Estimation and prediction of average vehicle occupancies using traffic accident records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver’s age, and driver’s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Freeway travel time estimation and prediction using dynamic neural networks

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. ^ This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.^

Demographic effects of thatch harvest and implications for sustainable use of irapai palm (Lepidocaryum tenue, Mart.), by riverine communities in the Peruvian Amazon

Lepidocaryum tenue Mart. (Arecaceae) is a small, understory palm of terra firme forests of the western and central Amazon basin. Known as irapai, it is used for roof thatch by Amazonian peoples who collect its leaves from the wild and generate income from its fronds and articles fabricated from them. Increasing demand has caused local concern that populations are declining. Cultivation attempts have been unsuccessful. The purpose of this study was to investigate market conditions and quantify population dynamics and demographic responses of harvested and unharvested irapai growing near Iquitos, Peru. ^ Ethnobotanical research included participant surveys to determine movement of thatch tiles, called crisnejas, through Moronacocha Port. I also conducted a seed germination trial, and for four years studied five populations growing in communities with similar topography and soils but different land tenure and management strategies. Stage, survival, leaf production, and reproductive transitions were used to calculate ramet demographic rates and develop population projection matrices. ^ Weavers made an average of 20–30 crisnejas per day (90–130 leaves each), and earned US$0.09 to 0.70 each (US$1.80 to 21.00 per day). Average crisnejas per month sold per vendor was 2,955 with a profit range of US$0.05 to 0.32 per crisneja. Wholesalers worked with capital outlay from US$100 to 400, and an estimated ten to twenty vendors could be found at a given time. Consumers paid between US$0.23 to 1.20 per crisneja. Although differences in demographic rates by location existed, most were not significant enough to attribute to management. ^ After 60 months, mean seed germination rate was 19.5% in all media (37.9% in peat). Seedling survival was less than two percent after twelve months. Annual palm mortality was three percent, and occurred disproportionately in small (<50 cm) palms. Small palms grew more in height. Unharvested palms grew less than harvested palms. Large palms (≥50 cm) produced more leaves, were more likely to reproduce, and collectors harvested them more frequently. Reproductive potentials (sexual and asexual) were low. Population growth rates were greater than or not significantly different from 1.0, indicating populations maintained or increased in size. Current levels of irapai harvest appear sustainable. DNA analysis of stems and recruits is recommended to understand population composition and stage-specific asexual fecundity. ^

Variables affecting the collection and preservation of human scent components through instrumental and biological evaluations

In certain European countries and the United States of America, canines have been successfully used in human scent identification. There is however, limited scientific knowledge on the composition of human scent and the detection mechanism that produces an alert from canines. This lack of information has resulted in successful legal challenges to human scent evidence in the courts of law. ^ The main objective of this research was to utilize science to validate the current practices of using human scent evidence in criminal cases. The goals of this study were to utilize Headspace Solid Phase Micro Extraction Gas Chromatography Mass Spectrometry (HS-SPME-GC/MS) to determine the optimum collection and storage conditions for human scent samples, to investigate whether the amount of DNA deposited upon contact with an object affects the alerts produced by human scent identification canines, and to create a prototype pseudo human scent which could be used for training purposes. ^ Hand odor samples which were collected on different sorbent materials and exposed to various environmental conditions showed that human scent samples should be stored without prolonged exposure to UVA/UVB light to allow minimal changes to the overall scent profile. Various methods of collecting human scent from objects were also investigated and it was determined that passive collection methods yields ten times more VOCs by mass than active collection methods. ^ Through the use of polymerase chain reaction (PCR) no correlation was found between the amount of DNA that was deposited upon contact with an object and the alerts that were produced by human scent identification canines. Preliminary studies conducted to create a prototype pseudo human scent showed that it is possible to produce fractions of a human scent sample which can be presented to the canines to determine whether specific fractions or the entire sample is needed to produce alerts by the human scent identification canines. ^

Comparison of repeated and two non-repeated readings conditions on reading abilities of students with emotional and/or behavioral disabilities

