Construction of dynamic stochastic simulation models using knowledge-based techniques

Over the past three decades, computer-based simulation models have proven themselves to be cost-effective alternatives to the more structured deterministic methods of systems analysis. During this time, many techniques, tools and languages for constructing computer-based simulation models have been developed. More recently, advances in knowledge-based system technology have led many researchers to note the similarities between knowledge-based programming and simulation technologies and to investigate the potential application of knowledge-based programming techniques to simulation modeling. The integration of conventional simulation techniques with knowledge-based programming techniques is discussed to provide a development environment for constructing knowledge-based simulation models. A comparison of the techniques used in the construction of dynamic stochastic simulation models and those used in the construction of knowledge-based systems provides the requirements for the environment. This leads to the design and implementation of a knowledge-based simulation development environment. These techniques were used in the construction of several knowledge-based simulation models including the Advanced Launch System Model (ALSYM)

Hardware synthesis from DDL description

The details of digital systems can be conveniently input into the design automation system by means of hardware description language (HDL). The computer aided design and test (CADAT) system at NASA MSFC is used for the LSI design. The digital design language (DDL) was selected as HDL for the CADAT System. DDL translator output can be used for the hardware implementation of the digital design. Problems of selecting the standard cells from the CADAT standard cell library to realize the logic implied by the DDL description of the system are addressed

A Generative Model For Zero Shot Learning Using Conditional Variational Autoencoders

Zero shot learning in Image Classification refers to the setting where images from some novel classes are absent in the training data but other information such as natural language descriptions or attribute vectors of the classes are available. This setting is important in the real world since one may not be able to obtain images of all the possible classes at training. While previous approaches have tried to model the relationship between the class attribute space and the image space via some kind of a transfer function in order to model the image space correspondingly to an unseen class, we take a different approach and try to generate the samples from the given attributes, using a conditional variational autoencoder, and use the generated samples for classification of the unseen classes. By extensive testing on four benchmark datasets, we show that our model outperforms the state of the art, particularly in the more realistic generalized setting, where the training classes can also appear at the test time along with the novel classes

Superconducting Mechanism through direct and redox layer doping in Pnictides

The mechanism of superconductivity in pnictides is discussed through direct doping in superconducting FeAs and also in charge reservoir REO layers. The un-doped SmFeAsO is charge neutral SDW (Spin Density Wave) compound with magnetic ordering below 150 K. The Superconducting FeAs layers are doped with Co and Ni at Fe site, whereas REO layers are doped with F at O site. The electron doping in SmFeAsO through Co results in superconductivity with transition temperature (Tc) maximum up to 15 K, whereas F doping results in Tc upto 47 K in SmFeAsO. All these REFe/Co/NiAsO/F compounds are iso-structural to ZrCuSiAs structure. The samples are crystallized in a tetragonal structure with space group P4/nmm. Variation of Tc with different doping routes shows the versatility of the structure and mechanism of occurrence of superconductivity. It seems doping in redox layer is more effective than direct doping in superconducting FeAs layer.Comment: 4 Pages text + Figs: ([email protected]

The accuracy of the Raypex5 electronic apex locator using stainless-steel hand K-file versus nickel-titanium rotary Mtwo file

Objectives: Today many clinicians use both stainless-steel hand K-files and nickel- titanium rotary files during endodontic treatment. It is of great importance for the clinician to have confidence in the accuracy of an apex locator even if these files were used interchangeably. The purpose of this in-vitro study was to evaluate the accuracy of the Raypex5 electronic apex locator using stainless-steel hand K-file versus nickel-titanium rotary Mtwo file. Study design: Twenty straight and single canals of maxillary central teeth were used. Access cavities were prepared; actual working length were determined and compared with electronic working length obtained by means of apex locator Raypex5 using stainless-steel hand K-file and nickel-titanium rotary Mtwo file. Data was analyzed by paired T-test. Results: There was no significant difference between 15/0.02 stainless-steel hand K- file and 10/0.04 NiTi rotary Mtwo file for the mean differences between actual and electronic working length (p=0.126). Conclusions: Under the conditions of this in-vitro study, Raypex5 registered more measurements in acceptable range using 15/0.02 stainless-steel hand K- file and 10/0.04 NiTi rotary Mtwo file. It is possible to use them interchangeably without compromising the working length

Two-Hop Routing with Traffic-Differentiation for QoS Guarantee in Wireless Sensor Networks

This paper proposes a Traffic-Differentiated Two-Hop Routing protocol for Quality of Service (QoS) in Wireless Sensor Networks (WSNs). It targets WSN applications having different types of data traffic with several priorities. The protocol achieves to increase Packet Reception Ratio (PRR) and reduce end-to-end delay while considering multi-queue priority policy, two-hop neighborhood information, link reliability and power efficiency. The protocol is modular and utilizes effective methods for estimating the link metrics. Numerical results show that the proposed protocol is a feasible solution to addresses QoS service differenti- ation for traffic with different priorities.Comment: 13 page

Decision-making process of Kala Azar care: results from a qualitative study carried out in disease endemic areas of Nepal

BACKGROUND: Analysis of consumer decision making in the health sector is a complex process of comparing feasible alternatives and evaluating the levels of satisfaction associated with the relevant options. This paper makes an attempt to understand how and why consumers make specific decisions, what motivates them to adopt a specific health intervention, and what features they find attractive in each of the options. METHOD: The study used a descriptive-explanatory design to analyze the factors determining the choices of healthcare providers. Information was collected through focus group discussions and in-depth interviews. RESULTS: The results suggest that the decision making related to seeking healthcare for Kala Azar (KA) treatment is a complex, interactive process. Patients and family members follow a well-defined road map for decision making. The process of decision making starts from the recognition of healthcare needs and is then modified by a number of other factors, such as indigenous knowledge, healthcare alternatives, and available resources. Household and individual characteristics also play important roles in facilitating the process of decision making. The results from the group discussions and in-depth interviews are consistent with the idea that KA patients and family members follow the rational approach of weighing the costs against the benefits of using specific types of medical care. CONCLUSION: The process of decision making related to seeking healthcare follows a complex set of steps and many of the potential factors affect the decision making in a non-linear fashion. Our analysis suggests that it is possible to derive a generalized road map of the decision-making process starting from the recognition of healthcare needs, and then modifying it to show the influences of indigenous knowledge, healthcare alternatives, and available resources