Facial Attribute Classification (FAC) has attracted increasing attention in computer vision and pattern recognition. However, state-of-the-art FAC methods perform face detection/alignment independently. The inherent dependencies between these tasks are not fully exploited. In addition, most predict all facial attributes using the same CNN network architecture, which ignores different learning c...

Multi-objective evolutionary algorithms using the weighted sum of the objectives as the fitness functions feature simple execution and effectiveness in multiobjective optimization. However, they cannot find the Pareto solutions on the non-convex part of the Pareto frontier, and thus are difficult to find evenly distributed solutions. Under the circumstances, this paper proposes a new evolutiona...

This paper proposes an idea of using evolutionary multiobjective optimization (EMO) to optimize scalarizing functions. We assume that a scalarizing function to be optimized has already been generated from an original multiobjective problem. Our task is to optimize the given scalarizing function. In order to efficiently search for its optimal solution without getting stuck in local optima, we ge...

The notion of Pareto-optimality is one of the major approaches to multiobjective programming. While it is desirable to find more Pareto-optimal solutions, it is also desirable to find the ones scattered uniformly over the Pareto frontier in order to provide a variety of compromise solutions to the decision maker. In this paper, we design a genetic algorithm for this purpose. We compose multiple...

in distribution systems, in order to diminish power losses and keep voltage profiles within acceptable limits, network reconfiguration and capacitor placement are commonly used. in this paper, the hybrid shuffled frog leaping algorithm (hsfla) is used to optimize balanced and unbalanced radial distribution systems by means of a network reconfiguration and capacitor placement. high accuracy and ...

Data cube queries containing aggregate functions often combine multiple tables through join operations. We can extend this to “Multi-Join Expansion_Aggregate” data cube queries by using more than one aggregate functions in “SELECT” statement in conjunction with relational operators. In parallel processing for such queries, it must be decided which attribute to use as a partitioning attribute, i...

Cloud computing is a recent technology provides a flexible, on-demand and low cost feature of computing resources. The Main issue in Cloud Computing is user identity privacy and data content privacy. The User Privacy in Cloud Computing is achieved by various data access control Schemes. Existing Fully Anonymous Access control scheme with decentralized attribute authority provides data content p...

This study focuses on mechanism design in order to solve multi-attribute e-procurement problems. In particularly, this study addresses two realistic requirements in mechanism design: (1) specifications of request/proposal on multiple attributes, and (2) incentive compatibility on information exchange/disclosure. Taking into account the needs and emergence of advanced mechanisms in eprocurement,...

When we try to implement a multi-objective genetic algorithm (MOGA) with variable weights for finding a set of Pareto optimal solutions, one difficulty lies in determining appropriate search directions for genetic search. In our MOGA, a weight value for each objective in a scalar fitness function was randomly specified. Based on the fitness function with the randomly specified weight values, a ...

Significance and relevance of certain features are obtained by various techniques. Feature subset selection involves summarizing mutual associations between class decisions and attribute values in a pre-classified database. In this paper genetic algorithm is used to find the relevant set of features by optimizing the fitness function and using the operators like crossover and mutation. Fuzzy lo...