Intelligent drug delivery system using UML diagrams analysis

A novel intelligent drug delivery system potential for the more effective therapy of the diabeticswas proposed, and the composition of system was analyzed. Based on the design of micro-electro-mechanicalsystems (MEMS), an iterative modeling process was introduced. Unified modeling language (UML) was em-ployed to describe the function requirement, and different diagrams were built up to explore the static model,the dynamic model and the employment model. The mapping analysis of different diagrams can simply verifythe consistency and completeness of the system model.     

A proposed quantitative methodology for the evaluation of the effectiveness of Human Element,Leadership and Management (HELM) training in the UK

In 2006, a review of maritime accidents found that non-technical skills (NTSs) are the single largest contributing factor towards such incidents. NTSs are composed of both interpersonal and cognitive elements. These include things such as situational awareness, teamwork, decision making, leadership, management and communication skills. In a crisis situation, good NTSs allow a deck officer to quickly recognise that a problem exists and then harness the resources that are at their disposal to safely and efficiently bring the situation back under control. This paper has two aims. The first is to develop a methodology which will enable educators to quantitatively assess the impact of Maritime and Coastguard Agency (MCA)-approved Human Element, Leadership and Management (HELM) training on deck officer’s NTSs with a view to identifying further training requirements. The second is to determine whether the HELM training provided to develop the NTSs of trainee deck officers is fit for purpose. To achieve these aims, a three-phase approach was adopted. Initially, a taxonomy for deck officer’s NTSs is established, behavioural markers are identified and the relative importance of each attribute is calculated using the analytical hierarchy process (AHP). Subsequently, a set of scenarios were identified for the assessment of deck officer’s NTSs in a ship bridge simulator environment. A random selection of students that have completed the Chief Mate (CM) programme was performed, and data regarding their NTS-related performance in the scenarios was collected. Finally, the collected data was fed into the evidential reasoning (ER) algorithm, utility values were produced and, having established these values, the effectiveness of the HELM training that the students have received was then evaluated.     

Novel Application of High Voltage Electrostatics Corona Ions Discharge Related to Treatment,Sanitization and Disinfection of Biological Matter Such HIV-AIDS Infected Blood

A novel high-voltage electrostatics corona ions pre-charger apparatus and methods were invented earlier by Hamade related to treat various types of receptors such as but not limited to electret polymer, air filters, particulates, catalytic converters, bioaerosols, fluids, pollutants, virus, and bacteria. It is shown in this article that his work led to the construction of various prototype chargers, customized differently for each type of a receptor. In particular his recent development of biological matter corona charger (BMCC) prototype related to expose, treat, sanitize, and disinfect bioaerosols, virus, bacteria, and contaminated fluids and blood such as human immunodeficiency virus (HIV) - acquired immune deficiency syndrome (AIDS). It is shown in this paper that each previous investigated research contemplated ionized corona charger attendant to a charging process and the corona, imparts and provides enough treatment charges to receptors including the aforementioned receptors. Researchers often relied on adopting prior corona charger methods that do not necessarily and effectively solve the problems associated with them or utilize them for optimum treatment effect. The inventor exhaustively studied the characteristics of corona discharge, and has found that the greatest difficulty in corona discharge has to do with the maintenance of the corona, particularly when the receptor is being charged. This is due to variations in either the dielectric value between the corona electrode and a grounded base or flaws in the design as the receptor passes there between suppressing or hindering corona and its effectiveness. What is needed in-the-art is an apparatus and method to achieve maximum possible charge on a receptor, a charge order of magnitude greater than that used by other investigators. This often requires customizing each apparatus and method and does not just merely use one type of a charger to satisfy all applications. To satisfy this need, we build a low cost prototype BMCC that generates self-sustaining charge corona, eliminates many previous design flaws such as spark over, and make it ready for testing remotely or with apparatus.     

Neural network-based fuel consumption estimation for container ships in Korea

ABSTRACT

Due to the outstanding strength of advanced machine-learning techniques, they have become increasingly common in predictive studies in recent years, particularly in predicting ship energy performance. In constructing predictive models, prior studies have mostly employed vessels’ technical parameters to establish machine-learning algorithms. To bridge this research gap and enable wider applications, this paper presents the design of a multilayer perceptron artificial neural network (MLP ANN) as a machine-learning technique to estimate ship fuel consumption. We utilized the real operational data from 100–143 container ships to estimate fuel consumption for five different container ships grouped by size. We compared the performance of two ANN models and two multiple-regression models. Four input parameters (sailing time, speed, cargo weight, and capacity) were included in the first ANN and the first regression model, while the other two models only consider two inputs from physical function. The mean absolute percentage error of the ANN models with four inputs was the smallest and less than those in extended statistical models, demonstrating the MLP’s superiority over the statistical model. The MLP ANN model can thus be applied to confirm the effectiveness of the slow-steaming method for achieving energy efficiency.     

Training Needs of Coastal Resources Decision Makers in Ohio's Lake Erie Basin

This article describes results from a study focused on informational and knowledge needs of local coastal resources decision makers in the Ohio Lake Erie basin. New information was obtained through a series of focus groups of local decision makers and key training providers in the basin. The results suggest that training providers and local coastal resources decision makers have differing perceptions of knowledge and information needs and training venues. The results suggest a role for state and federal agency training providers as coordinators and facilitators of an enhanced learning network among decision makers, including support of an information clearinghouse, adoption of appropriate e-based learning modalities, and regionally based learning and practice networks to improve the function of the training market to meet local decision maker needs.     

