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What constitutes a species’ environment and distribution is of vital importance in ecology. Our understanding of the patterns of biogeographic distribution and their connection to the environmental responses of insects has been limited due to a lack of baseline data. The baseline distribution data for all species of a given group in a region can provide fundamental insights into biogeographic questions about historic patterns of diversity, endemism, and adaptive strategies to variable environments. Grasshoppers are one major group of insects for which a continent-wide perspective on distribution and response to environmental conditions can be obtained. This is because they were extensively surveyed in Australia for 54 years (1936-1989) as part of Commonwealth scientific expeditions for the Australian National Insect Collection. Field notebooks recorded by Dr Key and associates from those surveys can help fill the hole in our knowledge of invertebrate distribution patterns in Australia. In this thesis, I developed a database of historic occurrences of Australian grasshoppers based on those field notebooks. I transcribed and carefully geocoded field notebooks corresponding to surveys conducted in Western Australia (WA) and Tasmania. I collected 8975 geographic coordinates for 506 species having a confirmed or putative taxonomic name, based on our transcription and geolocation for 47 notebooks containing 590 pages (~24%, out of 2486 pages altogether). Of the 506 species identified from the notebook transcription, only 177 species had complete formal taxonomic names. I analyzed the occurrences that were recorded from WA using species distribution models (SDMs) to provide insights on the patterns of grasshopper diversity in Australia as well as their strategies of adaptation in response to variable climatic conditions. Overall, in this thesis I aimed to achieve the following goals: (i) digitize field notebooks and save them in a digital repository; (ii) transcribe and co

Free living ciliates are exposed to environmental challenges such as starvation, temperature fluctuations, high population density and salinity variations. Ciliates lower their metabolic activity and form cysts, an adaptive strategy evolved in response to environmental stress. In the present study on Pseudourostyla levis, a novel phenomenon of pseudoencystment had been noticed in which cells entered a state of dormancy but did not secrete a cyst wall. The process of pseudoencystment, which physiologically resembled true encystment, was functionally unrelated to it and was thus designated as pseudoencystment. Unlike true cysts, pseudocysts remained dormant for about 12 hours and then reverted to the active trophic state without any change in the environmental conditions. Another unique feature of pseudoencystment, was the synchronized induction of pseudocysts formation, achieved by a brief spell of starvation and the pseudocysts reverted to active trophic state without any change in environmental conditions. The state of dormancy did not provide any long-term protection to the ciliate and appeared to be a short term adaptation to the environment. The present study aimed to analyze the parameters for the induction of pseudocyst formation, cortical topological changes and to study the possible significance of this process. However, occasionally true cysts were also obtained by prolonged starvation, lasting 3-4 days but true cysts required either food or a fresh culture medium for excystation.

Response surface methods are widely used in slope reliability analysis due to the high efficiency. However, they are often criticized of the curse of high dimensionality, problem-dependent accuracy, and mechanism-free interpretation. To address these issues, this study proposes a response surface-guided adaptive slope reliability analysis method for slopes in spatially varying soils. A sparse quadratic polynomial is initialized using a two-fold dimensionality reduction technique. The response surface-based preliminary slope reliability analysis is successfully corrected to an unbiased, finite element-based target slope reliability analysis, during which the response surface updates iteratively with an increasing high accuracy from special emphasis nearby the failure domain. Two spatially varying soil slopes are investigated. Results indicate that the proposed method can provide an efficient and unbiased estimation of finite element-based target slope failure probability with a low variability, develop a more accurate and problem-oriented response surface model for slope reliability analysis, and explore failure mechanisms of slope stability in spatially varying soils. Its performance is insensitive to the accuracy of initial response surface. Additionally, it prominently outperforms both response surface and finite element-based subset simulations, regardless of high-dimensional or low-failure-probability problems. These advantages significantly enhance the application of response surface on practical slope reliability analysis.

