Adaptive control of nonlinear system based on QFT application to 3-DOF flight control system

Research on unmanned aerial vehicle (UAV) became popular because of remote flight access and cost-effective solution. 3-degree of freedom (3-DOF) unmanned helicopters is one of the popular research UAV, because of its high load carrying capacity with a smaller number of motor and requirement of forethought motor control dynamics. Various control algorithms are investigated and designed for the motion control of the 3DOF helicopter. Three-degree-of-freedom helicopter model configuration presents the same advantages of 3-DOF helicopters along with increased payload capacity, increase stability in hover, manoeuvrability and reduced mechanical complexity. Numerous research institutes have chosen the three-degree-of-freedom as an ideal platform to develop intelligent controllers. In this research paper, we discussed about a hybrid controller that combined with Adaptive and Quantitative Feedback theory (QFT) controller for the 3-DOF helicopter model. Though research on Adaptive and QFT controller are not a new subject, the first successful single Adaptive aircraft flight control systems have been designed for the U.S. Air Force in Wright Laboratories unmanned research vehicle, Lambda [1]. Previously researcher focused on structured uncertainties associated with controller for the flight conditions theoretically. The development of simulationbased design on flight control system response, opened a new dimension for researcher to design physical flight controller for plant parameter uncertainties. At the beginning, our research was to investigates the possibility of developing the QFT combined with Adaptive controller to control a single pitch angle that meets flying quality conditions of automatic flight control. Finally, we successfully designed the hybrid controller that is QFT based adaptive controller for all the three angles

Prevalent genotypes of meticillin-resistant Staphylococcus aureus: report from Pakistan

Meticillin-resistant Staphylococcus aureus (MRSA) is a major nosocomial pathogen in Pakistan and is emerging in the community. This is one of the first reports of the prevalent genotypes of MRSA in both hospital and community settings in Pakistan. Isolates collected in 2006-2007 were characterized by PFGE, staphylococcal cassette chromosome mec (SCCmec) typing and multilocus sequence typing (MLST). PFGE identified nine pulsotypes, the majority of isolates belonging to pulsotypes A (n=70) and B (n=38), which were predominant among hospital-onset MRSA (HO-MRSA) and community-onset MRSA (CO-MRSA) isolates, respectively. Among the HO-MRSA isolates, variants of SCCmec type III were prevalent, whilst SCCmec type IV or variants were predominant in the CO-MRSA isolates. MLST identified two principal sequence types, ST8 and ST239. An association was observed between ST8, PFGE pulsotype B and SCCmec type IV in the CO-MRSA (ST8-MRSA-IV). Similarly, ST239, PFGE pulsotype A and SCCmec type III were associated with HO-MRSA (ST239-MRSA-III). Therefore, the prevalent genotypes circulating in Pakistan at the time of study were ST8-MRSA-IV and ST239-MRSA-III in the community and hospital settings, respectively. A set of HO-MRSA isolates collected in 1997 were characterized by PFGE and SCCmec typing for comparison. The isolates belonged to two PFGE pulsotypes (A, n=28, B, n=11) and contained just two SCCmec types. These results suggest that an increase in genetic diversity occurred over the period 1997-2007 as a result of either microevolution or the importation of strains from surrounding areas

A wireless precoding technique for millimetre-wave MIMO system based on SIC-MMSE

A communication method is proposed using Minimum Mean Square Error (MMSE) precoding and Successive Interference Cancellation (SIC) technique for millimetre-wave multiple-input multiple-output (mm-Wave MIMO) based wireless communication system. The mm-Wave MIMO technology for wireless communication system is the base potential technology for its high data transfer rate followed by data instruction and low power consumption compared to Long-Term Evolution (LTE). The mm-Wave system is already available in indoor hotspot and Wi-Fi backhaul for its high bandwidth availability and potential lead to rate of numerous Gbps/user. But, in mobile wireless communication system this technique is lagging because the channel faces relative orthogonal coordination and multiple node detection problems while rapid movement of nodes (transmitter and receiver) occur. To improve the conventional mm-wave MIMO nodal detection and coordination performance, the system processes data using symbolized error vector technique for linearization. Then the MMSE precoding detection technique improves the link strength by constantly fitting the channel coefficients based on number of independent service antennas (M), Signal to Noise Ratio (SNR), Channel Matrix (CM) and mean square errors (MSE). To maintain sequentially encoded user data connectivity and to overcome data loss, SIC method is used in combination with MMSE. MATLAB was used to validate the proposed system performance

