Synthesis and properties of branched polyethylene/high-density polyethylene blends using a homogeneous binary catalyst system composed of early and late transition metal complexes

Branched polyethylene/high-density polyethylene blends (BPE/HDPE) with a wide range of molecular weights, melt flow indexes (MFI), and intrinsic viscosity were prepared using the homogeneous binary catalyst system composed by Ni(alpha-diimine)Cl-2 (1) (alpha-diimine = 1,4-bis(2,6-diisopropylphenyl)-acenaphthenediimine) and {Tp(Ms*)} TiCl3 (2) (Tp(Ms*)=hydridobis(3-mesitylpyrazol-1-yl)(5-mesityl-pyrazol-1-yl)) activated with MAO and/or TIBA in hexane at two different polymerization temperatures (30 and 55 degreesC) and by varying the nickel loading molar fraction (x(Ni)). At all Temperatures, a non-linear correlation between the x(Ni) and the productivity was observed, suggesting the occurrence of a synergistic effect between the nickel and the titanium catalyst precursors, which is more pronounced at 55 degreesC. The molecular weight of the BPE/HDPE blends considerably decreases with increasing Al/M molar ratio. The melt flow indexes (MFI) and intrinsic viscosities (eta) are strongly affected by x(Ni), but the melting temperatures are nearly constant, 132 +/- 3 degreesC. Dynamic mechanical thermal analysis (DMTA) shows the formation of different polymeric materials where the stiffness vanes according, to the x(Ni) and temperature used in the polymerization reaction. The surface morphology of the BPE/HDPE blends studied by scanning electron microscopy (SEM) revealed a low miscibility between the PE phases resulting in the formation of a sandwich structure after etching with o-xylene.

Optimizing feature selection through binary charged system search

Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.

Welded pipe fabrication; a course of instruction explaining all common cuts and layouts made on pipe, with explanations of short methods, the mathematics needed, and the tools used in developing patterns for, calculating, and fabricating any welded piping system.

Mode of access: Internet.

Porter's new system of mathematics : with the addition of a complete ready reckoner, for the use of farmers, mechanics, &c.

Mode of access: Internet.

A new system of practical astronomy : made plain and easy to those who have not studied mathematics : containing the elementary principles of the science, all the rules and tables necessary for making all the calculations for an almanac ... /

Includes index.

A Mixed Integer Quadratic Programming Model for the Low Autocorrelation Binary Sequence Problem

In this paper the low autocorrelation binary sequence problem (LABSP) is modeled as a mixed integer quadratic programming (MIQP) problem and proof of the model’s validity is given. Since the MIQP model is semidefinite, general optimization solvers can be used, and converge in a finite number of iterations. The experimental results show that IQP solvers, based on this MIQP formulation, are capable of optimally solving general/skew-symmetric LABSP instances of up to 30/51 elements in a moderate time. ACM Computing Classification System (1998): G.1.6, I.2.8.

The effectiveness of an intelligent tutoring system on the attitude and achievement of developmental mathematics students in a community college

This study examined the effectiveness of intelligent tutoring system instruction, grounded in John Anderson's ACT theory of cognition, on the achievement and attitude of developmental mathematics students in the community college setting. The quasi-experimental research used a pretest-posttest control group design. The dependent variables were problem solving achievement, overall achievement, and attitude towards mathematics. The independent variable was instructional method.^ Four intact classes and two instructors participated in the study for one semester. Two classes (n = 35) served as experimental groups; they received six lessons with real-world problems using intelligent tutoring system instruction. The other two classes (n = 24) served as control groups; they received six lessons with real-world problems using traditional instruction including graphing calculator support. It was hypothesized that students taught problem solving using the intelligent tutoring system would achieve more on the dependent variables than students taught without the intelligent tutoring system.^ Posttest mean scores for one teacher produced a significant difference in overall achievement for the experimental group. The same teacher had higher means, not significantly, for the experimental group in problem solving achievement. The study did not indicate a significant difference in attitude mean scores.^ It was concluded that using an intelligent tutoring system in problem solving instruction may impact student's overall mathematics achievement and problem solving achievement. Other factors must be considered, such as the teacher's classroom experience, the teacher's experience with the intelligent tutoring system, trained technical support, and trained student support; as well as student learning styles, motivation, and overall mathematics ability. ^

