Iowa Communications Network Performance Plan, FY 2009

Agency Performance Plan, Iowa Communications Network

On bounds for network revenue management

The Network Revenue Management problem can be formulated as a stochastic dynamic programming problem (DP or the\optimal" solution V *) whose exact solution is computationally intractable. Consequently, a number of heuristics have been proposed in the literature, the most popular of which are the deterministic linear programming (DLP) model, and a simulation based method, the randomized linear programming (RLP) model. Both methods give upper bounds on the optimal solution value (DLP and PHLP respectively). These bounds are used to provide control values that can be used in practice to make accept/deny decisions for booking requests. Recently Adelman [1] and Topaloglu [18] have proposed alternate upper bounds, the affine relaxation (AR) bound and the Lagrangian relaxation (LR) bound respectively, and showed that their bounds are tighter than the DLP bound. Tight bounds are of great interest as it appears from empirical studies and practical experience that models that give tighter bounds also lead to better controls (better in the sense that they lead to more revenue). In this paper we give tightened versions of three bounds, calling themsAR (strong Affine Relaxation), sLR (strong Lagrangian Relaxation) and sPHLP (strong Perfect Hindsight LP), and show relations between them. Speciffically, we show that the sPHLP bound is tighter than sLR bound and sAR bound is tighter than the LR bound. The techniques for deriving the sLR and sPHLP bounds can potentially be applied to other instances of weakly-coupled dynamic programming.

European research funding and regional technological capabilities: Network composition analysis

We use network and correspondence analysis to describe the compositionof the research networks in the European BRITE--EURAM program. Our mainfinding is that 27\% of the participants in this program fall into one oftwo sets of highly ``interconnected'' institutions --one centered aroundlarge firms (with smaller firms and research centers providing specializedservices), and the other around universities--. Moreover, these ``hubs''are composed largely of institutions coming from the technologically mostadvanced regions of Europe. This is suggestive of the difficulties of attainingEuropean ``cohesion'', as technically advanced institutions naturally linkwith partners of similar technological capabilities.

An enhanced concave program relaxation for choice network revenue management

The network choice revenue management problem models customers as choosing from an offer-set, andthe firm decides the best subset to offer at any given moment to maximize expected revenue. The resultingdynamic program for the firm is intractable and approximated by a deterministic linear programcalled the CDLP which has an exponential number of columns. However, under the choice-set paradigmwhen the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has beenproposed but finding an entering column has been shown to be NP-hard. In this paper, starting with aconcave program formulation based on segment-level consideration sets called SDCP, we add a class ofconstraints called product constraints, that project onto subsets of intersections. In addition we proposea natural direct tightening of the SDCP called ?SDCP, and compare the performance of both methodson the benchmark data sets in the literature. Both the product constraints and the ?SDCP method arevery simple and easy to implement and are applicable to the case of overlapping segment considerationsets. In our computational testing on the benchmark data sets in the literature, SDCP with productconstraints achieves the CDLP value at a fraction of the CPU time taken by column generation and webelieve is a very promising approach for quickly approximating CDLP when segment consideration setsoverlap and the consideration sets themselves are relatively small.

Iowa Communications Network, Strategic Plan, 2007

This report outlines the strategic plan for Iowa Communications Network, goals and mission.

Fiscal Year 2008 Annual Report of the Iowa Communications Network, December 2008

This is the Annual Report for Fiscal Year 2007 (July 1, 2007-June 30, 2008) for the Iowa Communications Network.

Iowa Department of Transportation Fiscal Year 2008 Report of Savings by Using Video Conferencing Through Iowa Communications Network to the Iowa General Assembly Pursuant to Iowa Code § II 84 Acts and Joint Resolutions Enacted at the 1994 Regular Session of the 75th General Assembly of the State of Iowa Iowa Code §8D.10 Report of Savings by State Agencies

Iowa Code § 8D.10 requires certain state agencies prepare an annual report to the General Assembly certifying the identified savings associated with that state agency’s use of the Iowa Communications Network (ICN). This report covers estimated cost savings related to video conferencing via ICN for the Iowa Department of Transportation (DOT). In FY 2008, the DOT did not conduct any sessions utilizing ICN’s video conferencing system. Therefore, no cost savings were calculated for this report.