Response surface methods are widely used in slope reliability analysis due to the high efficiency. However, they are often criticized of the curse of high dimensionality, problem-dependent accuracy, and mechanism-free interpretation. To address these issues, this study proposes a response surface-guided adaptive slope reliability analysis method for slopes in spatially varying soils. A sparse quadratic polynomial is initialized using a two-fold dimensionality reduction technique. The response surface-based preliminary slope reliability analysis is successfully corrected to an unbiased, finite element-based target slope reliability analysis, during which the response surface updates iteratively with an increasing high accuracy from special emphasis nearby the failure domain. Two spatially varying soil slopes are investigated. Results indicate that the proposed method can provide an efficient and unbiased estimation of finite element-based target slope failure probability with a low variability, develop a more accurate and problem-oriented response surface model for slope reliability analysis, and explore failure mechanisms of slope stability in spatially varying soils. Its performance is insensitive to the accuracy of initial response surface. Additionally, it prominently outperforms both response surface and finite element-based subset simulations, regardless of high-dimensional or low-failure-probability problems. These advantages significantly enhance the application of response surface on practical slope reliability analysis.

One of the most widespread applications of IoT technologies is smart metering. Despite remote metering in smart grids is not a novelty, the advent of Low Power Wide Area Network (LPWAN) wireless technologies allowed to extend the concept to gas and water distribution. However, these battery-supplied meters must ensure an operating lifetime longer than 10 years without any maintenance, thus leading to battery oversizing. This work focuses on LoRaWAN and proposes an innovative adaptive strategy for equalizing the message time duration in order to maximize the battery exploitation. A simulator has been purposely designed to evaluate the performance in a real-world scenario, considering a node density of hundreds of nodes per square km. The simulation results demonstrate that a better exploitation of the battery is possible, ensuring an increase by 10 times of the amount of the amount of useful user data bytes transferred by meters. © 2020 IEEE.

Quantum reading refers to the task of reading out classical information stored in a read-only memory device. In any such protocol, the transmitter and receiver are in the same physical location, and the goal of such a protocol is to use these devices (modeled by independent quantum channels), coupled with a quantum strategy, to read out as much information as possible from a memory device, such as a CD or DVD. As a consequence of the physical setup of quantum reading, the most natural and general definition for quantum reading capacity should allow for an adaptive operation after each call to the channel, and this is how we define quantum reading capacity in this paper. We also establish several bounds on quantum reading capacity, and we introduce an environment-parameterized memory cell with associated environment states, delivering second-order and strong converse bounds for its quantum reading capacity. We calculate the quantum reading capacities for some exemplary memory cells, including a thermal memory cell, a qudit erasure memory cell, and a qudit depolarizing memory cell. We finally provide an explicit example to illustrate the advantage of using an adaptive strategy in the context of zero-error quantum reading capacity., SCOPUS: ar.j, info:eu-repo/semantics/published

The world airport network (WAN) is one of the networked infrastructures that shape today's economic and social activity, so its resilience against incidents affecting the WAN is an important problem. In this paper, the robustness of air route networks is extended by defining and testing several heuristics to define selection criteria to detect the critical nodes of the WAN. In addition to heuristics based on genetic algorithms and simulated annealing, custom heuristics based on node damage and node betweenness are defined. The most effective heuristic is a multi-attack heuristic combining both custom heuristics. Results obtained are of importance not only for advance in the understanding of the structure of complex networks, but also for critical node detection., Peer Reviewed, Postprint (author's final draft)

The reliability of transit modes is a crucial issue to guarantee their competitiveness and attractiveness. Experience shows that buses covering busy lines with short headways tend to arrive irregularly at their stops, often in bunches and therefore remarkably affecting the service. Hence, this work presents a stochastic model capable of representing the operational activity of a bus transit network and the service disruptions which eventually end up causing deviations from desired schedule. At the same time, the model is tested on an ideal route as a decision making tool.

