Photostability of polyetherurethaneureas

Polyetherurethaneureas (PEUUs) were synthesised from polyethylene-glycols (PEGs) of molecular weight 400, 600 and 1000, 4,4′-diphenylmethanediisocyanate (MDI) and aliphatic diamine chain extenders, 1,3-propanediamine (PDA) and 1,6-hexanediamine (HDA). Polymer films were irradiated with 365 nm light at 293 K and the effects of polyether soft segment length and urea hard segment on photo-oxidative stability were studied by following the variation in weight-average molecular weight (M _w), gel formation and stress-strain properties. Changes in ultraviolet and infrared spectroscopy were monitored on photo-oxidation and hydroperoxide content determined. The soft segment length was increased by increasing the molecular weight of PEG from 400 to 1000 and hard segment structure was changed by variation of diamine. It was noted that the structure of urea and polyether soft segment length plays an important role in photostability of PEUUs. PDA chain extended PEUUs were more stable than HDA chain extended PEUUs.     

Spatial interest pixels (SIPs): useful low-level features of visual media data

Visual media data such as an image is the raw data representation for many important applications. Reducing the dimensionality of raw visual media data is desirable since high dimensionality degrades not only the effectiveness but also the efficiency of visual recognition algorithms. We present a comparative study on spatial interest pixels (SIPs), including eight-way (a novel SIP detector), Harris, and Lucas‐Kanade, whose extraction is considered as an important step in reducing the dimensionality of visual media data. With extensive case studies, we have shown the usefulness of SIPs as low-level features of visual media data. A class-preserving dimension reduction algorithm (using GSVD) is applied to further reduce the dimension of feature vectors based on SIPs. The experiments showed its superiority over PCA.

Amounts of nondeterminism in finite automata

Summary The amount of nondeterminism in a nondeterministic finite automaton (NFA) is measured by counting the minimal number of guessing points a string w has to pass through on its way to an accepting state. NFA's with more nondeterminism can achieve greater savings in the number of states over their deterministic counterparts than NFA's with less nondeterminism. On the other hand, for some nontrivial infinite regular languages a deterministic finite automaton (DFA) can already be quite succinct in the sense that NFA's need as many states (and even context-free grammars need as many nonterminals) as the minimal DFA has states.This research was supported in part by the National Science Foundation under Grant No. MCS 76-10076     

Strict interpretations of deterministic pushdown acceptors

Three results are established. The first is that every nondeterministic strict interpretation of a deterministic pushdown acceptor (dpda) has an equivalent, deterministic, strict interpretation. The second is that ifM ₁ andM ₂ are two compatible strict interpretations of the dpdaM, then there exist deterministic strict interpretationsM andM such thatL(M ) =L(M ₁)L(M ₂) andL(M ) =L(M ₁)L(M ₂). The third states that there is no dpda whose strict interpretations yield all the deterministic context-free languages.This author was supported in part by the National Science Foundation under Grant MCS-77-22323.     

Choroidal neovascular membrane in Best's vitelliform macular dystrophy

The right eye of a 9-year-old white boy with Best's vitelliform macular dystrophy had an intact egg-yolk lesion and a retinal pigment epithelial defect superiorly, suggesting an early pseudohypopyon stage. The disruptive phase of the left eye showed subretinal hemorrhages, a "signet ring," and a subretinal neovascular membrane.     

Searching for points-to analysis

The points-to analysis problem is to find the pointer relationships that could arise during program execution. Many points-to analysis algorithms exist, each making a particular trade off between cost of the analysis and precision of the results. In this paper, we show how points-to analysis algorithms can be defined as transformed versions of an exact algorithm. We present a set of program transformations over a general program model and use them to define some existing points-to analysis algorithms. Doing so makes explicit the approximations involved in these algorithms. We also show how the transformations can be used to define new points-to analysis algorithms. Our transformations are generic and may be useful in the design of other program analysis algorithms.     

Supersonic Nozzle Flow Simulations for Particle Coating Applications: Effects of Shockwaves,Nozzle Geometry,Ambient Pressure,and Substrate Location upon Flow Characteristics

Characteristics of supersonic flow are examined with specific regard to nano-particle thin-film coating. Effects of shockwaves, nozzle geometry, chamber pressure, and substrate location were studied computationally. Shockwaves are minimized to reduce fluctuations in flow properties at the discontinuities across diamond shock structures. Nozzle geometry was adjusted to ensure optimal expansion (i.e., P _exit = P _ambient), where shock formation was significantly reduced and flow kinetic energy maximized. When the ambient pressure was reduced from 1 to 0.01316 bar, the nozzle’s diverging angle must be increased to yield the optimum condition of minimized adversed effects. Beyond some critical distance, substrate location did not seem to be a sensitive parameter on flow characteristics when P _amb = 0.01316 bar; however, overly close proximity to the nozzle exit caused flow disturbances inside the nozzle, thereby adversely affecting coating gas flow.     

Assessing Flood Induced Land-Cover Changes Using Remote Sensing and Fuzzy Approach in Eastern Gujarat (India)

Natural hazards such as flooding can cause changes in land-cover. The present study deals with the changes in land-cover in three worst affected districts (Anand, Vadodara and Kheda) of Gujarat state in India due to severe flood during 2005. The Indian Remote Sensing (IRS) P6 Linear Imaging Self Scanning (LISS) III satellite imageries of pre- and post-flooding periods were used as sources of information for the study area. Three classification approaches (unsupervised ISODATA, supervised Maximum Likelihood Classifier, and fuzzy rule based) were used to extract flood induced land-cover information. Results obtained from the above classification approaches were compared. Soft computing technique such as fuzzy based image classification gave better separability amongst classes as compared to hard classification techniques. The accuracy assessment showed that the fuzzy approach can predict land-cover more accurately than traditional approach and also showed great potential for dealing with mapping of flood induced land-cover. Unsupervised classification results for the period October 2004 to October 2005 revealed decrease in inland water bodies (14.49%) and agricultural area (6.42%) while increase in remaining land-cover. During February 2005 to February 2006, all land-cover classes decreased except agricultural fallow and sparse vegetation. In case of supervised classification, decreasing trend was observed only in case of agricultural area (6.78%) during October 2004 to October 2005. Similarly, during February 2005 to February 2006, increase in coastal water bodies (0.73%) and sparse vegetation (1.7%) was observed where as decreasing trend was noticed in the remaining land-cover classes. In fuzzy based classification, only decrease in agricultural area (7.09%) was observed from October 2004 to October 2005, whereas during February 2005 to February 2006, decrease in area was exhibited in all land-cover classes except coastal water bodies and sparse vegetation. Change detection indicated interchange of areas between inland and coastal water bodies and decrease in agricultural area leading to increase in area of agricultural fallow and sparse vegetation.