Supplemental instruction, study habits, and the community college student

The purpose of this study was to demonstrate if the academic assistance program Supplemental Instruction (SI) facilitates the acquisition of effective study behaviors through strategies that transcend simple double-exposure to the course material. Its advocates claim it increases academic achievement using learner-centered knowledge and acquisition of effective study behaviors. SI sessions are specifically related to particular courses that students are taking. Sessions are facilitated by the SI leader who has taken the subject matter course in the past. Students review the content of the previous subject matter class using collaborative learning strategies coordinated by a SI leader. In addition, the SI leader models appropriate study behaviors in his or her interactions with the students. ^ An instructor at a large Florida community college who taught five classes of an Anatomy & Physiology I course (traditionally supported by SI) was identified. Two of the classes were randomly selected to participate in SI activities, and two classes were random chosen to participate in alternate, computer-based activities that dealt with the course content, but did not include work in developing students' study behaviors. These treatments were carried out over the course of an entire semester. Participation was mandatory. ^ Data were collected on two variables. Academic achievement in anatomy and physiology content was measured both pre- and post-treatment using an instructor developed examination. Student study behaviors were measured using pre- and post-treatment administration of the Study Behavior Inventory, a valid and reliable instrument that provides scores on three categories of study behaviors: (a) Academic self-efficacy, (b) Preparation for routine academic tasks, and (c) Preparation for long range academic tasks. Measures obtained at the end of the semester of treatment revealed no significant differences between the SI and alternative treatment groups in post-treatment achievement test score and the post-treatment scores on the three study behaviors categories when adjusted for pre-treatment scores. ^ These results suggest that the development of appropriate study behaviors requires more time than SI, as it is now implemented, can provide. In addition, results indicate that improved academic achievement may be attained through any number of means that include repeated exposure to course material. ^

Empowerment, social support, and self -esteem of parents involved in an elementary school program

Parent involvement (PI) in schooling has consistently been correlated with improved academic achievement in children. However, despite the apparent benefits of parent involvement, many schools serving low-income communities report consistent difficulty in facilitating the involvement of parents in their children's schooling. ^ The purpose of this exploratory pilot study was to examine key variables associated with a PI program at a school that served a low-income community. The program was selected because it sustained the involvement of parents for a prolonged period of time. It was also selected because the program was facilitated by social workers. ^ Derived from the literature, four lines of inquiry were examined: (a) the relationship between PI and parent strengths and development; (b) the relationship between PI and children's academic achievement; (c) facilitators for PI; and (d) barriers to PI. These lines of inquiry yielded the study's four primary research questions. The study employed a cross-sectional research design to address them. ^ Thirty-three parents, representing 16 school-involved (SI) parents and 17 non-school involved (NSI) parents, served as study participants. All 33 parents resided in a high poverty community. ^ Quantitative methods were selected to examine differences between study participants and PI. Measures of parental empowerment, social support, self-esteem, and direct and indirect measures of their children's academic achievement were utilized. Qualitative methods were developed to identify and describe SI and NSI parents' perceptions of facilitators for and barriers to PI. ^ This study's findings suggest that PI may yield important benefits for SI parents. These benefits include parents' perceptions of their empowerment, social support, and self-esteem. This study's findings also suggest a relationship between PI and reduced rates of children's school suspensions. This study did not, however, support relationships between PI and children's standardized test scores. This study concludes that despite the apparent benefits of PI for SI parents, PI may nonetheless be a proxy for several unspecified interventions that effect parents, children, schools and communities alike. More precise specifications and robust measures of PI are needed. ^

Empowerment, social support, and self-esteem of parents involved in an elementary school program

Parent involvement (PI) in schooling has consistently been correlated with improved academic achievement in children. However, despite the apparent benefits of parent involvement, many schools serving low-income communities report consistent difficulty in facilitating the involvement of parents in their children's schooling. The purpose of this exploratory pilot study was to examine key variables associated with a PI program at a school that served a low-income community. The program was selected because it sustained the involvement of parents for a prolonged period of time. It was also selected because the program was facilitated by social workers. Derived from the literature, four lines of inquiry were examined: (a) the relationship between PI and parent strengths and development; (b) the relationship between PI and children's academic achievement; (c) facilitators for PI; and (d) barriers to PI. These lines of inquiry yielded the study's four primary research questions. The study employed a cross-sectional research design to address them. Thirty-three parents, representing 16 school-involved (SI) parents and 17 nonschool involved (NSI) parents, served as study participants. All 33 parents resided in a high poverty community. Quantitative methods were selected to examine differences between study participants and PI. Measures of parental empowerment, social support, self-esteem, and direct and indirect measures of their children's academic achievement were utilized. Qualitative methods were developed to identify and describe SI and NSI parents' perceptions of facilitators for and barriers to PI. This study's findings suggest that PI may yield important benefits for SI parents. These benefits include parents' perceptions of their empowerment, social support, and self-esteem. This study's findings also suggest a relationship between PI and reduced rates of children's school suspensions. This study did not, however, support relationships between PI and children's standardized test scores. This study concludes that despite the apparent benefits of PI for SI parents, PI may nonetheless be a proxy for several unspecified interventions that effect parents, children, schools and communities alike. More precise specifications and robust measures of PI are needed.

