While quantitative investment management has been extensively investigated and many models built in order to provide investment suggestions through quantitative analysis, the combination of quantitative and qualitative analysis is relatively unexplored. The objective of this study is to construct a quantitative stock selection model based on the standard model built by Hsu et al. (2011) which could improve the stability of descriptor and factor structures and the combinability of quantitative and qualitative analysis. The research focuses on the structure of effective factors and descriptors when faced with different types of market trends. Furthermore, we test the performance of a Market Trend-Based Alpha Model (MTB alpha model) and compare with the standard alpha model. The strategy of portfolio construction is a TAIEX enhanced index fund. We find the enhanced index portfolio constructed by the MTB model produces an information ratio of 0.72, which is much higher than the standard model ratio of 0.41. This finding suggests that a MTB model could not only improve performance but also make the descriptor and factor structures more stable and much more easily for managers¡¦ adjusting.

The objective of this study is to build the platform, and the user can choose one model of the three models (1) base multi-factor alpha model (2) sector-specific alpha model (3) market trend-based multi-factor alpha model. The user can choose one target index of the four indexes (1) Electronic (2) Finance (3) Non-Finance Non-Electronics (4) TAIEX. The platform also combined the score of sector-specific model and market model, which we called hybrid model. The platform provides (1) elasticity of equity management (2) completeness of investment strategy (3) inclusiveness of alpha models and target indexes. The user can select a suit model and allocate the model and the target index, and quickly back-testing and evaluate performance. The contributions of this study are that help asset management companies quickly design investment strategies and back-testing, or product many different equity portfolio funds, and evaluate performance for stabled performance.

Noise and time-dependent fluctuations are usually undesirable signals. However, they have many applications. This dissertation deals with two kinds of sensing applications of fluctuation and noise: soil bulk density assessment and bacterium sensing. The measurement of Vibration-Induced Conductivity Fluctuations (VICOF) provides information about the bulk density and other parameters of soils. Bulk density is the physical property of soils that is important to both the agriculture and construction industries. The traditional measurements of soil bulk density are often time-consuming, expensive or destructive. To determine the soil bulk density without the above drawbacks, the VICOF measurement scheme was proposed. The research of VICOF in this dissertation includes two parts: the initial phase of study and the new methods and their theory. In the initial phase of study, the simple experiments, theory, and simulations of VICOF were tested for relations between the soil bulk density, wetness, salinity, and the VICOF data. Then, new measurement arrangements and their theoretical models were proposed to improve the weaknesses of the initial approach (such as large scattering of data due to loose and heavy contacts) and to calculate the relationship between the measured signals and the electromechanical transport parameters of the soils. The bacterium sensing study in this dissertation was proposed to explore simple, practical, rapid, sensitive, specific, portable, and inexpensive ways to detect and recognize bacteria by Fluctuation-Enhanced Sensing (FES). One such potential way of bacterium sensing is to analyze their odor. The research of bacterium sensing also includes two parts: the initial phase of study and the new methods and their theory. The initial phase study was proposed to explore the possibility of detecting and identifying bacteria by sensing their odor via FES with commercial Taguchi sensors. Then the subsequently developed new methods and their theory provide a simple way to generate binary patterns with perfect reproducibility based on the spectral slopes in different frequency ranges at FES. This new type of signal processing and pattern recognition is implemented at the block diagram level using the building elements of analog circuitries and a few logic gates with total power consumption in the microWatts range.

This dissertation describes experimental studies of how a spatially alternating magnetic field can effectively pin the magnetic flux in a superconducting thin film (Pb 82 Bi18), thereby enhancing the superconductivity. The spatially alternating magnetic field was provided by a periodic array of nano-sized magnetic structures: 300 nm spacing triangular array of cobalt rods with 100 nm diameter and 300 nm height. The superconducting film deposited on top of the magnetic structures, or an embedded Ferromagnet- Superconductor Hybrids (FSH), showed enhanced critical current and critical magnetic field. The embedded FSH also showed the field matching effect, the field compensation effect, and hysteresis. This dissertation also explains how to fabricate and characterize magnetic nano- structures. Electron beam lithography and electroplating method were used to fabricate the magnetic nanostructures. Scanning electron microscopy (SEM) and atomic force microscopy (AFM) were used to characterize the structures of the magnetic rods. Magnetic force microscopy (MFM) was used to study their magnetic properties.

This dissertation focuses on the effectiveness of scaffolding in technology-enhanced science learning environments, and specifically the relative merits of computer- and teacher-based scaffolding in science inquiry. Scaffolding is an instructional support that helps learners solve problems, carry out tasks, or achieve goals that they are unable to accomplish on their own. Although support such as scaffolding is necessary when students engage in complex learning environments, many issues must be resolved before educators can effectively implement scaffolding in instruction. To achieve this, this dissertation includes two studies: a systematic literature review and an experimental study. The two studies attempted to reveal some important issues which are not widely recognized in the existing literature. The primary problem confronting the educator is how to determine which of the numerous kinds of scaffolding will allow them to educate students most effectively. The scaffolding forms that researchers create are often confusing, overlapping, or contradictory. In response to this, the first study critically analyzed the ways that researchers have defined and applied scaffolding, and provided suggestions for future scaffolding design and research. Moreover, studies tend to focus only on computer-based scaffolding rather than examining ways to integrate it with teacher-based instruction. Although researchers generally recognize that teacher-based support is important, research in this area is limited. The second study of this dissertation employed a quasi-experimental design with four experimental conditions, each of which include a type of computer-based procedural scaffolding (continuous vs. faded) paired with a type of teacher-based metacognitive scaffolding (early vs. late). Each class was assigned to use one of the four conditions. The findings indicated that students receiving continuous computer-based procedural and early teacher-based metacognitive scaffolding performed statistically better at learning scientific inquiry skills than other treatment groups. Students using faded computer-based procedural and early teacher-based metacognitive scaffolding showed the worst performance. However, among the four groups there existed no statistically significant difference in terms of the effect on students? ability to learn science knowledge. Moreover, teacher-based metacognitive scaffolding did not have a significant impact on either science content knowledge or scientific inquiry skills.

