sets using a split sampling tool of the neural network software. The first data set was used for training and the second data set, which is normally about one fourth of the total available data, was used for testing the model. A one year data was set aside for validating the ANN model. The streamflow predicted using the model on weekly time step compared favorably with the measured streamflow data (R2 = 75%) during the validation period. Application of the model in assessing appropriate agricultural water management strategies for a large-scale irrigation scheme in the Awash River Basin, Ethiopia, has already been considered for publication in a referred journal.

Freedom of speech is under serious threat in the west, primarily in the US with policies and regulations infringing on this core value in democratic societies. Universities form policy in order to silence opinions they find contradictory to their values, causing students and teachers alike to risk academic punishment for statements which normally would be guarded within the First Amendment. The central argument behind these infringments are individuals subjective feelings towards, as one may put it, controversial opinions. The aim of this study is through an argument analysis, illustrate the values of freedom of speech in contrast to the demands of primarily minority groups and their advocates, using respectable philosophers and scientists such as John Stuart Mill to answer the question if infringements are applicable in democracies. The conclusions drawn in this essay based on all relevant arguments concludes the answer to be no; a democracy should not infringe on the freedom of speech to safeguard individuals from negative emotional reactions as a result of any legal speech.