Rule Based System for Diagnosing Wireless Connection Problems Using SL5 Object

There is an increase in the use of in-door wireless networking solutions via Wi-Fi and this increase infiltrated and utilized Wi-Fi enable devices, as well as smart mobiles, games consoles, security systems, tablet PCs and smart TVs. Thus the demand on Wi-Fi connections increased rapidly. Rule Based System is an essential method in helping using the human expertise in many challenging fields. In this paper, a Rule Based System was designed and developed for diagnosing the wireless connection problems and attain a precise decision about the cause of the problem. SL5 Object expert system language was used in developing the rule based system. An Evaluation of the rule based system was carried out to test its accuracy and the results were promising

KM Maturity Factors Affecting High Performance in Universities

This paper aims to measure Knowledge Management Maturity (KMM) in the universities to determine the impact of knowledge management on high performance. This study was applied on Al-Quds Open University in Gaza strip, Palestine. Asian productivity organization model was applied to measure KMM. Second dimension which assess high performance was developed by the authors. The controlled sample was (306). Several statistical tools were used for data analysis and hypotheses testing, including reliability Correlation using Cronbach’s alpha, “ANOVA”, Simple Linear Regression and Step Wise Regression.The overall findings of the current study suggest that KMM is suitable for measuring high performance. KMM assessment shows that maturity level is in level three. Findings also support the main hypothesis and it is sub- hypotheses. The most important factors effecting high performance are: Processes, KM leadership, People, KM Outcomes and Learning and Innovation. Furthermore the current study is unique by the virtue of its nature, scope and way of implied investigation, as it is the first comparative study in the universities of Palestine explores the status of KMM using the Asian productivity Model

Connection between electrical conductivity and diffusion coefficient of a conductive porous material filled with electrolyte

The paper focuses on the cross-property connection between the effective electrical conductivity and the overall mass transfer coefficient of a two phase material. The two properties are expressed in terms of the tortuosity parameter which generalized to the case of a material with two conductive phases. Elimination of this parameter yields the cross-property connection. The theoretical derivation is verified by comparison with computer simulation

Toward designing a quantum key distribution network simulation model

As research in quantum key distribution network technologies grows larger and more complex, the need for highly accurate and scalable simulation technologies becomes important to assess the practical feasibility and foresee difficulties in the practical implementation of theoretical achievements. In this paper, we described the design of simplified simulation environment of the quantum key distribution network with multiple links and nodes. In such simulation environment, we analyzed several routing protocols in terms of the number of sent routing packets, goodput and Packet Delivery Ratio of data traffic flow using NS-3 simulator

Analysis of the applicability of singlemode optical fibers for measurement of deformation with distributed systems BOTDR

Distributed optical fiber sensors allow monitoring physical effects across the whole cable. The paper presents results obtained from the performed tests and shows that single mode fibers can provide analyses of the deformation changes, when distributed optical systems BOTDR used. We used standard optical fiber G.652.D with primary and secondary protected layers and specialized cable SMC-V4 designed for this purpose. The aim was to compare the deformation sensitivity and determine which fiber types are the best to use. We deformed the fiber in the longitudinal and transverse directions and mechanically stressed in orthogonal directions to find how to localize optical fibers. They could be deployed in real use. For achieving optimal results of mechanical changes and acting forces, sensor fibers have to be located carefully

Implementation of Adaptive Unsharp Masking as a pre-filtering method for watermark detection and extraction

Digital watermarking has been one of the focal points of research interests in order to provide multimedia security in the last decade. Watermark data, belonging to the user, are embedded on an original work such as text, audio, image, and video and thus, product ownership can be proved. Various robust watermarking algorithms have been developed in order to extract/detect the watermark against such attacks. Although watermarking algorithms in the transform domain differ from others by different combinations of transform techniques, it is difficult to decide on an algorithm for a specific application. Therefore, instead of developing a new watermarking algorithm with different combinations of transform techniques, we propose a novel and effective watermark extraction and detection method by pre-filtering, namely Adaptive Unsharp Masking (AUM). In spite of the fact that Unsharp Masking (UM) based pre-filtering is used for watermark extraction/detection in the literature by causing the details of the watermarked image become more manifest, effectiveness of UM may decrease in some cases of attacks. In this study, AUM has been proposed for pre-filtering as a solution to the disadvantages of UM. Experimental results show that AUM performs better up to 11\% in objective quality metrics than that of the results when pre-filtering is not used. Moreover; AUM proposed for pre-filtering in the transform domain image watermarking is as effective as that of used in image enhancement and can be applied in an algorithm-independent way for pre-filtering in transform domain image watermarking

