Classification and Analysis of Risks in Software Engineering

Despite various methods that exist in software risk management, software projects have a high rate of failure. When complexity and size of the projects are increased, managing software development becomes more difficult. In these projects the need for more analysis and risk assessment is vital. In this paper, a classification for software risks is specified. Then relations between these risks using risk tree structure are presented. Analysis and assessment of these risks are done using probabilistic calculations. This analysis helps qualitative and quantitative assessment of risk of failure. Moreover it can help software risk management process. This classification and risk tree structure can apply to some software tools.

The Effects of Feeding Raw Fiber Concentrate on Growth Performance and Blood Metabolites of Suckling Holstein Calves

Sixteen female Holstein calves allocated in three treatments including: 1: control, 2: fed raw fiber concentrate (RFC) for 45 days and 3: fed RFC for 90 days. RFC supplement (Vitacel® 200) was added to milk immediately before feeding (10 g/L milk). Withers height and body weights of calves were measured monthly. Individual dry matter intake was recorded daily. Blood samples were taken monthly. The result showed that calves consumed RFC had significantly greater weaning and final body weight. Treatment effect on dry matter intake was not significant (p>0.05). Calves fed RFC had better feed efficiency. Withers height of calves fed RFC were taller than the control group (p

Application of Neural Network in User Authentication for Smart Home System

Security has been an important issue and concern in the smart home systems. Smart home networks consist of a wide range of wired or wireless devices, there is possibility that illegal access to some restricted data or devices may happen. Password-based authentication is widely used to identify authorize users, because this method is cheap, easy and quite accurate. In this paper, a neural network is trained to store the passwords instead of using verification table. This method is useful in solving security problems that happened in some authentication system. The conventional way to train the network using Backpropagation (BPN) requires a long training time. Hence, a faster training algorithm, Resilient Backpropagation (RPROP) is embedded to the MLPs Neural Network to accelerate the training process. For the Data Part, 200 sets of UserID and Passwords were created and encoded into binary as the input. The simulation had been carried out to evaluate the performance for different number of hidden neurons and combination of transfer functions. Mean Square Error (MSE), training time and number of epochs are used to determine the network performance. From the results obtained, using Tansig and Purelin in hidden and output layer and 250 hidden neurons gave the better performance. As a result, a password-based user authentication system for smart home by using neural network had been developed successfully.

Growth and Mineral Content of Mokara chark kuan Pink Orchid as Affected by Allelopathic Lantana camara Weed

Growth and mineral nutrient elemental content were studied in Mokara chark kuan pink terrestrial orchid and wild Lantana camara weed agroecosystem. The treated subplots were encircled with L. camara plants and sprayed weekly with L. camara 10% leaf aqueous extract. Allelopathic interactions were possible through extensive invading root of L. camara plants into the treated orchid subplots and weekly L. camara leaf aqueous extract sprayings. Orchid growth was not significantly different in between the control and treated plots, but chlorosis and yellowish patches of leaves were observed in control orchid leaves. Nitrogen content in L. camara leaf was significantly higher than in orchid leaf, the order of importance of mineral nutrient contents in L. camara leaf was K>Mg>Na>N. In treated orchid leaf, the order of importance was N>K>Mg>Na. Orchid leaf N content from the treated plot was higher than control, but Mg and Na contents were almost similar.

A Novel Strategy for Oriented Protein Immobilization

A new strategy for oriented immobilization of proteins was proposed. The strategy contains two steps. The first step is to search for a docking site away from the active site on the protein surface. The second step is trying to find a ligand that is able to grasp the targeted site of the protein. To avoid ligand binding to the active site of protein, the targeted docking site is selected to own opposite charges to those near the active site. To enhance the ligand-protein binding, both hydrophobic and electrostatic interactions need to be included. The targeted docking site should therefore contain hydrophobic amino acids. The ligand is then selected through the help of molecular docking simulations. The enzyme α-amylase derived from Aspergillus oryzae (TAKA) was taken as an example for oriented immobilization. The active site of TAKA is surrounded by negatively charged amino acids. All the possible hydrophobic sites on the surface of TAKA were evaluated by the free energy estimation through benzene docking. A hydrophobic site on the opposite side of TAKA-s active site was found to be positive in net charges. A possible ligand, 3,3-,4,4- – Biphenyltetra- carboxylic acid (BPTA), was found to catch TAKA by the designated docking site. Then, the BPTA molecules were grafted onto silica gels and measured the affinity of TAKA adsorption and the specific activity of thereby immobilized enzymes. It was found that TAKA had a dissociation constant as low as 7.0×10-6 M toward the ligand BPTA on silica gel. The increase in ionic strength has little effect on the adsorption of TAKA, which indicated the existence of hydrophobic interaction between ligands and proteins. The specific activity of the immobilized TAKA was compared with the randomly adsorbed TAKA on primary amine containing silica gel. It was found that the orderly immobilized TAKA owns a specific activity twice as high as the one randomly adsorbed by ionic interaction.

