Regional Development Programs: A Reason for Them Failing

This paper contributes to the analysis of the design of regional development programs. This is a case study the birth, life, death and afterlife of a stately development program in Norway, supporting diffusion of innovations by promoting e-business in SMEs (small and medium sized enterprises). The study shows that joint projects like regional development programs have to be designed such that the present value of the future benefits always exceeds the present value of the future effort for all stakeholders vital for the survival of the project. The study also indicate that a development program not always have one common goal which all the stakeholders agree upon. There are several stakeholders who may have different goals by playing a part in the realization of the program. Even if some parties evaluate the results of a development program as a failure, other may have attained their goals. The lessons learned from this study may advise the designers of development programs involving many independent stakeholders. There is a lack of research examining failing development programs, investigating the reasons for it to be considered a failure. This paper shows why a development program was terminated and gives hint to how joint programs could be designed in order for the program to deliver the wanted results to all the key stakeholders.

Multimodal Biometric Authentication Using Choquet Integral and Genetic Algorithm

The Choquet integral is a tool for the information fusion that is very effective in the case where fuzzy measures associated with it are well chosen. In this paper, we propose a new approach for calculating fuzzy measures associated with the Choquet integral in a context of data fusion in multimodal biometrics. The proposed approach is based on genetic algorithms. It has been validated in two databases: the first base is relative to synthetic scores and the second one is biometrically relating to the face, fingerprint and palmprint. The results achieved attest the robustness of the proposed approach.

Adaptive Score Normalization: A Novel Approach for Multimodal Biometric Systems

Multimodal biometric systems integrate the data presented by multiple biometric sources, hence offering a better performance than the systems based on a single biometric modality. Although the coupling of biometric systems can be done at different levels, the fusion at the scores level is the most common since it has been proven effective than the rest of the fusion levels. However, the scores from different modalities are generally heterogeneous. A step of normalizing the scores is needed to transform these scores into a common domain before combining them. In this paper, we study the performance of several normalization techniques with various fusion methods in a context relating to the merger of three unimodal systems based on the face, the palmprint and the fingerprint. We also propose a new adaptive normalization method that takes into account the distribution of client scores and impostor scores. Experiments conducted on a database of 100 people show that the performances of a multimodal system depend on the choice of the normalization method and the fusion technique. The proposed normalization method has given the best results.

Isolation and Classification of Red Blood Cells in Anemic Microscopic Images

Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. Anemia is a lack of RBCs is characterized by its level compared to the normal hemoglobin level. In this study, a system based image processing methodology was developed to localize and extract RBCs from microscopic images. Also, the machine learning approach is adopted to classify the localized anemic RBCs images. Several textural and geometrical features are calculated for each extracted RBCs. The training set of features was analyzed using principal component analysis (PCA). With the proposed method, RBCs were isolated in 4.3secondsfrom an image containing 18 to 27 cells. The reasons behind using PCA are its low computation complexity and suitability to find the most discriminating features which can lead to accurate classification decisions. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network RBFNN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained within short time period, and the results became better when PCA was used.

Kinetic Theory Based CFD Modeling of Particulate Flows in Horizontal Pipes

The numerical simulation of fully developed gas–solid flow in a horizontal pipe is done using the eulerian-eulerian approach, also known as two fluids modeling as both phases are treated as continuum and inter-penetrating continua. The solid phase stresses are modeled using kinetic theory of granular flow (KTGF). The computed results for velocity profiles and pressure drop are compared with the experimental data. We observe that the convection and diffusion terms in the granular temperature cannot be neglected in gas solid flow simulation along a horizontal pipe. The particle-wall collision and lift also play important role in eulerian modeling. We also investigated the effect of flow parameters like gas velocity, particle properties and particle loading on pressure drop prediction in different pipe diameters. Pressure drop increases with gas velocity and particle loading. The gas velocity has the same effect ((proportional toU2 ) as single phase flow on pressure drop prediction. With respect to particle diameter, pressure drop first increases, reaches a peak and then decreases. The peak is a strong function of pipe bore.

Numerical Simulation of High Pressure Hydrogen Emerges to Air

Numerical simulation performed to investigate the behavior of the high pressure hydrogen jetting of air. High pressure hydrogen (30–40 MPa) was injected to air at atmospheric pressure through 2mm orifice. Numerical simulations were performed with Kiva3V code with 2D axisymmetric geometry. Numerical simulations showed that auto ignition of high pressure hydrogen to air are possible due to molecular diffusion. Auto ignition was predicted at hydrogen-air contact surface due to mass and energy exchange between high temperature hydrogen and air heated by shock wave.

