GOM : new genetic optimizing model for broadcasting tree in MANET

Data broadcasting in a mobile ad-hoc network (MANET) is the main method of information dissemination in many applications, in particular for sending critical information to all hosts. Finding an optimal broadcast tree in such networks is a challenging task due to the broadcast storm problem. The aim of this work is to propose a new genetic model using a fitness function with the primary goal of finding an optimal broadcast tree. Our new method, called Genetic Optimisation Model (GOM) alleviates the broadcast storm problem to a great extent as the experimental simulations result in efficient broadcast tree with minimal flood and minimal hops. The result of this model also shows that it has the ability to give different optimal solutions according to the nature of the network.

Psychological and interpersonal dimensions of sexual function and dysfunction

Introduction. There are limited outcome data on the etiology and efficacy of psychological interventions for male and female sexual dysfunction as well as the role of innovative combined treatment paradigms.
Aim. This study aimed to highlight the salient psychological and interpersonal issues contributing to sexual health and dysfunction, to offer an etiological model for understanding the evolution and maintenance of sexual symptoms, and to offer recommendations for clinical management and research.
Methods. This study reviewed the current literature on the psychological and interpersonal issues contributing to male and female sexual dysfunction.
Main Outcome Measure. This study provides expert opinion based on a comprehensive review of the medical and psychological literature, widespread internal committee discussion, public presentation, and debate.
Results. Medical and psychological therapies for sexual dysfunctions should address the intricate biopsychosocial influences of the patient, the partner, and the couple. The biopsychosocial model provides an integrated paradigm for understanding and treating sexual dysfunction.
Conclusions. There is need for collaboration between healthcare practitioners from different disciplines in the evaluation, treatment, and education issues surrounding sexual dysfunction. In many cases, neither psychotherapy alone nor medical intervention alone is sufficient for the lasting resolution of sexual problems. The assessment of male, female, and couples’ sexual dysfunction should ideally include inquiry about predisposing, precipitating, maintaining, and contextual factors. Research is needed to identify efficacious combined and/or integrated treatments for sexual dysfunction.

Computational exploration of the biological basis of Black-Scholes expected utility function

It has often been argued that there exists an underlying biological basis of utility functions. Taking this line of argument a step further in this paper, we have aimed to computationally demonstrate the biological basis of the Black-Scholes functional form as applied to classical option pricing and hedging theory. The evolutionary optimality of the classical Black-Scholes function has been computationally established by means of a haploid genetic algorithm model. The objective was to minimize the dynamic hedging error for a portfolio of assets that is built to replicate the payoff from a European multi-asset option. The functional form that is seen to evolve over successive generations which best attains this optimization objective is the classical Black-Scholes function extended to a multiasset scenario.

Identifying capabilities for the IT function to create agility in information systems

In this paper, we identify the necessary capabilities of the IT function to create agility in existing information systems. Agility is the ability to quickly sense and respond to environment perturbations. We contrast the agility perspective from a widely used industry framework with research perspectives on agility in the IS literature. We suggest Beer’s Viable System Model (VSM) is a useful meta-level theory to house agility elements from IS research literature, and apply VSM principles to identify the capabilities required of the IT function. Indeed, by means of a survey of 34 organisations, we confirm that the meta-level theory better correlates with reported agility measures than existing practice measures do on their own. From a research perspective, the incorporation of the VSM mechanism helps to explain ‘why’ the IT function is capable of creating agility. From a practical perspective of ‘how’, the findings point to a new set of capabilities of the IT function for future versions of the industry frameworks to enable agility.

Agility in information systems : enabling capabilities for the IT function

This research identifies how the IT function can create agility in existing information systems. Agility is the capability to quickly sense and respond to environmental perturbations. We contrasted perspectives on agility from a widely used industry framework and that of the IS research literature. Beer’s Viable System Model was a useful meta-level theory to house agility elements from IS research and it introduced cybernetic principles to identify the processes required of the IT function. Indeed, our surveys of 70 organizations confirmed that the applied theory better correlates with reported agility than does existing industry best practice.

