Reduce of Fermentation Time in Composting Process by Using a Special Microbial Consortium

Composting is the process in which municipal solid waste (MSW) and other organic waste materials such as biosolids and manures are decomposed through the action of bacteria and other microorganisms into a stable granular material which, applied to land, as soil conditioner. Microorganisms, especially those that are able to degrade polymeric organic material have a key role in speed up this process. The aim of this study has been established to isolation of microorganisms with high ability to production extracellular enzymes for degradation of natural polymers that are exists in MSW for decreasing time of degradation phase. Our experimental study for isolation designed in two phases: in first phase we isolated degrading microorganism with selected media that consist a special natural polymer such as cellulose, starch, lipids and etc as sole source of carbon. In second phase we selected microorganism that had high degrading enzyme production with enzymatic assay for seed production. However, our findings in pilot scale have indicated that usage of this microbial consortium had high efficiency for decreasing degradation phase.

Metamorphism, Formal Grammars and Undecidable Code Mutation

This paper presents a formalisation of the different existing code mutation techniques (polymorphism and metamorphism) by means of formal grammars. While very few theoretical results are known about the detection complexity of viral mutation techniques, we exhaustively address this critical issue by considering the Chomsky classification of formal grammars. This enables us to determine which family of code mutation techniques are likely to be detected or on the contrary are bound to remain undetected. As an illustration we then present, on a formal basis, a proof-of-concept metamorphic mutation engine denoted PB MOT, whose detection has been proven to be undecidable.

An Adaptive Dynamic Fracture for 3D Fatigue Crack Growth Using X-FEM

In recent years, a new numerical method has been developed, the extended finite element method (X-FEM). The objective of this work is to exploit the (X-FEM) for the treatment of the fracture mechanics problems on 3D geometries, where we showed the ability of this method to simulate the fatigue crack growth into two cases: edge and central crack. In the results we compared the six first natural frequencies of mode shapes uncracking with the cracking initiation in the structure, and showed the stress intensity factor (SIF) evolution function as crack size propagation into structure, the analytical validation of (SIF) is presented. For to evidence the aspects of this method, all result is compared between FEA and X-FEM.

Encoding and Compressing Data for Decreasing Number of Switches in Baseline Networks

This method decrease usage power (expenditure) in networks on chips (NOC). This method data coding for data transferring in order to reduces expenditure. This method uses data compression reduces the size. Expenditure calculation in NOC occurs inside of NOC based on grown models and transitive activities in entry ports. The goal of simulating is to weigh expenditure for encoding, decoding and compressing in Baseline networks and reduction of switches in this type of networks. KeywordsNetworks on chip, Compression, Encoding, Baseline networks, Banyan networks.

Texture Feature-Based Language Identification Using Wavelet-Domain BDIP and BVLC Features and FFT Feature

In this paper, we propose a texture feature-based language identification using wavelet-domain BDIP (block difference of inverse probabilities) and BVLC (block variance of local correlation coefficients) features and FFT (fast Fourier transform) feature. In the proposed method, wavelet subbands are first obtained by wavelet transform from a test image and denoised by Donoho-s soft-thresholding. BDIP and BVLC operators are next applied to the wavelet subbands. FFT blocks are also obtained by 2D (twodimensional) FFT from the blocks into which the test image is partitioned. Some significant FFT coefficients in each block are selected and magnitude operator is applied to them. Moments for each subband of BDIP and BVLC and for each magnitude of significant FFT coefficients are then computed and fused into a feature vector. In classification, a stabilized Bayesian classifier, which adopts variance thresholding, searches the training feature vector most similar to the test feature vector. Experimental results show that the proposed method with the three operations yields excellent language identification even with rather low feature dimension.

MICOSim: A Simulator for Modelling Economic Scheduling in Grid Computing

This paper is concerned with the design and implementation of MICOSim, an event-driven simulator written in Java for evaluating the performance of Grid entities (users, brokers and resources) under different scenarios such as varying the numbers of users, resources and brokers and varying their specifications and employed strategies.

Power Line Carrier Equipment Supporting IP Traffic Transmission in the Enterprise Networks of Energy Companies

This article discusses the questions concerning of creating small packet networks for energy companies with application of high voltage power line carrier equipment (PLC) with functionality of IP traffic transmission. The main idea is to create converged PLC links between substations and dispatching centers where packet data and voice are transmitted in one data flow. The article contents description of basic conception of the network, evaluation of voice traffic transmission parameters, and discussion of header compression techniques in relation to PLC links. The results of exploration show us, that convergent packet PLC links can be very useful in the construction of small packet networks between substations in remote locations, such as deposits or low populated areas.