Carbon nanotube reinforced aluminum based nanocomposite fabricated by thermal spray forming

The present research concentrates on the fabrication of bulk aluminum matrix nanocomposite structures with carbon nanotube reinforcement. The objective of the work was to fabricate and characterize multi-walled carbon nanotube (MWCNT) reinforced hypereutectic Al-Si (23 wt% Si, 2 wt% Ni, 1 wt% Cu, rest Al) nanocomposite bulk structure with nanocrystalline matrix through thermal spray forming techniques viz. plasma spray forming (PSF) and high velocity oxy-fuel (HVOF) spray forming. This is the first research study, which has shown that thermal spray forming can be successfully used to synthesize carbon nanotube reinforced nanocomposites. Microstructural characterization based on quantitative microscopy, scanning and transmission electron microscopy (SEM and TEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), Raman spectroscopy and X ray photoelectron spectroscopy (XPS) confirms (i) retention and macro/sub-macro level homogenous distribution of multiwalled carbon nanotubes in the Al-Si matrix and (ii) evolution of nanostructured grains in the matrix. Formation of ultrathin β-SiC layer on MWCNT surface, due to chemical reaction of Si atoms diffusing from Al-Si alloy and C atoms from the outer walls of MWCNTs has been confirmed theoretically and experimentally. The presence of SiC layer at the interface improves the wettability and the interfacial adhesion between the MWCNT reinforcement and the Al-Si matrix. Sintering of the as-sprayed nanocomposites was carried out in an inert environment for further densification. As-sprayed PSF nanocomposite showed lower microhardness compared to HVOF, due to the higher porosity content and lower residual stress. The hardness of the nanocomposites increased with sintering time due to effective pore removal. Uniaxial tensile test on CNT-bulk nanocomposite was carried out, which is the first ever study of such nature. The tensile test results showed inconsistency in the data attributed to inhomogeneous microstructure and limitation of the test samples geometry. The elastic moduli of nanocomposites were computed using different micromechanics models and compared with experimentally measured values. The elastic moduli of nanocomposites measured by nanoindentation technique, increased gradually with sintering attributed to porosity removal. The experimentally measured values conformed better with theoretically predicted values, particularly in the case of Hashin-Shtrikman bound method.

Design strategies for an artificial neural network based algorithm for automatic incident detection on major arterial streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our nation’s highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Design Strategies for an Artificial Neural Network Based Algorithm for Automatic Incident Detection on Major Arterial Streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our national highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Design and fabrication of two switched superconductivity microstrip hairpin filters using series micro-electro-mechanical systems (MEMS) switches

Series Micro-Electro-Mechanical System (MEMS) switches based on superconductor are utilized to switch between two bandpass hairpin filters with bandwidths of 365 MHz and nominal center frequencies of 2.1 GHz and 2.6 GHz. This was accomplished with 4 switches actuated in pairs, one pair at a time. When one pair was actuated the first bandpass filter was coupled to the input and output ports. When the other pair was actuated the second bandpass filter was coupled to the input and output ports. The device is made of a YBa2Cu 3O7 thin film deposited on a 20 mm x 20 mm LaAlO3 substrate by pulsed laser deposition. BaTiO3 deposited by RF magnetron sputtering in utilized as the insulation layer at the switching points of contact. These results obtained assured great performance showing a switchable device at 68 V with temperature of 40 K for the 2.1 GHz filter and 75 V with temperature of 30 K for the 2.6 GHz hairpin filter. ^

The development of an optimized system of narcotic and explosive contraband mimics for calibration and training of biological detectors