Students with emotional and/or behavioral disorders (EBD)present considerable academic challenges along with emotional and/or behavioral problems. In terms of reading, these students typically perform one-to-two years below grade level (Kauffman, 2001). Given the strong correlation between reading failure and school failure and overall success (Scott & Shearer-Lingo, 2002), finding effective approaches to reading instruction is imperative for these students (Staubitz, Cartledge, Yurick, & Lo, 2005). This study used an alternating treatments design to comparethe effects of three conditions on the reading fluency, errors, and comprehension of four, sixth-grade students with EBD who were struggling readers. Specifically, the following were compared: (a) Repeated readings in which participants repeatedly read a passage of about 100-150 words, three times, (b) Non-repeated readings in which participants sequentially read an original passage of about 100-150 words once, and (c) Equivalent non-repeated readings in which participants sequentially read a passage of about 300-450 words, equivalent to the number of words in the repeated readings condition. Also examined were the effects of the three repeated readings practice trials per sessions on reading fluency and errors. The reading passage difficulty and length established prior to commencing were used for all participants throughout the standard phase. During the enhanced phase, the reading levels were increased 6 months for all participants, and for two (the advanced readers), the length of the reading passages was increased by 50%, allowing for comparisons under more rigorous conditions. The results indicate that overall repeated readings had the best outcome across the standard and enhanced phases for increasing readers’ fluency, reducing their errors per minute, and supporting fluency answers to literal comprehension questions correctly as compared to non-repeated and equivalent non-repeated conditions. When comparing nonrepeated and equivalent non-repeated readings,there were mixed results. Under the enhanced phases, the positive effects of repeated readings were more demonstrative. Additional research is needed to compare the effects of repeated and equivalent non-repeated readings across other populations of students with disabilities or varying learning styles. This research should include collecting repeated readings practice trial data for fluency and errors to further analyze the immediate effects of repeatedly reading a passage.

Xavier Zapata (FIU graduate student) collecting a groundwater sample, Taylor Slough

This material is based upon work supported by the National Science Foundation through the Florida Coastal Everglades Long-Term Ecological Research program under Cooperative Agreements #DBI-0620409 and #DEB-9910514. This image is made available for non-commercial or educational use only.

Design, fabrication, and evaluation of on-chip micro-supercapacitors

Due to the increasing demand for high power and reliable miniaturized energy storage devices, the development of micro-supercapacitors or electrochemical micro-capacitors have attracted much attention in recent years. This dissertation investigates several strategies to develop on-chip micro-supercapacitors with high power and energy density. Micro-supercapacitors based on interdigitated carbon micro-electrode arrays are fabricated through carbon microelectromechanical systems (C-MEMS) technique which is based on carbonization of patterned photoresist. To improve the capacitive behavior, electrochemical activation is performed on carbon micro-electrode arrays. The developed micro-supercapacitors show specific capacitances as high as 75 mFcm-2 at a scan rate of 5 mVs -1 after electrochemical activation for 30 minutes. The capacitance loss is less than 13% after 1000 cyclic voltammetry (CV) cycles. These results indicate that electrochemically activated C-MEMS micro-electrode arrays are promising candidates for on-chip electrochemical micro-capacitor applications. The energy density of micro-supercapacitors was further improved by conformal coating of polypyrrole (PPy) on C-MEMS structures. In these types of micro-devices the three dimensional (3D) carbon microstructures serve as current collectors for high energy density PPy electrodes. The electrochemical characterizations of these micro-supercapacitors show that they can deliver a specific capacitance of about 162.07 mFcm-2 and a specific power of 1.62mWcm -2 at a 20 mVs-1 scan rate. Addressing the need for high power micro-supercapacitors, the application of graphene as electrode materials for micro-supercapacitor was also investigated. The present study suggests a novel method to fabricate graphene-based micro-supercapacitors with thin film or in-plane interdigital electrodes. The fabricated micro-supercapacitors show exceptional frequency response and power handling performance and could effectively charge and discharge at rates as high as 50 Vs-1. CV measurements show that the specific capacitance of the micro-supercapacitor based on reduced graphene oxide and carbon nanotube composites is 6.1 mFcm -2 at scan rate of 0.01Vs-1. At a very high scan rate of 50 Vs-1, a specific capacitance of 2.8 mFcm-2 (stack capacitance of 3.1 Fcm-3) is recorded. This unprecedented performance can potentially broaden the future applications of micro-supercapacitors.

