An Agent Based Architecture ForComponent-Based Software Development

Today\u27s companies are facing major changes in their organizations due to the changing environment in which they operate. They have to decrease the costs, decrease time to market, and improve quality. These imperatives have led to changes in the placement and role of IS department in the organization (Fried, 1995). Together with the recent advances in communication technology and powerful workstations, end-users have become more involved with the application development. Besides, the business processes change so fast that the traditional SDLC is too slow to keep up with these fluctuating requirements in the application domain. The need for rapid application development to respond to users\u27 changing needs, among the other mentioned trends, encourages the use of reusable software components. In (ATP, 1995), it is stated that at the level of vertical-market products, software design costs are generally $1 million to$10 million with near zero cost of reproducing additional units, and the typical production quantity is one. Reusable software components help organizations recover costs, improve quality through specialization, and develop rapidly from existing components

Robust portfolio choice with CVaR and VaR under distribution and mean return ambiguity

Cataloged from PDF version of article.We consider the problem of optimal portfolio choice using the Conditional Value-at-Risk (CVaR) and Value-at-Risk (VaR) measures for a market consisting of n risky assets and a riskless asset and where short positions are allowed. When the distribution of returns of risky assets is unknown but the mean return vector and variance/covariance matrix of the risky assets are fixed, we derive the distributionally robust portfolio rules. Then, we address uncertainty (ambiguity) in the mean return vector in addition to distribution ambiguity, and derive the optimal portfolio rules when the uncertainty in the return vector is modeled via an ellipsoidal uncertainty set. In the presence of a riskless asset, the robust CVaR and VaR measures, coupled with a minimum mean return constraint, yield simple, mean-variance efficient optimal portfolio rules. In a market without the riskless asset, we obtain a closed-form portfolio rule that generalizes earlier results, without a minimum mean return restriction

Mean semi-deviation from a target and robust portfolio choice under distribution and mean return ambiguity

Cataloged from PDF version of article.We consider the problem of optimal portfolio choice using the lower partial moments risk measure for a market consisting of n risky assets and a riskless asset. For when the mean return vector and variance/covariance matrix of the risky assets are specified without specifying a return distribution, we derive distributionally robust portfolio rules. We then address potential uncertainty (ambiguity) in the mean return vector as well, in addition to distribution ambiguity, and derive a closed-form portfolio rule for when the uncertainty in the return vector is modelled via an ellipsoidal uncertainty set. Our result also indicates a choice criterion for the radius of ambiguity of the ellipsoid. Using the adjustable robustness paradigm we extend the single-period results to multiple periods, and derive closed-form dynamic portfolio policies which mimic closely the single-period policy. © 2013 Elsevier B.V. All rights reserved

Continuation method for nonlinear complementarity problems via normal maps

Cataloged from PDF version of article.In a recent paper by Chen and Mangasarian (C. Chen, O.L. Mangasarian, A class of smoothing functions for nonlinear and mixed complementarity problems, Computational Optimization and Applications 2 (1996), 97±138) a class of parametric smoothing functions has been proposed to approximate the plus function present in many optimization and complementarity related problems. This paper uses these smoothing functions to approximate the normal map formulation of nonlinear complementarity problems (NCP). Properties of the smoothing function are investigated based on the density functions that de®nes the smooth approximations. A continuation method is then proposed to solve the NCPs arising from the approximations. Su cient conditions are provided to guarantee the boundedness of the solution trajectory. Furthermore, the structure of the subproblems arising in the proposed continuation method is analyzed for di erent choices of smoothing functions. Computational results of the continuation method are reported. Ó 1999 Elsevier Science B.V. All rights reserved

Low/Zero-Carbon Buildings for a Sustainable Future

Fossil fuel-based energy consumption is still dominant in the world today, and there is a consensus on the limited reserves of these energy resources. Therefore, there is a strong stimulation into clean energy technologies to narrow the gap between fossil fuels and renewables. In this respect, several commitments and codes are proposed and adopted for a low energy-consuming world and for desirable environmental conditions. Sectoral energy consumption analyses clearly indicate that buildings are of vital importance in terms of energy consumption figures. From this point of view, buildings have a great potential for decisive and urgent reduction of energy consumption levels and thus greenhouse gas (GHG) emissions. Among the available retrofit solutions, greenery systems (GSs) stand for a reliable, cost-effective and eco-friendly method for remarkablemitigation of energy consumed in buildings. Through the works comparing the thermal regulation performance of uninsulated and green roofs, it is observed that the GS provides 20°C lower surface temperature in operation. Similar to green roofs, vertical greenery systems (VGSs) also reduce energy demand to approximately 25% as a consequence of wind blockage effects in winter. Therefore, within the scope of this chapter, GSs are evaluated for a reliable and effective retrofit solution toward low/zero carbon buildings (L/ZCBs)