Questions: The link between the carbon composition of aquatic plants and (1) plant strategies and (2) habitat nutrient availability has received little attention. We tested whether three aquatic species belonging to the three adaptive strategies defined by Grime (ruderal, stress tolerant and competitive) had contrasting carbon allocation patterns, and if these patterns varied in the same way between populations distributed along a gradient of habitat nutrient content. Location: Wetlands in the northern Rhône River Basin, France. Methods: The three species were sampled in 17 wetlands along a gradient of nutrient content in the northern Rhône River Basin. In each population sampled, we measured plant water content, C/N ratio, structural compounds (lignin and structural polysaccharides) and storage compounds (free sugars and starch) in two seasons (spring and autumn 2012). Results: The stress-tolerant species had higher content of structural compounds than the competitive and ruderal species. The content of storage compounds was higher in the competitive and stress-tolerant species compared to the ruderal species. Allocation of carbon compounds varied with habitat nutrient content in different ways for the three species, suggesting contrasting plasticities, possibly linked to plant strategy. Conclusion: Plant strategies and habitat nutrient content are likely key drivers in plant carbon allocation and should be taken into account when studying interactions between habitat and plant quality.

A spectral method for kinetic plasma simulations based on the expansion of the velocity distribution function in a variable number of Hermite polynomials is presented. The method is based on a set of non-linear equations that is solved to determine the coefficients of the Hermite expansion satisfying the Vlasov and Poisson equations. In this paper, we first show that this technique combines the fluid and kinetic approaches into one framework. Second, we present an adaptive strategy to increase and decrease the number of Hermite functions dynamically during the simulation. The technique is applied to the Landau damping and two-stream instability test problems. Performance results show 21% and 47% saving of total simulation time in the Landau and two-stream instability test cases, respectively., QC 20151202

Проаналізовано сучасний стан технічного обслуговування мобільної сільськогосподарської техніки (МСГТ) увага зосереджена на транспортних засобах в сільськогосподарському виробництві. З’ясовано передумови переходу з планово-запобіжної стратегії на альтернативні, які забезпечують необхідний рівень експлуатаційної надійності. Сформульовано основні завдання технічної експлуатації, спрямовані на підтримання справного технічного стану МСГТ. Виявлено, що технічна діагностика займає головне місце у встановленні діагнозу і рівня технічно справного стану МСГТ, наведено схему етапів прогнозування її технічного стану. Встановлено, що на базі прогнозної інформації за допомогою діагностики і методів інформаційної теорії стає можливим перехід від планово-запобіжної до адаптивної стратегії, яка найбільше пристосовує до технічний стан МСГТ до умов її функціонування. Така стратегія є гнучкою в управлінні технічним станом МСГТ та забезпечує максимальну роботоздатність МСГТ при мінімальних витратах. Analyzed the modern state of the maintenance service the mobile of agricultural machinery. Attention basically focused on vehicles in agricultural production. It was found prerequisites of transition from plannedpreventive strategies to alternative which provide a given level of operational reliability. This is the first of all adaptive strategy that is based on the monitoring of technical condition diagnostics systems. Formulated tasks of technical operation designed to maintain good technical condition the mobile agricultural machinery. It was found that ensure maximum of operational reliability is a high priority in the technical operation of a modern market economy.For introduction adaptive maintenance strategy must be consider the following: the use of onboard diagnostic systems enables better monitoring of technical condition; Information technologies provide fast calculations of various indicators of diagnostic information, and necessary to consider individual performance technical co

Tuning compilations is the process of adjusting the values of a compiler options to improve some features of the final application. In this paper, a strategy based on the use of a genetic algorithm and a multi-objective scheme is proposed to deal with this task. Unlike previous works, we try to take advantage of the knowledge of this domain to provide a problem-specific genetic operation that improves both the speed of convergence and the quality of the results. The evaluation of the strategy is carried out by means of a case of study aimed to improve the performance of the well-known web server Apache. Experimental results show that a 7.5% of overall improvement can be achieved. Furthermore, the adaptive approach has shown an ability to markedly speed-up the convergence of the original strategy.

