Forest and range mapping in the Houston area with ERTS-1

ERTS-1 data acquired over the Houston area has been analyzed for applications to forest and range mapping. In the field of forestry the Sam Houston National Forest (Texas) was chosen as a test site, (Scene ID 1037-16244). Conventional imagery interpretation as well as computer processing methods were used to make classification maps of timber species, condition and land-use. The results were compared with timber stand maps which were obtained from aircraft imagery and checked in the field. The preliminary investigations show that conventional interpretation techniques indicated an accuracy in classification of 63 percent. The computer-aided interpretations made by a clustering technique gave 70 percent accuracy. Computer-aided and conventional multispectral analysis techniques were applied to range vegetation type mapping in the gulf coast marsh. Two species of salt marsh grasses were mapped

Theory of size-dependent resonance Raman intensities in InP nanocrystals

The resonance Raman spectrum of InP nanocrystals is characterized by features ascribable to both longitudinal (LO) and transverse (TO) optical modes. The intensity ratio of these modes exhibits a strong size dependence. To calculate the size dependence of the LO and TO Raman cross sections, we combine existing models of Raman scattering, the size dependence of electronic and vibrational structure, and electron vibration coupling in solids. For nanocrystals with a radius >10 Å, both the LO and TO coupling strengths increase with increasing radius. This, together with an experimentally observed increase in the electronic dephasing rate with decreasing size, allows us to account for the observed ratio of LO/TO Raman intensities

Estimating spillovers using imprecisely measured networks

In many experimental contexts, whether and how network interactions impact the outcome of interest for both treated and untreated individuals are key concerns. Networks data is often assumed to perfectly represent these possible interactions. This paper considers the problem of estimating treatment effects when measured connections are, instead, a noisy representation of the true spillover pathways. We show that existing methods, using the potential outcomes framework, yield biased estimators in the presence of this mismeasurement. We develop a new method, using a class of mixture models, that can account for missing connections and discuss its estimation via the Expectation-Maximization algorithm. We check our method's performance by simulating experiments on real network data from 43 villages in India. Finally, we use data from a previously published study to show that estimates using our method are more robust to the choice of network measure

Sums and differences of four k-th powers

We prove an upper bound for the number of representations of a positive integer $N$ as the sum of four $k$-th powers of integers of size at most $B$, using a new version of the Determinant method developed by Heath-Brown, along with recent results by Salberger on the density of integral points on affine surfaces. More generally we consider representations by any integral diagonal form. The upper bound has the form $O_{N}(B^{c/\sqrt{k}})$, whereas earlier versions of the Determinant method would produce an exponent for $B$ of order $k^{-1/3}$ in this case. Furthermore, we prove that the number of representations of a positive integer $N$ as a sum of four $k$-th powers of non-negative integers is at most $O_{\epsilon}(N^{1/k+2/k^{3/2}+\epsilon})$ for $k \geq 3$, improving upon bounds by Wisdom.Comment: 18 pages. Mistake corrected in the statement of Theorem 1.2. To appear in Monatsh. Mat

Feasibility study of high performance hydrogen-oxygen fuel cells Final technical report

Engineering analysis for evaluating moving bed and mediator hydrogen-oxygen fuel cell conceptual design

The control of a nuclear reactor using helium- 3 gas control elements

Control system for water moderated reactor using helium-3 ga

Understanding Leader Problem-Solving Style Preferences in an Organizational Hierarchy

This study explored the problem solving styles of individuals in leadership positions in an attempt to identify whether specific problem solving preferences existed among leaders. The results indicated that in this organization the leadership team did exhibit a preference toward the Ideator style of problem solving. In addition to identifying problem solving preferences of leaders, this study also attempted to support other research (Mann 2003) and ascertain whether problem solving is a component of leadership. According to the results of the study and related literature, evidence supports the theory that creative problem solving is an important component of leadership and that it can be enhanced by training (Wheeler 2001). This study demonstrates its significance as there are various benefits an organization or an individual may gain by understanding problem-solving preferences. For example, organizations can align similar or different styles when creating workforce teams, demands of specific positions may be examined and compared against individual preferences, and personal/professional development may include awareness to preferences as well as provide recommendations on improving areas of weakness and sensitivity to other styles. Overall, “people should become aware of their Creative Problem Solving preferences so they can better understand their strengths and weaknesses when solving problems creatively” (Puccio, 1999 p. 172)

Does Self-Complexity Predict Dishonest Behavior Via Cognitive Dissonance?

Psychologists disagree about what, if any, benefit high self-complexity might provide. Although Linville (1987) demonstrated that high complexity buffers against stress, other studies have found that it leads to more negative outcomes in the long term (Diehl et al., 2001). Cognitive dissonance is an important factor in regulating behavior, particularly moral behavior (Aronson, Fried, & Stone, 1999), and may explain how self-complexity leads to negative life outcomes. The present study examined if high self-complexity might buffer against the tension of cognitive dissonance, thus increasing the likelihood of dishonest behavior. Participants completed a selfcomplexity measure, and then they completed a dissonance-rousing task where they must choose between providing honest answers or maximizing their personal gain. Regression analysis showed that high self-complexity predicted greater dishonest behavior, but a disruption of cognitive dissonance could not account for this relationship. The possibility of personality as a potential mediating variable for the established relationship, and avenues for future research, are discussed