An Optimization Model of CMMI-Based Software Project Risk Response Planning

Risk response planning is of importance for software project risk management (SPRM). In CMMI, risk management was in the third capability maturity level, which provides a framework for software project risk identification, assessment, risk planning, risk control. However, the CMMI-based SPRM currently lacks quantitative supporting tools, especially during the process of implementing software project risk planning. In this paper, an economic optimization model for selecting risk reduction actions in the phase of software project risk response planning is presented. Furthermore, an example taken from a Chinese software industry is illustrated to verify the application of this method. The research provides a risk decision method for project risk managers that can be used in the implementation of CMMI-based SPRM.

Transient Energy and its Impact on Transmission Line Faults

Transmission and distribution lines are vital links between the generating unit and consumers. They are exposed to atmosphere, hence chances of occurrence of fault in transmission line is very high which has to be immediately taken care of in order to minimize damage caused by it. In this paper Discrete wavelet transform of voltage signals at the two ends of transmission lines have been analyzed. The transient energy of the detail information of level five is calculated for different fault conditions. It is observed that the variation of transient energy of healthy and faulted line can give important information which can be very useful in classifying and locating the fault.

DAMQ-Based Approach for Efficiently Using the Buffer Spaces of a NoC Router

In this paper we present high performance dynamically allocated multi-queue (DAMQ) buffer schemes for fault tolerance systems on chip applications that require an interconnection network. Two virtual channels shared the same buffer space. Fault tolerant mechanisms for interconnection networks are becoming a critical design issue for large massively parallel computers. It is also important to high performance SoCs as the system complexity keeps increasing rapidly. On the message switching layer, we make improvement to boost system performance when there are faults involved in the components communication. The proposed scheme is when a node or a physical channel is deemed as faulty, the previous hop node will terminate the buffer occupancy of messages destined to the failed link. The buffer usage decisions are made at switching layer without interactions with higher abstract layer, thus buffer space will be released to messages destined to other healthy nodes quickly. Therefore, the buffer space will be efficiently used in case fault occurs at some nodes.

Evaluating and Selecting Optimization Software Packages: A Framework for Business Applications

Owing the fact that optimization of business process is a crucial requirement to navigate, survive and even thrive in today-s volatile business environment, this paper presents a framework for selecting a best-fit optimization package for solving complex business problems. Complexity level of the problem and/or using incorrect optimization software can lead to biased solutions of the optimization problem. Accordingly, the proposed framework identifies a number of relevant factors (e.g. decision variables, objective functions, and modeling approach) to be considered during the evaluation and selection process. Application domain, problem specifications, and available accredited optimization approaches are also to be regarded. A recommendation of one or two optimization software is the output of the framework which is believed to provide the best results of the underlying problem. In addition to a set of guidelines and recommendations on how managers can conduct an effective optimization exercise is discussed.

Mouse Pointer Tracking with Eyes

In this article, we expose our research work in Human-machine Interaction. The research consists in manipulating the workspace by eyes. We present some of our results, in particular the detection of eyes and the mouse actions recognition. Indeed, the handicaped user becomes able to interact with the machine in a more intuitive way in diverse applications and contexts. To test our application we have chooses to work in real time on videos captured by a camera placed in front of the user.

Study on the Effect of Sulphur, Glucose, Nitrogen and Plant Residues on the Immobilization of Sulphate-S in Soil