Tuning compilations is the process of adjusting the values of a compiler options to improve some features of the final application. In this paper, a strategy based on the use of a genetic algorithm and a multi-objective scheme is proposed to deal with this task. Unlike previous works, we try to take advantage of the knowledge of this domain to provide a problem-specific genetic operation that improves both the speed of convergence and the quality of the results. The evaluation of the strategy is carried out by means of a case of study aimed to improve the performance of the well-known web server Apache. Experimental results show that a 7.5% of overall improvement can be achieved. Furthermore, the adaptive approach has shown an ability to markedly speed-up the convergence of the original strategy.

The treatment period over which radiation therapy is administered extends over several weeks. Since tumor shrinkage in response to radiation therapy and weight loss due to radiation-induced mucositis may impact on the dose distribution in both target and organ at risk in patients with head and neck cancer, the anatomical changes of tumor and neck volumes during this period should be taken into consideration. We investigated the anatomical changes that occurred in the target and normal structure of the neck during radiation therapy for pharyngeal cancer, and evaluated the necessity of an adaptive strategy. Ten patients with pharyngeal cancer who underwent radical chemoradiation therapy using 3-dimensional conformal radiation therapy RT (66-70 Gy in 33-35 fractions) between April 2009 and September 2010 were enrolled in the study. Patients underwent CT scans every week during their course of treatment. We analyzed the CT data in the radiation treatment planning system and measured changes of tumor, organ at risk, and neck volume. Gross tumor volume (GTV) was rapidly reduced by 28% of the original volume on average in the first 3 weeks. The right and left submandibular glands volume decreased to 70% and 63% of their initial volumes on average, respectively. The volume of the neck in the radiation fields decreased to 89% of its initial volume on average by the sixth week mainly caused by body weight loss due to acute radiation morbidity. Considerable anatomical change in the radiation filed that will affect dose distribution of the target and organ at risk was observed during radiation therapy for head and neck cancer.

A methodology to analyze impact, vulnerability and adaptation to climate change in conjunctive-use systems at basin scale is presented. Based on the value obtained for various indices under possible future scenarios (indices obtained from the results of a system management model), a systematic procedure is presented to identify problems and solutions to adapt to climate change effects. The future hydrological scenarios to be analyzed can be approached by starting from the historical series available for the system and taking into account the changes expected in the key statistics of the series. A method to predict the expected changes in the key statistics using the results of previous climate change studies in the area has been developed. A " downscaling" procedure is proposed to translate the climatic variations into results on a basin scale. The methodology has been applied to the case study of the Serpis River Basin (Eastern Spain). © 2011 Elsevier B.V.

This paper presents an adaptive robust predictive current control (RPCC) for grid-connected three-phase inverters that exhibit zero steady-state current error. The error correction is achieved by means of an adaptive strategy that works in parallel with the deadbeat algorithm, therefore preserving the typical fast response of the predictive law. The resulting control adapts to any particular L or LCL filter by estimation of the resistive part of the filter. As a variety of the RPCC class of control, it offers the best tradeoff between robustness and speed. © 2009 IEEE.

Data-intensive applications are becoming increasingly common in Grid environments. These applications require enormous volume of data for the computation. Most conventional meta-scheduling approaches are aimed at computation intensive application and they do not take data requirement of the applications into account, thus leading to poor performance. Efficient scheduling of data-intensive applications in Grid environments is a challenging problem. In addition to process utilization and average turnaround time, it is important to consider the worst-case turnaround time in evaluating the performance of Grid scheduling strategies. In this paper, we propose an adaptive scheduling scheme that takes into account both the computational requirements and the data requirements of the jobs while making scheduling decisions. In our scheme, data transfer is viewed in par with computation and explicitly considered when scheduling. Jobs are dispatched to the sites that are optimal in terms of both data transfer time and computation time. In addition, our scheme overlaps a job's data transfer time with its own queuing time and other jobs' computation time as much as possible. Trace-based simulations show that the proposed scheme can gain significant performance benefits for data-intensive jobs. © 2009 IEEE.

