Building distributed heterogeneous smart phone Java applications an evaluation from a development perspective

The advances in mobile phone technology have enabled such devices to be programmed to run general-purpose applications using a special edition of the Java programming language. Java is designed to be a heterogeneous programming language targeting different platforms. Such ability when coupled with the provision of high-speed mobile Internet access would open the door for a new breed of distributed mobile applications. This paper explores the capabilities and limitations of this technology and addresses the considerations that must be taken when designing and developing such distributed applications. Our findings are verified by building a test client-server system where the clients in this system are mobile phones behaving as active processing elements not just mere service requesters

Ant Colony Optimization Based Subset Feature Selection in Speech Processing: Constructing Graphs with Degree Sequences

Feature selection or the process of selecting the most discriminating feature subset is an essential practice in speech processing that significantly affects the performance of classification. However, the volume of features that presents in speech processing makes the feature selection perplexing. Moreover, finding the optimal feature subset is a NP-hard problem (2n). Thus, a good searching strategy is required to avoid evaluating large number of combinations in the whole feature subsets. As a result, in recent years, many heuristic based search algorithms are developed to address this NP-hard problem. One of the several meta heuristic algorithms that is applied in many application domains to solve feature selection problem is Ant Colony Optimization (ACO) based algorithms.  ACO based algorithms are nature-inspired from the foraging behavior of actual ants. The success of an ACO based feature selection algorithm depends on the choice of the construction graph with respect to runtime behavior. While most ACO based feature selection algorithms use fully connected graphs, this paper proposes ACO based algorithm that uses graphs with prescribed degree sequences. In this method, the degree of the graph representing the search space will be predicted and the construction graph that satisfies the predicted degree will be generated. This research direction on graph representation for ACO algorithms may offer possibilities to reduce computation complexity from O(n2) to O(nm) in which m is the number of edges. This paper outlines some popular optimization based feature selection algorithms in the field of speech processing applications and overviewed ACO algorithm and its main variants. In addition to that, ACO based feature selection is explained and its application in various speech processing tasks is reviewed. Finally, a degree based graph construction for ACO algorithms is proposed

Learning Process Enhancement for Robot Behavior

Designing a simulated system and training it to optimize its tasks in simulated environment helps the designers to avoid problems that may appear when designing the system directly in real worl

A Study On The Effects Of Noise Level, Cleaning Method, And Vectorization Software On The Quality Of Vector Data.

In this paper we study different factors that affect vector quality. Noise level, cleaning method, and vectorization software are three factors that may influence the resulting vector data. Real scanned images from GREC'03 contest are used in the experiment. Three different levels of salt-and-pepper noise (5olo, l0%o, and l5o/o) are used. Noisy images are cleaned by six cleaning algorithms and then three different commercial raster to vector software are used to vectorize the cleaned images. vector Recovery Index (VRI) is the performance evaluation criteria used in this study to judge the quality of the resulting vectors compared to their ground truth data. Statistical analysis on the VRI values shows that vectorization software have the biggest influence on the quality of the resulting vectors

Protein Conformantional Search Using Bees Algorithm

Proteins perform many biological functions in the human body. The structure of the protein determines its function. In order to predict the protein structure computationally, protein must be represented in a proper representation. To this end, an energy function is used to calculate its energy and a conformational search algorithm is used to search the conformational search space to find the lowest free energy corformation

Swarm Intelligence Based Protein Conformational Search Algorithm.

There is no doubt of the role that proteins play in the biological processes inside the human body. Proteins can perform their function only when they fold into their tertiary structure. The thermodynamics hypothesis formulated by Anfinsen stated that the tertiary structure of a protein in its physiological environment is the conformation with the lowest free energy

Removing Edge Defect In Color-Based Image Retrieval.

Growth of digital image archive is increasing rapidly and the demand for effective and efficient tools for searching through large amounts of visual data is great. One of the contributing factors toward an efficient tool is the quality of images being handle

Towards developing distributed heterogeneous mobile phone applications

The advances in the mobile phone technology have enabled such devices to be programmed to run general-purpose applications using a special mobile edition of the Java programming language.Java is designed to be a heterogeneous programming language targeting different platforms.Such ability when coupled with the provision of high-speed mobile Internet access would open the door for a new breed of distributed mobile applications.This paper explores the limitations of this technology and addresses the consideration that must be taken when designing and developing such applications

Clustering In Fingerprint Recognition System.

Clustering of fngerprints can help to reduce the complesity of the search process in a database