Effect of VA-Mycorrhiza on Growth and Yield of Sunflower (Helianthus annuus L.) at Different Phosphorus Levels

The effect of seed inoculation by VA- mycorrhiza and different levels of phosphorus fertilizer on growth and yield of sunflower (Azargol cultivar) was studied in experiment farm of Islamic Azad University, Karaj Branch during 2008 growing season. The experiment treatments were arranged in factorial based on a complete randomized block design with three replications. Four phosphorus fertilizer levels of 25%, 50% 75% and 100% P recommended with two levels of Mycorrhiza: with and without Mycorrhiza (control) were assigned in a factorial combination. Results showed that head diameter, number of seeds in head, seed yield and oil yield were significantly higher in inoculated plants than in non-inoculated plants. Head diameter, number of seeds in head, 1000 seeds weight, biological yield, seed yield and oil yield increased with increasing P level above 75% P recommended in non-inoculated plants, whereas no significant difference was observed between 75% and 100% P recommended. The positive effect of mycorrhizal inoculation decreased with increasing P levels due to decreased percent root colonization at higher P levels. According to the results of this experiment, application of mycorrhiza in present of 50% P recommended had an appropriate performance and could increase seed yield and oil production to an acceptable level, so it could be considered as a suitable substitute for chemical phosphorus fertilizer in organic agricultural systems.

Concept Abduction in Description Logics with Cardinality Restrictions

Recently the usefulness of Concept Abduction, a novel non-monotonic inference service for Description Logics (DLs), has been argued in the context of ontology-based applications such as semantic matchmaking and resource retrieval. Based on tableau calculus, a method has been proposed to realize this reasoning task in ALN, a description logic that supports simple cardinality restrictions as well as other basic constructors. However, in many ontology-based systems, the representation of ontology would require expressive formalisms for capturing domain-specific constraints, this language is not sufficient. In order to increase the applicability of the abductive reasoning method in such contexts, we would like to present in the scope of this paper an extension of the tableaux-based algorithm for dealing with concepts represented inALCQ, the description logic that extends ALN with full concept negation and quantified number restrictions.

Portfolio Management: A Fuzzy Set Based Approach to Monitoring Size to Maximize Return and Minimize Risk

Fuzzy logic can be used when knowledge is incomplete or when ambiguity of data exists. The purpose of this paper is to propose a proactive fuzzy set- based model for reacting to the risk inherent in investment activities relative to a complete view of portfolio management. Fuzzy rules are given where, depending on the antecedents, the portfolio size may be slightly or significantly decreased or increased. The decision maker considers acceptable bounds on the proportion of acceptable risk and return. The Fuzzy Controller model allows learning to be achieved as 1) the firing strength of each rule is measured, 2) fuzzy output allows rules to be updated, and 3) new actions are recommended as the system continues to loop. An extension is given to the fuzzy controller that evaluates potential financial loss before adjusting the portfolio. An application is presented that illustrates the algorithm and extension developed in the paper.

A Multivariate Moving Average Control Chart for Photovoltaic Processes

For the electrical metrics that describe photovoltaic cell performance are inherently multivariate in nature, use of a univariate, or one variable, statistical process control chart can have important limitations. Development of a comprehensive process control strategy is known to be significantly beneficial to reducing process variability that ultimately drives up the manufacturing cost photovoltaic cells. The multivariate moving average or MMA chart, is applied to the electrical metrics of photovoltaic cells to illustrate the improved sensitivity on process variability this method of control charting offers. The result show the ability of the MMA chart to expand to as any variables as needed, suggests an application with multiple photovoltaic electrical metrics being used in concert to determine the processes state of control.

Enhancement of Methane Productivity of Anaerobic Reactors of Wastewater Treatment Plants

This paper describes technological possibilities to enhance methane productionin the anaerobic stabilization of wastewater treatment plant excess sludge. This objective can be achieved by the addition of waste residues: crude glycerol from biodiesel production and residues from fishery. The addition ofglycerol in an amount by weight of 2 – 5% causes enhancement of methane production of about 250 – 400%. At the same time the percentage increase of total solids concentration in the outgoing sludge is ten or more times less. The containment of methane in biogas is higher in case of admixed substrate.