Data-intensive applications are becoming increasingly common in Grid environments. These applications require enormous volume of data for the computation. Most conventional meta-scheduling approaches are aimed at computation intensive application and they do not take data requirement of the applications into account, thus leading to poor performance. Efficient scheduling of data-intensive applications in Grid environments is a challenging problem. In addition to process utilization and average turnaround time, it is important to consider the worst-case turnaround time in evaluating the performance of Grid scheduling strategies. In this paper, we propose an adaptive scheduling scheme that takes into account both the computational requirements and the data requirements of the jobs while making scheduling decisions. In our scheme, data transfer is viewed in par with computation and explicitly considered when scheduling. Jobs are dispatched to the sites that are optimal in terms of both data transfer time and computation time. In addition, our scheme overlaps a job's data transfer time with its own queuing time and other jobs' computation time as much as possible. Trace-based simulations show that the proposed scheme can gain significant performance benefits for data-intensive jobs. © 2009 IEEE.

Data-intensive applications are becoming increasingly common in Grid environments. These applications require enormous volume of data for the computation. Most conventional meta-scheduling approaches are aimed at computation intensive application and they do not take data requirement of the applications into account, thus leading to poor performance. Efficient scheduling of data-intensive applications in Grid environments is a challenging problem. In addition to process utilization and average turnaround time, it is important to consider the worst-case turnaround time in evaluating the performance of Grid scheduling strategies. In this paper, we propose an adaptive scheduling scheme that takes into account both the computational requirements and the data requirements of the jobs while making scheduling decisions. In our scheme, data transfer is viewed in par with computation and explicitly considered when scheduling. Jobs are dispatched to the sites that are optimal in terms of both data transfer time and computation time. In addition, our scheme overlaps a job's data transfer time with its own queuing time and other jobs' computation time as much as possible. Trace-based simulations show that the proposed scheme can gain significant performance benefits for data-intensive jobs. © 2009 IEEE.

Traffic congestion on urban road networks has been recognized as one of the most serious problems with which modern cities are confronted. It is generally anticipated that Dynamic Route Guidance Systems (DRGS) will play an important role in reducing urban traffic congestion and improving traffic flows and safety. One of the most critical issues in designing these systems is in the development of optimal routing strategies that would maximize the benefits to overall system as well as individual users. Infrastructure based DRGS have advantage of pursuing system optimal routing strategy, which is more essential under abnormal traffic conditions such as non-recurrent congestion and natural disaster. However user compliance could be a problem under such a strategy, particularly when some of equipped drivers are urged not to choose minimum travel time path for the sake of improving the total network travel time. On the other hand, In-vehicle based DRGS can utilize the user-specified route selection criteria to avoid "Braess Paradox" under normal traffic conditions. However, it may be of little use under abnormal traffic conditions and high DRGS market penetration. In conducting the comparative analysis between system optimal strategy and user equilibrium strategy, significant differences were found within the mid-range traffic demand. The maximum total travel time difference occurs when the level of traffic demand is half of the system capacity. At this point, system optimal route guidance strategy can save more than 11% of the total travel time of user equilibrium route guidance strategy. The research proposes an adaptive routing strategy as an efficient dynamic route guidance under non-recurrent traffic congestion. Computation results show that there is no need to implement system optimal routing strategy at the initial stage of the incident. However, it is critical to use system optimal routing strategy as freeway and arterial are getting congested and the queue delay