In order to evaluate the relationship between the sulphur (S), glucose (G), nitrogen (N) and plant residues (st), sulphur immobilization and microbial transformation were monitored in five soil samples from 0-30 cm of Bastam farmers fields of Shahrood area following 11 treatments with different levels of Sulphur (S), glucose (G), N and plant residues (wheat straw) in a randomized block design with three replications and incubated over 20, 45 and 60 days, the immobilization of SO4 -2-S presented as a percentage of that added, was inversely related to its addition rate. Additions of glucose and plant residues increased with the C-to-S ratio of the added amendments, irrespective of their origins (glucose and plant residues). In the presence of C sources (glucose or plant residues). N significantly increased the immobilization of SO4 -2-S, whilst the effect of N was insignificant in the absence of a C amendment. In first few days the amounts of added SO4 -2-S immobilized were linearly correlated with the amounts of added S recovered in the soil microbial biomass. With further incubation the proportions of immobilized SO4 -2-S remaining as biomass-S decreased. Decrease in biomass-S was thought to be due to the conversion of biomass-S into soil organic-S. Glucose addition increased the immobilization (microbial utilization and incorporation into the soil organic matter) of native soil SO4 -2-S. However, N addition enhance the mineralization of soil organic-S, increasing the concentration of SO4 - 2-S in soil.

Probe Selection for Pathway-Specific Microarray Probe Design Minimizing Melting Temperature Variance

In molecular biology, microarray technology is widely and successfully utilized to efficiently measure gene activity. If working with less studied organisms, methods to design custom-made microarray probes are available. One design criterion is to select probes with minimal melting temperature variances thus ensuring similar hybridization properties. If the microarray application focuses on the investigation of metabolic pathways, it is not necessary to cover the whole genome. It is more efficient to cover each metabolic pathway with a limited number of genes. Firstly, an approach is presented which minimizes the overall melting temperature variance of selected probes for all genes of interest. Secondly, the approach is extended to include the additional constraints of covering all pathways with a limited number of genes while minimizing the overall variance. The new optimization problem is solved by a bottom-up programming approach which reduces the complexity to make it computationally feasible. The new method is exemplary applied for the selection of microarray probes in order to cover all fungal secondary metabolite gene clusters for Aspergillus terreus.

HDS: Alumina- Boria Supported Catalysts

Hydrodesulfurization (HDS) of dibenzothiophene (DBT) in a high pressure batch reactor was done at 320 °C on CoMoS/Al2O3-B2O3 (4, 10, and 16 wt. % of Boria) using nhexadecane as solvent, dimethyldisulfide (DMDS) in tetradecane as sulfur agent, and stirring at 1000 rpm. The effects of boria were investigated by using X-ray diffraction (XRD), Temperature programmed desorption (TPD) of ammonia, and Brunauer-Emmet- Teller (BET) experiments. The results showed that the catalyst prepared with low boria content (4 wt. %) had HDS activity (in pseudo first order kinetic constant basis) value ~1.45 times higher to that of CoMoS/Al2O3 catalyst.

mCRM-s New Opportunities of Customer Satisfaction

This paper aims at a new challenge of customer satisfaction on mobile customer relationship management. In this paper presents a conceptualization of mCRM on its unique characteristics of customer satisfaction. Also, this paper develops an empirical framework in conception of customer satisfaction in mCRM. A single-case study is applied as the methodology. In order to gain an overall view of the empirical case, this paper accesses to invisible and important information of company in this investigation. Interview is the key data source form the main informants of the company through which the issues are identified and the proposed framework is built. It supports the development of customer satisfaction in mCRM; links this theoretical framework into practice; and provides the direction for future research. Therefore, this paper is very useful for the industries as it helps them to understand how customer satisfaction changes the mCRM structure and increase the business competitive advantage. Finally, this paper provides a contribution in practice by linking a theoretical framework in conception of customer satisfaction in mCRM for companies to a practical real case.

GeNS: a Biological Data Integration Platform

The scientific achievements coming from molecular biology depend greatly on the capability of computational applications to analyze the laboratorial results. A comprehensive analysis of an experiment requires typically the simultaneous study of the obtained dataset with data that is available in several distinct public databases. Nevertheless, developing a centralized access to these distributed databases rises up a set of challenges such as: what is the best integration strategy, how to solve nomenclature clashes, how to solve database overlapping data and how to deal with huge datasets. In this paper we present GeNS, a system that uses a simple and yet innovative approach to address several biological data integration issues. Compared with existing systems, the main advantages of GeNS are related to its maintenance simplicity and to its coverage and scalability, in terms of number of supported databases and data types. To support our claims we present the current use of GeNS in two concrete applications. GeNS currently contains more than 140 million of biological relations and it can be publicly downloaded or remotely access through SOAP web services.

