Metabolomics is a post genomic field of research concerned with the study of low molecular weight compounds within a biological system permitting the investigation of the metabolite differences between natural and perturbed systems (such as cells, organs and tissues). Rapid identification and discrimination of biological samples based upon metabolic differences and physiological status in microbiology, mammalian systems (particularly for disease diagnosis), plants and food science is highly desirable. Volatile organic compound (VOC) profiling is a novel area of research where the composition of the VOCs emitted by the biological samples can be correlated to its origin and physiological status. The aim of this project was to investigate the applicability of VOC profiling as a potential complementary tool within metabolomics.In this project the discrimination of bacteria using a novel gas phase separation method was investigated and the development of VOC-based profiling tools for the collections of VOCs emitted from biological samples was also studied. The optimisation and validation of a high throughput method for VOC analysis was achieved and this was used to assess wound healing.VOC metabolite profiling was further extended to the discrimination of S. typhimurium contaminated meat; the study was conducted in parallel with metabolite profiling analysis for the analysis of non-volatile small molecules. Finally, enhanced vibrational spectroscopic techniques were applied to the characterisation and screening of dye molecules in contaminated foodstuffs using Raman spectroscopy. This thesis clearly demonstrates that VOC metabolic profiling is a complementary tool within the metabolomics toolbox, one of its great attractions is that it permits the characterisation of biological samples in a rapid and non-invasive manner. The technique provides detailed chemical information regarding the VOC composition present above the headspace of the sample and can be used to understand its physiological status and biological origin. VOCs metabolite profiling will become a valuable tool for non-invasive analysis of many biological systems. Raman spectroscopy is a sensitive and non-destructive technique which can generate detailed chemical and structural information regarding the analyte under investigation with little or no sample preparation needed. The effect of the weak Raman signal can be significantly amplified by coupling the analyte molecule to surfaces of nanoparticles and demonstrated that it is ideal for analysing aqueous dye solutions in a quantitative manner.

The goal of this master's thesis is appreciation actual estate of intradepartmental administration in company Minerva Boskovice and concept unprecedented solution. Dissertation contain analyze and concept of implementation based on present available information systems.

Master´s thesis focuses on company´s internal documentation and Document Management Systems. It presents a proposal for the project of SharePoint implementation in the selected organisational unit of a company, using the Cloud Computing technology. An assessment of risks, resulted from the project and especially from the Cloud Computing, leads to the essential part of this paper, to the proposal of security arrangements and solutions. The arrangements will be advised to the organisational unit considering the economic cost comparison with potential risks.

Increased competition by new market entries has long been studied with defensive marketing strategies (DMS) being identified as one of the ways of combating a new competitor. There is limited research concerning the Swedish eCommerce business landscape and its competitive environment and adding the fact that Amazon, in late 2020, launched in Sweden this study aims to outline what DMS Swedish eCommerce businesses have implemented as a result of Amazon’s entry. Qualitative semi-structured interviews were held with respondents in key positions of firms, where the individual either was working with or consulting eCommerce businesses. The findings suggested that, in its generality, that no new DMS has been implemented as a result of the market entry. Amazon is expressed to have a weak position and lack in several aspects compared to Swedish eCommerce. The biggest fear lies in Amazon’s future with many potential “strong cards” left to play in their sleeve. However, the entry of Amazon increased the focus of some areas, as they were seen to become more important for survival and competing.