Current commercially available mimics contain varying amounts of either the actual explosive/drug or the chemical compound of suspected interest by biological detectors. As a result, there is significant interest in determining the dominant chemical odor signatures of the mimics, often referred to as pseudos, particularly when compared to the genuine contraband material. This dissertation discusses results obtained from the analysis of drug and explosive headspace related to the odor profiles as recognized by trained detection canines. Analysis was performed through the use of headspace solid phase microextraction in conjunction with gas chromatography mass spectrometry (HS-SPME-GC-MS). Upon determination of specific odors, field trials were held using a combination of the target odors with COMPS. Piperonal was shown to be a dominant odor compound in the headspace of some ecstasy samples and a recognizable odor mimic by trained detection canines. It was also shown that detection canines could be imprinted on piperonal COMPS and correctly identify ecstasy samples at a threshold level of approximately 100ng/s. Isosafrole and/or MDP-2-POH show potential as training aid mimics for non-piperonal based MDMA. Acetic acid was shown to be dominant in the headspace of heroin samples and verified as a dominant odor in commercial vinegar samples; however, no common, secondary compound was detected in the headspace of either. Because of the similarities detected within respective explosive classes, several compounds were chosen for explosive mimics. A single based smokeless powder with a detectable level of 2,4-dinitrotoluene, a double based smokeless powder with a detectable level of nitroglycerine, 2-ethyl-1-hexanol, DMNB, ethyl centralite and diphenylamine were shown to be accurate mimics for TNT-based explosives, NG-based explosives, plastic explosives, tagged explosives, and smokeless powders, respectively. The combination of these six odors represents a comprehensive explosive odor kit with positive results for imprint on detection canines. As a proof of concept, the chemical compound PFTBA showed promise as a possible universal, non-target odor compound for comparison and calibration of detection canines and instrumentation. In a comparison study of shape versus vibration odor theory, the detection of d-methyl benzoate and methyl benzoate was explored using canine detectors. While results did not overwhelmingly substantiate either theory, shape odor theory provides a better explanation of the canine and human subject responses.

The Development of an Optimized System of Narcotic and Explosive Contraband Mimics for Calibration and Training of Biological Detectors

Current commercially available mimics contain varying amounts of either the actual explosive/drug or the chemical compound of suspected interest by biological detectors. As a result, there is significant interest in determining the dominant chemical odor signatures of the mimics, often referred to as pseudos, particularly when compared to the genuine contraband material. This dissertation discusses results obtained from the analysis of drug and explosive headspace related to the odor profiles as recognized by trained detection canines. Analysis was performed through the use of headspace solid phase microextraction in conjunction with gas chromatography mass spectrometry (HS-SPME-GC-MS). Upon determination of specific odors, field trials were held using a combination of the target odors with COMPS. Piperonal was shown to be a dominant odor compound in the headspace of some ecstasy samples and a recognizable odor mimic by trained detection canines. It was also shown that detection canines could be imprinted on piperonal COMPS and correctly identify ecstasy samples at a threshold level of approximately 100ng/s. Isosafrole and/or MDP-2-POH show potential as training aid mimics for non-piperonal based MDMA. Acetic acid was shown to be dominant in the headspace of heroin samples and verified as a dominant odor in commercial vinegar samples; however, no common, secondary compound was detected in the headspace of either. Because of the similarities detected within respective explosive classes, several compounds were chosen for explosive mimics. A single based smokeless powder with a detectable level of 2,4-dinitrotoluene, a double based smokeless powder with a detectable level of nitroglycerine, 2-ethyl-1-hexanol, DMNB, ethyl centralite and diphenylamine were shown to be accurate mimics for TNT-based explosives, NG-based explosives, plastic explosives, tagged explosives, and smokeless powders, respectively. The combination of these six odors represents a comprehensive explosive odor kit with positive results for imprint on detection canines. As a proof of concept, the chemical compound PFTBA showed promise as a possible universal, non-target odor compound for comparison and calibration of detection canines and instrumentation. In a comparison study of shape versus vibration odor theory, the detection of d-methyl benzoate and methyl benzoate was explored using canine detectors. While results did not overwhelmingly substantiate either theory, shape odor theory provides a better explanation of the canine and human subject responses.

Improved Electronics for the Hall A Detectors at JLab: Summing Modules and VDC Amplifier/Discriminator Cards

Testing of summing electronics and VDC A/D Cards was performed to assure proper functioning and operation within defined parameters. In both the summing modules and the VDC A/D cards, testing for minimum threshold voltage for each channel and crosstalk between neighboring channels was performed. Additionally, the modules were installed in Hall A with input signals from shower detectors arranged to establish a trigger by summing signals together with the use of tested modules. Testing involved utilizing a pulser to mimic PMT signals, a discriminator, an attenuator, a scaler, a level translator, an oscilloscope, a high voltage power supply, and a special apparatus used to power and send signal to the A/D cards. After testing, modules were obtained that meet necessary criteria for use in the APEX experiment, and the A/D cards obtained were determined to have adequate specifications for their utilization, with specific results included in the appendix.