An analysis of the determinants and effects of ICT diffusion in developing countries

Using data from developing countries, this paper examines the links between ICT diffusion and per capita income, trade and financial indicators, education, and freedom indicators. Internet hosts, Internet users, personal computers and mobile phones represent indicators of ICT. The Gompertz model of technology diffusion is used to study ICT dissemination. The results show that income and government trade policies influence ICT diffusion. However, freedom indices may or may not affect ICT diffusion. Moreover, only personal computers and Internet hosts seem to have a positive association with income. Contrary to expectations, ICT diffusion is not associated with education.     

BASE: A bacteria foraging algorithm for cell formation with sequence data

A cellular manufacturing system (CMS) is considered an efficient production strategy for batch type production. A CMS relies on the principle of grouping machines into machine cells and grouping parts into part families on the basis of pertinent similarity measures. The bacteria foraging algorithm (BFA) is a newly developed computation technique extracted from the social foraging behavior of Escherichia coli (E. coli) bacteria. Ever since Kevin M. Passino invented the BFA, one of the main challenges has been employment of the algorithm to problem areas other than those for which the algorithm was proposed. This research work studies the first applications of this emerging novel optimization algorithm to the cell formation (CF) problem considering the operation sequence. In addition, a newly developed BFA-based optimization algorithm for CF based on operation sequences is discussed. In this paper, an attempt is made to solve the CF problem, while taking into consideration the number of voids in the cells and the number of inter-cell travels based on operational sequences of the parts visited by the machines. The BFA is suggested to create machine cells and part families. The performance of the proposed algorithm is compared with that of a number of algorithms that are most commonly used and reported in the corresponding scientific literature, such as the CASE clustering algorithm for sequence data, the ACCORD bicriterion clustering algorithm and modified ART1, and using a defined performance measure known as group technology efficiency and bond efficiency. The results show better performance of the proposed algorithm.     

Lie group method for solving viscous barotropic vorticity equation in ocean climate models

In studying the problem of the nonlinear viscous barotropic non-divergent vorticity equation on $f$- and $\beta$- planes, the method of Lie group has been applied. The method reduces the number of independent variables by one, and consequently, for the case of three independent variables we applied the method successively twice and the nonlinear partial differential equation reduces to ordinary differential equation. Investigation of exact solutions of the viscous barotropic non-divergent vorticity equation on $f$- and $\beta$- planes, via the application of Lie group, provides large classes of new exact solutions which include both Rossby and Rossby–Haurwitz waves as special cases. Also, The Lie symmetries of the viscous barotropic non-divergent vorticity equation with two parameters $F$ and $\beta$, are determined. The possible reductions of the viscous barotropic vorticity equation with two parameters $F$ and $\beta$ have been investigated by means of one- dimensional Lie subalgebras.     

Analyzing and optimizing of electro-thermal MEMS micro-actuator performance by BFA algorithm

Microsystem Technologies - Most of the MEMS nature are black box problems, and the evaluation of fitness process is based on physical measurements or hard to be transformed into augmented form....     

Dimension reduction and its application to model-based exploration in continuous spaces

The sample complexity of a reinforcement-learning algorithm is highly coupled to how proficiently it explores, which in turn depends critically on the effective size of its state space. This paper proposes a new exploration mechanism for model-based algorithms in continuous state spaces that automatically discovers the relevant dimensions of the environment. We show that this information can be used to dramatically decrease the sample complexity of the algorithm over conventional exploration techniques. This improvement is achieved by maintaining a low-dimensional representation of the transition function. Empirical evaluations in several environments, including simulation benchmarks and a real robotics domain, suggest that the new method outperforms state-of-the-art algorithms and that the behavior is robust and stable.     

A hybrid OBL-based firefly algorithm with symbiotic organisms search algorithm for solving continuous optimization problems

The metaheuristic optimization algorithms are relatively new optimization algorithms introduced to solve optimization problems in recent years. For example, the firefly algorithm (FA) is one of the metaheuristic algorithms inspired by the fireflies' flashing behavior. However, its weakness in terms of exploration and early convergence has been pointed out. In this paper, two approaches were proposed to improve the FA. In the first proposed approach, a new improved opposition-based learning FA (IOFA) method was presented to accelerate the convergence and improve the FA's exploration capability. In the second proposed approach, a symbiotic organisms search (SOS) algorithm improved the exploration and exploitation of the first approach; two new parameters set these two goals, and the second approach was named IOFASOS. The purpose of the second method is that in the process of the SOS algorithm, the whole population is effective in the IOFA method to find solutions in the early stages of implementation, and with each iteration, fewer solutions are affected in the population. The experiments on 24 standard benchmark functions were conducted, and the first proposed approach showed a better performance in the small and medium dimensions and exhibited a relatively moderate performance in the higher dimensions. In contrast, the second proposed approach was better in increasing dimensions. In general, the empirical results showed that the two new approaches outperform other algorithms in most mathematical benchmarking functions. Thus, The IOFASOS model has more efficient solutions.

     

The ETH‐MAV Team in the MBZ International Robotics Challenge

This study describes the hardware and software systems of the Micro Aerial Vehicle (MAV) platforms used by the ETH Zurich team in the 2017 Mohamed Bin Zayed International Robotics Challenge (MBZIRC). The aim was to develop robust outdoor platforms with the autonomous capabilities required for the competition, by applying and integrating knowledge from various fields, including computer vision, sensor fusion, optimal control, and probabilistic robotics. This paper presents the major components and structures of the system architectures and reports on experimental findings for the MAV‐based challenges in the competition. Main highlights include securing the second place both in the individual search, pick, and place the task of Challenge 3 and the Grand Challenge, with autonomous landing executed in less than 1 min and a visual servoing success rate of over for object pickups.     

U-shaped energy loss curves utilization for distributed generation optimization in distribution networks

We propose novel techniques to find the optimal achieve the maximum loss reduction for distribution networks location, size, and power factor of distributed generation （DG） to Determining the optimal DG location and size is achieved simultaneously using the energy loss curves technique for a pre-selected power factor that gives the best DG operation. Based on the network＇s total load demand, four DG sizes are selected. They are used to form energy loss curves for each bus and then for determining the optimal DG options. The study shows that by defining the energy loss minimization as the objective function, the time-varying load demand significantly affects the sizing of DG resources in distribution networks, whereas consideration of power loss as the objective function leads to inconsistent interpretation of loss reduction and other calculations. The devised technique was tested on two test distribution systems of varying size and complexity and validated by comparison with the exhaustive iterative method （EIM） and recently published results. Results showed that the proposed technique can provide an optimal solution with less computation.     

2001 International Symposium on Lightning Protection 19-23 November 2001, Santos, S.P., Brazil

This letter offers a state space representation of a voltage sourced inverter that forms the building block of modern flexible AC transmission systems (FACTS), such as STATCOM, SSSC, and UPFC. The representation includes consideration of the output phase, firing angle, and the conduction period. This model is used to devise a control algorithm of the DC link voltage and the output voltage. The concepts are demonstrated with a case study using PSCAD and MATLAB.     

智能语音领域检索策略分析

针对智能语音产业的发展现状以及语音领域的申请文件的特殊性,系统地提出了语音领域专利检索的对策建议。