Effects of cooperative and individual integrated learning system on attitudes and achievement in mathematics

This study compares the effects of cooperative delivery (CD) and individual delivery (ID) of integrated learning system (ILS) instruction in mathematics on achievement, attitudes and behaviors in adult (16-21 yrs.) high school students (grades 9-13). The study was conducted in an urban adult high school in Miami-Dade County Public Schools using a pre-test/post-test design. Achievement was measured using the Test of Adult Basic Education (TABE) by CTB MC-Graw-Hill and Compass Learning. An attitudinal survey measured attitudes towards mathematics, the computer-related lessons, and attitudes toward group activities. Behavior was assessed using computer lab observations. ^ Two-way analyses of variance (ANOVA) were conducted on achievement (TABE and Compass) by group and time (pre and post). A one-way ANOVA was conducted on the overall attitude by group on the five components (i.e., content mathematics, delivery/computers, cooperative, partners, and self efficacy) and a one-way ANOVA was conducted on the on-task behavior by group. ^ The results of the study revealed that CD and ID students working on mathematics activities delivered by the ILS performed similarly on achievement tests of the TABE. The CD-ILS students had significantly better overall mathematics attitudes than the ID-ILS students and the ID-ILS group was on-task significantly more than the CD-ILS group. This study concludes that regularity and period of time over which the ILS is used may prove to be important variables although there were insufficient data to fully investigate the impact of models of use. Additionally, a minimum amount of time-on-system is necessary before gains can become apparent in innumeracy and increasing exposure to the system may have beneficial effects on learning. ^

Effects of Cooperative and Individual Integrated Learning System on Attitudes and Achievement in Mathematics

The purpose of this study was to determine the effects of a computer-based Integrated Learning Systems (ILS) model used with adult high school students engaging mathematics activities. This study examined achievement, attitudinal and behavior differences between students completing ILS activities in a traditional, individualized format compared to cooperative learning groups.

XML storage and retrieval using the semantic binary object -oriented database system (SEM-ODB)

Over the past five years, XML has been embraced by both the research and industrial community due to its promising prospects as a new data representation and exchange format on the Internet. The widespread popularity of XML creates an increasing need to store XML data in persistent storage systems and to enable sophisticated XML queries over the data. The currently available approaches to addressing the XML storage and retrieval issue have the limitations of either being not mature enough (e.g. native approaches) or causing inflexibility, a lot of fragmentation and excessive join operations (e.g. non-native approaches such as the relational database approach). ^ In this dissertation, I studied the issue of storing and retrieving XML data using the Semantic Binary Object-Oriented Database System (Sem-ODB) to leverage the advanced Sem-ODB technology with the emerging XML data model. First, a meta-schema based approach was implemented to address the data model mismatch issue that is inherent in the non-native approaches. The meta-schema based approach captures the meta-data of both Document Type Definitions (DTDs) and Sem-ODB Semantic Schemas, thus enables a dynamic and flexible mapping scheme. Second, a formal framework was presented to ensure precise and concise mappings. In this framework, both schemas and the conversions between them are formally defined and described. Third, after major features of an XML query language, XQuery, were analyzed, a high-level XQuery to Semantic SQL (Sem-SQL) query translation scheme was described. This translation scheme takes advantage of the navigation-oriented query paradigm of the Sem-SQL, thus avoids the excessive join problem of relational approaches. Finally, the modeling capability of the Semantic Binary Object-Oriented Data Model (Sem-ODM) was explored from the perspective of conceptually modeling an XML Schema using a Semantic Schema. ^ It was revealed that the advanced features of the Sem-ODB, such as multi-valued attributes, surrogates, the navigation-oriented query paradigm, among others, are indeed beneficial in coping with the XML storage and retrieval issue using a non-XML approach. Furthermore, extensions to the Sem-ODB to make it work more effectively with XML data were also proposed. ^