Tato práce se zabývá problémem kanadského cestujícího (CTP), který se dá definovat jako problém hledání nejkratší cesty ve stochastickém prostředí. V rešeršní části práce je zpracován přehled typů tohoto problému a k nim existujících metod řešení. V dalších částech se práce zaměřuje na stochastickou variantu CTP (SCTP), pro kterou jsou vybrané metody řešení (strategie) probrány více do hloubky. Zároveň jsou prezentovány i originální strategie pojmenované UCTO2 a UCTP. Dále se práce zabývá popisem okenní aplikace implementované v jazyku Java. Ta byla vyvinuta pro ověření a otestování správné funkce vybraných strategií. Nakonec jsou vyhodnoceny provedené experimenty, a z nich plynoucí srovnání vybraných strategií., This thesis deals with Canadian traveller problem (CTP), which can be defined as the shortest path problem in a stochastic environment. The overview of different CTP variants is presented in theoretical part of this thesis, as well as known solutions to these variants. In the next parts, the thesis focuses on the stochastic variation of CTP (SCTP). For this variant chosen solutions (strategies) are discussed more in depth. At the same time, the original strategies named UCTO and UCTP are presented. Further, the thesis deals with the description of a window application implemented in Java, which has been developed to validate and test the functionality of selected strategies. The final part contains experiments and comparison of selected strategies.

Táto práca sa zaoberá riešením problému kanadského cestujúceho. Predstavme si, že cestujúci má mapu, na ktorej je každá cesta spojená s časom potrebným na jej prejdenie. Táto mapa však nemusí byť úplne spoľahlivá a na niektorých úsekoch môže byť tamojšími podmienkami cesty spôsobené, že čas na prejdenie daného úseku bude dlhší, alebo že priechod bude nemožný. Práca sa zaoberá prehľadom typov tohto problému a ich riešeniami. Ďalej sa zaoberá popisom dvoch aplikácií implementovaných v jazyku Python, ktoré slúžia na overenie daných stratégií riešenia problému. Na záver sú vyhodnotené dané experimenty a porovnaná efektivita daných stratégií., This thesis deals with Canadian traveller problem. Imagine a traveller that have a map on which every road is associated with time that is needed to get through this road. Hovewer, this map may not be totally reliable, and the time needed to pass through on some of the roads may be different due to bad road conditions, or the pass will be impossible. This thesis deals with type overview of this problem and the solutions. Further, the thesis deals with the description of two applications implemented in Python, which serves on verification of the strategies. The final part contains experiments and comparison of effectiveness of selected strategies.

Táto práca sa zaoberá riešením problému kanadského cestujúceho. Predstavme si, že cestujúci má mapu, na ktorej je každá cesta spojená s časom potrebným na jej prejdenie. Táto mapa však nemusí byť úplne spoľahlivá a na niektorých úsekoch môže byť tamojšími podmienkami cesty spôsobené, že čas na prejdenie daného úseku bude dlhší, alebo že priechod bude nemožný. Práca sa zaoberá prehľadom typov tohto problému a ich riešeniami. Ďalej sa zaoberá popisom dvoch aplikácií implementovaných v jazyku Python, ktoré slúžia na overenie daných stratégií riešenia problému. Na záver sú vyhodnotené dané experimenty a porovnaná efektivita daných stratégií., This thesis deals with Canadian traveller problem. Imagine a traveller that have a map on which every road is associated with time that is needed to get through this road. Hovewer, this map may not be totally reliable, and the time needed to pass through on some of the roads may be different due to bad road conditions, or the pass will be impossible. This thesis deals with type overview of this problem and the solutions. Further, the thesis deals with the description of two applications implemented in Python, which serves on verification of the strategies. The final part contains experiments and comparison of effectiveness of selected strategies.