The research conducted two quantitative surveys to test the applied theory. The first survey mailed a Likert-type questionnaire to the clients of an Australian IT consultancy. The second survey invited international members of professional interest groups to complete a web-based questionnaire. The responses from the surveys were analyzed using partial-least-squares modeling. The data analysis positively correlated the maturity of IT function processes prescribed by the VSM and the likelihood of agility in existing information systems. We claim our findings generalize to other large organizations in OECD member countries.

The research offers an agility-capability model of the IT function to explain and predict agility in existing information systems. A further contribution is to improve industry ‘best practice’ frameworks by prescribing processes of the IT function to develop in maturity.

The use of Fe-30% Ni and Fe-30% Ni-Nb alloys as model systems for studying the microstructural evolution during the hot deformation of austenite

The development of physically-based models of microstructural evolution during thermomechanical processing of metallic materials requires knowledge of the internal state variable data, such as microstructure, texture, and dislocation substructure characteristics, over a range of processing conditions. This is a particular problem for steels, where transformation of the austenite to a variety of transformation products eradicates the hot deformed microstructure. This article reports on a model Fe-30wt% Ni-based alloy, which retains a stable austenitic structure at room temperature, and has, therefore, been used to model the development of austenite microstructure during hot deformation of conventional low carbon-manganese steels. It also provides an excellent model alloy system for microalloy additions. Evolution of the microstructure and crystallographic texture was characterized in detail using optical microscopy, X-ray diffraction (XRD), SEM, EBSD, and TEM. The dislocation substructure has been quantified as a function of crystallographic texture component for a variety of deformation conditions for the Fe-30% Ni-based alloy. An extension to this study, as the use of a microalloyed Fe-30% Ni-Nb alloy in which the strain induced precipitation mechanism was studied directly. The work has shown that precipitation can occur at a much finer scale and higher number density than hitherto considered, but that pipe diffusion leads to rapid coarsening. The implications of this for model development are discussed.

On the stress function-based OWA determination method with optimization criteria

The ordered weighted averaging (OWA) determination method with stress function was proposed by Yager, and it makes the OWA operator elements scatter in the shape of the stress function. In this paper, we extend the OWA determination with the stress function method using an optimization model. The proposed method transforms the OWA optimal solution elements into the interpolation points of the stress function. The proposed method extends the basic form of the stress function method with both scale and vertical shift transformations.We also explore a number of properties of this optimization-based stress function method. The OWA operator optimal solution elements can distribute as the shape of the given stress function in a parameterized way, in which case, the solution always possesses the arithmetic average operator as a special case.

Spectral element model updating for damage identification using clonal selection algorithm

A spectral element model updating procedure is presented to identify damage in a structure using Guided wave propagation results. Two damage spectral elements (DSE1 and DSE2) are developed to model the local (cracks in reinforcement bar) and global (debonding between reinforcement bar and concrete) damage in one-dimensional homogeneous and composite waveguide, respectively. Transfer matrix method is adopted to assemble the stiffness matrix of multiple spectral elements. In order to solve the inverse problem, clonal selection algorithm is used for the optimization calculations. Two displacement-based functions and two frequency-based functions are used as objective functions in this study. Numerical simulations of wave propagation in a bare steel bar and in a reinforcement bar without and with various assumed damage scenarios are carried out. Numerically simulated data are then used to identify local and global damage of the steel rebar and the concrete-steel interface using the proposed method. Results show that local damage is easy to be identified by using any considered objective function with the proposed method while only using the wavelet energy-based objective function gives reliable identification of global damage. The method is then extended to identify multiple damages in a structure. To further verify the proposed method, experiments of wave propagation in a rectangular steel bar before and after damage are conducted. The proposed method is used to update the structural model for damage identification. The results demonstrate the capability of the proposed method in identifying cracks in steel bars based on measured wave propagation data.

