The effect of mastery learning on a course in accounting information system (AIS): A comparison within public and private universities in Taiwan

The Accounting Information System (AIS) is an important course in the Department of Accounting (DoAc) of universities in Taiwan. This course is required for seniors not only because it meets the needs of the profession, but also because it provides continual study for the department's students.^ The scores of The National College and University Joint Entrance Examination (NUEE) show that students with high learning ability are admitted to public universities with high scores, while those with low learning ability are admitted only to private universities. The same situation has been found by the researcher while teaching an AIS course in DoAc of The Public Chun Shin University (CSU) and The Private Chinese Culture University (CCU).^ The purpose of this study was to determine whether low ability students enrolled in private universities in Taiwan in a mastery learning program could attain the same level as high ability students from public universities enrolled in a traditional program. An experimental design was used. The mastery learning method was used to teach three groups of seniors with low learning ability studying in the DoAc at CCU. The traditional method was used to teach the control group which consisted of senior students of DoAc of CSU with high learning ability. As a part of the mastery learning strategy, a formative test, quizzes, and homework were completed by the experimental group only, while the mid-term examination was completed by both groups as part of the course. The dependent variable was the summative test, the final examination. It was completed by both groups upon the course's completion.^ As predicted, there were significant differences between the two groups' results on the pretest. There were no significant differences between the two groups' results on the posttest. These findings support the hypothesis of the study and reveal the effectiveness of mastery learning strategies with low learning ability students. ^

Variable responses within epiphytic and benthic microalgal communities to nutrient enrichment

We examined the spatial extent of nitrogen (N) and phosphorus (P) limitation of each of the major benthic primary producer groups in Florida Bay (seagrass, epiphytes, macroalgae, and benthic microalgae) and characterized the shifts in primary producer community composition following nutrient enrichment. We established 24 permanent 0.25-m2 study plots at each of six sites across Florida Bay and added N and P to the sediments in a factorial design for 18 mo. Tissue nutrient content of the turtlegrass Thalassia testudinum revealed a spatial pattern in P limitation, from severe limitation in the eastern bay (N:P > 96:1), moderate limitation in two intermediate sites (approximately 63:1), and balanced with N availability in the western bay (approximately 31:1). P addition increased T. testudinum cover by 50-75% and short-shoot productivity by up to 100%, but only at the severely P-limited sites. At sites with an ambient N:P ratio suggesting moderate P limitation, few seagrass responses to nutrients occurred. Where ambient T. testudinum tissue N:P ratios indicated N and P availability was balanced, seagrass was not affected by nutrient addition but was strongly influenced by disturbance (currents, erosion). Macroalgal and epiphytic and benthic microalgal biomass were variable between sites and treatments. In general, there was no algal overgrowth of the seagrass in enriched conditions, possibly due to the strength of seasonal influences on algal biomass or regulation by grazers. N addition had little effect on any benthic primary producers throughout the bay. The Florida Bay benthic primary producer community was P limited, but P-induced alterations of community structure were not uniform among primary producers or across Florida Bay and did not always agree with expected patterns of nutrient limitation based on stoichiometric predictions from field assays of T. testudinum tissue N:P ratios.

Design and construction of a portable force-reflecting manual controller for teleoperation systems

A man-machine system called teleoperator system has been developed to work in hazardous environments such as nuclear reactor plants. Force reflection is a type of force feedback in which forces experienced by the remote manipulator are fed back to the manual controller. In a force-reflecting teleoperation system, the operator uses the manual controller to direct the remote manipulator and receives visual information from a video image and/or graphical animation on the computer screen. This thesis presents the design of a portable Force-Reflecting Manual Controller (FRMC) for the teleoperation of tasks such as hazardous material handling, waste cleanup, and space-related operations. The work consists of the design and construction of a prototype 1-Degree-of-Freedom (DOF) FRMC, the development of the Graphical User Interface (GUI), and system integration. Two control strategies - PID and fuzzy logic controllers are developed and experimentally tested. The system response of each is analyzed and evaluated. In addition, the concept of a telesensation system is introduced, and a variety of design alternatives of a 3-DOF FRMC are proposed for future development.