Speedup of Data Vortex Network Architecture

In this paper, 3X3 routing nodes are proposed to provide speedup and parallel processing capability in Data Vortex network architectures. The new design not only significantly improves network throughput and latency, but also eliminates the need for distributive traffic control mechanism originally embedded among nodes and the need for nodal buffering. The cost effectiveness is studied by a comparison study with the previously proposed 2- input buffered networks, and considerable performance enhancement can be achieved with similar or lower cost of hardware. Unlike previous implementation, the network leaves small probability of contention, therefore, the packet drop rate must be kept low for such implementation to be feasible and attractive, and it can be achieved with proper choice of operation conditions.

A Cell-Based Multiphase Interleaving Buck Converter with Bypass Capacitors

Today-s Voltage Regulator Modules (VRMs) face increasing design challenges as the number of transistors in microprocessors increases per Moore-s Law. These challenges have recently become even more demanding as microprocessors operate at sub voltage range at significantly high current. This paper presents a new multiphase topology with cell configuration for improved performance in low voltage and high current applications. A lab scale hardware prototype of the new topology was design and constructed. Laboratory tests were performed on the proposed converter and compared with a commercially available VRM. Results from the proposed topology exhibit improved performance compared to the commercially available counterpart.

MPPT Operation for PV Grid-connected System using RBFNN and Fuzzy Classification

This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.

A Numerical Study on Thermal Dissociation of H2S

The main issue in sweetening natural gas is H2S dissociation. The present study is concerned with simulating thermal dissociation of H2S in industrial natural gas carbon black furnace. The comparison of calculated results against experimental measurements shows good agreement. The results show that sulfur derived from H2S thermal dissociation peaked at φ=0.95. H2S thermal dissociation is enhanced in equivalence ratio upper than 1 and H2S oxidization is increased in equivalence ratio lower than 1. H2 concentration of H2S thermal dissociation is increased with increase of equivalence ratio up to 1. Also, H2S concentration decreased in outlet as equivalence ratio increases. H2S thermal dissociation to hydrogen and Sulfur reduces its toxic characteristics and make economical benefits.

Model-free Prediction based on Tracking Theory and Newton Form of Polynomial

The majority of existing predictors for time series are model-dependent and therefore require some prior knowledge for the identification of complex systems, usually involving system identification, extensive training, or online adaptation in the case of time-varying systems. Additionally, since a time series is usually generated by complex processes such as the stock market or other chaotic systems, identification, modeling or the online updating of parameters can be problematic. In this paper a model-free predictor (MFP) for a time series produced by an unknown nonlinear system or process is derived using tracking theory. An identical derivation of the MFP using the property of the Newton form of the interpolating polynomial is also presented. The MFP is able to accurately predict future values of a time series, is stable, has few tuning parameters and is desirable for engineering applications due to its simplicity, fast prediction speed and extremely low computational load. The performance of the proposed MFP is demonstrated using the prediction of the Dow Jones Industrial Average stock index.

Finite Element Modeling of two-dimensional Nanoscale Structures with Surface Effects

Nanomaterials have attracted considerable attention during the last two decades, due to their unusual electrical, mechanical and other physical properties as compared with their bulky counterparts. The mechanical properties of nanostructured materials show strong size dependency, which has been explained within the framework of continuum mechanics by including the effects of surface stress. The size-dependent deformations of two-dimensional nanosized structures with surface effects are investigated in the paper by the finite element method. Truss element is used to evaluate the contribution of surface stress to the total potential energy and the Gurtin and Murdoch surface stress model is implemented with ANSYS through its user programmable features. The proposed approach is used to investigate size-dependent stress concentration around a nanosized circular hole and the size-dependent effective moduli of nanoporous materials. Numerical results are compared with available analytical results to validate the proposed modeling approach.

Towards a Suitable and Systematic Approach for Component Based Software Development

Software crisis refers to the situation in which the developers are not able to complete the projects within time and budget constraints and moreover these overscheduled and over budget projects are of low quality as well. Several methodologies have been adopted form time to time to overcome this situation and now in the focus is component based software engineering. In this approach, emphasis is on reuse of already existing software artifacts. But the results can not be achieved just by preaching the principles; they need to be practiced as well. This paper highlights some of the very basic elements of this approach, which has to be in place to get the desired goals of high quality, low cost with shorter time-to-market software products.

Simulated Annealing and Genetic Algorithm in Telecommunications Network Planning

The main goal of this work is to propose a way for combined use of two nontraditional algorithms by solving topological problems on telecommunications concentrator networks. The algorithms suggested are the Simulated Annealing algorithm and the Genetic Algorithm. The Algorithm of Simulated Annealing unifies the well known local search algorithms. In addition - Simulated Annealing allows acceptation of moves in the search space witch lead to decisions with higher cost in order to attempt to overcome any local minima obtained. The Genetic Algorithm is a heuristic approach witch is being used in wide areas of optimization works. In the last years this approach is also widely implemented in Telecommunications Networks Planning. In order to solve less or more complex planning problem it is important to find the most appropriate parameters for initializing the function of the algorithm.