Data Needs for Children with Special Needs in Refugee Populations

This article examines the challenges that affect the identification and assessment of refugee children with special needs in Turkey and provides recommendations related to data collection and assessment of these learners that is broadly relevant in refugee settings

Opioid prescribing by multiple providers in Medicare: retrospective observational study of insurance claims

Objectives: To estimate the frequency and characteristics of opioid prescribing by multiple providers in Medicare and the association with hospital admissions related to opioid use. Design: Retrospective cohort study. Setting: Database of prescription drugs and medical claims in 20% random sample of Medicare beneficiaries in 2010. Participants: 1 808 355 Medicare beneficiaries who filled at least one prescription for an opioid from a pharmacy in 2010. Main outcome measures Proportion of beneficiaries who filled opioid prescriptions from multiple providers; proportion of these prescriptions that were concurrently supplied; adjusted rates of hospital admissions related to opioid use associated with multiple provider prescribing. Results: Among 1 208 100 beneficiaries with an opioid prescription, 418 530 (34.6%) filled prescriptions from two providers, 171 420 (14.2%) from three providers, and 143 344 (11.9%) from four or more providers. Among beneficiaries with four or more opioid providers, 110 671 (77.2%) received concurrent opioid prescriptions from multiple providers, and the dominant provider prescribed less than half of the mean total prescriptions per beneficiary (7.9/15.2 prescriptions). Multiple provider prescribing was highest among beneficiaries who were also prescribed stimulants, non-narcotic analgesics, and central nervous system, neuromuscular, and antineoplastic drugs. Hospital admissions related to opioid use increased with multiple provider prescribing: the annual unadjusted rate of admission was 1.63% (95% confidence interval 1.58 to 1.67%) for beneficiaries with one provider, 2.08% (2.03% to 2.14%) for two providers, 2.87% (2.77% to 2.97%) for three providers, and 4.83% (4.70% to 4.96%) for four or more providers. Results were similar after covariate adjustment. Conclusions: Concurrent opioid prescribing by multiple providers is common in Medicare patients and is associated with higher rates of hospital admission related to opioid use

On Newton's method for Huber's robust M-estimation problems in linear regression

The Newton method of Madsen and Nielsen (1990) for computing Huber's robust M-estimate in linear regression is considered. The original method was proved to converge finitely for full rank problems under some additional restrictions on the choice of the search direction and the step length in some degenerate cases. It was later observed that these requirements can be relaxed in a practical implementation while preserving the effectiveness and even improving the efficiency of the method. In the present paper these enhancements to the original algorithm are studied and the finite termination property of the algorithm is proved without any assumptions on the M-estimation problems

Evaluation of the Effectiveness of a Gaze-Based Training Intervention on Latent Hazard Anticipation Skills for Young Drivers: A Driving Simulator Study

A PC-based training program (Road Awareness and Perception Training or RAPT; Pradhan et al., 2009), proven effective for improving young novice drivers\u27 hazard anticipation skills, did not fully maximize the hazard anticipation performance of young drivers despite the use of similar anticipation scenarios in both, the training and the evaluation drives. The current driving simulator experiment examined the additive effects of expert eye movement videos following RAPT training on young drivers\u27 hazard anticipation performance compared to video-only and RAPT-only conditions. The study employed a between-subject design in which 36 young participants (aged 18-21) were equally and randomly assigned to one of three experimental conditions, were outfitted with an eye tracker and drove four unique scenarios on a driving simulator to evaluate the effect of treatment on their anticipation skills. The results indicate that the young participants that viewed the videos of expert eye movements following the completion of RAPT showed significant improvements in their hazard anticipation ability (85%) on the subsequent experimental evaluation drives compared to those young drivers who were only exposed to either the RAPT training (61%) or the Video (43%). The results further imply that videos of expert eye movements shown immediately after RAPT training may improve the drivers\u27 anticipation skills by helping them map and integrate the spatial and tactical knowledge gained in a training program within dynamic driving environments involving latent hazards. © 2018 by the authors