Image Based and Hybrid Visual Servo Control of an Unmanned Aerial Vehicle

The use of unmanned aerial vehicles (UAVs) for military, scientific, and civilian sectors are increasing drastically in recent years. This study presents algorithms for the visual-servo control of an UAV, in which a quadrotor helicopter has been stabilized with visual information through the control loop. Unlike previous study that use pose estimation approach which is time consuming and subject to various errors, the visual-servo control is more reliable and fast. The method requires a camera on-board the vehicle, which is already available on various UAV systems. The UAV with a camera behaves like an eye-in-hand visual servoing system. In this study the controller was designed by using two different approaches; image based visual servo control method and hybrid visual servo control method. Various simulations are developed on Matlab, in which the quadrotor aerial vehicle has been visual-servo controlled. In order to show the effectiveness of the algorithms, experiments were performed on a model quadrotor UAV, which suggest successful performance.     

An effective and efficient Web content extractor for optimizing the crawling process

Classical Web crawlers make use of only hyperlink information in the crawling process. However, focused crawlers are intended to download only Web pages that are relevant to a given topic by utilizing word information before downloading the Web page. But, Web pages contain additional information that can be useful for the crawling process. We have developed a crawler, iCrawler (intelligent crawler), the backbone of which is a Web content extractor that automatically pulls content out of seven different blocks: menus, links, main texts, headlines, summaries, additional necessaries, and unnecessary texts from Web pages. The extraction process consists of two steps, which invoke each other to obtain information from the blocks. The first step learns which HTML tags refer to which blocks using the decision tree learning algorithm. Being guided by numerous sources of information, the crawler becomes considerably effective. It achieved a relatively high accuracy of 96.37% in our experiments of block extraction. In the second step, the crawler extracts content from the blocks using string matching functions. These functions along with the mapping between tags and blocks learned in the first step provide iCrawler with considerable time and storage efficiency. More specifically, iCrawler performs 14 times faster in the second step than in the first step. Furthermore, iCrawler significantly decreases storage costs by 57.10% when compared with the texts obtained through classical HTML stripping. Copyright © 2013 John Wiley & Sons, Ltd.     

Iniencephaly: neuroradiological and surgical features. Case report and review of the literature

We present a gridded genomic library of the honey-bee (Apis mellifera) for comparative and basic genetic study of the honeybee genome. The library will be established as a "Reference Library" system, and clones as well as data will be shared with the entire scientific community. This will accelerate the molecular level of honeybee genetics, combining the efforts of different laboratories. Because of male haploidy and the high rate of recombination, the honeybee is becoming a model organism for genomic studies of naturally occurring traits and behavioral genetics. The library consists of about 110,000 clones spotted at high density onto four filter membranes, representing 22 genome equivalents. Preliminary analysis using single-copy sequences revealed a positive clone number of the same order. The techniques for library generation and preliminary analysis as well as library access are described.     

Delay extraction-based passive macromodeling techniques for transmission line type interconnects characterized by tabulated multiport data

This paper introduces a novel algorithm for delay extraction-based passive macromodeling of multiconductor transmission line type interconnects characterized by multiport (Y, Z, S, or H) tabulated parameters. The algorithm determines a unique logarithm of the H parameters, which is then approximated using a low-order rational function. Subsequently, the DEPACT (delay extraction-based passive compact transmission line macromodel) algorithm is applied to obtain a passive and causal macromodel for SPICE simulation. The new method leads to compact, low-order macromodels resulting in faster transient simulations.     

Simplified Macromodel of MTLs With Incident Fields (SiMMIF)

Electromagnetic compatibility (EMC) analysis of high-speed designs has become imperative due to rapidly increasing radio-frequency interference and emerging technological trends such as higher operating frequencies, denser layouts, and multifunction convergent products. In this paper, a simplified macromodel of multiconductor transmission lines (MTLs) exposed to incident fields is presented. The proposed formulation can also handle frequency dependence of resistance, capacitance, conductance, and inductance (RLGC) line parameters. The method employs the recently developed delay-extraction-based compact and passive MTL macromodel, while developing closed-form expressions for incident field analysis. An error bound for the proposed macromodel is also presented. The macromodel is simulation program with integrated circuit emphasis (SPICE) compatible and overcomes the mixed frequency/time simulation difficulties usually encountered during transient analysis, while guaranteeing the stability of the global transient simulation. The algorithm provides higher accuracy as well as significant speed gains for EMC analysis of transmission line networks as compared to the existing techniques.     

A multi-objective genetic algorithm for the hot mix asphalt problem

Neural Computing and Applications - It is desirable for the work done in any construction process to be both cost-effective and durable. A thorough consideration of the matter reveals that the...