Vision-based range estimation using helicopter flight data

Pilot aiding during low-altitude flight depends on the ability to detect and locate obstacles near the helicopter's intended flightpath. Computer-vision-based methods provide one general approach for obstacle detection and range estimation. Several algorithms have been developed for this purpose, but have not been tested with actual flight data. This paper presents results obtained using helicopter flight data with a feature-based range estimation algorithm. A method for recursively estimating range using a Kalman filter with a monocular sequence of images and knowledge of the camera's motion is described. The helicopter flight experiment and four resulting datasets are discussed. Finally the performance of the range estimation algorithm is explored in detail based on comparison of the range estimates with true range measurements collected during the flight experiment

Improving the delivered power quality from WECS to the grid based on PMSG control model

Renewable energy has become one of the most energy resources nowadays, especially, wind energy. It is important to implement more analysis and develop new control algorithms due to the rapid changes in the wind generators size and the power electronics development in wind energy applications. This paper proposes a grid-connected wind energy conversion system (WECS) control scheme using permanent magnet synchronous generator (PMSG). The model works to improve the delivered power quality and maximize its value. The system contained one controller on the grid side converter (GSC) and two simulation packages used to simulate this model, which were PSIM software package for simulating power circuit and power electronics converters, and MATLAB software package for simulating the controller on Simulink. It employed a meta-heuristic technique to fulfil this target effectively. Mine-blast algorithm (MBA) and harmony search optimization technique (HSO) were applied to the proposed method to get the best controller coefficient to ensure maximum power to the grid and minimize the overshoot and the steady state error for the different control signals. The comparison between the results of the MBA and the HSO showed that the MBA gave better results with the proposed system

Olmesartan modulates proliferating cell nuclear antigen expression and improves dextran sulfate - induced ulcerative colitis in rats

Background: Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized by sudden attacks of remissions and exacerbations with increased incidence of cancer colon. The present study aims to determine the possible ameliorative mechanisms of Olmesartan in UC induced experimentally in rat.Methods: Adult albino rats were randomly grouped into control, UC model non treated group: Rats received dextran sodium (DSS) orally for 21 days with intra-colic administration of acetic acid (AA) for 3 consecutive days for induction of UC model, Olmesartan (1, 5, 10mg/kg/orally) and UC + Olmesartan in different doses (1 mg, 5 mg and 10 mg/kg/day orally).Results: DSS orally and AA intra-rectal produced sever colitis manifested by significant weight loss, watery and bloody diarrhea. Significant increase in serum and colonic tissue levels of tumor necrosis factor alpha and interleukine-1β. Pro-apoptotic Bax protein, myeloperoxidase (MPO) and expression of PCNA significantly increased in colonic tissue. Lipid peroxidation (MDA) significantly elevated while reduced glutathione (GSH) was depleted in UC non-treated group compared with normal control group. Treatment with Olmesartan (5 mg, 10 mg/kg/day, orally) ameliorated mucosal ulceration and improved inflammatory signs as confirmed by immunohistochemical and histopathological examination. Also, Olmesartan significantly attenuates overexpression of PCNA in colonic mucosa.Conclusions: Our results point out that Olmesartan had ameliorative effects on UC by its anti-inflammatory, antioxidant and anti-apoptotic effects and attenuates PCNA expression which is the main cause of dysplasia and colorectal cancer. Olmesartan may be a promising therapeutic drug for treating UC and protection of colorectal carcinoma. 

A Comparative Simulation Study of the Thermal Performances of the Building Envelope Wall Materials in the Tropics

he building walls which form the major part of the building envelope thermally interact with the changing surrounding environment throughout the day influencing the indoor thermal comfort of the space. This paper aims at assessing in detail the different aspects (thermophysical properties, thickness, exposure to solar heat gain, etc.) of opaque building wall materials affecting the indoor thermal environment and energy efficiency of the buildings in tropical climate (in the summer and winter days) by conducting simplified simulation analysis using the Integrated Environmental Solutions Virtual Environment (IES-VE) program. Besides, the thermal efficiency of a number of selected wall materials with different thermal properties and wall configurations was analysed to determine the most optimal option for the studied climate. This study first developed the conditions for parametric simulation analysis and then addressed selected findings by comparing the thermal responses of the materials to moderate outdoor temperature and energy-saving potential. While energy consumption estimation for a complete operational building is a complex method by which the performance of the wall materials cannot be properly defined, as a result, this simplistic simulation approach can guide the designers to preliminary analyse the different building wall materials in order to select the best thermal efficiency solution