Tato práce se zabývá problémem kanadského cestujícího (CTP), který se dá definovat jako problém hledání nejkratší cesty ve stochastickém prostředí. V rešeršní části práce je zpracován přehled typů tohoto problému a k nim existujících metod řešení. V dalších částech se práce zaměřuje na stochastickou variantu CTP (SCTP), pro kterou jsou vybrané metody řešení (strategie) probrány více do hloubky. Zároveň jsou prezentovány i originální strategie pojmenované UCTO2 a UCTP. Dále se práce zabývá popisem okenní aplikace implementované v jazyku Java. Ta byla vyvinuta pro ověření a otestování správné funkce vybraných strategií. Nakonec jsou vyhodnoceny provedené experimenty, a z nich plynoucí srovnání vybraných strategií., This thesis deals with Canadian traveller problem (CTP), which can be defined as the shortest path problem in a stochastic environment. The overview of different CTP variants is presented in theoretical part of this thesis, as well as known solutions to these variants. In the next parts, the thesis focuses on the stochastic variation of CTP (SCTP). For this variant chosen solutions (strategies) are discussed more in depth. At the same time, the original strategies named UCTO and UCTP are presented. Further, the thesis deals with the description of a window application implemented in Java, which has been developed to validate and test the functionality of selected strategies. The final part contains experiments and comparison of selected strategies.

Tato práce se zabývá problémem kanadského cestujícího (CTP), který se dá definovat jako problém hledání nejkratší cesty ve stochastickém prostředí. V rešeršní části práce je zpracován přehled typů tohoto problému a k nim existujících metod řešení. V dalších částech se práce zaměřuje na stochastickou variantu CTP (SCTP), pro kterou jsou vybrané metody řešení (strategie) probrány více do hloubky. Zároveň jsou prezentovány i originální strategie pojmenované UCTO2 a UCTP. Dále se práce zabývá popisem okenní aplikace implementované v jazyku Java. Ta byla vyvinuta pro ověření a otestování správné funkce vybraných strategií. Nakonec jsou vyhodnoceny provedené experimenty, a z nich plynoucí srovnání vybraných strategií., This thesis deals with Canadian traveller problem (CTP), which can be defined as the shortest path problem in a stochastic environment. The overview of different CTP variants is presented in theoretical part of this thesis, as well as known solutions to these variants. In the next parts, the thesis focuses on the stochastic variation of CTP (SCTP). For this variant chosen solutions (strategies) are discussed more in depth. At the same time, the original strategies named UCTO and UCTP are presented. Further, the thesis deals with the description of a window application implemented in Java, which has been developed to validate and test the functionality of selected strategies. The final part contains experiments and comparison of selected strategies.

Táto práca sa zaoberá riešením problému kanadského cestujúceho. Predstavme si, že cestujúci má mapu, na ktorej je každá cesta spojená s časom potrebným na jej prejdenie. Táto mapa však nemusí byť úplne spoľahlivá a na niektorých úsekoch môže byť tamojšími podmienkami cesty spôsobené, že čas na prejdenie daného úseku bude dlhší, alebo že priechod bude nemožný. Práca sa zaoberá prehľadom typov tohto problému a ich riešeniami. Ďalej sa zaoberá popisom dvoch aplikácií implementovaných v jazyku Python, ktoré slúžia na overenie daných stratégií riešenia problému. Na záver sú vyhodnotené dané experimenty a porovnaná efektivita daných stratégií., This thesis deals with Canadian traveller problem. Imagine a traveller that have a map on which every road is associated with time that is needed to get through this road. Hovewer, this map may not be totally reliable, and the time needed to pass through on some of the roads may be different due to bad road conditions, or the pass will be impossible. This thesis deals with type overview of this problem and the solutions. Further, the thesis deals with the description of two applications implemented in Python, which serves on verification of the strategies. The final part contains experiments and comparison of effectiveness of selected strategies.

Статья посвящена особенностям приспособления современных учителей к негативным организационным и макросоциальным факторам. Основываясь на концепции социальной апатии и проведении фокус-группового и нарративных интервью с педагогами г. Томска, выявляются смыслы и стратегии адаптации учителей к условиям современной системы образования., The aim of the study was to identify positive strategies for teacher adaptation to the negative organizational and macrosocial factors. The methodology was based on the concept of the social apathy. A focus-group interview method was used in order to recognize the meanings and ways of interpreting teachers' experience that encourage them to continue working or to leave the profession.