The construction and optimization of an ion mobility spectrometer for the analysis of explosives and drugs

Today, over 15,000 Ion Mobility Spectrometry (IMS) analyzers are employed at worldwide security checkpoints to detect explosives and illicit drugs. Current portal IMS instruments and other electronic nose technologies detect explosives and drugs by analyzing samples containing the headspace air and loose particles residing on a surface. Canines can outperform these systems at sampling and detecting the low vapor pressure explosives and drugs, such as RDX, PETN, cocaine, and MDMA, because these biological detectors target the volatile signature compounds available in the headspace rather than the non-volatile parent compounds of explosives and drugs.^ In this dissertation research volatile signature compounds available in the headspace over explosive and drug samples were detected using SPME as a headspace sampling tool coupled to an IMS analyzer. A Genetic Algorithm (GA) technique was developed to optimize the operating conditions of a commercial IMS (GE Itemizer 2), leading to the successful detection of plastic explosives (Detasheet, Semtex H, and C-4) and illicit drugs (cocaine, MDMA, and marijuana). Short sampling times (between 10 sec to 5 min) were adequate to extract and preconcentrate sufficient analytes (> 20 ng) representing the volatile signatures in the headspace of a 15 mL glass vial or a quart-sized can containing ≤ 1 g of the bulk explosive or drug.^ Furthermore, a research grade IMS with flexibility for changing operating conditions and physical configurations was designed and fabricated to accommodate future research into different analytes or physical configurations. The design and construction of the FIU-IMS were facilitated by computer modeling and simulation of ion’s behavior within an IMS. The simulation method developed uses SIMION/SDS and was evaluated with experimental data collected using a commercial IMS (PCP Phemto Chem 110). The FIU-IMS instrument has comparable performance to the GE Itemizer 2 (average resolving power of 14, resolution of 3 between two drugs and two explosives, and LODs range from 0.7 to 9 ng). ^ The results from this dissertation further advance the concept of targeting volatile components to presumptively detect the presence of concealed bulk explosives and drugs by SPME-IMS, and the new FIU-IMS provides a flexible platform for future IMS research projects.^

The Construction and Optimization on an Ion Mobility Spectrometer for the Analysis of Explosives and Drugs

Today, over 15,000 Ion Mobility Spectrometry (IMS) analyzers are employed at worldwide security checkpoints to detect explosives and illicit drugs. Current portal IMS instruments and other electronic nose technologies detect explosives and drugs by analyzing samples containing the headspace air and loose particles residing on a surface. Canines can outperform these systems at sampling and detecting the low vapor pressure explosives and drugs, such as RDX, PETN, cocaine, and MDMA, because these biological detectors target the volatile signature compounds available in the headspace rather than the non-volatile parent compounds of explosives and drugs. In this dissertation research volatile signature compounds available in the headspace over explosive and drug samples were detected using SPME as a headspace sampling tool coupled to an IMS analyzer. A Genetic Algorithm (GA) technique was developed to optimize the operating conditions of a commercial IMS (GE Itemizer 2), leading to the successful detection of plastic explosives (Detasheet, Semtex H, and C-4) and illicit drugs (cocaine, MDMA, and marijuana). Short sampling times (between 10 sec to 5 min) were adequate to extract and preconcentrate sufficient analytes (> 20 ng) representing the volatile signatures in the headspace of a 15 mL glass vial or a quart-sized can containing ≤ 1 g of the bulk explosive or drug. Furthermore, a research grade IMS with flexibility for changing operating conditions and physical configurations was designed and fabricated to accommodate future research into different analytes or physical configurations. The design and construction of the FIU-IMS were facilitated by computer modeling and simulation of ion’s behavior within an IMS. The simulation method developed uses SIMION/SDS and was evaluated with experimental data collected using a commercial IMS (PCP Phemto Chem 110). The FIU-IMS instrument has comparable performance to the GE Itemizer 2 (average resolving power of 14, resolution of 3 between two drugs and two explosives, and LODs range from 0.7 to 9 ng). The results from this dissertation further advance the concept of targeting volatile components to presumptively detect the presence of concealed bulk explosives and drugs by SPME-IMS, and the new FIU-IMS provides a flexible platform for future IMS research projects.