0/1 Multiple Knapsack Problem, a generalization of more popular 0/1 Knapsack Problem, is NP-hard and considered harder than simple Knapsack Problem. 0/1 Multiple Knapsack Problem has many applications in disciplines related to computer science and operations research. Quantum Inspired Evolutionary Algorithms (QIEAs), a subclass of Evolutionary algorithms, are considered effective to solve difficult problems particularly NP-hard combinatorial optimization problems. A hybrid QIEA is presented for multiple knapsack problem which incorporates several features for better balance between exploration and exploitation. The proposed QIEA, dubbed QIEA-MKP, provides significantly improved performance over simple QIEA from both the perspectives viz., the quality of solutions and computational effort required to reach the best solution. QIEA-MKP is also able to provide the solutions that are better than those obtained using a well known heuristic alone.

In this paper an enhanced approach based on a modified biogeography optimization with predator and prey behavior (PMBBO) is presented. The approach uses several predators with new proposed prey’s movement formula. The potential of using a modified predator and prey model is to increase the diversification along the optimization process so to avoid local optima and reach the optimal solution quickly. The proposed approach is used in tuning the gains of PID controller for nonlinear systems (Mass spring damper and an inverted pendulum) and has given remarkable results when compared to genetic algorithm and classical BBO.

In today's globally networked environment, enterprises need collaborating using Information Technology (IT) and other tools to succeed in this dynamic and heterogeneous business environment. The Global Village Services Reference Model (GVSRM) is a model based on SOSA (Service Oriented Strategies and Architectures) ontology for global village services realization. In this model, three architectural abstraction layers have been considered for global village: ‘infrastructure for global village services’, ‘global village services provisioning’, and ‘using global village services’. Despite of relative completeness of this model, one of its obvious shortcomings is lack of attention to the crucial issue of interoperability in the global village. Based on this model, the grid of global village is comprised of VHGs (Virtual Holding Governance). The VHG is a temporary, scalable, dynamic cluster/association comprising of existing or newly service provider organizations which its aim is satisfying the requirements of global village actors through electronic processes. In this paper, we will propose a federated approach for interoperability among the VHGs of the global village and then improve the GVSRM by adding the corresponding interoperability components to it.

Granting banking facility is one of the most important parts of the financial supplies for each bank. So this activity becomes more valuable economically and always has a degree of risk. These days several various developed Artificial Intelligent systems like Neural Network, Decision Tree, Logistic Regression Analysis, Linear Discriminant Analysis and etc, are used in the field of granting facilities that each of this system owns its advantages and disadvantages. But still studying and working are needed to improve the accuracy and performance of them. In this article among other AI methods, fuzzy expert system is selected. This system is based on data and also extracts rules by using data. Therefore the dependency to experts is omitted and interpretability of rules is obtained. Validity of these rules could be confirmed or rejected by banking affair experts.
For investigating the performance of proposed system, this system and some other methods were performed on various datasets. Results show that the proposed algorithm obtained better performance among the others.

As the wireless nodes are having limited battery life, energy efficiency is the most important design consideration in mobile ad hoc networks. Many multipath routing schemes are possibly exploiting multiple disjoint routes between any pair of source and destination in order to provide aggregated bandwidth, fault-tolerance and load-balancing properties. Hence we propose an optimized energy efficient routing scheme by slightly modifying MMRE-AOMDV route update rules in order to generate more energy efficient routes than MMRE-AOMDV routing protocol, called an Optimized Minimal Maximal nodal Residual Energy AOMDV (OMMRE-AOMDV) protocol. It reduces the energy consumption, average end to end delay, routing overhead and normalized routing overhead. It also improves packet delivery ratio and throughput. Simulation results show that the OMMRE-AOMDV routing protocol has performed better than AOMDV and MMRE-AOMDV routing protocols.

In this paper, we evaluate the effects of neurofeedback training protocols of the relative power of the beta-I band and the fractal dimension on the reaction time of human by the Test of Variables of Attention (TOVA) to show which of these two protocols have the great ability for the improving of the reaction time. The findings of this research show that both protocols have a good ability (p < 0.01) to improving of the reaction time and can create the significant difference (as mean dRT = 37.3 ms for the beta-I protocol and dRT = 19.6 ms for the fractal protocol) in the reaction time. Of course, we must express, the Beta-I protocol has the more ability to improving of the reaction time and it is able to provide a faster reaction time.

The present paper is dedicated to the presentation and implementation of an optimized technique allowing an on-line estimation of a robot manipulator parameters to use them in a computed torque control. Indeed the proposed control law needs the exact robot model to give good performances. The complexity of the robot manipulator and its strong non-linearity makes it hard to know its parameters. Therefore, we propose in this paper to use neuro-fuzzy networks Sequential Adaptive Fuzzy Inference System (SAFIS) to estimate the parameters of the controlled robot manipulator.

With the evolution of higher computing speed, efficient communication technologies, and advanced display techniques the legacy HCI techniques become obsolete and are no more helpful in accurate and fast flow of information in present day computing devices. Hence the need of user friendly human machine interfaces for real time interfaces for human computer interaction have to be designed and developed to make the man machine interaction more intuitive and user friendly. The vision based hand gesture recognition affords users with the ability to interact with computers in more natural and intuitive ways. These gesture recognition systems generally consist of three main modules like hand segmentation, hand tracking and gesture recognition from hand features, designed using different image processing techniques which are further integrated with different applications. An increase use of new interfaces based on hand gesture recognition designed to cope up with the computing devices for interaction. This paper is an effort to provide a comparative analysis between such real time vision based hand gesture recognition systems which are based on interaction using single and multiple hand gestures. Single hand gesture based recognition systems (SHGRS) have fewer complexes to implement, with a constraint to the count of different gestures which is large enough with various permutations and combinations of gesture, which is possible with multiple hands in multiple hand gesture recognition systems (MHGRS). The thorough comparative analysis has been done on various other vital parameters for the recognition systems.

In this paper, HSV color local maximum edge binary patterns (LMEBP) histogram and LMEBP joint histogram are integrated for content based image retrieval (CBIR). The local HSV region of image is represented by LMEBP, which are evaluated by taking into consideration the magnitude of local difference between the center pixel and its neighbors. This LMEBP differs from the existing LBP in a manner that it extracts the information based on distribution of edges in an image. Further the joint histogram is constructed between uniform two rotational invariant first three LMEBP patterns. The color feature is extracted by calculating the histogram on Hue (H), Saturation (S) and LMEBP histogram on Value (V) spaces. The feature vector of the system is constructed by integrating HSV LMEBP histograms and LMEBP joint histograms. The experimentation has been carried out for proving the worth of our algorithm. It is further mentioned that the databases considered for experiment are Corel-1K and Corel-5K. The results after being investigated show a significant improvement in terms of their evaluation measures as compared to previously available spatial and transform domain methods on their respective databases.

Multilevel association rules provide the more precise and specific information. Apriori algorithm is an established algorithm for finding association rules. Fast Apriori implementation is modified to develop new algorithm for finding frequent item sets and mining multilevel association rules. MAFIA is another established algorithm for finding frequent item sets. In this paper, the performance of this new algorithm is analyzed and compared with MAFIA algorithm.