A note on the dual scaling of dominance data and its relationship to correspondence analysis

Dual scaling of a subjects-by-objects table of dominance data (preferences,paired comparisons and successive categories data) has been contrasted with correspondence analysis, as if the two techniques were somehow different. In this note we show that dual scaling of dominance data is equivalent to the correspondence analysis of a table which is doubled with respect to subjects. We also show that the results of both methods can be recovered from a principal components analysis of the undoubled dominance table which is centred with respect to subject means.

Distribution and abundance of six species of fish larvae in peruvian waters and their relationship with physical and biological environment

Estudio de muestras recolectadas con el BIONESS a varias profundidades en trece estaciones.

Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.

Utilização da Virtual Private Network Caso da Universidade Jean Piaget de Cabo Verde

O trabalho científico realizado no âmbito dos regulamentos dos cursos de graduação para a obtenção de grau de licenciatura na Universidade Jean Piaget de Cabo Verde, pretende analisar a utilização da VPN, mais concretamente na Universidade Jean Piaget de Cabo Verde. Durante a elaboração desse trabalho será feito uma breve introdução sobre redes de computadores, sobre segurança na rede, um enquadramento teórico sobre VPN, bem como a sua contextualização num ambiente organizacional, mostrando as várias vantagens do seu uso, custo e beneficio e por fim o caso prático na Universidade Jean Piaget.

Red meat and cancer risk in a network of case-control studies focusing on cooking practices.

BACKGROUND: Consumption of red meat has been related to increased risk of several cancers. Cooking methods could modify the magnitude of this association, as production of chemicals depends on the temperature and duration of cooking. METHODS: We analyzed data from a network of case-control studies conducted in Italy and Switzerland between 1991 and 2009. The studies included 1465 oral and pharyngeal, 198 nasopharyngeal, 851 laryngeal, 505 esophageal, 230 stomach, 1463 colon, 927 rectal, 326 pancreatic, 3034 breast, 454 endometrial, 1031 ovarian, 1294 prostate and 767 renal cancer cases. Controls included 11 656 patients admitted for acute, non-neoplastic conditions. Odds ratios (ORs) and confidence intervals (CIs) were estimated by multiple logistic regression models, adjusted for known confounding factors. RESULTS: Daily intake of red meat was significantly associated with the risk of cancer of the oral cavity and pharynx (OR for increase of 50 g/day = 1.38; 95% CI: 1.26-1.52), nasopharynx (OR = 1.29; 95% CI: 1.04-1.60), larynx (OR = 1.46; 95% CI: 1.30-1.64), esophagus (OR = 1.46; 95% CI: 1.23-1.72), colon (OR = 1.17; 95% CI: 1.08-1.26), rectum (OR = 1.22; 95% CI:1.11-1.33), pancreas (OR = 1.51; 95% CI: 1.25-1.82), breast (OR = 1.12; 95% CI: 1.04-1.19), endometrium (OR = 1.30; 95% CI: 1.10-1.55) and ovary (OR = 1.29; 95% CI: 1.16-1.43). Fried meat was associated with a higher risk of cancer of oral cavity and pharynx (OR = 2.80; 95% CI: 2.02-3.89) and esophagus (OR = 4.52; 95% CI: 2.50-8.18). Risk of prostate cancer increased for meat cooked by roasting/grilling (OR = 1.31; 95% CI: 1.12-1.54). No heterogeneity according to cooking methods emerged for other cancers. Nonetheless, significant associations with boiled/stewed meat also emerged for cancer of the nasopharynx (OR = 1.97; 95% CI: 1.30-3.00) and stomach (OR = 1.86; 95% CI: 1.20-2.87). CONCLUSIONS: Our analysis confirmed red meat consumption as a risk factor for several cancer sites, with a limited impact of cooking methods. These findings, thus, call for a limitation of its consumption in populations of Western countries.

The complete amino acid sequence for brain beta spectrin (beta fodrin): relationship to globin sequences.

The amino acid sequence of mouse brain beta spectrin (beta fodrin), deduced from the nucleotide sequence of complementary DNA clones, reveals that this non-erythroid beta spectrin comprises 2363 residues, with a molecular weight of 274,449 Da. Brain beta spectrin contains three structural domains and we suggest the position of several functional domains including f-actin, synapsin I, ankyrin and spectrin self association sites. Analysis of deduced amino acid sequences indicated striking homology and similar structural characteristics of brain beta spectrin repeats beta 11 and beta 12 to globins. In vitro analysis has demonstrated that heme is capable of specific attachment to brain spectrin, suggesting possible new functions in electron transfer, oxygen binding, nitric oxide binding or heme scavenging.