A theory of structural model validity in simulation.

During the last decennia, the practice of simulation has become increasingly popular among many system analysts, model builders and general scientists for the purpose of studying complex systems that surpass the operability of analytical solution techniques. As a consequence of the pragmatic orientation of simulation, a vital stage for a successful application is the issue of validating a constructed simulation model. Employing the model as an effective instrument for assessing the benefit of structural changes or for predicting future observations makes validation an essential part of any productive simulation study. The diversity of the employment field of simulation however brings about that there exists an irrefutable level of ambiguity concerning the principal subject of this validation process. Further, the literature has come up with a plethora of ad hoc validation techniques that have mostly been inherited from standard statistical analysis. It lies within the aim of this paper to reflect on the issue of validation in simulation and to present the reader with a topological parallelism of the classical philosophical polarity of objectivism versus relativism. First, we will position validation in relation to verification and accreditation and elaborate on the prime actors in validation, i.e. a conceptual model, a formal model and behaviour. Next, we will formally derive a topological interpretation of structural validation for both objectivists and relativists. As will be seen, recent advances in the domain of fuzzy topology allow for a valuable metaphor of a relativistic attitude towards modelling and structural validation. Finally, we will discuss several general types of modelling errors that may occur and examine their repercussion on the natural topological spaces of objectivists and relativists. We end this paper with a formal, topological oriented definition of structural model validity for both objectivists and relativists. The paper is concluded with summarising the most important findings and giving a direction for future research.Model; Simulation; Theory; Scientists; Processes; Statistical analysis;

Aquaculture Productivity Convergence in India: A Spatial Econometric Perspective

This paper provides an illustration of evaluating productivity convergence using spatial econometric modelling framework for the aquaculture sector in India. Productivity has been measured using Total Factor Productivity (TFP). The b- and s-convergence concepts that are used to test the convergence hypothesis have been extended to examine the possible presence of spatial autocorrelation and spatial heterogeneity. The results have confirmed the productivity convergence hypothesis, the presence of spillover effects on TFP growth and the presence of spatial regimes in the TFP convergence process which have policy implications. The paper concludes by providing recommendations for further research.Agricultural and Food Policy,

Local Stereo Matching Using Adaptive Local Segmentation

We propose a new dense local stereo matching framework for gray-level images based on an adaptive local segmentation using a dynamic threshold. We define a new validity domain of the fronto-parallel assumption based on the local intensity variations in the 4-neighborhood of the matching pixel. The preprocessing step smoothes low textured areas and sharpens texture edges, whereas the postprocessing step detects and recovers occluded and unreliable disparities. The algorithm achieves high stereo reconstruction quality in regions with uniform intensities as well as in textured regions. The algorithm is robust against local radiometrical differences; and successfully recovers disparities around the objects edges, disparities of thin objects, and the disparities of the occluded region. Moreover, our algorithm intrinsically prevents errors caused by occlusion to propagate into nonoccluded regions. It has only a small number of parameters. The performance of our algorithm is evaluated on the Middlebury test bed stereo images. It ranks highly on the evaluation list outperforming many local and global stereo algorithms using color images. Among the local algorithms relying on the fronto-parallel assumption, our algorithm is the best ranked algorithm. We also demonstrate that our algorithm is working well on practical examples as for disparity estimation of a tomato seedling and a 3D reconstruction of a face

A hybrid genetic algorithm for solving a layout problem in the fashion industry.

As of this writing, many success stories exist yet of powerful genetic algorithms (GAs) in the field of constraint optimisation. In this paper, a hybrid, intelligent genetic algorithm will be developed for solving a cutting layout problem in the Belgian fashion industry. In an initial section, an existing LP formulation of the cutting problem is briefly summarised and is used in further paragraphs as the core design of our GA. Through an initial attempt of rendering the algorithm as universal as possible, it was conceived a threefold genetic enhancement had to be carried out that reduces the size of the active solution space. The GA is therefore rebuilt using intelligent genetic operators, carrying out a local optimisation and applying a heuristic feasibility operator. Powerful computational results are achieved for a variety of problem cases that outperform any existing LP model yet developed.Fashion; Industry;

Demand for Fish by Species in India: Three-stage Budgeting Framework

The demand studies for the fish sector are limited by their high degree of aggregation, and the lack of empirical basis for estimating the underlying elasticity of demand. In this study, the three-stage budgeting framework with quadratic almost ideal demand system (QAIDS) model has been used for fish demand analysis by species, using consumer expenditure survey data of India. Income and price elasticities of fish demand have been evaluated at mean level for different economic groups and have been used to project the demand for fish to a medium-term time horizon, by the year 2015. The domestic demand for fish by 2015 has been projected as 6.7-7.7 million tonnes. Aquaculture would hold the key to meet the challenges of future needs. Among species, Indian major carps (IMC) would play a dominating role in meeting the fish demand. Results have shown that the estimated price and income elasticities of demand vary across species and income classes. Fish species have not been found as homogenous commodities for consumers. All the eight fish types included in the study have been found to have positive income elasticity greater than one for all the income levels. Hence, with higher income, fish demand has been projected to increase substantially with change in the species mix. The own-price elasticities by species have been found negative and near to unitary.Agricultural and Food Policy,