The Strategy of Creating a Virtual Interactive Platform for the Low-Carbon Open Innovations Relay

A strategy for the creation of a Virtual Interactive Platform (or Networking Platform) to combine the four web-baseness of expert systems on the transfer and diffusion of low-carbon technologies. It used the concept of “Open Innovation” and “Triple Helix” with regard to theories of “Green Growth” and “Carbon Footprint”. Interpreters expert systems operate on the basis of models of the “Predator-Prey” for the process of transfer and diffusion of technologies, taking into account the features caused by the need to mitigate the effects of climate change.

Phase Transition Characteristics of Flame-Synthesized Gamma-Al2O3 Nanoparticles with Heat Treatment

In this study, the phase transition characteristics of flame-synthesized γ-Al2O3 nanoparticles to α-Al2O3 have been investigated. The nanoparticles were synthesized by using a coflow hydrogen diffusion flame. The phase transition and particle characteristics of the Al2O3 nanoparticles were determined by examining the crystalline structure and the shape of the collected nanoparticles before and after the heat treatment. The morphology and crystal structure of the Al2O3 nanoparticles were determined from SEM images and XRD analyses, respectively. The measured specific surface area and averaged particle size were 63.44m2/g and 23.94nm, respectively. Based on the scanning electron microscope images and x-ray diffraction patterns, it is believed that the onset temperature of the phase transition to α-Al2O3 was existed near 1200oC. The averaged diameters of the sintered particles heat treated at 1,260oC were approximately 80nm.

Catalytic Gasification of Olive Mill Wastewater as a Biomass Source under Supercritical Conditions

Recently, a growing interest has emerged on the development of new and efficient energy sources, due to the inevitable extinction of the nonrenewable energy reserves. One of these alternative sources which have a great potential and sustainability to meet up the energy demand is biomass energy. This significant energy source can be utilized with various energy conversion technologies, one of which is biomass gasification in supercritical water. Water, being the most important solvent in nature, has very important characteristics as a reaction solvent under supercritical circumstances. At temperatures above its critical point (374.8oC and 22.1MPa), water becomes more acidic and its diffusivity increases. Working with water at high temperatures increases the thermal reaction rate, which in consequence leads to a better dissolving of the organic matters and a fast reaction with oxygen. Hence, supercritical water offers a control mechanism depending on solubility, excellent transport properties based on its high diffusion ability and new reaction possibilities for hydrolysis or oxidation. In this study the gasification of a real biomass, namely olive mill wastewater (OMW), in supercritical water conditions is investigated with the use of Ru/Al2O3 catalyst. OMW is a by-product obtained during olive oil production, which has a complex nature characterized by a high content of organic compounds and polyphenols. These properties impose OMW a significant pollution potential, but at the same time, the high content of organics makes OMW a desirable biomass candidate for energy production. The catalytic gasification experiments were made with five different reaction temperatures (400, 450, 500, 550 and 600°C) and five reaction times (30, 60, 90, 120 and 150s), under a constant pressure of 25MPa. Through these experiments, the effects of reaction temperature and time on the gasification yield, gaseous product composition and OMW treatment efficiency were investigated.

Analysis of Drying Kinetics of a Slurry Droplet in the Falling Rate Period of Spray Drying

The heat and mass transfer was investigated during the falling rate period of spray drying of a slurry droplet. The effect of the porosity of crust layer formed from primary particles during liquid evaporation was studied numerically using the developed mathematical model which takes into account the heat and mass transfer in the core and crust regions, the movement of the evaporation interface, and the external heat and mass transfer between the drying air and the droplet surface. It was confirmed that the heat transfer through the crust layer was more intense in the case of the dense droplet than the loose one due to the enhanced thermal conduction resulting in the higher average droplet temperature. The mass transfer was facilitated in the crust layer of loose droplet owing to the large pore space available for diffusion of water vapor from the evaporation interface to the outer droplet surface. The longer drying time is required for the droplet of high porosity to reach the final moisture content than that for the dense one due to the larger amount of water to be evaporated during the falling rate.