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The goal of this thesis is to evaluate travelers' experience with Highway Advisory Radio (HAR) and Citizens' Band Radio Advisory System (CBRAS) technologies on both Florida Interstate Highway system (FIH) and the Florida Turnpike Enterprise (FTE) toll roads. To achieve this goal, two different survey tools were used. The first tool is a random digit dialing phone survey known as CATI (Computer-Assisted Telephone Interviewing). The second tool is a field survey that intercepts travelers at the Florida Turnpike Enterprise (FTE) service plazas and the Florida Interstate Highway (FIH) rest areas. HAR and CBRAS are traditional components of the Advanced Traveler Information Systems (ATIS). This thesis pays special attention to the effectiveness of HAR and CBRAS in improving travelers' experience. Feedback to analyze these two technologies was collected via a telephonic survey and a field survey. Two different field surveys (one for HAR and one for CBRAS) were designed and implemented to obtain feedback on these technologies. The field survey for CBRAS is unique and has never been done before for this purpose. A sample size of 1000 HAR surveys was collected through the CATI phone survey. Field surveys were collected at five locations across the state, including central, southeast, and southwest regions of Florida. The HAR field survey sample size was 1610 and the CBRAS field survey sample size was 613. All field surveys were conducted by UCF students at each of the five locations, over a 13-week data collection period. The HAR messages were designed to alert drivers of any adverse roadway traffic or weather conditions. The CBRAS is limited to truck drivers with the closed system radio pre-installed in their vehicles. However, truck drivers were also asked some questions on HAR if they do not use CBRAS. Basic statistical analysis was used to determine a number of performance indicators which include system's use and awareness, usability of provided information, route diversion, and travelers' demographics. In addition, the two HAR phone and field samples were combined together and examined using a decision tree model. Target questions were selected from the survey to build the tree network. The tree model aimed at identifying trends between categorical differences of travelers with respect to specific questions. Understanding travelers' satisfaction with HAR is critical to knowing its benefits. The ending results indicated that both basic statistical analysis and the decision tree model are in agreement. A comparison between HAR phone and field surveys indicates the following. Travelers interviewed for the HAR field survey were more aware of the HAR than travelers surveyed by phone. A small portion of the surveyed samples used HAR (22% and this was consistent between the phone and the field surveys). Also, 80% or more were satisfied with HAR for both phone and field samples and the majority (85% or more) supported its continuation as an indication of willingness to use it in the future, especially in emergency conditions. In terms of the types of messages they want to hear from HAR, traffic congestion was the most common. Dynamic Message Signs (DMS) were the most preferred source of travel information and were the alternative for HAR, if HAR gets terminated. This was followed by smartphone applications which received twice as much support from field surveyed travelers (28%) when compared to phone surveyed travelers (15%). The CATI Phone Survey was biased towards elderly people (60% of the sample) and mainly females (58%) that use the FTE roadway system. Users satisfied with the system are those who only use these roadways once per week or less. The survey ultimately shows that travelers rely on modern modes of obtaining traffic information than traditional ones, such as HAR. DMS, and smart phone applications are leading communication tools among all type of travelers. The HAR field survey was less biased with respect to age and gender distribution (56% were under 50 and 62% were males). Both surveys indicate that the sample is well educated (about 60% have an associate degree or higher). CBRAS serves a small segment of commercial truck drivers (only 12% out of 613 used CBRAS). However, this small segment used it heavily (84% used it sometimes, often, or always). And 92% of CBRAS users were satisfied or strongly satisfied with it. CBRAS was used mostly for route divergence, with 72% of the drivers relying on it for this purpose. Truck drivers who never used CBRAS (88% of the sample) were asked questions about HAR. Only 27% of them used HAR and 57% of these used it sometimes, often, or always with 72% of the truck users being satisfied with HAR compared to the 92% satisfied with CBRAS. The most common complaint about HAR by truck drivers was that it is not easy to access or understand. Based on responses of truck drivers for both HAR and CBRAS field surveys above, it seems that GPS navigation was the most preferred source of travel information (28%). In addition to the basic statistics, a decision tree model, using SAS Enterprise Miner was performed. The statistical analysis results indicated satisfaction of travelers. The decision tree model was used to predict and profile responses to all answered questions that each survey shared. Training data was included in the model and the model was able to leverage the questions. Results of the decision tree model predicted high user satisfaction rates. Analyses of the three implemented surveys show that HAR and CBRAS technologies are not used by a large proportion of travelers, but their users are typically satisfied with these technologies. A small portion of the surveyed sample of truck drivers uses CBRAS but they use it heavily and were very satisfied with it. The travelers' satisfaction level with HAR was high. The HAR and CBRAS systems are in the middle of a heated competition lead by digital communication, it may be a sign of the time to create HAR/CBRAS smart phone applications for the longevity of these traditional technologies.