Fish Supply Projections by Production Environments and Species Types in India

The supply studies on the fisheries sector in India have been addressed at the disaggregated level by production environment and by species groups. These would be more imperative and useful for assessing the fish supply at the national level. The fish supply projections by species groups under different production environments have been obtained to a medium-term horizon, by the year 2015 under various technological scenarios. The study has concluded that the supply response to fish price changes has been stronger under aquaculture than marine environment in India. Price and technology have been reported as the important instruments to induce higher supply. The change in the relative prices of fish species would change the species-mix in the total supply. The fish production has been projected as 4.6-5.5 million tonnes of inland fish and 3.2-3.6 million tonnes of marine fish by the year 2015. More than 60 per cent of the additional fish production will be contributed by aquaculture and mainly by the Indian major carps.Agricultural and Food Policy,

Keys in the Clouds: Auditable Multi-device Access to Cryptographic Credentials

Personal cryptographic keys are the foundation of many secure services, but storing these keys securely is a challenge, especially if they are used from multiple devices. Storing keys in a centralized location, like an Internet-accessible server, raises serious security concerns (e.g. server compromise). Hardware-based Trusted Execution Environments (TEEs) are a well-known solution for protecting sensitive data in untrusted environments, and are now becoming available on commodity server platforms. Although the idea of protecting keys using a server-side TEE is straight-forward, in this paper we validate this approach and show that it enables new desirable functionality. We describe the design, implementation, and evaluation of a TEE-based Cloud Key Store (CKS), an online service for securely generating, storing, and using personal cryptographic keys. Using remote attestation, users receive strong assurance about the behaviour of the CKS, and can authenticate themselves using passwords while avoiding typical risks of password-based authentication like password theft or phishing. In addition, this design allows users to i) define policy-based access controls for keys; ii) delegate keys to other CKS users for a specified time and/or a limited number of uses; and iii) audit all key usages via a secure audit log. We have implemented a proof of concept CKS using Intel SGX and integrated this into GnuPG on Linux and OpenKeychain on Android. Our CKS implementation performs approximately 6,000 signature operations per second on a single desktop PC. The latency is in the same order of magnitude as using locally-stored keys, and 20x faster than smart cards.Comment: Extended version of a paper to appear in the 3rd Workshop on Security, Privacy, and Identity Management in the Cloud (SECPID) 201

A Multistage Budgeting Approach to the Analysis of Demand for Fish: An Application to Inland Areas of Bangladesh

This study was conducted to estimate the elasticities of demand for eight different fish types and four income groups in Bangladesh using year-round data collected from inland areas of the country. It uses a three-stage budgeting framework that estimates a demand function for food in the first stage, a demand function for fish (as a group) in the second stage, and a set of demand functions for fish by type in the third stage using a quadratic extension of the Almost Ideal Demand System (QUAIDS) model. The Heckman procedure was used in stage three to remove the possible bias in the parameter estimates brought about by zero consumption. The magnitude of both price and income elasticities varies across different fish types and income quartile groups, indicating the relevance of estimation specific to fish types and quartiles. Except for assorted small fish, the other seven fish types included in the study were found to have positive income elasticity for all income levels. Assorted small fish is an inferior commodity for the richest quartile of the population.Bangladesh, fish demand elasticities, Inverse Mills Ratio, multi-stage budgeting, quadratic extension to Almost Ideal Demand System (QUAIDS), Demand and Price Analysis, International Development, Public Economics, Research Methods/ Statistical Methods, C3, Q21,

A prony algorithm for shallow water waveguide analysis

Submitted in partial fulfillment of the requirements for the degree of Ocean Engineer at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution August 1987Low frequency acoustic propagation in shallow water is examined from a normal mode context. By modelling the far field pressure field as a modal sum, propagating mode characteristics of wavenumber, initial phase, attennation and amplitude may be estimated using a high resolution parameter modeling technique. The advantages of such an algorithm are the resolution of closely spaced modes in a range independent environment and the ability to analyze range dependent waveguides. This thesis presents the application of a Prony algorithm to the shallow water environment. The algorithm operates directly on the signal matrix. Synthetically generated, range independent pressure fields are used to analyze the technique'S performance and to observe its sensitivity to variations in model specifications. Noise is added to determine the threshold of acceptable performance. As a consequence of field data tests, further enhancements to the algorithm are suggested. Range dependent performance is evaluated on a coastal wedge example and geoacoustic parameter shift example