Semantic Support for Hypothesis-Based Research from Smart Environment Monitoring and Analysis Technologies

Improvements in the data fusion and data analysis phase of research are imperative due to the exponential growth of sensed data. Currently, there are developments in the Semantic Sensor Web community to explore efficient methods for reuse, correlation and integration of web-based data sets and live data streams. This paper describes the integration of remotely sensed data with web-available static data for use in observational hypothesis testing and the analysis phase of research. The Semantic Reef system combines semantic technologies (e.g., well-defined ontologies and logic systems) with scientific workflows to enable hypothesis-based research. A framework is presented for how the data fusion concepts from the Semantic Reef architecture map to the Smart Environment Monitoring and Analysis Technologies (SEMAT) intelligent sensor network initiative. The data collected via SEMAT and the inferred knowledge from the Semantic Reef system are ingested to the Tropical Data Hub for data discovery, reuse, curation and publication.

Parametric Analysis on Information Technology Adoption and Organizational Efficiency in Northern Nigeria

The adoption and diffusion of Information Technology (IT) is one of the fastest growing trends in organizations operating within Nigeria’s economy. Public and private organizations make huge capital investments in an attempt acquire and adopt the state-of-the-art IT for improving operational efficiency. In this study the level of IT adoption is considered the primary driver of efficiency witnessed by organizations. The research gathered data on the intensity of IT usage, and resultant efficiency increase in the organizations’ operations. The data was analyzed using multiple regression analysis and reveals that high level of IT usage has enhance efficiency of private and public organizations in Northern part of Nigeria with organizations having strategic intent on IT adoption indicating higher efficiency gains.

Factors Affecting the Citizen’s Intention to Adopt E-government in Saudi Arabia

This paper discusses E-government, in particular the challenges that face its development and widespread adoption in Saudi Arabia. E-government can be defined based on an existing set of requirements. E-government has been implemented for a considerable time in developed countries. However, E-government services still face many challenges in their implementation and general adoption in Saudi Arabia. In addition, the literature review and the discussion identify the influential factors, such as quality of service, diffusion of innovation, computer and information literacy, culture, lack of awareness, technical infrastructure, website design, and security, that affect the citizens’ intention to adopt E-government services in Saudi Arabia. Consequently, these factors have been integrated in a new model that would influence citizen to adopt E- government services. Therefore, this research presents an integrated model for ascertaining the intention to adopt E-government services and thereby aiding governments in accessing what is required to increase adoption.

The Relationship between Fugacity and Stress Intensity Factor for Corrosive Environment in Presence of Hydrogen Embrittlement

Hydrogen diffusion is the main problem for corrosion fatigue in corrosive environment. In order to analyze the phenomenon, it is needed to understand their behaviors specially the hydrogen behavior during the diffusion. So, Hydrogen embrittlement and prediction its behavior as a main corrosive part of the fractions, needed to solve combinations of different equations mathematically. The main point to obtain the equation, having knowledge about the source of causing diffusion and running the atoms into materials, called driving force. This is produced by either gradient of electrical or chemical potential. In this work, we consider the gradient of chemical potential to obtain the property equation. In diffusion of atoms, some of them may be trapped but, it could be ignorable in some conditions. According to the phenomenon of hydrogen embrittlement, the thermodynamic and chemical properties of hydrogen are considered to justify and relate them to fracture mechanics. It is very important to get a stress intensity factor by using fugacity as a property of hydrogen or other gases. Although, the diffusive behavior and embrittlement event are common and the same for other gases but, for making it more clear, we describe it for hydrogen. This considering on the definite gas and describing it helps us to understand better the importance of this relation.

Feature Preserving Nonlinear Diffusion for Ultrasonic Image Denoising and Edge Enhancement

Utilizing echoic intension and distribution from different organs and local details of human body, ultrasonic image can catch important medical pathological changes, which unfortunately may be affected by ultrasonic speckle noise. A feature preserving ultrasonic image denoising and edge enhancement scheme is put forth, which includes two terms: anisotropic diffusion and edge enhancement, controlled by the optimum smoothing time. In this scheme, the anisotropic diffusion is governed by the local coordinate transformation and the first and the second order normal derivatives of the image, while the edge enhancement is done by the hyperbolic tangent function. Experiments on real ultrasonic images indicate effective preservation of edges, local details and ultrasonic echoic bright strips on denoising by our scheme.

Multigrid Bilateral Filter

It has proved that nonlinear diffusion and bilateral filtering (BF) have a closed connection. Early effort and contribution are to find a generalized representation to link them by using adaptive filtering. In this paper a new further relationship between nonlinear diffusion and bilateral filtering is explored which pays more attention to numerical calculus. We give a fresh idea that bilateral filtering can be accelerated by multigrid (MG) scheme which likes the nonlinear diffusion, and show that a bilateral filtering process with large kernel size can be approximated by a nonlinear diffusion process based on full multigrid (FMG) scheme.