Design of a Permanent Magnet Synchronous Machine for the Hybrid Electric Vehicle

Permanent magnet synchronous machines are known as a good candidate for hybrid electric vehicles due to their unique merits. However they have two major drawbacks i.e. high cost and small speed range. In this paper an optimal design of a permanent magnet machine is presented. A reduction of permanent magnet material for a constant torque and an extension in speed and torque ranges are chosen as the optimization aims. For this purpose the analytical model of the permanent magnet synchronous machine is derived and the appropriate design algorithm is devised. The genetic algorithm is then employed to optimize some machine specifications. Finally the finite element method is used to validate the designed machine.

A Reproduction of Boundary Conditions in Three-Dimensional Continuous Casting Problem

The paper discusses a 3D numerical solution of the inverse boundary problem for a continuous casting process of alloy. The main goal of the analysis presented within the paper was to estimate heat fluxes along the external surface of the ingot. The verified information on these fluxes was crucial for a good design of a mould, effective cooling system and generally the whole caster. In the study an enthalpy-porosity technique implemented in Fluent package was used for modeling the solidification process. In this method, the phase change interface was determined on the basis of the liquid fraction approach. In inverse procedure the sensitivity analysis was applied for retrieving boundary conditions. A comparison of the measured and retrieved values showed a high accuracy of the computations. Additionally, the influence of the accuracy of measurements on the estimated heat fluxes was also investigated.

Kinetics of Palm Oil Cracking in Batch Reactor

The kinetics of palm oil catalytic cracking over aluminum containing mesoporous silica Al-MCM-41 (5% Al) was investigated in a batch autoclave reactor at the temperatures range of 573 – 673 K. The catalyst was prepared by using sol-gel technique and has been characterized by nitrogen adsorption and x-ray diffraction methods. Surface area of 1276 m2/g with average pore diameter of 2.54 nm and pore volume of 0.811 cm3/g was obtained. The experimental catalytic cracking runs were conducted using 50 g of oil and 1 g of catalyst. The reaction pressure was recorded at different time intervals and the data were analyzed using Levenberg- Marquardt (LM) algorithm using polymath software. The results show that the reaction order was found to be -1.5 and activation energy of 3200 J/gmol.

Estimation of Forest Fire Emission in Thailand by Using Remote Sensing Information

The forest fires in Thailand are annual occurrence which is the cause of air pollutions. This study intended to estimate the emission from forest fire during 2005-2009 using MODerateresolution Imaging Spectro-radiometer (MODIS) sensor aboard the Terra and Aqua satellites, experimental data, and statistical data. The forest fire emission is estimated using equation established by Seiler and Crutzen in 1982. The spatial and temporal variation of forest fire emission is analyzed and displayed in the form of grid density map. From the satellite data analysis suggested between 2005 and 2009, the number of fire hotspots occurred 86,877 fire hotspots with a significant highest (more than 80% of fire hotspots) in the deciduous forest. The peak period of the forest fire is in January to May. The estimation on the emissions from forest fires during 2005 to 2009 indicated that the amount of CO, CO2, CH4, and N2O was about 3,133,845 tons, 47,610.337 tons, 204,905 tons, and 6,027 tons, respectively, or about 6,171,264 tons of CO2eq. They also emitted 256,132 tons of PM10. The year 2007 was found to be the year when the emissions were the largest. Annually, March is the period that has the maximum amount of forest fire emissions. The areas with high density of forest fire emission were the forests situated in the northern, the western, and the upper northeastern parts of the country.

