Comparative study on various type of lightning arrester at solar farm

The Photovoltaic (PV) system is vulnerable to a lightning strike. This overvoltage from lightning strikes could potentially damage PV components, including inverter, cable and the panel itself. To cater this issue, a lightning protection system (LPS) had been installed throughout the solar farm area as a device to attract and assist lightning flow to the ground. Although a proper LPS system had been established, there are still incidents related to lightning strikes on the solar panel, ultimately causing severe damage to the overall PV system. This paper focuses on studying and simulating PV solar farms electrical field behavior in various lighting protection systems. Also, it analyses several types of LPS arrangement, PV panel mounting and construction toward the influence of the lightning electric field. The Finite Element Method (FEM) has been used for this research. The simulation results show that most of the lighting attachments affected the PV panel at the corner edge of each side. The sharp point at the edge creates nonuniform electric field and increases electric field intensity. This paper will suggest a design of PV and LPS systems for better prevention of lightning strike phenomena

Reliability Analysis of Component-Based Systems with Multiple Failure Modes

This paper presents a novel approach to the reliability modeling and analysis of a component-based system that allows dealing with multiple failure modes and studying the error propagation among components. The proposed model permits to specify the components attitude to produce, propagate, transform or mask different failure modes. These component-level reliability specifications together with information about systems global structure allow precise estimation of reliability properties by means of analytical closed formulas, probabilistic modelchecking or simulation methods. To support the rapid identification of components that could heavily affect systems reliability, we also show how our modeling approach easily support the automated estimation of the system sensitivity to variations in the reliability properties of its components. The results of this analysis allow system designers and developers to identify critical components where it is worth spending additional improvement efforts

Simulation for training in sinus floor elevation : new surgical bench model

Objectives: to describe a bench model (workshop of abilities) for sinus floor elevation (SFE) training that simulates the surgical environment and to assess its effectiveness in terms of trainees? perception. Study design: thirty-six randomly selected postgraduate students entered this cross-sectional pilot study and asked to fill in an anonymous, self-applied, 12-item questionnaire about a SFE workshop that included a study guide containing the workshop?s details, supervised practice on a simulated surgical environment, and assessment by means of specific check-lists. Results: Thirtiy-six fresh sheep heads were prepared to allow access to the buccal vestible. Using the facial tuber, third premolar and a 3D-CT study as landmarks for trepanation, the sinus membrane was lifted, the space filled with ceramic material and closed with a resorbable membrane. The participants agreed on their ability to perform SFE in a simulated situation (median score= 4.5; range 2-5) and felt capable to teach the technique to other clinicians or to undertake the procedure for a patient under supervision of an expert surgeon (median= 4; range 1-5 ). There were no differences on their perceived ability to undertake the technique on a model or on a real patient under supervision of an expert surgeon (p=0.36). Conclusions: Clinical abilities workshops for SFE teaching are an essential educational tool but supervised clinical practice should always precede autonomous SFE on real patients. Simulation procedures (workshop of abilities) are perceived by the partakers as useful for the surgical practice. However, more studies are needed to validate the procedure and to address cognitive and communication skills, that are clearly integral parts of surgical performance

Financial time series prediction using spiking neural networks

In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. The performance of the spiking neural network was benchmarked against three systems: two "traditional", rate-encoded, neural networks; a Multi-Layer Perceptron neural network and a Dynamic Ridge Polynomial neural network, and a standard Linear Predictor Coefficients model. For this comparison three non-stationary and noisy time series were used: IBM stock data; US/Euro exchange rate data, and the price of Brent crude oil. The experiments demonstrated favourable prediction results for the Spiking Neural Network in terms of Annualised Return and prediction error for 5-Step ahead predictions. These results were also supported by other relevant metrics such as Maximum Drawdown and Signal-To-Noise ratio. This work demonstrated the applicability of the Polychronous Spiking Network to financial data forecasting and this in turn indicates the potential of using such networks over traditional systems in difficult to manage non-stationary environments. © 2014 Reid et al

Model-driven performance analysis

Abstract. Model-Driven Engineering (MDE) is an approach to develop software systems by creating models and applying automated transformations to them to ultimately generate the implementation for a target platform. Although the main focus of MDE is on the generation of code, it is also necessary to support the analysis of the designs with respect to quality attributes such as performance. To complement the model-toimplementation path of MDE approaches, an MDE tool infrastructure should provide what we call model-driven analysis. This paper describes an approach to model-driven analysis based on reasoning frameworks. In particular, it describes a performance reasoning framework that can transform a design into a model suitable for analysis of real-time performance properties with different evaluation procedures including rate monotonic analysis and simulation. The concepts presented in this paper have been implemented in the PACC Starter Kit, a development environment that supports code generation and analysis from the same models.

ProMARTES: Performance Analysis Method and Toolkit for Real-Time Systems

In this chapter, we present a cycle-accurate performance analysis method for real-time systems that incorporates the following phases: 1. profiling SW components at high accuracy, 2. modeling the obtained performance measurements in MARTE-compatible models, 3. generation, scheduling analysis and simulation of a system model, 4. analysis of the obtained performance metrics, and 5. a subsequent architecture improvement. The method has been applied to a new autonomous navigation system for robots with advanced sensing capabilities, enabling validation of multiple performance analysis aspects, such as SW/HW mapping, real-time requirements and synchronization on multiprocessor schemes. The case-study has proved that the method is able to use the profiled low-level performance metrics throughout all the phases, resulting in high prediction accuracy. We have found a range of inefficient design directions leading to RT requirements failure, and recommended to robot owners a design decision set to reach an optimal solution

Enhancing the Security of Software Defined Mobile Networks (SDMN) based on Blockchain Technology

The blockchain involves future developments and new technologies. The emergence of a blockchain is a challenge for the conventional social organization and mode of activity. Data latency and mobile network capacity would no longer be a limitation for mobile users in next-generation networks of Software Defined Mobile Networks (SDMN). But there are many benefits to Software Defined Mobile Networking, it also contributes to certain security problems like DDoS / DoS attacks, unauthorized access, and single data point error. To enhance the security and privacy of the SDMN control plane, this paper proposes a new SDMN-based “Simplified Byzantine Fault Tolerance (SBFT)” algorithm to send signals between controllers and also set up an analysis study to investigate SBFT's security and results. However, there are many benefits of Software Defined Mobile Networking (SDMN), and then it helps to resolve other security concerns including DDoS / DoS attacks, unauthorized access, and single point failure. Blockchain, an evolving revolutionary technology, will offer creative approaches to address security issues in Software-Defined Mobile networks in an efficient way. This study proposes an SDMN-based Simplified Byzantine Fault Tolerance (SBFT) for enhancing the mobile network's security and privacy

Adopting Open SOurce Software Engineering (OSSE) Practices by Adopting OSSE Tools

The open source movement has created and uses a set of software engineering tools..

An XML-Based Language to Support Performance and Reliability Modeling and Analysis in Software Architectures

Abstract. In recent years, the focus of software development has pro-gressively shifted upward, in the direction of the abstract level of ar-chitecture specification. However, while the functional properties of the systems have been extensively dealt with in the literature, relatively less attention has been given until recently to the specification and analysis at the architectural level of quality attributes such as performance and reliability. The contribution of this paper is twofold: first we discuss the type of information that should be provided at the architectural level in order to successfully address the problem of performance and reliability modeling and analysis of software systems; based on this discussion, we define an extension of the xADL architectural language that enables the support for stochastic modeling and analysis of performance and relia-bility in software architectures.