The applied computer science of economic analyses: Internet prioritization and Internet pricing, and software engineering and software pricing for the mass market

This research examines evolving issues in applied computer science and applies economic and business analyses as well. There are two main areas. The first is internetwork communications as embodied by the Internet. The goal of the research is to devise an efficient pricing, prioritization, and incentivization plan that could be realistically implemented on the existing infrastructure. Criteria include practical and economic efficiency, and proper incentives for both users and providers. Background information on the evolution and functional operation of the Internet is given, and relevant literature is surveyed and analyzed. Economic analysis is performed on the incentive implications of the current pricing structure and organization. The problems are identified, and minimally disruptive solutions are proposed for all levels of implementation to the lowest level protocol. Practical issues are considered and performance analyses are done. The second area of research is mass market software engineering, and how this differs from classical software engineering. Software life-cycle revenues are analyzed and software pricing and timing implications are derived. A profit maximizing methodology is developed to select or defer the development of software features for inclusion in a given release. An iterative model of the stages of the software development process is developed, taking into account new communications capabilities as well as profitability. ^

Development of a mathematical and computer model to assess water quality impacts of hazardous compounds from minor gasoline spills in the inter-tidal zone of the Miami River, Florida

The objective of this study was to develop a model to predict transport and fate of gasoline components of environmental concern in the Miami River by mathematically simulating the movement of dissolved benzene, toluene, xylene (BTX), and methyl-tertiary-butyl ether (MTBE) occurring from minor gasoline spills in the inter-tidal zone of the river. Computer codes were based on mathematical algorithms that acknowledge the role of advective and dispersive physical phenomena along the river and prevailing phase transformations of BTX and MTBE. Phase transformations included volatilization and settling. ^ The model used a finite-difference scheme of steady-state conditions, with a set of numerical equations that was solved by two numerical methods: Gauss-Seidel and Jacobi iterations. A numerical validation process was conducted by comparing the results from both methods with analytical and numerical reference solutions. Since similar trends were achieved after the numerical validation process, it was concluded that the computer codes algorithmically were correct. The Gauss-Seidel iteration yielded at a faster convergence rate than the Jacobi iteration. Hence, the mathematical code was selected to further develop the computer program and software. The model was then analyzed for its sensitivity. It was found that the model was very sensitive to wind speed but not to sediment settling velocity. ^ A computer software was developed with the model code embedded. The software was provided with two major user-friendly visualized forms, one to interface with the database files and the other to execute and present the graphical and tabulated results. For all predicted concentrations of BTX and MTBE, the maximum concentrations were over an order of magnitude lower than current drinking water standards. It should be pointed out, however, that smaller concentrations than the latter reported standards and values, although not harmful to humans, may be very harmful to organisms of the trophic levels of the Miami River ecosystem and associated waters. This computer model can be used for the rapid assessment and management of the effects of minor gasoline spills on inter-tidal riverine water quality. ^

An examination of the effects of a summer book-reading program on the language and early literacy outcomes of toddlers from high risk environments

The current study examined the impact of an early summer literacy program and the mediating effects of the home literacy environment on the language and literacy outcomes of a group of children at-risk for long-term developmental and academic delays. Participating children (n=54) were exposed to an intensive book-reading intervention each summer (June through mid August) over a 3-year period. The current study implemented an ex post facto, quasi-experimental design. This nonequivalent group design involved a pretest and posttest over three time points for a non-randomized treatment group and a matched non-treatment comparison group. Results indicated that literacy scores did improve for the children over the 3-year period; however, language scores did not experience the same rate of change over time. Receptive language was significantly impacted by attendance, and race/ethnicity. Expressive language was impacted significantly by gestational age and attendance. Results also indicated that language outcomes for young children who are exposed to a literacy program were higher than those who did not participate; however, only receptive language yielded significance at the p<.05 level. These study results also found that activities in the home that support literacy and learning do indeed impact language and literacy outcomes for these children, specifically, the age at which a child is read to, the number of books in the home, a child’s enjoyment of reading, and whether a child looks at books on his or her own impact language scores. This study concluded that at-risk young children do benefit from center-based literacy intervention. This literacy experience, however, is also driven by the children's home environment, their attendance to the program, whether they were premature or not and the type of caregiver.