Defect Cause Modeling with Decision Tree and Regression Analysis

The main aim of this study is to identify the most influential variables that cause defects on the items produced by a casting company located in Turkey. To this end, one of the items produced by the company with high defective percentage rates is selected. Two approaches-the regression analysis and decision treesare used to model the relationship between process parameters and defect types. Although logistic regression models failed, decision tree model gives meaningful results. Based on these results, it can be claimed that the decision tree approach is a promising technique for determining the most important process variables.

Impact of Implementing VPN to Secure Wireless LAN

Many corporations are seriously concerned about security of networks and therefore, their network supervisors are still reluctant to install WLANs. In this regards, the IEEE802.11i standard was developed to address the security problems, even though the mistrust of the wireless LAN technology is still existing. The thought was that the best security solutions could be found in open standards based technologies that can be delivered by Virtual Private Networking (VPN) being used for long time without addressing any security holes for the past few years. This work, addresses this issue and presents a simulated wireless LAN of IEEE802.11g protocol, and analyzes impact of integrating Virtual Private Network technology to secure the flow of traffic between the client and the server within the LAN, using OPNET WLAN utility. Two Wireless LAN scenarios have been introduced and simulated. These are based on normal extension to a wired network and VPN over extension to a wired network. The results of the two scenarios are compared and indicate the impact of improving performance, measured by response time and load, of Virtual Private Network over wireless LAN.

Optimization of New 25A-size Metal Gasket Design Based on Contact Width Considering Forming and Contact Stress Effect

At the previous study of new metal gasket, contact width and contact stress were important design parameter for optimizing metal gasket performance. However, the range of contact stress had not been investigated thoroughly. In this study, we conducted a gasket design optimization based on an elastic and plastic contact stress analysis considering forming effect using FEM. The gasket model was simulated by using two simulation stages which is forming and tightening simulation. The optimum design based on an elastic and plastic contact stress was founded. Final evaluation was determined by helium leak quantity to check leakage performance of both type of gaskets. The helium leak test shows that a gasket based on the plastic contact stress design better than based on elastic stress design.

Diffusion Analysis of a Scalable Feistel Network

A generalization of the concepts of Feistel Networks (FN), known as Extended Feistel Network (EFN) is examined. EFN splits the input blocks into n > 2 sub-blocks. Like conventional FN, EFN consists of a series of rounds whereby at least one sub-block is subjected to an F function. The function plays a key role in the diffusion process due to its completeness property. It is also important to note that in EFN the F-function is the most computationally expensive operation in a round. The aim of this paper is to determine a suitable type of EFN for a scalable cipher. This is done by analyzing the threshold number of rounds for different types of EFN to achieve the completeness property as well as the number of F-function required in the network. The work focuses on EFN-Type I, Type II and Type III only. In the analysis it is found that EFN-Type II and Type III diffuses at the same rate and both are faster than Type-I EFN. Since EFN-Type-II uses less F functions as compared to EFN-Type III, therefore Type II is the most suitable EFN for use in a scalable cipher.

Influence of Hydraulic Retention Time on Biogas Production from Frozen Seafood Wastewater using Decanter Cake as Anaerobic Co-digestion Material

In this research, an anaerobic co-digestion using decanter cake from palm oil mill industry to improve the biogas production from frozen seafood wastewater is studied using Continuously Stirred Tank Reactor (CSTR) process. The experiments were conducted in laboratory-scale. The suitable Hydraulic Retention Time (HRT) was observed in CSTR experiments with 24 hours of mixing time using the mechanical mixer. The HRT of CSTR process impacts on the efficiency of biogas production. The best performance for biogas production using CSTR process was the anaerobic codigestion for 20 days of HRT with the maximum methane production rate of 1.86 l/d and the average maximum methane production of 64.6%. The result can be concluded that the decanter cake can improve biogas productivity of frozen seafood wastewater.

Mean-Square Performance of Adaptive Filter Algorithms in Nonstationary Environments

Employing a recently introduced unified adaptive filter theory, we show how the performance of a large number of important adaptive filter algorithms can be predicted within a general framework in nonstationary environment. This approach is based on energy conservation arguments and does not need to assume a Gaussian or white distribution for the regressors. This general performance analysis can be used to evaluate the mean square performance of the Least Mean Square (LMS) algorithm, its normalized version (NLMS), the family of Affine Projection Algorithms (APA), the Recursive Least Squares (RLS), the Data-Reusing LMS (DR-LMS), its normalized version (NDR-LMS), the Block Least Mean Squares (BLMS), the Block Normalized LMS (BNLMS), the Transform Domain Adaptive Filters (TDAF) and the Subband Adaptive Filters (SAF) in nonstationary environment. Also, we establish the general expressions for the steady-state excess mean square in this environment for all these adaptive algorithms. Finally, we demonstrate through simulations that these results are useful in predicting the adaptive filter performance.