The IRS Collection Division: Contacts and Settlements

In his study -The IRS Collection Division: Contacts and Settlements - by John M. Tarras, Assistant Professor School of Hotel, Restaurant and Institutional Management, Michigan State University, Tarras initially states: “The collection division of the internal revenue service is often the point of contact for many hospitality businesses. The author describes how the division operates, what the hospitality firm can expect when contacted by it, and what types of strategies firms might find helpful when negotiating a settlement with the IRS.” The author will have you know that even though most chance meetings with the IRS Collection Division are due to unfortunate tax payment circumstances, there are actually more benign reasons for close encounters of the IRS kind. This does not mean, however, that brushes with the IRS Collection Division will end on an ever friendlier note. “…the Tax Reform Act of 1986 with its added complexity will cause some hospitality firms to inadvertently fail to make proper payments on a timely basis,” Tarras affords in illustrating a perhaps less pugnacious side of IRS relations. Should a hospitality business owner represent himself/herself before the IRS? Never, says Tarras. “Too many taxpayers ruin their chances of a fair settlement by making what to them seem innocent remarks, but ones that turn out to be far different,” warns Professor Tarras. Tarras makes the distinction between IRS the Collection Division, and IRS the Audit Division. “While the Audit Division is interested in how the tax liability arose, the Collection Division is generally only interested in collecting the liability,” he informs you. Either sounds firmly in hostile territory. They don’t bluff. Tarras does want you to know that when the IRS threatens to levy on the assets of a hospitality business, they will do so. Those assets may extend to personal and real property as well, he says. The levy action is generally the final resort in an IRS collection effort. Professor Tarras explains the lien process and the due process attached to that IRS collection tactic. “The IRS can also levy a hospitality firm owner's wages. In this case, it is important to realize that you are allowed to exempt from levy $75 per week, along with $25 per week for each of your dependents (unless your spouse works),” Professor Tarras says with the appropriate citation. What are the options available to the hospitality business owner who finds himself on the wrong side of the IRS Collection Division? Negotiate in good faith says Professor Tarras. “In many cases, a visit to the IRS office will greatly reduce the chances that a simple problem will turn into a major one,” Tarras advises. He dedicates the last pages of the discussion to negotiation strategies.

Estimation and Prediction of Average Vehicle Occupancies using Traffic Accident Records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver¡¯s age, and driver¡¯s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Freeway Travel Time Estimation and Prediction Using Dynamic Neural Networks

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.

Critical problem solving scale : creating and choosing alternative solutions

This thesis extends previous research on critical decision making and problem-solving by refining and validating a self-report measure designed to assess the use of critical decision making and problem solving in making life choices. The analysis was conducted by performing two studies, and therefore collecting two sets of data on the psychometric properties of the measure. Psychometric analyses included: item analysis, internal consistency reliability, interrater reliability, and an exploratory factor analysis. This study also included regression analysis with the Wonderlic, an established measure of general intelligence, to provide preliminary evidence for the construct validity of the measure.

Resources use and conservation attitudes of local people in the Western Terai landscape, Nepal

Two protected areas: Royal Bardia National Park (RBNP) and Royal Suklaphanta Wildlife Reserve (RSWR) in the Western Terai, Nepal, are under threats due to present political turmoil, uncontrolled immigration, inefficient land reform policies and unsustainable resource use. I did a stratified random questionnaire survey of 234 households to determine how resource use patterns and problems influence conservation attitudes. Chi-square, Student's t, Mann-Whitney and Kruskal-Wallis tests, and multiple regression were used. There was spatio-temporal variability in resource use patterns and dependency. People were collecting eight and seven types of resources in RBNP and RSWR, respectively. However, people in RBNP were more dependent on resources than RSWR. In both areas, the problem of firewood is serious. The mean attitude score of RBNP (8.4 ± 1.44) was significantly higher than the score of RSWR (7.7 ± 1.66; t = 3.24, p = 0.0007). Conservation attitude was determined by variables such as participation in trainings, wildlife damage, and satisfaction towards user groups.

Navigation and meteorological data during campaign TARA_20110826Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20110928Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.

Navigation and meteorological data during campaign TARA_20110626Z of the Tara Oceans expedition 2009-2013

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present dataset contains navigation and meteorological data measured during one campaign of the Tara Oceans Expedition. Latitude and Longitude were obtained from TSG data.