Researchers at the University of Central Florida (UCF) have been working during the past few years on different strategies to improve freeway safety in real-time. An ongoing research at UCF has investigated crash patterns that occurred on a stretch of Interstate-4 located in Orlando, FL and created statistical models to predict in real-time the likelihood of a crash in terms of time and space. The models were then tested using PARAMICS micro-simulation and different strategies that would reduce the risk of crashes were suggested. One of the main recommended strategies was the use of Variable Speed Limits (VSL) which intervenes by reducing the speed upstream the segment of high risk and increasing the speed downstream. The purpose of this study is to examine the recommendations reached by the micro-simulation using the UCF driving simulator. Drivers' speed behavior in response to changes in speed limits and different information messages are observed. Different scenarios that represent the recommendations from the earlier micro-simulation study and three different messages displayed using Variable Message Signs (VMS) as an added measure to advice drivers about changes in the speed limit were created. In addition, abrupt and gradual changes in speed were tested against the scenarios that maintained the speed limit constant or did include a VSL or VMS in the scenarios' design (base case). Dynamic congestion was also added to the scenarios' design to observe drivers' reactions and speed reductions once drivers approached congestion. A total of 85 subjects were recruited. Gender and age were the controlling variables for the subjects' recruitment. Each of the subjects drove 3 out of a total of 24 scenarios. In addition, a survey was conducted and involved hypothetical questions, including knowledge about VMS and VSL, and questions about their driving behavior. The survey data were useful in identifying the subjects' compliance with the speed limit and VSL/VMS acceptance. Two statistical analytical techniques were performed on the data that were collected from the simulator: ANOVA and PROC MIXED. The ANOVA test was used to investigate if the differences in speed and reaction distances between subjects were statistically significant for each sign compared to the base case. The PROC MIXED analysis was used to investigate the differences of all scenarios (24x24) based on the spot speed data collected for each driver. It was found from the analyses that drivers follow better the message displayed on VMS that informs them that the speed is changing, whether it is or not, strictly enforced as opposed to providing the reason for change or no information. Moreover, an abrupt change in speed produced immediate results; however both abrupt and gradual changes in speed produced the same reduction in speed at the target zone. It was also noticed that most drivers usually drive 5 mph above the speed limit, even though in the survey analysis the majority of them stated that they drive in compliance with the speed limit or with the flow of traffic. This means that if a modest speed reduction of 5 mph is requested they will ignore it, but if a 10 mph reduction is recommended they will reduce the speed by at least 5 mph. Consequently, it was noticed that drivers arrived at the congestion zone with a slower speed than the base speed limit due to the combination of VMS and VSL signage. By having drivers approaching congestion with a slower speed, potential rear-end crashes could be avoided. Comparing the two genders indicated that females are more likely to follow the VMS's recommendations to reduce the speed. Also females in general drive above the speed limit between 2 mph and 3 mph, while males drive above the speed limit between 5 mph and 8 mph. From the analysis of the age factor, it was concluded that drivers from the 16-19 age group drive faster and drivers from the 45 and above age group drive slower, than the drivers from the other groups. In general, all drivers reduced and/or increased their speed accordingly when a VMS and/or VSL was present in the scenario advising for this change in the speed limit. The investigations conducted for this thesis proved that the recommendations suggested previously based on the crash risk model and micro-simulation (Abdel-Aty et al., 2006) aid drivers in reducing their speed before they approach a segment of high risk and by doing so reduce the likelihood of a crash. Finally, the real-time safety benefits of VMS and VSL should be continuously evaluated in future studies.