SEROPREVALENCE OF BRUCELLOSIS IN ANIMALS AT GOVERNMENT AND PRIVATE LIVESTOCK FARMS IN PUNJAB

Seroprevalence of brucellosis in 1473 cattle and 481 buffaloes from various Government and 286 cattle and 223 buffaloes from different private livestock farms was carried out by performing Rose Bengal plate test (RBPT) and serum agglutination test (SAT). RBPT recorded the seroprevalence as 14.70% in cattle and 15.38% in buffaloes at Government and 18.53% in cattle and 35.40% in buffaloes at various private livestock farms. Out of these RBPT positive animals, 7.19% cattle and 2.91% buffaloes at Government whereas 9.00% cattle and 23.70% buffaloes at private livestock farms were found sero- positive when applied SAT

PEG Branched Polymer for Functionalization of Nanomaterials with Ultralong Blood Circulation

Nanomaterials have been actively pursued for biological and medical applications in recent years. Here, we report the synthesis of several new poly(ethylene glycol) grafted branched-polymers for functionalization of various nanomaterials including carbon nanotubes, gold nanoparticles (NP) and gold nanorods (NRs), affording high aqueous solubility and stability for these materials. We synthesize different surfactant polymers based upon poly-(g-glutamic acid) (gPGA) and poly(maleic anhydride-alt-1-octadecene) (PMHC18). We use the abundant free carboxylic acid groups of gPGA for attaching lipophilic species such as pyrene or phospholipid, which bind to nanomaterials via robust physisorption. Additionally, the remaining carboxylic acids on gPGA or the amine-reactive anhydrides of PMHC18 are then PEGylated, providing extended hydrophilic groups, affording polymeric amphiphiles. We show that single-walled carbon nanotubes (SWNTs), Au NPs and NRs functionalized by the polymers exhibit high stability in aqueous solutions at different pHs, at elevated temperatures and in serum. Morever, the polymer-coated SWNTs exhibit remarkably long blood circulation (t1/2 22.1 h) upon intravenous injection into mice, far exceeding the previous record of 5.4 h. The ultra-long blood circulation time suggests greatly delayed clearance of nanomaterials by the reticuloendothelial system (RES) of mice, a highly desired property for in vivo applications of nanomaterials, including imaging and drug delivery

Evaluating the antidiabetic and antioxidant properties of 5- benzyl-1,3,4-oxadiazole-2-thiol

Purpose: To evaluate 5-Benzyl-1,3,4-oxadiazole-2-thiol (OXPA) for antidiabetic and antioxidant properties. Methods: Antidiabetic activity was evaluated using three in vitro models, glucose uptake by yeast cells, alpha amylase inhibition assay and hemoglobin glycosylation inhibition assays. Antioxidant potential was determined by DPPH radical scavenging, reducing power and lipid peroxidation assays. Results: OXPA showed antidiabetic activity in all the three models. The activity of the compound was comparable with that of metronidazole in glucose uptake by yeast cells, but the alpha amylase inhibition activity of the compound was slightly lower than that of acarbose, whereas the hemoglobin glycosylation inhibition activity of the compound was higher than that of vitamin E. DPPH free radical and hydrogen peroxide scavenging activity of the compound was comparable with that of vitamin C. In reducing power assay, the activity of the compound was lower than that of vitamin C (p > 0.05). Conclusion: The results of antidiabetic and antioxidant activity indicate that OXPA may be a drugcandidate for treating both diabetes and its associated oxidative stress

Exploring the potential of four medicinal plants for antioxidant enzymes activity, proximate and nutritional composition

A study was conducted to evaluate the antioxidant enzymes activity, proximate and nutritional composition of four medicinal plants, which may contribute to folk pharmacological use in the treatment of different diseases. Plant samples were extracted and antioxidant enzymes like superoxide dismutase (SOD), peroxidase (POD), polyphenol oxidase (PPO) and ascorbate peroxide (APX) activity were estimated. Medicinal plants were also analysed for moisture, ash, protein, fibre, carbohydrate, and fats contents. Plant samples were wet digested and mineral composition in terms of nitrogen (N), phosphorus (P), potassium (K), calcium (Ca), magnesium (Mg), and sodium (Na) was determined. The results revealed that antioxidant activity, proximate and nutritional composition differs significantly among tested medicinal plants extract. The leaves of medicinal plants showed more proximate composition (moisture contents, crude protein, fats contents), nutrient accumulation (N, P, K, Ca, Mg and Na), and antioxidant enzymes (POD, PPO, and APX activity). Among medicinal plants, Tribulus terrestris L. showed the highest amount of crude protein, crude fibre, gross energy, and N and Ca contents. Maximum K, Mg, Na contents, POD, PPO and APX activity was observed in Cenchrus ciliaris L. The ash, fats, phosphorus and SOD activity was more in Euphorbia hirta L. While, Cyperus rotundus L. produced maximum carbohydrates concentration among the tested plants. It is concluded that the target medicinal species had emerged as a good source of the antioxidant and nutritive source, which could play an important role in human nutrition. The extracts of these plants parts can be used in the synthesis of mineral and antioxidant-containing drugs and medicines. This study will provide a baseline for the pharmacology industry