An Improved Phenomenological Model for Polymer Desorption

We propose a phenomenological model for the process of polymer desorption. In so doing, we omit the usual theoretical approach of incorporating a fictitious viscoelastic stress term into the flux equation. As a result, we obtain a model that captures the essence of the phenomenon of trapping skinning, while preserving the integrity of the experimentally verified Fickian law for diffusion. An appropriate asymptotic analysis is carried out, and a parameter is introduced to represent the speed of the desorption front. Numerical simulations are performed to illustrate the desorption dynamics of the model. Recommendations are made for future modifications of the model, and provisions are made for the inclusion of experimentally determined frontal speeds.

Manipulation of Probiotics Fermentation of Yogurt by Cinnamon and Licorice: Effects on Yogurt Formation and Inhibition of Helicobacter Pylori Growth in vitro

Probiotic bacteria especially Lactobacillus spp. and Bifidobacterium exert suppressive effect on Helicobacter pylori. Cinnamon and licorice have been traditionally used for the treatment of gastric ulcer. The objectives of this study were to determine the effects of herbs on yogurt fermentation, the level of probiotic bacteria in yogurt during 28 days storage and the effect of herbal yogurt on the growth of H. pylori in vitro. Cinnamon or licorice was mixed with milk and the mixture was fermented with probiotic bacteria to form herbal-yogurt. Changes of pH and total titratable acids were monitored and the viability of probiotic bacteria was evaluated during and after refrigerated storage. The in vitro inhibition of H. pylori growth was determined using agar diffusion and minimum inhibitory concentration (MIC) method. The presence of herbs did not affect the probiotic population during storage. There were no significant differences in pH and TTA between herbal-yogurts and plain-yogurt during fermentation and storage. Water extract of cinnamon-yogurt showed the highest inhibition effect (13.5mm) on H. pylori growth in comparison with licorice-yogurt (11.2mm). The present findings indicate cinnamon and licorice has bioactive components to decrease the growth of H. pylori.

Monte Carlo Simulation of Copolymer Heterogeneity in Atom Transfer Radical Copolymerization of Styrene and N-Butyl Acrylate

A high-performance Monte Carlo simulation, which simultaneously takes diffusion-controlled and chain-length-dependent bimolecular termination reactions into account, is developed to simulate atom transfer radical copolymerization of styrene and nbutyl acrylate. As expected, increasing initial feed fraction of styrene raises the fraction of styrene-styrene dyads (fAA) and reduces that of n-butyl acrylate dyads (fBB). The trend of variation in randomness parameter (fAB) during the copolymerization also varies significantly. Also, there is a drift in copolymer heterogeneity and the highest drift occurs in the initial feeds containing lower percentages of styrene, i.e. 20% and 5%.

Trapping Efficiency of Diesel Particles Through a Square Duct

Diesel Engines emit complex mixtures of inorganic and organic compounds in the form of both solid and vapour phase particles. Most of the particulates released are ultrafine nanoparticles which are detrimental to human health and can easily enter the body by respiration. The emissions standards on particulate matter release from diesel engines are constantly upgraded within the European Union and with future regulations based on the particles numbers released instead of merely mass, the need for effective aftertreatment devices will increase. Standard particulate filters in the form of wall flow filters can have problems with high soot accumulation, producing a large exhaust backpressure. A potential solution would be to combine the standard filter with a flow through filter to reduce the load on the wall flow filter. In this paper soot particle trapping has been simulated in different continuous flow filters of monolithic structure including the use of promoters, at laminar flow conditions. An Euler Lagrange model, the discrete phase model in Ansys used with user defined functions for forces acting on particles. A method to quickly screen trapping of 5 nm and 10 nm particles in different catalysts designs with tracers was also developed. Simulations of square duct monoliths with promoters show that the strength of the vortices produced are not enough to give a high amount of particle deposition on the catalyst walls. The smallest particles in the simulations, 5 and 10 nm particles were trapped to a higher extent, than larger particles up to 1000 nm, in all studied geometries with the predominant deposition mechanism being Brownian diffusion. The comparison of the different filters designed with a wall flow filter does show that the options for altering a design of a flow through filter, without imposing a too large pressure drop penalty are good.