The purpose of this thesis was to evaluate the impact of dynamic message signs (DMS) on the Orlando-Orange County Expressway Authority (OOCEA) toll road network using the Post-Deployment DMS Survey analysis. DMS are electronic traffic signs used on roadways to give travelers information about travel times, traffic congestion, accidents, disabled vehicles, AMBER alerts, and special events. The particular DMS referred to in this study are large rectangular signs installed over the travel lanes and these are not the portable trailer mount signs. The OOCEA has added twenty-nine fixed DMS to their toll road network from 2006-2008. At the time of the post-deployment survey, a total of twenty-nine DMS were up and running on the OOCEA toll road network. Since most of the travelers on the OOCEA toll roads were from Orange, Osceola, and Seminole counties, this study was limited to these counties. This thesis documents the results for the post-deployment survey analysis. The instrument used to analyze the travelers' perception of DMS was a survey that utilized computer aided telephone interview. The post-deployment survey was conducted during the month of May, 2008. Questions pertaining to the acknowledgement of DMS on the OOCEA toll roads, satisfaction with travel information provided on the network, formatting of the messages, satisfaction with different types of messages, diversion questions (Revealed and Stated preferences), and classification/socioeconomic questions (such as age, education, most traveled toll road, county of residence, and length of residency) were asked to the respondents. This thesis is using results of the multinomial logit model for diversion of traffic. This model takes into account the different diversion decisions from the post development survey (stay vs. divert all the way vs. divert and come back vs. abandon trip) and explains the differences in the diversion behavior. Drivers that use SunPass or Epass tend to stay on the toll road during unexpected congestion. Frequent SR 408 users are more likely to divert and stay off the toll road and frequent SR 417 users are more likely to divert and get back on the toll road. Drivers whose stated preference was to divert off the toll road were more likely to do the same in the real world. However, not too many of the respondents were likely to abandon their trips in the real world even if they said they would in a hypothetical congestion scenario. Users of 511 were more likely to divert and get back on the toll road or abandon their trips due to unexpected congestion. OOCEA can use this study to concentrate on keeping their toll roads more attractive during unexpected congestion to keep drivers from diverting all the way or abandoning their trips. For example, better incident management in clearing accidents more efficiently (thereby decreasing delay) and encouraging the use of SunPass or EPass could help drivers stay than divert or abandon their trip. This thesis also used ordered logit model for satisfaction. This model explains the levels of magnitude of satisfaction with traveler information on OOCEA toll roads. Drivers who acquired traveler information from DMS were less likely to be dissatisfied with traveler information provided on toll roads than other respondents. Drivers who were satisfied with accuracy and information on hazard warnings on DMS were more likely to be satisfied with information provided on toll roads than other respondents. This thesis provides a microscopic insight on the driver behavior on toll roads. This thesis expands the diversion and satisfaction models from previous studies in a way that OOCEA can identify specific groups of drivers related to a given response behavior (i.e., diverts off toll roads or dissatisfied with traveler information). Such analysis can be conducted in the future in the same study area or replicated in other areas to quantify the effects of individual and choice related attributes on choice behavior.

This dissertation proposes a Dynamic Message Signs (DMS) diversion control system based on principles of existing Advanced Traveler Information Systems and Advanced Traffic Management Systems (ATMS). The objective of the proposed system is to alleviate total corridor traffic delay by choosing optimized diversion rate and alternative road signal-timing plan. The DMS displays adaptive messages at predefined time interval for guiding certain number of drivers to alternative roads. Messages to be displayed on the DMS are chosen by an on-line optimization model that minimizes corridor traffic delay. The expected diversion rate is assumed following a distribution. An optimization model that considers three traffic delay components: mainline travel delay, alternative road signal control delay, and the travel time difference between the mainline and alternative roads is constructed. Signal timing parameters of alternative road intersections and DMS message level are the decision variables; speeds, flow rates, and other corridor traffic data from detectors serve as inputs of the model. Traffic simulation software, CORSIM, served as a developmental environment and test bed for evaluating the proposed system. MATLAB optimization toolboxes have been applied to solve the proposed model. A CORSIM Run-Time-Extension (RTE) has been developed to exchange data between CORSIM and the adopted MATLAB optimization algorithms (Genetic Algorithm, Pattern Search in direct search toolbox, and Sequential Quadratic Programming). Among the three candidate algorithms, the Sequential Quadratic Programming showed the fastest execution speed and yielded the smallest total delays for numerical examples. TRANSYT-7F, the most credible traffic signal optimization software has been used as a benchmark to verify the proposed model. The total corridor delays obtained from CORSIM with the SQP solutions show average reductions of 8.97%, 14.09%, and 13.09% for heavy, moderate and light traffic congestion levels respectively when compared with TRANSYT-7F optimization results. The maximum model execution time at each MATLAB call is fewer than two minutes, which implies that the system is capable of real world implementation with a DMS message and signal update interval of two minutes.

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