Encapsulation of FBG sensor into the PDMS and its effect on spectral and temperature characteristics

Fiber Bragg Grating (FBG) is the most distributed type of fiber-optic sensors. FBGs are primarily sensitive to the effects of temperature and deformation. By employing different transformation techniques, it is possible to use FBG to monitor any physical quantity. To use them as parts of sensor applications, it is essential to encapsulate FBGs to achieve their maximum protection against external effects and damage. Another reason to encapsulate is increasing of sensitivity to the measured quantity. Polydimethylsiloxane (PDMS) encapsulation appears to be an interesting alternative due to convenient temperature and flexibility of the elastomer. This article describes an experimental proposal of FBG PDMS encapsulation process, also providing an analysis of the FBG spectral characteristics and temperature sensitivity, both influenced by high temperature and the process of polydimethylsiloxane curing itself. As for the PDMS type, Sylgard 184 was employed. Encapsulation consisted of several steps: allocation of FBG to PDMS in its liquid state, curing PDMS at the temperature of 80°C ± 5 %, and a 50-minute relaxation necessary to stabilize a Bragg wavelength. A broadband light source and an optical spectrum analyzer were both used to monitor the parameters during the processes of curing and relaxation. Presented results imply that such a method of encapsulation does not have any influence on the structure or functionality of the FBG. At the same time, a fourfold increase of temperature sensitivity was monitored when compared to a bare FBG

Server resource dimensioning and routing of service function chain in NFV network architectures

The Network Function Virtualization (NFV) technology aims at virtualizing the network service with the execution of the single service components in Virtual Machines activated on Commercial-off-the-shelf (COTS) servers. Any service is represented by the Service Function Chain (SFC) that is a set of VNFs to be executed according to a given order. The running of VNFs needs the instantiation of VNF instances (VNFI) that in general are software components executed on Virtual Machines. In this paper we cope with the routing and resource dimensioning problem in NFV architectures. We formulate the optimization problem and due to its NP-hard complexity, heuristics are proposed for both cases of offline and online traffic demand. We show how the heuristics works correctly by guaranteeing a uniform occupancy of the server processing capacity and the network link bandwidth. A consolidation algorithm for the power consumption minimization is also proposed. The application of the consolidation algorithm allows for a high power consumption saving that however is to be paid with an increase in SFC blocking probability

Nonlinear autoregressive moving average-L2 model based adaptive control of nonlinear arm nerve simulator system

This paper considers the trouble of the usage of approximate strategies for realizing the neural controllers for nonlinear SISO systems. In this paper, we introduce the nonlinear autoregressive moving average (NARMA-L2) model which might be approximations to the NARMA model. The nonlinear autoregressive moving average (NARMA-L2) model is an precise illustration of the input–output behavior of finite-dimensional nonlinear discrete time dynamical systems in a neighborhood of the equilibrium state. However, it isn't always handy for purposes of neural networks due to its nonlinear dependence on the manipulate input. In this paper, nerves system based arm position sensor device is used to degree the precise arm function for nerve patients the use of the proposed systems. In this paper, neural network controller is designed with NARMA-L2 model, neural network controller is designed with NARMA-L2 model system identification based predictive controller and neural network controller is designed with NARMA-L2 model based model reference adaptive control system. Hence, quite regularly, approximate techniques are used for figuring out the neural controllers to conquer computational complexity. Comparison were made among the neural network controller with NARMA-L2 model, neural network controller with NARMA-L2 model system identification based predictive controller and neural network controller with NARMA-L2 model reference based adaptive control for the preferred input arm function (step, sine wave and random signals). The comparative simulation result shows the effectiveness of the system with a neural network controller with NARMA-L2 model based model reference adaptive control system. Index Terms--- Nonlinear autoregressive moving average, neural network, Model reference adaptive control, Predictive controller DOI: 10.7176/JIEA/10-3-03 Publication date: April 30th 202