Static Single Point Positioning Using The Extended Kalman Filter

Global Positioning System (GPS) technology is widely used today in the areas of geodesy and topography as well as in aeronautics mainly for military purposes. Due to the military usage of GPS, full access and use of this technology is being denied to the civilian user who must then work with a less accurate version. In this paper we focus on the estimation of the receiver coordinates ( X, Y, Z ) and its clock bias ( δtr ) of a fixed point based on pseudorange measurements of a single GPS receiver. Utilizing the instantaneous coordinates of just 4 satellites and their clock offsets, by taking into account the atmospheric delays, we are able to derive a set of pseudorange equations. The estimation of the four unknowns ( X, Y, Z , δtr ) is achieved by introducing an extended Kalman filter that processes, off-line, all the data collected from the receiver. Higher performance of position accuracy is attained by appropriate tuning of the filter noise parameters and by including other forms of biases.

Dexamethasone: Impact on Testicular Activity

Dexamethasone (Dex) is a synthetic glucocorticoid that is used in therapy. However prolonged treatments with high doses are often required. This causes side effects that interfere with the activity of several endocrine systems, including the gonadotropic axis. The aim of our study is to determine the effect of Dex on testicular function in prepubertal Wistar rats. Newborn Wistar rats are submitted to intraperitoneal injection of Dex (1μg of Dex dissolved in NaCl 0.9% / 5g bw) for 20 days and then sacrificed at the age of 40days. A control group received NaCl 0.9%. The rat is weighed daily. The plasmatic levels of testosterone, LH and FSH were measured by radioimmunoassay. A histomorphometric study was performed on sections of testis. Treated groups showed a significant decrease in body weight (p

Prevalence of Epstein-Barr Virus Latent Membrane Protein-1 in Jordanian Patients with Hodgkin's Lymphoma and Non- Hodgkin's Lymphoma

The aim of this study was to estimate the frequency of EBV infection in Hodgkin's lymphoma (HL) and non-Hodgkin's lymphoma (NHL) occurring in Jordanian patients. A total of 55 patients with lymphoma were examined in this study. Of 55 patients, 30 and 25 were diagnosed as HL and NHL, respectively. The four HL subtypes were observed with the majority of the cases exhibited the mixed cellularity (MC) subtype followed by the nodular sclerosis (NS). The high grade was found to be the commonest subtype of NHL in our sample, followed by the low grade. The presence of EBV virus was detected by immunostating for expression of latent membrane protein-1 (LMP-1). The frequency of LMP-1 expression occurred more frequent in patients with HL (60.0%) than in patients with NHL (32.0%). The frequency of LMP-1 expression was also higher in patients with MC subtype (61.11%) than those patients with NS (28.57%). No age or gender difference in occurrence of EBV infection was observed among patient with HL. By contrast, the prevalence of EBV infection in NHL patients aged below 50 was lower (16.66%) than in NHL patients aged 50 or above (46.15%). In addition, EBV infection was more frequent in females with NHL (38.46%) than in male with NHL (25%). In NHL cases, the frequency of EBV infection in intermediate grade (60.0%) was high when compared with frequency of low (25%) or high grades (25%). In conclusion, analysis of LMP-1 expression indicates an important role for this viral oncogene in the pathogenesis of EBV-associated malignant lymphomas. These data also support the previous findings that people with EBV may develop lymphoma and that efforts to maintain low lymphoma should be considered for people with EBV infection.

Organization as System, Psychic Dynamism as Equilibration: A Conceptualization

Organizations are supposed to be systems and consequently require defining the notion of equilibrium within. However, organizations comprise people and unavoidably entail their irrational aspects. Then, the question is what is the organizational equilibrium and equilibrating mechanisms considering these aspects. Hence, some arguments are provided here to conceptualize human unconsciousness, irrationalities and consequent uncertainties within organizations in the form of a system of psychic dynamism. The assumption is this dynamism maintains the psychic balance of the organization through a psychodynamic point of view. The resultant conceptualization expected to promote the understanding of such aspects in different organizational settings by hypothesizing organizational equilibration from this perspective. As a result, the main expectation is, if it is known that how the organization equilibrates in this sense, we can explain and deal with such irrationalities and unconsciousness by rational and, of course conscious, planning and accomplishing.