Nanostructures are nanometer scale structures (characteristic length less than 100 nm) such as nanowires, ultra-small junctions, etc. Since nanostructures are less stable, their characteristic volume is much smaller compared to defect sizes and their characteristic length is close to acoustical phonon wavelength. Moreover, because nanostructures include significantly fewer charge carriers than microscale structures, electronic noise in nanostructures is enhanced compared to microscale structures. Additionally, in microprocessors, due to the small gate capacitance and reduced noise margin (due to reduced supply voltage to keep the electrical field at a reasonable level), the electronic noise results in bit errors. On the other hand, the enhanced noise is useful for advanced sensing applications which are called fluctuation-enhanced sensing. In this dissertation, we first survey our earlier results about the limitation of noise posed on specific nano processors. Here, single electron logic is considered for voltage controlled logic with thermal excitations and generic shot noise is considered for current-controlled logic. Secondly, we discuss our recent results on the electronic noise in nanoscale sensors for SEnsing of Phage-Triggered Ion Cascade (SEPTIC, for instant bacterial detection) and for silicon nanowires for viral sensing. In the sensing of the phage-triggered ion cascade sensor, bacteriophage-infected bacteria release potassium ions and move randomly at the same time; therefore, electronic noise (i.e., stochastic signals) are generated. As an advanced model, the electrophoretic effect in the SEPTIC sensor is discussed. In the viral sensor, since the combination of the analyte and a specific receptor located at the surface of the silicon nanowire occurs randomly in space and time, a stochastic signal is obtained. A mathematical model for a pH silicon nanowire nanosensor is developed and the size quantization effect in the nanosensor is also discussed. The calculation results are in excellent agreement with the experimental results in the literature.

We construct the multi-factor model using fundamental cross-sectional approach in the thesis. We adopt the principal of BARRA¡¦E3 for constructing our multi-factor model. In our study period, we finally obtain 34 significant explanatory factors including 7 risk indices and 27 industry factors. In particular, the industry factors are an important risk source of the stock returns. The explanatory power of the multi-factor model is 43.18% on average and it ranges from 12.89% to 82.35%. The study results can be considered satisfactory. Moreover, based on the multi-factor model, we construct the Taiwan Weighted Stock Index enhanced index fund by the tracking error minimization method in our study. Enhanced Index Fund was built to make use of both passive management and active management to construct a portfolio which has the similar characteristics but higher returns compared to benchmark index. Hence, we want to track the Taiwan Weighted Stock Index while producing at least 2% outperformance over the Taiwan Weighted Stock Index. Our empirical period is from January 2000 to December 2005 and the simulated period is from January 2006 to December 2007. The performance of our constructed Taiwan Weighted Stock Index enhanced index fund in the simulated period is better than the benchmark and the tracking error is 1.36%. We are satisfied with the study results.

<p>The important protein hormone insulin, responsible for different kind of functions in our body but mainly storage of nutrients, has for a long time been used for treatment of diabetic patients. This important protein is both physically and chemically unstable. Especially during production where the insulin protein is exposed to unnatural environmental conditions such as acidic pH has this been causing problems since huge volumes of the product go to waste.</p><p>In the human body the environment for the protein is tolerable with normal body temperature and the right pH, but when the protein is commercially synthesised the environmental conditions are not ultimate. What happens during these unfavourable conditions is that the insulin starts to fibrillate. Meaning that linear, biologically inactive aggregates are formed. If then under these kinds of conditions such as high temperature and acidic pH, the insulin comes in contact with hydrophobic surfaces then the fibrillation of the protein goes even faster.</p><p>In the following experiment I am going to investigate if the experiments and conclusions done before, where different kinds of additives to insulin solutions have been used to enhance the amyloid fibrillation of insulin, are as effective as it has been proposed and I am going to prove that the presence of hydrophobic surfaces, such as coated silicon surfaces or glass and addition of preformed fibrils, so called seeds, increase amyloid fibrillation of the insulin protein under certain conditions, in comparison with the normal fibrillation under the same conditions.</p>

<p>The evolvement of the uplink in the third generation mobile telecommunication system is an ongoing process. The Enhanced Uplink (EUL) concept is being developed to meet the expected need from more advanced services, like video streaming and mobile broadband. One idea for further improvement in the EUL concept is to introduce Time Division Multiple Access (TDMA), which is studied in this master thesis.</p><p>The master thesis assignment is to study the consequences of introducing TDMA in EUL. The goal has been to identify the gains and problems, and how they can be handled. A derived theoretical framework and system simulations, using a radio network simulator, are used.</p><p>The overall conclusion is that there is a potentially large gain with an introduction of TDMA in EUL. Simulations in favorable conditions have shown that the system throughput can increase by 100% when there are only User Equipment (UE) that are using EUL in the system and by 50% when there is a mix of speech and EUL UE’s. When using TDMA the uplink load also shows improvements, the mean is generally higher but the variance is generally smaller.</p><p>Due to major differences in experienced interference between passive and active UE’s, the signal quality will vary a lot. The big variation in signal quality is identified as the main problem with introducing TDMA in EUL. It is shown that this problem can generate extreme high uplink load, which have a negative impact both on the resource efficiency and the coverage.</p>

Thesis (Ph. D.)--University of Missouri-Columbia, 1998. / Typescript. Vita. Includes bibliographical references (leaves 154-161). Also available on the Internet.