Exploiting the Bipartite Structure of Entity Grids for Document Coherence and Retrieval

International audienceDocument coherence describes how much sense text makes in terms of its logical organisation and discourse flow. Even though coherence is a relatively difficult notion to quantify precisely, it can be approximated automatically. This type of coherence modelling is not only interesting in itself, but also useful for a number of other text processing tasks, including Information Retrieval (IR), where adjusting the ranking of documents according to both their relevance and their coherence has been shown to increase retrieval effectiveness.The state of the art in unsupervised coherence modelling represents documents as bipartite graphs of sentences and discourse entities, and then projects these bipartite graphs into one–mode undirected graphs. However, one–mode projections may incur significant loss of the information present in the original bipartite structure. To address this we present three novel graph metrics that compute document coherence on the original bipartite graph of sentences and entities. Evaluation on standard settings shows that: (i) one of our coherence metrics beats the state of the art in terms of coherence accuracy; and (ii) all three of our coherence metrics improve retrieval effectiveness because, as closer analysis reveals, they capture aspects of document quality that go undetected by both keyword-based standard ranking and by spam filtering. This work contributes document coherence metrics that are theoretically principled, parameter-free, and useful to IR

Assessment of essential minerals and physico-chemical analysis of floral origins fresh honey produced by Apis mellifera

Abstract Honey is one of the best nutritious substances in the world, having different services in the body functions regulation. Ten elements (K, Na, Ca, Co, Cr, Mn, Mo, Ni, Pb, Se) from honey samples were analyzed from 80 different locations of Punjab and ten floras. The aim of the present study was to determine the quality and quantity of minerals and Physico-chemical analysis in honey. A flame photometer was used to measure the concentration of major minerals (K, Ca and Na). The concentration of micro minerals (Co, Cr, Mn, Mo, Ni, Pb and Se) was analyzed using Atomic Absorption Spectrometer. The concentration of macro-elements obtained was as follow (in ppm): K (166-1732), Na (107-418) and Ca (07-99), while the concentration of microelements (in ppm) Co (1-2), Cr (>1), Mn ( Co > Ni > Pb > Cr > Mo > Mn. The findings showed that all the heavy metals like Co, Cr, Ni and Pb were present in trace amounts and close to International Honey Quality Standard. The result of given honey samples represented highest value of moisture (31.23%), color (80 mm pfund), pH (8.23), acidity (72.02 meq/kg), electrical conductivity (0.85 ms/cm) and ash contents (0.83%)

Data Stream Clustering for Real-Time Anomaly Detection: An Application to Insider Threats

Insider threat detection is an emergent concern for academia, industries, and governments due to the growing number of insider incidents in recent years. The continuous streaming of unbounded data coming from various sources in an organisation, typically in a high velocity, leads to a typical Big Data computational problem. The malicious insider threat refers to anomalous behaviour(s) (outliers) that deviate from the normal baseline of a data stream. The absence of previously logged activities executed by users shapes the insider threat detection mechanism into an unsupervised anomaly detection approach over a data stream. A common shortcoming in the existing data mining approaches to detect insider threats is the high number of false alarms/positives (FPs). To handle the Big Data issue and to address the shortcoming, we propose a streaming anomaly detection approach, namely Ensemble of Random subspace Anomaly detectors In Data Streams (E-RAIDS), for insider threat detection. E-RAIDS learns an ensemble of p established outlier detection techniques [Micro-cluster-based Continuous Outlier Detection (MCOD) or Anytime Outlier Detection (AnyOut)] which employ clustering over continuous data streams. Each model of the p models learns from a random feature subspace to detect local outliers, which might not be detected over the whole feature space. E-RAIDS introduces an aggregate component that combines the results from the p feature subspaces, in order to confirm whether to generate an alarm at each window iteration. The merit of E-RAIDS is that it defines a survival factor and a vote factor to address the shortcoming of high number of FPs. Experiments on E-RAIDS-MCOD and E-RAIDS-AnyOut are carried out, on synthetic data sets including malicious insider threat scenarios generated at Carnegie Mellon University, to test the effectiveness of voting feature subspaces, and the capability to detect (more than one)-behaviour-all-threat in real-time. The results show that E-RAIDS-MCOD reports the highest F1 measure and less number of false alarm = 0 compared to E-RAIDS-AnyOut, as well as it attains to detect approximately all the insider threats in real-time