Development and in vitro Characterization of Self-nanoemulsifying Drug Delivery Systems of Valsartan

The present study is aim to prepare and evaluate the selfnanoemulsifying drug delivery (SNEDDS) system of a poorly water soluble drug valsartan in order to achieve a better dissolution rate which would further help in enhancing oral bioavailability. The present research work describes a SNEDDS of valsartan using labrafil M 1944 CS, Tween 80 and Transcutol HP. The pseudoternary phase diagrams with presence and absence of drug were plotted to check for the emulsification range and also to evaluate the effect of valsartan on the emulsification behavior of the phases. The mixtures consisting of oil (labrafil M 1944 CS) with surfactant (tween 80), co-surfactant (Transcutol HP) were found to be optimum formulations. Prepared formulations were evaluated for its particle size distribution, nanoemulsifying properties, robustness to dilution, self emulsication time, turbidity measurement, drug content and invitro dissolution. The optimized formulations are further evaluated for heating cooling cycle, centrifugation studies, freeze thaw cycling, particle size distribution and zeta potential were carried out to confirm the stability of the formed SNEDDS formulations. The prepared formulation revealed t a significant improvement in terms of the drug solubility as compared with marketed tablet and pure drug.

Phase Equilibrium in Aqueous Two-phase Systems Containing Poly (propylene glycol) and Sodium Citrate at Different pH

The phase diagrams and compositions of coexisting phases have been determined for aqueous two-phase systems containing poly(propylene glycol) with average molecular weight of 425 and sodium citrate at various pH of 3.93, 4.44, 4.6, 4.97, 5.1, 8.22. The effect of pH on the salting-out effect of poly (propylene glycol) by sodium citrate has been studied. It was found that, an increasing in pH caused the expansion of two-phase region. Increasing pH also increases the concentration of PPG in the PPGrich phase, while the salt-rich phase will be somewhat mole diluted.

Cognitive Radio Networks (CRN): Resource Allocation Techniques Based On DNA-inspired Computing

Spectrum is a scarce commodity, and considering the spectrum scarcity faced by the wireless-based service providers led to high congestion levels. Technical inefficiencies from pooled, since all networks share a common pool of channels, exhausting the available channels will force networks to block the services. Researchers found that cognitive radio (CR) technology may resolve the spectrum scarcity. A CR is a self-configuring entity in a wireless networking that senses its environment, tracks changes, and frequently exchanges information with their networks. However, CRN facing challenges and condition become worst while tracks changes i.e. reallocation of another under-utilized channels while primary network user arrives. In this paper, channels or resource reallocation technique based on DNA-inspired computing algorithm for CRN has been proposed.

Educational Robotics Constructivism and Modeling of Robots using Reverse Engineering

The project describes the modeling of various architectures mechatronics specifically morphologies of robots in an educational environment. Each structure developed by students of pre-school, primary and secondary was created using the concept of reverse engineering in a constructivist environment, to later be integrated in educational software that promotes the teaching of educational Robotics in a virtual and economic environment.

Unsupervised Texture Classification and Segmentation

An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of independent non-Gaussian densities. The algorithm estimates the data density in each class by using parametric nonlinear functions that fit to the non-Gaussian structure of the data. This improves classification accuracy compared with standard Gaussian mixture models. When applied to textures, the algorithm can learn basis functions for images that capture the statistically significant structure intrinsic in the images. We apply this technique to the problem of unsupervised texture classification and segmentation.

Estimating Frequency, Amplitude and Phase of Two Sinusoids with Very Close Frequencies

This paper presents an algorithm to estimate the parameters of two closely spaced sinusoids, providing a frequency resolution that is more than 800 times greater than that obtained by using the Discrete Fourier Transform (DFT). The strategy uses a highly optimized grid search approach to accurately estimate frequency, amplitude and phase of both sinusoids, keeping at the same time the computational effort at reasonable levels. The proposed method has three main characteristics: 1) a high frequency resolution; 2) frequency, amplitude and phase are all estimated at once using one single package; 3) it does not rely on any statistical assumption or constraint. Potential applications to this strategy include the difficult task of resolving coincident partials of instruments in musical signals.