RUPSec: An Extension on RUP for Developing Secure Systems - Requirements Discipline

The world is moving rapidly toward the deployment of information and communication systems. Nowadays, computing systems with their fast growth are found everywhere and one of the main challenges for these systems is increasing attacks and security threats against them. Thus, capturing, analyzing and verifying security requirements becomes a very important activity in development process of computing systems, specially in developing systems such as banking, military and e-business systems. For developing every system, a process model which includes a process, methods and tools is chosen. The Rational Unified Process (RUP) is one of the most popular and complete process models which is used by developers in recent years. This process model should be extended to be used in developing secure software systems. In this paper, the Requirement Discipline of RUP is extended to improve RUP for developing secure software systems. These proposed extensions are adding and integrating a number of Activities, Roles, and Artifacts to RUP in order to capture, document and model threats and security requirements of system. These extensions introduce a group of clear and stepwise activities to developers. By following these activities, developers assure that security requirements are captured and modeled. These models are used in design, implementation and test activitie

Renewable Energy Supply Options in Kuwait

This paper compares planning results of the electricity and water generation inventory up to year 2030 in the State of Kuwait. Currently, the generation inventory consists of oil and gas fired technologies only. The planning study considers two main cases. The first case, Reference case, examines a generation inventory based on oil and gas fired generation technologies only. The second case examines the inclusion of renewables as part of the generation inventory under two scenarios. In the first scenario, Ref-RE, renewable build-out is based on optimum economic performance of overall generation system. Result shows that the optimum installed renewable capacity with electric energy generation of 11% . In the second scenario, Ref-RE20, the renewable capacity build-out is forced to provide 20% of electric energy by 2030. The respective energy systems costs of Reference, Ref-RE and Ref-RE20 case scenarios reach US dollar 24, 10 and 14 billion annually in 2030.

Retrospective Synthetic Focusing with Correlation Weighting for Very High Frame Rate Ultrasound

The need of high frame-rate imaging has been triggered by the new applications of ultrasound imaging to transient elastography and real-time 3D ultrasound. Using plane wave excitation (PWE) is one of the methods to achieve very high frame-rate imaging since an image can be formed with a single insonification. However, due to the lack of transmit focusing, the image quality with PWE is lower compared with those using conventional focused transmission. To solve this problem, we propose a filter-retrieved transmit focusing (FRF) technique combined with cross-correlation weighting (FRF+CC weighting) for high frame-rate imaging with PWE. A restrospective focusing filter is designed to simultaneously minimize the predefined sidelobe energy associated with single PWE and the filter energy related to the signal-to-noise-ratio (SNR). This filter attempts to maintain the mainlobe signals and to reduce the sidelobe ones, which gives similar mainlobe signals and different sidelobes between the original PWE and the FRF baseband data. Normalized cross-correlation coefficient at zero lag is calculated to quantify the degree of similarity at each imaging point and used as a weighting matrix to the FRF baseband data to further suppress sidelobes, thus improving the filter-retrieved focusing quality.

Image Transmission in Low-Power Networks in Mobile Communications Channel

This paper studies a vital issue in wireless communications, which is the transmission of images over Wireless Personal Area Networks (WPANs) through the Bluetooth network. It presents a simple method to improve the efficiency of error control code of old Bluetooth versions over mobile WPANs through Interleaved Error Control Code (IECC) technique. The encoded packets are interleaved by simple block interleaver. Also, the paper presents a chaotic interleaving scheme as a tool against bursts of errors which depends on the chaotic Baker map. Also, the paper proposes using the chaotic interleaver instead of traditional block interleaver with Forward Error Control (FEC) scheme. A comparison study between the proposed and standard techniques for image transmission over a correlated fading channel is presented. Simulation results reveal the superiority of the proposed chaotic interleaving scheme to other schemes. Also, the superiority of FEC with proposed chaotic interleaver to the conventional interleavers with enhancing the security level with chaotic interleaving packetby- packet basis.

Development of an Organizational Knowledge Capabilities Assessment (OKCA) Method for Innovative Technology Enterprises

Knowledge capabilities are increasingly important for the innovative technology enterprises to enhance the business performance in terms of product competitiveness, innovation and sales. Recognition of the company capability by auditing allows them to further pursue advancement, strategic planning and hence gain competitive advantages. This paper attempts to develop an Organizations- Knowledge Capabilities Assessment (OKCA) method to assess the knowledge capabilities of technology companies. The OKCA is a questionnaire-based assessment tool which has been developed to uncover the impact of various knowledge capabilities on different organizational performance. The collected data is then analyzed to find out the crucial elements for different technological companies. Based on the results, innovative technology enterprises are able to recognize the direction for further improvement on business performance and future development plan. External environmental factors affecting organization performance can be found through the further analysis of some selected reference companies.