The efficacy of an interactive computer system for teaching developmental mathematics to college students

Many students are entering colleges and universities in the United States underprepared in mathematics. National statistics indicate that only approximately one-third of students in developmental mathematics courses pass. When underprepared students repeatedly enroll in courses that do not count toward their degree, it costs them money and delays graduation. This study investigated a possible solution to this problem: Whether using a particular computer assisted learning strategy combined with using mastery learning techniques improved the overall performance of students in a developmental mathematics course. Participants received one of three teaching strategies: (a) group A was taught using traditional instruction with mastery learning supplemented with computer assisted instruction, (b) group B was taught using traditional instruction supplemented with computer assisted instruction in the absence of mastery learning and, (c) group C was taught using traditional instruction without mastery learning or computer assisted instruction. Participants were students in MAT1033, a developmental mathematics course at a large public 4-year college. An analysis of covariance using participants' pretest scores as the covariate tested the null hypothesis that there was no significant difference in the adjusted mean final examination scores among the three groups. Group A participants had significantly higher adjusted mean posttest score than did group C participants. A chi-square test tested the null hypothesis that there were no significant differences in the proportions of students who passed MAT1033 among the treatment groups. It was found that there was a significant difference in the proportion of students who passed among all three groups, with those in group A having the highest pass rate and those in group C the lowest. A discriminant factor analysis revealed that time on task correctly predicted the passing status of 89% of the participants. ^ It was concluded that the most efficacious strategy for teaching developmental mathematics was through the use of mastery learning supplemented by computer-assisted instruction. In addition, it was noted that time on task was a strong predictor of academic success over and above the predictive ability of a measure of previous knowledge of mathematics.^

The effectiveness of an intelligent tutoring system on the attitude and achievement of developmental mathematics students in a community college

This study examined the effectiveness of intelligent tutoring system instruction, grounded in John Anderson's ACT theory of cognition, on the achievement and attitude of developmental mathematics students in the community college setting. The quasi-experimental research used a pretest-posttest control group design. The dependent variables were problem solving achievement, overall achievement, and attitude towards mathematics. The independent variable was instructional method. Four intact classes and two instructors participated in the study for one semester. Two classes (n = 35) served as experimental groups; they received six lessons with real-world problems using intelligent tutoring system instruction. The other two classes (n = 24) served as control groups; they received six lessons with real-world problems using traditional instruction including graphing calculator support. It was hypothesized that students taught problem solving using the intelligent tutoring system would achieve more on the dependent variables than students taught without the intelligent tutoring system. Posttest mean scores for one teacher produced a significant difference in overall achievement for the experimental group. The same teacher had higher means, not significantly, for the experimental group in problem solving achievement. The study did not indicate a significant difference in attitude mean scores. It was concluded that using an intelligent tutoring system in problem solving instruction may impact student's overall mathematics achievement and problem solving achievement. Other factors must be considered, such as the teacher's classroom experience, the teacher's experience with the intelligent tutoring system, trained technical support, and trained student support; as well as student learning styles, motivation, and overall mathematics ability.

Digital signal processing implementation for near real-time wavelet transformation system for binary images

Communication has become an essential function in our civilization. With the increasing demand for communication channels, it is now necessary to find ways to optimize the use of their bandwidth. One way to achieve this is by transforming the information before it is transmitted. This transformation can be performed by several techniques. One of the newest of these techniques is the use of wavelets. Wavelet transformation refers to the act of breaking down a signal into components called details and trends by using small waveforms that have a zero average in the time domain. After this transformation the data can be compressed by discarding the details, transmitting the trends. In the receiving end, the trends are used to reconstruct the image. In this work, the wavelet used for the transformation of an image will be selected from a library of available bases. The accuracy of the reconstruction, after the details are discarded, is dependent on the wavelets chosen from the wavelet basis library. The system developed in this thesis takes a 2-D image and decomposes it using a wavelet bank. A digital signal processor is used to achieve near real-time performance in this transformation task. A contribution of this thesis project is the development of DSP-based test bed for the future development of new real-time wavelet transformation algorithms.