Two-way left-turn lane (TWLTL) is one of the common median treatments on the roadway. It is found that a number of crashes reported in Florida State are related to TWLTLs. This research focused on evaluating the effect of TWLTLs on these crashes by using the statistical crash prediction model that can estimate the expected number of crashes on TWLTLs. The crash database for analysis was extracted from the Florida Traffic Crash Database based on the TWLTL section list provided by FDOT and combined with some traffic characteristics. It consisted of totally 1688 sample sections within a three-year period from 1996 to 1998. Based on the crash database, distribution fittings for Poisson, Negative Binomial and Lognormal regression were conducted for average number of crashes. According to the results, statistical crash predictive model was developed to estimate the average number of crashes. Negative Binomial regression was applied with four variables, ADT, access density, posted speed and number of lanes for the TWLTL sections. The regression parameters were estimated by using maximum likelihood method with statistical software. The findings of the analysis indicated that all of the variables adopted in the predictive model significantly affect the occurrence of crashes. And the average number of crashes increases with the increase of ADT, access density and number of lanes, while with the decrease of posted speed. After that, the goodness-of-fit of developed model was performed in term of Pearson's R-square and likelihood ratio index. The results showed that the Negative Binomial regression model could explain the relationship between the variables and the crash occurrence In the third part, an approach was developed to identify the TWLTL sections with safety concern. For an undivided roadway, the approach can be carried out to judge if the TWLTL is appropriate to be selected as the median treatment. During the process, the whole database was divided into six categories according to the posted speed and number of lanes. By adopting the selected percentile value from the distribution of average number of crashes for each category in the predictive model, the critical ADT values according to specific access density, number of lane and posted speed level for each category were calculated and tabulated. With the comparison of the actual ADT value and the critical ADT value, if the actual ADT is higher than the critical value, the TWLTL section is determined as the critical section, which means the TWLTL is not appropriate to be selected as the median treatment in this roadway section.

PlanetLab Server Manager je aplikace, která pomáhá uživatelům realizovat projekty zaměřené na vývoj aplikací pro distribuované sítě. Aplikace primárně umožňuje vyhledávání serverů podle jejich geografické polohy a umožňuje přístup na tyto servery a jejich vykreslení na mapě. Práce čtenáře seznámí se síťí PlanetLab a její infrastukturou. Dále popisuje aplikaci PlanetLab Server Manager (také známou jako plbmng) a identifikuje problémy v její aktuální verzi. Diplomová práce se zaměřuje na řešení identifikovaných problémů a specifikuje provedená vylepšení do aplikace. Také je v ní pomocí nově přidané funkcionality provedena analýza stavu sítě PlanetLab. Tato práce se zaměřuje na vylepšení stávající funkcionality tím, že je aplikace plně přepsána do jazyka Python 3. Kvůli stávající implementaci v jazyce Bash, jehož vlastnosti se od jazyka Python liší, bude nutné kompletně přeplánovat stávající funkce aplikace, aby bylo plně využito výhod jazyka Python. Aplikace je také rozšířena o možnosti filtrování serverů na základě jejich stavu a další vylepšení. Zdrojové kódy aplikace jsou dostupné na repozitáři GitHUB pod licencí MIT a dále je aplikace dostupná v repozitářích PyPI.