Economic value of natural Coastal wetlands: A critique

Recent estimates by J. Gosselink, E. Odum, and R. Pope of the economic value of natural wetlands have had considerable impact on analyses and discussions of public policies concerning natural wetlands management. However, these economic value estimates are neither conceptually nor empirically correct. First, these workers failed to recognize the nature of the process by which economic values are determined and made an illegitimate marriage of the principles of systems ecology and economic theory. Second, where Gosselink et al. attempted to apply proper economic principles, their calculations resulted in economic value estimates that are most likely in error.     

Application of a real-coded genetic algorithm for the fitting of a ship hull surface through a single non-uniform B-spline surface

In digital ship-design processes, surface modeling needs to be as accurate as possible for effectiveness in ship production as well as numerical analysis of the performance. Traditionally, the form of a ship hull is constructed from a set of cross-sectional data. This approach entails difficulties in the cross-sectional spacing and accuracy of the characteristic curves, such as the stern and bow profiles, deck side line, bottom tangential line, and unconnected curves. Genetic algorithms (GAs) have attracted increasing attention as a multimodal optimization solution for surface reconstruction that enable construction of a single non-uniform B-spline (NUB) surface at the initial stage of ship design with constraints such as knuckles, discontinuity conditions, and bulbous bows with high curvatures, . The first, simultaneous multi-fitting GA determines the boundary curves, such as the stem and stern profiles, and finds the common knot values for both curves. Similarly, the same GA technique is applied for other boundary curves at the bottom and the deck. The second GA is employed to fit the interior data points after the boundary curves are fitted. The encoded design variables for surface construction are the locations of the vertices and the knot values. Those variables are modified for improving the surface quality until a predefined degree of precision is attained. In four instances of application, the GA technique developed in this research has been shown to provide good, single, NUB surfaces with high efficiency. In the early design stage, a single NUB surface is more convenient for performance visualization and finite-element methods. It can be readily translated into many CAD/CAM packages, which facilitate the smooth transition of data across the different design stages.     

Ship underwater noise assessment by the acoustic analogy,part III: measurements versus numerical predictions on a full-scale ship

The acoustic analogy represents a powerful and versatile approach, able to numerically predict the noise generated by a body moving in a fluid. It is widely used to provide essential indications about the aeroacoustic behavior of aircraft and helicopters (even at a design stage) and, eventually, to pursue effective strategies aimed at desirable reduction and/or control of noise. Nevertheless, applications in the area of hydroacoustics and in the prediction of ship underwater noise are very rare. In this paper, the potential of the acoustic analogy is directly tested on a large ferry, for which a measurement campaign at sea was performed. In spite of the complexity of the tested configuration [the ship mounts two contracted and loaded tip (CLT) propellers located ahead of two rudders, and its hull is characterized by a rather elongated skeg] and the many variables not taken into account in the numerical simulation (such as the contribution from machinery noise and the probable occurrence of tip vortex cavitation), the agreement between the measured and computed noise spectra is quite satisfactory. The analysis suggests many interesting features of the ship hydroacoustic field: the dominant role played by nonlinear sources far from the body and the relevance of scattering effects from the hull surface. Furthermore, the scattered pressure seems to contribute to alter the frequency content of the resulting signatures with respect to the blade passage frequencies. Finally, an overview of future developments and applications of this numerical approach for marine/maritime problems is presented.     

A predictive dynamic traffic assignment model in congested capacity-constrained road networks

In this paper, a predictive dynamic traffic assignment model in congested capacity-constrained road networks is formulated. A traffic simulator is developed to incrementally load the traffic demand onto the network, and updates the traffic conditions dynamically. A time-dependent shortest path algorithm is also given to determine the paths with minimum actual travel time from an origin to all the destinations. The traffic simulator and time-dependent shortest path algorithm are employed in a method of successive averages to solve the dynamic equilibrium solution of the problem. A numerical example is given to illustrate the effectiveness of the proposed method.     

Modeling and analysis of a fuel-injection pump used in diesel engines

The Fuel-Injection Pump (FIP) used in diesel engine has a higher-pair cam-mechanism to pressurize the fuel for injection. This paper proposes a methodology to model FIP from a multibody Dynamics (MBD) perspective. The results from the model include the temporal behavior of driving torque, contact Hertz stress and reaction forces at various joints. The model helps the designer to assess the effect of various cam profiles, link parameters and other design variables. It is necessary that these parameters be optimized for future high pressure applications. For this purpose, a cam-mechanism with offset follower axis is analysed. Decoupled Natural Orthogonal Complement (DeNOC) matrices based algorithm is used to model FIP without and with offset cam-mechanism. The study shows that, the offset cam-mechanism allows reduction in the side-thrust, reaction forces, and the contact Hertz stress acting on the cam-follower interface. As a typical case, for an FIP working around a pressure value of 600 bar, an optimum offset value is found to be 9.5 mm and it shows a reduction of about 45% in side thrust values. To validate the modeling approach, experimental studies are performed on pump without and with offset cam-mechanism. Experimental results are in qualitative agreement with the theoretical model results.