Cuckoo search algorithm based for tunning both PI and FOPID controllers for the DFIG-Wind energy conversion system

Wind Energy has received great attention in this century. It influences the new power systems, adding new challenges to the power system expansion problem. Nowadays, double feed induction generator (DFIG) wind turbines are used majorly in wind farms, due to their advantages over other types. Therefore, the analysis of the system using this type has become very important. In this paper, a wind turbine modelling was introduced with suggested controllers, in order to enhance the system response, with respect to both pitch control and maximum output power. Cuckoo search algorithm (CSA), a meta-heuristic optimization technique, was implemented to determine the gains of a proportional-integral (PI) controller and fractional order proportional-integral-derivative (FOPID) controller to optimize the system, which considered three control loops: pitch, rotor-side converter, and grid-side converter control loop. Simulation results were determined using MATLAB/Simulink. The comparative analysis of the results showed that the PI Controller gave the simplest and the best response in case of the pitch and rotor-side control loops while the FOPID was the best when applied to the grid-side control loop. Based on the results and discussion, a suggestion of using a compination of each controller was introduced

Web pre-fetching schemes using Machine Learning for Mobile Cloud Computing

Pre-fetching is one of the technologies used in reducing latency on network traffic on the Internet. We propose this technology to utilise Mobile Cloud Computing (MCC) environment to handle latency issues in context of data management. However, overaggressive use of the pre-fetching technique causes overhead and slows down the system performance since pre-fetching the wrong objects data wastes the storage capacity of a mobile device. Many studies have been using Machine Learning (ML) to solve such issues. However, in MCC environment, the pre-fetching using ML is not widely used. Therefore, this research aims to implement ML techniques to classify the web objects that require decision rules. These decision rules are generated using few ML algorithms such as J48, Random Tree (RT), Naive Bayes (NB) and Rough Set (RS).These rules represent the characteristics of the input data accordingly. The experimental results reveal that J48 performs well in classifying the web objects for all three different datasets with testing accuracy of 95.49%, 98.28% and 97.9% for the UTM blog data, IRCache, and Proxy Cloud Computing (CC) datasets respectively. It shows that J48 algorithm is capable to handle better cloud data management with good recommendation to users with or without the cloud storage

High-Throughput Sequencing and Metagenomic Data Analysis

Metagenomic approaches are a growing branch of science and have many applications in different fields. Metagenomics seems to be the ideal culture-independent technique for unraveling the biodiversity of soils and to study how this biodiversity is affected with continuously changing conditions. In addition, its application in clinical and diagnostic approaches was reported. The emergence of several next-generation sequencing (NGS) strategies enriched the metagenomics. The combination between NGS and metagenomic approaches helped the investigators resolve several issues regarding the microbial diversity and the functions and relationships among different microbial flora. A number of NGS approaches were developed including Roche/454 pyrosequencing, Illumina/Solexa sequencing, and Applied Biosystems/SOLiD sequencing. In this chapter, different NGS platforms are discussed in terms of principle, advantages, and limitations. In addition, third-generation sequencing technologies are also addressed

Transcultural aspects of cannabis use : a descriptive overview of cannabis use across cultures

Purpose of Review: This narrative review summarises cultural aspects of cannabis use across different (sub)cultures, nations, and gender, racial, and ethnic groups. Specifically, we aimed to overview historical and traditional contexts of cannabis use and physical and mental health-related correlates, as well as emerging cannabis-related policies and their impacts on medicinal and recreational use of cannabis. In addition, we discuss how cultural factors may affect cannabis use behaviours and sociocultural underpinnings of cannabis use disorder trajectories. Recent Findings: Cannabis is the most widely cultivated, trafficked, and used illicit drug worldwide, although cannabis is being legalised in many jurisdictions. More than 4% of individuals globally have used cannabis in the last year. Being traditionally used for religious and ritualistic purposes, today cannabis use is interwoven with, and influenced by, social, legal, economic, and cultural environments which often differ across countries and cultures. Notably, empirical data on distinct aspects of cannabis use are lacking in selected underrepresented countries, geographical regions, and minority groups. Summary: Emerging global policies and legislative frameworks related to cannabis use have impacted the prevalence and attitudes toward cannabis in different subcultures, but not all in the same way. Therefore, it remains to be elucidated how and why distinct cultures differ in terms of cannabis use. In order to understand complex and bidirectional relationships between cannabis use and cultures, we recommend the use of cross-cultural frameworks for the study of cannabis use and its consequences and to inform vulnerable people, clinical practitioners, and legislators from different world regions.Publisher PDFPeer reviewe