Latent structure of mentoring function scales

The latent structure of a 16-item mentoring function instrument was analyzed with the responses of 568 full-time employees. Features of the analyses included (a) assessment of the items' distributional properties (i.e., skewness and kurtosis); (b) assessment of the factor structure using the Satorra-Bentler scaled test statistic; and (c) evaluation of the instrument's invariance across sex. Confirmatory factor analyses using the scaled chi-square supported a two-factor oblique model that consisted of psychosocial and career-related mentoring functions. The invariance tests suggested that the structure was invariant across sex groups.

Emerging hypothesis verification using function-based geometric models and active vision strategies

This paper describes an investigation into the use of parametric 2D models describing the movement of edges for the determination of possible 3D shape and hence function of an object. An assumption of this research is that the camera can foveate and track particular features. It is argued that simple 2D analytic descriptions of the movement of edges can infer 3D shape while the camera is moved. This uses an advantage of foveation i.e. the problem becomes object centred. The problem of correspondence for numerous edge points is overcome by the use of a tree based representation for the competing hypotheses. Numerous hypothesis are maintained simultaneously and it does not rely on a single kinematic model which assumes constant velocity or acceleration. The numerous advantages of this strategy are described.

A probabilistic model with parsinomious representation for sensor fusion in recognizing activity in pervasive environment

To tackle the problem of increasing numbers of state transition parameters when the number of sensors increases, we present a probabilistic model together with several parsinomious representations for sensor fusion. These include context specific independence (CSI), mixtures of smaller multinomials and softmax function representations to compactly represent the state transitions of a large number of sensors. The model is evaluated on real-world data acquired through ubiquitous sensors in recognizing daily morning activities. The results show that the combination of CSI and mixtures of smaller multinomials achieves comparable performance with much fewer parameters.

High glucose-induced impairment in insulin secretion is associated with reduction in islet glucokinase in a mouse model of susceptibility to islet dysfunction

Type 2 diabetes is characterized by islet dysfunction resulting in hyperglycemia, which can then lead to further deterioration in islet function. A possible mechanism for hyperglycemia-induced islet dysfunction is the accumulation of advanced glycation end products (AGE). The DBA/2 mouse develops pancreatic islet dysfunction when exposed to a high glucose environment and/or obesity-induced insulin resistance. To determine the biochemical cause of dysfunction, DBA/2 and C57BL/6 control islets were incubated in 11.1 mM or 40 mM glucose in the absence or presence of the AGE inhibitor aminoguanidine (AG) for 10 days. Basal (2.8 mM glucose) insulin release was increased in both DBA/2 and C57BL/6 islets incubated with 40 mM vs 11.1 mM glucose for 10 days. Chronic exposure to hyperglycemia decreased glucose (20 mM)-stimulated insulin secretion in DBA/2 but not in C57BL/6 islets. AG significantly increased fold-induced insulin release in high glucose cultured DBA/2 mouse islets, but did not affect C57BL/6 islet function. DBA/2 islet glucokinase was significantly reduced following 40 mM glucose culture, compared with 11.1 mM glucose cultured DBA/2 islets and 40 mM glucose cultured C57BL/6 islets. Incubation of islets with AG resulted in a normalization of DBA/2 islet glucokinase levels. In conclusion, chronic high glucose-induced increases in AGE can result in islet dysfunction and this is associated with reduced glucokinase levels in a mouse model with susceptibility to islet failure.

A hybrid ART-GRNN online learning neural network with a ε-insensitive loss function

In this brief, a new neural network model called generalized adaptive resonance theory (GART) is introduced. GART is a hybrid model that comprises a modified Gaussian adaptive resonance theory (MGA) and the generalized regression neural network (GRNN). It is an enhanced version of the GRNN, which preserves the online learning properties of adaptive resonance theory (ART). A series of empirical studies to assess the effectiveness of GART in classification, regression, and time series prediction tasks is conducted. The results demonstrate that GART is able to produce good performances as compared with those of other methods, including the online sequential extreme learning machine (OSELM) and sequential learning radial basis function (RBF) neural network models.