Off-line and on-line affective recognition of a computer user through a biosignal processing approach

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. ^ In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment ("relaxation" vs. "stress") are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. ^ For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). ^ In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the "relaxation" vs. "stress" states.^

The relationship of immigrant status to perceptions of reading and reading literacy among young Black students: A test of the Cultural -Ecological Theory of School Performance

This study tests Ogbu and Simons' Cultural-Ecological Theory of School Performance using data from the Progress in International Reading Literacy Study of 2001 (PIRLS), a large-scale international survey and reading assessment involving fourth grade students from 35 countries, including the United States. This theory argues that Black immigrant students outperform their non-immigrant counterparts, academically, and that achievement differences are attributed to stronger educational commitment in Black immigrant families. Four hypotheses are formulated to test this theory: Black immigrant students have (a) more receptive attitudes toward reading; (b) a more positive reading self-concept; and (c) a higher level of reading literacy. Furthermore, (d) the relationship of immigrant status to reading perceptions and literacy persists after including selected predictors. These hypotheses are tested separately for girls and boys, while also examining immigrant students' generational status (i.e., foreign-born or second-generation). ^ PIRLS data from a subset of Black students (N=525) in the larger U.S. sample of 3,763 are analyzed to test the hypotheses, using analysis of variance, correlation and multiple regression techniques. Findings reveal that hypotheses a and b are not confirmed (contradicting the Cultural-Ecological Theory) and c and d are partially supported (lending partial support to the theory). Specifically, immigrant and non-immigrant students did not differ in attitudes toward reading or reading self-concept; second-generation immigrant boys outperformed both non-immigrant and foreign-born immigrant boys in reading literacy, but no differences were found among girls; and, while being second-generation immigrant had a relatively stronger relationship to reading literacy for boys, among girls, selected socio-cultural predictors, number of books in the home and length of U.S. residence, had relatively stronger relationship to reading self-concept than did immigrant status. This study, therefore, indicates that future research employing the Cultural-Ecological Theory should: (a) take gender and generational status into account (b) identify additional socio-cultural predictors of Black children's academic perceptions and performance; and (c) continue to build on this body of evidence-based knowledge to better inform educational policy and school personnel in addressing needs of all children. ^

Off-line and On-line Affective Recognition of a Computer User through A Biosignal Processing Approach

Physiological signals, which are controlled by the autonomic nervous system (ANS), could be used to detect the affective state of computer users and therefore find applications in medicine and engineering. The Pupil Diameter (PD) seems to provide a strong indication of the affective state, as found by previous research, but it has not been investigated fully yet. In this study, new approaches based on monitoring and processing the PD signal for off-line and on-line affective assessment (“relaxation” vs. “stress”) are proposed. Wavelet denoising and Kalman filtering methods are first used to remove abrupt changes in the raw Pupil Diameter (PD) signal. Then three features (PDmean, PDmax and PDWalsh) are extracted from the preprocessed PD signal for the affective state classification. In order to select more relevant and reliable physiological data for further analysis, two types of data selection methods are applied, which are based on the paired t-test and subject self-evaluation, respectively. In addition, five different kinds of the classifiers are implemented on the selected data, which achieve average accuracies up to 86.43% and 87.20%, respectively. Finally, the receiver operating characteristic (ROC) curve is utilized to investigate the discriminating potential of each individual feature by evaluation of the area under the ROC curve, which reaches values above 0.90. For the on-line affective assessment, a hard threshold is implemented first in order to remove the eye blinks from the PD signal and then a moving average window is utilized to obtain the representative value PDr for every one-second time interval of PD. There are three main steps for the on-line affective assessment algorithm, which are preparation, feature-based decision voting and affective determination. The final results show that the accuracies are 72.30% and 73.55% for the data subsets, which were respectively chosen using two types of data selection methods (paired t-test and subject self-evaluation). In order to further analyze the efficiency of affective recognition through the PD signal, the Galvanic Skin Response (GSR) was also monitored and processed. The highest affective assessment classification rate obtained from GSR processing is only 63.57% (based on the off-line processing algorithm). The overall results confirm that the PD signal should be considered as one of the most powerful physiological signals to involve in future automated real-time affective recognition systems, especially for detecting the “relaxation” vs. “stress” states.